Where Do We Go From Here? An Examination of the Relationship Between Changes in Social Structure and Strategic Priorities in Cross-Sector Collaborative Organizations

Abstract

Cross-sector collaborative organizations are increasingly viewed as an effective means of addressing multifaceted health and social challenges. Given their dependence on volunteers to develop and implement strategy, members’ perceptions of future strategic priorities is a critical concern for leaders and sponsors of these organizations. Research set in more hierarchical, single-sector organizations acknowledges the important relationship between structure and strategy; however, relatively little research has explored these relationships in the context of collaborative organizations. We examined these relationships using multiple rounds of an Internet survey. All three dimensions of social structure (locus of decision making, formalization, and integration) had independent associations with participant’ perceptions of different strategic priorities, suggesting there is more than one approach to influencing the perceived priorities of the alliance. However, some dimensions of the social structure changed more than other dimensions over time, highlighting differential opportunities for influencing strategic priorities.

Keywords

multisector health care alliances social structure perceptions of strategic priorities

Introduction

Cross-sector collaborative forms of organizations are increasingly viewed as an effective means of addressing multifaceted health and social challenges (Institute of Medicine, 2013; Nicholson, 2013). The advantage of these collaborative approaches, relative to independent and uncoordinated efforts, is that they are a local response to a fragmented health care system that typically lacks coordination. They attempt to ameliorate these problems by bringing together diverse stakeholders to work collaboratively to improve health and social conditions in local communities (Painter & Lavizzo-Mourey, 2008; Roussos & Fawcett, 2000). Identifying future strategic priorities is a critical activity for these types of organizations as they are often heavily dependent on time-limited and restricted revenue sources (e.g., program-specific grants; Scheirer, 2005; Scheirer, Hartling, & Hagerman, 2008; Shediac-Rizkallah & Bone, 1998). As these revenue sources expire, they are faced with important strategic decisions that may affect the allocation of resources, relationships with participants and funders, and even survival of the alliance as an organization (Carroll & Stater, 2009; Tuckman & Chang, 1991). Consequently, an important consideration for leaders, members, and sponsors of these organizations is a better understanding of the factors that may influence stakeholder’ perceptions about the strategic direction. Stakeholder perceptions of these issues are especially important in the context of collaborative organizations, which consist predominantly of volunteers where members are often responsible for developing and implementing strategy.

Social structure—defined as the pattern of relationships among organizational participants (Scott, 1998)—in particular, may play an important role in influencing perceptions of strategic priorities. Previous research has emphasized the relationship between structure and strategy (Chandler, 1962; Mintzberg, 2009). Initial discussions of this relationship argued that that an organization’s strategy shapes its structure, often indirectly via tasks and technology (Chandler, 1962), while more recent arguments have described the relationship as reciprocal (Mintzberg, 2009). For example, enacted structures may constrain future strategies (Hall & Saias, 1980). Notwithstanding these arguments, we submit that multisector collaborative organizations possess unique characteristics (e.g., diverse goals, dependence on volunteers to set strategy) that differentiate them from more hierarchical, single-sector organizations and raise questions about how structure and strategy are related.

Given these differences and the importance of identifying future priorities for these organizations, we examined changes in three different aspects of the social structure of multisector health care alliances (“alliances”) to address the following question—What is the relationship between changes in alliance’ social structure and members’ perceptions of future priorities? The study extends other research in this area by providing insights into the relationship between structure and strategy in collaborative organizations designed to address complex health and social issues. Findings of the study are important for leaders and sponsors of multisector organizations and programs who are interested in identifying ways to sustain their efforts over the long term and enhance their opportunities for being effective.

Conceptual Framework

The Distinctiveness of Multisector Alliances as Collaborative Organizations

We define an alliance (and cross-sector collaborative organizations more generally) as a collection of three or more legally autonomous organizations from different industry sectors (e.g., education, health care, criminal justice) that work together to achieve a collective goal (Provan & Kenis, 2008). Although alliances may be legally constituted entities, they differ from other legal entities, such as dyadic partnerships, joint ventures, and single-sector equity-based alliances, due to multiplex relationships that span multiple industry sectors. While there is some debate about whether collaborative, cross-sectoral organizations represent new organizational forms (Agranoff, 2006; McGuire, 2006), others have effectively argued that collaborative organizations such as the alliances we study occupy a unique, “midrange” space in how organizations address complex social problems. At one extreme are organizations that interact very little when addressing these problems, opting instead to pursue these problems independently. At the other extreme are organizations that attempt to address these problems by formally merging their capabilities. Regardless of one’s views on how “new” these approaches are, there is greater agreement that their prevalence as a means of addressing complex social problems is on the rise (Ansell & Gash, 2008).

Future Strategic Priorities: Change or Maintain Status Quo?

Organizational scholars have believed for some time now that a critical issue faced by most organizations is a tension between change and stability (March, 1991). Change is believed to provide a number of benefits for organizations, such as adaptation to shifts in the external environment (e.g., new policies, new technology) and improved competitive positioning. Indeed, for some organizational analysts, change is tantamount to organizational survival (Boulding, 1950; Cameron & Whetten, 1983; Quinn & Cameron, 1983). Others, however, have argued the benefits of a more stable model of organizations, one that enables organizations to better exploit existing knowledge and resources, as opposed to searching for new opportunities (March, 1991). More recently, however, there is growing recognition that this “tension” may be a false dichotomy and that change and stability may not be mutually exclusive issues for organizations (Birkinshaw, Crilly, Bouquet, & Lee, 2016; Tushman & O’Reilly, 1996). For example, organizations may be interested in expanding geographically (e.g., globally or simply beyond a local market) while remaining responsive to local needs and interests (Birkinshaw et al., 2016; Tushman & O’Reilly, 1996).

Together, the previous arguments suggest that organizations may emphasize change, stability, or some combination of the two when considering what activities to prioritize moving forward. Research suggests that organizations achieve “ambidexterity”—both change and stability—through structural differentiation (Benner & Tushman, 2003; Tushman & O’Reilly, 1996). For example, organizations may have a dedicated research and development unit to explore new technologies while manufacturing units focus on refining existing technologies to make them more efficient. Such approaches, however, are less feasible in collaborative organizations, which often lack high levels of differentiation, but instead identify new ideas and implement and refine these ideas through the efforts of distributed networks of volunteers (Butterfoss, 2007; Nicholson, 2013). Such distinctions raise important questions about whether these organizations can be ambidextrous and if so, what does it look like in practice?

