Micromanaging
Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition
Tania Babina et al.
NBER Working Paper, June 2023
Abstract:
We study the shifts in U.S. firms' workforce composition and organization associated with the use of AI technologies. To do so, we leverage a unique combination of worker resume and job postings datasets to measure firm-level AI investments and workforce composition variables, such as educational attainment, specialization, and hierarchy. We document that firms with higher initial shares of highly-educated workers and STEM workers invest more in AI. As firms invest in AI, they tend to transition to more educated workforces, with higher shares of workers with undergraduate and graduate degrees, and more specialization in STEM fields and IT skills. Furthermore, AI investments are associated with a flattening of the firms' hierarchical structure, with significant increases in the share of workers at the junior level and decreases in shares of workers in middle-management and senior roles. Overall, our results highlight that adoption of AI technologies is associated with significant reorganization of firms' workforces.
Canceling Disputes: How Social Capital Affects the Arbitration of Disputes on Wikipedia
Florian Grisel
Law & Social Inquiry, forthcoming
Abstract:
This article examines how social capital affects the resolution of disputes by focusing on English Wikipedia’s Arbitration Committee, sometimes described as “Wikipedia’s Supreme Court.” Drawing on quantitative and qualitative data, the article contends that the Arbitration Committee not only examines the merits of the claims made by the disputants, but also and more crucially considers the position of each disputant within the community of editors in its decision-making process. In doing so, the Arbitration Committee does not simply decide or arbitrate disputes but seeks to attenuate their impact on Wikipedia’s social fabric. This data allows us to revisit sociological debates on the role of social capital, by revealing the ways in which well-connected individuals employ it strategically in order to obfuscate their noncompliance with norms, thus leading to what I call “dispute cancellation.”
Pay Suppression in Social Impact Contexts: How Framing Work Around the Greater Good Inhibits Job Candidate Compensation Demands
Insiya Hussain et al.
Organization Science, forthcoming
Abstract:
Past research suggests that when organizations communicate the benefits of their work for human welfare -- that is, use a social impact framing for work -- job candidates are willing to accept lower wages because they expect the work to be personally meaningful. We argue that this explanation overlooks a less socially desirable mechanism by which social impact framing leads to lower compensation demands: the perception among job candidates that requesting higher pay will breach organizational expectations to value work for its intrinsic (rather than extrinsic) rewards, or constitute a motivational norm violation. We find evidence for our theory across five studies: a qualitative study (Study 1), a hiring experiment with undergraduate students (Study 2), an online labor market field experiment (Study 3), a vignette-based simulation (Study 4), and a stimulus sampling study using multiple occupations (Study 5). Exploratory analyses find that the negative effects are unique to monetary (versus nonmonetary) job rewards. Together, results uncover a novel mechanism by which emphasizing work for the greater good leads job candidates to accept lower wages -- one that reflects candidates self-censoring on pay from concerns about violating organizational norms rather than solely from a willingness to trade higher pay for potentially meaningful work. Our research contributes to understandings of how social responsibility messaging impacts workers’ perceptions of organizations and negotiation behavior. It also holds implications for emerging scholarship on managers’ implicit theories of employee work motivation.
On the Allocation and Impacts of Managerial Training
Achyuta Adhvaryu, Emir Murathanoglu & Anant Nyshadham
NBER Working Paper, June 2023
Abstract:
We study the allocation and productivity consequences of training production line supervisors in soft skills via a randomized controlled trial. Consistent with standard practice for training investments within firms, we asked middle managers -- who sit above supervisors in the hierarchy -- to nominate members of their supervisory team for training. Program access was randomized within these recommendation rankings. Highly recommended supervisors experienced no productivity gains; in contrast, less-recommended supervisors' productivity increased 12% relative to controls. This was not due to poor information or favoritism. Instead, consistent with the fact that supervisor turnover comes at a large effort cost to middle managers due to gaps in coverage and onboarding, middle managers prioritized retention over productivity impacts. Indeed, treated supervisors were 15% less likely to quit than controls; this gain was most pronounced for highly recommended supervisors. Misallocation of training can help explain the persistence of low managerial quality in firms.
