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Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

Academics and businesses alike have begun to recognise sustainability as a vital component of supply chain competitive advantage in recent years. Inconclusive results have been found in empirical studies of sustainable supply chain management (SSCM) that have ignored contextual variables concerning the dynamic role of firm capability in favour of testing alternative assumptions about the effect of various elements of the triple bottom line (TBL) on firm performance outcomes. The present study examines whether and how firm capabilities mediate the connection between SSCM, from a TBL standpoint, and firm financial performance outcomes.

Using the stakeholder theory, the study employed 325 survey responses from firms operating in different industries in Ghana (a less-researched context but one that plays a key role regarding SSCM practices) and the partial least squares structural equation model (PLS-SEM) technique to simultaneously assess the relationships amongst the variables.

It was discovered that the connections between all the TBL facets of SSCM practices and firm performance are positive and significant, and these relationships are mediated by firm capabilities.

By examining the underlying variables and relationships that contribute to the establishment of the rather complex relationship between SSCM practices from a TBL perspective and the performance of a firm, the research contributes to current knowledge on SSCM practices, firm capabilities and firm performance.

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

Little is known about the determinants of supply chain finance (SCF) adoption among small and medium-sized enterprises (SMEs) in developing countries. This study aims to address this relevant research gap and hence, draws on the resource-based view and transaction cost economies to empirically investigate five factors that make SCF adoption practicable among SMEs in Ghana.

The approach involves a sample of 257 SME managers/owners and modelling via structural equations modelling.

All five factors (innovative capability, information sharing, inter- and intra-firm collaboration, external financing and trade process digitization) were found to impact positively and significantly on SCF adoption. The findings provide SME managers/owners with a research model which guides them on how to settle the SCF process.

This paper used a cross-sectional survey, which makes it impossible to access changes over time. In addition, the use of quantitative method limits respondents from expressing their feelings fully. Using a mixed or qualitative methodology will provide avenues for future research.

This paper offers a completive advantage for Ghanaian SMEs to strengthen their relationships while collaborating with each other. The findings suggest that by adopting SCF solutions, SMEs can optimize their liquidity and working capital. The factors underpinning SCF adoption are of incredible attractiveness for SME managers/owners to discover the relevant practice of SCF solutions. SMEs should adopt SCF strategies for improving their capability to respond promptly to transactions.

This paper is among the few papers that have examined these five factors in a developing economy context. The study also provides new understanding of the factors that influence SCF adoption in the context of a developing economy.

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

Idea of circular economy defies the classical “make-use-dispose” approach of linear economic model. In the context of health-care industry, it relies heavily on the supply chain practices implemented by industry stakeholders. The purpose of this study is to explore such relationships, study their structure and put it across for attaining sustainability at large.

This study is an empirical research conducted on 145 health-care firms. The collected data is analysed to develop structural and measurement model. The five constructed hypotheses are examined and tested through structural equation modelling.

The study illustrates the latent relationships that exist among the stakeholders involvement, sustainable supply chain practices, sustainable performance and circular economy for health-care industry. It is found that the adoption of sustainable supply chain practices improves health-care performance, which, in turn, have positive influence on circular economy.

The structural and measurement model is developed in the context of circular health-care economy. It can be validated or improvised by conducting similar research in other industry using different methods. This research work fulfils the long existing gap in research by offering a linkage between various constructs to achieve health-care circular economy. Based on the research results, future researchers can build theories of circular economy and sustainability for health-care industry.

The study attempts to study the supply chain ways to achieve circular economy for Indian health-care sector. It considered latent relationships among the set of constructs, which are needed for theory building at later stage.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

This impact pathway manuscript motivates and guides operations and supply chain management (OSCM) researchers to deeply consider the role of suppliers in greenhouse gas (GHG) emissions reduction. It prompts a reconsideration and update of their understanding of climate change in their research and the positive influence that research could have, specifically on reducing GHG emissions and slowing climate disasters.

The authors use qualitative research methods, including a literature review, interviews with NGOs, focus groups with purchasing professionals and in-depth case studies.

The results provide insights into purchasing’s role in the engagement of suppliers in GHG emissions reduction efforts as organizations begin to advance the sustainability journey toward suppliers’ emissions reduction and their contribution to improvements in supply chain GHG emissions. The paper calls for more actionable academic research that can contribute to theory and practice.

This impact pathway article discusses how the topic of GHG supply chain emissions reduction is viewed in both research and practice. The current dire state of the environment and purchasing and supply chain involvement in GHG emissions reduction initiatives points to the need to develop impactful research. The paper closes with guidance on potential future research opportunities.

The pressure on companies to reduce their GHG emissions has never been more significant, and companies have never before made as many public commitments to reduce their GHG emissions both internally and across the supply chain as they are making today. Managers must truly understand their role in reducing GHG emissions and their supply chain implications.

GHG emissions reduction and associated climate change are top issues on the global climate agenda. Reducing emissions (and related climate change) has important positive implications for human health. This is especially true among underrepresented communities, which tend to be disproportionately impacted by living and working in weather-exposed climates with poor air quality.

The authors aim to stimulate new research and discussion through this pathway paper. The climate crisis is real, and the world is missing its GHG reduction targets. If companies limit their efforts and continue to make excuses, the world will continue its path to climate disaster.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.