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This study aims to delve into the perspectives of educators on integrating ChatGPT, an AI language model into management education. In the current research, educators were asked to talk as widely as possible about the perceived benefits, limitations of ChatGPT in management education and strategies to improve ChatGPT for management education. Also, shedding light on what motivates or inhibits them to use ChatGPT in management education in the Indian context.

Interpretative phenomenological analysis commonly uses purposive sampling. In this research, the purpose is to delve into educators’ perspectives on ChatGPT in management education. The data was collected from the universities offering management education in Uttarakhand, India. The final sample size for the study was constrained to 57 educators, reflecting the point of theoretical saturation in data collection.

The present study involved educators discussing the various advantages of using ChatGPT in the context of management education. When educators were interviewed, their responses were categorized into nine distinct sub-themes related to the benefits of ChatGPT in management education. Similarly, when educators were asked to provide their insights on the limitations of using ChatGPT in management education, their responses were grouped into six sub-themes that emerged during the interviews. Furthermore, in the process of interviewing educators about potential strategies to enhance ChatGPT for management education, their feedback was organized into seven sub-themes, reflecting the various approaches suggested by the educators.

In the qualitative study, perceptions and experiences of educators at a certain period are captured. It would be necessary to conduct longitudinal research to comprehend how perceptions and experiences might change over time. The study’s exclusive focus on management education may not adequately reflect the experiences and viewpoints of educators in another discipline. The findings may not be generalizable and applicable to other educational disciplines.

The research has helped in identifying the strengths and limitations of ChatGPT as perceived by educators for management education. Understanding educators’ perceptions and experiences with ChatGPT provided valuable insight into how the tool is being used in real-world educational settings. These insights can guide higher education institutions, policymakers and ChatGPT service providers in refining and improving the ChatGPT tool to better align with the specific needs of management educators.

Amid the rising interest in ChatGPT’s educational applications, a research gap exists in exploring educators’ perspectives on AI tools like ChatGPT. While some studies have addressed its role in fields like medical, engineering, legal education and natural sciences, the context of management education remains underexplored. This study focuses on educators’ experiences with ChatGPT in transforming management education, aiming to reveal its benefits, limitations and factors influencing adoption. As research in this area is limited, educators’ insights can guide higher education institutions, ChatGPT providers and policymakers in effectively implementing ChatGPT in Indian management education.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

Dark tourism, a phenomenon encompassing visits to sites associated with death, suffering, and historical atrocities, has gained increasing scholarly attention in recent years. This chapter explores the concept's historical roots, motivations for engagement, and its transformative impact on heritage sites, culminating in a case study of the Malcha Mahal Haunted Heritage Walks in Delhi. Despite being abandoned for centuries, this historic site gained prominence with the occupation by the self-proclaimed royal family of Oudh in the 1980s. The introduction of the Haunted Heritage Walk by Delhi Tourism aimed to harness the dark tourism potential of this previously neglected monument. However, initial challenges such as deteriorating conditions and safety concerns necessitated collaborative efforts with government departments for conservation and site preparation. Interviews with visitors revealed diverse motivations for attendance, ranging from thrill-seeking to appreciation of the monument's historical significance. Since the walk's inception, conservation efforts have commenced, accompanied by landscaping initiatives and amenities for visitors. While the future conservation and tranquility of Malcha Mahal remain uncertain amid increasing tourist interest, its transformation into an alternative destination within Delhi underscores the potential of dark tourism to revitalize neglected heritage sites. Sustainable tourism planning is essential to preserve the monument's unique features and manage tourism while maintaining its integrity for future generations.

It is largely acknowledged that arbitrating the flow of knowledge can help firms strategically leverage tacit and explicit internal knowledge. However, despite the apparent scholarly and managerial acceptance of the criticality of the flow of knowledge between various stakeholders, the academic understanding of knowledge arbitrage remains coarse-grained. There are practically no empirical insights available to unravel the consequences of firms’ knowledge arbitrage choices regarding rewards and risks. This study aims to identify the risks that emerge as firms channel the flow of knowledge from surplus to deficit areas within organizational boundaries. To this end, the authors investigate several subsumed subprocesses in knowledge arbitrage to map the associated risks.

