Strategic decision making – Special Issue: Yearly Review of Management
Charles R. Schwenk
This article deals with research on strategic decision making and the factors that affect it. Much of this research is a subset of strategic process research which was the subject of an earlier review in this journal (Huff & Reger, 1987).
Most scholars in strategic management are familiar with the distinction between “content” research which deals with the content of strategies and “process” research which examines the strategic decision process and the factors that affect it. Content research has been quite useful in providing rules and guidelines on the types of strategies which lead to the best performance for different types of organizations in different competitive conditions. In the current turbulent business environment, however, some of these generalizations are becoming less useful. Consider, for example, Porter’s (1980) discussion of the three generic strategies of cost leadership, differentiation, and focus and the importance of not attempting to pursue more than one generic strategy at once. Due to the use of flexible manufacturing and other manufacturing innovations some companies have found that it is possible to pursue a low cost and a differentiation strategy simultaneously. The recent book Reengeneering the Corporation (Hammer & Champy, 1993) discuss the need for reexamining old generalizations and assumptions in this way:
Business reengineering means putting aside much of the received wisdom of two hundred years of industrial management. It means forgetting how work was done in the age of the mass market and deciding how it can best be done now. . . . At the heart of business reengineering lies the notion of discontinuous thinking – identifying and abandoning the outdated rules and fundamental assumptions that underlie current business operations (Hammer & Champy, 1993, pp. 2-3).
Admittedly, this advice may be overstated and is easier to give than to follow. If, however, we wish to study strategic management in an era when some of the old rules regarding strategy content are no longer valid, how do we go about it? One possibility is to study the way executives conceptualize strategic problems, the way they develop their own rules and guidelines, the personal and organizational characteristics that influence this process, and the ways these rules influence their own decision making. This is the focus of the work that has come to be called the cognitive perspective in strategic management and strategic decision making.
The conceptual roots of this work go back to the work of Simon on “bounded rationality”. March and Simon (1958) state:
Because of the limits of human intellective capacities in comparison with the complexities of the problems that individuals and organizations face, rational behavior calls for simplified models that capture the main features of a problem without capturing all its complexities (p. 169).
Before beginning the review of past research in this general area, it is appropriate to define it more precisely. A prior review of strategic process research by Huff and Reger (1987) in this journal was consulted to aid in this definition. They identified nine basic topics under the heading of strategic process research. These were divided into topics dealing with formulation and those dealing with implementation. Under formulation, they identified four topics including planning prescriptions, decision aids, planning practices, and agendas and attention. Under implementation they also identified four topics including systematic implementation, evolutionary prescriptions, structure-systems & outcomes, and contextual influences. Finally, they identified a ninth topic which they called integrative research.
This present review will cover a more narrow domain than that of Huff and Reger. Strategy implementation will not be specifically covered. Further, the topic areas around which the discussion will be organized are different than those identified by Huff and Reger. In preparing this paper, I reviewed all issues of the major journals which publish work on strategic decision making since 1987. These journals include Academy of Management Journal, Academy of Management Review, Administrative Science Quarterly, Journal of Management, Journal of Management Studies, and Strategic Management Journal. Some additional articles and books will also be discussed where appropriate. The resulting list of topics is not the only way this past research can be clustered. Nor do I claim that the list is exhaustive. I do feel, however, that these categories provide a useful way of summarizing the major themes of recent research in this field. Once I have reviewed research on the traditional topics I will discuss several emerging areas of research which might help in redirecting or enhancing research on these topics.
Streams of Research Related to Strategic Decision Making
Several major areas of research will be discussed in the next sections of this paper. These include (1) Strategic Decision Models and Characteristics, (2) Biases in Strategic Decision Making, (3) Individual and Organizational Minds, and (4) Upper Echelons (CEOs, Top Management Teams, and Boards of Directors). These topics are logically connected in the study of strategic decision making. In explaining these connections, I will begin with the characteristics of upper echelons. As Hambrick and Mason (1984) noted, the observable characteristics of upper echelons influence the ways these individuals view their business and its environment. The individual and collective views of upper echelons (dominant logic or knowledge structures) may then introduce biases into the decision process. These, in turn, influence the characteristics of the strategic decision process itself.
The following sections of the article deal with the status of current research related to each of these aspects of strategic decision making, beginning with strategic decision models and characteristics because an understanding of this topic will provide a framework for examining the other areas to be covered. I will then discuss some important new developments in strategic decision research under the headings of information technology and strategic decision making, competitive strategic decision making, and international strategic decision making.
Strategic Decision Models and Characteristics
For the past few decades, researchers have attempted to model the strategic decision process and identify the major types or categories of strategic decisions. This is a difficult task since strategic decisions are often described as “unstructured”, “unprogrammed”, and “messy”. Mintzberg, Raisinghani, and Theoret (1976) provided an early attempt at modeling the process of strategic decision making and identified three major phases with subroutines or subphases within each. These included the following:
THE IDENTIFICATION PHASE
1. The Decision Recognition Routine: Opportunities, problems, and crises are recognized and evoke decisional activity.
2. The Diagnosis Routine: Information relevant to opportunities, problems, and crises is collected and problems are more clearly identified.
THE DEVELOPMENT PHASE
3. The Search Routine: Organizational decision makers go through a number of activities to generate alternative solutions to problems.
4. The Design Routine: Ready-made solutions which have been identified are modified to fit the particular problem or new solutions are designed.
THE SELECTION PHASE
5. The Screen Routine: This routine is activated when the search routine identifies more alternatives than can be intensively evaluated. Alternatives are quickly scanned and the most obviously infeasible are eliminated.
6. The Evaluation-Choice Routine: An alternative is chosen either through a process of analysis and judgment or a process of bargaining among decision makers.
7. The Authorization Routine: When the individual making the decision does not have the authority to commit the organization to a course of action, the decision must move up the organizational hierarchy until it reaches a level at which the necessary authority resides.
The model also includes interrupts and “recycles” by which decision makers may return to earlier phases as necessary (Mintzberg et al. 1976).
