Relationship Between Information Technology Integration, Senior Leadership Involvement in Postmerger Integration, and Merger Performance

Relationship Between Information

Technology Integration, Senior Leadership

Involvement in Postmerger Integration, and

Merger Performance

Section 1: Background and Context

Mergers and acquisitions (M&A) are a common occurrence among businesses of

every type and across different industries. Organizations employ M&A as a strategy for

securing competitive advantage, market positioning, acquiring new competencies and

knowledge, survival, improving efficiency, and many more reasons (Osarenkhoe &

Hyder, 2015). However, M&A can be complicated and hardly guaranteed to be successful

(Galpin, 2018; Rebner & Yeganeh, 2019). In health care, where hospitals are increasingly

merging or acquired as a strategic response to the more challenging business and

regulatory environment, successful mergers are vital for the social good (Frakt, 2015).

The goal of this study was to evaluate the relationship between information technology

(IT) integration, senior leadership involvement in postmerger integration (PMI), and the

postmerger performance of hospitals. The results from the study could be useful in

assisting hospital leaders to lead their organizations more effectively in achieving

postmerger success.

Historical Background

Hospitals and other health care organizations are vital parts of the U.S. economy

and integral to the well-being of the communities in which they operate. In an analysis of

a 2016 survey of U.S. hospitals, American Hospital Association (AHA, 2018) reported

that approximately 5.9 million people were employed by hospitals with additional 10.6

million jobs provided through businesses supporting health care, making a total of 16.5

million jobs through hospitals. The economic impact, according to the AHA report, is

approximately $3.0 trillion (AHA, 2018). However, hospitals’ influence goes beyond

their economic value as the health and well-being of people transcend monetary value.

The reality, for health care providers, is that policy and economic changes create

demanding environments necessitating health care organization leaders to seek ways to

thrive financially as well as fulfill their socially responsible goals of caring for their

communities. M&A are strategic growth tools that an increasing number of organizations

use, including hospitals (Alaranta & Henningsson, 2008; Fleishon, Itri, Boland, &

Duszak, 2017; Osarenkhoe & Hyder, 2015). Research, however, indicates a high rate of

failure of M&A (Alaranta & Henningsson, 2008; Gomes, Angwin, Weber, & Yedidia

Tarba, 2013). Understanding the relationship between factors impacting M&A outcomes

would be beneficial to health care business leaders.

Problem Statement

M&A are on the rise among hospitals in the United States compared with the

decade before 2010 (Fleishon et al., 2017; Schmitt, 2017). In its September 2017 report,

the Agency for Healthcare Research and Quality of the U.S. Department of Health and

Human Services stated that up to 70% of hospitals belong to a hospital system, an

increase from the 2013 figure of 62% of hospitals in a system or merger. The general

business problem that I addressed in this study is that a hospital merger does not easily

translate to profitability or improved performance. The specific business problem that I

addressed in this study is that some hospital leaders do not understand the relationship

between IT integration, senior leadership involvement in PMI, and postmerger

performance.

Purpose Statement

The purpose of this quantitative ex post facto study was to examine the

relationship between hospitals’ (a) IT integration, (b) senior leadership involvement in

PMI, and (c) postmerger performance. The independent variables were hospitals’ IT

integration and senior leadership involvement in PMI. The dependent variable was

postmerger performance. The targeted population consisted of senior leaders of general

acute care hospitals and hospital systems located in the midwestern states of Ohio,

Michigan, Indiana, Illinois, and Wisconsin with prior involvement in a merger or

acquisition. The results from this study may enhance hospital leaders’ understanding of

achieving desirable results from M&A. The implications for social change include the

potential to have a better understanding of how to improve postmerger hospital

performance, thereby enhancing the ability of hospitals and health systems to provide

quality care for their communities, increase positive patient outcomes and the overall

well-being of their communities, and create positive economic impact.

Target Audience

The target audience for this portfolio was business leaders of hospitals in the

midwestern United States who manage the M&A, and postmerger functions of their

hospitals. These stakeholders are senior executives, directors, and other mid- to

seniorlevel officers who are involved in the strategic decision-making process and

implementation of mergers. Though focused on the midwestern states of Ohio, Michigan,

Indiana, Illinois, and Wisconsin, the study is applicable to other hospital business leaders

across the United States. Obtaining a better understanding of the relationship between the

variables of IT integration and senior leadership engagement in PMI can enable a better

management of the M&A process and enhance M&A outcomes among hospitals. The

continued high propensity for the poor performance and failure of mergers increased the

necessity for leaders to understand how to improve M&A integration outcomes.

Research Question and Hypotheses

The goal of this study was to examine the relationship between IT integration,

senior leadership involvement in PMI, and postmerger performance of hospitals. The

study includes two independent variables (IT integration and senior leadership

involvement in PMI) and one dependent variable (postmerger performance). The research

question for this study was: What is the relationship between IT integration, senior

leadership involvement in PMI, and postmerger performance?

The null and alternate hypotheses were as follows:

(H0): There is no statistically significant relationship between IT integration,

senior leadership involvement in PMI, and postmerger performance.

(Ha): There is a statistically significant relationship between IT integration, senior

leadership involvement in PMI, and postmerger performance.

Significance

Health care organizations, particularly hospitals, will derive value from this study.

Successfully navigating an M&A provides hospitals with opportunities for growth and

continuous service to their communities.

Contribution to Business Practice

In a value-based care environment, hospital leaders face the challenge of

providing high-quality care while reimbursements and payment rates are lower than in the

previous fee-for-service climate (Frakt, 2015). The industry trend of employing the

business strategy of M&A demands that hospital leaders transform M&A into improved

performance and profitability. Achieving the performance objectives of an M&A depends

on a successful PMI of IT systems and resources (Alaranta & Mathiassen, 2014). This

study may contribute to the practice of business in some ways. First, it may provide

health care business leaders with a model for understanding the relationship between IT

integration, senior leadership involvement in PMI, and merger performance. The model

can be a viable tool in enhancing the success of M&A among hospitals. Second, the study

may contribute to existing literature on M&A practice specific to hospitals and health

care organizations, which has been sparsely studied to date.

Implications for Social Change

A hospital failure potentially has significant negative consequences for the

community in which it operates because avenues for caring for the population’s health

can be hampered or limited. Also, because hospitals have a significant economic impact

on their communities through direct and indirect employment, the failure of a hospital

may have dire economic and social consequences. The implications for positive social

change include the potential of providing a better understanding of ways to improve

postmerger performance and enhance sustainability. When performance improves,

hospital systems can offer better quality care, remain in business, support research, and

contribute to the well-being of their communities.

Theoretical Framework

The theoretical framework for this study was the postacquisition integration

model developed by Haspeslagh and Jemison (1991). Haspeslagh and Jemison developed

the theory after researching for more than 8 years into 20 organizations in the United

States, Japan, and Europe (Haspeslagh & Jemison, 1991). Haspeslagh and Jemison

proposed that value creation in a merger or acquisition takes place after the acquisition

event, essentially stating that the performance of a merger is dependent on a good PMI

process. Haspeslagh and Jemison also proposed that a business leader’s ability to

envision the strategic objective of an M&A will affect the decision-making process, the

postacquisition approach, and ultimately the performance of the combined company after

the acquisition. Haspeslagh and Jemison’s framework outlined the two factors that

influence the path to integration as (a) the need for strategic interdependence and (b)

organizational autonomy. Through their model, Haspeslagh and Jemison suggested that

the degree to which either of these factors is prevalent will determine if the integration

approach will be absorption, preservation, symbiosis or holding (Haspeslagh & Jemison,

1991). I used this model to derive a better understanding of the different approaches to

integration health care organization leaders employ and evaluate the relationship with

postmerger performance. Figure 1 depicts Haspeslagh and Jemison’s PMI model.

Need for Strategic Interdependence

Low High

Figure 1. Haspeslagh and Jemison’s types of acquisition integration approaches. From

Managing acquisitions: Creating value through corporate renewal (p. 145) by P. C.

C. Haspeslagh and D. B. Jemison. Reprinted with permission.

Value creation from a merger takes place during the integration process. Central

to Haspeslagh and Jemison’s framework is the theory that PMI is the source of value

creation in M&A. Haspeslagh and Jemison (1991) theorized that leaders must be engaged

in shaping and guiding the integration process, ensuring that the requisite environment

exists for a smooth transfer of capabilities to derive value and achieve the planned

objective of the M&A. The capabilities for transfer between the merging firms are

strategic and are resources, assets, and skills, including IT, that are combined to improve

the competitive advantage of the newly formed organization. Figure 2 shows an overview

of the acquisition process, as outlined by Haspeslagh and Jemison.

Holding Absorption

Preservation Symbiosis

High

Low

Need for

Organizational

Autonomy

Figure 2. The Acquisition Process. Reprinted from Managing acquisitions: Creating

value through corporate renewal (p. 107) by P. C. Haspeslagh and D. B. Jemison, 1991,

Reprinted with permission.

Central to the integration process are the interactions of the constructs of the atmosphere

for capability transfer and the strategic capabilities to be transferred. Figure 3 shows the

alignment between the constructs of Haspeslagh and Jemison’s framework and the

variables for this study.

Figure 3. Alignment of the Acquisition Process Constructs and Variables. Adapted from

Adapted from Managing acquisitions: Creating value through corporate renewal (p.

107) by P. C. Haspeslagh and D. B. Jemison, 1991, New York, NY: Free Press.

Representative Literature Review

Business leaders pursue M&A as a growth and competitive strategy. Companies

utilize M&A to acquire new skills and resources, derive financial synergies, achieve

economies of scale, minimize competition, improve market positioning, diversify, and

facilitate growth (Brueller, Carmeli, & Markman, 2018; Burns et al., 2015; Osarenkhoe &

Hyder, 2015). Attesting to the prevalence of M&A activity as a growth strategy,

Thomson Reuters reported an increase of 37%, amounting to $3.3 trillion within the first

9 months of 2018, compared with the same period the previous year (Thomson Reuters,

2018). This trend of increasing M&A activity is expected to continue during the next decade,

primarily due to advances in technology (Chang, Chang, & Wang, 2014; Rebner & Yeganeh,

2019). Despite the volume of activity, ample evidence exists of failure of

M&A to increase shareholder value or achieve the premerger objectives (Friedman,

Carmeli, Tishler, & Shimizu, 2016; Galpin, 2018; King, 2017; Rebner & Yeganeh, 2019).

The need exists for further research that goes beyond conceptual analyses of M&A

approaches and provides empirical support that may be beneficial to business practice

(Lu, 2018). Business leaders will find great value in having a better understanding of the

M&A process and how to derive the desired benefits from it. The growth in M&A and

the challenges associated with them are pervasive across many business sectors.

M&A is prevalent in the health care industry. Like other businesses, hospitals and

health systems embark on M&A in pursuit of growth, to achieve a competitive advantage,

prevent closures, and shore up decreasing revenues in an increasingly demanding

business climate with reducing reimbursement rates for services rendered (Frakt, 2015).

However, achieving the profitability or performance objectives of M&A seems to be

difficult, and studies on the crucial factors and methods for successful hospital mergers

and PMI are limited (Reddy, Qamar, & Yahanpath, 2019). According to Lineen (2014),

M&A activities among hospitals rarely achieve the desired results without a systems

integration. Integrating merged organizations is more crucial to merger success than other

strategic initiatives (Osarenkhoe & Hyder, 2015). It is, therefore, vital for leaders of

hospitals and hospital systems to understand the intricacies of managing M&A and PMI

to achieve business objectives.

This section includes a review of literature from scholarly peer-reviewed journals,

periodicals, and seminal works relevant to the research question: What is the relationship

between IT integration, senior leadership involvement in PMI, and postmerger

performance? I organized this review into six main headings. These categories are M&A

in health care, making mergers work, Haspeslagh and Jemison’s PMI framework,

leadership, IT integration, and postmerger performance. Under the first heading M&A in

health care, I provided an overview of the extant literature on M&A in health care. The

intent of this segment was to articulate the strategic importance of M&A to hospitals in

the United States. In the next segment, making mergers work, I present a review of M&A

typologies and postacquisition integration frameworks, provide some insight into the

constraints or challenges that they present, and discuss the reason that I chose to use

Haspeslagh and Jemison’s PMI framework. The subsequent segments include an

elaboration of Haspeslagh and Jemison’s PMI framework, a discussion of some of the

constructs, and a review of the critical concepts of leadership, IT systems integration

postmerger, and performance.

