The Antecedents of Business Model Innovation in Malaysian Manufacturing SMES

The Antecedents of Business Model Innovation in Malaysian Manufacturing SMES | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Antecedents of Business Model Innovation in Malaysian Manufacturing SMES Indra Sumantri Eddie Mat Senal, Lin Dar Ong, Su Teng Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8091090/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the past few years, there has been a growing interest from academics and practitioners in understanding the factors that affect business model innovation (BMI). Nevertheless, there remains a lack of understanding of what drives SMEs to be engaged in BMI. Drawing upon the Strategic Entrepreneurship Theory (SET), the aim of this research is to examine the effect of the external and internal drivers of manufacturing SMEs on BMI. These factors include environmental dynamism, absorptive capacity, and entrepreneurial orientation. The data were collected from 282 manufacturing SME managers in Malaysia using a quantitative survey method. The Partial Least Squares (PLS) modeling technique was utilized to examine the data. The findings revealed that entrepreneurial orientation is positively related to BMI, while environmental dynamism and absorptive capacity have shown adverse results. The findings imply that entrepreneurial orientation is an important factor influencing manufacturing SMEs to be engaged in BMI. Hence, the results suggested that BMI in manufacturing SMEs significantly depends on its entrepreneurial activities which changes its core business processes. This study builds upon existing research by examining the factors that influence BMI in small and medium-sized manufacturing enterprises. Business model innovation Environmental dynamism Absorptive capacity Entrepreneurial orientation Antecedents of business model innovation Figures Figure 1 1. INTRODUCTION Since the late 1970s, SMEs have contributed a significant role in Malaysia. Like other countries, SMEs are a substantial backbone of Malaysia’s economy and industrial development in providing jobs and growth opportunities (Amin et al., 2016 ; SME Governance Working Group, 2024 ). SMEs represent 97.4 per cent of the overall business establishments registered in 2024 (SME Governance Working Group, 2024 ). Notwithstanding, SMEs also face many limitations and constraints in terms of resources, technologies, market access, and capabilities compared to their bigger rivals, such as multinational corporations (MNCs) and large firms. Despite having deficiencies in sizes, resources, and capabilities (Abdullah et al., 2011 ; Songling et al., 2018 ), SMEs’ contribution to the country’s economic growth has made it a popular subject among researchers (Abdullah et al., 2011 ). Nevertheless, this study focuses on SMEs in the manufacturing sector in Malaysia. As described by Ho et al. ( 2016 ), the manufacturing sector plays a significant role in a country's economy, which motivates this study. Having said that, manufacturing SME business operations are associated with various aspects of innovation. As of August 2025, Malaysian manufacturing SMEs accounted for 5.3% percent 57,187 of all the country's SMEs (SME Corporation Malaysia, 2025). In high-cost operating environments, manufacturing SMEs are increasingly looking toward innovation to ensure their productivity growth, especially to achieve non-price-based competition. Although innovation has always been central to manufacturing, product and process innovation has always been a great challenge for SMEs because it involves high investment (Chin & Lim, 2018 ). Moreover, a study conducted by Lim and Shyamala ( 2011 ) indicated that manufacturing SMEs in Malaysia faced impediments to innovation due to costs, labor, risks, and financing that have hindered them from engaging in innovation activities. Lee and Lee ( 2006 ) exposed that financial constraint is one of the severe factors that hamper manufacturing SMEs from being involved in innovation activities. An interesting finding by Chin and Lim ( 2018 ) revealed that Malaysian manufacturing SMEs are less likely to be engaged in product and process innovation and are keen on non-technological innovations such as organizational and marketing innovation. Furthermore, according to Bashir and Verma ( 2017 ), in a turbulent and unpredictable business environment, new products and process innovations do not always result in success. In this regard, it is interesting to unfold how manufacturing SMEs adopt and utilize their capabilities to modify or innovate business model. 1.1 Business Model Innovation Throughout the years, research on BMI has increased significantly (Foss & Saebi, 2017 ), thus gaining popularity and a growing interest among scholars and business strategists to decipher the triggers, predictors, antecedents, theories, practices, and outcomes of the phenomenon. Studies on BMI have spread across in different areas and disciplines, including innovation management, strategic management, and entrepreneurship (Schneider & Spieth, 2013 ). Moreover, multiple studies and theories have attempted to explain the concept and definition of BMI. The agreement on BMI’s meaning and construct clarity still lacks underpinning theory and therefore requires more empirical testing (Foss & Saebi, 2017 ; 2018 ). The fundamentals and interpretation of BMI depend on how the concept of a business model is characterized and viewed. Similar to BMI, several studies have listed various definitions of business model and its component. The clear notion of a business model was emphasized by Teece ( 2018 ), where the researcher defined it as the framework or structure of the value creation, delivery, and capture mechanisms that a firm employs. Another concrete definition was provided by Zott et al. ( 2011 ), where a business model is regarded as the overall relationship between elements such as value proposition, revenue model, and a network of relationships. Nonetheless, the most profound insight into the business model definition was proposed by Osterwalder ( 2004 ). The scholar has outlined the nine building blocks later known as the business model canvas (BMC). The nine elements are value proposition, target customer, distribution channel, relationship, value configuration, core competency, partner network, cost structure, and revenue model, which coined the comprehensive definition of business model. Based on these components, Osterwalder ( 2004 ) described the term business model as a conceptual instrument that encompasses a collection of components and their interconnections and enables the articulation of a company's profit-making logic. It represents the value the firm has to offer to customers, the structure of the company and its collaborative network of partners to create revenue streams that are both profitable and sustainable, which form a unique blueprint of all the business operations of the firm. The novelty and closely integrated structure of the company makes it challenging for competitors and rivals to replicate the business model. Along with Teece’s ( 2007 ) idea of the business model, Zott et al. ( 2011 ) emphasized that a business model does not stand alone. It consists of integration and interdependency among the elements. Most importantly, the business model has emerged into a new unit of analysis, thus explaining how value is created and how companies operate with a holistic approach (Zott et al., 2011 ). BMI involves developing, reinventing, redesigning, refining, or replacing the current business model (Teece, 2018 ). The adjustments or changes in the original business could involve one or more components, such as value proposition, channels, customer relationships, or revenue streams in the architecture. Thus, changes in one of the components will affect the other (Teece, 2018 ). Although this makes sense, to some scholars, BMI encompasses the transformation of the entire framework of the business model rather than focusing solely on a single or an individual component (Foss & Saebi, 2017 ). In this regard, BMI and business model are interrelated. However, they are not to be used or applied interchangeably. BMI represents a new dimension or subject of innovation (Foss & Saebi, 2017 ; Zott et al., 2011 ). According to Zott et al. ( 2011 ), BMI represents a new source of innovation. It enhances the conventional topics of process, product, and organizational innovation and entails new ways of working together and partnering. It also underlines the firm’s core attributes, similar to changes in product, structure, delivery, and process (Zott & Amit, 2008 ). Nevertheless, a distinguishing characteristic of BMI from the traditional product or process innovation is something that cannot be simplified to, for example, not just technological advancements, but also encompasses the overall structure of the firm (Teece, 2010 ). According to Anwar ( 2018 ), BMI is distinct from innovation in the sense that it enables SMEs on the spot when a new opportunity arises. Another important aspect for a firm to innovate its business model is understanding and sensing the customers’ unmet needs. Drawing upon Strategic Entrepreneurship Theory (SET), this research intends to investigate the key antecedents of BMI explicitly by assessing the relationship between the firms’ external and internal drivers on BMI. It aims to provide a better understanding of what enables firms specially manufacturing SMEs to be engaged in BMI. Since there are significant gaps in the understanding of the drivers of BMI (Foss & Saebi, 2017 ; 2018 ), results from this study will specifically reveal whether environmental dynamism, absorptive capacity, and entrepreneurial orientation make an important key predictor of BMI. These constructs were introduced based on the suggestions put forward by previous researchers. Consequently, the findings provide solid empirical evidence on the enabling constructs that influence manufacturing SMEs to be engaged in innovating their business model, which was found to be scarce in the literature. In light of this, the findings extend knowledge on BMI construct clarity and provide new insightful results with the antecedents of BMI centered on the Strategic Entrepreneurship perspective. Based on the literature, only a limited number of studies have concerned the drivers and antecedents of BMI (Motjolopane & Ruhode, 2022 ), for instance in recent research carried out by Bhatti et al. ( 2021 ) on IT firms operating in Pakistan. Hence, the scarcity was also mentioned by Foss and Saebi ( 2017 ), where it was found that there are gaps in the understanding of the antecedents of BMI. According to the researchers, the factors leading to BMI can differ in their characteristics and can be internal or external to the firm. There were few antecedents, or the drivers of BMI, that have been studied by prior researchers identified in the literature. In a recent study conducted by Faiz et al. ( 2024 ), digital leadership capabilities was identified as a significant driver influencing BMI, entrepreneurial passion was found to positively affects BMI (Dinibutun, 2024 ), and Adomako ( 2024 ) has proven that international orientation positively affects BMI. Despite these findings, other vital constructs could still be an important driver of BMI that has yet to be tested. The constructs include varied classifications of the number of internal and external BMI drivers (Gatautis et al., 2019 ), which could be the drivers or enablers of BMI. For instance, Foss and Saebi ( 2017 ) proposed open innovation, servitization, sustainability, stakeholders, and many more. Bashir and Verma ( 2019 ) introduced five BMI drivers, that is leadership, technology, organizational structure, culture, and inertia. Nonetheless, this study presented environmental dynamism as the external, while absorptive capability and entrepreneurial orientation as the internal antecedents. In response, this study adds to the existing body of literature by enhancing the understanding of what enables manufacturing SMEs to conduct BMI. The relationship between BMI and its link between entrepreneurship, strategy, and performance has not received sufficient attention. Therefore, research on these relationships is warranted to understand better the impact of BMI on the performance of entrepreneurial firms (Foss & Saebi, 2017 ). The limited knowledge of the factors and reasons behind how SMEs innovate their business models has become a major concern among researchers (Foss & Saebi, 2017 ; 2018 ). Consequently, this study revealed BMI construct clarity, thus providing new insight into the antecedents' impact on BMI. Therefore, it is worthwhile to investigate these causal relationships from SMEs’ point of view. Furthermore, the originality of this study addressed BMI from a holistic perspective through a synergistic influence of the firms’ internal and external factors within the context of Strategic Entrepreneurship Theory. 