Jeho Lee

Balancing Exploration and Exploitation Through Structural Design: The Isolation of Subgroups and Organizational Learning

The classic trade-off between exploration and exploitation in organizational learning has attracted vigorous attention by researchers over the last two decades. Despite this attention, however, the question of how firms can better maintain the balance of exploration and exploitation remains unresolved. Drawing on a wide range of research on population and organization structure, we argue that an organization divided into semi-isolated subgroups may help strike this balance. We simulate such an organization, systematically varying the interaction pattern between individuals to explore how the degree of subgroup isolation and intergroup connectivity influences organizational learning. We also test this model with a range of contingency variables highlighted in the management research. We find that moderate levels of cross-group linking lead to the highest equilibrium performance by enabling superior ideas to diffuse across groups without reducing organizational diversity too quickly. This finding is remarkably resilient to a wide range of variance in factors such as problem complexity, environmental dynamism, and personnel turnover.

Exploration and Exploitation in the Presence of Network Externalities

This paper examines the conditions under which exploration of a new, incompatible technologyis conducive to firm growth in the presence of network externalities. In particular, this study is motivated by the divergent evolutions of the PC and the workstation markets in response to a new technology: reduced instruction set computing (RISC). In the PC market, Intel has developed new microprocessors by maintaining compatibility with the established architecture, whereas it was radically replaced by RISC in the workstation market. History indicates that unlike the PC market, the workstation market consisted of a large number of power users, who are less sensitive to compatibility than ordinary users. Our numerical analysis indicates that the exploration of a new, incompatible technology is more likely to increase the chance of firm growth when there are a substantial number of power users or when a new technology is introduced before an established technology takes off.

Reconsideration of the Winner-Take-All Hypothesis: Complex Networks and Local Bias

The literature on network effects has popularized a hypothesis that competition between incompatible technologies results in the “winner-take-all” outcome. For the survival of the firm in this sort of competition, the installed base has been emphasized. We argue that the validity of this hypothesis depends on how customers interact with one another (e.g., if they exchange advice or files). In some interaction networks, customers influenced by their acquaintances may adopt a lagging technology even when a lead technology has built a large installed base. The presence of such a local bias facilitates the persistence of incompatibilities. When local bias cannot be sustained in other interaction networks, one technology corners the market. Our study suggests that overemphasizing the installed base, while ignoring network structure, could mislead practitioners.

Exploration, exploitation and adaptive rationality: the neo-Schumpeterian perspective

Abstract Resource allocation between exploration of emerging technological possibilities and exploitation of known technological possibilities involves a delicate trade-off. We develop a model to represent this trade-off under the time-pressing situation where the firm’s existing basis of survival is constantly challenged by competitors’ innovation and imitation. We examine how the employment of an adaptive rule improves a balance between the exploration and the exploitation. Simulation experiments show that an adaptively rational decision rule, or a step-by-step exploration of unknown opportunities based on feedback on returns, is more likely to increase firm survival under diverse conditions than an all-or-nothing approach regarding the unknown opportunities. Furthermore, our study suggests that the adaptively rational rule is self-protected from too much loss, while its potential pay-off can be unbounded above.

Forest Fire Model as a Supercritical Dynamic Model in Financial Systems

Recently large-scale cascading failures in complex systems have garnered substantial attention. Such extreme events have been treated as an integral part of self-organized criticality (SOC). Recent empirical work has suggested that some extreme events systematically deviate from the SOC paradigm, requiring a different theoretical framework. We shed additional theoretical light on this possibility by studying financial crisis. We build our model of financial crisis on the well-known forest fire model in scale-free networks. Our analysis shows a nontrivial scaling feature indicating supercritical behavior, which is independent of system size. Extreme events in the supercritical state result from bursting of a fat bubble, seeds of which are sown by a protracted period of a benign financial environment with few shocks. Our findings suggest that policymakers can control the magnitude of financial meltdowns by keeping the economy operating within reasonable duration of a benign environment.