Jaeho Choi

Jaeho Choi
  • Doctoral Student

Contact Information

  • office Address:

    3038 SH-DH
    3620 Locust Walk
    Philadelphia, PA 19104

Research Interests: Organizational Learning, Managerial Cognition, Strategic Decision Making

Links: Personal Website

Overview

Jaeho Choi is a Ph.D. Candidate in Management (with a concentration in Strategy) at the Wharton School, University of Pennsylvania. He studies organizational learning, managerial cognition, strategic decision-making, and organizational design. Throughout his research, he explores the processes by which organizational decision-makers learn from prior experience, represent the world around them, and engage in strategic actions. To investigate these topics, his work employs a mix of research methods, including computational modeling and empirical (e.g., archival, experimental, & textual) analyses. His work has been published in journals such as Organization Science, Strategic Management Journal, and Journal of Business Research. Prior to his doctoral studies at Wharton, he received both his M.S. in Business Administration and dual B.A. in Public Administration and Business Administration from Yonsei University, Seoul, South Korea.

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Research

  • Jaeho Choi and Daniel A Levinthal (2022), Wisdom in the wild: Generalization and adaptive dynamics, Organization Science.

    Abstract: Learning from experience is a central mechanism underlying organizational capabilities. However, in examining how organizations learn from past experiences, much of the literature has focused on situations in which actors are facing a repeated event. We direct attention to a relatively under-examined question: when an organization experiences a largely idiosyncratic series of events, at what level of granularity should these events, and the associated actions and outcomes, be encoded? How does generalizing from experience impact the wisdom of future choices and what are the boundary conditions, or factors that might mitigate the degree of desired generalization? To address these questions, we develop a computational model that incorporates how characteristics of opportunities (cf., acquisition candidates, new investments, product development) might be encoded so that experiential learning is possible even when the organization’s experience is a series of unique events. Our results highlight the power of learning through generalization in a world of novelty, as well as the features of the problem environment that reduce this “power.”

  • Jaeho Choi, Anoop Menon, Haris Tabakovic (2021), Using machine learning to revisit the diversification–performance relationship, Strategic Management Journal.

    Abstract: In this article, we examine the relationship between corporate diversification and firm performance using a machine learning technique called natural language processing (NLP). By applying a widely used NLP technique called topic modeling to unstructured text from annual reports, we create a new, multidimensional measure that captures the degree of diversification of both multisegment and single-segment firms. Additionally, we introduce a novel method to incorporate human judgments into the interpretation of machine-learned patterns, which allows us to measure diversification across multiple dimensions, such as products and geographies. Finally, we illustrate how these new measures can generate novel insights into the relationship between the degree and type of diversification and firm performance, furthering our understanding of the diversification–performance relationship.

  • Jaeho Choi, Mooweon Rhee, Young-Choon Kim (2019), Performance feedback and problemistic search: The moderating effects of managerial and board outsiderness, Journal of Business Research, 102, pp. 21-33.

    Abstract: Extending the research on performance feedback and problemistic search, which theorizes that firm performance below the aspiration level triggers organizational search behaviors, this study examines how the inside-outside distinction of the firm management team and board members can influence the allocation of organizational attention to the performance feedback process. A longitudinal study of Korean manufacturing firms demonstrates that while a firm management team's outside experience intensifies the firm's R&D investment in response to underperformance, this effect is substituted by the presence of outside directors on the board. Our results indicate that both managers and board members can have notable influence on performance feedback and suggest that performance feedback research should examine the factors that affect the attention processing of key decision makers.

Teaching

Past Courses

  • MGMT101 - INTRO TO MANAGEMENT

    We all spend much of our lives in organizations. Most of us are born in organizations, educated in organizations, and work in organizations. Organizations emerge because individuals can't (or don't want to) accomplish their goals alone. Management is the art and science of helping individuals achieve their goals together. Managers in an organization determine where their organization is going and how it gets there. More formally, managers formulate strategies and implement those strategies. This course provides a framework for understanding the opportunities and challenges involved in formulating and implementing strategies by taking a "system" view of organizations,which means that we examine multiple aspects of how managers address their environments, strategy, structure, culture, tasks, people, and outputs, and how managerial decisions made in these various domains interrelate. The course will help you to understand and analyze how managers can formulate and implement strategies effectively. It will be particularly valuable if you are interested in management consulting, investment analysis, or entrepreneurship - but it will help you to better understand and be a more effective contributor to any organizations you join, whether they are large, established firms or startups. This course must be taken for a grade.

In the News

Activity

In the News

How Businesses Can Get Inside the Minds of Their Competitors

Wharton research using natural language processing techniques advances the field of competitive strategy analysis to previously untested terrain.

Knowledge @ Wharton - 05/30/2018
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