Contextual factors and business strategy choice: The case of us hospitals

Abstract

US hospitals are struggling with how to compete and remain viable in an increasingly turbulent and competitive environment. Using Porter’s generic strategies and resource dependence theory, this study examined the relationship between environmental factors and business strategy choice among U.S. hospitals. The study used longitudinal data from 2006 to 2016 of US urban, general acute care hospitals from the American Hospital Association Annual Survey, Medicare cost reports, and Area Health Resource File. Multinomial regression was used to analyze the data. and Discussion: Our findings showed four types of hospital strategy: cost-leadership, differentiation, hybrid, and stuck-in-the-middle. A greater number of physicians (county-level) increases the likelihood of pursuing differentiation and hybrid strategy. On the other hand, a higher older adult population (65 years+) increases the likelihood of pursuing a cost-leadership strategy. Similarly, lower competition and higher Medicare Advantage penetration increases the likelihood of pursuing cost-leadership over hybrid strategy. An increase in the unemployment rate decreases the likelihood of pursuing differentiation and cost-leadership strategies versus the hybrid strategy. Finally, hospitals pursuing a differentiation strategy tended to be larger, teaching, and not-for-profit. The results showed the importance of environmental and organizational factors in predicting the strategy choice of hospitals.

Keywords

strategy hospitals environment market strategic choice resource dependence theory

Introduction

An organizational strategy is a long term plan to achieve pre-specified goals.¹ Understanding organizational strategy is especially important for US hospitals given the many changes occurring in the hospital environment during recent years, such as the Patient Protection and Affordable Care Act (ACA) (2010), value-based reimbursement, and emergence of new technologies.² Hospitals may struggle to adopt an appropriate strategy to compete and remain viable in an increasingly turbulent and competitive environment.³ Because hospitals like other firms face limitations in access to resources,⁴ there are constraints for them to implement alternative strategies. Moreover, fundamentally different organizational arrangements are needed for pursuing each strategy.⁵ Thus, it is important to understand why a hospital pursues a particular competitive strategy.

Strategic management focuses on aligning the organization’s strategy with its external environment.⁶ Some studies have investigated the strategic response of hospitals to the changes in the industry environment in the 1980s.^7–9 Hospitals do change strategy in response to major environmental shifts. The results of these studies show that hospitals have become more proactive and that they may change their strategy in response to environmental conditions. However, these studies have some limitations. First, there have been many changes in the health care environment since the 1980s such as the ACA, value-based reimbursement, demographic and economic changes, which may affect hospital strategic positioning. Second, prior studies have been limited to one US state (Texas) or system hospitals,^7–9 so the findings may not be generalizable.

Using Porter’s generic strategies and resource dependence theory (RDT), our study makes a contribution to the literature by using longitudinal, national data for the period of 2006–2016, to examine the environmental antecedents of business strategy choice of US hospitals. Understanding the contextual factors of hospital business strategy such as hospital characteristics and environmental factors is important from a managerial and policy perspective.

Conceptual framework

The conceptual framework of this study was based on Porter’s generic strategies and RDT. Porter’s generic strategies framework describes how an organization pursues competitive advantage across its chosen market.⁵ There are two main or pure generic strategies: cost leadership and differentiation.¹⁰ Cost leaders are internally-oriented and emphasize cost control by constructing efficient-scale facilities and pursuing cost minimization activities in areas, such as R&D, marketing, operations, and staffing.^10,11 On the other hand, differentiators are externally-oriented or market-oriented firms, and they usually focus on the breath of product or service offerings, quality, technology, uniqueness, or customer service.¹⁰ Literature shows that hospitals have used many different bases for pursuing differentiation strategy, such as the creation of a “high tech” image and use of the latest (and most expensive) technologies.¹²

Porter describes the cost leadership and differentiation strategies as being mutually exclusive because each represents a fundamentally different approach to constructing and maintaining competitive advantage. Successful organizations should exclusively compete on one of the two generic strategies. Firms that are not completely committed to one of the two generic strategies are referred to as having a “stuck-in-middle” strategy or muddlers.¹⁰

