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The study aims to identify the potential drivers of big data analytics (BDA) practices in the supply chain and develop a sustainability evaluation model to evaluate drivers of big data for sustainability development.

The mixed-method approach was applied to assess sustainability dimensions and calculate the score using two phases. In Phase I, the BDA drivers in the e-commerce industry were finalised using the partial least square based structural equation modelling (PLS-SEM) method. In Phase II, a case study in the Indian fashion e-commerce industry was carried out to evaluate sustainability dimensions with respect to drivers of BDA and the sustainability score was calculated using the fuzzy analytical hierarchical process (AHP) method.

The index for economic sustainability (0.220), social sustainability (0.142) and environmental sustainability (0.182) were derived. The higher index value of economic sustainability compared to social sustainability and environmental sustainability signified those drivers of big data bring social and environmental uncertainty along with economic sustainability.

The study will help practitioners promote BDA use for developing environmental/social/economic sustainability in supply chains. Policymakers must ensure whether the integration of BDA practices brings down cost and brings strategic value for ensuring big data success. The study will help managers decide a constant trade-off between the requirement for social, environmental and economic performance.

The study corroborates and adds to the BDA literature by emphasising the positive role of BDA in sustainability development in the supply chain area and highlighting the significant role of different drivers of BDA in sustainability development.

Risk in the Halal food supply chain is considered as the failure to deliver the product which complies with Halal standards. The purpose of this paper is to identify the risk elements associated with Halal food supply chains and prioritise them appropriately towards better management.

This research used a systematic literature review to identify various risk elements in the Halal food supply chain and consolidate them with the expertise of professionals and academicians. Further, the fuzzy analytic hierarchical process (fuzzy AHP) is applied to prioritise the identified risk elements.

The findings of the research suggest that “supply-related risks” are the most prominent risk. Raw material integrity issue is a vital element in the Halal food supply chain. The failure of the supplier to deliver material that complies with Halal standards reduces the industrial economic advantage. This study recommends that the integration of internal processes and outsourcing elements can mitigate the risk of the Halal food supply chain by having a holistic view of the processing and delivery of Halal foods.

Systematic literature review and experts’ opinion are used to identify and consolidate risks. For the literature review, only the SCOPUS database is used; thus, there is a chance to overlook some risk elements. Additionally, the fuzzy AHP analysis depends on relative preference weight. Therefore, care should be taken while constructing a pairwise comparison matrix for risk elements.

The findings of the study can help the managers who have a holistic view on risk mitigation of the Halal food supply chain. This study may assist managers to share information about the processing of Halal food from top to bottom to manage risk.

This study may act as a baseline for undertaking future research in the area of risk management of the Halal food supply chain.

The contribution of women toward entrepreneurial activities has gained significant attention in recent years because of economic and social concerns, government support and initiatives and increased education and awareness. Women’s entrepreneurial activity has increased and women-owned businesses can today be found in every sector of the economy, irrespective of region. In India, government bodies such as the Ministry of Micro, Small and Medium Enterprises (MSMEs) and several other organizations (private and NGOs) have adopted considerable measures to promote women entrepreneurship (WE). To improve WE, the critical factors of WE adoption need to be identified and evaluated. The purpose of this paper is to identify, prioritize and evaluate the critical success factors of WE adoption in Indian MSMEs.

This paper proposes a methodology based on fuzzy analytical hierarchal process to prioritize the critical success factors of WE adoption. A numerical analysis of Indian MSMEs is presented to demonstrate the use of the proposed method. This proposed method considered fuzzy framework, which can handle impreciseness and uncertainty. Sensitivity analysis is also performed to test the robustness of the proposed model.

Potential critical success factors are identified from relevant literature and validated by industry experts. This research finalize the critical success factors of WE adoption in Indian MSMEs under seven dimensions, so prioritization of identified critical success factors can be developed and insights relationship of factors would be explored. The results of the study found that individual, management and government dimensions take paramount importance while women aim to become entrepreneurs in Indian MSMEs.

This study is limited to identifying evaluation factors; other factors have not been identified and categorized. Evaluation is one by experts in this area so it is natural that views of decision-makers may be subjective and vary with regard to industry-type, priorities, resources, etc.

This study will help industry to identify, evaluate and prioritize factors for successful implementation of women entrepreneurship. MSMEs could device these factors by applying the outcome of the study in their decisions with higher priority to implement women entrepreneurship culture.

Potential factors are identified from relevant literature and validated by industry experts. Indian MSMEs could device these factors by applying the outcome of the study in their decisions with higher priority to adopt women entrepreneurship.

Due to the introduction of new vaccines in the child immunization program and inefficient vaccine supply chain (VSC), the universal immunization program (UIP), India is struggling to provide a full schedule of vaccination to the targeted children. In this paper, the authors investigate the critical factors for improving the performance of the existing VSC system by implementing the next-generation vaccine supply chain (NGVSC) in India.

The authors design a fuzzy multi-criteria framework using a fuzzy analytical hierarchical process (FAHP) and fuzzy multi-objective optimization on the basis of ratio analysis (FMOORA) to identify and analyze the critical barriers and enablers for the implementation of NGVSC. Further, the authors carry out a numerical simulation to validate the model.

The outcome of the analysis contends that demand forecasting is the topmost supply chain barrier and sustainable financing is the most important/critical enabler to facilitate the implementation of the NGVSC. In addition, the simulation reveals that the results of the study are reliable.

The findings of the study can be useful for the child immunization policymakers of India and other developing countries to design appropriate strategies for improving existing VSC performance by implementing the NGVSC.

