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Technology uptake in supply chains frequently encounters challenges when immediate, tangible benefits are not evident. Therefore, this article's central objective is to pinpoint the risks affecting the integration of supply chain technologies for enduring outcomes. Subsequently, these risks will be organized into a hierarchical structure, facilitating a clearer comprehension of their direct and indirect interconnections.

A combined TISM and quantitative approach has been used to build the hierarchal structure and to validate the direct, and indirect relationship among risks adopting supply chain technologies. A total of 41 respondents participated in the TISM survey, which resulted in creating a level hierarchical structure. Further, 233 responses are used for the quantitative study using SEM to validate the model obtained from TISM.

The study's findings indicated the social risks come out with the highest driving power. This includes the fear of job displacement, community disparity and change in the work culture of an organization. At the same time, technological risks can cause system integration, scalability issues, obsolesce compatibility issues, system failures and supply chain sustainability issues.

The novelty of the study can be found in the developed framework and its subsequent confirmation via quantitative evaluation. TISM provides the theoretical foundation, while a quantitative investigation is carried out to verify this theory.

This study aims to explore the key drivers contributing to supply chain resilience, with specific attention on agility, absorptive capacity and ambidexterity. It focuses on the roles of supply chain absorptive capacity (SCAC), supply chain ambidexterity (SCAB), supply chain agility (SCAG) and supply chain flexibility (SCF) in enhancing supply chain resilience (SCR).

A survey based on a questionnaire with established scales for SCAC, SCAB, SCAG, SCF and SCR was conducted among professionals in various industries within India, receiving 356 responses. Structural equation modeling is used to test the hypothesis.

The study reveals significant relationships between SCAC, SCAB, SCAG and SCR. SCAC and SCAB are positively correlated with SCAG, which in turn positively influences SCR. Further, SCF directly influences SCR and moderates the relationships between SCAC/SCAB and SCAG, enhancing the agility and resilience of the supply chain. These findings underline the importance of integrating knowledge management, adaptability and flexibility in supply chain strategies to cope with the dynamic business environment.

The uniqueness of this study lies in its integrated investigation of absorptive capacity, ambidexterity, agility and supply chain flexibility, with a specific focus on the moderating role of flexibility. This research is unique in demonstrating how these dynamic capabilities transform disruptions into innovative and growth opportunities for supply chain management.

Agriculture is a vital sector for every country, especially for a country like India, where the majority of the population is dependent on agriculture as their earning source. Technological improvements in agriculture will increase output with proper forecasting of input resources. In this study, the author tries to investigate the attitude of end users (farmers) about the use of Industry 4.0 (I4.0) technologies.

The unified theory of acceptance and use of technology (UTAUT) model is used to assess the behavioral aspects. The significance of socioeconomic and technological factors is highlighted, providing the study with a thorough understanding of farmers' decision-making processes. A research questionnaire was developed for data collection, and descriptive and inferential statistics were used to analyse the results using AMOS and SPSS software.

A total of 371 survey responses were collected. The results demonstrate that the hypothesis regarding UTAUT model components is validated, while several mediating hypotheses are not supported, indicating that they are not significant in farmers' decision-making.

In this study, socioeconomic and technological factors are considered to be mediating and moderating elements between the constructs of the UTAUT model. Increasing the accuracy and reliability of our study by integrating mediating and moderating variables. This study assists industry specialists in understanding the elements that farmers consider while switching toward new technologies.

The purpose of this study is to examine the impact of sustainable supply chain management (SSCM) practices on both competitive advantage (CA) and organizational performance (OP) in the manufacturing sector in Ethiopia.

Data for the study were collected from a sample of 221 manufacturing companies operating in the four manufacturing groups/sectors in Ethiopia. In addition, data analysis was performed using the partial least squares method, which is a variance-based Structural Equation Modeling approach in the Smart-PLS software version (SmartPLS 4.0).

Based on the statistical analysis of the collected data, it demonstrates that SSCM has a significant and positive impact on both competitive advantage and organizational performance. Furthermore, statistical findings offer proof of the clear connection between competitive advantage and organizational performance. Moreover, competitive advantage indirectly mediates the relationship between SSCM and OP.

The primary limitation of this research is its reliance on a cross-sectional design. The generalizability of the findings obtained from the present study may be hindered. The variable under investigation in this research assessed organizational performance, a concept that is widely acknowledged to be extremely dynamic.

The study provides managers and researchers with valuable information on Sustainable Supply Chain Management strategies and how they influence competitive advantage and organizational performance in commercial and industrial environments.

This paper adds to the body of knowledge by providing new data and empirical insights into the relationship between SSCM practices and the performance of manufacturing companies in Ethiopia.

This study aims to evaluate the sustainable supply chain performance indicators. At a macro level, the identification of the sustainable supply chain management (SSCM) performance indicators is done through exhaustive literature survey and interviews with experts. Furthermore, these indicators are evaluated through a hybrid approach, i.e. total weighted interpretive structural modelling (TWISM) followed by analytic hierarchical process (AHP).

Micro small and medium enterprises (MSMEs) in India are a major contributor to nation’s GDP. However, this sector struggles to comprehend benefits from implementation of SSCM due to a lack of appropriate performance evaluation metrics. The purpose of this paper is to contribute to the body of knowledge in SSCM by proposing and evaluating a set of SSCM performance indicators.

The paper highlights the SSCM performance indicators and concludes that business strategies, implementation planning and impact of stakeholders are the top SSCM performance indicators (SPIs). Therefore, the decision-makers must initially focus on strategic requirements which foster the implementation of SSCM, thereby ensuring profitability for all stakeholders.

Although the proposed framework was validated through a case study on Indian automobile component manufacturing MSMEs, future research would explore the extension of the framework to other industries.

The originality of this study lies in the application of the novel TWISM-AHP tool. Furthermore, the SPIs identified in the study, consider the integration of the triple bottom line from the MSME perspective. The TWISM-AHP analysis will be beneficial for SC decision-makers to enhance the SSCM performance based on the identified indicators and their criticality.