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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.

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.

Management of hazardous waste is a big challenge to a common biomedical waste treatment facility (CBWTF) because of variations in the amount of different kinds of waste collected and treated from various health-care facilities (HCFs). Hence, prediction of health-care waste (HCW) will be very helpful for the CBWTF in allocation of resources, transportation, storage and disposal of medical waste (MW). This study aims to focus on the current MW handling and disposal practices at CBWTF in Uttarakhand, India. The study also models the seasonal variation in the HCW quantities collected and treated in CBWTF at Uttarakhand (India).

Data were collected for two years (2013 and 2014) from CBWTF, and polynomial regression models were used to represent the complex nonlinear relationship among the variables.

The fixed trends in the waste generated in two years represent the seasonal variations and illness patterns. The load of approximately 527 kg/day biomedical waste, including all the three categories (red, yellow and blue), was estimated at CBWTF at Uttarakhand, India. The composition of the total waste was calculated as: yellow category (327 kg/day, 62.23 per cent), red category (190 kg/day, 36.66 per cent) and blue category (10 kg/day, 1.44 per cent). CBWTF needs to run an incinerator for 3.30 h, autoclaving machine for 4 h and shredder for 20 min daily as per the calculated load.

This study is focused on only one CBWTF in Uttarakhand, so the model needs to be validated considering other facilities.

The model will help the CBWTF to plan its capacity and allocate resources.

Infectious waste coming out from HCFs can be managed in a proper way.

This study is the first of its kind conducted for CBWTF, Uttarakhand, India.

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 cyber-physical system (CPS) is a well proven technology for improving system performance, resilience, and interconnectivity. In emerging nations like India, the logistics industry lacks practices connecting logistical equipment with cyberspace. This paper aims to bridge this gap by identifying and evaluating the performance metrics of connectivity solutions. Its goal is to establish an appropriate infrastructure that enables seamless connectivity within the CPS-enabled logistics ecosystem.

A novel integrated decision method is employed to classify the optimal connectivity solution for CPS. It integrates Regret Theory (RT) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-1) method in a Hesitant Fuzzy (HF) environment. This method considers the psychological traits of decision-makers and effectively incorporates their hesitancy for the classification.

The findings highlight security (c10) as the foremost critical performance metric, followed by cost (c6), scalability (c9), traceability (c2) and trustworthiness (c1) to build connective infrastructure for CPS. For extensive coverage scenarios, like freight transportation, cellular connectivity (a2) emerges as the most suitable connectivity solution.

This study provides a roadmap to logistics managers for selecting a suitable connectivity infrastructure to enhance seamless connectivity in logistics operations and processes. Technology providers can utilize the findings to develop the CPS infrastructure for effective freight logistics management.

This research introduces a novel decision-making tool for making choices related to advanced technology assessment. It holds significant value in facilitating well-informed decisions in the digital transformation era.

Growth in a number of the supply chain (SC) disruptions threatens the enterprises globally. Earlier studies and reports say that many organizations go out of businesses within two or three years after they experience a major disruption. Therefore, companies in today’s volatile business arena need to possess the necessary resilience level to combat supply china disruptions. This is even more important for organizations of developing nations, which are constantly struggling to gain the advantages of globalization and to grab the new opportunities. Thus, this paper aims to help organizations understand their SC resilience level through a framework.

The methodology comprises integrated Delphi – fuzzy logic approach in identifying formative elements of SC resilience from a diverse resilience related body of knowledge and distinguish key obstacles of SC resilience based on their performance level.

Findings reveal that SC flexibility components such as sourcing, manufacturing and logistic flexibility are the major contributors of SC resilience index of case organization. Similarly, lack of risk management culture, inter-organizational relationships, information sharing and integration of SC stakeholders are the major inhibitors of resilience. Thus, the organization needs to overcome these identified obstacles to enhance their SC resilience level.

Present study offers a novel focus of research on SC resilience measurement that is significant for understanding the level of immunity enterprises possess to unanticipated SC interruptions, and the ability to bounce back after an unforeseen event.

This paper proposes an integrated Delphi – fuzzy logic framework for measuring SC resilience. In doing so, the study identifies key potential inhibitors of SC resilience of the case company under study.

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.

Nowadays healthcare waste (HCW) has become a big challenge for the hospital management, especially, in developing countries like India. Like other developing countries, Indian healthcare waste disposal (HCWD) industry is also fragmented, as some hospitals are having their own in-house waste treatment facilities and others are outsourcing the process to government authorized Common Biomedical Waste Treatment Facilities. Literature also lacks the quantitative studies in selecting the HCWD strategy and, hence, the purpose of this paper is to identify and prioritize the factors, which affect the selection of HCWD strategy and to propose the model to select the HCWD strategy and to apply the proposed model to select the HCWD strategy in Uttarakhand, Northern State of India.

Grey theory-based analytic hierarchy process approach has been applied to evaluate the HCWD options and select the appropriate strategy for the healthcare facilities (HCFs).

From the literature, six criteria have been used to evaluate the HCWD strategies: “access to expertise,” “overdependence,” “transportation & risk associated,” “Government rules,” “environmental factors,” and “economic factors.” “Outsourcing” strategic option (0.61) got the higher desirability index than “in-house treatment” (0.39).

The proposed methodology can be used by the researchers and experts in the field to evaluate the strategic options and select the appropriate strategy.

The HCFs and other generators of HCW can select the alternative, whether they should treat the infectious waste in-house or they should go for outsourcing.

In the field of HCW management, this is the first study of its kind, which helps to evaluate and select the HCWD strategies. The proposed model has been applied in Uttarakhand, Northern State of India to make the comparison between “in-house” and “outsource” strategies.