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Sustainability issues on economic, environmental and social perspectives have drawn attention of environmentalists, ecologists and governments. In this context, circular economy provides an opportunity to transform waste into resources, reduction of production and consumption activities; and reduction of carbon footprints, all at the same time. The purpose of this paper is to develop a strategic framework for measuring circular supply chain management.

A grounded theory approach has been used to develop the strategic framework for circular supply chain management.

This study provides an integrative framework for studying, designing and evaluating circular supply chain management performance matrix.

A conceptual strategic framework has been proposed to measure the performance of circular supply chain management. Further empirical studies may be carried out to validate the framework.

The conceptual strategic framework provides key indicators for reducing material consumption, reducing waste, reducing carbon footprint and recycling opportunities throughout the supply chain. These may be utilized by practitioners for gaining competitive advantage.

This paper provides insights into development of circular supply chains that provides opportunities for cost reduction and securing competitive advantage for a business in the long run.

The surging entrance of new mobile payment merchants into the growing market has prompted the need for an in-depth understanding of loyalty formation to retain customers. This study examines customers' loyalty generation process in mobile payment services by exploring the serial effect of cognitive drivers (i.e. brand awareness, perceived quality, brand image, perceived value and layout) on affective response, satisfaction and loyalty.

A survey using self-administered questionnaires was conducted. The data was collected from 370 consumers who have experience using mobile payment services in Vietnam. The data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural networks (ANN) analysis.

The results indicated that all the proposed cognitive drivers show significant impacts on affective response, which, in turn, translates into satisfaction and loyalty. The post-hoc analysis revealed enjoyment as the vital affective response in determining satisfaction. Moreover, the multigroup analysis indicated that the relationship between affective response and satisfaction is stronger for the female group. In addition, the ANN's nonlinear result revealed complementary insight into the importance of cognitive drivers.

The current study revealed both linear and nonlinear mechanisms that explicate the roles of cognitive drivers and affective responses in fostering loyalty toward mobile payment merchants. The findings add to the existing literature that emphasizes consumers' initial mobile payment adoption.

The purpose of this paper is to investigate students' adoption intention (ADI) and actual usage (ATU) of artificial intelligence (AI)-based teacher bots (T-bots) for learning using technology adoption model (TAM) and context-specific variables.

A mixed-method design is used wherein the quantitative and qualitative approaches were used to explore the adoption of T-bots for learning. Overall, 45 principals/directors/deans/professors were interviewed and NVivo 8.0 was used for interview data analysis. Overall, 1,380 students of higher education institutes were surveyed, and the collected data was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.

The T-bot's ADI’s antecedents found were perceived ease of use, perceived usefulness, personalization, interactivity, perceived trust, anthropomorphism and perceived intelligence. The ADI influences the ATU of T-bots, and its relationship is negatively moderated by stickiness to learn from human teachers in the classroom. It comprehends the insights of senior authorities of the higher education institutions in India toward the adoption of T-bots.

The research provides distinctive insights for principals, directors and professors in higher education institutes to understand the factors affecting the students' behavioral intention and use of T-bots. The developers and designers of T-bots need to ensure that T-bots are more interactive, provide personalized information to students and ensure the anthropomorphic characteristics of T-bots. The education policymakers can also comprehend the factors of T-bot adoption for developing the policies related to T-bots and their implications in education.

T-bot is a new disruptive technology in the education sector, and this is the first step in exploring the adoption factors. The TAM model is extended with context-specific factors related to T-bot technology to offer a comprehensive explanatory power to the proposed model. The research outcome provides the unique antecedents of the adoption of T-bots.

The purpose of this study was to investigate the online shopping intention of customers by watching artificial intelligence (AI)–based deepfake video advertisements using media richness (MR) theory and Information Manipulation Theory 2 (IMT2).

A conceptual model was developed to understand customers' online shopping intention by watching deepfake videos. A quantitative survey was conducted among the 1,180 customers using a structured questionnaire to test the conceptual model, and data were analyzed with partial least squares structural equation modeling.

The outcome of this research provides the antecedents of the online shopping intention of customers after watching AI-based deepfake videos. These antecedents are MR, information manipulation tactics, personalization and perceived trust. Perceived deception negatively influences customers' online shopping intention, and cognitive load has no effect. It also elucidates the manipulation tactics used by the managers to develop AI-based deepfake videos.

The distinctive model that emerged is insightful for senior executives and managers in the e-commerce and retailing industry to understand the influence of AI-based deepfake videos. This provides the antecedents of online shopping intention due to deepfakes, which are helpful for designers, marketing managers and developers.

