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Freight transportation practices accounted for a significant share of environmental degradation and climate change over the years. Therefore, environmentally responsible transport practices (ERTPs) become a serious concern of freight shippers and transport service providers. Past studies generally ignored the assessment of ERTPs of freight transport companies during a transport service contract. To bridge the above literature gap, this paper proposed a hierarchical framework for evaluating freight transport companies based on ERTPs.

In a data-driven decision-making environment, transport firm selection is affected by multiple expert inputs, lack of information availability, decision-making ambiguity and background of experts. The evaluation of such decisions requires a multi-criteria decision-making method under a group decision-making approach. This paper used a data-driven method based on the intuitionistic fuzzy-set-based analytic hierarchy process (IF-AHP) and VIseKriterijumska Kompromisno Rangiranje (IF-VIKOR) method. The applicability of the proposed framework is validated with the Indian freight transport industry.

The result analysis shows that environmental knowledge sharing among freight transport actors, quality of organizations human resource, collaborative green awareness training programs, promoting environmental awareness program for employees and compliance of government transport emission law and practice have been ranked top five ERTPs which significantly contribute to the environmental sustainability of freight transport industry. The proposed framework also ranked freight transport companies based on ERTPs.

This research is expected to provide a reference to develop ERTPs in the emerging economies freight transport industry and contribute to the development of a sustainable freight transport system.

This study assesses the environmental responsibility of the freight transportation industry. The emerging economies logistics planners can use proposed framework for assessing the performance of freight transportation companies based on ERTPs.

The balancing of sustainability dimensions is the prime agenda of supply chain organisations. The supply chain sustainability greatly influenced by its freight transport activities. Most of the previous work discussed the economic and environmental sustainability of freight transport industry; although the social sustainability (SS) dimension paid less attention to researchers and practitioners of emerging economies. The purpose of this study is to investigate the importance of SS indicators in the freight transport industry. The SS assessment framework is validated with the Indian freight transport industry.

The proposed framework considers four SS dimension and 25 indicators. The SS indicators’ importance varies with the individual company's prospect. Therefore the proposed framework is used in multi-company perspective as well as in industry perspective to present more realistic results. The importance weight of SS dimension and indicators are computed with a novel multi-criteria decision-making (MCDM) method, i.e. fuzzy best–worst method (FBWM).

The prioritisation of SS indicators in each company perspective is compared with an industry perspective. The contribution to community health and education program is most valuable indicator followed by the prevention of child and forced labour. The model robustness is tested through sensitivity analysis and reported that less variation in indicators’ ranking.

To authors best of knowledge, this is the first study to highlight the importance of SS indicators in the freight transport industry. This study contributes to the sustainability assessment literature by providing a nuanced perception of the SS indicators and put forward managerial implications for improving the SS of the freight transport industry. The proposed framework could be treated as a benchmark for other developing nation's freight transport industry.

The digital evolution of production and logistics systems requires seamless integration of various functions. Cyber-physical systems (CPS) can streamline operations, reduce costs and optimise freight transport dynamics. Therefore, CPS adoption is essential to transform existing logistics infrastructure by connecting logistical equipment to cyberspace. This research addresses the critical issue of low CPS adoption in logistics. By analysing the barriers, the study proposes effective strategies to increase CPS integration significantly.

This study used the technology-organisation-environment (TOE) framework and identified 18 barriers to CPS adoption in freight logistics. The barriers were then analysed using the fuzzy data-driven multi-criteria decision-making (MCDM) method, i.e. fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL).

The computational analysis of the proposed framework shows that “the complexity of CPS and lagged data-driven logistics infrastructure” (T₁) is a major technological inhibitor to CPS adoption. The “high cost of CPS technology” (O₈) and a “lack of top management support” (O₃) are the top causal inhibitors at the organisational level. “Lack of data governance and regulatory framework” (E₂) is the main environmental inhibitor.

The causal mapping of the TOE-based barriers helps policymakers and logisticians to develop strategies or follow recommended adoption strategies to improve CPS adoption in logistics.