Researchers since Mintzberg et al. have focused on identifying and describing the major categories or types of strategic decision processes. In perhaps the most extensive study of strategic decision processes to date, Hickson, Butler, Cray, Mallory, and Wilson (1986) examined 150 decision processes in British organizations and developed a typology which included three basic types of processes; fluid, constricted, and sporadic. A fluid decision process is one that is steadily paced, formally channelled, and speedy. A constricted process is one that is narrowly channelled. It is moderately restricted in terms of the effort made to obtain information and in terms of the number of organizational members who participate in the decision. Finally, a sporadic process is one that is spasmodic, protracted, and contains many interrupts and recycles (pp. 114-124).
Hart (1992) synthesized earlier research on strategic decision models and developed his own integrative framework which included five styles of strategy making processes. The first Hart called the command mode, in which strategy is driven by the organization’s leader or by a small top management team. The second is the symbolic mode. In this mode, strategy is driven by the organization’s mission and vision of the future. The third is the rational mode, in which strategy is driven by formal structure and planning systems. In the fourth mode, the transactive mode, strategy formulation is driven by internal processes and mutual adjustment. Finally, in the fifth or generative mode, strategy is most strongly influenced by the initiative of organizational actors.
A topic which is closely related to strategic decision making is strategic issue diagnosis. Much of the work in this stream was conducted by Jane Dutton and her colleagues (Dutton & Ashford, 1993; Dutton & Duncan, 1987; Dutton, Fahey & Narayanan, 1983). Strategic issue diagnosis deals with the early phases of the strategic decision making process, including identification of issues and the assessment of the characteristics of issues. This process is obviously linked to the later stages of strategic decision making, selling issues to top management, and the creation of momentum for change.
While there has been a great deal of conceptual work done on strategic decision models, efforts to assess the validity of the models empirically is somewhat more rare. Hitt and Tyler (1991) examined the decision making behavior of executives to determine which of three decision making models, the rational-normative model, the external control model, or the strategic choice model received the greatest empirical support. Strong support was found for the rational-normative mode, an important and somewhat surprising finding since many decision theorists regard the rational-normative model as less valid than some of the more politically-oriented models.
At this point in time, a good deal of progress has been made in clarifying and differentiating alternative decision models. More empirical research of the type exemplified by Hitt and Tyler is now needed to test the predictions of alternative models.
The work previously cited deals with overall decision processes and styles. I will now discuss research on two specific process characteristics which differentiate strategic decisions. These are the level of rationality and the level of conflict and politics in the process.
Rationality and Incrementalism in Strategic Decision Models
Most strategic process typologies deal with the subject of decisional rationality or the extent to which decision makers follow a systematic process in reaching carefully thought-out goals. If the process is less systematic and goals evolve over time it is often called incremental. At one time there was a debate about whether the strategic decision process was rational or incremental. Since Quinn’s (1980) treatment of the topic of logical incrementalism, however, research and theory have focused on the ways logical and incremental process interact in strategic decision making. Johnson (1988) examined different definitions of incrementalism and used data from a longitudinal field study to demonstrate incremental processes in strategic change. Dean and Sharfman (1993) discussed what they called “procedural rationality” or the degree to which strategic decision processes are rational and orderly. Schoemaker (1993) showed the benefits of applying both rational and behavioral principles in explaining strategic decisions. Finally, Fredrickson and Iaquinto (1989) demonstrated evolutionary changes in the comprehensiveness of decision processes (one variable associated with rationality) which they called “creeping rationality”.
Conflict and Politics in Strategic Decision Making
One characteristic of strategic decision processes which has received a great deal of attention is the degree of conflict and political maneuvering present in the decision. Eisenhardt and Bourgeois (1988) differentiated between conflict and politics in the following way:
Politics are the observable, but often covert, actions by which executives enhance their power to influence a decision. These actions include behind-the-scenes coalition formation, offline lobbying and cooptation attempts, withholding information, and controlling agendas. Politics contrast with the straightforward influence tactics of open and forthright discussion, with full sharing of information, in settings open to all decision makers (pp. 737-738).
In a study of politics in eight firms in the microcomputer industry they found that politics tended to emerge when power was centralized and that the use of organizational politics was negatively related to organizational performance. In a later conceptual article, Eisenhardt suggested that agency theory might provide a framework within which to study conflict in strategic decision making (Eisenhardt, 1989).
According to Eisenhardt and Bourgeois’ definition of politics, open expression of conflict in the strategic decision process would not be considered politics and should be treated separately. The role of conflict in strategic decision making has been studied by a number of authors. One aspect of conflict is disagreement on the goals of an enterprise and the means for reaching those goals. Dess and Origer (1987) summarize a number of studies which reached conflicting conclusions about the relationship between disagreement on goals and means for achieving those goals among top management and organizational performance. Some studies have shown a positive relationship while others have shown a negative relationship. Schwenk and Cosier (1993) suggested that the lack of consistent results in these studies may be due to the fact that disagreement must be expressed in a productive way in strategic decision making in order for it to have positive effects on organizational performance. Techniques for introducing conflict into strategic decision making like devil’s advocacy and dialectical inquiry have been studied as ways of improving decision making performance (Schweiger, Sandberg & Ragan, 1986; Schwenk, 1982, 1984a, 1984b). In a meta-analysis of past research Schwenk (1990) showed that past studies supported the value of devil’s advocacy as a way of introducing conflict into decision making and improving decision making performance.
The body of literature I have just reviewed deals with how strategic decisions are made. The next topic is closely related since it deals with the biases which may reduce the quality of strategic decisions.
Biases in Strategic Decision Making
The decisional biases I will cover were first systematically studied by cognitive psychologists (Tversky & Kahneman, 1973). The following discussion incorporates a number of topics that might not traditionally be included under the strict definition of biases (e.g., heuristics, escalating commitment, and self-serving attribution patterns) but which affect strategic decisions in ways similar to the traditionally identified biases.