To identify relevant sources for this review, I searched several databases through

the Walden University Library. The databases that I used for the study include

ABI/INFORM Collection, Business Source Complete, Emerald Insight, SAGE Journals,

ScienceDirect, IEEE Xplore Digital Library, and Google Scholar. Keywords that I used

in the searches included a mix of the following: merger, acquisition, post-merger,

postacquisition, integration, post-acquisition integration, post-merger integration,

healthcare, leadership, performance, post-merger integration theory, Haspeslagh and

Jemison framework, information technology integration, information systems integration,

healthcare IT, M&A, and M&A framework. The literature review contains 139 selected

resources. Of these 139 resources, 102 are peer-reviewed journal articles published after

2015. The other 37 resources are seminal works and peer-reviewed journal articles

published before 2015.

M&A in Health Care

Hospitals are vital to the well-being of their communities. Beyond attending to the

physical and mental health of the population, the economic impact of hospitals in the

United States is more than $3 trillion, and hospitals support more than 16.5 million jobs

(AHA, 2018). Despite the significant reach, the high cost of health care in the United

States, currently about 18% of the gross domestic product (GDP), is a source of concern

for practitioners and policymakers (King, 2017). The Centers for Medicare & Medicaid

Services (CMS) projected that the cost of health care in the United States would rise to

about 20% of GDP by 2027, raising the call for improvements on how care is delivered.

Understanding the reasons health care organizations merge is fundamental to a

useful analysis of what enhances the performance of a merger. Policy changes in the

health care industry and the increasing pressure to reduce health care costs while

improving quality of care and patient outcomes are forcing health care organizations to

move towards mergers, acquisitions, and consolidation (Fleishon et al., 2017; King,

2017). With the implementation of the value-based care and reimbursement models under

the Affordable Care Act (ACA) and subsequent policy changes, hospitals and clinicians

are challenged to reevaluate their processes and develop new approaches to care

coordination and delivery (Rajaram et al., 2015; Srinivasan & Desai, 2017). Fleishon et

al. (2017) found that due to the changes in the industry, there is a growing trend toward

M&A. The drive for M&A opportunities is a conscious strategic objective of leaders with

the primary intent of creating value and improving profitability (Fleishon et al., 2017;

Rahman & Lambkin, 2015). Despite the established trend toward M&A among hospitals,

the performance results have been varied, necessitating the need to improve practices in

the areas of governance, change management, culture, operations, finances, productivity,

and compensation (Fleishon et al., 2017; Henningsson & Kettinger, 2016). A good

understanding of how to achieve M&A objectives is, therefore, vital for business leaders

in the health care industry.

Industry fragmentation is another reason for the growth of M&A in health care.

West, Johnson, and Ashish (2017) stated that a high degree of fragmentation exists in the

U.S. health care industry, which has increased provider consolidation and acquisition of

physician practices. Hospitals proffer better care coordination, improved quality of care,

and better operational efficiency as reasons driving the acquisitions of physician practices

(West et al., 2017). However, evidence from available research showed that financial

objectives are the primary motivators for the acquisitions (West et al., 2017). Noles,

Reiter, Boortz-Marx, and Pink (2015) similarly identified financial performance as a

driver for M&A activity. Hospitals with weaker financial performance are more

susceptible to M&A (Noles et al., 2015; Zand, 2018). The desire for a stronger market

position and improving the quality of services offered to patients are other drivers for

M&A in health care (Postma & Roos, 2016; Schmitt, 2017). Achieving economies of

scale, a higher purchasing power, reduction of staffing costs, achieving leverage with

payers, and deriving synergy from integrating resources and systems are additional

reasons why M&A activities are on the increase amongst hospitals and health care

providers (Hauptman, Bookman, & Heinig, 2017; Schmitt, 2017; Zand, 2018). However,

M&A can be disruptive to business operations, and problems can arise from the activity,

failing to achieve the acquisition objectives.

Making Mergers Work

Making mergers work is a challenge that goes beyond signing the agreement to

acquire or merge with another business. Despite the promise of potentially faster growth,

increased capabilities, and resources, most M&A fall short of their objectives (Brueller et

al., 2018; Klar & Shufelt, 2015). Nevertheless, business organizations continue to utilize

M&A as a growth strategy regardless of the evidence of a high probability of failure to

achieve their performance or growth objectives (Frantz, 2018; Nandi & Nandi, 2017).

M&A occurs when two organizations combine resources and capabilities to form a new

company. M&A take different forms, depending on the goals of the parties involved

(Brueller et al., 2018). M&A may be vertical or horizontal, related, or unrelated, as well

as other forms (Brueller et al., 2018; Chatterjee & Brueller, 2015). Brueller et al. (2018)

suggested a classification of M&A into three main groups: annex and assimilate, harvest

and protect, and link and promote. Annex and assimilate are acquisitions where the target

firm’s core assets are taking over or absorbed by the acquiring firm (Brueller et al., 2018).

Harvest and protect are M&A that focused on integrating and expanding capabilities to

enhance productivity, innovation, and entrance into different markets (Brueller et al.,

2018; Swaminathan, Groening, Mittal, & Thomaz, 2014). According to Brueller et al.

(2018), link and promote describes acquisitions focused on creating shared value and

growth of both firms. By grouping M&A in this manner, Brueller et al. (2018) essentially

tied Haspeslagh and Jemison’s PMI approaches to each merger category. However, other

scholars have suggested different theories and approaches that may apply to PMI as well.

M&A offers leaders a path toward renewing and rejuvenating their organizations.

M&A is a strategy for corporate renewal that is predicated on a solid understanding of the

firm’s business domain, as well as clarity on the M&A would impact renewal (Dao,

Strobl, Bauer, & Tarba; 2017; Haspeslagh & Jemison, 1991). Organizations may pursue

M&A to eliminate management inefficiencies, achieve synergy, diversify, expand market

reach, and to encourage favorable assets expansion (Haspeslagh & Jemison, 1991).

Central to the idea of synergy creation through M&A is the concept of strategic fit

(Bauer, Strobl, Dao, Matzler, & Rudolf, 2018; Haspeslagh & Jemison, 1991). Bauer et al.

(2018) described strategic fit as an organization’s orientation toward synergy creation via

exploration and exploitation. Exploration refers to the creation of new knowledge,

whereas exploitation implies modifying and improving existing processes for a better

outcome (Bauer et al., 2018). A strategic fit analysis is required prior to an M&A to

ensure there is an alignment between the merging firms.

PMI Theories and Frameworks

Ideas and approaches abound on how to effectively integrate companies

postmerger. Scholars have identified effective postacquisition integration as a key to

ensuring M&A success (Henningsson & Kettinger, 2016). A crucial question then is:

What is the right approach to PMI? Haspeslagh and Jemison (1991) proposed a PMI

framework, which is the theoretical foundation for this doctoral study. However, other

scholars have suggested different theories and approaches that may be applied as well.

Nandi and Nandi (2017) evaluated and proposed the activity theory as an approach to

manage the M&A process and improve PMI. Contingent to Nandi and Nandi’s (2017)

proposition is the understanding that the social identity perspective or the people aspect of

an M&A is crucial to any postmerger success. The activity theory originated from the

work of Russian psychologists, Vygotsky, Leont’ev, and others from the 1920s

(Engestrom, 2000). According to Nandi and Nandi (2017), the activity theory posits that

all human learning takes place in the form of activities because people cannot be treated

in isolation from their social and cultural environments. The activity theory is mainly

descriptive and provides a means of uniting human consciousness and cognitive abilities

with action (Karanasios & Allen, 2018; Karanasios, Allen, & Finnegan, 2015). Nandi and

Nandi (2017) found the activity theory to be a useful framework for organizational

learning, interactions, and process integrations. The activity theory offers a way to

manage multiple activities, remove hindrances to operating in smaller, more integral units

while maintaining ordered processes, and emphasize the provision of tools for

organizational effectiveness (Nandi & Nandi, 2017). Although the activity theory

provides a path to PMI, it does not provide an overarching methodology for information

systems integration. Researchers have suggested other theoretical approaches.

The extent to which the organizational units and employees coalesce into a single,

unified, cohesive, and functional organization impacts M&A success. The meso-unit

theory, proposed by Frantz (2018), offers another lens through which to implement PMI.

Integrating to form a unified and cohesive organization is a necessary process that

includes knowledge transfer (Frantz, 2018; Sarala, Junni, Cooper, & Tarba, 2016).

Knowledge transfer is crucial for postmerger performance (Ahammad, Tarba, Liu, &

Glaister, 2016; Frantz, 2018). Total count of work units and teams in the merging

organizations are indicative of the complexity of the integration process (Frantz, 2018;

Lauser, 2010; Turner & Baker, 2019). The meso-unit theory of PMI postulates that the

number of work units to be integrated in a merged organization has a significantly higher

negative impact on the time to achieve integration than the total number of people

involved (Frantz, 2018). The imperative of aligning IT integration and business strategies

is validated through research and provides a foundation for Frantz’s analysis (Frantz,

2018; Reynolds & Yelton’ 2015). The research by Frantz (2018) showed support for the

proposition that the number of work units that must integrate negatively affects the

integration performance of the merged organization. Frantz (2018) also found that the

number of players in the work units negatively affects integration performance, and the

amount of knowledge transfer per work unit negatively impacts the integration

performance of the merged organization. The findings indicate that the organizational

structure has a more significant impact on the difficulty of integration than the number of

employees affected by a merger (Frantz, 2018). The significance of the theory is that PMI

can be more successful if practitioners work at effecting better organizational structures

and enhance communications across teams. Regardless of the organizational structure of

the merging firms, defining the strategic vision for a merger is essential and foundational

to successful integration. Also, though crucial, achieving a successful PMI goes beyond

work unit cohesion. Therefore, a more comprehensive lens for PMI is preferred.

The effectiveness of the PMI phase of an M&A determines the merger outcome.

Researchers and practitioners commonly accept the criticality of the PMI for value

creation from an M&A (Angwin & Meadows, 2015). Value creation, a measure of

postmerger performance, implies the collective value of the newly created firm is higher

than the addition of the values of the individual companies (Barney, 1991; Rahman,

Lambkin, & Hussain, 2016; Sarala et al., 2016). Value creation enhances the firm’s

competitive advantage and improves long-term performance (Barney, 1991; Martin,

Butler, & Bolton, 2017). However, Angwin and Meadows (2015) stressed the need for a

critical review of the available approaches given what they perceived as limited empirical

evidence provided in the studies that proposed the approaches, as well as the largely

conceptual nature of the methodologies. Angwin and Meadows stated that the failure of

pre-merger approaches in predicting postmerger performance was a significant reason for

the development of PMI typologies. Clougherty and Duso (2011) implied that the need

for additional typologies is a result of researchers identifying that synergy creation and

the subsequent value addition from a merger, comes from multiple means. Angwin and

Meadows identified Haspeslagh and Jemison’s framework as the most renowned

typology for PMI in literature. They also opined that there are potentially four to five

additional approaches spanning cultural, psychological, and resource-based integration

approaches. To evaluate the occurrences of the different approaches to postacquisition

integration, Angwin and Meadows conducted a mixed-method study of M&A, which

they described as a novel for the field at the time of the research. The population for the

study was executives of UK companies who have completed an M&A within

approximately 2 years of the study. Analysis of the findings revealed support for

Haspeslagh and Jemison’s PMI approaches of absorption, preservation, and symbiotic, as

well as approaches Angwin and Meadows referred to as intensive care and re-orientation,

which aligns with the resource-based view. A key premise of Haspeslagh and Jemison’s

PMI framework is the resource-based view.

The resource-based view (RBV) is another theoretical lens for viewing PMI. The

RBV of the firm, based on the work of Wernerfelt (1984), postulates that businesses that

have resources that are unique, valued, difficult to imitate, and that other resources cannot

substitute, will experience continuous competitive advantage and sustained growth

(Henningsson & Øhrgaard, 2016; Nason & Wiklund, 2018; Wernerfelt, 1984). In their

work on approaches to PMI, Bodner and Capron (2018) broadly classified the approaches

to PMI into two: reconfiguration and organization design. Reconfiguration incorporates

the tools used for reassigning or combining resources, product lines, or organizational

units (Bodner & Capron, 2018). The implication is that resources drive the

reconfiguration process, which is an application of the RBV (Bodner & Capron, 2018).

The premise of the RBV is that value creation in a merger can only occur through

capabilities transfer (Angwin & Meadows, 2015; Bodner & Capron, 2018). Capabilities

represent the unique resources possessed by the firm that enable its operations,

decisionmaking, and business activities (Henningsson & Øhrgaard, 2016; Nason &

Wiklund, 2018; Newmeyer, Swaminathan, & Hulland, 2016). The RBV approach

provides firms a way to combine resources from different organizations or units to create

value and is premised on the idea that resources drive organizational reconfiguration

during PMI, and that the reconfiguration of the resources occurs continuously (Bodner &

Capron, 2018). Reconfiguration of the merging companies occurs when their resources

are redistributed and reorganized within the newly formed firm. Henningsson and

Øhrgaard (2016) also identified the use of RBV as a theoretical approach to PMI of IT.

