Knowledge that Transforms

To refine the understanding of the social network characteristics of entrepreneurial teams, we present a new construct: structural role complementarity. In particular, we examine the variation between team members’ respective abilities to act as network brokers. Based on the cofounding networks of 9,461 entrepreneurs and 2,446 large-scale industrial enterprises over 45 years in Russia’s emerging economy (1869–1913), our findings show that variation among team members’ brokering ability significantly predicts the starting capital raised by their firm. The effect is moderated by the team’s average brokering potential. When both the team’s average and variation in brokering potential is high, firms raise greater starting capital. By using multiple membership models, we demonstrate that greater starting capital is largely attributable to team factors rather than the attributes of the individual team members. We also take advantage of discriminatory laws that were passed in 1887 in an instrumental variable analysis to address potential endogeneity issues. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2874 .

We propose a spatial capital asset pricing model and a spatial arbitrage pricing theory (S-APT) that extend the classical asset pricing models by incorporating spatial interaction. We then apply the S-APT to study the comovements of eurozone stock indices (by extending the Fama–French factor model to regional stock indices) and the futures contracts on S&P/Case–Shiller Home Price Indices; in both cases, spatial interaction is significant and plays an important role in explaining cross-sectional correlation. The e-companion is available at https://doi.org/10.1287/mnsc.2016.2627 .

We investigate the impact of delay announcements on the coordination within hospital networks using a combination of empirical observations and numerical experiments. We show that patients take delay information into account when choosing emergency service providers and that such information can help increase coordination in the network, leading to improvements in performance of the network, as measured by Emergency Department wait times. Our numerical results indicate that the level of coordination that can be achieved is limited by the patients ’ sensitivity to waiting, the load of the system, the heterogeneity among hospitals, and, importantly, the method hospital use to estimate delays. We show that delay estimators that are based on historical average may cause oscillation in the system and lead to higher average waiting times when patients are sensitive to delay. We provide empirical evidence which suggests that such oscillations occurs in hospital networks in the US.

An individual’s tolerance of risk can be quantified by using decision models with tuned parameters that maximally fit a set of risky choices the individual has made. A goal of this model fitting procedure is to identify parameters that correspond to stable underlying risk preferences. These preferences can be modeled as an individual difference, indicating a particular decision maker’s tastes and willingness to accept risk. Using hierarchical statistical methods, we show significant improvements in the reliability of individual risk preference parameter estimates over other common methods for cumulative prospect theory. This hierarchical procedure uses population-level information (in addition to an individual’s choices) to break “ties” (or near ties) in the fit quality for sets of possible risk preference parameters. By breaking these statistical ties in a sensible way, researchers can avoid overfitting choice data and thus more resiliently measure individual differences in people’s risk preferences.

Bringing a new product to market involves both a creative ideation stage and an execution stage. When time-to-market constraints are binding, important questions are how to divide limited time between the two stages and who should make this decision. We introduce a laboratory experiment that closely resembles this setting: it features a product development task with an open design space, a downstream cost increase, and two development stages. We show that performance is significantly worse when designers choose for themselves when to transition from ideation to execution and that decision control explains a large share of performance variation even after controlling for individual differences. How the time is allocated between ideation and execution does not affect mean performance, but later transition increases risk. One driver of poor design outcomes in the designer-initiated transition regime are delays in physical construction and testing of designs. We show that such delays can be prevented by “nudging” designers toward early prototyping. However, the most important performance driver is the lack of task structure in endogenous regimes, which can be remedied by demanding a concrete, performance-oriented deliverable prior to a transition. Data and the electronic companion are available at https://doi.org/10.1287/mnsc.2016.2709 .

