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The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize existing systems and processes. This research aims to inspire the creation of new innovative solutions for industries. By harnessing blockchain technology, organizations can pinpoint key areas that could significantly benefit from its use, such as streamlining operations, providing secure and transparent digital solutions and fortifying data security.

This study presents a robust multi-criteria decision-making framework for assessing blockchain drivers in selected Indian industries. We initiated with an extensive literature review to identify potential drivers. We then sought the opinions of experts in the field to validate and refine our list. This meticulous process led us to identify 26 drivers, which we categorized into five main categories. Finally, we employed the Best-Worst Method to determine the relative importance of each criterion, ensuring a comprehensive and reliable assessment.

The authors have ranked the blockchain drivers based on their degree of importance using the Best-Worst Method. This study reveals the priority of BC implementation, with the retail industry identified as the most in need, followed by the Banking and Healthcare industries. Various critical factors are identified where blockchain technology could help reduce costs, increase efficiency and enable new innovative business models.

While this study acknowledges potential bias in driver assessment relying on literature and expert opinions, its findings carry significant practical implications. We have identified key areas where blockchain technology could be transformative by focusing on select industries. Future research should encompass other industries and real-world case studies for practical insights that could delve into the adoption challenges and benefits of blockchain technology in many other industries, thereby amplifying the relevance of our findings.

Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in specific industries or sectors. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain across different Indian industries. Our research seeks to address this gap by using advanced multi-criteria decision-making techniques. We aim to provide a comprehensive understanding of the significance of blockchain technology in critical Indian industries, offering valuable insights that can inform strategic decision-making and drive innovation in the country’s business landscape.

The purpose of the study is to explore the relationship among organisation information technology support (OITS), knowledge sharing behaviour (KSB) and service innovation performance (SIP) in the context of the Indian Hospitality Industry (IHI). This study also attempts to examine the role of KSB as a mediator in the relationship between IT support and SIP and the firm age test as a moderating variable for service innovation performance.

Proposed relations are empirically examined, and the study was carried out on 115 employees from 71 randomly selected hotels situated in the major five travel destinations of Uttarakhand state of India. Initially, confirmatory factor analysis was performed to validate the construct, afterword structural equation modeling (SEM)-Path analysis was accomplished. The researcher examines the mediation and moderation relations of the variables through statistical tests executed with the help of AMOS 24 and SPSS 26.

The study result indicated that organisation IT support has a positive influence on knowledge sharing and SIP. The mediation result findings showed KSB is partially mediated between OITS and SIP. Sequentially, firm age moderation found the statistical results shown significant difference in young and old hotels.

This study only covers the aspect of the “knowledge sharing behaviour” dimension among the major organizations’ IT support capabilities and examined both variables that might be anticipated in SIP. Considering this limitation, new areas of research investigation are open to future researchers.

The study has both theoretical and managerial implications for academicians, practitioners and researchers. An attempt to conceptualise detailed insights on organisational IT support adaptation and KSB enhancement, which further leads to lifting SIP. Moreover, the study recommended for professionals to implement KM practices and mobilise the knowledge resources optimally to achieve better organizational outcomes.

The study attempts to delineate the proposed relationship and provides valuable insights for practitioners and academicians by including the knowledge sharing dimension to improve the SIP context of the IHI.

The study aims to examine the effect of knowledge management strategy (KMS) on knowledge-sharing behavior (KSB) and its subsequent effect on knowledge performance (KP). It also throws light on the mediating role of KM enablers (KMEs) and KSB.

In purview of previous literature, several hypotheses were framed. Structural equation modeling (SEM) using SPSS 20, PROCESS macro and AMOS 20 was used to examine the research hypotheses in a sample of empirical data collected from 350 employees of information technology (IT) service provider firms.

This paper empirically proves the existence of mediation effect of the proposed mediators (KME, KSB) between predictors (KMS, KSB) and outcomes (KSB, KP) in different hypothesized relationships. Result provides empirical evidence toward the positive influence of KMS dimensions (internal-oriented KMS, external-oriented KMS) on KSB and also confirms the influence of KSB on KP.

This study examines the effect of KMS and KSB on KP with reference to the IT sector, thereby limiting generalization to other sectors. Practical and managerial implications have been discussed in the later sections of the study.

This study adds value to the existing KM literature by adjoining the links among knowledge strategy, sharing behavior and performance.

This paper aims to examine the relationship between financial distress risk and stock returns in the Indian context.

