Process, content and context: synergistic effects on organizational performance

Process, content and context: synergistic effects on organizational performance – includes appendix

David J. Ketchen, Jr.

Explaining, and often predicting, organizational performance is a primary research objective in the field of strategic management. Indeed, the quest to understand and control performance is an important way to distinguish strategic management from other organizational sciences (Hrebiniak, Joyce & Snow, 1989; Meyer, 1991; Summer et al., 1990). The performance implications of the major decisions that are made in anticipation of, or in response to, environmental conditions are of particular interest to strategy researchers.

Inquiry related to the link between strategic decision making and performance traditionally has been divided into process and content research (e.g., Summer et al., 1990). Process research looks at the activities leading to and supporting strategic decisions (Huff & Reger, 1987); in other words, process research has examined “how” strategy is formed. Content research focuses on the subject of a strategic decision (i.e., “what” is decided) and thus is concerned with the competitive strategy of corporations or their business units (Fahey & Christensen, 1986). Both process and content researchers have sought to establish a relationship between strategic decisions and performance, but the nature and relative intensity of the link remains unclear. Several authors assert that the distinction between process and content is, to a large extent, artificial (e.g., Blair & Boal, 1991; Huff & Reger, 1987); thus, making such a distinction may impede progress toward understanding the relationship between strategy and performance. Although useful for labeling research efforts, a process/content distinction obscures the possibility that process influences content, content influences process, or that a synergistic influence exists.

Rich, albeit preliminary, evidence that the overall coherence between process and content is a critical influence on organizational performance is offered by Pettigrew and Whipp (1991, 1993). In addition, their inquiry suggested that the role of the context (both internal and external to the organization) in which process and content exist must be considered. Pettigrew and Whipp’s efforts can perhaps best be described as theory building because they sought to explore the nature of strategy as “holistically as possible” (1993, p. 7). This led them to use a case-study methodology in order to identify broad constructs that are critical to strategic management. Their study of eight large firms in mature industries suggested that process, content, and context are key constructs in explaining organizational performance. Their observations also revealed that the linkage among these constructs are reciprocal and continuous. This tight coupling (Weick, 1976) serves as a point of departure for the present study, in which we employed a quantitative research approach to identify the nature and systematic consequences of key process, content, and context interactions. Specifically, we investigated the moderating influence of organizational size (i.e., internal context) as we attempted to understand the nature of the process/content relationship and its link to performance within a dynamic external context (the health care industry).

Process, Content and Performance

The historical development of the field of strategic management has been such that the concept of strategy has generally been viewed in terms of two constructs – process and content. Research focused on either process or content offers numerous studies that address the implications of specific strategic variables for performance. In this section, several important streams of inquiry are briefly reviewed. Given the large volume of relevant research, this review is not meant to be exhaustive.(1) Instead, the purpose of this review is to (a) establish that the majority of the studies within both the process and content streams have provided equivocal results regarding their relationship with performance, and (b) identify lines of inquiry within the domain of each construct that have begun to establish the performance implications of important variable-level measures.

Strategy Process and Performance

The strategy process includes the activities leading up to and supporting a choice of strategy (Huff & Reger, 1987). The process of crafting strategy (Mintzberg, 1987a) can be seen as a sequence of behaviors where decision makers scan the environment to gather data about important events and trends, then convert this data into information through interpretation systems (Daft & Weick, 1984), producing understandings of situations that serve as the basis for subsequent decision making (Mintzberg, Raisinghani & Theoret, 1976), action (Dutton, Fahey & Narayanan, 1983), and ultimately, performance (Thomas, Clark & Gioia, 1993).

Much of the strategy process literature focuses on identifying the effects of various individual (e.g., Miller, Kets de Vries & Toulouse, 1982), group (e.g., Thomas & McDaniel, 1990), and organizational (e.g., Hall, 1984) factors on the strategy process. Some empirical research has sought to link the strategy process to performance, but the findings have generally been ambiguous. For example, some authors have found the extent of an organization’s strategic planning to be a predictor of performance (e.g., Rhyne, 1986) while others claim that there is no systematic relationship (Pearce, Freeman & Robinson, 1987), or that the link is so tenuous that it cannot be directly measured (Hogarth & Makridakis, 1981).

However, studies have offered two aspects of the strategy process (political activity and information usage) that may have strong performance implications. Political activity refers to the lobbying, coalition formation, conflict, and bargaining surrounding the strategy process (Narayanan & Fahey, 1982). High levels of political activity have been associated with poor performance, especially under “high velocity” conditions (i.e., where change is extremely rapid – Eisenhardt & Bourgeois, 1988), because politics distract managers from coping with strategic issues (e.g., key environmental events) and constrict the ability to resolve the multiple interpretations fostered by such issues when they are actually addressed (Dutton et al., 1983; Janis, 1989).

Information usage refers to the amount of available data that organizations process in making strategic decisions (Thomas & McDaniel, 1990). Information usage thus represents a key aspect of comprehensiveness in strategy making (i.e., the degree to which organizations attempt to be exhaustive or “rational” in all aspects of forming strategy – Fredrickson, 1984; Fredrickson & Mitchell, 1984). Specifically, gathering and processing information is essential to pursuing rationality across strategic activities (e.g., generating alternatives and assessing their potential costs/benefits). Such information processing efforts may be critical when managers grapple with complex issues (Mintzberg et al., 1976). Indeed, chief executive officers (CEOs) in high performing firms have been shown to scan the environment more frequently and more broadly in response to strategic uncertainty than their counterparts in low performing firms (Daft, Sormunen & Parks, 1988). Thus, while some of the process literature is inconclusive with respect to explaining performance differences across firms, the concepts of political activity and information usage appear to be promising predictors.

Strategy Content and Performance

One of the tenets that underlies the choice of competitive strategy is that a well-conceived strategy positions a firm to confront the competitive forces present in the environment (Hofer & Schendel, 1978; Thorelli, 1977). A firm’s strategy must deal with industry forces such as actual and potential competitors, buyer and supplier behavior, and product/service substitutes (Porter, 1980). If a firm’s strategy enables it to respond to, predict, or dictate these environmental forces, it is likely to be high performing. In this sense, the expectation that the content of a firm’s strategy is a key determinant of its performance is a cornerstone of the strategic management literature.

Despite this expectation, various streams of research offer conflicting results regarding the link between strategy content and performance. Among the most popular streams of content research, at different levels of analysis, are those that consider the performance implications of (a) diversification strategy and (b) market share. Diversification research has attempted to explain firm performance in terms of the degree of relatedness of diversification. A strategy of related diversification is thought to outperform unrelated diversification (Bettis, 1981; Palepu, 1985; Rumelt, 1974); however, the overall results are equivocal, if not contradictory (Bettis & Hall, 1982; Michel & Shaked, 1984). The market share strategy-performance relationship is also unclear. Some studies have revealed a positive relationship between market share and profitability (e.g., Buzzell, Gale & Sultan, 1975; Gale, 1972). Others have suggested that low market share businesses may perform well (e.g., Hamermesh, Anderson & Harris, 1978), while a third group found that leading market share businesses lack robust profitability (e.g., Schwalbach, 1991; Woo, 1983). Thus, despite the volume of relevant strategy content research, this work has not been able to clearly define the relationship between strategy and performance.

However, empirical results have been promising with respect to two other aspects of strategy content: (a) breadth of target market and (b) method of developing competitive advantage. Breadth of target market refers to the extent to which an organization attempts to serve the entire range of potential customer segments (Zammuto, 1988). Miles (1982) argues that firms generally adopt one of two approaches to address the issue of breadth. An organization can seek to expand its operations and, ultimately, derive profits across as much of the entire market as possible (a “domain-offense” strategy) or concentrate its efforts on one or more specific segments of the market (a “domain-defense” strategy). Research indicates that this choice influences performance. Specifically, Zajac and Shortell (1989) found that hospitals which “defend” a narrow market domain are much less successful than hospitals that continuously seek to expand their domain. This wider breadth of target market allows the hospital to best meet the diverse needs of a changing marketplace (Shortell, Morrison & Friedman, 1990).

