Team Contest Research Articles

Winner's effort in multi-battle team contests

In multi-battle team contests with pairwise battles, how battles are organized—sequentially or (partially) simultaneously—may affect the expected winner's total effort (WE), a natural objective in R&D races, elections, and sports. We focus on noise (modeled via the contest success function's discriminatory power) and across-team heterogeneity, abstracting from player-specific heterogeneity. With sufficient noise, we show that: (1) If teams are symmetric, all temporal structures yield the same WE; and (2) If teams are asymmetric, WE is maximized by a fully simultaneous contest and minimized by a fully sequential one. With no noise, we show that: (3) If teams are symmetric, WE is maximized by a fully sequential contest and minimized by a fully simultaneous one; and (4) If teams are asymmetric, neither the fully sequential nor the fully simultaneous temporal structures maximize or minimize WE. Our results use a novel technique that simplifies temporal structure comparisons: extractions and mergers.

Prize-allocation rules in generalized team contests

Prize-allocation rules in generalized team contests

The best at the top? Candidate ranking strategies under closed list proportional representation

Abstract Under closed-list proportional representation, a party's electoral list determines the order in which legislative seats are allocated to candidates. When candidates differ in their ability, parties face a trade-off between competence and incentives. Ranking candidates in decreasing order of competence ensures that elected politicians are most competent. Yet, party lists create incentives for candidates that may lead parties not to place their best candidates at the top of the list. We examine this trade-off in a game-theoretical model in which parties rank their candidates on a list, candidates choose their campaign effort, and the election is a team contest for multiple prizes. We analyze how the candidates’ objectives, voters’ attention and media coverage, incumbency, the number of parties competing in the election, and the electoral environment influence how parties rank candidates.

Positive and Negative Sorting in Team Contests*

This paper investigates the formation of teams in a contest. A manager sorts four workers—who differ in their productivity—into two teams. Workers on each team join forces to produce team output, and one team wins a prize; for example, a bonus package. Two sorting patterns are possible: Positive sorting requires that each team consist of players of same caliber and negative sorting the opposite. We characterize the optimum. We further extend the model to allow the manager to set a prize schedule for the workers on each team upon a win, allocate productive resources between teams, and pick the level of competition of the contest.

Alliance Formation in Team Contests with Imperfectly Discriminatory Elimination

Alliance Formation in Team Contests with Imperfectly Discriminatory Elimination

Optimal prize design in team contests with pairwise battles

This paper studies the effort-maximizing design of a team contest with an arbitrary number (odd or even) of pairwise battles. In a setting with full heterogeneity across players and battles, the organizer determines the prize allocation rule (or the winning rule of an indivisible prize) contingent on battle outcomes. We propose a measure of team's strength, which plays a crucial role in prize design. The optimal design is a majority-score rule with a headstart score granted to the weaker team: All battles are assigned team-invariant scores, the weaker team is given an initial headstart score which is the difference in strengths between teams, and the team collecting higher total scores from its winning battles wins the entire prize. The optimal rule resembles the widely-adopted Elo rating system.

Allocation rules of indivisible prizes in team contests

Allocation rules of indivisible prizes in team contests

The older the wiser? Determinants of misbehavior in team contests

AbstractObjectiveWe empirically investigate age and ability as potentially important drivers of individual misconduct in team contests.MethodsWe estimate fixed effects regression models using data from top‐level soccer. In addition, we carry out a comprehensive sensitivity analysis.ResultsOur estimates indicate a significant positive association between a player's age, on the one hand, and his (relative) ability, on the other, with the propensity to misbehave.ConclusionOur results are consistent with social learning theory, in the sense that the high‐status group of players may have learned that the consequences of misbehavior are small and manageable. Furthermore, we demonstrate that misbehavior is costly to both the players and their teams.

Dynamic team contests with complementary efforts

Dynamic team contests with complementary efforts

The Dual Effects of Team Contest Design on On-Demand Service Work Schedules

Emerging on-demand service platforms (OSPs) have recently embraced teamwork as a strategy for stimulating workers’ productivity and mediating temporal supply and demand imbalances. This research investigates the team contest scheme design problem considering work schedules. Introducing teams on OSPs creates a hierarchical single-leader multi-follower game. The leader (platform) establishes rewards and intrateam revenue-sharing rules for distributing workers’ payoffs. Each follower (team) competes with others by coordinating the schedules of its team members to maximize the total expected utility. The concurrence of interteam competition and intrateam coordination causes dual effects, which are captured by an equilibrium analysis of the followers’ game. To align the platform’s interest with workers’ heterogeneous working-time preferences, we propose a profit-maximizing contest scheme consisting of a winner’s reward and time-varying payments. A novel algorithm that combines Bayesian optimization, duality, and a penalty method solves the optimal scheme in the nonconvex equilibrium-constrained problem. Our results indicate that teamwork is a useful strategy with limitations. Under the proposed scheme, team contest always benefits workers. Intrateam coordination helps teams strategically mitigate the negative externalities caused by overcompetition among workers. For the platform, the optimal scheme can direct teams’ schedules toward more profitable market equilibria when workers have inaccurate perceptions of the market. History: This paper has been accepted for the Service Science Special Issue on Innovation in Transportation-Enabled Urban Services. Funding: This work was supported by the National Science Foundation [Grant FW-HTF-P 2222806]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/serv.2023.0320 .

