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This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting.

The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology.

The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively.

The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach.

This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

The purpose of this paper is to identify the factors and most significant reasons leading to supply chain inefficiency with respect to high cost, high lead time and poor quality at wholesale stage of mango supply chain in India, and also to find out the measures which may be taken to improve supply chain efficiency.

The paper opted for an exploratory study using the quantitative and qualitative method of research. The study was conducted at Asia’s largest and world’s second largest fruits and vegetable wholesale market (Mandi) in Azadpur, Delhi. Factors have been identified using factor analysis and the measures to improve supply chain efficiency in fruits sector have been found out through semi-structured interviews with agri- and food-supply chain experts.

Based on the factor analysis, three factors were identified for high cost, namely, operational charges, labour and resources; four factors were identified for high lead time, namely, operational issues, labour, resources and infrastructure; and four factors were identified for poor quality, namely, operational issues, infrastructure, resources and poor ambience. It was also found that operational factor is the most significant factor leading to supply chain inefficiency. The study also highlighted the measures for improving supply chain efficiency based on the outcome of the interviews.

This study is limited to the wholesale stage of fruit supply chain with the focus on Azadpur Mandi, Delhi, India, with specific reference to mango. Also, the measures have been identified for only the most significant reasons under each factor leading to supply chain inefficiency with respect to cost, time and quality.

There is a dearth of literature on improving the supply chain efficiency pertaining to the wholesale stage of fruits and vegetable sector in India. This paper tries to fulfil the gap and contributed to the literature on agriculture supply chain, which may be helpful for the researchers as well as the practitioners to improve food supply chain pertaining to developing countries.

This study explores the factors that impact the quality of fresh produce in the transportation phase of the supply chain and the mitigation framework for improving the quality to curb the losses.

This study aimed for an exploratory analysis using both quantitative and qualitative research methods. Using a questionnaire with responses from 172 transporters from the Uttar Pradesh region, India, primary data were gathered through a survey. Factors were identified using factor analysis and mitigation strategies were suggested for the factors through semi-structured interviews with six experts in transportation, agribusiness and food supply chain.

Four factors that impact the quality were identified based on the factor analysis, namely operational issues, poor preservation, lack of ease of in-transit and poor infrastructure. The operational issue was found to be the main factor influencing the quality of fresh produce. The study also proposed the mitigation framework for the factors based on the interview results.

The present study is confined to the fresh produce supply chain transportation process, particularly fruits with an emphasis on the Uttar Pradesh region, India.

There is a lack of literature on implying mitigation strategies for factors affecting fresh produce quality in the transport process in India. Thus, this study attempts to fulfill this gap and has added to the food supply chain literature that could help scholars and practitioners in improving the food supply chain in developing economies.

The main aim of this paper is to develop a supply chain efficiency framework to improve overall business performance in the competitive era. This paper offers a critical literature review on supply chain efficiency that aims to reveal the basic research that has been carried out, the problem areas and requirements for the efficiency in the new era of the supply chain.

The methodology followed during this research involves beginning with a wide base of articles lying at the supply chain intersection, performance measurement topics, and then screening the list to concentrate on supply chain efficiency.

Findings show that supply chain efficiency in the modern era remains an open research field. This research contributes to the supply chain literature by clarifying the supply chain efficiency definition, defining key measurements and variables for supply chain efficiency and developing a supply chain efficiency framework to improve overall performance.

This study will be very useful to the scholars working in this field. The proposed framework would help researchers and academicians to understand every dimension and variable of supply chain efficiency, allowing practitioners to measure efficiency levels and identify improvement measures. This framework would also act as a comprehensive guide for future studies and business practices.

As there are several state-of-the-art review papers on various supply chain areas, there is a lack of literature available on supply chain efficiency studies that can provide a comprehensive framework for researchers on related literature. Thus, the present study seeks to bridge this gap in the supply chain literature. Also, this study will provide a strong basis for researchers and academicians to apply the supply chain efficiency measurement system to the dynamic supply chain.

The purpose of this paper is to identify the issues and challenges in humanitarian logistics and to develop a framework for effectively managing the humanitarian logistics in disaster relief supply chain operations in India.

This paper presents a framework to manage humanitarian logistics effectively in disaster management through qualitative analysis. First, the author examines the challenges facing the humanitarian logistics and supply chain through the reviews of the literature on various disasters. Then, the author presented a framework based on the best practices and initiatives taken worldwide in the preparedness and response stage of the humanitarian supply chain to manage and reduce the aftermath of any disaster in context to India.