The method used to develop competitive advantage refers to how an organization competes within its chosen domain (Zammuto, 1988). The assumption that organizations develop competitive advantages either through capitalizing on new opportunities (e.g., continuously offering new products/services) or exploiting those already available (e.g., maintaining a static product/service mix) underlies much of the extant strategic management research (e.g., Miles & Snow, 1978; Porter, 1980). Recent empirical research has found that, under dynamic conditions, a focus on introducing new, cutting-edge offerings is positively related to performance over time because it allows the organization to keep pace with, or even anticipate, the changing requirements of its domain (Ketchen, Thomas & Snow, 1993; Shortell, et al, 1990). In summary, despite the equivocality that characterizes most of the content-performance research, an organization’s breadth of target market and method of developing competitive advantage appear to affect its performance outcomes.

Toward an Integrated Approach to Strategy and Performance

Taken together, the process and content streams of research provide only limited understanding of the nature of the effects of each on performance. However, the growing recognition of the interplay between process and content (e.g., Huff & Reger, 1987; Pettigrew & Whipp, 1991, 1993) suggests that understanding the performance implications of the alignment of process and content is an important concern. The empirical studies that address this concern have generally taken a configurational perspective, where organizations are viewed in terms of sets or groups that are alike within and different between groups along important dimensions (Miller & Mintzberg, 1983). In contrast, most organizational inquiry focuses on linear (or bivariate) relationships. The differences between the two perspectives direct how organizational performance is analyzed. Specifically, while studies based on a linear approach provide evidence regarding “simple causation,” the degree to which an independent variable impacts a dependent variable (Miller & Mintzberg, 1983), configurational studies focus on whether or not performance varies across different confluences of process and/or content variables (i.e., groups).

The results regarding the performance implications of process/content fit are ambiguous. Segev’s (1987) study of the match between Miles and Snow’s (1978) strategic types and Mintzberg’s (1973) modes of strategy-making offers weak evidence that fitting process and content increases performance. Also, Miller (1989) found that the match between process and content is related to performance for firms following a differentiation strategy (Porter, 1980), but not for firms employing a cost leadership or focus strategy. This led Miller to suggest that fit is sometimes, but not always, needed. At a broader level, the strategic groups literature is a body of configurational inquiry that often examines the performance implications of the alignment of a variety of process and/or content factors. Strategic group (or configuration) membership is expected to be related to performance (Porter, 1979); yet evidence for the absence of a relationship (e.g., Cool & Schendel, 1987; Hayes, Spence & Marks, 1983) and ambiguous results (e.g., Caves & Pugel, 1980; Oster, 1982) abound.

The ambiguous results of previous studies may be driven by insufficient accounting for the internal and external contexts that impact, and are impacted by, process and content (Pettigrew & Whipp, 1991, 1993). For example, both Miller (1989) and Segev (1987) use a firm’s generic strategy as the key internal context variable influencing the impact of process/content interactions on performance. However, to a large extent, a generic strategy can be defined as a particular confluence of strategy process and content (e.g., Miles & Snow, 1978). Thus, the assertion that generic strategy moderates the impact of process/content fit on performance may be logically untenable in light of the operational definition usually used for generic strategy.

An alternative internal context variable is organizational size. The view of size as a critical constraint on the activities of an organization has deep roots in the literature (e.g., Blau & Schoenherr, 1971; Pugh, Hickson, Hinings & Turner, 1968). Subsequent authors have elaborated on this premise and offer insight to how size might affect the relationship between strategy and performance (e.g., Aldrich, 1979; Finkelstein & Hambrick, 1990; Hall, 1984). Thus, we suggest that organizational size is a key moderator of the impact of the process/content interaction on organizational performance.

In terms of the external context, Miller (1989), Segev (1987), and many strategic groups studies (e.g., Hergert, 1987; Newman, 1978) use firms from multiple industries in their sample but do not control for industry type. Thus, multiple external contexts are represented but not accounted for, making results difficult to interpret (Dess, 1987). We chose to focus on a geographic segment of one industry (hospitals), thus ensuring that the external context was relatively uniform across organizations.

Propositions and Hypotheses

Overall, strategic choice is the theory that underlies this inquiry. Strategic choice is grounded in the assumption that managerial decisions about how the organization will respond to environmental conditions are critical determinants of organizational outcomes (Child, 1972). Thus, the overarching relationship of interest in strategic choice research (and indeed, in the present study) is the strategy-performance link (Meyer, 1991; Summer et al., 1990). Early efforts to develop the strategic choice perspective considered it necessary to account for both process and content in order to define the role of strategy in influencing a firm’s fate. For example, Miles and Snow (1978) emphasize the need for organizations to coordinate and maintain consistency between strategic decision processes and selected strategies. Failure to do so leads a firm to become a “reactor” and, ultimately, to suffer poor performance. Following the foundational theorizing of the 1970s, studies tended to be focused on specific aspects of the strategy-performance link (Fahey & Christensen, 1986; Hrebiniak et al., 1989). The work of Pettigrew and Whipp (1991, 1993) marked a return to a broader focus in the effort to define the strategy-performance relationship; it also highlights the need to account for context.

Like any theory, strategic choice can provide the basis for pursuing three fundamental research aims: description, explanation, and prediction (Kerlinger, 1986; Snow & Thomas, 1994). Previous case study research grounded in the strategic choice perspective provides a description of the need to develop an overall alignment among process, content, and context (Pettigrew & Whipp, 1991, 1993). The propositions and hypotheses developed below take the next logical steps by (a) examining the extent to which alignment between process and content explains organizational performance beyond the main effects of each and (b) testing several specific predictions within the general domain described by earlier inquiry. The number and variety of process and content variables whose performance implications have been previously examined means that any single investigation of these relationships is unlikely to be exhaustive. Thus, the focus here is on two key process variables and two key content variables discussed earlier that have been strongly linked to performance in prior research.

Strategy Processes’ Impact on Performance

The extant literature suggests that how a firm’s strategic decisions are made should have a considerable impact on its performance (Huff & Reger, 1987). Two key process variables that have been associated with performance are political activity and information usage. Political activity is viewed as an attempt to increase power during decision processes through coalition formation, lobbying and cooptation, withholding information, and centralization of decision power (Pfeffer, 1981). These activities have been shown to be associated with poor firm performance, particularly in dynamic environments, because they (a) divert top managers’ attention away from environmental scanning (Janis, 1989), leaving critical issues unrecognized (Thomas, Shankster & Mathieu, 1994) and (b) impede the flow of accurate information to and amongst key decision makers (Eisenhardt & Bourgeois, 1988). Further, for issues that capture managers’ attention, intense levels of political activity may decrease interpretation consensus and effectiveness (Dutton et al., 1983). Indeed, the resulting multiple perspectives of strategic issues cause executives to direct their attention and effort away from coping with an issue and toward lobbying and confrontational activities in order to gain support for their particular interpretation (Narayanan & Fahey, 1982).

Information usage refers to the amount of available data that organizations process in addressing strategic decisions (Daft & Macintosh, 1981; Thomas et al., 1993; Thomas & McDaniel, 1990). Strategic decisions are decisions about issues that are ill-structured and open to multiple interpretations (Daft & Weick, 1984; Dutton et al., 1983). In dynamic settings, the inherent rapid pace of change enhances this ambiguity (Daft & Lengel, 1986). In response to dynamic conditions, top managers need to process relatively large amounts of relevant information in order to develop understandings of complex issues (Huber, O’Connell & Cummings, 1975). Following this interpretation process, high levels of information processing foster the generation of new alternatives, possibly leading to better strategic decisions and, ultimately, increased performance (Daft et al., 1988).

These arguments suggest that:

P1: The strategy process will be significantly related to organizational performance.

Specifically, we expect that:

H1a: In a dynamic environment, the level of political activity among top managers during the strategy process will be negatively related to organizational performance.

H1b: In a dynamic environment, the level of information usage among top managers during the strategy process will be positively related to organizational performance.

Strategy Content’s Impact on Performance

As described above, the strategy content-performance link is central to the field of strategic management, yet most of the relevant evidence is equivocal. However, breadth of target market (i.e., whether an organization appeals to consumers in general or only to particular segments) and method of developing competitive advantage (i.e., whether, within its chosen domain, an organization pursues new opportunities or harvests existing ones) are two content variables that have begun to be systematically linked to performance (e.g., Ketchen et al., 1993; Shortell et al., 1990; Zajac & Shortell, 1989). In addition to this empirical support, the conceptual work of Zammuto (1988) indicates that these two dimensions capture the essence of strategy content. Specifically, Zammuto argues that research grounded both in strategic choice (e.g., Miles & Snow, 1978) and organizational ecology (e.g., Brittain & Freeman, 1980) offers breadth of target market and method of developing competitive advantage as the fundamental criteria that define organizational strategy. Once an organization is positioned along these key dimensions, shifts in strategy are inhibited, though not precluded, by the loss of resources and time usually inherent in such changes (Caves & Porter, 1977; Tushman & Romanelli, 1985). Because strategic shifts are difficult, performance should vary directly with the extent that the needs of the environment are matched by an organization’s breadth of target market and method of developing competitive advantage (Zammuto, 1988). The specific postures along these dimensions that are expected to prosper in a dynamic environment are specified below.

