Economic Efficiency and Adoption Determinants of Insect-Based Technologies for Organic Waste Recycling into Fertilizer

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Mugendi, Beatrice W. Muriithi, Raphael Gitau, Dennis Beesigamukama, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6264404/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Inappropriate handling of the abundant organic waste generated annually imposes far-reaching impacts on the environment, economies, and societal well-being. Insect-based technologies are gaining traction in recycling of organic waste and recovering valuable macro and micro-nutrients. However, there is little information about the costs and benefits of using black soldier fly (BSF) in recycling organic waste into fertilizer compared to conventional composting. This study determined factors influencing the adoption of BSF and its cos-effectiveness in recycling organic waste using logistic regression, cost-benefit analysis, and sensitivity analysis. A household survey was conducted among 222 households in Kiambu County, Kenya. Results revealed that membership in waste management groups, access to recycling information, and perception of diversification of recycled products significantly and positively influenced the adoption of BSF. Households adopting BSF recycle 3-fold higher volumes of organic waste annually and generate 5-fold higher return on investment than those using conventional composting. Our findings reveal that BSF is profitable, and a potential economically efficient technology for managing organic waste and promoting greener economies. These results should inform research and policy decisions aimed at developing and promoting efficient waste management technologies and integrate frass fertilizer production into smallholder cropping systems. Figures Figure 1 Figure 2 Figure 3 1. Introduction Globally, over two billion tonnes of organic waste are generated annually in urban and peri-urban areas, with only 16% of this waste being recycled [ 1 ]. In Kenya,70–80% of waste generated daily is mainly organic [ 2 ]. Yet only 10% of the total organic waste is properly disposed off in designated dumpsites and recycling facilities [ 2 ]. The illegally disposed organic waste (90%) results in economic losses, public health hazards, and environmental degradation [ 3 , 4 ] Additional threats include unpleasant odors, explosions of greenhouse gases including methane and carbon dioxide, breeding sites for disease-causing organisms, and disruption of biogeochemical cycles 5–7]. Therefore, there is an urgent need for local solutions and technologies that efficiently bio-convert organic waste into valuable products while promoting environmental restoration [ 8 ]. Efficient bioconversion of organic waste in closed-loop economies is a multifaceted problem that is caused by inefficient recycling and composting technologies, inappropriate collection and disposal infrastructure, and weak enforcement of laws and regulations that pave the way for illegal littering and dumping [ 9 ]. Moreover, there is a lack of public awareness on the potential economic benefits of efficient and cost-effective waste management practices [ 10 ]. Conventionally organic waste is managed through composting to produce bio-fertilizers [ 11 ]. However, the conventional composting methods are slow and, if not controlled, they induce negative effects such as directly contributing to the contamination of surface and drinking water, transmission of zoonotic diseases, and emission of methane, carbon dioxide, and offensive smells [ 12 , 13 ]. Therefore, there is a need for efficient, sustainable, and circular based bioeconomy interventions for managing organic waste, which can be achieved through insect-based technologies. The use of insect-based technologies such as black soldier fly ( Hermetia illucens , BSF) to recycle organic waste into larval biomass for feed and nutrient-rich organic fertilizer with minimal environmental footprint has gained global attention [ 14 – 18 ]. BSF larvae feed on a range of organic wastes including food waste (food scraps and any inedible portions of food), livestock waste (manure), and market waste (vegetable and fruit refuse) [ 19 ].The larvae have high affinity for organic waste and promote closed loop organic waste management through reducing volumes [ 20 , 21 ] pathogen concentrations [ 22 ], greenhouse gas emissions [ 23 ] and heavy metal concentrations [ 24 ]. The byproduct of this waste bioconversion process called “frass” consists of mixture of uneaten substrates, insect feces, insect shed exoskeleton, and dead insects. Frass has excellent fertilizing properties due to its rich organic matter, macro and micro-nutrients, and trace elements [ 25 – 28 ]. Recent studies have demonstrated frass’ potential to improve soil health [ 29 ], boost plant growth and yield [ 14 , 27 , 30 ] suppressing disease and pests [ 31 ], increasing farmers profits and reducing environmental burden of global warming and use of synthetic fertilizers [ 16 ]. However, some studies found that the application of BSF can inhibit plant growth due to the phytotoxicity of fresh frass and recommended further post processing to produce stable frass fertilizer [ 32 ]. Frass fertilizer is potentially a promising fertilizer, however further multidisciplinary research is required to fully evaluate its potential [ 33 ]. Despite the steady increase in literature promoting circular bio-economies and sustainable agricultural production through the use of BSF in recycling organic waste into frass, information on the economic aspects of its production is limited [ 34 ]. Existing studies have identified the nutritional composition of frass from different waste sources [ 35 ], socio-economic benefits of insect-based feed in poultry production [ 36 ], economic value of using frass in maize production BSF as an organic waste recycler [ 16 , 37 ], and cost benefits of BSF as an alternative fish ingredient [ 38 ]. All these studies show the potential benefits of adopting BSF in bio-converting waste into animal feed or frass fertilizer. However, there is limited research on the economic efficiency of producing frass compared to conventional composting among households, which is relevant when exploring the adoption and scalability of frass production. This paper addresses this knowledge gap by identifying the determinants of adopting BSF in recycling organic waste and estimating the cost-effectiveness of recycling organic waste into organic fertilizer using BSF larvae compared to conventional composting. We further discuss the externalities (immaterial benefits) associated with recycling organic waste into fertilizer among households based on existing literature. The study provides information on the economic benefits of using BSF in recycling organic waste compared to conventional composting thereby supporting the development of this novel frass fertilizer. 2 Materials and methods 2.1 Study area The study was conducted in Kiambu County, Kenya (Fig. 1 ). The county was purposively selected based on previous promotion efforts on recycling of organic waste conducted by icipe and the government in the area. 2.2 Data collection and sampling procedure The study utilized both primary and secondary data. The primary data was collected through a household-level survey using a semi-structured questionnaire with approval from the Egerton University Ethics and Review Committee (EUREC). The data entailed sociodemographic characteristics such as (age, years of schooling, gender, size of household, size of land for recycling, perceptions), institutional factors (such as distance to the source of waste, distance to the main market outlet, group membership, access to credit, access to extension services). Other variables included waste streams and types (such as livestock waste, market waste, farmyard waste, and kitchen waste), production requirements (such as start-up capital, operational and maintenance costs), and marketing (such as market price and main market outlets). A pretest was conducted to test the validity of the questionnaire. The secondary data were collected from reviews of relevant published and grey literature from research institutions and government agencies. The study employed a multistage sampling technique. In the first stage, Kiambu County was purposively selected as detailed in the previous section. In the second stage, two-wards from each of the 12 sub-counties in Kiambu County, where the majority of organic fertilizer producers resided, were purposively selected. Using a list of households recycling organic waste into fertilizer provided by icipe , and the County Department of Agriculture, Livestock, and Fisheries, a sample of the survey respondents was then randomly selected at the third stage. Proportion probability to size technique was used to determine the sample size to be randomly selected for each of the wards. The sample size was calculated at a confidence level of 95% and 0.05 precision, as [ 39 ] suggested when the population is known. n = \(\:\frac{N}{1+N\left({e}^{2}\right)}\) n = \(\:\frac{500}{1+500\left({0.05}^{2}\right)}\) = 222 (1) where n is the sample size, N is the target population, and e is the acceptable margin of error. The sample of 222 comprised 105 households using BSF and the remaining 117 were households using conventional (windrow) z composting to recycle organic waste into fertilizer. This sample size was representative of households recycling organic waste into fertilizer and the methodology can be replicated in other regions or countries. Moreover, the sample was derived from a heterogeneous population with no significant demographic and socio-economic characteristics that could affect the results. The EXCEL tool and STATA software were used to conduct descriptive analysis and econometric models. 2.3 Model specification 2.3.1 Logistic regression model The study adopted a logistic regression model to determine the factors influencing the choice of BSF for recycling organic waste into fertilizer. These factors include household characteristics, institutional factors, and perceived benefits [ 40 , 41 ] [ 42 , 43 ]. The logistic model was preferred to Ordinary Least Square and Probit because it corrects the linearity problem by transforming the dependent variable into logs, allowing for modelling nonlinear dependence linearity and easier interpretation [ 44 ]. The functional form of a binary logistic regression model is specified as illustrated in Eq. (2) P = ( Y = 1) = \(\:\frac{{e}^{\varvec{\beta\:}\varvec{X}i}}{1\:+\:{e}^{\varvec{\beta\:}\varvec{X}i}}\) (2) with a cumulative distribution function as illustrated in Eq. (3) F ( βX ) = \(\:\frac{1}{1\:+\:{e}^{\beta\:Xi}}\) (3) where Y = choice of an approach for recycling organic waste (specified as 1 if a household adopts BSF and 0 conventional composting), Xi is a vector of the explanatory variables, and β is a vector of the parameters to be estimated. Eq. (2) can also be written as illustrated in Eq. (4) Pi = \(\:\frac{1}{1\:+\:{e}^{-\varvec{Z}\varvec{i}}}\) (4) The probability that a producer household chooses to adopt BSF for recycling organic waste is illustrated in Eq. (4) and can be illustrated as follows in Eq. ( 5 ) $$\:\frac{Pi}{1\:-\:\:Pi\:}\:=\:\frac{1\:+\:{e}^{\varvec{Z}\varvec{i}}}{1\:+\:{e}^{-\varvec{Z}\varvec{i}}}$$ 5 where \(\:\frac{Pi}{1\:-\:\:Pi\:}\) is the odds ratio in favour of a household choice of adopting BSF. Therefore, taking the natural logarithms of Eq. ( 5 ) will be expressed as illustrated in Eq. (6) L i = ln \(\:\left[\frac{Pi}{1\:-\:\:Pi\:}\right]\) = Z i = β 0 + β 1 X 1 + ⋯ + β n X n + ε (6) where Pi is the probability of a producer household adopting BSF for organic waste recycling, which ranges between 1 and 0 , and Zi is a function of n explanatory variables Xi. The probability that a household adopts BSF in recycling organic waste is denoted by 1 and 0 if a household adopts conventional (windrow) composting. β 0 is the intercept, β 1 ... β n are coefficients of the model and ε is the error term. The variables are illustrated in Table 4 as continuous and categorical variables. Qualitative data was collected using a 5-point Likert scale and transformed to binary variables during analysis. 2.3.2 Cost Benefit Analysis (CBA) methodology This study adopted an allocative efficiency perspective and concepts of cost benefit analysis theory to evaluate the cost-effectiveness of using BSF compared to conventional composting. Cost-benefit analysis (CBA) indicators were used in estimating the cost-effectiveness of using BSF in recycling organic waste into fertilizer compared to conventional composting. This study adopted the approach used by Mogaka et al. [ 45 ] and [ 46 ] and employed four decision indicators: net present value (NPV), internal rate of return (IRR), return on investment (ROI), benefit-cost ratio, and sensitivity analysis to test for robustness of the NPV The NPV is the present value of discounted future net benefits, that is discounted financial benefits minus financial costs, with discounting accounting for inflation and risk aversion. A recycling method is deemed viable when NPV > 0 and rejected if otherwise, and it is expressed as follows; NPV (B, C) = \(\:{\sum\:}_{t=0}^{T}\frac{Bt}{{(1+r)}^{t}}-\:{\sum\:}_{t=0}^{T}\frac{Ct}{{\left(1+r\right)}^{t}}\:\) (7) where t is the lifecycle, B is the stream of benefits, C represents the costs, and r is the discount rate (12%, which is the opportunity cost of capital (Central Bank of Kenya lending rate (average of reference period 2022–2023)) The IRR calculates the discount rate at which the NPV has a zero-value (Eq. (8)) and compares it with the predetermined discount rate ( r ). ( B 0 + \(\:\frac{Bt}{{(1+i)}^{t}})\) – ( C 0 + \(\:\frac{Ct}{{(1+i)}^{t}})=0\) (8) where i is the discount rate The benefit-cost ratio is illustrated in Eq. ( 9 ). $$\:\frac{B}{C}=\:\frac{{\sum\:}_{t=0}^{T}\frac{Bt}{{(1+r)}^{t}}}{{\sum\:}_{t=0}^{T}\frac{Ct}{{(1+r)}^{t}}}$$ 9 where B represents the benefits, C represents the costs, r represents the discount rate, and t represents the time in years. The Return on Investment measures the gains/loss accrued from an investment, that is the recycling method, relative to the money invested (Eq. (10)). Return on investment (%) = \(\:\:\frac{net\:income}{total\:variable\:costs}\) × 100 (10) When computing the decision indicators, the following assumptions were used. Costs and revenues were expressed in US dollars, and all prices were estimated based on recall of the previous production cycle. The prices of the fertilizer and dried larvae were inclusive of taxes The discount rate (12%) controlled for the inflation rate [ 47 ] The lifecycle for recycling organic waste among households was arbitrarily selected to be 10 years The computation of the costs did not account for depreciation, interest on capital, sunk cost, and land value. 