Production Lines
Judgment Aggregation in Creative Production: Evidence from the Movie Industry
Hong Luo, Jeffrey Macher & Michael Wahlen
Management Science, forthcoming
Abstract:
We study a novel, low-cost approach to aggregating judgment from a large number of industry experts on ideas that they encounter in their normal course of business. Our context is the movie industry, in which customer appeal is difficult to predict and investment costs are high. The Black List, an annual publication, ranks unproduced scripts based on anonymous nominations from film executives. This approach entails an inherent trade-off: Low participation costs enable high response rates, but nominations lack standard criteria, and which voters see which ideas is unobservable and influenced by various factors. Despite these challenges, we find that such aggregation is predictive: Listed scripts are substantially more likely to be released than observably similar, but unlisted, scripts, and, conditional on release and investment levels, listed scripts generate higher box-office revenues. We also find that this method mitigates entry barriers for less-experienced writers, as (i) their scripts are more likely to be listed than those by experienced writers and to rank higher if listed and (ii) within scripts by less-experienced writers, being listed is associated with a higher release rate. Yet, the gap in release probabilities relative to experienced writers remains large, even for top-ranked scripts. These results can be explained by the premise that scripts from less-experienced writers are more visible among eligible voters than scripts from experienced writers. This highlights idea visibility as an important determinant of votes and surfaces the trade-offs, as well as potential limitations, associated with such methods.
Sharing the Wealth: The Effects of TCJA Bonuses on Employee Pay Satisfaction
Michelle Hutchens, Dan Lynch & Bridget Stomberg
Indiana University Working Paper, December 2020
Abstract:
Approximately 60 public companies announced they would share cash windfalls from the Tax Cuts and Jobs Act (TCJA) with rank-and-file employees through bonuses, higher wages, or increased benefits. We use employee survey data from Culture X to examine how the announcement of these TCJA bonuses affected employee pay satisfaction. Although employees are economically better off upon receiving these bonuses, prior literature suggests employee pay satisfaction could decrease if employees perceive the bonuses to be unfairly small. Using a difference-in-difference design, we find a greater decline in pay satisfaction among employees at firms announcing a TCJA bonus versus those that do not. Consistent with dissatisfaction about unfairly small bonuses, we document a larger decline in pay satisfaction at announcing firms with larger increases in CEO bonuses and larger share repurchases around the TCJA. Our results provide new insights into how workers respond to changes in compensation stemming from corporate tax savings.
Doing Well By Doing Good: Improving Store Performance with Employee-friendly Scheduling Practices at the Gap, Inc
Saravanan Kesavan et al.
University of North Carolina Working Paper, July 2020
Abstract:
We estimate the causal effects of employee-friendly scheduling practices on store financial performance at the US retailer Gap, Inc. The randomized field experiment evaluated a multi-component intervention designed to improve dimensions of work schedules - inconsistency, unpredictability, inadequacy, and lack-of-employee control - shown to undermine employee well-being and productivity. The experiment was conducted in 28 stores in the San Francisco and Chicago metropolitan areas during a 9-month period between November 2015 and August 2016. Intent-to-treat (ITT) analyses indicate that implementing employee-friendly scheduling practices increased store productivity by 5.1%, a result of increasing sales (by 3.2%) while also decreasing labor (by 1.8%). Drawing on qualitative interviews with managers and quantitative analyses of employee shift-level data, we offer evidence that the intervention improved financial performance through two mechanisms: enhanced employee effort and store execution. Given the common assumption that employee-friendly scheduling practices are costly for business because they reduce labor flexibility for employers, we give particular attention to examining how the intervention reduced labor hours. Analyses indicate that a significant proportion of the reduction can be traced to improved employee schedule adherence and the subsequent decrease in downstream "paper cuts" to the labor budget that occurs as one employee's tardiness cascades throughout the day and to coworkers. Our findings thus provide compelling evidence that schedule adherence is not exogenous to managers' scheduling behavior or to scheduling algorithms. Employers place profits at risk when they underestimate the business benefits of employee-friendly scheduling practices.
The diversity bonus in pooling local knowledge about complex problems
Payam Aminpour et al.
