Managers of the Month
Firm Performance Pay as Insurance against Promotion Risk
Alvin Chen
Journal of Finance, October 2024, Pages 3497-3541
Abstract:
The prevalence of pay based on risky firm outcomes for nonexecutive workers presents a puzzling departure from conventional contract theory, which predicts insurance provision by the firm. When workers at the same firm compete against each other for promotions, the optimal contract features pay based on firm outcomes as insurance against promotion risk. The model's predictions are consistent with many observed phenomena, such as performance-based vesting and overvaluation of equity pay by nonexecutive workers. It also generates novel predictions linking a firm's hierarchy to its workers' pay structure.
The Crowdless Future? Generative AI and Creative Problem-Solving
Léonard Boussioux et al.
Organization Science, forthcoming
Abstract:
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy business ideas generated by the human crowd (HC) and collaborative human-AI efforts using two alternative forms of solution search. The challenge attracted 125 global solvers from various industries, and we used strategic prompt engineering to generate the human-AI solutions. We recruited 300 external human evaluators to judge a randomized selection of 13 out of 234 solutions, totaling 3,900 evaluator-solution pairs. Our results indicate that while human crowd solutions exhibited higher novelty -- both on average and for highly novel outcomes -- human-AI solutions demonstrated superior strategic viability, financial and environmental value, and overall quality. Notably, human-AI solutions cocreated through differentiated search, where human-guided prompts instructed the large language model to sequentially generate outputs distinct from previous iterations, outperformed solutions generated through independent search. By incorporating “AI in the loop” into human-centered creative problem-solving, our study demonstrates a scalable, cost-effective approach to augment the early innovation phases and lays the groundwork for investigating how integrating human-AI solution search processes can drive more impactful innovations.
The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations
Jacqueline Lane et al.
Harvard Working Paper, August 2024
Abstract:
The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay between objective criteria, which are quantifiable, and subjective criteria, which rely on personal judgment. We conducted a field experiment with MIT Solve, involving 72 experts and 156 community screeners who evaluated 48 solutions for the 2024 Global Health Equity Challenge. Screeners received assistance from GPT-4, offering recommendations and, in some cases, rationale. We compared a human-only control group with two AI-assisted treatments: a black box AI and a narrative AI with probabilistic explanations justifying its decisions. Our findings show that AI-assisted screeners were 9 percentage points more likely to fail a solution. For objective criteria, there was no significant difference between the black box and narrative AI conditions. However, for subjective criteria, screeners adhered to narrative AI’s recommendations 12 percentage points more often than the black box AI’s. These effects were consistent across both experts and non-experts. Mouse tracking data showed that deeper engagement with AI’s objective failure recommendations led to more overrides of the AI, particularly in the narrative AI condition, reflecting increased scrutiny. Conversely, deeper engagement with AI’s subjective failure recommendations led to greater alignment with AI, particularly in the black box condition. This research underscores the importance of developing AI interaction expertise in creative evaluation processes that combine human judgment with AI insights. While AI can standardize decision-making for objective criteria, human oversight and critical thinking remain indispensable in subjective assessments, where AI should complement, not replace, human judgment.
How Does Artificial Intelligence Shape Audit Firms?
Kelvin Law & Michael Shen
Management Science, forthcoming
Abstract:
Does artificial intelligence (AI) displace auditors? We exploit the staggered hiring of AI employees at audit office locations across the United States as a proxy for the use of AI at local audit offices. The main findings are as follows. First, relative to audit offices that do not yet hire AI employees, those that do hire AI employees have a 4.3% increase in the number of auditor jobs, particularly among junior and midlevel auditors. Second, using AI is associated with an increased demand for soft skills (e.g., cognitive skills) in auditor jobs. Third, audit offices that use AI have more accurate going concern and internal control opinions. Semistructured interviews of 11 seasoned audit partners confirm that investment in AI is centralized at the national level, but the decision to deploy it often resides at the local audit office level. Notably, none of the partners believe that AI has replaced or will replace human auditors. Overall, our study -- comprising both empirical and qualitative data -- suggests that using AI does not replace auditors, but rather changes the skills required for these jobs and improves audit quality.
The Wade Test: Generative AI and CEO Communication
Prithwiraj Choudhury, Bart Vanneste & Amirhossein Zohrehvand
Harvard Working Paper, August 2024
Abstract:
Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO communication? This study investigates whether AI can mimic a human CEO and whether employees’ perception of the communication’s source matter. In a field experiment with a firm, we extend the idea of a Turing test (i.e., a computer mimicking a person), to the idea of generative AI mimicking a specific person, namely the CEO. We call this the “Wade test” and assess if employees can distinguish between communication from their CEO and communication generated by an AI trained on the CEO’s prior communications. We find that AI responses are correctly identified 59% of the time, somewhat better than random chance. When employees believe a response is AI generated, regardless of its actual source, they perceive it as less helpful. To assess causal mechanisms, a second study with a general audience, using public statements from CEOs and from an AI intended to mimic those CEOs, finds that AI-labeled responses (irrespective of their actual source) are rated as less helpful. These findings highlight that, when using generative AI in CEO communication, people may inaccurately identify the source of communication and exhibit aversion towards communication they identify as being AI generated.