2.3.3 Sensitivity analysis Sensitivity analysis identifies critical variables whose positive or negative variations significantly impact the recycling method’s NPV. In this study, the optimistic-pessimistic scenario was applied. It involved assigning optimistic (most favourable) and pessimistic (least favourable) values and computing the effect on NPV, ceteris paribus. Based on the assumptions of a perfect market, an arbitrary 10% change in the selected variables was used. Critical variables were variables in which a variation of +/- 10% of the value in the base case had a more than 10% variation on NPV [ 48 ]. 2.3.4 Externalities Cost-effectiveness of recycling organic waste into fertilizer using BSF larvae also involves the determination of immaterial benefits (externalities) such as the effect on soil health, crop yield, GHG emissions, and social impact from the adoption of BSF compared to conventional composting. The Systematic Literature Review methodology was applied in determining the externalities. In the first step, Web of Science and Google Scholar search engines were used to identify literature related to use of insects such as BSF in organic waste management. Duplicate fields were dropped in the second step followed by screening to filter the irrelevant records based on research title. Full articles were then assessed for eligibility and those not mentioning the externalities were excluded. 3. Results 3.1 Determinants of adopting BSF in recycling organic waste into fertilizer The sociodemographic and institutional characteristics were statistically and significantly different among households using BSF and conventional composting (Table 4 ). The age of heads of households using BSF was on average 44 years, with 16 years of formal schooling and 2 years of organic waste recycling experience. Their counterpart windrow composting household heads were on average 56 years old, with 11 years of schooling and 5 years of organic waste recycling experience. Both practices have been introduced in the recent past by the County Government and icipe , respectively, with BSF being the latest. At farm level, 55% of households using BSF and 19% of households using conventional composting recycled segregated waste generated from their homesteads or had access to segregated waste. The logistic regression model demonstrated a good fit to the data (Table 1 ). The model's results demonstrated a good fit to the data as the predictors included in the model adequately explained the adoption of BSF in recycling organic waste (pseudo-R2 value of 0.796). Variables that significantly influenced the household choice of BSF technology in recycling organic waste into fertilizer included the age of the household head, number of years spent schooling, size of land explicitly used for recycling organic waste into fertilizer (production unit), number of social associations/ groups a household head belongs, access to agricultural/environmental extension information, and household perception of recycling organic waste into diverse products. Table 1 Logistic Regression Model results for factors influencing the choice of BSF for recycling organic waste into fertilizer among surveyed households in Kiambu County. Variable Odds ratio t-value p-value [95% Conf. Interval] Marginal effect (dy/dx) Age 0.937(0.034) -1.82 0.069 0.873 1.005 -0.0029(0.001) ** Household size 1.591(0.397) 1.86 0.063 0.976 2.594 0.0208(0.004) * Education 1.594(0.225) 3.30 .001 1.209 2.101 0.0207(0.010) *** Farm size¹ 0.929(0.030) -2.28 .023 .872 .99 -0.0033(0.001) * Group-mem 2.032(0.627) 2.30 .022 1.11 3.721 0.0316(0.014) ** Segregation 0.894(0.642) -0.16 .876 .218 3.657 -0.0049(0.031) Access-info 2.493(0.725) 3.14 .002 1.41 4.41 0.0407(0.014) *** Products 19.696(20.421) 2.87 .004 2.581 150.292 0.1422(0.040) *** Profitability 3.432(4.810) 0.88 .379 .22 53.515 0.0578(0.075) Nutritional-composition 1.456(0.968) 0.56 .572 .396 5.357 0.0171(0.030) Experience 0.486(0.136) -2.58 .01 .281 .84 -0.0321(0.01) *** Value-addition 4.374(4.048) 1.59 .111 .713 26.83 0.0658(0.043) Constant 0.000(0.002) -2.77 .006 0 .112 Mean dependent var 0.473 SD dependent var 0.500 Pseudo r-squared 0.785 Number of obs 222 Wald Chi-square (12) 42.566 Prob > chi2 0.000 Akaike crit. (AIC) 92.017 Bayesian crit. (BIC) 136.253 Notes: ¹Farm size using the compost fertilizer/BSF frass; Significance level: *p < 0.1; **p < 0.05; ***p < 0.01, robust standard errors (parenthesis) 3.2 Cost-effectiveness of using BSF in recycling organic waste into fertilizer The initial capital investment for BSF is, on average,31-fold ( $ 232.4) higher than conventional composting ( $ 7.6) (Table 4 ), spread evenly across a period of 10 years. The contribution of the various cost components to the total investment cost is illustrated in (Fig. 2 (a & b)). There is a variation in the cost components between the two methods, which is driven by the variation in the production process. Labour costs constitute the largest proportion of the variable cost in both methods, with 53.28% for BSF and 54.14% for conventional composting (Fig. 2 (c & d)), revealing the labour-intensive nature of recycling organic waste. Fig. 2 : Estimated contribution of various cost components to initial capital investment (fixed costs) and variable costs for recycling organic waste into fertilizer using BSF (a & c) and conventional composting (b & d). On average households using BSF recycle 3.4-fold higher (38.5 tonnes) volume of organic waste annually than households using conventional composting (11.5 tonnes). Recycling 1 MT of organic waste with BSF yielded a substantially 36-fold higher average profit ( $ 417.82) and 3-fold higher gross margin (55.4%) than using conventional composting which yielded an average profit of $ 11.25 and gross margin of 16.6% (Table 2 ) without accounting for the market value of family labour. In a scenario where we account for family labour as an opportunity cost of time, income reduced by 21% and 80% among households using BSF and conventional composting respectively revealing the high contribution of family labour especially among households using conventional composting. The main benefit of adopting BSF technology for organic waste management is its rapid conversion rate, typically within 2–5 weeks, which translates to high-profit margins. Farmers recycling organic waste using BSF larvae produced, on average, 7–8 cycles, while those using conventional composting produced 2–3 cycles annually. The market price of frass was, on average, $ 0.26 per kg and increased slightly to $ 0.29 per kg upon value addition, contrasted with compost, whose average market price was $ 0.08 per kg and increased to $ 0.15 per kg with value addition. Value addition to the recycled fertilizer increased average profit by 0.5-folds and 8-folds among households using BSF and conventional composting respectively. Table 2 Estimated annual profit from recycling 1 MT of organic waste into fertilizer per production cycle Quantity (kgs) Sale price ( $ ) Annual revenue ( $ ) Annual cost ( $ ) Annual profit ( $ ) Gross margin BSF frass 2930.67 0.26 771.97 BSF dried larvae 390.5 1.03 402.52 756.67 417.81 55.36% Compost 1385 0.08 113.42 102.16 11.25 16.63% If family labour was valued at labour market price Frass 345.89 Compost -9.01 Value addition (packaging, treatment, amendment) Frass 606.76 Compost 110.21 If compost was sold at the same market price as frass 364.86 Production cycles BSF 7–8 cycles Conventional 2–3 cycles Note: $1 = KES 135.82 [ 47 ] Using BSF larvae in recycling organic waste into fertilizer realized on average, 38-folds higher net present value ( $ 2128.36) than conventional composting ( $ 55.97) (Table 3 ). Recycling organic waste using BSF and conventional composting had an internal rate of return greater than the discount rate, indicating that both practices are profitable. The return on investment for BSF was 5-folds higher that of conventional composting. Table 3 Cost-benefit analysis indicators for recycling organic waste into fertilizer using BSF-assisted and conventional composting Decision indicators BSF-assisted composting Conventional composting Net present value (10 yrs) $ 2128.36 $ 55.97 Internal rate of return 150% 121% Benefit-cost ratio 1.47 1.10 Return on investment 47.22% 9.57% Table 4 Descriptive summary statistics for variables used in logistic regression Variable Variable description Mean Statistical difference BSF-assisted composting (n = 105) Conventional composting (n = 117) Age Age of household head in years 43.94 56.19 t = 8.16*** Hhsize Size of household members 4.92 4.21 t=-3.33*** Education Number of years spent by household head in schooling 16.30 11.25 t=-11.05*** Farm size Size of land used for fertilizer/BSF production in square paces 27.05 42.37 t = 8.84*** Groupmem Number of groups a household head belongs to that promote recycling of organic waste 2.35 1.43 t=-8.12*** Accessinfo Household access to environmental/agricultural information (number of times) 2.54 0.94 t=-9.46*** Experience Number of years the household has been efficiently recycling organic waste 2.10 5.07 t = 11.38*** Segregation Household access to or practice of segregating waste at source (1 = yes, 0 = No) 0.55 0.19 χ 2 = 31.01*** Product Household perception of recycling waste into diverse products (1 = positive, 0 = negative) 0.92 0.56 χ 2 = 36.29*** Profitability Household perception of profitability of recycling waste (1 = positive, 0 = negative) 0.91 0.53 χ 2 = 38.21*** Nutritional composition Household perception of high nutritional comp organic fertilizer (1 = positive, 0 = negative) 0.77 0.52 χ 2 = 14.39*** Value-add Value addition/ amendment to the recycled organic fertilizer (1 = Yes, 0 = No) 0.30 0.11 χ 2 = 12.84 Capital-req Initial capital requirement for recycling ( $ ) $ 232.4 $ 7.6 Significance level: ***p < 0.01 3.3 Sensitivity analysis In BSF larvae-based organic waste recycling, varying factors such as production cycle, frass quantity, sale price, labour cost and investment cost by +/- 10% impacted the NPV by more than 10% (Fig. 3 ). Production cycle was the most influential, followed by frass quantity and sale price, with moderate sensitivity observed for dried larvae quantity, dried larvae sale price, labour cost, and investment cost. NPV showed the least sensitivity to lifecycle, discount rate, and waste acquisition cost. Assessing the variable impact aids in identifying critical factors for NPV robustness. Varying the variables to establish their effect on the NPV helps determine the critical factors that are crucial in determining the robustness of the NPV. Discussion 4.1 Determinants of choice of adopting BSF technology for recycling organic waste into fertilizer The results above reveal that household characteristics, institutional factors, and perceived benefits significantly influence household choice to adopt BSF technology for recycling organic waste. The age of the household head was a significant negative predictor. The marginal effects (Table 1 ) indicate that as the age of the household head increases by one year, the probability of adopting BSF for recycling organic waste into fertilizer decreases. This implies that households reduce their likelihood of adopting technologies as the head ages. The plausible reason for this outcome is the high labour requirement for sourcing and pre-treating the waste before recycling using BSF larvae. Since older farmers have less energy than younger ones, they would likely adopt a recycling approach that does not require much effort and time. Our findings are consistent with Mwangi and Kariuki [ 49 ] and Zondo [ 50 ] highlighting that old farmers are risk-averse compared to their younger counterparts. Household size was a significant positive predictor. The marginal effect indicates that, an increase in household size by one member, increases the household’s probability of adopting BSF. This implies that farmers with larger families are more likely to adopt BSF. Labour is an important input in recycling organic waste. Larger families translate to more labour available for transforming the waste into fertilizer [ 50 ]. The findings were consistent with [ 51 , 52 ] which stated that larger family-sized households were likely to adopt agricultural technologies requiring more labour force. The number of years spent in schooling demonstrated a statistically significant positive association. The marginal