According to Henningsson and Øhrgaard, the resource-based view helps to outline how

IT resources could create value postacquisition. A key limitation of RBV is that it

positions a firm in a combative association with its external environment, does not foster

collaboration, and assumes that only the uniqueness of resources drives mergers (Nason

& Wiklund, 2018).

These challenges raised the need for a different approach to PMI.

The resource dependence theory (RDT) is another theoretical perspective

applicable to PMI. According to Wei and Clegg (2017), RDT is complementary to the

RBV. Based on the work of Pfeffer and Salancik (1978), RDT postulates that

organizations are limited and impacted by their environments and act to manage their

resource dependencies (Hillman, Withers, & Collins, 2009). In their study of the sources

of value destruction postmerger, Wei and Clegg integrated RDT and RBV to develop new

insights on how strategic resources are identified in acquired firms and redistributed after

the merger. Applying RDT to PMI is based on the proposition that businesses are systems

with dependencies on their external environments, and therefore, develop strategies for

integration that are reactive or aimed at limiting their external dependence (Gaffney,

Kedia, Clampit, 2013; Wei & Clegg, 2017). Applying RDT to M&A, Pfeffer (1976)

proposed that a firm seeks merger for three primary reasons, which are (a) to reduce

competition by absorbing a competitor, (b) to manage dependence on suppliers or buyers

by acquiring them, and (c) to diversify operations to lessen dependence on organizations

with which it interacts (Pfeffer, 1976; Wei & Clegg, 2017). The crux of RDT, therefore,

is the need for firms to acquire resources that will reduce their dependence on other

organizations or the uncertainties of their environments (Wei & Clegg, 2017). This core

principle is essential to M&A but limits many mergers and subsequent integration efforts

to just eliminating dependencies. In addition to evaluating the use of RDT and RBV in

PMI, the social identity theory is another approach to PMI proposed by researchers.

The social identity theory offers a people perspective to PMI. The social identity

theory, based on the original work of Henri Tajfel, focuses on group processes and

intergroup dynamics (Abrams & Hogg, 1990; Wei & Clegg, 2018). Wei and Clegg

(2018) described the central proposition of the social identity theory as the perception of

the social world as existing in social categories, and membership of these social

categories can impact an individual’s self-definition. Applying the social identity theory

to M&A can assist in understanding the complex organizational change associated with

PMI (Elstak, Bhatt, Van Riel, Pratt, & Berens, 2015; Wei & Clegg, 2018). Through their

study of social identity theory and how it impacts organizational identity during PMI,

Wei and Clegg (2018) found that different levels of organizational dominance, i.e., low or

high, create different responses and conformity to the new identity. Wei and Clegg (2018)

proposed that defining and sorting out the organizational identity issues is a prerequisite

to successful PMI. Wei and Clegg (2018) went further to assert that the findings from

their study suggest the need for an alignment between levels of organizational dominance

and overall integration approach. Though the theory provides a strong foundation for

integrating people and teams, it does not provide an overarching strategy that may be

applied to holistically to all aspects of the merging organizations.

Haspeslagh and Jemison’s PMI Framework

Different factors influence an organization’s approach to PMI. Haspeslagh and

Jemison (1991) suggested that these reasons may include the acquiring firm executives’

perception of performance, the size of the target firm, types of synergies desired, acquired

firm’s profitability, strategic or organizational task needs, culture, and the political

characteristics of the firm. Haspeslagh and Jemison (1991) stated that how these factors

influence PMI is contingent on the strategic intent for the merger and how value will be

created postmerger. The main objective of the PMI process is to identify and implement

the best way of creating value from the resources available from the merging firms

(Bodner & Capron, 2018; Haspeslagh & Jemison; 1991). In their seminal work on PMI,

Haspeslagh and Jemison (1991) described integration as a flexible or adaptive process of

interaction which occurs when companies merge in an environment that supports the

transfer of capability. This process is vital to making mergers successful but fraught with

challenges that make it an uncomfortable endeavor for leaders (Haspeslagh & Jemison,

1991; Steigenberger, 2017). The transfer of strategic capabilities is the crux of the

integration process (Bodner & Capron, 2018; Haspeslagh & Jemison, 1991). However, a

successful PMI requires the creation of an environment that supports cooperation,

collaboration, and learning by the individuals in the merging organizations. Figure 2 is an

overview of the acquisition process flow outlined by Haspeslagh and Jemison.

Steigenberger (2017) described the process of PMI as the degree of interaction and

coordination between the merged firms.

Using a two-dimensional matrix, Haspeslagh and Jemison (1991) described the

core dimensions of PMI as strategic interdependence between the acquiring and target

firms, and organizational autonomy. The extent of the need for either of the two factors,

determine the approach to postacquisition integration and yield the four approaches:

absorption, symbiosis, preservation, and holding (Haspeslagh & Jemison, 1991; Malik &

Bebenroth, 2018; Marchand, 2015). Strategic interdependence describes how value

creation through resource sharing, practical skill transfer, and management capability

transfer (Haspeslagh & Jemison, 1991; Schönreiter, 2018). Organizational autonomy

describes the degree to which it is necessary to preserve the strategic capabilities of the

acquired firm, particularly in areas such as organizational culture (Brueller et al., 2018;

Haspeslagh & Jemison, 1991). Understanding and implementing PMI based on a firm’s

need for autonomy or strategic interdependence is vital for postacquisition success.

Strategic and organizational fit are two vital pre-requisites in the premerger phase

of an M&A. Strategic fit describes the means of potential synergy creation in a merger

(Bauer et al., 2018; Haspeslagh & Jemison, 1991). Strategic fit indicates a merger’s

value-creation probability and how the acquired firm complements the parent company

(Bauer et al., 2018; Haspeslagh & Jemison, 1991). According to Bauer and Matzler

(2014), three elements determining the strategic fit for M&A are premerger relatedness of

the organizations, similarity, and complementarity. Though evaluating the strategic and

organizational fit is vital before the merger, these two attributes alone do not indicate how

the merger will proceed, or if there will be value created (Bauer & Matzler, 2014;

Haspeslagh & Jemison, 1991). Cultural and political fit are other determinants of M&A

outcomes evaluated by researchers during the premerger phase (Bauer & Matzler, 2014;

Sarala et al., 2016). Though very impactful, neither the premerger nor the postmerger

phase can unilaterally determine the outcome of an M&A (Bauer & Matzler, 2014).

Effective implementation of both phases is vital. The premerger decision making and

PMI processes present different challenges that should be managed appropriately to

derive value from the acquisition.

Researchers consider the postmerger phase as the more critical stage of an M&A.

Many studies emphasize the criticality of the PMI phase (Bauer & Matzler, 2014;

Graebner, Heimeriks, Huy, & Vaara, 2017; Yoon & Kim, 2015). Confusion, stress,

communication break-down, and poor performance increases when the PMI is poorly

executed (Yoon & Kim, 2015). Scholars have generally described PMI from two

perspectives: the organizational behavior or strategic perspective, and the process

perspective (Bauer & Matzler, 2014; Graebner et al., 2017; Yoon & Kim, 2015).

Haspeslagh and Jemison (1991), and more recently Bauer and Matzler (2014), identified

four prevailing perspectives as the capital markets school, strategic school, organizational

behavior school, and the process perspective. Graebner, Heimeriks, Huy, and Vaara

(2017) align with the processual view of PMI, describing it as a dynamic

multidimensional process through which the merging organizations combine to form one

new company. For integration to be successful, every process requires to be managed

while allowing for the flexibility to respond to unplanned events during the integration

process (Graebner et al., 2017). M&A success therefore depends on the core constructs of

the respective school of thought, and may include business reconfiguration,

organizational integration, cultural and strategic fit, relatedness, leadership, and

postmerger outcomes (Bauer & Matzler, 2014; Bodner & Capron, 2018; Brueller et al.,

2018; Henningsson, Yetton, & Wynne, 2018; Zollo & Singh, 2004). Haspeslagh and

Jemison’s PMI framework closely aligns with the process perspective (Haspeslagh &

Jemison, 1991). Haspeslagh and Jemison (1991) suggested a positive M&A outcome

depends on (a) a clear understanding of an appropriate integration approach, (b)

flexibility and ability to adjust as needed, and (c) ability to execute and deliver as

intended.

Achieving a timely and successful postacquisition integration is crucial to

attaining the objectives of an M&A. Validating Haspeslagh and Jemison’s approaches,

Steigenberger (2017) described them as the most influential of PMI models. Similarly, in

their mixed methods analyses of postacquisition strategies, Angwin and Meadows (2015)

acknowledged Haspeslagh and Jemison’s approaches as the most prominent strategy but

pointed out that the methods lack enough empirical evidence for or against the typologies.

This reasoning formed the basis of the work done by Angwin and Meadows (2015). The

research data obtained by Angwin and Meadows (2015), showed empirical support for

Haspeslagh and Jemison’s PMI strategies of preservation, symbiosis, and absorption.

However, the framework has some limitations.

No singular theoretical framework can account for all potential variabilities in

M&A practice. Though highly reviewed and recommended by scholars and practitioners,

Haspeslagh and Jemison’s PMI has some limitations (Angwin & Meadows, 2015; Bauer

et al., 2018; Calipha, Brock, Rosenfeld, & Dvir, 2018). A limitation of the framework is

its foundation on the RBV, implying that value creation is only possible through

capability transfer (Angwin & Meadows, 2015; Calipha et al., 2018). According to

Angwin and Meadows (2015), value creation based on RBV, as proposed by Haspeslagh

and Jemison, neglects M&A between organizations with unrelated businesses. Also,

Zaheer, Castañer, and Souder (2013) suggested that the relationship between integration

derived from the need for strategic interdependence, and autonomy, may be more

dynamic and fluid, than as suggested by Haspeslagh and Jemison. Another potential

limitation is the thought proposed by Henningsson et al. (2018) that it is preferable, and

likely more productive, to adapt a collection of methods when implementing IT

integration postmerger or acquisition.

Leadership in M&A

Effective leadership is integral to the success of an organization. Leadership is a

complex multi-dimensional process that is crucial to an organization’s survival and

ability to achieve its mission (Madanchian, Hussein, Noordin, & Taherdoost, 2017;

Northouse, 2016). Leadership is a crucial factor in the success of M&A (Bodner &

Capron, 2018; Haspeslagh & Jemison, 1991; Rouzies, Colman, & Angwin, 2018;

Sapkota, Ivanov, & Bachman, 2019). However, employees’ perceptions of leadership

impact organizational performance significantly, and not necessarily the leader’s

behavior or the intended leadership effect (Jacobsen & Bøgh Andersen, 2015). M&A are

periods of organizational change that can introduce a significant level of stress on

employees as well as leaders that can impact the merger outcome (Rebner & Yeganeh,

2019; Sapkota et al., 2019; Yoon & Kim, 2015). The role and importance of leadership in

M&A have been mainly ignored historically (Sitkin & Pablo, 2005). Recent studies point

to a new focus on the role leadership plays in M&A (Naranjo-Gil, 2015). However, gaps

remain, and more studies would be beneficial to understanding leadership impact on the

outcome of M&A (Junni & Sarala, 2014). A goal of this study is to provide additional

insight into leadership impact in M&A through an examination of the relationship

between leadership and postmerger performance.

Existing studies on leadership in M&A are limited. Despite the preponderance of

research on business leadership, focus on the area of M&A has received little attention

(Junni & Sarala, 2014; Northouse, 2016; Osarenkhoe & Hyder, 2015). Junni and Sarala

(2014) conducted a meta-analysis of recent empirical studies between 2000 and 2013 on

the role and impact of leadership on M&A. Of the 69 studies identified, no specific health

care industry-focused research was identified. Rather, the focus of most recent studies of

leadership in M&A was on the service, high-tech, and manufacturing industries (Junni &

Sarala, 2014). This doctoral study focused on M&A leadership in the hospital and

hospital system setting.

Leadership is vital to the success of M&A. Junni and Sarala (2014) identified five

main M&A leadership perspectives summing up the direction of prior research into the

role of leadership in M&A. These perspectives include the behavior of M&A leaders,

critical studies like gender impact on M&A leadership, traits, and power and politics in

M&A leadership. According to Junni and Sarala (2014), significant evidence exists in

support of leadership impact on M&A performance, integration outcomes, and

employee/manager reactions. Similarly, Steigenberger (2017), in a meta-analysis of the

challenge of M&A integration over the prior 30 years, found that leadership

interventions, communications, and structural interventions in the form of integration

depth and speed are crucial to M&A success. Steigenberger (2017) further emphasized

the need for additional research on the impact of leadership and structural interventions in

M&A. Steigenberger (2017) posited that such an examination would provide a better

understanding of the factors for the success or failure of M&A integrations. The

qualitative case study by Jap, Gould, and Liu (2017) affirmed the findings of Junni and

Sarala (2014) as well as Steigenberger (2017). In their study of a merger to form a global

bank, Jap et al. (2017) found that a deliberate and strategic approach to the M&A process

involved leadership planning, internal and external stakeholder involvement, brand

repositioning, and planning for IT integration. Jap et al. (2017) identified that these

factors, in addition to effective leadership, a customer-focused approach, and

organizational flexibility as critical to M&A integration success.

