Purpose: The purpose of this paper is to explore the phenomenon of collaborative resilience through in-depth case study research in India. This study endeavours to identify and model the critical success factors of collaborative resilience.Design/methodology/approach: Eight critical success factors of collaborative resilience were identified through literature search. Modelling and analysis of these factors was conducted using grey-based DEMATEL method. Data were collected from supply chain experts in Indian industries.Findings: It was found that organizational factors like top management commitment and resilience system design exhibit highest causality on the entire system. Also, co-adaptive transformation and resilience goal alignment are most important for managers. Overall, this research provides a guideline and mechanism to build collaborative resilience in supply chains.Practical implications: Through the identification of eight critical success factors, this research has related and grounded the concept of collaborative resilience into pre-exiting supply chain practices and concepts. Through rigorous quantitative modelling and analysis of these factors, this research provides a guideline to managers for building collaborative resilience in supply chains.Originality/value: To the best of the authors’ knowledge, this is the first study that has proposed the concept of collaborative resilience in supply chain and has conducted empirical research on the phenomenon in India.

Purpose: The purpose of this paper is to understand the process and role of supply chain collaboration in Indian agri-food industry and highlight the perceptions of buyers and suppliers towards each other. The paper seeks to find out how can collaboration in agri-food supply chain lead to low wastage and better efficiency. Also, the paper attempts to capture the nuances of collaborative practices and perceptions of buyers and suppliers towards collaboration.Design/methodology/approach: Case study methodology in a top Indian food-processing firm was conducted to explore the application and benefits of collaboration in supply chains. In-depth interviews with upstream supply chain members were conducted to understand the process of supply chain collaboration. Grounded Theory Methodology was used to analyze the transcripts.Findings: Firstly, through content analysis of interview transcripts a comprehensive framework and a generic model was derived to understand the process of supply chain collaboration. Supplier selection, Joint Planning and Information sharing were found to be main antecedents while profits; waste reduction and supply chain efficiency were major outcomes of collaboration. Secondly, it was found that the suppliers are usually more skeptical of the buyers and don’t trust them easily. While, for buyers, it is very important to have good relations with suppliers and should make provide incentives to suppliers for collaboration.Originality/value: To the best of our knowledge, this is the first study to elaborate the process and outcomes of collaborative activities along an Indian agri-food supply chain through in-depth qualitative study. In developing countries, agriculture industry is the backbone of economy. Therefore, the insights developed in this study may be useful for managers in agribusiness to dwell into such supply chain practices that would increase profit and efficiency, and decrease wastage.

Artificial Intelligence (AI) adoption is transforming many industries, but its impact on the healthcare sector is life-changing. Recent studies and tests show that AI can deliver identical or better prognoses, diagnoses, and surgical outcomes than medical professionals. Healthcare sectors are adopting AI, and its applications are reforming it by reducing expenditure and exceeding patient satisfaction. The dearth of AI advocacy and adoption has forfeited large annual opportunity costs for the health industry and artificial intelligence engineers (AIE). There is a shortage of studies using quantitative models to test the barrier interrelationship and its effect on AI adoption, especially from the perspective of a developing country like India. Therefore, this study explores the barriers to adopting AI in healthcare in India. A total of 250 barriers related to technology adoption are determined after thoroughly analyzing previous studies and several focus group discussions (FGDs). Barriers are reduced to 16 most relevant barriers through multiple Healthcare expert FGDs and the DELPHI method. Interpretive structural modelling (ISM) and crossimpact matrix multiplication applied to classification (MICMAC) are the analytical techniques used to classify the barriers into different impact levels and importance. The derived outcomes from the ISM and MICMAC methods illustrate that the unavailability of infrastructure and policy support and AI's potential cybersecurity vulnerabilities are the predominant problems for AI adoption in healthcare. The outcome is proposed to add to the theory of technology adoption, which facilitates the organizations in selecting the technology and opening the path for its spread and use by healthcare stakeholders.