In an earlier paper (Schwenk, 1984c), I identified a number of biases which I felt might affect strategic decision making and in a separate paper (Schwenk, 1986) I outlined one model of the way these biases might interact in an organizational context. Since that time, there have been a number of conceptual and empirical pieces and studies which have extended these ideas (Bateman & Zeithaml, 1989a, 1989b; Bukszar & Connolly, 1988; Clapham & Schwenk, 1991; Golden, 1992; Lyles & Thomas, 1988; Walsh, 1988; Zajac & Bazerman, 1991). These can be divided into a number of major themes including biases in causal attributions (Clapham & Schwenk, 1991; Huff & Schwenk, 1990; Lant, Milliken & Batra, 1992; Salancik & Meindl, 1984; Staw, McKechnie & Puffer, 1983), escalating commitment (called strategic persistence in the strategy literature) (Bateman & Zeithaml, 1989a, 1989b; Duhaime & Schwenk, 1985; Finkelstein & Hambrick, 1990; Hambrick, Geletkanycz & Fredrickson, 1993; Lant et al., 1992; Miller, 1991; Milliken & Lant, 1991; Schwenk, 1986; Schwenk & Tang, 1989), and biases in recollection, which have implications for the modeling of strategic decision processes (Golden, 1992; Huber & Power, 1986; Schwenk, 1985).
A persistent bias in causal attribution has been identified by those studying this topic. In discussing past performance, executives tend to attribute good outcomes to their own actions and qualities while attributing poor outcomes to external factors such as environmental events and bad luck. Researchers disagree about the reasons for this attributional bias and the relationship between this bias and decision making and company performance. Salancik and Meindl (1984) have argued that such biased attributions are used deliberately as part of a strategy for managing the perceptions of shareholders and other stakeholders in the company and encouraging an “illusion of management control”, the illusion that management is in control of outcomes for the firm. Clapham and Schwenk (1991) and Huff and Schwenk (1990), on the other hand, view these biased attributions as part of executives’ attempts to make sense of the changing environment in which they operate. In this view, these attributions are not merely an attempt to influence the beliefs of stakeholders. They represent the beliefs of the executives who make them.
Escalating commitment is a tendency to increase commitment to a failing course of action. A number of strategy researchers have become interested in escalating commitment because of the obvious importance of this phenomenon in understanding organizational and strategic failure. Duhaime and Schwenk (1985) and Schwenk (1984c, 1986) discussed the ways escalating commitment may affect strategic decisions. Bateman and Zeithaml (1989a), in a laboratory experiment, showed that failure feedback on a previous decision, coupled with a positive decision frame and low perceived organizational slack lead to the strongest escalation of financial commitment to a course of action.
Both Finkelstein and Hambrick (1990) and Miller (1991) showed that executives with longer tenure in their companies were more likely to be committed to the status quo and to persist in strategies which they were already pursuing. Hambrick et al. (1993) confirmed this finding but showed that the effects for tenure in an industry were stronger than the effects for tenure in a company. Since tenure with an industry and with a company tend to be correlated, this suggests that the effects found for company tenure in earlier studies may have actually been effects for industry tenure. They also showed that commitment to the status quo was higher in companies with better past performance and that commitment to the status quo was higher in companies in which managers had higher discretion.
Biases in recollection may affect decision makers’ ability to learn from the past. Golden (1992) found evidence that executives’ recollections of their past strategies are often biased. Executives recall past strategies as being more rational and consistent with current strategies than they really were. This finding indirectly supports the contentions of Huber and Power (1985) and Schwenk (1985) regarding biases in executives’ reports of their past decisions. To the extent that executives’ memories of their past strategies are distorted, they will be unable to learn the appropriate lessons from past mistakes and will, as the cliche states, be destined to repeat them.
The next topic I will cover deals explicitly with the mental models from which strategic decisions emerge. These models have been discussed at both the individual and organizational levels.
Individual and Organizational Minds
Research on this topic deals with the attempt to represent the way executives understand strategic problems, competitive conditions, and the internal and external environments they face (Huff, 1990; Porac & Thomas, 1990; Voyer, 1993). Such analysis is often described in terms of cognitive maps and cognitive mapping even though the results are not always represented in terms of maps.
The work of Huff (1990) provides a good introduction to cognitive mapping and some of the areas to which it may be applied. An important first question regarding individual and organizational minds has to do with the nature of maps of minds and the purposes they are supposed to serve.
Huff (1990, pp. 14-42) suggests that there are at least five approaches to mapping managers’ minds. First, there are maps which assess attention, association, and the importance of concepts. Researchers working with written documents using this type of mapping would examine the frequency of use of words as a reflection of the importance of certain concepts to them. They would also look at clusters of words which indicate the importance of certain themes. Finally, they would look at changes in word use as a reflection of changing patterns of attention. Second, there are maps that show dimensions of categories and cognitive taxonomies. Maps of this type show hierarchical relationships between broad concepts and more specific subcategories. Third, there are maps that show influence, causality, and system dynamics. Such maps, often called causal maps, represent decision-makers’ beliefs about the ways some cognitive elements affect others. Fourth, some maps show the structure of arguments. The procedures for constructing these maps are influenced by the disciplines of philosophy, rhetoric, and speech communication. Finally, there are maps that specify schemas, cognitive frames, and perceptual codes. Such maps assess expectations and the complex hierarchical frameworks of which they are a part, using language as a sign of the underlying structure.
One important question in this area has to do with whether organizations have schemata or cognitive maps (or minds) as do individuals (Grant, 1988; Lyles & Schwenk, 1992; Prahalad & Bettis, 1986). Another has to do with changes in cognitive maps or schemata over time (Barr, Stimpert & Huff, 1992; Fahey & Narayanan, 1989; Narayanan & Fahey, 1990, Huff & Schwenk, 1990). Another deals with the study of strategists’ understanding of their competitors (Porac & Thomas, 1990; Porac, Thomas & Baden-Fuller, 1989; Reger & Huff, 1993).
Regarding the question of whether organizations have cognitive maps, Prahalad and Bettis suggest that companies’ strategic decisions are guided by a dominant management logic which is a shared understanding of the factors relevant to the business’s strategy and the relationship between these factors. They suggest that the dominant logic is a shared schema (a term generally used to describe individual-level cognitive structures) among the dominant coalition of a firm (Prahalad & Bettis, 1986, p. 491). They suggest that the breadth of the dominant logic sets upper limits on the diversity of technologies or markets that a firm can participate in. They do not, however, elaborate on the process by which individual-level cognitions are combined into organizational schemata.
Lyles and Schwenk (1992) elaborated on the processes by which individual level schemata are combined into organizational level knowledge structures and the processes by which knowledge structures change in response to environmental changes. They suggested that when environmental change invalidates existing assumptions organizational members articulate and advocate elements of the new knowledge structure. These are then combined through the activities of key decision makers (or the dominant coalition) into a new knowledge structure which is communicated to the other members of the organization.
