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The purpose of this paper is threefold: first, to study internationalization-performance relationship of Indian born global (IBG) firms from multi-theoretical lens and establish the nature of this relationship; second, to highlight the role of foreign equity in moderating this relationship; and third, to establish the relevance of export intensity (EI) in determining these firms’ financial performance.

In total, 411 IBG firms were identified based on born global (BG) definition and post-entry internationalization age requirement of this study. A balanced panel comprising of three years from 2010 to 2012 was analyzed using pooled panel and moderated multiple regression techniques.

The authors empirically prove that though EI and financial performance are positively related at overall level, this relationship is curvilinear in nature. In presence of foreign equity this positive curvilinear relationship is moderated to inverted-U shape.

The data sample is restricted to 411 private limited IBGs between the years 2009 and 2012. Implications of the findings are for policy makers and managers to sharpen their strategic foresight for exporting firms in its post-entry period. Also, investors can take level of internationalization into cognizance when investing in BG firms.

The authors believe the results have practical implications for numerous parties, such as shareholders, institutional investors, scholars, policymakers and managers. It emboldens modern day managers to make further foray into internationalization due to its positive benefits on both productivity as well as profitability. Also, firms that look for foreign equity participation have to balance their strategies for greater scale and scope into international markets.

This is the first study that brings out the vital relationship aspect of EI with financial performance of IBG firms in their post-entry internationalization period, adding to international business literature in area of BG firms in their post-entry internationalization period.

One of the most active areas of study in the field of corporate governance, board interlocks is a phenomenon that is both pervasive and perplexing. This paper aims to examine and integrate the empirical research on board interlocks to fill the void left by the lack of a recent review.

The bibliometric analysis methodology, which emphasizes methodological rigor and transparency, was used to analyze the board interlocks literature. Eighty publications published since 2000 were chosen as the subject of this research because they reveal the key contributions to the field of board interlocks. Additionally, their clustering pattern is also identified.

The authors classify various studies conducted on board interlocks into three clusters: “Social Capitalization”, “Antecedents and Outcomes” and “Corporate Governance”.

This literature review helps better comprehend the board interlocks literature by pointing out several areas of study that, if pursued, would add to the existing body of knowledge and open future research directions.

The purpose of this paper is to establish sufficient potential for a novel perspective that could enhance understanding of the rationale behind voluntary disclosures. In this paper, the authors seek to provide an integrated view from different disciplines that points to a new dimension. This dimension is expected to promote a better understanding of voluntary disclosures in corporate governance.

The authors use the conceptual underpinnings of agency theory and integrate several perspectives from different disciplines. Through the support of simple matrices and a conceptual figure, an interesting finding is proposed that could help provide a new way of looking at voluntary disclosures.

The established view holds that due to information asymmetry between the shareholders and the management, voluntary disclosures are more meaningful for the shareholders of the firm. The authors, however, suggest that since information asymmetry is already embedded in several roles and strategic actions of the board, it leads to the development of a third dimension in understanding voluntary disclosures.

Information asymmetry has been well understood as one of the key aspects of the agency theory. The authors' strive to apply this phenomenon while looking at the roles of the board and the strategic actions that result therein. The result is an enhanced understanding of the motivations behind voluntary disclosures.

The hospitality and tourism sector has witnessed phenomenal growth in customer numbers during the postpandemic times. This growth has been accompanied by the use of technologies in customer interface and backend activities, including the adoption of self-serving technologies. This study aims to analyze the existing practices and challenges and establish a research agenda for the implementation of generative artificial intelligence (AI) (such as ChatGPT) and similar tools in the hospitality and tourism industry.

This study analyzes the existing literature and practices. This study draws upon these practices to outline a novel research agenda for scholars and practitioners working in this domain.

The integration of generative AI technologies, such as ChatGPT, will have a transformational impact on the hospitality and tourism industry. This study highlights the potential challenges of implementing such technologies from the perspectives of companies, customers and regulators.

This study serves as a reference material for those who are planning to use generative AI tools like ChatGPT in their hospitality and tourism businesses. This study also highlights potential pitfalls that ChatGPT-enabled systems may encounter during service delivery processes.

This study is a pioneering work that assesses the applications of ChatGPT in the hospitality and tourism industry. This study highlights the potential and challenges in implementing ChatGPT within the hospitality and tourism industry.

The increased digital interactions in the B2B industry have enhanced the importance of customer engagement as a measure of firm performance. This study aims to map and analyze temporal and spatial journeys for customer engagement in B2B markets from a bibliometric perspective.

The extant literature on customer engagement research in the B2B context was analyzed using bibliometric analysis. The citation analysis, keyword analysis, cluster analysis, three-field plot and bibliographic coupling were used to map the intellectual structure of customer engagement in B2B markets.

The research on customer engagement in the B2B context was studied more in western countries. The analysis suggests that customer engagement in B2B markets will take centre stage in the coming times as digital channels make it easier to track critical metrics besides other key factors. Issues like digital transformation, the use of artificial intelligence for virtual engagement, personalization, innovation and salesforce management by leveraging technology would be critical for improved B2B customer engagement.

The study provides a comprehensive reference to scholars working in this domain.