Purpose: Research on sustainability has progressed from a singular focus on one aspect to a simultaneous focus on more than one aspect of the triple bottom line. However, there is a dearth of research that explains why sustainability-related decisions in business often do not bear the expected results. Research that provides managers with a tool to achieve environmental sustainability of logistics without compromising the economic sustainability is scarce. Hence, the purpose of this paper is to bridge the above gaps and to explore the factors that affect investment in technology to balance environmental and economic sustainability of logistics. A model based on system dynamics approach explains the simultaneous interplay of these factors. Simulating the model helps the managers of logistics function decide the size of investment in technology, to achieve environmental efficiency without negatively influencing the economic performance.Design/methodology/approach: A model based on system dynamics approach explains the simultaneous interplay of these factors. Simulating the model helps the managers of logistics function decide the size of investment in technology, to achieve ecological efficiency without compromising with the economic performance.Findings: Collaboration with regulatory authorities and with players within the same industry and across industries is a must so that eco-logistics does not become an economic burden for businesses. The decision to invest in technology for eco-logistics is further accentuated if the technology promises some added economic benefits.Research limitations/implications: From a theoretical perspective, the research has added to the less extensive literature on system dynamics modelling, which is a mixed methodology, combining both qualitative and quantitative techniques. The research is also one of the few attempts that have attempted to simultaneously study more than one aspects of sustainability in business, quantitatively through simulation. Simulation was demonstrated through a single case study, Future works can aim to apply the causal loop diagram to firms in varied sectors.Practical implications: The managers can use the causal loop diagram to assess the environmental performance of logistics and decide on appropriate level of investment to balance ecological and economic performance of logistics.Originality/value: The causal loop diagram has been developed through primary data collection via semi-structured interviews. The results were validated by presenting them to respondents to ensure they represent their view points. The results are, therefore, practical and original. This research does not build upon an existing data set or aims to test the applicability of any existing model. The model for this research has been developed from the grass-roots level.

The healthcare sector has undergone significant changes in recent times due to the implementation of digitalization and Industry 4.0 technology. Digital Twins (DTs), which are virtual replicas of physical objects, products and/or services, have the potential to become a significant competitive advantage within the healthcare industry. Our present study aims to fill the existing research gap and contribute to the advancement of DT in healthcare supply chain and operations management by finding the barriers for DT adoption. We achieved this by synthesizing relevant literature and conducting a systematic literature review. We have further categorized the barriers using the Technology-Organization-Environment (TOE) framework as the outcome of the research, both as a theoretical contribution and to assist industry practitioners in focusing on barriers specific to their domain for the successful implementation of DT technology. The future research avenues are proposed based on the identified barriers.

Purpose: The purpose of this paper is to identify and prioritize the drivers, enablers and resistors of agri-logistics improvements in an emerging economy like India. The field of agri-logistics lies at the critical intersection of the agricultural and logistics sectors and is capable of ameliorating the state of food distribution in the country. The inefficiencies inherent in the food distribution system in India lead to massive post-harvest wastage that is estimated at around 13bn dollars per annum. This paper examines the improvement drivers, enablers and resistors of agri-logistics that can significantly contribute toward the enhancement of the agricultural supply chain. Design/methodology/approach: The synthesis and prioritization of drivers, enablers and resistors was based on an extensive literature review and consultation with experts. With the help of semi-structured interviews and a fuzzy analytic hierarchy process approach, the research develops a drivers-enablers-resitors framework. Findings: The outcome is a hierarchy-based framework that prioritizes the drivers, enablers and resistors of agri-logistics. The research reveals the critical areas where decision makers should channelize their resources and efforts to gain maximum benefits. Originality/value: The segmentation of the factors impacting agri-logistics into drivers, enablers and resistors provides a fresh perspective on the issue and helps improve understanding of the problem. Prioritization of the factors represents a unique contribution to the field of agri-logistics.