Perceived Environmental Dynamism, Relative Competitive Performance, and Top Management Team Heterogeneity: Examining Correlates of Upper Echelons' Advice-Seeking

Organization Studies34(9) 1327 –1356

© The Author(s) 2013Reprints and permissions:

sagepub.co.uk/journalsPermissions.navDOI: 10.1177/0170840612470229

www.egosnet.org/os

Perceived Environmental Dynamism, Relative Competitive Performance, and Top Management Team Heterogeneity: Examining Correlates of Upper Echelons’ Advice-Seeking

Mariano L. M. HeydenNewcastle Business School, Australia

Sebastiaan van DoornWarwick Business School, UK

Marko ReimerWHU Otto Beisheim School of Management, Germany

Frans A. J. Van Den BoschRotterdam School of Management, Erasmus University, Netherlands

Henk W. VolberdaRotterdam School of Management, Erasmus University, Netherlands

AbstractAdvice-seeking is one of the most basic practices in making real-life decisions and has been shown to be a predominant mode of knowledge acquisition at the upper echelons level. Chief Executive Officers (CEOs) in particular seek advice to obtain formulated judgments, opinions, and suggestions about current strategic directions and recommended alternatives for future courses of action. In this study we distinguish between intra-organizational and extra-organizational sources of advice and examine how factors at the environmental, firm, and top management team (TMT) level relate to patterns of CEO advice-seeking. We develop and test

Corresponding author:Mariano L. M. Heyden, Newcastle Business School Australia, University Dr. SRS153, Callaghan 2308, Newcastle NSW, Australia.Email: [email protected]

470229OSS34910.1177/0170840612470229Organization StudiesHeyden et al.2013

Article

at Erasmus Univ Rotterdam on July 20, 2015oss.sagepub.comDownloaded from

http://oss.sagepub.com/

1328 Organization Studies 34(9)

hypotheses linking perceived environmental dynamism, relative competitive firm performance, and TMT heterogeneity to CEO advice-seeking from internal and external sources and uncover asymmetric patterns. We discuss implications for upper echelons theory and strategic decision-making research.

Keywordsadvice-seeking, environmental dynamism, firm performance, strategic decision-making, top management teams, upper echelons theory

Introduction

Scholarly inquiry into the role of advice in the executive suite has been gaining significant momentum (Alexiev, Jansen, Van den Bosch, & Volberda, 2010; McDonald, Khanna, & Westphal, 2008; Vissa & Chacar, 2009). Advice-seeking is one of the most basic practices in making real-life decisions and has been argued to be the predominant mode of knowledge acquisition at the upper echelons level (Heavey, Mowday, Kelly, & Roche, 2009a; Huber, 1991; McDonald & Westphal, 2003; Mintzberg, 1973). Advice sought by top managers embodies formulated judg-ments and opinions about current strategy and recommended alternatives for future courses of action (McDonald & Westphal, 2003). Whereas advice can be beneficial for improving decision comprehensiveness by exposing top managers to different perspectives and interpretations (e.g. Budescu & Rantilla, 2000; McDonald et al., 2008; Vissa & Chacar, 2009; Yaniv, 2004), advice can also be injurious by introducing biases or reinforcing existing ones (e.g. Bonaccio & Dalal, 2006; Gino, 2008; McDonald & Westphal, 2003).

The source from which advice is sought has been at the core of the academic discourse on advice-seeking and its implications. Empirical work has corroborated consequences of advice-seeking from different sources on variables such as radical innovation (Alexiev et al., 2010), strategic inertia (McDonald & Westphal, 2003), and performance (McDonald et al., 2008; Vissa & Chacar, 2009). Part of the variation in the consequences of advice-seeking seems to stem from differences in the insights provided by intra-organizational and extra-organizational sources of information (Haas & Hansen, 2007; Kyriakopoulos, 2011). For instance, in the con-text of product development teams, Kyriakopoulos (2011) observed that whereas external sources of information tend to generate novel but difficult-to-use insights, information from internal contacts tends to be easier to comprehend but less novel. Considering that distinct sources of advice may inform top managers differentially, it is somewhat surprising that upper echelons and strategic decision-making literatures have not yet probed into potential anteced-ents of advice-seeking.

In this study we seek to address the aforementioned gap by examining potential antecedents of CEO advice-seeking from different sources. We conceptualize advice-seeking as a problem-solving behavior in which a decision-maker searches for knowledge to help cope with a decision problem (Yaniv, 2004). Attesting to the unique contextual position of Chief Executive Officers (CEOs) at the intersection with the external environment, the firm, and disposition of key execu-tives (Arendt, Priem, & Ndofor, 2005; McDonald & Westphal, 2003; McDonald et al., 2008; Mintzberg, 1973), we hypothesize and test how perceived environmental dynamism, relative com-petitive firm performance, and top management team (TMT) heterogeneity relate to CEO advice-seeking. Following Alexiev et al. (2010), we analytically distinguish between intra-organizational and extra-organizational sources of advice as two important knowledge streams available to decision-makers. These sources of advice funnel judgments and recommendations about current and future strategy, as interpreted from different frames of reference, to the focal CEO.



Heyden et al. 1329

Engaging with the identified gap in this manner, we seek to contribute to the literature in several ways. First, in the context of the current body of knowledge on advice-seeking at the upper eche-lons level, we draw attention to possible antecedents of advice-seeking to complement those that have solidified the importance of advice-seeking as an influential determinant of strategy and outcomes (Alexiev et al., 2010; McDonald et al., 2008; McDonald & Westphal, 2003; Vissa & Chacar, 2009). If advice-seeking research is to fulfill its promise for uncovering untapped explana-tory power in upper echelons and strategic decision-making research, it becomes imperative to understand both the anteceding factors of different patterns of advice-seeking as well as the related consequences. By conceptualizing advice-seeking as a problem-solving behavior, we can contribute to the literature by adding possible antecedents of this behavior, whereas received models have mainly emphasized the associated consequences. In taking this view we endorse an emerging approach viewing upper echelons’ behaviors and processes as criteria or, at minimum, intervening variables (e.g. Finkelstein, Hambrick, & Cannella, 2009; Knight et al., 1999; Papadakis & Barwise, 2002; Simons, Pelled, & Smith, 1999; Simsek, 2007). Explicitly acknowledging that upper eche-lons’ behaviors are induced ultimately offers a more comprehensive conceptual basis for under-standing how, and perhaps more importantly when, top managers’ advice-seeking behaviors influence strategy and outcomes.

Second, we contribute to upper echelons theory by proposing that advice-seeking enables non-TMT actors to influence the field of vision of top decision-makers. At the core of upper echelons scholarship rests the assertion that top managers’ field of vision is attentionally delimited as executives cannot be looking in every direction or listening to every possible piece of news (Finkelstein et al., 2009, p. 47; see also Cho & Hambrick, 2006). The inclusion of advisers in the upper echelons framework implies that individuals who may or may not be members of the top management team (TMT), or even of the firm, can influence strategic choice through their provi-sion of advice. By theorizing why CEOs turn to different sources, we can contend that patterns of advice-seeking could be a contributing factor for the issues and solutions that are prioritized and attended to –and the ones that are not.

Notably, whereas most studies on advice-seeking at the upper echelons level have restricted their analysis to singular sources of advice (McDonald et al., 2008; McDonald & Westphal, 2003; Vissa & Chacar, 2009; see Alexiev et al., 2010 for a notable exception), we base our model on the premise that CEOs can tap into different advice networks. As intra- and extra-organizational sources vary in the interpretations they channel to a CEO, they prime attention and influence the scope of the CEO’s field of vision differentially. In advancing this view we strike at a core prem-ise of upper echelons theory by shedding light on an important filtering mechanism through which differential worldviews of managers emerge and, by extension, why variation in strategic choices ensue.

Finally, our theorization and allied empirical analysis extends the conceptual work on advice-seeking (e.g. Arendt et al., 2005; Jones & Cannella, 2011) as well as research conducted in experi-mental settings (e.g. Bonaccio & Dalal, 2006; Gino, 2008; Sniezek, Schrah, & Dalal, 2004; Van Swol & Sniezek, 2005; Yaniv & Kleinberger, 2000), by bringing research on advice-seeking closer to the complex set of cross-level factors confronting strategic decision-makers. In high-lighting the external environmental context, internal firm context, and TMT disposition, whilst viewing CEO advice-seeking as problem-solving information search from internal and external sources, we start to unravel how patterns of advice-seeking emerge (e.g. single source versus multi-source information search). Although rational models of decision-making prescribe exten-sive search and systematic analysis of all pertinent information (Goll & Rasheed, 2005; Mueller, Mone, & Barker, 2007), the behavioral foundations of decision-making imply that CEOs are




unable or unwilling to meaningfully process all inputs in a timely fashion themselves (Cyert & March, 1963). In understanding patterns of advice-seeking we can start to anticipate situations that may introduce, reinforce, or counterbalance biases in decision-making. This can allow schol-ars and managers to devise mechanisms to help surmount or overcome informational biases and ultimately help top managers improve the overall quality of decisions (Hambrick, 2007).

Literature Review

The informational role of advice in models of judgment and choice has been of central concern to organizational scholars and has been tackled from different complementary traditions. Organizational behavior theorists for instance have elucidated cognitive and social-psychologi-cal processes underlying the utilization of advice. Studies within this tradition have primarily examined the role of advice in the context of discrete decision problems with limited or no con-sequence for the user of the advice beyond the experimental setting. Key overarching findings from this literature suggest that as decisions become more complex (e.g. Gino, Brooks, & Schweitzer, 2012; Gino & Moore, 2007; Yaniv, 2004) and stakes become higher with associated payoffs more uncertain (e.g. Brockner et al., 1984; Pogrebna, 2008; Post, Van den Assem, Baltussen, & Thaler, 2008), individuals will tend to rely more on advice.

In turn, information systems theorists focusing on the organization as a whole have endeav-ored to understand the interplay between impersonal and rule-based information systems (e.g. enterprise resource planning systems) and less formalized and interpersonal channels (e.g. advice) in their attempts to optimize decision support tools (Onkal et al., 2009; Saunder & Jones, 1990; Yasai-Ardekani & Nystrom, 1996). One important observation that emerges from this tradition is that as more codified information becomes available through formalized systems, the more decision-makers will tend to rely on interpersonal media (e.g. De Alwis, Majid, & Chaundhry, 2006; Ko, Kirsch, & King, 2005).

More recently, strategy scholars have started theorizing about the role of advice and advisers in contemporary models of strategic decision-making based on a recognition that acquiring knowledge through interpersonal channels is the predominant mode of seeking important infor-mation at the upper echelons level (Arendt et al., 2005; Jones & Cannella, 2011; Heavey et al., 2009a; Huber, 1991; Mintzberg, 1973). A handful of empirical studies in this emerging literature have corroborated the importance of advice-seeking for several variables of interest. McDonald and Westphal (2003), for instance, drew on social categorization theory and looked at how advice sought by CEOs from their friends outside the organization was related to strategic inertia and spiraling decline in performance. Following this line of thought, McDonald et al. (2008) found that CEOs with larger risk-sensitive compensation packages were inclined to seek more advice from their circle of close external contacts, with implications for firm performance. Vissa and Chacar (2009) in turn adopted a social capital lens and theorized on the structure of entrepre-neurial teams’ external advice networks and the TMT conditions that could translate a favorable network position into performance benefits for new ventures.