Despite Porter’s original generic strategies, some researchers have argued that differentiation and cost leadership are dimensions along which firms can score low and high.^12–15 Therefore, researchers have suggested the existence of another strategy, usually referred to as a hybrid strategy. With the hybrid strategy, a firm may successfully and simultaneously pursue both cost leadership and differentiation strategies.^14,16,17

Porter argues that firms experiencing similar environment characteristics may pursue the same strategy.⁵ Thus, some environmental factors may explain the likelihood of choosing a specific strategy in hospitals.^10,18,19 Resource dependence theory provides insights into the contextual factors that may influence strategic choice.²⁰ This open system theory assumes that organizations are not in control of all of the resources they need to survive and that many of their strategies for survival include attempts to reduce their dependence on external resources in times of uncertainty by securing necessary inputs.²⁰

Hospitals may view different strategies as a way to secure necessary resources including patients and financial reimbursement.²¹ By using a specific strategy and offering unique services, hospitals may appeal to patients that perceive their services and outcomes to be better than those of hospitals with a different strategy.²² Hospitals may also choose a strategy as an approach for improving efficiency and minimizing cost, which could appeal to payer groups including Medicare, Medicaid, and private insurance groups, which increasingly value cost containment activities.^2,16,19,23

According to RDT, contextual factors such as the characteristics of the external environment can influence strategic adaptation. Previous studies exploring how the external environment is associated with the likelihood of a hospital adopting a certain strategy have viewed the environment through the Dess and Beard’s²⁴ lenses of munificence, dynamism, and complexity.

Munificence is conceptualized as the availability of resources in the environment that supports organizational growth.²⁵ Literature suggests that the scarcity of resources in the environment can be challenging for organizations and may affect their strategy.²⁶ For hospitals operating in an environment with a scarcity of resources, the best strategy may be to focus on minimizing the cost of products or services, or a cost leadership strategy. On the other hand, a higher degree of munificence can provide a necessary buffer to the organization in the form of financial slack that can facilitate growth.²⁷ Hospitals in this type of environment, may pursue a differentiation strategy by offering high-quality services or investing in unique and more expensive services.²⁸ Similarly, hospitals with a hybrid strategy can benefit from the availability of resources in their environment. However, these hospitals may be more limited than differentiators in their ability to exploit available resources given their pursuit of a cost leadership strategy in some parts of their operations.^28,29 Therefore, we hypothesize:

H1a. Hospitals in more munificent environments are more likely to pursue a differentiation strategy compared to cost leadership and hybrid strategies.

H1b. Hospitals in more munificent environments are more likely to pursue a hybrid strategy compared to a cost-leadership strategy.

A dynamic environment is characterized by rapid changes in the external environment that may introduce uncertainty around an organization and affect its strategy.⁷ In healthcare, those rapid changes refer to various market elements like changes in the unemployment rate and population.³⁰ Some studies have suggested that organizations that that pursue low-cost or differentiation strategies in a dynamic environment may be competitively vulnerable compared to firms with a hybrid strategy.^28,29 Hospitals that compete based on a hybrid strategy have advantages of both low-cost and differentiation strategy and have more flexibility than hospitals with low-cost or differentiation strategy. Hospitals pursuing a cost leadership strategy in a dynamic environment may face challenges due to the rapid environmental changes. These hospitals may be limited in their ability to improve services, or to expand its marketing activities. Similarly, hospitals pursuing a differentiation strategy may be vulnerable in a dynamic environment. For example, changes in demographic characteristics as well as economic conditions can affect demand for medical services, especially unique services that usually are more expensive.³¹ However, differentiators are more externally oriented than cost-leaders, and may be able to adapt better than cost-leaders in a dynamic environment. Thus, we hypothesize:

H2a. Hospitals in a more dynamic environment are more likely to pursue a differentiation strategy compared to a cost-leadership strategy.

H2b. Hospitals in more dynamic environments are more likely to pursue a hybrid strategy compared to cost-leadership and differentiation.

