Recent changes stemming from the Affordable Care Act (ACA), such as reimbursement penalties for increased readmission rates, have underscored the hospital industry's need to be concerned with quality outcomes. Many of these outcomes are heavily dependent on a hospital's ability to manage community health (Proenca, 2003). Furthermore, there continues to be greater emphasis on community health given demands for hospitals to engage in population health management. To effectively manage community health, hospitals need to have a clear understanding of the needs of their surrounding communities and develop services to meet these needs. Despite the importance of such an orientation, hospitals vary in the degree to which they engage in activities to understand these needs (Olden & Clement, 2000). Such variations represent an important opportunity to improve the health of local communities and raise important questions about the sources of these differences.
Variations in community orientation by hospitals—defined as the organization-wide generation, dissemination, and use of community intelligence to address present and future community health needs (Proenca, 1998)—may be attributed to differences in organizational and environmental characteristics, which may act as catalysts or constraints on hospitals' willingness and ability to engage in such activities. Few studies, to date, have examined the correlates of community orientation (Alexander, Young, Weiner, & Hearld, 2009; Proenca, Rosko, & Zinn, 2000). These studies were primarily focused on organizational correlates of community orientation. Consequently, it is important to assess the community orientation activities of hospitals in years before the community health needs assessment (CHNA) requirement as these activities served as one means of meeting the needs associated with managing the health of populations, which was a major priority of health care reform from the onset. Likewise, the consideration of a broader set of correlates will help expand our understanding of the conditions that support or hinder hospital engagement in community orientation activities. This study does this by exploring whether three dimensions of the environment—munificence, dynamism, and complexity—as well as organizational factors, are associated with the degree of community orientation among hospitals during the period of 2007–2010.
Theoretical Framework and Hypotheses
Institutional theory maintains that certain institutions (i.e., government agencies, professional associations, and citizens) within the environment exert pressure on organizations (DiMaggio & Powell, 1983; Oliver, 1991). Organizations make structural changes in response to these forces (Scott, 1987) and mimic existing models of acceptable organizational behavior and operations to appear legitimate within society (Suchmann, 1995). Legitimacy derives from three types of isomorphic processes—coercive, mimetic, and normative (DiMaggio & Powell, 1983). Coercive isomorphism is pressure from legal and regulatory entities. Mimetic isomorphism is pressure to conform and imitate other successful organizations as a result of uncertainty within the environment. Normative isomorphism is pressure that flows from professional standards within the industry. As a result of these pressures, organizations may respond by imitating other organizations or striking a compromise with external stakeholders to survive (Oliver, 1991), and in this case, survival entails providing the community-oriented activities demanded by the local population or professional standards.
In health care, institutional theory has been used to describe why organizations adopt certain innovations or strategies. For example, Zinn, Weech, and Brannon (1998) found that nursing homes are subject to coercive isomorphism when they serve a higher proportion of Medicare patients and will adopt quality improvement practices similar to area hospitals. That is, nursing homes with a higher number of Medicare patients responded to the demands of hospitals following Medicare postdischarge quality guidelines by adopting total quality management practices to encourage transfer of patients to their facilities.
For similar reasons, it is expected that isomorphic pressures will force hospitals to offer community orientation activities. Specifically, we submit that hospitals will choose to offer community orientation activities to meet the expectations of the local community and stakeholders (Ginn, Shen, & Moseley, 2009a). Thus, from an institutional perspective, when the external environment puts more pressure on hospitals to serve the health needs of the community, hospitals will become more community oriented.
Resource Dependence Theory
Whereas institutional theory is concerned with governmental or societal pressures, resource dependence theory is concerned with the effects of resource scarcity (Oliver, 1991). Resource dependence theory assumes that organizations reduce uncertainty and dependence on the environment by pursuing an array of strategies, including structural changes such as mergers, acquisitions, and interorganizational relationships (Hillman, Withers, & Collins, 2009; Pfeffer & Salancik, 1978). For example, research has shown that hospitals develop relationships with other organizations (Alexander & Morrisey, 1989) or provide more specialized care (Banaszak-Holl, Zinn, & Mor, 1996) in response to scarce resources. Consistent with other research, we submit that hospitals will engage in community-oriented activities as a response to the external environment to better manage their resource dependencies (Ginn et al., 2009a; Ginn, Shen, & Moseley, 2009b; Proenca et al., 2000).
