Prizes In Contests Research Articles

Intermediate prizes in multi-dimensional contests

Intermediate prizes in multi-dimensional contests

Competition and Collaboration in Crowdsourcing Communities: What Happens When Peers Evaluate Each Other?

Crowdsourcing has evolved as an organizational approach to distributed problem solving and innovation. As contests are embedded in online communities and evaluation rights are assigned to the crowd, community members face a tension: They find themselves exposed to both competitive motives to win the contest prize and collaborative participation motives in the community. The competitive motive suggests they may evaluate rivals strategically according to their self-interest, the collaborative motive suggests they may evaluate their peers truthfully according to mutual interest. Using field data from Threadless on 38 million peer evaluations of more than 150,000 submissions across 75,000 individuals over 10 years and two natural experiments to rule out alternative explanations, we answer the question of how community members resolve this tension. We show that as their skill level increases, they become increasingly competitive and shift from using self-promotion to sabotaging their closest competitors. However, we also find signs of collaborative behavior when high-skilled members show leniency toward those community members who do not directly threaten their chance of winning. We explain how the individual-level use of strategic evaluations translates into important organizational-level outcomes by affecting the community structure through individuals’ long-term participation. Although low-skill targets of sabotage are less likely to participate in future contests, high-skill targets are more likely. This suggests a feedback loop between competitive evaluation behavior and future participation. These findings have important implications for the literature on crowdsourcing design, and the evolution and sustainability of crowdsourcing communities. Funding: This work was supported by the National Science Foundation [Grant IIS-1514283] and the U.S. Office of Naval Research [Grant N00014-17-1-2542]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.15163 .

Allocation rules of indivisible prizes in team contests

Allocation rules of indivisible prizes in team contests

Allocation Rules of Indivisible Prizes in Team Contests

Allocation Rules of Indivisible Prizes in Team Contests

Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents

Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents

Fatter or fitter? On rewarding and training in a contest

AbstractCompetition between heterogeneous participants leads to low‐effort provision in contests. A principal can divide her fixed budget between skill‐enhancing training and the contest prize. Training can reduce heterogeneity, increasing effort. It also reduces the contest prize, making effort fall. We set up an incomplete‐information contest with heterogeneous players and show how this trade‐off is related to the size of the budget of an effort‐maximizing principal. A selection problem arises implying a cost associated with a win by the inferior player. The principal has a larger incentive to train the laggard, reducing the prize on offer.

Winning by Learning? Effect of Knowledge Sharing in Crowdsourcing Contests

Crowdsourcing is a new way for online crowds to get involved in a company’s research and development process. Businesses can host public contests on online platforms (such as Kaggle, Topcoder, and Tongal) to seek new product ideas and technological solutions. In the contest communities, members usually have a “coopetitive” relationship: they compete against each other for the contest prize, while at the same time also cooperate with each other by sharing information and knowledge. This work investigates the effect of knowledge sharing in such crowdsourcing contests. Surprisingly, we find that the knowledge sharing process may not always help improve crowdsourcing contestants’ performance. The effectiveness of knowledge sharing is influenced by the volume, quality, and generativity of shared knowledge. Shared knowledge is only beneficial when it is of high quality or when it has high potential of being further developed collectively by the community. Meanwhile, the development process has to be diverging; narrowing the development process in one direction can restrict the community creativity and negatively influence crowdsourcing performance. Our work informs the crowdsourcing practitioners to be more cautious when they enable collaboration such as knowledge sharing for the contest community.

Attracting High‐Quality Contestants to Contest in the Context of Crowdsourcing Contest Platform

Contests have long existed to source ideas and solutions. The emergence of crowdsourcing contest platforms greatly reduces the costs and broadens the reach of running contests by facilitating access to a large pool of labor, making contests a cost‐efficient approach to procure ideas/solutions even for employers of limited resources. As a result, the use of contests surges and there is a flux of small‐to‐medium size contests to these platforms. This study focuses on these new waves of small‐to‐medium‐size contests on crowdsourcing contest platforms and extends the literature in several ways: First, prior literature focuses extensively on contest prize, we also consider the effect of contest duration, which plays salient role on contest platforms. Our findings provide evidence that contest duration affects both the number and the quality of contestants attracted to a contest. Second, prior literature assumes contests exist independently and that the quality distribution of contestants is exogenous; accordingly, the number of contestants can be regarded as a proxy of contest performance. We show that contest design parameters have direct effects on the quality distribution of contestants. Specifically, increasing contest duration, while attracting more contestants, results in a downward shift on the quality distribution of the contestants attracted to the contest. Third, recognizing that each contest does not exist independently on crowdsourcing contest platforms, we also incorporate the number of competing contests in our model. Our results provide practical recommendations on how to set up successful contests and attract high‐quality contestants to a contest on a crowdsourcing contest platform.

