Britannia Industries: A Valuation Dilemma

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Asian Journal of Management Cases, Ahead of Print.
Abhay Khanna, an independent financial advisor based in Delhi, consistently seeks out companies with strong fundamentals and potential for long-term growth to benefit his clients. Recently, he assessed the financial records of Britannia Industries, a prominent Indian food company, wondering whether it might be undervalued in the current market. To assess this, he employed the widely used multi-stage dividend discount model to determine its intrinsic value. This involved forecasting Britannia Industries’ future financial statements and dividends, prompting Abhay to carefully consider various assumptions and predictions to identify a potentially undervalued investment opportunity. This scenario presents students with the role of equity research analysts tasked with evaluating Britannia Industries’ financial worth using dividend discount valuation techniques.

JTAER, Vol. 19, Pages 863-879: Understanding the Adoption Dynamics of ChatGPT among Generation Z: Insights from a Modified UTAUT2 Model

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JTAER, Vol. 19, Pages 863-879: Understanding the Adoption Dynamics of ChatGPT among Generation Z: Insights from a Modified UTAUT2 Model

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer19020045

Authors: Antun Biloš Bruno Budimir

This research delves into the factors influencing the adoption of ChatGPT, a sophisticated AI-based chatbot, among Generation Z members in Croatia. Employing an extended UTAUT2 model, the impact of various factors on the behavioral intention to use ChatGPT is explored. The study included 694 Generation Z participants, and data were collected through an online survey featuring self-reporting questions. The analysis utilized statistical software packages for performing both confirmatory and exploratory factor analyses, in addition to hierarchical linear regression. Key findings reveal that performance expectancy, social influence, hedonic motivation, habit, and personal innovativeness significantly influence the behavioral intention to use ChatGPT. However, effort expectancy, facilitating conditions, and price value do not exhibit a significant impact. Notably, the study excludes the use behavior factor due to multicollinearity issues with behavioral intention. While the research does not focus on moderating factors, it reports that the adapted UTAUT2 model explains 65% of the variance in the adoption of ChatGPT by Generation Z users.