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The objective of the study is to test a conceptual model based on the interrelation between data-driven supply chain quality management practices (DDSCQMP) and the performance of organized retailing firms in India.

Based on a comprehensive review of literature, the dimensions of DDSCQMP concerning the Indian organized retail sector have been extracted. Considering the research objectives, the research data has been collected using a structured questionnaire from Indian retailers. Overall 133 questionnaires were responded successfully from retailers. The model was tested using structured equation modeling (SEM) through PLS 3.0.

The research findings confirm hypotheses and reveal the statistically significant relationship between DDSCQMP and retailers' performance at an aggregate level. However, the results of the individual-level analysis of DDSCQMP appear to vary from practice to practice. Among various DDSCQMP, “customer focus” with the highest beta (ß) value was found to have the greatest impact on performance followed by “employee relations”.

The study provides empirical justification for a structural model that identifies a positive and significant relationship between DDSCQMP and organizational performance within the context of organized retail sector of India.

In the uncertain business environment, the supply chains are under pressure to balance routine operations and prepare for adverse events. Consequently, this research investigates how artificial intelligence is used to enable resilience among supply chains.

This study first analyzed the relationship among different characteristics of AI-enabled supply chain and how these elements take it towards resilience by collecting the responses from 27 supply chain professionals. Furthermore, to validate the results, an empirical analysis is conducted where the responses from 231 supply chain professionals are collected.

Findings indicate that the disruption impact of an event depends on the degree of transparency kept and provided to all supply chain partners. This is further validated through empirical study, where the impact of transparency facilitates the mass customization of the procurement strategy to Last Mile Delivery to reduce the impact of disruption. Hence, AI facilitates resilience in the supply chain.

This study adds to the domain of supply chain and information systems management by identifying the driving and dependent elements that AI facilitates and further validating the findings and structure of the elements through empirical analysis. The research also provides meaningful implications for theory and practice.

Today many firms are pushed towards digitalization to ensure business continuity and their survival due to COVID-19. Therefore, this study aims to investigate the emerging knowledge management models in the era of digitalization and disruption.

The authors have adopted a semi-structured approach composed of qualitative data collection from 37 business executives from India representing different industry sectors. The authors adopted a three-layer coding process (axial, open and selective) to develop a framework grounded in organizational information processing theory.

Scanning the business environment leads to understand the status of current and potential business through intelligence of information, whereas better planning and execution can be achieved through employing and using the information intelligently that fits to the overall and strategic objective of the business. Overall, the business continuity can be obtained by information prosperity across the business by engaging diverse stakeholders. According to the findings, these aspects lead to the effective implementation of digital knowledge to ensure business continuity in uncertain business environment.

The study offers the insights for managing and executing the knowledge in digital platforms, where they can think of developing a system architecture on the basis of degree of uncertainty and information processing requirements for combining the knowledge.

The present study is unique, where it offers the meaningful visions to the designers and users of virtual knowledge management systems.

The study aims to map the links between Industry 4.0 (I-4.0) technologies and circular economy (CE) for sustainable operations and their role to achieving the selected number of sustainable development goals (SDGs).

The study adopts a systematic literature review method to identify 76 primary studies that were published between January 2010 and December 2020. The authors synthesized the existing literature using Scopus database to investigate I-4.0 technologies and CE to select SDGs.

The findings of the study bridge the gap in the literature at the intersection between I-4.0 and sustainable operations in line with the regenerate, share, optimize, loop, virtualize and exchange (ReSOLVE) framework leading to CE practices. Further, the study also depicts the CE practices leading to the select SDGs (“SDG 6: Clean Water and Sanitation,” “SDG 7: Affordable and Clean Energy,” “SDG 9: Industry, Innovation and Infrastructure,” “SDG 12: Responsible Consumption and Production” and “SDG 13: Climate Action”). The study proposes a conceptual framework based on the linkages above, which can help organizations to realign their management practices, thereby achieving specific SDGs.

The originality of the study is substantiated by a unique I-4.0-sustainable operations-CE-SDGs (ISOCES) framework that integrates I-4.0 and CE for sustainable development. The framework is unique, as it is based on an in-depth and systematic review of the literature that maps the links between I-4.0, CE and sustainability.

This paper aims to identify and examine the determinants for sustainable manufacturing in cement manufacturing industry in India. Further, the study examines the causal relationship between different indicators of sustainable manufacturing.

Author (s) have identified and extracted the key dimensions of sustainable manufacturing from literature. After identification of the key dimensions, analytic hierarchy process (AHP) is used to finalize the weights and further DEMATEL is used to understand the causal relationship between key dimensions.

Findings from AHP provide the weightage to the all 13 indicators of sustainable manufacturing. From AHP, it is identified that material cost has maximum weightage, whereas material consumption has minimum weightage. From DEMATEL, it is evident that occupational health safety and safety has maximum influencing variables, whereas air emission does not have any influencing variables.

The approach adopted in the study will help firms to identify the weightage of key dimensions and further the interdependency can be developed to understand the causal relationship between different indicators of sustainable manufacturing.

