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Corporate and philanthropic models of hospital governance: a taxonomic evaluation.

Increasing market pressures and regulatory changes have presented hospitals with important strategic challenges in the areas of cost control and resource acquisition (Delbecq and Gill 1988; Shortell 1989). As a result, an increasing number of hospitals face the threat of financial insolvency and closure (Muller and McNeil 1986; Moscovice 1989). Given the formal and legal responsibility of hospital governance to maintain organizational viability and effectiveness, many health care experts contend that hospital boards are being compelled to adopt a more active, critical role in strategy formulation, environmental adaptation, and internal control of hospital management (Barrett and Windham 1984; Alexander, Morlock, and Gifford 1988; Delbecq and Gill 1988; Shortell 1989).

Despite general agreement on the necessity of a more central role for governance, considerable question remains about the form of hospital governance most appropriate for such enhanced board functioning. Two contrasting models of governance dominate this debate: the "philanthropic," volunteer board model traditionally associated with hospitals, or the "corporate" model typically found in the commercial sector. Some health care experts have argued that the philanthropic model, with its emphasis on asset preservation and constituent representation, has worked well and thus needs only minor modifications to become adaptive to the current environmental conditions facing hospitals (Umbdenstock, Hageman, and Amundson 1990; Griffith 1988). Others, however, have broadly questioned the capacity of the traditional, voluntary board model to meet the new strategic challenges posed by a competitive health care environment (Barrett and Windham 1984; Delbecq and Gill 1988; Shorter 1989). These critics view the philanthropic model as anachronistic and recommend the full or partial adoption of the corporate model of governance, with its emphasis on streamlined decision making and strategy development (Kovner 1990; Delbecq and Gill 1988; Shortell 1989).

To date, the debate about the appropriate form of hospital governance has been conjectural and prescriptive, rather than empirical. However, without an understanding of the forms of governance that are actually used by hospitals, the theoretical integrity and practical utility of the corporate-philanthropic governance distinction cannot be assessed. In this study, we propose to attend to this gap in the literature by addressing the following research questions: (1) what are the dominant forms of hospital governance? (2) to what extent do these dominant forms conform to the theoretical archetypes -- corporate or philanthropic? and (3) are certain forms of governance more or less prevalent among hospitals operating under particular organizational and environmental conditions?


The contrast between the corporate and philanthropic models of governance has been presented in several recent writings in the health care literature (Alexander, Morlock, and Gifford 1988; Delbecq and Gill 1988; Fennell and Alexander 1989; Shortell 1989; Kovner 1990). Table 1 summarizes the dimensions along which corporate and philanthropic boards are commonly assumed to differ.

While the corporate-philanthropic governance distinction appears to have gained acceptance in the health care literature, only limited empirical support of these models exists. The first aim of this study, therefore, is to develop an empirically based taxonomy of hospital governance forms in order to assess the theoretical integrity of this governance distinction.

A multivariate, taxonomic approach is dictated by several considerations. First, embedded in the corporate-philanthropic governance distinction is the assumption that the composition, structures, and activities of governing boards cohere into integrated patterns or configurations. This holistic, integrated conception of governance cannot be adequately captured by examining a single feature or dimension of governance (Barrett and Windham 1984), or even by examining multiple governance characteristics independently (Pfeffer 1973; Alexander, Morlock, and Gifford 1988). Second, organizational features are interrelated in complex and integral ways. Organizations may be driven toward a common configuration to achieve internal harmony among its elements of strategy, structure, and context. For hospital governing boards, therefore, a "fit" may exist among various critical dimensions of board structure, composition, and activity as well as between such board configurations and the organizational or environmental context in which the board operates. Finally, the literature on population ecology indicates that over an extended time period, the environment selects out poorly adapted organizational forms. Specifically, only a limited number of possible strategies and structures are feasible in any one type of environment (Hannan and Freeman 1977; McKelvey 1981). To the extent that boards will perform a more central function in hospital viability and survival, an assessment of the number and type of different forms or configurations of governance will provide researchers and hospitals with information on the likely competitors for environmental fitness.

Debate over the corporate-philanthropic governance distinction has also failed to acknowledge the possibility that (a) different forms of governance may be more or less appropriate under different conditions, or (b) certain hospitals may lack the ability or willingness to change their governance configurations. For example, several health care experts have universally prescribed the adoption of the corporate model by hospital boards (Kovner 1990; Delbecq and Gill 1988; Shortell 1989). These writers argue convincingly that the corporate model, with its streamlined decision-making process and greater integration of governance and management, allows for a more rapid strategic response to volatile market conditions, and thus is more adaptive than the philanthropic model to a competitive health care market. Yet these writers do not take into account the degree to which technical (market) and institutional pressures facing hospitals vary in strength across the health care sector (Alexander and D'Aunno 1990). The implications of such variation for the role and form of hospital governance, the resources available for governance change, and the presence or absence of inertial forces will systematically affect the distribution of governing board forms in the hospital sector.

The open systems perspective on organizational behavior suggests that organizations are inextricably tied to their environments, and that structure and behavior in organizations can be explained through an examination of the linkages that exist between organizations and the environments in which they operate. To date, open systems studies of hospitals and other delivery organizations have addressed organizational change by focusing on "rational" strategic adaptation, a perspective emphasizing purposeful change to increase organizational efficiency or access to resources, or both, in the face of environmental contingencies. Often ignored in such discussions is the role of the institutional environment, which asserts that organizations have normative as well as technical or structural sources (DiMaggio and Powell 1983). Organizations are created by and reflect the development and elaboration of institutional roles and beliefs that are independent of structural or relational complexities and technical efficiencies (Meyer and Rowan 1977). Institutional theories emphasize that the survival of organizations depends on their conformity to these externally enclosed requirements and that "institutionalization" promotes stability and conformity in organizations as they seek to maintain legitimacy in the eyes of important external actors (e.g., the community, the state). In this context, governance and governing boards in hospitals serve a key role in linking the organization to important segments of its external environment. Whether or not boards engage in active management or policymaking in hospitals, their existence and structure show the community that the hospitals are indeed conforming to what society believes is the best way to organize health care services--voluntaristic control (Pfeffer 1973; Starkweather 1988).

