Knowledge that Transforms

Contests are a historically important and increasingly popular mechanism for encouraging innovation. A central concern in designing innovation contests is how many competitors to admit. Using a unique data set of 9,661 software contests, we provide evidence of two coexisting and opposing forces that operate when the number of competitors increases. Greater rivalry reduces the incentives of all competitors in a contest to exert effort and make investments. At the same time, adding competitors increases the likelihood that at least one competitor will find an extreme-value solution. We show that the effort-reducing effect of greater rivalry dominates for less uncertain problems, whereas the effect on the extreme value prevails for more uncertain problems. Adding competitors thus systematically increases overall contest performance for high-uncertainty problems. We also find that higher uncertainty reduces the negative effect of added competitors on incentives. Thus, uncertainty and the nature of the problem should be explicitly considered in the design of innovation tournaments. We explore the implications of our findings for the theory and practice of innovation contests.

Commerce depends on buyers and sellers fulfilling their contractual obligations; mechanisms inducing such performance are essential to well-functioning markets. Internet-enabled reputation mechanisms that collect and disseminate consumer feedback have emerged as prominent means for inducing seller performance in online and offline markets. This paper compares the ability of reputation and more traditional litigation-like mechanisms for dispute resolution to induce efficient economic outcomes. We use a game-theoretic formulation and derive results for their relative efficiency and effectiveness individually or as complements. We find that the popular view of reputation as an efficient and relatively costless way to induce seller effort under all circumstances is incorrect; reputation is less efficient than litigation in inducing any given level of effort. Thus, reputation improves efficiency only in settings where the high cost of litigation, insufficient damage levels, or low court accuracy induce suboptimal effort or cause market failure. When adverse selection is important, reputation helps reveal the true types of market participants, which may offset its higher cost of inducing effort. Finally, adding reputation to existing litigation mechanisms increases seller effort and may require adjusting damage awards to avoid inducing excessive effort that reduces economic efficiency.

This paper analyzes the optimal procurement, processing, and production decisions of a meat-processing company (hereafter, a “packer”) in a beef supply chain. The packer processes fed cattle to produce two beef products, program (premium) boxed beef and commodity boxed beef, in fixed proportions, but with downward substitution of the premium product for the commodity product. The packer can source input (fed cattle) from a contract market, where long-term contracts are signed in advance of the required delivery time, and from a spot market on the spot day. Contract prices are taken to be of a general window form, linear in the spot price but capped by upper and lower limits on realized contract price. Our analysis provides managerial insights on the interaction of window contract terms with processing options. We show that the packer benefits from a low correlation between the spot price and product market uncertainties, and this is independent of the form of the window contract. Although the expected revenues from processing increase in spot price variability, the overall impact on profitability depends on the parameters of the window contract. Using a calibration based on the report by the GIPSA (Grain Inspection, Packers and Stockyards Administration. 2007. GIPSA livestock and meat marketing study, vol. 3: Fed cattle and beef industries. Report, U.S. Department of Agriculture, Washington, DC), this paper elucidates for the first time the value of long-term contracting as a complement to spot sourcing in the beef supply chain. Our comparative statics results provide some rules of thumb for the packer for the strategic management of the procurement portfolio. In particular, we show that higher variability (higher spot price variability, product market variability, and correlation) increases the profits of the packer, but decreases the reliance on the contract market relative to the spot market.

Provision of real-time information by a firm to its customers has become prevalent in recent years in both the service and retail sectors. In this paper, we study a retail operations model where customers are strategic in both their actions and in the way they interpret information, whereas the retailer is strategic in the way it provides information. This paper focuses on the ability (or the lack thereof) to communicate unverifiable information and influence customers' actions. We develop a game-theoretic framework to study this type of communication and discuss the equilibrium language emerging between the retailer and its customers. We show that for a single retailer and homogeneous customer population setting, the equilibrium language that emerges carries no information. In this sense, a single retailer providing information on its own cannot create any credibility with the customers. We study how the results are impacted due to the heterogeneity of the customers. We provide conditions under which the firm may be able to influence the customer behavior. In particular, we show that the customers' willingness to pay and willingness to wait cannot be ranked in an opposite manner. However, even when the firm can influence each customer class separately, the effective demand is not impacted.