Brains versus brawn: Ordinal rank effects in job training
Alexander Chesney & Scott Carrell
Journal of Public Economics, October 2024
Abstract:
This paper analyzes ordinal rank across cognitive and physical ability within an initial job training program. Using a rich administrative dataset and conditional random assignment of trainees to peer groups, we test whether rank effects vary across contemporaneous training and long-term career outcomes. We find cognitive ordinal rank, measured by an individual’s score on the Armed Forces Qualification Test (AFQT), has a meaningful impact on completing initial training into the U.S. Air Force (USAF). This ranking also affects occupational specialization for trainees that arrive without a preassigned occupation. We also show physical ordinal rank, measured by an individual’s initial fitness score, affects job training performance. Both sets of ranking effects impact behavioral misconduct outcomes and vary by gender. Finally, the interaction between cognitive and physical ordinal ranking has multiplicative effects on a limited set of outcomes.
“Abuser” or “Tough Love” Boss?: The moderating role of leader performance in shaping the labels employees use in response to abusive supervision
Robert Lount, Woohee Choi & Bennett Tepper
Organizational Behavior and Human Decision Processes, July 2024
Abstract:
We invoke leader categorization theory and labeling theory to examine the circumstances under which individuals come to perceive their managerial leaders as “abusers” or “tough love” bosses. In a field study, we show that leader performance moderates the relationship between a leader’s abusive supervision and the degree to which their followers label them as an abuser or a tough love leader. Heightened leader performance lowers the willingness to label the leader as an “abuser” while increasing one’s labeling the leader as a “tough love” boss. This study also documents that leader performance moderates the indirect effect between abusive supervision and upward hostility (through abuser labeling) and the indirect effect between abusive supervision and positive career expectations (through tough love labeling). In a follow-up experiment, we again document that leader performance moderates the relationship between abusive supervision and the degree to which followers label their leaders as an abuser. Additionally, we provide support for a moderated indirect effect on a range of negative behavioral outcomes directed toward the leader through abuser labeling. We discuss the studies’ implications for theory, future research, and practice pertaining to abusive supervision.
The Psychological Design of Firm Boundaries: Preempting Escalating Commitment through Buy Vs. Make
Daniel Keum
Academy of Management Journal, forthcoming
Abstract:
Strong ownership of the product development process, while facilitating the generation of new products, can exacerbate escalating commitment and impede timely termination. We examine how managers, with foresight, use buy vs. make decisions to create psychological and organizational distance from a product and preempt escalating commitment. Using detailed product-level data from the fashion industry and its unique features, we show that managers contract manufacture risky products even when they can be readily manufactured in-house, especially core products that are central to a firm’s identity and hence more prone to escalating commitment. Our findings highlight cognitive bias as a source of internal transaction cost and bring its preemption to the forefront of buy vs. make decisions. Our study develops a cognitive foundation for transaction cost theory that does not depend on opportunism or asset specificity and highlights the psychological designing of firm boundaries as a strategy for improving the decision environment.
Head Impact, Concussion, and Salary in the NFL: Is There a Compensating Wage-Risk Premium?
Bhavneet Walia et al.
American Behavioral Scientist, forthcoming
Abstract:
Sport epidemiological studies have estimated cumulative head impact and concussion rates by American football position group. Meanwhile, the sports economics literature has examined National football league (NFL) player-salary variation, and sports statisticians have studied NFL player productivity. Merging novel data and methodologies, we estimate whether players in position-groups with higher head impact or concussion risk are paid a compensating next-contract salary premium controlling for NFL experience, contract year, and productivity. For 2006 to 2017 NFL seasons, we consider all 1,162 fully observed player contracts and all 290 fully observed, non-rookie player contracts. Specifying two sets of contract-length frequency-weighted, contract-year (of signing) fixed effects linear regressions, we find robust evidence that players receive lagged, next-contract compensation for additional on-field productivity and experience. However, position groups with higher estimated cumulative head impact and, alternatively, higher estimated concussion rate are paid a significant and substantial next-contract dispremium. Results are consistent with an augmented compensating salary-differential theory, in which firm and employee share risk.
Sharing is Caring: Employee Stock Ownership Plans and Employee Well-Being in U.S. Manufacturing
Adrianto Adrianto et al.
University of Minnesota Working Paper, August 2024
Abstract:
Do employees fare better in firms they partly own? Examining workers' reviews of their employers on Glassdoor, we compare employee satisfaction between firms in which workers own company shares through an employee stock ownership plan (ESOP) and conventional firms in which they do not. Focusing on workers in U.S. manufacturing, we find employees report greater satisfaction in employee-owned firms overall and with specific aspects of jobs such as firm culture. This satisfaction premium is greater when the ESOP is the product of collective bargaining or employees own a larger stake of firm equity. Employee well-being can thus differ by ownership arrangement.