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This study aims to examine the factors (Stimuli) enhancing perceived utilitarian, social and conditional values (Organisms) of social commerce (s-commerce) platforms and their impact on small and medium enterprises’ (SMEs’) behavioral intention (Response) to adopt s-commerce.

Survey data were gathered from 304 Indian SMEs using s-commerce platforms. Data were analyzed using SmartPLS 3 software.

The results indicated that perceived values significantly impact SMEs’ behavioral intention to adopt s-commerce. Among conditional, utilitarian and social values, the conditional value of s-commerce sites was found to be the strongest motivator for SMEs to adopt s-commerce.

This research contributes to the growing literature on s-commerce, explaining how perceived value influences the decision of SMEs to adopt s-commerce platforms.

Among the significant influencers, perceived usefulness and perceived reputation were found to be the most effective triggers that stimulate perceived values of s-commerce sites. The findings draw due attention from policymakers toward environmental cues such as the legal and regulatory environment, which are instrumental in creating the most important perceived value for SMEs, i.e. conditional value.

By employing the inputs from the theory of consumption values and the Stimulus-Organism-Response framework, this original study looked beyond the technology factors and examined the role of perceived values of s-commerce platforms in shaping SMEs’ behavioral intention to adopt.

The aim of this study is to evaluate Big Data Analytics (BDA) drivers in the context of food supply chains (FSC) for transition to a Circular Economy (CE) and Sustainable Operations Management (SOM).

Ten different BDA drivers in FSC are examined for transition to CE; these are Supply Chains (SC) Visibility, Operations Efficiency, Information Management and Technology, Collaborations between SC partners, Data-driven innovation, Demand management and Production Planning, Talent Management, Organizational Commitment, Management Team Capability and Governmental Incentive. An interpretive structural modelling (ISM) methodology is used to indicate the relationships between identified drivers to stimulate transition to CE and SOM. Drivers and pair-wise interactions between these drivers are developed by semi-structured interviews with a number of experts from industry and academia.

The results show that Information Management and Technology, Governmental Incentive and Management Team Capability drivers are classified as independent factors; Organizational Commitment and Operations Efficiency are categorized as dependent factors. SC Visibility, Data-driven innovation, Demand management and Production Planning, Talent Management and Collaborations between SC partners can be classified as linkage factors. It can be concluded that Governmental Incentive is the most fundamental driver to achieve BDA applications in FSC transition from linearity to CE and SOM. In addition, Operations Efficiency, Collaborations between SC partners and Organizational Commitment are key BDA drivers in FSC for transition to CE and SOM.

The interactions between these drivers will provide benefits to both industry and academia in prioritizing and understanding these drivers more thoroughly when implementing BDA based on a range of factors. This study will provide valuable insights. The results from this study will help in drawing up regulations to prevent food fraud, implementing laws concerning government incentives, reducing food loss and waste, increasing tracing and traceability, providing training activities to improve knowledge about BDA and focusing more on data analytics.

The main contribution of the study is to analyze BDA drivers in the context of FSC for transition to CE and SOM. This study is unique in examining these BDA drivers based on FSC. We hope to find sustainable solutions to minimize losses or other negative impacts on these SC.

The authors originally explore the factors for blockchain technology (BCT) adoption in agricultural supply chains (ASCs) to enhance circularity and understand the dependencies, hierarchical structure and causalities between these factors.

Based on an extant literature review and expert opinion, the present study identified ten enablers for adopting BCT to leverage the circular economy (CE) practices in the ASCs. Then, using an integrated interpretive structural modeling and decision-making trial and evaluation laboratory (ISM-DEMATEL) approach, hierarchical and cause–effect relationships are established.

It was observed that traceability is the most prominent enabler from the CE perspective in ASCs. However, traceability, being a net effect enabler, will be realized through the achievement of other cause enablers, such as seamless connectivity and information flow and decentralized and distributed ledger technology. The authors also propose a 12 Rs framework for enhancing circularity in ASC operations.

The paper identifies enablers to BCT adoption that will enhance circularity in ASC operations. The ISM hierarchical model is based on the driving and dependence powers of the enablers, and DEMATEL aids in identifying causal relationships among the enablers.

The study's findings and proposed 12 Rs framework may help the practitioners and policymakers devise effective BCT implementation strategies in ASCs, thereby empowering sustainability and circularity.

This study enriches the literature by identifying and modeling enablers for BCT adoption in ASCs. The study also proposes a new 12 Rs framework to help enhance ASC circularity.