This study is a pioneering effort to unveil the adoption barriers of CPS in the freight logistics industry and suggest strategies for fostering adoption. This research could provide valuable insights for logistics organisations to support CPS-driven logistics modernisation.

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

The humanitarian supply chain (HSC) area is rich with conceptual frameworks with a focus on the importance of information and digital technology (IDT) applications. These frameworks have a limited scope in investigating and prioritizing barriers to IDT adoption in HSCs. The present study thus identifies and prioritizes the barriers to IDT adoption in organizations involved in HSCs.

By using a literature review allied with expert discussions and a fuzzy analytic hierarchy process (F-AHP), the study identifies and prioritizes a comprehensive set of barriers that organizations involved in HSCs may consider to improve IDT adoption.

The study investigates five main barriers (strategic, organizational, technological, financial and human) interlocked with 25 sub-barriers impacting the level of IDT adoption in organizations involved in HSCs. The findings indicate that strategic barriers (SBs) are of greatest importance, followed by organizational, technological, financial and human barriers. The findings indicate the difference in ranking barriers influencing the adoption of IDTs in HSCs compared to the commercial supply chain.

Although a three-step method adopted for this study is rigorous in terms of the way this research is conducted, it is essential to report that prioritization is based on the subjective opinions of the experts.

The findings aim to assist policymakers and practitioners in developing effective strategies to improve IDT adoption in organizations engaged in HSCs. Moreover, the prioritization of barriers provides a systematic way to overcome any barriers to improve HSC performance.

This study is first of its kind that investigates and prioritizes the barriers to IDT adoption in HSCs.

In the era of the circular economy, the economic growth of a country is highly dependent on the sustainable performance of the manufacturing sector. In today’s increasingly competitive world, it is important to constantly improve the manufacturing or service industry. Quality with quantity is a main characteristic, which helps a company stay in the competition. Flexibility and responsiveness to customer demands are very important for success. Generally, additional time is needed for setup caused by poor design of equipment. At this point, the terms continuous process improvement and single-minute exchange of dies (SMED) as an approach of lean manufacturing come into play. Lean manufacturing system has been identified as an approach for improving the performance of the process and product.

In this paper, high setup time is considered as major problem in the industry and a major cause and effect for high setup time was found. On the basis of the literature review and experts’ opinions, four categories of barriers, namely method, manpower, machine and tools are identified. In this study, a hybrid approach comprising of the analytic hierarchy process (AHP) and graph theoretic approach (GTA) has been used. First, prioritization of different categories of barriers by AHP has been done, and second, GTA has been applied for finding the barriers' intensity index. Based on this study, machine and manpower barriers have emerged as major hurdles in the high setup time of machine. The proposed framework will help organizations quantify barriers in high setup time in different manufacturing processes, thereby developing effective strategies for sustainable production.

Findings of this research will contribute to ensuring sustainable competitive advantages, but it has some limitations. Development of the permanent matrix equation for barriers of high setup time is complex and lengthy when barriers are more in number. Absolute and relative values considered while quantifying the intensity of barriers are based on experts’ opinions, which may be inconsistent. In spite of these limitations, organizations can use an illustrated approach to quantify the barriers, thereby developing strategies for successful implementation of high setup time for making them sustainable in the global market. Organizations can also benchmark their sustainability preparedness with the best in the industry. As a future scope of study, high setup time can be reduced by using SMDE technology can be further validated through an empirical and case-based approach to generalize the findings.

Authors remain confined only to setup time. The approach is generalizable and can be extended in other areas. As a future scope of study, high setup time can be reduced by using single minute die exchange technology and can be further validated through an empirical and case-based approach to generalize the findings.

The study guides and facilitates researchers and practitioners in using the most appropriate techniques such as AHP and GTA for empirical studies and in developing, modifying and/or reviewing application frameworks for production. It also guides implementation experience regarding high setup time by using advanced techniques such as single point die exchange (SMDE), which can be beneficiary for both developing and developed country contexts. Industries can accelerate implementation by understanding and using most important AHP, GTA and SMDE techniques.