1.2 Theoretical background In this study, Strategic Entrepreneurship Theory was adopted to research on BMI. Strategic Entrepreneurship Theory explains how firms especially SMEs explore and exploit opportunities through internal capabilities and external opportunities when facing uncertainty must adapt to respond to altering sources of value creation by reconfiguring their existing business practices (Amit & Zott, 2012 ; Schneider & Spieth, 2013 ). In addition, Strategic Entrepreneurship Theory explicitly pays attention to the entrepreneurial action of established firms to provide additional insights to further enhance the understanding of BMI. The notion of Strategic Entrepreneurship is particularly suitable for studying contemporary firms where change has become constant, intermittent, rapid, and unpredictable. Driven by technological advancement and globalization, Strategic Entrepreneurship Theory was coined by Hitt et al. ( 2001 ) as a new entrepreneurial strategy for creating the most valuable entrepreneurial firms. Specifically, the theory implies firms identify and exploit entrepreneurial opportunities based on their internal capabilities and external environment as their core (Hitt et al., 2001 ; Schneider & Spieth, 2013 ). In this sense, applying Strategic Entrepreneurship Theory in the framework is able to answer what allows firms to perform BMI that requires additional attention. 2. HYPOTHESES DEVELOPMENT 2.1 The relationship between environmental dynamism and BMI Environmental dynamism pertains to how quickly changes occur and the level of unpredictability within the environment (Dess & Beard, 1984 ). Jansen et al. ( 2006 ) describe environmental dynamism as technological changes, variations in customer preferences, changes in product demand or supply of materials, and the unpredictability of change. In addition, according to Jansen et al. (2005), rapidly changing environments render existing products and services outdated. Moreover, Chang et al. ( 2011 ) pointed out that dynamic market conditions might compel firms to participate simultaneously in exploitative and exploratory innovations. Thus, to remain competitive, firms need to shift from existing products, services, and markets through exploratory innovations to enhance their financial performance (Jansen et al., 2006 ). Environmental dynamism was proven to influence innovation activity. Research carried out by Soto-Acosta et al. ( 2018 ) on Spanish manufacturing SMEs has shown that environmental dynamism was found to have a positive and significant impact on innovation ambidexterity. In this study, environmental dynamism was introduced in the research framework posited to have an influence on BMI, thus suggesting that manufacturing SMEs deploy ambidextrous innovations based on the external pressure of the environment. Moreover, in advancing the BMI research, this importance was also addressed by Foss and Saebi ( 2017 ) in their proposed causal web in which environmental dynamism could be an important antecedent of BMI that requires to be clarified, elaborated, and researched. Building on the above arguments, this study posits that dynamic environments influence manufacturing SMEs to be engaged in BMI practices. Therefore, the subsequent hypothesis is postulated. H1 Environmental dynamism is positively related to BMI. 2.2 The relationship between absorptive capacity and BMI When facing uncertainty in a dynamic environment, the firm’s current knowledge may become obsolete and therefore needs continuous renewal. Hence, to achieve profitable innovations, firms require effective abilities to renew their knowledge base through acquisition, assimilation, and knowledge utilization (Jantunen, 2005 ). These abilities are what Cohen and Levinthal ( 1990 ) coined as absorptive capacity. According to Cohen and Levinthal ( 1990 ), absorptive capacity relates to the firm's ability to identify or assess the value of new information by exploiting useful external knowledge from the environment, assimilating and then applying it to commercial ends. Zahra and George ( 2002 ) have reconceptualized the definition of absorptive capacity that was introduced by Cohen and Levinthal ( 1990 ) into a set of organizational routines and processes known as potential capacity (knowledge acquisition and assimilation) and realized capacity (knowledge transformation and exploitation). These routines and processes produce a dynamic organizational capability vital for the firm to achieve competitive advantage. Potential absorptive capacity allows a firm to be receptive to external knowledge, whereas realized absorptive capacity indicates its ability to utilize the acquired knowledge and convert it into innovative results (Zahra & George, 2002 ). According to Ramayah et al. ( 2020 ), the ability to exploit external knowledge is an essential element of innovative capabilities, and firms need to possess realized absorptive capacity to excel in innovation. A review of past literature shows that most of the studies on absorptive capacity are related to innovation (Zou et al., 2018 ). Thus, most empirical studies have revealed a significant relationship between absorptive capacity and innovation. A study by Ramayah et al. ( 2020 ) has shown that absorptive capacity served as a significant indicator of innovation performance (product and process innovation) among manufacturing firms in Malaysia. Similarly, according to Zou et al. ( 2018 ), absorptive capacity is a significant indicator of innovation. While numerous studies have examined the relationship between absorptive capacity and innovation (Zou et al., 2018 ), there is still limited cause-and-effect research found in the literature to understand the influence between the construct and BMI. Therefore, to fill this gap, absorptive capacity was introduced as an important internal driver in the current study research framework that could influence manufacturing SMEs to innovate their business model. Following Jantunen ( 2005 ), the absorptive capacity construct applied in this study is characterized based on the three dimensions that are knowledge acquisition, dissemination and utilization. In this study, absorptive capacity was viewed as a higher-order construct to investigate how manufacturing SMEs exploit new knowledge gathered and acquired from their external environment for value creation (Ramayah et al., 2020 ; Valentina & Passiante, 2009 ; Zahra & George, 2002 ). Nonetheless, this study will provide an empirical understanding of whether absorptive capacity promotes manufacturing SMEs to search for new knowledge and increases their ability to make the necessary changes in their business model. Henceforth, based on prior studies and grounded on these arguments, this study posits that absorptive capacity influences manufacturing SMEs to innovate their business model and consequently results in the formulation of the following hypothesis: H2 Absorptive capacity is positively related to BMI. 2.3 The relationship between entrepreneurial orientation and BMI According to Foss and Saebi ( 2017 ; 2018 ), entrepreneurship is intrinsically associated to BMI, where the connection is tightly associated with entrepreneurial vision, imagination, and judgment. Notably, Schneider and Spieth ( 2013 ) outlined that entrepreneurial actions are essential when firms seek to innovate their business model. Entrepreneurial orientation was initially coined by Miller ( 1983 ) which include three dimensions that is innovativeness, risk-taking and proactiveness. As the advancement of strategic management study, the concept of entrepreneurship has shifted towards the study of entrepreneurial orientation. Expanding from this concept, along with Miller’s ( 1983 ) three entrepreneurial dimensions, Lumpkin and Dess ( 1996 ) have drawn on extensive research by characterizing entrepreneurial orientation by adding two other dimensions, namely competitive aggressiveness and autonomy. Although all the five dimensions itemized by Lumpkin and Dess ( 1996 ) are considered comprehensive, there is no consensus in the literature concerning the dimension of entrepreneurial orientation (Martin & Javalgi, 2016 ). For instance, to some researchers like Jantunen et al. ( 2005 ), Wiklund ( 1999 ), and Covin and Slevin ( 1989 ), entrepreneurial orientation is represented as a one-dimension construct, while to others such as Ferreira et al. ( 2015 ), Covin and Miller (2014), Lee and Lim ( 2009 ), and Hughes and Morgan ( 2007 ) it has been viewed as a multidimensional construct. In this study, the entrepreneurial orientation construct was viewed and conceptualized following Jantunen et al. ( 2005 ), succeeding the original concept of Miller ( 1983 ) and Covin and Slevin ( 1989 ), which consists of innovativeness, proactiveness and risk-taking dimensions. Prior studies have shown that entrepreneurial orientation led to BMI. Asemokha et al. ( 2019 ) have identified a significant relationship between entrepreneurial orientation and BMI based on an industrial sample of 95 international SMEs in Finland. According to Foss and Saebi ( 2017 ), BMI research may be advanced by drawing on theorizing in the entrepreneurship streams, which can help meet the gaps in the BMI literature because the close interrelationship between BMI and entrepreneurship is scarce and has not received sufficient attention (Foss & Saebi, 2017 ). Therefore, based on strategic entrepreneurship theory, this study anticipated that, in facing uncertainty in the environment, manufacturing SMEs with a higher level of risk-taking, innovativeness, and proactiveness would enable them to explore opportunities and exercise innovative changes in their business model. Accordingly, entrepreneurial orientation was presented as an internal driver in the research framework to examine whether the particular construct significantly affects BMI. Hence, based on these arguments, it is hypothesized that: H3 Entrepreneurial orientation is positively related to BMI. Guided by the Strategic Entrepreneurship Theory framework, the conceptual model for this study is shown in Fig. 1 below. (Insert Fig. 1 here) 3. METHODS 3.1 Sample and data collection In this study, primary data were collected using a cross-sectional survey method. Based on this approach, the data collection process was conducted over a short timeframe only once (Bougie & Sekaran, 2019 ; Christensen et al., 2015). In selecting the right sample for this study, a judgment purposive non-probability sampling was applied. The targeted population encompasses Malaysian SMEs involved in the manufacturing sector, with a total of 75,684 population. Notwithstanding, this study employed the classification of manufacturing industries following the categorization set by the Organisation for Economic Co-operation and Development (2011), which ranges from high-technology sectors such as pharmaceuticals to low-technology industries like food and beverage products. Based on the current definition provided by SME Corporation Malaysia (2017), Malaysian manufacturing SMEs are defined as firms of having annual sales turnover (total revenue including other incomes) not exceeding RM50 million or having a total number of full-time employees not exceeding 200 workers. For a firm to be classified as a manufacturing SME in Malaysia, a business must only satisfy one of the two qualifying criteria used in the definition, or whichever is lower. Therefore, the definition of manufacturing SMEs strictly follow the above criteria and classification. The sampling data were from various local manufacturing industries such as The Federation of Malaysian Manufacturers (FMM), Malaysia External Trade Development Corporation (MATRADE), and the Ministry of Entrepreneur Development and Cooperatives (MEDAC) company directory lists. Data were collected from a single key informant from each identified manufacturing SME through judgment sampling design. The targeted respondents are mainly top executives, specifically the senior or