In sum, hospitals are subject to strong institutional and technical (market) pressures, both of which directly impinge on the role and function of a hospital governing board. To a great extent, these pressures are conflicting and dictate structures and processes that are quite different from each other. On the one hand, market forces and competition suggest a board that is streamlined in its decision-making structure, closely integrated with management, and capable of assisting management by bringing skills and expertise to the process of strategic development. On the other hand, the hospital remains a community organization with close ties and responsibilities to the community it serves. In addition, this organization is responsible to a number of state-sponsored regulators and accrediting bodies on which it depends for continued funding and legitimacy. We suggest that these forces will be present in varying degrees among all hospitals, and that the relative emphasis on institutional versus technical pressures on hospitals will determine the configuration that hospital governing boards assume.

Using this theoretical framework, several hypotheses are advanced that specify the organizational and environmental circumstances under which hospitals are likely to adopt (or be constrained from adopting) a corporate governance configuration. Hospitals that face a comparatively large number of similar providers in their operating environments, for example, may be more likely to adopt the corporate governance model than hospitals that confront only a few competitors, or none at all. Hospitals operating in close geographical proximity with one another are likely to experience greater market pressure as a result of competition for patient admissions and physician affiliations than are hospitals with few competitors in their operating environments (Garnick et al. 1987; Robinson and Luft 1987, 1988). Given highly volatile and competitive market conditions, the corporate governance model is expected to be more adaptive than the philanthropic model, since it allows for more streamlined decision making and more rapid strategic response (Delbecq and Gill 1988; Shortell 1989). Hence:

H1. Hospitals with a greater number of competitors in their market area are more likely to exhibit the corporate model of governance than are hospitals with fewer competitors.

While both urban and rural hospitals confront strong market pressures, urban hospitals have greater access to capital and human resource markets and may thus be more likely to adopt a corporate governance configuration. Urban hospitals, for example, have access to a larger pool of corporate executives who may serve on the board. By contrast, rural hospitals face a continuing population decline and a falling population density, trends that not only reduce tax base subsidization and philanthropic support, but also limit access to human capital (Moscovice 1989). Further, as the sole health provider within the community, a rural hospital possesses a greater degree of institutional visibility than does its urban counterpart (Muller and McNeil 1986). Greater public scrutiny on rural hospitals may further limit their capacity to alter their governance configuration. Hence:

H2. Hospitals located in urban environments are more likely to exhibit the corporate model of governance than hospitals located in rural environments.

Alexander, Morlock, and Gifford (1988) found that religious and secular not-for-profit hospitals were not only more likely than state, county, and municipal hospitals to restructure along corporate lines, but were also more likely to alter their governance practices after corporate restructuring. These researchers suggest that government hospitals experience less discretion than private, voluntary hospitals to alter their internal structure or patterns of service delivery (Alexander and Scott 1984). Government hospitals are subject not only to most of the external controls confronting voluntary, not-for-profit hospitals, but also to additional public and political controls. If it is true that these greater institutional pressures constrain the capacity of government hospitals to adapt to increasing market pressure, then:

H3. Private not-for-profit hospitals are more likely to exhibit the corporate model of governance than are publicly owned (government) hospitals.

While both large and small hospitals face increasing market pressure, the ability of hospitals to adapt is, in part, a function of resources available in excess of those required to maintain core functioning (organizational slack). Such organizational flexibility, typically associated with size, allows larger hospitals to add new functions, to augment or reorganize existing staff, and to otherwise make environmental adaptations through the internal restructuring of resources (Alexander and Morrisey 1989). While the capacity to restructure offers larger hospitals a relative adaptive advantage over smaller hospitals, it frequently introduces a new strategic contingency: managing greater organizational complexity. Coping with this new strategic contingency further increases the likelihood that larger hospitals will adopt a corporate form of governance, because organizational complexity puts greater power in the hands of top management and heightens the demand for board members with specific expertise. Hence:

H4. Larger hospitals are more likely than smaller hospitals to exhibit the corporate model of governance.

Recent research suggests that the form and function of governing boards of hospitals that are members of multihospital systems will differ from those of governing boards of hospitals that are not system members (Fennell and Alexander 1987). The organizational and administrative umbrella provided by multihospital systems represents an institutional context for system hospitals that may alter both their environmental boundaries and their responses to environmental pressures. Specifically, redefining the organizational boundaries to the system level may affect the extent to which adaptation responses occur at the hospital or system headquarters. For example, in multihospital systems many functions, including boundary spanning, management control, and policy/strategy development, occur at the system level rather than at the level of the individual hospital board. In a sense, system status itself buffers individual hospitals from their environments, so that additional hospital board efforts to buffer from or adapt to their environments become less necessary (Fennell and Alexander 1987). Consequently, we anticipate that more corporate forms of governance will be less common among system hospitals as the governance burden for responding to technical/market pressures shifts from the local board to the system:

H5. Hospitals that are members of multihospital systems are less likely than nonsystem hospitals to exhibit the corporate form of governance.