effect (Table 1 ) suggests that an additional year of schooling increases the household probability of selecting BSF. Farmers with higher levels of formal education are more cognizant of new technologies within relatively short durations [ 53 ]. The findings were consistent with Sennuga et al. [ 54 ] indicating that there is an essential link between education levels and making informed choices. This is because education empowers the farmers to interpret, perceive, and respond to new technologies and practices and justifies their efficient production performance. Hence farmers with higher education are more likely to embrace BSF technology for recycling organic waste. The size of land used for recycling organic waste into fertilizer (production unit) demonstrated a statistically significant negative association. The marginal effect indicates that an increase in the size of land required for recycling organic waste by a square pace ( \(\:\frac{1}{43560}\) th acre) reduces a household's probability of adopting BSF. This implies that the less land requirement for recycling increases the likelihood of using new technologies like BSF. This is because land is a scarce resource, especially among the urban poor and those working in informal sectors. These results are consistent with Hanboonsong et al. [ 55 ] and Kibaara et al. [ 56 ] which reported that insect-based technologies for managing organic waste are efficient in space. The number of social associations/groups a household head belonged to was a significant positive predictor. The associated marginal effect (Table 1 ) suggests that an increase in the number of social associations/ groups the household head belonged to, increases a household's probability of adopting BSF. This reveals that belonging to a social group fosters social networking and knowledge exchange about the advantages of new technologies [ 57 ]. The findings complement Sseguya et al. [ 58 ], who observed that belonging to a group fosters farmer peer learning and consolidation of inputs through community banking models, thus encouraging the adoption of technologies. Access to agricultural/environmental extension information on recycling organic waste was a significant positive predictor. The corresponding marginal effect indicates that households that accessed extension information had an increased probability of adopting BSF. These results reveal that access to extension information increases awareness and the probability of adopting BSF technology for organic waste management. Our findings were similar to [ 50 ] which reported that extension agents are essential service providers who empower farmers on the relevant agricultural and environmental technologies that will enhance their productivity and profit margins. This emphasizes the importance of extension information in disseminating and promoting agricultural technologies and innovations. Respondents’ perception of recycling organic waste into diverse products was a significant positive predictor. The marginal effect indicates that respondents who perceived recycling of organic waste as a potential diversification process for soil amendment, animal protein source, and bio-energy were probably more likely to choose BSF than those who did not perceive recycling to have potential diversified products. The results indicate that perception is a vital factor affecting the adoption of insect-based technologies. These findings were consistent with Liu et al. [ 28 ] and Salam et al. [ 59 ], which stated that household perception of the use of BSF technology to convert organic waste into diverse, economically viable improved adoptability. 4.2 Economic efficiency of using BSF larvae in recycling organic waste into fertilizer The cost-benefit analysis indicators and sensitivity analysis results reveal that using BSF in recycling organic waste into fertilizer is economically efficient compared to conventional composting. The high NPV is attributed to the reduced time for recycling organic waste using BSF and the high selling price per kg of frass. It reveals the high potential of BSF as an emerging and profitable livelihood opportunity for households living in peri-urban areas where organic waste is abundant. These results are consistent with a study by Munthali et al. [ 38 ] and Groeneveld et al. [ 60 ] which found that that BSF farming was economically viable as an alternative animal feed ingredient. A study by Beesigamukama et al. [ 16 ] on the economic value of frass found that investing in frass fertilizer production among farmers rearing insects increased their income significantly. Moreover, value addition increases frass marketability and value, resulting in higher profit margins. The multiple recycling cycles (7–8 times annually) and higher volumes of organic waste recycled (7.5 MT annually) reveal that households recycling organic waste using BSF recycled more waste compared to those using conventional composting. To a large extent, these findings unveil the potential of BSF technology in managing organic waste. Moreover, food and market waste, which constitutes a large proportion of organic waste illegally disposed of [ 61 ], was the primary type of waste recycled using BSF, further emphasizing the role of BSF in promoting bio-circular economies, especially in urban and peri-urban areas. Additionally, BSF labour cost per man-day was higher compared to conventional composting implying that BSF offers job opportunities for unskilled and semi-skilled labour. On the other hand, labour accounts for a large proportion of operating costs [ 34 ], and this calls for investing in local solutions that reduce labour requirements, such as waste segregation at source, to increase the gross margins accrued from recycling waste. The difference in IRR between the two recycling methods is attributed to the variations in cash flow and initial capital requirement. BCR attempts to summarize the overall monetary value of an investment. The higher BCR for using BSF implies that the overall monetary benefits of recycling organic waste into frass are higher compared to conventional composting. The ROI indicates that BSF’s profitability was 5-fold higher than that of conventional composting. This work provides the first discussion on the cost-effectiveness of recycling organic waste using BSF larvae compared to conventional composting. The CBA indicators reveal that recycling organic waste into fertilizer is cost-effective. In addition, it can provide a secondary source of income for farmers and cushion them against high fertilizer prices while promoting regenerative agriculture. 4.3 Externalities associated with recycling organic waste into fertilizer Recycling organic waste generates non-monetary positive/negative externalities, which is critical for determining the economic efficiency of recycling organic waste. These externalities include the effect on soil health, crop yield, GHG emissions, and social impact (evaluated as labour requirement and job creation). Frass influences bacterial growth and soil enzymes resulting in a significant impact in soil health and fertility [ 62 ]. BSF-composted fertilizer could be categorized as an NPK compound fertilizer with an average composition of 3.4% N, 2.9% P2O5, and ,3.5% K2O, and C/N ratio of 13–16 [ 15 , 26 , 63 ]. Additionally, frass is a suitable soil amendment that influences soil fungal/bacterial composition, and rapidly releases nitrogen needed for plant absorption [ 64 ]. This implies that frass is a potentially efficient substitute for promoting soil health. The effect of frass on plant growth and health vary depending on the crop varieties and frass type [ 35 ]. This is because the nutritional composition of frass is greatly determined by the feed substrate (organic waste) used [ 65 ]. Germination indexes improved when frass fertilizer was used compared to conventional compost because frass is a more stable organic fertilizer [ 12 , 18 ]. Moreover, the rich nutrients and organic matter in frass fertilizer reduce the need to use chemicals for plant disease protection [ 66 ] and crops produce higher yield compared to compost from conventional composting [ 16 , 67 ]. These findings imply that frass could, therefore, be a partial or complete substitute to highly priced inorganic fertilizer while promoting efficient organic waste management [ 68 ]. Recycling organic waste using BSF larvae reduces global warming potential by 50% compared to conventional composting, thus, BSF technology is environmentally friendly and conserves environmental resources [ 69 ]. Additionally, recycling organic waste using BSF larvae reduces odour and GHGs (CH 4 , NH 3 , and N 2 O) associated with bioconversion of organic waste [ 70 , 71 ]. Moreover, the short waste recycling duration associated with BSF larvae reduces the emissions of N 2 O compared to conventional composting, whose recycling takes longer [ 72 ]. The total ammonia emitted from BSF composting was 0.12 to 10% that of conventional composting, implying that less overall Nitrogen is lost during BSF composting [ 73 ]. These results reveal that recycling organic waste using BSF has lower environmental footprint compared to conventional composting and therefore more environmentally efficient. Using BSF in recycling organic waste promotes social interaction through learning from one another and creates employment through the demand for extra labour. Social interaction attracts the technical know-how required for adopting and implementing new technologies. Adopting these technologies creates job opportunities, culminating into social impact [ 74 , 75 ]. Although the additional labour cost signifies a welfare loss to the farmer, the employment created for the society signifies a welfare/economic gain to the society. Conclusion and policy recommendations This study discusses the factors influencing adoption of BSF and its cost-effectiveness in recycling organic waste into fertilizer. We show that BSF has huge potential in recycling organic waste, especially in urban and peri-urban areas, because of the diverse nature of organic waste recycled and the multiple possible production cycles. For every tonne of waste recycled, BSF was profitable and cost-effective, with 5-fold higher return on investment than conventional composting. Moreover, the use of BSF in recycling organic waste has lower GHG emissions, while the frass fertilizer promotes regeneration of soil health, which increases crop yield. It is important to emphasize the economic potential of using BSF in recycling organic waste in circular and green economy advocacy. Increasing the uptake of BSF in recycling organic waste into fertilizer will require awareness campaigns and capacity-building programs among households, governments, civil societies, and private sector actors in the waste management and fertilizer industry. These results should inform further BSF feasibility studies, efficient waste management programs, and livelihood diversification efforts in waste-abundant areas. Although our study was conducted in Kiambu County, Kenya, the use of BSF in recycling organic waste is being advanced globally. The methodology used in this study can be easily replicated in other regions and contexts. This study used cross-sectional data and was limited to the financial benefits of using BSF in recycling organic waste into frass fertilizer compared to conventional compost. Future research should consider longitudinal data and a more comprehensive assessment of the environmental and social benefits of using BSF in recycling organic waste. Declarations Authors contribution Perpetual G. Mugendi: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Visualization, Validation, Writing – original draft, Revising the draft. Beatrice W. Muriithi: Conceptualization, Investigation, Methodology, Project administration, Software, Supervision, Visualization, Validation, Writing – review & editing. Raphael Gitau: Conceptualization, Investigation, Methodology, Supervision, Visualization, Validation, writing – review & editing. Dennis Beesigamukama: Project administration, Supervision, Validation, writing – review & editing. Shaphan Y. Chia: Project administration, Supervision, Validation, writing – review & editing. Teresia G. Wamwondwe: Methodology, Validation, writing – review & editing. Kassie Menale: Project administration, Supervision, Validation, writing – review & editing. Chrysantus M. Tanga: Conceptualization, Investigation, Methodology, Project administration, Visualization, Validation, writing – review & editing. Funding The authors gratefully acknowledge the financial support for this research by the following organizations and agencies: Australian Centre for International Agricultural Research (ACIAR) (ProteinAfrica –Grant No: LS/2020/154), Novo Nordisk Foundation (RefIPro: NNF22SA0078466), the Rockefeller Foundation (WAVE-IN—Grant No: 2021 FOD 030); Bill & Melinda Gates Foundation (INV-032416); IKEA Foundation (G-2204-02144), Horizon Europe (NESTLER - Project: 101060762 - HORIZON-CL6-2021-FARM2FORK-01), the Curt Bergfors Foundation Food Planet Prize Award; Norwegian Agency for Development Cooperation, the Section for Research, Innovation, and Higher Education grant number RAF–3058 KEN–18/0005 (CAP–Africa). We also gratefully acknowledge the support of Egerton University and icipe core funding provided by the Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC); the Australian Centre for International Agricultural Research (ACIAR); the Norwegian Agency for Development Cooperation (Norad); the Federal Democratic Republic of Ethiopia; and the Government of the Republic of Kenya. The first author, Perpetual G. Mugendi, was financially supported by Louis Dreyfus Foundation (LDF) through a postgraduate scholarship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed herein do not necessarily reflect the official opinion of the donors. Data availability Data presented in this manuscript is available upon request from the corresponding author Ethics declarations Ethics approval and consent to participate This study was approved by Egerton University Ethic Review Committee (EUREC) and was in accordance with the university guidelines and requirements for research. All the research processes, such as data collection using a household survey, were done in accordance with the ethical committee's standards and procedures. Consent to Participate declaration Informed consent was obtained from all subjects and/or their legal guardian(s). Consent to Publish Declaration: Not applicable. Competing interest The authors affirm that they have no known financial or interpersonal conflicts that would have appeared to impact the research presented in this study. Clinical trial number Not applicable References Kaza S, Yao LC, Bhada-Tata P, Van Woerden F. What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050 [Internet]. 