Assessing Production Risks and Value Chain Sustainability in Nepal's Lentil (Lens culinarisMedik.) Sector: An Evidence-based Econometric Analysis

Assessing Production Risks and Value Chain Sustainability in Nepal's Lentil (Lens culinarisMedik.) 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Sector: An Evidence-based Econometric Analysis Binod Ghimire, Shiva Chandra Dhakal, Santosh, Ram Chandra Bastakoti This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7043104/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Commodity value chain sustainability is critical for agricultural growth, especially for lentil ( Lens culinaris ), an important commercial legume in Nepal grown under risky conditions. This study assesses production risks and value chain sustainability using econometric modelling. Data were collected through surveys of 473 farmers, 155 traders, 85 business enablers, 12 key informant interviews, and 4 focus group discussions. Employing a triple bottom-line framework, value chain mapping, exploratory factor analysis, scaling, indexing, and Seemingly Unrelated Regression, the study reveals a buyer-driven, multi-actor, informal, inclusive, multi-channel, yet profitable lentil value chain with limited product and information flows and weak actor linkages. Seven distinct marketing channels were identified. Sustainability assessment rated economic and environmental dimensions as “good,” while the social dimension was “moderate.” The value chain excels in profitability, employment, scalability, household food security, nutrition, and soil fertility but faces constraints in coordination, value share, farmers’ bargaining power, market information, storage, pricing, and value addition. Yield and profit risks were most significant due to high output variability, while cost risks remained low. Farmers perceived climatic hazards (mean score 4.11) and disease incidence (3.86) as major risks. Key risk-management strategies included crop diversification (4.09), seed saving (4.02), and cooperative involvement (3.60). Factor analysis identified seven strategic risk groups. Seemingly Unrelated Regression revealed that strategy adoption is significantly influenced by risk types, gender, income, land size, group membership, credit access, and service proximity. Risk aversion was low in 7.3% of farmers, medium in 72.3%, and high in 11.2%. From sustainability perspective, cost reduction, early warning systems with rapid response teams, use of improved seeds, crop diversification, collective actions, and stronger value chain coordination are recommended. Agricultural Economics & Policy Triple bottom line Sustainability Value chain Risk Lentil Nepal Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Agriculture is the main economic sector in Nepal, contributing around 24% of GDP and supporting around 65% of the population (MoALD, 2022 ). Nepal’s diverse agro-climatic conditions, natural resources, and unique products provide a competitive advantage in high-value crops such as vegetables, spices, tea, and pulses, offers substantial agricultural production (Paudel, 2016 ). Among these lentil ( Lens culinaris Medik.) holds the vital place. Nepal is one of the world’s top lentil producing countries, ranking fifth and contributing about 4.35% to the global area and production (Ghimire et al., 2024 ). In South Asia where half of the world’s lentils are grown, Nepal plays a key role. Winter lentils are the most important legume crop in the country, making up 65% of total pulse production and 63% of the area used for pulses (Dhakal, 2021; Ghimire et al., 2023 ). Lentils are grown on about 213,000 hectares and produce nearly 263,000 tons annually (MoALD, 2021 ), supporting the livelihoods of around 700,000 farming households (USAID, 2011 ). Nepali lentils are valued for their small size, bright pink color, taste, cooking quality, and high micronutrient content including iron and zinc (Darai et al., 2017 ). They are in demand domestically and internationally, contributing to income generation, employment, and exports (USAID, 2011 ). However, lentil remains less prioritized than cereals and vegetables and is often grown under low-input, rain-fed conditions. Prioritizing lentil is crucial for enhancing food security and rural livelihoods (Gautam et al., 2022; Ghimire et al., 2022 ). However, the lentil value chain in Nepal faces several structural and systemic challenges. In developing countries like Nepal, value chains are often long and fragmented (Trienekens, 2011 ), burdened by low investment, weak infrastructure, transport delays, high transaction costs, and unpredictable regulations (Adhikari et al., 2024 ). Most farms are small-scale, traditional, and fragmented, with farmers lacking technology and market knowledge, resulting in low yields and quality (Kumar et al., 2020). Farmers face market uncertainties, while processors and traders struggle with unreliable quantity and quality. Farmer groups and cooperatives are weak compared to private traders, limiting benefits for members. Traders and processors often mention small, fragmented, and irregular supplies and poor product quality as major challenge in the sector (Neopane et al., 2021). Agricultural commercialization depends on efficient resource use and sustainable commodity value chains that minimize risks (Ghimire et al., 2024 ). Assessing sustainability is complicated by multi-stakeholder relationships and diverse services (Josserand, 2018). In addition to these structural gaps, farmers are highly exposed to risks stemming from climate variability, pests, diseases, and price volatility (Cervantes-Godoy et al., 2013 ). Risk aversion and lack of coping mechanisms constrain the adoption of sustainable practices (Cheng, Yip & Yeung, 2012 ). Further, globalization and fragmented production processes pose key challenges to the environmental, social, and economic sustainability of agricultural value chains, generating complex risks (Adamowicz, 2021 ). Technology adoption improves productivity and sustainability, but risk aversion especially among smallholders, hinders uptake, making effective risk management essential for policy and innovation. Mapping value chain interactions helps identify factors influencing agribusiness performance (Zamora, 2016 ). Yet sustainability is increasingly critical due to evolving regulations, societal expectations, and value addition that jointly impact poverty and hunger reduction (FAO and UNDP, 2020). Despite many studies on agricultural commodity value chains, there is still limited research that looks at both production risks and value chain sustainability. While lentil production, trade and export trends have been studied, few have focused on how farmers perceive risks, how they cope with them, or how sustainable the overall value chain is. This is especially important for Nepal, where lentils play a key role in rural livelihoods and national exports but are often grown under uncertain and risky conditions. In this regard, this study aims to fill that gap by using both qualitative and quantitative methods to explore risks, sustainability, and coordination within the lentil value chain. It applies a triple bottom line framework and econometric analysis to understand economic, social and environmental aspects of sustainability and associated risks dimension. The findings are expected to support better policies and practical actions supportive to Agriculture Development Strategy (ADS, 2015) and SDG2 that strengthen the lentil sector and make it more resilient. The tools and approach used here can also be useful for studying other crops and regions. The study specifically aims to: Identify and analyze key production and marketing risks and risk management strategies in lentil farming Assess the sustainability of the lentil value chain in triple bottom line framework Provide evidence-based insights to support policy and institutional decisions that strengthen the lentil sector 2 Theoretical background and literature review 2.1 Sustainability assessment of value chain; Triple Bottom Line Approach (TBL) Awareness of sustainability has grown significantly in recent years, becoming an increasingly important concern across society, leading to greater interest in this subject among academics and experts (Correia, 2019 ). The value chain sustainability is an activity of adding values from raw agriculture production and its transformation to specific products for the final consumer and disposed later in a way that is lucrative all over the chain, broad social welfare, and does not exhaust the natural environment in the long term (Neven, 2014 ). The sustainability delivers values and gains in the present along with assured benefit to the future generations (Alhaddi, 2015 ). The Triple Bottom Line (TBL) approach, coined by Elkington ( 1997 ) and emphasized by Goran and Wagner ( 2015 ), focuses on people, profit, and planet, highlighting social equity, environmental quality, and economic benefits for sustainable development (Elkington, 1998 ). It offers a framework for assessing how well a company is performing in each of these three areas. Goel ( 2010 ). Loviscek ( 2020 ) emphasized TBL as a sustainable chain management framework, assessing social, human, and environmental impact alongside profitability (McKenzie, 2004 ; Savitz & Weber, 2006 ). The environmental aspect, often overlooked, is crucial for economic development and monetization (Nogueira et al., 2023 ; Slaper & Hall, 2011 ). The widely accepted nested spheres model, or Venn diagram (Fig. 1 ), illustrates the convergence of these elements in sustainability (Correia, 2019 ). Economic dimension (Profit) The Economic Dimension (Profit) of the Triple Bottom Line (TBL) examines how a company’s business activities influence the broader financial system, with an emphasis on the value it generates (Elkington, 1997 ). It also considers the societal effects of the company’s economic performance, viewing the economy as a key component of sustainability that ensures support for future generations (Spangenberg, 2005 ). Social dimension (People) The social dimension (People) refers to the influence of an organization on the citizen’s wellbeing (Engardio et al., 2007 ) and involves performing business culture that benefit human capital, labor, and to the public as a whole (Elkington, 1997 ). These practices contribute value to society and community. Environmental dimension (Planet) The environmental dimension, often referred to as 'Planet,' focuses on practices that protect and conserve environmental and natural resources for future generations, while still delivering value in the present. Incorporating the Triple Bottom Line approach includes the implementation of sustainable supply chain management, which integrates social, economic, and environmental considerations into the operations of the supply or value chain, ensuring that sustainability is addressed across all areas of performance (Moreno & Salgado, 2012 ). 2.2 Agriculture production risk factors and management strategies Agriculture is essential for human food production, yet it involves numerous risks (Kay et al., 2012 ; Olson, 2011 ). Ellis (1988) categorized agricultural risks into four types: natural threats (such as pests, diseases, and weather), market fluctuations (output prices), social uncertainty (resource conflicts), and state activities and wars, all impacting farmers' livelihoods. Hardaker et al. ( 2004 ) identified price, transaction and yield as three primary risk categories in agriculture. Hazell and Norton ( 1986 ) argue that farmers' responses to different hazards are influenced by their farming systems, environmental conditions, policies, and institutional frameworks, which ultimately shape their decision-making processes. Yield inconsistency in agriculture production arises due to numerous uncontrollable factors, predominantly associated with weather irregularities, such as inadequate rainfall, diseases outbreak, and pest introduction. These risks are primarily caused by natural phenomena (Valdes & Konandreas, 1981 ). Yield risk is measured by CV (coefficient of variation), which shows the variation relative to the average yield (Hardaker et al., 2004 ). 2.3 Risk management strategies Farm size, creativity, age, experience, and risk sensitivity influence farmer’s preferences of risk management strategies, making it essential to identify sources of risk to select the appropriate strategy farmers (Pennings, et al., 2008). Identifying risk sources is vital for effective agricultural management strategies. Factors such as farming ecosystem, agricultural income, and the land size affect how risks are handled. Risk tolerance behavior of a decision maker influences the types and scales of agricultural methods, impacting the production structure and stable growth of household income (Wencong et al., 2006). Evans and Ngau (1991) suggest that farm households can boost performance by expanding land, investing in inputs, hiring staff, switching to cash crops, or selling more yield, enhancing productivity and sustainability. In Nepal, subsistence farmers face greater harm from production risks than market risks due to their reliance on domestic consumption of their produce. Unmanaged farming hazards negatively impact the economy, farmer well-being, and agricultural productivity (Chhetri, 2019). Without timely risk management, the sustainability of the farming industry is threatened, as neglected farms may become unfit for future generations (Hardaker et al., 2015; Shrestha & Nepal, 2016). For agricultural practices to be sustainable in the long term, it is essential to manage and mitigate the associated risks. This research studied lentil production risk dimension to identify key production risks and management strategies for a resilient lentil production system. 3 Research Methods 3.1 Sampling and data collection methods 3.1.2 Study area and data collection procedure This research used different types of primary dataset and followed the standard ethics during the data collection procedure. Desk review and piloting survey were done to develop coordination schema. Using Cochran’s formula (Cochran, 1963 ), 473 lentil producers were surveyed from four major producing districts: Rautahat, Dang, Bardiya, and Kailali in 2022. Following the lentil harvest, a trader-level survey was conducted in 2022/23 across 12 major markets of Nepal. Based on the coordination schema, a well-designed and pretested semi-structured interview schedule was developed and used for data collection. Both simple random sampling and purposive sampling techniques were applied. Primary data from traders in the lentil value chain were collected through face-to-face interviews and phone calls. The selection of traders was supported by information from farmers tracing the product flow along the chain. 3.1.2 Focus group discussions and key informant interviews Data collection was further supported, validated, and supplemented through focus group discussions (FGDs). Four FGDs at the production level and two FGDs at the trader level were conducted using checklists. These qualitative discussions gathered information on current production status, associated risks, risk management, marketing situations, value chain governance, and opportunities for sustainable lentil chain improvement, including strengths, weaknesses, opportunities, and threats. Additionally, 12 key informants from directly related stakeholders were interviewed. These included government officials, public representatives, and members of chambers of commerce and industry, covering all major markets. Key informant interviews are qualitative, in-depth interviews with knowledgeable community members who understand the local context and trends (Kumar, 1987 ). The expert insights from key informants, representative views from focus groups, and business enabler surveys formed the basis of the assessment. 3.1.3 Observations Direct and participatory observations were also conducted covering logistics, cultivation practices, harvest, postharvest handling, transportation, processing, storage, weighing and packaging, trading, waste, and by-product management. Participatory observation is an effective approach to gather locally grounded information, especially when the value chain is not well documented (Stein and Barron, 2017 ). 3.1.4 Sample size and survey methods The study surveyed 473 farmers at the production level using a semi-structured questionnaire through face-to-face interviews. At the trader level, 155 traders were surveyed using a similar questionnaire administered both via face-to-face interviews and phone calls. Additionally, a business enablers survey targeted farmer and trade associations, private sector actors, I/NGOs, and government sector representatives. This survey included 85 respondents and was conducted online through Google Forms and direct visits. 3.2 Methods and technique of data analysis Both descriptive, analytical and inferential statistical tools were used for data analysis. To fulfil the specific objectives collected data were made entry in Microsoft excel sheet and processed. Analytical tools used were value chain map, indexing, scaling, and sustainability performance assessment. In order to have a visual representation of the whole chain, common chain was mapped with product, money and information flow along the actors. Analysis specifying function of each actor across the chain was mentioned within the map. Lentil value chain governance with information flow and linkage between the actors was analysed to show how the chain was performing. Further, Seemingly Unrelated Regression (SUR) model was used following Exploratory Factor Analysis to analyse production risks and influencing factors for adoption of risk management strategies. All statistical tests were performed with the use of MS-Excel and STATA version 14 software. 3.2.1 Value chain sustainability assessment For the sustainability assessment of lentil value chain in Nepal, 85 responses including progressive farmers, key informants, business enablers, government and private sector stakeholders from all value chain stages and scientific domains were taken using google forms to assess and quantify the level of social, economic and environmental dimensions in Nepal. Further, suggestions were recorded from focus group discussions. The selection of the sustainability indicators depends on the level of the organization and the type of activities or sectors (Moreno and Salgado, 2012 ). Once the main processes of the value chain are mapped, indicators must be associated to each segment, for all three sustainability dimensions-TBL (Moreno and Salgado 2012 ). For judgment Sustainability Assessment of Food and Agriculture (SAFA) Systems Guidelines from the FAO ( 2014 ) was adopted which were developed for assessing the impact of food and agriculture operations on the environment, economy, and society. The SAFA tool has been widely used for sustainable agriculture assessments in developed and developing nations (Leknoi et al., 2023 ). For this study, the selection of triple bottom-line sustainability indicators (economic, social and environmental) specifically adapted to the context of lentil value chain and proposed a multidimensional sustainability assessment based on a set of 32 criteria. Each indicator was also evaluated by experts qualitatively to grasp the real scenarios towards the sustainable lentil value chain which helps to penetrate the local and global market. The selected sustainability indicators that relate to the economic, social, and environmental elements of the lentil value chain in Nepal are shown in Table 1 . As followed by Gebre and Rik ( 2016 ), the assessment was done by a qualitative method with five score categories. Five points score value (1 = unacceptable situation, 5 = best situation) with regards to each different 32-dimensional indicators were applied and obtained result for each indicator was converted into scores on a percentage scale and interpreted based on decision criteria (Table 2 ). Average judgement rating = average of all responses on particular indicator Performance score (%) = average rating on particular indicator/ maximum possible score (5) Performance score (%) on theme = Sum of average ratings on indicators under the theme/ maximum possible score for theme Table 1 Selected Triple Bottom-Line Indicators for Sustainability assessment of the lentil Value Chain Economic Social Environmental Scalability Inclusiveness Agrobiodiversity conservation Market demand Gender equality Use of chemicals Added value share Potential to engage small scale poor farmers Resilience Value adding activities Rural employment opportunity Land restoration Market diversity Farming method technological innovations Soil fertility enhancement Competitiveness Storage facility Profitability Value chain stakeholder relations and support Fair trade and price Fair income distribution along the chain Supportive to household food and nutrition security Fair/unbiased wage system Opportunity for household income generation Child/forced labor Potential to use local resources Grievance handling mechanism Availability of inputs Farmers bargaining power Associated risks management Dependency for seed Government support and scheme (Sources: Author's construction based on Gebre and Rik ( 2016 ), SAFA-FAO ( 2014 ), and KIS, 2022) Table 2 Decision criteria based on score value Points scored Percentage scored Chain performance rating 5 80–100 Best 4 60–80 Good 3 40–60 Moderate 2 20–40 Limited 1 0–20 Unacceptable (Source: Adopted from Gebre and Rik, 2016 ) 3.2.2 Scaling technique A five-point Likert scale was used to assess farmers’ perceptions of risk factors and the strategies they adopt in lentil farming. A total of 473 lentil farmers were interviewed and asked to rate the importance of selected risk factors and management strategies. These items were developed based on focus group discussions and a pilot survey, resulting in seven key risk factors and eighteen risk management strategies included in the questionnaire. The Likert scale was chosen for its ease of use, reliability, and ability to reflect subjective evaluation more effectively than smaller scales (Taherdoost, 2019 ). For each item, farmers rated their perception on a five-point scale. For risk occurrence, the categories were: very unlikely (1), unlikely (2), sometimes (3), likely (4), and very likely (5). For management strategies, responses were: strongly disagree (1), disagree (2), neutral (3), agree (4), and strongly agree (5). Each item was scored using weighted average means to calculate an index value using the formula: I_inf = ∑ (s i × f i ) / N, where s i is the scale value, f i is the frequency of responses, and N is the total number of respondents. The scale values were determined as 1, (1–1/n), (1–2/n), …, (1–5/n), where n is the number of ranking categories. A mean score above 2.5 was interpreted as indicating high risk occurrence or strong agreement with adoption of a strategy, while scores below 2.5 were considered low. After scoring, factor analysis was used to reduce the number of variables and identify key underlying dimensions for both risk factors and management strategies. 3.2.3 Exploratory factor analysis (EFA) model specification Exploratory factor analysis was applied for this study to create a summary latent variable (factor) for a large number of variables of risks and management strategies. Following Tabachnik and Fidell (2007), factor analysis model presented as; $$\:Xi=\alpha\:j1F1+\alpha\:j2F2+\dots\:\alpha\:jmFm+\epsilon\:j$$ Where; j = 1, 2, 3, 4. .. p indicates number of variables, Xj represents j-th variable, αjm denotes factor loading of j-th variable on m-th factor, Fm represents factor m, εj indicates unique factor. EFA is a type of technique that analyses the uni-dimensionality (characteristics) of each of the defined risk management practices (Bartholomew et al., 2011 ), in order to reduce it to a common score (smaller number of factors) by examining relationships among these quantitative factors (Pallant, 2013 ). In conducting factor analysis, two methods are mostly commonly used, namely, principal axis factoring and principal component analysis. In this study, principal axis factoring with varimax rotation was employed. The justification for this was that principal axis factoring does not assume that all of the variables (items) included in the study account for 100% of the variance. Therefore, principal axis factoring categorizes the total variance into common variance, unique variance and error variance; however, principal component analysis assumes that there is no error variance, which means that the total variance of the variable is accounted for by its components (Rietveld and Van Hout 1993 ). In connection to this, factor loading indicates the contribution of the variable to each factor. A factor loading of 0.30 or greater is considered statistically meaningful (Tabachnick and Fidell 2007 ). The larger the factor loading, the more the variable has contributed to that factor (Harman 1976 ). The factor analysis produced factor score, also known as a factor loading, is a measurement that correlates a particular variable to a given factor. When a factor score is high, this suggests that there is a notably strong connection between a certain factor and a common variance in the observed data. The magnitude of the factor score (loading) determines the number of factors to retain. The extracted number of factors represented the risk management strategies employed by the farmers. To confirm whether the data from the measurements was sufficient for factor analysis (test the validity), the Kaiser-Meyer-Olkin (KMO) test (Lorenzo-Seva et al., 2011 ) and the Bartlett’s sphericity test (Hair et al., 2006 ) were performed. In the KMO test, as the values of the test vary from 0 to 1, values above 0.7 are recommended as being desirable for applying EFA (Hair et al., 2006 ) and a statistically significant Bartlett test (p < 0.05) indicates that sufficient correlations exist between the variables to continue with the analysis (Hair et al., 2006 ; Pallant, 2013 ). Diagnostic tests in Factor analysis Factors with Eigen values greater than 1, Bartlett’s Test of Sphericity (p < 0.05) and the Kaiser-Meyer-Olkin Measure (KMO) of Sampling Adequacy (cut-off of above 0.40) were taken into consideration. If this requirement is not met, distinct and reliable factors cannot be produced. However, if this problem occurs, it can be solved by increasing the sample size (Yong and Pearce 2013 ). This technique enabled the researchers to manage and reduce the number of original variables into a smaller group of new correlation components, which are linear combinations of the original variables. The Kaiser-Meyer-Oklin (KMO) method measured the appropriateness for component analysis of data sets (Kaiser 1960 ). The KMO index varies from 0 to 1, with results of 0.6 or greater suitable for component analysis. The latent root criterion (eigenvalue > 1) was used to determine how many components to retain in each data set to extract. After the numbers of components were identified, the varimax rotational method was performed in order to minimize the number of variables that have high loadings on each component. A component loading of ± 0.4 was employed as a cut off criterion to determine the inter correlation among the original variables accepted in this study. 