Changes in Social Structure

There is long-standing scholarly interest in structural attributes of bureaucratic organizations, dating back at least as far as Weber (1947). Nevertheless, structure has not received the same level of attention in the cross-sector collaborative organization literature (Bryson, Crosby, & Stone, 2006), especially empirical tests of theoretical propositions (cf., Ansell & Gash, 2008). According to Bryson et al. (2006), this is likely due to an emphasis on organizing as a process (e.g., conditions that give rise to alliances) rather than the organization as a formal arrangement. Consequently, relatively little research has examined different dimensions of social structure in the context of cross-sector collaborative organizations and its consequences for organizational functioning. The few notable exceptions examined networks of single sector, direct service providers that defined their scope of work narrowly (i.e., mental health services), rather than convening organizations with broad goals (e.g., improving the health of the community), which rely on a broad range of volunteer member organizations from different industry sectors to get work done. Consequently, it is unclear whether existing theoretical perspectives on structure apply as well to these organizations.

The emphasis on organizing as a process, as well as the complex and ambiguous environments that collaborative organizations often operate, has led some organizational analysts to conclude that structure is dynamic in collaborative organizations (Huxham & Vangen, 2005).

Therefore, we focus on changes in three dimensions of alliance social structure that others have considered as structural correlates of collaborative-level performance (Bryson et al., 2006) and we submit are especially important in the context of cross-sector collaborative organizations because of their dependence on volunteers from diverse industry sectors to develop and implement strategy.

Locus of decision-making authority refers to where power resides and organizational decisions are made in an alliance (Aiken & Hage, 1968; Damanpour, 1991). Formalization is defined as the degree to which the purpose of alliance activities (e.g., committees, meetings) and the processes used to make decisions and get work done are clearly articulated to and recognized by members. This definition differs somewhat from formalization in more traditional, hierarchically structured organizations (e.g., prescribed rules of job behavior/job descriptions; formal operating procedures) due to the voluntary nature of their membership. Integration refers to approaches utilized by an organization to communicate and draw together the activities performed by different organizational members (Scott, 1998). In the case of alliances, where the majority of participants may be volunteers and not “employees” of the organization, we define integration as the extent to which an alliance and its leaders engage in efforts to coordinate and align the efforts of internal and external stakeholders. In the sections below, we describe arguments about the general benefits and costs of these different dimensions, followed by a discussion of how they may comparatively contribute to whether participants emphasize change or stability as a future priority.

Locus of Decision-Making Authority

Centralized decision-making authority has been argued to expedite decision making and enable tighter coordination of interdependent activities (Fredrickson & Mitchell, 1984). Similarly, centralization can streamline information processing and facilitate more efficient and consistent communication across a large number of constituents (Auh & Menguc, 2007). Thus, more centralized authority structures may be particularly effective at initiating change in settings such as alliances where there are different values and goal orientations among members. On the other hand, studies have found that higher levels of centralization can reduce the quality and quantity of ideas utilized for problem solving (Nord & Tucker, 1987; Sheremata, 2000). Moreover, higher levels of decision-making centralization can reduce one’s sense of control over work, thereby diminishing the likelihood that organizational participants will seek out and find innovative solutions (Atuahene-Gima, 2003; Damanpour, 1991).

Formalization

Formalization can act as a frame of reference that directs attention toward restricted aspects of one’s surrounding environment (Weick, 1979). Consequently, a clearer understanding of how decisions are made or why certain processes are in place may reduce the likelihood that organizational members will experiment and deviate from existing behaviors or utilize novel knowledge sources. Indeed, some have argued that formalization is directed toward reducing variation in behaviors that may lead to change, thus reinforcing the status quo (Benner & Tushman, 2003). On the other hand, due in part to its ability to enhance predictability, formalization has also been shown to reduce role ambiguity and role conflict in organizations while fostering greater organizational commitment (Podsakoff, Williams, & Todor, 1986). Greater clarity about existing roles and responsibilities, in turn, can help organizations such as alliances identify gaps in existing capabilities and personnel, both of which may highlight opportunities and the need for change.

Integration

Interest in integration and its conceptual counterpart, differentiation, have a long history in organizational research (Fayol, 1916; Lawrence, Lorsch, & Garrison, 1967). Differentiation refers to how various activities performed by an organization are distributed among individuals and work units, while integration refers to approaches utilized by an organization to communicate and coordinate the activities performed by these different entities (Scott, 1998). On one hand, higher levels of differentiation are believed to be associated with a number of positive organizational outcomes, such as innovation, because it reflects more diverse knowledge bases that can be used to identify and solve problems (Aiken, Bacharach, & French, 1980). On the other hand, more, and more diverse, knowledge bases likely provide diminishing returns without an ability to connect them (Jansen, Van Den Bosch, & Volberda, 2006; Pertusa-Ortega, Zaragoza-Sáez, & Claver-Cortés, 2010). Integration is especially important in an alliance context because differentiation occurs by design, through the participation of stakeholders from different industry sectors. Thus, the real challenge is harnessing those diverse knowledge bases.

Collectively, the previous arguments suggest that the three dimensions of an alliance’s social structure are likely to be associated with members’ assessments of an alliance’s future priorities regarding change or stability. However, consistent with theoretical development efforts in this area (Ansell & Gash, 2008; Bryson et al., 2006), they are less definitive with respect to the direction of these relationships. Therefore, we do not offer explicit, a priori hypotheses. Instead, we focus our attention in this analysis on comparisons between these dimensions—directionally and statistically—to provide a foundation for future researchers considering the simultaneous and relative impact of the different dimensions of social structure.

Method

Study Context

The Aligning Forces for Quality (AF4Q) initiative—the Robert Wood Johnson Foundation’s (RWJF) signature effort to lift the overall quality of health care, reduce racial and ethnic disparities in 16 targeted communities (Scanlon et al., 2016)—was predicated on this belief. The premise of AF4Q was that the greatest improvements in the quality of care can be achieved when aligning the efforts of key forces of actors from different industry sectors, including health care providers (physicians and hospitals), purchasers (employers and insurers), and consumers (patients), through multistakeholder alliances. Consistent with these ambitious goals, the initiative adopted a broad vision of improving quality by implementing and disseminating innovative quality improvement programs, such as the patient-centered medical home, community-wide public reporting, improving access to care). However, RWJF left the identification and prioritization of specific goals and the approaches for pursuing them to be determined by the alliances. The alliances we studied were at a critical juncture—the conclusion of the AF4Q program—which meant that generous financial and technical support that had been provided by RWJF was coming to an end. Consequently, alliances and their members were engaged in a process of evaluating what their strategic priorities should be moving forward.

Data Sources

Data were drawn from an Internet-based survey of alliance participants fielded in five different periods: Round 1 (April 2007-December 2007); Round 2 (October 2008-October 2009); Round 3 (October 2010-February 2012); Round 4 (April 2013-April 2015); and Round 5 (June 2015-September 2015). The response rates for these rounds were 47.8% (n = 570), 48.5% (n = 623), 56.5% (n = 604), 53.9% (n = 557), and 38.6% (n = 638), respectively. The first four survey rounds provided information related to participant’ perceptions of alliance governance and management (e.g., decision-making style). The fifth round occurred during the summative evaluation stage of the project and focused on alliance participant’ perceptions of issues related to sustainability (e.g., positioning to meet goals over next 5 years). All survey rounds captured information related to participant characteristics (e.g., level of participation).