upper management level, preferably the Managers or Chief Executive Officers (CEOs) who may have critical information and knowledge about the company’s operation. Following Foss and Saebi ( 2018 ), top management was viewed as the central monitor of a firm that plays an essential position in making sure the implementation of BMI. A self-administered closed-ended questionnaires were designed and applied to collect the required data. Before disseminating the questionnaires, the research ethics clearance was attained from the Universiti of Malaya Research Ethics Committee (UMREC). UMREC’s consent is necessary to undertake an ethics review to ensure that the research components, such as the methodology are carried out soundly, and any possible risks to the subjects are mitigated and handled with diligence. Determining the proper sample size is critical when employing survey research. Hair et al. ( 2014 ; 2017 ; 2019a ) recommended that power analysis to be utilized to establish the necessary sample size for a study that applied PLS-SEM. Using power analysis, the minimum sample size can be determined by accounting for the maximum number of predictors drawn in the research model (Hair et al., 2014 ). The calculation requires information on effect size, significance level (α) and sample size to compute the minimum sample size requirement (Hair et al., 2018 ). Following Hair et al.’s ( 2017 ) recommendation, G*Power (Faul et al., 2007 ) version 3.1.9.7 was employed to compute the sample size required for this study. The calculation for the minimum size requirement for this study was done following the most recommended settings for conducting social and business science research (Hair et al., 2014 ; 2017 ; Memon et al., 2020 ). Based on the G*Power computation, the minimum sample size required for this study is 92. Although the minimum sample size has been identified and since conducting surveys among SMEs tends to suffer from low response rates (Dennis Jr., 2003 ), therefore, to increase the response rate of this study, 800 questionnaires were distributed. Bougie and Sekaran ( 2019 ) recommended that a 30 per cent response rate is acceptable and exceptional. Thus, in ensuring optimum results, this study goes along with Memon et al.’s ( 2020 ) suggestion that a sample size between 160 and 300 is the most appropriate for multivariate statistical analysis, especially for PLS-SEM. Considering the G*Power result analysis, Bougie and Sekaran’s ( 2019 ) and Memon et al.’s ( 2020 ) suggestion, this study has collected 282 usable responses (35.25% effective response rate). 3.2 Measures The standard measurements utilized in the questionnaire were adapted and derived based on the original scales developed by the previous researchers, which have been validated and applied in numerous studies. As this study aims to understand the antecedents of BMI, the unit of analysis is the firm or organizational level. Environmental dynamism was assessed using a 7-point Likert scale developed by Jansen et al. ( 2006 ) consisting of five items. Based on the original scale, environmental dynamism was measured using statements anchored from 1 (strongly disagree) to 7 (strongly agree). Absorptive capacity was assessed using a 7-point Likert scale developed by Jantunen ( 2005 ) consisting of 16 items. Based on the original scale, absorptive capacity was measured using statements anchored from 1 (strongly disagree) to 7 (strongly agree). Entrepreneurial orientation was assessed using a 7-point Likert scale developed by Jantunen et al. ( 2005 ) consisting of nine items. Based on the original scale, entrepreneurial orientation was measured using statements anchored from 1 (strongly disagree) to 7 (strongly agree). BMI was measured using the scale developed by Guo et al. ( 2016 ). The 5-point Likert scale consisting of nine items was developed based on the work by Zott and Amit ( 2007 ; 2008 ). The scale ranging from 1 (strongly disagree) to 5 (strongly agree). 4. RESULTS 4.1 Demographic profile of the respondents. The demographic profile shows that the majority 63.8 per cent of the manufacturing SMEs that partook in this study were from the low-technology industry (wood, pulp, paper, food, beverages, tobacco, textiles, leather, and footwear products). Notably, private limited manufacturing SMEs formed 57.1 per cent of the majority of respondents and are mostly small in size, with annual sales of RM300,000 to RM15 million with full-time employees ranging from 5 to 75. It is observed that 44.3 per cent of the respondents have been operating for 6 to 10 years, 63.1 per cent were in urban, and 58.2 per cent were managers. Astoundingly, only 2.1 per cent of the respondents were unfamiliar with the term business model, which indicates their high literacy of the study theme. 4.2 Data analysis Partial Least Squares Structural Equation Modelling (PLS-SEM) using the SmartPLS software version 3.3.7 (Ringle et al., 2015) was employed to examine the measurement and structural model of this study. Hair et al. (2019a; 2019b) emphasized that the benefits of utilizing PLS-SEM include, it can handle small sample size data and non-normally distributed data. Given that the data was gathered from a single source, Common Method Bias (CMB) constitutes a significant concern (Podsakoff et al., 2003). Therefore, CMB was addressed by testing the full collinearity adhering to the recommendations by Kock and Lynn (2012) and Kock (2015). In this approach, each variable was regressed against a common variable. If the VIF values is ≤ 3.3, then CMB is not present. The analysis indicated a VIF of less than 3.3; thus, confirmed that CMB was not a threat ( Table 1 ). (Insert Table 1 here) 4.2.1 Measurement model The measurement model was tested following the two-step method recommended by Anderson and Gerbing (1988). Firstly, the convergent validity was performed to assess the validity and reliability of the measurement model. The loadings, average variance extracted (AVE), and the composite reliability (CR), were assessed following Hair et al. (2019a) and Ramayah et al. (2018). The values of loadings should be ≥ 0.5, AVE should be ≥ 0.5, and the CR should be ≥ 0.7. As shown in Table 2, the AVEs were all higher than 0.5, and the CRs were all higher than 0.7. Ten items that were found to have low loadings were removed. (Insert Table 2 here ) As shown in Table 2 , absorptive capacity in this study represents a second-order construct Type I (reflective-reflective) where the loadings of knowledge acquisition, knowledge dissemination, and knowledge utilization measured the AVE and CR. Based on the analysis, the second-order measurements were also valid and reliable. Secondly, the discriminant validity using the Heterotrait Monotrait Ratio of Correlations (HTMT) criterion was performed based on Henseler et al.’s (2015) recommendation and Franke and Sarstedt (2019) updated. The HTMT values should be ≤ 0.85 (stricter criterion) or ≤ 0.90 (lenient criterion). As shown in Table 3 , all the HTMT values were lower than 0.85, thus conclude that the respondents understood that all the four constructs were distinct. Based on the results, it shows that the measurement items were both valid and reliable. (Insert Table 3 here) 4.2.2 Structural model Next, the evaluation of structural models was performed. The assessment determines the model’s capabilities to forecast one or more target constructs (Hair et al., 2017). In response to the recommendations of Hair et al. (2019a) and Ramayah et al. (2018), the path coefficients (β), standard errors, t-values, and p-values for the structural model using a 5,000-sample re-sample bootstrapping procedure were reported. Nonetheless, in light of the criticism of Hahn and Ang (2017), who have contended that p -values are not an adequate benchmark for assessing the significance of hypotheses; instead, a blend of criteria like p -values, confidence intervals, and effect sizes (f 2 ) was implemented. Table 4 shows the outcomes of the hypothesis testing. Next, the impact of the three predictors on BMI was evaluated, where the value of R 2 was 0.251 (Q 2 = 0.121). This indicates that all the three predictors were accounted for 25.1% of the variance in BMI, thus indicating a moderate model. Thus, it was found that only entrepreneurial orientation ( β = 0.264, p < 0.01) is positively related to BMI, thus give support for H3. (Insert Table 4 here) Subsequently, the predictive relevance (Q 2 ) of the model was evaluated through the blindfolding method in SmartPLS, where the omission distance ( D ) value of eight (8) was selected. If Q 2 > 0, the model has demonstrated predictive relevance for a specific endogenous construct (Hair et al., 2017; 2019a). The Q 2 value for BMI (Q 2 = 0.121) are greater than 0, thus indicating that the model possesses sufficient predictive relevance. 5. DISCUSSION This study provides insight on the antecedents of BMI. Although there are few existing literatures that have been doing similar research, however, there are still lacking of understanding on what drives firms to be involved in BMI especially in relation to manufacturing SMEs in Malaysia. The lack of empirical studies on BMI (Heikkilä & Bowman, 2018 ; Randhawa et al., 2021 ) and its driver (Gatautis et al., 2019 ; Miroshnychenko et al., 2021 ) have motivated this study. This research adds to the body of knowledge on strategy and entrepreneurship by looking into the effects of the external and internal drivers on BMI. The study's conclusions are captivating to scholars and professionals alike. The study's theoretical and practical consequences are shown in the following. 5.1 Theoretical implications From a theoretical perspective, this work advances our understanding of BMI and adds to the body of literature. Despite the fact that an increasing amount of research has demonstrated the antecedents of BMI, thus little emphasis has been presented on the linking mechanism between strategy, entrepreneurship, and BMI from the lens of Strategic Entrepreneurship Theory. Noteworthy, the study also aims to understand the influences of the external and internal drivers of the firm on BMI. Specifically, this research adds to the body of existing literature based on two perspectives. Firstly, in terms of the relationship between the firm’s internal capabilities, the results have found a significant positive relationship between entrepreneurial orientation and BMI. The positive relationship between entrepreneurial orientation and BMI provides new insight into the literature by implying that entrepreneurship and BMI are interrelated, thus backed the theoretical perspective of Foss and Saebi ( 2017 ). Furthermore, the empirical finding suggests that manufacturing SMEs are more likely to innovate their business model if they have a stronger entrepreneurial orientation. Moreover, the result has reduced the gap in the interrelationship between BMI and entrepreneurship, which has not received sufficient attention (Foss & Saebi, 2017 ; 2018 ). The finding also translated that established firms that exercise entrepreneurial orientation resulted in BMI, thus further supports and validated the previous work of Asemokha et al. ( 2019 ), which has proven that entrepreneurial orientation significantly influences BMI. Based on the literature review, only few studies have examined these relationships, which is a serious gap in this study. Therefore, the finding provides empirical evidence contributing to the extension of BMI literature where entrepreneurial orientation plays an essential predictor for BMI. Secondly, through the lens of Strategic Entrepreneurship Theory, this study extends research on the importance of conceptualization of the internal drivers of the firm which provides the answer to how entrepreneurial orientation can be associated with BMI. Hence, it is evidenced that entrepreneurial orientation is a strong antecedent of BMI. 5.2 Practical Implications Several practical implications have been derived from the study's findings that could offer valuable insights especially for practitioners such as policymakers, SME managers, academicians, and entrepreneurs. Firstly, the study have revealed important ramifications of entrepreneurial orientation toward BMI. In realizing this importance, policymakers should consider fostering knowledge of entrepreneurial culture within SMEs to ensure that they become more agile, responsive, and resilient when facing a crisis. Therefore, policy makers should identify this key