Park, Seamans, and Zhu (2021). Homing and platform responses to entry: Historical evidence from the U.S. newspaper industry. Strategic Management Journal, 42(4), 684—709.

  • Research Summary: We examine how heterogeneity in customers' tendencies to single-home or multi-home affects a platform's competitive responses to new entrants in the market. We first develop a formal model to generate predictions about how a platform will respond. We then empirically test it, leveraging a historical setting: TV station entry into local U.S. newspaper markets from 1945 to 1963. A notable feature of this setting is a quasi-natural experiment: the staggered geographic and temporal rollout of TV stations that was temporarily halted during the Korean War. We find that platform firms indeed take their customers' homing tendencies into account in their responses to competition: after a TV station enters the newspaper market, newspaper firms with more single-homing consumers had lower subscription prices, circulations, and advertising rates.

  • Managerial Summary: The theoretical and empirical results in our paper suggest that platform firms operating in multi-sided market settings need to consider their customers' single-homing and multi-homing tendencies. Heterogeneity in these tendencies is an important demand-side factor to consider when formulating responses to a competitor's entry.

Eggers and Park (2018). Incumbent adaptation to technological change: The past, present, and future of research on heterogeneous incumbent response. Academy of Management Annals, 12(1), 357—389.

  • Abstract: Schumpeter famously popularized “creative destruction” as the process whereby new entrants replaced existing firms. In most cases, however, some incumbent firms survive and even thrive across technological discontinuities. Moving beyond incumbent-entrant dynamics, organizations and innovation research has begun to explore incumbent heterogeneity in response to technological change—why some incumbents do well and adapt, whereas others struggle. As a phenomenon-driven research area, scholars with different theoretical perspectives have brought their own lenses to bear, but these perspectives have evolved independently. The result is a research stream with a scattered collection of detailed, within-industry perspectives on the phenomenon without a clear ability to link different mechanisms or articulate boundary conditions. This article brings these relevant literatures together to paint a more holistic picture of incumbent adaptation to technological change. To improve generalizability and begin building a more general, cross-industry theory, we emphasize recognizing specific nuances of different technological changes and how they fit with the existing capabilities, knowledge, position, and cognition of incumbent firms to understand which incumbents are swept away in the wave of creative destruction and which may survive.

Park and Shapira (2018). Risk and uncertainty. The Palgrave Encyclopedia of Strategic Management. Palgrave Macmillan, UK.

  • Abstract: Risk is the situation under which the decision outcomes and their probabilities of occurrences are known to the decision-maker, and uncertainty is the situation under which such information is not available to the decision-maker. Research on decision-making under risk and uncertainty has two broad streams: normative and descriptive. Normative research models how decision should be made under risk and uncertainty, whereas descriptive research studies how decisions under risk and uncertainty are actually made. Descriptive studies have exposed weaknesses of some normative models in describing people’s judgment and decision-making and have compelled the creation of more intricate models that better reflect people’s decision under risk and uncertainty.

Park and Shapira (2018). Risk taking. The Palgrave Encyclopedia of Strategic Management. Palgrave Macmillan, UK.

  • Abstract: Risk taking is the willingness to accept the level of risk associated with a certain decision. In other words, it refers to making decision that entails risk. In this article, we focus on managerial risk-taking. We discuss the variable risk preference model in depth, summarize the effect of performance feedback on risk-taking, and highlight some of the strategy research on risk-taking that takes the upper echelon perspective of organizations. The variable risk preference model assumes that managers have two reference points in making risky decisions—aspiration point and survival point—and which reference point they pay attention to affects their risk-taking behavior. Performance feedback has an influence on risk-taking that often makes decision-makers take a more longitudinal perspective and change their risk attitudes. Some strategy research on managerial risk-taking that adopts the upper echelon perspective examines the linkages between trait and risk-taking behavior and between incentive structure and risk-taking.

Park, Boyle, and Shapira (2017). How do decision stakes affect omission bias? Academy of Management Annual Meeting Best Paper Proceedings.

  • Abstract: People prefer harms caused by omission to equal or lesser harms caused by action, a tendency known as omission bias. Several studies, however, have challenged the existence of this bias, and some even found evidence of the opposite bias (i.e., action bias). In this paper, we study when omission bias is more likely to manifest than action bias. Building on prospect theory, we hypothesize that people will show more omission bias in high stakes situations. By conducting two laboratory experiments and through analyzing the Major League Baseball (MLB) batters’ swinging behaviors, we find support for this hypothesis in three different high stakes contexts (monetary, environmental, and rivalry), and we conclude that omission bias is more likely to occur in high stakes decision-making situations. We also test whether this relationship is mediated by affect–anticipated regret and happiness–and find that only anticipated happiness partially mediates the effect of stakes on omission bias.