Advanced Technology Adoption: Selection or Causal Effects?
Daron Acemoglu et al.
AEA Papers and Proceedings, May 2023, Pages 210-214
Abstract:
This paper uses data from the 2019 Annual Business Survey to document that firms adopting advanced technologies are larger in terms of employment than other firms in their same industry and cohort. Using data from the Longitudinal Business Survey, we show that adopters were already large and growing faster before artificial intelligence, robotics, cloud computing, and specialized software systems became broadly available. These findings support the view that adopters are large because of selection and not because adopting advanced technologies for automation causally expands their employment.
Time Is Not Money! Temporal Preferences for Time Investments and Entry into Entrepreneurship
Cédric Gutierrez, Randolph Sloof & Donal Crilly
Organization Science, forthcoming
Abstract:
Starting a business requires investing both money and time in the hope of future financial benefits. Because investments and potential gains happen over time, the way in which individuals value the future relative to the present -- that is, their temporal preferences -- may be an important driver behind the decision to become an entrepreneur. Whereas existing research examines temporal preferences for financial gains, we advance this research by theorizing about temporal preferences not only for money, but also for the future time commitments that entrepreneurship entails. Results from a laboratory-in-the-field study show that individuals who heavily discount future time investments are more likely to become entrepreneurs. In two follow-up studies, we confirm that recent start-up founders discount future time investments more than salaried workers. We also provide suggestive evidence of the mechanisms at play: recent start-up founders perceive the future differently than salaried workers, both viewing themselves as more agentic vis-à-vis the future and perceiving the future as more distant. We discuss the implications of temporal preferences -- not only for money, but also for time -- for understanding the behavioral drivers of entrepreneurship.
Is Your Machine Better Than You? You May Never Know
Francis de Véricourt & Huseyin Gurkan
Management Science, forthcoming
Abstract:
Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based prescriptions. This paper explores the extent to which a decision maker (DM) supervising a machine to make high-stakes decisions can properly assess whether the machine produces better recommendations. To that end, we study a setup in which a machine performs repeated decision tasks (e.g., whether to perform a biopsy) under the DM’s supervision. Because stakes are high, the DM primarily focuses on making the best choice for the task at hand. Nonetheless, as the DM observes the correctness of the machine’s prescriptions across tasks, the DM updates the DM’s belief about the machine. However, the DM is subject to a so-called verification bias such that the DM verifies the machine’s correctness and updates the DM’s belief accordingly only if the DM ultimately decides to act on the task. In this setup, we characterize the evolution of the DM’s belief and overruling decisions over time. We identify situations under which the DM hesitates forever whether the machine is better; that is, the DM never fully ignores but regularly overrules it. Moreover, the DM sometimes wrongly believes with positive probability that the machine is better. We fully characterize the conditions under which these learning failures occur and explore how mistrusting the machine affects them. These findings provide a novel explanation for human–machine complementarity and suggest guidelines on the decision to fully adopt or reject a machine.
Caught Between a Clock and a Hard Place: Temporal Ambivalence and Time (Mis)management in Teams
Colin Fisher, Sujin Jang & Richard Hackman
Organization Science, forthcoming
Abstract:
This paper examines how teams manage temporal ambivalence, or the simultaneous and conflicting perceptions of time as a resource, including how much time has passed and whether there is enough of it left. Team members’ time perceptions influence how a team manages time; thus, effective time management requires some collective resolution of temporal ambivalence. To study the effects of temporal ambivalence on time management processes and performance in teams, we conducted a laboratory study in which we manipulated perceptions of time by engineering a wall clock to run at different speeds (normal, fast, or slow) to instantiate different types of temporal ambivalence. Using both quantitative and qualitative analyses, we found that managing temporal ambivalence effectively is essential for teams to appropriately allocate time to different phases of work. Specifically, teams often misallocated their time by either transitioning too late or too early between phases of work, both of which were associated with worse team performance than transitioning closer to the temporal midpoint. Teams with heightened temporal ambivalence were more likely to manage time poorly following one or more of three dysfunctional patterns: bypassing comments, glossing over contradictions, and following passively. By contrast, teams that managed temporal ambivalence effectively did so through time management huddles, in which team members briefly and collectively took time away from the main task to explicitly discuss how to allocate their time. We discuss the implications of these findings for research on team process, ambivalence, and time management in organizations.