Lean manufacturing system has been identified as an approach for improving the performance of the process and product. A lean manufacturing system is part of corporate culture, like tools and approaches. High setup time can be classified as waste for the company. Reduction in time is a direct way to increase the productivity and profit. Therefore, there is a need to reduce the time by using some new lean methodology. In global industry, different techniques are used for reduction of time.

This article aimed to propose and validate a roadmap to enhance the insertion of social sustainability practices in logistics activities considering the scenario of companies operating in Brazil.

The initial construction of the aforementioned roadmap was based on a detailed literature review and the fine-tuning as well as validation of it was carried out through a Delphi process developed with professionals specialized in the area of logistics and sustainability.

As main results, it is highlighted that the validated roadmap includes actions ranging from meeting and adapting legal issues related to sustainability, through the initial diagnosis of the company, motivation and awareness of the importance of social sustainability, followed by encouraging the inclusion of social sustainability practices in logistic activities, and finally, the identification of opportunities for improvement and establishment of execution plans within the organization. The phases and actions of the validated roadmap converge towards restructuring and redefinition of the organizational culture oriented towards meeting sustainable guidelines, and also contemplate the dynamics of seeking continuous improvement throughout all levels and sectors belonging to a given organization.

The originality of this study lies in the fact that the roadmap focuses on the inclusion of social sustainability practices in logistic activities, since, according to the literature, social aspects are still relegated to the background when compared to environmental and economic aspects.

The inclusion of sustainable practices in the service only supply chain (SOSC) is less evident in the literature. The aim of this research is to analyse the enablers of sustainability to be implemented in (SOSC).

A rigorous literature review and experts’ outlook are used to identify fifteen key enablers of sustainability to be implemented in the SOSC. These key enablers are analysed by the interpretive structural modelling (ISM) and fuzzy decision making trial and evaluation laboratory (DEMATEL) technique. A case study of an Indian hospital is taken for testing the relevancy of the research.

ISM identified the six hierarchical levels of the enablers and MICMAC classified the enablers into four categories based on the driving and dependence power of the enablers. The fuzzy DEMATEL technique categorized the enablers into cause and effect groups. Four enablers were found in the effect group and eleven enablers were identified in the cause group.

This research will help the managers in identifying the enablers of sustainability to implement in the SOSC and to handle the critical enablers with care.

This is the first of its kind of study which not only identifies the key enablers to achieve sustainability in the SOSC but also derives the hierarchy levels of enablers and categorizes these enablers into cause and effect groups.

Big data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.

The results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.

The present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

In today’s uncertain business environment, Industry 4.0 is regarded as a viable strategic plan for addressing a wide range of manufacturing-related challenges. However, it appears that its level of adoption varies across many countries. In the case of a developing economy like India, practitioners are still in the early stages of implementation. The implementation of Industry 4.0 appears to be complex, and it must be investigated holistically in order to gain a better understanding of it. Therefore, an attempt has been made to examine the Industry 4.0 implementation for the Indian manufacturing organization in a detailed way by analyzing the complexities of relevant variables.

SAP-LAP (situation-actor-process and learning-action-performance) and an efficient interpretive ranking process (e-IRP) were used to analyze the various variables influencing Industry 4.0 implementation. The variables were identified, as per SAP-LAP, through a thorough review of the literature and based on the perspectives of various experts. The e-IRP has been used to prioritize the selected elements (i.e. actors with respect to processes and actions with respect to performance) of SAP-LAP.

This study ranked five stakeholders according to their priority in Industry 4.0 implementation: government policymakers, industry associations, research and academic institutions, manufacturers and customers. In addition, the study also prioritized important actions that need to be taken by these stakeholders.

The results of this study would be useful in identifying and managing the various actors and actions related to Industry 4.0 implementation. Accordingly, their prioritized sequence would be useful to the practitioners in preparing the well-defined and comprehensive strategic roadmap for Industry 4.0.

This study has adopted qualitative and quantitative approaches for identifying and prioritizing different variables of Industry 4.0 implementation. This, in turn, helps the stakeholder to comprehend the concept of Industry 4.0 in a much simpler way.