A common theme in the aforementioned studies is an emphasis on advice-seeking from extra-organizational sources, consistent with a general observation that interpersonal information search is often skewed towards outside sources (Heavey et al., 2009a; Keegan, 1974; Menon & Pfeffer, 2003). In the context of global strategy, for instance, Heavey et al. (2009a) noted that external information is favored by managers over internal information (Menon & Pfeffer, 2003), and interpersonal sources over impersonal ones (Aguilar, 1967; Ghoshal, 1988; Keegan, 1974; Mintzberg, 1973). Acknowledging this limitation in prior studies, Alexiev et al. (2010) carried the



Heyden et al. 1331

conversation forward by drawing on organizational learning and showed that advice sought from both internal and external sources could be significant antecedents of radical innovations, contingent on the composition of the TMT. The overarching conclusion that stems from these empirical stud-ies is that there are substantial implications for using advice from both internal and external sources.

Although evident from the above-mentioned studies that advice-seeking is a pervasive property of decision-making in organizations, received work has focused primarily on its consequences. This approach, however, assumes advice-seeking as an exogenous behavior and omits the fact that individuals seek advice in relation to specific challenges based on the expectation that advice will help in tackling a particular intellectual task (Gino & Moore, 2007; Yaniv, 2004). Accordingly, we proceed to complement these studies by conceptualizing advice-seeking as a directed problem-solving behavior in which a decision-maker searches for information from different possible sources to assist in reaching a suitable conclusion in relation to an anteceding factor.

The rationale for advice-seeking

Top managers rely on knowledge to inform their strategic decisions. Although strategic decisions are subject to contingencies not completely known or understood when choices are made (Arendt et al., 2005; Child, 1972; Tichy & Bennis, 2007), comprehensive decisions that take into account multiple perspectives and knowledge inputs can decrease discrepancies between choices made and outcomes desired (Forbes, 2007; Heavey, Simsek, Roche, & Kelly, 2009b). Upper echelons scholars have long elaborated on how the knowledge encased in the formative experiences of top managers informs decision-making (see Carpenter, Geletkanycz, & Sanders, 2004 for a review). The core narrative of this tradition is that the experiences of a decision-maker serve as a concep-tual filter through which managers view the world (Hambrick & Mason, 1984). However, the uncertain nature of strategic decisions implies that knowledge embodied in formative experi-ences often becomes redundant in the face of new scenarios, as outdated conceptual filters become less receptive to novel stimuli (Collins, Percy, Smith, & Kruschke, 2011; Gino & Moore, 2007; Sacchi & Burigo, 2008).

As a result, top managers have been shown to scan for information from their internal and exter-nal organizational domains for key insights to inform their decisions (Boyd & Fulk, 1996; Forbes, 2007; Garg, Walters, & Priem, 2003; Mueller et al., 2007). The broader literature on scanning has proposed that top managers acquire information through impersonal or interpersonal modes and can draw on intra- and or extra-organizational sources (Garg et al., 2003; Heavey et al., 2009a). Information acquired through impersonal modes embodies codified knowledge typically found in media such as fact reports, newspapers, or web-based sources. However, the informational inputs top managers acquire through impersonal scanning are often incomplete, non-exclusive, or obsolete by the time they are published (Eisenhardt & Bourgeois, 1988; Huber, 1991; Mintzberg, Raisinghani, & Theoret, 1976). Ironically, modern information systems entrusted with processing bulks of impersonal information along preset performance indicators often provide managers with an over-flow of factual and descriptive inputs. This information overload can make it inherently difficult to extract meaning in a timely and sensible fashion (Chenhall, 2003). Therefore, as Nebus (2006, p. 616) for instance notes, ‘[d]espite recent advances in technology, people continue to prefer to con-verse with other people as the primary means of obtaining important information.’

CEOs fulfill a particular role as they are entrusted to make comprehensive choices to safeguard the well-being of the organization (Lewin & Stevens, 1994). Although CEOs can obtain relevant insights through impersonal scanning modes, this mode of search is unlikely to provide unique or




preferential insights that can confer competitive advantages (Nag & Gioia, 2012). Reliance on experiential knowledge acquired from ‘doing,’ such as experimentation or formative professional experiences (Hambrick & Mason, 1984; Regnér, 2001), or codified impersonal information (Auster & Choo, 1993; Bonaccio & Dalal, 2010), also have limitations. These sources of information may therefore provide insufficient grounds for justifying commitment to courses of action that may have irreversible consequences for the firm, its stakeholders, and the CEO (Bonaccio & Dalal, 2010; Isenberg, 1986; Mueller et al., 2007).

Seeking advice can provide CEOs with qualitatively better knowledge than their competitors or they themselves might possess. Performance advantages can accrue to a CEO who acquires insights that are unique, tacit, difficult to replicate, and not commoditized (Haas & Hansen, 2007; Inkpen & Tsang, 2005). Advice facilitates the transfer of complex and non-codified insights to a CEO and CEOs purposefully turn to contacts with some form of expertise, authority, or goodwill for judg-ments and recommendations. Of particular value is dissenting advice from dissimilar others, as these have been particularly shown to improve accuracy of subsequent judgments (McDonald et al., 2008; Van Swol & Ludutsky, 2007; Yaniv, 2004). Insights acquired from advisers improve the likelihood that ensuing strategic choices are based on qualitatively better judgments of changes in the environment, comprehensive understanding of the firm’s capabilities and competitive strengths, and appropriate assessment of different options (McDonald et al., 2008; Nebus, 2006; Onkal et al., 2009; Schrah et al., 2006).

The suggestions of advisers are often weighted at a premium because of perceived trustworthi-ness, quality, and exclusivity (cf. McDonald & Westphal, 2003; Schrah, Dalal, & Sniezek, 2006; Szulanski, Cappetta, & Jensen, 2004). As McDonald and Westphal (2003, p. 2) note, ‘executives assign greater weight to information and advice from personal sources, such as informal conversa-tions with colleagues, than to impersonal sources, such as written reports and recommendations or the output of management information systems, in making strategic decisions.’ However, different sources of advice have been shown to serve as channels for insights that may lead CEOs to draw very different conclusions about current strategy and course of proper action for the future.

Sources of advice

The boundary of the firm serves as an important demarcation line for the nature of knowledge available in the population (Huber, 1991; Kyriakopoulos, 2011). CEOs can draw on external sources of knowledge through their contacts with actors at other companies or focus on seeking insights from managers within their own organization (Alexiev et al., 2010; De Alwis et al., 2006; Menon & Pfeffer, 2003; Menon, Thompson, & Choi, 2006). These sources of advice differ mark-edly in the frames of reference in which their judgments and recommendations about current and future strategy are embedded.

Intra-organizational sources of advice. Internal sources of advice comprise other agents in the firm (e.g. lower and middle level managers) and act as a conduit for knowledge generated within functional and organizational boundaries (Raes, Heijltjes, Glunk, & Roe, 2011; Spender, 1996). Internal sources channel insights from those with deep firm-specific knowledge and intricate contextually relevant understandings (Maurer, Bartsch, & Ebers, 2011). These sources facilitate efficient transfer of system-dependent knowledge with low transaction cost and minimal loss of firm-specific meaning (Beck & Kieser, 2003). Internal advisers can expose weaknesses that may have gone unnoticed in the abstraction of strategy formulation, by pinpointing key operational and functional concerns that may impede effective strategy execution. In line with this, internal sources



Heyden et al. 1333

can also highlight how to exploit strengths by providing insights from those who interact on a more intimate basis with concrete organizational practices. Involving internal advisers can further be instrumental for building a widely shared consensus on future strategic trajectories based on the (guise of) participative leadership (Tsai & Ghoshal, 1998).

However, advice obtained from intra-organizational sources is usually conditioned by organi-zational memory and thus more likely to be characterized by informational elements consistent with the dominant logic of the firm (Argyris, 1976; Bettis & Prahalad, 1995). Internal sources are therefore likely to recirculate commonly shared understandings or uncontroversial perspectives consistent with prevailing assumptions and beliefs. As internal advisers are also unlikely to chal-lenge views of higher status members such as the CEO, the receiver is often subjected to ingratia-tion in the form of flattery and opinion conformity (Boot, Milbourn, & Thakor, 2005; Park, Westphal, & Stern, 2011). Given career progression and preservation motives, internal sources may additionally be less likely to communicate information supportive of decisions that would shift the balance of power to other actors competing for limited organizational rewards (Menon et al., 2006). Accordingly, internal sources will tend to prioritize issues and concerns related to their own immediate domains of activities, and confine their judgments and recommendations within the narrow scope of their firm-specific undertakings (e.g. functional).

Extra-organizational sources of advice. Advice from external sources (e.g. managers at other firms) is typically sought from actors with knowledge not proprietary to the focal firm, its members or its internal relations (Menon & Pfeffer, 2003). External advisers channel insights developed or applied outside the organization’s usual frame of reference (Wolfram, Mann, & Samson, 1997). Advice from external sources offers a variety of interpretations as it embodies beliefs interpreted through different cognitive schemas, allowing for the framing of issues and answers in a broader perspec-tive. Engaging with extra-organizational sources allows for identification of unfamiliar or weak signals previously unrecognized due to lack of relevant associated knowledge or outdated interpre-tative schemas (Cohen & Levinthal, 1990).

Knowledge from external sources typically highlights emerging developments by providing decisions-makers with assessments of best practices, market knowledge, and specialized expert analysis (Glückler & Armbrüster, 2003; Larsson, Hedelin, & Garlin, 2003; Kets de Vries, 1989). These recommendations from external advisors are typically considered more impartial because external advisors are often unattached to prior courses of action (Menon & Pfeffer, 2003). This external advice can help the basic questioning of underlying operating assumptions or governing principles of the dominant logic that can potentially become, or have become, harmful to the func-tioning of the firm (Akbar, 2003; McDonald et al., 2008; Robson & Bennet, 2000).

Menon and Pfeffer (2003) note, however, that insights from outside sources tend to be less rich in detail and more subjectively valued because they tend to be a scarcer resource (cf. Gino, 2008; McDonald et al., 2008). Advice from outsiders may lack profundity as these advisers are often unable to incorporate covert nuances and firm-specific idiosyncrasies in their considerations, resulting in generic, simplistic, and shallow judgments. Moreover, out-siders may perceive an inability of the CEO to formulate future strategic trajectories autono-mously when the CEO turns to them for advice. As outsiders typically have a lower stake in the outcomes of a decision and fewer vested interests in ongoing configurations, they can be more severe in their evaluations and prescriptions (Goldsmith & Fitch, 1997). By disregarding the strengths of the firm based on systems-dependent inter-linkages that are unobservable or incomprehensible to outsiders, however, the applicability of their recommendations could be undermined or even harmful.




The preceding elaboration on the potential benefits and pitfalls of different sources of information rests on the premise that intra-organizational and extra-organizational sources serve as conduits for knowledge that has been filtered from different angles of firm-specific understandings. Although the normative decision-making literature would prescribe multisource information search from internal and external sources to improve comprehensiveness (Forbes, 2007; Fredrickson & Mitchell, 1984; Mueller et al., 2007), resource-constrained CEOs are unlikely to be willing or able to do so. It becomes evident that understanding how different factors may induce CEOs to seek advice from distinct sources is imperative. Attesting to the unique contextual position of CEOs at the intersection with the external environment, internal firm, and disposition of key executives (Arendt et al., 2005; McDonald & Westphal, 2003; McDonald et al., 2008; Mintzberg, 1973), we proceed to hypothesize how perceived environmental dynamism, relative competitive firm perfor-mance, and TMT heterogeneity relate to CEO advice-seeking from intra- and extra-organizational sources.