3.2.4 Seemingly Unrelated Regression (SUR) model Based on the factor analysis, the main risk management strategies were identified and used for further analysis in the seemingly unrelated regression model (SUR) to identify the determinants of production risk management strategies since more than one risk management strategy was continuous. The SUR model allowed correlations among the residuals of each dependent variable. The SUR model is an extension of the multiple linear regression models and is used to estimate several continuous dependent variables jointly (Gujarathi 2004 ). According to Zellner ( 1962 ), the SUR model is specified as; Y im = B 0 + B m X im + ε im Where Yim (m = 1, 2, 3. .. k) represents the dependent variables which indicate the factor score for each risk management strategy chosen by the i th farmer, B 0 represents the constant term, B m represents coefficients of explanatory variables, X im represents explanatory variables and εim represents the error terms. The above equation can be interpreted for each risk management strategies (m) as; Y* i1 = γ + B 1 X i1 + ε i1 , Y* i2 = δ + B 2 X i2 + ε i2 , Y* im = φ + B m X im + ε im In this study, the factor scores obtained from the factor analysis output were used as the dependent variables in SUR model. The SUR model is estimated by the usual ordinary least square method (Cappellari and Jenkins 2003 ), and the model allows correlation between residuals (Belderbos et al. 2004 ). The test for correlation between residuals was carried out using the Breusch–Pagan test of independence. Before commencing the SUR model, a test for multicollinearity using variance inflation factor (VIF) was employed. 4 Results and Discussion 4.1 Lentil value chain governance The concept of “value chain” was introduced by Porter ( 1985 ) to describe all activities essential to transform a product from beginning to final consumption. Gibbon ( 2001 ) described a value chain as a sequence where products gain value at each stage. This study identified six major actors in the Nepalese lentil value chain: input suppliers, producers, collectors, processors, distributors (wholesalers and retailers), and consumers (Fig. 2 ). The value chain map reveals how diverse businesses interrelate, exposing stakeholders and their roles (Gebre et al., 2020 ) and serves as an entry point for smallholder inclusion (Lundy et al., 2014 ). Agricultural value chain mapping includes direct and indirect actors, networks, and external influencers (Lundy et al., 2012 ). The lentil chain in Nepal shows actors performing activities at various scales but mostly small and informal, lacking credit, technical skills, and facing high transaction costs and information asymmetry leading to market distortions. Producers’ input needs remain unsatisfied in quality, quantity, and timing, with limited alternatives and price differentiation. Lentil moves as a raw product up to processors, after which it is sold as whole or split lentil domestically and overseas. Information flows vertically and horizontally among traders but farmers receive limited horizontal information. Local collectors, communicating with processors, set low prices on fresh lentil due to farmers’ weak bargaining power and lack of storage. Farmers sometimes form groups or cooperatives to access better market information and bargaining but lack infrastructure and business skills. About 52% of traders provide short-term credit to suppliers, yet 82.8% of households accept buyer-determined prices with only 17.2% able to negotiate, reflecting a buyer-driven chain where large collectors and processors dominate price setting (USAID, 2011 ; Zamora, 2016 ). Value chain governance is immature and informal with absence of mutual trust. Producers operate individually, restricting bargaining capacity, while large collectors and processors dominate, influencing prices to their advantage. Exporters and processors maintain contacts with international buyers but report delays in payments. Actors participate mainly for profit and lack services or information-sharing mechanisms. Improvements in value chains and marketing play a crucial role in farm-level profitability and commercialization but product flows lack adequate value addition, branding, and after-sale services (Neupane et al., 2013 ; USAID, 2011 ). Developing sustained lentil value chains requires access to resources and formal networks often beyond local producers’ reach. Incentive systems such as performance rewards, price premiums, profit-sharing, and market access are nearly absent (Zamora, 2016 ). A holistic approach is needed to ensure economic prosperity, environmental protection, and social integrity across the chain (Asif et al., 2011 ). In the study area, seven frequently used lentil marketing channels were identified, with a total of 1,021 metric tons supplied by sample respondents to end users through various intermediaries. The largest volume, 44.56%, moved through the channel where lentils passed from producers to local collectors, processors, wholesalers, retailers, and finally consumers, reflecting the high capacity of local collectors to purchase directly from farmers. Other significant channels included producer-large collector-processors-wholesalers-retailers-consumers (18.41%) and producer-local collector-processors-retailers-consumers (11.26%). Smaller shares were observed in channels involving direct producer-consumer sales (4.02%) and producer-large collector-retailer-consumer (3.62%), the latter being the smallest due to retailers’ limited capacity to sell whole lentils without processing. Cooperatives also played roles as producers and aggregators, supplying lentils to local or distant collectors. 4.2 Sustainability performance assessment of lentil value chain A sustainable value chain is an economically viable, socially just and environmentally friendly way of production, and addition of value to the product until it makes it to the consumer (Subedi, 2017 ). The sustainability of the lentil value chain in Nepal was assessed through selected 32 different indicators based on economic, social and environmental theme. These indicators were based on guidelines adopted from FAO ( 2014 ) SAFA, (Gebre and Rik, 2016 ) and discussions with experts and stakeholders related to lentil value chain in Nepal. Based on this result, the overall lentil value chain sustainability performance was found at moderate level with average judgement rating of 2.99 and performance score 59.80% (Table 3 ). Similar to this result, Subedi ( 2017 ) opinioned that among the existing ones, very few value chains are efficient and render smooth flow of quality input materials to farmers and agro product to consumers in Nepal. Assessment resulted that the economic and environmental dimension rated at good level whereas, social dimension was rated moderate level of sustainability. Similar study conducted by Gebre and Rik, ( 2016 ) reported moderate level of sustainability within banana value chain in Ethiopia. Also, Gebre et al., ( 2022 ) reported economic, social, and environmental indicators have moderate sustainability performance in their study on banana value chain sustainability assessment at Ethiopia. Likewise, Barua and Rahman, ( 2021 ) resulted moderate level of sustainability in all economic, social and environmental dimensions of goat value chain in Bangladesh. The sustainability results for each indicator on the percentage scale and overall performance based on theme was presented in heatplot (Fig. 3 ). Table 3 Summary of lentil value chain ratings by sustainability dimensions in Nepal (Source: lentil business enablers survey, 2023; KIS, 2023 & FGD, 2023) Economic sustainability There were 14 indicators based on economic dimensions with average judgement rating of 3.06 and performance score in percentage 61.15%. Based on this rating and percentage score economic sustainability level for Nepalese lentil value chain was found at good level. However, within the economic theme, moderate (6 indicators) to good (8 indicators) level of sustainability were found for the assigned indicators ranging from 46.43 to 73.57 percentage score (Fig. 3 ). Lentil value chain in Nepal found higher sustainability score with scalability, market demand, support to household food and nutrition security, support to household income, profitability, market diversity, potential to use local resources and competitiveness. In contrast, lower performance score was found with the indicator availability of inputs, associated risks and crop failure, added value share, value adding activities, government support and subsidy schemes. These findings align with CRS ( 2018 ), which reported low marketable surplus, government incentives and significantly fluctuating lentil prices hindering economic participation and benefits in the lentil value chain in Nepal. Interestingly, despite storage and value addition being reported as key bottlenecks in the lentil value chain, most farmers expressed satisfaction with outcomes related to profitability and employment. This suggests that, while structural inefficiencies persist, the sector continues to deliver meaningful economic benefits to smallholders. Social sustainability Social sustainability aspect of lentil value chain in Nepal was found at moderate level. The social indicators were found poorly addressed along the lentil chain in Nepal compared to economic and environmental. There were 13 indicators based on social dimensions with average judgement rating of 2.90 and performance score 57.95%. Based on this rating and percentage score social sustainability level for Nepalese lentil value chain was found at moderate level. However, within the theme, moderate (8 indicators) to good (5 indicators) level of sustainability were found for the assigned indicators ranging from 51.43 to 68.33 percentage score. Social dimensions of lentil value chain in Nepal found higher sustainability score with inclusiveness, gender equality, potential to engage small scale poor farmers, rural employment opportunity and farming method and technological innovations. Whereas; lower performance score was found with the indicator storage facility, stakeholder relations and support, fair income distribution, fair/unbiased wage system, grievance handling mechanism, farmers bargaining power and dependency for seed. From the study area it was found that there was no long-term business relationship between producers and traders and lack trust in relationship leading to distortion of the chain. Similar to this result, Subedi ( 2017 ) reported lack of coordination among the actors of value chain at different level has caused loss and degradation of agro products in Nepal. Environment sustainability Environment sustainability aspect of lentil value chain in Nepal was found at good level. This reflects that the lentil value chain is environmentally friendly in Nepal. The environmental indicators were found adequately addressed along the lentil chain in Nepal. There were 5 indicators based on environmental dimensions with average judgement rating of 3.04 and performance score 60.80%. Based on this rating and percentage score environmental sustainability level for Nepalese lentil value chain can be indicated at good level. However, within the theme, moderate (2 indicators) to good (3 indicators) level of sustainability were found for the assigned indicators ranging from 55.71 to 64.52 percentage score. Environmental dimensions of lentil value chain in Nepal found higher sustainability score with indicators agrobiodiversity conservation/conservation of local seeds, resilience and soil fertility enhancement. Whereas; lower performance score was found with the indicator use of chemicals and land degradation. The economic, social and environmental sustainability indicators for the lentil value chain showed at moderate level of performance providing evidence of the positive effect and scope in the country with sustainable development of the lentil sector in Nepal. The chain has an advantage in terms of scalability, profitability, employment, market demand, competitiveness, income as well as food and nutrition security, inclusiveness and gender equality biodiversity conservation, Resilience and soil fertility enhancement. Thus, lentil sector value chain in Nepal can be upgraded and strengthened as inclusive, pro-poor and nutrition sensitive value chain model. Similar to this result, Gautam et al., ( 2023 ) reported an inclusive, competitive and sustainable lentil seed system can be established through a value chain approach in Nepal. Similarly, there is a need to create a new system of agriculture transformation that addresses existing barriers and unaffordable policies to support high level entrepreneurial spirit among actors (Alex et al., 2015 ). 4.3 Production risks and marketing constraints In this study, during focus group discussion 7 types of major risks were realized by farmers in lentil farming. Individual responses from the sampled farmers were taken for occurrence level for each risk factors. Farmers perceived climatic hazard as a major risk and highly occurrence with mean score value 4.11 followed by incidence of disease with mean score 3.86 (Fig. 4 .). Similarly, occurrence of crop failure, lower farm income and unreliable market were ranked third, fourth and fifth with mean score value 3.37, 3.13 and 2.94 respectively. Erratic rainfall during flowering phase, flooding and drought within the crop period and frequent incidence of Stemphylium blight diseases leading to crop failure and low yield are major challenges perceived by majority of farmers in the study area. Similarly, based on index value among various marketing related challenges, price fluctuation with index value 0.9 was listed as the major trade related challenge creating risks in lentil sector. Similar to this result, Gautam et al., ( 2023 ) also mentioned price fluctuation as a major problem with index value 0.783 mainly as a result of scientific pricing mechanism. Likewise, low quality and volume of lentil availability (0.71) and poor linkages with value chain actors (0.60) were also the challenges in lentil marketing system in Nepal followed by poor lacking market related infrastructures and irregular demand and supply (Fig. 5 ). 4.4 Lentil production risk assessment 4.4.1 Risk analysis on yield, revenue, and profit of lentil In agriculture, the main risk categories include financial, price, production, economic, and personal risks, which arise from various interconnected factors. Table 4 compares production, financial, and profit risks based on variance analysis, showing that yield and profit risks were similar, while cost risks were notably lower. The coefficient of variation (CV) analysis showed that financial and cost risks are relatively lower (0.83) than those related to lentil yield (1.05) and profit (1.08). The coefficient of variation for yield and profit exceeded 1, indicating high variability and exposure to climate and input-related risks. The small variation in input usage suggests a low cost risk. However, the high variation in output, likely due to farmers' seed choices and fluctuations in market supply and demand, makes yield and price risks the most critical. Supporting this, Haile et al. ( 2017 ) also reported that yield and market-related price risks significantly affect to global food supply. Based on this result, to minimize the risks of yield, high-yielding varieties should be made available to all the farmers with a package of practices that accelerate production. Similarly, profit risk can be minimized by the provision of a minimum support price of lentil and facilitating the creation of a strong lentil value chain linkage. Table 4 Comparison of yield, cost, and profit risks in lentil farming Yield risk Value Financial/cost risk Value Profit risk Value Total production (kg) 118780.5 Total Variable Cost (NPR) 6272877 Total profit (NPR) 10820920.6 Average Production (kg) 251.12 Average Variable Cost (NPR) 13261.9 Average profit (NPR) 22877.21 Variance 70004.52 Variance 1.22e + 08 Variance 6.17e + 08 SD 264.58 SD 11052.4 SD 24830.72 CV 1.053 CV 0.833 CV 1.085 Source: Field survey (2022) 4.4.2 Associated risks factors perceived by lentil farmers in production system Risk perception is a subjective judgment which measures the probability and the consequences of some uncertain events (Sjoberg et al., 2004 ). In this study, during focus group discussion 7 types of major risks were realized by farmers in lentil farming. Individual responses from the sampled farmers were taken for occurrence level for each risk factors and responses regarding risk aversions statement. Farmers perceived climatic hazard as a major risk and highly occurrence with mean score value 4.11 followed by incidence of disease with mean score 3.86. Erratic rainfall during flowering phase, flooding and drought within the crop period and frequent incidence of Stemphylium blight diseases leading to crop failure and low yield are major challenges perceived by majority of farmers in the study area. Similarly, occurrence of crop failure, lower farm income and unreliable market were ranked third, fourth and fifth with mean score value 3.37, 3.13 and 2.94 respectively. About 47 percent of farmers perceived very likely occurrence of climatic hazard and 49% perceived likely occurrence of disease in lentil farming in the study area. Inputs availability and lack of credit risks were also perceived but with least occurrence among the identified risks in lentil production in the study area. The farmers in the study area found inaccessibility of improved seed and were also unable to purchase and use high yielding varieties; therefore, they opted to use their own home saved seed. The non-availability of fertilizers for lentil crop and treating lentil as a crop with no fertilizer required was the other crucial problem that affected the production potential of lentil producers in the study area which in turn negatively affected the production and market potential of the farmers. Lack of credit with the lowest mean score of 2.51 was perceived to be least important risk factor for lentil farmers in the study area may be due to involvement in groups and cooperatives and easy access to credit facility through their membership organization. The details about the risk factors and level of occurrence based on five-point scale as perceived by sampled farmers are presented in Table 5 . Table 5 also presents ranks of the mean scores to show which of the 7 risk factors were important in lentil production for the farmers in the study area. Table 5 Farmer perceived responses on level of risks occurrence and their rank Associated risks Level of occurrence (%) Mean score Rank by mean SD Very unlikely Unlikely Sometimes Likely Very likely Crop failure 2.54 16.91 39.96 21.56 19.03 3.37 3 1.05 Climatic hazards 0.00 5.29 25.16 22.20 47.36 4.11 1 0.96 Inputs unavailability 8.67 26.43 45.88 14.16 4.86 2.80 6 0.95 Incidence of disease 0.00 5.50 24.10 49.05 21.35 3.86 2 0.81 Lower income 5.07 22.41 38.05 23.04 11.42 3.13 4 1.04 Unreliable market 7.40 27.06 33.83 26.85 4.86 2.94 5 1.01 Lack of credit 20.72 36.36 18.82 18.82 5.29 2.51 7 1.16 Source: Own computation result based on survey data (2022) 4.4.3 Exploratory Factor Analysis The seven risk factors were subjected to EFA to assess their validity and reliability. The results report the suitability of the data to be analyzed, factor extraction and rotation, and interpretation. The result in Table 6 suggested that three factors were retained as a principal-component factors of associated risks with Eigen value greater than 1. Based on Kaiser’s criterion, the 7 risks items were reduced to 3 factors as a result of varimax rotated principal-component factor analysis for perceived risks by lentil farmers in the study area. The Kaiser-Meyer-Olkin (KMO) sample adequacy test result showed a value of 0.573 and a Bartlett’s test value (Chi2 = 130.15, p < 0.000) implied that sufficient and reliable factors were produced (Bartlett, 1951 ). These results suggest that factor analysis could be conducted with the data. The number from the varimax rotation resulted the factor loading which depicts the strength of the relationships between the items included and the factors. The magnitude of the factor loading determines the number of factors to retain. In addition to this, the mean associated with each item indicates the relative importance of the risks in the study area. Three of the risk management strategies were named as market and institutional risk, production risk and climatic and input risk, and the naming of each factor was done based on the characteristics of the items included within that factor. Table 6 Varimax rotated factor loadings of perceived risks by lentil farmers Perceived risks Factor loading 1 2 3 Crop failure (R1) -0.0445 -0.7216 0.2102 Climatic hazards (R2) -0.3666 -0.0394 0.6650 Inputs unavailability (R3) 0.1724 -0.0877 0.8138 Incidence of disease (R4) -0.5866 0.3747 0.0655 Lower income (R5) 0.0493 0.7614 0.0508 Unreliable market (R6) 0.6911 0.2144 0.2002 Lack of credit (R7) 0.6321 0.0763 -0.1793 Principal-component factors and variance Eigenvalues 1.52684 1.30683 1.08594 Total variance explained 0.2181 0.1867 0.1551 Cumulative % of variance explained 0.2181 0.4048 0.5599 Diagnostic tests Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.573 Bartlett's Test of Sphericity 130.15*** Source: Own computation result based on survey data (2022) Note: Factor 1= Market and Institutional, 2= Production, 3= Climatic & input. Loadings of greater than 0.4 are in bold. 4.4.4 Risk management strategies adopted by farmers Farmers’ perceptions of and responses to risk are important in understanding their risk behavior and management. The welfare of the farm family and survival of agri-business depends on how well farming related risks are perceived and managed (Hardaker et al., 2004 ). According to the result of this study as presented in Table 8 , crop diversification, saving seed for next year, involvement in cooperatives were the major risk management strategies followed by lentil farmers in the study area with mean score value 4.09, 4.02 and 3.60 respectively. Similar to this result, Sapkota ( 2021 ) mentioned crop diversification as the most important risk management strategy followed by farmers in Nepal. Likewise, diverse income source, saving income, having strength and trusted relationship especially with local collectors, having own irrigation facility, using disease resistant improved varietal seed, access to information and buying seed from authentic sources were also some of the strategies adopted by farmers. Buying seed from authentic sources, frequent contact with agri-technician, making formal/informal contacts with buyer, listening agriculture programs and using mobiles applications were the strategies least adopted by the lentil farmers in the study area. Among 18 strategies, farmers disagreed on adoption of 6 different strategies which were insurance scheme, information on climatic parameters, use of drought/flood resistant improved varieties, buying and saving inputs for lentil crop, use of disease resistant varieties and storing of grains for certain time period. The details about the risk management strategies adopted by sampled farmers and their rank are presented in Table 7 . Table 7 ranks the mean scores among 18 strategies adopted by the farmers in lentil production. Table 7 Mean score and rank for risk management strategies adopted by lentil farmers Label Risk management strategies 1 Mean score SD Rank by mean RM1 Crop diversification 4.09 1.05 1 RM2 Buying seed from authentic sources 2.63 1.12 9 RM3 Possession of off farm income source 3.32 1.41 4 RM4 Adoption of insurance scheme 1.57 0.63 17 RM5 Taking information regarding climatic parameters 1.82 0.84 13 RM6 Having own irrigation facility 2.78 0.97 7 RM7 Use of drought/flood resistant improved varieties 1.63 0.67 16 RM8 Saving own produce for seed 4.02 0.91 2 RM9 Saving inputs like fertilizer for lentil season 1.35 0.47 18 RM10 Regular contact with agri-technicians 2.46 1.21 11 RM11 Listening