The strategic types (domain-offense and domain-defense) identified by Miles (1982) capture an organization’s breadth of target market (Thomas & McDaniel, 1990). An organization is said to follow a domain-offense strategy if it aims to expand its areas of operation (or “domain”) through actions such as pursuing additional market niches and competing with other organizations for resources. Organizations following a domain-defense strategy focus on protecting existing areas of operation through, for example, cultivating repeat customers and enacting cooperative arrangements with other organizations. Dynamic industries, such as the one examined here, appear to offer favorable prospects for offensive approaches, which enable organizations to capitalize on changes in the array of market niches often fostered by a shifting environment (Hedberg, Nystrom & Starbuck, 1976). Further, shifts in the environment may render previously fertile domains barren (Tushman & Anderson, 1986), suggesting that a domain-defensive approach is risky.

An organization’s method of developing competitive advantage is reflected in the specific actions that it takes within its chosen domain. Perhaps the most critical of these interventions is the choice of which products/services to offer the marketplace, because it is these offerings that potential customers embrace or reject, thereby determining the organization’s success or failure to a large extent (e.g., Porter, 1980). Dynamic conditions offer organizations the opportunity to profitably implement new, innovative offerings in response to trends such as changing consumer preferences. Indeed, the success of organizations confronted by a dynamic setting has been linked to the ability to differentiate and change their arrays of product/service offerings to meet the needs of the domain within which they compete (Shortell et al., 1990; Thomas et al., 1993).

These arguments lead us to expect that:

P2: Strategy content will be significantly related to organizational performance.

Specifically, it is anticipated that:

H2a: In a dynamic environment, organizations following a domain-offense strategy will exhibit higher performance than those following a domain-defense strategy.

H2b: In a dynamic environment, the extent to which competitive advantage is developed through capitalizing on new opportunities will be positively related to organizational performance.

Process/Content Synergy and Performance

Recognition that a firm’s strategy is often revealed in the patterns of its strategic decisions (Mintzberg, 1987b) highlights the importance of the process/content interaction. An organization may begin its existence choosing key actions such as which market segments to serve and how to develop competitive advantage based on rudimentary causal maps. However, the relative success of these initial (and subsequent) actions are stored in the organization’s memory (Walsh & Ungson, 1991). The resultant “retained set” of cause maps, procedures, and behaviors provides a framework for defining what data will be analyzed and how it will be interpreted and acted upon (Hall, 1984). Thus, a firm’s history, embedded in previous choices about strategic content (i.e., the firm’s realized strategy – Mintzberg & Waters, 1985), is a key to understanding the present processes the firm uses to choose strategy.

Further, the interpretation of a firm’s strategic options is a reflection of both its strategic processes and the content of its past strategic decisions (Milliken & Lant, 1991). That is, the content of a firm’s strategy creates a limited set of strategic decision making processes (Daft & Weick, 1984). Subsequently, processes activated for making strategic decisions about what to do in the future (i.e., the processes used to identify and communicate intended strategies – Mintzberg & Waters, 1985) are constrained by the mechanisms in place to achieve existing strategic goals. In this way, strategic process and content become intertwined conceptually as well as temporally (Miller & Friesen, 1983).

An implication of this tight linkage is that process/content interactions may impact performance by facilitating (or failing to facilitate) both internal coordination and fit with the demands of the environment. For example, Bourgeois and Eisenhardt (1988) suggest that innovative firms in high velocity environments need to maximize the speed of their strategic processes in order to take advantage of the opportunities offered by the rapid and discontinuous change. Because high levels of politics and information usage increase information processing requirements (Eisenhardt & Bourgeois, 1988; Fredrickson & Mitchell, 1984), and thus may slow the strategy process, performance may decrease when such activities are coupled with an expansionist market orientation and change in specific offerings.

In an empirical sense, these arguments suggest that process/content interactions will have a significant impact on performance in addition to the influences originating from process and content. Thus, we offer the general prediction that, in a dynamic environment:

P3: The fit between strategy process and strategy content will explain additional variance in organizational performance beyond that explained by the main effects of process and content.

The tight conceptual linkages between the constructs of strategy process and strategy content suggest that the specific interactions among process and content variables linked individually with performance will impact performance as well. Thus, for dynamic environments, the following hypotheses are relevant:

H3a: The fit between political activity and breadth of target market will be significantly related to organizational performance.

H3b: The fit between political activity and method of developing competitive advantage will be significantly related to organizational performance.

H3c: The fit between information usage and breadth of target market will be significantly related to organizational performance.

H3d: The fit between information usage and method of developing competitive advantage will be significantly related to organizational performance.

The Moderating Effects of Size

The nature and intensity of the influence of process, content, and process/content interactions on performance may vary based on the different organization-environment relations experienced by large and small organizations. To the extent that an organization can enact an environment that is favorable to itself, it may enjoy robust performance (Smircich & Stubbart, 1985). Large organizations are often better able to shape the environment than small firms because the formers’ greater resource base (Pfeffer & Salancik, 1978) allows them to impose their perspective on other players in the industry (Mintzberg, 1987b; Weick, 1979) in order to create conditions conducive to their own success. Thus, a focus on market power suggests that large firms should outperform their smaller counterparts (Porter, 1979).

However, increased size not only provides greater market power, it also can lead to structural complexity. As organizations expand, structural characteristics such as occupational types and levels of hierarchy grow in number and diversity (Blau & Schoenherr, 1971; Hall, Haas & Johnson, 1967; Pugh et al., 1968). Such increases in internal complexity often create inertial tendencies that prevent large firms from responding quickly to market changes (Quinn, 1985). Specifically, the complexity inherent in many large firms restricts managers’ ability to affect change (Aldrich, 1979; Miller et al., 1982), limiting the range of strategic options available to the organization (Finkelstein & Hambrick, 1990; Gioia & Chittipeddi, 1991; Hambrick & Finkelstein, 1987). Conversely, in small firms, the sub-units involved in making and implementing a decision are often relatively homogeneous and few in number. This structural simplicity can allow small firms to respond more quickly to challenges in the environment (Mintzberg, 1989), possibly enhancing organizational performance under dynamic settings. Thus, a focus on structural constraints in organizations implies that small firms should outperform large players.

In summary, prior theoretical and empirical inquiry indicates that the strategy-performance relationship will vary between large and small organizations. However, extant research offers conflicting guidance as to how the precise nature and consequences of process/content interactions might differ between large and small organizations. Hence, we limit our prediction to the following general proposition:

P4: The nature of the impact of strategy process, strategy content, and process/content fit on performance will differ between large and small organizations.

Method

Overview

Industry Studied. Because the nature of the strategy-performance linkage might vary by industry conditions (Dess, 1987; Hrebiniak & Joyce, 1985), we focused on a single industry. The health care industry was chosen as an attractive setting for addressing the research issues of this study in part because the dynamic state of the industry (Kimberly & Zajac, 1985; Shortell et al., 1990) has forced top managers to think and act strategically. Thus, hospital top managers may have a strong sense of what the organization’s strategy is as well as how it is formed. Also, past research provided confidence that top managers from different hospitals would perceive different levels of political activity and information usage (Meyer, 1982) and respond strategically to the environment in different ways (Shortell & Zajac, 1990).

