Search results

Corporate leadership and environmental, social and governance (ESG) performance are closely intertwined, as effective corporate leadership can facilitate the achievement of strong ESG performance. Thus, the purpose of the study is to investigate the impact of corporate board leadership on the ESG performance of listed firms.

The sample has been taken from the listed firms of the Nifty 500 index spanning the period of 10 years from 2012 to 2022. Dynamic panel data estimations are applied through a fixed effect model.

The findings of this study revealed that board size, board independence and board qualification have a significant positive influence on ESG performance. It is evident that good corporate governance practices can positively influence ESG performance by fostering accountability, transparency and ethical behavior, as well as better integrating ESG considerations into their decision-making processes and ensuring that ESG issues are prioritized at the highest levels of management. Further findings also revealed that chief executive officer (CEO) duality has a significant negative relationship with ESG performance, which goes against the belief of stakeholder theory.

It has practical implications for policymakers, as they can enact new regulations pertaining to the CEO’s position in the organizations to make corporate governance responsible for improved sustainability and ESG performance.

There are very few studies analyzing the impact of corporate board structure on ESG performance related to emerging markets. Thus, this study contributes to that literature by using the methodology GMM panel data for the first time as per our knowledge

By celebrating tourism destinations through cruise collections, luxury brands open to new influences. They may develop deeper connections with certain geographical areas, but may also challenge the quintessentially national dimension of luxury brand culture. The best example of synergies between a luxury fashion brand and tourism destinations are the Christian Dior cruise collections with Maria Grazia Chiuri at the helm. This chapter is to understand how cruise collections may enhance luxury fashion houses' brand culture through the connections they develop with tourism destinations. Further, the chapter assesses the extent to which destinations can benefit from the exposure provided by luxury fashion brands' cruise collections.

This paper aims to investigate the role of corporate governance on the bank profitability of Indian banks vis-à-vis South Asian Association for Regional Cooperation (SAARC) nations.

For the Corporate Governance Index, the authors examined board accountability, transparency and disclosure and audit committee, while Tobin’s Q, return on equity and return on assets are used to measure the bank’s profitability. The study used a two-stage analysis based on balanced panel data for robust findings. Sample of this study consists of 60 commercial banks from India and 60 banks from SAARC nations for the period of 2009–2021. This study used panel regression and a generalized method of moment approach using the CAMELS framework on banking industry-specific variables to determine their respective impacts.

The findings of this study suggest that board accountability is positive and significantly affects the profitability of banks as indicated by return on assets, return on equity and Tobin’s Q. In contrast, the audit committee has a positive and insignificant impact on return on assets, return on equity and Tobin’s Q, while transparency and disclosure have a negative and significant impact on these metrics. Furthermore, the country dummy result shows a significant positive impact on all the bank performance parameters, implying that Indian banks have the highest degree of convergence with corporate governance as compared to other SAARC nations.

This study provides insight to the regulators, policymakers and financial institutions to evaluate the role of corporate governance in emerging economies. However, the findings of the study should be interpreted with caution, as the results are sensitive to the disparity between India and other SAARC nations' government policies, climatic circumstances and cultural or religious traditions.

To the best of the authors’ knowledge, this is the first attempt to gauge the performance of Indian banks vis-à-vis SAARC nations using the CAMELS framework approach. Further, findings of this study suggest some novel evidence tying corporate governance quality with the profitability of banks among SAARC nations.

The purpose of the paper is to propose a semantic model for describing open source software (OSS) in a machine–human understandable format. The model is extracted to support source code reusing and revising as the two primary targets of OSS through a systematic review of related documents.

Conducting a systematic review, all the software reusing criteria are identified and introduced to the web of data by an ontology for OSS (O4OSS). The software semantic model introduced in this paper explores OSS through triple expressions in which the O4OSS properties are predicates.

This model improves the quality of web data by describing software in a structured machine–human readable profile, which is linked to the related data that was previously published on the web. Evaluating the OSS semantic model is accomplished through comparing it with previous approaches, comparing the software structured metadata with profile index of software in some well-known repositories, calculating the software retrieval rank and surveying domain experts.

Considering context-specific information and authority levels, the proposed software model would be applicable to any open and close software. Using this model to publish software provides an infrastructure of connected meaningful data and helps developers overcome some specific challenges. By navigating software data, many questions which can be answered only through reading multiple documents can be automatically responded on the web of data.

This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.

The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.

This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.

Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.

This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.

This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.

This study anchoring on the theory of conservation of resources examines the relationship between family incivility, negative rumination and service delivery. This study also analyses the mediating role of negative rumination in the relationship between family incivility and service delivery. This study also examines psychological capital and perceived organisational support (POS) as boundary conditions influencing the relationships postulated in the study.

To test the relationships among the variables, responses were drawn from 419 frontline hotel employees at two-time points and the hypothesised relationships were tested using structural equation modelling.

The structural equation modelling analysis proved that family incivility is negatively related to service delivery. It was also found that family incivility is positively associated with negative rumination and an inverse relationship between negative rumination and service delivery. This study also found support for the mediating role of negative rumination and the moderating roles of psychological capital and perceived organisational support.

This study findings extend the theory and provide guidelines for managers to mitigate the adverse effect of family incivility on employees and their service delivery. Employees and managers can use psychological capital and POS as strategies to prevent the spill-over effect of family incivility on service delivery.

To the best of the authors’ knowledge, no prior studies have examined the effect of family incivility on service delivery. By establishing the mediating mechanism and boundary conditions, this study adds value to the theory and practice.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.