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The academic accounting labor market is experiencing rapid changes on several fronts. We examine accounting program leaders’ perceptions of Assistant Professor hiring criteria, including how the criteria have changed in recent years. We ask program leaders to provide qualitative perspectives, rate the importance of 56 possible hiring criteria, and, in a supplemental analysis, rank and rate four hypothetical Assistant Professor candidates. Based on responses from 54 accounting program leaders, the results reveal a complex setting with research and teaching considerations, a focus on collegiality and professional experience, and an increasing focus on diversity. Specifically, Research Intensive schools (Carnegie R1 and/or doctorate in business) are more top-tier research and top-tier doctoral program focused, while Non-Research Intensive schools (all others) are more focused on general skills, other refereed journals, practitioner research, teaching experience, service, CPA licensure, and other professional certifications.
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According to a 2020 survey of 600 senior executives conducted by Harvard Business Review, 55% of organizations agreed that data analytics for decision making is extremely important and 92% asserted data analytics for decision making will be even more important in two years (bit.ly/3PBRENs). Organizations that strategically deploy tools across their finance and accounting functions have an opportunity to better structure manual processes into more stable, accurate, repeatable, and readily auditable procedures (see Gregory Kogan, Nathan Myers, Daniel J. Gaydon, and Douglas M. Boyle, "Advancing Digital Transformation," Strategic Finance, December 2021, bit.ly/3V45v0h). [...]financial decision makers are increasingly expected to engage data analytics to enhance decision making and create more efficient processes. Deployment/communication It's very important to assign responsibilities to team members (e.g., business analysts establish requirements, IT specialists gather required data, and data scientists develop and test advanced modeling techniques) with the requisite skills that vary among the phases. [...]unstructured data is data that has no uniform structure and typically isn't text-based, for example, image or sound files.
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This study examines how product market competition differentially affects existing versus new analysts. I find that new analysts' coverage increase is significantly higher than the existing analysts' coverage increase when a portfolio firm faces high competition, suggesting existing analysts’ tendency to avoid competition among analysts for their career success. I also find that new analysts' one-year earnings forecasts accuracy decrease is significantly larger than the one of the existing analysts when the portfolio firm faces high competition. These findings indicate that existing analysts consider the situation firm faces, product market competition, and they are more competent than new analysts.