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Mugendi","email":"","orcid":"","institution":"Egerton University","correspondingAuthor":false,"prefix":"","firstName":"Perpetual","middleName":"G.","lastName":"Mugendi","suffix":""},{"id":448896978,"identity":"07bae11c-08b2-413a-9d1b-8359c6e6953f","order_by":1,"name":"Beatrice W. Muriithi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACAxCRYMCQwMbe2MCQQIIWgwQ2noOkaAFSCQwSRKkHAnOxM2YfHhT8yeOTfNz44eEOGwZ+6eMX8GqxnJ1jPAPosGI26cRmicQzaQySfTkF+B12O8cY5JfENunENobEtsMMBmd48DsRoUXyIEjLf1K0SDCCtBwAamE/QMAvacVALcaJbTxgvyTzSPbw4NXBYC6dvJnxxx+5xPntxx9+/LnDTo6fh/0Bfj0ogLGBAWgFjwFpWoCAJFtGwSgYBaNgBAAAbq1DiveNta8AAAAASUVORK5CYII=","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":true,"prefix":"","firstName":"Beatrice","middleName":"W.","lastName":"Muriithi","suffix":""},{"id":448896979,"identity":"c048d918-3030-41d8-896c-032410febad8","order_by":2,"name":"Raphael Gitau","email":"","orcid":"","institution":"Egerton University","correspondingAuthor":false,"prefix":"","firstName":"Raphael","middleName":"","lastName":"Gitau","suffix":""},{"id":448896980,"identity":"cc1ed78f-c131-45d2-9e89-0190b2012a7d","order_by":3,"name":"Dennis Beesigamukama","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Dennis","middleName":"","lastName":"Beesigamukama","suffix":""},{"id":448896981,"identity":"e841e8ba-1484-4d45-8e39-35a91cc62dfa","order_by":4,"name":"Shaphan Y. Chia","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Shaphan","middleName":"Y.","lastName":"Chia","suffix":""},{"id":448896982,"identity":"b4179d5a-85fa-4535-a3ee-29c6f0e757b9","order_by":5,"name":"Teresia G. Wamwondwe","email":"","orcid":"","institution":"Egerton University","correspondingAuthor":false,"prefix":"","firstName":"Teresia","middleName":"G.","lastName":"Wamwondwe","suffix":""},{"id":448896983,"identity":"ee7ce8e7-deec-4292-8cc0-88c10a0a9c88","order_by":6,"name":"Kassie Menale","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Kassie","middleName":"","lastName":"Menale","suffix":""},{"id":448896984,"identity":"511e8a0e-0621-49a2-879f-2b6ad79385f9","order_by":7,"name":"Chrysantus M. Tanga","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Chrysantus","middleName":"M.","lastName":"Tanga","suffix":""}],"badges":[],"createdAt":"2025-03-19 20:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6264404/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6264404/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82137370,"identity":"8f2dc38d-bc4c-493b-a909-dac7e589cfd5","added_by":"auto","created_at":"2025-05-07 06:17:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87386,"visible":true,"origin":"","legend":"\u003cp\u003eMap of households recycling organic waste into fertilizer using BSF and conventional composting in Kiambu, Kenya\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6264404/v1/0aac735a68ea138dc8e82755.jpg"},{"id":82137369,"identity":"5e8e4c70-386a-4e5d-af98-302544c91bc8","added_by":"auto","created_at":"2025-05-07 06:17:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75567,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated contribution of various cost components to initial capital investment (fixed costs) and variable costs for recycling organic waste into fertilizer using BSF (a \u0026amp; c) and conventional composting (b \u0026amp; d).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6264404/v1/10ad4fae3d7c0824ace81ca3.jpg"},{"id":82141147,"identity":"db8212c5-b18d-4ff6-9bd3-6c3bbe492355","added_by":"auto","created_at":"2025-05-07 06:33:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52772,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity analysis on variations of variables on net present value\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6264404/v1/63fb958df73aa2b74bcf7e78.jpg"},{"id":82143553,"identity":"dfd5b87f-3b0a-4237-9f3a-c6964395d066","added_by":"auto","created_at":"2025-05-07 06:41:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1497880,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6264404/v1/762ebfe9-084f-469d-b5f7-3b57c1e770ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Economic Efficiency and Adoption Determinants of Insect-Based Technologies for Organic Waste Recycling into Fertilizer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGlobally, over two billion tonnes of organic waste are generated annually in urban and peri-urban areas, with only 16% of this waste being recycled [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Kenya,70\u0026ndash;80% of waste generated daily is mainly organic [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Yet only 10% of the total organic waste is properly disposed off in designated dumpsites and recycling facilities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The illegally disposed organic waste (90%) results in economic losses, public health hazards, and environmental degradation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Additional threats include unpleasant odors, explosions of greenhouse gases including methane and carbon dioxide, breeding sites for disease-causing organisms, and disruption of biogeochemical cycles 5\u0026ndash;7]. Therefore, there is an urgent need for local solutions and technologies that efficiently bio-convert organic waste into valuable products while promoting environmental restoration [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEfficient bioconversion of organic waste in closed-loop economies is a multifaceted problem that is caused by inefficient recycling and composting technologies, inappropriate collection and disposal infrastructure, and weak enforcement of laws and regulations that pave the way for illegal littering and dumping [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Moreover, there is a lack of public awareness on the potential economic benefits of efficient and cost-effective waste management practices [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Conventionally organic waste is managed through composting to produce bio-fertilizers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the conventional composting methods are slow and, if not controlled, they induce negative effects such as directly contributing to the contamination of surface and drinking water, transmission of zoonotic diseases, and emission of methane, carbon dioxide, and offensive smells [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, there is a need for efficient, sustainable, and circular based bioeconomy interventions for managing organic waste, which can be achieved through insect-based technologies.\u003c/p\u003e \u003cp\u003eThe use of insect-based technologies such as black soldier fly (\u003cem\u003eHermetia illucens\u003c/em\u003e, BSF) to recycle organic waste into larval biomass for feed and nutrient-rich organic fertilizer with minimal environmental footprint has gained global attention [\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. BSF larvae feed on a range of organic wastes including food waste (food scraps and any inedible portions of food), livestock waste (manure), and market waste (vegetable and fruit refuse) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].The larvae have high affinity for organic waste and promote closed loop organic waste management through reducing volumes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] pathogen concentrations [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], greenhouse gas emissions [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and heavy metal concentrations [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe byproduct of this waste bioconversion process called \u0026ldquo;frass\u0026rdquo; consists of mixture of uneaten substrates, insect feces, insect shed exoskeleton, and dead insects. Frass has excellent fertilizing properties due to its rich organic matter, macro and micro-nutrients, and trace elements [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Recent studies have demonstrated frass\u0026rsquo; potential to improve soil health [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], boost plant growth and yield [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] suppressing disease and pests [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], increasing farmers profits and reducing environmental burden of global warming and use of synthetic fertilizers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, some studies found that the application of BSF can inhibit plant growth due to the phytotoxicity of fresh frass and recommended further post processing to produce stable frass fertilizer [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Frass fertilizer is potentially a promising fertilizer, however further multidisciplinary research is required to fully evaluate its potential [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the steady increase in literature promoting circular bio-economies and sustainable agricultural production through the use of BSF in recycling organic waste into frass, information on the economic aspects of its production is limited [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Existing studies have identified the nutritional composition of frass from different waste sources [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], socio-economic benefits of insect-based feed in poultry production [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], economic value of using frass in maize production BSF as an organic waste recycler [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and cost benefits of BSF as an alternative fish ingredient [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. All these studies show the potential benefits of adopting BSF in bio-converting waste into animal feed or frass fertilizer. However, there is limited research on the economic efficiency of producing frass compared to conventional composting among households, which is relevant when exploring the adoption and scalability of frass production.\u003c/p\u003e \u003cp\u003eThis paper addresses this knowledge gap by identifying the determinants of adopting BSF in recycling organic waste and estimating the cost-effectiveness of recycling organic waste into organic fertilizer using BSF larvae compared to conventional composting. We further discuss the externalities (immaterial benefits) associated with recycling organic waste into fertilizer among households based on existing literature. The study provides information on the economic benefits of using BSF in recycling organic waste compared to conventional composting thereby supporting the development of this novel frass fertilizer.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eThe study was conducted in Kiambu County, Kenya (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The county was purposively selected based on previous promotion efforts on recycling of organic waste conducted by \u003cem\u003eicipe\u003c/em\u003e and the government in the area.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection and sampling procedure\u003c/h2\u003e \u003cp\u003eThe study utilized both primary and secondary data. The primary data was collected through a household-level survey using a semi-structured questionnaire with approval from the Egerton University Ethics and Review Committee (EUREC). The data entailed sociodemographic characteristics such as (age, years of schooling, gender, size of household, size of land for recycling, perceptions), institutional factors (such as distance to the source of waste, distance to the main market outlet, group membership, access to credit, access to extension services). Other variables included waste streams and types (such as livestock waste, market waste, farmyard waste, and kitchen waste), production requirements (such as start-up capital, operational and maintenance costs), and marketing (such as market price and main market outlets). A pretest was conducted to test the validity of the questionnaire. The secondary data were collected from reviews of relevant published and grey literature from research institutions and government agencies.