Data Collection. Data on both strategy process (i.e., political activity and information usage) and content (i.e., domain offense/domain defense) were collected through a questionnaire distributed in 1987 to the CEOs of all 545 public-access hospitals (i.e., not prison or military-affiliated) in a single state (the population of the state’s hospitals). Ritvo, Salipante and Notz’s (1979) finding that the CEO is the primary interpreter of issues confronting the hospital, coupled with Provan’s (1991) finding that hospital CEOs possess far more information regarding strategy than other actors, indicated that a focus on CEOs as informants on strategy was appropriate. The questionnaire response rate was 39% of the population, while 156 of the 210 responses were usable.(2) The average age of the CEO informants was 44; approximately 75 percent had degrees in hospital administration. The informants had an approximate average of 12 years of managerial experience and five years of strategic decision-making experience in their hospitals. Ninety-four percent of the hospitals were general hospitals; the remainder were specialized facilities such as psychiatric and rehabilitation hospitals. These organizations ranged in location from major metropolitan areas to rural areas and were approximately equally distributed across five ownership categories: church, nonprofit-nonchurch, county, hospital authority-district, and corporation. Chi-Square analyses indicated no significant differences in type (i.e., general or speciality), ownership, and size, between the 156 hospitals used in this study and the nonresponding hospitals.

Archival measures of strategy content (i.e., change in product/service mix – the measure of method of developing competitive advantage) were taken from the American Hospital Association’s Guide to the Health Care Field across the years 1987-1989. Performance measures (i.e., profit per admission and admissions per bed) for the years 1990-1991 were obtained from the Center for Healthcare Industry Performance Studies, a source of high-quality archival data, as were measures of size (i.e., number of hospital beds). Because of missing data, statistical tests involving profit per admission focused on 143 organizations whereas those involving admissions per bed utilized 154.

Constructs and Variables

Strategy Process. Two process variables were measured: political activity and information usage. Political activity was measured using a four item scale based on Pfeffer (1981) – (see Appendix). These items asked CEOs to indicate the extent to which strategy formation processes in their organizations can be characterized by activities such as coalition formation, lobbying, and cooptation. A sample item for the scale is: “To what extent do coalitions among top managers change over different strategic issues?”

We employed a case-scenario methodology to uncover the nature of information usage during strategic processes. This method involves presenting informants with a realistic though hypothetical description of an organizational issue to which they respond in a survey format. By providing a common reference point across informants, scenarios enable researchers to assess the variance in processes (e.g., information usage) that likely exists between organizations facing the same issues (Fredrickson, 1986). As a result, strategy researchers, including Fredrickson (1984), Fredrickson and Mitchell (1984), Cosier and Aplin (1980), and Ireland, Hitt, Bettis and de Porras, (1987) have used the case scenario method when seeking to provide stimuli that are uniform across informants.

Before constructing our scenarios, a list of possible topics was compiled by tapping several sources: interviews with health care executives, hospital strategic planning documents, articles in leading health care journals, cases that had been written for hospital administration classes, and the popular press. We then formed an expert panel that consisted of the president of the state’s hospital association, the president of the state’s physician association, two hospital CEOs, a chief operating officer, a chief financial officer, a marketing director, a general counsel (most from different hospitals), and two faculty members whose primary research interest was hospital administration. Our primary goal with this panel was to select topics and draft scenarios that would be considered strategic and that were being faced by the hospitals in the state. As a result of this process, health maintenance organizations and satellite care centers were selected as the most appropriate issues.

The next step was to draft scenarios that would provide a realistic yet balanced presentation of informational elements across the two scenarios. Each scenario contained sixteen key pieces of information that hospitals might use in making sense of the issue. To ensure realism, we adopted much of this information from strategic planning documents that we had obtained from several hospitals in the state. We then interviewed each panel member to refine and cross-check the content of the scenarios to establish that they were accurate depictions of the hospital environment.

In the subsequent questionnaire, we provided informants with the two case scenarios (each about one page in length) and then asked the extent to which the hospital would process the information items contained in the cases. For example, following the scenario on satellite care centers, CEOs were queried about the extent to which information items including “staff feels that the hospital has capacity to meet changing demands of the community,” “self-employment and service-oriented jobs in the area are increasing,” and “occupancy rate of the hospital is down” would be used to clarify and define possible issues during strategic decision processes. The sixteen item scale (representing the key sixteen pieces of information that defined each scenario) ranged from one to seven and was coded such that a high score indicated that more information is used during strategic processes. To ensure that there was no order bias, we used two versions of the questionnaire that differed in terms of the presentation order of the scenarios.(3)

Strategy Content. Two strategy content variables were measured: breadth of target market and method of developing competitive advantage. Breadth of target market was assessed through a domain offense/domain defense scale based on the strategic patterns identified by Miles (1982). This scale measures the extent to which the CEO believes his/her hospital seeks to expand its areas of operation (domain offense) or emphasizes serving a limited set of market segments (domain defense). The seven item domain offense/domain defense scale was based on the dimensions offered by Miles (1982) but was framed in terms of hospitals’ concerns (see Appendix). It was coded so that high scores indicated domain-offensive approaches. A sample item is: “To what extent does your hospital continually search for new patient bases?”

To assess method of developing competitive advantage, we measured each hospital’s change in product/service mix over the three year period (1987 to 1989) that followed the collection of the process and domain offense/domain defense data. During this period, the American Hospital Association’s annual Guide to the Health Care Field reported 54 product/service categories for all hospitals in the United States. Using this list, we constructed a profile of changes in product/service offerings for each of the hospitals between the years 1987 and 1989. Service changes were differentially weighted because the reasons for introducing a service often vary: some may be offered in order to be unique, relative to competitors (e.g., open heart surgery facilities), while others may be offered merely to keep pace with the industry (e.g., health promotion services). Thus, based on a system developed by Hambrick (1979) and used by Thomas et al. (1993), service additions were weighted: a service added by 1989 that one-third or less of the hospitals offered in 1987 was given a weight of three; a service added by 1989 that between one-third and two-thirds of the hospitals had in 1987 was given a weight of two; and a service added by 1989 that greater than two-thirds of the hospitals provided in 1987 was given a weight of one. The difference between the number of services offered in 1987 and the weighted sum of services offered in 1989 was used to measure the method of developing competitive advantage. A high score indicated that a hospital was altering its product/service mix to take advantage of new opportunities while a low score suggested that the hospital was trying to exploit existing opportunities.

Context. As described above, the focus here is on organizational size. Kimberly (1976) notes that the measurement of size is controversial in many settings (or “external contexts”). However, in the health care industry, the number of hospital beds is a well-established, widely-accepted measure of size (e.g., Alexander & Amburgey, 1987; Ginn, 1990; Provan, 1991). This measure is robust across important variables such as location (e.g., type of community) and ownership (e.g., private vs. public). Thus, size was measured as the number of licensed beds in each hospital.

Performance. Hospital outcome measures should include both effectiveness (e.g., financial performance) and efficiency (e.g., productivity) indicators (Fottler, 1987). Financial viability is crucial to survival in the dynamic health care environment (Shortell et al., 1990), while efficiency measures are important because competition for patients has been intensifying (Fottler & Lanning, 1986). Accordingly, in this study, both financial and efficiency measures were included. Specifically, profit per admission ([net inpatient revenue-inpatient costs]/number of hospital admissions) and admissions per bed (number of hospital admissions/number of beds) were measured. Performance data from 1990 and 1991 were used, thus our working assumption was that a one- to four-year lag would be sufficient for the effects of strategy on performance to be observed. Also, data from the two years were averaged into composite measures to guard against one-year “outlier” performance.

Data Analysis

Regression analyses were used to find the extent to which process, content, and their fit explain variance in organizational performance (Venkatraman, 1989). First, these links were examined across all organizations. Main effect models were used to define the impact of process and content on performance. To find if the fit between process and content was a significant influence on performance across all organizations, a hierarchical approach was taken: the four main effects were entered, followed by the process/content interactions.(4) F-tests were then used to find if the interactions made a statistically significant contribution to explaining variance in performance beyond that explained by the main effects.

A second set of regressions examined the extent to which size moderates the process-content-performance links. Following Miller et al. (1982), the sample was divided into large and small firms through a median split. Chow tests were then done to find if splitting the sample provided a meaningful distinction.(5) For those performance measures where the split was significant, four regressions were then run: main effect models for both size categories as well as full models (main effects plus interactions) for both.(6) Once again, F-tests were then used to find if the interactions made a significant contribution to explaining variance in performance beyond that explained by the main effects.

Results

Table 1 gives means, standard deviations, appropriate Cronbach alphas, and Pearson zero-order correlations for the process, content, context, and performance variables. All Cronbach alphas were greater than .80, indicating that the measures were reliable (Carmines & Zeller, 1979). Multivariate statistics indicated that the set of strategy variables was significantly related to the set of performance measures (Wilks’s Lambda = .767, [F.sub.8, 274] = 4.96, p [less than] .001).