Measures

Dependent Variables

Two issues were salient for the alliances when considering their future priorities at the termination of major funding: (a) The value proposition of the alliance and (b) the programmatic strategy. Value proposition refers to the perceived advantage of pursuing the alliance’s goals (e.g., improving community health) via collaborative means relative to doing so independently. Programmatic strategy refers to the number and types of programs used by the alliance in pursuit of its goals and the target population(s) of those programs.

Based on these issues, we constructed a single dependent variable that reflected whether alliance members viewed change or maintaining the status quo in these areas as a priority for the alliance. The variable was based on four survey items from the final round of the survey that asked respondent opinion’s about the level of priority the alliance should give to four goals in the future: (a) sustaining the alliance’s role as a neutral forum, (b) ensuring that initiatives started by the alliance continue to be offered, (c) expanding the population(s) that the alliance initiatives serve, and (d) initiating new programs beyond those currently offered. All four items were rated on a 5-point scale (1 = not at all important, 5 = very important). We averaged the first two items to create a single variable indicating “maintaining the status quo” as a priority. Similarly, we averaged the last two items to create a variable reflective of “change” as a priority. We then grouped respondents into one of four mutually exclusive categories based on whether their average score on these two variables was above or below 4.0, which was chosen as the cutoff because it indicated whether respondents believed it was a “high” or “essential” priority. These four categories were labelled as: (a) change as a major priority (i.e., average score of 4.0 or greater on change variable only; e.g., expand public reporting to other markets); (b) maintaining the status quo as a major priority (i.e., average score of 4.0 or greater on maintaining the status quo variable only; e.g., maintain existing portfolio of programs); (c) both change and maintaining the status quo as major priorities (i.e., average score of 4.0 or greater on both variables; e.g., keep existing programs but alliance needs a change in leadership); and (d) neither change nor maintaining the status quo as major priorities (i.e., average score less than 4.0 on both the change and status quo variables; e.g., disband alliance entirely).

Independent Variables

The study included three independent variables of primary interest (Table 1). Locus of decision-making authority at a given point in time was assessed as the alliance-level average of two items, both of which were measured on a 5-point scale (1 = strongly disagree; 5 = strongly agree). To construct a point-in-time variable, we first constructed a composite score for individual respondents by averaging across these two items for individual respondents. We then aggregated to the alliance-level by averaging the composite scores for individual respondents within an alliance, r_wg = 0.69; intraclass correlation coefficient (ICC; 2) = 0.13. The final analytic variable was operationalized as the change in centralized authority between Round 4 and Round 1 (Round 4 average centralized authority—Round 1 average centralized authority). Because higher scores reflect more centralized decision-making authority, positive values of this variable indicate increasing levels of centralized decision-making authority.

Table 1.

Social Structure Variable Definitions, Items, and Descriptive Statistics.

Variable	Definition	Survey items	r_wg (ICC)	Round 1, M (SD)	Round 2, M (SD)	Round 3, M (SD)	Round 4, M (SD)	Change^a, t (p)
Centralized decision-making authority	The locus of power and organizational decisions in an alliance.	1. At present, the main authority of the alliance is vested in the alliance’s members (reverse scored). 2. At present, the main authority of the alliance is vested in the alliance’s leaders.	0.69 (0.13)	2.50 (0.94)	2.47 (0.93)	2.47 (1.01)	2.38 (0.98)	−1.60 (.13)
Formalization	The degree to which the purpose of alliance activities (e.g., committees, meetings) and the processes used to make decisions and get work done are clearly articulated to and known by members.	1. At meetings, the purpose of each task or agenda item is well-defined. 2. The alliance task forces and committees have clearly defined roles and responsibilities. 3. I get enough advance notice and background information to prepare for the alliance meetings. 4. The alliance has standard procedures for making decisions.	0.90 (0.83)	3.91 (0.62)	3.96 (0.64)	4.09 (0.64)	4.09 (0.64)	4.77 (.001)
Integration	The extent to which an alliance and its leaders engage in efforts to align the efforts of stakeholders.	1. The alliance’s leadership gets people to work productively together. 2. The alliance’s leadership utilizes the skills and talents of many, not just a few. 3. The alliance’s leadership promotes teamwork among the alliance members. 4. The balance of responsibility between the alliance members and paid staff is appropriate.	0.88 (0.70)	4.07 (0.67)	3.96 (0.64)	4.00 (0.65)	4.09 (0.64)	1.91 (.08)

Note. ICC = intraclass correlation coefficient.

Difference between Round 4 and Round 1.

Formalization at a given point in time was assessed as the alliance-level average of four items. All items were measured on a 5-point scale (1 = strongly disagree; 5 = strongly agree). To construct a point-in-time variable, we first constructed a composite score for individual respondents by averaging across these items for individual respondents. We then aggregated to the alliance-level by averaging the composite scores for individual respondents within an alliance, r_wg = 0.90; ICC(2) = 0.83. The final analytic variable was operationalized as the change in formalization between Round 4 and Round 1. Because higher scores reflect greater formalization, positive values of this variable indicate increasing levels of formalization.

Finally, integration was assessed as the alliance-level average of four items. All items were measured on a 5-point scale (1 = strongly disagree; 5 = strongly agree). Once again, a composite score for individual respondents was first constructed by averaging across the four items for individual respondents, followed by aggregation to the alliance-level by averaging the composite scores for individual respondents within an alliance, r_wg = 0.88; ICC(2) = 0.70. The final analytic variable was calculated as the difference in integration between Round 4 and Round 2, with positive values of this variable indicate increasing levels of integration.

Control Variables

The analysis controlled for several respondent characteristics that may be associated with their perceptions of sustainability. We controlled for a respondent’s level of involvement in alliance activities with three dummies: (a) 0% to 5% of his or her time devoted to alliance activities (referent), (b) 5% to 25%, and (c) 25% to 100%. Six dummies were used to account for different types of stakeholders: (a) insurer/health plan (referent), (b) employer, (c) provider organization (hospital/health system, physician/physician organization), (d) consumer organization (patient advocacy organization); (e) government organization, and (f) other organization (e.g., nonprofit organization, academic institution). Three dummy indicators were included to control for the organizational structure of the alliance: (a) independent, stand-alone alliance (referent); (b) subsidiary of a parent organization; and (c) informal partnership. Alliance size was measured as the number of alliance members. Following D’Aunno, Alexander, and Jiang (2017), we measured the heterogeneity of alliance members with a modified Gini coefficient (based on the proportion of participants belonging to the different stakeholder groups identified above).