Hypotheses

Perceived environmental dynamism and CEO advice-seeking

A firm’s ability to devise adequate adaptive responses stems partly from the ability of its CEO to anticipate market dynamics and judge exogenous changes accurately. Organizational task envi-ronments become dynamic due to irregularity in forces that are beyond the control of individual businesses (Aldrich, 1979; Baum & Wally, 2003; Dess & Beard, 1984). These dynamic environ-ments are characterized by ‘rapid, discontinuous change in demand, competitors, technology, and/or regulations such that information is often inaccurate, unavailable, or obsolete’ (Eisenhardt & Bourgeois, 1988, p. 816). This results in high uncertainty and increased complexity, while simul-taneously commanding enhanced decision responsiveness from the CEO (Baum & Wally, 2003; Lawrence & Lorsch, 1967). Milliken (1987) suggested that in general terms uncertainty can be understood as a ‘perceived inability to predict something accurately.’ In particular, she suggested that decision-makers experience uncertainty ‘when they perceive the organizational environment, or a particular component of that environment, to be unpredictable’ (p. 136).

Perceived environmental dynamism and CEO internal advice-seeking. In the face of stable environ-ments CEOs can focus on aligning internal capabilities with predictable requirements. Lee and Miller (1996), for instance, noted that CEOs of firms facing stable environments tended to focus on internal sources of competitive advantage such as internal cost-saving strategies based on operational efficiency. As associated change rates are low or predictable in these situations, CEOs will be inclined to focus on refinement of existing practices and the accumulation of firm-specific insights regarding operational concerns and potential efficiency gains. Building an in-depth under-standing of current activities and how to leverage efficiency gains would imply that CEOs seek advice from designated middle and/or front line managers responsible for suggestions on how to optimize current practices (Holmqvist, 2003; Maurer et al., 2011).

However, as the environment becomes more dynamic, the knowledge residing within the firm’s boundaries becomes less informative to a CEO. Internal advice pertains largely to firm-specific knowledge of existing activities and product/market combinations which may have become out-dated or redundant in the face of new environmental demands (Baum & Wally, 2003). As internal advisers interpret environmental stimuli in terms of the narrow confines of their firm-specific activities and vested interests (Bettis & Prahalad, 1995), CEOs may expect internal sources to be



Heyden et al. 1335

less informative in providing insights that can help them make sense of the more wide-spread implications of environmental changes for current and future strategy (Lawrence & Lorsch, 1967). Accordingly, CEOs will be less likely to seek out knowledge from internal sources as environ-ments become more dynamic. Thus,

HYPOTHESIS 1a: Perceived environmental dynamism will be negatively related to CEO internal advice-seeking.

Perceived environmental dynamism and CEO external advice-seeking. Perceived environmental dyna-mism can be expected to prime CEOs to engage in advice-seeking efforts geared at obtaining inputs to make sense of, and cope with, forces that are beyond the direct control of the firm. From a social systems level, exogenous uncertainty would prime decision makers to mimic the behavior of other organizations in their environment by adopting best-practices, comparable market posi-tions, and similar technologies (DiMaggio & Powell, 1983; Galaskiewicz & Wasserman, 1989; Greve, 1998). Chenhall (2003), taking an information systems perspective, suggested that deci-sion-makers tend to adjust their information systems to be more open and focused on external information under these environmental conditions. Consistent with this, Arendt et al. (2005) pro-posed from a strategic decision-making angle that under these circumstances CEOs will be more likely to seek advice from external sources.

When CEOs perceive the environment to be dynamic, they will tend to gear their information search towards external sources of advice to keep up-to-date with developments and adapt swiftly by imputing probabilities as events unfold. External advice provides interpretations from actors who may have noticed weak signals or identified new blind spots that may otherwise remain uni-dentified by the CEO in light of new environmental conditions (Ansoff, 1975). External advisers can thus serve as an early warning system about the nature and possible direction of environmental changes (Ansoff, 1980; Reinhardt, 1984). This in turn can assist the CEO in judging how emerging issues should be framed and interpreted, and thus what strategic action should be subsequently undertaken (Dutton & Jackson, 1987; Sharma, 2000). Accordingly, as environments become more dynamic CEOs can be expected to seek advice from outsiders to improve their assessment and comprehension of new opportunities and threats confronting the firm. Thus,

HYPOTHESIS 1b: Perceived environmental dynamism will be positively related to CEO external advice-seeking.

Relative competitive performance and CEO advice-seeking

CEOs evaluate, and are evaluated by, their firm’s performance relative to close competitors, where a par-level of performance can be considered the smallest outcome that would be deemed satisfac-tory by the decision-maker (Cyert & March, 1963; Schneider, 1992). Close competitors typically have similar aspirations and follow converging strategies (Staber, 2010) and the main source of performance variation rests in the execution of intended strategies (Geletkanycz & Hambrick, 1997; Kisfalvi, 2000). Whereas above-par performance breeds confidence in current approaches, competitive underperformance triggers search behaviors to find adaptive solutions (Cyert & March, 1963). As a firm is outperformed by its close competitors, the CEO cannot fully attribute underperformance to outside (e.g. environmental) forces, as these would be expected to affect the competitors as well or even attest to the superiority of adaptive responses from rivals (Clapham & Schwenk, 1991). In managing the internal context of the firm, relative competitive performance




functions as a feedback indicator in evaluating past decisions and constitutes a parity benchmark for perceived success or failure of strategy execution (Greve, 1998).

Relative competitive underperformance and CEO internal advice-seeking. In evaluating their relative competitive position CEOs engage in problem-solving efforts to more accurately judge how weak-nesses can be addressed in order to improve future competitiveness. Competitive underperformance reflects firm-specific problems that can trigger motivated efforts towards finding a solution by investigating previous decisions and implementation trajectories (Cyert & March, 1963; see also Argote & Greve, 2007; Vissa, Greve, & Chen, 2010). In order to attend to these problems, CEOs aim to expose underlying causes of competitive weaknesses by consulting internal sources with more intricate understandings of inner workings and operational activities of the firm (Vissa et al., 2010). These sources can help single-out underexploited strengths or firm-specific constraints that may have been overlooked in the abstraction of strategy formulation.

CEOs can also seek internal advice for more instrumental purposes in these situations. Competitive underperformance impacts the CEO on an individual level by tainting their reputation and casting doubt upon their competence (Gino et al., 2012; Wiesenfeld, Wurthmann, & Hambrick, 2008). This would increase anxiety associated with job security factors such as remuneration and career mobility opportunities (Denis & Serrano, 1996; Gibbons & Murphy, 1992; Fee & Hadlock, 2004). As CEOs experience anxiety due to these career concerns, they may seek information that is likely to reaffirm beliefs that previous choices and actions were justified (Park et al., 2011). By engaging internal advisers CEOs can foster perceptions of participative leadership and integrative decision-making (Brousseau, Driver, Hourihan, & Larsson, 2006), whilst surveying endorsement for previous strategic choices among organizational members. In doing so, the CEO can attribute responsibility for mistakes to those who can be held accountable for poor execution of appropriate strategic choices (Harvey & Fischer, 1997). Thus,

HYPOTHESIS 2a: Relative competitive underperformance will be positively related to CEO internal advice-seeking.

Relative competitive underperformance and CEO external advice-seeking. Low performance has been shown to be associated with restricted information processing and centralized decision-making (Staw, Sandelands, & Dutton, 1981; see also Bourgeois & Eisenhardt, 1988). Poor performance imposes accountability pressures on the focal CEO leading to more centralized decision-making and an increase in information processing burden on the focal actor. To cope with the increased information processing requirements individuals have been shown to be discouraged in their acquisition of insights that may be at odds with previously reached conclusions or inconsistent with deeply ingrained assumptions (Greve, 2010). The recommendations from external sources are not immediately executable as they tend to be more distant from the dominant logic of the firm and fail to account for firm specific idiosyncrasies (Gino, 2008; McDonald et al., 2008). Outsiders may be also more critical and candid in their recommendations, essentially discrediting previous choices and forcing CEOs to fully rethink the validity of previous judgments (Westphal & Bednar, 2005).

This implies that external advice would require more effort to process before it can be meaning-fully interpreted and applied to expose or solve firm-specific problems (Gino, 2008). As decreasing performance lowers the ability of the CEO to distinguish and process new discrepant information (Greve, 2010), CEOs may be discouraged to ask outsiders for their recommendations when com-petitors are outperforming them. Additionally, seeking advice from external sources in light of



Heyden et al. 1337

underperformance can be interpreted as a signal of the CEO’s incompetence or inability to solve the strategic challenges the firm is faced with (Bergh & Gibbons, 2011). Taken together, this may indicate a tendency not to seek external advice-seeking in cases of relative competitive underper-formance. Thus,

HYPOTHESIS 2b: Relative competitive underperformance will be negatively related to CEO external advice-seeking.

TMT heterogeneity and CEO advice-seeking

The composition of the organization’s TMT has long been shown to matter for strategic choice (Hambrick & Mason, 1984). Studying the disposition of TMT as a function of heterogeneity in attributes such as education, functional experience, and tenure has been at the core of upper eche-lons research (Carpenter et al., 2004; Finkelstein et al., 2009; Nielsen, 2010). Combining perspec-tives from various domains of experience through enriching informational debate often results in multiple attractive ideas and alternatives for coping with focal decision issues (Simons et al., 1999; Van Knippenberg, De Dreu, & Homan, 2004). Homogeneity in attributes in turn implies that exec-utives are more likely to have overlapping frames of reference, shared cause-effect understandings, and a common arsenal of problem-solving heuristics (Bantel & Jackson, 1989; Hambrick, Cho, & Chen, 1996). This experiential commonality typically facilitates a more profound analysis within parameters of communal knowledge boundaries.

TMT heterogeneity and CEO internal advice-seeking. Internal advice is expected to be less informative for a CEO confronted with multiple viable alternatives, such as likely to emerge from a heterogene-ous TMT. Internal advisers may be largely supportive of existing practices and unable to put options into a broader perspective and internal advice may be colored by internal power differen-tials, vested interests, and organizational customs that distort the objective valuation of different options (Tsai, 2002; Walton & Dutton, 1969). By prioritizing recommendations that are supportive of narrow firm-specific domains of activity (e.g. functional unit) or vested interest, internal sources may fail to confer merit to alternatives that, although beneficial, may contradict or even cannibal-ize on their extant activities. Seeking internal advice may also have an unintended, but foreseeable, side-effect that may deter CEOs from seeking it. To the extent that multiple attractive options are generated by a heterogeneous TMT, asking agents lower down in the organization for their opinion on alternatives might create unfounded unrest, spreading of rumors, and upfront resistance to a decision that is yet to be made (Maurer & Ebers, 2006).

When heterogeneity is low, the TMT is inclined to foster analogous interpretations of issues and devise fewer, but more deeply focused, sets of alternatives to cope with intellectual challenges (Van Knippenberg et al., 2004). When CEOs observe singularity of opinion based on depth of understanding, as likely to emerge from homogeneous TMTs, they may perceive a high degree of group efficacy in the TMT’s perspective and proceed to search for information that positively rein-forces group cohesion (Choi & Kim, 1999; Janis, 1982; Park 1990; Peterson et al., 1998; Stasser & Titus, 1985, 1987). Thus, when CEOs are confronted with multiple viable alternatives resulting out of the disposition of heterogeneous TMTs, they will not be inclined to seek advice from sources within the organization.

HYPOTHESIS 3a: TMT heterogeneity will be negatively related to CEO internal advice-seeking.