agriculture programs, and using ICTs 2.71 1.14 8 RM12 Adoption of disease resistant varieties 1.77 0.80 15 RM13 Storage for fetching higher price 1.81 0.78 14 RM14 Search alternative potential buyers 2.52 0.88 10 RM15 Formal/informal contracts with buyer 2.05 0.73 12 RM16 Establishing trusted relationship with buyers 2.99 1.21 6 RM17 Saving money in bank 3.19 1.17 5 RM18 Involvement in a cooperative 3.60 1.15 3 Source: Own computation result based on survey data (2022) 1 Mean score (1 = totally disagree, 5 = totally agree) Following the descriptive analysis of the important risk management strategies, a factor analysis was performed, as shown in Table 9 . The Bartlett test of sphericity was significant at 1% level. The null hypothesis was therefore rejected indicating that the variables are correlated and factor analysis is appropriate for the data. The result of the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO test) was 0.684, validating the adequacy of the present sample which is considered as mediocre (Field, 2009 ) indicating that the data is suitable for factor analysis. The Kaiser-Meyer-Olkin measure of sampling adequacy is 0.684 is greater than 0.5, which is supported the use of principal component/factor analysis (Kaiser, 1974 ). The eigenvalues measure the amount of the variation explained by each factor and is largest for the first factor and smaller for the subsequent factors. Accordingly, proportion of variance explained by the first 7 components was 59.69%. Factor analysis was conducted and 7 components were retained. The number of components to be retained was guided by the most commonly used Kaisers criterion which requires that only those components with an eigenvalue greater than 1 should be retained (Kaiser, 1960 ). These 7 components were defined and named considering the variables with greater loads (Hair et al., 2006 ). The components labeled are as follows: (1) awareness and production diversification strategies, (2) seed management strategies, (3) institutional involvement strategies, (4) land and input management strategies, (5) input-output management strategies, (6) Income diversification and saving strategies, and (7) Marketing strategies. Varimax rotation with Kaiser Normalization was used to facilitate interpretation of the factor matrix. From the result, factor 1 accounted for 16.94% of the total variance in the model. Based on the variables that loaded highly on component 1, it was interpreted as awareness and production diversification strategies. The statements that loaded highly on this component are growing different types of crops, taking information regarding climatic parameters and listening agriculture programs, use mobile apps and other media. Strategies like using disease, flood and drought resistant varietal seed of lentil and saving seed for next year loaded highly on factor 2 therefore this factor is labeled as seed management strategy. This factor explained 12.8% of the total variance in the model. Due to uncertainty of seed availability farmers save their harvest as a seed for next year. Seed management strategy helps smallholder farmers to improve their crops yield by using improved varietal seed. Factor 3 termed as institutional involvement strategies accounted for 7.8% of total variance. Involvement in a cooperative, remain contact with extension workers and information applications loaded highly on this factor. This will enable the smallholder farmers have better access to technical information on how to manage risk in lentil production through contact visits from agricultural extension workers and cooperatives. Factor 4 was interpreted as farm and input management strategies with two variables loading and accounted for 7.3% of the total variance. These variables are: adopting farm insurance scheme and saving some sort of inputs from previous season to produce lentil. With 6.7% of total variance, factor 5 was labelled as input-output management strategies including buying seed from authentic source, having own irrigation facility and maintaining trusted relationship with local buyers exists. Similarly, factor 6 was interpreted as income diversification and saving strategy explaining 6.4% of variance. Income diversification strategies would enable smallholder farmers to reduce their variability in income and saving of the farm income provide some sort of security in uncertainty situation. Hence the role of income diversification and saving for managing risk was perceived as important among lentil farmers in the study area. Also, this result is consistent with the findings of Belanieh and Drake ( 2003 ) for Eastern Highlands Ethiopian smallholder farmers. Lastly, factor 7 with variables storage of grains and seeking potential buyers to gain higher profit by selling lentil was interpreted as marketing strategy with 6.01% of variance explained. Similar to this finding, Bhattarai ( 2021 ) reported the empirical evidence that the farmers in Nepal use multidimensional strategic approach for risk reduction and management. Table 8 Varimax rotated result of factor loadings for risk management strategies adopted by lentil farmers Risk management strategies Factor loading 1 2 3 4 5 6 7 RM1 -0.5592 -0.1706 0.0608 -0.1256 -0.0685 -0.1257 -0.0212 RM2 0.0256 0.3750 0.3579 0.1519 0.4253 -0.2835 0.2536 RM3 -0.3603 0.3187 0.3268 -0.2646 -0.0405 0.4567 -0.0354 RM4 -0.0824 0.2551 -0.0488 0.7512 0.0792 -0.0231 0.0243 RM5 0.6989 0.1066 0.0339 0.1182 0.0108 -0.0214 0.0308 RM6 0.1461 -0.2113 0.1177 0.1580 0.5930 -0.0316 -0.2096 RM7 0.2861 0.6160 -0.0635 0.2553 -0.1025 -0.1125 0.1243 RM8 -0.1194 -0.7669 -0.0120 -0.0223 -0.0910 -0.1392 0.0789 RM9 0.0050 0.0609 -0.0635 0.8487 -0.0488 -0.0133 -0.0516 RM10 0.2912 0.0909 0.4949 0.3754 0.1802 0.2129 0.1101 RM11 0.4751 -0.1739 0.3665 -0.1548 -0.2913 -0.0584 -0.0998 RM12 0.3777 0.4537 -0.1364 -0.0702 -0.0528 -0.1692 -0.1740 RM13 0.1328 -0.0434 -0.1118 -0.0283 0.2459 0.0945 -0.7137 RM14 0.2300 -0.1390 -0.1409 -0.0891 0.2276 0.1763 0.6740 RM15 0.3511 0.1025 -0.1174 0.2989 0.2222 0.4909 -0.0564 RM16 -0.0533 0.1200 -0.1469 -0.1474 0.7327 0.0260 0.0534 RM17 -0.0601 -0.0830 0.0505 0.0045 -0.0769 0.7771 0.0577 RM18 -0.2260 -0.0655 0.7497 -0.1106 -0.0224 0.0239 -0.0090 Principal-component factors and variance Eigen values 3.04899 1.53833 1.41026 1.31298 1.20442 1.14699 1.08253 Total variance explained 0.1694 0.12807 0.0783 0.0729 0.0669 0.0637 0.0601 Cumulative percent of variance explained 0.1694 0.2549 0.3332 0.4061 0.4731 0.5368 0.5969 Diagnostic tests Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.684 Bartlett's Test of Sphericity 1099.42*** Source: Own computation result based on survey data (2022) Note: Factor 1=awareness and production diversification strategies, 2=seed management strategies, 3=institutional involvement strategies, 4=Farm and input management strategies, 5=input-output management strategies, 6=Income diversification and saving strategies, and 7=Marketing strategies. Note: Loadings of greater than 0.4 are in bold. Table 9 Description and expected sign of the farmers' socio-economic variables used in SUR model Variable’s name Description and measures Mean Expected sign Dependent Variables (7 retained factors after factor analysis) Factor scores of seven individual strategies Score of individual risk management strategies factor after factor analysis (Awareness and production diversification, Seed management, Institutional involvement, Farm and input management, Input-output management, Income diversification and saving, and Marketing strategies). (5.66e-09, 1.43e-08, -4.40e-09, 2.13e-08, 2.72e-08, 6.18e-09, 3.38e-09) Independent Variables ACESS_TECH 1 if farmers have access to technical services and 0 otherwise 0.28 + HH_EDU Educated farmers are expected to acquire improved seed and technologies faster than illiterate farmers. Years of schooling of the household head in number 3.38 + ACCESS_CREDIT 1 if farmers have access to a loan and 0 otherwise 0.76 + LAND_SIZE It shows the amount of total land owned by farmers measured in hectare 1.08 + MAIN_OCCU 1 if household’s main occupation is farming and 0 otherwise 0.88 + GENDER 1 if household head is male; and 0 otherwise 0.68 ± DIS_TECHSOURCE It denotes the farm distance from government technical offices measured in km 4.68 - MEMBERSHIP This represents involvement of lentil farmers in farmer’s groups or cooperatives. From this membership, they can get technical assistance, inputs, and information. 0.51 + TRAINING 1 if the farmer has received training on lentil farming and 0 otherwise. 0.35 + ECON_ACTIVE It represents the number of members in the family between the ages of 15 and 59 years. 4.74 + EXPERIENCE Experience of sampled farmers in lentil farming measured in years. 19.24 + AGE_HHH It is the age of the household head farming lentil (years) 49.12 - LogINCOME Annual household income from lentil (NPR in Natural logarithm) 9.67 ± Perceived risk factor scores after factor analysis (Predicted risk factor) Prf 1 - Market and Institutional Score of individual perception about the market and institutional risk factor after factor analysis -1.01e-08 + Prf 2 - Production Score of individual perception about the production risk factor after factor analysis -1.70e-09 + Prf 3 - Climatic and input Score of individual perception about climatic and input risk factor after factor analysis 8.92e-09 + Source: Own illustrations based on field survey (2022) 4.4.5 Determinants of risk management strategies The result from the varimax rotation method yields seven factors. These seven factors were regressed against the socio-economic, demographic and institutional factors. To do so, the SUR model was applied, since it contains seven simultaneously regressed equations which have correlated residuals. Description and expected sign of the farmers' socio-economic variables used in SUR model is presented in Table 9 . The SUR model results in Table 10 revealed that the independent variables explain the total variance of 28%, 17%, 15%, 21%, 14%, 12% and 11% for the awareness and production diversification, seed management, institutional involvement, farm and input management, input-output management, income diversification and saving and Marketing strategies respectively. In addition to the R 2 value, the χ2 statistics are significant for each dependent variable at a one percent probability level, which shows the overall fitness of the model with the data used in the analysis process. The test for the correlation between the residuals resulted in a significant χ2 value (χ2 (21) = 45.43, p < 0.002), which implies that there is a significant relationship between residuals; therefore, the SUR model best fit with the data. The result depicted that the awareness and product diversification strategy was significantly and positively affected by perceived risk behavior of farmers on market & institutional and production risk factors. Whereas; climatic & input risk perceived factors affects negatively may be due to beyond of farmer’s control. Also, distance of farm to technical source, and income from lentil production are negatively significant at 5% and 1% level respectively indicating that the management strategy decreases with increase in distance to technical source and increased in income from lentil. Seed management strategy was significantly and positively affected by market and institutional risk factors perception and negatively by perceived climatic and input risk factors. Institutional involvement strategy was found negatively and significantly affected by land size and positively affected by perceived climatic and input risk factors. But contradicts to this result, the study of Nahraeni ( 2012 ); Kislingerova and Spicka ( 2022 ) found that large farm size provides a greater management capacity and greater economies of scale for the farmers and could lead them to apply different risk management practices. Similarly, farm and input management strategy were positively affected by perceived risk factors (production and market and institutional) and experience whereas; negatively affected by gender of household head. The farmers are intelligent on their farms due to the practical experience that they develop. The finding is in line with Girma et al., ( 2023 ); Adimassu and Kessler ( 2016 ) and Chikezie et al. ( 2019 ). This indicates that the farm and input management strategies were increased when the household head was women or farm decision made by women in a household. Input-output management strategies were affected positively by perceived risk factors (climatic and input, production) and if main occupation is agriculture but affects negatively with increased in income from lentil. Likewise, perceived risk factors (production, market & institutional) and income from lentil were the determinants of adopting income diversification and saving strategies where increase in income from lentil affects negatively in the adoption. Perceived production risk factor, access to credit, gender of household head as male and membership in groups and cooperatives affected positively to adopt marketing strategies among the lentil farmers. Access to credit and involvement in farmers group/cooperatives are found positive determinants of adopting marketing strategies for risk management in the study area. Similar to this result, James and Yunxian ( 2021 ) also found that social group membership provided collective interventions to ensure good risk protection management and optimization strategies. Also, Girma et al., ( 2023 ) resulted positive relationship between membership and production related risk management strategies by maize farmers in Ethiopia. Table 10 Relationship between risk management strategies and socioeconomic variables of the lentil farmers Explanatory variables Risk Management Strategies Awareness and product diversification Seed management Institutional involvement Farm and input management Input-output management Income diversification and saving Marketing ACESS_TECH 0.010 (0.086) -0.006 (0.092) -0.101 (0.092) -0.043 (0.091) -0.105 (0.091) 0.084 (0.092) 0.056 (0.933) HH_EDU -0.005 (0.012) -0.007 (0.013) -0.0004 (0.013) 0.014 (0.013) -0.017 (0.013) 0.007 (0.013) -0.003 (0.013) Prf 1 0.267*** (0.042) 0.095** (0.045) -0.074 (0.045) 0.167*** (0.044) 0.065 (0.044) 0.125*** (0.044) 0.019 (0.045) Prf 2 0.080* (0.042) 0.054 (0.045) -0.010 (0.045) 0.156*** (0.044) 0.178*** (0.044) -0.222*** (0.044) 0.109** (0.045) Prf 3 -0.201*** (0.043) -0.227*** (0.046) 0.199*** (0.046) -0.011 (0.045) 0.197*** (0.045) 0.029 (0.046) 0.019 (0.046) ACCESS_CREDIT 0.023 (0.066) -0.062 (0.070) -0.025 (0.070) -0.039 (0.069) 0.060 (0.069) -0.102 (0.069) 0.203*** (0.071) LAND_AREA -0.0005 (0.033) 0.009 (0.035) -0.008* (0.035) 0.0004 (0.035) -0.006 (0.035) 0.042 (0.035) -0.015 (0.035) MAIN_OCCU -0.129 (0.131) -0.113 (0.140) -0.212 (0.140) -0.128 (0.138) 0.270** (0.138) -0.032 (0.139) -0.054 (0.141) GENDER 0.141 (0.092) -0.068 (0.098) 0.167 (0.099) -0.046** (0.097) -0.057 (0.097) -0.093 (0.098) 0.207** (0.099) DIS_TECHSOURCE -0.014** (0.007) 0.004 (0.007) 0.007 (0.007) 0.010 (0.007) -0.0009 (0.007) -0.003 (0.007) -0.003 (0.007) MEMBERSHIP 0.105 (0.087) -0.030 (0.092) 0.084 (0.092) 0.077 (0.096) -0.001 (0.091) 0.048 (0.092) 0.177* (0.093) TRAINING -0.093 (0.088) 0.116 (0.094) 0.030 (0.094) 0.104 (0.093) 0.129 (0.093) 0.021 (0.094) 0.052 (0.095) ECON_ACTIVE 0.0002 (0.017) -0.0008 (0.018) -0.004 (0.018) 0.005 (0.018) -0.008 (0.018) -0.020 (0.018) -0.015 (0.018) EXPERIENCE -0.0001 (0.004) -0.001 (0.004) 0.004 (0.004) 0.0071** (0.004) 0.0005 (0.004) 0.002 (0.004) -0.005 (0.004) AGE_HHH 0.002 (0.003) 0.003 (0.003) -0.0001 (0.003) 0.0007 (0.003) -0.002 (0.003) -0.004 (0.003) -0.0003 (0.003) LogINCOME -0.189*** (0.056) -0.015 (0.060) -0.012 (0.060) -0.168 (0.059) -0.140** (0.060) -0.011** (0.060) -0.018 (0.061) Constant 1.795*** (0.575) 0.201 (0.613) 0.109 (0.616) 1.442 (0.607) -0.907 (0.610) 0.424 (0.610) 0.051 (0.619) Summary Statistics Number of obs. 473 473 473 473 473 473 473 LR Ch 2 (16) 109.10*** 38.72*** 34.10*** 50.15*** 50.34*** 44.54*** 29.56*** R 2 0.28 0.17 0.15 0.21 0.14 0.12 0.11 Source: Estimation based on Field survey (2022) Note: Standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Figure in parentheses indicates standard error. 4.4.6 Risk aversion behavior of lentil farmers Because of having limited resources, information, and knowledge to cope with adverse events, farmers are often risk-averse. This behavior can influence delay farm decision making process making them reluctant to adopt and invest in new technology and practices. Based on farmers' opinion, study resulted majority of lentil farmers (73.2%) were medium risk averse, 17.8% where low risk averse and only 9.1% were high risk averse (Fig. 6 ). Result revealed that most farmers want to minimize large risks, they will accept small and/or moderate risks. Hence, they are cautious but willing to try new approaches with additional support, advisory services and capacity building mechanisms to make better decisions and be able to manage their risks. This result can be generalized as showing that most farmers in Nepal and similar areas are moderately risk-averse, needing support to try new and improved farming practices (Begho, 2021 ). Similar to this result, CRS ( 2018 ) reported smallholders and women farmers in lentil production are generally risk averse, and take longer time to accept new technologies in their report about lentil value chain study in Nepal. 5 Discussion The findings highlight a risk-sustainability paradox, while lentils are profitable and globally demanded, their production is increasingly vulnerable to weather, pests, and market fluctuations. This aligns with studies by Adimassu & Kessler ( 2016 ) and Girma et al. ( 2023 ), who observed that farmers’ risk perception influences both input use and sustainability engagement. 5.1 Sustainability assessment of lentil value chain A sustainable value chain involves production that is economically viable, socially fair, and environmentally responsible, adding value to the product throughout its journey to the consumer (Subedi, 2017 ). The moderate level of sustainability performance of lentil value chain in Nepal was found while analyzing value chain sustainability performance. The social dimension of sustainability was rated at a moderate level, while the economic and environmental dimensions received good ratings. Supportive to this result, Lentil production is seen as a beneficial crop for rotation, providing environmental, economic, and health benefits while supporting food security through local or national sourcing (Warne et al., 2019). Likewise, Subedi ( 2017 ) stated that only a few existing value chains efficiently ensure the smooth flow of quality inputs to farmers and agro-products to consumers, limiting overall market effectiveness. Similarly, Gebre and Rik ( 2016 ) found moderate sustainability in Ethiopia's banana value chain, and Gebre et al. ( 2022 ) reported moderate sustainability across economic, social, and environmental factors in their study in banana value chain sustainability assessment. Similarly, Das et al. (2018) reported economic and ecological potential of legumes including lentil to achieve sustainable growth. Economic sustainability level for the Nepalese lentil value chain was found at a good level. Similar to this result, CRS ( 2018 ) reported low marketable surplus, government incentives and significantly fluctuating lentil prices hindering economic participation and benefits in the lentil value chain in Nepal. The social sustainability aspect of the lentil value chain in Nepal was found at a moderate level, characterized as poorly addressed compared to economic and environmental. Similarly, Subedi ( 2017 ) noted that the lack of coordination among value chain actors at various levels has led to the loss and degradation of agricultural products in Nepal. The environment sustainability aspect of the lentil value chain in Nepal was found at a good level. Environmental benefits and soil nitrogen fixation are the key factors for a good level of sustainability. Similar to this result, Ved Prakash et al. (2002) found a 23.4% increase in soil nitrogen and rice yields after lentil cultivation in India, while Gautam et al. ( 2023 ) suggested a value chain approach for a sustainable lentil seed system in Nepal. Similarly, Alex et al. ( 2015 ) called for a new agricultural transformation system to overcome barriers and support entrepreneurship among actors. The sustainability scores in this study align with Verza et al. ( 2024 ), who found that traceability and certification systems enhanced both price stability and environmental performance in lentil chains. However, unlike export-oriented chains in Canada or Ethiopia, Nepal’s lentil sector lacks coordination platforms, limiting value-added sustainability practices. Weak horizontal coordination among farmers and minimal vertical integration with processors and exporters limit chain efficiency. Public-private models and ICT tools may offer new opportunities for real-time risk sharing and sustainability tracking, as highlighted by FAO and UNDP (2020). 5.2 Factors, perception and management of risk Agriculture sector faces myriads of risks (Iturrioz, 2009). For the livelihood of subsistence farmers, production risks have more severe consequences than market risks because much of what they produced is consumed at home (Sapkota, 2021 ). In this study, farmers perceived climatic hazard as a major risk and highly occurring with a mean score value of 4.11, followed by the incidence of disease with a mean score of 3.86. Similarly, occurrence of crop failure, lower farm income and unreliable market were ranked third, fourth and fifth with mean score value 3.37, 3.13 and 2.94, respectively. Similar to this result, Bhandari and Joshi ( 2023 ) reported weather irregularities and disease incidence were serious risk factors in lentil production in Nepal. Further, Iturrioz (2009) highlighted that climatic variables and market forces are the most significant risk factors in agriculture, both of which are unpredictable due to climate change and market liberalization. Additionally, several studies in Nepal, including those by Acharya ( 2018 ), Shrestha et al. ( 2019 ), and Khanal et al. ( 2018 ), have documented the impacts of climate change, such as extreme weather events, irregular rainfall, and prolonged droughts, which negatively affect agricultural production. Crop diversification, mix cropping, saving seed for next year and involvement in cooperatives were the major strategies for risk management adopted by lentil farmers with mean score value 4.09, 4.02 and 3.60, respectively. Farmers totally disagreed on adoption of the insurance scheme, information on climatic parameters, use of drought-resistant improved varieties, buying and saving inputs for the lentil crop, use of disease-resistant varieties, and storing of grains for a certain time period. In line with this result, Sapkota ( 2021 ) found that Nepalese farmers mainly use crop diversification and integrated farming as risk management strategies, along with joining farmers' groups and cooperatives. Further, Bhattarai ( 2021 ) reported that the farmers in Nepal use multidimensional strategic approach for risk reduction and management. 