In the sections below, both institutional and resource dependence theories are used to explain why organizational factors may be associated with hospitals' level of community orientation, whereas resource dependence theory is exclusively used to explain the relationships between environmental factors with community orientation.
Hospital ownership. Not-for-profit hospitals have historically been strongly connected to the local community when compared with their for-profit counterparts (Ginn et al., 2009a; Schlesinger, Gray, & Bradley, 1996; Shortell, Washington, & Baxter, 2009). Research has found that not-for-profit hospitals participate in community benefit activities more often than for-profit hospitals (Song, Lee, Alexander, & Seiber, 2013). According to institutional theory, not-for-profit hospitals are more likely to be community oriented given coercive pressures placed on them by community benefit laws (Ginn & Moseley, 2006) as well as the normative expectations of not-for-profit organizations. Likewise, the Internal Revenue Service requires not-for-profit hospitals to provide a certain amount of uncompensated care and show participation in community building activities to maintain their tax exempt status. In an effort to comply with Internal Revenue Service regulations, we expect not-for-profit hospitals to engage in more of those activities related to community orientation. Thus, it is hypothesized that:
H1: Not-for-profit hospitals are associated with a higher degree of community orientation when compared with for-profit hospitals.
Hospital size. Hospitals that undertake community-oriented activities require a variety of resources. For example, conducting community health assessments and developing appropriate services to satisfy identified health needs require additional staffing, technology, and financial resources (Shortell et al., 2009). Larger hospitals typically have access to more slack resources to support these activities (Proenca et al., 2000) and, on average, offer more disease prevention services (Olden & Clement, 2000), which may be the result of their increased size being able to support and garner additional collaborative relationships with other organizations. Moreover, smaller hospitals have a diminished capacity for innovation due to fewer interorganizational relationships (Goes & Park, 1997) and, subsequently, decreased access to resources. Therefore, it is hypothesized that:
H2: Larger hospitals are associated with a higher degree of community orientation when compared with smaller hospitals.
System affiliation. System affiliation fosters an environment where hospitals are more likely to conform to established standards and exhibit behaviors of other hospitals within the system as a result of mimetic pressure (Ginn et al., 2009b). In addition, system-affiliated hospitals may have greater access to resources that assist in providing community-oriented activities. Although system- and non-system-affiliated hospitals may be equally motivated to provide community-oriented activities given the increased focus on population health, the provision of such activities will be dependent on those hospitals that have the resources to do so—in this case, system-affiliated hospitals. Although results vary across environments (Alexander et al., 2009), hospitals associated with a system have greater economies of scale and greater resources (e.g., financial and human capital) for the activities associated with being more community oriented (Bazzoli, Chan, Shortell, & D'Aunno, 2000; Shortell et al., 2009). Consistent with these arguments, system-affiliated hospitals are more responsive to the community (Lee, Alexander, & Bazzoli, 2003). Thus, it is hypothesized that:
H3: System-affiliated hospitals are associated with a higher degree of community orientation.
Network affiliation. Organizations associated with a network can maintain a level of autonomy while managing their resource dependency to continue effectively providing services (Provan & Milward, 2001). Hospitals build relationships with other health organizations to manage resource needs (Ginn et al., 2009a; Zinn, Proenca, & Rosko, 1997). Goes and Park (1997) noted that each member of a collaborative relationship has distinctive capabilities that allow the relationship to expand its outreach through diversification. Following this reasoning, network-affiliated hospitals can utilize the expertise and groundwork laid by other organizations to assist them in providing community-oriented activities. Therefore, we hypothesize that:
H4: Network-affiliated hospitals are associated with a higher degree of community orientation.
Munificence. Munificence represents the scarcity or abundance of resources within the environment that an organization depends on (Castrogiovanni, 1991). Organizations located in more munificent environments can acquire the necessary resources for survival and goal attainment. Studies suggest that hospitals located in wealthier communities have better financial performance, which contributes to hospitals' ability to provide essential medical services (McCue & Diana, 2007). Hospitals operating in environments with more abundant resources may be more likely to acquire the resources (e.g., revenue, requisite staff) and build interorganizational relationships to support community-oriented activities. Therefore, it is hypothesized that:
H5: Hospitals in markets with greater environmental munificence are associated with a higher degree of community orientation.