The optimal allocation of prizes in two-stage contests

We study two-stage contests in which the designer can award a prize for winning in each stage, and also a prize for winning in both stages. For this purpose, we analyze the optimal allocation of prizes for a designer who wishes to maximize the players’ total effort when the matches in each stage are modeled as Tullock contests. It is demonstrated that the prize for winning in both stages should be allocated in the two-stage Tullock contest with two players, but not when there are more than two players.

Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents

Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents

Never Too Late? The Role of Visiting Delay in Crowdsourcing Contests

This paper studies the role of visiting delay in crowdsourcing contests – the time elapsed between the start of a contest and a solver’s first visit to the contest. Because crowdsourcing platforms often host multiple contests parallelly, solvers may not be aware of contests when they open for participation. This creates heterogeneity among solvers in terms of their visiting delay and awareness of contest details. We theorize that visiting delay may impact solvers’ submission behavior and performance through two countervailing forces: a deadline effect – an increased intention to participate induced by a tighter deadline, and a time-disadvantage effect – a decreased intention to participate due to the limited time available in the contest. Using a novel dataset from an established crowdsourcing platform, we show the heterogeneous effects of visiting delay on the submission behavior, namely, the time to first submission and the number of submissions, through various empirical analyses. We demonstrate that when solvers have higher levels of visiting delay, the deadline effect dominates the time-disadvantage effect, resulting in a faster submission time initially. However, after the first submission, the time-disadvantage effect dominates the deadline effect, resulting in fewer and slower submissions. Additionally, the deadline (time-disadvantage) effect is amplified (attenuated) by the average contest prize amount in a non-linear manner. Finally, we show that these dynamics affect the solvers’ likelihood of developing an acceptable submission and a winning submission. Our results provide implications for seekers and platform designers in scheduling contests and in designing incentives for managing the effects of visiting delay.

Prizes in Contests with Many Entrants

We examine the properties of all-pay contests in the spirit of Moldovanu and Sela (2001) as the number of entrants grows large under organizer objectives of expected and expected maximum outcomes. Unlike the case with a small number of entrants, with a large number of entrants a single prize becomes optimal even for an organizer with concave utility. Diminishing returns or risk-aversion on the part of the organizer do not justify multiple prizes in large contests. With optimal prizes determined asymptotically, we characterize the limiting value of outcomes in an optimal contest; exactly in the case of linear production and up to bounds in the concave/convex case. In all cases the limiting value is bounded away from zero. In the linear case, the limit is one-half the maximum feasible outcome.

Fatter or Fitter? On rewarding and training in a contest

Competition between heterogeneous participants often leads to low effort provision in contests. We consider a principal who can divide her fixed budget between skill-enhancing training and the contest prize. Training can reduce heterogeneity, which increases effort. But it also reduces the contest prize, which makes effort fall. We set up an incomplete-information contest with heterogeneous players and show how this trade-off is related to the size of the budget when the principal maximizes expected effort. A selection problem can also arise in this framework in which there is a cost associated with a contest win by the inferior player. This gives the principal a larger incentive to train the expected laggard, reducing the size of the prize on offer.

Fatter or Fitter? On rewarding and training in a contest

Competition between heterogeneous participants often leads to low effort provision in contests. We consider a principal who can divide her fixed budget between skill-enhancing training and the contest prize. Training can reduce heterogeneity, which increases effort. But it also reduces the contest prize, which makes effort fall. We set up an incomplete-information contest with heterogeneous players and show how this trade-off is related to the size of the budget when the principal maximizes expected effort. A selection problem can also arise in this framework in which there is a cost associated with a contest win by the inferior player. This gives the principal a larger incentive to train the expected laggard, reducing the size of the prize on offer.

The optimal allocation of prizes in contests with costly entry

Contestants often need to incur an opportunity cost to participate in the competition. In this paper, we accommodate costly entry and study the effort-maximizing prize allocation rule in a contest environment of all-pay auction with incomplete information as in Moldovanu and Sela (2001). As equilibrium entry can be stochastic, our analysis allows prize allocation rule to be contingent on the number of entrants. With free entry, Moldovanu and Sela establish the optimality of winner-take-all when effort cost function is linear or concave. Costly entry introduces a new trade-off between eliciting effort from entrants and encouraging entry of contestants, which might demand a more lenient optimal prize allocation rule. Surprisingly, we find that the optimality of winner-take-all is robust to costly entry when cost function is linear or concave. On the other hand, we provide examples to show that the new trade-off due to costly entry does make a difference to the optimal design when effort cost function is convex.