A framework has been developed to manage humanitarian logistics in the disaster relief operation, which would improve the humanitarian supply chain in India and help to effectively manage natural disasters in the preparedness and response stage at the state and district levels.

The paper mainly emphasises on the preparedness and response stage of disaster supply chain management in Indian context.

None of the disaster incidents can be stopped from taking place, but the impact can be minimised by proper preparedness and effective response during the operations of humanitarian logistics. With this hope, the framework has been developed, which if implemented would help to plan and manage any disaster incident in an effective manner, which ultimately would save millions of lives and cost in terms of infrastructure, property, assets etc.

As natural disaster incidents are occurring frequently in Indian states, there is an urgent need for a framework to manage the logistics operations effectively and efficiently during any disaster relief operations. Limited literature is found on developing and presenting a framework focusing on the preparedness and response phase of disaster supply chain management in context to India. Hence, this paper is believed to be the first to fulfil this gap with main emphasis on the preparedness and response stage of disaster supply chain management in Indian scenario.

In today’s ever-changing global business environment, successful survival of manufacturing firms/production units depends on the extent of fulfillment of dynamic customers’ demands. Appropriate supply chain strategy is of vital concern in this context. Lean principles correspond to zero inventory level; whereas, agile concepts motivate safety inventory to face and withstand in turbulent market conditions. The leagile paradigm is gaining prime importance in the contemporary scenario which includes salient features of both leanness and agility. While lean strategy affords markets with predictable demand, low variety and long product life cycle; agility performs best in a volatile environment with high variety, mass-customization and short product life cycle. Successful implementation of leagile concept requires evaluation of the total performance metric and development of a route map for integrating lean production and agile supply in the total supply chain. To this end, the purpose of this paper is to propose a leagility evaluation framework using fuzzy logic.

A structured framework consisting of leagile capabilities/attributes as well as criterions has been explored to assess an overall leagility index, for a case enterprise and the data, obtained thereof, has been analyzed. Future opportunities toward improving leagility degree have been identified as well. This paper proposes a Fuzzy Overall Performance Index to assess the combined agility and leanness measure (leagility) of the organizational supply chain.

The proposed method has been found fruitful from managerial implication viewpoint.

This paper aimed to present an integrated fuzzy-based performance appraisement module in an organizational leagile supply chain. This evaluation module helps to assess existing organizational leagility degree; it can be considered as a ready reference to compare performance of different leagile organization (running under similar supply chain architecture) and to benchmark candidate leagile enterprises; so that best practices can be transmitted to the less-performing organizations. Moreover, there is scope to identify ill-performing areas (barriers of leagility) which require special managerial attention for future improvement.

The purpose of this paper is to develop a multi-level hierarchical framework (evaluation index system) toward evaluating an “appraisement index” from the prospectus of measuring and monitoring resilient performance of the candidate industry.

In this reporting, vagueness, imprecision, as well as inconsistency associated with subjective evaluation information (aligned with ill-defined assessment indices of SC resilience performance), has been tackled by the application of fuzzy theory.

Subjective evaluation information (expressed in linguistic term) acquired from the committee of decision makers (called expert group), against different resilience indices/metrics, has been fruitfully explored through the proposed fuzzy-based resilience performance appraisement module. Finally, a case study from an Indian automobile company has been conducted from the perspective of checking effectiveness of the proposed methodology for evaluation of appraisement index indicating SC resilience extent.

This methodology might be successfully applied to help other decision-making problems from the perspective of performance appraisal and benchmarking of candidate alternatives/choices under predefined criteria and subjective evaluation circumstances.

Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated since apart from objective criteria a number of subjective criteria need to be evaluated simultaneously. Plenty of decision support systems have been well documented in existing literature which considers either objective or subjective data set; however, decision support module with simultaneous consideration of objective as well as subjective data has rarely been attempted before. The paper aims to discuss these issues.

Motivated by this, present work exhibits application potential of preference ranking organization method for enrichment evaluations (extended to operate under fuzzy environment) to solve decision-making problems which encounter both objective as well as subjective evaluation data.

An empirical case study has been demonstrated in the context of robot selection problem. Finally, a sensitivity analysis has been performed to make the robot selection process more robust. A trade-off between objective criteria measure and subjective criteria measure has been shown using sensitivity analysis.

Robot selection has long been viewed as an important decision-making scenario in the industrial context. Appropriate robot selection helps in enhancing value of the product and thereby, results in increased profitability for the manufacturing industries. The proposed decision support system considering simultaneous exploration of subjective as well as objective database is rarely attempted before.