The study makes a pioneering effort to comprehensively analyze the vast corpus of literature on customer engagement in B2B markets for business insights.

This paper aims to investigate the use of Industry 4.0 (I4.0) technology and its barriers in human resourcemanagement (HRM) for Smart HR 4.0 and its impact on HR performance.

The research has been conducted using the grounded theory approach. Semi-structured interviews were conducted with 122 senior HR officers of national and multi-national companies in India after the extensive literature review. NVivo 8.0 software was used for the analysis of the interview data.

I4.0 technology is used for HRM functions by HR professionals. It is revealed that Smart HR 4.0 that emerged from the I4.0 technology has leveraged the HR performance. It is also found that usage barriers, traditional barriers and risk barriers affect the use of I4.0 technology in HRM.

A model is developed using the grounded theory approach for HR managers to understand the impact of I4.0 on HRM. This study reveals the barriers affecting the use of I4.0 technology in HRM. It also provides the model for HR performance that emerged through the use of I4.0 technology in HR and Smart HR 4.0. The research delivered key insights for the HR professionals, marketers of HR technology and technology developers.

Electric discharge drilling (EDD) is used to drill quality microholes on any conductive materials. EDD process parameters play a crucial role in the drilling. Depending upon the material characteristics, the cost of drilling also changes. Therefore, a suitable method is required to control the process parameters and drill quality microholes.

The input process parameters in the present work are peak current (Ip), pulse on-time (Ton) and pulse off-time (Toff). The trials were intended in accordance to central composite face-centered design of response surface methodology (RSM). The output responses, namely drilling rate (DR) and electrode wear ratio (EWR), were converted into a single response, that is, grade using Grey relational analysis (GRA). The grade value is further modeled by regression analysis. The empirical model was figured out using teaching–learning-based optimization (TLBO). The RSM-Grey-TLBO-based multicriteria decision-making (MCDM) is used to investigate the optimized process parameter setting.

The RSM-Grey-TLBO-based MCDM approach suggests that the optimized setting for DR and EWR is Ip: 3A; Ton: 40 µs; Toff: 42 µs. The percentage errors for the predicted and experimental results are 8.1 and 7.5% in DR and EWR, respectively.

The parametric optimization of EDD using RSM-Grey-TLBO-based MCDM approach while machining commercially pure titanium is still underway. Thus, this MCDM approach will give a path to the researchers working in this direction.

This study aims to develop a practical and effective approach for market segmentation using customer experience dimensions derived from online reviews.

The research investigates over 6,500 customer evaluations of food establishments on Taiwan’s Yelp platform through the Latent Dirichlet allocation (LDA) data mining approach. By using the LDA-derived experience dimensions, cluster analysis discloses market segments. Subsequently, sentiment analysis is used to scrutinize the emotional scores of each segment.

Mining online review data helps discern divergent and new customer experience dimensions and sheds light on the divergent preferences among identified customer segments concerning these dimensions. Moreover, the polarity of sentiments expressed by consumers varies across such segments.

Analyzing customer attributes extracted from online reviews for segmentation can enhance comprehension of customers’ needs. Further, using sentiment analysis and attributes of online reviews result in rich profiling of the identified segments, revealing gaps and opportunities for marketers.

This research presents a new approach to segmentation, which surmounts the restrictions of segmentation methods dependent on survey-based information. It contributes to the field and provides a valuable means for conducting customer-focused market segmentation. Furthermore, the suggested methodology is transferable across different sectors and not reliant on particular data sources, creating possibilities in diverse scenarios.

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.

Sustainable production (SP) is an efficient and influential approach of production for Indian manufacturing industries as it preserves the social, environmental and economic aspects of production activities altogether. The objective of this research work is to investigate the implementation status of SP practices in Indian manufacturing industries by utilizing empirical survey methodology.

A questionnaire survey methodology was adapted, and the questionnaire was prepared by intense literature survey along with by opinions from experts in the field of SP. This questionnaire was sent to 753 different organizations at different locations across India. This study collected responses from manufacturing industries as per 2021 directory of Confederation of Indian Industries for the duration of 7 week. Top level managers were the target respondents. The study propagated with 242 responses which were observed complete in all respects.

The study identified that though the majority of the organizations are claiming to follow SP practices since long time, they actually are lagging in proper understanding SP practices. Majority of them are implementing it in specific departments in their organization. They are coming across multiple barriers in the implementation of SP practices among which unrecognized financial benefits and lack of proper government policies are prime. The study suggests that the Indian organizations needs feasible framework with adaptable guidelines.

This work is centered towards manufacturing organizations and targets only the leading industrial sectors in India. Thus, the outcomes of this study may not be generalized for all the sectors of Indian industries. Additionally, it can also be assumed that higher number of responses would have contributed to more clear visualization of implementation status of SP practices among Indian industries.

Sustainable approaches in production activities are very lucrative for industries worldwide, due to their advantages. Numerous researchers are also putting their efforts to explore more about various aspects of sustainability. Mostly they are focusing on single or few aspects of SP and its implementation in particular region or country. Very few research works are dedicated to knowing the implementation status of SP in Indian manufacturing industries and they are limited in various aspects. This study presents a dedicated approach to investigate the implementation status of SP practices in Indian manufacturing industries.