Analytic Strategy

Our univariate analysis served two purposes. First, we wanted to assess members’ opinions about sustainability issues during the summative stage of the evaluation to determine whether certain types of opportunities were viewed as more important priorities to alliance participants. Second, we wanted to evaluate how the social structure of alliances had changed over the AF4Q program. Our multivariate analysis tested the relationship between these changes and members’ opinions using a multinomial logistic regression model. The analysis accounted for clustering of individuals within alliances. Prior to estimating these models, we first tested the assumption of the independence of irrelevant alternatives using the Hausman and McFadden test and the Small and Hsiao test (Cheng & Long, 2007). Both tests suggested that a multinomial logistic regression was appropriate given our outcomes. Results are reported as average marginal effects, or, marginal effects calculated at the actual value of the covariates. To facilitate interpretation in the multivariate analysis, the independent variables were normalized to range between 0 and 100; thus, the relationships reported based on these models can be interpreted as the change of probability of reporting a priority (e.g., change; maintain status quo) for each 1 percentage point increase in social structure.

The study also included two supplementary analyses. One analysis tested the robustness of our social structure variable operationalization strategy. A second analysis used open-ended responses from survey respondents to understand better the differences between the four strategic priority categories. More details on both of these analyses are provided later.

Results

Sample Characteristics

On average, the degree of centralized decision-making authority declined over the study period, although the change was not statistically significant (t = −1.60, p = .13; Table 1). In Round 1, the alliance-level degree of centralized decision-making authority was 2.50, on average and declined to 2.38 in Round 4. In contrast, the degree of formalization increased significantly over the study period (t = 4.77, p < .001), from an average of 3.91 in Round 1 to 4.09 in Round 4. The degree of integration increased between Round 1 (M = 4.07) and Round 4 (M = 4.09), although once again this change was not statistically significant (t = 1.91, p = .08).

Survey respondents were predominantly providers (31.9%), followed by “other” stakeholders (18.9%) and alliance staff members (17.5%; Table 2). Nearly one half of the respondents (46.0%) reported devoting 5% or less of their time to alliance activities, while less than one fifth (18.1%) reported devoting more than 25% of their time to alliance activities. Nine of the study alliances (60%) were structured as independent alliances, while three were structured as subsidiaries of a parent organization (20%) and three were structured as informal partnerships of organizations (20%). There were 110 members, on average, per alliance.

Table 2.

Sample Characteristics.

Dependent variables
Both change and maintain status quo as major priorities, n (%)	244 (38.4)
Change as major priority, n (%)	148 (23.3)
Maintain status quo as major priority, n (%)	94 (14.8)
Neither change nor status quo as major priority, n (%)	150 (23.6)
Control variables
Respondent level
Level of participation, n (%)
0% to 5%	290 (46.0)
65% to 25%	226 (35.9)
26% to 100%	114 (18.1)
Stakeholder type, n (%)
Staff	113 (17.5)
Insurer	55 (8.5)
Provider	206 (31.9)
Government	27 (4.2)
Employer	25 (3.9)
Consumer	97 (15.0)
Other	122 (18.9)
Alliance level
Organizational structure, n (%)
Independent	9 (60.0)
Suborganization	3 (20.0)
Partnership	3 (20.0)
Alliance size, M (SD)	110.3 (76.7)
Gini coefficient, M (SD)	0.7 (0.1)

Over 38% of the survey respondents believed that the alliance should adopt both change and maintain the status quo as major priorities over the next 5 years (Table 2). Similar percentages of respondents believed that the alliance should adopt change as its major priority (23.3%) or it should adopt neither change nor maintain the status quo as major priorities (23.6%). The fewest number of respondents (14.8%) believed that the alliance should maintain the status quo as a major priority in the future.

Multinomial Logistic Regression Results

Because our primary interest in this study was in comparing how different dimensions of an alliance’s social structure were associated with respondent perceptions of an alliance’s priorities, the results below are organized around each priority.

Change as the major priority

As alliances increased in formalization, integration, and centralized authority, members were less convinced that change should be the major priority (Table 3). The magnitudes of these relationships, however, varied substantially across the three dimensions, with the marginal effect for increasing levels of integration over 3 times larger than the marginal effects for formalization and centralized authority, respectively. A 1 percentage point increase in the level of integration was associated with a 0.019 (p < .001) lower probability of reporting “change as the major priority.” A 1 percentage point increase in the level of centralized decision-making authority in an alliance was associated with a 0.006 (p < .01) lower probability of a respondent reporting “change as the major priority.” Finally, a 1 percentage point increase in the level of formalization was associated with a 0.007 lower probability of respondent reporting “change as the major priority,” although this relationship was not statistically significant (p = .17).

Table 3.

Multinomial Regression Results, Change in Social Structure.

	Both change and maintaining status quo as major priorities	Change as the major priority	Maintain status quo as major priority	Neither change nor status quo as major priorities
	ME	ME	ME	ME
Social structure variables
Increase in centralized authority	−0.003	−0.006**	0.002	0.006
Increase in formalization	−0.013	−0.007	0.006	0.014*
Increase in integration	0.020***	−0.019***	−0.005	0.004
Control variables
Level of participation
0% to 5%	Referent	Referent	Referent	Referent
5% to 25%	0.005 (0.054)	−0.023 (0.033)	0.086 (0.028)**	−0.069 (0.043)
25% to 100%	0.209 (0.060)***	−0.036 (0.060)	0.001 (0.049)	−0.174 (0.046)***
Stakeholder type
Insurers	Referent	Referent	Referent	Referent
Employers	0.075	−0.024	−0.096*	0.044
Providers	0.079	0.045	−0.078	−0.045
Government	−0.045	0.100	0.014	−0.070
Consumer	0.129	−0.103	0.060	−0.087
Other	0.075	−0.058	0.038	−0.055
Staff	−0.005	−0.025	−0.009	0.039
Alliance size	−0.0005	0.001***	0.00006	−0.001***
Gini	−0.392***	−0.242***	−0.152***	0.786***
Alliance type
Stand alone	Referent	Referent	Referent	Referent
Partnership	0.068	0.114***	−0.028	−0.155***
Suborganization	−0.172*	0.428***	−0.049	−0.206***
Average predictions	0.394	0.242	0.152	0.211

p < .05. **p < .01. ***p < .001.

Maintain status quo as the major priority

None of the changes in social structure were significantly associated with members’ assessments of maintaining the status quo as a major priority.

