Sanjiv Erat

White Lies

In this paper we distinguish between two types of white lies: those that help others at the expense of the person telling the lie, which we term altruistic white lies, and those that help both others and the liar, which we term Pareto white lies. We find that a large fraction of participants are reluctant to tell even a Pareto white lie, demonstrating a pure lie aversion independent of any social preferences for outcomes. In contrast, a nonnegligible fraction of participants are willing to tell an altruistic white lie that hurts them a bit but significantly helps others. Comparing white lies to those where lying increases the liars payoff at the expense of another reveals important insights into the interaction of incentives, lying aversion, and preferences for payoff distributions. Finally, in line with previous findings, women are less likely to lie when it is costly to the other side. Interestingly though, we find that women are more likely to tell an altruistic lie. This paper was accepted by Teck Ho, decision analysis.

Managing Delegated Search Over Design Spaces

Organizations increasingly seek solutions to their open-ended design problems by employing a contest approach in which search over a solution space is delegated to outside agents. We study this new class of problems, which are costly to specify, pose credibility issues for the focal firm, and require finely tuned awards for meeting the firms needs. Through an analytical model, we examine the relationship between problem specification, award structure, and breadth of solution space searched by outside agents toward characterizing how a firm should effectively manage such open-ended design contests. Our results independently establish and offer a causal explanation for an interesting phenomenon observed in design contests---clustering of searchers in specific regions of the solution space. The analysis also yields a cautionary finding---although the breadth of search increases with number of searchers, the relationship is strongly sublinear (logarithmic). Finally, from the practical perspective of managing the delegated search process, our results offer rules of thumb on how many and what size awards should be offered, as well as the extent to which firms should undertake problem specification, contingent on the nature (open-endedness and uncertainty) of the design problem solution being delegated to outside agents. This paper was accepted by Kamalini Ramdas, entrepreneurship and innovation.

Introduction of New Technologies to Competing Industrial Customers

Motivated by several examples from industry, such as the introduction of a biotechnology-based process innovation in nylon manufacturing, we consider a technology provider that develops and introduces innovations to a market of industrial customers---original equipment manufacturers (OEMs). The technology employed by these OEMs determines the performance quality of the end product they manufacture, which in turn forms the basis of competition among them. Within this context of downstream competition, we examine the technology providers introduction strategies when improving technologies are introduced sequentially. We develop a two-period game-theoretic framework to account for the strategic considerations of the parties involved (i.e., the technology provider and the OEMs). Our main result indicates that the technology provider may find it beneficial to induce partial adoption of the new technology, depending on the technological progress the provider intends to offer in the future. We analyze many technology-specific and market-related characteristics---such as volume-based pricing for new component technologies, upgrade prices, and OEMs with differing capabilities---that correspond to various business settings. Our key result (i.e., partial adoption) proves to be a robust phenomenon. We also develop additional insights regarding the interactions between adoption and OEM capabilities.

Sequential Testing of Product Designs: Implications for Learning

Past research in new product development (NPD) has conceptualized prototyping as a “design-build-test-analyze” cycle to emphasize the importance of the analysis of test results in guiding the decisions made during the experimentation process. New product designs often involve complex architectures and incorporate numerous components, and this makes the ex ante assessment of their performance difficult. Still, design teams often learn from test outcomes during iterative test cycles enabling them to infer valuable information about the performances of (as yet) untested designs. We conceptualize the extent of useful learning from analysis of a test outcome as depending on two key structural characteristics of the design space, namely whether the set of designs are “close” to each other (i.e., the designs are similar on an attribute level) and whether the design attributes exhibit nontrivial interactions (i.e., the performance function is complex). This study explicitly considers the design space structure and the resulting correlations among design performances, and examines their implications for learning. We derive the optimal dynamic testing policy, and we analyze its qualitative properties. Our results suggest optimal continuation only when the previous test outcomes lie between two thresholds. Outcomes below the lower threshold indicate an overall low performing design space and, consequently, continued testing is suboptimal. Test outcomes above the upper threshold, on the other hand, merit termination because they signal to the design team that the likelihood of obtaining a design with a still higher performance (given the experimentation cost) is low. We find that accounting for the design space structure splits the experimentation process into two phases: the initial exploration phase, in which the design team focuses on obtaining information about the design space, and the subsequent exploitation phase in which the design team, given their understanding of the design space, focuses on obtaining a “good enough” configuration. Our analysis also provides useful contingency-based guidelines for managerial action as information gets revealed through the testing cycle. Finally, we extend the optimal policy to account for design spaces that contain distinct design subclasses.

Consumer Mental Accounts and Implications to Selling Base Products and Add-ons

Firms in a variety of industries offer add-on products to consumers who have previously purchased a base product. We posit that consumers, in making their decisions as to whether to purchase add-ons that complement the base products, find a greater need for the value offered by the add-ons when the “unrecovered” value (i.e., price paid minus the benefits obtained so far) associated with the base products is higher. We conduct experiments that test the proposed hypothesis and examine the strategic implications of such consumer decision making to a firm that sells base product add-on pairs. Consistent with our hypothesis, the experiments show that a consumers unrecovered value associated with the base product is positively correlated to his likelihood of purchasing the add-on. Formal modeling of this bias shows that firms may find penetration pricing strategies (such as loss leader pricing) suboptimal. Furthermore, the identified bias leads the firm to spend more resources toward enhancing both the base product and the add-on quality, especially so when the add-on will be offered before the consumer has a chance to extensively use the base product. Finally, the effect of competition in the base product market is also considered.

Making the Best Even Better: How Idea Pool Structure can make the Top Ideas Exceptional

In any pool of ideas, it is often the case that a small fraction of top ideas have significantly higher quality, both in absolute terms and relative to other ideas in the pool. This study formulates a model of idea pools, and examines the impact of the “structure” of idea pools on the extent to which the top ideas in an idea pool are exceptional. Our results demonstrate that the dispersion of ideas in the pool (defined in terms of the dissimilarity between ideas in the pool) has a positive impact on the value derived from the top ideas. The empirical content of the model is assessed by examining the citations received by top patents in a patent pool, and results consistent with the theoretical model are found. Finally, the study examines the optimal design of idea pools, and managerial rules-of-thumb are derived for the optimal choice of idea pool size, and the dispersion of ideas within the pool.

White lies

When do people tell white lies? In this paper we distinguish between two types of white lies: those that help others at the expense of the person telling the lie, which we term altruistic white lies, and those that help both others and the liar, which we term Pareto white lies. We find a large fraction of participants are reluctant to tell even a Pareto white lie, demonstrating a pure lie aversion independent of any social preferences for outcomes. In contrast, a non-negligible fraction of participants are willing to tell an altruistic white lie that hurts them a bit but significantly helps others. Comparing white lies to those where lying increases the liars payoff at the expense of another reveals important insights into the interaction of incentives, lying aversion, and social preferences for payoff distributions. Finally, in line with previous findings, women are less likely than men to lie when it is costly to the other side. Interestingly, we find that women are more likely to tell an altruistic lie, but tend to tell fewer Pareto lies.