Abstracts of current working papers


Whatever it takes: Rivalry and unethical behavior (with Gavin Kilduff,  Adam Galinsky and James J. Reade) - old version from 2012.

New version is conditionally accepted at the Academy of Management Journal.

Abstract.  This research investigates the link between rivalry and unethical behavior. We propose that people will engage in greater unethical behavior when competing against their rivals than when competing against non-rival competitors. Across a series of experiments and an archival study, we find that rivalry is associated with increased use of deception, unsportsmanlike behavior, willingness to employ unethical negotiation tactics, and misreporting of performance. We also explore the psychological underpinnings of rivalry, which help to illuminate how it differs from general competition, and why it increases unethical behavior. Rivalry as compared to non-rival competition was associated with increased status concerns, contingency of self-worth, and performance goals; mediation analyses revealed that performance goals played the biggest role in explaining why rivalry promoted greater unethicality. Lastly, we find that merely thinking about a rival can be enough to promote greater unethical behavior, even in domains unrelated to the rivalry. These findings highlight the importance of rivalry as a widespread, powerful, yet largely unstudied phenomenon with significant organizational implications. Further, the results help to inform when and why unethical behavior occurs within organizations, and demonstrate that the effects of competition are dependent upon relationships and prior interactions.


Networks in the laboratory (with Syngjoo Choi and Shachar Kariv)

This version: March 2015. Prepared for The Oxford Handbook on the Economics of Networks, edited by Y. Bramoulle, A. Galeotti, and B. Rogers, Oxford University Press.

Abstract. This chapter surveys experimental research on networks in economics. The first part considers experiments on games played on networks. Th
e second part discusses experimental research on markets and networks. It concludes by identifying important directions for future research.

Keywords: experiments, social networks, network games, markets, coordination, public goods, cooperation, social learning, communication, trading. JELC91, C92, D85, L14, Z13.



This version: January 2015.

Abstract. The tension between efficiency and equilibrium is a central feature of economic systems. In many contexts, social networks mediate this trade-off: an individual's network position determines equilibrium play, but at the same time social relations allow coordination on a more efficient norm of behavior. We examine this trade-off in a game of strategic complements played on different networks. The game has a unique interior Nash equilibrium, but subjects can achieve a higher payoff by following a "collaborative norm". In a simple and symmetric network, the circle, subjects are able to establish and maintain a collaborative norm. In a simple but asymmetric network, the wheel, the collaborative norm persists, but with play closer to equilibrium. In more complex and asymmetric networks of 15 and 21 nodes, the norm disappears and Nash point predictions exactly describe play on every node of both networks. We provide evidence that subjects base their decisions on their degree, rather than the overall network structure. Methodologically, the paper shows the capabilities of UbiquityLab: a novel platform to conduct interactive experiments online with a large number of participants.

Keywords: network, online experiment, network game, strategic complements. JEL: C99, D03, D85, Z13.


Network cognition (with Roberta Dessi and Sanjeev Goyal)

This version: July 2015.

Abstract. We study individual ability to memorize and recall information about friendship networks using a combination of experiments and survey-based data. In the experiment subjects are shown a network, in which their location is exogenously assigned, and they are then asked questions about the network after it disappears. We find that subjects exhibit three main cognitive biases: (i) they underestimate the mean degree compared to the actual network; (ii) they overestimate the number of rare degrees; (iii) they underestimate the number of frequent degrees. We then analyze survey data from two "real" friendship networks from a Silicon Valley firm and from a University Research Center. We find, somewhat remarkably, that individuals in these real networks also exhibit these biases. The experiments yield three further findings: (iv) network cognition is affected by the subject's location, (v) the accuracy of network cognition varies with the nature of the network, and (vi) network cognition has a significant effect on economic decisions.

Keywordsnetwork cognition, friendship networks, cognitive biases.



This version: July 2015.

Abstract. This paper proposes and tests experimentally a dynamic model of bargaining to analyze decentralized markets where buyers and sellers obtain information about past deals through their social network. There is a unique equilibrium outcome which depends crucially on the peripheral (least connected) individuals in each group. The main testable predictions are that groups with high density and/or low variability in the number of connections across individuals allow their members to obtain a better deal. These predictions are tested in a lab experiment through 4 treatments that vary the network that groups of 6 subjects are assigned to. The results of the experiment lend support to the theoretical predictions: subjects converge to a high equilibrium demand if they are assigned to a network that is dense and/or has low variability in number of connections across members. An extension explores an alternative set-up in which buyers and sellers belong to the same social network: if the network is regular and the agents are homogeneous then the unique equilibrium division is 50-50.

Keywords: experiment, network, communication, noncooperative bargaining, 50-50 division. JEL: C91, C92, D83, C73.