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COVID-19 is a global event affecting supply chain operations and human health. With COVID-19, many issues in business models, business processes and supply chains, especially in the manufacturing industry, have had to change. The ability to analyze supply chain performances and ensure circularity in supply chains has become one of the factors whose importance has increased rapidly with COVID-19. Therefore, it aims to determine which supply chain performance criteria come to the fore for the company under consideration to accelerate the transformation into high performance and circularity in supply chains.

In this study, a new circular-SCOR model is proposed, and 17 supply chain performance measurement criteria are prioritized for a manufacturing company in the context of circular economy principles during COVID-19 by using stepwise weight assessment ratio analysis and analytical hierarchy process method, separately.

As a result, for both methods, in the case study discussed, the demand fulfillment rate is determined as the most prominent criterion in line with the circular economy principles in the COVID-19 period in manufacturing supply chains.

It is expected that this study will contribute to managers and policy makers as it addresses the “new normal” that started after COVID-19 and the criteria to be considered in supply chain performance measurement and emphasizes the need to adopt circular supply chains, especially in manufacturing industries.

In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and sustainability paradigms. In this way, this research aims to identify the attributes that a supply chain (SC) should follow to be resilient and sustainable, and then to evaluate their importance according to industry experts.

This study suggests a hybrid approach. The authors identified the most commonly used criteria using literature review, and then applied fuzzy Delphi technique (FDT) with the objective of surveying experts to find the attributes used in practice and asked to assess their relevance.

The resilient-sustainable supply chain (RSSC) is formed by four dimensions: resiliency, economic, environmental and social. A total of 15 criteria are identified, and the most important are visibility, flexibility, supply chain risk management (SCRM) culture, work conditions and communication.

This study used a literature review, so it is subject to a time frame, and the criteria could no longer be relevant as the time and business conditions change. Also, the findings may not be completely applicable throughout different industries, and therefore the finding cannot be replicated to other businesses.

This study will assist decision-makers among other interested parties to construct and/or strengthen an integrated SC that mixes resiliency and sustainability.

This study contributes to the state-of-art by producing a characterization of the resilient and sustainable supply chain for the automotive industry. Also, this research produces a new and holistic framework for resilient and sustainable SCPM supporting the decision-making process.

The main problem addressed by this research is the current debate between the negative and positive effects of industrial clusters. This debate is a result of gaps between theoretical implications and empirical evidence in both the classical agglomeration theory and the agglomeration lifecycle theory. The purpose of this study is to propose a framework for developing an index measuring both organizational cluster involvement and organizational supply chain including the three pillars (economic, social, and environmental). Furthermore, the index acts as a quantitative predictor of the stages of the life cycle of industrial clusters. Adopting a case study methodology, the applicability of the index development framework is demonstrated. First, cross-sectional exploratory interviews are performed to locate items measuring the three pillars of organizational sustainability within Egyptian communication industry. Second, an explanatory, cross-sectional approach is applied gathering data from eight professionals related to involvement and supply chain sustainability of their organizations. Analytical hierarchical process is used for weighting and aggregating individual item metrics into two indicators (Saaty, 1980). Measuring, managing, and controlling capabilities of organization's supply chains outweighs the need to manage risks. The proposed framework aids firms within a cluster in making timely decisions about what needs addressing to improve supply chain sustainability performance. Hence, all environmental, social, and economic capabilities can be effectively monitored and controlled.

It is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan.

The authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others.

The findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors.

The major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited.

To date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.

The paper aims to explore how business intelligence (BI), integration and agility influence supply chain performance.

The study was performed by the exploratory sequential mixed method in two phases including meta-synthesis as a qualitative method and survey as a quantitative method. Data were collected through a survey of 369 Iranian companies across various industries. Structural equation modeling was used to test hypotheses.

The results show that BI, integration and agility play an important role in achieving better supply chain performance. In the meantime, BI has the greatest impact on supply chain performance. Additionally, BI has a positive and significant effect on the integration and agility of the supply chain. The study also found that integration has a direct effect on supply chain agility.

To the best of the authors' knowledge, the paper theoretically and empirically presents a new conceptual model of the relationship between BI, integration, agility and supply chain performance. The study helps researchers and practitioners to achieve insights into supply chain performance improvement.

The current research aims to investigate the relationship between supply chain (SC) processes maturity and SC performance in the context of an emerging market (i.e. Morocco). Based on the SCOR model, the authors propose and test a thorough conceptual framework in which information systems moderates the relationship between SC processes maturity and performance. The effects of firm age and size are also taken into account.

Based on data collected from 175 top and middle managers using self-administered questionnaires, the authors empirically assessed the conceptual model using a partial least squares (PLS) estimation.

The study's findings demonstrate that SC processes maturity has a significant effect on SC performance. Second, information systems act as a moderator in the relationship between SC maturity and performance, e.g. the impact of supply chain processes maturity on supply chain performance measures is stronger in the presence of information systems support. Ultimately, firm size and age were found to have no significant impact on supply chain performance.

