Difference in willingness of innovation adoption among innovation types in Dutch hospitals

(1)

Difference in willingness

of innovation adoption

among innovation types

in Dutch hospitals

(2)

(3)

Master Graduation Report

Burak Gediktas

Amsterdam, 1 July 2017 burak_gediktas@hotmail.com

MSc Entrepreneurship joint degree between: Universiteit van Amsterdam

Faculty of Economics and Business Vrije Universiteit Amsterdam Faculty of Economics and Business Administration

Supervisory team

Universiteit van Amsterdam Dr. Nazlihan Uğur

(4)

(5)

Acknowledgements

I am very grateful that I had a lot of people in my environment that helped me out during all the phases of my project.

First of all, I would like to thank Nazlihan Uğur, my supervisor, who has helped me throughout my project and always gave me the advice I needed. You have always reminded me of sticking to the academic perspectives, but also keeping in mind the practical perspectives while doing this graduation project.

I would also like to thank the heads of the medical departments of all hospitals that have participated in my project. Despite their busy schedules, they still managed to make time for me and participate in this research.

Besides my supervisory team and the participants, I would like to thank all my friends who helped me to stay focused on my project and finish it successfully. Last but definitely not least, I want to thank my parents and family for supporting and motivating me both within and outside of this graduation project.

Thank you, All of you.

(6)

Preface

Doing a graduation project feels like a last opportunity to ‘show what you’ve got’. The last project before obtaining the master’s degree should consist of a combination of the application of knowledge that has been gained during the courses, earlier experiences and exploration of new topics.

During my project I tried to incorporate knowledge that I have gained during the Master Entrepreneurship and experience I gained in the health care innovation sector during my Bachelor Science, Business and Innovation. Besides the fact that I chose a topic that I like, I also wanted my topic to be relevant for my future career. Innovation in health care is what inspires me. During this project I narrowed my interest in innovation down to the innovation adoption decision in hospitals.

Lastly I wanted to improve my skills in doing research more autonomously. I also wanted to gain more experience in a medical environment and how to reach out to specialists from various disciplines.

The copyright of this master thesis rests with the author. The author is solely responsible for the content of this thesis, including mistakes. The universities cannot be held liable for the content of the author’s thesis.

(7)

Abstract

The objective of this research was to explore the differences in willingness to adopt among product, process, position and paradigm innovations in Dutch hospitals. To further understand these differences, the research has focused on which innovation adoption criteria are important when deciding about the adoption of innovations, for every innovation type separately. To reach this objective, a quantitative methodology has been used, supported with a survey that has been sent to the heads of medical departments of all general hospitals in The Netherlands. With the survey, the willingness of adoption for the four innovation types has been measured. Also, the prioritization of innovation adoption criteria has been measured to further understand the adoption decision. The most important findings of this research were that paradigm innovations were least likely to be adopted and position innovations were most likely to be adopted. Investigating the innovation adoption criteria has showed that there is only a prioritization for process and paradigm innovations. Additionally, it has been found that for these two types, efficiency is the most important innovation adoption criterium and safety is the least important. While these findings are slightly missing the statistical power to be robust, they still offer new insights that have practical value. We can conclude that there is a difference among innovation types in terms of willingness to adopt them and that there is a prioritization of innovation adoption criteria when deciding about the adoption of an innovation. However, there is still more research needed on the dynamics in a hospital and on the influences, both from inside and outside the hospital, that affect the innovation adoption decision that cause these deviations in adoption.

(8)

Figures

FIGURE 1:THE INNOVATION TYPE MAPPING TOOL (ROWLEY ET AL.,2011) ... 17

FIGURE 2:CHARACTERISTICS OF INNOVATIONS: QUALITY OF CARE, COSTS, SAFETY, EFFICIENCY AND HEALTH OUTCOMES ARE BEING CONSIDERED DURING THE INNOVATION ADOPTION DECISION.(OMACHONU & EINSPRUCH,2010) ... 22

FIGURE 3:COMPOSITION OF THE HOSPITALS THAT ARE PART OF THE SAMPLE AND HAVE PARTICIPATED IN THE STUDY. ... 25

FIGURE 4:NAMES OF THE HOSPITALS THAT ARE PART OF THE SAMPLE.UMC ARE UNIVERSITY MEDICAL CENTRES.STZ ARE THE BIG HOSPITALS,OVA ARE THE MEDIUM HOSPITALS AND SAZ ARE THE SMALL HOSPITALS (DUTCH HOSPITAL DATA,2014). ... 26