6 Conclusion and Recommendations This study assessed production risks and value chain sustainability among lentil farmers in Nepal, revealing a buyer-driven, informal, and multi-actor value chain with limited product and information flow and weak vertical and horizontal linkages. It also highlights key risks and sustainability challenges, offering useful evidence to improve lentil value chains in Nepal and other similar regions. Seven marketing channels were identified, with the largest volume transacted through local collector-led channels and the smallest through direct producer-consumer and large collector-retailer channels. The lentil value chain demonstrates significant potential for rural employment and income generation, yet communication between farmers and traders remains informal and trust-limited. Using a triple bottom line approach, the lentil value chain showed moderate sustainability, with strong economic and environmental performance but moderate social sustainability that requires attention. Key strengths include scalability, market demand, food and nutrition security, profitability, inclusiveness, gender equality, rural employment, innovation, biodiversity conservation, resilience, and soil fertility. However, challenges persist in input availability, risk management, value addition, government support, storage infrastructure, stakeholder coordination, fair income distribution, grievance handling, farmer bargaining power, seed dependency, chemical use, and land restoration. Production risks such as climatic hazards, disease, and crop failure are major concerns for lentil farmers. Yield and profit risks were found to be the most significant due to high output variability, while cost risks remained low, highlighting the need for improved seed access, production practices, and value chain support. Risk management strategies primarily include crop diversification, seed saving, cooperative participation, diversified income sources, trusted relationships with collectors, irrigation, and information access. Adoption of formal strategies like certified seed use, extension contact, crop insurance, and climate information remains low, signaling the need for improved facilitation and policy support. Most farmers remain moderately risk-averse, preferring seed self-sufficiency and inclusive commercialization models. Yield improvement and crop management programs are vital to mitigating these risks. Econometric modelling using a Seemingly Unrelated Regression (SUR) approach identified seven strategic groups of risk management ranging from awareness to marketing significantly influenced by perceived risk types, gender, landholding, household income, group membership, access to credit, and distance to technical support. This study demonstrates the value of combining econometric analysis with value chain sustainability assessment under a triple-bottom-line framework. The SUR model proved effective in identifying behavioral drivers of risk management. Higher income from lentil found negatively influenced strategy adoption in some cases, while access to cooperatives involvement, credit, and information positively supported marketing and seed-related strategies adoption. These results emphasize the role of socio-economic and institutional factors in shaping farmers’ risk behavior and the effectiveness of their coping mechanisms. Recommendations Based on the study’s findings and aligned with the Sustainable Development Goals (SDGs), the following recommendations are proposed to promote an inclusive, climate-resilient, and market-oriented lentil system in Nepal and similar regions. These targeted actions aim to strengthen both production and value chain sustainability: a. Risk reduction and climate resilience (SDG 2, SDG 13) Initiate early detection systems and rapid response team of expert to respond quickly to outbreaks of disease, pests, and potential climate events in lentil growing pockets. Increase easy access to insurance scheme and climate-smart practices for smallholder farmers. b. Input and production efficiency (SDG 2, SDG 12) Support the production group to adopt improved, disease-resistant lentil varieties Encourage collective approach for input management, crop production/management, and marketing management to reduce costs and improve efficiency. c. Market access, governance and coordination (SDG 2, SDG12, SDG13) Establish multi-actor platforms that bring together farmers, traders, service providers, and policymakers to improve coordination, solve problems, and drive innovation. Apply a “technology-push and market-pull” approach aligning research, extension and market for a resilient and sustainable lentil value chain. Strengthen infrastructure and services such as storage, transport, finance, price and market information, and technical support to enhance the resilience. Strengthen infrastructure and services such as storage, transport, finance, price and market information, and technical support to enhance the resilience. Declarations Acknowledgements This manuscript is a part of the PhD research work under Department of Agricultural Economics and Agribusiness Management, Agriculture and Forestry University, Nepal. Lentil producers, traders, and business enablers at Nepal were highly acknowledge for their time and information. We acknowledge all the stakeholders and officials who directly or indirectly involved during this study. Author contributions CRediT: Binod Ghimire : Conceptualization, research design, formal analysis, investigation, methodology, visualization, writing-original draft, coordinated with co-authors for suggestions and feedback to finalize the article. Final approval of the version for publication; Shiva Chandra Dhakal : Conceptualization, methodology, supervision, validation, writing: review and editing, approval for publication; Santosh Marahatta : Software, supervision, validation, writing – review & editing and approval for publication; Ram Chandra Bastakoti : Resources, supervision, validation, visualization, writing – review & editing, approval for publication. All authors approved the final version and are accountable for the work's integrity and accuracy. The corresponding author takes full responsibility for correspondence. Ethical Statement This research was approved by the Agriculture and Forestry University, Directorate of Research and Extension (Ref.-280/082/83). Written and Verbal informed consent was obtained from all participants, who were assured of their voluntary participation, the right to withdraw at any time, and the confidentiality of their responses. No minors, clinical trials, or sensitive personal data were involved. Conflict of interests The authors herewith declare no any competing interests. Funding Funding for this study was supported by WTO Chairs Programme, Kathmandu University School of Management, Nepal (Grant number: KUSoM-2023) and USAID Agriculture Higher Education Nepal-2023. ORCID Binod Ghimire: https://orcid.org/0000-0003-0546-3496 Shiva Chandra Dhakal: 0000-0002-2801-8937 Santosh Marahatta: 0000-0002-5128-4029 Data availability statement Data generated from primary source will not be accessible publicly but can be made available by corresponding author upon reasonable request. References Acharya, R. (2018). The effect of changing climate and market conditions on crop yield and acreage allocation in Nepal. Climate, 6(2). https://doi.org/https:/doi.org/ 10.3390/cli6020032. Adamowicz, M. (2021). Agricultural development processes in the context of globalization challenges and new approaches to the concept of sustainable development. Zagadnienia Ekonomiki Rolnej , 366 (1), 24–45. Adhikari, A., Ghimire, S., & Khatiwada, P. (2024). Agricultural trade deficit and its impact on Nepalese economy: A comprehensive review. Innovations in Agriculture , 7 , 1–11. Adimassu, Z., & Kessler, A. (2016). 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The Himalayan Times . https://epaper.thehimalayantimes.com (Accessed June 20, 2023) Sultan, A., & Saurabh, D. (2013). Achieving sustainable development through value chain. International Journal of Managing Value and Supply Chains (IJMVSC) , 4 (2), 39–46. https://doi.org/10.5121/ijmvsc.2013.4204 Tabachnick, B., & Fidell, L. (2007). Using multivariate statistics (5th ed.). New York, NY: Allyn and Bacon. Taherdoost, H. (2019). What is the best response scale for survey and questionnaire design: Review of different lengths of rating scale/attitude scale/Likert scale. International Journal of Academic Research in Management (IJARM) , 8 (1), 1–12. Trienekens, J. H. (2011). Agricultural value chains in developing countries: A framework for analysis. International Food and Agribusiness Management Review , 14 (2), 51–82. USAID. (2011). Value chain/market analysis of the lentil sub-sector in Nepal . United States Agency for International Development (USAID), prepared by ANSAB under NEAT Activity, Prime Contract No. EEM-I-00-07-00008, AID-367-TO-11-00001. USAID. (2012). A note on indicators of sustainability for value chain project. United States Agency for International Development. Valdes, A., & Konandreas, P. (1981). Assessing Food Security Based on National Aggregates in Developing Countries. In A. Valdes (Ed.), Food Security for Developing countries, Boulder, Colo, Westview Press. Verza, M., Ceccacci, A., Frigo, G., Mulazzani, L., & Chatzinikolaou, P. (2024). Legumes on the rise: The impact of sustainability attributes on market prices. Sustainability, 16(7), 2644. https://doi.org/10.3390/su16072644 Yong, G., & Pearce, S. (2013). A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79–94. Zamora, E. A. (2016). Value chain analysis: A brief review. Asian Journal of Innovation and Policy, 5(2), 116–128. https://doi.org/10.7545/ajip.2016.5.2.116 Zellner, A. (1962). An efficient method of estimating seemingly unrelated regression equations and test for aggregation bias. Journal of the American Statistical Association, 57(298), 348–368. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7043104","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":480507639,"identity":"5731ad29-fe33-4856-af62-4bfe5b7cc88b","order_by":0,"name":"Binod Ghimire","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBACA2YgwcNwgIeBvQHEtSBFC88BEFeCCC0MEC0MDBIJICYRWszZeQ8+ePPrjozuzOdXN/wokGDgb+9OwKvFspkv2XBu3zMes9s5ZTd7gA6TOHN2A36HHeYxk+btOQzSknaDB6jFQCKXWC03z6Td/EO0Fp4fQPIG+7HbRNli2cxjbDi3AajlTA7bbRkDCR6CfjHnP2P44M2fw/Zmx48/u/nmj40cf3svfi1gwNgGInmgcUQc+AMi2B8QqXoUjIJRMApGGgAAa1BI54lYMcEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0546-3496","institution":"Agriculture and Forestry University, Nepal","correspondingAuthor":true,"prefix":"","firstName":"Binod","middleName":"","lastName":"Ghimire","suffix":""},{"id":480507640,"identity":"50db150d-a84a-45d1-ab72-36248f72dfa2","order_by":1,"name":"Shiva Chandra Dhakal","email":"","orcid":"https://orcid.org/0000-0002-2801-8937","institution":"Agriculture and Forestry University, Nepal","correspondingAuthor":false,"prefix":"","firstName":"Shiva","middleName":"Chandra","lastName":"Dhakal","suffix":""},{"id":480507641,"identity":"3aab0876-04fb-48cb-94d6-11bb0792dd7c","order_by":2,"name":"Santosh","email":"","orcid":"https://orcid.org/0000-0002-5128-4029","institution":"Agriculture and Forestry University, Nepal","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"Santosh","suffix":""},{"id":480507642,"identity":"a8d17568-ce31-4481-8976-4079b2034932","order_by":3,"name":"Ram Chandra Bastakoti","email":"","orcid":"","institution":"Agriculture and Forestry University, Nepal","correspondingAuthor":false,"prefix":"","firstName":"Ram","middleName":"Chandra","lastName":"Bastakoti","suffix":""}],"badges":[],"createdAt":"2025-07-04 05:11:12","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7043104/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7043104/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86172628,"identity":"e90fd570-5c89-4ed9-b253-a3af1c3819d9","added_by":"auto","created_at":"2025-07-07 14:45:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":48461,"visible":true,"origin":"","legend":"\u003cp\u003eThe nested spheres model (left) and the overlapping spheres model (right)\u003c/p\u003e\n\u003cp\u003eSource: Sandhu et al. (2014)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/6273e16fe14e403b18ea5d5f.png"},{"id":86172630,"identity":"970042b8-1cb2-4900-8ffa-33945956c7fb","added_by":"auto","created_at":"2025-07-07 14:45:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":94146,"visible":true,"origin":"","legend":"\u003cp\u003eLentil value chain map in the study area (Source: Author’s design based on field survey, 2022, traders survey, 2022/23, FGD)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/7152bf1c2a8336ce681bda37.png"},{"id":86172633,"identity":"2bf78b42-25c8-4970-ad9b-2f2ee3116280","added_by":"auto","created_at":"2025-07-07 14:45:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":210263,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap visualization of sustainability indicator performance scores by theme\u003c/p\u003e\n\u003cp\u003e(Source: lentil business enablers survey, 2023; KIS, 2022 \u0026amp; FGD, 2023)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/cb2b60d4ca962eb823dd3c1a.png"},{"id":86172632,"identity":"38157162-3a20-4d75-9cb1-c421611c1149","added_by":"auto","created_at":"2025-07-07 14:45:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19332,"visible":true,"origin":"","legend":"\u003cp\u003eLentil production risks assessment based on Likert scale (source: field survey, 2022)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/419c5d20c35074b904ce6b0f.png"},{"id":86172639,"identity":"23505aa2-de21-4b2b-be3e-5805f83e8e8f","added_by":"auto","created_at":"2025-07-07 14:45:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":40311,"visible":true,"origin":"","legend":"\u003cp\u003eChallenges with lentil marketing system (source: traders level survey, 2023)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/0bb52410d25e45177998eaab.png"},{"id":86173058,"identity":"f240753f-07e7-4d16-a215-c2bbaa949b47","added_by":"auto","created_at":"2025-07-07 14:53:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":19132,"visible":true,"origin":"","legend":"\u003cp\u003eRisk aversion behavior of lentil farmers.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/bfa578a8a1494f496d5a7974.png"},{"id":86174747,"identity":"e79e309e-3bce-442d-80a3-d4a74a407888","added_by":"auto","created_at":"2025-07-07 15:09:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2735946,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7043104/v1/e3a37f27-d5af-4efa-beb0-2d934b68745b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssessing Production Risks and Value Chain Sustainability in Nepal's Lentil (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eLens culinaris\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eMedik.) Sector: An Evidence-based Econometric Analysis\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAgriculture is the main economic sector in Nepal, contributing around 24% of GDP and supporting around 65% of the population (MoALD, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nepal\u0026rsquo;s diverse agro-climatic conditions, natural resources, and unique products provide a competitive advantage in high-value crops such as vegetables, spices, tea, and pulses, offers substantial agricultural production (Paudel, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong these lentil (\u003cem\u003eLens culinaris\u003c/em\u003e Medik.) holds the vital place. Nepal is one of the world\u0026rsquo;s top lentil producing countries, ranking fifth and contributing about 4.35% to the global area and production (Ghimire et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In South Asia where half of the world\u0026rsquo;s lentils are grown, Nepal plays a key role. Winter lentils are the most important legume crop in the country, making up 65% of total pulse production and 63% of the area used for pulses (Dhakal, 2021; Ghimire et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Lentils are grown on about 213,000 hectares and produce nearly 263,000 tons annually (MoALD, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), supporting the livelihoods of around 700,000 farming households (USAID, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Nepali lentils are valued for their small size, bright pink color, taste, cooking quality, and high micronutrient content including iron and zinc (Darai et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). They are in demand domestically and internationally, contributing to income generation, employment, and exports (USAID, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, lentil remains less prioritized than cereals and vegetables and is often grown under low-input, rain-fed conditions. Prioritizing lentil is crucial for enhancing food security and rural livelihoods (Gautam et al., 2022; Ghimire et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, the lentil value chain in Nepal faces several structural and systemic challenges. In developing countries like Nepal, value chains are often long and fragmented (Trienekens, \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), burdened by low investment, weak infrastructure, transport delays, high transaction costs, and unpredictable regulations (Adhikari et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Most farms are small-scale, traditional, and fragmented, with farmers lacking technology and market knowledge, resulting in low yields and quality (Kumar et al., 2020). Farmers face market uncertainties, while processors and traders struggle with unreliable quantity and quality. Farmer groups and cooperatives are weak compared to private traders, limiting benefits for members. Traders and processors often mention small, fragmented, and irregular supplies and poor product quality as major challenge in the sector (Neopane et al., 2021). Agricultural commercialization depends on efficient resource use and sustainable commodity value chains that minimize risks (Ghimire et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Assessing sustainability is complicated by multi-stakeholder relationships and diverse services (Josserand, 2018).\u003c/p\u003e\u003cp\u003eIn addition to these structural gaps, farmers are highly exposed to risks stemming from climate variability, pests, diseases, and price volatility (Cervantes-Godoy et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Risk aversion and lack of coping mechanisms constrain the adoption of sustainable practices (Cheng, Yip \u0026amp; Yeung, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Further, globalization and fragmented production processes pose key challenges to the environmental, social, and economic sustainability of agricultural value chains, generating complex risks (Adamowicz, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Technology adoption improves productivity and sustainability, but risk aversion especially among smallholders, hinders uptake, making effective risk management essential for policy and innovation. Mapping value chain interactions helps identify factors influencing agribusiness performance (Zamora, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Yet sustainability is increasingly critical due to evolving regulations, societal expectations, and value addition that jointly impact poverty and hunger reduction (FAO and UNDP, 2020).\u003c/p\u003e\u003cp\u003eDespite many studies on agricultural commodity value chains, there is still limited research that looks at both production risks and value chain sustainability. While lentil production, trade and export trends have been studied, few have focused on how farmers perceive risks, how they cope with them, or how sustainable the overall value chain is. This is especially important for Nepal, where lentils play a key role in rural livelihoods and national exports but are often grown under uncertain and risky conditions. In this regard, this study aims to fill that gap by using both qualitative and quantitative methods to explore risks, sustainability, and coordination within the lentil value chain. It applies a triple bottom line framework and econometric analysis to understand economic, social and environmental aspects of sustainability and associated risks dimension. The findings are expected to support better policies and practical actions supportive to Agriculture Development Strategy (ADS, 2015) and SDG2 that strengthen the lentil sector and make it more resilient. The tools and approach used here can also be useful for studying other crops and regions. The study specifically aims to:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIdentify and analyze key production and marketing risks and risk management strategies in lentil farming\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAssess the sustainability of the lentil value chain in triple bottom line framework\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eProvide evidence-based insights to support policy and institutional decisions that strengthen the lentil sector\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"2 Theoretical background and literature review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Sustainability assessment of value chain; Triple Bottom Line Approach (TBL)\u003c/h2\u003e\n \u003cp\u003eAwareness of sustainability has grown significantly in recent years, becoming an increasingly important concern across society, leading to greater interest in this subject among academics and experts (Correia, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The value chain sustainability is an activity of adding values from raw agriculture production and its transformation to specific products for the final consumer and disposed later in a way that is lucrative all over the chain, broad social welfare, and does not exhaust the natural environment in the long term (Neven, \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). The sustainability delivers values and gains in the present along with assured benefit to the future generations (Alhaddi, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe Triple Bottom Line (TBL) approach, coined by Elkington (\u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e) and emphasized by Goran and Wagner (\u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), focuses on people, profit, and planet, highlighting social equity, environmental quality, and economic benefits for sustainable development (Elkington, \u003cspan class=\"CitationRef\"\u003e1998\u003c/span\u003e). It offers a framework for assessing how well a company is performing in each of these three areas. Goel (\u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). Loviscek (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) emphasized TBL as a sustainable chain management framework, assessing social, human, and environmental impact alongside profitability (McKenzie, \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e; Savitz \u0026amp; Weber, \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). The environmental aspect, often overlooked, is crucial for economic development and monetization (Nogueira et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Slaper \u0026amp; Hall, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). The widely accepted nested spheres model, or Venn diagram (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), illustrates the convergence of these elements in sustainability (Correia, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEconomic dimension (Profit)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe Economic Dimension (Profit) of the Triple Bottom Line (TBL) examines how a company\u0026rsquo;s business activities influence the broader financial system, with an emphasis on the value it generates (Elkington, \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e). It also considers the societal effects of the company\u0026rsquo;s economic performance, viewing the economy as a key component of sustainability that ensures support for future generations (Spangenberg, \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSocial dimension (People)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe social dimension (People) refers to the influence of an organization on the citizen\u0026rsquo;s wellbeing (Engardio et al., \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e) and involves performing business culture that benefit human capital, labor, and to the public as a whole (Elkington, \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e). These practices contribute value to society and community.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEnvironmental dimension (Planet)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe environmental dimension, often referred to as \u0026apos;Planet,\u0026apos; focuses on practices that protect and conserve environmental and natural resources for future generations, while still delivering value in the present. Incorporating the Triple Bottom Line approach includes the implementation of sustainable supply chain management, which integrates social, economic, and environmental considerations into the operations of the supply or value chain, ensuring that sustainability is addressed across all areas of performance (Moreno \u0026amp; Salgado, \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Agriculture production risk factors and management strategies\u003c/h2\u003e\n \u003cp\u003eAgriculture is essential for human food production, yet it involves numerous risks (Kay et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Olson, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Ellis (1988) categorized agricultural risks into four types: natural threats (such as pests, diseases, and weather), market fluctuations (output prices), social uncertainty (resource conflicts), and state activities and wars, all impacting farmers\u0026apos; livelihoods. Hardaker et al. (\u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e) identified price, transaction and yield as three primary risk categories in agriculture. Hazell and Norton (\u003cspan class=\"CitationRef\"\u003e1986\u003c/span\u003e) argue that farmers\u0026apos; responses to different hazards are influenced by their farming systems, environmental conditions, policies, and institutional frameworks, which ultimately shape their decision-making processes.\u003c/p\u003e\n \u003cp\u003eYield inconsistency in agriculture production arises due to numerous uncontrollable factors, predominantly associated with weather irregularities, such as inadequate rainfall, diseases outbreak, and pest introduction. These risks are primarily caused by natural phenomena (Valdes \u0026amp; Konandreas, \u003cspan class=\"CitationRef\"\u003e1981\u003c/span\u003e). Yield risk is measured by CV (coefficient of variation), which shows the variation relative to the average yield (Hardaker et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Risk management strategies\u003c/h2\u003e\n \u003cp\u003eFarm size, creativity, age, experience, and risk sensitivity influence farmer\u0026rsquo;s preferences of risk management strategies, making it essential to identify sources of risk to select the appropriate strategy farmers (Pennings, et al., 2008). Identifying risk sources is vital for effective agricultural management strategies. Factors such as farming ecosystem, agricultural income, and the land size affect how risks are handled. Risk tolerance behavior of a decision maker influences the types and scales of agricultural methods, impacting the production structure and stable growth of household income (Wencong et al., 2006). Evans and Ngau (1991) suggest that farm households can boost performance by expanding land, investing in inputs, hiring staff, switching to cash crops, or selling more yield, enhancing productivity and sustainability.