Dynamism. Environmental dynamism is the rate of instability or uncertainty within an environment (Dess & Beard, 1984; Sharfman & Dean, 1991; Zinn et al., 1997). Although some have suggested that dynamism may stifle adoption of innovations, others have argued that dynamism can make organizations more aware of and responsive to the needs and demands of stakeholders (Miller & Friesen, 1983). This is because organizations in more dynamic environments more actively seek support from a diverse group of external stakeholders to guard against the unpredictable nature of the market (Goll & Rasheed, 2004). Therefore, we expect that, as the environment or surrounding community experiences change, hospitals may respond by engaging in more community-oriented activities that are directly or indirectly receptive to the needs of the community.
H6: Hospitals in markets with greater environmental dynamism are associated with a higher degree of community orientation.
Complexity. Environmental complexity refers to the heterogeneity that exists within an organization's market (Dess & Beard, 1984) and is operationalized as “anything that measures the intricacy of the environment, whether it is competition or the number of regulations,” (Yeager et al., 2014, p. 52). In this study, we measure complexity as the number of hospitals in the market, indicating a greater level of competition. Research shows that hospitals in areas with higher market competition will mimic the behavior of other hospitals to reduce uncertainty and decrease the negative effects of falling behind the competition (Frambach & Schillewaert, 2002).
In addition, we measure complexity by the regulations that organizations are required to contend with and the knowledge necessary to adhere to these regulations (Cannon & St. John, 2007). Hospitals located in communities with a greater number of stringent regulations adapt to comply with those regulations. For example, a regulatory environment, such as those that consist of certificate-of-need (CON) laws, which require hospitals to provide a certain level of uncompensated care for indigent populations, may promote more community-orientated activities in these hospitals. Ultimately, hospitals in highly complex markets may be compelled to conform to societal and regulatory standards, and it is hypothesized that:
H7: Hospitals in markets with greater environmental complexity are associated with a higher degree of community orientation.
Research Design and Operationalization of Variables
Using hospital-year as the unit of analysis, this study conducted a panel data analysis (2007–2010) to test the study hypotheses. The study relied on 10,295 hospital-year observations from the American Hospital Association (AHA) Annual Survey from 2007 to 2010. Data from the AHA Annual Survey were combined with county level data from Area Health Resource Files. Data from 2010 were considered as the last year for this analysis given that the community orientation scale was eliminated from the AHA survey and transitioned to one qualitative question in later years. The study sample excluded government-owned hospitals as these facilities have distinct governance structures, regulations, and funding sources that make it difficult to draw unbiased conclusions when compared with nongovernment-owned hospitals. Variable definitions and data sources of each variable are presented in Table 1.
Community orientation can be thought of as existing along a continuum and, in this study, is measured as a degree of occurrence as opposed to being represented as a binary variable (Proenca, 1998). In keeping with prior research that has used the community orientation scale (Ginn & Moseley, 2006; Proenca, 1998; Proenca et al., 2000), to determine a hospital's degree of community orientation, an aggregated score was computed based on 13 dichotomous questions included in the AHA Annual Survey. Table 2 presents each of the items included in the community orientation scale and the number of hospitals that responded “yes” to engaging in each activity. Therefore, community orientation is a continuous variable ranging from 0 to 13, with zero representing hospitals not providing any community-oriented activities and 13 signifying a hospital that provides all of the community-oriented activities.
Hospital ownership (for-profit and not-for-profit) was a dichotomous variable (0 and 1, respectively). Hospital size was a continuous variable measured as the number of staffed hospital beds. System affiliation was assessed with a binary indicator variable (0 = independent, 1 = system). Likewise, network membership was assessed with a binary indicator variable (0 = not a network member, 1 = network member).
Each dimension of the environment was measured using multiple variables that have been utilized in previous studies as exhibited by the most recent systematic review of studies using resource dependence theory to examine environmental factors (Yeager et al., 2014). Environmental munificence was measured with two variables: (a) the amount of per capita income (per $1000) in the county that the hospital serves and (b) the percentage of the county population under the age of 65 years with health insurance. Environmental dynamism was assessed with three variables: (a) the year-to-year county level percent change in population size, (b) the year-to-year change in the unemployment rate, and (c) the year-to-year change in the number of persons falling below the poverty level. Environmental complexity was measured with two variables: (a) market competition (Herfindahl–Hirschman Index [HHI]) and (b) states with CON laws. Competition was a continuous variable ranging from 0 to 1 or low concentration/high competition to high concentration/low competition. The National Conference of State Legislatures provided the list of states with and without CON laws. The measure used for CON laws was a binary variable (0 = no CON law, 1 = CON law).