To the best of the authors’ knowledge, the study is the first empirical study to propose the improvement of VSC performance by designing the NGVSC.

The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context.

A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes.

The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology.

This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM).

Massive open online courses (MOOCs) are among the most recent e-learning initiatives to gain widespread acceptance among universities. However, despite MOOCs' “much-documented” benefits, many questions are being raised late regarding the long-term sustainability of the open online teaching e-learning model. With high dropout rates in MOOCs courses, recent research has focused on the challenges limiting MOOCs’ growth. But most of the research is directed toward students’ perspectives, leaving the instructors’ perspective. One of the most important aspects of instructors’ perspective is the motivation for MOOCs' development and delivery.

The present study collected the data from 25 MOOC developers of Indian origin. To prioritize or rank the motivational factor behind developing a MOOC, a fuzzy-analytical hierarchical process (F-AHP) technique was applied to the data set. The primary motivational factors considered for the study were professional development, altruism, personal development, institutional development, intrigue, monetary benefits and peer influence.

The results showed that professional development and personal development are two prime motives that drive MOOCs development. Monetary benefits and peer influence were the least important factors among all the factors considered for the study.

Previous studies have identified and modeled the motivational factors that contribute toward developing MOOCs. However, there was little knowledge about the hierarchy among the motivating factors. The present study fills this gap by establishing the ranking of motivational factors responsible for MOOCs development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0205.

This study aims to construct a valid hierarchical sustainable human resource management (SHRM) model with interrelationships among its attributes in terms of qualitative information.

This study applies the fuzzy Delphi method to validate SHRM attributes and visualize the causal interrelationships among these attributes using a fuzzy decision-making trial and evaluation laboratory method.

This study finds that green performance management and compensation lead to human resource benefits and economic sustainability in the HRM model.

Open environmental communication, green human resource planning, green training and development, employee eco-friendly behavior and organizational culture are the top five criteria supporting practical improvement in the healthcare industry.

The emergence of new, unprepared, and inexperienced health care entities with inadequate human resource management (HRM) potentially causing social problems within the industry, SHRM is necessary to balance the social, environment, and economic performance and must be studied by both academicians and practitioners. However, the HRM application field is still in its infancy, which limits the understanding of its potential.

The purpose of this research is to present an integrated methodological framework to aid in performance stewardship of management institutions according to their strategies based on a holistic evaluation encompassing social, economic and environmental dimensions.

A Mamdani fuzzy inference system (FIS) approach was adopted to design the quantitative models with respect to balanced scorecard (BSC) perspectives to demonstrate dynamic capability. Individual models were developed for each perspective of BSC using Mamdani FIS. Data was collected from subject matter experts in management education.

The proposed methodology is able to successfully compute the scores for each perspective. Effective placement, teaching learning process, faculty development and systematic feedback from the stakeholders were found to be the key drivers for revenue generation. The model is validated as the results were well accepted by the head of the institution after implementation.

The model resulting from this study will assist the institution to cyclically assess its performance, thus enabling continuous improvement. The strategy map provides the causality of the objectives across the four perspectives to aid the practitioners to better strategize. Also this study contributes to the literature of BSC as well to the applications of multi-criteria decision-making (MCDM) techniques.

Mamdani FIS integrated BSC model is a significant contribution to the academia of management education to quantitatively compute the performance of institutions. This quantified model reduces the ambiguity for practitioners to decide the performance levels for each metric and the priorities of metrics.

The aim of this study is to identify and rank the factors of innovation capability (IC) in Indian micro, small and medium enterprises (MSMEs). This study focuses on ascertaining the important factors that help in enhancing the IC with an emblematic focus on the MSME sector of India.

This paper proposes a multicriteria decision-making methodology, which is based on fuzzy analytic hierarchical process to prioritize the factors that enhance the IC of MSMEs. Finally, sensitivity analysis is conducted to examine the ranking stability.

Knowledge management is the most important enabler, followed by creativity and idea management and organizational culture.

Several organizations promote the strategic measures for enhancing the IC. To increase their capability to innovate, there is a need to identify, acknowledge and implement the drivers of IC into practice.

Prioritization done in the study facilitates the entrepreneurs to determine the most important factors that need crucial attention in dealing with sensitive issues of IC. Entrepreneurs can take several steps to implement the most important factors for enhancing the IC into practices for meeting the needs of the consumers, generating profits and enhancing the competitiveness.

The purpose of this paper is to identify and prioritize the measures of intellectual capital (IC) of e‐learning service companies that ultimately influence firms' competitive advantages.

Through focus group interviews, content analysis, and the analytic hierarchy process, this paper identifies five dimensions and 15 indicators to measure the IC of e‐learning service companies in Taiwan.

The findings and prioritization of ICs can help the e‐learning companies to understand the critical success factors that facilitate gaining their competitive advantages in Taiwan.

The focus of this paper is only on e‐learning companies located in Taiwan, thus the results cannot be generalized to all e‐learning companies. Additionally, only five main dimensions are identified from the study, there is a possibility that this study does not cover all the important dimensions of IC of e‐learning companies.

e‐Learning companies can use the IC measurement tool developed in this study to detect IC weaknesses and strengths. Moreover, e‐learning companies need to re‐consider the portfolio of their IC that make e‐leaning more competitive in industry.

This paper finding contributes to the present body of knowledge and also highlights IC dimensions that can provide a reference for e‐leaning companies to develop favorable strategies for achieving their goal of enhancing competitive advantages.