\u003c/p\u003e\n \u003cp\u003eIn Nepal, subsistence farmers face greater harm from production risks than market risks due to their reliance on domestic consumption of their produce. Unmanaged farming hazards negatively impact the economy, farmer well-being, and agricultural productivity (Chhetri, 2019). Without timely risk management, the sustainability of the farming industry is threatened, as neglected farms may become unfit for future generations (Hardaker et al., 2015; Shrestha \u0026amp; Nepal, 2016). For agricultural practices to be sustainable in the long term, it is essential to manage and mitigate the associated risks. This research studied lentil production risk dimension to identify key production risks and management strategies for a resilient lentil production system.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Research Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Sampling and data collection methods\u003c/h2\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.2 Study area and data collection procedure\u003c/h2\u003e\n \u003cp\u003eThis research used different types of primary dataset and followed the standard ethics during the data collection procedure. Desk review and piloting survey were done to develop coordination schema. Using Cochran\u0026rsquo;s formula (Cochran, \u003cspan class=\"CitationRef\"\u003e1963\u003c/span\u003e), 473 lentil producers were surveyed from four major producing districts: Rautahat, Dang, Bardiya, and Kailali in 2022.\u003c/p\u003e\n \u003cp\u003eFollowing the lentil harvest, a trader-level survey was conducted in 2022/23 across 12 major markets of Nepal. Based on the coordination schema, a well-designed and pretested semi-structured interview schedule was developed and used for data collection. Both simple random sampling and purposive sampling techniques were applied. Primary data from traders in the lentil value chain were collected through face-to-face interviews and phone calls. The selection of traders was supported by information from farmers tracing the product flow along the chain.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.2 Focus group discussions and key informant interviews\u003c/h2\u003e\n \u003cp\u003eData collection was further supported, validated, and supplemented through focus group discussions (FGDs). Four FGDs at the production level and two FGDs at the trader level were conducted using checklists. These qualitative discussions gathered information on current production status, associated risks, risk management, marketing situations, value chain governance, and opportunities for sustainable lentil chain improvement, including strengths, weaknesses, opportunities, and threats.\u003c/p\u003e\n \u003cp\u003eAdditionally, 12 key informants from directly related stakeholders were interviewed. These included government officials, public representatives, and members of chambers of commerce and industry, covering all major markets. Key informant interviews are qualitative, in-depth interviews with knowledgeable community members who understand the local context and trends (Kumar, \u003cspan class=\"CitationRef\"\u003e1987\u003c/span\u003e). The expert insights from key informants, representative views from focus groups, and business enabler surveys formed the basis of the assessment.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.3 Observations\u003c/h2\u003e\n \u003cp\u003eDirect and participatory observations were also conducted covering logistics, cultivation practices, harvest, postharvest handling, transportation, processing, storage, weighing and packaging, trading, waste, and by-product management. Participatory observation is an effective approach to gather locally grounded information, especially when the value chain is not well documented (Stein and Barron, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.4 Sample size and survey methods\u003c/h2\u003e\n \u003cp\u003eThe study surveyed 473 farmers at the production level using a semi-structured questionnaire through face-to-face interviews. At the trader level, 155 traders were surveyed using a similar questionnaire administered both via face-to-face interviews and phone calls. Additionally, a business enablers survey targeted farmer and trade associations, private sector actors, I/NGOs, and government sector representatives. This survey included 85 respondents and was conducted online through Google Forms and direct visits.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Methods and technique of data analysis\u003c/h2\u003e\n \u003cp\u003eBoth descriptive, analytical and inferential statistical tools were used for data analysis. To fulfil the specific objectives collected data were made entry in Microsoft excel sheet and processed.\u003c/p\u003e\n \u003cp\u003eAnalytical tools used were value chain map, indexing, scaling, and sustainability performance assessment. In order to have a visual representation of the whole chain, common chain was mapped with product, money and information flow along the actors. Analysis specifying function of each actor across the chain was mentioned within the map. Lentil value chain governance with information flow and linkage between the actors was analysed to show how the chain was performing. Further, Seemingly Unrelated Regression (SUR) model was used following Exploratory Factor Analysis to analyse production risks and influencing factors for adoption of risk management strategies. All statistical tests were performed with the use of MS-Excel and STATA version 14 software.\u003c/p\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1 Value chain sustainability assessment\u003c/h2\u003e\n \u003cp\u003eFor the sustainability assessment of lentil value chain in Nepal, 85 responses including progressive farmers, key informants, business enablers, government and private sector stakeholders from all value chain stages and scientific domains were taken using google forms to assess and quantify the level of social, economic and environmental dimensions in Nepal. Further, suggestions were recorded from focus group discussions.\u003c/p\u003e\n \u003cp\u003eThe selection of the sustainability indicators depends on the level of the organization and the type of activities or sectors (Moreno and Salgado, \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). Once the main processes of the value chain are mapped, indicators must be associated to each segment, for all three sustainability dimensions-TBL (Moreno and Salgado \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). For judgment Sustainability Assessment of Food and Agriculture (SAFA) Systems Guidelines from the FAO (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) was adopted which were developed for assessing the impact of food and agriculture operations on the environment, economy, and society. The SAFA tool has been widely used for sustainable agriculture assessments in developed and developing nations (Leknoi et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFor this study, the selection of triple bottom-line sustainability indicators (economic, social and environmental) specifically adapted to the context of lentil value chain and proposed a multidimensional sustainability assessment based on a set of 32 criteria. Each indicator was also evaluated by experts qualitatively to grasp the real scenarios towards the sustainable lentil value chain which helps to penetrate the local and global market. The selected sustainability indicators that relate to the economic, social, and environmental elements of the lentil value chain in Nepal are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. As followed by Gebre and Rik (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), the assessment was done by a qualitative method with five score categories. Five points score value (1\u0026thinsp;=\u0026thinsp;unacceptable situation, 5\u0026thinsp;=\u0026thinsp;best situation) with regards to each different 32-dimensional indicators were applied and obtained result for each indicator was converted into scores on a percentage scale and interpreted based on decision criteria (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAverage judgement rating\u0026thinsp;=\u0026thinsp;average of all responses on particular indicator\u003c/p\u003e\n \u003cp\u003ePerformance score (%)\u0026thinsp;=\u0026thinsp;average rating on particular indicator/ maximum possible score (5)\u003c/p\u003e\n \u003cp\u003ePerformance score (%) on theme\u0026thinsp;=\u0026thinsp;Sum of average ratings on indicators under the theme/ maximum possible score for theme\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSelected Triple Bottom-Line Indicators for Sustainability assessment of the lentil Value Chain\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEconomic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSocial\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEnvironmental\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScalability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInclusiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAgrobiodiversity conservation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarket demand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender equality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUse of chemicals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdded value share\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePotential to engage small scale poor farmers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eValue adding activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural employment opportunity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLand restoration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarket diversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarming method technological innovations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoil fertility enhancement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCompetitiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStorage facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfitability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eValue chain stakeholder relations and support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFair trade and price\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFair income distribution along the chain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupportive to household food and nutrition security\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFair/unbiased wage system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpportunity for household income generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChild/forced labor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePotential to use local resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrievance handling mechanism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAvailability of inputs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFarmers bargaining power\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAssociated risks management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDependency for seed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGovernment support and scheme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e(Sources: Author\u0026apos;s construction based on Gebre and Rik (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), SAFA-FAO (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e), and KIS, 2022)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDecision criteria based on score value\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePoints scored\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage scored\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChain performance rating\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u0026ndash;100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBest\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u0026ndash;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimited\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnacceptable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e(Source: Adopted from Gebre and Rik, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.2 Scaling technique\u003c/h2\u003e\n \u003cp\u003eA five-point Likert scale was used to assess farmers\u0026rsquo; perceptions of risk factors and the strategies they adopt in lentil farming. A total of 473 lentil farmers were interviewed and asked to rate the importance of selected risk factors and management strategies. These items were developed based on focus group discussions and a pilot survey, resulting in seven key risk factors and eighteen risk management strategies included in the questionnaire.\u003c/p\u003e\n \u003cp\u003eThe Likert scale was chosen for its ease of use, reliability, and ability to reflect subjective evaluation more effectively than smaller scales (Taherdoost, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). For each item, farmers rated their perception on a five-point scale. For risk occurrence, the categories were: very unlikely (1), unlikely (2), sometimes (3), likely (4), and very likely (5). For management strategies, responses were: strongly disagree (1), disagree (2), neutral (3), agree (4), and strongly agree (5).\u003c/p\u003e\n \u003cp\u003eEach item was scored using weighted average means to calculate an index value using the formula:\u003c/p\u003e\n \u003cp\u003eI_inf = \u0026sum; (s\u003csub\u003ei\u003c/sub\u003e \u0026times; f\u003csub\u003ei\u003c/sub\u003e) / N,\u003c/p\u003e\n \u003cp\u003ewhere s\u003csub\u003ei\u003c/sub\u003e is the scale value, f\u003csub\u003ei\u003c/sub\u003e is the frequency of responses, and N is the total number of respondents. The scale values were determined as 1, (1\u0026ndash;1/n), (1\u0026ndash;2/n), \u0026hellip;, (1\u0026ndash;5/n), where n is the number of ranking categories.\u003c/p\u003e\n \u003cp\u003eA mean score above 2.5 was interpreted as indicating high risk occurrence or strong agreement with adoption of a strategy, while scores below 2.5 were considered low. After scoring, factor analysis was used to reduce the number of variables and identify key underlying dimensions for both risk factors and management strategies.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.3 Exploratory factor analysis (EFA) model specification\u003c/h2\u003e\n \u003cp\u003eExploratory factor analysis was applied for this study to create a summary latent variable (factor) for a large number of variables of risks and management strategies. Following Tabachnik and Fidell (2007), factor analysis model presented as;\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:Xi=\\alpha\\:j1F1+\\alpha\\:j2F2+\\dots\\:\\alpha\\:jmFm+\\epsilon\\:j$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eWhere; j\u0026thinsp;=\u0026thinsp;1, 2, 3, 4. .. p indicates number of variables, Xj represents j-th variable, \u0026alpha;jm denotes factor loading of j-th variable on m-th factor, Fm represents factor m, \u0026epsilon;j indicates unique factor.\u003c/p\u003e\n \u003cp\u003eEFA is a type of technique that analyses the uni-dimensionality (characteristics) of each of the defined risk management practices (Bartholomew et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e), in order to reduce it to a common score (smaller number of factors) by examining relationships among these quantitative factors (Pallant, \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn conducting factor analysis, two methods are mostly commonly used, namely, principal axis factoring and principal component analysis. In this study, principal axis factoring with varimax rotation was employed. The justification for this was that principal axis factoring does not assume that all of the variables (items) included in the study account for 100% of the variance. Therefore, principal axis factoring categorizes the total variance into common variance, unique variance and error variance; however, principal component analysis assumes that there is no error variance, which means that the total variance of the variable is accounted for by its components (Rietveld and Van Hout \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e). In connection to this, factor loading indicates the contribution of the variable to each factor. A factor loading of 0.30 or greater is considered statistically meaningful (Tabachnick and Fidell \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e). The larger the factor loading, the more the variable has contributed to that factor (Harman \u003cspan class=\"CitationRef\"\u003e1976\u003c/span\u003e). The factor analysis produced factor score, also known as a factor loading, is a measurement that correlates a particular variable to a given factor. When a factor score is high, this suggests that there is a notably strong connection between a certain factor and a common variance in the observed data. The magnitude of the factor score (loading) determines the number of factors to retain. The extracted number of factors represented the risk management strategies employed by the farmers.\u003c/p\u003e\n \u003cp\u003eTo confirm whether the data from the measurements was sufficient for factor analysis (test the validity), the Kaiser-Meyer-Olkin (KMO) test (Lorenzo-Seva et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e) and the Bartlett\u0026rsquo;s sphericity test (Hair et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e) were performed. In the KMO test, as the values of the test vary from 0 to 1, values above 0.7 are recommended as being desirable for applying EFA (Hair et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e) and a statistically significant Bartlett test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) indicates that sufficient correlations exist between the variables to continue with the analysis (Hair et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Pallant, \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnostic tests in Factor analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFactors with Eigen values greater than 1, Bartlett\u0026rsquo;s Test of Sphericity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and the Kaiser-Meyer-Olkin Measure (KMO) of Sampling Adequacy (cut-off of above 0.40) were taken into consideration. If this requirement is not met, distinct and reliable factors cannot be produced. However, if this problem occurs, it can be solved by increasing the sample size (Yong and Pearce \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). This technique enabled the researchers to manage and reduce the number of original variables into a smaller group of new correlation components, which are linear combinations of the original variables. The Kaiser-Meyer-Oklin (KMO) method measured the appropriateness for component analysis of data sets (Kaiser \u003cspan class=\"CitationRef\"\u003e1960\u003c/span\u003e). The KMO index varies from 0 to 1, with results of 0.6 or greater suitable for component analysis. The latent root criterion (eigenvalue\u0026thinsp;\u0026gt;\u0026thinsp;1) was used to determine how many components to retain in each data set to extract. After the numbers of components were identified, the varimax rotational method was performed in order to minimize the number of variables that have high loadings on each component. A component loading of \u0026plusmn;\u0026thinsp;0.4 was employed as a cut off criterion to determine the inter correlation among the original variables accepted in this study.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.4 Seemingly Unrelated Regression (SUR) model\u003c/h2\u003e\n \u003cp\u003eBased on the factor analysis, the main risk management strategies were identified and used for further analysis in the seemingly unrelated regression model (SUR) to identify the determinants of production risk management strategies since more than one risk management strategy was continuous. The SUR model allowed correlations among the residuals of each dependent variable. The SUR model is an extension of the multiple linear regression models and is used to estimate several continuous dependent variables jointly (Gujarathi \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). According to Zellner (\u003cspan class=\"CitationRef\"\u003e1962\u003c/span\u003e), the SUR model is specified as;\u003c/p\u003e\n \u003cp\u003eY\u003csub\u003eim\u003c/sub\u003e = B\u003csub\u003e0\u003c/sub\u003e + B\u003csub\u003em\u003c/sub\u003eX\u003csub\u003eim\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026epsilon;\u003csub\u003eim\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eWhere Yim (m\u0026thinsp;=\u0026thinsp;1, 2, 3. .. k) represents the dependent variables which indicate the factor score for each risk management strategy chosen by the i\u003csup\u003eth\u003c/sup\u003e farmer, B\u003csub\u003e0\u003c/sub\u003e represents the constant term, B\u003csub\u003em\u003c/sub\u003e represents coefficients of explanatory variables, X\u003csub\u003eim\u003c/sub\u003e represents explanatory variables and \u0026epsilon;im represents the error terms.\u003c/p\u003e\n \u003cp\u003eThe above equation can be interpreted for each risk management strategies (m) as;\u003c/p\u003e\n \u003cp\u003eY*\u003csub\u003ei1\u003c/sub\u003e = \u0026gamma;\u0026thinsp;+\u0026thinsp;B\u003csub\u003e1\u003c/sub\u003eX\u003csub\u003ei1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026epsilon;\u003csub\u003ei1\u003c/sub\u003e, Y*\u003csub\u003ei2\u003c/sub\u003e = \u0026delta;\u0026thinsp;+\u0026thinsp;B\u003csub\u003e2\u003c/sub\u003eX\u003csub\u003ei2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026epsilon;\u003csub\u003ei2\u003c/sub\u003e, Y*\u003csub\u003eim\u003c/sub\u003e = \u0026phi;\u0026thinsp;+\u0026thinsp;B\u003csub\u003em\u003c/sub\u003eX\u003csub\u003eim\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026epsilon;\u003csub\u003eim\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eIn this study, the factor scores obtained from the factor analysis output were used as the dependent variables in SUR model. The SUR model is estimated by the usual ordinary least square method (Cappellari and Jenkins \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), and the model allows correlation between residuals (Belderbos et al. \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). The test for correlation between residuals was carried out using the Breusch\u0026ndash;Pagan test of independence. Before commencing the SUR model, a test for multicollinearity using variance inflation factor (VIF) was employed.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4 Results and Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 Lentil value chain governance\u003c/h2\u003e\n \u003cp\u003eThe concept of \u0026ldquo;value chain\u0026rdquo; was introduced by Porter (\u003cspan class=\"CitationRef\"\u003e1985\u003c/span\u003e) to describe all activities essential to transform a product from beginning to final consumption. Gibbon (\u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e) described a value chain as a sequence where products gain value at each stage. This study identified six major actors in the Nepalese lentil value chain: input suppliers, producers, collectors, processors, distributors (wholesalers and retailers), and consumers (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The value chain map reveals how diverse businesses interrelate, exposing stakeholders and their roles (Gebre et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) and serves as an entry point for smallholder inclusion (Lundy et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Agricultural value chain mapping includes direct and indirect actors, networks, and external influencers (Lundy et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). The lentil chain in Nepal shows actors performing activities at various scales but mostly small and informal, lacking credit, technical skills, and facing high transaction costs and information asymmetry leading to market distortions.\u003c/p\u003e\n \u003cp\u003eProducers\u0026rsquo; input needs remain unsatisfied in quality, quantity, and timing, with limited alternatives and price differentiation. Lentil moves as a raw product up to processors, after which it is sold as whole or split lentil domestically and overseas. Information flows vertically and horizontally among traders but farmers receive limited horizontal information. Local collectors, communicating with processors, set low prices on fresh lentil due to farmers\u0026rsquo; weak bargaining power and lack of storage. Farmers sometimes form groups or cooperatives to access better market information and bargaining but lack infrastructure and business skills. About 52% of traders provide short-term credit to suppliers, yet 82.8% of households accept buyer-determined prices with only 17.2% able to negotiate, reflecting a buyer-driven chain where large collectors and processors dominate price setting (USAID, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zamora, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eValue chain governance is immature and informal with absence of mutual trust. Producers operate individually, restricting bargaining capacity, while large collectors and processors dominate, influencing prices to their advantage. Exporters and processors maintain contacts with international buyers but report delays in payments. Actors participate mainly for profit and lack services or information-sharing mechanisms. Improvements in value chains and marketing play a crucial role in farm-level profitability and commercialization but product flows lack adequate value addition, branding, and after-sale services (Neupane et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; USAID, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Developing sustained lentil value chains requires access to resources and formal networks often beyond local producers\u0026rsquo; reach. Incentive systems such as performance rewards, price premiums, profit-sharing, and market access are nearly absent (Zamora, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). A holistic approach is needed to ensure economic prosperity, environmental protection, and social integrity across the chain (Asif et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn the study area, seven frequently used lentil marketing channels were identified, with a total of 1,021 metric tons supplied by sample respondents to end users through various intermediaries. The largest volume, 44.56%, moved through the channel where lentils passed from producers to local collectors, processors, wholesalers, retailers, and finally consumers, reflecting the high capacity of local collectors to purchase directly from farmers. Other significant channels included producer-large collector-processors-wholesalers-retailers-consumers (18.41%) and producer-local collector-processors-retailers-consumers (11.26%). Smaller shares were observed in channels involving direct producer-consumer sales (4.02%) and producer-large collector-retailer-consumer (3.62%), the latter being the smallest due to retailers\u0026rsquo; limited capacity to sell whole lentils without processing. Cooperatives also played roles as producers and aggregators, supplying lentils to local or distant collectors.