Hardly Managing
A formal account of bullshit jobs
Laurent Gauthier
Theory and Society, December 2025, Pages 959-990
Abstract:
"Bullshit jobs" were introduced by anthropologist David Graeber (2018): well paid jobs perceived as useless by those holding them and raising questions about the legitimacy and social meaning of work. Empirical studies in sociology and economics have shown that a large share of all jobs may be qualified as bullshit jobs according to Graeber's definition (10-40%). However, this phenomenon has not been given a formal theoretical account: Graeber's work has not been addressed by economists. Our purpose is to provide a formal explanation for why such jobs can arise inside organizations. Our central hypothesis is that when managers are incentivized to extend the wage bill, organizations may sustain well-paid positions that are net negatives. We propose a simple model of high- and low-skill labor, combined with middle management's specific incentives. We show that a pooling equilibrium exists where high-skill jobs squander resources and become bullshit jobs. Within the model, the hypothesis is confirmed: the specified incentive structure is sufficient to produce bullshit jobs. Our formal account of bullshit jobs frames them as an organizational cost, which links anthropological insights with formal modeling in the sociology of work.
Leaving money on the table: As diagnostic aids become more useful, operators use them less efficiently
Fernando Munoz Gomez Andrade et al.
Journal of Experimental Psychology: Applied, forthcoming
Abstract:
Diagnostic aids can assist human operators in everyday and high-stakes decision tasks, but performance typically falls short of best possible levels, reflecting a tendency toward disuse. To mitigate disuse, it is important to understand how task context influences aid dependence. The present study tested the prediction that aid use will become less efficient either as the aid becomes more reliable or the decision maker's task becomes more difficult. Participants (N = 127; data collected in 2023) performed a signal detection task with and without support from a diagnostic aid, where task difficulty and aid reliability varied between subjects. Analyses compared observed levels of aided performance with the predictions of an optimal strategy. Aided performance was consistently suboptimal but fell furthest from optimal when the aid was most reliable and when the task was most difficult. Costs of disuse to decision accuracy were substantial. Findings replicate and extend earlier patterns of suboptimal use, indicating that a mechanism of disuse is a failure to increase aid dependence appropriately in response to increases in aid quality or task demand.
Bargaining with a Deadline: Evidence from the NBA
Xin Nong & Weijing Huang
Journal of Sports Economics, forthcoming
Abstract:
Theoretical models show that reputational concerns provide a natural explanation for "deadline effects," characterized by a surge of agreements reached just before a deadline in bargaining. This paper provides empirical evidence for this claim using a novel dataset on deadline trades from 30 National Basketball Association (NBA) teams between 2000 and 2024. The NBA imposes a publicly known deadline, after which teams cannot trade players for the remainder of the season. Our analysis reveals a statistically significant negative relationship between general managers' tenure and the likelihood of making deadline trades, controlling for age and team performance. This pattern suggests that new managers, seeking to establish reputations as tough negotiators, are more likely to hold firm until the deadline. We also find that while 58 percent of deadline trades involve important assets, they have no systematic effect on subsequent team performance.
Roadmap or Compass? The Value of Prior Collaborative Experience in an Unfamiliar Task Environment
Julien Clement & Sarath Balachandran
Organization Science, forthcoming
Abstract:
When a temporary team faces an unfamiliar task environment, it should particularly benefit from including members who have collaborated before. Although several studies have made this prediction, it has not been supported empirically. We reconcile this discrepancy by distinguishing between prior collaborations in tightly versus loosely coupled roles, defined by the degree of interdependence among collaborators during prior work. Both forms of prior collaboration can help teammates communicate effectively, aiding team adaptation in new contexts. However, prior collaboration in tightly coupled roles also fosters shared routines that may create inertia and impede adaptation. As a result, we argue that the value of tightly coupled experience declines in unfamiliar environments, whereas the value of loosely coupled experience increases. We test these ideas using data from esports, where professional players with varying collaborative histories are randomly assigned to temporary teams. Unanticipated changes to the game exogenously alter teams' familiarity with their task environments. Consistent with our theory, we find that tightly coupled collaborative experience enhances team performance in familiar task environments but degrades it in unfamiliar ones. Loosely coupled experience provides modest benefits in familiar environments but substantially enhances performance in unfamiliar ones. Overall, our findings suggest that when environments change, tightly coupled experience can act as a faulty roadmap -- anchoring teams to outdated routines -- whereas loosely coupled experience can serve as a compass that promotes coordination and adaptation.
Evaluating the Efficacy of Application Costs for Managing Congestion in Online Matching Markets
Ni Huang et al.