The authors amalgamate the MR and IMT2 theory to understand the online shopping intention of the customers after watching AI-based deepfake videos. This work is a pioneer in examining the effect of AI-based deepfakes on the online shopping intention of customers by providing a framework that is empirically validated.

The purpose of this article is to provide an analysis of quality management using the Malcolm Baldrige National Quality Award Criteria (MBNQA) criteria in a 300‐bed hospital in South India.

Based on Malcolm Baldrige National Quality Award (MBNQA) criteria in‐depth interviews are conducted with the heads of the departments in the case hospital. Data is analysed and compared with the MBNQA points to evaluate the performance of the hospital in all the seven criteria's of MBNQA.

The paper presents the strengths and opportunities for improvement through MBNQA criteria. The total points scored are 753 out of 1,000 points. This reveals that quality performance of case hospital is of higher level. However among all the seven criteria, the hospital has still more opportunity to improve the quality in MBNQA criteria no. 4, i.e. measure, analysis and knowledge management.

This study brings out a potential area of research about how the ratings and activities in the case hospital compares with other health care organisations.

The outcome of this paper clearly indicates that MBNQA criteria act as a powerful tool to analyse the quality performance of the hospital. The health care organisations can use MBNQA as self‐assessment tool to evaluate and to improve the health of the hospitals. MBNQA as self‐assessment tool help the hospitals to lay the road map for world‐class performance.

The paper illustrates the measurement of quality performance through MBNQA to the healthcare administrators that is the first step for managing and improving quality in health care organisations. It provides lessons for those hospitals that have already started quality initiatives.

Given the widespread lack of proper mechanism for disaster management, this paper aims to develop a disaster mitigation framework using quality circle (QC) – a bottom‐up approach.

The paper considers QC and discussing the utility of the concept with respect to disaster management. Discusses the process of systematically building a disaster mitigation framework.

By having the proposed framework, the disasters that occur can be tackled speedily. Owing to the direct involvement of public (key stakeholders), the proposed framework strengthens the knowledge and awareness on disaster management, which in turn helps towards disaster preparedness and disaster mitigation effectively.

The current efforts at disaster mitigation are not successful. The proposed framework provides proactive collaboration among all players including central, state governments and local people to examine risks and vulnerability to all hazards and to implement measures to reduce the damage to a minimum. The application of a framework will help to make plans more functional and relevant and will ensure successful disaster mitigation.

As no systematic frameworks exist in disaster management and planning, this paper offers to provide a comprehensive framework, which involves all the stakeholders. The value of the paper is largely in the area of bringing new possibilities to the attention of the government, public and research and practitioner communities dealing with disaster management.

The purpose of this paper is to identify the critical distribution practices of agile supply chains and provide a comprehensive framework that can be used to improve the responsiveness of supply chains. The research is carried out in the context of different manufacturing industries and provides empirical evidence that agile supply chain distribution enhances organisational performance.

The paper employed survey research, using a sample of 128 manufacturing companies.

The paper explores the critical distribution practices of supply chains that make supply chains agile. Collaborative distribution, order commitment, distribution flexibility and inventory management are the key SCM distribution practices associated with agile supply chains, and have significant impact on organisational performance.

Data were collected from a single node/respondent of a supply chain. Further research could be carried out using mutiple node data of each supply chain to make the research more meaningful and generalisable.

The findings may be used to gauge the competitive capabilities of SCM distribution and to guide organisations to measure and improve supply chain responsiveness and organisational performance.

The paper provides evidence regarding the impact of the critical distribution practices of agile supply chains on performnace.

The paper aims to develop and examine benchmarking performance measures for the extended enterprise (EE).

A research model was constructed based on 16 performance measures in eight categories. An online survey by questionnaire is conducted with manufacturing industries in China. There is an evaluation of the level of importance among these performance measures. Results of the survey are subjected to appropriate statistical tests to establish reliability and validity.

Results of the empirical research provide the benchmarking performance measures of a successful EE. Results of the survey indicate that performance measures in operation and customer categories are more important than others.

The paper has a limitation on the sample size. Further, data collection would be beneficial.

Participants of EEs can use these performance measures to design their benchmarking and key performance indictors to pursue the continued success of their EEs.

The paper builds on current literature and develops a conceptual model, which is then tested via a questionnaire survey. Only a limited literature has addressed the benchmarking performance measures for EE.