Both change and status quo as major priorities

Increasing levels of integration were associated with a greater likelihood of respondents believing both change and maintaining the status quo were important priorities, with a 1 percentage point increase in the level of integration associated with a 0.020 (p < .001) greater probability of reporting “both change and maintaining the status quo as major priorities.” In contrast, respondents who were members of alliances with increasing levels of formalization and centralized decision-making authority were not significantly associated with the belief that both change and maintaining the status quo were major priorities.

Neither change nor maintain status quo as major priorities

A 1 percentage point increase in the level of formalization was associated with a 0.014 (p < .001) higher probability of reporting “neither change nor maintain status quo as major priorities.” The other two dimensions of social structure—centralized decision-making authority and integration—were not significantly associated with the belief that neither change nor maintaining the status quo were major priorities.

In sum, our analysis indicates that increases in all three dimensions of the social structure were consistently associated with two strategic priorities. Specifically, increases in all three dimensions were associated with a decreased likelihood of members believing that change is a major priority for the future and an increased likelihood of members believing neither change nor maintaining the status quo were major priorities. In contrast, the findings were more mixed with respect to “both change and maintaining the status quo as major priorities,” with increasing levels of centralized authority and formalization associated with a lower likelihood of perceiving this as a major priority and increasing levels of integration associated with a greater likelihood of perceiving this as a major priority.

Supplemental analysis

We conducted a supplemental analysis as a check on our operationalization of social structure. Specifically, we repeated the analysis using the Round 4 level of social structure as the independent variables instead of change over time. This analysis (available from the corresponding author on request) found relatively few significant relationships between social structure and members’ perceptions of strategic priorities and point to a number of interesting questions and considerations for future researchers. For example, these findings suggest that changes in social structure may be more salient for members and thus, may be more important considerations for alliance leaders than point-in-time assessments. From a research standpoint, such findings also underscore the importance of using methodological designs that can capture these dynamic processes (e.g., longitudinal data, qualitative or mixed methods).

Discussion

The purpose of this article was to extend previous research by simultaneously examining multiple dimensions of social structure and their relationship with future strategic priorities in the context of multisector health care alliances. In doing so, we addressed the often theorized but empirically underexamined relationship between structural characteristics and strategy. In general, the priority most strongly endorsed by alliance members was pursuing change while maintaining the status quo, with nearly 40% of all respondents indicating this as the major priority. This finding—combined with nearly 25% of the respondents also suggesting “change as the major priority”—indicate that most members believe change of some type was necessary for the alliances to be successful in the future. In contrast, relatively few members (15%) believed that the alliances should emphasize strictly “staying the course” as the major priority. It was somewhat surprising, however, to see nearly one quarter of the respondents indicate that the alliances should not make change nor maintain the status quo as major priorities.

Based on these findings, we were interested in better understanding the four priorities and how they differed from each other. To do so, we conducted another supplementary analysis that examined responses to the open-ended survey question that asked respondents “Please let us know what other thoughts you have about the effectiveness, future, or sustainability of the alliance.” Table 4 provides a description of the number and percentage of respondents providing responses to the open-ended question, along with some illustrative responses by priority category.

Table 4.

Illustrative Open-Ended Responses by Sustainability Priority Category.

Sustainability priority	Providing open-ended response, n (% of category)	Not providing open-ended response, n (% of category)	Response
Change as the major priority	51 (34.5)	97 (65.5)	“Identifying new sources of funding or developing a market product that could generate a consumer-based revenue stream would provide for sustainability beyond RWJF AF4Q funding.” “The new leader of [the alliance] gives the board hope . . . you need to recruit a strong leader to head the organization if you want to move forward and continue to be a significant presence.”
Maintain status quo as the major priority	47 (50.0)	47 (50.0)	“Create a more clearly focused role and better communication about vision and goals.” “AF4Q was a great concept but got buried in too many goals and projects. The focus needs to be on equal participation of all stakeholders, generating results from a few key initiatives and value by making these results scalable, transferable, and permanent.”
Both change and stability as a major priority	119 (48.8)	125 (51.2)	“Collaboration is a key to creating an environment which embraces change.” “The leadership is strong with great insight and flexibility to make changes quickly with specific programs when appropriate in the community to make them more successful.”
Neither change nor stability as a major priority	56 (37.3)	94 (62.7)	“After having many conversations . . . the value proposition is not clearly defined or articulated.” “For every stakeholder group, [the alliance] needs to do a better job of demonstrating how it will add value to what organizations are already doing on their own—in a way that convinces organizational leadership that the organization is better off collaborating with [the alliance].” “It is unclear from my perspective of serving on a committee as to the impact of the work of [the alliance]. I really can’t name any specific initiatives from [the alliance] that have shown a demonstrable impact in the community . . . it isn’t clear exactly how this group was related to the results. I’m not really sure why it exists except to provide employment for staff.”

Respondents in the “neither change nor maintain the status quo as major priorities” category could be best characterized as questioning the value of the alliance, to them personally, to the organizations they represented, and to the community at large. In most cases, respondents felt that the alliance was not able to establish a clear value proposition in the community. In contrast, respondents in the “maintaining the status quo as a major priority” category were in agreement with the strategies and programs adopted by the alliance, but believed the alliance simply needed to focus and communicate those strategies better to existing stakeholders. For members endorsing “both change and maintaining the status quo as major priorities.” change and stability were not inherently at odds with each other. Rather, stability in certain domains of the alliance were important for providing capacity to change in other areas. Respondents in the “change as a major priority” were similar in their views that significant changes were required for the alliance to be successful in the future; however, they expressed a wide range of opinions about what those changes should be. For some respondents, new products and services were necessary for the alliance to be sustained. For others, changes in the leadership of the alliance were necessary to be successful in the future.

Although change was a priority for a majority of the respondents, our multivariate analysis indicated that perceptions of increasing levels of two of the three dimensions (centralized decision making and integration) of social structure were associated with a lower likelihood of respondents believing that change was a major priority. One explanation for these findings is that perceived increases in these dimensions of social structure may serve as a barrier to novel problem solving and experimentation (Benner & Tushman, 2003; Nord & Tucker, 1987), resulting in members believing the current course is the correct course (i.e., organizational inertia). This may be the case especially for centralized decision making if it promotes decisions among a small cadre of people (Latour, 1984). Similar findings for integration, however, seem more counterintuitive given the espoused advantages of aligning and integrating the skills and knowledge of a diverse membership (Dyer & Singh, 1998). One potential explanation for this finding is that, while integration as a goal for alliances may be desirable, the structures required to produce integration may be burdensome, time consuming, and even create conflict among participants. For example, the organizational demography literature shows that certain types of diversity among top management teams—namely functional background and length of time with the organization—is associated with less innovation (Ancona & Caldwell, 1992; O’Reilly, Snyder, & Boothe, 1993) and less comprehensive assessments of opportunities and threats in the environment (Miller, Burke, & Glick, 1998). Likewise, other research has found that diversity in the types of information that members bring to bear on a problem is beneficial in promoting desired outcomes (e.g., novel problem solving), while value diversity (e.g., mission of the organization, goals) is detrimental to such outcomes, especially when tasks are complex and interdependent (Jehn, Northcraft, & Neale, 1999). Such is the case with alliances that draw on members from diverse industry sectors to work together to address problems that often cannot be addressed independently. It may be that increasing levels of integration that pull together these diverse perspectives help enhance the knowledge bases available to the alliance, but these enhancements are offset by conflicting values. Such explanations remain speculative at this point, however, and future research is needed to assess their validity.