TMT heterogeneity and CEO external advice-seeking. The enriching informational debate of hetero-geneous TMTs may result in multiple viable options, potentially increasing decisional complex-ity by confounding the CEO’s ability to accurately judge the appropriateness of competing, polarized, and potentially orthogonal alternatives (Hodgkinson & Wright, 2002). In the face of multiple competing alternatives TMT members could experience affective conflict and become less supportive of ensuing choices, as it becomes more difficult to agree on an appropriate course of action without marginalizing individual contributions (Knight et al., 1999; Mooney, Holahan, & Amason, 2007). In the face of multiple competing alternatives, decision-makers become more sensitive to the payoffs of others (Schwarz, 2004). Studies in laboratory settings have shown that when multiple competing alternatives are generated, actors turn to help from outsiders to justify the selection of one alternative over another (Gino, Shang, & Croson, 2009; Harvey, Harries, & Fischer, 2000).

In the face of multiple viable alternatives the CEO can resort to more objective outsiders who could assist in affective conflict resolution by helping to make sense of the merits of various options (Hambrick, 1995; Mooney et al., 2007; Tinsley, 1998). In order to foster support for an imminent choice without leaving individuals feeling neglected, external advisers may assist by evaluating alternatives and tilt the scale in favor of a particular alternative by introducing objective information that may rationalize a selection. Thus, CEOs of more heterogeneous TMTs may resort to outside advisers for judgments and opinions that may justify the choice of a particular alternative when confronted with multiple options (Hambrick, 1995). Therefore,

HYPOTHESIS 3b: TMT heterogeneity will be positively related to CEO external advice-seeking.

Methods

Research design and sample properties

The study was based on a random sample of Dutch firms drawing on survey data collected annu-ally over a four-year period. Multiple indicators based on existing scales were collected through a large scale mixed mode survey (mail & web-based) as part of a larger ongoing project into the innovation level of the respective population. CEOs, presidents, and general managers from firms in multiple industries were targeted as respondents and were identified from the REACH data-base, which compiles data on organizations registered at The Netherlands Chamber of Commerce. These executives were initially sent a paper version of the questionnaire with a return envelope. The cover letter addressed the purpose of the study, a brief profile of the research team, and a link to a web-based version of the questionnaire. Confidentiality was guaranteed and as an added incentive to participate the respondents were offered an executive report of their firm’s competi-tive position vis-à-vis national and industry averages with recommendations about their strengths and weaknesses.

The average response rate was almost 13 percent sample-wide, which is in line with average response rates from large scale sampling of corporate elites (Cycyota & Harrison, 2006; Hambrick, Geletkanycz, & Fredrickson, 1993). To further increase the reliability of measures, questionnaires were sent out to a second executive in the firm after two weeks. We managed to get multiple respondents for 372 of the observations used for our analysis (10.6%). Consequently, an inter-rater agreement score (rwg) was calculated for each item used for the analyses (James, Demaree, & Wolf, 1993). The average inter-rater agreement ranged from 0.85 to 0.91, which suggests high agreement



Heyden et al. 1339

between raters. The examination of intra-class correlations also revealed a strong level of inter-rater reliability, as correlations were consistently significant at the 0.001 level (Jones, Johnson, Butler, & Main, 1983).

To check for potential biases stemming from the method of data collection the differences between the web-based and paper-based respondents were checked, as well as differences between respondents of different ages using the sample average as a cutoff. T-test results did not indicate significant differences for the items used in this study. Finally, to check for common method variance a Harman single-factor test was conducted on items included in our multivariate model to examine whether common method variance was augmenting relationships. Multiple factors were found, and a first general factor did not account for the majority of variance extracted, thus sub-stantiating that common method bias was not misguiding our interpretations (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).

Measures and operationalizations

The core constructs were measured using established multi-item scales previously validated in the literature. Table 1 provides an overview of the variables, the corresponding set of items measured on seven-point Likert-type scales, their means and standard deviations, standardized factor loadings, Cronbach’s alpha, and average extracted variance. For the first hypothesis, per-ceived environmental dynamism was operationalized as a latent factor reflecting multiple items, corresponding to the variable ξ1 in Figure 1. For the second hypothesis, relative competitive underperformance was modeled as a latent factor reflecting multiple items measuring perceived financial performance in relation to the firm’s closest competitors, as indicated by ξ2 in Figure 1. The perceived relative performance items were inverted to capture perceived underperformance in order to facilitate interpretation in line with our theoretical premises. For the third and final hypothesis TMT heterogeneity was operationalized as a latent function of multiple items meas-uring variety in functional background experiences present in the TMT, as indicated by ξ3 in Figure 1.

The dependent variables related to the source from which CEOs sought advice were operation-alized using items asking about the respondent’s extent to which knowledge inputs about current strategy and future strategy from interpersonal sources were sought, based on Alexiev et al.’s (2010) seven-point scale, as adapted from McDonald and Westphal (2003). Following Alexiev et al. (2010), we focused on knowledge sought from sources within the focal organization (‘CEO internal advice-seeking’) and knowledge sought from sources outside the organization (‘CEO external advice-seeking’). These two items were then modeled onto two corresponding latent vari-ables, η1 and η2 respectively, as shown in Figure 1.

Controls. We controlled for potential influences that might drive the dependent variables from different levels. From the CEO level CEO tenure was included as years as CEO at the focal com-pany and CEO age in years, as more experienced and older CEOs could be more inclined to rely on their own experiences or intuition to inform judgment (Arendt et al., 2005), and CEO advanced degree if the CEO had a masters, multiple masters, or PhD as a proxy for their ability to process information (Hambrick & Mason, 1984). We also controlled for the intensity of advice-seeking to control for the general propensity of a CEO to seek advice. The propensity for seeking advice was operationalized as a summated index of two seven-point items asking about the extent to which the CEO had resorted to internal or external sources more generally. At the TMT level we




Table 1. Factor table and descriptives.

Model Variable Item Descriptions Mean (SD) Factor Loadingsa

Cronbach’s α

Average Variance Extracted

Latent Variables Perceived Environmental Dynamism (ξ1) (Jansen et al., 2006)

Changes in our market environment are very intense

4.60 (1.61) .83 .82 65.45

Clients in our markets regularly demand completely new products and/or services

4.11 (1.62) .81

The markets in which we operate are constantly experiencing changes

4.74 (1.57) .88

Demand fluctuates rapidly and frequently in our markets

4.50 (1.16) .72

Relative Competitive Performance (ξ2) b(Jansen et al., 2006)

Your return on assets compared to your closest competitors

4.81 (1.15) .84 .82 65.35

Your revenue growth compared to your closest competitors

4.81 (1.21) .78

Your profit compared to your closest competitors

4.74 (1.10) .80

Your acquisition of new customers compared to your closest competitors

4.68 (1.04) .82

TMT Heterogeneity (ξ3)(Alexiev et al., 2010; Campion et al., 1993)

The members of the management team have divergent areas of expertise

5.73 (1.20) .79 .81 65.94

The management team members have a great variety of backgrounds

5.45 (1.31) .85

The management team is comprised of members with diverse experiences

5.47 (1.22) .86

The members of the management team have skills that complement each other strongly

5.54 (1.11) .75

Internal Advice-Seeking (η1)(Alexiev et al., 2010; McDonald & Westphal, 2003)

To what extent did you acquire knowledge from the managers within your organization about your future strategy

5.03 (1.41) .97 .94 94.48

To what extent did you acquire knowledge from the managers within your organization about the current strategy

5.02 (1.42) .97



Heyden et al. 1341

Model Variable Item Descriptions Mean (SD) Factor Loadingsa

Cronbach’s α

Average Variance Extracted

External Advice-Seeking (η2)(Alexiev et al., 2010; McDonald & Westphal, 2003)

To what extent did you acquire knowledge from the managers of other organizations about your future strategy

3.60 (1.56) .95 .89 90.34

To what extent did you acquire knowledge from the managers of other organizations about your current strategy

3.82 (1.61) .95

Observed variables

CEO tenure 13.12 (10.41) CEO advanced degree .34 (.47) CEO age 47.23 (9.08) Propensity to seek advice 8.88 (2.21) TMT size (log) 1.53 (.51) Firm size (log) 4.16 (1.18) Firm age (log) 1.25 (.52)

aPrincipal component extraction; bReverse coded for interpretation.

Table 1. (Continued)

controlled for TMT size by taking the log of the number of team members, as this has been shown to be influential for decision-making dynamics (Certo, Lester, Dalton, & Dalton, 2006).

At the firm level we controlled for firm size as log of employees (Autio, Sapienza, & Almeida, 2000), as larger firms tend to have more slack resources and more internal variety, thus potentially influencing advice-seeking (Bourgeois, 1981), and log of firm age, as older firms may have more established and sophisticated information systems that can influence the CEO advice-seeking due to the amount of accessible bits of raw information (Chenhall, 2003). To further mitigate size effects we restricted our analysis to sampled firms with ≥ 20 employees, as CEOs from smaller firms are more likely to be actively involved in day-to-day operational activities making internal advice-seeking in terms of our conceptualization difficult to tease out from regular everyday com-munications with other members of the organization (Ainsworth & Cox, 2003; Staber, 2010). To mitigate industry and year effects without adding parameters in our structural equation model we mean centered the industry average for each item for the year of observation and missing data were imputed based on the sample average to maintain necessary statistical power. We further allow our latent predictor variables (ξ1, ξ2, ξ3) to correlate (Φ) as to isolate the effect of unob-served common predictors of the independent constructs that could potentially lie outside the specified model. The final sample used for our analysis corresponded with 3518 observations for the four-year window (2006–2009). The largest sub-clusters in the sample were Manufacturing and Mining (26.55%), Business Services (22.80%), Construction (13.39%), and Transport and Trade (12.39%). Responses from the remaining eight industries each accounted for between 1.0% and 6.05% of the sample.

Validity and reliability. Statistically, Fornell and Larcker (1981) argued that constructs demonstrate discriminant validity if the variance extracted for each is higher than the squared correlation




ξ 1P

erce

ived

En

viro

nm

enta

lD

ynam

ism

ξ 2R

elat

ive

Com

pet

itiv

eU

nd

erp

erfo

rman

ce

η 1C

EO

In

tern

al

Ad

vice

-See

kin

g

η 2C

EO

Ext

ern

al

Ad

vice

-See

kin

g

ζ 1 ζ 2

H1a

= .0

4 (n

s)

Y1

Y2

Y3

Y4

λy 23

=. 9

1***

λy 12

=. 9

1***

λy 11

=. 9

7***

λy 24

=. 8

7***

X1

X2

X3

X4

λx 11

= .9

4***

λx 23

= .7

7***

λx 12

= .7

7***

λx 24

=.8

9***

ξ 3T

MT

Het

erog

enei

ty

X5

X6

λx 35

= .8

5***

λx 36

= .8

2***

H1b

= .1

0***

H2a

=.0

8**

H2b

=-.

05 (

ns)

H3a

=-.

14**

*

H3b

=.1

0***

Con

trol

s in

clud

ed in

mod

el

X11

TM

T s

ize

X12

Fir

m s

ize

X10

Pro

pen

sity

for

See

kin

g A

dvi

ce

X7

CE

OT

enu

re

X13

Fir

m A

ge

X8

CE

O A

dva

nce

dD

egre

e

X9

CE

O A

ge

Fig

ure

1. S

EM O

utpu

t M

odel

a .a N

= 3

518.