\u003c/p\u003e \u003cp\u003eThe study employed a multistage sampling technique. In the first stage, Kiambu County was purposively selected as detailed in the previous section. In the second stage, two-wards from each of the 12 sub-counties in Kiambu County, where the majority of organic fertilizer producers resided, were purposively selected. Using a list of households recycling organic waste into fertilizer provided by \u003cem\u003eicipe\u003c/em\u003e, and the County Department of Agriculture, Livestock, and Fisheries, a sample of the survey respondents was then randomly selected at the third stage. Proportion probability to size technique was used to determine the sample size to be randomly selected for each of the wards.\u003c/p\u003e \u003cp\u003eThe sample size was calculated at a confidence level of 95% and 0.05 precision, as [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] suggested when the population is known.\u003c/p\u003e \u003cp\u003e \u003cem\u003en\u003c/em\u003e = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{N}{1+N\\left({e}^{2}\\right)}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003en \u003cem\u003e=\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{500}{1+500\\left({0.05}^{2}\\right)}\\)\u003c/span\u003e\u003c/span\u003e \u003cem\u003e=\u003c/em\u003e 222 (1)\u003c/p\u003e \u003cp\u003ewhere n is the sample size, N is the target population, and \u003cem\u003ee\u003c/em\u003e is the acceptable margin of error. The sample of 222 comprised 105 households using BSF and the remaining 117 were households using conventional (windrow) z composting to recycle organic waste into fertilizer. This sample size was representative of households recycling organic waste into fertilizer and the methodology can be replicated in other regions or countries. Moreover, the sample was derived from a heterogeneous population with no significant demographic and socio-economic characteristics that could affect the results. The EXCEL tool and STATA software were used to conduct descriptive analysis and econometric models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Model specification\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Logistic regression model\u003c/h2\u003e \u003cp\u003eThe study adopted a logistic regression model to determine the factors influencing the choice of BSF for recycling organic waste into fertilizer. These factors include household characteristics, institutional factors, and perceived benefits [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The logistic model was preferred to Ordinary Least Square and Probit because it corrects the linearity problem by transforming the dependent variable into logs, allowing for modelling nonlinear dependence linearity and easier interpretation [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The functional form of a binary logistic regression model is specified as illustrated in Eq.\u0026nbsp;(2)\u003c/p\u003e \u003cp\u003e \u003cem\u003eP\u003c/em\u003e = (\u003cem\u003eY\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{e}^{\\varvec{\\beta\\:}\\varvec{X}i}}{1\\:+\\:{e}^{\\varvec{\\beta\\:}\\varvec{X}i}}\\)\u003c/span\u003e\u003c/span\u003e (2)\u003c/p\u003e \u003cp\u003ewith a cumulative distribution function as illustrated in Eq.\u0026nbsp;(3)\u003c/p\u003e \u003cp\u003e \u003cem\u003eF\u003c/em\u003e (\u003cem\u003eβX\u003c/em\u003e) =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{1}{1\\:+\\:{e}^{\\beta\\:Xi}}\\)\u003c/span\u003e\u003c/span\u003e (3)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eY\u003c/em\u003e\u0026thinsp;=\u0026thinsp;choice of an approach for recycling organic waste (specified as \u003cem\u003e1\u003c/em\u003e if a household adopts BSF and 0 conventional composting), \u003cem\u003eXi\u003c/em\u003e is a vector of the explanatory variables, and \u003cem\u003eβ\u003c/em\u003e is a vector of the parameters to be estimated. Eq.\u0026nbsp;(2) can also be written as illustrated in Eq.\u0026nbsp;(4)\u003c/p\u003e \u003cp\u003e \u003cem\u003ePi =\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{1}{1\\:+\\:{e}^{-\\varvec{Z}\\varvec{i}}}\\)\u003c/span\u003e\u003c/span\u003e (4)\u003c/p\u003e \u003cp\u003eThe probability that a producer household chooses to adopt BSF for recycling organic waste is illustrated in Eq.\u0026nbsp;(4) and can be illustrated as follows in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\frac{Pi}{1\\:-\\:\\:Pi\\:}\\:=\\:\\frac{1\\:+\\:{e}^{\\varvec{Z}\\varvec{i}}}{1\\:+\\:{e}^{-\\varvec{Z}\\varvec{i}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Pi}{1\\:-\\:\\:Pi\\:}\\)\u003c/span\u003e\u003c/span\u003e is the odds ratio in favour of a household choice of adopting BSF. Therefore, taking the natural logarithms of Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e5\u003c/span\u003e) will be expressed as illustrated in Eq.\u0026nbsp;(6)\u003c/p\u003e \u003cp\u003e \u003cem\u003eL\u003c/em\u003e \u003csub\u003e \u003cem\u003ei\u003c/em\u003e \u003c/sub\u003e \u003cem\u003e= ln\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left[\\frac{Pi}{1\\:-\\:\\:Pi\\:}\\right]\\)\u003c/span\u003e\u003c/span\u003e \u003cem\u003e= Z\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;β\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;β\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e \u003cem\u003e+ ⋯ + β\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e\u003cem\u003eX\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eε\u003c/em\u003e (6)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ePi\u003c/em\u003e is the probability of a producer household adopting BSF for organic waste recycling, which ranges between \u003cem\u003e1\u003c/em\u003e and \u003cem\u003e0\u003c/em\u003e, and \u003cem\u003eZi\u003c/em\u003e is a function of \u003cem\u003en\u003c/em\u003e explanatory variables \u003cem\u003eXi.\u003c/em\u003e The probability that a household adopts BSF in recycling organic waste is denoted by 1 and 0 if a household adopts conventional (windrow) composting. \u003cem\u003eβ\u003c/em\u003e\u003csub\u003e0\u003c/sub\u003e is the intercept, \u003cem\u003eβ\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e ... \u003cem\u003eβ\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e are coefficients of the model and \u003cem\u003eε\u003c/em\u003e is the error term. The variables are illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e as continuous and categorical variables. Qualitative data was collected using a 5-point Likert scale and transformed to binary variables during analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Cost Benefit Analysis (CBA) methodology\u003c/h2\u003e \u003cp\u003eThis study adopted an allocative efficiency perspective and concepts of cost benefit analysis theory to evaluate the cost-effectiveness of using BSF compared to conventional composting. Cost-benefit analysis (CBA) indicators were used in estimating the cost-effectiveness of using BSF in recycling organic waste into fertilizer compared to conventional composting. This study adopted the approach used by Mogaka et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and employed four decision indicators: net present value (NPV), internal rate of return (IRR), return on investment (ROI), benefit-cost ratio, and sensitivity analysis to test for robustness of the NPV\u003c/p\u003e \u003cp\u003eThe NPV is the present value of discounted future net benefits, that is discounted financial benefits minus financial costs, with discounting accounting for inflation and risk aversion. A recycling method is deemed viable when NPV\u0026thinsp;\u0026gt;\u0026thinsp;0 and rejected if otherwise, and it is expressed as follows;\u003c/p\u003e \u003cp\u003e \u003cem\u003eNPV (B, C) =\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sum\\:}_{t=0}^{T}\\frac{Bt}{{(1+r)}^{t}}-\\:{\\sum\\:}_{t=0}^{T}\\frac{Ct}{{\\left(1+r\\right)}^{t}}\\:\\)\u003c/span\u003e\u003c/span\u003e (7)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003et\u003c/em\u003e is the lifecycle, \u003cem\u003eB\u003c/em\u003e is the stream of benefits, \u003cem\u003eC\u003c/em\u003e represents the costs, and \u003cem\u003er\u003c/em\u003e is the discount rate (12%, which is the opportunity cost of capital (Central Bank of Kenya lending rate (average of reference period 2022\u0026ndash;2023))\u003c/p\u003e \u003cp\u003eThe IRR calculates the discount rate at which the NPV has a zero-value (Eq.\u0026nbsp;(8)) and compares it with the predetermined discount rate (\u003cem\u003er\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e(\u003cem\u003eB\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Bt}{{(1+i)}^{t}})\\)\u003c/span\u003e\u003c/span\u003e \u0026ndash; (\u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e + \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{Ct}{{(1+i)}^{t}})=0\\)\u003c/span\u003e\u003c/span\u003e (8)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ei\u003c/em\u003e is the discount rate\u003c/p\u003e \u003cp\u003eThe benefit-cost ratio is illustrated in Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\frac{B}{C}=\\:\\frac{{\\sum\\:}_{t=0}^{T}\\frac{Bt}{{(1+r)}^{t}}}{{\\sum\\:}_{t=0}^{T}\\frac{Ct}{{(1+r)}^{t}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eB\u003c/em\u003e represents the benefits, \u003cem\u003eC\u003c/em\u003e represents the costs, \u003cem\u003er\u003c/em\u003e represents the discount rate, and \u003cem\u003et\u003c/em\u003e represents the time in years.\u003c/p\u003e \u003cp\u003eThe Return on Investment measures the gains/loss accrued from an investment, that is the recycling method, relative to the money invested (Eq.\u0026nbsp;(10)).\u003c/p\u003e \u003cp\u003eReturn on investment (%) \u003cem\u003e=\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\frac{net\\:income}{total\\:variable\\:costs}\\)\u003c/span\u003e\u003c/span\u003e \u003cem\u003e\u0026times; 100\u003c/em\u003e (10)\u003c/p\u003e \u003cp\u003eWhen computing the decision indicators, the following assumptions were used.\u003c/p\u003e \u003cp\u003e \u003col style=\"list-style-type:lower-roman;\"\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCosts and revenues were expressed in US dollars, and all prices were estimated based on recall of the previous production cycle.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe prices of the fertilizer and dried larvae were inclusive of taxes\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe discount rate (12%) controlled for the inflation rate [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe lifecycle for recycling organic waste among households was arbitrarily selected to be 10 years\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe computation of the costs did not account for depreciation, interest on capital, sunk cost, and land value.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Sensitivity analysis\u003c/h2\u003e \u003cp\u003eSensitivity analysis identifies critical variables whose positive or negative variations significantly impact the recycling method\u0026rsquo;s NPV. In this study, the optimistic-pessimistic scenario was applied. It involved assigning optimistic (most favourable) and pessimistic (least favourable) values and computing the effect on NPV, ceteris paribus. Based on the assumptions of a perfect market, an arbitrary 10% change in the selected variables was used. Critical variables were variables in which a variation of +/- 10% of the value in the base case had a more than 10% variation on NPV [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4 Externalities\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCost-effectiveness of recycling organic waste into fertilizer using BSF larvae also involves the determination of immaterial benefits (externalities) such as the effect on soil health, crop yield, GHG emissions, and social impact from the adoption of BSF compared to conventional composting. The Systematic Literature Review methodology was applied in determining the externalities. In the first step, Web of Science and Google Scholar search engines were used to identify literature related to use of insects such as BSF in organic waste management. Duplicate fields were dropped in the second step followed by screening to filter the irrelevant records based on research title. Full articles were then assessed for eligibility and those not mentioning the externalities were excluded.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Determinants of adopting BSF in recycling organic waste into fertilizer\u003c/h2\u003e \u003cp\u003eThe sociodemographic and institutional characteristics were statistically and significantly different among households using BSF and conventional composting (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The age of heads of households using BSF was on average 44 years, with 16 years of formal schooling and 2 years of organic waste recycling experience. Their counterpart windrow composting household heads were on average 56 years old, with 11 years of schooling and 5 years of organic waste recycling experience. Both practices have been introduced in the recent past by the County Government and \u003cem\u003eicipe\u003c/em\u003e, respectively, with BSF being the latest. At farm level, 55% of households using BSF and 19% of households using conventional composting recycled segregated waste generated from their homesteads or had access to segregated waste.\u003c/p\u003e \u003cp\u003eThe logistic regression model demonstrated a good fit to the data (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The model's results demonstrated a good fit to the data as the predictors included in the model adequately explained the adoption of BSF in recycling organic waste (pseudo-R2 value of 0.796). Variables that significantly influenced the household choice of BSF technology in recycling organic waste into fertilizer included the age of the household head, number of years spent schooling, size of land explicitly used for recycling organic waste into fertilizer (production unit), number of social associations/ groups a household head belongs, access to agricultural/environmental extension information, and household perception of recycling organic waste into diverse products.