Management Science, forthcoming
Abstract:
Matching platforms seek to facilitate market clearing, but congestion arises with imbalances in supply and demand. In online labor markets, when workers can apply to jobs without restriction, they may apply to an excessive volume of positions to maximize their likelihood of securing work, overwhelming employers and making screening difficult if not altogether unmanageable. Prior research has theoretically argued that imposing application costs on workers can mitigate this issue. However, the efficacy of such a solution has yet to be evaluated empirically in matching platforms where employers incur significant screening costs. We address that gap here, considering a prominent online labor market that imposed application costs on workers. We report evidence that application costs successfully improved matching outcomes via at least two channels. First, the application costs reduced bid volumes, lowering employer screening costs in turn. Second, the application costs led workers to become more selective in their applications, focusing on the employers and jobs that they were best suited for and putting greater effort into differentiating themselves, including actively reaching out to employers via direct messages. These worker-side, secondary responses enhance the first-order benefit of the application costs (i.e., constraining application volumes). Finally, the workers' increased selectivity comes paired with risk aversion among workers, who become more likely to apply for jobs requiring familiar skills and less likely to apply for jobs posted by employers in different time zones or speaking a different language. We discuss the implications of our findings for workers' longer-term career trajectories and market sustainability generally.
Of opinionated bosses and yes men
Yuqi (Angela) Jiang & Suraj Prasad
Journal of Economic Behavior & Organization, January 2026
Abstract:
This paper develops a theory of opinionated bosses -- this is where a boss reveals her opinions to a worker who is tasked with gathering information. When the worker gathers information across multiple tasks, which he views as substitutes, the boss may selectively reveal her opinions to the worker on a well known task to redirect his effort to the task that is less well known. The benefit is a broader expertise across activities in the organization when rewards across these activities are implicitly determined. The cost is that the worker becomes a yes man. Being opinionated can, i) go hand in hand with weaker opinions, ii) lead to excessive levels of conformity and initiative, and finally, iii) improve the tradeoff between insurance and explicit incentives when a worker is risk averse.
The Mean-Variance Innovation Tradeoff in AI-Augmented Evaluations
Cyrille Grumbach, Jacqueline Lane & Georg von Krogh
Harvard Working Paper, January 2026
Abstract:
Evaluating and selecting among numerous alternative solutions shapes the trajectory and rate of innovation. Central to this process is a fundamental tension between novelty and feasibility that evaluators, operating under bounded rationality, cannot consider simultaneously and therefore rely on heuristics to guide their evaluations. A common heuristic is criteria-sequencing, in which evaluators prioritize alternative criteria at different evaluation stages. Yet, the idiosyncratic ways evaluators sequence these criteria often introduce inconsistencies, creating significant path dependencies in the process. In this paper, we propose that artificial intelligence (AI) offers a potential lever to structure evaluators' criteria-sequencing heuristics. Leveraging a field experiment with 353 evaluators, we investigate how the sequencing of AI recommendations focusing on novelty and feasibility shapes the mean and variance of innovation among selected solutions. Our results reveal a mean-variance innovation tradeoff: a feasibility-then-novelty sequence leads to selections with higher mean innovation, whereas a novelty-then-feasibility sequence yields selections with greater innovation variance. Furthermore, a post hoc analysis uncovers that the format accompanying AI recommendations also matters. A dynamic format (i.e., interactive chatbot) increases the innovation variance among selected solutions but reduces their mean innovation relative to a static format (i.e., fixed explanatory content). Because these effects operate independently, our findings show that in AI-augmented evaluations, both the sequence of criteria and the format accompanying AI recommendations shape the mean-variance innovation tradeoff. These differences have important implications for the composition of innovation portfolios. Our paper contributes to innovation evaluation research and to emerging literature on human-AI collaboration in innovation-related contexts.
Traumatic Shocks, Near-Misses, and Radical Innovation
Luis Ballesteros
Boston University Working Paper, November 2025
Abstract:
This study examines how direct exposure to traumatic shocks shapes the trajectory and composition of local inventive activity in the United States from 1995 to 2022. Using geolocated U.S. patents and sudden natural-disaster footprints in a boundary design with staggered difference-in-differences , the results reveal a distinct post-shock divergence in radical innovation among locations directly affected, those nearly missing the disaster, and those never exposed. Relative to near miss locations, disaster areas expand into new technological domains about 41% more often and exhibit roughly 29% higher upper tail novelty. Disaster areas also outperform never-exposed locations by 124% and 22% on the respective measures. This boundary divergence is both extensive, where inventors in hit areas explore new technology subclasses, and intensive, where their inventions venture further from existing knowledge combinations. In contrast, near-miss locations show a 17% drop in new entries and a 12% decline in technology novelty versus never-exposed areas. These effects are strongest three to six years post-disaster, consistent with lags between idea generation and patent filing, and attenuated in severe-disaster zones, suggesting a recalibrated willingness to take inventive risks that is bounded by local capacity constraints. Additional analyses show that increased exploration extends beyond disaster-relevant technologies and is not driven by economic rebounds, market demand, or selective migration. This study contributes new evidence to the behavioral foundations of innovation under uncertainty and underscores the spatial and, often, serendipitous nature of strategic search after trauma.