We show that a two-sided matching platform can successfully compete by limiting the number of choices it offers to its customers, while charging higher prices than platforms with unrestricted choice. We develop a stylized model of online dating where agents with different outside options match based on how much they like each other. Starting from these microfoundations, we derive the strength and direction of indirect network effects and show that increasing the number of potential matches has a positive effect due to larger choice, but also a negative effect due to competition between agents on the same side. Agents resolve the trade-off between these competing effects differently, depending on their outside options. For agents with high outside options, the choice effect is stronger than the competition effect, leading them to prefer an unrestricted-choice platform. The opposite is the case for agents with low outside options, who then have higher willingness to pay for a platform restricting choice, as it also restricts the choice set of their potential matches. Moreover, since only agents with low outside options self-select into the restricted choice platform, the competition effect is mitigated further. This allows multiple platforms offering different number of choices to coexist without the market tipping.

Multiplicative growth processes that are subject to random shocks often have an asymmetric distribution of outcomes. In a series of incentivized laboratory experiments, we show that a large majority of participants either strongly underestimate the asymmetry or ignore it completely. Participants misperceive the spread of the outcome distribution to be too narrowband, and they estimate the median and the mode to lie too close to the center of the distribution, failing to account for the compound nature of average growth. The observed biases are measured irrespective to risk preferences and they appear under a variety of conditions. The biases are largely consistent with a behavioral model in which geometric growth is confused with linear growth. This confusion is a possible driver of investors’ difficulties with real-world financial products like leveraged exchange-traded funds and retirement savings plans. Data and the online appendix are available at https://doi.org/10.1287/mnsc.2016.2618 .

Behavioral pricing and revenue management aim to incorporate realistic consumer behavior into firms’ pricing and inventory models. The key input to these models is market demand, which is often assumed to inherit the characteristics of consumer behavior—as when, for example, one assumes that a market consisting of loss-averse consumers is more responsive to losses than to gains. Yet market demand and consumer behavior need not be related, and so, we argue, that approach to modeling market demand is misguided. This paper proposes an approach that accounts for the heterogeneity in consumer valuation: we aggregate the demand of individual loss-averse consumers to obtain market demand and show that market demand may be more responsive to gains or losses, or it may be equally responsive. Our results have profound implications not only for how best to characterize the market demand of behaviorally biased consumers but also for determining the firm’s optimal pricing policy.

We study platform design in online markets in which buying involves a (nonmonetary) cost for consumers caused by privacy and security concerns. Firms decide whether to require registration at their website before consumers learn relevant product information. We derive conditions under which a monopoly seller benefits from ex ante registration requirements and demonstrate that the profitability of registration requirements is increased when taking into account the prospect of future purchases or an informational value of consumer registration to the firm. Moreover, we consider the effectiveness of discounts (store credit) as a means to influence the consumers’ registration decision. Finally, we confirm the profitability of ex ante registration requirements in the presence of price competition. The online appendix is available at https://doi.org/10.1287/mnsc.2016.2595 .

Customers often evaluate products at brick-and-mortar stores to identify their “best-fit” product but buy it for a lower price at a competing online retailer. This free-riding behavior by customers is referred to as “showrooming,” and we show that this is detrimental to the profits of the brick-and-mortar stores. We first analyze price matching as a short-term strategy to counter showrooming. Price matching allows customers to purchase a product from the store for less than the store’s posted price, so one would expect the price matching strategy to be less effective as the fraction of customers who seek the matching increases. However, our results show that with an increase in the fraction of customers who seek price matching, the store’s profits initially decrease and then increase. While price matching could be used even when customers do not exhibit showrooming behavior, we find that it is more effective when customers do showrooming. We then study exclusivity of product assortments as a long-term strategy to counter showrooming. This strategy can be implemented in two different ways: (1) by arranging for exclusivity of known brands (e.g., Macy’s has such an arrangement with Tommy Hilfiger) or (2) through the creation of store brands at the brick-and-mortar store (T. J. Maxx sells a large number of store brands). Our analysis suggests that implementing exclusivity through store brands is better than exclusivity through known brands when the product category has few digital attributes. However, when customers do not showroom, the known-brand strategy dominates the store-brand strategy. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2764 .