Mod

el fi

t st

atis

tics:

CFI

.986

; NFI

.983

; RM

SEA

.035

. *p<

.05;

**p

<.0

1; *

**p<

.001

for

unst

anda

rdiz

ed M

axim

um L

ikel

ihoo

d es

timat

es. C

orre

latio

ns b

etw

een

exog

enou

s va

riab

les

mod

eled

but

om

itted

for

expo

sitio

nal e

ase:

Φ (ξ 1

ξ2)

= .1

1***

; Φ (ξ 1

ξ3)

= -

.15*

**; Φ

(ξ 2

ξ3)

= -

.19*

**. S

quar

ed M

ultip

le C

orre

latio

ns η

1 =

.42

and η 2

= .4

3.



Heyden et al. 1343

Tab

le 2

. Bi

vari

ate

corr

elat

ions

.

(I)(II

)(II

I)(IV

)(V

)(V

I)(V

II)(V

III)

(IX)

(X)

(XI)

(I)C

EO in

tern

al

advi

ce-s

eeki

ng

(II)

CEO

ext

erna

l ad

vice

-see

king

.28

***

(III)

Perc

eive

d en

viro

nmen

tal

dyna

mis

m

.17

***

.18

***

(IV)

Com

petit

ive

unde

rper

form

ance

.13

***

.05

**.0

8 **

*

(V)

TM

T h

eter

ogen

eity

−.2

3 **

*−

.10

***

−.1

3 **

*−

.16

***

(

VI)

CEO

ten

ure

−.0

5 *

−.0

4 *

.01

.04

*.0

4

(VII)

CEO

adv

ance

d de

gree

.12

***

.09

***

.01

.03

−.0

2−

.20

***

(VIII

)C

EO a

ge.0

0.0

0.0

0−

.01

.00

.08

***

−.0

3

(IX

)Pr

open

sity

to

seek

ad

vice

.65

***

.64

***

.17

***

.11

***

−.2

3 **

*−

.09

***

.12

***

−.0

1

(X)

TM

T s

ize

(log)

.19

***

.06

**.0

6 **

*.0

8 **

*−

.09

***

.02

.13

***

.01

.13

***

(X

I)Fi

rm s

ize

(log)

.09

***

.04

*.0

3−

.01

−.0

5 **

−.0

2.1

9 **

*.0

0.1

0 **

*.3

1 **

*

(XII)

Firm

age

(lo

g).0

3−

.04

*−

.04

*−

.04

*−

.01

.09

***

.01

.00

.01

.11

***

.18

***

*p<

.05;

**p

<.0

1; *

**p<

.001

.




between the constructs. Hair, Anderson, Tatham, and Black (1998) extended this condition by pro-posing that the composite reliability should be above the 0.70 threshold and an extracted variance above the 0.50 threshold. All our measures were consistent with these using a principal component extraction. Reliability scores were further computed and were all in line with generally accepted standards of good reliability of > .70, as shown in Table 1.

Hypotheses Testing and Results

Table 2 provides an overview of our bivariate analysis. We proceeded to test our proposed model adopting structural equation modeling (SEM) as our multivariate analytical technique. SEM with latent variables can be used when one aims to test specific hypotheses about the dependence rela-tionship among certain constructs where a well-defined structure is imposed a priori (MacDonald & Ho, 2002). This technique has the advantage of explicitly considering the measurement error in the indicators and simultaneously estimating a system of structural equations (Jöreskog & Sörbom, 1984). We further adhered to recommendations by Zaheer, McEvily, and Perrone (2008) and adopt Bagozzi and Heatherton’s (1994) partial disaggregation approach to test the structural models. This is because as the number of items and parameters increases, the model ‘can be unwieldy because of the likely high levels of random error in typical items and the many parameters that must be estimated’ (Bagozzi & Heatherton, 1994, p. 43). The partial disaggregation model repre-sents a compromise between the most aggregative approach (i.e. the standard practice of summing responses to all items into single scales) and the most disaggregative approach (i.e. treating each item as an individual indicator of its respective factor) (Bagozzi & Foxall, 1996). Our hypotheses were tested on this model specification.

Table 3. SEM coefficientsa.

A. CEO Internal Advice-Seeking (η1)

B. CEO External Advice-Seeking (η2)

b. (s.e.) p. b. (s.e.) p.

Hypothesized Relations

H1: Perceived environmental dynamism (ξ1)

.04 (.02) .10 (.02) ***

H2: Relative competitive underperformance (ξ2)

.08 (.03) ** −.05 (.03)

H3: TMT heterogeneity (ξ3)

−.14 (.03) *** .10 (.03) ***

Controls CEO tenure (X7) .00 (.00) .00 (.00) CEO advanced degree

(X8).07 (.04) .04 (.05)

CEO age (X9) .00 (.00) .00 (.00) Propensity to seek

advice (X10).35 (.01) *** .40 (.01) ***

TMT size (X11) .26 (.04) *** −.09 (.05) * Firm size (X12) −.03 (.02) −.03 (.02) Firm age (X13) .04 (.04) −.10 (.04) *

aN: 3518. *p<.05; **p<.01; ***p<.001. Model fit statistics: CFI .986; NFI .983; RMSEA .035. Industry and year effects mitigated by mean-centering items based on the sector average for the focal year. Factor loadings for observed items X1-X6 and Y1-Y4 displayed in Figure 1. Squared Multiple Correlations η1 = .42 and η2 = .43.



Heyden et al. 1345

Model results

Table 3 displays the output model for our SEM, where we consider coefficients with p-values lower than .05 as statistically significant given our sample size (Cohen, 1992). Looking at the coefficients corresponding to our first set of hypotheses (1a and 1b), we expected that perceived environmental dynamism would be negatively related to CEO internal advice-seeking, whereas perceived environ-mental dynamism would be positively related to CEO external advice-seeking. For hypothesis 1a, we did not find support for the notion that perceived environmental dynamism was negatively related to CEO internal advice-seeking (b = .04; NS), despite sufficient statistical power (Cashen & Geiger, 2004; Cohen, 1992). For hypothesis 1b, we did find a positive and significant coefficient at the .001 level (b = .10) in the hypothesized direction, thus corroborating our expectation that perceived envi-ronmental dynamism is positively related to CEO external advice-seeking in our population.

For our second set of hypotheses, 2a and 2b, we found that performance lower than closest competitors was positively related to CEO internal advice-seeking (b = .08; p < .01), thus corrobo-rating hypothesis 2a. We further found no discernible impact of competitive underperformance on external advice-seeking despite sufficient statistical power (b = -.05, NS), providing no support for hypothesis 2b. As for the third set of hypotheses, we expected that TMT heterogeneity would be negatively related to CEO internal advice-seeking (hypothesis 3a) but positively related to CEO external advice-seeking (hypothesis 3b). Our results are significant at the .001 level and in the hypothesized directions. We observe a statistically significant negative effect of TMT heterogene-ity on CEO advice-seeking from intra-organizational sources (b= -.14; p <. 001) and a statistically positive effect on CEO advice-seeking from extra-organizational sources (b = .10; p < .001). Our findings have several implications for theory.

Discussion

The study of advice-seeking at the upper echelons level has emerged as crucial for understanding the process and outcomes of strategic decision-making. Contributing to this young and growing literature, we have set out to examine CEO internal and external advice-seeking behaviors by focusing on antecedents reflecting the external environment context, the internal firm context, and the disposition of the TMT. We specifically looked at patterns of CEO advice-seeking in relation to perceived environmental dynamism, relative competitive firm performance, and TMT heteroge-neity. In doing so we uncovered asymmetric patterns of advice-seeking in relation to intra-organi-zational and extra-organizational sources of advice. Our theorizations and findings allude to several interesting implications for strategic decision-making and upper echelons scholarship.

Theoretical implications

Studying antecedents of advice-seeking. In the context of the current body of knowledge on advice-seeking at the upper echelons level, we draw attention to possible antecedents of advice-seeking to complement those that have solidified the importance of advice-seeking as an influential determinant of strategy and outcomes (Alexiev et al., 2010; McDonald et al., 2008; McDonald & Westphal, 2003; Vissa & Chacar, 2009). If advice-seeking research is to fulfill its promise for uncovering untapped explanatory power in upper echelons and strategic decision-making research, it becomes imperative to understand the factors that induce different patterns of advice-seeking and the related consequences. Although upper echelons theory has a strong tradition of conceptual-izing the characteristics and behaviors of the organization’s senior-most managers as antecedents of strategy and outcomes, studies have not fully embraced the plausibility that most behaviors may be contextually induced (Finkelstein et al., 2009).




Yaniv (2004, p. 1) noted that individuals seek advice in relation to different challenges based on the expectation that advice will help in tackling an intellectual task. Adopting this premise in the context of upper echelons theory, we can conceptualize advice-seeking as a problem-solving behavior in which a CEO searches for knowledge from different potential sources to help cope with a decision problem. By acknowledging that advice-seeking behaviors are not exogenously given, and shifting the focus to uncovering the potential antecedents of these behaviors, we can advance towards a more comprehensive conceptual understanding of how, and perhaps more importantly when, top managers’ advice-seeking behaviors influence strategy and outcomes. In doing so we underscore the value of viewing top managers’ behaviors as outcome or mediating variables (e.g. Amason, 1996; Knight et al. 1999; Papadakis & Barwise, 2002; Simons et al., 1999; see also Finkelstein et al., 2009).

In line with this conceptual framing, our empirical analysis shows for instance that when envi-ronments are regarded as stable, the CEO may not seek advice from intra-organizational sources and seek little to no advice from external ones. It could be that under these circumstances top managers will rely primarily on the experiential knowledge encased in their formative experiences to inform strategic choice (Collins et al., 2011) or simply persist with extant courses of strategy (Finkelstein & Hambrick, 1990). Thus, when environments are not regarded as being dynamic, CEO advice-seeking behaviors can be expected to be a weak predictor of subsequent strategic choice. Additionally, it could very well be the case that the tendency of CEOs to seek advice from intra-organizational sources in light of competitive underperformance, paired with a tendency not to seek advice from extra-organizational sources, could translate into limited variety in the judg-ments and recommendations acquired about current and future strategy. Under these conditions we can expect that CEO advice-seeking behaviors from intra-organizational sources will be a better predictor of subsequent strategic choices –or lack thereof.1

Decision-making involvement and upper echelons’ field of vision. At the core of upper echelons scholarship rests the assertion that top managers’ field of vision is attentionally delimited as an executive cannot be looking in every direction or listening to every possible piece of news (Finkelstein et al., 2009, p. 47; see also Cho & Hambrick, 2006). By theorizing why CEOs turn to intra-organizational or extra-organ-izational sources of advice, we can contend that patterns of advice-seeking could be a contributing factor for the issues and solutions that are prioritized and attended to – and the ones that are not. The inclusion of advisers in the upper echelons theory implies that actors who may or may not be members of the TMT, or even of the firm, can influence strategic choice through the advice they provide.

We contend that upper echelons theory can benefit from highlighting the anteceding factors and boundary conditions under which decision-making involvement is expanded beyond the formal team of executives, for instance, through the use of advisers. Although we have no reason to ques-tion the core premise that the worldview of top managers influences subsequent action, it does become important to determine whose worldview is reflected in the decision-making team, and acknowledge that this need not be confined to hierarchical or even firm boundaries. We propose that as internal and external sources vary in the information they channel to a CEO, they prime attention and influence the scope of the CEO’s field of vision differentially. By bringing the scope of decision-making involvement to the forefront we strike at a core premise of upper echelons scholarship by shedding light on an alternative filtering mechanism through which differential worldviews of managers emerge and, by extension, why variation in strategic choices ensue. For instance, studies have shown that high quality decisions are most often rooted in stable and con-sistent preferences, however, these ‘silent whisperers’ could help account for lack of consistency in the CEO’s worldview if they sway her/his attention incoherently (Cho & Hambrick, 2006; Grimpe & Kaiser, 2010; Mitchell, Shepherd, & Sharfman, 2011).