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic Regression Model results for factors influencing the choice of BSF for recycling organic waste into fertilizer among surveyed households in Kiambu County.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003et-value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[95% Conf.\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInterval]\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMarginal effect (dy/dx)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.937(0.034)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0029(0.001) **\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold size\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.591(0.397)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.594\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0208(0.004) *\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.594(0.225)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.209\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.101\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0207(0.010) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarm size¹\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.929(0.030)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.023\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.872\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.99\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0033(0.001) *\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup-mem\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.032(0.627)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.022\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.721\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0316(0.014) **\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSegregation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.894(0.642)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.876\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.218\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.657\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0049(0.031)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccess-info\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.493(0.725)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0407(0.014) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProducts\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.696(20.421)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.004\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.581\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e150.292\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1422(0.040) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.432(4.810)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.379\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.515\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0578(0.075)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutritional-composition\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.456(0.968)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.572\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.396\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.357\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0171(0.030)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperience\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.486(0.136)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.281\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.84\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0321(0.01) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValue-addition\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.374(4.048)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.111\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.713\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0658(0.043)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000(0.002)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.77\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.112\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean dependent var\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eSD dependent var\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePseudo r-squared\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eNumber of obs\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWald Chi-square (12)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.566\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eProb \u0026gt; chi2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAkaike crit. (AIC)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.017\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eBayesian crit. (BIC)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e136.253\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNotes: ¹Farm size using the compost fertilizer/BSF frass; Significance level: *p \u0026lt; 0.1; **p \u0026lt; 0.05; ***p \u0026lt; 0.01, robust standard errors (parenthesis)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Cost-effectiveness of using BSF in recycling organic waste into fertilizer\u003c/h2\u003e \u003cp\u003e The initial capital investment for BSF is, on average,31-fold (\u003cspan\u003e$\u003c/span\u003e232.4) higher than conventional composting (\u003cspan\u003e$\u003c/span\u003e7.6) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4\u003c/span\u003e), spread evenly across a period of 10 years. The contribution of the various cost components to the total investment cost is illustrated in (Fig.\u0026nbsp;2 (a \u0026amp; b)). There is a variation in the cost components between the two methods, which is driven by the variation in the production process. Labour costs constitute the largest proportion of the variable cost in both methods, with 53.28% for BSF and 54.14% for conventional composting (Fig.\u0026nbsp;2 (c \u0026amp; d)), revealing the labour-intensive nature of recycling organic waste. \u003cb\u003eFig.\u0026nbsp;2\u003c/b\u003e: Estimated contribution of various cost components to initial capital investment (fixed costs) and variable costs for recycling organic waste into fertilizer using BSF (a \u0026amp; c) and conventional composting (b \u0026amp; d).\u003c/p\u003e\u003cp\u003eOn average households using BSF recycle 3.4-fold higher (38.5 tonnes) volume of organic waste annually than households using conventional composting (11.5 tonnes). Recycling 1 MT of organic waste with BSF yielded a substantially 36-fold higher average profit (\u003cspan\u003e$\u003c/span\u003e417.82) and 3-fold higher gross margin (55.4%) than using conventional composting which yielded an average profit of \u003cspan\u003e$\u003c/span\u003e11.25 and gross margin of 16.6% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e) without accounting for the market value of family labour. In a scenario where we account for family labour as an opportunity cost of time, income reduced by 21% and 80% among households using BSF and conventional composting respectively revealing the high contribution of family labour especially among households using conventional composting.\u003c/p\u003e \u003cp\u003eThe main benefit of adopting BSF technology for organic waste management is its rapid conversion rate, typically within 2–5 weeks, which translates to high-profit margins. Farmers recycling organic waste using BSF larvae produced, on average, 7–8 cycles, while those using conventional composting produced 2–3 cycles annually. The market price of frass was, on average, \u003cspan\u003e$\u003c/span\u003e0.26 per kg and increased slightly to \u003cspan\u003e$\u003c/span\u003e0.29 per kg upon value addition, contrasted with compost, whose average market price was \u003cspan\u003e$\u003c/span\u003e0.08 per kg and increased to \u003cspan\u003e$\u003c/span\u003e0.15 per kg with value addition. Value addition to the recycled fertilizer increased average profit by 0.5-folds and 8-folds among households using BSF and conventional composting respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimated annual profit from recycling 1 MT of organic waste into fertilizer per production cycle\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantity (kgs)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSale price (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnnual revenue (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnnual cost (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAnnual profit (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGross margin\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSF frass\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2930.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e771.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSF dried larvae\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e390.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e402.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e756.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e417.81\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.36%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1385\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113.42\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.63%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" morerows=\"1\" nameend=\"c4\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eIf family labour was valued at labour market price\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrass\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e345.89\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCompost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-9.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" morerows=\"1\" nameend=\"c4\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eValue addition (packaging, treatment, amendment)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrass\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e606.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCompost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eIf compost was sold at the same market price as frass\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e364.86\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eProduction cycles\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBSF\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7–8 cycles\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eConventional\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2–3 cycles\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: $1 = KES 135.82 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eUsing BSF larvae in recycling organic waste into fertilizer realized on average, 38-folds higher net present value (\u003cspan\u003e$\u003c/span\u003e2128.36) than conventional composting (\u003cspan\u003e$\u003c/span\u003e55.97) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Recycling organic waste using BSF and conventional composting had an internal rate of return greater than the discount rate, indicating that both practices are profitable. The return on investment for BSF was 5-folds higher that of conventional composting.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCost-benefit analysis indicators for recycling organic waste into fertilizer using BSF-assisted and conventional composting\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecision indicators\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBSF-assisted composting\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConventional composting\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNet present value (10 yrs)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e2128.