A number of researchers have examined changes in cognitive maps over time. Huff and Schwenk (1990) documented changes in causal reasoning about performance (an element of cognitive maps) in auto and oil company executives as they attempted to formulate new understandings of their companies and environments in response to performance declines. Fahey and Narayanan (1989) and Narayanan and Fahey (1990) examined changes in cognitive maps and causal understandings over time within the television industry. Their work shows that causal mapping can be used as a research tool to help researchers understand how executives conceptualize change. Barr et al. (1992) examined changes in cognitive maps for a matched pair of railroad companies from 1949 to 1973 to assess patterns in managerial understanding during decline and renewal. They found that for corporate renewal it was important that managers recognize new conditions created by environmental change. It is even more important that they be able to link change in the environment to corporate strategy and modify that linkage over time.
Another line of research addresses the characteristics of those who formulate strategy. These studies have focused mainly on the CEO and other members of the top management team (TMT), though there has also been a good deal of research on boards of directors (see Daily & Schwenk, forthcoming, and Goodstein, Gautam & Boeker, 1994 for reviews). Because TMTs have been the subject of the greatest amount of recent research, I will focus on TMT research in my review.
Research on TMTs has generally dealt with the characteristics of these teams which are related to company performance and the factors which might moderate this relationship. Hambrick and Mason (1984) discussed some of the theoretical foundations of this research, identified TMT characteristics which might be examined in the future, and developed a set of propositions to guide future research. These propositions relate observable characteristics (such as age, functional tracks, education, socioeconomic roots, and financial position), to strategic choices (such as acquisition, diversification, innovation, and backward and forward integration), which are, in turn, related to performance.
Characteristics of TMTs which have been examined empirically include but are not limited to age, education, functional experience, tenure, and other work-related experience. Norburn (1986), for example, examined the characters of directors (similar to American CEOs) of Britain’s largest companies in three types of industries; those in growth (GOGOs), those in turbulence (YOYOs), and those in decline (DODOs). He found that directors of companies in declining industries were more likely to have production backgrounds, to be older, to be less likely to retire early, and to have come from different geographical locations than those in turbulent or growing industries. Directors in growth industries tended to be more international in orientation, to show more patronage influence, and to be paid more than those in declining or turbulent industries.
Researchers have also attempted to assess the relationship between heterogeneity of TMT characteristics and company performance. Priem (1989) explored the relationship between several types of TMT heterogeneity (e.g heterogeneity of age, education, tenure, and functional background) and company performance. He hypothesized that diversity is not beneficial and may actually be harmful to company performance in a stable industry. He argued that because the study was conducted in the relatively stable paints and allied products industry, diversity would generally be negatively related to performance. The small sample size of this study caused most of the correlations were to be insignificant; however, the majority of the correlations were positive, the opposite of what the author hypothesized. The results suggest that even in some stable industries TMT heterogeneity may be positively related to performance.
Bantel and Jackson (1989) assessed the relationship between TMT heterogeneity and innovation in a sample of banks. Examining several of the same types of heterogeneity studied by Priem, they found significant positive relationships between heterogeneity of functional backgrounds and innovation. They did not find significant relationships between innovation and heterogeneity of age, tenure or education.
Murray (1989) examined the degree of heterogeneity of TMTs of Fortune 500 companies in the oil and food industries on several dimensions and found that heterogeneity of characteristics like age and tenure was positively related to long term performance in oil companies.
Other research has examined the causes and consequences of TMT change and strategic change. Michel and Hambrick (1992), for example, demonstrated a relationship between TMT characteristics and companies’ approaches to diversification. Wiersema and Bantel (1992) showed that firms with TMTs that were younger, had higher team tenure, and had higher educational levels were more likely to change corporate strategy. Keck and Tushman (1993) found that long periods of stability in a firm’s environment are associated with longer team tenure and greater team homogeneity. Technological change, strategic reorientations, and environmental jolts are associated with greater team heterogeneity and increased team change. Wiersema and Bantel (1993) investigated TMT change and its relationship to various dimensions of firms’ environments. They showed that turnover of TMT members was lowest when they faced munificent, stable, and simple environments.
Two issues seem to be important in this area of research. The first is the issue of causality. Research on upper echelons sometimes shows significant relationships between upper echelon characteristics and performance but researchers wish to argue that differences in upper echelon characteristics cause differences in performance. One methodology which allows for the demonstration of causality is laboratory research; a topic which will be discussed later in the paper.
The second issue has to do with moderating variables. Thus far, a number of moderating variables, including managerial discretion (Finkelstein and Hambrick, 1990) environmental turbulence, and competition (Murray, 1989) have been explored.
In summary, research on strategic decision making has shown progress in at least four areas, strategic decision models and characteristics, biases in strategic decision making, individual and organizational minds, and upper echelons. The development of a more complete understanding of each of these areas and the refinement of approaches for studying decision making and the factors that affect it provide the basis for incorporating new topics into research. The next section covers three emerging topics which should influence research on strategic decision making in the future.
The preceding was a brief summary of research in traditional areas of strategic decision making. At this point I would like to discuss three emerging topics which I think are especially likely to yield interesting research questions. These will be used to generate propositions for future research. They include Strategic Decision Making and Information Technology, Competitive Strategic Decision Making, and International Strategic Decision Making.
Strategic Decision Making and Information Technology
Huber (1990) conducted a literature review and developed a number of propositions regarding the effects of advanced information technologies on organizational design and decision making. He defined advanced information technologies in this way:
Advanced information technologies are devices (a) that transmit, manipulate, analyze, or exploit information; (b) in which a digital computer processes information integral to the user’s communication or decision task; and (c) that have either made their appearance since 1970 or exist in a form that aids in communication or decision tasks to a significantly greater degree than did pre-1971 forms (p. 48).
Huber developed a number of propositions regarding the ways these technologies should affect strategic decision making as well as organizational design and intelligence. These propositions argued that advanced information technologies should reduce centralization in decision making in centralized organizations but increase centralization in decentralized organizations (Propositions 4a and 4b), that they should lead to more rapid and accurate identification of problems and opportunities (Proposition 10), and that they should lead to more rapid and higher-quality decisions (Propositions 14 and 12).