Heyden et al. 1347

Given this, a further implication of our study is a call for a cautious reassessment and specifica-tion of who the upper echelons really are in a given research context, and why studying the TMT exclusively in terms of formal executives has produced inconsistent findings in the literature (Carpenter et al., 2004). Some scholars have indeed hinted to the possibility that upper echelons might consist of a stable core and a dynamic periphery (e.g. Finkelstein et al., 2009; Jones & Cannella, 2011; Mooney & Amason, 2011; Roberto, 2003). However, although these scholars acknowledge that top managers are embedded actors, they have confined the periphery of upper echelons membership exclusively to other senior managers or non-executive board members. It seems, however, that the strategic decision-making team could be even more fluid than previously thought and different contextual factors can define the bounds of upper echelons membership dif-ferentially. In bringing advisers into the realm of strategic decision-making, we can contemplate the possibility that upper echelons may consist of at least a stable core, a dynamic periphery, and satellite actors who are engaged under specific conditions —either in core or peripheral roles, although more empirical evidence is warranted to substantiate this claim.

Managing biases in strategic decision-making. Finally, we offer a contribution to strategic decision-making research more specifically. Our theorization and allied empirical analysis extends the con-ceptual work on advice-seeking (e.g. Arendt et al., 2005; Jones & Cannella, 2011) as well as research conducted in experimental settings (e.g. Bonaccio & Dalal, 2006; Gino, 2008; Sniezek et al., 2004; Van Swol & Sniezek, 2005; Yaniv & Kleinberger, 2000), by bringing research on advice-seeking closer to the complex set of cross-level factors confronting strategic decision-makers. Although rational models of decision-making prescribe extensive search and systematic analysis of all perti-nent information (Goll & Rasheed, 2005; Mueller et al., 2007), the behavioral foundations of deci-sion-making imply that CEOs would be unable to meaningfully process all inputs in a timely fashion themselves (Cyert & March, 1963). The general pattern we observe is that CEOs are unlikely to engage in comprehensive multi-source advice-seeking in relation to the factors we examined. It seems that CEOs exhibit more focused patterns of search for informational inputs to cope with dif-ferent decision problems.

These non-comprehensive information search strategies may not be dispositionally determined (e.g. CEO tenure, CEO education), but rather resemble a problem-solving behavior in which the CEO exhibits an observable preference for a given source of advice. Although it could be imagined that CEOs would consistently turn to the same source for advice, the asymmetric patterns of advice-seeking we observe imply a more dynamic preference for tapping into different advice-networks —an observation that would partly rule out access to different sources of advice as a determinant of patterns of advice-seeking. To the extent that comprehensive search is a norma-tively desired condition (Mueller et al., 2007), it becomes imperative to understand patterns that may introduce, counterbalance, or reinforce biases in strategic decision-making (McDonald & Westphal, 2003). Understanding these patterns can allow us to devise mechanisms to help sur-mount or overcome informational biases and ultimately help top managers improve the overall quality of decisions (Hambrick, 2007).

Boundary conditions and future research

Our study is subject to some boundary conditions that pave the way for new research opportunities. First, we have looked at correlates, which is not the same as causality. Although our analytical approach allowed us to observe quantitative differences in relation to different sources of advice, still we did not theorize the order in which decision problems stemming from cross-level factors are pri-oritized and attended to. This provides fertile ground for future multilevel research into the causal and




temporal patterns of these relations. We have further restricted our scope to additive effects, although these cross-level factors might coexist and interact in more complex and counterintuitive ways. Future research could benefit from examining how contextual conditions interact to influence CEO advice-seeking and even consider broadening the set of predictor variables with micro-level factors such as CEO personality characteristics (e.g. Buyl, Boone, Hendriks, & Matthyssens, 2011). Future research should also address contingency factors, which could potentially influence CEOs’ advice-seeking behavior (e.g. type of decision problem, time pressure; quality of advice) (Schotter, 2003).

In a similar vein, researchers could try to integrate behavioral and network views of advice-seeking, by considering how membership in interlocking directorates influences advice-seeking behavior (e.g. Pettigrew, 1992). Although data restrictions inhibited us from testing these relations in this study, it seems plausible that executives who served several years in leading positions in global investment banks or strategy consulting firms before becoming CEOs, would have built networks linking them to top managers in many different institutional environments (Abdi & Aulakh, 2012). Therefore, these CEOs are able to seek better quality advice from different sub-clusters within their network of external advisors. Further identification of the specific identities of subgroups of internal and external advisers beyond our conceptualization and operationalization could also help refine findings (e.g. experts vs. non-experts). Finally, the role of boards of directors could also complement these findings (McDonald et al., 2008), as board mandates frequently out-line the strategic profile of the firm, which in turn may influence the scope of CEO advice-seeking, especially for new executives (Shen & Cannella, 2002).

Acknowledgements

We are most appreciative for the editorial guidance from Michael Lounsbury and the constructive comments from four anonymous reviewers. We would like to thank Shahzad Ansari, Marta Geletkanycz, Matthias Mahlendorf, Hermann Ndofor, Dodo zu Knyphausen-Aufseβ, Utz Schäffer, and participants of the 3rd EIASM Workshop on Top Management Teams and Business Strategy Research for invaluable comments and suggestions. All errors and omissions are our own.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Note

1. Interestingly, post-hoc analyses reveal that under conditions of high environmental dynamism the hypoth-esized relation in H2a becomes statistically non-significant and H2b remains non-significant, consistent with a threat-rigidity explanation (Staw et al., 1981). Under conditions of low perceived environmental dynamism H2a remains robust, but the negative relation hypothesized in H2b becomes statistically sig-nificant. This significant negative relation implies that when firms are underperforming under conditions of low perceived environmental dynamism, CEO external advice-seeking will be on the low side but not necessarily absent. We thank an anonymous reviewer for highlighting this thought-provoking possibility.

References

Abdi, M., & Aulakh, P. (2012). Do country-level institutional frameworks and interfirm governance arrange-ments substitute or complement in international business relationships? Journal of International Business Studies, 43, 477–497.

Aguilar, F. (1967). Scanning the business environment. New York, NY: Macmillan.



Heyden et al. 1349

Ainsworth, S., & Cox, J. W. (2003). Families divided: Culture and control in small family business. Organization Studies, 24, 1463–1485.

Akbar, H. (2003). Knowledge levels and their transformation: Toward the integration of knowledge creation and individual learning. Journal of Management Studies, 40, 1997–2021.

Aldrich, H. E. (1979) Organizations and environments. Englewood Cliffs, NJ: Prentice-Hall.Alexiev, A. S., Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2010). Top management team

advice seeking and exploratory innovation: The moderating role of TMT heterogeneity. Journal of Management Studies, 47, 1343–1364.

Amason, A. C. (1996). Distinguishing the effects of functional and dysfunctional conflict on strategic deci-sion making: Resolving a paradox for top management teams. Academy of Management Journal, 39, 123–148.

Ansoff, H. I. (1975). Managing strategic surprise by response to weak signals. California Management Review, 18, 21–33.

Ansoff, H. I. (1980). Strategic issue management. Strategic Management Journal, 1, 131–148.Arendt, L. A., Priem, R. L., & Ndofor, H. A. (2005). A CEO-adviser model of strategic decision making.

Journal of Management, 31, 680–699.Argote, L., & Greve, H. R. (2007). A behavioral theory of the firm – 40 years and counting: Introduction and

impact. Organization Science, 18, 337–349.Argyris, C. (1976). Single-loop and double-loop models in research on decision making. Administrative

Science Quarterly, 21, 363–375.Auster, E., & Choo, C. W. (1993). Environmental scanning by CEOs in two Canadian industries. Journal of

the American Society for Information Science, 44, 194–203.Autio, E., Sapienza, H. J., & Almeida, J. (2000). Effects of age at entry, knowledge intensity, and imitability

on international growth. Academy of Management Journal, 43, 909–924.Bagozzi, R. P., & Foxall, G. R. (1996). Construct validation of a measure of adaptive-innovative cognitive

styles in consumption. International Journal of Research in Marketing, 13, 201–213.Bagozzi, R. P., & Heatherton, T. F. (1994). A general approach for representing multifaceted personality

constructs: Application to state self-esteem. Structural Equation Modeling, 1, 35–67.Bantel, K., & Jackson, S. (1989). Top management and innovations in banking: Does the composition of the

top team make a difference? Strategic Management Journal, 10, 107–124.Baum, J. R., & Wally, S. (2003). Strategic decision speed and firm performance. Strategic Management

Journal, 24, 1107–1129.Beck, N., & Kieser, A. (2003). The complexity of rule systems, experience, and organizational learning.

Organization Studies, 24, 793–814.Bergh, D. D., & Gibbons, P. (2011). The stock market reaction to the hiring of management consultants: A

signaling theory approach. Journal of Management Studies, 48, 544–567.Bettis, R. A., & Prahalad, C. K. (1995). The dominant logic: retrospective and extension. Strategic

Management Journal, 16, 5–14.Bonaccio, S., & Dalal, R. S. (2006). Advice taking and decision-making: An integrative literature review, and

implications for the organizational sciences. Organizational Behavior and Human Decision Processes, 101, 127–151.

Bonaccio, S., & Dalal, R. (2010). Evaluating advisors: A policy-capturing study under conditions of complete and missing information. Journal of Behavioral Decision Making, 23, 227–249.

Boot, A. W. A., Milbourn, T. T., & Thakor, A. V. (2005). Sunflower management and capital budgeting. Journal of Business, 78, 501–527.

Bourgeois, L. J. III. (1981). On the measurement of organizational slack. Academy of Management Review, 6, 29–39.

Bourgeois, L. J. III, & Eisenhardt, K. M. (1988). Strategic decision processes in high velocity environments: Four cases in the microcomputer industry. Management Science, 34(7), 816–835.

Boyd, K. B., & Fulk, J. (1996). Executive scanning and perceived uncertainty: A multidimensional model. Journal of Management, 22, 1–21.




Brockner, J., Nathanson, S., Friend, A., Harbeck, J., Samuelson, C., & Houser, R. (1984). The role of modeling processes in the “knee deep in the big muddy” phenomenon. Organizational Behavior and Human Performance, 33, 77–99.

Brousseau, K., Driver, M., Hourihan, G., & Larsson, R. (2006). The seasoned executive’s decision-making style. Harvard Business Review, 87, 1–10.

Budescu, D. V., & Rantilla, A. K. (2000). Confidence in aggregation of expert opinions. Acta Psychologica, 104, 371–398.

Buyl, T., Boone, C., Hendriks, W., & Matthyssens, P. (2011). Top management team functional diversity and firm performance: The moderating role of CEO characteristics. Journal of Management Studies, 48, 151–177.

Campion, M. A., Medsker, G. J., & Higgs, A. C. (1993). Relations between work group characteristics and effectiveness: Implications for designing effective work groups. Personnel Psychology, 46, 823–847.

Carpenter, M. A., Geletkanycz, M. A., & Sanders, W. G. (2004). Upper echelons research revisited: Antecedents, elements, and consequences of top management team composition. Journal of Management, 30, 749–777.

Cashen, L. H., & Geiger, S. W. (2004). Statistical power and the testing of null hypotheses: A review of contemporary management research and recommendations for future studies. Organizational Research Methods, 7, 151–167.

Certo, T. S., Lester, R. H., Dalton, C. M., & Dalton, D. R. (2006). Top management teams, strategy and finan-cial performance: a meta-analytical examination. Journal of Management Studies, 43, 813–839.