M&A leadership studies have been more focused on pre-merger roles of leaders,

and less on the integration or postagreement phase. According to Osarenkhoe and Hyder

(2015), executive leaders of organizations agree that integrating newly merged firms is

very crucial to the success of the merger, and of greater importance than other strategic

efforts at such periods. The PMI phase places a significant amount of pressure on leaders’

organizational, personal, and crisis management abilities (Appelbaum, Gandell, Shapiro,

Belisle, & Hoeven, 2000). Researchers have found that postmerger stress and leadership

have a statistically significant impact on PMI and postmerger performance (Yoon & Kim,

2015). The uncertainties and stress introduced as a result of the organizational transition

occasioned by a merger or acquisition dictate the need for effective leadership to lessen

the people impact, communicate, create the right environment, and successfully

implement the transition (Bradley, 2016; Savovic, 2017; Yoon & Kim, 2015). The

available evidence suggests a positive leadership impact on PMI. Despite the evidence,

studies are limited and more research into how leadership impacts the postmerger process

would enhance available knowledge and increase the probability of achieving successful

M&A integration.

Understanding how leadership impacts postmerger performance (PMP) is crucial

to enhancing the success of M&A. Leaders provide direction, ensure alignment across the

organization, and commitment to the corporate goal (Clay-Williams, Ludlow, Testa, Li,

& Braithwaite; 2017). A thorough understanding of the impact of leadership on the M&A

process and outcome is limited amongst scholars and practitioners (Gomes et al., 2013).

In a study of the impact of the dimensions of transformational leadership on PMP,

Savovic (2017) found that leadership, and specifically transformational leadership,

positively impacts PMP. Savovic (2017) carried out a quantitative study to assess the

impact that inspirational motivation, idealized influence, individual consideration, and

intellectual stimulation, the dimensions of transformational leadership have on PMP.

Savovic (2017) hypothesized that transformational leadership positively influences PMP

and that transformational leaders encourage workers to accept change, which in turn

impacts PMP positively. Savovic (2017) also hypothesized that transformational leaders

could positively impact PMP through individual consideration of each employee. Using

Bass and Avolio’s (2000) Multifactor Leadership Questionnaire to survey participants,

analysis of the findings by Savovic (2017) showed that all the four dimensions of

transformational leadership evaluated have a positive impact on PMP. Similarly,

Vasilaki, Tarba, Ahammad, and Glaister (2016) found that the leadership style impacts

the approach to people integration into the new organization postmerger. Human

integration and organizational identity impacts employee behavior, which ultimately

impacts PMP (Vasilaki et al., 2016). The implication of the studies by Savovic (2017)

and Vasilaki et al. (2016) is that leadership impacts performance in a merger. The

effectiveness of leadership is, therefore, crucial and integral to achieve the desired

outcomes from M&A.

Successful PMI is vital to the outcome or performance of a merger and

researchers have found evidence supporting the criticality of clinical leadership in PMI in

a hospital setting. Through systematic research of multiple studies, Ingebrigtsen et al.

(2014) found evidence that showed that clinical leadership impacts the outcome of health

care IT adoption. According to Ingebrigtsen et al. (2014), health care IT adoption and

integration impacts cost-effectiveness, patient care, and ultimately, a hospital’s

performance. Emphasizing the importance and impact of health care leadership on

performance, Sarto and Veronesi (2016) evaluated the subject through a systematic

analysis of existing studies. According to Sarto and Veronesi (2016), most research has

focused disproportionately on financial and operational resources. Sarto and Veronesi

(2016) amplified the need to focus on other areas of study, such as social performance

and quality of care as measures of performance. Sarto and Veronesi (2016) found that

clinical leadership enhance hospital efficiency and effectiveness, improve

decisionmaking, and provide significant benefit to the hospital. The point by Sarto and

Veronesi

(2016) emphasize the need to evaluate the impact of leadership on the PMI performance.

Further supporting the findings of Ingebrigtsen et al. (2014) and Sarto and Veronesi

(2016) is the quantitative study by Naranjo-Gil (2015) on the role of top management

teams in hospitals facing strategic change and the impact on performance. Naranjo-Gil

(2015) found that the quality, experience, and diversity of senior leadership impacts the

ability of an organization to manage the short-term performance challenges that may

result from a merger and effectively strategized for improved long-term results.

There is consensus on the importance of effective strategic leadership in

influencing M&A outcomes. Strategic leadership, in this instance, refers to executive or

senior-level leaders of organizations. Haspeslagh and Jemison (1991) stated that

seniorlevel leaders tended to pass on the management of the PMI phase to mid or lower-

level managers, a situation that potentially creates a gap or limitation to the smooth

implementation of the postmerger phase. A correlation exists between leadership type and

M&A approach (Angwin & Meadows, 2009). Specifically, Angwin and Meadows (2009)

found that alignment exists between the kind of executive and the strategic

interdependence approach to M&A, while no such alignment exists for the holding

approach to M&A. The finding implies a direct impact on the integration approach and,

ultimately, PMP. Furthermore, the criticality of leadership to postmerger success is

accentuated by the impact of the choice of PMI strategies, speed of integration,

communication, corporate culture, human resource management, and other leadership

decisions on M&A outcomes (Gomes et al., 2013; Rouzies et al., 2018). A seemingly

obvious implication of these studies is that leadership needs to be engaged and involved

in the PMI process and should be effective.

Leadership Involvement

Measuring leadership involvement in M&A is not something researchers have

done in the past. Despite the well-acknowledged criticality of the postmerger phase of an

M&A, gaps in literature and research into this phase of M&A persist (Angwin &

Meadows, 2015; Weber & Tarba, 2013). Dahl and Olsen (2013) suggested that leadership

involvement is a quality based mainly on employees’ perception of leadership. Dahl and

Olsen (2013) and Henningsson, et al. (2018) argued that leadership involvement (LI)

reflects workers’ perception of the extent to which leaders engage in the planning and

execution of work operations, in this regard PMI, and participate in creating a facilitating

environment for collaboration, communication, and quality or safety compliance. Other

researchers have stated that leadership is central to an organization’s drive toward quality

and excellence, regardless of the industry (Birken et al., 2015; Kanji, 2008). Leadership

that is participative or involved is essential to continuous quality improvement and

enhance organizational excellence (Kanji, 2008). Other researchers have linked

leadership involvement as predictors of organizational excellence, stating that

organizational excellence implies the efficiency of operations and effectiveness in service

(Thürer, Tomašević, Stevenson, Fredendall, & Protzman, 2018). Leadership effectiveness

can be determined by how much an organization’s performance is enhanced under the

direction of a leader (Datta, 2015; Yukl, 2013). Similarly, patient outcomes provide a

means of measuring the effectiveness of service in hospital settings (Porter, Larsson, &

Lee, 2016). Better hospital quality index scores are indicative of leadership effectiveness

and involvement in activities impacting quality outcomes (Datta, 2015; Goff et al., 2015;

Parand, Dopson, Renz, & Vincent, 2014; Tasi, Keswani, & Bozic, 2019; Vaughn et al.,

2006). Quality patient outcomes or hospital quality are, therefore, indicative of LI.

Safety or quality leadership reflects LI. Quality leadership reflects participative

management (O’Dea & Flin, 2001). Participative management essentially means LI (Dahl

& Olsen, 2013; O’Dea & Flin, 2001). Quality delivery is a useful measure of LI in health

care delivery (McKean & Snyderman, 2019). Evidence from research shows that senior,

executive, or strategic leadership directly impacts safety climate and patient outcomes

(Kelloway, Mullen, & Francis, 2006; McFadden, Stock, & Gowen, 2015). Leadership

that is involved enables improvements in patient safety and quality outcomes (Barling,

Loughlin, & Kelloway, 2002; Kelloway et al., 2006; McFadden et al., 2015; Rankin et

al., 2016; Sandberg, 2018). Involved leadership is crucial to any business or process

implementation (Richter et al., 2016; Sandberg, 2018). Therefore, quality metrics are

viable and credible measures of LI. Also, senior leadership involvement has a moderating

effect on the quality of care and patient safety outcomes.

M&A activity impacts patient quality of care outcomes. In a study of the impact

of hospital mergers on treatment intensity and patient outcomes, Hayford (2012) found a

negative impact on patient health outcomes. Using data from California’s Office of

Statewide Health Planning and Development (OSHPD) for 1990 through 2006, which

included 40 mergers, Hayford (2012) identified an increase in patient mortality rate and

the use of bypass surgery and angioplasty in patients with heart disease (Hayford, 2012).

This study showed a clear association between the quality of patient outcomes and

hospital M&A activity. This finding and the direct relationship between LI and quality

provided a viable argument for the direction of this study. Another research crucial to this

study's direction was the work of Arvonen and Pettersson (2002) on leadership as a

predictor of cost and change effectiveness. In a study of 49 departments of a Swedish

firm, Arvonen and Pettersson (2002) found evidence supporting leadership involvement

as a predictor of cost and efficiency. This finding is informative on the use of cost

reduction and efficiency measures to measure leadership involvement in creating a

supporting and productive postmerger environment. Reinforcing this direction is the

evidence that attaining cost efficiencies is an underlying driver for hospital mergers

(Hayford, 2012; Schmitt, 2017). Cost reduction and efficiency is also an essential metric

in the Center for Medicare and Medicaid's hospital value-based purchasing program.

Another vital consideration is that M&A typically involves efforts at achieving synergy

through resource sharing or transfer (Brueller et al., 2018; Hayford, 2012; Osarenkhoe &

Hyder, 2015). A product of synergy creation is potential service consolidation, which

theoretically, should result in improved patient outcomes, cost efficiency, and cost

reduction (Avdic, Lundborg, & Vikström, 2019; Colla, Bynum, Austin, & Skinner, 2016;

Hayford, 2012; Schmitt, 2017). The implication is that using quality improvements as a

measure of LI and a factor in health care M&A is a practice supported by research.

IT Integration

IT integration is critical to achieving efficiencies and providing access to better

patient care. IT provides hospitals with a means of making health care delivery systems

safer, more accessible, efficient, and affordable (Agarwal, Gao, DesRodes, & Jha, 2010;

Bowens, Frye, & Jones’ 2010; Ross, Stevenson, Lau, & Murray, 2016; Singh & Sittig,

2016). Though questions remain on the relationship between health care IT (HIT) and

hospital performance, researchers have found that HIT contributes to improving

profitability, providing competitive advantage, reducing cost, minimizing errors, and

significantly reducing waste (Mello, Chandra, Gawande, & Studdert, 2010; Wang, Wang,

& McLeod, 2018). An integrated HIT system enables hospitals to improve the quality of

care, productivity, and financial performance (Kohli & Tan, 2016; Wang et al., 2018).

With the strategic objectives of many hospitals and health care M&A being to improve

market positioning, achieve efficiencies, improve and consolidate care delivery, ensuring

an efficient integration of the IT systems of the merging hospitals is therefore vital to the

overall success (Bradley, 2016). However, achieving a successful integration does not

come easily.

Integrating the IT systems of merging organizations poses a significant challenge.

PMI significantly determines the success or otherwise of M&A (Angwin & Meadows,

2015; Baker & Niederman, 2014; Chang et al., 2014; Henningsson et al., 2018;

Steigenberger, 2017). Researchers identified IT integration as essentially the most

challenging and crucial of all areas pertinent to the outcome of the M&A due mainly to

the dependence of businesses on their information systems, particularly in health care

(Baker & Niederman, 2014; Bradley, 2016; Chang et al., 2014; Henningsson et al., 2018).

It, therefore, seems imperative to develop an effective plan for the integration process,

with a considerable focus on IT. However, the gaps in the literature on the relationship

between IT integration and postmerger performance present an opportunity for further

research that will be beneficial to business practice.