Multiservice providers, such as telecommunication and financial service companies, can benefit from understanding how customers' service portfolios evolve over the course of their relationships. This can provide guidance for managerial issues such as customer valuation and predicting customers' future behavior, whether it is acquiring additional services, selectively dropping current services, or ending the relationship entirely. In this research, we develop a dynamic hidden Markov model to identify latent states that govern customers' affinity for the available services through which customers evolve. In addition, we incorporate and demonstrate the importance of separating two other sources of dynamics: portfolio inertia and service stickiness. We then examine the relationship between state membership and managerially relevant metrics, including customers' propensities for acquiring additional services or terminating the relationship, and customer lifetime value. Through a series of illustrative vignettes, we show that customers who have discarded a particular service may have an increased risk of canceling all services in the near future (as intuition would suggest) but also may be more prone to acquire more services, a provocative finding of interest to service providers. Our findings also emphasize the need to look beyond the previous period, as in much current research, and consider how customers have evolved over their entire relationship in order to predict their future actions.

We develop comparative results for ratio-based efficiency analysis (REA) based on the decision-making units' (DMUs') relative efficiencies over sets of feasible weights that characterize preferences for input and output variables. Specifically, we determine (i) ranking intervals, which indicate the best and worst efficiency rankings that a DMU can attain relative to other DMUs; (ii) dominance relations, which show what other DMUs a given DMU dominates in pairwise efficiency comparisons; and (iii) efficiency bounds, which show how much more efficient a given DMU can be relative to some other DMU or a subset of other DMUs. Unlike conventional efficiency scores, these results are insensitive to outlier DMUs. They also show how the DMUs' efficiency ratios relate to each other for all feasible weights, rather than for those weights only for which the data envelopment analysis (DEA) efficiency score of some DMU is maximized. We illustrate the usefulness of these results by revisiting reported DEA studies and by describing a recent case study on the efficiency comparison of university departments.

Companies and managers are apt to forget information, yet classic game theory analysis assumes that all players have perfect recall. This paper expands the literature by examining how introducing forgetfulness into a multiplayer game-theoretic framework can help or hinder cooperative behavior. We find that forgetfulness impacts the ability of firms to cooperate in countervailing directions. On one hand, forgetfulness can diminish the ability to punish deviators, making cooperation more difficult. On the other hand, under some conditions forgetfulness can make meting out severe punishments—even below-(stage) minimax punishments—credible and decrease the ability for players to effectively deviate, facilitating cooperation even in circumstances where cooperation cannot be sustained under perfect recall. We apply our model to a number of strategic games that commonly appear in the literature.

A common approach to innovation, parallel search, is to identify a large number of opportunities and then to select a subset for further development, with just a few coming to fruition. One potential weakness with parallel search is that it permits repetition. The same, or a similar, idea might be generated multiple times, because parallel exploration processes typically operate without information about the ideas that have already been identified. In this paper we analyze repetition in five data sets comprising 1,368 opportunities and use that analysis to address three questions: (1) When a large number of efforts to generate ideas are conducted in parallel, how likely are the resulting ideas to be redundant? (2) How large are the opportunity spaces? (3) Are the unique ideas more valuable than those similar to many others? The answer to the first question is that although there is clearly some redundancy in the ideas generated by aggregating parallel efforts, this redundancy is quite small in absolute terms in our data, even for a narrowly defined domain. For the second question, we propose a method to extrapolate how many unique ideas would result from an unbounded effort by an unlimited number of comparable idea generators. Applying that method, and for the settings we study, the estimated total number of unique ideas is about one thousand for the most narrowly defined domain and greater than two thousand for the more broadly defined domains. On the third question, we find a positive relationship between the number of similar ideas and idea value: the ideas that are least similar to others are not generally the most valuable ones.

A service plan is a type of optional warranty beyond manufacturers' base warranties that retailers offer to consumers. In this paper, we examine how a service plan affects the role played by a manufacturer's base warranty. Analysis shows that when consumers can assess product quality (i.e., the probability of product failure), the manufacturer's warranty is negatively affected by the presence of a service plan. In the presence of such a plan, a base warranty is offered only when the manufacturer is very cost-efficient in providing a warranty relative to the retailer. In this case, although the double-marginalization problem is aggravated, offering a (limited) base warranty reduces the total warranty cost in the channel and provokes the retailer into enlarging the service plan coverage. When consumers cannot assess product quality, a high-quality manufacturer is motivated to offer a base warranty to signal its quality. In the presence of a service plan, however, a very cost-efficient manufacturer is discouraged from doing so.

This paper develops dynamic measures of the systemic risk of the financial sector as a whole. It defines systemic risk as the conditional probability of failure of a sufficiently large fraction of the total population of financial institutions. This definition recognizes that the cause of systemic distress is the correlated failure of institutions to meet obligations to creditors, customers, and trading partners. The likelihood estimators of the failure probability are based on a dynamic hazard model of correlated failure timing that captures the influence on failure timing of time-varying macroeconomic and sector-specific risk factors, and of spillover effects. Tests indicate that our measures provide accurate out-of-sample forecasts of the term structure of systemic risk in the United States for the period from 1998 to 2009.