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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.

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.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.

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.

This study explores consumers' perceptions of purchasing fast food items through online platforms. The central idea of this research is to practically assess the various elements impacting the consumers’ perceptions of online purchasing of fast food items and find out the factors with high importance and performance value.

A quantitative research approach was used to collect data from 402 participants in the form of a pen-and-paper-based method using a 5-point Likert scale. The collected data were analyzed using structural equation modeling (SEM) and importance-performance analysis. Theory of planned behavior and technology acceptance model form the basis for this research.

The findings indicate that constructs such as convenience, perceived quality and perceived healthiness positively influence consumers' perceptions of online purchasing of fast food items. On the other hand, competitive prices, discounts and promotions (CPDP) and online shopping experience have no significant impact on perceived value for money.

A constraint of this study is that it was done in a particular geographical location, which restricts the generalizations of the findings. The study only examined consumers' perceptions of online fast food purchasing, and future research could explore consumers' actual behaviors toward personalized fast food recommendations by online sellers.

The research supports and extends the existing literature by comprehensively understanding consumers' perceptions of purchasing fast food online. These findings can help online fast food sellers improve their services and develop targeted marketing strategies.

This research aims to analyse the perceptions of practitioners in three regions regarding the challenges faced by their firms during the pandemic, considered a black-swan event. It examines the strategies implemented to mitigate and recover from risks, evaluates the effectiveness of these strategies and assesses the difficulties encountered in their implementation.

In the summer of 2022, an online survey was conducted among supply chain (SC) practitioners in France, Poland and the St. Louis, Missouri region of the USA. The survey aimed to understand the impact of COVID-19 on their firms and the SC strategies employed to sustain operations. These regions were selected due to their varying levels of SC development, including infrastructure, economic resources and expertise. Moreover, they exhibited different responses in safeguarding the well-being of their citizens during the pandemic.

The study reveals consistent perceptions among practitioners from the three regions regarding the impact of COVID-19 on SCs. Their actions to enhance SC resilience primarily relied on strengthening collaborative efforts within their firms and SCs, thus validating the tenets of the relational view.

COVID-19 is (hopefully) our black-swan pandemic occurrence during our lifetime. Nevertheless, the lessons learned from it can inform future SC risk management practices, particularly in dealing with rare crises. During times of crisis, leveraging existing SC structures may prove more effective and efficient than developing new ones. These findings underscore the significance of relationships in ensuring SC resilience.

This study aims to evaluate the adoption of four types of supplier sustainability risk management (SSRM) strategies, namely, risk avoidance (RA), risk acceptance (RAC), collaboration-based risk mitigation (CBM) and monitoring-based risk mitigation (MBM) in Sri Lankan apparel and retail industries, and to investigate their effect on supply chain performance (SCP).

This study uses the dynamic capability view (DCV) to develop its hypotheses. Data collected from 89 firms were analysed using partial least square (PLS) structural equation modelling and PLS-based multiple group analysis.

Sri Lankan apparel and retail firms adopt RA and MBM strategies relatively more than CBM and RAC strategies, whereas there is no significant difference between the two industries in terms of the use of SSRM strategies. The path analysis revealed significant effects of RA and RAC strategies on SCP of both industries. The effect of CBM strategy on SCP is moderated by industry, while MBM has no significant impact.

While managing supplier sustainability risks effectively, RA and RAC strategies provide more opportunities for managers to improve SCP. In achieving SCP, CBM strategies are proven to be more effective for retail industry compared with the apparel sector. Although MBM strategies offer sustainability advantages to firms, their contribution to improving the performance of apparel and retail supply chains is not significant. This research is limited to only two industries (apparel and retail) in Sri Lanka, where the evidence for the effects of SSRM strategies is not available for other contexts.

Either the effects of the four types of SSRM strategies on SCP or the moderating effect of industry on these effects have not been empirically confirmed in the literature. Evaluating the extent to which different strategies are implemented in Sri Lankan apparel and retail industries is another significant contribution of this research. Furthermore, this study contributes by using DCV to a sustainability-based supply chain risk management research.

Green practices are essential for sustainability. However, it is challenging due to the socioeconomic and environmental concerns. Similarly, after the induced SDG-12 and SDG-13 by United Nations, the pressure groups forced manufacturers to consider sustainability. Therefore, this research aims to examine the sustainability through multifaceted green functions in manufacturing is examined.

Data were collected from 293 supply chain professionals of manufacturers from a developing economy. Hypotheses were tested through a quantitative method using partial least squares-structural equation modeling with the help of SmartPLS version 4 to validate the measurement model.

The findings revealed that all six direct hypotheses were supported. However, out of four hypotheses of mediation, one was not supported. Besides, a sequential mediation of green supply chain environmental cooperation and green human resource management was supported. The findings illustrated that green supply chain practices positively influence all used variables.

This research provides practical insight to practitioners to implement green practices in their supply chain networks for social, economic and environmental sustainability and compliance with SDG-12 and SDG-13. The sustainability was validated in a higher-order construct (HOC) (formative), including sequential mediation in the model with the support of resource dependency theory. Therefore, this study adds substantial literature to the existing body of knowledge.

This research provides an interdisciplinary framework by adding knowledge to the Resource Dependency Theory to address Sustainable Development Goals-12 (SDGs) and SDG-13. Likewise, this research provides an extension towards the body of knowledge on the issue, which can be used in future research and critical examinations for cleaner and sustainable production. So far, in Pakistan, no research has looked at the function of these integrated variables in the manufacturing industry with a diligent focus on sustainability as it was validated in a higher-order construct (formative) with one sequential mediation, which makes this research unique.

This study aims to present a state-of-the-art review of building information modelling (BIM) in the Swedish construction practice with a focus on wood construction. It focuses on examining the extent, maturity and actual practices of BIM in the Swedish wood construction industry, by analysing practitioners’ perspectives on the current state of BIM and its perceived benefits.

A qualitative approach was selected, given the study’s exploratory character. Initially, an extensive review was undertaken to examine the current state of BIM utilisation and its associated advantages within the construction industry. Subsequently, empirical data were acquired through semi-structured interviews featuring open-ended questions, aimed at comprehensively assessing the prevailing extent of BIM integration within the Swedish wood construction sector.

The research concluded that the wood construction industry in Sweden is shifting towards BIM on different levels, where in some cases, the level of implementation is still modest. It should be emphasised that the wood construction industry in Sweden is not realising the full potential of BIM. The industry is still using a combination of BIM and traditional methods, thus, limiting the benefits that full BIM implementation could offer the industry.

This study provided empirical evidence on the current perceptions and state of practice of the Swedish wood construction industry regarding BIM maturity.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.