A recent book dealing with Group Decision Support Systems (Jessup & Valacich, 1993) provides several additional literature reviews and conceptual pieces which may provide guidance for researchers wishing to examine the effects of information technology on strategic decision making. In addition to a piece which extends the ideas in Huber’s 1990 AMR article (Huber, Valacich & Jessup, 1993) pieces by Weick and Meader on sensemaking and Group Support Systems (1993) and one by Connolly on behavioral decision theory and Group Support Systems (1993) provide connections between Group Support Systems and some of the streams of research discussed earlier in the paper. Though none of these pieces deal directly with strategic decision making, researchers familiar with strategic management should see the implications.
A recent paper by Molloy and Schwenk (forthcoming) directly examines the effects of information technology on strategic decision making. Through an in-depth study of eight strategic decisions involving the use of information technology, the authors provide evidence to support several of the propositions from Huber’s 1990 paper. Specifically, their data suggest that the use of information technology increases the speed and quality of problem identification and decision making. The data also argue that information technology is less likely to be used in crisis decisions than in decisions in which time pressure is less intense and that information technology allows for more complete communication about the strategic problem throughout the organization.
Competitive Decision Making
Zajac and Bazerman (1991) have proposed a line of research which unites the work on strategic decision making with the work on competitive strategy. They review research on cognitive biases such as overconfidence, the “winner’s curse”, limited problem frames, and escalation of commitment. These biases are discussed in the context of insufficient consideration of the contingent decisions of competitive others. The authors suggest that “competitive blind spots” may provide a partial explanation for such phenomena as industry overcapacity, new business failure, and acquisition premiums. The directions suggested by Zajac and Bazerman are very promising and it seems that more of the research on decisional biases in strategic management should be conducted in the context of competitive strategy.
Zajac and Bazerman (1991) have suggested that there should be more research which deals with the points of contact between strategic decision making and competitive decision making. One stream of research deals with the role of cognitive structures in competitor definition and analysis. Porac and Thomas (1990) examined the use of taxonomic mental models in competitor definition. Drawing on cognitive categorization theory, they develop propositions about the ways decision makers define the salient attributes of competitors and strategic groups, as well as the ways their definitions change over time. Reger and Huff (1993) in a study of bank holding companies examined the shared perceptions of industry participants about strategic commonalities among firms. They noted that industry participants cluster competitors in ways not easily captured using more traditional ways of defining strategic groups. This result is important since decision makers’ perceptions and cognitions can be expected to influence industry evolution.
A recent series of papers in SMJ has offered suggestions on using game theory as a basis for this new line of research (Camerer, 1991; Postrel, 1991; Saloner, 1991). Contributions from the discipline of experimental economics, especially as it relates to game theory may be particularly appropriate for the study of competitive strategic decision making. Weigelt, Camerer, and Hanna (1992, p. 165) note that in addition to addressing external and internal validity, economists also strive for “theoretical validity”. Economic theory assumes that individuals act rationally in order to maximize their well-being, focusing on the conditions associated with equilibria in games and markets. Therefore, experimental economics brings an “economic orientation” to research reflected in a focus on incentives and on learning over repeated exchanges, transactions, or moves in a game.
Experimental economics (Isaac, 1992), especially research related to game theory, also has the advantage that it emphasizes the competitive context. Thus, experiments in the game theory context may help to meet Zajac and Bazerman’s call for more research that marries strategic decision making and competitive strategy.
International Strategic Decision Making
Most of the research in strategic decision making, as with research on most other topics in management, has been conducted in the United States. In the past, researchers who studied decision making in countries other than the U.S. often paid little attention to possible differences in decision making processes due to national context. For example, Shrivastava and Grant (1985) studied decision making processes in Indian firms and identified several common types of decision processes which were similar to those found in North American contexts. Their article did not focus on decision process characteristics which might be unique to Indian companies. Hickson et al. (1986) in a study mentioned earlier in this paper, collected data from a number of British-based companies and some U.S. companies and only briefly discussed possible differences between them.
More recently, researchers have become more sensitive to the international context. Evidence for this assertion is provided by a recent study on CEO cognitive maps. One of the tenets of the work on dominant management logic is that top executives managing diverse businesses must have more complex cognitive maps (Prahalad & Bettis, 1986) and that those managing international firms with a greater geographic scope must have more complex cognitive maps than those managing firms with only a national scope (Bartlett & Ghoshal, 1989). Calori, Johnson, and Sarnin (1994) provided some support for this contention in a study of the cognitive maps of CEOs. They found that CEOs of firms with an international scope had more complex and comprehensive cognitive maps than those from firms with only a national geographic scope.
Cosier, Schwenk, and Dalton (1992) examined the ways Japanese and U.S. executives handle conflict in decision making. Surprisingly, Japanese executives reported that their typical company decisions involved more conflict than those of U.S. executives and that the final decision was less likely to reflect the desires of the person in charge of the decision than in U. S. companies.
Finally, Maruyama (1994) has identified four different “management mindscapes” (sets of assumptions which determine approaches to decision making and management). While Maruyama’s concept of mindscapes is not the same as the concept of cognitive maps, it seems that an executive’s cognitive map would be a result of his or her mindscape. He notes that the prevalence of these mindscapes is different in different cultures.
It may he that many of the conclusions about strategic decision making developed in the U.S. context will have to be modified in order to be applicable across cultures. The studies cited above represent the sort of research which will lead to such modifications.
Research Topics at the Interfaces
Table 1 shows the twelve points of interface between the four “traditional” topics and the three “emerging” topics previously discussed. Based on my own knowledge of research in strategic decision making (and possibly my own biases) I have identified six interfaces as having especially high potential for future research.
I will briefly list research questions which might be pursued in each of these six high-potential interfaces. The questions I pose are not intended as an exhaustive list of questions but rather as an initial list which should encourage other researchers to develop their own questions. Further, some of these questions have been partially addressed in earlier studies and I am recommending more work on them.
