This paper’s argument is that founding team composition—in particular, members’ prior company affiliations—shapes new firm behaviors. Firms with founding teams whose members have worked at the same company engage in exploitation because they have shared understandings and can act quickly. Conversely, founding teams whose members have worked at many different companies have unique ideas and contacts that encourage exploration. In addition, firms whose founding teams have both common and diverse prior company affiliations have advantages that allow them to grow. The results suggest team composition is an important antecedent of exploitative and explorative behavior and firm ambidexterity. The terms “exploration ” and “exploitation ” have been used broadly to capture a wide array of firm actions and behaviors. The concepts are central to studies of adaptation, organizational learning, and

While a firm’s ability to jointly pursue both an exploitative and exploratory orientation has been posited as having positive performance effects, little is currently known about the antecedents and consequences of such ambidexterity in small- to medium-sized firms (SMEs). To that end, this study focuses on the pivotal role of top management team (TMT) behavioral integration in facilitating the processing of disparate demands essential to attaining ambidexterity in SMEs. Then, to address the bottom-line importance of an ambidextrous orientation, the study hypoth-esizes its association with relative firm performance. Multisource survey data, including CEOs and TMT members from 139 SMEs, provide support for both hypotheses.

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Typologies are an important way of organizing the complex cause-effect relationships that are key building blocks of the strategy and organization literatures. Here, I develop a novel theoretical perspective on causal core and periphery, which is based on how elements of a configuration are connected to outcomes. Using data on high-technology firms, I empirically investigate configurations based on the Miles and Snow typology using fuzzy set qualitative comparative analysis (fsQCA). My findings show how the theoretical perspective developed here allows for a detailed analysis of causal core, periphery, and asymmetry, shifting the focus to midrange theories of causal processes. Types and typologies are ubiquitous, both in every-day social life and in the language of the social sciences. Everybody uses them, but almost no one pays any attention to the nature of their construction.-McKinney (1969: 4) The notion of causality plays a key role in both the strategy and organization literatures. For in-stance, cause-effect relationships are the central way in which strategic decisions and organization-al structures are understood and communicated in organizations (Ford, 1985; Huff, 1990; Huff & Jen-kins, 2001). Building on this insight, the cognitive strategy literature has aimed to map and explain the causal reasoning of managers regarding both organizational performance and competitive envi-ronments (e.g., Barr, Stimpert, & Huff, 1992; Nad-karni & Narayanan, 2007a, 2007b; Reger & Huff, 1993). Similarly, cause-effect relationships are the main building blocks of the organizational design literature and have recently received increasing at-tention (e.g., Burton & Obel, 2004; Grandori & Fur-

Number of pages 40

research advice of Andrew King, Larry Singell and Stephen Johnson. Thanks also are due to

Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author.

Scholars who view organizational, social, and technological systems as sets of interdependent decisions have increasingly used simulation models from the biological and physical sciences to examine system behavior. These models shed light on an enduring managerial question: how much exploration is necessary to discover a good configuration of decisions? The models suggest that, as interactions across decisions intensify and local optima proliferate, broader exploration is required. The models typically assume, however, that the interactions among decisions are distributed randomly. Contrary to this assumption, recent empirical studies of real organizational, social, and technological systems show that interactions among decisions are highly patterned. Patterns such as centralization, small-world connections, power-law distributions, hierarchy, and preferential attachment are common. We embed such patterns into an NK simulation model and obtain dramatic results: holding fixed the total number of interactions among decisions, a shift in the pattern of interaction can alter the number of local optima by more than an order of magnitude. Thus, broader exploration is far more valuable in the face of some interaction patterns than in the face of others. We develop simple, intuitive rules of thumb that allow a decision maker to examine two interaction patterns and determine which requires greater investment in broad exploration

doi 10.1287/mnsc.1070.0712

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