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This case was researched using publicly available sources, including Mercury Systems financial filings and press releases, news stories about the seasoned equity offering, financial information from Bloomberg and industry information from IBISWorld Industry Reports and articles related to seasoned/secondary equity offerings, intangible asset valuation and the use of revolving lines of credit. Quotes are taken from Mercury financial reports and press releases and express the (optimistic) opinions of company executives.

Mercury Systems, a technology company in the aerospace and defense industry, announced a six million share seasoned stock offering in June 2019. This resulted in a 6% stock price decrease. A stock price decrease is a typical event when a firm announces the issuance of new common shares, but with Mercury Systems, there were concerns about how much money the firm needed to fund its strategy of growth through acquisitions. If internally generated funds were not sufficient, should the firm issue debt or have another seasoned equity issue? Students will look at the objectives and success of the most recent seasoned equity issue, determine future funds needs and how the firm should finance these needs.

This case is appropriate for undergraduate and graduate students in corporate finance electives. Typically, topics such as seasoned equity offerings are not covered in introductory courses, so this is recommended for finance electives. Even in advanced finance courses, sometimes there is insufficient time to cover seasoned equity offerings.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.