It is also notable that increasing levels of formalization were associated with a greater likelihood of respondents endorsing “neither change nor maintain the status quo” as the major priority. This finding, along with the open-ended responses from participants who endorsed this priority and expressed concerns regarding the value proposition of the alliances, suggests that perceptions of increasing levels of formalization may raise questions in the minds of participants regarding the role and importance of the alliance in the community. One potential explanation for this finding is that perceptions of increasing formalization may attenuate the collaborative advantages of the alliance in the eyes of participants by moving it in the direction of existing hierarchical organizations in the community. If so, then the real paradox for alliance leaders may be that some changes in social structure that enable it to effectively coordinate participant’ efforts comes at the expense of members’ perceptions of the alliance’s value to the community.

Limitations

Several limitations related to the data and measures should be recognized that point to opportunities for future research. First, the analysis relies on data from a common source, that is, surveys of participants. Thus, the data may be subject to common-method bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). We diagnosed whether common-method variance (CMV) was a problem with two tests (Podsakoff et al., 2003; Richardson, Simmering, & Sturman, 2009). First, we conducted Harman’s single-factor test where all variables are loaded onto a single factor via factor analysis and constrained so that there is no rotation (Eichhorn, 2014). CMV may be present if the single factor explains more than 50% of the variance. In our case, the single factor accounted for 39.6% of the variance. The second test (Common Latent Factor) was similar to the Harman single-factor test with all observed variables being related to a single factor; however, the test retains the latent factors and their relationships that were included in the main analysis. CMV may be present if the common shared variance of this new latent factor exceeds 50%. In our case, the shared variance was 44.6%. Collectively, these analyses indicate that CMV was not a significant issue for the study. Second, the study response rate was lower than we would have liked, especially in Round 5 (39%). Researchers using data from earlier waves of the survey conducted analyses to identify possible nonresponse bias and found little evidence of any differences between responders and nonresponders in terms of their perceptions of the alliance. Third, our dependent variable was based on respondent’ opinions about alliance priorities in the future. We believe such opinions are important, especially in the context of collaborative organizations such as alliances that depend on the voluntary cooperation of its members. Nevertheless, other assessments of the strategic priorities (e.g., actual strategic direction) might be beneficial in future studies. Likewise, we constructed our dependent variable using cutoff values of 4.0. This value was chosen because we believed it represented a clear delimitation (i.e., “high” or “essential”) of a respondent’s opinion about a given priority; yet other cutoff values are possible. Finally, there was a lag of approximately 18 months between the final survey used to construct our variables related to perceptions of strategic priorities and the Round 4 survey used in the construction of our social structure variables. Ideally, the items used to construct the social structure variables would have been available in the final survey, but the focus of the survey at this point had shifted to meet the needs of the summative portion of the evaluation.

Theoretical Implications

One of the primary theoretical contributions of our study is a better appreciation of the value of “ambidexterity” and what it looks like in the context of collaborative organizations. Previously, theoretical (and empirical) considerations of ambidextrous organizations have predominantly focused on independent, hierarchically structured organizations, and focused on how these organizations may engage in both exploration and exploitation and its effect on outcomes (O’Reilly & Tushman, 2013; Raisch & Birkinshaw, 2008; Raisch, Birkinshaw, Probst, & Tushman, 2009), with some notable exceptions in the strategic alliance literature (Lavie & Rosenkopf, 2006; Lavie, Stettner, & Tushman, 2010; Rothaermel & Deeds, 2004). Our findings suggest that ambidexterity is also an important consideration for cross-sectoral collaborative organizations, despite lacking the structural differentiation often utilized by more hierarchically structured organizations to achieve ambidexterity (Benner & Tushman, 2003; Jansen et al., 2006). Specifically, the alliances we studied attempted to achieve ambidexterity by promoting stability in the core process of collaboration to enable change in its programmatic activities, both content and delivery. Doing so allowed the alliances to adapt to changing external circumstances while preserving one of the primary value propositions of the alliances—collaboration across different industry sectors.

Another theoretical implication of our study pertains to the role of social structure in cross-sectoral collaborative organizations. Previous theoretical work has acknowledged the importance of structure, but has tended to offer an unspecified view of its impact; (e.g., “collaborative structure . . . [is] likely to influence a collaboration’s overall effectiveness; Bryson et al., 2006, p. 49). Our study extends this work by identifying and distinguishing among three different dimensions of collaborative structure, and thus provides a more nuanced understanding of structural influences on collaborative functioning. For example, our study suggests that changes in some dimensions of the social structure (integration) can promote strategic priority “ambidexterity,” while changes in other dimensions (centralized decision making and integration) can dampen members’ views on change alone as a priority.

Similarly, previous theoretical treatments of collaborative organizations have argued that structures are likely to be dynamic to reflect the complexity and ambiguity that arises from collaboration (e.g., loosely defined membership boundaries; membership turnover; broadly defined, dynamic goals; Bryson et al., 2006; Huxham & Vangen, 2005). Our findings here again suggest that the story is more complicated, with formalization being the only dimension that changed significantly over the study period. One possible explanation for this finding relates to the types of alliances we studied, which had adopted broadly defined goals but lacked a specific “roadmap” of how to reach those goals. Under these circumstances, establishing perceptions of (even low) formalization may be difficult during early stages of alliance development when strategic plans and work processes are in flux and the real advantages of formalization may accrue to alliances during later stages while implementing and executing strategies. Such a possibility suggests that different levels of social structure may be more or less advantageous at different points in an alliance’s evolution. It also highlights an important opportunity to integrate two areas of collaborative theory that have largely evolved independently—the developmental, life-cycle trajectories of collaborative organizations (cf., D’Aunno & Zuckerman, 1987a, 1987b; Oliver, 2001) and the relationship between collaborative characteristics (e.g., structural, managerial) and outcomes (cf., Provan & Kenis, 2008; Provan & Milward, 1995, 2001).