Chenhall, R. H. (2003). Management control systems design within its organizational context: Findings from contingency-based research and directions for the future. Accounting, Organizations and Society, 28, 127–168.

Child, J. (1972). Organization structure, environment and performance: The role of strategic choice. Sociology, 6, 1–22.

Cho, T. S., & Hambrick, D. C. (2006). Attention as the mediator between top management team characteristics and strategic change: The case of airline deregulation. Organization Science, 17, 453–469.

Choi, J. N., & Kim, M. U. (1999). The organizational application of groupthink and its limitations in organiza-tions. Journal of Applied Psychology, 84, 297–306.

Clapham, S., & Schwenk, C. R. (1991). Self-serving attributions, managerial cognition, and company performance. Strategic Management Journal, 12, 219–229.

Cohen, J. (1992). A power primer. Quantitative Methods in Psychology, 122, 155–159.Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innova-

tion. Administrative Science Quarterly, 35, 128–152.Collins, E. C., Percy, E. J., Smith, E. R., & Kruschke, J. K. (2011). Integrating advice and experience: Learning

and decision making with social and nonsocial cues. Journal of Personality and Social Psychology, 100, 967–982.

Cycyota, C. S., & Harrison, D. A. (2006). What (not) to expect when surveying executives: A meta-analysis of top manager response rates and techniques over time. Organizational Research Methods, 9, 133–160.

Cyert, R. N., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ: Prentice-Hall.De Alwis, G., Majid, S., & Chaudhry, A. S. (2006). Transformation in managers’ information seeking

behavior: A review of the literature. Journal of Information Science, 32, 362–385.Denis, D. J., & Serrano, J. M. (1996). Active investors and management turnover following unsuccessful

control contests. Journal of Financial Economics, 40, 239–266.Dess, G. G., & Beard, D. W. (1984). Dimensions of organizational task environments. Administrative Science

Quarterly, 29, 52–73.DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective

rationality in organizational fields. American Sociological Review, 48, 147–160.Dutton, J. E., & Jackson, S. E. (1987). Categorizing strategic issues: Links to organizational action. Academy

of Management Review, 12, 76–90.Eisenhardt, K. M., & Bourgeois, L. J. III. (1988). Politics of strategic decision making in high-velocity envi-

ronments: Toward a midrange theory. Academy of Management Journal, 31, 737–770.



Heyden et al. 1351

Fee, C. E., & Hadlock, C. J. (2004). Management turnover across the corporate hierarchy. Journal of Accounting and Economics, 37, 3–38.

Finkelstein, S., & Hambrick, D. C. (1990). Top management team tenure and organizational outcomes: The moderating role of managerial discretion. Administrative Science Quarterly, 35, 484–503.

Finkelstein, S., Hambrick, D. C., & Cannella, A. A. (2009). Strategic leadership: Theory and research on executives, top management teams, and boards. Oxford: Oxford University Press.

Forbes, D. P. (2007). Reconsidering the strategic implications of decision comprehensiveness. Academy of Management Review, 32, 361–376.

Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.

Fredrickson, J. W., & Mitchell, T. R. (1984). Strategic decision processes: Comprehensiveness and perfor-mance in an industry with an unstable environment. Academy of Management Journal, 27, 399–423.

Galaskiewicz, H., & Wasserman, S. (1989). Mimetic processes within an interorganizational field: An empirical test. Administrative Science Quarterly, 34, 454–479.

Garg, V. K., Walters, B. A., & Priem, R. L. (2003). Chief executive scanning emphases, environmental dynamism, and manufacturing firm performance. Strategic Management Journal, 24, 725–744.

Geletkanycz, M. A., & Hambrick, D. C. (1997). The external ties of top executives: Implications for strategic choice and performance. Administrative Science Quarterly, 42, 654–681.

Ghoshal, S. (1988). Environmental scanning in Korean firms: Organizational isomorphism in action. Journal of International Business Studies, 19, 69–86.

Gibbons, R., & Murphy, K. (1992). Optimal incentive contracts in the presence of career concerns: Theory and evidence. Journal of Political Economy, 100, 468–501.

Gino, F. (2008). Do we listen to advice just because we paid for it? The impact of advice cost on its use. Organizational Behavior and Human Decision Processes, 107, 234–245.

Gino, F., Brooks, A. W., & Schweitzer, M. E. (2012). Anxiety, advice, and the ability to discern: Feeling anxious motivates individuals to seek and use advice. Journal of Personality and Social Psychology, 102, 497–512.

Gino, F., & Moore, D. A. (2007). Effects of task difficulty on use of advice. Journal of Behavioral Decision Making, 20, 21–35.

Gino, F., Shang, J., & Croson, R. (2009). The impact of information from similar or different advisors on judgment. Organizational Behavior and Human Decision Processes, 108, 287–302.

Glückler, J., & Armbrüster, T. (2003). Networked reputation bridging uncertainty in management consulting: The mechanisms of trust and networked reputation. Organization Studies, 24, 269–297.

Goldsmith, D. J., & Fitch, K. (1997). The normative context of advice as social support. Human Communication Research, 23, 454–476.

Goll, I., & Rasheed, A. M. A. (2005). The relationships between top management demographic characteris-tics, rational decision making, environmental munificence, and firm performance. Organization Studies, 26, 999–1023.

Greve, H. R. (1998). Performance, aspirations, and risky organizational change. Administrative Science Quarterly, 44, 58–86.

Greve, H. R. (2010). Positional rigidity: low performance and resource acquisition in large and small firms. Strategic Management Journal, 32, 103–114.

Grimpe, C., & Kaiser, U. (2010). Balancing internal and external knowledge acquisition: the gains and pains from R&D outsourcing. Journal of Management Studies, 47, 1483–509.

Haas, M. R., & Hansen, M. T. (2007). Different knowledge, different benefits: toward a productivity perspec-tive on knowledge sharing in organizations, Strategic Management Journal, 28, 1133–1153.

Hair, J. F. Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Upper Saddle River, NJ: Prentice Hall.

Hambrick, D. C. (1995). Fragmentation and the other problems CEOs have with their top management teams. California Management Review, 37, 110–127.

Hambrick, D. C. (2007). Upper echelons theory: An update. Academy of Management Review, 32, 334–343.




Hambrick, D. C., Cho, T. S., & Chen, M. J. (1996). The influence of top management team heterogeneity on firms’ competitive moves. Administrative Science Quarterly, 41, 659–684.

Hambrick, D. C., Geletkanycz, M. A., & Fredrickson, J. W. (1993). Top executive commitment to the status quo: Some tests of its determinants. Strategic Management Journal, 14, 401–418.

Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organizations as a reflection of its top managers. Academy Management Review, 9, 193–206.

Harvey, N., & Fischer, I. (1997). Taking advice: Accepting help, improving judgment, and sharing responsi-bility. Organizational Behavior and Human Decision Processes, 70, 117–133.

Harvey, N., Harries, C., & Fischer, I. (2000). Using advice and assessing its quality. Organizational Behavior and Human Decision Processes, 81, 252–273.

Heavey, C., Mowday, R. T., Kelly, A., & Roche, F. (2009a). Reconceptualizing executive environmental scanning and search: Implications for international leadership research and practice. In W. H. Mobley, Y. Wang, & M. Li (Eds.), Advances in global leadership, Vol. 5 (pp. 65–92). Bingley: Emerald Group Publishing Limited.

Heavey, C., Simsek, Z., Roche, F., & Kelly, A. (2009b). Decision comprehensiveness and corporate entre-preneurship: The moderating role of managerial uncertainty preferences and environmental dynamism. Journal of Management Studies, 46, 1289–1314.

Hodgkinson, G. P., & Wright, G. (2002). Confronting strategic inertia in a top management team: Learning from failure. Organization Studies, 23, 949–977.

Holmqvist, M. (2003). A dynamic model of intra- and interorganizational learning. Organization Studies, 24, 95–123.Huber, G. (1991). Organizational learning: The contributing processes and the literatures. Organization

Science, 2, 88–115.Inkpen, A. C., & Tsang, E. W. K. (2005). Social capital, networks and knowledge transfer. Academy of

Management Review, 30, 146–165.Isenberg, D. J. (1986). Thinking and managing: A verbal protocol analysis of managerial problem solving.

Academy of Management Journal, 29, 775–788.James, L. R., Demaree, R. G., & Wolf, G. (1993). Rwg: An assessment of within-group interrater agreement.

Journal of Applied Psychology, 78, 306–309.Janis, I. L. (1982). Groupthink: Psychological studies of policy decisions and fiascoes. Boston, MA: Houghton

Mifflin.Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2006). Exploratory innovation, exploitative

innovation and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52, 1661–1674.

Jones, A. P., Johnson, L. A., Butler, M. C., & Main, D. S. (1983). Apples and oranges: An empirical comparison of commonly used indices of interrater agreement. Academy of Management Journal, 26, 507–519.

Jones, C. D., & Cannella, A. A. (2011). Alternate configurations in configurations in strategic decision making. In M. A. Carpenter (Ed.), The handbook of research on top management teams (pp. 15–34). Cheltenham: Edward Elgar.

Jöreskog, K. G., & Sörbom, D. (1984). LISREL VI user’s guide (3rd ed.). Mooresville, IN: Scientific Software.Keegan, W. J. (1974). Multinational scanning: A study of the information sources utilized by headquarters

executives in multinational companies. Administrative Science Quarterly, 9, 411–421.Kets de Vries, M. F. R. (1989). Leaders who self-destruct: The causes and cures. Organizational Dynamics,

17, 4–17.Kisfalvi, V. (2000). The threat of failure, the perils of success and CEO character: Sources of strategic persis-

tence. Organization Studies, 21, 611–639.Knight, D., Pearce, C. L., Smith, K. G., Olian, J. D., Sims, H. P., & Smith, K. A. (1999). Top management

team diversity, group process, and strategic consensus. Strategic Management Journal, 20, 445–465.Ko, D.-G., Kirsch, L. J., & King, W. R. (2005). Antecedents of knowledge transfer from consultants to clients

in enterprise system implementations. MIS Quarterly, 29, 59–85.Kyriakopoulos, K. (2011). Improvisation in product innovation: The contingent role of market information

sources and memory Types. Organization Studies, 32, 1051–1078.



Heyden et al. 1353

Larsson, E., Hedelin, L., & Garlin, T. (2003). Influence of expert advice on expansion goals of small businesses in rural Sweden. Journal of Small Business Management, 41, 205–212.

Lawrence, P. R., & Lorsch, J. W. (1967). Differentiation and integration in complex organizations. Administrative Science Quarterly, 12, 1–47.

Lee, J., & Miller, D. (1996). Strategy, environment and performance in two technological contexts: Contingency theory in Korea. Organization Studies, 17, 729–750.

Lewin, A. Y., & Stephens, C. U. (1994). CEO attitudes as determinants of organization design: An integrated model. Organization Studies, 15, 183–212.

MacDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7, 64–82.

Maurer, I., Bartsch, V., & Ebers, M. (2011). The value of intra-organizational social capital: How it fosters knowledge transfer, innovation performance, and growth. Organization Studies, 32, 157–185.

Maurer, I., & Ebers, M. (2006). Dynamics of social capital and their performance implications: Lessons from biotechnology start-ups. Administrative Science Quarterly, 51, 262–292.

McDonald, I. M., Khanna, P., & Westphal, J. D. (2008). Getting them to think outside the circle: Corporate governance, CEO’s external advice networks, and firm performance. Academy of Management Journal, 51, 453–475.