Early Joiners and Startup Performance
Joonkyu Choi et al.
Federal Reserve Working Paper, February 2023
Abstract:
We show that early joiners -- non-founder employees in the first year of a startup -- play a critical role in explaining firm performance. We use administrative employee-employer matched data on all US startups and utilize the premature death of workers as a natural experiment exogenously separating talent from young firms. We find that losing an early joiner has a large negative effect on firm size that persists for at least ten years. When compared to that of a founder, losing an early joiner has a smaller effect on firm death but intensive margin effects on firm size are similar in magnitude. We also find that early joiners become relatively more important with the age of the firm. In contrast, losing a later joiner yields only a small and temporary decline in firm performance. We provide evidence that is consistent with the idea that organization capital, an important driver of startup success, is embodied in early joiners.
The impact of absent co-workers on productivity in teams
Sam Hoey, Thomas Peeters & Jan van Ours
Labour Economics, forthcoming
Abstract:
We study how workers in production teams are affected by the temporary absence and replacement of a co-worker using data on injuries in the National Hockey League. We distinguish between the absence of a substitute worker, who performs the same tasks as the focal workers, and the absence of a complementary co-workers, who performs complementary tasks to the focal workers. When either type of co-worker is absent, remaining workers produce less output per working time. In the case of a substitute absentee, they compensate for this by increasing their working time at the expense of the (less able) replacement worker. This renders the output loss per remaining substitute worker to be insignificant. For the absence of a complementary worker, the productivity loss leads to a loss of total output per worker, because remaining workers cannot take over the absent co-worker’s tasks.
Does Employee Happiness Have an Impact on Productivity?
Clément Bellet, Jan-Emmanuel De Neve & George Ward
Management Science, forthcoming
Abstract:
This paper provides evidence from a natural experiment on the relationship between positive affect and productivity. We link highly detailed administrative data on the behaviors and performance of all telesales workers at a large telecommunications company with survey reports of employee happiness that we collected on a weekly basis. We use variation in worker mood arising from visual exposure to weather -- the interaction between call center architecture and outdoor weather conditions -- to provide a quasi-experimental test of the effect of happiness on productivity. We find evidence of a positive impact on sales performance, which is driven by changes in labor productivity -- largely through workers converting more calls into sales and to a lesser extent by making more calls per hour and adhering more closely to their schedule. We find no evidence in our setting of effects on measures of high-frequency labor supply such as attendance and break-taking.
Founder personality and entrepreneurial outcomes: A large-scale field study of technology startups
Brandon Freiberg & Sandra Matz
Proceedings of the National Academy of Sciences, 9 May 2023
Abstract:
Technology startups play an essential role in the economy -- with seven of the ten largest companies rooted in technology, and venture capital investments totaling approximately $300B annually. Yet, important startup outcomes (e.g., whether a startup raises venture capital or gets acquired) remain difficult to forecast -- particularly during the early stages of venture formation. Here, we examine the impact of an essential, yet underexplored, factor that can be observed from the moment of startup creation: founder personality. We predict psychological traits from digital footprints to explore how founder personality is associated with critical startup milestones. Observing 10,541 founder–startup dyads, we provide large-scale, ecologically valid evidence that founder personality is associated with outcomes across all phases of a venture’s life (i.e., from raising the earliest funding round to exiting via acquisition or initial public offering). We find that openness and agreeableness are positively related to the likelihood of raising an initial round of funding (but unrelated to all subsequent conditional outcomes). Neuroticism is negatively related to all outcomes, highlighting the importance of founders’ resilience. Finally, conscientiousness is positively related to early-stage investment, but negatively related to exit conditional on funding. While prior work has painted conscientiousness as a major benefactor of performance, our findings highlight a potential boundary condition: The fast-moving world of technology startups affords founders with lower or moderate levels of conscientiousness a competitive advantage when it comes to monetizing their business via acquisition or IPO.