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2 Sustainability performance assessment of lentil value chain\u003c/h2\u003e\n \u003cp\u003eA sustainable value chain is an economically viable, socially just and environmentally friendly way of production, and addition of value to the product until it makes it to the consumer (Subedi, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). The sustainability of the lentil value chain in Nepal was assessed through selected 32 different indicators based on economic, social and environmental theme. These indicators were based on guidelines adopted from FAO (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) SAFA, (Gebre and Rik, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) and discussions with experts and stakeholders related to lentil value chain in Nepal. Based on this result, the overall lentil value chain sustainability performance was found at moderate level with average judgement rating of 2.99 and performance score 59.80% (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Similar to this result, Subedi (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) opinioned that among the existing ones, very few value chains are efficient and render smooth flow of quality input materials to farmers and agro product to consumers in Nepal. Assessment resulted that the economic and environmental dimension rated at good level whereas, social dimension was rated moderate level of sustainability. Similar study conducted by Gebre and Rik, (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported moderate level of sustainability within banana value chain in Ethiopia. Also, Gebre et al., (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported economic, social, and environmental indicators have moderate sustainability performance in their study on banana value chain sustainability assessment at Ethiopia. Likewise, Barua and Rahman, (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) resulted moderate level of sustainability in all economic, social and environmental dimensions of goat value chain in Bangladesh. The sustainability results for each indicator on the percentage scale and overall performance based on theme was presented in heatplot (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eSummary of lentil value chain ratings by sustainability dimensions in Nepal\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\" width=\"752\" height=\"222\"\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e(Source: lentil business enablers survey, 2023; KIS, 2023 \u0026amp; FGD, 2023)\u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eEconomic sustainability\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThere were 14 indicators based on economic dimensions with average judgement rating of 3.06 and performance score in percentage 61.15%. Based on this rating and percentage score economic sustainability level for Nepalese lentil value chain was found at good level. However, within the economic theme, moderate (6 indicators) to good (8 indicators) level of sustainability were found for the assigned indicators ranging from 46.43 to 73.57 percentage score (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Lentil value chain in Nepal found higher sustainability score with scalability, market demand, support to household food and nutrition security, support to household income, profitability, market diversity, potential to use local resources and competitiveness. In contrast, lower performance score was found with the indicator availability of inputs, associated risks and crop failure, added value share, value adding activities, government support and subsidy schemes. These findings align with CRS (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), which reported low marketable surplus, government incentives and significantly fluctuating lentil prices hindering economic participation and benefits in the lentil value chain in Nepal. Interestingly, despite storage and value addition being reported as key bottlenecks in the lentil value chain, most farmers expressed satisfaction with outcomes related to profitability and employment. This suggests that, while structural inefficiencies persist, the sector continues to deliver meaningful economic benefits to smallholders.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSocial sustainability\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSocial sustainability aspect of lentil value chain in Nepal was found at moderate level. The social indicators were found poorly addressed along the lentil chain in Nepal compared to economic and environmental. There were 13 indicators based on social dimensions with average judgement rating of 2.90 and performance score 57.95%. Based on this rating and percentage score social sustainability level for Nepalese lentil value chain was found at moderate level. However, within the theme, moderate (8 indicators) to good (5 indicators) level of sustainability were found for the assigned indicators ranging from 51.43 to 68.33 percentage score. Social dimensions of lentil value chain in Nepal found higher sustainability score with inclusiveness, gender equality, potential to engage small scale poor farmers, rural employment opportunity and farming method and technological innovations. Whereas; lower performance score was found with the indicator storage facility, stakeholder relations and support, fair income distribution, fair/unbiased wage system, grievance handling mechanism, farmers bargaining power and dependency for seed. From the study area it was found that there was no long-term business relationship between producers and traders and lack trust in relationship leading to distortion of the chain. Similar to this result, Subedi (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) reported lack of coordination among the actors of value chain at different level has caused loss and degradation of agro products in Nepal.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEnvironment sustainability\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eEnvironment sustainability aspect of lentil value chain in Nepal was found at good level. This reflects that the lentil value chain is environmentally friendly in Nepal. The environmental indicators were found adequately addressed along the lentil chain in Nepal. There were 5 indicators based on environmental dimensions with average judgement rating of 3.04 and performance score 60.80%. Based on this rating and percentage score environmental sustainability level for Nepalese lentil value chain can be indicated at good level. However, within the theme, moderate (2 indicators) to good (3 indicators) level of sustainability were found for the assigned indicators ranging from 55.71 to 64.52 percentage score. Environmental dimensions of lentil value chain in Nepal found higher sustainability score with indicators agrobiodiversity conservation/conservation of local seeds, resilience and soil fertility enhancement. Whereas; lower performance score was found with the indicator use of chemicals and land degradation.\u003c/p\u003e\n \u003cp\u003eThe economic, social and environmental sustainability indicators for the lentil value chain showed at moderate level of performance providing evidence of the positive effect and scope in the country with sustainable development of the lentil sector in Nepal. The chain has an advantage in terms of scalability, profitability, employment, market demand, competitiveness, income as well as food and nutrition security, inclusiveness and gender equality biodiversity conservation, Resilience and soil fertility enhancement. Thus, lentil sector value chain in Nepal can be upgraded and strengthened as inclusive, pro-poor and nutrition sensitive value chain model. Similar to this result, Gautam et al., (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported an inclusive, competitive and sustainable lentil seed system can be established through a value chain approach in Nepal. Similarly, there is a need to create a new system of agriculture transformation that addresses existing barriers and unaffordable policies to support high level entrepreneurial spirit among actors (Alex et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3 Production risks and marketing constraints\u003c/h2\u003e\n \u003cp\u003eIn this study, during focus group discussion 7 types of major risks were realized by farmers in lentil farming. Individual responses from the sampled farmers were taken for occurrence level for each risk factors. Farmers perceived climatic hazard as a major risk and highly occurrence with mean score value 4.11 followed by incidence of disease with mean score 3.86 (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.). Similarly, occurrence of crop failure, lower farm income and unreliable market were ranked third, fourth and fifth with mean score value 3.37, 3.13 and 2.94 respectively. Erratic rainfall during flowering phase, flooding and drought within the crop period and frequent incidence of Stemphylium blight diseases leading to crop failure and low yield are major challenges perceived by majority of farmers in the study area.\u003c/p\u003e\n \u003cp\u003eSimilarly, based on index value among various marketing related challenges, price fluctuation with index value 0.9 was listed as the major trade related challenge creating risks in lentil sector. Similar to this result, Gautam et al., (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) also mentioned price fluctuation as a major problem with index value 0.783 mainly as a result of scientific pricing mechanism. Likewise, low quality and volume of lentil availability (0.71) and poor linkages with value chain actors (0.60) were also the challenges in lentil marketing system in Nepal followed by poor lacking market related infrastructures and irregular demand and supply (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003e4.4 Lentil production risk assessment\u003c/h2\u003e\n \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.1 Risk analysis on yield, revenue, and profit of lentil\u003c/h2\u003e\n \u003cp\u003eIn agriculture, the main risk categories include financial, price, production, economic, and personal risks, which arise from various interconnected factors. Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e compares production, financial, and profit risks based on variance analysis, showing that yield and profit risks were similar, while cost risks were notably lower.\u003c/p\u003e\n \u003cp\u003eThe coefficient of variation (CV) analysis showed that financial and cost risks are relatively lower (0.83) than those related to lentil yield (1.05) and profit (1.08). The coefficient of variation for yield and profit exceeded 1, indicating high variability and exposure to climate and input-related risks. The small variation in input usage suggests a low cost risk. However, the high variation in output, likely due to farmers\u0026apos; seed choices and fluctuations in market supply and demand, makes yield and price risks the most critical. Supporting this, Haile et al. (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) also reported that yield and market-related price risks significantly affect to global food supply. Based on this result, to minimize the risks of yield, high-yielding varieties should be made available to all the farmers with a package of practices that accelerate production. Similarly, profit risk can be minimized by the provision of a minimum support price of lentil and facilitating the creation of a strong lentil value chain linkage.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of yield, cost, and profit risks in lentil farming\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYield risk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFinancial/cost risk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfit risk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal production\u003c/p\u003e\n \u003cp\u003e(kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e118780.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Variable\u003c/p\u003e\n \u003cp\u003eCost (NPR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6272877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal profit (NPR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10820920.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003cp\u003eProduction (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e251.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage Variable\u003c/p\u003e\n \u003cp\u003eCost (NPR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13261.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003cp\u003eprofit (NPR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22877.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVariance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70004.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVariance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22e\u0026thinsp;+\u0026thinsp;08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVariance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.17e\u0026thinsp;+\u0026thinsp;08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e264.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11052.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24830.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eSource: Field survey (2022)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.2 Associated risks factors perceived by lentil farmers in production system\u003c/h2\u003e\n \u003cp\u003eRisk perception is a subjective judgment which measures the probability and the consequences of some uncertain events (Sjoberg et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). In this study, during focus group discussion 7 types of major risks were realized by farmers in lentil farming. Individual responses from the sampled farmers were taken for occurrence level for each risk factors and responses regarding risk aversions statement. Farmers perceived climatic hazard as a major risk and highly occurrence with mean score value 4.11 followed by incidence of disease with mean score 3.86. Erratic rainfall during flowering phase, flooding and drought within the crop period and frequent incidence of Stemphylium blight diseases leading to crop failure and low yield are major challenges perceived by majority of farmers in the study area. Similarly, occurrence of crop failure, lower farm income and unreliable market were ranked third, fourth and fifth with mean score value 3.37, 3.13 and 2.94 respectively. About 47 percent of farmers perceived very likely occurrence of climatic hazard and 49% perceived likely occurrence of disease in lentil farming in the study area. Inputs availability and lack of credit risks were also perceived but with least occurrence among the identified risks in lentil production in the study area. The farmers in the study area found inaccessibility of improved seed and were also unable to purchase and use high yielding varieties; therefore, they opted to use their own home saved seed. The non-availability of fertilizers for lentil crop and treating lentil as a crop with no fertilizer required was the other crucial problem that affected the production potential of lentil producers in the study area which in turn negatively affected the production and market potential of the farmers. Lack of credit with the lowest mean score of 2.51 was perceived to be least important risk factor for lentil farmers in the study area may be due to involvement in groups and cooperatives and easy access to credit facility through their membership organization. The details about the risk factors and level of occurrence based on five-point scale as perceived by sampled farmers are presented in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e also presents ranks of the mean scores to show which of the 7 risk factors were important in lentil production for the farmers in the study area.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFarmer perceived responses on level of risks occurrence and their rank\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAssociated risks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eLevel of occurrence (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMean score\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRank by mean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVery unlikely\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnlikely\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLikely\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVery likely\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCrop failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClimatic hazards\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInputs unavailability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncidence of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnreliable market\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of credit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Own computation result based on survey data (2022)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.3 Exploratory Factor Analysis\u003c/h2\u003e\n \u003cp\u003eThe seven risk factors were subjected to EFA to assess their validity and reliability. The results report the suitability of the data to be analyzed, factor extraction and rotation, and interpretation. The result in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e suggested that three factors were retained as a principal-component factors of associated risks with Eigen value greater than 1. Based on Kaiser\u0026rsquo;s criterion, the 7 risks items were reduced to 3 factors as a result of varimax rotated principal-component factor analysis for perceived risks by lentil farmers in the study area. The Kaiser-Meyer-Olkin (KMO) sample adequacy test result showed a value of 0.573 and a Bartlett\u0026rsquo;s test value (Chi2\u0026thinsp;=\u0026thinsp;130.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.000) implied that sufficient and reliable factors were produced (Bartlett, \u003cspan class=\"CitationRef\"\u003e1951\u003c/span\u003e). These results suggest that factor analysis could be conducted with the data. The number from the varimax rotation resulted the factor loading which depicts the strength of the relationships between the items included and the factors. The magnitude of the factor loading determines the number of factors to retain. In addition to this, the mean associated with each item indicates the relative importance of the risks in the study area. Three of the risk management strategies were named as market and institutional risk, production risk and climatic and input risk, and the naming of each factor was done based on the characteristics of the items included within that factor.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eVarimax rotated factor loadings of perceived risks by lentil farmers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePerceived risks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFactor loading\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCrop failure (R1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.7216\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClimatic hazards (R2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.3666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6650\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInputs unavailability (R3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8138\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncidence of disease (R4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.5866\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0655\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower income (R5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7614\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0508\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnreliable market (R6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6911\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of credit (R7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6321\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1793\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003ePrincipal-component factors and variance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEigenvalues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.52684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal variance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1551\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCumulative % of variance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnostic tests\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKaiser-Meyer-Olkin Measure of Sampling Adequacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBartlett\u0026apos;s Test of Sphericity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130.15***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Own computation result based on survey data (2022)\u003c/p\u003e\n \u003cp\u003eNote: Factor 1= Market and Institutional, 2= Production, 3= Climatic \u0026amp; input. Loadings of greater than 0.4 are in bold. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.4 Risk management strategies adopted by farmers\u003c/h2\u003e\n \u003cp\u003eFarmers\u0026rsquo; perceptions of and responses to risk are important in understanding their risk behavior and management. The welfare of the farm family and survival of agri-business depends on how well farming related risks are perceived and managed (Hardaker et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). According to the result of this study as presented in Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, crop diversification, saving seed for next year, involvement in cooperatives were the major risk management strategies followed by lentil farmers in the study area with mean score value 4.09, 4.02 and 3.60 respectively. Similar to this result, Sapkota (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) mentioned crop diversification as the most important risk management strategy followed by farmers in Nepal. Likewise, diverse income source, saving income, having strength and trusted relationship especially with local collectors, having own irrigation facility, using disease resistant improved varietal seed, access to information and buying seed from authentic sources were also some of the strategies adopted by farmers. Buying seed from authentic sources, frequent contact with agri-technician, making formal/informal contacts with buyer, listening agriculture programs and using mobiles applications were the strategies least adopted by the lentil farmers in the study area. Among 18 strategies, farmers disagreed on adoption of 6 different strategies which were insurance scheme, information on climatic parameters, use of drought/flood resistant improved varieties, buying and saving inputs for lentil crop, use of disease resistant varieties and storing of grains for certain time period. The details about the risk management strategies adopted by sampled farmers and their rank are presented in Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e ranks the mean scores among 18 strategies adopted by the farmers in lentil production.