While both teaching and nonteaching hospitals confront strong market pressure, teaching hospitals may be more wedded than nonteaching hospitals to the traditional philanthropic model as a consequence of their emphasis on service to the medical and academic communities. Furthermore, teaching hospitals may be subject to greater institutional scrutiny from the medical profession than nonteaching hospitals, and thus may experience less discretion to alter their governance practices.

H6. Teaching hospitals are less likely than nonteaching hospitals to exhibit the corporate form of governance.



Data for this analysis were obtained from a survey conducted in 1985 by the American Hospital Association (AHA) and the Hospital Research and Educational Trust. A sample of 1,577 nonprofit community hospitals was selected for study.(1) Comparisons with the population of nonprofit community hospitals has a somewhat smaller proportion of government hospitals (30.1 percent in the sample versus 36.3 percent in the population). The sample also overrepresented such hospitals in the East North Central census region (22 percent in the panel sample versus 17.4 percent in the population) and underrepresented them in the Pacific region (4.7 percent versus 10.5 percent, respectively). Aside from these exceptions, the sample is representative of the population of nonprofit community hospitals extant in 1985 on the dimensions of bed size, control, urban-rural location, multihospital system membership, and census region.


Measurement of governance types was based on a broad range of hospital governance attributes conforming to those cited in the literature as distinguishing corporate from philanthropic models of governance. These attributes can be classified into six central dimensions of hospital governance: (1) size, (2) committee structure and activity, (3) board member selection, (4) board composition, (5) CEO power and influence, and (6) bylaws and activities. The computations of both the governing board measures and the external validation measures are presented in greater detail in the Appendix.


The central analytic procedure used in this inquiry was cluster analysis. Cluster analysis is a multivariate statistical technique that seeks to partition or subdivide a set of objects into a hierarchical arrangement of homogeneous subgroupings (Lorr 1983). Cluster analysis is thus a powerful structure-seeking technique that is particularly useful when the number and types of groups (e.g., governance configurations) cannot be determined a priori by the researcher. Ward's clustering method was selected for this analysis. Although biased toward producing clusters of similar size, Ward's method is superior when the clusters are not well separated in multidimensional space (Aldenderfer and Blashfield 1984). Furthermore, Ward's method has been found to outperform other hierarchical methods, except in the presence of outliers (for review, see Punj and Stewart 1983).

Following specification of the observations to be clustered and the clustering attributes of these observations, six analytic procedures were followed (Lorr 1983). First, dimensional analyses were performed on the prespecified set of population attributes using factor-analytic techniques. This set of procedures delineates those attributes inappropriate for further analysis. Inappropriateness is a function either of limited contribution by a variable to the overall variance in the factor structure or of high correlation with another variable.

The second step was detection and elimination of multivariate outlying observations. This was necessary because most clustering algorithms are sensitive to outliers and will produce inaccurate clustering configurations if outliers are retained (Lorr 1983). Third, the clustering algorithm was applied to the reduced list of observations and attributes. Fourth, the resultant cluster solutions were evaluated for reliability through the use of discriminant analysis. Fifth, interpretations of the cluster solution were derived from an analysis of the dendogram and cluster profiles. Finally, analyses of covariance (ANCOVA) were employed to externally validate the cluster solution and to test the hypotheses. A more detailed description of this analytic strategy can be found in Lewis and Alexander (1986).



Dimensional analysis was performed through the examination of the intercorrelation matrix, descriptive statistics, and factor loadings. Together with outlier elimination, this resulted in the retention of 1,526 observations and 12 standardized variables for cluster analysis.(2) Once Ward's method was applied, the cluster solution was examined to determine the number of optimal clusters. Optimality was evaluated by plotting the cubic clustering criterion (CCC) against the number of clusters and examining the plot for peaks in the distribution anywhere above a CCC value of 2 or 3 (Sarle 1983). The cluster solution did not demonstrate, however, a clearly defined optimal number of clusters because the value of the CCC continued to rise without peaking above the value of 2. Therefore, parsimony, cluster stability, and theoretical relevance were employed as additional criteria to determine the appropriate number of clusters. Based on these criteria, 16 clusters were retained.


The reliability of the cluster solution was examined using discriminant analysis. This technique was used to identify cases incorrectly placed in a given cluster by computing the probability that an observation belonged to a cluster (May 1982). The results of this analysis reveal that 90 percent of the observations were correctly classified, where correct classification occurs when the probability of membership has a value greater than .50. Using a more conservative test suggested by Lewis and Alexander (1986), the individual probabilities of membership within each cluster were summed and divided by the size of the cluster. These averages range from 73 percent to 97 percent, suggesting that the discriminant analysis was able to successfully recover the clusters generated by Ward's method. Canonical discriminant function analysis was used to identify governance attributes that significantly discriminate among the clusters. Seven of the original 12 attributes were found to be significant discriminators. In decreasing order of importance these were: CEO voting privileges on the board (CEOBD85), CEO influence in board member selection (CEOIN85), number of standing committees (NUMCOM85), frequency of strategic committee meetings (COMMET85), limit on board member terms (LIMYRS85), emphasis on strategic activities (IMP85), and corporate representation on the board (PCTCOR85). While data on these governance attributes will be displayed, nonsignificant characteristics will be excluded from further description and interpretation.


The basic structure of the taxonomy can be seen in the dendogram. A dendogram traces the hierarchical development of a set of observations (e.g., hospitals). It begins with individual organizations and displays the order in which they cluster into successively larger, more heterogeneous subgroups. The top level of the dendogram displays the hospitals joined in the optimal cluster configuration for the data.