Practice Implications

The study’s findings point to a number of implications for leaders, sponsors, and advocates of collaborative, cross-sectoral organizations such as alliances. First, with over half of all respondents indicating some type of change as a strategic priority and our findings that changing perceptions of social structure are associated with these priorities, our study highlights the importance of leaders possessing effective change management skills. For alliance leaders, however, acquiring and applying such skills may be complicated by some unique properties of alliances. Specifically, it is not clear whether the same types of change management skills that are effective in hierarchical organizations would apply equally well in collaborative organizations, which depend on voluntary participation. For example, leaders may find it difficult to change perceptions of the social structure when members devote relatively little time to alliance activities and member turnover is a persistent concern (Alexander, Hearld, & Shi, 2015). It seems plausible that a different set of change management skills may be to address such issues, or perhaps similar skill sets applied differently. Thus, the search for effective change management strategies in these settings may currently be less prescriptive and less dependent on received wisdom from common sources (e.g., consultants, popular press) and more likely to proceed in a trial-and-error fashion.

Perhaps most concerning for practitioners and sponsors of these types of collaborative efforts is the finding that nearly 25% of all respondents reported “neither change nor the status quo” as the major priority, which for many members seems to reflect a question of whether the alliance provides value. If true, then alliance leaders and sponsors may have a more central issue to contend with—how to cultivate (or reestablish) perceptions of value among participants. The findings in our study suggest that one means of doing so is by creating perceptions of less centralized decision making, less formalization, and even less integration in the eyes of members. Yet the descriptive analysis also suggests this may be a challenge for alliance leaders, with alliances experiencing increases over time, on average, for two of the three dimensions. Moreover, it seems reasonable to believe that perceptions that veer too low may present problems of their own (e.g., inability to reach consensus on decisions, failure to combine diverse skills and resources in effective ways). Thus, future research that examines the optimal levels of social structure would be beneficial for alliance leaders.

Finally, our finding that perceptions of increasing integration were, in general, more strongly associated with perceived priorities than the other dimensions suggests that this may be another area of emphasis for leaders when considering how to shape perceived strategic priorities. Perceptions of integration may be especially important in situations where strategic decisions and their implementation are distributed among members, yet members are only loosely bound to the organization. That is, without a perception of sufficient levels of integration, the alliance may struggle to maintain the efforts of members and fail to capitalize on one of its espoused advantages—leveraging the capabilities of a diverse membership. Even so, our study found that the association between perceptions of increasing integration and the different priorities were not uniform in their direction or magnitude, suggesting that the effects of increasing integration on member perceptions of the future direction of the alliance are more pervasive on one hand, but harder to control for alliance leaders, on the other.

Conclusion

The identification of future strategic priorities is a critical (and likely ongoing) activity for organizations such as alliances that depend on time-limited funding sources (e.g., grants). Member perceptions of these future priorities, in particular, are important considerations for alliance leaders given their dependence on members to set strategy and get work done. Building on emerging conceptual work that recognizes that change and stability may not be mutually exclusive priorities for organizations, this study finds that increasing levels of social structure are differentially associated with different priorities, highlighting a number of practical opportunities and challenges for alliance leaders, sponsors, and other advocates interested in sustaining or altering the future direction of alliances.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Robert Wood Johnson Foundation.

References

Agranoff

(2006). Inside collaborative networks: Ten lessons for public managers. Public Administration Review, 66(s1), 56-65.

Aiken

Bacharach

S. B.

French

J. L.

(1980). Organizational structure, work process, and proposal making in administrative bureaucracies. Academy of Management Journal, 23, 631-652.

Aiken

Hage

(1968). Organizational interdependence and intra-organizational structure. American Sociological Review, 33, 912-930.

Alexander

J. A.

Hearld

L. R.

Shi

(2015). Assessing organizational change in multisector community health alliances. Health Services Research, 50, 98-116.

Ancona

D. G.

Caldwell

D. F.

(1992). Bridging the boundary: External activity and performance in organizational teams. Administrative Science Quarterly, 37, 634-665.

Ansell

Gash

(2008). Collaborative governance in theory and practice. Journal of Public Administration Research and Theory, 18, 543-571.

Atuahene-Gima

(2003). The effects of centrifugal and centripetal forces on product development speed and quality: How does problem solving matter? Academy of Management Journal, 46, 359-373.

Auh

Menguc

(2007). Performance implications of the direct and moderating effects of centralization and formalization on customer orientation. Industrial Marketing Management, 36, 1022-1034.

Benner

M. J.

Tushman

M. L.

(2003). Exploitation, exploration, and process management: The productivity dilemma revisited. Academy of Management Review, 28, 238-256.

10.

Birkinshaw

Crilly

Bouquet

Lee

S. Y.

(2016). How do firms manage strategic dualities? A process perspective. Academy of Management Discoveries, 2, 51-78.

11.

Boulding

K. E.

(1950). Collective bargaining and fiscal policy. American Economic Review, 40, 306-320.

12.

Bryson

J. M.

Crosby

B. C.

Stone

M. M.

(2006). The design and implementation of cross-sector collaborations: Propositions from the literature. Public Administration Review, 66(s1), 44-55.

13.

Butterfoss

F. D.

(2007). Coalitions and partnerships in community health: San Francisco, CA: John Wiley.

14.

Cameron

K. S.

Whetten

D. A.

(1983). Models of the organizational life cycle: Applications to higher education. Review of Higher Education, 6, 269-299.

15.

Carroll

D. A.

Stater

K. J.

(2009). Revenue diversification in nonprofit organizations: Does it lead to financial stability. Journal of Public Administration Research and Theory, 19, 947-966.

16.

Chandler

A. D.

(1962). Strategy and structure: Chapters in the American industrial enterprise. Cambridge: MIT Press.

17.

Cheng

Long

J. S.

(2007). Testing for IIA in the multinomial logit model. Sociological Methods & Research, 35, 583-600.

18.

D’aunno

T. A.

Alexander

J. A.

Jiang

(2017). Creating value for participants in multistakeholder alliances: The shifting importance of leadership and collaborative decision-making over time. Health Care Management Review, 42, 100-111.

19.

D’Aunno

T. A.

Zuckerman

H. S.

(1987a). A life-cycle model of organizational federations: The case of hospitals. Academy of Management Review, 12, 534-545.

20.

D’Aunno

T. A.

Zuckerman

H. S.

(1987b). The emergence of hospital federations: An integration of perspectives from organizational theory. Medical Care Research and Review, 44, 323-343.

21.

Damanpour

(1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34, 555-590.

22.

Dyer

J. H.

Singh

(1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23, 660-679.

23.

Eichhorn

B. R.

(2014). Common method variance techniques. Retrieved from https://www.lexjansen.com/mwsug/2014/AA/MWSUG-2014-AA11.pdf

24.

Fayol

(1916). General principles of management. In Shafritz

J. M.

Ott

J. S.

Jang

Y. S.

(Eds.), Classics of organization theory (pp. 48-60). Belmont, CA: Wadsworth.

25.