Defining the IT integration strategy is a necessity for an effective PMI. A clear

business strategy that aligns with the IT integration strategy is vital for success (Baker &

Niederman, 2014; Bradley, 2016). Misaligned business and IT strategy create a challenge

that may not be easily overcome (Baker & Niederman, 2014). IT integration strategies

must incorporate IT infrastructures, applications and data systems, IT management,

policies, and support (Chang et al., 2014; Wijnhoven, Spil, Stegwee, & Fa; 2006). Using

three case studies of hospitals in M&A, Wijnhoven et al. (2006) proposed a business-IT

alignment model based on Haspeslagh and Jemison’s PMI framework. According to

Wijnhoven et al. (2006), if the merger objective is absorption, a situation where the

acquired firm is fully absorbed into the acquiring company, IT integration objective

would be a complete integration of all IT resources. If symbiosis or preservation are the

M&A objectives, IT integration goals would be partial integration or a co-existence of the

firms’ IT resources, respectively (Chang et al., 2014; Lohrke, Frownfelter-Lohrke, &

Ketchen, 2016; Wijnhoven et al., 2006). Wijnhoven et al. (2006) further stated that

possible IT integration approaches are (a) renewal, (b) takeover, (c) standardization, and

(d) synchronization. Table 1 shows the M&A goals and the aligned IT integration

strategies, as identified by Wijnhoven et al. (2006). Baker and Niederman (2014)

described these strategies as transformation, consolidation, combination, or co-existence,

while Henningsson and Kettinger (2016) similarly categorized the IT integration

approaches as renewal, absorption, best of the breed, and co-existence. Renewal or

transformation implies the formation of a new IT entity with new designs and processes

(Baker & Niederman, 2014; Wijnhoven et al., 2006). When the IT integration is a

takeover, the IT systems of one of the merging firms are wholly absorbed by the other,

while standardization and synchronization involve integrating comparable IT operations

and minimal integration, preserving the IT entities, respectively (Wijnhoven et al., 2006).

Table 1

M&A Strategies and IT Integration Approaches

M&A integration

ambition

M&A objectives IT integration

objectives

IT integration

approaches

High Absorption Complete IT

integration

Renewal

Takeover

Standardization

Moderate Symbiosis Partial IT integration Standardization

Low Preservation IT coexistence Synchronization

Note. Adapted from “Post-merger IT integration strategies: An IT alignment perspective,”

by F. Wijnhoven, T. Spil, R. Stegwee, and R. T. A. Fa, 2006, The Journal of Strategic

In examining the criticality of IT integration to the outcome of M&A, Henningsson and

Kettinger (2016) stated that possible outcomes of failed integration efforts include

business inefficiencies, business disruption, unrealized potential, staff reaction, delay, and

overspending. Furthermore, Henningsson and Kettinger (2016) found five contextual

factors for IS integration failure as time pressure, complexity, inflexibility or merger

unreadiness, sociotechnical differences, and power relations. Mitigating IT integration

and PMI failure requires a significant reliance on organizational leadership (Henningsson

& Kettinger, 2016). This finding supported a key premise of this study. Other researchers

have provided health care-specific insights on postmerger IT integration.

M&A in the health care provider space transcends activities between hospitals and

hospital systems. In a mixed study of M&A activity between hospitals and physician

practices, West et al. (2017) found that though clinical integration was limited between

the hospitals and the practices, all hospitals fully integrated their HIT systems. This

finding by West et al. (2017) is significant in the light of Haspeslagh and Jemison’s

(1991) PMI framework through which they asserted that organizations would either

pursue a strategic interdependence or organizational autonomy approach to integration.

According to Haspeslagh and Jemison (1991), whichever of the two approaches is

preferred or implemented determines the level of the integration achieved. When there is

a high desire for strategic interdependence and a low appetite for organizational

autonomy, the outcome is absorption. Absorption occurs when the processes, resources,

and assets of the acquired firm are fully taken over and replaced with the acquiring

company’s systems without any deference to which of the organizations may have the

superior system (Haspeslagh & Jemison, 1991). On the opposite end of absorption is

preservation, which occurs when strategic interdependence (SI) is a low priority while

maintaining organizational autonomy (OA) is of a higher priority (Haspeslagh &

Jemison, 1991). Symbiosis, a third possible outcome of the mix of the two approaches,

occurs when SI is high, and OA is a top priority as well. The findings by West et al.

(2017) on minimal clinical integration with fully integrated IT systems, point to

Symbiosis as the approach taken by all the hospitals in their study and makes

understanding the relationship between health IT integration and postmerger performance

vital.

The impact of IT on organizational performance has been the subject of several

studies. Rivard, Raymond, and Verreault (2006) used an integrated model that comprised

of a resource-based approach and a competitive strategy framework to evaluate the

contributions of IT to business. Using a mixed approach for their study, Rivard et al.

(2006) found significant support for their integrated model and evidence affirming the

vital role of IT for more excellent organizational performance. According to Rivard et al.

(2006), the results show a significant correlation between IT support for strategy and

market performance. Similarly, Rivard et al. (2006) found a meaningful relationship

between IT support for firm assets and profitability. These findings show that IT is

critical to organizational performance. In a study of the relationship between IS strategy

and organizational performance, Leidner and Preston (2011) similarly found that IT is

crucial to business performance and that performance diminishes where there was no

clear IT strategy. Therefore, ensuring proper planning and implementation of IT changes

during a merger and acquisition is vital merger performance. Williams, Mayer, Chien,

and Williams (2015) conducted a qualitative phenomenological study of the factors that

impact IT integration in a postmerger environment. Williams et al. (2015) stated that they

intended to derive information that may be a useful guide for business leaders tasked with

leading IT integration efforts, and for strategic decision-makers. Also, Williams et al.

(2015) sought to understand the relationship between entropy and the five postmerger

factors of leadership, communication, organizational culture, people, and strategy.

Though the researchers showed a relationship between the factors identified and

postmerger IT integration, the extent of the impact was not fully defined. The researchers

suggested that further research might help with providing the desired clarity and

measures.

Beyond IT integration and leadership, researchers have identified several other

factors that impact M&A outcomes. Integration speed and a people-first approach toward

integration are crucial factors (Jap, Gould, & Liu, 2017; Uzelac, Bauer, Matzler, &

Waschak, 2016). Additional factors identified in the literature include communication and

interactions between merging firms, alignment, knowledge transfer, geography, and

economic value (Graebner et al., 2017; McCarthy & Aalbers, 2016). The divergent views

amplify the need for clarity and more empirical study of factors impacting postmerger

performance (PMP).

Postmerger Performance

Evaluating postmerger performance (PMP) of businesses is an area of significant

interest to scholars and researchers. Reddy et al. (2019) evaluated mergers in India and

China from 2004 to 2006 to determine if these mergers created value. According to

Reddy et al. (2019), value creation is a measure of PMP. Using a representative sample of

140 M&A events, with 70 randomly selected from the Shanghai and Shenzhen Index in

China and 70 randomly chosen from the BSE 100 Index in India, respectively, Reddy et

al. (2019) conducted a quantitative study of the activities to assess the PMP. Relying on

existing empirical studies, Reddy et al. (2019) chose the use of abnormal returns, other

financial metrics like the return on equity (ROE) and return on assets (ROA), and

volatility to test if M&A created value postmerger. The results from the study showed

that M&A did not initially generate value in Chinese firms but added significant value

later. Analyses of Indian firms showed that M&A did not create value initially or later

postmerger. The results observed from the Indian market diverged from the Chinese

market and is a pointer to the implication that profiting from an M&A cannot be

assumed. Leaders need to effectively evaluate their firm’s market and dynamics before

embarking on an M&A. In another investigation of sources of value creation or

destruction in a merger or acquisition, Ibrahimi and Meghouar (2019) evaluated

horizontal M&A using quantitative methods. Ibrahimi and Meghouar (2019) identified

several factors that should provide useful information to business leaders on the factors

that enhance effective PMP. Ibrahimi and Meghouar (2019) found that the value creators

included business turnover, operational cost, savings or profit from tax, and reduction in

fixed assets. Postmerger value destroyers identified included debts, operating expenses,

and significant variations in finance charges (Ibrahimi & Meghouar, 2019). The results

from these studies may also be considered a testament to the fact that there are many

determinants of the outcome of a merger.

Improving business performance is an important strategic objective of M&A. The

evidence, however, suggests mixed results in performance (Henningsson & Kettinger,

2016; Jap, Gould, & Liu, 2017; Rahman & Lambkin, 2015). Zhang, Wang, Li, Chen, and

Wang (2018) reported that studies on the performance results of acquiring firms had

shown inconsistent results. In a study of the performance impact of M&A on firms in

emerging economies, Zhang et al. (2018) found a positive correlation between the type of

M&A and business performance, which they evaluated in financial terms like return on

assets and price-earnings ratio. According to Zhang et al. (2018), a positive relationship

exists for value-chain-extension and technology-driven mergers. This finding, according

to Zhang et al. (2018), supports the need for firms to focus on resource integration

postM&A to achieve better results. Schmitt (2017), on the other hand, posited that

hospital mergers should result in a reduction of costs. In a quantitative study of hospital

mergers in the United States between 2000 and 2010, Schmitt (2017) found that acquired

hospitals achieved a cost reduction between 4 and 7% in the years after the merger. Cost

reduction impacts performance positively (King, 2017; Schmitt, 2017). Schmitt’s

findings support the theory that cost reductions achieved through M&A will enhance

performance in a merger focused on extending the value-chain through expansion or

entry into new markets (Zhang et al., 2018). Other factors impact M&A outcomes.

Researchers have used different metrics to assess and measure the factors that

impact the performance of hospitals. Indicators such as financial performance, efficiency,

effectiveness, patient safety, quality, employee satisfaction, work-life balance, mortality

rates, cost, readmission rates, and many more, have been used by researchers to evaluate

the performance of hospitals (Davis et al., 2013; Gu & Itoh, 2016; Markazi-Moghaddam

et al., 2016). Wang et al. (2018) conducted a quantitative study of the impact of

investments in HIT on hospital performance and productivity. Wang et al. (2018) found

that investments in HIT correlate positively with a hospital’s financial performance.

Pourmohammadi, Hatam, Shojaei, and Bastani (2018) took a holistic approach in their

meta-analysis of existing studies on hospital performance, to determine the critical

performance indicators. Pourmohammadi et al. (2018) found that factors impacting

hospital performance may fall into three categories: efficiency or utilization, financial,

and effectiveness. Efficiency and utilization are further dependent on cost, the number of

hospital beds as well as human resources, technology utilization, and clinical resource

utilization. Effectiveness, on the other hand, is a measure of quality, safety, and

responsiveness to patient needs, the employees, and the community at large. In a review

of the literature on hospital performance from 1977 to 2014, Markazi-Moghaddam et al.

(2016) found significant references to quality, safety, mortality, readmission rates, and

patient satisfaction as indicators of hospital performance, in addition to efficiency and

effectiveness. In their work on the role of service quality on hospital performance, Lim et

al. (2018) found evidence supporting a relationship between service quality, patient

satisfaction, and hospital financial performance. Hospital performance is, therefore,

multi-dimensional and goes beyond financial results (Lim et al., 2018; Markazi-

Moghaddam et al. , 2016; Pourmohammadi et al., 2018).

Determining the PMP of a hospital system is essential to understanding if the

merger achieved the expected benefits and the implications the change may have on the

merged organization’s future direction. Traditional performance measures focus mainly

on the financial metrics of an organization postmerger (Rahman & Lambkin, 2015).

Measuring hospitals’ PMP provides a different challenge because they are primarily

involved in providing care to their patients and communities (Gu & Itoh, 2016;

Pourmohammadi et al.; 2018). In a study of health system frameworks across eight

countries, Braithwaite et al. (2017) identified key performance indicators used by

governments, regulatory, and professional bodies to measure how well a hospital is

doing. Braithwaite et al. (2017) conducted a systematic review of the available literature

first to identify comparable nations using performance indicators for monitoring health

care. The eight countries identified were England, Canada, United States, Denmark,

Australia, New Zealand, Scotland, and The Netherlands. Next, Braithwaite et al. (2017)

determined the specific indicators, assessed each for applicability, and then compared the

frameworks for each country. The results of the study showed that the leading

performance indicators are access to care, patient experience, safety and quality,

efficiency, and population health outcomes. According to Braithwaite et al. (2017), these

internationally recognized indicators provide a universal and logical method of measuring

a hospital’s performance. Monitoring these qualities provide the necessary pressure on

hospitals to improve and achieve better outcomes (Braithwaite et al., 2017; Parand et al.,

2014). Applying these non-financial metrics to measuring a hospital’s PMP will,

therefore, be consistent with research. King (2017) agreed with the value of quality

metrics as identified by Braithwaite et al. (2017) but went a little further to stress the

importance of other parameters, mainly to regulatory authorities in the U.S. Federal Trade

Commission (FTC), which monitors mergers between hospitals. In an article analyzing

the current state of health care in the United States, King (2017) stated that the FTC

imposed restrictions on mergers forced a halt on transactions that are perceived to

undermine the quality of clinical care and severely impact health care costs for the

consumer through a potential increase in prices. The focus of the FTC on quality of

clinical care is an indicator of the importance of using quality metrics like those identified

by Braithwaite et al. (2017) in determining PMP. However, other views exist among

researchers. Greaney (2018) agreed that achieving efficiencies through vertical mergers

and integrated care delivery systems is vital but seems to dissent on the relative

importance when compared with the economic impacts from such alliances. Greaney

(2018) opined that gaps exist in current antitrust laws and measurements of the effects of

health care mergers, stating that the economic and market impact of vertical mergers

needs careful monitoring. The authors of all three studies reviewed help to emphasize the

importance of appropriate PMP measurements to all stakeholders.