The purpose of this paper is to map the causal relations among various supply chain flexibility (SCF) dimensions having significant impact on the Indian personal hygiene industry.

The author(s) have gone through extensive literature review and extracted 22 SCF dimensions. After conducting field visits and expert interaction in the firm related to case industry, 11 major SCF dimensions that seem to have a significant amount of influence on supply chain performance of the firms were retained for further consideration. The author(s) have used decision making trial and evaluation laboratory (DEMATEL) to establish initial causality and structural equation model (SEM) to investigate the contribution of different flexibility dimensions on overall SCF.

After DEMATEL analysis, three major SCF dimensions were considered for SEM modeling. The result shows that product flexibility and physical distribution flexibility have favorable influence on the SCF, while the demand management flexibility adversely impacts overall SCF.

The approach adopted in the study can help firms to determine and exercise the flexibility dimensions of a particular supply chain. The DEMATEL and SEM offer a facilitation to explain the causal relationship between the different dimensions to take long-term decisions and address the uncertainty in the demand and supply side.

This paper has made an attempt to evaluate the supply chain flexibilities, prioritize them and evaluate the relationship amongst these flexibilities and the degree to which they affect or are affected by one another in the Indian personal hygiene industry.

The purpose of this study is to quantify the supply chain flexibility for an Indian soap manufacturing firm and to measure its performance. The authors made an attempt to find key strategic and operational decision-making dimensions for developing effective supply chain flexibility environment.

The authors have extracted 11 supply chain flexibility dimensions through extensive literature review. The authors used a decision-making trial and evaluation laboratory (DEMATEL) to make causal analysis and prioritizing the dimensions. After DEMATEL analysis three major supply chain flexibility dimensions that seem to have significant amount of influence on supply chain performance of the firms were retained for further consideration. The authors have developed an excel-based template for quantitative assessment of flexibility performance indicators.

This study provides key enablers for the successful implementation of flexibility concepts in Indian soap manufacturing firms and gives a view how to measure the performance through designing template based on real data. This template can be used in other firms also by simply modifying the key attributes.

A flexibility index has been defined here with the purpose of assessing the level of flexibility vis-a-vis what is desired and is meant to be evaluated from time to time, to assess if the firm is improving its flexibility or not. The index assumes importance in view of the fact that it has been prepared based on feedbacks of both the upper and the lower management people of the firm engaged in policymaking and operations.

The purpose of this paper is to identify dimensions of competitiveness, factors affecting the competitiveness and building the framework of competitiveness for the Indian auto-component industry and further develop and validate a survey instrument based on the identified factors.

Dimensions of competitiveness and factors affecting it are extracted out after extensive literature review. A theoretical framework is developed using these factors. A survey instrument is developed based on the theoretical framework and validated through a pilot survey.

In total, 30 variables are found to be reliable in establishing the potential indicators of competitiveness. There are three significant contributions to the theory of competitiveness. It provides a theoretical framework of competitiveness to address the current market conditions of volatility. Second, it incorporates the dimensions like supply chain management, presence of global value chains and employee empowerment. Third, it clearly identifies the dimensions of competitiveness relevant in current context, like ethical behavior of firms, protection of intellectual property and innovation.

The proposed approach provides a good basis for assessing the competitive performance of the companies. This can help researchers and practitioners in deciding how to improve the competitiveness of a company.

The research proposes a theoretical framework for measuring the competitiveness of firms from a specific industry. This study indicates the factors affecting the competitiveness of Indian auto-component industry. The findings can be useful for both researchers and practitioners.

The health-care industry has multiple stakeholders, with knowledge dispersed among clinicians, experts and patients and their families. As the adoption of health-care information technologies (HITs) depends on multiple factors, this study aims to uncover the motivators for adopting them.

The study considers 391 respondents, representing the health-care sector, to evaluate the motivators for adopting HITs for better-dispersed knowledge management. The authors analyze the responses using exploratory factor analysis (EFA) to identify the actual structure of the factors, followed by confirmatory factor analysis (CFA).

EFA categorized the factors into four classes: quality management; information sharing; strategic governance; and available technological infrastructure. CFA revealed that the strategic governance factor is most predictive of successfully adopting HITs that model the normative pressure of Institutional theory in health-care organizations. These results indicate that, along with considerations of finances, care quality and infrastructure, effective government involvement and policy-making are important for successful HIT adoption.

Results reveal that stakeholders’ motivating factors for HIT adoption in a developed economy like the United Arab Emirates are based on considering HITs as a knowledge management mechanism. These factors may help other nations in HIT implementation and drive valuable innovations in the health-care sector. This research presents the implications for health-care professionals and stakeholders in relation to adopting HITs and their role in knowledge flow for efficient care.

HITs offer an affordable and convenient platform for collaboration among diverse teams in the health-care sector. Apart from this, it helps in facilitating an interactive platform for knowledge creation and transfer for the benefit of users and providers.

Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT).

This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA).

EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use.

The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive.

This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry.

This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.