Fredrickson

J. W.

Mitchell

T. R.

(1984). Strategic decision processes: Comprehensiveness and performance in an industry with an unstable environment. Academy of Management Journal, 27, 399-423.

26.

Hall

D. J.

Saias

M. A.

(1980). Strategy follows structure! Strategic Management Journal, 1, 149-163.

27.

Huxham

Vangen

S. E.

(2005). Managing to collaborate. Abingdon, England: Taylor & Francis.

28.

Institute of Medicine. (2013). Population health implications of the Affordable Care Act. Washington, DC: National Academies Press.

29.

Jansen

J. J.

Van Den Bosch

F. A.

Volberda

H. W.

(2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52, 1661-1674.

30.

Jehn

K. A.

Northcraft

G. B.

Neale

M. A.

(1999). Why differences make a difference: A field study of diversity, conflict and performance in workgroups. Administrative Science Quarterly, 44, 741-763.

31.

Latour

(1984). The powers of association. Sociological Review, 32, 264-280.

32.

Lavie

Rosenkopf

(2006). Balancing exploration and exploitation in alliance formation. Academy of Management Journal, 49, 797-818.

33.

Lavie

Stettner

Tushman

M. L.

(2010). Exploration and exploitation within and across organizations. Academy of Management Annals, 4, 109-155.

34.

Lawrence

P. R.

Lorsch

J. W.

Garrison

J. S.

(1967). Organization and environment: Managing differentiation and integration. Boston, MA: Harvard Business School Press.

35.

March

J. G.

(1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71-87.

36.

McGuire

(2006). Collaborative public management: Assessing what we know and how we know it. Public Administration Review, 66(s1), 33-43.

37.

Miller

C. C.

Burke

L. M.

Glick

W. H.

(1998). Cognitive diversity among upper-echelon executives: Implications for strategic decision processes. Strategic Management Journal, 19, 39-58.

38.

Mintzberg

(2009). Managing. San Francisco, CA: Berrett-Koehler.

39.

Nicholson

(2013). Community health collaboratives: Supporting innovation in public policy, care delivery, and coordination. Population Health Management, 16(S1), S-2-S-3.

40.

Nord

W. R.

Tucker

(1987). Implementing routine and radical innovations. New York, NY: Free Press.

41.

O’Reilly

C. A.

III Snyder

Boothe

(1993). Effects of executive team demography on organizational change. In Huber

G. P.

Glick

W. H.

(Eds.), Organizational change and redesign: Ideas and insights for improving performance (pp. 147-175). New York, NY: Oxford University Press.

42.

O’Reilly

C. A.

III. Tushman

M. L.

(2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27, 324-338.

43.

Oliver

A. L.

(2001). Strategic alliances and the learning life-cycle of biotechnology firms. Organization Studies, 22, 467-489.

44.

Painter

M. W.

Lavizzo-Mourey

(2008). Aligning forces for quality: A program to improve health and health care in communities across the United States. Health Affairs, 27, 1461-1463.

45.

Pertusa-Ortega

E. M.

Zaragoza-Sáez

Claver-Cortés

(2010). Can formalization, complexity, and centralization influence knowledge performance? Journal of Business Research, 63, 310-320.

46.

Podsakoff

P. M.

MacKenzie

S. B.

Lee

J.-Y.

Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879-903.

47.

Podsakoff

P. M.

Williams

L. J.

Todor

W. D.

(1986). Effects of organizational formalization on alienation among professionals and nonprofessionals. Academy of Management Journal, 29, 820-831.

48.

Provan

K. G.

Kenis

(2008). Modes of network governance: Structure, management, and effectiveness. Journal of Public Administration Research and Theory, 18, 229-252.

49.

Provan

K. G.

Milward

H. B.

(1995). A preliminary theory of interorganizational network effectiveness: A comparative study of four community mental health systems. Administrative Science Quarterly, 40, 1-33.

50.

Provan

K. G.

Milward

H. B.

(2001). Do networks really work? A framework for evaluating public-sector organizational networks. Public Administration Review, 61, 414-423.

51.

Quinn

R. E.

Cameron

(1983). Organizational life cycles and shifting criteria of effectiveness: Some preliminary evidence. Management Science, 29, 33-51.

52.

Raisch

Birkinshaw

(2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34, 375-409.

53.

Raisch

Birkinshaw

Probst

Tushman

M. L.

(2009). Organizational ambidexterity: Balancing exploitation and exploration for sustained performance. Organization Science, 20, 685-695.

54.

Richardson

H. A.

Simmering

M. J.

Sturman

M. C.

(2009). A tale of three perspectives: Examining post hoc statistical techniques for detection and correction of common method variance. Organizational Research Methods, 12, 762-800.

55.

Rothaermel

F. T.

Deeds

D. L.

(2004). Exploration and exploitation alliances in biotechnology: A system of new product development. Strategic Management Journal, 25, 201-221.

56.

Roussos

S. T.

Fawcett

S. B.

(2000). A review of collaborative partnerships as a strategy for improving community health. Annual Review of Public Health, 21, 369-402.

57.

Scanlon

D. P.

Beich

Leitzell

Shaw

B. W.

Alexander

J. A.

Christianson

J. B.

. . . McHugh

(2016). The aligning forces for quality initiative: Background and evolution from 2005 to 2015. American Journal of Managed Care, 22(Suppl. 12), S346-S359.

58.

Scheirer

M. A.

(2005). Is sustainability possible? A review and commentary on empirical studies of program sustainability. American Journal of Evaluation, 26, 320-347.

59.

Scheirer

M. A.

Hartling

Hagerman

(2008). Defining sustainability outcomes of health programs: Illustrations from an on-line survey. Evaluation and Program Planning, 31, 335-346.

60.

Scott

W. R.

(1998). Organizations: Natural, rational and open systems. London, England: Prentice Hall.

61.

Shediac-Rizkallah

M. C.

Bone

L. R.

(1998). Planning for the sustainability of community-based health programs: Conceptual frameworks and future directions for research, practice and policy. Health Education Research, 13, 87-108.

62.

Sheremata

W. A.

(2000). Centrifugal and centripetal forces in radical new product development under time pressure. Academy of Management Review, 25, 389-408.

63.

Tuckman

H. P.

Chang

C. F.

(1991). A methodology for measuring the financial vulnerability of charitable nonprofit organizations. Nonprofit and Voluntary Sector Quarterly, 20, 445-460.

64.

Tushman

M. L.

O’Reilly

C. A.

(1996). The ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38(4), 8-30.

65.

Weber

(1947). Legitimate authority and bureaucracy. In Henderson

A. M.

Parsons

(Eds.), The theory of social and economic organization (pp. 328-340).New York, NY: Free Press.

66.

Weick

K. E.

(1979). The social psychology of organizing. Columbus, OH: McGraw-Hill.