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean score and rank for risk management strategies adopted by lentil farmers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLabel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRisk management strategies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMean\u003c/p\u003e\n \u003cp\u003escore\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRank by mean\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCrop diversification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuying seed from authentic sources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePossession of off farm income source\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdoption of insurance scheme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTaking information regarding climatic parameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHaving own irrigation facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUse of drought/flood resistant improved varieties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSaving own produce for seed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSaving inputs like fertilizer for lentil season\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular contact with agri-technicians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eListening agriculture programs, and using ICTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdoption of disease resistant varieties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStorage for fetching higher price\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSearch alternative potential buyers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFormal/informal contracts with buyer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEstablishing trusted relationship with buyers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSaving money in bank\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvolvement in a cooperative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Own computation result based on survey data (2022)\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMean score (1\u0026thinsp;=\u0026thinsp;totally disagree, 5\u0026thinsp;=\u0026thinsp;totally agree)\u003c/p\u003e\n \u003cp\u003eFollowing the descriptive analysis of the important risk management strategies, a factor analysis was performed, as shown in Table \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e. The Bartlett test of sphericity was significant at 1% level. The null hypothesis was therefore rejected indicating that the variables are correlated and factor analysis is appropriate for the data. The result of the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO test) was 0.684, validating the adequacy of the present sample which is considered as mediocre (Field, \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e) indicating that the data is suitable for factor analysis. The Kaiser-Meyer-Olkin measure of sampling adequacy is 0.684 is greater than 0.5, which is supported the use of principal component/factor analysis (Kaiser, \u003cspan class=\"CitationRef\"\u003e1974\u003c/span\u003e). The eigenvalues measure the amount of the variation explained by each factor and is largest for the first factor and smaller for the subsequent factors. Accordingly, proportion of variance explained by the first 7 components was 59.69%.\u003c/p\u003e\n \u003cp\u003eFactor analysis was conducted and 7 components were retained. The number of components to be retained was guided by the most commonly used Kaisers criterion which requires that only those components with an eigenvalue greater than 1 should be retained (Kaiser, \u003cspan class=\"CitationRef\"\u003e1960\u003c/span\u003e). These 7 components were defined and named considering the variables with greater loads (Hair et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). The components labeled are as follows: (1) awareness and production diversification strategies, (2) seed management strategies, (3) institutional involvement strategies, (4) land and input management strategies, (5) input-output management strategies, (6) Income diversification and saving strategies, and (7) Marketing strategies. Varimax rotation with Kaiser Normalization was used to facilitate interpretation of the factor matrix.\u003c/p\u003e\n \u003cp\u003eFrom the result, factor 1 accounted for 16.94% of the total variance in the model. Based on the variables that loaded highly on component 1, it was interpreted as awareness and production diversification strategies. The statements that loaded highly on this component are growing different types of crops, taking information regarding climatic parameters and listening agriculture programs, use mobile apps and other media. Strategies like using disease, flood and drought resistant varietal seed of lentil and saving seed for next year loaded highly on factor 2 therefore this factor is labeled as seed management strategy. This factor explained 12.8% of the total variance in the model. Due to uncertainty of seed availability farmers save their harvest as a seed for next year. Seed management strategy helps smallholder farmers to improve their crops yield by using improved varietal seed.\u003c/p\u003e\n \u003cp\u003eFactor 3 termed as institutional involvement strategies accounted for 7.8% of total variance. Involvement in a cooperative, remain contact with extension workers and information applications loaded highly on this factor. This will enable the smallholder farmers have better access to technical information on how to manage risk in lentil production through contact visits from agricultural extension workers and cooperatives. Factor 4 was interpreted as farm and input management strategies with two variables loading and accounted for 7.3% of the total variance. These variables are: adopting farm insurance scheme and saving some sort of inputs from previous season to produce lentil. With 6.7% of total variance, factor 5 was labelled as input-output management strategies including buying seed from authentic source, having own irrigation facility and maintaining trusted relationship with local buyers exists. Similarly, factor 6 was interpreted as income diversification and saving strategy explaining 6.4% of variance. Income diversification strategies would enable smallholder farmers to reduce their variability in income and saving of the farm income provide some sort of security in uncertainty situation. Hence the role of income diversification and saving for managing risk was perceived as important among lentil farmers in the study area. Also, this result is consistent with the findings of Belanieh and Drake (\u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) for Eastern Highlands Ethiopian smallholder farmers. Lastly, factor 7 with variables storage of grains and seeking potential buyers to gain higher profit by selling lentil was interpreted as marketing strategy with 6.01% of variance explained. Similar to this finding, Bhattarai (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported the empirical evidence that the farmers in Nepal use multidimensional strategic approach for risk reduction and management.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eVarimax rotated result of factor loadings for risk management strategies adopted by lentil farmers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRisk management strategies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eFactor loading\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.5592\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4253\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.2835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.2536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.3603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.2646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4567\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7512\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6989\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.2113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.5930\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.2096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6160\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.1025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.1243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.7669\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0789\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8487\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4949\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.1802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.1101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4751\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.2913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4537\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.1740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.2459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.7137\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.2276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6740\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.2222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4909\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0564\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7327\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0534\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7771\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRM18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.2260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7497\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-0.0090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrincipal-component factors and variance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEigen values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.04899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.53833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.20442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.08253\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal variance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.0601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCumulative percent of variance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.4731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.5969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eDiagnostic tests\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eKaiser-Meyer-Olkin Measure of Sampling Adequacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eBartlett\u0026apos;s Test of Sphericity 1099.42***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Own computation result based on survey data (2022)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNote: Factor 1=awareness and production diversification strategies, 2=seed management strategies, 3=institutional involvement strategies, 4=Farm and input management strategies, 5=input-output management strategies, 6=Income diversification and saving strategies, and 7=Marketing strategies. Note: Loadings of greater than 0.4 are in bold. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDescription and expected sign of the farmers\u0026apos; socio-economic variables used in SUR model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u0026rsquo;s name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription and measures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExpected sign\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eDependent Variables (7 retained factors after factor analysis)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFactor scores of seven individual strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScore of individual risk management strategies factor after factor analysis (Awareness and production diversification, Seed management, Institutional involvement, Farm and input management, Input-output management, Income diversification and saving, and Marketing strategies).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(5.66e-09, 1.43e-08, -4.40e-09, 2.13e-08, 2.72e-08, 6.18e-09, 3.38e-09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eIndependent Variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACESS_TECH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 if farmers have access to technical services and 0 otherwise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHH_EDU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducated farmers are expected to acquire improved seed and technologies faster than illiterate farmers. Years of schooling of the household head in number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACCESS_CREDIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 if farmers have access to a loan and 0 otherwise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLAND_SIZE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIt shows the amount of total land owned by farmers measured in hectare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAIN_OCCU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 if household\u0026rsquo;s main occupation is farming and 0 otherwise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGENDER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 if household head is male; and 0 otherwise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDIS_TECHSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIt denotes the farm distance from government technical offices measured in km\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEMBERSHIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThis represents involvement of lentil farmers in farmer\u0026rsquo;s groups or cooperatives. From this membership, they can get technical assistance, inputs, and information.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTRAINING\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 if the farmer has received training on lentil farming and 0 otherwise.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eECON_ACTIVE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIt represents the number of members in the family between the ages of 15 and 59 years.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXPERIENCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExperience of sampled farmers in lentil farming measured in years.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGE_HHH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIt is the age of the household head farming lentil (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLogINCOME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnual household income from lentil (NPR in Natural logarithm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003ePerceived risk factor scores after factor analysis (Predicted risk factor)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrf\u003csub\u003e1\u003c/sub\u003e- Market and Institutional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScore of individual perception about the market and institutional risk factor after factor analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.01e-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrf\u003csub\u003e2\u003c/sub\u003e- Production\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScore of individual perception about the production risk factor after factor analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.70e-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrf\u003csub\u003e3\u003c/sub\u003e- Climatic and input\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScore of individual perception about climatic and input risk factor after factor analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.92e-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eSource: Own illustrations based on field survey (2022)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.5 Determinants of risk management strategies\u003c/h2\u003e\n \u003cp\u003eThe result from the varimax rotation method yields seven factors. These seven factors were regressed against the socio-economic, demographic and institutional factors. To do so, the SUR model was applied, since it contains seven simultaneously regressed equations which have correlated residuals. Description and expected sign of the farmers\u0026apos; socio-economic variables used in SUR model is presented in Table \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThe SUR model results in Table \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e revealed that the independent variables explain the total variance of 28%, 17%, 15%, 21%, 14%, 12% and 11% for the awareness and production diversification, seed management, institutional involvement, farm and input management, input-output management, income diversification and saving and Marketing strategies respectively. In addition to the R\u003csup\u003e2\u003c/sup\u003e value, the \u0026chi;2 statistics are significant for each dependent variable at a one percent probability level, which shows the overall fitness of the model with the data used in the analysis process. The test for the correlation between the residuals resulted in a significant \u0026chi;2 value (\u0026chi;2 (21)\u0026thinsp;=\u0026thinsp;45.43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.002), which implies that there is a significant relationship between residuals; therefore, the SUR model best fit with the data. The result depicted that the awareness and product diversification strategy was significantly and positively affected by perceived risk behavior of farmers on market \u0026amp; institutional and production risk factors. Whereas; climatic \u0026amp; input risk perceived factors affects negatively may be due to beyond of farmer\u0026rsquo;s control. Also, distance of farm to technical source, and income from lentil production are negatively significant at 5% and 1% level respectively indicating that the management strategy decreases with increase in distance to technical source and increased in income from lentil.\u003c/p\u003e\n \u003cp\u003eSeed management strategy was significantly and positively affected by market and institutional risk factors perception and negatively by perceived climatic and input risk factors. Institutional involvement strategy was found negatively and significantly affected by land size and positively affected by perceived climatic and input risk factors. But contradicts to this result, the study of Nahraeni (\u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e); Kislingerova and Spicka (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that large farm size provides a greater management capacity and greater economies of scale for the farmers and could lead them to apply different risk management practices. Similarly, farm and input management strategy were positively affected by perceived risk factors (production and market and institutional) and experience whereas; negatively affected by gender of household head. The farmers are intelligent on their farms due to the practical experience that they develop.\u003c/p\u003e\n \u003cp\u003eThe finding is in line with Girma et al., (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e); Adimassu and Kessler (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Chikezie et al. (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). This indicates that the farm and input management strategies were increased when the household head was women or farm decision made by women in a household. Input-output management strategies were affected positively by perceived risk factors (climatic and input, production) and if main occupation is agriculture but affects negatively with increased in income from lentil. Likewise, perceived risk factors (production, market \u0026amp; institutional) and income from lentil were the determinants of adopting income diversification and saving strategies where increase in income from lentil affects negatively in the adoption. Perceived production risk factor, access to credit, gender of household head as male and membership in groups and cooperatives affected positively to adopt marketing strategies among the lentil farmers. Access to credit and involvement in farmers group/cooperatives are found positive determinants of adopting marketing strategies for risk management in the study area. Similar to this result, James and Yunxian (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) also found that social group membership provided collective interventions to ensure good risk protection management and optimization strategies. Also, Girma et al., (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) resulted positive relationship between membership and production related risk management strategies by maize farmers in Ethiopia.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab10\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship between risk management strategies and socioeconomic variables of the lentil farmers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eExplanatory variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eRisk Management Strategies\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAwareness and product diversification\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSeed management\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInstitutional involvement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFarm and input management\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInput-output management\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncome diversification and saving\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMarketing\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACESS_TECH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.010 (0.086)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.006 (0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.101\u003c/p\u003e\n \u003cp\u003e(0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.043\u003c/p\u003e\n \u003cp\u003e(0.091)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.105\u003c/p\u003e\n \u003cp\u003e(0.091)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003cp\u003e(0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003cp\u003e(0.933)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHH_EDU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.005 (0.012)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003cp\u003e(0.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0004\u003c/p\u003e\n \u003cp\u003e(0.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003cp\u003e(0.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.017\u003c/p\u003e\n \u003cp\u003e(0.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003cp\u003e(0.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003cp\u003e(0.013)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrf\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.267*** (0.042)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.095**\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.074\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.167***\u003c/p\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.125***\u003c/p\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrf\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.080* (0.042)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.156***\u003c/p\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.178***\u003c/p\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.222***\u003c/p\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.109**\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrf\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.201*** (0.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.227***\u003c/p\u003e\n \u003cp\u003e(0.046)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.199***\u003c/p\u003e\n \u003cp\u003e(0.046)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.197***\u003c/p\u003e\n \u003cp\u003e(0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003cp\u003e(0.046)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003cp\u003e(0.046)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACCESS_CREDIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.023 (0.066)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.062\u003c/p\u003e\n \u003cp\u003e(0.070)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.025\u003c/p\u003e\n \u003cp\u003e(0.070)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.039\u003c/p\u003e\n \u003cp\u003e(0.069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003cp\u003e(0.069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.102\u003c/p\u003e\n \u003cp\u003e(0.069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.203***\u003c/p\u003e\n \u003cp\u003e(0.071)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLAND_AREA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0005 (0.033)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003cp\u003e(0.035)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.008*\u003c/p\u003e\n \u003cp\u003e(0.035)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003cp\u003e(0.035)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003cp\u003e(0.035)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003cp\u003e(0.035)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003cp\u003e(0.035)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAIN_OCCU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.129\u003c/p\u003e\n \u003cp\u003e(0.131)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.113\u003c/p\u003e\n \u003cp\u003e(0.140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.212\u003c/p\u003e\n \u003cp\u003e(0.140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.128\u003c/p\u003e\n \u003cp\u003e(0.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.270**\u003c/p\u003e\n \u003cp\u003e(0.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.032\u003c/p\u003e\n \u003cp\u003e(0.139)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.054\u003c/p\u003e\n \u003cp\u003e(0.141)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGENDER\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.141 (0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.068\u003c/p\u003e\n \u003cp\u003e(0.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003cp\u003e(0.099)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.046**\u003c/p\u003e\n \u003cp\u003e(0.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.057\u003c/p\u003e\n \u003cp\u003e(0.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.093\u003c/p\u003e\n \u003cp\u003e(0.