factor to motivate SMEs to positively implement BMI for success especially at the start-up stage. Furthermore, SME Corporation Malaysia could also leverage the findings by emphasizing awareness and training programs for entrepreneurs, start-ups or as well as established firms on the importance of entrepreneurial orientation practices. This idea can be put forward as a foundation in the upcoming SME Masterplan or SME road map syllabus. Secondly, the empirical evidence from this study provides suggestions that also benefit SMEs and entrepreneurs. The results shows that SMEs’ internal capabilities, namely entrepreneurial orientation is relatively crucial for manufacturing SMEs to participate in changing their business model. It is further suggested that entrepreneurial orientation can help SME managers especially the manufacturers to develop their risk-taking, proactive and innovative ability to explore and exploit opportunities in a dynamic business environment and then initiate procedures and actions that promote BMI. Notwithstanding, SME managers might need to strengthen their internal capabilities to identify opportunities and advantages in the market. Thirdly, the literacy and understanding of BMI practices in Malaysia are still in their infancy. However, as a developing country with a robust, open and diversified economy, Malaysian SMEs can be expected to benefit from this study. Although BMI is still considered a new strategy for Malaysian business, most manufacturing SMEs involved in this study have shown that they have experience the practice of BMI. However, policy makers need more actions, especially the Ministry of Entrepreneur Development and Cooperatives (MEDAC) and the Ministry of Economic Affairs (MEA), to promote and create awareness to reap the full benefit of BMI. Finally, this study provides some empirical evidence that could be beneficial for academicians and entrepreneurs to understand the necessary factors that could influence SMEs to be engaged in BMI. 6. CONCLUSION Malaysian SMEs are confronting a constantly evolving global environment, particularly with regards to the COVID-19 pandemic recovery, political instability, inflation, globalization, and growing trends of digitalization that has impacted their fundamental ways of doing business. By staying ahead of the curve and anticipating changes in the marketplace, SMEs can adapt to new demands, seize fresh chances, and avoid potential pitfalls. As a result, prioritizing and supporting SMEs, especially those in the manufacturing sector are of crucial importance for ensuring their long-term sustainability and to guarantee that they continue to be strong in the face of the ever-changing global landscape. As such, prioritizing on this sector can help create a more focused and cohesive approach to Malaysia’s economic development and allows for a focused allocation of resources towards important areas with room to grow and develop significantly. Nonetheless, for the above reasons, this study was motivated and built upon the framework developed by Foss and Saebi ( 2017 ) based on the Strategic Entrepreneurship Theory (Hitt et al., 2001 ; Ireland et al., 2001 ) framework to shed light on the antecedents of BMI. Even though SMEs' strategic growth and the effects of various strategies on their performance have been the subject of several studies, thus limited studies were executed to empirically understand the external and internal drivers of manufacturing SMEs on BMI (Gatautis et al. 2019 ; Miroshnychenko et al., 2021 ). Regarding the clarity of the BMI construct, this study offers fresh perspective on the causes of BMI. Nevertheless, driven by uncertainty, strategic entrepreneurial firms, especially manufacturing SMEs require solid internal capabilities to be engaged in BMI. Finally, the study inspires future avenues for researchers to explore other vital dimensions or scopes of BMI and its drivers. 7. LIMITATIONS AND FUTURE RESEARCH Despite valuable insights offered in this study, it also comes with certain limitations, which set off potential areas and opportunities for future research avenues. This study's primary drawback is that it only focuses at Malaysian manufacturing SMEs. Since data were collected simply on manufacturing SMEs, therefore results obtained from this study do not represent the overall SME sectors in Malaysia, thus raising questions on the generalizability of the findings. Nonetheless, it is also possible that different results may be attained under other SME sectors, such as services or agriculture. Another limitation is the use of cross-sectional design, which is limited in its ability to fully comprehend the causal conclusions. Even if the study has several limitations, the results offer novel and significant insights into a deeper comprehension of the factors that influence or precede BMI. In spite of these limitations, this research provides several recommendations for future research avenues. Firstly, future studies may apply a mix-method interview and focus approach to obtain more informative data to reflect the generalized population. Future research could employ a mixed-method approach to provide a more thorough study; depending solely on quantitative data from closed-ended questions provides little insight into respondents' perceptions. Secondly, the results indicated that entrepreneurial orientation acts as a BMI driver which has a positive influence on BMI. Hence, prior literature also exposed diverse internal and external drivers that can be considered equally important to understanding BMI’s antecedents. For instance, Foss and Saebi ( 2017 ) proposed dynamic capabilities, change in strategy, open innovation, and servitization as the internal antecedents, while sustainability, change in competition, technologies, network position, and stakeholder demands as the external. Bashir and Verma ( 2019 ) suggested leadership, technology, organizational structure, culture, and inertia, while Asemokha et al. ( 2019 ) suggested market orientation or learning orientation as the spectrum of strategic orientations. Therefore, future studies may consider testing these constructs or other variables that may influence BMI practices in SMEs. Since the study of BMI is at an infant stage, examining these or other possible variables will enrich and develop new insights into the antecedents of BMI. In line with Miroshnychenko et al. ( 2021 ) and Gatautis et al. ( 2019 ), future studies should emphasis more on a wide-ranging list of BMI drivers that influence BMI practices in SMEs. 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13:21:42","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":164322,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8091090/v1/a898f0b23e65c17fcedb1892.html"},{"id":98230033,"identity":"75c70cff-0661-44e0-8fcb-43491f7ee1ed","added_by":"auto","created_at":"2025-12-15 13:21:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51435,"visible":true,"origin":"","legend":"\u003cp\u003eThe conceptual model\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8091090/v1/6c85230bfd94a06fc7148e8e.png"},{"id":101754189,"identity":"40f644f6-8f7a-44a6-b8ce-d4ca46ca84af","added_by":"auto","created_at":"2026-02-03 10:41:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":799446,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8091090/v1/0c86dfc6-338c-4a88-aecf-7463f7dbf1f9.pdf"},{"id":98230043,"identity":"040fae7f-85af-44cd-8110-f56812bf662a","added_by":"auto","created_at":"2025-12-15 13:21:41","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":40279,"visible":true,"origin":"","legend":"","description":"","filename":"1.Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8091090/v1/d7eaabe6749ebcf143ba400c.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThe Antecedents of Business Model Innovation in Malaysian Manufacturing SMES\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eSince the late 1970s, SMEs have contributed a significant role in Malaysia. Like other countries, SMEs are a substantial backbone of Malaysia\u0026rsquo;s economy and industrial development in providing jobs and growth opportunities (Amin et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; SME Governance Working Group, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). SMEs represent 97.4 per cent of the overall business establishments registered in 2024 (SME Governance Working Group, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Notwithstanding, SMEs also face many limitations and constraints in terms of resources, technologies, market access, and capabilities compared to their bigger rivals, such as multinational corporations (MNCs) and large firms. Despite having deficiencies in sizes, resources, and capabilities (Abdullah et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Songling et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), SMEs\u0026rsquo; contribution to the country\u0026rsquo;s economic growth has made it a popular subject among researchers (Abdullah et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Nevertheless, this study focuses on SMEs in the manufacturing sector in Malaysia. As described by Ho et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), the manufacturing sector plays a significant role in a country's economy, which motivates this study. Having said that, manufacturing SME business operations are associated with various aspects of innovation. As of August 2025, Malaysian manufacturing SMEs accounted for 5.3% percent 57,187 of all the country's SMEs (SME Corporation Malaysia, 2025).\u003c/p\u003e\u003cp\u003eIn high-cost operating environments, manufacturing SMEs are increasingly looking toward innovation to ensure their productivity growth, especially to achieve non-price-based competition. Although innovation has always been central to manufacturing, product and process innovation has always been a great challenge for SMEs because it involves high investment (Chin \u0026amp; Lim, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Moreover, a study conducted by Lim and Shyamala (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) indicated that manufacturing SMEs in Malaysia faced impediments to innovation due to costs, labor, risks, and financing that have hindered them from engaging in innovation activities. Lee and Lee (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) exposed that financial constraint is one of the severe factors that hamper manufacturing SMEs from being involved in innovation activities. An interesting finding by Chin and Lim (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) revealed that Malaysian manufacturing SMEs are less likely to be engaged in product and process innovation and are keen on non-technological innovations such as organizational and marketing innovation. Furthermore, according to Bashir and Verma (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), in a turbulent and unpredictable business environment, new products and process innovations do not always result in success. In this regard, it is interesting to unfold how manufacturing SMEs adopt and utilize their capabilities to modify or innovate business model.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 Business Model Innovation\u003c/h2\u003e\u003cp\u003eThroughout the years, research on BMI has increased significantly (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), thus gaining popularity and a growing interest among scholars and business strategists to decipher the triggers, predictors, antecedents, theories, practices, and outcomes of the phenomenon. Studies on BMI have spread across in different areas and disciplines, including innovation management, strategic management, and entrepreneurship (Schneider \u0026amp; Spieth, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Moreover, multiple studies and theories have attempted to explain the concept and definition of BMI. The agreement on BMI\u0026rsquo;s meaning and construct clarity still lacks underpinning theory and therefore requires more empirical testing (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe fundamentals and interpretation of BMI depend on how the concept of a business model is characterized and viewed. Similar to BMI, several studies have listed various definitions of business model and its component. The clear notion of a business model was emphasized by Teece (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), where the researcher defined it as the framework or structure of the value creation, delivery, and capture mechanisms that a firm employs. Another concrete definition was provided by Zott et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), where a business model is regarded as the overall relationship between elements such as value proposition, revenue model, and a network of relationships.