To account for additional differences in the organizational and environmental makeup of hospitals, and in keeping with previous research, control variables were also included in the analysis. Hospital location, rural or urban, is considered as it may have an influence on the hospital's access to resources, number of external relationships, and ability to offer activities that qualify as being community oriented. Specifically, research has found that rural hospitals are unable to assess and manage community health at the same rate as urban hospitals (Zhang, Mueller, & Chen, 2009). Second, the teaching status of the hospital is included as a control variable as previous research shows that academic medical centers historically provide a substantial amount of indigent care (Moy, Valente, Levin, & Griner, 1996). Therefore, there may be differences in how responsive academic and nonacademic medical centers are to community needs and the delivery of community-oriented activities.
First, given the dichotomous nature of the items, the Kuder–Richardson Formula 20 (KR-20) was used to test the reliability of the community orientation scale (Kuder & Richardson, 1937). KR-20 estimates showed that all of the items were internally consistent (KR-20 = 0.86). Next, descriptive and additional statistics (tolerance and variance inflation factors) were estimated to identify multicollinearity among independent variables. The results of the tests revealed no issues of multicollinearity, with tolerance levels higher than 0.20 and variance inflation factors below 5. A multivariate regression with random effects was then performed to test the relationships between the organizational and environmental factors and the summated score for community orientation. We opted for this approach, as opposed to others such as a hospital-level fixed-effect panel model, because we were substantively interested in time-invariant differences between hospitals. In addition, although the dependent variable reflected count data, its distribution did not follow a Poisson distribution; therefore, we discarded this approach based on initial univariate analysis.
Descriptive statistics for the entire sample of hospitals (N = 10,295) are shown in Table 3. Most hospitals included in the sample were not-for-profit (83.3%) and affiliated with a multihospital system (64.3%). Furthermore, 40.2% of hospitals in the sample were affiliated with a network. On average, hospitals in the sample had approximately 195 beds staffed for use. As it relates to market characteristics, there was wide variation between the counties where hospitals were located. The counties in which the hospitals were operating had an average per capita income of approximately $37,000 and an average of 436,262 persons under the age of 65 years with health insurance. In addition, there was a substantial amount of change in county level population size (0.62%), unemployment rate (20.87%), and poverty (4.71%) from year to year. The sample hospitals were also located in relatively high concentrated markets with an average HHI score of 0.67, and 62.5% of the hospitals were located in states with CON laws.
Table 3 also displays the percentage of change between the sample of hospitals included in 2007 and those hospitals included in 2010. Hospitals in each year closely reflected the composition of hospitals within the entire sample. However, chi-square and one-way analysis of variance tests showed statistically significant differences between 2007 and 2010 based on the number of community orientation activities performed, system affiliation, per capita income, percentage of population under the age of 65 years with health insurance, and percent change in the population size, unemployment rate, and poverty level.
Because of missing values for several independent variables, the regression results, as shown in Table 4, are based on a final sample of 10,101 hospital-year observations. Hypothesis 1 was supported, with not-for-profit hospitals reporting a higher degree of community orientation compared with for-profit hospitals (B = 1.75, p < .001). Hospital size was positively related to community orientation (B = 0.003, p < .001), providing support for Hypothesis 2. Hypotheses 3 and 4 were also supported as there was a significant association between system-affiliated hospitals and community orientation (B = 0.543, p < .001) and network-affiliated hospitals and community orientation (B = 0.201, p = .001), respectively.
In terms of market characteristics, there were mixed results. For one of the environmental munificence measures used to test Hypothesis 5, a significant relationship was observed. The percentage of the population under 65 years old with health insurance was associated with a higher degree of community orientation (B = 0.028, p < .001). However, per capita income was not significantly associated with the degree of community orientation. Hypothesis 6 posited that environmental dynamism was associated with community orientation, and the analysis did not support this. Community orientation was not significantly associated with the changes in population size (B = 0.007, p = .409), the unemployment rate (B = −0.0005, p = .297), and the poverty level (B = −0.0002, p = .752). The analysis found partial support for Hypothesis 7 with a significant association between community orientation and hospitals in states with CON laws (B = 0.341, p = .001). Finally, the analysis showed that urban hospitals had a higher degree of community orientation when compared with rural hospitals (B = 1.341, p = .001).