Performance diminishes when M&A impacts organizational effectiveness. In an

article presenting the results of their study of exergy destruction in mergers, Olcay, Öner,

and Olcay (2019) raised some valid points about the mixed outcomes of M&A. Exergy is

the maximum amount of useful work possible (Kalogirou, Karellas, Badescu, &

Braimakis, 2016). According to Olcay et al. (2019), research shows that M&A often

results in reduced innovation and multiple failures (Federico, Langus, & Valletti, 2018).

Though much debate continues, Olcay et al. (2019) approached assessing the subject by

conceptualizing M&A performance as exergy, using the principles of thermodynamics

analysis of mixing physical systems as the basis of their approach. According to Olcay et

al. (2019), horizontal mergers typically develop out of the desire to reduce cost, increase

negotiation, and market power, and diminish competition. Vertical mergers, on the other

hand, seek to maximize benefits through synergy (Koch, Wendling, & Wilson, 2017;

Olcay et al., 2019). Using a mixed-methods approach that relied on secondary data

sources, Olcay et al. (2019) summarized factors that influence pre-merger performance as

cultural fit, strategic fit, and company and industry attributes. Olcay et al. (2019) stated

that these considerations are as vital to successful M&A performance as other postmerger

factors that researchers have studied with varied results. Applying the principles of

thermodynamics to M&A, Olcay et al. (2019) found that the exergy of the newly formed

firm is lower than the sum of the exergies of the companies before the merger or

acquisition. When the merged firms are less compatible culturally or strategically, the

exergy loss from a merger is higher (Olcay et al., 2019). A potential implication of the

findings of Olcay et al. (2019) is a reduction in performance in the newly formed

company, due to a loss of exergy. Insights from Olcay et al. (2019) align with the views

expressed by Zaheer et al. (2013) on synergy sources and PMIs. Zaheer et al. (2013)

found that firms may disaffect employees of acquired companies when they seek to

leverage similarities and complementarity through a high level of PMI. Employee

disaffection may invariably lead to loss of effort and work performance. Bereskin, Byun,

Officer, and Oh (2018), in their quantitative analysis of the effect of cultural similarity on

M&A outcomes, found that a higher cultural fit bodes well for the performance of an

M&A. Considering the cultural fit and strategic fit as critical pre-merger factors enables

the improvement of the postmerger performance of the newly formed company (Bereskin

et al., 2018; Olcay et al., 2019). For leaders, these studies imply that careful analyses of

factors beyond financial or market metrics should go into the decision-making and review

process for M&A. Multiple influences determine postmerger performance, which

business leaders need to be aware of and integrate into their planning.

Transition

Hospital business leaders need to understand how to maximize the postmerger

performance of their organizations. This need becomes even more critical as the rate of

M&A among hospitals will grow over the next several years, and evidence abounds that a

significant percentage of M&A fail to achieve pre-merger goals (Chang et al., 2014;

Friedman et al., 2016; Rebner & Yeganeh, 2019). Better performing hospitals imply

better care delivery, improved patient outcomes, business viability, and profitability

(Fleishon et al., 2017). Understanding the relationship between IT integration, senior

leadership involvement in the merger process, and postmerger performance would

contribute to the industry knowledge and help business leaders to lead their organizations

more effectively through M&A.

This section included the purpose of this study, the research question and

hypotheses, and a review of representative literature relevant to the study. The subsequent

sections expand on the study. Section 2 provides information on the research method and

design, while Section 3 includes the study, the findings, and conclusions.

Section 2: Project Design and Process

Successful M&A are crucial to hospitals and health care organizations.

Understanding the relationship between critical factors could be pivotal in determining

how well a hospital is able to continue to serve its patients and community. Section 2

includes detailed information about the study method and design. This section also

includes a discussion on the sources of data, the data analysis, and important ethical

considerations.

Method and Design

Aligning research method and design to the type of study is essential to the

research process and outcome. The following subsection includes an evaluation of the

research methodology and the reasoning informing the choice.

Method

The purpose of this quantitative ex post facto study was to examine the

relationship between IT integration, senior leadership involvement in PMI, and

postmerger performance of hospitals. The population consisted of senior leaders of

general acute care hospitals and hospital systems located in the midwestern states of

Ohio, Michigan, Indiana, Illinois, and Wisconsin with prior involvement in a successful

merger or acquisition. The results of this study may enhance hospital leaders’

understanding of achieving desirable results from M&A. The implications for social

change include the potential to have a better understanding of how to improve postmerger

hospital performance, thereby enhancing the ability of health care organizations to

provide quality care for their communities, increase positive patient outcomes, and

encourage the overall well-being of their communities.

I chose to use a quantitative research methodology for this study. The quantitative

research methodology is fact driven, relies on measurements and numeric data, and is

more akin to the positivist philosophy (McCusker & Gunaydin, 2015; Saunders, Lewis, &

Thornhill, 2015). The problem of study points to the existence of factors that impact the

outcome of a business decision, which lends to positivism as a philosophical approach

and partly informed the choice of a quantitative methodology. Also, quantitative research

is best suited for testing theories or hypotheses and for explaining a business or social

change through impartial measurements and factual analysis of data (Fassinger &

Morrow, 2013; Firestone, 1987; McCusker & Gunaydin, 2015). Quantitative research is

suitable for determining the relationships between two or more variables, which was the

goal of this study. Some of the disadvantages of quantitative methods include their

limitation in propelling a deeper understanding of a phenomenon beyond what the

numerical data show (Barnham, 2015). Quantitative methods are not useful for evaluating

the experiences of participants or for assessing their meanings (Barnham, 2015; Saunders

et al., 2015). Qualitative methods would be more appropriate in such cases. Qualitative

research is exploratory and uses open-ended and nonnumeric data (Barnham, 2015;

Saunders et al., 2015). Qualitative research is appropriate for developing an

understanding of a social phenomenon and interpreting experiences (Sumskis &

Moxham, 2017). A qualitative research approach would have been fitting for this study if

the goal were to discover the strategies that can enhance the performance of an M&A.

The primary research question for the study is: What is the relationship between IT

integration, senior leadership involvement in PMI, and postmerger performance in hospitals?

H0: There is no statistically significant relationship between IT integration, senior

leadership involvement in PMI, and postmerger performance.

Ha: There is a statistically significant relationship between IT integration, senior

leadership involvement in PMI, and postmerger performance.

Design

Secondary data analysis affords a researcher with a cost-effective way of using

archival data to evaluate new research questions. Secondary data analysis is a reliable

research option for answering new research questions when the source and process of

data collection are reliable and credible, and the original study fits the new inquiry (Boo

& Froelicher, 2013; Johnston, 2017). Advances in technology have enhanced the ability

to gather and transfer large quantities of data, usable for secondary data analysis;

however, it does not minimize the need for quality and a reasoned theoretical approach to

the research (Boo & Froelicher, 2013; Johnston, 2017). I used secondary data analysis for

this study.

The ex post facto research design is a nonexperimental design commonly used in

social research. The ex post facto design allows for a study to begin after the event has

occurred (Giuffre, 1997; Salkind, 2010). A benefit of this design is the absence of

influence over events or data captured since it occurs after the fact, and the event

measured is real (Giuffre, 1997; Salkind, 2010). Another advantage of the ex post facto

design is that it enhances ethically acceptable research because it eliminates the exposure

of participants or study subjects to potentially harmful experiments. However, a potential

shortcoming of the design is in the area of internal validity. This limitation is due to a

lack of control over the independent variables and participant selection (Salkind, 2010).

Lack of internal validity will limit the ability to determine causality (Ittner, 2014;

Salkind, 2010). Internal validity issues may be overcome or minimized by controlling for

influences that may impact the outcomes of the study (Ittner, 2014). The goal of this

study was not a determination of the causal effect of a variable or its impact, but to

establish if a relationship exists among crucial variables, resulting in specific, measurable

facts. An experimental design would have been inappropriate for the timeframe and scope

of this study.

Data Analysis

The AHA and Irving Levin Associates are health care industry-recognized sources

of information and M&A intelligence. Researchers have widely used data from AHA and

Irving Levin Associates (King. 2017; Schmitt, 2017). I utilized data from Irving Levin

Associates and AHA to identify the target hospitals with a history of M&A from 2013 to

2017 in the midwestern states of Ohio, Illinois, Indiana, Michigan, and Wisconsin.

Archival data from the Center for Medicare and Medicaid Services and

AHA’s annual survey of hospitals (ASDB) and its supplemental IT survey (ITDB) were

the primary sources of data for the analysis. The AHA data included responses to AHA’s

annual survey and supplemental IT survey of hospital chief executives. Researchers

support the use of an archival data collection technique as a viable, credible, and practical

approach to data collection (Ellram & Tate, 2016; Schmitt, 2017; Shultz, Hoffman, &

Reiter-Palmon, 2005). The AHA data are valid, reliable, and credible (AHA, 2020;

Schmitt, 2017). The data source is relied on by the Office of the National Coordinator for

Health Information Technology (ONC), a governmental policy making agency of the

Office of the Secretary for the U.S. Department of Health and Human Services (HHS), as

well as the U.S. Census Bureau and Center for Medicare and Medicaid Services (AHA,

2020). I linked the data from AHA with the Hospital Compare data (HCDB) from the

Center for Medicare and Medicaid Services (CMS). The Medicare Provider Identifier

links the two data sets. All Medicare-certified providers, which is essentially almost

every hospital in the United States, are required to submit annual costs and operational

reports to CMS (Center for Medicare & Medicaid Services, 2016; Schmitt, 2017). This

report, in addition to the results from the survey of patient’s experiences by CMS,

culminates in the Hospital Compare data (Center for Medicare & Medicaid Services,

2016). A vital measure of the Hospital Compare information is CMS’ Total Performance

Score (TPS). The TPS, according to CMS, is a composite score that links hospital quality

to Medicare payment and measures a hospital’s performance in (a) clinical care, (b)

patient and caregiver-centered experience of care, (c) safety, and (d) efficiency and cost

reduction. A few essential assumptions regarding the archival data were that (a) the data

were not manipulated in any way to portray specific results, (b) all data were truthful and

accurately reflect the state of the hospitals at the point of data collection, and (c) the

information was obtained ethically from the chief executives or designated leaders of the

respective hospitals. Missing data present a potential problem that impacts research

reliability. Data analysis for this study included only complete data.

Data source mapping

The AHA ITDB is a supplement of the ASDB. The survey instruments are

complementary and both data contain the same hospital demographics and primary

identifiers. Figure 4 shows the study approach, with the incorporation of TPS data from

CMS’ HCDB. The HCDB contains general hospital information, results from the survey

of patients’ experiences, measures of the quality of care, payment, and value of care

received. The HCDB contains information that could provide valuable data for the

variables for my study but has limitations as a singular source of comprehensive data for

the study. The independent variables (IVs) for my study were IT integration and senior

leadership involvement. The dependent variable (DV) was postmerger performance. The

IT integration predictor variable was nominal (categorical), whereas senior leadership

involvement (IV) and postmerger performance (DV) were of the ratio scale of

measurement (continuous).

Figure 4. Data source mapping. AHA data supplemented with CMS total performance

score.

Data Analysis Techniques

Several data analysis techniques are available and utilized by researchers for

quantitative and qualitative studies. I leveraged the multiple linear regression data

analysis technique for this study. Other quantitative analysis methods include the t-test

and the analysis of variance (ANOVA). According to Green and Salkind (2017), the t-test

is useful for evaluating hypotheses that involve a single mean or the difference between

two means. The ANOVA is a tool for assessing the relationship between one or more

factors and a dependent variable (Green & Salkind, 2017). The type of ANOVA

appropriate for analysis depends on the number of factors available per case, in addition

to the dependent variable (Green & Salkind, 2017). The multiple linear regression

analysis is an extension of a bivariate linear regression, which is useful to predict the

relationship between two variables; that is, one variable forecasts another. Unlike the

bivariate linear regression, the multiple linear regression is useful for evaluating the

relationship between multiple independent variables and a dependent variable (Green &

Salkind, 2017). Acikkar and Sivrikaya (2018) described the multiple linear regression as

a flexible, easy to use, and powerful tool for statistical analysis. In addition to affirming

the importance of multiple linear regression in research, Nimon and Oswald (2013)

stressed the value of adding alternative indices like validity coefficients, structure

coefficients, and relative weights to compensate for the effect of multicollinearity due to

intercorrelation between predictors. Green and Salkind identified some vital assumptions

for the use of multiple linear regression. These assumptions include normality of

distribution of the dependent variable, equality of variances for all levels of the

independent variables, and random sampling of the population. Data assumptions for the

use of multiple linear regression for this study included lack of multicollinearity,

homoscedasticity, normality, linearity, absence of any significant outliers, and

independence of residuals. A violation of these assumptions may result in an inaccurate

analysis. A thorough evaluation of each assumption was necessary to ensure the validity

of results. I used the multiple linear regression for this study, to evaluate the relationship

between IT integration, senior leadership involvement in PMI, and postmerger

performance in hospital systems.