Environmental complexity refers to the degree of heterogeneity (Dess & Beard, 1984). A heterogeneous environment contains diverse types and a large number of entities that the organization needs to interact with to access critical resources. In healthcare, a complex environment refers to various market elements, such as Medicare Advantage (MA) (managed care) penetration and competition. It is expected that firms operating in a complex environment need a more externally oriented strategy. According to Porter, differentiators are continuously monitoring their environment to explore new opportunities.⁵ Similarly, firms with a hybrid strategy have the characteristics of both cost leadership and differentiation, and this strategy can be the choice of hospitals in more complex environments that may need a mix of strategies. On the other hand, firms with a cost leadership strategy are more internally oriented and they concentrate more on internal resources to maximize efficiency or minimize their costs. Therefore:

H3a. Hospitals in more complex environments are more likely to pursue a differentiation strategy compared to a cost-leadership strategy.

H3b. Hospitals in more complex environments are more likely to pursue a hybrid strategy compared to a cost-leadership strategy.

Methodology

Data and sample

We used longitudinal data from 2006 to 2016 of the US urban, general acute care hospitals. These years were selected because of the significant changes occurring in the US health care environment during this period (e.g., Affordable Care Act). We used three secondary datasets in the analysis: American Hospital Association (AHA) Annual Survey, Medicare Cost Reports, and the Area Health Resource File (AHRF). The AHA Annual Survey comprises information on organizational characteristics, such as ownership and system affiliation. The Medicare Cost Reports includes financial performance data. Finally, the AHRF file provides environmental characteristics at the county level, such as per capita income and physician supply.

The sample of this study comprised all private general acute care hospitals in the United States. Private, general acute care hospitals have different strategic behavior compared to specialty (e.g., long-term, psychiatric, substance abuse, etc.) and government hospitals. In addition, we focus on hospitals in urban areas given their different environmental challenges compared to those in rural areas (Trinh & O’connor, 2000). Finally, by confining the sample to hospitals in urban areas, we expect the competitive environment to be reasonably comparable for hospitals in the study. The final sample size was an average of 2700 hospitals per year with 29,518 hospital-year observations.

Measures

The dependent variable represents the hospital strategic group membership based on Porter’s generic strategies framework: cost-leader, differentiator, hybrid, and stuck in the middle. Strategic group membership was determined in three steps. First, we created composite scores for cost leadership and differentiation. Three measures were used to capture the cost leadership dimension: total expenses to the number of beds occupied, total costs per patient day, and total salaries per patient day.^32–34 To operationalize differentiation, we used three measures: (1) total number of services offered to measure breadth of operations; (2) number of high technology services offered (a cardiac catheterization laboratory, an extracorporeal lithotripter, magnetic resonance imaging, open-heart surgery, and organ transplantation capability); and (3) number of rare services, defined as a service offered by less than 25% of all the hospitals in the sample. We confirmed the unidimensionality of the cost leadership and differentiation scales using factor analysis. Next, we created composite scores for the cost leadership and differentiation scales.

Second, we used a two-stage (hierarchical and non-hierarchical) clustering procedure for grouping hospitals in strategic groups. A two-stage model is valuable because it increases the validity of cluster solutions^12–14: (1) hierarchical clustering to determine the number of groups (i.e., Ward’s method), and (2) a nonhierarchical clustering (i.e., K-means). In the first stage, the results of the Ward’s method showed that a four-group solution was the desired solution in each year (see Appendix A for more details).

Third, we used the standardized composite measures for cost-leadership and differentiation to cluster the hospitals using the K-means method. After performing the clustering, the four groups were labeled based on the mean score of cost leadership and differentiation composite measure/score. To accomplish this, we ranked the four groups that resulted from the K-means cluster analysis, based on their mean composite score for cost-leadership and mean composite score for differentiation. The group with the lowest cost composite score (1st in rank) and low differentiation score (e.g., 3rd of 4th in rank) was classified as a “Cost-Leadership” group. “Differentiation” is represented as the group with the highest differentiation composite score mean (1st in the rank) and low cost-leadership score means (e.g., 3rd or 4th in rank). We identified “Stuck-in-the-middle” as the worst-ranked in both cost-leadership and differentiation composite score means (sum of the two ranks). Finally, we identified “Hybrid” as a better-ranked in both cost-leadership composite score and differentiation compared to stuck-in-the-middle (sum of the two ranks). In addition, the hybrid has better differentiation scores than cost leaders, and lower costs than differentiators (Table 1).