Putting Teams into the Gig Economy: A Field Experiment at a Ride-Sharing Platform

The gig economy provides workers with the benefits of autonomy and flexibility but at the expense of work identity and coworker bonds. Among the many reasons why gig workers leave their platforms, one unexplored aspect is the lack of an organization identity. In this study, we develop a team formation and interteam contest field experiment at a ride-sharing platform. We assign drivers to teams either randomly or based on similarity in age, hometown location, or productivity. Having these teams compete for cash prizes, we find that (1) compared with those in the control condition, treated drivers work longer hours and earn 12% higher revenue during the contest; (2) the treatment effect persists two weeks postcontest, albeit with half of the effect size; and (3) drivers in hometown-similar teams are more likely to communicate with each other, whereas those in age-similar teams continue to work longer hours and earn higher revenue during the two weeks after the contest ends. Together, our results show that platform designers can leverage team identity and team contests to increase revenue and worker engagement in a gig economy.This paper was accepted by David Simchi-Levi, behavioral economics and decision analysis.Funding: Financial support from the platform through the Michigan Institute for Data Science is gratefully acknowledged.Supplemental Material: The e-companion are data are available at https://doi.org/10.1287/mnsc.2022.4624 .

Effort and risk-taking in tournaments with superstars – evidence for teams

ABSTRACT Competition is often observed between heterogenous teams. Heterogeneity in ability is critical for the effectiveness of different tournament designs. I investigate how the presence of a dominant competitor or superstar does affect the decisions of other competitors in team contests. In particular, I use novel data from top-level professional basketball to investigate the consequences of superstar presence on effort and risk-taking of teams in rank-order contests. To identify the effect, I exploit exogenous variation in superstar dominance, induced by an institutional reform. My results demonstrate that the effect of competing with a superstar on effort does depend on the level of superstar dominance and the number of dominant teams in the contest. For tournaments with a single and clearly dominant superstar team, I find a sizable and significant negative effect of superstar presence on effort of other competing teams. Reduced dominance by the superstar, however, is found to result in a positive peer effect. I also present results for a robust association between competing with a superstar and risk-taking, indicating that a dominant superstar decreases risk-taking. Presence of a weak superstar, however, is estimated to increase risk-taking among other competitors.

Dynamic Resource Allocation in Team Contests with Imperfectly Discriminatory Elimination (Appendix)

Dynamic Resource Allocation in Team Contests with Imperfectly Discriminatory Elimination (Appendix)

Allocation Rules of Indivisible Prizes in Team Contests

Allocation Rules of Indivisible Prizes in Team Contests

Optimal Biased Design of Dynamic Multi-Battle Team Contests

Optimal Biased Design of Dynamic Multi-Battle Team Contests

Virtual teams in a gig economy

While the gig economy provides flexible jobs for millions of workers globally, a lack of organization identity and coworker bonds contributes to their low engagement and high attrition rates. To test the impact of virtual teams on worker productivity and retention, we conduct a field experiment with 27,790 drivers on a ride-sharing platform. We organize drivers into teams that are randomly assigned to receiving their team ranking, or individual ranking within their team, or individual performance information (control). We find that treated drivers work longer hours and generate significantly higher revenue. Furthermore, drivers in the team-ranking treatment continue to be more engaged 3 mo after the end of the experiment. A machine-learning analysis of 149 team contests in 86 cities suggests that social comparison, driver experience, and within-team similarity are the key predictors of the virtual team efficacy.

Equilibrium player choices in team contests with multiple pairwise battles

We consider games in which team leaders strategically choose the order of players sent to the battlefield in majoritarian team contests with multiple pairwise battles as in Fu et al. (2015). We consider one-shot order-choice games and battle-by-battle sequential player choice games. We show that as long as the number of players on each team is the same as the number of battles, the equilibrium winning probability of a team and the ex ante expected effort of each player in a multi-battle contest are independent of whether players' assignments are one-shot or battle-by-battle sequential. This equilibrium winning probability and ex ante expected total effort coincide with those where the player matching is chosen totally randomly with an equal probability lottery by the contest organizer. Finally, we show how player choices add subtleties to the equivalence result by examples.

Dynamic Resource Allocation in Team Contests with Imperfectly Discriminatory Elimination

Dynamic Resource Allocation in Team Contests with Imperfectly Discriminatory Elimination

The Older the Wiser? Determinants of Misbehaviour in Team Contests

The Older the Wiser? Determinants of Misbehaviour in Team Contests

Designing practical and fair sequential team contests: The case of penalty shootouts

Economists have long recognized that the effect of move order on outcomes is non-negligible in sequential contests. We study tiebreak mechanisms used in team sports and known as penalty shootouts through a dynamic model. We characterize all order-independent mechanisms where two balanced teams have equal chances to win the shootout whenever they are tied after equal numbers of attempts; thus, move order has no relevance for winning chances. In most sports, such as football and hockey, teams take penalties in a fixed order, known as ABAB, while some tournaments adopted the alternating-order variant, ABBA. We find that these and all other exogenous-order mechanisms – with one exception – are order-dependent in regular rounds. Although ABBA is order independent in sudden-death rounds, ABAB is not. Our theory supports empirical studies linking ABAB to unfair outcomes and multiple equilibria in terms of winning chances of the first- vs. second-kicking teams in different football traditions.