Proceedings of the National Academy of Sciences, 2 February 2021
Abstract:
Recently, theoreticians have hypothesized that diverse groups, as opposed to groups that are homogeneous, may have relative merits [S. E. Page, The Diversity Bonus (2019)] - all of which lead to more success in solving complex problems. As such, understanding complex, intertwined environmental and social issues may benefit from the integration of diverse types of local expertise. However, efforts to support this hypothesis have been frequently made through laboratory-based or computational experiments, and it is unclear whether these discoveries generalize to real-world complexities. To bridge this divide, we combine an Internet-based knowledge elicitation technique with theoretical principles of collective intelligence to design an experiment with local stakeholders. Using a case of striped bass fisheries in Massachusetts, we pool the local knowledge of resource stakeholders represented by graphical cognitive maps to produce a causal model of complex social-ecological interdependencies associated with fisheries ecosystems. Blinded reviews from a scientific expert panel revealed that the models of diverse groups outranked those from homogeneous groups. Evaluation via stochastic network analysis also indicated that a diverse group more adequately modeled complex feedbacks and interdependencies than homogeneous groups. We then used our data to run Monte Carlo experiments wherein the distributions of stakeholder-driven cognitive maps were randomly reproduced and virtual groups were generated. Random experiments also predicted that knowledge diversity improves group success, which was measured by benchmarking group models against an ecosystem-based fishery management model. We also highlight that diversity must be moderated through a proper aggregation process, leading to more complex yet parsimonious models.
True Motives: Prosocial and Instrumental Justifications for Behavioral Change in Organizations
Matthew Amengual & Evan Apfelbaum
Management Science, forthcoming
Abstract:
When organizations want their employees to adopt behaviors that advance prosocial and instrumental aims, which motive should they express? A groundswell of recent work suggests that highlighting prosocial actions inspires and motivates employees. Building on this work, we embed a field experiment in the context of an organizational change initiative (Study 1). A large university sought to change the behavior of administrative employees who purchase office supplies, encouraging them to place orders of at least $50, referred to as "bundling." We exploit the fact that the organization could justify the same behavior in contrasting ways. We randomly assign employees to view either a prosocial ("limiting pollution"), instrumental ("limiting costs"), or mixed motive ("limiting pollution and limiting costs") for caring about bundling each time they access the organization's procurement system. We then evaluate changes in employees' behavior by comparing a six-month baseline to a six-month experimental period, covering 10,169 purchases in 556 offices. Contrary to expectations from related research, the instrumental motive was most effective for changing behavior, leading to significantly more bundling than the prosocial motive. Two follow-up vignette experiments probe theoretical mechanisms. They indicate that an instrumental motive seems more genuine (i.e., reflecting the organization's true motive) than a prosocial motive (Study 2) and that seeming genuine increases individuals' intention to bundle (Study 3). This research reveals that prosocial justifications can be less effective than instrumental ones and suggests that perceptions of genuineness may shape the effectiveness of behavioral change efforts in organizations.
Demand Conditions and Worker Safety: Evidence from Price Shocks in Mining
Kerwin Charles et al.
Journal of Labor Economics, forthcoming
Abstract:
We investigate how demand conditions affect employers' provision of safety - something about which theory is ambivalent. Positive demand shocks relax financial constraints that limit safety investment, but simultaneously raise the opportunity cost of increasing safety rather than production. We study the U.S. metals mining sector, leveraging exogenous demand shocks from short-term variation in global commodity prices. We find that positive price shocks substantially increase workplace injury rates and safety regulation non-compliance. While these results indicate the general dominance of the opportunity cost effect, shocks that only increase mines' cash-flow lower injury rates, illustrating that financial constraints also affect safety.
How Bad Apples Promote Bad Barrels: Unethical Leader Behavior and the Selective Attrition Effect
Robert Cialdini et al.
Journal of Business Ethics, February 2021, Pages 861-880
Abstract:
We present a theoretical rationale and supporting studies revealing how unethical leader behavior fosters an unethical climate within workgroups that increases member turnover intentions and malfeasance. Drawing on the attraction-selection-attrition model of organizational behavior, we propose a selective attrition effect whereby unethical leader behavior results in the retention of group members who are more comfortable with dishonesty and, consequently, more likely to engage in unethical behavior toward their group. In two experiments, exposure to unethical leader behavior (vs. ethical leader behavior) increased group members' likelihood of choosing to leave the group. Members who chose to remain in a group with an unethical leader were more likely than those who chose to leave to cheat their group in a subsequent task. A two time-period survey replicated these findings and identified psychological distress as the mechanism driving group members' turnover intentions. This research extends our understanding of the complex relationships between unethical leadership and follower turnover intentions, psychological distress, and malfeasance. We contribute to the behavioral ethics literature by identifying a previously underappreciated form of selective attrition that produces internal costs to groups and organizations, independent of reputational consequences and whether the unethicality is publicized.