Several pieces of information are contained in the dendogram. First, the larger clusters can be interpreted as the most prevalent governance configurations. Second, the branching structure of the cluster solution indicates what might be considered families, or related groupings, of governance configurations within the overall taxonomy. Finally, the joining levels of clusters of observations suggest the integrity of a given cluster as reflected in the length of the intact line before the line joins other clusters.

The pattern of branching in the cluster solution suggests four major branches or families. Descriptive information on all clusters and branches in the clustering solution is presented in Table 2.


To facilitate interpretation and to provide a common referent for comparison, simplified cluster profiles were constructed to correct for unequal variances across governance attributes and across clusters. These profiles were developed by assigning P, C, or zero signs to each critical governance attribute equal to the number of standard deviations it displayed from the sample mean for that attribute. Specifically, cluster mean scores on governance attributes that fell between 0.0 and 0.10 standard deviations from the sample mean were assigned a zero sign. Cluster mean scores that fell between 0.10 and 1.0 standard deviations above or below the sample mean were assigned either a single P sign, indicating that the attribute showed a philanthropic tendency, or a single C sign indicating a corporate direction. Cluster mean scores that fell between 1.0 and 2.0 standard deviations above or below the sample mean were assigned either two P signs or two C signs, and so forth. A similar display scheme, using lowercase symbols, was employed for those board attributes determined not to be significant discriminators in the cluster solution.

Since these simplified cluster profiles are based on standardized mean values, it is important to bear in mind that the cluster descriptions that follow are not based on absolute values, but on values relative to the sample mean. Since the primary purpose of creating a taxonomy is to identify common or dominant groupings, the discussion now focuses on those clusters within each branch that contain large numbers of hospitals.

Branch One

This branch is the second largest in the taxonomy, consisting of five clusters and 489 hospitals. Three clusters dominate this family, the largest being CL-10 (N = 150), followed by CL-9 (N = 135), and CL-3 (N = 100). All three contribute to a family profile characterized by numerous standing committees, active strategic committees, and a greater degree of CEO power and influence on the board. The three dominant clusters differ, however, with respect to three critical governance characteristics. CL-9 shows an average degree of corporate representation on the board, a higher likelihood of limiting the terms of board members, and a lower likelihood of placing strategic issues at the top of the agenda. CL-3 displays greater corporate representation on the board, a substantially higher likelihood of limiting board member terms, and a substantially higher likelihood of placing strategic issues at the top of the agenda. Finally, CL-10 exhibits greater corporate representation on the board, a lower likelihood of limiting board member terms, and an average likelihood of placing strategic issues at the top of the board agenda.

Branch Two

This branch contains four clusters, representing a total of 319 hospitals. Two clusters dominate this family, CL-8 (N = 117) and CL-2 (N = 107). Both contribute to a family profile characterized by less corporate representation on the board, a lower degree of CEO power and influence on the board, and a substantially higher likelihood that board member terms will be limited. The two dominant clusters differ, however, with respect to three critical governance characteristics. CL-8 shows fewer standing committees, an average frequency of strategic committee meetings, and a lower likelihood of placing strategic issues at the top of the agenda. CL-2 exhibits more standing committees, more active strategic committees, and a substantially higher likelihood of placing strategic issues at the top of the agenda.

Branch Three

This branch is the largest in the taxonomy, encompassing 609 hospitals within four clusters. Two of the largest clusters irrespective of branch/family dominate this family, CL-1 (N = 265) and CL-6 (N = 193). Both contribute to a family profile characterized by an average number of standing committees, more active strategic committees, less corporate representation on the board, a lower degree of CEO power and influence on the board, and a tendency not to limit board member terms. The two dominant clusters differ with respect to the emphasis placed on strategic activity. CL-1 shows a lower likelihood of placing strategic issues at the top of the agenda. CL-6 displays a higher likelihood of placing strategic issues at the top of the board agenda.

Branch Four

This branch is the smallest of the four in the taxonomy, consisting of only two clusters retaining a total of 109 hospitals. CL-4 (N = 79) is the larger of the two, and contains well over twice the number of hospitals in CL-14 (N = 30). Both contribute to a family governance profile characterized by very few standing committees and very inactive strategic committees. The two clusters in this family differ with respect to all of the other critical governance characteristics. CL-14 exhibits an average degree of corporate representation on the board, a greater degree of CEO power and influence on the board, a higher likelihood of limiting board member terms, and an average likelihood of placing strategic issues at the top of the agenda. CL-4 exhibits less corporate representation on the board, a lower degree of CEO power and influence on the board, a lower likelihood of limiting board member terms, and a lower likelihood of placing strategic issues at the top of the agenda.


The taxonomy described in the preceding sections suggests strongly that neither philanthropic nor corporate models (in their pure form) are predominant governance configurations among hospitals. Rather, prevailing forms consist of a mix of philanthropic and corporate governance attributes in different combinations. In other words, the corporate-philanthropic models of hospital governance may be viewed as operating on a continuum, with points on that continuum represented by different "hybrids." The relative positions of clusters along the corporate-philanthropic continuum were determined by constructing "net scores" for each cluster based on the simplified cluster profiles.(3) These net scores reflect the degree to which a given cluster (e.g., hospitals with similar governance configurations) manifests a corporate or philanthropic character: higher net scores with a P designation indicate a more philanthropic orientation, while higher net scores with a C designation suggest a more corporate form. Analysis of these cluster net scores indicates that CL-4 of Branch Four exhibits the most pronounced philanthropic governance features (net score = 6P), followed by CL-5 (net score = 5P) and CL-1 (net score = 4P) of Branch Three. Because it is the largest cluster in the sample, the philanthropic orientation of CL-1 is particularly noteworthy. Similarly, the analysis of cluster net scores indicates that CL-3 and CL-13 of Branch One demonstrate the strongest corporate tendencies (net scores = 9C and 7C, respectively).