Table 2 summarizes the regression results for all organizations. Equation 1 under each performance variable shows mixed evidence regarding Proposition 1, which predicted that the strategy process would be significantly related to organizational performance. Process was significantly related to profit per admission ([F.sub.3, 139] = 5.89, p [less than] .001), but not to admissions per bed. No support was found for the expectation of Hypothesis 1a that political activity would be negatively related to performance, but the significant, positive impact of information usage on profit per admission offers partial support for Hypothesis 1b.

Equation 2 under each performance measure provides strong support for Proposition 2, which predicted that strategy content would be significantly related to performance. Content impacted both dependent variables ([F.sub.3, 150] = 5.02 for admissions per bed, p [less than] .01; [F.sub.3, 139] = 10.04 for profit per admission, p [less than] .001). There was some support for Hypothesis 2a: the extent to which an organization pursues a domain-offense strategy was positively related to profit per admission (beta = 0.27, p [less than] .01). Also, as predicted by Hypothesis 2b, pursuing new opportunities (i.e., high change in product/service mix) was positively related to both profit per admission and admissions per bed (beta = 0.18 and 0.21, respectively; both p [less than] .05).

Comparing Equations 3 and 4 under both performance measures allows examination of Proposition 3, which predicted that the fit between strategy process and strategy content would be significantly related to organizational performance. In both cases, Equation 3 includes the main effects of all the process and content variables, while Equation 4 includes these same variables plus the interactions between the two sets. The evidence related to Proposition 3 was mixed: process/content fit enhanced the ability to explain profit per admission (change in r-squared = .07, [F.sub.9, 133] = 3.65, p [less than] .05), but not admissions per bed.

The specific interaction terms in Equation 4 for each dependent variable are relevant to Hypotheses 3a-3d. No support was found for Hypotheses 3a and 3b, which predicted, respectively, that the fit between political activity and (a) breadth of target market and (b) method of developing competitive advantage would be related to performance. Mixed evidence was found regarding Hypothesis 3c, [TABULAR DATA FOR TABLE 1 OMITTED] [TABULAR DATA FOR TABLE 2 OMITTED] which predicted that the fit between information usage and breadth of target market would be related to performance, and Hypothesis 3d, which predicted that the fit between information usage and method of developing competitive advantage would be related to performance. Both interactions were statistically significant for profit per admission (beta = -1.34 and -1.28, respectively; both p [less than] .05), but not for admissions per bed.

The first step in examining Proposition 4, which predicted that the nature of the influence of process, content, and process/content fit on performance would differ between large and small organizations, was to perform a median split of the sample based on size. The median size for the hospitals in this study was 120 beds. Chow tests suggested that the large/small distinction was meaningful in terms of explaining profit per admission ([F.sub.8, 125] = 8.64, p [less than] .01) but not admissions per bed ([F.sub.8, 136] = 0.43). Thus, only profit per admission was examined in subsequent analyses.

Table 3 displays the results related to Proposition 4. Neither of the process variables was significantly related to performance for either large or small organizations. However, in terms of content, domain-offense/domain-defense played a key role for large hospitals (beta = 0.48, p [less than] .001), while change in product/service mix was significant for the small hospitals (beta = 0.21, p [less than] .05). In both groups, process/content fit significantly increased the ability to explain profitability (change in [R.sup.2] = .32, [F.sub.8, 63] = 12.29, p [less than] .001 for large hospitals; change in [R.sup.2] =. 17, [F.sub.8, 62] = 3.76, p [less than] .05 for small hospitals).

Several of the specific process/content interactions relevant to Proposition 4 were significant. In large organizations, the interaction of political activity and domain-offense/domain-defense strategy was significantly related to profit per admission (beta = 3.13, p [less than] .001). Also for large organizations, the interactions of information usage with the two content variables were significant (beta = -4.12, p [less than] .001 for domain-offense/domain-defense strategy; beta = -2.11, p [less than] .05 for change in product/service mix). In small organizations, the interaction of political activity and change in product/service mix was a significant predictor of profit per admission (beta = -1.16, p [less than] .05).

In sum, the findings indicated that (1) there were significant main effects for strategy process and strategy content on performance when the full sample was analyzed; (2) the process/content interactions significantly enhanced explanation of organizational performance; and (3) context (i.e., size) was a key moderator of these relationships.

Discussion

The traditional distinction between process and content has been maintained throughout much of the research on strategic management. Previous inquiry argues that this dichotomy is to a large extent artificial (Huff & Reger, 1987; Pettigrew & Whipp, 1991, 1993); thus, integrated approaches to strategy (i.e., those that account for both process and content as well as their synergistic effects) are needed. The results of this study demonstrate that process and content factors impact performance as do interactions among them. Thus, the study offers support for the [TABULAR DATA FOR TABLE 3 OMITTED] notion that we must move beyond approaches that focus on just the main effects of process and content on performance and examine the synergies that can emerge from their interaction as well. However, there is empirical value in assessing the main effects of process and content variables. In this sense, the position that the process/content distinction is artificial may be an overstatement. Clearly, the two are tightly coupled (Weick, 1976), but they also maintain distinct characteristics, including making unique contributions to explaining performance.

This study began by investigating the determinants of performance across all the organizations in the sample. Here we found that both domain-offense approaches to the market and product/service change have a positive impact on profitability, particularly when information usage is low. Apparently, in the health care industry, the alignment of high levels of information usage strategic processes with opportunistic strategic content inhibits the flexibility needed to prosper (Fredrickson & Mitchell, 1984). Dynamic conditions appear to offer a unique challenge whereby offensive-minded organizations must emphasize (as suggested by Weick, 1979, 1987) the implementation of new offerings (i.e., action) rather than analysis (i.e., inference). In contrast, organizations following defensive strategies should conduct wide-ranging information processing efforts to identify those offerings that are vital to maintain existing niches and markets.

In trying to understand the roles of process and content for predicting performance, researchers must pay attention to context (Pettigrew & Whipp, 1991). Indeed, evidence was found that one aspect of internal context (i.e., size) moderates the content-performance relationship. For large organizations, the strongest determinant of performance is the extent to which top managers perceive their organizations as having a domain offense or domain defense strategy. This suggests that the market power of large actors allows them to impose their strategic perspective (Mintzberg, 1987b) on the environment in order to create circumstances beneficial for themselves (Daft & Weick, 1984). Further, large organizations’ tendency toward inertia (Quinn, 1985) means that they need to find ways to be innovative and creative in their strategy making; thus, an offense-oriented market perspective is beneficial. In contrast, the actual pattern of strategic actions in the market (i.e., product/service change) is the driving force for smaller organizations that have little slack or economies of scale. Perhaps the vulnerability to environmental forces faced by small organizations means that they benefit by offering unique product/ service attributes to attract customers.

Context is also a critical factor when considering the impact of process/ content interactions on performance. For example, we found that successful large organizations that develop a domain-offensive perspective foster political activity in their strategic processes, but, overall, decrease the amount of information used to assess strategic issues. A possible explanation is that political activity serves as a process stimulus in large, inertial firms through creating constructive conflict (Narayanan & Fahey, 1982). The benefits accrued by dissolving bureaucratic tendencies and “shaking up” standard practices may outweigh the costs of slowing decision making. In contrast, information usage does not appear to necessarily offer frame-breaking or routine-busting benefits. Unlike political activity, increased amounts of information can frequently be processed through existing structures with little or no qualitative adjustment. For small organizations, political activity appears detrimental, especially when product/service change is frequent. Opportunities are rather transient in dynamic environments; thus, there is value in quickly implementing strategic changes. However, top executives often have a high level of commitment to the status quo (Hambrick, Geletkanycz & Fredrickson, 1993). To the extent that they use politics to protect existing conditions, change will be slowed or even prevented. This may be particularly worrisome for small firms, given the role of product/service offerings in determining their performance.

At a broader level, the findings with respect to strategy, size, and performance appear to inform the choice-determinism debate (e.g., Hrebiniak & Joyce, 1985). Specifically, strategy (including process, content, and process/content interactions) explained 65% of the variance in profit for large organizations, but only 28% for small ones. This finding appears to offer support for the ability of large firms to control their environment (Pfeffer & Salancik, 1978) and for the liability of smallness (Carroll & Delacroix, 1982). At the very least, it suggests that further research is needed regarding the role of context variables such as size in this critical debate.

