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The purpose of this study is to examine Indian language journals published in Arts, Humanities and Social Sciences (AHSS) included in the UGC-CARE list, which is an initiative of the University Grants Commission (UGC) of India. This study argues that although these journals do not appear in international databases, they are valuable because they frequently publish and have published for years, opinions, memoirs and critical review articles, especially the local culture.

This study examines 298 journals categorised into two groups: monolingual (189) and multilingual (109). The first group included 189 journals published in 15 Indian languages. Monolingual journals were examined using five criteria: year of publication, subject area, frequency, language and geographical zone of the publisher. Multilingual journals analysed as per languages covered.

The analysis reveals that the UGC-CARE List includes journals published between 1899 and 2019. The most common languages are Hindi (67), Urdu (31), Sanskrit (9) and Marathi (26). The frequency of majority (114) of journals is quarterly. Associations, universities, individual publishers and learned societies as publishers are dominant. Analysis of multilingual journals indicated that the highest number of journals (34) are published in English and Hindi.

Journals that fulfil the stringer criteria of three UGC-CARE journal analysis protocols find a place in the CARE List. The list is dynamic and is updated quarterly to maintain its currency and therefore its credibility. The list is available at http://ugccare.unipune.ac.in and is the list preferred by Indian Higher Education Institutes.

UGC-CARE List includes journals published by Indian publishers especially in the fields of Arts, Humanities and Social Sciences. It is the first initiative to battle against the predatory journals and effort to bring the Indian legacy of journals on the world map of journals and periodicals.

This study aims to comprehensively analyse the implementation and effectiveness of corporate social responsibility (CSR) policies within the context of the Indian coal mining sector. Furthermore, it investigates the alignment between CSR initiatives and the unique challenges faced by the coal mining sector and examines the outcomes and impacts of these initiatives on the employees of the sector and their perspective on the situation.

This study adopts a comprehensive qualitative research method, including a review of the literature, case studies and stakeholder interviews. This study seeks to deconstruct the application of CSR policies.

The analysis developed a deeper understanding of the complexities surrounding CSR policies in the Indian coal mining sector, offering insights into strategies for enhancing the effectiveness and relevance of these initiatives while fostering sustainable development.

This study reveals a rich tapestry of theoretical implications and how they connect to important organisational and societal paradigms. The results of this qualitative analysis can work as a foundation for creating scales to measure the level of efficiency of CSR policies implemented by different companies. Furthermore, this study goes beyond theoretical knowledge and gives companies, regulators and communities information they can use. By looking at how CSR policies work in the real world, a road map for responsible resource extraction and community growth can be made.

The findings are unique in exploring the CSR initiatives and the unique challenges faced by the coal mining sector. This study offers insight on the employees of the sector and their perspectives on the situation and delves into the multifaceted dimensions of CSR practices.

The ongoing transition in the attitude of consumers toward health and environment has a direct implication on the organic food industries, making it necessary to examine the drivers of the purchase intention of organic food items, specifically in developing economies like India. Therefore, this study tries to frame and validate the instrumental scale by collecting data from 574 organic food item consumers to examine the determinants of purchase intention among consumers in India.

This study has employed advanced statistical tools i.e. Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Harmon’s single factor test and other statistical measures using SPSS and AMOS 23, for framing and validating the instrumental scale for this study.

The results of EFA explain 67.714% variance of total research variable variance with six major constructs. Moreover, the result of the CFA confirms the six factors and the proposed instrumental scale. The finding explicates that health consciousness, ecological trustworthiness and functional value are the major drivers of the purchase intention of organic food items.

This study has major policy implications for organic producers, processor and marketers for understanding the complex phenomenon of organic consumer behavior. The result explains that marketers and producers should adopt ad hoc marketing strategies that aim to promote the organic food items as healthy and safe.

There is hardly any study that has proposed and validated an instrumental scale with these factors collectively in India for studying the purchase intention of organic food consumers in India.

The purpose of the current study is to examine the implications of the implementation of Goods and Service Tax (GST) on the revenue efficiency of the sub-national governments in India. Furthermore, the study aims to compare the revenue efficiency of the Indian states for the pre-GST and post-GST periods in India.

The study has used the annual revenue of value-added tax (VAT)/GST of the Indian states for the period ranging from 2012–2013 to 2020–2021 for the pre- and post-GST periods. The empirical results are based on the panel regression model for examining the implications of GST adoption on the Indian states.

The analysis shows that the implementation of GST in India has negatively impacted the revenue efficiency of the Indian states. Moreover, the results affirm that the contribution of the service sector to the state's Net State Domestic Product (NSDP), credit-deposit ratio (CDR) and outstanding net bank credit (ONBC) ratio of schedule commercial banks (SCBs) positively and states' dependency on central transfers (DCT) negatively impact the tax revenue efforts of the state governments. Furthermore, the GST adoption has a greater impact on the revenue efficiency of the minor states in comparison to major states which may widen the inter-state disparity gap as GST revenue constitutes a major share in the Own Tax Revenue (OTR) of the Indian states in aggregate.

The current study will act as a guide for government, policymakers and for the sitting of the fifteenth finance commission in India for future policy formulation on GST and compensation to the Indian states. Similarly, this study can be used as a base for conducting future studies on the implications of GST at the national, sub-national, and international levels.