Previous research on hospital community orientation has focused solely on the influence of organizational factors. This research has extended earlier work by considering the relationship between community orientation and environmental factors as well as organizational factors. Although the inclusion of environmental factors additionally explained the variation in hospital community orientation (as evidenced in Figure 1), the results of this study suggest that organizational factors related to the internal capabilities of the organization are more robust correlates of a hospital's degree of community orientation, consistent with findings from prior research (Proenca et al., 2000). In addition, our analysis suggests that market factors are selectively associated with a hospital's community orientation. Furthermore, examining years at the start of ACA implementation greatly informs future studies on hospital community orientation that can test the same relationships to determine whether the same factors are significant after the enactment of additional health reform efforts such as the CHNA requirement.
The finding that not-for-profit hospitals have a higher degree of community orientation, as compared with for-profit hospitals, is likely associated with the community benefit activities typically associated with not-for-profits maintaining tax exempt status. Future studies are likely to see even higher correlation between hospitals' not-for-profit status and the degree of community orientation, given the ACA requirement that charitable hospitals must conduct CHNAs and develop strategies for improvement, both of which are included within the current list of activities comprising community orientation. Larger hospitals were also associated with community orientation, although the magnitude of this relationship was small. We also found that hospitals that are system or network affiliated have a higher degree of community orientation. Hospitals that have partnerships with other health care organizations may be imitating the behavior of facilities to which they are connected. The formal arrangement of hospitals affiliated with systems may mandate certain behavior, whereas hospitals affiliated with a network enter a cooperative agreement that may voluntarily incite a change in behavior similar to the network-affiliated organization (Lee et al., 2003). In either instance, the hospital may take on any community-oriented behavior that is reflective of the organizations to which the hospital is closely connected. Moreover, the relationships that hospitals maintain with other organizations may allow hospitals to have greater capacity for undertaking community-oriented activities.
As it relates to environmental munificence, per capita income was not associated with community orientation. Conversely, an increase in the percentage of the population under 65 years old with health insurance was significantly related to a higher degree of community orientation. Our finding may indicate that having a larger portion of the population under the age of 65 years with health insurance is reflective of a community that may be more concerned about health care, in general, as well as the population health activities offered by their local hospital. As a result, we may find that hospitals in these areas may be experiencing more pressure to provide services associated with community orientation.
Environmental dynamism was unrelated to community orientation for each of the measures chosen. This suggests that dynamism is not an important aspect of the resource environment because it is largely intractable from a hospital's perspective. Perhaps, hospitals were unable to immediately respond to the needs of a fast-growing lower socioeconomic population. The recent recession that occurred between 2008 and 2009 saw dramatic increases in the unemployment rate and poverty level and negatively affected the health care sector as well (Truffer et al., 2010). During this period, which is captured by this study, hospitals may have lacked the necessary funding and capacity to pursue a community orientation strategy regardless of the demand or need for the related services. On a more positive note, the nonsignificance of the relationship between these variables also indicates that the hospitals in the sample were not decreasing their services in the face of deteriorating conditions.
Finally, community orientation was significantly associated with only one of the two environmental complexity measures. Market competition may not have been a significant correlate of community orientation because of the particular measure chosen. Studies have noted that the multidimensional nature of environmental complexity may promote the use of other measures (i.e., modified HHI, competitors' geographical concentration) when examining the influence of complexity (Cannon & St. John, 2007). One explanation for why CON laws were significantly associated with community orientation is that CON regulations stipulate that hospitals provide a certain level of care to underserved populations (Campbell & Fournier, 1993). Therefore, hospitals in states governed by CON laws may be more responsive to the local community as a result of the regulatory environment.