On a related point, the findings inform the relationship between strategy and different types of performance. While strategy was strongly related to financial performance (i.e., profit per admission), it had minimal influence on an operational measure of performance (i.e., admissions per bed). Although an organization’s particular offerings played a role in attracting clients, the low amount of variance explained suggests that the propensity to use the services of a particular hospital may be driven by external context factors such as physician referrals, reputation in the community, number of beds in the market; and by resource endowments (Wernerfelt, 1984) such as location. An implication is that managing impressions and cultivating a positive organizational image (Albert & Whetten, 1985; Dutton & Dukerich, 1991) may be a key to overcoming certain difficult-to-control external obstacles in order to attract clients.

The results of this study should be assessed with some recognition of its limitations. First, it should be noted that data on information usage were gathered through the use of hypothetical, though realistic, case scenarios, rather than in reference to actual situations. Also, the generalizability of our findings may be limited because data were drawn from one industry. For example, hospital size may be, in part, a function of factors such as specialized skill development and population demographics that do not play significant roles in some contexts. However, an increasing number of industries are, like health care, dynamic, including semiconductors, financial services, and retailing (Peters, 1990). Further, the health care industry has been characterized in recent years by factors likely to be of increasing importance to many organizations in the future, including the proliferation of strategic alliances (Longest, 1990; Miles & Snow, 1986) and fluid participation (i.e., variable based on decision content) among organizational members (Ashmos & McDaniel, 1991; Peters, 1990). Thus, the circumstances that have challenged health care organizations since the mid-1980s may foreshadow the future for other contexts. A final concern is the number and comprehensiveness of the variables chosen to operationalize process, content, and context. Employing an extensive array of variables could have rendered the interpretation of interactions untenable. Instead, this study focused on a limited set of variables that had been strongly linked to performance in prior research. Future research might consider additional process, content, and context variables, as well as their synergies, in order to enhance understanding of the determinants of performance.

Finally, as researchers attempt to clarify the nature and consequences of the synergies between process, content, and context, integration of specific process and content issues is an area that seems ripe for research. For example, scholars might look at topics that are traditionally considered as part of the domain of content from a process perspective. Preliminary steps in this direction have examined the implications of cognitive biases and implementation processes for acquisition success (Duhaime & Schwenk, 1985; Jemison & Sitkin, 1986) and the role of top managers’ cognitions in defining differentially-performing strategic groups in an industry (Reger & Huff, 1993). The opposite approach is also relevant: studies focused on the performance implications of strategic processes need to account for the content of the decisions. In both cases, the role of context is likely to be important as well.

Conclusion

Since its emergence in the early 1960s, the field of strategic management has focused on increasing understanding of strategic processes, actions, and performance in organizations. However, the maintenance of a process/content dichotomy may restrict progress toward clearly understanding the relationship between strategy and performance. The findings of this study support this perspective by offering evidence that managers can increase the performance of organizations by understanding and ensuring synergies between process, content, and context. Many contexts, including health care, are increasingly dynamic. Given such conditions, managers are tempted to view the pursuit of new opportunities as a key to success. Indeed, managers should be encouraged to consider emerging alternatives such as new organizational forms (e.g., networks) and sophisticated information technology systems as responses to environmental change (Miles & Snow, 1986; Scott Morton, 1991). The findings presented support the notion that, under dynamic conditions, a strategy focused on market growth and opportunism can enhance organizational performance, but caution that managers must match these actions with context-specific strategic decision making processes.

Acknowledgement: The authors wish to thank the Center for Healthcare Industry Performance Studies (1550 Old Henderson Road, Columbus, Ohio, 43220; 800-859-2447) for providing data for this study. We also thank Chuck Snow and Mick Fekula for their valuable insights.

Appendix

Table A1. Political Activity

Seven point Likert scales were provided for the following items:

“To what extent…

* Do coalitions among top managers change over different strategic issues?

* Is strategic decision making characterized by the ‘push and pull’ of different interests (e.g., administrators, physicians) in the hospital?

* Is conflict an accepted action during strategic decision making?

* Can strategic decision making in this hospital be characterized as an exercise in bargaining, negotiation, and compromise?”

Table A2. Domain Offense/Domain Defense

Seven point Likert scales were provided for the following items:

“To what extent does your hospital…

* Continually search for new patient bases?

* Try to be the first to offer innovative medical services in the area?

* Offer a wide range of medical services?

* Strongly compete with other hospitals for new patients?

* Acquire new medical technology to attract patients?

* Enter into joint ventures with other hospitals in the area?

* Focus on a particular segment of the population to serve?”

Notes

1. For more comprehensive reviews of the strategy literature, see Fahey and Christensen (1986), Huff and Reger (1987), Hrebiniak, Joyce and Snow (1989), and Mintzberg (1990a, 1990b).

2. Of the 54 unusable responses, 31 were because the CEO did not see one or more of the issues addressed in the survey as strategically relevant to his or her hospital, 15 were because the survey was only partially completed, six were because product/service data were unavailable, and two were because the informant was not the CEO.

3. T-tests were done to find whether there were significant differences between responses to the questionnaire items which measured information usage based on the content of the two case scenarios. The t-tests showed that there were no significant differences between responses to the two case scenarios; thus, responses across the cases were averaged for subsequent analyses.

4. Examining the propositions and hypotheses relevant to all organizations (Propositions 1-3, Hypotheses 1a-3d) required us to analyze four regression equations for each performance variable. Hospital size was controlled for in these equations.

Performance = a + [b.sub.1]Size + [b.sub.2]Political Activity + [b.sub.3]Information Usage + e

= a + [b.sub.1]Size + [b.sub.2]Domain Offense/Domain Defense + [b.sub.3]Change in Product/Service Mix + e

= a + [b.sub.1]Size + [b.sub.2]Political Activity + [b.sub.3]Information Usage + [b.sub.4]Domain Offense/Domain Defense + [b.sub.5]Change in Product/Service Mix + e

= a + [b.sub.1]Size + [b.sub.2]Political Activity + [b.sub.3]Information Usage + [b.sub.4]Domain Offense/Domain Defense + [b.sub.5]Change in Product/Service Mix + [b.sub.6]Political Activity x Domain Offense/Domain Defense + [b.sub.7]Political Activity x Change in Product/Service Mix + [b.sub.8]Information Usage x Domain Offense/Domain Defense + [b.sub.9]Information Usage x Change in Product/Service Mix + e

5. The Chow test uses an F-statistic to assess whether splitting a sample into two sub-samples significantly reduces error. If error is significantly reduced, this means that the best fitting model for each sub-sample is different and thus the variable which is the basis for the split is a significant moderator of the relationship under examination. See Hambrick and Lei (1985) for a full explanation of the Chow test.

6. Specifically, the following regression equations were examined for each size category:

Performance = a + [b.sub.1]Political Activity + [b.sub.2]Information Usage + [b.sub.3]Domain Offense/Domain Defense + [b.sub.4]Change in Product/Service Mix + e

= a + [b.sub.1]Political Activity + [b.sub.2]Information Usage + [b.sub.3]Domain Offense/Domain Defense + [b.sub.4]Change in Product/Service Mix + [b.sub.5]Political Activity x Domain Offense/Domain Defense + [b.sub.6]Political Activity x Change in Product/Service Mix + [b.sub.7]Information Usage x Domain Offense/Domain Defense + [b.sub.8]Information Usage x Change in Product/Service Mix + e

References

Albert, Y S. & Whetten, D.A. (1985). Organizational identity. Pp. 263-295 in L.L. Cummings & B.M. Staw (Eds.), Research in organizational behavior, Vol. 7. Greenwich, CT: JAI Press.

Aldrich, H. (1979). Organizations and environments. Englewood Cliffs, NJ: Prentice-Hall.

Alexander, J.A. & Amburgey, T.L. (1987). The dynamics of change in the American hospital industry: Transformation or selection? Medical Care Review, 44: 279-321.

Ashmos, D.P. & McDaniel, R.R. (1991). Physician participation in hospital strategic decision making: The effect of hospital strategy and decision content. Health Services Research, 26: 375-401.

Bettis, R.A. (1981). Performance differences in related and unrelated firms. Strategic Management Journal, 2: 379-394.

Bettis, R.A. & Hall, W.K. (1982). Diversification strategy, accounting determined risk, and accounting determined return. Academy of Management Journal, 25: 254-264.

Blair, J.D. & Boal, K.B. (1991). Strategy formation processes in health care organizations: A context-specific examination of context-free strategy issues. Journal of Management, 17: 305-344.