FIGURE 5:SUMMARY OF THE DESCRIPTIVE ANALYSIS ... 33

FIGURE 6:RESULTS OF THE ONE-WAY ANOVA CONDUCTED ON THE WILLINGNESS TO ADOPT INNOVATION TYPES ... 34

FIGURE 7:THE RESULTS OF THE TUKEY TEST FOR WILLINGNESS TO ADOPT AMONG INNOVATION TYPE ... 35

FIGURE 8:THE MEANS OF THE RANKS THAT THE INNOVATION ADOPTION CRITERIA HAVE PER INNOVATION TYPE ON A SCALE FROM (1) LEAST IMPORTANT TO (5) MOST IMPORTANT ... 36

FIGURE 9:THE TEST STATISTICS OF THE FRIEDMAN TEST FOR EVERY INNOVATION TYPE ... 36

FIGURE 10:RANKING OF INNOVATION ADOPTION CRITERIA AMONG INNOVATION TYPES ... 37

FIGURE 11:RESULTS OF THE ONE-WAY ANOVA FOR PARADIGM INNOVATIONS ... 38

FIGURE 12:THE INTERPRETATION OF THE RANKING OF INNOVATION ADOPTION CRITERIA FOR PARADIGM INNOVATIONS BASED ON THE TUKEY TEST... 38

FIGURE 13:RESULTS OF THE ONE-WAY ANOVA FOR PROCESS INNOVATIONS ... 39

FIGURE 14:THE INTERPRETATION OF THE RANKING OF INNOVATION ADOPTION CRITERIA FOR PROCESS INNOVATIONS BASED ON THE TUKEY TEST ... 39

(10)

1. Introduction

1.1 Background

Innovations bring improvements to our lives, especially in this dynamic era of fast technological development. New technologies lead to new product and service innovations. There are industries in which these innovations are implemented very quickly, but in some industries, innovations do not reach the target group and fail. In general, we know that people and institutions do not like change because it brings uncertainty and difficulties (Cain & Mittman, 2002). These uncertainties tend to make people conservative and stick to known practices. Therefore, adopting innovations is something that is being done very cautiously. But how does this apply to the health care industry?

Across all disciplines, health care has become a very complex industry in the last decades (P E Plsek et al., 2001). More and more actors are getting involved and health care innovation is now a process that has significant barriers (Herzlinger, 2006). These barriers make the adoption of innovations in health care more difficult. The various stakeholders with a different agenda, financial challenges, hindering regulations and insurers that demand cost-effectiveness besides medical improvement are all influences that hinder the adoption of innovations (Lansisalmi, Kivimäki, Aalto, & Ruoranen, 2006). These influences kill or drive an innovation and play a role in whether the innovation ends up being used in hospitals and clinics or not. Innovations in health care have lifted the industry to a higher level of efficiency, efficacy and convenience (Chaudhry et al., 2006). But what makes some innovations end up in the clinical environment while some are not even getting close?

Innovations bring various improvements to health care. However, not every innovation that brings an improvement is adopted by hospitals. There are several studies done on determinants that influence the adoption of innovations in hospitals (Fleuren, Wiefferink, & Paulussen, 2004). Also, models have been proposed to predict whether an innovation will be easily adopted or not. Although these models can provide some predictions about the adoption, the generalizability suffers due to the existence of various innovation types. How do the different innovation types affect the adoption of innovations? We do know little to what extent these innovation types influence the decision whether an innovation will be adopted or not.

(11)

However, we do know that the more change an innovation brings, the more uncertainty comes with it (Cain & Mittman, 2002). Researchers have suggested that uncertainty negatively affects the innovation adoption decision (Greenhalgh, Robert, Macfarlane, Bate, & Kyriakidou, 2004; A. D. Meyer & Goes, 1988; M. Meyer, Johnson, & Ethington, 1997). Also, the rising pressure of governments to reduce the costs plays an important role in the adoption of innovations (Lansisalmi et al., 2006). Besides cost-effectiveness, efficiency, quality, safety and health outcomes are important factors that influence the innovation adoption decision (Greenhalgh et al., 2004; Omachonu & Einspruch, 2010).

The purpose of this study is to examine whether there is a difference in willingness to adopt an innovation among different innovation in Dutch hospitals. To further understand these differences, we want to look at the prioritization of innovation adoption criteria when deciding about the adoption of an innovation. This study provides insights in the different innovation types, their mutual differences and if hospitals are more likely to adopt one type than the other. This knowledge could particularly help medical innovation companies to fine-tune their innovations to the criteria that hospitals find important and expect to see in an innovation. Also, knowing with criteria are found more important during the decision-making for the adoption of an innovation could offer an advantage when developing medical innovations.

The motivation of the study lies in generating new knowledge in the field of innovation adoption that can help us to better understand the phenomenon. We want to get to know more about the relationship between the type of an innovation and the willingness of adoption.