Discouragement effect and intermediate prizes in multi-stage contests: Evidence from Davis Cup

The discouragement effect of being the lagging player in multi-stage contests is a well-documented phenomenon. In this study, we utilize data from 2447 Davis Cup matches in team tennis tournaments to test the effect of being behind or ahead on individuals’ performance with and without intermediate prizes. Using several different strategies to disentangle the effect of being ahead in the interim score from the effect of selection, we find the usual discouragement effect. However, the discouragement effect disappears after the introduction of intermediate prizes in the form of ranking points. The lagging favorite had close to a 20-percentage point greater probability of winning compared to matches without such a prize. We show that this result is not driven by the selection of better players into tournaments with intermediate prizes. As predicted by previous theoretical studies, our empirical findings suggest that intermediate prizes may mitigate or even eliminate the ahead–behind effects that arise in multi-stage contests.

The Optimal Allocation of Prizes in Contests with Costly Entry

Contestants often need to incur an opportunity cost to participate in the competition. In this paper, we accommodate costly entry and study the effort-maximizing prize allocation rule in a contest environment of all-pay auction with incomplete information as in Moldovanu and Sela (2001). As equilibrium entry can be stochastic, our analysis allows prize allocation rule to be contingent on the number of entrants. With free entry, Moldovanu and Sela establish the optimality of winner-take-all when effort cost function is linear or concave. Costly entry introduces a new trade-off between eliciting effort from entrants and encouraging entry of contestants, which might demand a more lenient optimal prize allocation rule. Surprisingly, we find that the optimality of winner-take-all is robust to costly entry when cost function is linear or concave. On the other hand, we provide examples to show that the new trade-off due to costly entry does make a difference to the optimal design when effort cost function is convex.

Stag hunt contests and alliance formation

We consider a three-party game of conflict with potential alliance formation, introducing the concept of a stag hunt alliance and using the concept as a novel solution to the alliance formation puzzle in contests. In a stag hunt alliance, allied inputs interact as (multiplicative) complements in the contest success function, reflecting the idea that allied efforts are coordinated and targeted against non-allies. Allowing for asymmetry among conflicting parties, we find conditions for stable alliance formation and show that, in some circumstances, the formation of an alliance can improve the expected payoffs of both the allied and unallied parties relative to unallied conflict. At the same time, the expected payoffs of allied parties also can be greater than their payoffs under a three-party exogenous settlement division without conflict. Hence, the ability to form stag hunt alliances may not simply change conflict structures, but may sometimes generate conflict when settlements are possible. Our results depend on how allies divide the contest prize in the event of victory, and we consider both the case of exogenous division according to a pre-specified rule and endogenous division in a second-stage intra-alliance contest. We also show that the threat of the latter can be used to establish an intuitive exogenous rule by simple bargaining. Finally, we specify conditions that determine which parties choose to ally with one another.

The role of noise in alliance formation and collusion in conflicts

Many real-world conflicts are to some extent determined randomly by noise. The way in which noise is modeled in contest success functions (CSFs) has has important implications both for the possibility of forming cooperative relationships as well as for the features of such relationships. In a one-shot conflict, we find that when noise is modeled as an exponential parameter in the CSF, there is a range of values for which an alliance between two parties can be beneficial, whereas that is not the case for an additive noise parameter. In an infinitely repeated conflict setting with additive noise, sustaining collusion via Nash reversion strategies is easier the more noise there is and more difficult the larger the contest's prize value, while an increase in the contest's number of players can make sustaining collusion either more or less difficult, all in marked contrast to the case of an exponential noise parameter. Which noise specification is appropriate is therefore an important consideration for modeling any conflict situation.

Selecting contestants for a rent-seeking contest

In this paper, a contest designer derives profits from aggregate effort exerted by the contestants. I develop a revelation mechanism that enables the contest designer to select a subset of contestants from a pool of candidates in a way that maximizes her profits, even though she is uninformed about the candidates’ valuations for the contest prize. I prove the existence of an incentive compatible and individually rational mechanism. I solve the designer’s problem by using a three-stage game. At Stage 0, the designer designs a mechanism. At Stage 1, candidates participate in the mechanism then a subset of candidates become contestants. Lastly, at Stage 2, information is revealed and the contestants participate in a contest. I show that the optimal size of a contest depends on contestants’ types, the cost of the prize to the designer and on the marginal cost that a contestant imposes on the designer. Contrary to models in which an entry fee s access to the contest, the designer can elicit truthful revelations by imposing revelation costs, and in turn is able to select the optimal subset of contestants.