Blau, P.M. & Schoenherr, R.A. (1971). The structure of organizations. New York: Basic Books.

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

Brittain, J. & Freeman, J. (1980). Organizational proliferation and density dependent selection. Pp. 291-338 in J. Kimberly & R. Miles (Eds.), The organizational life cycle. San Francisco: Jossey-Bass.

Buzzell, R.D, Gale, B.T., & Sultan, R.G.M. (1975). Market share – A key to profitability. Harvard Business Review, 53,(1): 97-106.

Carmines, E.G. & Zeller, R.A. (1979). Reliability and validity assessment. Newbury Park, CA: Sage.

Carroll, G. & Delacroix, J. (1982). Organizational mortality in the newspaper industries of Argentina and Ireland: An ecological approach. Administrative Science Quarterly, 27: 169-198.

Caves, R. & Porter, M. (1977). From entry barriers to mobility barriers: Conjectural decisions and contrived deterrence to new competition. Quarterly Journal of Economics, 91: 241-261.

Caves, R. & Pugel, T. (1980). Intraindustry differences in conduct and performance: Viable strategies in U.S. manufacturing industries. New York University Monograph.

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

Cool, K. & Schendel, D. (1987). Strategic group formation and performance: The case of the U.S. pharmaceutical industry, 1963-1982. Management Science, 33: 1102-1124.

Cosier, R.A. & Aplin, J.C. (1980). A critical view of dialectical inquiry as a tool in strategic planning. Strategic Management Journal, 1: 343-356.

Daft, R.L. & Lengel, R.H. (1986). Organizational information requirements, media richness, and structural design. Management Science, 32: 554-571.

Daft, R.L. & Macintosh, N.B. (1981). A tentative exploration into the amount and equivocality of information processing in organizational work units. Administrative Science Quarterly, 26: 207-224.

Daft, R.L., Sormunen, J. & Parks, D. (1988). Chief executive scanning, environmental characteristics, and company performance: An empirical study. Strategic Management Journal, 9: 123-139.

Daft, R.L. & Weick, K.E. (1984). Toward a model of organizations as interpretive systems. Academy of Management Review, 9: 284-295.

Dess, G.G. (1987). Consensus on strategy formulation and organizational performance: Competitors in a fragmented industry. Strategic Management Journal, 8: 259-277.

Duhaime, I.M. & Schwenk, C.R. (1985). Conjectures on cognitive simplification in acquisition and divestment decision making. Academy of Management Review, 10: 287-295.

Dutton, J.E. & Dukerich, J. (1991). Keeping an eye on the mirror: The role of image and identity in organizational adaptation. Academy of Management Journal, 34: 517-554.

Dutton, J.E, Fahey, L. & Narayanan, V.K. (1983). Toward understanding strategic issue diagnosis. Strategic Management Journal, 4: 307-323.

Eisenhardt, K.M. & Bourgeois, L.J. (1988). Politics of strategic decision making in high velocity environments: Toward a mid-range theory. Academy of Management Journal, 31: 737-770.

Fahey, L. & Christensen, H.K. (1986). Evaluating the research on strategy content. Journal of Management, 12: 167-183.

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.

Fottler, M.D. (1987). Health care organizational performance: Present and future research. Journal of Management, 13: 367-391.

Fottler, M.D. & Lanning, J.A. (1986). A comprehensive incentive approach to employee health care cost containment. California Management Review, 29: 75-94.

Fredrickson, J.W. (1984). The comprehensiveness of strategic decision processes: Extension, observations, future directions. Academy of Management Journal, 27: 445-466.

Fredrickson, J.W. (1986). An exploratory approach to measuring perceptions of strategic decision process constructs. Strategic Management Journal, 7: 473-483.

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

Gale, B.T. (1972). Market share and rate of return. Review of Economics and Statistics, 54: 412-423.

Ginn, G.O. (1990). Strategic change in hospitals: An examination of the response of the acute care hospital to the turbulent environment of the 1980s. Health Services Research, 25: 565-591.

Gioia, D.A. & Chittipeddi, K. (1991). Sensemaking and sensegiving in strategic change initiation. Strategic Management Journal, 12: 433-448.

Hall, R.H, Haas, J.E. & Johnson, N.J. (1967). Organizational size, complexity, and formalization. American Sociological Review, 32: 903-912.

Hall, R.I. (1984). The natural logic of management policy making: Its implications for the survival of an organization. Management Science, 30: 905-927.

Hambrick, D.C. (1979). Environmental scanning, organizational strategy, and executive roles: A study in three industries. Unpublished doctoral dissertation, Pennsylvania State University.

Hambrick, D.C. & Finkelstein, S. (1987). Managerial discretion: A bridge between polar views on organizations. Pp. 369-406 in L.L. Cummings & B.M. Staw (Eds.), Research in organizational behavior, Vol. 9. Greenwich, CT: JAI Press.

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. & Lei, D. (1985). Toward an empirical prioritization of contingency variables for business strategy. Academy of Management Journal, 28: 763-788.

Hamermesh, R.G., Anderson, M.J. & Harris, J.E. (1978). Strategies for low market share businesses. Harvard Business Review, 56(3): 95-102.

Hayes, S.L. III, Spence, A.M., & Marks, D.V.P. (1983). Competition in the investment banking industry. Cambridge, MA: Harvard University Press.

Hedberg, B.L., Nystrom, P.C. & Starbuck, W.H. (1976). Camping on seesaws: Prescriptions for a self-designing organization. Administrative Science Quarterly, 21: 41-65.

Hergert, M. (1987). Causes and consequences of strategic grouping in U.S. manufacturing industries. International Studies of Management and Organization, 18: 26-49.

Hofer, C. & Schendel, D. (1978). Strategy formulation: Analytical concepts. St. Paul, MN: West Publishing.

Hogarth, R.M. & Makridakis, S. (1981). Forecasting and planning: An evaluation. Management Science, 27(2): 115-138.

Hrebiniak, L.G. & Joyce, W.F. (1985). Organizational adaptation: Strategic choice and environmental determinism. Administrative Science Quarterly, 30: 336-349.

Hrebiniak, L.G., Joyce, W.F. & Snow, C.C. (1989). Strategy, structure, and performance: Past and future research. Pp. 3-54 in C.C. Snow (Ed.), Strategy, organization design, and human resource management. Greenwich, CT: JAI Press.

Huber, G.P., O’Connell, M.J. & Cummings, L.L. (1975). Perceived environmental uncertainty: Effects of information and structure. Academy of Management Journal, 18: 725-740.

Huff, A.S. & Reger, R.K. (1987). A review of strategic process research. Journal of Management, 13: 211-236.

Ireland, R.D., Hitt, M.A., Bettis, R.A. & de Porras, D.A. (1987). Strategy formulation processes: Differences in perceptions of strength and weakness indicators and environmental uncertainty by managerial level. Strategic Management Journal, 8: 469-486.

Janis, I.L. (1989). Crucial decisions: Leadership in policymaking and crisis management. New York: Free Press.

Jemison, D.B. & Sitkin, S.B. (1986). Corporate acquisitions: A process perspective. Academy of Management Review, 11: 145-163.

Kerlinger, F. (1986). Foundations of behavioral research. New York: Holt, Rinehart & Winston.

Ketchen, D.J., Thomas, J.B. & Snow, C.C. (1993). Organizational configurations and performance: A comparison of theoretical approaches. Academy of Management Journal, 36: 1278-1313.

Kimberly, J.R. (1976). Organizational size and the structuralist perspective: A review, critique, and proposal. Administrative Science Quarterly, 21: 571-597.

Kimberly, J.R. & Zajac, E.J. (1985). Strategic adaptation in health care organizations: Implications for theory and research. Medical Care Review, 42: 267-301.

Longest, B.B. (1990). Interorganizational linkages in the health sector. Health Care Management Review, 15(1): 17-28.

Meyer, A.D. (1982). Adapting to environmental jolts. Administrative Science Quarterly, 27: 515-536.

Meyer, A.D. (1991). What is strategy’ s distinctive competence? Journal of Management, 17: 821-833.

Michel, A. & Shaked, I. (1984). Does business diversification affect performance? Financial Management, 13(4): 18-25.

Miles, R.E. & Snow, C.C. (1978). Organizational strategy, structure, and process. New York: McGraw-Hill.