The relative positions of the branches along the corporate-philanthropic continuum were assessed by calculating "net percentages" for each branch.(4) Like cluster net scores, branch net percentages indicate the degree to which the hospitals that comprise a given branch exhibit a philanthropic or corporate orientation. A positive net percentage indicates that a branch has a relatively greater philanthropic orientation, while a negative net percentage suggests a branch has a relatively greater corporate bearing. Analysis of branch net percentages indicates that Branch One demonstrates the most pronounced corporate bearing (net percent = -100 %). Branch Three and Branch Four, on the other hand, exhibit the most philanthropic orientation (net percent = +45 %), followed by Branch Two (net percent = +34%). An analysis of the branches suggests, therefore, that philanthropic configurations of governance are more prevalent in our sample than corporate forms: Branches Two, Three, and Four on the philanthropic side of the continuum hold a total of 1,037 hospitals, while Branch One on the corporate side contains 489 hospitals.


One-way analyses of covariance (ANCOVAs) were conducted to validate the cluster solution and to test hypotheses concerning the organizational and environmental conditions under which the corporate governance configuration is more likely to occur. Validation consists of introducing a set of meaningful external criteria (e.g., attributes not employed in the cluster analysis) to determine if the cluster solution is capable of differentiating among governance groupings on these criteria (Aldenderfer and Blashfield 1984). For hypothesis testing, we assessed the directionality of such differences by examining the level or value of the validating variable against the position of governance groupings along the corporate-philanthrophic continuum. ANCOVA was used to adjust the dependent variable (i.e., each external validator) for bed size. This adjustment was made because the intercorrelation matrix suggests that bed size may have a significant confounding effect with respect to the other external validators.

Results of the ANCOVAs are displayed in Table 4. Because comparisons among the 16 clusters resulting from the taxonomic analysis would be exceedingly cumbersome, we elected to compare branches or families of clusters. For each validating variable, cluster branches are arrayed in ascending mean order. Horizontal lines over the branch labels indicate nonsignificant differences among branches based on pairwise t-test comparisons.

ANCOVA results suggest that the branch structure differentiates, to varying degrees, on all but two external validating variables--multihospital system membership and teaching hospital status. Further, even when differences in bed size were controlled, consistent and significant distinctions were obtained between the corporately structured governance branch (BR-1) and those branches that were predominantly philanthropic in their form (BR-2, BR-3, BR-4). Some differentiation also occurred among the three "philanthropic" branches, most notably between Branch Three and Branch Four on competition, urban location, and private versus public control. No significant differences among the three philanthropic governance branches were evidenced for bed size, multihospital system membership, and teaching hospital status. Taken together, these findings suggest that the taxonomy most effectively differentiates between predominantly corporate governance forms and those groupings that fall more toward the philanthropic end of the corporate-philanthropic continuum.

Hypotheses 1-6 posited, respectively, that corporate forms of governance would be found more frequently among hospitals that (1) operated in competitive environments, (2) were located in urban areas, (3) operated under private control/ownership, (4) were larger, (5) were not members of multihospital systems, and (6) were not teaching hospitals. ANCOVA results fully supported three of the six hypotheses and partially supported a fourth. Even when differences in bed size were taken into account, the predominantly corporate governance branch (BR-1) differed in the predicted direction from each of the more philanthropic branches with respect to three organizational and environmental variables (with the exception of multihospital system membership). Specifically, hospitals with boards classified in Branch One operated in environments with a mean of 12.02 competitors compared to a mean of 8.67 for the next closest branch (BR-3). Similarly, Branch One hospitals were predominantly private, with 77 percent of branch membership composed of either secular or religious voluntary hospitals. The next highest percentage of private hospitals was found in Branch Three with 69 percent. Consistent with the prediction of hypothesis 4, average bed size of hospitals with the most highly corporate governance forms (BR-1) was the largest among the four branches, with a mean bed size of 236. Partial support was obtained for hypothesis 2 concerning urban versus rural location. Branch One hospitals were significantly more likely to be located in urban environments than were hospitals in two of the three "philanthropic" branches (BR-2, BR-4). Fifty-six percent of Branch One hospitals were located in urban settings versus only 46 percent of Branch Two hospitals and 38 percent of Branch Four hospitals. Although Branch One hospitals were more likely to be located in urban environments than Branch Three hospitals (56 percent to 52 percent, respectively), the difference was not statistically significant when differences in bed size were taken into account. Finally, two hypotheses did not receive support. Frequency of multihospital system membership did not differ statistically across the four branches. Each comprised 19-23 percent system hospitals. Likewise, no statistically significant differences were found among branches with respect to teaching hospitals; the proportion of teaching hospitals across branches ranged from 8 to 10 percent.


The principal aim of this study has been to assess the theoretical integrity of corporate and philanthropic governance models. Toward this end, an empirically based taxonomy of hospital governance forms was developed, and several hypotheses were tested relating corporate and philanthropic models of governance to specific organizational and environmental conditions.

The results of the taxonomic analysis reveal that hospital governance configurations conform only approximately to the corporate-philanthropic governance typology. Neither the corporate model nor the philanthropic model in their pure forms are found to be prevailing governance configurations. Furthermore, the taxonomic analysis indicates that a substantial degree of variation exists in hospital governance forms. Taken together, these findings suggest that the corporate-philanthropic governance distinction must be seen as an ideal conception rather than as an accurate depiction of hospital governance forms in practice.