Determining and using an appropriate sample size is vital to research quality. A

priori power analysis is useful in determining the minimum required sample size. With

the use of a G power analysis to derive the appropriate sample size, the appropriate or

minimum sample size was 68 participants. I assumed medium effect size of 0.15, an alpha

of 0.05, and a power of 0.80. The statistical power of 0.80 sufficiently handles Type I and

Type II errors (Perugini, Gallucci, & Costantini, 2018). Figure 5 shows a graphical model

of the sample size for multiple linear regression, with the parameters defined previously.

Figure 5. Graphical model of a priori power analysis for linear multiple regression using

the free G*Power 3.1 software by F. Faul, E. Erdfelder, A. Buchner, and A. Lang, 2009.

Ethics

Maintaining ethical standards in research is crucial for the well-being of the

participants. The Belmont principles for ethical research emphasized respect for

participants, beneficence, and justice as crucial elements for acceptable research that is

humane and factors in the well-being of the participants (Brakewood & Poldrack, 2013;

Vitak, Shilton, & Ashktorab; 2016). According to Brakewood and Poldrack (2013),

studies using secondary data typically align with the Belmont principles for protecting

human participants. Though the data for this study was from archival records, adhering to

these principles enhances the ethical quality of the study, and ensures compliance with

the standards of Walden University’s Institutional Review Board (IRB). Scrubbing of the

data for this study to remove personally identifiable characteristics like the name of the

participant or hospital ensures adherence to ethical principles of research. Storing the data

on a secure, encrypted device for 5 years is crucial for safeguarding the data and adhering

to ethical standards of research. These vital steps were essential parts of this study. AHA

obtains its extensive hospital data from an annual survey of hospital chief executives.

AHA encourages executives to participate voluntarily through a letter and communicates

the importance of the responses in providing a picture of health care practice in the

United States and information that may assist policy makers, researchers, and various

stakeholders in the health care industry. AHA attests to a response rate of more than 75%

to its annual surveys. The data collection instruments for the AHA annual survey of

hospitals and the supplemental IT survey are publicly available through its websites. The

collaboration with federal and state health care agencies, industry recognition and

participation, lend to support the assumption that the data was collected ethically.

Reporting requirements for all hospitals and providers participating in Medicare demands

that hospitals provide crucial performance information to CMS through the Hospital

Inpatient Quality Reporting and Hospital Outpatient Quality Reporting programs. These

reports follow an ethical standard, are assumed to be truthful, and verifiable (Center for

Medicare & Medicaid Services, 2016). The Hospital Compare data are publicly available.

The Walden University IRB approval number for this study is 06-24-20-0971438.

Transition and Summary

Section 2 began with a restatement of the purpose of this study, followed by a

detailed description of the research method and design. The section also included a

thorough evaluation of the data sources, the role of the researcher, and ethical

contemplations. The following section, Section 3, will contain findings from the analysis

of the data, the interpretation of the data and possible applications to the postmerger

performance of hospital systems.

Section 3: The Deliverable

Executive Summary

Hospitals play a vital role in the well-being of their communities. Modern-day

health care challenges make it imperative that health care organizations are effective in

discharging their primary responsibilities. A good understanding of variables impacting

the successful implementations of M&A will enable health care firms and their leaders to

respond to society's health needs more effectively. In this section, I present a summary of

my findings and the potential implications for social change.

Purpose of the Study

The purpose of this quantitative ex post facto study was to examine the

relationship between hospitals’ (a) IT integration, (b) senior leadership involvement in

PMI, and (c) postmerger performance. The independent variables were hospitals’ IT

integration and senior leadership involvement in PMI. The dependent variable was

postmerger performance. The targeted population consisted of senior leaders of general

acute care hospitals and hospital systems in the midwestern states of Ohio, Michigan,

Indiana, Illinois, and Wisconsin, with prior involvement in a merger or acquisition. This

study’s results could be beneficial to hospitals as it may enhance the leaders’

understanding of how to achieve desired results from M&A. The social change

ramifications of the project include the potential to enable better postmerger hospital

performance, thereby enhancing hospitals’ ability to provide quality care for their

communities, achieve better patient outcomes, create positive economic impact, and the

enhance overall well-being of their communities.

Goals and Objectives

The goal of this secondary data analysis was to determine if a relationship exists

between IT integration, senior leadership involvement in the process of integrating the

hospitals and systems brought together via an M&A, and postmerger performance.

Understanding if a relationship exists and its impact could be valuable in managing the

M&A process for better outcomes. Better postmerger performance could invariably lead

to positive contributions to society and better patient outcomes. My objective for this

study was to offer a fresh perspective to leaders of health care organizations on how to

steer their firms to success in M&A.

Overview of Findings

Using data from Irving Levin Associates and the AHA Annual Survey of

Hospitals, I identified acute care hospitals from the targeted midwestern states of Ohio,

Michigan, Illinois, Indiana, and Wisconsin with M&A activity (i.e., acquired), between

2013 and 2017. A total of 89 hospitals matched the criteria of acute care, nonfederal, and

general medical-surgery hospitals. Table 2 shows the total count by state.

Table 2

Hospital M&A Count by State

State

Count

Ohio 18

Michigan 27

Indiana 11

Illinois 24

Wisconsin 9

The focus on acquired hospitals presented some challenges for this study. One is

that some hospitals lose their unique identifiers after they are acquired and absorbed into

an existing system to form a larger organization. Consequently, determining the

performance of the acquired hospital becomes difficult postmerger. Despite this

challenge, focusing on the acquired hospital instead of the acquiring hospital was the

intent of this study because it presented a unique perspective for evaluating the research

question. I eliminated acquired hospitals without unique system identifiers postmerger

from the final sample population for analysis, including only hospitals with an individual

identifier before and after the M&A in the study. The effect was the elimination of a total

of 17 hospitals from the initial sample. Table 3 shows the final breakdown of the target

hospital count by state.

Table 3

Target Hospitals Count With M&A Count by State

State

Count

Ohio 16

Michigan 20

Indiana 6

Illinois 24

Wisconsin 6

Note. Total count of target hospitals, N = 72.

For the data analysis, I used archived data from the CMS Hospital Compare

Database. Specifically, the 2018 total performance score and the efficiency and cost

reduction scores from the hospital value-based purchasing data for postmerger

performance and leadership involvement measures, respectively. I linked the CMS data to

the data from the AHA annual survey IT supplement for 2018. The two records are linked

using the Medicare Provider ID, which is unique to each hospital. The AHA IT survey

included questions on IT systems interoperability, integration, and implementation

challenges. For data on IT integration, I used responses to Question 23a, “Do you use the

same primary inpatient EMR/EHR system vendor for your primary outpatient EMR/EHR

system?” EMR is “electronic medical records,” and EHR means “electronic health

records.” AHA defined the primary system as the system used for the largest number of

patients or that which represents the hospital’s single most substantial investment. AHA

captured responses to the question using a 5-point scale from 1 to 5, mapped to “yes,

share a single instance,” “yes, but do not share the single instance,” “no,” “do not know,”

and “not applicable.” Number 1 represents the highest level of integration, which is

sharing a single instance or full integration. Number 2 is indicative of partial integration

(i.e., “yes, but do not share the single instance”), whereas 3 indicates limited to no

integration.

Recommendations

My research findings indicate that senior leaders may have a great effect on the

outcome of M&A in hospitals. A significant relationship exists between senior leadership

involvement in the PMI process and postmerger performance. To derive value from

M&A and achieve improved performance, senior leaders of health care organizations

would benefit from understanding how to stay engaged in the PMI process and provide

guidance that will shepherd process leaders through the merger implementation.

Presentation of the Findings

The main research question for this study was as follows: What is the relationship

between IT integration, senior leadership involvement in PMI, and postmerger

performance? Using SPSS, I conducted a multiple linear regression analysis to if a

relationship exists between the independent variables (a) IT integration and (b) senior

leadership involvement in integration, and the dependent variable, postmerger

performance (PMP).

This section includes the findings of the statistical tests, the testing of the

assumptions, and an inferential analysis of the findings.

Descriptive Statistics

A total of 72 cases were included in the analysis. All cases evaluated included

complete sets of data for the predictor and criterion variables. One of the predictor

variables, IT Integration, is polytomous with five possible categories or levels. To use

polytomous variables in a standard multiple linear regression require dummy variables

(Laerd Statistics, 2018). I created a dummy variable for each of the three categories of

responses in the data for IT Integration levels (IT_Int_Full=Yes single instance,

IT_Int_Part=Yes but not single instance, and IT_Int_No=No). The fourth category with

two responses (“Do not know”), was ignored. No participant provided a response

matching the fifth level, “not applicable.” The reference group for the dummy variables

was IT_Int_Full=Yes single instance. Table 4 shows the frequency of responses to the IT

Integration question.

Table 4

IT Integration Response Frequency

Valid Yes, single instance Frequency 48

Percent

66.7

Valid percent

Cumulative

percent

66.7 66.7

Yes, but not single

instance

3 4.2 4.2 70.8

No 19 26.4 26.4 97.2

Do not know 2 2.8 2.8 100.0

Total 72 100.0 100.0

Table 5 shows the descriptive statistics. Analysis of the deidentified data for the hospitals

in the dataset included the dependent variable, postmerger performance (mean, 39.31;

standard deviation, 10.54) and senior leadership involvement (mean, .98; standard

deviation, .056).

Table 5

Descriptive Statistics

Mean

Std.

Deviation

Postmerger

performance

39.31 10.54

Leadership involvement .98 .056

IT_Int_Full=Yes single

instance

.67 .48

IT_Int_Part=Yes but

not single instance

.04 .20

IT_Int_No=No .26 .44

Note. N = 72.

Testing of Assumptions

The testing of assumptions is essential to determine if the multiple linear

regression model is a good fit for the data analysis. Assumption testing is a necessary step

before answering the research question. Using the SPSS software, I evaluated for the

independence of residuals, linearity, homoscedasticity, multicollinearity, outliers, and

normality of distribution. The data and variables for the study already met the other core

requirements for using multiple linear regression: a continuous dependent variable and

two or more independent variables, which may be continuous or nominal.

Independence of residuals. The test for the independence of residuals (or

observations), is a test to determine if there is serial correlation or 1st-order

autocorrelation. Serial correlation implies that the residuals are not independent, and

contiguous residuals are correlated (Chen, 2016; Laerd Statistics, 2018). I ran the

DurbinWatson test to evaluate the independence of residuals. Results from the Durbin-

Watson statistic can range in value from 0 to 4 (Fields, 2009; Laerd Statistics, 2018). A

value close or equal to 2 indicates independence of the residuals. For my analysis, there

was independence of residuals, as assessed by a Durbin-Watson statistic of 2.073. Table 6

depicts the model summary with the Durbin-Watson statistic.

Table 6

Model Summaryb

Adjusted R Std. Error of Durbin-

Model R R Square Square the Estimate Watson

1 .631a .399 .372 8.3507136 2.073

Note. a. Predictors: (Constant), IT_Int_No=No, IT_Int_Part=Yes but not single instance,

Leadership Involvement.

b. Dependent Variable: Postmerger Performance.

Linearity. To evaluate linearity between the independent variables and the

dependent variable, I used the SPSS scatterplot procedure to generate a Scatter/Dot plot

of the unstandardized predicted values and the studentized residuals. A careful analysis of

the plot points to a linear relationship between the independent variables and the

dependent variable. See Figure 6. I also evaluated for linearity between the dependent

variable and each of the independent variables using partial regression plots. I ignored the

partial plot between the dummy variables of the categorical independent variable (IT

Integration) and the dependent variable, a standard approach in regression analysis (Laerd

Statistics, 2018). Figure 7 shows the partial regression plot for total performance score

and leadership involvement. Figures 6 and 7 show the linearity of the relationships.

Figure 6. Scatter plot of studentized residuals by unstandardized predicted value showing

a linear relationship.

Figure 7. Partial regression plot of leadership involvement and total performance score

showing a linear relationship.

Figures 8 and 9 show the partial regression plots for the dummy variables. I did not

consider these plots in determining linearity as the dummy variables are categorical.

Figure 8. Partial regression plot of IT_Int_Part=Yes but not single instance and total

performance score showing a non-linear relationship.

Figure 9. Partial regression plot of IT_Int_No=No and total performance score showing a

non-linear relationship.