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.207**\u003c/p\u003e\n \u003cp\u003e(0.099)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDIS_TECHSOURCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.014** (0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e(0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003cp\u003e(0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003cp\u003e(0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0009\u003c/p\u003e\n \u003cp\u003e(0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003cp\u003e(0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003cp\u003e(0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEMBERSHIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.105 (0.087)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003cp\u003e(0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003cp\u003e(0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003cp\u003e(0.096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003cp\u003e(0.091)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003cp\u003e(0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.177*\u003c/p\u003e\n \u003cp\u003e(0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTRAINING\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.093 (0.088)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003cp\u003e(0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003cp\u003e(0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003cp\u003e(0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003cp\u003e(0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003cp\u003e(0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003cp\u003e(0.095)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eECON_ACTIVE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0002 (0.017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0008\u003c/p\u003e\n \u003cp\u003e(0.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003cp\u003e(0.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003e(0.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003cp\u003e(0.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.020\u003c/p\u003e\n \u003cp\u003e(0.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003cp\u003e(0.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEXPERIENCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0001 (0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003cp\u003e(0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e(0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0071**\u003c/p\u003e\n \u003cp\u003e(0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003cp\u003e(0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003cp\u003e(0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003cp\u003e(0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGE_HHH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002 (0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e(0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0001\u003c/p\u003e\n \u003cp\u003e(0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0007\u003c/p\u003e\n \u003cp\u003e(0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003cp\u003e(0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003cp\u003e(0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0003\u003c/p\u003e\n \u003cp\u003e(0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLogINCOME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.189*** (0.056)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003cp\u003e(0.060)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.012\u003c/p\u003e\n \u003cp\u003e(0.060)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.168\u003c/p\u003e\n \u003cp\u003e(0.059)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.140**\u003c/p\u003e\n \u003cp\u003e(0.060)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.011**\u003c/p\u003e\n \u003cp\u003e(0.060)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003cp\u003e(0.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.795*** (0.575)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003cp\u003e(0.613)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003cp\u003e(0.616)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.442\u003c/p\u003e\n \u003cp\u003e(0.607)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.907\u003c/p\u003e\n \u003cp\u003e(0.610)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003cp\u003e(0.610)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003cp\u003e(0.619)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eSummary Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of obs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLR Ch\u003csup\u003e2\u003c/sup\u003e (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109.10***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.72***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.10***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.15***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.34***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.54***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.56***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eSource: Estimation based on Field survey (2022)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eNote: Standard errors in parentheses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1. Figure in parentheses indicates standard error.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\n \u003ch2\u003e4.4.6 Risk aversion behavior of lentil farmers\u003c/h2\u003e\n \u003cp\u003eBecause of having limited resources, information, and knowledge to cope with adverse events, farmers are often risk-averse. This behavior can influence delay farm decision making process making them reluctant to adopt and invest in new technology and practices. Based on farmers\u0026apos; opinion, study resulted majority of lentil farmers (73.2%) were medium risk averse, 17.8% where low risk averse and only 9.1% were high risk averse (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). Result revealed that most farmers want to minimize large risks, they will accept small and/or moderate risks. Hence, they are cautious but willing to try new approaches with additional support, advisory services and capacity building mechanisms to make better decisions and be able to manage their risks. This result can be generalized as showing that most farmers in Nepal and similar areas are moderately risk-averse, needing support to try new and improved farming practices (Begho, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similar to this result, CRS (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported smallholders and women farmers in lentil production are generally risk averse, and take longer time to accept new technologies in their report about lentil value chain study in Nepal.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"5 Discussion","content":"\u003cp\u003eThe findings highlight a risk-sustainability paradox, while lentils are profitable and globally demanded, their production is increasingly vulnerable to weather, pests, and market fluctuations. This aligns with studies by Adimassu \u0026amp; Kessler (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Girma et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), who observed that farmers\u0026rsquo; risk perception influences both input use and sustainability engagement.\u003c/p\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Sustainability assessment of lentil value chain\u003c/h2\u003e\u003cp\u003eA sustainable value chain involves production that is economically viable, socially fair, and environmentally responsible, adding value to the product throughout its journey to the consumer (Subedi, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The moderate level of sustainability performance of lentil value chain in Nepal was found while analyzing value chain sustainability performance. The social dimension of sustainability was rated at a moderate level, while the economic and environmental dimensions received good ratings. Supportive to this result, Lentil production is seen as a beneficial crop for rotation, providing environmental, economic, and health benefits while supporting food security through local or national sourcing (Warne et al., 2019). Likewise, Subedi (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) stated that only a few existing value chains efficiently ensure the smooth flow of quality inputs to farmers and agro-products to consumers, limiting overall market effectiveness. Similarly, Gebre and Rik (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found moderate sustainability in Ethiopia's banana value chain, and Gebre et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported moderate sustainability across economic, social, and environmental factors in their study in banana value chain sustainability assessment. Similarly, Das et al. (2018) reported economic and ecological potential of legumes including lentil to achieve sustainable growth.\u003c/p\u003e\u003cp\u003eEconomic sustainability level for the Nepalese lentil value chain was found at a good level. Similar to this result, CRS (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported low marketable surplus, government incentives and significantly fluctuating lentil prices hindering economic participation and benefits in the lentil value chain in Nepal. The social sustainability aspect of the lentil value chain in Nepal was found at a moderate level, characterized as poorly addressed compared to economic and environmental. Similarly, Subedi (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) noted that the lack of coordination among value chain actors at various levels has led to the loss and degradation of agricultural products in Nepal.\u003c/p\u003e\u003cp\u003eThe environment sustainability aspect of the lentil value chain in Nepal was found at a good level. Environmental benefits and soil nitrogen fixation are the key factors for a good level of sustainability. Similar to this result, Ved Prakash et al. (2002) found a 23.4% increase in soil nitrogen and rice yields after lentil cultivation in India, while Gautam et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) suggested a value chain approach for a sustainable lentil seed system in Nepal. Similarly, Alex et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) called for a new agricultural transformation system to overcome barriers and support entrepreneurship among actors. The sustainability scores in this study align with Verza et al. (\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who found that traceability and certification systems enhanced both price stability and environmental performance in lentil chains. However, unlike export-oriented chains in Canada or Ethiopia, Nepal\u0026rsquo;s lentil sector lacks coordination platforms, limiting value-added sustainability practices. Weak horizontal coordination among farmers and minimal vertical integration with processors and exporters limit chain efficiency. Public-private models and ICT tools may offer new opportunities for real-time risk sharing and sustainability tracking, as highlighted by FAO and UNDP (2020).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Factors, perception and management of risk\u003c/h2\u003e\u003cp\u003eAgriculture sector faces myriads of risks (Iturrioz, 2009). For the livelihood of subsistence farmers, production risks have more severe consequences than market risks because much of what they produced is consumed at home (Sapkota, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, farmers perceived climatic hazard as a major risk and highly occurring with a mean score value of 4.11, followed by the incidence of disease with a mean score of 3.86. Similarly, occurrence of crop failure, lower farm income and unreliable market were ranked third, fourth and fifth with mean score value 3.37, 3.13 and 2.94, respectively. Similar to this result, Bhandari and Joshi (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported weather irregularities and disease incidence were serious risk factors in lentil production in Nepal. Further, Iturrioz (2009) highlighted that climatic variables and market forces are the most significant risk factors in agriculture, both of which are unpredictable due to climate change and market liberalization. Additionally, several studies in Nepal, including those by Acharya (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Shrestha et al. (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and Khanal et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), have documented the impacts of climate change, such as extreme weather events, irregular rainfall, and prolonged droughts, which negatively affect agricultural production.\u003c/p\u003e\u003cp\u003eCrop diversification, mix cropping, saving seed for next year and involvement in cooperatives were the major strategies for risk management adopted by lentil farmers with mean score value 4.09, 4.02 and 3.60, respectively. Farmers totally disagreed on adoption of the insurance scheme, information on climatic parameters, use of drought-resistant improved varieties, buying and saving inputs for the lentil crop, use of disease-resistant varieties, and storing of grains for a certain time period. In line with this result, Sapkota (\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that Nepalese farmers mainly use crop diversification and integrated farming as risk management strategies, along with joining farmers' groups and cooperatives. Further, Bhattarai (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that the farmers in Nepal use multidimensional strategic approach for risk reduction and management.\u003c/p\u003e\u003c/div\u003e"},{"header":"6 Conclusion and Recommendations","content":"\u003cp\u003eThis study assessed production risks and value chain sustainability among lentil farmers in Nepal, revealing a buyer-driven, informal, and multi-actor value chain with limited product and information flow and weak vertical and horizontal linkages. It also highlights key risks and sustainability challenges, offering useful evidence to improve lentil value chains in Nepal and other similar regions. Seven marketing channels were identified, with the largest volume transacted through local collector-led channels and the smallest through direct producer-consumer and large collector-retailer channels. The lentil value chain demonstrates significant potential for rural employment and income generation, yet communication between farmers and traders remains informal and trust-limited.\u003c/p\u003e\n\u003cp\u003eUsing a triple bottom line approach, the lentil value chain showed moderate sustainability, with strong economic and environmental performance but moderate social sustainability that requires attention. Key strengths include scalability, market demand, food and nutrition security, profitability, inclusiveness, gender equality, rural employment, innovation, biodiversity conservation, resilience, and soil fertility. However, challenges persist in input availability, risk management, value addition, government support, storage infrastructure, stakeholder coordination, fair income distribution, grievance handling, farmer bargaining power, seed dependency, chemical use, and land restoration.\u003c/p\u003e\n\u003cp\u003eProduction risks such as climatic hazards, disease, and crop failure are major concerns for lentil farmers. Yield and profit risks were found to be the most significant due to high output variability, while cost risks remained low, highlighting the need for improved seed access, production practices, and value chain support. Risk management strategies primarily include crop diversification, seed saving, cooperative participation, diversified income sources, trusted relationships with collectors, irrigation, and information access. Adoption of formal strategies like certified seed use, extension contact, crop insurance, and climate information remains low, signaling the need for improved facilitation and policy support. Most farmers remain moderately risk-averse, preferring seed self-sufficiency and inclusive commercialization models. Yield improvement and crop management programs are vital to mitigating these risks.\u003c/p\u003e\n\u003cp\u003eEconometric modelling using a Seemingly Unrelated Regression (SUR) approach identified seven strategic groups of risk management ranging from awareness to marketing significantly influenced by perceived risk types, gender, landholding, household income, group membership, access to credit, and distance to technical support. This study demonstrates the value of combining econometric analysis with value chain sustainability assessment under a triple-bottom-line framework. The SUR model proved effective in identifying behavioral drivers of risk management. Higher income from lentil found negatively influenced strategy adoption in some cases, while access to cooperatives involvement, credit, and information positively supported marketing and seed-related strategies adoption. These results emphasize the role of socio-economic and institutional factors in shaping farmers\u0026rsquo; risk behavior and the effectiveness of their coping mechanisms.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eRecommendations\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eBased on the study\u0026rsquo;s findings and aligned with the Sustainable Development Goals (SDGs), the following recommendations are proposed to promote an inclusive, climate-resilient, and market-oriented lentil system in Nepal and similar regions. These targeted actions aim to strengthen both production and value chain sustainability:\u003c/p\u003e\n\u003cp\u003ea. \u0026nbsp;Risk reduction and climate resilience (SDG 2, SDG 13)\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eInitiate early detection systems and rapid response team of expert to respond quickly to outbreaks of disease, pests, and potential climate events in lentil growing pockets.\u003c/li\u003e\n \u003cli\u003eIncrease easy access to insurance scheme and climate-smart practices for smallholder farmers.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eb. \u0026nbsp;Input and production efficiency (SDG 2, SDG 12)\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSupport the production group to adopt improved, disease-resistant lentil varieties\u003c/li\u003e\n \u003cli\u003eEncourage collective approach for input management, crop production/management, and marketing management to reduce costs and improve efficiency.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003ec. \u0026nbsp;Market access, governance and coordination (SDG 2, SDG12, SDG13)\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eEstablish multi-actor platforms that bring together farmers, traders, service providers, and policymakers to improve coordination, solve problems, and drive innovation.\u003c/li\u003e\n \u003cli\u003eApply a \u0026ldquo;technology-push and market-pull\u0026rdquo; approach aligning research, extension and market for a resilient and sustainable lentil value chain.\u003c/li\u003e\n \u003cli\u003eStrengthen infrastructure and services such as storage, transport, finance, price and market information, and technical support to enhance the resilience.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eStrengthen infrastructure and services such as storage, transport, finance, price and market information, and technical support to enhance the resilience.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript is a part of the PhD research work under Department of Agricultural Economics and Agribusiness Management, Agriculture and Forestry University, Nepal. Lentil producers, traders, and business enablers at Nepal were highly acknowledge for their time and information. We acknowledge all the stakeholders and officials who directly or indirectly involved during this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCRediT:\u0026nbsp;\u003cstrong\u003eBinod Ghimire\u003c/strong\u003e: Conceptualization, research design, formal analysis, investigation, methodology, visualization, writing-original draft, coordinated with co-authors for suggestions and feedback to finalize the article. Final approval of the version for publication;\u0026nbsp;\u003cstrong\u003eShiva Chandra Dhakal\u003c/strong\u003e: Conceptualization, methodology, supervision, validation, writing: review and editing, approval for publication;\u0026nbsp;\u003cstrong\u003eSantosh Marahatta\u003c/strong\u003e: Software, supervision, validation, writing \u0026ndash; review \u0026amp; editing and approval for publication;\u0026nbsp;\u003cstrong\u003eRam Chandra Bastakoti\u003c/strong\u003e: Resources, supervision, validation, visualization, writing \u0026ndash; review \u0026amp; editing, approval for publication.\u003c/p\u003e\n\u003cp\u003eAll authors approved the final version and are accountable for the work\u0026apos;s integrity and accuracy. The corresponding author takes full responsibility for correspondence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was approved by the Agriculture and Forestry University, Directorate of Research and Extension (Ref.-280/082/83). Written and Verbal informed consent was obtained from all participants, who were assured of their voluntary participation, the right to withdraw at any time, and the confidentiality of their responses. No minors, clinical trials, or sensitive personal data were involved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors herewith declare no any competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for this study was supported by WTO Chairs Programme, Kathmandu University School of Management, Nepal (Grant number: KUSoM-2023) and USAID Agriculture Higher Education Nepal-2023.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eORCID\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBinod Ghimire: https://orcid.org/0000-0003-0546-3496\u003c/p\u003e\n\u003cp\u003eShiva Chandra Dhakal: 0000-0002-2801-8937\u003c/p\u003e\n\u003cp\u003eSantosh Marahatta: 0000-0002-5128-4029\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData generated from primary source will not be accessible publicly but can be made available by corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAcharya, R. 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Journal of the American Statistical Association, 57(298), 348\u0026ndash;368.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Agriculture and Forestry University, Chitwan, Nepal","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Triple bottom line, Sustainability, Value chain, Risk, Lentil, Nepal","lastPublishedDoi":"10.21203/rs.3.rs-7043104/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7043104/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCommodity value chain sustainability is critical for agricultural growth, especially for lentil (\u003cem\u003eLens culinaris\u003c/em\u003e), an important commercial legume in Nepal grown under risky conditions. This study assesses production risks and value chain sustainability using econometric modelling. Data were collected through surveys of 473 farmers, 155 traders, 85 business enablers, 12 key informant interviews, and 4 focus group discussions. Employing a triple bottom-line framework, value chain mapping, exploratory factor analysis, scaling, indexing, and Seemingly Unrelated Regression, the study reveals a buyer-driven, multi-actor, informal, inclusive, multi-channel, yet profitable lentil value chain with limited product and information flows and weak actor linkages. Seven distinct marketing channels were identified. Sustainability assessment rated economic and environmental dimensions as \u0026ldquo;good,\u0026rdquo; while the social dimension was \u0026ldquo;moderate.\u0026rdquo; The value chain excels in profitability, employment, scalability, household food security, nutrition, and soil fertility but faces constraints in coordination, value share, farmers\u0026rsquo; bargaining power, market information, storage, pricing, and value addition. Yield and profit risks were most significant due to high output variability, while cost risks remained low. Farmers perceived climatic hazards (mean score 4.11) and disease incidence (3.86) as major risks. Key risk-management strategies included crop diversification (4.09), seed saving (4.02), and cooperative involvement (3.60). Factor analysis identified seven strategic risk groups. Seemingly Unrelated Regression revealed that strategy adoption is significantly influenced by risk types, gender, income, land size, group membership, credit access, and service proximity. Risk aversion was low in 7.3% of farmers, medium in 72.3%, and high in 11.2%. From sustainability perspective, cost reduction, early warning systems with rapid response teams, use of improved seeds, crop diversification, collective actions, and stronger value chain coordination are recommended.\u003c/p\u003e","manuscriptTitle":"Assessing Production Risks and Value Chain Sustainability in Nepal's Lentil (Lens culinarisMedik.) Sector: An Evidence-based Econometric Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 14:45:05","doi":"10.21203/rs.3.rs-7043104/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa33b825-cf05-4407-a108-05711c042e73","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51027246,"name":"Agricultural Economics \u0026 Policy"}],"tags":[],"updatedAt":"2025-07-07T14:45:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-07 14:45:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7043104","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7043104","identity":"rs-7043104","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}