This study aims to propose an integrated approach for supplier selection based on the lean, agile, resilience, green, and sustainable (LARGS) paradigm. This approach was validated using structural equation modelling (SEM) and the intuitionistic fuzzy TOPSIS method. A comprehensive literature review was conducted, identifying twenty-six criteria, which were then consolidated into five main criteria. A questionnaire was distributed to 237 individuals from manufacturing companies listed on the Tehran Stock Exchange, and the collected data were analyzed using third-order factor analysis and the partial least squares method. Subsequently, the proposed integrated approach was applied to evaluate four suppliers in an intuitionistic fuzzy environment, utilizing expert opinions and a case study on the automotive industry. The results demonstrate the effectiveness and practicality of the proposed approach in terms of prioritizing and selecting suitable suppliers according to LARGS criteria. In conclusion, this study contributes to the existing literature by proposing an integrated approach that addresses the decision-making challenges in supplier selection. This approach offers a practical tool for managers seeking to enhance sustainable supply chain performance from the LARGS perspective.

This study aims to identify and analyze the sustainable supply chain management (SSCM) implementation barriers in the context of Iran to determine the barriers and establish a cause-and-effect relationship between them. The Fuzzy Delphi Method (FDM) is used to assess the barriers to SSCM implementation in Iran, and a fuzzy decision-making trial and evaluation laboratory (DEMATEL) is used to obtain qualitative assessments from multiple experts regarding how to mitigate the impact of the barriers. To validate the proposed methodology, out of 20 barriers identified through the literature review and 9 more barriers suggested by experts, 26 barriers are identified to be relevant to the context of Iran using FDM. Six SSCM implementation barriers (i.e., economic sanctions; banking problems; economic instability; high inflation rate; lack of regulation and guidance from the government and lack of a globally competitive environment) were determined as important barriers in the cause group. All of them are related to Iran’s economic situation, the economic sanctions against Iran, and the government’s neglect of the importance of sustainability issues, all of which are obviously out of the companies’ control; moreover, the impact-relation map for each has been developed to facilitate the visualization of its interactions (i.e., influencing and influenced) with other barriers. The outcomes achieved are unique to Iranian companies and cannot be generalized to every company in other countries; however, the proposed approach might serve as a foundation for analyzing and comprehending the interactions between barriers. The suggested technique would identify the most effective areas for directing resources and efforts to reduce the effects of barriers to successful SSCM implementation.

To obtain a sustainable competitive advantage in the dynamic environment, it is necessary for Chinese high-tech enterprises to focus on their technology habitual domains in formulating ambidextrous innovation strategy. This study integrates technology habitual domain, exploratory innovation and exploitative innovation within a framework and explores the influence mechanism among them. Based on an in-depth case study on KTE, representing a high-tech enterprise in China, we have several findings. Firstly, we depict the evolution mechanism of technology habitual domain; secondly, we find that the high-tech enterprise’s technology habitual domain will cultivate and develop the firms’ dynamic capabilities; and thirdly, the expansion of technology habitual domain will promote exploitative innovation, while the transformation of technology habitual domain will promote exploratory innovation. These findings can be useful guidance for high-tech enterprises in China who are aiming to achieve ambidextrous innovation to better adapt to the turbulent environment, and thus achieving sustainability.

This research investigates the impact of the technologies through an integrated Fuzzy Analytic Hierarchy Process (F-AHP) and VIKOR model to determine their viability as a marketing strategy for business growth in the Prosthetics and Orthotics (P&O) medical device industry. Based on expert data, the study evaluates the integration of Industry 4.0 technologies and ranks them by priority for marketing performance: “Artificial Intelligence & Machine Learning” (0.3295), “Internet of Things” (0.4325), “Virtual Reality & Augmented Reality” (0.5000), and “Big Data” (0.5704). The findings confirm that the proposed model effectively Leverage the industry 4.0 technologies to enhance marketing strategies, using Pakistan as a case study. This research serves as a blueprint for addressing the integration of next-generation marketing tools, technological advancements, and business growth challenges in the P&O industry. It contributes to the growing body of knowledge on the role of technology in improving healthcare marketing and business performance in emerging markets. Future research should explore the broader impact of Industry 4.0 technologies on healthcare marketing, focusing on strategic decision-making, efficient marketing resource allocation, and performance measurement to ensure sustained success in the P&O medical device sector. The study concludes that prioritizing Industry 4.0 technologies, however, limitations such as sample size, data collection constraints, and model complexity may Leverage the generalizability of the results. Future research should address these limitations by expanding the scope of expert involvement and exploring the application of this model in other emerging economies, to further validate the findings and assess the broader implications for healthcare marketing strategies globally.

In the context of advanced prosthetic and orthotic medical devices, funding is a major challenge, especially in low-income countries. This research aims to investigate the best funding solution for such medical devices to offer disabled people a better quality of life and improve their health and economic situation. This is the first time such methods are being used in a study based on related research involving a fuzzy analytic hierarchy process (FAHP)/VIekriterijumsko KOmpromisno Rangiranje (VIKOR) model to find the best funding source. A survey questionnaire created by the author and completed by Pakistan subject experts was used to analyze data via a weightage value ranking system as an assessment tool. Prioritization of funding alternatives was based on main criteria and subcriteria. Limitations include sample number of study participants, amount of data collected, number of models used, and time constraints. Potential funding sources were ranked based on a VIKOR weightage value model using a hybrid decision-making process that showed results as “private insurance” having a weightage value of (0.1956) as being the best funding source since they are having the minimum weightage and then next from best to least they were “need-based” with a weightage value of (0.2510), “self-pay” with a weightage value of (0.7970), and finally “government-based” having a weightage value of (0.9636). Implications of this study conclude that the proposed model efficiently finds the best funding sources for advanced prosthetic and orthotic (P&O) medical devices in low-income countries. Executing this model in low-income countries such as Pakistan can help solve P&O medical device coverage challenges and offer disabled people better opportunities to work and contribute to their quality of life and economy.