Introduction to Study 2

Drawing on the ideas of bounded rationality and the limited ability of decision-makers to acquire and process all relevant information (Cyert and March, 1963; Simon, 1947), an august literature has emerged which suggests that firm strategy is determined by managerial cognition in the form of heightened attention to some event, domain or category (see e.g., Cho and Hambrick, 2006; Gavetti, 2005; Gioia and Manz, 1985; Kaplan, 2008; Marcel, Barr, and Duhaime, 2010; Tripsas and Gavetti, 2000). Further, at any point in time, what event or issue captures the attention of decision-makers is argued to be determined by the filter of their formative experiences (Cyert and March, 1963; Finkelstein and Hambrick, 1990; Walsh, 1995). Thus, an apparently plausible central narrative of this literature is that decision-makers confronted with more data than can be comprehended, deal with inflowing information through a selective-attention and action sequence (cf. Fiske and Taylor, 1991; Ocasio, 1997). In attention-outcome models, the specific attention focus of decision-makers predicts whether strategic actions related to the focus of attention will be prescribed and legitimized (Cho and Hambrick, 2006; Eggers and Kaplan, 2009). By stressing the funneling effect of cognitive filters linked to decision-makers’ experiences, such models neatly express how the domain of managerial attention determines the domain of organizational action. While insightful in explaining say, firm’s speed of new

50

market entry or adoption of an emerging technology by virtue of a new market or technology having registered itself on the decision-makers’ attention screen (Eggers and Kaplan, 2009; Nadkarni and Barr, 2008), the models do however fall short of explaining why strategic responses diverge when managerial attention is focused on the same event or issue. For example, when faced with the same pressing environmental concerns, decision-making teams have been noted to vary in their responses (Russo and Fouts, 1997; Sharma, 2000).

This paper addresses the void in understanding identified above by bridging the cognitive psychology (Neisser, 1967; Sternberg, 2008) and adaptive learning (Kaufmann, 1989; Levinthal, 1997) literatures to introduce the concept of attention to search. We argue attention to search as a critical cognitive mechanism that can predict variation in firms’ actions when decision-making teams note and respond to the same stimulus. The concept we propose emphasizes cognition as decision-makers’ inclination towards problem-solving. Akin to organizational- system models of adaptive learning (Levinthal, 1997; Levinthal and March, 1981), the concept distinguishes between two basic and opposing problem-solving preferences based on local or nonlocal information processing. The first identifies a heuristic adopted by decision-makers preferring low risk and high certainty of returns, who seek incrementally better solutions near the domain of their extant expertise. The latter describes an algorithm favored by more risk-tolerant actors, who seek radically better solutions with potentially high albeit uncertain returns in realms distant to extant expertise (cf. Fleming, 2001; Levinthal, 1997). Because the two imply a difference in the opportunity landscape with reference to which data is gathered and analyzed and alternative feasible solutions are found, attention to search allows room for theorizing about variation in firms’ responses. The concept assumes that, given a stimulus, decision-makers with bounded rationality avoid cognitive overload by turning to a local or a nonlocal search algorithm, which simplifies decision-making by delineating the search perimeters and information analysis. However, contrary to the assumption of focused

51

attention on a domain (e.g., the task or general environment) or a specific issue or event (e.g., the emergence of a new technology) as a means of reducing cognitive burden, attention to search assumes that decision-makers can simultaneously attend to multiple domains and factors including, organizational competences, resource availability and competitor actions (cf. Kraatz and Zajac, 2001; Tripsas and Gavetti, 2000).

Inasmuch as managerial cognition is a function of past formative experiences (Finkelstein and Hambrick, 1990; Miller, Burke, and Glick, 1998), this paper further investigates whether the collective educational, functional and industry experiences of a firm’s top management team (TMT), the decision- making group with arguably the most impact on firm strategy (Cannella, Park, and Lee, 2008; Hambrick and Mason, 1984), influence TMT attention to search. Empirical evidence of a relationship between TMT experiences and attention to search should promote confidence in the nomological validity of the concept. In addition, we also investigate whether attention to search as the product of combined TMT experiences explains the observed variance in adaptive paths when firms confront industry volatility. Instability of the environment and allied uncertainty typically educe an adaptive reaction from firms (Elenkov, 1997; Lant, Milliken, and Batra, 1992). In examining the effect of TMT attention to search, we particularly engage with the research on strategic renewal. This literature has a rich tradition of inquiring into the micro-foundations of strategy to develop a better understanding of what role executive cognition plays in determining why some firms adopt a course of renewal that sees business contraction, while others renew in the opposite direction by expanding the scope of operations and, still others, by restructuring and streamlining operations (Agarwal and Helfat, 2009; Barr, Stimpert, and Huff 1992; Dutton and Jackson, 1987; Eggers and Kaplan, 2009). By specifically studying the effect of TMT attention to search on internal and external strategic renewal (Capron and Mitchell, 2009) in the form of restructuring and entry into related and unrelated product-markets respectively,

52

this paper seeks to demonstrate the potential of the attention to search concept as a predictor of variation in firm behavior and, more generally, it aims to present a model of the antecedents and consequences of attention to search as the cognitive mechanism that connects decision-makers attributes to firm-level adaptive change. We test our theory using Generalized Estimating Equations (GEE) to analyze ten-year panel data from industrial and commercial machinery and computer equipment firms in cluster 35 of the Standard Industrial Classification scheme. Following earlier studies of managerial cognition (Kaplan, 2008; Osborne, Stubbart, and Ramprasad, 2001), we employ textual analysis of letters to shareholders to assess TMT attention to search. We find that when industry volatility increases, higher levels of TMT education are associated with more attention to nonlocal search and greater TMT length of industry tenure is related to more attention to local search. Counter-intuitively, we find that following industry volatility, a positive relation between TMT functional diversity and attention to nonlocal search becomes weaker. Our analysis also shows that while more TMT attention to local search is linked to renewal through restructuring and entry into related product-markets, more TMT attention to nonlocal search leads to renewal through unrelated diversification and acquisitions. This paper makes several contributions. Perhaps most prominently, it enriches the literature on managerial cognition and strategic decision-making through a new conceptualization of cognition as attention to search. Foreshadowing our detailed discussion below, by emphasizing cognition in terms of information processing, risk and return preferences, attention to search fosters prediction of variation in organization behavior in a way that extant notions of attention focus and cognitive-schemas cannot. Further to this, by advancing a model in which cognitive processes act as the link between TMT attributes and firm outcomes, the paper adds to the upper-echelon literature by casting more light on the black-box of TMT demography (Lawrence, 1997). The article also adds to understanding of the micro-foundations of strategic renewal by revealing how decision-making

53

depends on executives’ problem-solving routines. Last but not the least, while scholars building on the evolutionary (Nelson and Winter, 1982) and learning (March, 1991) frameworks have put a great deal of stock in environment and organization-level drivers of adaptive change (see Lavie, Stettner, and Tushman, 2010), this article draws attention to the role of managerial agency. In doing so, it points to the value of a closer integration between the cognitive, learning and evolutionary literatures.