Table 1. Research at the Intersection of Traditional and Emerging
Does laboratory research have a role to play in the area of strategic decision making? Since the inception of the field, researchers have debated this question. A recent survey (Schwenk & Dalton, 1991, p. 285) has shown that only slightly more than 3% of the empirical studies in strategic management published in the leading journals in the field during the 1986-1987 period made use of laboratory research. On the other hand, a set of recommendations developed by a group of leading academics in strategic management for improving doctoral education recommends an increased emphasis on laboratory research (Summer, Bettis, Duhaime, Grant, Hambrick, Snow & Zeithaml, 1991, pp. 383-384). These authors observed that most laboratory research in the past has focused on process issues and that there has been an increasing emphasis on strategy process research and theory building recently in the field. For this reason, they recommended that experimental research should receive more attention in doctoral education.
Despite the recommendations of some researchers that laboratory research should play a larger role, there are some who argue that it is inappropriate in strategic management. Laboratory research is sometimes deemed inappropriate for management in general and particularly inappropriate in strategic management.
Those who argue against laboratory research typically discuss problems with subjects and contexts (Locke, 1986, pp. 3-4). First, they suggest that the subjects in laboratory experiments are often college students who differ greatly from the executives and other professionals to whom the results are generalized. Gordon, Slade, and Schmitt (1987) have summarized these objections and suggested that the continued use of undergraduate students as laboratory subjects indicates that behavioral researchers in management are in danger of developing a “science of the sophomore”. They surveyed five of the major management and psychology journals and identified studies in which the behavior of students was compared with that of non-students and found that in the majority of cases, at least some statistically-significant differences were identified between student and non-student subjects. Though the authors did not suggest that these differences indicate a need to abandon laboratory research, their results are sometimes cited as support by the detractors of laboratory research.
The second, and more serious objection to laboratory research has to do with the artificiality of the context. Concerns in this area include the simplicity of the task, the low level of motivation created in subjects by the task, and possible demand characteristics (Locke, 1986, pp. 3-5). Regarding the simplicity of laboratory tasks, some researchers argue that strategic management or strategic decision making is an extremely complex process with a great many variables to be considered and that laboratory tasks contain too few variables to evoke behavior representative of that found in the real world. The argument has also been made that laboratory tasks evoke low motivation from subjects and that they are subject to demand characteristics which induce ready cooperation and conformity.
In my view, both of these objections should be taken seriously, but not as arguments for abandoning laboratory research in the study of strategic decision making. Rather, they should provide guidelines for researchers in designing future experiments. Whenever possible, researchers should attempt to conduct laboratory experiments using members of the population to which they wish to apply the results. In many cases, this will mean using executives. In some cases, however, undergraduate subjects may be appropriate because the results are intended to apply to the population in general. This is true, for example, of research on cognitive biases. Further, whenever possible the experimental context should be complex and realistic enough to evoke behavior similar to the behavior subjects would exhibit in “the real world”.
Now let us turn our attention to the arguments in favor of laboratory research. If it is possible for a researcher to answer the questions of interest in the field, it makes little sense to go the laboratory. However, there are at least two possible reasons to make use of laboratory research. The first is accessibility and the second is causality.
Laboratory research is usually used for variables which are not easily accessible in the field. Often, these variables have to do with the characteristics of decision processes and the ways environmental and organizational factors affect decision processes. If we want to understand which factors affect the strategic decision process and what the important characteristics of this process are, why do we not, as Henry Mintzberg would suggest, simply ask key decision makers to tell us? The answer is, we should! However, a small amount of personal reflection as well as a large body of empirical research should convince us that self-reports of decision processes are not always reliable (see the discussion of biases in recollection earlier in this paper, Golden, 1992; Huber & Power, 1985; Schwenk, 1985 for references to the empirical research supporting this statement). Executives cannot always recall the details of complex decision processes. What is worse, they tend to reconstruct events in a way that makes the processes seem more purposeful and logical than they actually were. They do not do this from a desire to deceive. Indeed, they may not even be aware of what factors affected their decisions.
It should not be surprising that executives cannot always accurately describe their own decision processes and identify the factors which affect them. In the often hectic pace of organizational life where decisions are interconnected and numerous activities are occurring simultaneously (Mintzberg, 1973) executives may not have time for the reflection necessary to reconstruct their past thoughts and identify the influences on them. Properly-designed laboratory experiments, however, can directly assess the effects of specific variables which have been operationalized within the laboratory context.
A second reason to consider laboratory research has to do with establishing causality. It is generally impossible when observing real-world decision making to determine which elements of the decision process or context caused particular outcomes. If field studies have identified several possible causal agents, however, then it is possible to examine these in controlled laboratory contexts to determine the causal link between them and the outcomes.
For these reasons, we must check the theories we build on self-reports of executives by using laboratory research. Laboratory research may not allow us to observe cognitive processes directly but it does allow us to design tests for the theories we develop about cognitive processes and the factors that affect them; tests which can be conducted under controlled conditions.
Though laboratory research may be appropriate for some topics in the area of strategic decision making it is not equally appropriate for all topics. Table 2 shows each of the 12 interfaces between the traditional and emerging topics with my judgments regarding the areas which are most promising for future laboratory research.
Table 2. Potential for Laboratory Research at the Intersection of
Traditional and Emerging Topics
Acknowledgment: I have tried in this paper to outline some of the more promising areas for future research at these interfaces. I wish to thank Susan Rhodes and Beverly Tyler for helpful comments on an earlier draft of this manuscript.
Bantel, K. & Jackson, S. (1989). Top management and innovations in banking. Strategic Management Journal, 10: 107-124.
Barr, P., Stimpert, L. & Huff, A. (1992). Cognitive change, strategic action, and organizational renewal. Strategic Management Journal, 13 (Special Issue): 15-36.
Bartlett, C. & Ghoshal, S. (1989). Managing Across Borders: The Transnational Solution. London: Hutchinson Business Books.
Bateman, T. & Zeithaml, C. (1989a). The psychological context of strategic decisions: A model and convergent experimental findings. Strategic Management Journal, 10: 59-74.
—–. (1989b). The psychological context of strategic decisions: A test of relevance to practitioners. Strategic Management Journal, 10: 587-592.
Bukszar, E. & Connolly, T. (1988). Hindsight bias and strategic choice: Some problems in learning from experience. Academy of Management Journal, 31: 628-641.
Calori, R., Johnson, G. & Sarnin, P. (1994). CEOs’ cognitive maps and the scope of the organization. Strategic Management Journal, 15: 437-457.
