State of The Dotcom-Era Accounting Information Systems (AIS) Faculty and Implications for The Artificial Intelligence (AI)-Era - Akhilesh Chandra; Charles F. Malone (Journal of Accounting and Management Information Systems (JAMIS), 2024)
Research Questions- What was the state of accounting information systems (AIS) faculty in accounting programs of US universities and colleges (hereafter, institutions) at the peak of Dotcom? What can the artificial intelligence (AI)-era accounting education learn from its Dotcom experience? Motivation- Accounting education environment during the Dotcom-led innovations and the current AI- and Generative AI (GenAI)-led innovations bears similarities in many respects. While AIS faculty teach AIS courses where students learn information systems (IS) concepts including technology, processes and internal controls in greater detail and depth relative to other accounting courses, our literature review suggests a paucity of research on AIS faculty, especially during the Dotcom-era. AIS faculty is an appropriate proxy for the IS and information technology (IT) skills of accounting graduates' market-ready quality. Therefore, we examine AIS faculty's institutional characteristics during the Dotcom-era and consider implications for the AI-era accounting education to minimize capacity gaps, technology gaps, and resource gaps. Idea- We analyze US accounting programs for AIS faculty's (i) individual features and (ii) association with institutional features. Data- We hand-collect data, from 1998-1999 Hasselback Accounting Faculty Directory (HAFD), which is just before the Dotcom's bust and reflects the culmination of a series of actions taken by accounting programs and accounting education during the Dotcom-era. HAFD, our primary data source, provides faculty and program information in sufficient detail and granularity. Tools- We use count data econometric models corresponding to Poisson and Negative Binomial (NEGBIN) processes, since our response variable (i.e., AIS faculty) and its proxies suggest that they approximate a Poisson probability distribution. Findings- We find that doctoral programs supplying AIS faculty are public institutions and mostly in the southern states. AIS faculty are (i) less in private institutions; (ii) less in professor ranks; (iii) proportionately more with a PhD and certified public accountant (CPA) credentials; and (iv) similar in gender split, vis-à-vis all accounting faculty. AIS faculty associate positively with total accounting faculty size, accreditation and public institutions, and negatively with the presence of a doctoral program in the department. Contribution- We contribute to the existing research stream that examines accounting program quality and faculty background which proxy graduate's market-readiness. At the theoretical and usefulness level, we contribute by using accounting education's Dotcom experience to identify specific implications for the AI-era. At the methodological level, we theorize the count-data econometric features of AIS faculty and consider its five proxies, each with a different theoretical significance to associate with its factors. Significance- We discuss significance of our results by posing questions to stir debate, dialogue and discussion for devising action-based strategies that are sustainable, inclusive and equitable.
Keywords: M41; 650; Accounting Information Systems (AIS) faculty; Artificial Intelligence (AI); Dotcom; Accounting education; Poisson; Negative Binomial (NEGBIN); Hasselback accounting faculty directory