McDonald, M. L., & Westphal, J. D. (2003). Getting by with the advice of their friends: CEOs’ advice net-works and firms’ strategic responses to poor performance. Administrative Science Quarterly, 48, 1–32.

Menon, T., & Pfeffer, J. (2003). Valuing internal vs. external knowledge: Explaining the preference for outsiders. Management Science, 49, 497–513.

Menon, T., Thompson, L., & Choi, H. S. (2006). Tainted knowledge vs. tempting knowledge: People avoid knowledge from internal rivals and seek knowledge from external rivals. Management Science, 52, 1129–1144.

Milliken, F.J. (1987). Three types of perceived uncertainty about the environment: State, effect, and response uncertainty. Academy of Management Review, 12, 133–143.

Mintzberg, H. (1973). The nature of managerial work, New York, NY: Harper & Row.Mintzberg, H., Raisinghani, D., & Theoret, A. (1976). The structure of unstructured decision processes.

Administrative Science Quarterly, 21, 246–275.Mitchell, R.J., Shepherd, D.A., & Sharfman, M.P. (2011). Erratic strategic decisions: When and why manag-

ers are inconsistent in strategic decision making. Strategic Management Journal, 38, 683–704.Mooney, A. C., & Amason, A. C. (2011). In search of the CEOs inner circle and how it is formed. In M. A.

Carpenter (Ed.), The handbook of research on top management teams (pp. 35–48). Cheltenham: Edward Elgar.

Mooney, A. C., Holahan, P. J., & Amason, A. C. (2007). Don’t take it personally: Exploring cognitive conflict as a mediator of affective conflict. Journal of Management Studies, 44, 733–758.

Mueller, G. C., Mone, M. A., & Barker, V. L. III (2007). Formal strategic analyses and organizational performance: Decomposing the rational model. Organization Studies, 28, 863–883.

Nag, R., & Gioia, D. A. (2012). From common to uncommon knowledge: Foundations of firm-specific use of knowledge as a resource. Academy of Management Journal, 55, 421–457.

Nebus, J. (2006). Building collegial information networks: A theory of advice network generation. Academy of Management Review, 31, 615–637.

Nielsen, S. (2010). Top management team diversity: A review of theories and methodologies. International Journal of Management Reviews, 12, 301–316.

Onkal, D., Goodwin, P., Thomson, M., Gonul, S., & Pollock, A. (2009). The relative influence of advice from human experts and statistical methods on forecast adjustments. Journal of Behavioral Decision Making, 22, 390–409.

Papadakis, V. M., & Barwise, P. (2002). How much do CEOs and top managers matter in strategic decision-making? British Journal of Management, 13, 83–95.

Park, S. H., Westphal, J. D., & Stern, I. (2011). Set up for a fall: The insidious effects of flattery and opinion conformity toward corporate leaders. Administrative Science Quarterly, 55, 257–302.




Park, W. W. (1990). A review of research on groupthink. Journal of Behavioral Decision Making, 3, 229–245.

Peterson, R. S., Owens, P. D., Tetlock, P. E., Fan, E. T., & Martorana, P. (1998). Group dynamics in top management teams: Groupthink, vigilance, and alternative models of organizational failure and success. Organizational Behavior and Human Decision Processes, 73, 272–305.

Pettigrew, A. M. (1992). On studying managerial elites. Strategic Management Journal, 13, 163–182.Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in

behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879–903.

Pogrebna, G. (2008). Naïve advice when half a million is at stake. Economics Letters, 98, 148–154.Post, T., Van den Assem, M. J., Baltussen, G., & Thaler, R. H. (2008). Deal or no deal? Decision making

under risk in a large-payoff game show. American Economic Review, 98, 38–71.Raes, A. M. L., Heijltjes, M. G., Glunk, U., & Roe, R. A. (2011). The interface of the top management team

and middle managers: A process model. Academy of Management Review, 36, 102–126.Regnér, P. (2001). Complexity and multiple rationalities in strategy processes. In T. Elfring, & H. W. Volberda

(Eds.), Rethinking strategy (pp. 43–56). London: Sage.Reinhardt, W. A. (1984). An early warning system for strategic planning. Long Range Planning, 17,

25–34.Roberto, M. A. (2003). The stable core and dynamic periphery in top management teams. Management

Decision, 41, 120–131.Robson, P. J. A., & Bennet, R. J. (2000). SME growth: The relationship with business advice and external

collaboration. Small Business Economics, 15, 193–208.Sacchi, S., & Burigo, M. (2008). Strategies in the information search process: Interaction among task

structure, knowledge, and source. Journal of General Psychology, 135, 252–270.Saunder, C., & Jones, J. W. (1990). Temporal sequences in information acquisition for decision making: A

focus on source and medium. Academy of Management Review, 15, 29–46.Schneider, S. L. (1992). Framing and conflict: Aspiration level contingency, the status quo, and current

theories of risky choice. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 1040–1057.

Schotter, A. (2003). Decision-making with naïve advice. American Economic Review, 93, 196–201.Schrah, G. E., Dalal, R. S., & Sniezek, J. A. (2006). No decision maker is an island: Integrating expert advice

with information acquisition. Journal of Behavioral Decision Making, 19, 43–60.Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making. Journal of

Consumer Psychology, 14, 332–348.Sharma, S. (2000). Managerial interpretations and organizational context as predictors of corporate choice of

environmental strategy. Academy of Management Journal, 43, 681–697.Shen, W., & Cannella Jr., A. A. (2002). Revisiting the performance consequences of CEO succession: The

impacts of successor type, postsuccession senior executive turnover, and departing CEO tenure. Academy of Management Journal, 45, 717–733.

Simons, T., Pelled, L. H., & Smith, K. A. (1999). Making use of difference: Diversity, debate, and decision comprehensiveness in top management teams. Academy of Management Journal, 42, 662–673.

Simsek, Z. (2007). CEO tenure and organizational performance: An intervening model. Strategic Management Journal, 28, 653–662.

Sniezek, J. A., Schrah, G. E., & Dalal, R. S. (2004). Improving judgment with prepaid expert advice. Journal of Behavioral Decision Making, 17, 173–190.

Spender, J.-C. (1996). Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, 17, 45–62.

Staber, U. (2010). Imitation without interaction: How firms identify with clusters. Organization Studies, 31, 153–174.

Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: Biased informa-tion sampling during discussion. Journal of Personality and Social Psychology, 48, 1448–1467.



Heyden et al. 1355

Stasser, G., & Titus, W. (1987). Effects of information load and percentage of shared information on the dissemination of unshared information during group discussion. Journal of Personality and Social Psychology, 53, 53–81.

Staw, B. M., Sandelands, L. E., & Dutton, E. (1981). Threat-rigidity effects in organizational behavior: A multilevel analysis. Administrative Science Quarterly, 26, 501–524.

Szulanski, G., Cappetta, R., & Jensen, R. J. (2004). When and how trustworthiness matters: Knowledge trans-fer and moderating effect of causal ambiguity. Organization Science, 15, 600–613.

Tichy, N. M., & Bennis, W. G. (2007). Making judgment calls. Harvard Business Review, 85, 94–102.Tinsley, C. (1998). Models of conflict resolution in Japanese, German and American cultures. Journal of

Applied Science, 83, 316–323.Tsai, W. (2002). Social structure of competition within a multiunit organization: Coordination, competition

and intraorganizational knowledge sharing. Organization Science, 13, 179–190.Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy of

Management Journal, 41, 464–476.Van Knippenberg, D., De Dreu, C. K., & Homan, A. C. (2004). Work group diversity and group performance:

An integrative model and research agenda. Journal of applied Psychology, 89, 1008–1022.Van Swol, L. M., & Ludutsky, C. (2007). Tell me something I don’t know: Decision makers’ preference for

advisors with unshared information. Communication Research, 34, 297–312.Van Swol, L. M., & Sniezek, J. A. (2005). Factors affecting the acceptance of expert advice. British Journal

of Social Psychology, 44, 443–461.Vissa, B., & Chacar, A. S. (2009). Leveraging ties: The contingent value of entrepreneurial teams’ external

advice networks on Indian software venture performance. Strategic Management Journal, 30, 1179–1191.Vissa, B., Greve, H. R., & Chen, W. R. (2010). Business group affiliation and firm search behavior in India:

Responsiveness and focus of attention. Organization Science, 21, 696–712.Walton, R. E., & Dutton, J. M. (1969). The management of interdepartmental conflict: A model and review.

Administrative Science Quarterly, 14, 73–84.Westphal, J. D., & Bednar, M. K. (2005). Pluralistic ignorance in corporate boards and firms’ strategic persis-

tence in response to low firm performance. Administrative Science Quarterly, 50, 262–298.Wiesenfeld, B. M., Wurthmann, K., & Hambrick, D. C. (2008). The stigmatization and devaluation of elites

associated with corporate failures: A process model. Academy of Management Review, 33, 231–251.Wolfram, J. R., Mann, L., & Samson, D. (1997). Benchmarking as a mixed metaphor: Disentangling assump-

tions of competition and collaboration. Journal of Management Studies, 34, 285–315.Yaniv, I. (2004). Receiving other people’s advice: Influence and benefit. Organizational Behavior and

Human Decision Processes, 93, 1–13.Yaniv, I., & Kleinberger, E. (2000). Advice taking in decision making: Egocentric discounting and reputation

formation. Organizational Behavior and Human Decision Processes, 83, 260–281.Yasai-Ardekani, M., & Nystrom, P. C. (1996). Designs for environmental scanning systems: Tests of a con-

tingency theory. Management Science, 42, 187–204.Zaheer, A., McEvily, B., & Perrone, V. (1998). Does trust matter? Exploring the effects of interorganizational

and interpersonal trust on performance. Organization Science, 9, 1–20.

Author biographies

Mariano L. M. Heyden is Assistant Professor of Strategy and Business Policy at the Newcastle Business School, Australia. He obtained his PhD from the Rotterdam School of Management, Erasmus University in the Netherlands. His current research focuses on cognitive, social, and behavioral influences of upper and middle echelons on strategic renewal.

Sebastiaan van Doorn is Assistant Professor of Strategic Entrepreneurship at the Warwick Business School in the UK. He obtained his PhD from the Rotterdam School of Management, Erasmus University, in the Netherlands. Prior to joining Warwick University he was Visiting Professor at Singapore Management




University. His current research interests include corporate entrepreneurship, upper echelons and middle management, social capital, and the attention based view.

Marko Reimer is Assistant Professor at the Institute of Management Accounting and Control at WHU Otto Beisheim School of Management in Germany. He obtained his PhD from the TU Berlin in Germany. His current research interests include top management impact on management control systems from an upper echelons perspective.

Frans A. J. Van Den Bosch is Emeritus Professor of Management of Organization-Environment Interfaces at the Rotterdam School of Management, Erasmus University, in the Netherlands. He received his PhD from Leiden University in the Netherlands. His current research interests include managerial and knowledge-based theories of the firm, strategic renewal, co-evolutionary theory building, corporate governance, and corporate responsiveness.

Henk W. Volberda is Professor of Strategic Management and Business Policy at the Rotterdam School of Management, Erasmus University, in the Netherlands. He obtained his PhD from the University of Groningen in the Netherlands. His research focuses on strategic renewal and innovation, strategic flexibil-ity, hypercompetition and new organizational forms, coevolution of firms and industries, and knowledge flows and absorptive capacity.



Documents

Perceived Environmental Dynamism, Relative Competitive Performance, and Top Management Team Heterogeneity: Examining Correlates of Upper Echelons' Advice-Seeking