Outliers. Testing for outliers allows for checking for data points that are well

outside their predicted values. Running the SPSS Casewise diagnostics did not produce

any results, implying that there were no standardized residuals greater than ±3 standard

deviation. The result suggested the absence of outliers. Further analysis using studentized

deleted residuals did not reveal any residual that needed further investigation as a

potential outlier. The examinations indicated there were no major violations of this

assumption. Additional tests for leverage and influential points did not reveal any cases

with high leverage or that are influential. Results observed were within normal and

acceptable ranges (Cook & Weisberg, 1982; Huber, 1981). See Table 7.

Table 7

Residuals Statisticsa

Predicted Value

Minimum

17.871

Maximum

53.843

Mean

Std.

Deviation N

39.312 6.654 72

Std. Predicted Value -3.222 2.184 .000 1.000 72

Standard Error of

Predicted Value

1.182 4.867 1.802 .797 72

Adjusted Predicted

Value

14.880 53.138 39.265 7.073 72

Residual -20.348 19.0289 .000 8.172 72

Std. Residual -2.437 2.279 .000 .979 72

Stud. Residual -2.999 2.313 .003 1.032 72

Deleted Residual -30.816 19.775 .047 9.183 72

Stud. Deleted Residual -3.195 2.391 .002 1.049 72

Mahal. Distance .435 23.132 2.958 4.626 72

Cook's Distance .000 1.156 .036 .147 72

Centered Leverage

Value

.006 .326 .042 .065 72

Note. a. Dependent Variable: Postmerger Performance.

Homoscedasticity. The assumption of homoscedasticity refers to the absence of a

clear pattern in the spread of residuals. The existence of an increasing or decreasing

pattern would indicate the likelihood of heteroscedasticity, which would be a violation of

the assumption and increase the possibility of a Type I error (Rosopa, Schaffer, &

Schroeder, 2013). The examination of the studentized residuals against the

unstandardized predicted values showed homoscedasticity, as no clear pattern was

observed (see Figure 6).

Multicollinearity. Multicollinearity occurs when there is a high degree of

correlation between two or more predictor variables. I used the Pearson Correlation

statistic to evaluate the correlation between the predictor variables. Table 8 shows the

results. The bivariate correlations were mostly small to medium. However, I observed a

relatively high negative correlation of -.847 between two dummy variables representing

the highest and lowest levels of IT integration. To eliminate the situation described by

Disatnik and Sivan (2014) as an illusion of multicollinearity, I examined the tolerance

and variance inflation factor (VIF) values in the collinearity statistics created by SPSS

(see Table 9). All tolerance values are greater than .1 and VIF values less than 10,

signifying that there was no violation of the assumption of multicollinearity (Hair, Black,

Babin, & Anderson, 2014).

Table 8

Correlations

IT_Int_Part

Postmerger Leadership =Yes but

Performanc Involveme not single IT_Int_No

e nt instance =No

Pearson Correlation Postmerger

Performance

1.000 -.627 -.027 -.131

Leadership

Involvement

-.627 1.000 .147 .248

IT_Int_Part=Yes

but not single

instance

-.027 .147 1.000 -.125

IT_Int_No=No -.131 .248 -.125 1.000

Sig. (1-tailed) Postmerger

Performance

. .000 .410 .136

Leadership

Involvement

.000 . .109 .018

IT_Int_Part=Yes .410 .109 . .148

but not single

instance

IT_Int_No=No .136 .018 .148 .

Note. N = 72.

Table 9

Collinearity Statisticsa

Collinearity Statistics

Model Tolerance VIF

1 (Constant)

Leadership Involvement

.907 1.103

IT_Int_Part=Yes but not

single instance

.951 1.052

IT_Int_No=No .912 1.096

Note. a. Dependent Variable: Postmerger Performance.

Normality. To confirm that the assumption of normality was not violated, I

examined the distribution of the standardized residuals using the histogram depicted in

Figure 10. The results suggested that the residuals are normally distributed.

Figure 10. Histogram showing normality of distribution.

The P-P plot of regression standardized residual further confirmed the observation that

the assumption of normality was not violated (see Figure 11).

Figure 11. The normal P-P plot of regression standardized residual.

To affirm the conclusion of normality, I used SPSS to generate a Q-Q plot of studentized

residual. Figure 12 shows the result, which also confirms that the assumption of

normality was not violated.

Figure 12. Q-Q of studentized residual showing normality.

Inferential Results

Standard multiple linear regression, α = .05 (two-tailed), was used to examine the

usefulness of IT integration and senior leadership involvement in PMI in predicting

postmerger performance of hospitals. The independent variables were IT integration and

senior leadership involvement (SLI). IT integration was reclassified into three dummy

independent variables; full integration (IT_Int_Full), partial integration (IT_Int_Part), and

no integration (IT_Int_No). The dependent variable was postmerger performance (PMP).

The null hypothesis was that there is no statistically significant relationship between IT

integration, senior leadership involvement in PMI, and PMP. The alternative hypothesis

was that there is a statistically significant relationship between IT integration, senior

leadership involvement in PMI, and PMP. I conducted preliminary analyses to assess

whether the assumptions of multicollinearity, outliers, normality, linearity,

homoscedasticity, and independence of residuals were met; no serious violations were

noted (see Testing of Assumptions). The model was able to significantly predict PMP:

F(3, 68) = 15.026, p < .001, R2 = .399. The R2 (.399) value indicated that approximately

40% of variations in PMP is accounted for by the linear combination of the predictor

variables (SLI, IT_Int_Full, IT_Int_Part, and IT_Int_No). The adjusted R2 was 37.2%.

Senior leadership involvement was statistically significant to the prediction (t = -6.55, p <

.001, β = -.647). The dummy variables for the levels of IT integration, IT_Int_Part (t

= .751, p = .455, β = .072), and IT_Int_No (t = .386, p = .700, β = .038) were not

statistically significant (see Table 11).

Table 10

Anovaa

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 3143.472 3 1047.824 15.026 .000b

Residual 4741.940 68 69.734

Total 7885.412 71

Note. a. Dependent Variable: Postmerger Performance.

b. Predictors: (Constant), IT_Int_No=No, IT_Int_Part=Yes but not single instance,

Leadership Involvement.

Table 11

Regression Analysis Summary for Predictor Variables

Variable Β SE Β β t p

Leadership

Involvement -121.363 18.527 -.647 -6.550 <.001

Partial IT

Integration 3.794 5.051 .072 .751 .455

No IT Integration .903 2.338 .038 .386 .700

Note. N= 72. Dependent Variable: Postmerger Performance.

The hypotheses for this study were:

(H0): There is no statistically significant relationship between IT integration,

senior leadership involvement in PMI, and postmerger performance.

(Ha): There is a statistically significant relationship between IT integration, senior

leadership involvement in PMI, and postmerger performance.

The results of the study showed that the null hypothesis can be rejected for senior

leadership involvement in PMI because a statistically significant relationship with

postmerger performance exists. The null hypothesis cannot be rejected for IT integration

because there was no statistically significant relationship. The alternate hypothesis was

rejected for IT integration because there was no statistically significant relationship with

postmerger performance. However, the alternate hypothesis was accepted for senior

leadership involvement in PMI because there was a statistically significant relationship

with postmerger performance.

Despite the findings that the dummy categorical predictors were not statistically

significant, the magnitude of the slope coefficients for these categorical variables

and the observed ranges of the 95% confidence intervals, -6.285 to 13.873 for

partial integration, and -3.762 to 5.569 for no integration, warranted their

inclusion in the final model. This approach to modeling categorical variables in

the regression equation is supported in statistical analysis (Gunter, Chernick, &

Jiajing Sun, 2011; Laerd Statistics, 2018). The slope coefficients (B) for

IT_Int_Part (partial IT integration) and IT_Int_No (no IT integration) compare

the mean of each variable with the reference group, IT_Int_Full

(full IT integration).

Table 12

Coefficientsa

Standardi

zed

Unstandardized Coefficie

Coefficients nts

95.0% Confidence

Interval for B

Model B Std. Error Beta t Sig.

Lower

Bound

Upper

Bound

1 (Constant) 158.134 18.032 8.769 .000 122.151 194.117

Leadership

Involvement

-121.363 18.527 -.647 -6.550 .000 -158.334 -84.392

IT_Int_Part=Yes but

not single instance

3.794 5.051 .072 .751 .455 -6.285 13.873

IT_Int_No=No .903 2.338 .038 .386 .700 -3.762 5.569

The negative slope for leadership involvement (-121.363) indicates a

corresponding increase in PMP for each 1-point decrease in each variable. Similarly, the

positive regression coefficient for partial IT integration (3.794) indicates that better

integration would result in a corresponding increase in PMP. The negative slope (coefficient)

for leadership involvement may be explained by the nature of the data evaluated.

Measurement of the CMS data was against a baseline developed from prior efficiency and

cost reduction. Therefore, an increasing value signified a departure from the baseline, i.e., a

departure from the expected level of efficiency, which reflected senior leadership involvement

for this study. Overall, the regression model shows that leadership significantly impacts

postmerger performance, aligning with the PMI framework by Haspeslagh and Jemison

(1991). The model substantively supports the PMI framework by Haspeslagh and Jemison

(1991) on senior leadership's influence and the integration of resources on postmerger

outcomes. Haspeslagh and Jemison (1991) posited that leaders must be engaged in shaping

and guiding the integration process, ensuring that the requisite environment exists for a

smooth transfer of capabilities to derive value and achieve the planned objective of the M&A.

The results from this study support the theory on the impact of leadership on M&A outcomes.

Recommendations for Action

This study's findings can assist senior leaders and managers of hospitals in

understanding how to guide the postmerger process for better results effectively. The

results affirmed that senior leadership involvement in the PMI phase has a significant

relationship with postmerger performance. Health care industry leaders may benefit from

understanding the criticality of engagement in the postmerger phase of an M&A and not

only in the initial deal-making phase. Further research may be helpful to determine the

type of leadership and the scope of involvement that would be more beneficial in the

postmerger phase. The study also adds credence to the criticality of resource integration

to enhancing value creation from an M&A. To a lesser degree than senior leadership

involvement in PMI, IT integration could improve value creation. This insight would be

beneficial to senior and mid-level managers who involved in PMI activities. Though

industry practices may vary, this study's findings may find applicability in other business

sectors beyond health care as M&A activity is pervasive across industries despite the high

rate of failure to create value (Alaranta & Henningsson, 2008; Rebner & Yeganeh, 2019).

The criticality of senior leadership involvement and resource integration to M&A

outcomes suggests the need for senior business leaders to develop a roadmap for periodic

check-ins and engagement with mid-tier leaders who manage the PMI process. This plan

may ensure continued involvement and provide an opportunity for prompt course

correction if necessary. My goal is to communicate the findings of this study through

health care industry organizations and professional bodies. I would also seek

opportunities for sharing the insights gained from the study at appropriate conferences or

industry-related events.

Implications for Social Change

Hospitals are crucial to societal wellbeing. Apart from the extremely critical role

of caring for the sick and health care research, hospitals play a significant role in their

communities' economic wellbeing. Hospitals account for providing more than 16 million

jobs in the United States alone, with an economic impact of $3.0 trillion (AHA, 2018).

Therefore, providing leaders of such an essential part of the society with insight on how

better to achieve their objectives of value creation through mergers is vital and has

significant ramifications for social wellbeing. Current developments in health care have

further amplified the implications of this study for social change. The coronavirus disease

(COVID-19) has exacerbated the financial, patient care, and resource pressures on

hospitals and their leaders (Dauner, Perlman, & Dougherty, 2020). The findings of this

study may help equip health care leaders with the knowledge that will help to eliminate a

potential source of additional pressure. Assisting hospital leaders to understand the

relationship between IT integration, senior leadership involvement in merger integration,

and postmerger performance, may help them to achieve the desired efficiencies, cost

reduction, and transfer of competencies and knowledge that they desire from M&A. The

ultimate implication for society is better patient care and outcomes.

Skills and Competencies

The DBA program was a journey of intense learning and development for me.

Throughout the journey, I have acquired skills and competencies that will make me a

better practitioner and leader. My professional experience in health care IT and the

awareness of its role in patient care contributed to my decision to study M&A and the

role of leadership and health care IT in determining its outcome. Through the process of

literature review and analysis of secondary data, I learned more about M&A, the different

phases, and factors that are crucial to its success and impact the postmerger performance

of the newly formed organization. Sharing the insights garnered through this process may

be beneficial to health care leaders specifically and other business leaders as well across

other industries, with interest in M&A. My DBA portfolio, including my skills, and

competencies as a business leader, can be accessed through waldenu.optimalresume.com.

Relationship Between Information Technology Integration, Senior Leadership Involvement in Postmerger Integration, and Merger Performance

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