Peer-Reviewed Journal Articles

  • Rhee, L. and Leonardi, P. 2024. Borrowing Networks for Innovation: The Role of Attention Allocation in Secondhand Brokerage. Forthcoming at Strategic Management Journal
  • Rhee, L. 2024. CEO Attentional Vigilance: Behavioral Implications for the Pursuit of Exploration. Forthcoming at Academy of Management Journal
  • Joseph, J., Rhee, L. and Wilson, A. 2023. Corporate Hierarchy and Organizational Learning: Member Turnover, Code Change, and Innovation in the Multiunit Firm. Organization Science 34(3): 1332-1352
  • Ocasio, W., Rhee, L. and Boynton, D. 2020. March and the Pursuit of Organizational Intelligence: The Interplay between Procedural Rationality and Sensible Foolishness. Industrial and Corporate Change 29(1): 225-239
  • Rhee, L., Ocasio, W. and Kim, T. 2019. Performance Feedback in Hierarchical Business Groups: The Cross-Level Effects of Cognitive Accessibility on R&D Search Behavior. Organization Science 30(1): 51-69
  • Rhee, L. and Leonardi, P. 2018. Which Pathway to Good Ideas? An Attention-based View of Innovation in Social Networks. Strategic Management Journal 39(4): 1188-1215

Other Publications

  • Leonardi, P. and Rhee, L. 2018. Finding New Ideas When You Don’t Have a Broad Network. Harvard Business Review Online. March 16.
  • Ocasio, W., Rhee, L. and Milner, D. 2017. Attention, Knowledge and Organizational Learning. In Linda Argote and John Levine (Eds.), The Oxford Handbook on Group and Organizational Learning. Oxford University Press
  • Rhee, L. 2015. Cognitive Advantage: Effects of Holistic and Analytic Managerial Attention on Product Innovation. Academy of Management Best Paper Proceeding
  • Rhee, L. and Leonardi, P. 2014. Networks, Attention and Good Ideas: Taking Advantage of Social Structure. Academy of Management Best Paper Proceedings

Current Research Projects

Organizational Cognition and the Adoption of Discontinuous Technologies: Evidence from Cloud Computing in the Prepackaged Software Industry

This study reveals the significance of organizational cognition in driving the adoption of discontinuous technologies. While managerial cognition plays a pivotal role in identifying and assessing the potential of discontinuous technologies, it does not fully explain why numerous organizations, even after recognizing these innovations, face challenges in their adoption. This paper argues for a broader understanding of cognition, extending beyond top managers to include organizational members. Utilizing Glassdoor data from software product companies and adopting a linguistic topic model to measure organizational cognition, I have found that a firm’s adoption rate of a discontinuous technology (cloud computing in this context) increases when organizational members consider a wide range of perspectives about innovation, rather than adhering to any specific viewpoint. Moreover, this multifaceted cognition enhances the presumed benefit of managerial attention on the adoption of discontinuous technologies. This study has implications for research in organizational cognition and microfoundations of strategy.

Problemistic Search and Family CEOs in Business Groups

This study examines the role of family CEOs in business groups in their firm’s problemistic search in response to underperformance. I argue that family CEOs, driven by a heightened sense of familial responsibility, intensify their firm’s problemistic search to remedy performance shortfalls. This intensity is amplified by negative media attention on family-dominant governance, reliance on internal sales transactions, and direct kinship to the group chairperson. Analyzing a unique dataset from South Korean business groups, I provide empirical support for the hypotheses. Using a coarsen exact matching technique, I also show that firms exhibit divergent behavior in problemistic search simply due to the difference between family CEOs and professional CEOs. This study holds theoretical implications regarding performance feedback in the contexts of multilevel hierarchies and multiple goals.

Organizations as Decision Boundaries: How Aggregation Structure Can Compensate for Flawed Mental Representations (with Felipe Csaszar)

Because aggregation structures and mental representations have opposing effects on fallibility—mental representations are a source of errors while aggregation structures aim to overcome these—aggregation structures can be used to compensate for flawed mental representations. Yet given the multiple aggregation structures from which to choose and given that their effects depend on environmental factors, it is not clear which structure is best suited to what circumstances. To provide an answer to that question, we develop a formal model of group decision making among individuals who base their decisions on flawed mental representations. The model predicts the performance of three different aggregation structures (delegation, unanimity, and averaging) under different environments (defined by their munificence, uncertainty, complexity, and attribute dominance). We show that the concept of decision boundary, an idea we borrow from the machine learning literature, explains when and how aggregation structures compensate for flawed representations. This allows us to characterize the conditions under which it is preferable to use different aggregation structures as well as situations where all aggregation structures perform poorly. More generally, our paper provides a theoretical framework to understand how aggregation structure, mental representations, and the task environment jointly determine organizational performance.

Founder’s Entry Strategy and Funding Performance in the Crowdfunding Industry: The Mediating Role of Founder’s Attention (with Dalee Yoon and Joon Mahn Lee)

Building on recent studies on founders’ entry strategy type and the attention-based view, our study examines the under-explored relationship between the entrepreneurial entry strategy and funding performance. In doing so, we offer a novel perspective on the link between entry strategies (e.g., hybrid entrepreneur, multi-business entrepreneur, full-time entrepreneur) and start-up performance and develop our theory of the mediating effect of founder attention on the founder entry strategy–the start-up performance relationship. We study our research question in the research context of crowdfunding. Our findings are consistent across various robustness checks using multiple measures of founder attention and funding performance. Moreover, we address potential endogeneity concerns by adopting two-stage instrumental variable analyses as well as a propensity score matching method.

Exploitative and Explorative Learning from Others’ Failures: Evidence from Peers’ Product Recalls (with Linyi Zhang and Tony Tong)

While studies have recognized the importance of peers’ failures for a focal firm’s learning, there remains limited evidence on what specifically focal firms do in their learning from peers’ failures. Addressing this gap, we employ the opportunity-motivation-ability (OMA) framework to examine a focal firm’s exploitative and explorative activities in the face of peers’ failures. Drawing from a unique dataset of product recall events from various industries, coupled with patent data from 2005 to 2017, we discover that firms increase exploitation and decrease exploration in response to peers’ product recalls. This tendency to learn by exploitation is intensified when firms’ financial performance falls below aspiration levels and when they have a surplus of inventors. Moreover, our study reveals that decreases in inventor turnover, triggered by peers’ product recalls, result in increased exploitation and reduced exploration, suggesting inventor turnover as a mediator. This study not only contributes to the literature on learning from others’ experiences by intertwining opportunity, motivation, and ability as key factors that shape the dominant direction of a focal firm’s learning and the variations in its learning rate, but also fills a gap in empirical research by providing evidence on the specific learning activities firms undertake in response to peers’ failures. Additionally, it expands upon March’s (1991) mutual learning model by highlighting the role of inventor turnover in learning from peers’ failures.