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e55.97\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternal rate of return\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenefit-cost ratio\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReturn on investment\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.22%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.57%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive summary statistics for variables used in logistic regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistical difference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBSF-assisted composting\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;105)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConventional composting\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;117)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge of household head in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;8.16***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHhsize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSize of household members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-3.33***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of years spent by household head in schooling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-11.05***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarm size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSize of land used for fertilizer/BSF production in square paces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;8.84***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroupmem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of groups a household head belongs to that promote recycling of organic waste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-8.12***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessinfo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold access to environmental/agricultural information (number of times)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-9.46***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of years the household has been efficiently recycling organic waste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;11.38***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSegregation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold access to or practice of segregating waste at source (1\u0026thinsp;=\u0026thinsp;yes, 0\u0026thinsp;=\u0026thinsp;No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;31.01***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProduct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold perception of recycling waste into diverse products (1\u0026thinsp;=\u0026thinsp;positive, 0\u0026thinsp;=\u0026thinsp;negative)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;36.29***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfitability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold perception of profitability of recycling waste (1\u0026thinsp;=\u0026thinsp;positive, 0\u0026thinsp;=\u0026thinsp;negative)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;38.21***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutritional composition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold perception of high nutritional comp organic fertilizer (1\u0026thinsp;=\u0026thinsp;positive, 0\u0026thinsp;=\u0026thinsp;negative)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;14.39***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValue-add\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue addition/ amendment to the recycled organic fertilizer (1\u0026thinsp;=\u0026thinsp;Yes, 0\u0026thinsp;=\u0026thinsp;No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;12.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCapital-req\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial capital requirement for recycling (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e232.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSignificance level: ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sensitivity analysis\u003c/h2\u003e \u003cp\u003eIn BSF larvae-based organic waste recycling, varying factors such as production cycle, frass quantity, sale price, labour cost and investment cost by +/- 10% impacted the NPV by more than 10% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Production cycle was the most influential, followed by frass quantity and sale price, with moderate sensitivity observed for dried larvae quantity, dried larvae sale price, labour cost, and investment cost. NPV showed the least sensitivity to lifecycle, discount rate, and waste acquisition cost. Assessing the variable impact aids in identifying critical factors for NPV robustness. Varying the variables to establish their effect on the NPV helps determine the critical factors that are crucial in determining the robustness of the NPV.\u003c/p\u003e"},{"header":"Discussion","content":"\u003ch2\u003e4.1 Determinants of choice of adopting BSF technology for recycling organic waste into fertilizer\u003c/h2\u003e\u003cp\u003eThe results above reveal that household characteristics, institutional factors, and perceived benefits significantly influence household choice to adopt BSF technology for recycling organic waste. The age of the household head was a significant negative predictor. The marginal effects (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) indicate that as the age of the household head increases by one year, the probability of adopting BSF for recycling organic waste into fertilizer decreases. This implies that households reduce their likelihood of adopting technologies as the head ages. The plausible reason for this outcome is the high labour requirement for sourcing and pre-treating the waste before recycling using BSF larvae. Since older farmers have less energy than younger ones, they would likely adopt a recycling approach that does not require much effort and time. Our findings are consistent with Mwangi and Kariuki [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and Zondo [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] highlighting that old farmers are risk-averse compared to their younger counterparts.\u003c/p\u003e\u003cp\u003eHousehold size was a significant positive predictor. The marginal effect indicates that, an increase in household size by one member, increases the household’s probability of adopting BSF. This implies that farmers with larger families are more likely to adopt BSF. Labour is an important input in recycling organic waste. Larger families translate to more labour available for transforming the waste into fertilizer [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The findings were consistent with [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] which stated that larger family-sized households were likely to adopt agricultural technologies requiring more labour force.\u003c/p\u003e\u003cp\u003eThe number of years spent in schooling demonstrated a statistically significant positive association. The marginal effect (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) suggests that an additional year of schooling increases the household probability of selecting BSF. Farmers with higher levels of formal education are more cognizant of new technologies within relatively short durations [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The findings were consistent with Sennuga et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] indicating that there is an essential link between education levels and making informed choices. This is because education empowers the farmers to interpret, perceive, and respond to new technologies and practices and justifies their efficient production performance. Hence farmers with higher education are more likely to embrace BSF technology for recycling organic waste.\u003c/p\u003e\u003cp\u003eThe size of land used for recycling organic waste into fertilizer (production unit) demonstrated a statistically significant negative association. The marginal effect indicates that an increase in the size of land required for recycling organic waste by a square pace (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{1}{43560}\\)\u003c/span\u003e\u003c/span\u003e\u003csup\u003eth\u003c/sup\u003e acre) reduces a household's probability of adopting BSF. This implies that the less land requirement for recycling increases the likelihood of using new technologies like BSF. This is because land is a scarce resource, especially among the urban poor and those working in informal sectors. These results are consistent with Hanboonsong et al. [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and Kibaara et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] which reported that insect-based technologies for managing organic waste are efficient in space.\u003c/p\u003e\u003cp\u003eThe number of social associations/groups a household head belonged to was a significant positive predictor. The associated marginal effect (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) suggests that an increase in the number of social associations/ groups the household head belonged to, increases a household's probability of adopting BSF. This reveals that belonging to a social group fosters social networking and knowledge exchange about the advantages of new technologies [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The findings complement Sseguya et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], who observed that belonging to a group fosters farmer peer learning and consolidation of inputs through community banking models, thus encouraging the adoption of technologies.\u003c/p\u003e\u003cp\u003eAccess to agricultural/environmental extension information on recycling organic waste was a significant positive predictor. The corresponding marginal effect indicates that households that accessed extension information had an increased probability of adopting BSF. These results reveal that access to extension information increases awareness and the probability of adopting BSF technology for organic waste management. Our findings were similar to [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] which reported that extension agents are essential service providers who empower farmers on the relevant agricultural and environmental technologies that will enhance their productivity and profit margins. This emphasizes the importance of extension information in disseminating and promoting agricultural technologies and innovations.\u003c/p\u003e\u003cp\u003eRespondents’ perception of recycling organic waste into diverse products was a significant positive predictor. The marginal effect indicates that respondents who perceived recycling of organic waste as a potential diversification process for soil amendment, animal protein source, and bio-energy were probably more likely to choose BSF than those who did not perceive recycling to have potential diversified products. The results indicate that perception is a vital factor affecting the adoption of insect-based technologies. These findings were consistent with Liu et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and Salam et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], which stated that household perception of the use of BSF technology to convert organic waste into diverse, economically viable improved adoptability.\u003c/p\u003e\u003ch2\u003e4.2 Economic efficiency of using BSF larvae in recycling organic waste into fertilizer\u003c/h2\u003e\u003cp\u003eThe cost-benefit analysis indicators and sensitivity analysis results reveal that using BSF in recycling organic waste into fertilizer is economically efficient compared to conventional composting. The high NPV is attributed to the reduced time for recycling organic waste using BSF and the high selling price per kg of frass. It reveals the high potential of BSF as an emerging and profitable livelihood opportunity for households living in peri-urban areas where organic waste is abundant. These results are consistent with a study by Munthali et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and Groeneveld et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] which found that that BSF farming was economically viable as an alternative animal feed ingredient. A study by Beesigamukama et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] on the economic value of frass found that investing in frass fertilizer production among farmers rearing insects increased their income significantly. Moreover, value addition increases frass marketability and value, resulting in higher profit margins.\u003c/p\u003e\u003cp\u003eThe multiple recycling cycles (7–8 times annually) and higher volumes of organic waste recycled (7.5 MT annually) reveal that households recycling organic waste using BSF recycled more waste compared to those using conventional composting. To a large extent, these findings unveil the potential of BSF technology in managing organic waste. Moreover, food and market waste, which constitutes a large proportion of organic waste illegally disposed of [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], was the primary type of waste recycled using BSF, further emphasizing the role of BSF in promoting bio-circular economies, especially in urban and peri-urban areas. Additionally, BSF labour cost per man-day was higher compared to conventional composting implying that BSF offers job opportunities for unskilled and semi-skilled labour. On the other hand, labour accounts for a large proportion of operating costs [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and this calls for investing in local solutions that reduce labour requirements, such as waste segregation at source, to increase the gross margins accrued from recycling waste.\u003c/p\u003e\u003cp\u003eThe difference in IRR between the two recycling methods is attributed to the variations in cash flow and initial capital requirement. BCR attempts to summarize the overall monetary value of an investment. The higher BCR for using BSF implies that the overall monetary benefits of recycling organic waste into frass are higher compared to conventional composting. The ROI indicates that BSF’s profitability was 5-fold higher than that of conventional composting. This work provides the first discussion on the cost-effectiveness of recycling organic waste using BSF larvae compared to conventional composting. The CBA indicators reveal that recycling organic waste into fertilizer is cost-effective. In addition, it can provide a secondary source of income for farmers and cushion them against high fertilizer prices while promoting regenerative agriculture.\u003c/p\u003e\u003ch2\u003e4.3 Externalities associated with recycling organic waste into fertilizer\u003c/h2\u003e\u003cp\u003eRecycling organic waste generates non-monetary positive/negative externalities, which is critical for determining the economic efficiency of recycling organic waste. These externalities include the effect on soil health, crop yield, GHG emissions, and social impact (evaluated as labour requirement and job creation).