Our study had several limitations that represent opportunities for future research. First, community orientation activities were self-reported by hospital staff, and there were no supporting documents to corroborate whether hospitals were indeed performing these activities. This may be improved as the community orientation scale transitioned to an open-ended question in the 2011 AHA Annual Survey. A mixed methods approach is likely necessary for studies that examine community orientation from 2011 and onward, which may assist researchers in obtaining more detailed information about community orientation activities. Second, the dichotomous nature of the questions does not reveal to what degree each individual activity was performed. Thus, the model assumes that each activity is equally important. Developing a new scale that weights community-oriented activities and accounts for the differing amount of time and resources necessary to perform that activity may be beneficial to future studies. Next, with improved methods for collecting data regarding hospitals' community-oriented behavior, future studies may benefit from exploring other perspectives such as institutional logics that would allow for exploring the role of culture and competing interests in influencing hospital community orientation. Finally, despite the theoretical arguments and the use of longitudinal data, the relationships we examined remain associational and we cannot rule out the possibility that the causal direction for some of them may be reversed.
This study found that organizational factors and certain environmental factors influence hospital community orientation. The variables included in the study explained nearly 18% of the variation in hospital community orientation, and collectively, organizational factors explained most of the variation in hospital community orientation. The internal composition of the hospital appears to matter more in determining to what extent hospitals assess community health needs and endeavor to offer the appropriate services to meet those needs. Such findings may be welcome news to practitioners and policymakers as they suggest that the correlates of community orientation activities may be under greater direct control of hospital decision-makers. In contrast, only specific environmental factors predict hospital community orientation, and many have no influence at all, pointing to the need for more research in this area. A better understanding of the factors that influence community orientation can assist hospital administrators and policymakers in stimulating the hospital's role in improving population health and responsiveness to community health needs. For instance, administrators can use these findings to determine how best to pursue a community orientation strategy. This may occur by building interorganizational relationships that help to offset the resources required to offer community-oriented activities. It is noted that, in recent years, hospitals have been successful in conducting CHNAs in conjunction with local entities. Hospital administrators may find additional value in partnering with their local health department, area hospitals, and other community-based agencies to not only carry out the CHNA but also obtain varied perspectives and resource capabilities when developing strategic plans for community health improvement. Furthermore, policymakers may consider using these findings to establish programs that help motivate hospitals that are least likely to be community oriented based on their organizational and environmental compositions. For example, a policy could focus on offering incentives to small, for-profit, and/or less connected hospitals to assist them in engaging in community-oriented activities.
Alexander J. A., & Morrisey M. A. (1989). A resource-dependence model of hospital contract management. Health Services Research
, 24(2), 259–284.
Alexander J. A., Young G. J., Weiner B. J., & Hearld L. R. (2009). How do system-affiliated hospitals
fare in providing community benefit? Journal of Information
, 46(1), 72–91.
Banaszak-Holl J., Zinn J. S., & Mor V. (1996). The impact of market and organizational characteristics on nursing care facility service innovation: A resource dependency perspective. Health Services Research
, 31(1), 97–117.
Bazzoli G. J., Chan B., Shortell S. M., & D'Aunno T. (2000). The financial performance of hospitals
belonging to health networks systems. Inquiry
, 37(3), 234–252.
Campbell E. S., & Fournier G. M. (1993). Certificate-of-need deregulation and indigent hospital care. Journal of Health Politics, Policy and Law
, 18(4), 905–925.
Cannon A. R., & St. John C. H. (2007). Measuring environmental complexity: A theoretical and empirical assessment. Organizational Research Methods
, 10(2), 296–321.
Castrogiovanni G. (1991). Environmental munificence: A theoretical assessment. Academy of Management Review
, 16, 542–565.
Dess G., & Beard D. (1984). Dimensions of organizational task environments. Administrative Science Quarterly
, 29, 52–73.
DiMaggio P. J., & Powell W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review
, 48(2), 147–160.
Frambach R. T., & Schillewaert N. (2002). Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. Journal of Business Research
, 55(2), 163–176.
Ginn G. O., & Moseley C. B. (2006). The impact of state community benefit laws on the community health orientation and health promotion services of hospitals
. Journal of Health Politics, Policy and Law
, 31(2), 321–344.
Ginn G. O., Shen J. J., & Moseley C. B. (2009a). Community benefit laws, hospital ownership, community orientation
activities, and health promotion services. Health Care Management Review
, 34(2), 109–118.
Ginn G. O., Shen J. J., & Moseley C. B. (2009b). Community orientation
and the strategic posture of hospitals
. Hospital Topics
, 87(3), 11–17.
Goes J. B., & Park S. H. (1997). Interorganizational links and innovation: The case of hospital services. Academy of Management Journal
, 40(3), 673–696.