In the second chapter the literature on various innovation types will be discussed. The developments of innovation type models through the years will be examined. Then, the models that are introduced by various researchers will be compared with each other. After the models are discussed, the literature on innovation adoption in health care will be briefly looked into.

In the third chapter the research design, sample, methods of data collection and analysis will be discussed. The reason for choosing the methods will be explained. The survey that has been conducted and the sample that has been used will be discussed.

In the fourth chapter the results of the study will be discussed. The results will be based on the research questions that are phrased. The chapter will start with the results of the survey and will

(12)

show what kind of relations can be observed between the innovation types and the innovation adoption and the prioritization of innovation adoption criteria.

The fifth chapter will include the discussion. In this chapter, the position of this research in the current literature will be discussed and we will look into how it relates to the innovation types and innovation adoption theory. Also, recommendations for further research will be made.

The sixth chapter will be the conclusion of this study. In this chapter the results of the survey will be analysed and conclusions will be drawn upon. The conclusion and hypothesis will be compared with each other and similarities and differences will be discussed.

1.2 Research question

To obtain meaningful results during this study, it is crucial to phrase research questions that have clear borders and will offer guidance in conducting the study.

To compare the different innovation types and their willingness of adoption, willingness to adopt an innovation will be studied for every innovation type. Elaborating on the purpose of this study, the following research question can be phrased:

By answering the above research question, it will be measured whether there is a difference in willingness to adopt an innovation among the different innovation types. Therefore we use the ‘innovation type’ and the ‘willingness to adopt an innovation’ when phrasing this question. With the answer to this research question we will be able to see the relative difference in willingness to adopt an innovation between the various innovation types. For instance, we could be able to say something about the willingness to adopt a product innovation versus a process innovation and if there is a difference between them.

To further describe the willingness to adopt various innovation types, we will look into the importance of various innovation adoption criteria in the decision of innovation adoption. We want to know the prioritization of innovation adoption criteria when considering the adoption of an innovation. Therefore, the following sub-question has been phrased:

What is the difference in willingness to adopt an innovation among innovation types?

(13)

By answering this research question, we might get to know more about which criteria are found more important during the innovation adoption decision. For instance, we might get to know if the costs of an innovation are more important than the quality improvement that it brings to the hospital.

Because we also want to know if there is a difference in prioritization of innovation adoption criteria among innovation types, another sub-question has been phrased to answer that matter. We want to understand if there is a difference among innovation types in which criteria play a more important role in the decision to adopt an innovation. Elaborating on this goal, the following sub-question has been formulated:

With this sub-question we want to measure whether there is a difference in the prioritization of innovation adoption criteria among innovation types. With this sub-question we want to measure whether some innovation adoption criteria are found more important when deciding whether to adopt an innovation or not. For instance, we might get to know if cost-effectiveness is more important than safety when adopting a new product innovation but efficiency is more important when adopting a process innovation. By answering this question we might be able to say something about the difference in priorities when adopting an innovation among the different innovation types.

What is the difference in the prioritization of innovation adoption criteria during the adoption decision among innovation types?

(14)

2. Literature review

2.1 Innovation in health care

In order to discuss how innovation types could affect the innovation adoption decision, it is important to first answer the question ‘What is innovation?’

Innovation can be defined as “the intentional introduction and application within a role, group, or organization, of ideas, processes, products or procedures, new to the relevant unit of adoption, designed to significantly benefit the individual, the group, or wider society” (West, 1990 p. 9). This definition is widely accepted in the field because it withholds the most important characteristics of innovation: (1) novelty (2) a benefit and (3) a component of application (Lansisalmi et al., 2006). Only the combination of these three characteristics can be called an innovation. An invention, for example, can also offer novelty and a benefit but cannot be called an innovation due to the lack of a component of application (Roberts, 1988).

Looking at innovation in health care we can define a much more discipline-specific definition. Innovation in health care can be defined as the introduction of a new concept, idea, service, process, or product with the goal to improve treatment, diagnosis, education, outreach, prevention and research, and with the underlying objective of improving quality, safety, outcomes, efficiency and costs (Omachonu & Einspruch, 2010). Innovations in health care aim to improve life expectancy, quality of life, diagnostic and treatment options, as well as the efficiency and cost effectiveness of the healthcare system (Omachonu & Einspruch, 2010). Innovation has lifted the health care system to higher levels of efficiency, efficacy and convenience (Chaudhry et al., 2006).

There are different aspects of innovations and perspectives on how to look at them. Because this study focuses on innovation types and their differences in innovation adoption, we will begin with discussing the different types of innovations and how they are defined in the literature. Then we will look at the innovation adoption criteria that are considered during the adoption decision of innovations in health care.