The taxonomic analysis also reveals that prevailing hospital governance configurations are characterized by a mix of corporate and philanthropic attributes. Predominantly corporate forms of governance, for example, were distinguished in the analysis from more philanthropic forms through such corporate characteristics as greater CEO power and influence vis-a-vis the board, more active strategic committees, and greater corporate membership on the board. Yet these predominantly corporate forms also displayed several "philanthropic" characteristics, such as large board size, numerous standing committees, occupational heterogeneity among board members, and diffuse responsibility for selecting new board members. Similarly, more philanthropic forms of governance also displayed a mix of corporate and philanthropic board characteristics. In general, the taxonomic analysis suggests that hospital boards are more accurately characterized as "hybrids" rather than as corporate or philanthropic in form.

The predominance of hybrid configurations lends empirical support to the contention made by several theorists that the function of hospital boards is both varied and complex, a function of several competing pressures, including technical, institutional, and historical forces (Alexander and Scott 1984; Fennell and Alexander 1989). Further evidence that hospital boards are confronted by multiple, competing demands may be seen in the relatively loose coupling of structure and activity demonstrated by several dominant governance configurations. This phenomenon may be a testimony to the presence of both institutional and market forces in hospitals' operating environments. As Meyer and Rowan (1977) suggest, decoupling administrative structures from production activity allows organizations to buffer their production activities (e.g., their technical core) and yet maintain legitimized structures. Decoupling governance structures from activities would allow a hospital, for example, to respond to competitive market pressure by emphasizing strategic activity, while at the same time adhering to institutional demands for constituent representation by retaining an occupationally heterogeneous board. If the health care sector is indeed highly developed both technically and institutionally (Alexander and D'Aunno 1990; Alexander and Scott 1984), then the claims by several health care theorists that a "blended" model of governance is the most adaptive form for hospitals may, in fact, hold some validity (Griffith 1988; Shortell 1989). Alternatively, the predominance of "hybrid" governance models may simply represent a transition from philanthropic forms to more corporate forms of governance. This alternative explanation implies, however, that the institutional pressures confronting hospitals have not remained stable, as the first interpretation suggests, but rather have decreased in strength and will continue to weaken in the future. Clearly, further empirical investigation is needed to test these competing accounts.

The taxonomic analysis also shows that measures of CEO power and influence vis-a-vis the board best distinguished more corporate forms of governance from more philanthropic forms. One possible interpretation is that the greater degree of CEO power and influence among more corporate configurations reflects the pathway through which the strategic contingencies of cost control and competition impinge on governance structure and activity. From a resource dependence perspective (Pfeffer and Salancik 1978), CEOs are the internal actors best able to address these strategic contingencies by virtue of their possession of extensive information on hospital operation and their functional authority in implementing strategic policy made by the board. Under these circumstances, resource dependence theory suggests that the CEO will gain power vis-a-vis the board and thereby will push for the adoption of a more strategically oriented, streamlined, businesslike board. Support for this proposition may be found in recent studies that show gains in power by hospital CEOs vis-a-vis the board throughout the 1980s (Alexander 1990) and that hospital CEOs want board members with greater business experience (Wesbury and Flory 1984; Koska 1989). While such evidence is suggestive, a conclusive test of the "pathway" hypotheses awaits future empirical work of a longitudinal nature.

Finally, the taxonomic analysis yielded the somewhat surprising finding that board size does not significantly distinguish more corporate forms of governance from more philanthropic forms. This finding was unexpected, given the wealth of literature in organization theory that suggests that size is associated with particular configurations of structure and activity (Blau and Scott 1962; Blau and Schoenherr 1971). One possible explanation is that board size may be a fixed constraint for hospitals. Historically, boards have been self-perpetuating bodies, placing no limit on the number of consecutive terms a board member may serve. Although many hospitals' boards have recently begun to impose such a limit, it may take several years of turnover to result in a smaller board size, particularly in light of the fact that it is difficult to fire board members without a major restructuring of the organization.

Beyond these descriptive findings, the analytic results of this study provided support for the thesis that board form varies systematically by specific organizational and environmental characteristics of hospitals. ANCOVA results indicate that hospitals exhibiting more corporate-type governance configurations are more likely to be large, privately owned, located in urban environments, and operating in competitive markets than are hospitals exhibiting more philanthropic governance configurations. Taken together, these findings indicate that hospitals facing stronger technical (e.g., market) forces and weaker institutional (e.g., regulatory, normative) pressures are more likely to exhibit corporate forms of governance than are hospitals that face either relatively weaker technical pressures or stronger institutional pressures, or both. These results, however, must be considered exploratory; future research should attempt a more detailed specification of environmental conditions, perhaps through the use of multiple indexes for such constructs as market competition and regulatory pressure. Moreover, future research might call greater attention to the organizational context in which hospital boards operate. For example, research by Alexander, Morlock, and Gifford (1988) suggests that corporately restructured hospitals may be more likely to demonstrate a corporate governance configuration than hospitals that have not undergone corporate restructuring.

The nonsignificant findings with respect to multihospital system membership may be a measurement issue. Data limitations prevented us from distinguishing among different forms or models of multihospital systems. Yet previous research indicates that governance structures vary systematically across multihospital system types (Lewis and Alexander 1986; Morlock and Alexander 1986). Future research might attempt a more detailed specification of multihospital system membership to account for variations in system characteristics such as the centralization of decision-making authority. For example, multihospital systems characterized by highly centralized decision making, particularly with respect to strategic issues, may be more likely to demonstrate philanthropic governance models at the local governing board level than do systems characterized by greater decentralization.