\u003c/p\u003e\u003cp\u003eNonetheless, the most profound insight into the business model definition was proposed by Osterwalder (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The scholar has outlined the nine building blocks later known as the business model canvas (BMC). The nine elements are value proposition, target customer, distribution channel, relationship, value configuration, core competency, partner network, cost structure, and revenue model, which coined the comprehensive definition of business model. Based on these components, Osterwalder (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) described the term business model as a conceptual instrument that encompasses a collection of components and their interconnections and enables the articulation of a company's profit-making logic. It represents the value the firm has to offer to customers, the structure of the company and its collaborative network of partners to create revenue streams that are both profitable and sustainable, which form a unique blueprint of all the business operations of the firm.\u003c/p\u003e\u003cp\u003eThe novelty and closely integrated structure of the company makes it challenging for competitors and rivals to replicate the business model. Along with Teece\u0026rsquo;s (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) idea of the business model, Zott et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) emphasized that a business model does not stand alone. It consists of integration and interdependency among the elements. Most importantly, the business model has emerged into a new unit of analysis, thus explaining how value is created and how companies operate with a holistic approach (Zott et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBMI involves developing, reinventing, redesigning, refining, or replacing the current business model (Teece, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The adjustments or changes in the original business could involve one or more components, such as value proposition, channels, customer relationships, or revenue streams in the architecture. Thus, changes in one of the components will affect the other (Teece, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although this makes sense, to some scholars, BMI encompasses the transformation of the entire framework of the business model rather than focusing solely on a single or an individual component (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this regard, BMI and business model are interrelated. However, they are not to be used or applied interchangeably. BMI represents a new dimension or subject of innovation (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zott et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to Zott et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), BMI represents a new source of innovation. It enhances the conventional topics of process, product, and organizational innovation and entails new ways of working together and partnering. It also underlines the firm\u0026rsquo;s core attributes, similar to changes in product, structure, delivery, and process (Zott \u0026amp; Amit, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Nevertheless, a distinguishing characteristic of BMI from the traditional product or process innovation is something that cannot be simplified to, for example, not just technological advancements, but also encompasses the overall structure of the firm (Teece, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). According to Anwar (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), BMI is distinct from innovation in the sense that it enables SMEs on the spot when a new opportunity arises. Another important aspect for a firm to innovate its business model is understanding and sensing the customers\u0026rsquo; unmet needs.\u003c/p\u003e\u003cp\u003eDrawing upon Strategic Entrepreneurship Theory (SET), this research intends to investigate the key antecedents of BMI explicitly by assessing the relationship between the firms\u0026rsquo; external and internal drivers on BMI. It aims to provide a better understanding of what enables firms specially manufacturing SMEs to be engaged in BMI. Since there are significant gaps in the understanding of the drivers of BMI (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), results from this study will specifically reveal whether environmental dynamism, absorptive capacity, and entrepreneurial orientation make an important key predictor of BMI. These constructs were introduced based on the suggestions put forward by previous researchers.\u003c/p\u003e\u003cp\u003eConsequently, the findings provide solid empirical evidence on the enabling constructs that influence manufacturing SMEs to be engaged in innovating their business model, which was found to be scarce in the literature. In light of this, the findings extend knowledge on BMI construct clarity and provide new insightful results with the antecedents of BMI centered on the Strategic Entrepreneurship perspective. Based on the literature, only a limited number of studies have concerned the drivers and antecedents of BMI (Motjolopane \u0026amp; Ruhode, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), for instance in recent research carried out by Bhatti et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) on IT firms operating in Pakistan. Hence, the scarcity was also mentioned by Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), where it was found that there are gaps in the understanding of the antecedents of BMI. According to the researchers, the factors leading to BMI can differ in their characteristics and can be internal or external to the firm.\u003c/p\u003e\u003cp\u003eThere were few antecedents, or the drivers of BMI, that have been studied by prior researchers identified in the literature. In a recent study conducted by Faiz et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), digital leadership capabilities was identified as a significant driver influencing BMI, entrepreneurial passion was found to positively affects BMI (Dinibutun, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and Adomako (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) has proven that international orientation positively affects BMI. Despite these findings, other vital constructs could still be an important driver of BMI that has yet to be tested. The constructs include varied classifications of the number of internal and external BMI drivers (Gatautis et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which could be the drivers or enablers of BMI. For instance, Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) proposed open innovation, servitization, sustainability, stakeholders, and many more. Bashir and Verma (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) introduced five BMI drivers, that is leadership, technology, organizational structure, culture, and inertia.\u003c/p\u003e\u003cp\u003eNonetheless, this study presented environmental dynamism as the external, while absorptive capability and entrepreneurial orientation as the internal antecedents. In response, this study adds to the existing body of literature by enhancing the understanding of what enables manufacturing SMEs to conduct BMI. The relationship between BMI and its link between entrepreneurship, strategy, and performance has not received sufficient attention. Therefore, research on these relationships is warranted to understand better the impact of BMI on the performance of entrepreneurial firms (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe limited knowledge of the factors and reasons behind how SMEs innovate their business models has become a major concern among researchers (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Consequently, this study revealed BMI construct clarity, thus providing new insight into the antecedents' impact on BMI. Therefore, it is worthwhile to investigate these causal relationships from SMEs\u0026rsquo; point of view. Furthermore, the originality of this study addressed BMI from a holistic perspective through a synergistic influence of the firms\u0026rsquo; internal and external factors within the context of Strategic Entrepreneurship Theory.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Theoretical background\u003c/h2\u003e\u003cp\u003eIn this study, Strategic Entrepreneurship Theory was adopted to research on BMI. Strategic Entrepreneurship Theory explains how firms especially SMEs explore and exploit opportunities through internal capabilities and external opportunities when facing uncertainty must adapt to respond to altering sources of value creation by reconfiguring their existing business practices (Amit \u0026amp; Zott, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Schneider \u0026amp; Spieth, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In addition, Strategic Entrepreneurship Theory explicitly pays attention to the entrepreneurial action of established firms to provide additional insights to further enhance the understanding of BMI.\u003c/p\u003e\u003cp\u003eThe notion of Strategic Entrepreneurship is particularly suitable for studying contemporary firms where change has become constant, intermittent, rapid, and unpredictable. Driven by technological advancement and globalization, Strategic Entrepreneurship Theory was coined by Hitt et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) as a new entrepreneurial strategy for creating the most valuable entrepreneurial firms. Specifically, the theory implies firms identify and exploit entrepreneurial opportunities based on their internal capabilities and external environment as their core (Hitt et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Schneider \u0026amp; Spieth, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In this sense, applying Strategic Entrepreneurship Theory in the framework is able to answer what allows firms to perform BMI that requires additional attention.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. HYPOTHESES DEVELOPMENT","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.1 The relationship between environmental dynamism and BMI\u003c/h2\u003e\u003cp\u003eEnvironmental dynamism pertains to how quickly changes occur and the level of unpredictability within the environment (Dess \u0026amp; Beard, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). Jansen et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) describe environmental dynamism as technological changes, variations in customer preferences, changes in product demand or supply of materials, and the unpredictability of change. In addition, according to Jansen et al. (2005), rapidly changing environments render existing products and services outdated. Moreover, Chang et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) pointed out that dynamic market conditions might compel firms to participate simultaneously in exploitative and exploratory innovations. Thus, to remain competitive, firms need to shift from existing products, services, and markets through exploratory innovations to enhance their financial performance (Jansen et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Environmental dynamism was proven to influence innovation activity. Research carried out by Soto-Acosta et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) on Spanish manufacturing SMEs has shown that environmental dynamism was found to have a positive and significant impact on innovation ambidexterity. In this study, environmental dynamism was introduced in the research framework posited to have an influence on BMI, thus suggesting that manufacturing SMEs deploy ambidextrous innovations based on the external pressure of the environment.\u003c/p\u003e\u003cp\u003eMoreover, in advancing the BMI research, this importance was also addressed by Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) in their proposed causal web in which environmental dynamism could be an important antecedent of BMI that requires to be clarified, elaborated, and researched. Building on the above arguments, this study posits that dynamic environments influence manufacturing SMEs to be engaged in BMI practices. Therefore, the subsequent hypothesis is postulated.