This is an empirical study wherein the Altman-Z score is used to identify the distressed and the non-distressed firms listed on Nifty 500. The author uses the Fama–French five-factor model to study the relationship between stock returns and distress risk. The study analyses the differences in the factor loadings among the portfolios sorted by distress. It evaluates if incorporating distress risk factors in conventional pricing models enhances the goodness of fit.

The study reported a positive relationship between the distress risk factor and stock returns in the distressed portfolios, signifying that distress risk is a systematic risk only for distressed portfolios. Furthermore, after including the financial distress risk premium, the observed fluctuations in the small-minus-big (SMB), high-minus-low (HML), RMW and CMA coefficients indicate a common association with distress risk-related information.

This study tests the Fama–French five factors for distress risk and examines its nature in asset pricing for emerging markets like India. The study examined the performance of the augmented Fama–French five-factor model across different sets of portfolios sorted based on distress.

Various scams and swindles in banks demand effective supervision and competent workforce, as it involves with workplace accountability and undertaking customer support services. The purpose of this paper is to examine the managerial effectiveness of selected public, private and foreign banks in India.

In total, 467 questionnaires from (middle and top-level) managers of (five public, five private and five foreign banks) fifteen banks have been considered. The descriptive statistics, t-test and ANOVA are used to differentiate each sector of banks.

The significant difference denoted in terms of managerial effectiveness among banks. The results revealed that managers of public banks are action-oriented and receptive to feedback, whereas the manager of private sector banks embodies self-disclosure and perceptiveness. The correlates, namely, action-orientation, self-disclosure and receptivity to feedback evident significant among foreign banks.

The consideration and application of such correlates would surely help managers, decision-makers and practitioners to enhance their effectiveness. Human resource professionals can use these results to develop programmes and policies for better management.

The study is imperative as it compares the behaviour of managers of public, private and foreign banks individually. The findings demonstrate that correlates of managerial effectiveness significantly differ among the banks.

The purpose of the present study is to identify the core cultural aspects perceived by the executives of public, private and foreign banks in India.

Of the 124 responses, 96 usable responses were assessed from middle and lower level managers. Qualitative content analysis and deconstruction method were used to identify the perceived cultural aspects.

Interestingly, managers of Indian banking industry stated that cultural aspects of their banks possess good work and working environment, prefer people, management, experience and promotions in comparison to other factors like policy, bonus, market, commitment, project, etc. It is also noted that cultural aspects of banks prefer learning, training and team working.

Assessment of the perception of managers toward their culture will foster the banks to develop integral subculture and to achieve the long-term organizational goals.

The study analyze the cultural aspects in Indian banking industry qualitatively, based on executives characteristics. This qualitative analysis helps to find out more contemporary and prevailing factors of banks.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This bibliometric study aims to analyze publication trends, active countries, collaborations, influential citations and thematic evolution in learning analytics (LA) research focused on higher education (HE) during and after the COVID-19 lockdown period.

From the Scopus database, this bibliometric analysis extracts and evaluates 609 scholarly articles on LA in HE starting in 2019. The multidimensional process identifies the scope impacts, advancing the understanding of LA in HE. An analysis of co-citation data uncovers the key influences that have shaped the literature. This study uses the stimulus-organism-response (SOR) theory to suggest future research directions and organizational adaptations to new LA technologies and learner responses to LA-enabled personalized interventions.

Learning analytics are becoming important in the HE environment during and after the COVID-19 lockout. Institutions have used LA to collect socio-technical data from digital platforms, giving them important insights into learning processes and systems. The data gathered through LA has assisted in identifying areas for development, opening the path for improved student success and academic performance evaluation and helping students transition to the workforce.

The study’s concentration on the post-COVID-19 timeframe may lead to paying attention to potential pandemic developments. Nonetheless, the findings provide a thorough picture of LA’s contributions to HE and valuable ideas for future study initiatives. Future research with the SOR framework suggests areas for additional study to maximize LA’s potential in diverse HE situations.

This study adds to the growing corpus of knowledge on learning analytics in HE, especially in light of the COVID-19 lockdown and its aftermath. By using bibliometric analysis, the study provides a complete and evidence-based understanding of how LA has been used to address challenges related to HE. This study uses bibliometric analysis and SOR theory to appraise and map HE learning analytics research. The selected study themes can help scholars, educators and institutions shape their future efforts to improve teaching, learning and support mechanisms through learning analytics.