The study's findings help SC managers to better understand how SC maturity contributes to SC performance. A firm effectively executing maturity factors in its SC processes is more likely to achieve a better SC performance. The authors also established the key role of information systems in strengthening the impact of SC maturity on performance. SC managers should capitalize on the use of information systems to achieve superior SC performance.

The present research bridges a gap pertaining to the impact of supply chain maturity on SC performance, particularly in emerging markets. It is the first of its kind to investigate the influence of SC maturity on SC performance the context of emerging markets.

This research aims to explore the various green supply chain management (GSCM) performance measures and develop the efficient performance measurement framework for evaluation of influence of GSCM adoption on organizational performance.

This research proposes a hybrid framework of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy weighted aggregated sum product assessment technique. The usefulness of proposed framework is validated using empirical case example of Indian manufacturing organization.

The finding reveals that the overall performance of case organization is 67.03% based on define set of performance measures. Further, the proposed framework has been validated with other three Indian automobile manufacturing organizations. The results obtained were confirmed with selected empirical case company. The proposed hybrid framework provides the effective path to measure and benchmark the impact of each performance measures on system performance.

This research is limited to automobile sector of India; hence the results obtained in this study may not be comprehensibly used to other sectors due to different product and process fields.

This research aids the industrial practitioners to effectively implement the green supply chain management (GSCM) and helps them to boost the overall performance of business organizations in three dimensions of sustainability.

This study investigates the supply chain efficiency of selected companies in the Indian food processing sector. Additionally, it explores the relationship between supply chain efficiency and firm performance.

To determine the supply chain efficiency, the study uses supply chain efficiency measures, such as supply chain length, inefficiency ratio and working capital productivity. Secondary data were collected from the Center for Monitoring Indian Economy (CMIE) Prowess database for the years 2011–2017. Various return measures, such as Return on Net Worth (RONW), Return on Total Assets (ROTA) and Return on Capital Employed (ROCE), were used to measure firm performance. Collected data were analyzed to investigate the relationship between supply chain efficiency and firm performance.

Findings of the study reveal the prevalence of inefficient supply chains in the context of the selected companies. There is a significant negative correlation between supply chain efficiency and firm performance. RONW has a significant negative correlation with the length of supply chain as well as supply chain inefficiency.

This study expands the limited existing research perspective; the study helps to understand the supply chain efficiency and firm performance.

This is an original piece of work and provides valuable insight into the relationship between supply chain efficiency and firm performance.

The purpose of this paper is to persuade a hybrid framework, which can be used to assess the performance of various supply chains and can be further used to segregate supply chains concerning critical KPMs. The KPMs have been selected in the COVID-19 pandemic condition.

A real case of e-commerce is presented to illustrate the working of the proposed framework comprising a hybrid methodology of BWM and Fuzzy TOPSIS to measure the performance of the e-commerce supply chains by identifying the critical key performance metrics (KPMs) and measuring the performance of the considered supply chains against these.

The proposed framework is illustrated using real-time data from experts, collected through interviews and discussions. It is found that rate of return on investment (SCPM 27), flexibility of service systems to meet particular customer needs (SCPM 23) and supplier lead time against industry norm (SCPM 33) are significantly weighed in assessing performance of the selected supply chains, with weights 0.07764, 0.06863 and 0.0547, respectively. Amazon and Flipkart are seen to stand out among the other supply chains taken for the present study with closeness coefficients as 0.945 and 0.516, respectively.

The contemporary world has seen the drastic attack of COVID-19 on many firms worldwide, and hence measuring the performance of the supply chains has become necessary so as to understand the critical factors affecting performance, their relative importance and the firm's relative standings. There have been studies in the recent past where researchers worked on similar motives to generate a framework to measure performance of supply chains, but it is seen that the methodologies lack flexibility with respect to effectively handling large data, uncertainty in human emotions, consistency, etc. This is where the current study stands out in effectively measuring the performance of supply chains so as to aid many firms affected by the pandemic.

This paper addresses a gap in task performance research, with a focus on supply chain operations, by exploring the role that defensive pessimism (DP)—a phenomenon sparsely studied in supply chain literature—has in the workplace. It investigates the roles that task complexity, perceptions of control and employee situatedness in the workplace play as predictors of DP, as well as addresses the relationship between defensive pessimism and supply chain performance.

Five hypotheses are developed and empirically tested employing the data-generating method, Monte Carlo simulation and then applying factor analysis and structural equation modeling (SEM) to survey data from practitioner members of the Council of Supply Chain Management Professionals.

The results reveal that task complexity and external locus of control heighten perceptions among employees that task completion could be outside their locus of control. The increased tendency to be defensively pessimistic about workplace commitments negatively impacts supply chain performance. This study found that task complexity and external locus of control encourage DP, negatively impacting supply chain performance (SCP).

This study explored underlying causes of defensive pessimism, a self-limiting behavior among supply chain professionals. In understanding the role of DP, it is possible to enhance SCP by managing task complexity, external locus of control and job autonomy—predictors of defensive pessimism in work commitments.