Table 1.

Cluster results assignment to strategic groups (2016).

Cluster groups	Cost-leadership composite score (mean)	Cost leadership rank^a	Differentiation composite score (mean)	Differentiation rank^b	Identified strategic group
1	0.7856686	4	2.412101	1	Differentiation
2	−0.1403393	1	−0.0799171	3	Cost-Leadership
3	0.0306939	2	0.7303677	2	Hybrid
4	0.0535798	3	−0.9471238	4	Stuck-in-the-Middle

^aThe lowest score on cost leadership composite is ranked 1.

^bThe highest score on differentiation composite is ranked 1.

The independent variables consisted of contextual environmental variables in three main categories: munificence, dynamism, and complexity.^24,35,36 Measures of munificence (H1a, H1b) included per capita income, number of active physicians per 1000 population, and percent of population 65 years and older.⁹ Measures of dynamism (H2a, H2b) included the moving average of percent change in county population for 3 years prior, and yearly change in the county unemployment rate.³⁵ Lastly, MA (managed care) penetration (percent of Medicare beneficiaries enrolled in MA plans), and hospital competition (Herfindahl-Hirschman Index) (squared of hospital market shares in the Hospital Service Area) were measures of complexity (H3a, H3b).³⁷

Control variables included organizational characteristics that may affect the strategy of hospitals, such as size (number of staffed beds), system affiliation (health system membership), Medicaid and Medicare payer mix (% of inpatient days covered by Medicare and Medicaid), teaching status (categorized as teaching hospital), and ownership type (for-profit vs not-for-profit).^8,19

Analysis

The unit of analysis was the hospital-year. The dependent variable was the business strategy choice of hospitals that included four categories: cost-leadership, differentiation, hybrid, and stuck-in-the-middle. Data were analyzed using multinomial regression with a generalized estimating equation (GEE). Rather than modeling the within-subject covariance structure, GEE treats it as a nuisance and simply models the mean response.³⁸ In addition, state fixed effects control for time-invariant, unobserved state-level factors that may affect the business strategy of hospitals, and year fixed effects control for time trend. Hausman’s specification test confirmed that the multinomial logistic regression met the assumption of the independence of irrelevant alternatives.^39,40 We used SAS 9.4 and Stata 14 for data management and data analysis. Odds ratios are reported for the multinomial regression results, and significance is established at p-value < 0.05.

Results

Table 2 shows significant differences across the four strategic groups in all dependent and independent variables except HHI, suggesting that the cluster analyses produced distinct clusters. The hybrid group had the highest mean operating margin (1.29), while the stuck-in-the-middle group has the lowest mean operating margin (−0.46). Hospitals in the differentiation group had the largest size and were more likely to be teaching hospitals and located in communities with higher per capita income, higher number of active physicians, and lower percentage of older population. Cost leader hospitals were more likely to be nonteaching and located in communities with higher population growth. Hybrid hospitals were located in communities with the lowest population growth. Finally, stuck in the middle hospitals were the smallest, and were likely to be located in communities with lower per capita income, lower physician supply, and higher percentage of older adults.

Table 2.

Descriptive analyses of dependent and independent variables (2016) (N = 3756).

