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This paper offers a fresh perspective on this debate by exploring the direct relationship between a firm’s stock price performance and its CSR activities, placing particular emphasis on the underlying intent or motive behind the CSR initiatives.

This research examines the relationship between a firm’s stock price and its corporate social responsibility (CSR) activities, distinguishing between responsive and adaptive CSR. While responsive CSR, often a response to negative events, elicits immediate positive stock performance, adaptive CSR initially triggers negative stock performance. However, long-term analysis reveals adaptive CSR leads to positive stock performance, especially for family firms. The study challenges the notion of market myopia, suggesting the market values responsive CSR in the short term but recognizes the long-term benefits of adaptive CSR over time. Clear communication about adaptive CSR intentions and benefits may help in accurate market valuation.

This research examines the relationship between a firm’s stock price and its CSR activities, distinguishing between responsive and adaptive CSR. While responsive CSR, often a response to negative events, elicits immediate positive market reactions, adaptive CSR initially triggers negative reactions. However, long-term analysis reveals adaptive CSR leads to positive returns, especially for family firms.

The study challenges the notion of market myopia, suggesting the market values responsive CSR in the short term but recognizes the long-term benefits of adaptive CSR over time. Clear communication about adaptive CSR intentions and benefits may help in accurate market valuation.

First, it expands on previous studies by exploring how the different motivations behind CSR activities lead to varying effects on stock returns. Second, it sheds new light on the subject of market myopia. The findings demonstrate that adaptive CSR initiatives can initially trigger market reactions similar to those caused by perceived over-investment, in contrast to the more favorable response to responsive CSR activities.

Millennials are a vital generational cohort of the Indian population, and understanding their motivation to participate in the stock market is crucial. This study aims to understand the investment decision-making behavior among millennials in the Indian Stock Market.

Using a cross-sectional research design that entails in-depth personal interviews, this study aims to understand the equity investment behavior of millennials. Verbatim texts from interview transcripts were used to analyze the content and arrive at themes.

The study investigated the motivation to enter the stock market and gained insights into how individuals make equity investment decisions considering economic and behavioral dimensions. The basis for stock selection was predominantly on the self-analysis of investors. Multiple stock selection priorities are also discussed. In addition, informants ensured asset diversification and exercised various strategies to overcome emotions. Furthermore, they suffered from various behavioral biases.

Individual investors are the least informed and most impacted stakeholders in the stock markets; therefore, this study contributes fresh insights to enhance their financial security. The paper also examines some noticeable behavioral tendencies retail investors exhibit and gathers helpful strategies for mitigating behavioral biases.

The uniqueness of the research lies in its adoption of a qualitative methodology that uses the investment experience of millennial investors to reveal the components of decision-making behavior and investor psychology. The findings are thereby unique and have significant managerial implications.

In today’s competitive era, it has become significant for companies to understand their end consumer and target customers effectively. One of the ways to accomplish this goal is data-driven marketing. The current study seeks to explore the differences between traditional marketing and digital marketing, the pros and cons of data-driven marketing and usage of artificial intelligence (AI) in data-driven marketing. The research objective was met by exploration of published papers in the past 10 years covering the evolution of data-driven marketing, functions of data engineering, application of technology like AI in data-driven marketing and opportunities and challenges. This study is significant as it provides the insight into the relationship between marketing and data engineering and thus helps marketers to frame strategies by leveraging data-driven marketing to improve consumer experience and gain a competitive edge. Moreover, this study is an interdisciplinary study including marketing, engineering and data science. This study focusses on use of innovative methods to improve profitability of business and consumer experience.

AI-powered digital human avatar influencer (DHAI) is a digitally created character with a human-like appearance and noteworthy social media presence. They mimic human behavior through form, behavior and emotional realism. However, there have been varied viewpoints in the literature about the effect of DHAI realism on consumer response. Therefore, this study aims to examine the effect of form, behavioral and emotional realism on consumer engagement and parasocial relationships that further affect attachment toward DHAI and brand, with the moderating effect of content authenticity.

Using a cross-sectional design, 426 respondents in India were asked to visit the Instagram page of a specific DHAI identified through a pretest study. The authors used the Smart PLS 4.0 version to examine the hypotheses.

Accordingly, based on the social presence theory, the findings of the quantitative study indicated that DHAI’s form, behavioral and emotional realism positively influence customers’ engagement with DHAI, but only the behavior and emotional realism of DHAI positively affect the parasocial relationship. Further, perceived DHAI’s content authenticity moderates the effect of DHAI engagement and parasocial relationship on DHAI sentimental attachment.

This study provides novel and practical insights for developing DHAI by considering realism characteristics for enhanced customer engagement, parasocial relationship and attachment toward DHAI and brands.

This study investigates the impact of social cognitive theory (SCT) constructs and perceived risks on university students’ trusting intentions towards Metaverse-based educational platforms in the UAE. By examining factors such as self-efficacy, outcome expectations and vicarious learning (from SCT), alongside perceived risks like performance, time, social and security concerns, this research addresses critical gaps in understanding trust dynamics in educational technology.

A quantitative survey was conducted with 176 university students who experienced a Metaverse-based classroom prototype. Data were analyzed using structural equation modeling (SEM) to evaluate the relationships between SCT constructs, perceived risks and trusting intentions.

The results demonstrate that SCT constructs significantly enhance trust by fostering self-efficacy and providing positive learning experiences. Conversely, perceived risks reduce trust, emphasizing the need to mitigate security concerns and usability barriers to improve adoption. These insights underline the dual importance of managing risks and promoting psychological readiness among students.

The findings offer actionable guidance for educators, policymakers and developers to design secure, user-friendly Metaverse platforms that align with educational objectives. The study emphasizes the importance of addressing perceived risks, enhancing student engagement and fostering trust to enable effective technology adoption in education.

This research provides a novel perspective on trust in Metaverse-based education by integrating SCT constructs with risk perceptions, offering a comprehensive framework to guide the successful implementation of immersive learning environments.