Miles, R.E. & Snow, C.C. (1986). Network organizations: New concepts for new forms. California Management Review, 28: 62-73.

Miles, R.H. (1982). Coffin nails and corporate strategies. Englewood Cliffs, NJ: Prentice-Hall.

Miller, D. (1989). Matching strategies and strategy making: Process, content, and performance. Human Relations, 42: 241-260.

Miller, D. & Friesen, P.H. (1983). Strategy-making and the environment: The third link. Strategic Management Journal, 4: 221-235.

Miller, D., Kets de Vries, M.F.R. & Toulouse, J. (1982). Top executive locus of control and its relationship to strategy-making, structure, and environment. Academy of Management Journal, 25: 237-253.

Miller, D. & Mintzberg, H. (1983). The case for configuration. Pp. 57-73 in G. Morgan (Ed.), Beyond method: Strategies for social research. Newbury Park, CA: Sage.

Milliken, F.J. & Lant, T.K. (1991). The effects of an organization’s recent performance history on strategic persistence and change: The role of managerial interpretations. Pp. 129-156 in P. Shrivastava, A.S. Huff & J.E. Dutton (Eds.), Advances in strategic management, Vol. 7. Greenwich, CT: JAI Press.

Mintzberg, H. (1973). Strategy making in three modes. California Management Review, 16: 44-53.

Mintzberg, H. (1987a). Crafting strategy. Harvard Business Review, 65(4): 66-75.

Mintzberg, H. (1987b). The strategy concept I: Five P’s for strategy. California Management Review, 30: 11-24.

Mintzberg, H. (1990a). Mintzberg on management: Inside our strange world of organizations. New York: Free Press.

Mintzberg, H. (1990b). Strategy formation: Ten schools of thought. Pp. 105-235 in J. Fredrickson (Ed.), Perspectives on strategic management. Cambridge, MA: Ballinger.

Mintzberg, H., Raisinghani, D. & Theoret, A. (1976). The structure of “unstructured” decisions. Administrative Science Quarterly, 21: 246-275.

Mintzberg, H. & Waters, J.A. (1985). Of strategies, deliberate and emergent. Strategic Management Journal, 6: 257-272.

Narayanan, V.K. & Fahey, L. (1982). The micro-politics of strategy formulation. Academy of Management Review, 7: 25-34.

Newman, H.H. (1978). Strategic groups and the structure-performance relationship. Review of Economics and Statistics, 60: 417-427.

Oster, S. (1982). Intraindustry structure and the ease of strategic change. Review of Economics and Statistics, 64: 376-384.

Palepu, K. (1985). Diversification strategy, profit, performance, and the entropy measure. Strategic Management Journal, 6: 239-255.

Pearce, J.A. II, Freeman, E.B. & Robinson, R.B. (1987). The tenuous link between formal strategic planning and financial performance. Academy of Management Review, 12: 658-675.

Peters, T. (1990). Prometheus barely unbound. Academy of Management Executive, 4(4): 70-84.

Pettigrew, A. & Whipp, R. (1991). Managing change for competitive success. Oxford: Basil Blackwell.

Pettigrew, A. & Whipp, R. (1993). Managing the twin processes of competition and change: The role of intangible assets. Pp. 3-42 in P.L. Lorange, B. Chakravarthy, J. Roos & A. Van de Ven (Eds.), Implementing strategic processes: Change, Learning, and Co-operation. Cambridge, MA: Blackwell Business.

Pfeffer, J. (1981). Power in organizations. Marshfield, MA: Pitman.

Pfeffer, J. & Salancik, G.R. (1978). The external control of organizations: A resource dependence view. New York: Harper & Row.

Porter, M.E. (1979). The structure within industries and companies’ performance. Review of Economics and Statistics, 61: 214-227.

Porter, M.E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. New York: Free Press.

Provan, K.G. (1991). Receipt of information and influence over decisions in hospitals by the board, chief executive officer, and medical staff. Journal of Management Studies, 28: 281-298.

Pugh, D.S., Hickson, D.J., Hinings, C.R. & Turner, C. (1968). Dimensions of organization structure. Administrative Science Quarterly, 13: 65-91.

Quinn, J.B. (1985). Managing innovation: Controlled chaos, Harvard Business Review, 63(3): 73-84.

Reger, R.K. & Huff, A.S. (1993). Strategic groups: A cognitive perspective. Strategic Management Journal, 14: 103-123.

Rhyne, L.C. (1986). The relationship of strategic planning to financial performance. Strategic Management Journal, 7: 423-436.

Ritvo, R.A., Salipente, R. & Notz, W.W. (1979). Environmental scanning and problem recognition by governing boards: The response of hospitals to declining birth rates. Human Relations, 3: 227-235.

Rumelt, R.P. (1974). Strategy, structure, and economic performance. Boston: Harvard Business School.

Schwalbach, J. (1991). Profitability and market share: A reflection on the functional relationship. Strategic Management Journal, 12: 299-306.

Scott Morton, M. (1991). The corporation of the 90’s: Information technology and organizational transformation. New York: Oxford University Press.

Segev, E. (1987). Strategy, strategy making, and performance. Management Science, 33: 258-269.

Shortell, S.M. & Zajac, E.J. (1990). Health care organizations and the development of the strategic management perspective. Pp. 144-180 in S. Mick (Ed.), Innovations in health care delivery. San Francisco: Jossey-Bass.

Shortell, S.M., Morrison, E.M. & Friedman, B. (1990). Strategic choices for America’s hospitals: Managing change in turbulent times. San Francisco: Jossey-Bass.

Smircich, L. & Stubbart, C. (1985). Strategic management in an enacted world. Academy of Management Review, 10: 724-736.

Snow, C.C. & Thomas, J.B. (1994). Field research methods in strategic management: Contributions to theory building and theory testing. Journal of Management Studies, 31: 457-480.

Summer, C.E., Bettis, R.A., Duhaime, I.H., Grant, J.H., Hambrick, D.C., Snow, C.C. & Zeithaml, C.P. (1990). Doctoral education in the field of business policy and strategy. Journal of Management, 16: 361-398.

Thomas, J.B., Clark, S.M. & Gioia, D.G. (1993). Strategic sensemaking and organizational performance: Linkages among scanning, interpretation, action, and outcomes. Academy of Management Journal, 36: 239-270.

Thomas, J.B. & McDaniel, R.R. (1990). Interpreting strategic issues: Effects of strategy and the information-processing structure of top management teams. Academy of Management Journal, 33: 286-306.

Thomas, J.B., Shankster, L.J. & Mathieu, J.E. (1994). Antecedents to organizational issue interpretation: The roles of single-level, cross-level, and content cues. Academy of Management Journal, 37: 1252-1284.

Thorelli, H.B. (1977.) Strategy + structure = performance: The strategic planning imperative. Bloomington, IN: Indiana University Press.

Tushman, M.L. & Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly, 31: 439-465.

Tushman, M.L. & Romanelli, E. (1985). Organizational evolution: A metamorphosis model of convergence and reorientation. Pp. 171-222 in B.M. Staw & L.L. Cummings (Eds.), Research in organizational behavior, Vol. 7. Greenwich, CT: JAI Press.

Venkatraman, N. (1989). The concept of fit in strategy research: Toward verbal and statistical correspondence. Academy of Management Review, 14: 423-444.

Walsh, J.P. & Ungson, G.R. (1991). Organizational memory. Academy of Management Review, 16: 57-91.

Weick, K.E. (1976). Educational organizations as loosely coupled systems. Administrative Science Quarterly, 21: 1-19.

Weick, K.E. (1979). The social psychology of organizing. Reading, MA: Addison-Wesley.

Weick, K.E. (1987). Substitutes for strategy. Pp. 221-233 in D. Teece (Ed.), The competitive challenge: Strategies for industrial innovation. Cambridge, MA: Ballinger.

Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5: 171-180.

Woo, C.Y. (1983). Evaluation of strategies and performance of low ROI market share leaders. Strategic Management Journal, 4: 123-135.

Zajac, E.J. & Shortell, S.M. (1989). Changing generic strategies: Likelihood, direction, and performance implications. Strategic Management Journal, 10: 413-430.

Zammuto, R.F. (1988). Organizational adaptation: Some implications of organizational ecology for strategic choice. Journal of Management Studies, 25(2): 105-120.

COPYRIGHT 1996 JAI Press, Inc.

COPYRIGHT 2004 Gale Group