Variable	Strategic group membership
Variable	Cost-leadership	Differentiation	Hybrid	Stuck-in-the-Middle	p-value
Environmental characteristics percent of population 65+(M/SD)	14.22 (3.87)	12.58 (2.14)	13.71 (3.17)	14.42 (3.78)	0.001
Number of active physicians	6.39 (1.91)	8.21 (0.94)	7.14 (1.59)	5.10 (2.24)	0.001
Per capita Income(M/SD)	40598.3 (11056.6)	48769.23 (17599.6)	42826.87 (12497.8)	38751.06 (10259)	0.001
Growth in population	32.25 (10.82)	29.91 (12.15)	17.96 (10.98)	20.27 (73.75)	0.033
Change in unemployment rate(M/SD)	6.86 (2.69)	6.56 (2.36)	6.58 (2.42)	7.18 (2.97)	0.001
Herfindahl-Hirschman index (HHI) (M/SD)	0.68 (0.34)	0.43 (0.33)	0.60 (0.34)	0.73 (0.33)	0.27
Medicare advantage penetration	31.33 (14.16)	34.21 (12.85)	30.05 (13.83)	29.95 (16.02)	0.019
Organizational characteristics hospital size (M/SD)	188.82 (177.85)	370.24 (325.19)	257.84 (194.44)	152.12 (171.92)	0.001
System affiliation (N/%)
1 if system affiliated	793 (77.37)	93 (86.11)	555 (81.14)	516 (72.98)	0.001
0 if independent	232 (22.63)	15 (13.89)	129 (18.86)	191 (27.02)
Control variables ownership (N/%)
1 if not-for-profit	763 (74.44)	103 (95.37)	591(86.40)	509 (71.99)	0.001
0 if for-profit	262 (25.56)	5 (4.63)	93 (13.60)	198 (28.01)
Teaching status (N/%)
1 if teaching	10 (0.98)	84 (77.78)	70 (10.23)	0	0.001
0 if non-teaching)	1015(99.02)	24 (22.22)	614 (89.77)	707 (100)
Medicare payer mix (M/SD)	43.40 (23.10)	41.02 (19.84)	44.31(20.81)	43.66 (24.58)	0.003
Medicaid payer mix (M/SD)	15.50 (14.10)	17.37 (13.28)	15.96 (12.41)	14.92 (14.18)	0.001

Table 3 presents the results of the multinomial regression analysis for hypotheses 1a, 2a, and 3a (reference group- differentiation), while Table 4 presents the results for hypotheses 1b, 2b, and 2b (reference group- hybrid). Hypotheses 1a and 1b focus on the relationship between market munificence and strategy. There was partial support for hypothesis 1a. Hospitals located in counties with a higher number of active physicians per 1000 population had 24% higher odds of pursuing a differentiation strategy compared to a cost-leadership (p < 0.01) (Table 3). However, there were no significant difference between differentiators and hybrids in terms of physician supply. In addition, contrary to our expectations, hospitals located in counties with a higher 65 years and older population had 14% and 13% lower odds of pursuing a differentiation strategy compared to a cost-leadership (p <0.01) or hybrid strategy (p <0.01), respectively. Finally, the results did not show any significant differences in the likelihood of pursuing a differentiation strategy over hybrid or cost-leadership strategies in markets with higher per capita income.

Table 3.

Multinomial regression of factors associated with the strategy choice of hospitals^a (N= 29,518).

Variable	Cost-leadership OR (95% CI)	Differentiation OR (95% CI)	Stuck-in-the middle OR (95% CI)
Munificence
Number of active physicians per 1000 population	0.86*** (−0.1858, −0.1015)	1.13* (0.2680, 0.0141)	0.73*** (−0.3684, −0.2687)
Per capita income	1.00 (−0.0039, 0.0090)	1.00 (−0.0167, 0.01190)	1.00 (−0.0026, 0.0112)
Population 65+	1.00 (−0.0024, 0.0070)	0.87*** (−0.2040, −0.0611)	0.99 (−0.0302, 0.0079)
Dynamism
Change in population size	1.00 (−0.001, 0.001)	1.00 (0.0000, 0.001)	0.99*** (0.0000, 0.001)
Change in unemployment rate	0.971*** (−0.0416, −0.0165)	0.96*** (−0.0106, −0.0604)	1.03*** (0.0177, 0.0443)
Complexity
Herfindahl-Hirschman index (HHI)	1.34*** (0.1136–0.4792)	0.99 (−0.4637, 0.4810)	1.12 (−0.0846, 0.3096)
Medicare advantage penetration	1.01*** (0.0084, 0.0181)	1.01** (0.0002, 0.0261)	0.99*** (−0.0047, −0.0012)
Organizational characteristics
Hospital size	0.99*** (−0.0015, −0.0009)	1.01** (0.001, 0.0009)	0.99*** (−0.0024, −0.0017)
System affiliation 1 if affiliated to system	1.03 (−0.0622, 0.1341)	0.83 (−0.4195, 0.0457)	1.00 (−0.1108, 0.1050)
Medicare payer mix	0.98*** (−0.0041, −0.0007)	0.97 (−0.0070, 0.0027)	0.99*** (−0.0047, −0.0012)
Medicaid payer mix	1.03*** (0.0030, 0.0088)	0.97 (−0.0141, 0.0019)	1.01*** (0.0015, 0.0079)
Ownership 1 if not-for-profit	0.39*** (−1.0808, −0.7545)	2.05* (−0.0413, 1.4789)	0.36*** (−1.1863, −0.8254)
Teaching status 1 if teaching	0.14*** (−2.3616, −1.4864)	2.58*** (2.8789, 3.6254)	0.27*** (−1.4787, −1.1211)

^aReference group = Hybrid.