Previous studies on the implications of GST are theoretical and conceptual. There is hardly any study at the national or sub-national level that has focused on the implications of GST on the revenue efficiency of the Indian states.

This study aims to investigate the factors that contribute to the overall tour experience and services provided by Top Tier Holidays. The study is mixed in nature, and the researchers have used analytical tools to analyse the data factually. Multiple regression using MS Excel is used in the study.

This case is based on the experiences of a real-life travel and tour company located in New Delhi, India. The case helps understand regression analysis to identify independent variables significantly impacting the tour experience. The CEO of the company is focused on improving the overall customer experience. The CEO has identified six principal determinants (variables) applicable to tour companies’ success. These variables are hotel experience, transportation, cab driver, on-tour support, itinerary planning and pricing.

Multiple regression analysis using Microsoft Excel is conducted on the above determinants (the independent variables) and the overall tour experience (the dependent variable). This analysis would help identify the relationship between the independent and dependent variables and find the variables that significantly impact the dependent variable. This case also helps us appreciate the importance of various parameters that affect the overall customer tour experience and the challenges a tour operator company faces in the current competitive business environment.

This case is designed for discussion with the undergraduate courses in business management, commerce and tourism management programmes. The case will build up readers’ understanding of linear regression with multiple variables. It shows how multiple linear regression can help companies identify the significant variables affecting business outcomes.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

In today’s competitive environment, understanding employee well-being and work engagement (WE) is crucial. This study explores the relationship between values, well-being and WE within positive organizational behavior (POB). The research aims to provide insights for promoting employee well-being and enhancing WE.

Using a cross-sectional approach, three hundred and seventy-two teachers from higher education institutes in India participated by completing questionnaires. Covariance-based structural equation modeling (CB-SEM) was employed to examine the mediation effect.

Human values i.e. benevolence (BE) and universalism (UN) significantly impacted teachers' WE. These relationships were mediated by positive emotions (PE), negative emotions (NE) and satisfaction with life (SWL). Interestingly, UN exhibited a positive relationship with PE and SWL and a negative relationship with NE. These findings contradict existing theories and may be attributed to India’s cultural aspects, particularly the concept of karma orientation.

The quantitative results obtained through CB-SEM could be complemented by future qualitative studies. Employing longitudinal research might yield different results. Generalizing the findings to other populations requires caution.

Institutions should prioritize human values in teacher recruitment and development to improve engagement. Promoting PE, managing NE and enhancing SWL can boost WE. Future research should explore mediation with other variables and use longitudinal studies to understand cultural impact and intervention strategies.

The study contributes to knowledge on WE within positive organizational behavior by examining BE and UN. Additionally, exploring the mediating effect of PE, NE and SWL adds further value.

In the information and technology age, where the “physical” world is merged with the “digital” world, the nature of social conditions, relations, citizenship and the flow of information has shifted from a moral and legal approach to a digital approach. Nowadays, the functioning, dissemination, conduct and governance of organisations and their members are regulated by techno-ethical and digital principles. Drawing on social cognitive theory, the study hypothesises that techno-ethical orientation predicts corporate ethical values (CEV) through the moderation of digital citizenship behaviour (DC). The study further proposes that each dimension of DC: online respect (OR) and online civic engagement (OCE), moderates the hypothesised relationship.

546 respondents from India participated in the study. The responses were captured using structured and well-established questionnaires. The analysis was performed using robust measures of correlation, regression, reliability (Cronbach’s alpha and composite reliability) and validity (convergent and discriminant validity). The moderation influence of DC was tested and analysed using structural equation modelling (SEM) Analysis of Moment Structures (AMOS).

The regression findings of the study revealed that the techno-ethical orientation positively predicts the CEV. R-square values showed a 24.1% variation in corporate ethical value was explained by techno-ethical orientation. It indicates that a positive techno-ethical orientation establishes the ethical context and corporate values. Besides, the moderation analysis using SEM AMOS indicates that at both low and high levels of OR and OCE, the relationship between techno-ethical orientation and CEV is positive and significant.

This study demonstrates a new facet of technology ethics that promotes the institutionalisation of CEV through DC. This study is the first to explore the interaction between techno-ethical orientation and CEV. Even though various former factors concerning ethical conduct have been examined, the results of the techno-ethical conduct of employees within the scope of an organisation have not been explored so far.

With the change in climate and increased pollution, there has been a need to reduce environmental carbon emissions. This research aims to develop a framework for reducing environmental carbon footprints to improve business performance.

This study uses Scientific Procedures and Rationales for the Systematic Literature Reviews (SPAR-4-SLR) approach. Articles are searched in the Scopus database using various keywords and their combinations. It resulted in 651 articles initially. After applying different screening criteria, 61 articles were considered for the final study.

This study provided four themes and sub-themes within each category. This research also used theories, methodologies and context (TMC) framework to provide future research questions. This study used the antecedents, decisions and outcomes (ADO) framework for synthesising the findings. The ADO framework will help to achieve carbon neutrality and improve firms' supply chain (SC) performance.

This study provides theoretical implications by highlighting the various theories that can be used in future research. This study also states the practical implications for the achievement of carbon neutrality by the firms.

This study contributes to the literature linking carbon neutrality with business performance.