Prioritising sustainable supply chain management practices by their impact on multiple interacting barriersSustainable development in supply chain management (SCM) is challenging to implement, so various studies have sought to identify appropriate practices that eliminate barriers and challenges' effects on sustainable SCM (SSCM). To overcome previous investigations' limitations, the present research developed a multi-attribute decision-making (MADM) framework for prioritising SSCM practices, which was applied to an Iranian case. A careful, systematic review of previous studies extracted a comprehensive list of SSCM barriers and practices. To shorten the long list of barriers identified, the fuzzy Delphi and fuzzy decisionmaking trial and evaluation methods were used to reduce the decision criteria list. These two approaches are particularly appropriate because of the criteria's complex interactions. In addition, fuzzy sets are useful when dealing with uncertainties in decision-making processes and obtaining experts' opinions. With the selected experts' help, the extent of each practice's impact on barriers was measured. The practices were then ranked by order of priority using six fuzzy MADM methods. The implemented methods' weights were determined using the correlation coefficient and standard deviation (CCSD) approach in order to prioritise the practices for the final time. The proposed methodological framework combines different approaches' results and increases the findings' empirical robustness by applying the CCSD method, thereby eliminating previous studies' limitations. Results show that "Lack of sustainable product and service promotion" and "Weak social and society-related pressures" are the top priority barriers and "Applying preventive and maintenance strategies to maximize equipment's effectiveness" and "Implementing reverse logistics" have been identified as the most important SSCM practices.

PurposeLiterature survey shows that it is not clear how knowledge management capability (KMC) and ambidexterity capability affect entrepreneurial creativity (EC) and entrepreneurial intensity (EI) promotion. While empirical studies have emphasized the importance of these factors in improving business performance, the cumulative effect and self-reinforcing loops of these factors in improving firm performance have not been identified. In this regard, the study seeks to investigate how to increase the entrepreneurial capabilities of KMC, EI, EC and ambidexterity of food firms to improve their performance.Design/methodology/approachThe method of the present study is applied in terms of purpose and is quantitative in terms of data collection. In order to collect the data, a questionnaire was designed that contained the variables of the conceptual model of the research. This questionnaire was distributed among industrial and academic experts in the Iranian food industry. The method of data collection is an online cross-sectional survey, and the method of data analysis is structural equation modeling using Smart PLS software to analyze the conceptual model.FindingsThe present study is cross-sectional survey research that examines the impact of KMC, EC and EI on firm performance by considering the mediating role of organizational ambidexterity. The research study shows a positive impact of entrepreneurial capabilities as KMC, EI, EC and ambidexterity on performance. Accordingly, if a firm builds KMC and fosters EC, it can achieve ambidextrous innovation and thus enhance its EI and performance in the food industry.Research limitations/implicationsThis study highlights the knowledge-based view (KBV) in explaining the role of KMC on innovative capabilities and its influence on performance. Research findings shed light on the importance of KMC as a prerequisite for innovation strategy. The study has also established the mediating role of ambidexterity in entrepreneurial value creation. According to the results, small and medium-sized enterprises (SMEs)' performance is positively influenced by entrepreneurial capabilities as KMC, EI, EC and ambidexterity.Originality/valueThis paper gives insights into how SMEs can improve their performance to gain a competitive advantage by developing knowledge and creative ideas in line with entrepreneurial goals. In this regard, the food industry can adopt new strategies to reduce the impact of these challenges to achieve superior performance and competitive advantage.

This study presents a multi-layer fuzzy-based decision-making approach to enhance the hospital Circular Supply Chain (CSC) performance by focusing on intensive care units (ICU) via key performance indicators analysis. In this regard, a Systematic Literature Review (SLR) and Institution Fuzzy Delphi (IFD) are employed to extract the relevant and prominent KPIs. After, a hybrid Fuzzy Cognitive Mapping (FCM) and Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) have been applied to illustrate a conceptual framework for the CSC performance management of the healthcare sector in the emerging economy of Iran. As a result, eight critical indicators emanated from the SLR-IFD approach. Furthermore, sixteen relationships amongst the performance indicators were identified via hybrid FCM-FDEMATEL. Inventory availability, information availability, innovation, and technology were selected as the most influential indicators. Besides, changing the information technology category, including information availability and Innovation and technology, had the most impact on the performance of the entire CSC. This study attempts to evaluate hospitals’ circular supply chain performance, by designing the circular evaluation framework. Hospital managers can use the results of this research to improve their internal circular supply chain performances in the intensive care units by understanding the different scenarios.

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PurposeEnvironmental awareness is increasing among people in developing countries. In this regard, companies should consider ecological goals in addition to financial goals. Since the food industry is recognised as one of the largest emitters of CO2, profit and ecological objectives are optimised in radio-frequency identification (RFID) based closed-loop supply chain in the food industry in this paper.Design/methodology/approachBased on the literature, companies with a green entrepreneurial orientation (GEO) can turn ecological problems into opportunities using their proactiveness. In this regard, a new mixed-integer non-linear mathematical model is presented for optimising a new multi-product RFID-based closed-loop supply chain with a GEO in the food industry. The case study in this paper is Ofogh-e Kourosh company which is located in Iran. The GAMS software is used to code this model.FindingsThe optimum number of new products and materials flow was found among the closed-loop supply chain entities. Some factors as price, quality and warranty of products were considered, and the number of reopening of facilities if needed was set. The optimum node for RFID installation was found.Originality/valueThe paper presents a multi-objective mathematical model for optimising a multi-product RFID-based closed-loop supply chain with a GEO in the food industry. In addition, this paper gives insights into how can model this type of supply chain considering ecological and financial attributes.