Network-Biased Technical Change: How Modern Digital Collaboration Tools Overcome Some Biases but Exacerbate Others
Lynn Wu & Gerald Kane
Organization Science, forthcoming
Abstract:
Using three years' data from more than 1,000 employees at a large professional services firm, we find that adopting an expertise search tool improves employee work performance in billable revenue, which results from improvements in network connections and information diversity. More importantly, we also find that adoption does not benefit all employees equally. Two types of employees benefit more from adoption of digital collaboration tools than others. First, junior employees and women benefit more from the adoption of digital collaboration tools than do senior employees and men, respectively. These tools help employees overcome the institutional barriers to resource access faced by these employees in their searches for expertise. Second, employees with greater social capital at the time of adoption also benefit more than others. The tools eliminate natural barriers associated with traditional offline interpersonal networks, enabling employees to network even more strategically than before. We explore the mechanisms for these differential benefits. Digital collaboration tools increase the volume of communication more for junior employees and women, indicating greater access to knowledge and expertise than they had before adoption. The tools also decrease the volume of communication for people with greater social capital, indicating more efficient access to knowledge and expertise. An important implication of our findings is that digital collaboration tools have the potential to overcome some of the demographic institutional biases that organizations have long sought to change. It does so, however, at the expense of potentially creating new biases toward network-based features - a characteristic we call "network-biased technical change."
The liking gap in groups and teams
Adam Mastroianni et al.
Organizational Behavior and Human Decision Processes, January 2021, Pages 109-122
Abstract:
Every relationship begins with a conversation. Past research suggests that after initial conversations, there exists a liking gap: people underestimate how much their partners like them. We extend this finding by providing evidence that it arises in conversations among small groups (Study 1), continues to exist in engineering teams working on a project together (Study 2), and is linked to important consequences for teams' ability to work together in a sample of working adults (Study 3). Additional evidence suggests that the liking gap is largest for peer relationships and that it is determined in part by the extent to which people focus on negative aspects of the impressions they make on others. Group conversations and team interactions often leave people feeling uncertain about where they stand with others, but our studies suggest that people are liked more than they know.
Super Mario Meets AI: The Effects of Automation on Team Performance and Coordination in a Videogame Experiment
Fabrizio Dell'Acqua, Bruce Kogut & Patryk Perkowski
Columbia University Working Paper, January 2021
Abstract:
Recent advances in artificial intelligence (AI) have piqued interest in how these technological advances will transform jobs and labor markets. While prior work has focused on understanding the tasks where AI outperforms humans, we ask how the introduction of automated agents affects teams, their routines, and organizations. We randomize the introduction of automated agents and new hires into "experimental firms" engaging in a coordination-based game on the Nintendo Switch console. We demonstrate experimentally that even in a task where automated agents outperform humans, the introduction of an automated agent decreases team performance. These effects are especially large in the short-term and in low- and medium-skilled teams. We furthermore document that automation can generate adverse spillover effects into teams that do not receive an automated agent but must coordinate with it. Our results indicate that these effects are driven by an increase in coordination failures, and we provide suggestive evidence that automation reduces team trust and individual effort provision. Overall, our team-based approach highlights that human-machine interaction is key to expanding our understanding of how AI will transform teams, organizations, and work more broadly.
Lowering the Bar? External Conditions, Opportunity Costs, and High-Tech Start-Up Outcomes
Annamaria Conti & Maria Roche
Organization Science, forthcoming
Abstract:
We assess the heterogeneous impact of economic downturns on individuals' decisions to bring high-technology ideas to the market in the form of new ventures. We thereby examine how worsening labor market conditions influence individuals' opportunity costs of starting new ventures, the resulting composition of the entrepreneurial pool, and start-up performance outcomes. Using a rich data set of start-up founders in the biotechnology and medical device sectors, we find that an increase in the unemployment rate is associated with a substantial rise in the share of entrepreneurs who are most sensitive to worsening labor market conditions. Additionally, we find that start-ups founded by these entrepreneurs display lower financial and innovative performance than start-ups founded by entrepreneurs who are relatively insensitive to business cycles. Finally, we provide suggestive evidence that individuals' heterogeneous response to worsening labor market conditions is a relevant factor in explaining the negative relationship between unemployment and start-up performance outcomes.