Goll I., & Rasheed A. A. (2004). The moderating effect of environmental munificence and dynamism on the relationship between discretionary social responsibility and firm performance. Journal of Business Ethics
, 49(1), 41–54.
Hillman A. J., Withers M. C., & Collins B. J. (2009). Resource dependence theory
: A review. Journal of Management
, 35(5), 1404–1427.
Kuder G. F., & Richardson M. W. (1937). The theory of the estimation of test reliability. Psychometrika
, 2(3), 151–160.
Lee S. D., Alexander J. A., & Bazzoli G. J. (2003). Whom do they serve? Community responsiveness among hospitals
affiliated with health systems and networks. Medical Care
, 41(1), 165–179.
McCue M. J., & Diana M. L. (2007). Assessing the performance of freestanding hospitals
. Journal of Healthcare Management
, 52(5), 299–307.
Miller D., & Friesen P. H. (1983). Strategy-making and environment: The third link. Strategic Management Journal
, 4(3), 221–235.
Moy E., Valente E. Jr., Levin R. J., & Griner P. F. (1996). Academic medical centers and the care of underserved populations. Academic Medicine
, 71(12), 1370–1377.
Olden P. C., & Clement D. G. (2000). The prevalence of hospital health promotion and disease prevention services: Good news, bad news, and policy implications. Milbank Quarterly
, 78(1), 115–146.
Oliver C. (1991). Strategic responses to institutional processes. Academy of Management Review
, 16(1), 145–179.
Pfeffer J., & Salancik G. R. (1978). The external control of organizations: A resource dependence perspective
. New York, NY: Harper & Row.
Proenca E. J. (1998). Community orientation
in health services organizations: The concept and its implementation. Health Care Management Review
, 23(2), 28–38.
Proenca E. J. (2003). A stakeholder approach to community health management. Journal of Health and Human Services
, 26(1), 10–34.
Proenca E. J., Rosko M. D., & Zinn J. S. (2000). Community orientation
: An institutional and resource dependence perspective. Health Services Research
, 35(5, Pt. 1), 1011–1035.
Provan K. G., & Milward H. B. (2001). Do networks really work? A framework for evaluating public-sector organizational networks. Public Administration Review
, 61(4), 414–423.
Schlesinger M., Gray B., & Bradley E. (1996). Charity and community: The role of nonprofit ownership in a managed health care system. Journal of Health Politics, Policy and Law
, 21(4), 697–750.
Scott W. R. (1987). The adolescence of institutional theory
. Administrative Science Quarterly
, 32(4), 439–511.
Sharfman M. P., & Dean J. W. (1991). Conceptualizing and measuring the organizational environment: A multidimensional approach. Journal of Management
, 17(4), 681–700.
Shortell S. M., Washington P. K., & Baxter R. J. (2009). The contribution of hospitals
and health care systems to community health. Annual Review of Public Health
, 30, 373–383.
Song P. H., Lee S. Y., Alexander J. A., & Seiber E. E. (2013). Hospital ownership and community benefits: Looking beyond uncompensated care. Journal of Healthcare Management
, 58(2), 126–142.
Suchmann M. C. (1995). Managing legitimacy: Strategic and institutional approaches. Academy of Management Review
, 20(3), 571–610.
Truffer C. J., Keehan S., Smith S., Cylus J., Sisko A., Poisal J. A., … Clemens M. K. (2010). Health spending projections through 2019: The recession's impact continues. Health Affairs
, 29(3), 522–529.
Yeager V. A., Menachemi N., Savage G. T., Ginter P. M., Sen B. P., & Beitsch L. M. (2014). Using resource dependency theory to measure the environment in health care organizational studies: A systematic review of the literature. Health Care Management Review
, 39(1), 50–65.
Zhang W., Mueller K. J., & Chen L. W. (2009). Do rural hospitals
lag behind urban hospitals
in addressing community health needs? An analysis of recent trends in US community hospitals
. Australian Journal of Rural Health
, 17(4), 183–188.
Zinn J. S., Proenca J., & Rosko M. D. (1997). Organizational and environmental factors in hospital alliance membership and contract management: A resource dependent perspective. Hospital & Health Services Administration
, 42(1), 67–86.
Zinn J. S., Weech R. J., & Brannon D. (1998). Resource dependence and institutional elements in nursing home TQM adoption. Health Services Research
, 33(2), 261–273.