This study used an exploratory qualitative approach to examine the risks that emerge as firms attempt to support knowledge flows within their organizational boundaries. The data were collected through open-ended essays via an online research platform from 45 full-time employees of firms operating in different sectors. The collected data were analyzed inductively through open, axial and selective coding.

The research findings identified three key subprocesses of knowledge arbitrage: knowledge diffusion, knowledge brokering and knowledge absorption. These subprocesses are susceptible to various risks arising the form of channels, champions, sharers and receivers of knowledge flows. In general, the study showed that a firm’s decision regarding knowledge flows, such as structured or random flows, or the presence or absence of designated coordinators to broker the flow carries specific risks for both sharers and receivers. In particular, while the risks of knowledge hiding, misinformation and disinformation manifest in all three subprocesses, low employee engagement, loss of knowledge and information overload also emerged as key risks in any two of the three subprocesses.

This study offers valuable insights by uncovering the hitherto unexplored risks in intrafirm knowledge arbitrage. Given that knowledge is a crucial organizational tool for driving performance, innovation and competitive advantage, understanding the risks associated with intrafirm arbitrated knowledge flows can help firms anticipate and mitigate the associated adverse consequences. The findings make a novel contribution by offering (a) a comprehensive categorization of the risks associated with knowledge arbitrage rooted in processes, people and structures and (b) a macro overview of knowledge arbitrage risks associated with the processes of knowledge diffusion, knowledge brokering and knowledge absorption.

The purpose of the current study is to help remove the obstacles to sustainable production and consumption by revealing the determinants of green consumption behaviour, which is one of the precursors of sustainable economic growth. This study aims to expand the theory of planned behaviour (TPB) model and contribute to the relevant literature by investigating the factors of social media usage, social media marketing and digital marketing interactions that have not been investigated before in relation to green product purchasing behaviour.

This study examines the effect of the extended TPB model on consumers’ intention to buy green products in Turkey, which has a Middle Eastern culture and is a developing economy. In the study, data collected from 409 participants with the questionnaire method were analysed using SmartPLS 4.0 and IBM SPSS 26 statistical programs.

The study findings revealed that all the structural elements of TPB (attitude, subjective norms, personal behaviour controls) and social media marketing and digital marketing interactions contribute to consumers’ green product purchasing behaviour. The study findings also demonstrated that the use of social media is not effective in the purchasing of green products.

Understanding consumers’ perspective on purchasing green products is crucial for policymakers, businesses and marketers, as it helps formulate appropriate strategies to support sustainable economic growth. In this respect, this study has important implications for sustainable consumption and production. In addition, to the best of the authors’ knowledge, the study is the first to examine consumers’ green product purchasing behaviour in the context of sustainable economy.

Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing information overload. However, the risk associated with GAI is high, and its widespread adoption for product/service information search purposes is uncertain. This study examined psychological drivers that impact consumer adoption of GAI platforms for retail information search.

We conducted 31 in-depth, semi-structured interviews with the lead GAI users regarding product/service information search. The data were analysed using a grounded theory paradigm and thematic analysis.

Results show that consumers experience uncertainty about GAI’s functioning. Their trust in GAI impacts the adoption and usage of this technology for information search. GAI provides unique settings to investigate potential additional factors, leveraging UTAUT as a theoretical basis. This study identified three overarching themes – technology characteristics, technology readiness and information characteristics – as possible drivers of adoption.

Consumers seek exhaustive and reliable information for purchase decisions. Due to the abundance of online information, they experience information overload. GAI platforms reduce information overload by providing synthesized and customized product/service search results. However, its reliability, trustworthiness and accuracy have been questioned. The functioning of GAI is opaque; the popular technology adoption model such as UTAUT is general and is unlikely to explain in totality the adoption and usage of GAI. Hence, this research provides the adoption drivers for this unique technology context. It identifies the determinants/antecedents of relevant UTAUT variables and develops an integrated conceptual model explaining GAI adoption for retail information search.