Camerer, C. (1991). Does strategy research need game theory? Strategic Management Journal, 12: 137-152.
Clapham, S. & Schwenk, C. (1991). Self-serving attributions, managerial cognition, and company performance. Strategic Management Journal, 12; 219-229.
Connolly, T. (1993). Behavioral decision theory and Group Support Systems. Pp. 270-280 in L. Jessup & J. Valacich (Eds.), Group support systems. New York: Macmillan.
Cosier, R., Schwenk, C. & Dalton, D. (1992). Managerial decision making in Japan, the U.S., and Hong Kong. The International Journal of Conflict Management, 3: 151-160.
Daily, C. & Schwenk, C. (forthcoming). Chief executive officers, top management teams, and boards of directors: Congruent or countervailing forces? Journal of Management.
Dean, J. & Sharfman, M. (1993). Procedural rationality in the strategic decision making process. Journal of Management Studies, 30: 587-610.
Dess, G. & Origer, N. (1987). Environment, structure, and consensus in strategy formulation: A conceptual integration. Academy of Management Review, 12: 313-330.
Duhaime, I. & Schwenk, C. (1985). Conjectures on cognitive simplification processes in acquisition and divestment decision making. Academy of Management Review, 10: 287-295.
Dutton, J. & Ashford, S. (1993). Selling issues to top management. Academy of Management Review, 18: 397-428.
Dutton, J. & Duncan, R. (1987). The creation of momentum for change through the process of strategic issue diagnosis. Strategic Management Journal. 8: 279-295.
Dutton, J., Fahey, L. & Narayanan, V. (1983). Toward understanding strategic issue diagnosis. Strategic Management Journal, 4: 307-323.
Eisenhardt. K. (1989). Agency theory: An assessment and review. Academy of Management Review. 14: 57-74.
Eisenhardt, K. & Bourgeois, L. (1988). Politics of strategic decision making in high velocity environments: Toward a midrange theory. Academy of Management Journal, 31: 737-770.
Fahey, L. & Narayanan, V. (1989). Linking changes in revealed causal maps and environmental change: An empirical study. Journal of Management Studies, 26: 361-378.
Finkelstein, S. & Hambrick, D. (1990). Top management team tenure and organizational outcomes: The moderating role of managerial discretion. Administrative Science Quarterly, 35: 484-503.
Fredrickson, J. & Iaquinto, A. (1989). Inertia and creeping rationality in strategic decision processes. Academy of Management Journal, 32: 516-542.
Golden, B. (1992). The past is past – Or is it? The use of retrospective accounts as indicators of past strategy. Academy of Management Journal, 35: 848-860.
Goodstein, J., Gautam, K. & Boeker, W. (1994). The effects of board size and diversity on strategic change. Strategic Management Journal, 15: 241-250.
Gordon, M., Slade, L. & Schmitt, N. (1986). The “science of the sophomore” revisited: From conjecture to empiricism. Academy of Management Review, 11: 191-207.
—–. (1987). Student guinea pigs: Porcine predictors and particularistic phenomena. Academy of Management Review, 12: 160-163.
Grant, R. (1988). On “Dominant Logic”, relatedness and the link between diversity and performance. Strategic Management Journal, 9: 639-642.
Hambrick, D. & Mason, P. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9: 193-206.
Hambrick, D., Geletkanycz, M. & Fredrickson, J. (1993). Top executive commitment to the status quo: Some tests of its determinants. Strategic Management Journal, 14: 401-418.
Hammer, M. & Champy, J. (1993). Reengineering the corporation. New York: Harper.
Hart, S. (1992). An integrative framework for strategy-making processes. Academy of Management Review, 2: 327-351.
Hickson, D., Butler, R., Cray, D., Mallory, G. & Wilson, D. (1986). Top decisions: Strategic decision making in organizations. San Francisco, CA: Jossey-Bass.
Hitt, M. & Tyler, B. (1991). Strategic decision models: Integrating different perspectives. Strategic Management Journal, 12: 327-352.
Huber, G. (1990). A theory of the effects of advanced information technologies on organizational design, intelligence, and decision making. Academy of Management Review, 15: 47-71.
Huber, G. & Power, D. (1985). Retrospective reports of strategic-level managers: Guidelines for increasing accuracy. Strategic Management Journal, 6: 171-180.
Huber, G., Valacich, J. & Jessup, L. (1993). A theory of the effects of Group Decision Support Systems on an organization’s nature and decisions. In L. Jessup & J. Valacich (Eds.), Group support systems. New York: Macmillan.
Huff, A. (1990). Mapping strategic thought, Chichester, England: Wiley.
Huff, A. & Reger, R. (1987). A review of strategic process research. Journal of Management, 13:211-236.
Huff, A. & Schwenk, C. (1990). Bias and sensemaking in good times and bad. Pp. 89-108 in A. Huff (Ed.), Mapping strategic thought. Chichester, England: Wiley.
Isaac, M. (1992). Research in experimental economics, Vol. 5. Greenwich, CT: JAI Press.
Jessup, L. & Valacich, J. (1993). Group support systems: New perspectives. New York: Macmillan.
Johnson, G. (1988). Rethinking incrementalism. Strategic Management Journal, 9: 75-91.
Keck, S. & Tushman, M. (1993). Environmental and organizational context and executive team structure. Academy of Management Journal, 36: 1314-1344.
Lant, T., Milliken, F. & Batra, B. (1992). The role of managerial learning and interpretation in strategic persistence and reorientation: An empirical exploration. Strategic Management Journal, 13: 585-608.
Locke, E. (Ed.) (1986). Generalizing from laboratory to field settings. Lexington, MA: Lexington Books.
Lyles, M & Schwenk, C. (1992). Top management, strategy, and organizational knowledge structures. Journal of Management Studies, 29: 155-174.
Lyles, M. & Thomas, H. (1988). Strategic problem formulation: Biases and assumptions embedded in alternative decision making models. Journal of Management Studies, 25: 131-146.
March, J. & Simon, H. (1958). Organizations. New York: Wiley.
Maruyama, M. (1994). Mindscapes in management. Aldershot, England: Dartmouth Publishing.
Michel, J. & Hambrick, D. (1992). Diversification posture and top management team characteristics. Academy of Management Journal, 35: 9-37.