***p < 0.01, ** p < 0.05.

Table 4.

Multinomial regression of factors associated with the strategy choice of hospitals^a (N = 29,518).

Variable	Cost-leadership OR (95% CI)	Hybrid OR (95% CI)	Stuck-in-the middle OR (95% CI)
Munificence
Number of active physicians per 1000 population	0.76*** (−0.4129, −0.1282)	0.87* (−0.0141, −0.2680)	0.64*** (−0.5904, −0.3006)
Per capita income	1.00 (−0.0148, 0.0151)	1.00 (−0.01190, 0.0167)	1.00 (−0.0135, 0.0172)
Population 65+	1.14*** (0.0623, 0.2051)	1.13*** (0.061, 0.2040)	1.13*** (0.0500, 0.1928)
Dynamism
Change in population size	1 (−0.0000- 0.0000)	1 (0.0000, 0.0000)	1.01*** (0.0000, 0.0000)
Change in unemployment rate	1.00 (−0.0200, 0.0330)	1.04*** (0.0604,0.0106)	1.06*** (0.0395, 0.0936)
Complexity
Herfindahl-Hirschman index (HHI)	1.35 (−0.1822, 0.7923)	1.01 (−0.4810, 0.4637)	1.13 (−0.3700, 0.6123)
Medicare advantage penetration	1.00 (−0.0132, 0.0134)	0.99** (−0.0261, −0.0002)	1.00 (−0.0088, 0.0179)
Organizational characteristics Hospital size	0.99*** (−0.0022, −0.0012)	0.99** (−0.0009, −0.0004)	0.99*** (−0.0030, −0.0019)
System affiliation 1 if affiliated to system	1.25* (−0.0174, 0.4632)	1.17 (−0.0457, 0.4195)	1.21 (−0.0604, 0.4285)
Control variables
Medicare payer mix	0.99 (−0.0051, 0.0046)	1.03 (−0.0027, 0.0070)	0.97 (−0.0057, 0.0041)
Medicaid payer mix	1.02** (0.0038, 0.0202)	1.03 (−0.0019, 0.0141)	1.1** (0.0025, 0.0191)
Ownership 1 if non-profit	0.19*** (−2.4034, −0.8693)	0.48* (−1.4789, 0.0413)	0.17*** (−2.4926, −0.9566)
Teaching status 1 if teaching	0.05*** (−5.7202, −4.6321)	0.38*** (−3.6254, −2.8789)	0.01*** (−4.9596, −4.1444)

***p < 0.01, **p < 0.05.

^aReference group = differentiation.

There was partial support for hypothesis 1b. Hospitals located in counties with a higher number of active physicians had 14% greater odds of pursuing a hybrid strategy compared to a cost-leadership (p < 0.05) (Table 4). However, there were no significant differences in the likelihood of pursuing a hybrid versus a cost-leadership strategy based on per capita income or percent of the population 65⁺ years.

Hypotheses 2a and 2b focus on the relationship between market dynamism and strategy. There was no support for hypothesis 2a. There was no significant difference between pursuing cost-leadership and differentiation strategies by the change in population or unemployment rate (Table 3). However, there was partial support for hypothesis 2b. Hospitals located in communities with a larger increase in unemployment rate had 3% and 4% greater odds of pursuing a hybrid strategy, compared to a cost-leadership or differentiation strategy, respectively (Table 4). The results did not show any significant differences in the likelihood of pursuing a hybrid strategy versus a cost-leadership or differentiation strategy based on change in population.