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e\u003cp\u003eEnvironmental dynamism is positively related to BMI.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.2 The relationship between absorptive capacity and BMI\u003c/h2\u003e\u003cp\u003eWhen facing uncertainty in a dynamic environment, the firm\u0026rsquo;s current knowledge may become obsolete and therefore needs continuous renewal. Hence, to achieve profitable innovations, firms require effective abilities to renew their knowledge base through acquisition, assimilation, and knowledge utilization (Jantunen, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). These abilities are what Cohen and Levinthal (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) coined as absorptive capacity.\u003c/p\u003e\u003cp\u003eAccording to Cohen and Levinthal (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), absorptive capacity relates to the firm's ability to identify or assess the value of new information by exploiting useful external knowledge from the environment, assimilating and then applying it to commercial ends. Zahra and George (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) have reconceptualized the definition of absorptive capacity that was introduced by Cohen and Levinthal (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) into a set of organizational routines and processes known as potential capacity (knowledge acquisition and assimilation) and realized capacity (knowledge transformation and exploitation).\u003c/p\u003e\u003cp\u003eThese routines and processes produce a dynamic organizational capability vital for the firm to achieve competitive advantage. Potential absorptive capacity allows a firm to be receptive to external knowledge, whereas realized absorptive capacity indicates its ability to utilize the acquired knowledge and convert it into innovative results (Zahra \u0026amp; George, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). According to Ramayah et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), the ability to exploit external knowledge is an essential element of innovative capabilities, and firms need to possess realized absorptive capacity to excel in innovation. A review of past literature shows that most of the studies on absorptive capacity are related to innovation (Zou et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Thus, most empirical studies have revealed a significant relationship between absorptive capacity and innovation. A study by Ramayah et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) has shown that absorptive capacity served as a significant indicator of innovation performance (product and process innovation) among manufacturing firms in Malaysia. Similarly, according to Zou et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), absorptive capacity is a significant indicator of innovation.\u003c/p\u003e\u003cp\u003eWhile numerous studies have examined the relationship between absorptive capacity and innovation (Zou et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), there is still limited cause-and-effect research found in the literature to understand the influence between the construct and BMI. Therefore, to fill this gap, absorptive capacity was introduced as an important internal driver in the current study research framework that could influence manufacturing SMEs to innovate their business model. Following Jantunen (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), the absorptive capacity construct applied in this study is characterized based on the three dimensions that are knowledge acquisition, dissemination and utilization. In this study, absorptive capacity was viewed as a higher-order construct to investigate how manufacturing SMEs exploit new knowledge gathered and acquired from their external environment for value creation (Ramayah et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Valentina \u0026amp; Passiante, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zahra \u0026amp; George, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNonetheless, this study will provide an empirical understanding of whether absorptive capacity promotes manufacturing SMEs to search for new knowledge and increases their ability to make the necessary changes in their business model. Henceforth, based on prior studies and grounded on these arguments, this study posits that absorptive capacity influences manufacturing SMEs to innovate their business model and consequently results in the formulation of the following hypothesis:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e\u003cp\u003eAbsorptive capacity is positively related to BMI.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 The relationship between entrepreneurial orientation and BMI\u003c/h2\u003e\u003cp\u003eAccording to Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), entrepreneurship is intrinsically associated to BMI, where the connection is tightly associated with entrepreneurial vision, imagination, and judgment. Notably, Schneider and Spieth (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) outlined that entrepreneurial actions are essential when firms seek to innovate their business model.\u003c/p\u003e\u003cp\u003eEntrepreneurial orientation was initially coined by Miller (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) which include three dimensions that is innovativeness, risk-taking and proactiveness. As the advancement of strategic management study, the concept of entrepreneurship has shifted towards the study of entrepreneurial orientation. Expanding from this concept, along with Miller\u0026rsquo;s (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) three entrepreneurial dimensions, Lumpkin and Dess (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) have drawn on extensive research by characterizing entrepreneurial orientation by adding two other dimensions, namely competitive aggressiveness and autonomy.\u003c/p\u003e\u003cp\u003eAlthough all the five dimensions itemized by Lumpkin and Dess (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) are considered comprehensive, there is no consensus in the literature concerning the dimension of entrepreneurial orientation (Martin \u0026amp; Javalgi, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For instance, to some researchers like Jantunen et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), Wiklund (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), and Covin and Slevin (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), entrepreneurial orientation is represented as a one-dimension construct, while to others such as Ferreira et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Covin and Miller (2014), Lee and Lim (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), and Hughes and Morgan (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) it has been viewed as a multidimensional construct.\u003c/p\u003e\u003cp\u003eIn this study, the entrepreneurial orientation construct was viewed and conceptualized following Jantunen et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), succeeding the original concept of Miller (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) and Covin and Slevin (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), which consists of innovativeness, proactiveness and risk-taking dimensions. Prior studies have shown that entrepreneurial orientation led to BMI. Asemokha et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) have identified a significant relationship between entrepreneurial orientation and BMI based on an industrial sample of 95 international SMEs in Finland. According to Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), BMI research may be advanced by drawing on theorizing in the entrepreneurship streams, which can help meet the gaps in the BMI literature because the close interrelationship between BMI and entrepreneurship is scarce and has not received sufficient attention (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTherefore, based on strategic entrepreneurship theory, this study anticipated that, in facing uncertainty in the environment, manufacturing SMEs with a higher level of risk-taking, innovativeness, and proactiveness would enable them to explore opportunities and exercise innovative changes in their business model. Accordingly, entrepreneurial orientation was presented as an internal driver in the research framework to examine whether the particular construct significantly affects BMI. Hence, based on these arguments, it is hypothesized that:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eH3\u003c/strong\u003e\u003cp\u003eEntrepreneurial orientation is positively related to BMI.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eGuided by the Strategic Entrepreneurship Theory framework, the conceptual model for this study is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Insert\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ehere)\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. METHODS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Sample and data collection\u003c/h2\u003e\u003cp\u003eIn this study, primary data were collected using a cross-sectional survey method. Based on this approach, the data collection process was conducted over a short timeframe only once (Bougie \u0026amp; Sekaran, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Christensen et al., 2015). In selecting the right sample for this study, a judgment purposive non-probability sampling was applied. The targeted population encompasses Malaysian SMEs involved in the manufacturing sector, with a total of 75,684 population. Notwithstanding, this study employed the classification of manufacturing industries following the categorization set by the Organisation for Economic Co-operation and Development (2011), which ranges from high-technology sectors such as pharmaceuticals to low-technology industries like food and beverage products.\u003c/p\u003e\u003cp\u003eBased on the current definition provided by SME Corporation Malaysia (2017), Malaysian manufacturing SMEs are defined as firms of having annual sales turnover (total revenue including other incomes) not exceeding RM50\u0026nbsp;million or having a total number of full-time employees not exceeding 200 workers. For a firm to be classified as a manufacturing SME in Malaysia, a business must only satisfy one of the two qualifying criteria used in the definition, or whichever is lower. Therefore, the definition of manufacturing SMEs strictly follow the above criteria and classification.\u003c/p\u003e\u003cp\u003eThe sampling data were from various local manufacturing industries such as The Federation of Malaysian Manufacturers (FMM), Malaysia External Trade Development Corporation (MATRADE), and the Ministry of Entrepreneur Development and Cooperatives (MEDAC) company directory lists. Data were collected from a single key informant from each identified manufacturing SME through judgment sampling design. The targeted respondents are mainly top executives, specifically the senior or upper management level, preferably the Managers or Chief Executive Officers (CEOs) who may have critical information and knowledge about the company\u0026rsquo;s operation. Following Foss and Saebi (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), top management was viewed as the central monitor of a firm that plays an essential position in making sure the implementation of BMI.\u003c/p\u003e\u003cp\u003eA self-administered closed-ended questionnaires were designed and applied to collect the required data. Before disseminating the questionnaires, the research ethics clearance was attained from the Universiti of Malaya Research Ethics Committee (UMREC). UMREC\u0026rsquo;s consent is necessary to undertake an ethics review to ensure that the research components, such as the methodology are carried out soundly, and any possible risks to the subjects are mitigated and handled with diligence.