A central premise underlying much of the prescriptive writing concerning the corporate-philanthropic distinction is the notion that the corporate model of governance is more adaptive to the current health care climate than is the philanthropic model. While this study offers empirical support for hypotheses based upon this assumption, the validity of the assumption itself has not yet been empirically assessed. Toward this end, the taxonomy could be used to test whether hospital boards with more corporate-type configurations differ significantly from those with more philanthropic-type configurations with respect to several critical outcomes, such as the speed of strategic response to environmental change, the incidence of CEO succession, the degree of benefit derived by the community, and the propensity to engage in major organizational change. The results of such an inquiry might lend greater weight to the proposition that corporate forms of hospital governance are indeed more responsive than philanthropic forms to the strategic challenges currently facing hospitals.

Finally, it is interesting to speculate about whether the variation in hospital governance configurations revealed by the taxonomic analysis will increase or decrease over time as hospital boards confront new challenges in the 1990s. The theoretical position adopted in this study is that the adoption of more corporate forms of governance is a function of changes in the relative strengths of technical and institutional pressures confronting hospitals. From this perspective, the institutional norms and standards that previously provided "structuration" in the health care sector, have weakened and become supplanted by increasing technical demands. Since there is no one best way to organize in order to achieve technical efficiencies and superior performance in the marketplace (Galbraith 1973), variation in hospital governance forms can be expected to increase as boards become both less concerned with mapping onto their own structures the characteristics of the institutional environment and more concerned with achieving technical efficiencies and buffering their technical cores from environmental disturbances.

While this theoretical position is compelling, Alexander and D'Aunno (1990) provide an equally plausible alternative perspective. They contend that the corporatization of the health sector may be driven not by changes in the relative strengths of technical and institutional pressures, but rather by a change in the content of institutional beliefs held by important groups in the health care sector. In particular, they point to the increasing popularity of the belief that health care should be run as a business. If the adoption of more corporate forms of governance is in fact a function of changes in the content of institutional beliefs, then variation in hospital governance configurations may be expected to decrease as hospital boards seek the gains in legitimacy that accrue by becoming isomorphic with the institutional environment. While this study can offer no empirical test of these competing theoretical predictions, future research on hospital governance is encouraged to adopt a taxonomic, configurational approach so that this question can be directly addressed.



Board Size (A1A). The number of members on a hospital's board.

Committee Structure and Activity

Number of Standing Committees (NUMCOM). NUMCOM is the number of standing committees a hospital board has, drawn from the following list: finance/budget committee, joint conference/professional affairs committee, quality assurance committee, bylaws committee, community relations committee, nominating committee, bioethics committee, strategic or institutional planning committee, personnel committee, and executive committee.

Frequency of Strategic Committee Meetings (COMMET). The frequency with which a hospital's strategic committees meet (score of 1 indicates less than two times a year, score of 2 indicates two times or more a year) is divided by the total number of strategic committees the hospital has. Following Shortell (1989) and Delbecq and Gill (1988), strategic committees included: finance/budget committee, quality assurance committee, nominating committee, strategic planning committee, and executive committee.

Board Member Selection

Diffusion of Board Member Selection Responsibility (DIFFUS). DIFFUS refers to the number of organizational bodies involved in the selection of new board members. Selection involvement consists of appointing, nominating, or electing board members. Organizational bodies may include the board nominating committee, board executive committee, governmental body, hospital board, hospital's corporation or association, hospital medical staff, local community, and parent corporation board.

Selection Criteria for New Board Members (BACK). This refers to the degree to which skills/expertise selection criteria are used in selection of new board members. It is constructed as the number of skills/expertise selection criteria used by a hospital, divided by the total number of selection criteria used by a hospital. Following Shortell (1989) and Delbecq and Gill (1988), the following criteria were considered skills/ expertise: business or financial skills, knowledge of health care issues or administration, background in clinical practice, and legal skills. Other possible selection criteria include: ability to raise money, ideology/values, involvement in community or civic activities, political influence in the community, regional or subgroup constituent (social or economic) representation, time available, other.

Board Composition

Occupational Heterogeneity of Board Members (HETER). The breadth or concentration of occupations represented on the governing board is calculated as a percentage of board membership of each of the 14 mutually exclusive groups squared, and then summed (similar to a Herfindahl index). The maximum value of the index is one if the entire board consists of one occupational group. Smaller values indicate a more heterogeneous board. Occupational categories assessed were: physicians, other health professionals, hospital's CEO, religious, lawyers, educators, bankers/financiers, independent business persons, corporate executives, farmers/ranchers, government officials/agency representatives, labor officials/representatives, and homemakers.

Corporate Representation on the Board (PCTCOR). A ratio-scaled measure is constructed as the number of board members occupationally classified as corporate executives, divided by the total number of board members.

Medical Representation on the Board (MD). A ratio-scaled measure is constructed as the number of board members who are physicians with active staff privileges at the hospital, divided by the total number of board members.

CEO Power and Influence

CEO Influence in Board Member Selection (CEOIN). A ratio-scaled measure is constructed as the number of organizational bodies involved in member selection to which the CEO belongs (range from 0 to 3), divided by the total number of bodies involved in board member selection (range from 0 to 8).

CEO Role on Governing Board (CEOBD). A score of 0 on this ordinal-scaled measure indicates that the CEO is not a member of the board, a score of 1 indicates that the CEO is a nonvoting (ex-officio) board member, a score of 2 indicates that the CEO is a voting board member, and a score of 3 indicates that the CEO is chair of the board.