Miller, D. (1991). Stale in the saddle: CEO tenure and the match between organization and environment. Management Science, 37: 34-52.
Milliken, F. & Lant, T. (1991). The impact of an organization’s recent performance history on strategic persistence and change: The role of managerial interpretations. In P. Shrivastava, A. Huff & J. Dutton (Eds.), Advances in strategic management, Vol. 7. Greenwich, CT: JAI Press.
Mintzberg, H. (1973). The nature of managerial work. New York: Harper and Row.
Mintzberg, H., Raisinghani, D. & Theoret, A. (1976). The structure of “unstructured” decision processes. Administrative Science Quarterly, 2: 246-275.
Molloy, S. & Schwenk, C. (forthcoming). Effects of information technology on strategic decision making. Journal of Management Studies.
Murray, A. (1989). Top management group heterogeneity and firm performance. Strategic Management Journal, 10: 125-142.
Narayanan, V. & Fahey, L. (1990). The evolution of revealed causal maps during decline: A case study of Admiral. Pp. 109-134 in A. Huff (Ed.), Mapping strategic thought. Chichester, England: Wiley.
Norburn, D. (1989). The Chief Executive: A breed apart. Strategic Management Journal, 10: 1-16.
Porac, J. & Thomas, H. (1990). Taxonomic mental models in competitor analysis. Academy of Management Review, 15: 224-243.
Porac, J., Thomas, H. & Baden-Fuller, C. (1989). Competitive groups as cognitive communities: The case of Scottish knitwear manufacturers. Journal of Management Studies, 26: 397-416.
Porter, M. (1980). Competitive strategy. New York: Free Press.
Postrel, S. (1991). Burning your britches behind you: Can policy scholars bank on game theory? Strategic Management Journal, 12: 153-155.
Prahalad, C. & Bettis, R. (1986). The dominant logic: A new linkage between diversity and performance. Strategic Management Journal, 7: 485-502.
Quinn, J. (1980). Strategies for change: Logical incrementalism. Homewood, IL: Irwin.
Reger, R. & Huff, A. (1993). Strategic groups: A cognitive perspective. Strategic Management Journal, 14: 103-124.
Salancik, G. & Meindl, J. (1984). Corporate attributions as strategic illusions of control. Administrative Science Quarterly, 29: 238-254.
Saloner, G. (1991). Modeling, game theory, and strategic management. Strategic Management Journal: 119-136.
Schoemaker, P. (1993). Strategic decisions in organizations: Rational and behavioral views. Journal of Management Studies, 30: 107-130.
Schweiger, D., Sandberg, W. & Ragan, J. (1986). Group approaches for improving strategic decision making: A comparative analysis of dialectical inquiry, devil’s advocacy, and consensus. Academy of Management Journal, 29: 51-71.
Schwenk, C. (1982). Effects of inquiry methods and ambiguity tolerance on prediction performance. Decision Sciences, 13: 207-221.
—–. (1984a). Inquiry method effects on prediction performance. Decision Sciences, 15: 449-462.
—–. (1984b). Effects of planning aids and presentation media on performance and affective responses in strategic decision making. Management Science. 30: 263-272.
—–. (1984c). Cognitive simplification processes in strategic decision making. Strategic Management Journal, 5: 111-128.
—–. (1985). The use of participant recollection in the modeling of organizational decision processes. Academy of Management Review. 10: 496-503.
—–. (1986). Information, cognitive bias, and commitment to a course of action. Academy of Management Review, 11: 298-310.
—–. (1990). Effects of devil’s advocacy and dialectical inquiry on decision making: A meta-analysis. Organizational Behavior and Human Decision Processes, 47: 161-176.
Schwenk, C. & Cosier, R. (1980). Effects of expert, devil’s advocate, and dialectical inquiry methods on prediction performance. Organizational Behavior and Human Performance, 26: 409-423.
—–. (1993). Effects of consensus and devil’s advocacy on strategic decision making. Journal of Applied Social Psychology, 23: 126-139.
Schwenk, C. & Dalton, D. (1991). The changing shape of strategic management research. Pp. 277-300 in P. Shrivastava, A. Huff & J. Dutton (Eds.), Advances in strategic management, Vol. 7. Greenwich, CT: JAI Press.
Schwenk, C. & Tang, M. (1989). Economic and psychological explanations for strategic persistence. Omega, 17: 559-570.
Shrivastava, P. & Grant, J. (1985). Empirically derived models of strategic decision making processes. Strategic Management Journal, 6: 97-113.
Staw, B., McKechnie, P. & Puffer, S. (1983). The justification of organizational performance. Administrative Science Quarterly, 28: 582-600.
Summer, C., Bettis, R., Duhaime, I, Grant, J., Hambrick, D., Snow, C. & Zeithaml, C. (1990). Doctoral education in the field of business policy and strategy. Journal of Management, 10: 361-398.
Tversky, A. & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185: 1124-1131.
Voyer, J. (1993). Pharmaceutical industry strategic groups based on cognitive maps. Academy of Management Best Paper Proceedings: 384-388.
Walsh, J. (1988). Top management turnover following mergers and acquisitions. Strategic Management Journal 9: 173-183.
Weick, K. & Meader, D. (1993). Sensemaking and Group Support Systems. Pp. 230-251 in L. Jessup & J. Valacich (Eds.), Group support systems. New York: Macmillan.
Weigelt, K., Camerer, C. & Hanna, M. (1992). The use of experimental economics in strategy research. Pp. 163-200 in P. Shrivastava, A. Huff & J. Dutton (Eds.), Advances in strategic management, Vol. 8. Greenwich, CT: JAI Press.
Wiersema, M. & Bantel, K. (1992). Top management team demographics and corporate strategic change. Academy of Management Journal. 35: 91-121.
—–. (1993). Top management team turnover as an adaptation mechanism: The role of the environment. Strategic Management Journal, 14: 485-504.
Zajac, E. & Bazerman, M. (1991). Blind spots in industry and competitor analysis: Implications of interfirm (mis)perceptions for strategic decisions. Academy of Management Review, 16: 37-56.
Charles R. Schwenk Indiana University
COPYRIGHT 1995 JAI Press, Inc.
COPYRIGHT 2004 Gale Group