\u003c/p\u003e\u003cp\u003eDetermining the proper sample size is critical when employing survey research. Hair et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e) recommended that power analysis to be utilized to establish the necessary sample size for a study that applied PLS-SEM. Using power analysis, the minimum sample size can be determined by accounting for the maximum number of predictors drawn in the research model (Hair et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The calculation requires information on effect size, significance level (α) and sample size to compute the minimum sample size requirement (Hair et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Following Hair et al.\u0026rsquo;s (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) recommendation, G*Power (Faul et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) version 3.1.9.7 was employed to compute the sample size required for this study.\u003c/p\u003e\u003cp\u003eThe calculation for the minimum size requirement for this study was done following the most recommended settings for conducting social and business science research (Hair et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Memon et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Based on the G*Power computation, the minimum sample size required for this study is 92.\u003c/p\u003e\u003cp\u003eAlthough the minimum sample size has been identified and since conducting surveys among SMEs tends to suffer from low response rates (Dennis Jr., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), therefore, to increase the response rate of this study, 800 questionnaires were distributed. Bougie and Sekaran (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) recommended that a 30 per cent response rate is acceptable and exceptional. Thus, in ensuring optimum results, this study goes along with Memon et al.\u0026rsquo;s (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) suggestion that a sample size between 160 and 300 is the most appropriate for multivariate statistical analysis, especially for PLS-SEM. Considering the G*Power result analysis, Bougie and Sekaran\u0026rsquo;s (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Memon et al.\u0026rsquo;s (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) suggestion, this study has collected 282 usable responses (35.25% effective response rate).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Measures\u003c/h2\u003e\u003cp\u003eThe standard measurements utilized in the questionnaire were adapted and derived based on the original scales developed by the previous researchers, which have been validated and applied in numerous studies. As this study aims to understand the antecedents of BMI, the unit of analysis is the firm or organizational level. Environmental dynamism was assessed using a 7-point Likert scale developed by Jansen et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) consisting of five items. Based on the original scale, environmental dynamism was measured using statements anchored from 1 (strongly disagree) to 7 (strongly agree).\u003c/p\u003e\u003cp\u003eAbsorptive capacity was assessed using a 7-point Likert scale developed by Jantunen (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) consisting of 16 items. Based on the original scale, absorptive capacity was measured using statements anchored from 1 (strongly disagree) to 7 (strongly agree). Entrepreneurial orientation was assessed using a 7-point Likert scale developed by Jantunen et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) consisting of nine items. Based on the original scale, entrepreneurial orientation was measured using statements anchored from 1 (strongly disagree) to 7 (strongly agree). BMI was measured using the scale developed by Guo et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The 5-point Likert scale consisting of nine items was developed based on the work by Zott and Amit (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The scale ranging from 1 (strongly disagree) to 5 (strongly agree).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. RESULTS","content":"\u003cp\u003e4.1 \u0026nbsp; \u0026nbsp; \u0026nbsp; Demographic profile of the respondents.\u003c/p\u003e\n\u003cp\u003eThe demographic profile shows that the majority 63.8 per cent of the manufacturing SMEs that partook in this study were from the low-technology industry (wood, pulp, paper, food, beverages, tobacco, textiles, leather, and footwear products). Notably, private limited manufacturing SMEs formed 57.1 per cent of the majority of respondents and are mostly small in size, with annual sales of RM300,000 to RM15 million with full-time employees ranging from 5 to 75. It is observed that 44.3 per cent of the respondents have been operating for 6 to 10 years, 63.1 per cent were in urban, and 58.2 per cent were managers. Astoundingly, only 2.1 per cent of the respondents were unfamiliar with the term business model, which indicates their high literacy of the study theme.\u003c/p\u003e\n\u003cp\u003e4.2 \u0026nbsp; \u0026nbsp; \u0026nbsp; Data analysis\u003c/p\u003e\n\u003cp\u003ePartial Least Squares Structural Equation Modelling (PLS-SEM) using the SmartPLS software version 3.3.7 (Ringle et al., 2015) was employed to examine the measurement and structural model of this study. Hair et al. (2019a; 2019b) emphasized that the benefits of utilizing PLS-SEM include, it can handle small sample size data and non-normally distributed data. Given that the data was gathered from a single source,\u0026nbsp;Common Method Bias (CMB) constitutes a significant concern (Podsakoff et al., 2003). Therefore, CMB was addressed by testing the full collinearity adhering to the recommendations by Kock and Lynn (2012) and Kock (2015). In this approach, each variable was regressed against a common variable. If the VIF values is \u0026le; 3.3, then CMB is not present. The analysis indicated a VIF of less than 3.3; thus, confirmed that CMB was not a threat (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Insert Table 1 here)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e4.2.1 \u0026nbsp; \u0026nbsp;Measurement model\u003c/p\u003e\n\u003cp\u003eThe measurement model was tested following the two-step method recommended by Anderson and Gerbing (1988). Firstly, the convergent validity was performed to assess the validity and reliability of the measurement model. The loadings, average variance extracted (AVE), and the composite reliability (CR), were assessed following Hair et al. (2019a) and Ramayah et al. (2018). The values of loadings should be \u0026ge; 0.5, AVE should be \u0026ge; 0.5, and the CR should be \u0026ge; 0.7. As shown in \u003cstrong\u003eTable 2,\u0026nbsp;\u003c/strong\u003ethe AVEs were all higher than 0.5, and the CRs were all higher than 0.7. Ten items that were found to have low loadings were removed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Insert Table 2 here\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAs shown in \u003cstrong\u003eTable 2\u003c/strong\u003e, absorptive capacity in this study represents a second-order construct Type I (reflective-reflective) where the loadings of knowledge acquisition, knowledge dissemination, and knowledge utilization measured the AVE and CR. Based on the analysis, the second-order measurements were also valid and reliable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecondly, the discriminant validity using the Heterotrait Monotrait Ratio of Correlations (HTMT) criterion was performed based on Henseler et al.\u0026rsquo;s (2015) recommendation and Franke and Sarstedt (2019) updated. The HTMT values should be \u0026le; 0.85 (stricter criterion) or \u0026le; 0.90 (lenient criterion). As shown in \u003cstrong\u003eTable 3\u003c/strong\u003e, all the HTMT values were lower than 0.85, thus conclude that the respondents understood that all the four constructs were distinct. Based on the results, it shows that the measurement items were both valid and reliable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Insert Table 3 here)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e4.2.2 \u0026nbsp; \u0026nbsp;Structural model\u003c/p\u003e\n\u003cp\u003eNext, the evaluation of structural models was performed. The assessment determines the model\u0026rsquo;s capabilities to forecast one or more target constructs (Hair et al., 2017). In response to the recommendations of Hair et al. (2019a) and Ramayah et al. (2018), the path coefficients (\u0026beta;), standard errors, t-values, and p-values for the structural model using a 5,000-sample re-sample bootstrapping procedure were reported. Nonetheless, in light of the criticism of Hahn and Ang (2017), who have contended that \u003cem\u003ep\u003c/em\u003e-values are not an adequate benchmark for assessing the significance of hypotheses; instead, a blend of criteria like \u0026nbsp;\u003cem\u003ep\u003c/em\u003e-values, confidence intervals, and effect sizes (f\u003csup\u003e2\u003c/sup\u003e) was implemented. \u003cstrong\u003eTable 4\u003c/strong\u003e shows the outcomes of the hypothesis testing. Next, the impact of the three predictors on BMI was evaluated, where the value of R\u003csup\u003e2\u003c/sup\u003e was 0.251 (Q\u003csup\u003e2\u003c/sup\u003e = 0.121). This indicates that all the three predictors were accounted for 25.1% of the variance in BMI, thus indicating a moderate model. Thus, it was found that only entrepreneurial orientation (\u003cem\u003e\u0026beta;\u003c/em\u003e = 0.264, p \u0026lt; 0.01) is positively related to BMI, thus give support for H3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Insert Table 4 here)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eSubsequently, the predictive relevance (Q\u003csup\u003e2\u003c/sup\u003e) of the model was evaluated through the blindfolding method in SmartPLS, where the omission distance (\u003cem\u003eD\u003c/em\u003e) value of eight (8) was selected. If Q\u003csup\u003e2\u003c/sup\u003e \u0026gt; 0, the model has demonstrated predictive relevance for a specific endogenous construct (Hair et al., 2017; 2019a). The Q\u003csup\u003e2\u003c/sup\u003e value for BMI (Q\u003csup\u003e2\u003c/sup\u003e = 0.121) are greater than 0, thus indicating that the model possesses sufficient predictive relevance.\u0026nbsp;\u003c/p\u003e"},{"header":"5. DISCUSSION","content":"\u003cp\u003eThis study provides insight on the antecedents of BMI. Although there are few existing literatures that have been doing similar research, however, there are still lacking of understanding on what drives firms to be involved in BMI especially in relation to manufacturing SMEs in Malaysia. The lack of empirical studies on BMI (Heikkil\u0026auml; \u0026amp; Bowman, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Randhawa et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and its driver (Gatautis et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Miroshnychenko et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) have motivated this study. This research adds to the body of knowledge on strategy and entrepreneurship by looking into the effects of the external and internal drivers on BMI. The study's conclusions are captivating to scholars and professionals alike. The study's theoretical and practical consequences are shown in the following.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Theoretical implications\u003c/h2\u003e\u003cp\u003eFrom a theoretical perspective, this work advances our understanding of BMI and adds to the body of literature. Despite the fact that an increasing amount of research has demonstrated the antecedents of BMI, thus little emphasis has been presented on the linking mechanism between strategy, entrepreneurship, and BMI from the lens of Strategic Entrepreneurship Theory. Noteworthy, the study also aims to understand the influences of the external and internal drivers of the firm on BMI.