Bylaws and Activity

Limit on Board Member Terms (LIMYRS). A score of 0 on this dummy-coded measure indicates that a hospital places no limit on board member terms, while a score of 1 indicates that a hospital does place a limit.

Board Member Compensation (COMP). A score of 0 on this dummy-coded measure indicates that no compensation is offered to board members, while a score of 1 indicates that compensation is offered. This measure excludes travel reimbursement from the definition of compensation.

Emphasis on Strategic Activity (IMP). This dummy-coded measure indicates whether or not in the past 12 months strategic issues have occupied most of the board's time. Topics classified as strategic issues include: diversification, mergers, joint ventures, strategic planning, and competitive position. Measure was coded 0 if strategic issues did not occupy most of the board's time, 1 if strategic issues occupied most of the board's time. Note that a score of 0 does not indicate that strategic issues were not important agenda items, merely that they were not the most important items.

External Validation Variables

Hospital Size. Hospital size is measured by the number of hospital statistical beds, from the 1985 American Hospital Association Annual Survey.

Hospital Ownership. Ownership is assessed using a dummy-coded variable. A score of 0 indicates that a hospital is publicly owned; a score of 1 indicates that it is privately owned.

Multihospital System Affiliation. A score of 0 on this dummy-coded variable indicates that a hospital has no affiliation with a multihospital system, while a score of 1 indicates an affiliation with a multihospital system. This measure excludes contract management affiliation.

Urban/Rural Location. Using a dummy-coded variable a score of 0 indicates that a hospital lies outside of a Metropolitan Statistical Area, while a score of 1 indicates that a hospital lies within an MSA.

Hospital (Market) Competition. This is measured as the number of other general hospitals within a 15-mile radius of the focal hospital.

Teaching Hospital. A score of 0 on this dummy-coded variable indicates that a hospital is not a member of the Council of Teaching Hospitals, while a score of 1 indicates that a hospital is a member.


We gratefully acknowledge the financial support of the Interuniversity Consortium for Organizational Studies, University of Michigan, and the American Hospital Association for providing the data for this study.


1. Investor-owned hospitals were excluded from the analysis based on evidence that governing boards of these organizations function as advisory boards to the corporate headquarters of multihospital systems, rather than as policymaking units in their own right (Alexander and Schroer 1985; Morlock and Alexander 1986).

2. The univariate statistics revealed that only 10 percent of the sample of hospitals offered compensation for board service (COMP85). Such a highly skewed distribution prevented the use of this variable in cluster analysis (Romesburg 1984). Hence, only 12 of the original 13 governing board attributes were standardized and submitted to the clustering algorithm.

3. Net scores were calculated. First, for each cluster, a numerical score was assigned to each critical governance attribute equal to the number of standard deviations it displayed in the simplified cluster profile. Second, each critical governance attribute was examined and designated as showing a corporate or philanthropic direction, based on the corporate-philanthropic distinction outlined earlier in this article. Third, these numerical scores were summed within each cluster to arrive at philanthropic and corporate subtotals. Finally, the corporate subtotal was subtracted from the philanthropic subtotal, resulting in a net score for each cluster.

4. Net percentages were calculated. First, the clusters within a family were designated as either philanthropic or corporate in their model governance, based on the net score derived using the method just described. Thus, clusters exhibiting a negative net score were designated corporate clusters, while clusters exhibiting a positive net score were designated philanthropic clusters. Clusters exhibiting a zero value were designated as neither corporate nor philanthropic in orientation. Second, the percentage of hospitals in a branch exhibiting a philanthropic governance orientation was subtracted from the percentage of hospitals in that branch exhibiting a corporate governance orientation, resulting in a net percentage for each branch. Third, the net percentages for each branch were plotted to show the relative positions of each family along the corporate philanthropic continuum.


Aldenderfer, M., and R. Blashfield. Cluster Analysis. Newbury Park, CA: Sage Publications, 1984.

Alexander, J. A. The Changing Character of Hospital Governance. Chicago: Hospital Research and Educational Trust, 1990.

Alexander, J. A., and T. D'Aunno. Transformation of Institutional Environments: Perspectives on the Corporatization of Health Care. Innovations in Health Care Delivery. Edited by S. Mick and associates. San Francisco: Jossey-Bass, 1990.

Alexander, J. A., and M. Morrisey. "A Resource-Dependence Model of Hospital Contract Management." Health Services Research 24, no. 2 (June 1989): 259-83.

Alexander, J. A., and K. Schroer. "Governance in Multihospital Systems: An Assessment of Decision-making Responsibility." Hospital & Health Services Administration 30, no. 2 (1985): 9-20.

Alexander, J. A., L. Morlock, and B. Gifford. "The Effects of Corporate Restructuring on Hospital Policymaking." Health Services Research 23, no. 2 (June 1988): 311-27.

Alexander, J. A., and W. Scott. "The Impact of Regulation on the Administrative Structure of Hospitals: Toward an Analytic Framework." Hospital & Health Services Administration 29, no. 3 (May/June 1984): 72-85.

American Hospital Association. Status of State Capital Expenditure Regulation. Chicago: AHA, 1987.

Barrett, D., and S. Windham. "Hospital Boards and Adaptability to Competitive Environments." Health Care Management Review 9 (Winter 1984): 11-20.

Blau, P., and R. Schoenherr. The Structure of Organizations. New York: Basic Books, Inc., 1971.

Blau, P., and W. Scott. Formal Organizations. San Francisco: Chandler, 1962.
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Author:Weiner, Bryan J.; Alexander, Jeffrey A.
Publication:Health Services Research
Date:Aug 1, 1993
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