Hypotheses 3a and 3b assess the relationship between market complexity and strategy. There was no support for hypothesis 3a. There was no significant association between environment complexity and the likelihood of pursuing cost-leadership versus differentiation strategy (Table 3). However, there was partial support for hypothesis 3b. Hospitals in more competitive markets (lower HHI) had 34% higher odds of having a hybrid strategy versus a cost-leadership strategy (p < 0.01) (Table 4). In addition, contrary to our expectations, hospitals located in markets with greater MA penetration had 1% lower odds of pursuing a differentiation strategy compared to a cost-leadership (p < 0.01).

Several control variables were significantly related to hospital strategy. Larger hospitals had 1% greater odds of pursuing a differentiation strategy as opposed to a cost-leadership or hybrid strategy (Table 3). Hospitals with a larger Medicaid inpatient population had 3% and 2% lower odds of pursuing a hybrid or differentiation strategy, respectively, compared to having a cost-leadership strategy. On the other hand, hospitals with a larger Medicare inpatient population had 1% lower odds of pursuing a hybrid strategy versus a cost-leadership or differentiation strategy. Not-for-profit hospitals had 81% and 61% lower odds of pursuing a cost-leadership strategy compared to differentiation or hybrid strategy, respectively. Finally, teaching hospitals had 95% and 62% greater odds of pursuing a differentiation strategy compared to a cost-leadership or hybrid strategy, respectively.

Discussion

This study used Porter’s generic strategies and RDT to examine US hospitals’ business strategy choice in relation to environmental factors. Our findings suggest four types of hospital strategy: cost-leadership, differentiation, hybrid, and stuck-in-the-middle. Furthermore, our findings indicate that both environmental and organizational factors are associated with the pursuit of a particular strategy.

Environmental factors, such as the number of active physicians (munificence), population 65+ (munificence), change in unemployment (dynamism), competition (complexity), and MA penetration (complexity) are associated with the likelihood of pursuing a specific business strategy. First, a greater number of physicians in the county increases the likelihood of pursuing differentiation and hybrid strategy. The availability of physicians in the market can provide a necessary buffer to the hospitals in the form of financial and professional slack that may facilitate organizational growth.²⁷ In such an environment, hospitals can expand their services by offering high-quality services or investing in unique and rarer services that require physicians as one of the critical resources.

Second, a higher older adult population (65 years and over) increases the likelihood of pursuing a cost-leadership strategy. Although it has been argued that a higher older adult population increases the demand for hospital care and that can be a sign of market munificence⁴¹; our results did not support this premise. One reason could be the type of health insurance and reimbursement rates for older adults versus younger populations. Since the older adult population is more likely to be covered by public insurance payers (Medicare or Medicaid), and these payers have lower reimbursement rates compared to private insurers,^42,43 this may force hospitals to adopt a cost-leadership strategy.

Third, an increase in the unemployment rate decreases the likelihood of pursuing differentiation and cost-leadership strategies versus the hybrid strategy. As mentioned before, a dynamic environment is characterized by rapid changes in the external environment, which may introduce uncertainty in an organization and affect its strategy.⁷ Since the hybrid strategy is more flexible than differentiation and cost-leadership strategies, hospitals may prefer to adopt this strategy in dynamic environments.

Fourth, lower competition and higher MA penetration increases the likelihood of pursuing cost-leadership over hybrid strategy. Lower competition represent a more stable and predictable environment, and as hypothesized a cost leadership strategy is most appropriate for this type of environment.^14,44 Hospitals that pursue a cost leadership strategy are required to become the lowest-cost producers in an industry. They must devote more effort to cost control so that above-average returns can be maintained. A cost leadership strategy is most effective in stable and predictable environments, since environments that are unpredictable or constantly changing will create diseconomies for organizations trying to pursue a cost leadership strategy.^14,36 With respect to MA penetration, hospitals pursuing a cost-leadership strategy may be better positioned to compete in attracting MA plans, given the MA focus on cost-containment.