\u003c/p\u003e\u003cp\u003eSpecifically, this research adds to the body of existing literature based on two perspectives. Firstly, in terms of the relationship between the firm\u0026rsquo;s internal capabilities, the results have found a significant positive relationship between entrepreneurial orientation and BMI. The positive relationship between entrepreneurial orientation and BMI provides new insight into the literature by implying that entrepreneurship and BMI are interrelated, thus backed the theoretical perspective of Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, the empirical finding suggests that manufacturing SMEs are more likely to innovate their business model if they have a stronger entrepreneurial orientation. Moreover, the result has reduced the gap in the interrelationship between BMI and entrepreneurship, which has not received sufficient attention (Foss \u0026amp; Saebi, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe finding also translated that established firms that exercise entrepreneurial orientation resulted in BMI, thus further supports and validated the previous work of Asemokha et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which has proven that entrepreneurial orientation significantly influences BMI. Based on the literature review, only few studies have examined these relationships, which is a serious gap in this study. Therefore, the finding provides empirical evidence contributing to the extension of BMI literature where entrepreneurial orientation plays an essential predictor for BMI. Secondly, through the lens of Strategic Entrepreneurship Theory, this study extends research on the importance of conceptualization of the internal drivers of the firm which provides the answer to how entrepreneurial orientation can be associated with BMI. Hence, it is evidenced that entrepreneurial orientation is a strong antecedent of BMI.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Practical Implications\u003c/h2\u003e\u003cp\u003eSeveral practical implications have been derived from the study's findings that could offer valuable insights especially for practitioners such as policymakers, SME managers, academicians, and entrepreneurs. Firstly, the study have revealed important ramifications of entrepreneurial orientation toward BMI. In realizing this importance, policymakers should consider fostering knowledge of entrepreneurial culture within SMEs to ensure that they become more agile, responsive, and resilient when facing a crisis.\u003c/p\u003e\u003cp\u003eTherefore, policy makers should identify this key factor to motivate SMEs to positively implement BMI for success especially at the start-up stage. Furthermore, SME Corporation Malaysia could also leverage the findings by emphasizing awareness and training programs for entrepreneurs, start-ups or as well as established firms on the importance of entrepreneurial orientation practices. This idea can be put forward as a foundation in the upcoming SME Masterplan or SME road map syllabus.\u003c/p\u003e\u003cp\u003eSecondly, the empirical evidence from this study provides suggestions that also benefit SMEs and entrepreneurs. The results shows that SMEs\u0026rsquo; internal capabilities, namely entrepreneurial orientation is relatively crucial for manufacturing SMEs to participate in changing their business model. It is further suggested that entrepreneurial orientation can help SME managers especially the manufacturers to develop their risk-taking, proactive and innovative ability to explore and exploit opportunities in a dynamic business environment and then initiate procedures and actions that promote BMI. Notwithstanding, SME managers might need to strengthen their internal capabilities to identify opportunities and advantages in the market.\u003c/p\u003e\u003cp\u003eThirdly, the literacy and understanding of BMI practices in Malaysia are still in their infancy. However, as a developing country with a robust, open and diversified economy, Malaysian SMEs can be expected to benefit from this study. Although BMI is still considered a new strategy for Malaysian business, most manufacturing SMEs involved in this study have shown that they have experience the practice of BMI.\u003c/p\u003e\u003cp\u003eHowever, policy makers need more actions, especially the Ministry of Entrepreneur Development and Cooperatives (MEDAC) and the Ministry of Economic Affairs (MEA), to promote and create awareness to reap the full benefit of BMI. Finally, this study provides some empirical evidence that could be beneficial for academicians and entrepreneurs to understand the necessary factors that could influence SMEs to be engaged in BMI.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. CONCLUSION","content":"\u003cp\u003eMalaysian SMEs are confronting a constantly evolving global environment, particularly with regards to the COVID-19 pandemic recovery, political instability, inflation, globalization, and growing trends of digitalization that has impacted their fundamental ways of doing business. By staying ahead of the curve and anticipating changes in the marketplace, SMEs can adapt to new demands, seize fresh chances, and avoid potential pitfalls. As a result, prioritizing and supporting SMEs, especially those in the manufacturing sector are of crucial importance for ensuring their long-term sustainability and to guarantee that they continue to be strong in the face of the ever-changing global landscape. As such, prioritizing on this sector can help create a more focused and cohesive approach to Malaysia\u0026rsquo;s economic development and allows for a focused allocation of resources towards important areas with room to grow and develop significantly.\u003c/p\u003e\u003cp\u003eNonetheless, for the above reasons, this study was motivated and built upon the framework developed by Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) based on the Strategic Entrepreneurship Theory (Hitt et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Ireland et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) framework to shed light on the antecedents of BMI. Even though SMEs' strategic growth and the effects of various strategies on their performance have been the subject of several studies, thus limited studies were executed to empirically understand the external and internal drivers of manufacturing SMEs on BMI (Gatautis et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Miroshnychenko et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regarding the clarity of the BMI construct, this study offers fresh perspective on the causes of BMI. Nevertheless, driven by uncertainty, strategic entrepreneurial firms, especially manufacturing SMEs require solid internal capabilities to be engaged in BMI. Finally, the study inspires future avenues for researchers to explore other vital dimensions or scopes of BMI and its drivers.\u003c/p\u003e"},{"header":"7. LIMITATIONS AND FUTURE RESEARCH","content":"\u003cp\u003eDespite valuable insights offered in this study, it also comes with certain limitations, which set off potential areas and opportunities for future research avenues. This study's primary drawback is that it only focuses at Malaysian manufacturing SMEs. Since data were collected simply on manufacturing SMEs, therefore results obtained from this study do not represent the overall SME sectors in Malaysia, thus raising questions on the generalizability of the findings. Nonetheless, it is also possible that different results may be attained under other SME sectors, such as services or agriculture. Another limitation is the use of cross-sectional design, which is limited in its ability to fully comprehend the causal conclusions. Even if the study has several limitations, the results offer novel and significant insights into a deeper comprehension of the factors that influence or precede BMI.\u003c/p\u003e\u003cp\u003eIn spite of these limitations, this research provides several recommendations for future research avenues. Firstly, future studies may apply a mix-method interview and focus approach to obtain more informative data to reflect the generalized population. Future research could employ a mixed-method approach to provide a more thorough study; depending solely on quantitative data from closed-ended questions provides little insight into respondents' perceptions.\u003c/p\u003e\u003cp\u003eSecondly, the results indicated that entrepreneurial orientation acts as a BMI driver which has a positive influence on BMI. Hence, prior literature also exposed diverse internal and external drivers that can be considered equally important to understanding BMI\u0026rsquo;s antecedents. For instance, Foss and Saebi (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) proposed dynamic capabilities, change in strategy, open innovation, and servitization as the internal antecedents, while sustainability, change in competition, technologies, network position, and stakeholder demands as the external. Bashir and Verma (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) suggested leadership, technology, organizational structure, culture, and inertia, while Asemokha et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) suggested market orientation or learning orientation as the spectrum of strategic orientations. Therefore, future studies may consider testing these constructs or other variables that may influence BMI practices in SMEs. Since the study of BMI is at an infant stage, examining these or other possible variables will enrich and develop new insights into the antecedents of BMI.\u003c/p\u003e\u003cp\u003eIn line with Miroshnychenko et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Gatautis et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), future studies should emphasis more on a wide-ranging list of BMI drivers that influence BMI practices in SMEs. Finally, future research may consider assessing the mediating effect of BMI between the internal and external drivers and its outcome.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e Ong Lin Dar acknowledges the support of the Universiti Malaya Grant by the European Union, \u003cstrong\u003eUMG023I-2024\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndra Sumantri Eddie Mat Senal:\u003c/strong\u003e Conceptualization, Methodology, Investigation, Data Curation, Writing \u0026ndash; Original Draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOng Lin Dar (Corresponding Author):\u003c/strong\u003e Conceptualization, Methodology, Validation, Resources, Writing \u0026ndash; Review \u0026amp; Editing, Supervision, Project Administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLee Su Teng:\u003c/strong\u003e Methodology, Formal Analysis, Validation, Writing \u0026ndash; Review \u0026amp; Editing, Visualization.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdullah, N., Halim, N. 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The capacity to innovate: A meta-analysis of absorptive capacity. \u003cem\u003eInnovation\u003c/em\u003e, 20(2), 87\u0026ndash;121. https://doi.org/gg3k6m.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Business model innovation, Environmental dynamism, Absorptive capacity, Entrepreneurial orientation, Antecedents of business model innovation","lastPublishedDoi":"10.21203/rs.3.rs-8091090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8091090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the past few years, there has been a growing interest from academics and practitioners in understanding the factors that affect business model innovation (BMI). Nevertheless, there remains a lack of understanding of what drives SMEs to be engaged in BMI. Drawing upon the Strategic Entrepreneurship Theory (SET), the aim of this research is to examine the effect of the external and internal drivers of manufacturing SMEs on BMI. These factors include environmental dynamism, absorptive capacity, and entrepreneurial orientation. The data were collected from 282 manufacturing SME managers in Malaysia using a quantitative survey method. The Partial Least Squares (PLS) modeling technique was utilized to examine the data. The findings revealed that entrepreneurial orientation is positively related to BMI, while environmental dynamism and absorptive capacity have shown adverse results. The findings imply that entrepreneurial orientation is an important factor influencing manufacturing SMEs to be engaged in BMI. Hence, the results suggested that BMI in manufacturing SMEs significantly depends on its entrepreneurial activities which changes its core business processes. This study builds upon existing research by examining the factors that influence BMI in small and medium-sized manufacturing enterprises.\u003c/p\u003e","manuscriptTitle":"The Antecedents of Business Model Innovation in Malaysian Manufacturing SMES","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 13:21:33","doi":"10.21203/rs.3.rs-8091090/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5ec76d83-78bb-4d21-9c47-ab914ae7b15f","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T22:15:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 13:21:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8091090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8091090","identity":"rs-8091090","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}