\u003c/p\u003e\u003cp\u003eFrass influences bacterial growth and soil enzymes resulting in a significant impact in soil health and fertility [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. BSF-composted fertilizer could be categorized as an NPK compound fertilizer with an average composition of 3.4% N, 2.9% P2O5, and ,3.5% K2O, and C/N ratio of 13–16 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Additionally, frass is a suitable soil amendment that influences soil fungal/bacterial composition, and rapidly releases nitrogen needed for plant absorption [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. This implies that frass is a potentially efficient substitute for promoting soil health.\u003c/p\u003e\u003cp\u003eThe effect of frass on plant growth and health vary depending on the crop varieties and frass type [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This is because the nutritional composition of frass is greatly determined by the feed substrate (organic waste) used [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Germination indexes improved when frass fertilizer was used compared to conventional compost because frass is a more stable organic fertilizer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Moreover, the rich nutrients and organic matter in frass fertilizer reduce the need to use chemicals for plant disease protection [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] and crops produce higher yield compared to compost from conventional composting [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. These findings imply that frass could, therefore, be a partial or complete substitute to highly priced inorganic fertilizer while promoting efficient organic waste management [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecycling organic waste using BSF larvae reduces global warming potential by 50% compared to conventional composting, thus, BSF technology is environmentally friendly and conserves environmental resources [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Additionally, recycling organic waste using BSF larvae reduces odour and GHGs (CH\u003csub\u003e4\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e, and N\u003csub\u003e2\u003c/sub\u003eO) associated with bioconversion of organic waste [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Moreover, the short waste recycling duration associated with BSF larvae reduces the emissions of N\u003csub\u003e2\u003c/sub\u003eO compared to conventional composting, whose recycling takes longer [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The total ammonia emitted from BSF composting was 0.12 to 10% that of conventional composting, implying that less overall Nitrogen is lost during BSF composting [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. These results reveal that recycling organic waste using BSF has lower environmental footprint compared to conventional composting and therefore more environmentally efficient.\u003c/p\u003e\u003cp\u003eUsing BSF in recycling organic waste promotes social interaction through learning from one another and creates employment through the demand for extra labour. Social interaction attracts the technical know-how required for adopting and implementing new technologies. Adopting these technologies creates job opportunities, culminating into social impact [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. Although the additional labour cost signifies a welfare loss to the farmer, the employment created for the society signifies a welfare/economic gain to the society.\u003c/p\u003e"},{"header":"Conclusion and policy recommendations","content":"\u003cp\u003eThis study discusses the factors influencing adoption of BSF and its cost-effectiveness in recycling organic waste into fertilizer. We show that BSF has huge potential in recycling organic waste, especially in urban and peri-urban areas, because of the diverse nature of organic waste recycled and the multiple possible production cycles. For every tonne of waste recycled, BSF was profitable and cost-effective, with 5-fold higher return on investment than conventional composting. Moreover, the use of BSF in recycling organic waste has lower GHG emissions, while the frass fertilizer promotes regeneration of soil health, which increases crop yield.\u003c/p\u003e\u003cp\u003eIt is important to emphasize the economic potential of using BSF in recycling organic waste in circular and green economy advocacy. Increasing the uptake of BSF in recycling organic waste into fertilizer will require awareness campaigns and capacity-building programs among households, governments, civil societies, and private sector actors in the waste management and fertilizer industry. These results should inform further BSF feasibility studies, efficient waste management programs, and livelihood diversification efforts in waste-abundant areas.\u003c/p\u003e\u003cp\u003eAlthough our study was conducted in Kiambu County, Kenya, the use of BSF in recycling organic waste is being advanced globally. The methodology used in this study can be easily replicated in other regions and contexts. This study used cross-sectional data and was limited to the financial benefits of using BSF in recycling organic waste into frass fertilizer compared to conventional compost. Future research should consider longitudinal data and a more comprehensive assessment of the environmental and social benefits of using BSF in recycling organic waste.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerpetual G. Mugendi:\u0026nbsp;Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Visualization, Validation, Writing – original draft, Revising the draft.\u003c/p\u003e\n\u003cp\u003eBeatrice W. Muriithi:\u0026nbsp;Conceptualization, Investigation, Methodology, Project administration, Software, Supervision, Visualization, Validation, Writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRaphael Gitau:\u0026nbsp;Conceptualization, Investigation, Methodology, Supervision, Visualization, Validation, writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDennis Beesigamukama: Project administration, Supervision, Validation, writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eShaphan Y. Chia: Project administration, Supervision, Validation, writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTeresia G. Wamwondwe: Methodology,\u0026nbsp;Validation, writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKassie Menale:\u0026nbsp;Project administration, Supervision, Validation, writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eChrysantus M. Tanga:\u0026nbsp;Conceptualization, Investigation, Methodology, Project administration, Visualization, Validation, writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the financial support for this research by the following organizations and agencies: Australian Centre for International Agricultural Research (ACIAR) (ProteinAfrica –Grant No: LS/2020/154), Novo Nordisk Foundation (RefIPro: NNF22SA0078466), the Rockefeller Foundation (WAVE-IN—Grant No: 2021 FOD 030); Bill \u0026amp; Melinda Gates Foundation (INV-032416); IKEA Foundation (G-2204-02144), Horizon Europe (NESTLER - Project: 101060762 - HORIZON-CL6-2021-FARM2FORK-01),\u0026nbsp;the Curt Bergfors Foundation Food Planet Prize Award; Norwegian Agency for Development Cooperation, the Section for Research, Innovation, and Higher Education grant number RAF–3058 KEN–18/0005 (CAP–Africa). We also gratefully acknowledge the support of Egerton University and \u003cem\u003eicipe\u003c/em\u003e core funding provided by the Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC); the Australian Centre for International Agricultural Research (ACIAR); the Norwegian Agency for Development Cooperation (Norad); the Federal Democratic Republic of Ethiopia; and the Government of the Republic of Kenya. The first author, Perpetual G. Mugendi, was financially supported by\u0026nbsp;Louis Dreyfus Foundation (LDF) through a postgraduate scholarship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed herein do not necessarily reflect the official opinion of the donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData presented in this manuscript is available upon request from the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by Egerton University Ethic Review Committee (EUREC) and was in accordance with the university guidelines and requirements for research. All the research processes, such as data collection using a household survey, were done in accordance with the ethical committee's standards and procedures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects and/or their legal guardian(s).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish Declaration:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that they have no known financial or interpersonal conflicts that would have appeared to impact the research presented in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKaza S, Yao LC, Bhada-Tata P, Van Woerden F. 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Journal of Environmental Management. 2020;265:110548. https://doi.org/10.1016/j.jenvman.2020.110548\u003c/li\u003e\n\u003cli\u003eLindberg L, Ermolaev E, Vinner\u0026aring;s B, Lalander C. Process efficiency and greenhouse gas emissions in black soldier fly larvae composting of fruit and vegetable waste with and without pre-treatment. Journal of Cleaner Production. 2022;338:130552. https://doi.org/10.1016/j.jclepro.2022.130552\u003c/li\u003e\n\u003cli\u003eNg\u0026rsquo;ang\u0026rsquo;a SK, Miller V, Girvetz E. Is investment in Climate-Smart-agricultural practices the option for the future? Cost and benefit analysis evidence from Ghana. Heliyon. 2021;7(4):e06653. https://doi.org/10.1016/j.heliyon.2021.e06653\u003c/li\u003e\n\u003cli\u003eKhatri-Chhetri A, Aggarwal PK, Joshi PK, Vyas S. Farmers\u0026rsquo; prioritization of climate-smart agriculture (CSA) technologies. Agricultural Systems. 2017;151:184\u0026ndash;91. https://doi.org/10.1016/j.agsy.2016.10.005\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Agriculture](https://www.springer.com/journal/44279)","snPcode":"44279","submissionUrl":"https://submission.nature.com/new-submission/44279/3","title":"Discover Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6264404/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6264404/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInappropriate handling of the abundant organic waste generated annually imposes far-reaching impacts on the environment, economies, and societal well-being. Insect-based technologies are gaining traction in recycling of organic waste and recovering valuable macro and micro-nutrients. However, there is little information about the costs and benefits of using black soldier fly (BSF) in recycling organic waste into fertilizer compared to conventional composting. This study determined factors influencing the adoption of BSF and its cos-effectiveness in recycling organic waste using logistic regression, cost-benefit analysis, and sensitivity analysis. A household survey was conducted among 222 households in Kiambu County, Kenya. Results revealed that membership in waste management groups, access to recycling information, and perception of diversification of recycled products significantly and positively influenced the adoption of BSF. Households adopting BSF recycle 3-fold higher volumes of organic waste annually and generate 5-fold higher return on investment than those using conventional composting. Our findings reveal that BSF is profitable, and a potential economically efficient technology for managing organic waste and promoting greener economies. These results should inform research and policy decisions aimed at developing and promoting efficient waste management technologies and integrate frass fertilizer production into smallholder cropping systems.\u003c/p\u003e","manuscriptTitle":"Economic Efficiency and Adoption Determinants of Insect-Based Technologies for Organic Waste Recycling into Fertilizer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:17:43","doi":"10.21203/rs.3.rs-6264404/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-26T13:05:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-14T15:42:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-06T12:39:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175451706655698141863691090105572756058","date":"2025-05-02T05:54:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169112045354445457517285161816524213028","date":"2025-05-01T10:37:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37836675541989879819036857968528960281","date":"2025-04-29T11:37:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152345513889392223122313116501361678765","date":"2025-04-25T20:38:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-25T12:18:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-22T07:44:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-16T04:04:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Agriculture","date":"2025-04-16T04:03:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Agriculture](https://www.springer.com/journal/44279)","snPcode":"44279","submissionUrl":"https://submission.nature.com/new-submission/44279/3","title":"Discover Agriculture","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f5632605-9357-433e-ae62-e0d8e1947d31","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T07:59:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 06:17:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6264404","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6264404","identity":"rs-6264404","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}