Organizational factors were also associated with the pursuit of a particular strategy. This aligns with prior research showing the importance of organizational factors as an important determinant of a hospital’s business strategy choice.¹⁹ Hospitals pursuing a differentiation strategy tended to be larger, teaching, and not-for-profit. This suggests the importance of organizational resources in pursuing a differentiation strategy. Larger hospitals may have slack resources available and economies of scale to invest in new technologies. Similarly, teaching, and not-for-profit hospitals may be better positioned in pursuing the latest technologies through grant and endowment funding. On the other hand, cost-leaders had a higher proportion of Medicaid inpatients. Given the lower reimbursement of Medicaid compared to other payers, a cost-leadership strategy is particularly important for hospitals more dependent on Medicaid.

Managerial implications

Our study results have implications for the future structure of the hospital industry. During the study period, US hospitals predominantly pursued internally oriented strategies (cost-leadership) rather than externally oriented strategies (differentiation and hybrid). The main reason could be the financial pressure that US hospitals have faced because of economic challenges like the Great Recession, lower reimbursement rates from Medicaid and Medicare, excessive administrative costs, reduced demand for hospital care, market competition, and staff shortages.^3,45 These factors may have forced hospitals to focus on their internal operations and pursue a cost-leadership strategy.

Our finding also suggest that hospital administrators should be aware of their environment and internal capabilities while developing their strategy. For example, hospitals with organizational slack resources (larger and teaching status) and operating in more munificent (higher physician supply) and competitive markets should consider becoming differentiators. As differentiators, these hospitals can compete by offering high-tech services and/or higher quality service. On the other hand, hospitals with lower slack resources and operating in less munificent markets (higher MA penetration and older population), but in more stable (lower changes in unemployment) and less competitive markets, may want to pursue a cost leadership strategy. In this case, an internal strategy focused on improving efficiency and lowering costs, may be the basis for competitive advantage. Finally, hospitals that are in the middle, with lower slack resources but operating in more munificent and dynamic markets may want to pursue a hybrid strategy. Hybrid hospitals are able to simultaneously pursue both cost leadership and differentiation strategies. This may provide them with the most flexibility to take advantage of a munificent environment, while adapting to changes associated with a dynamic market.

In summary, hospital administrators need to understand that pursuing an appropriate strategy and eventually gaining a competitive advantage is a vital element to survive in the increasingly competitive environment of hospitals. As such, hospital managers need to know the importance of these factors when they develop their competitive strategies, but they also need performance measures that can track the effectiveness of a hospital strategy.

Limitations

There are several limitations associated with the current study. First, one limitation of this study was the use of secondary data. Inherent to the nature of secondary data, the available data were not collected to address the specific research question or to test certain hypotheses. For example, measures related to organizational culture or leadership characteristics are not available for analysis, which may affect strategy of hospitals. Using secondary data also has other limitations such as missing values and the retrospective nature of data. Second, we used the organizational lens of RDT and Porter’s strategic grouping in examining hospital strategic behavior. However, these theories originated in other industries, so results of our study should be interpreted cautiously since the healthcare sector is different from other sectors in many respects. Third, our study findings may not be generalizable to other countries besides the US The US healthcare system is unique in that it is characterized by a third-party payer system with heavy government financing, but with primarily private ownership of healthcare facilities. Future research is needed to explore hospital strategic behavior in other countries. Fourth, we limited our study to urban acute care hospitals to have a more comparable sample across the US; however, the sample is not representative of all US hospitals. Finally, we are not able to preclude potential endogeneity. For example, while certain environmental factors, such as physician supply may influence hospital strategic behavior in the short-term. In the long-term, hospital strategic behavior has the potential to influence the physician supply in a given market. Despite these limitations, the results of this study can serve as a point of reference for future studies on business strategy choice of hospitals.

Conclusion

Our study provides a useful framework for managers to assess their current strategic positioning and potential implications. In this study, we focused on the effect of different environmental and organizational factors on the likelihood of pursuing different strategies. However, some questions remain unanswered: Is there any difference between the viability of business strategies in different environments? This question can be answered by examining the effect of different environmental factors on the viability of each strategy. In addition, we did not investigate the association between business strategy and hospitals performance. Future research is needed to examine how different strategies are associated with quality or financial performance of hospitals. Our sample was limited to US acute care hospitals; therefore, future research is needed to explore how internal and external factors may impact hospital strategic positioning.

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Akbar Ghiasi

Appendix

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