2.2 Innovation types

To look into the difference in willingness to adopt an innovation among innovation types, it is important to identify different types of innovation and discuss their mutual differences.

2.2.1 Early models

(15)

can be categorized on various characteristics. It is possible to observe a big variety in terminology that is being used for defining different types of innovations. Therefore it is not easy to compare innovation type studies because the terms that are being used are not similar. In early studies on innovation, binary models were popular under researchers (Rowley, Baregheh, & Sambrook, 2011). These models suggested that innovations consisted of two dimensions: product/process, administrative/technical or radical/incremental (Bantel & Jackson, 1989; Daft, 1978; Damanpour, 1991). Quickly it became clear that defining innovations in two dimensions was not capturing the bigger picture and there was need for more advanced models (Rowley et al., 2011). Cooper integrated the dimensions that were introduced before and designed a multi-dimensional model of innovation types (Cooper, 1998). In the early 2000’s researchers agreed that innovation could not be defined with simple models that consist of a couple of attributes (Rowley et al., 2011). The models that were suggested earlier became outdated when integrative and advanced frameworks were introduced by researchers like Oke et al (2007) and Bessant & Tidd (2007). With these models, researchers tried to identify and embed all kinds of innovations in their models. They did this by looking at the unique characteristics of innovations and tried to set clear borders between the various innovation types.

After the initial attempts of researchers to define innovation with several attributes turned out to be insufficient to cover all kinds of innovation, there were new studies done on identifying innovation types (Rowley et al., 2011). There have been suggestions of innovation frameworks which categorize innovations in different groups. Although most of them are trying to include all types of innovations in their models, none of them comes up with the same model . However, we can see some aspects that keep coming back in every model. For example, product and process innovations can be recognized in most models (Bessant & Tidd, 2007; Hovgaard & Hansen, 2004; Knight, 1967; Oke et al., 2007; Trott, 2008).

2.2.2 Universal model

From the variety in the models it becomes clear that it is a complex task to come up with a universal model that covers all models and includes all types of innovations that are described by all researchers. There has been a heavy discussion on the categorization of innovations to make sure that innovation research and practice gets a stable foundation (Baregheh, Rowley, & Hemsworth, 2016). Bessant and Tidd have used their 4 P’s to define four categories of innovation types (2007): product, process, position and paradigm innovations. The product and

(16)

process innovations are known, but the position and paradigm innovations are unique terms in the innovation type literature. With position innovation, the market that is being targeted with a product or service, the position, is changed (Bessant & Tidd, 2007). Paradigm innovations are introduced as innovations that affect the mindset of people (Bessant & Tidd, 2007). According to Bessant & Tidd, changing the way people think about commercial airflight was a paradigm innovation, especially low-cost airlines have made it possible for almost everyone to fly (Bessant & Tidd, 2007). The term ‘paradigm innovation’ can be compared with the organizational innovation suggested by Knight (1967), organizational innovation (Johannessen, Olsen, & Lumpkin, 2001; Trott, 2008) and structural innovations suggested by Varkey (2008). All the terms that are used by different researchers are meant to define the same phenomenon: changing the perception of what is ‘normal’.

While it is possible to observe multiple frameworks that consist of unique innovation type terms, when the definitions are examined, they all have some overlap. Another similarity that has to be emphasized is the recurrence of product innovations. Most researchers seem to agree with each other that a product innovation is a distinct group and has to be mentioned separately (Rowley et al., 2011). When looking at the different models, it can be observed that none of the researchers has the same thought about the terminologies of innovation types. Although they sometimes intend to describe the same phenomena, as discussed earlier this chapter, the terms are not named the same.

However, Rowley et al. have developed an innovation type mapping tool that makes it possible to visualize all innovation types into one single figure (2011). The innovation type mapping tool, as shown in Figure 1, takes the 4 innovation types suggested by Bessant & Tidd as a framework. Building on this framework Rowley et al manage to fit every innovation type that is described in the literature into one of the 4 innovation types proposed by Bessant & Tidd.

(17)

Figure 1: The innovation type mapping tool (Rowley et al., 2011)

As seen in Figure 1, the innovation types that are proposed by different researchers fit into the 4 innovation types suggested by Bessant & Tidd (2007). On the one hand, process innovation has the most sub-types of innovation. On the other hand, paradigm innovation does not have a single sub-type. The lack of sub-types can be explained by the fact that paradigm innovation is the most recently introduced innovation type in the literature. Research on paradigm innovations has been at a minimum level and therefore no sub-types have been proposed in the literature.

2.2.3 Innovation type characteristics

The four universal innovation types that are discussed in the universal model do not have clear borders. For example, sometimes it is possible to place an innovation in multiple categories (Francis & Bessant, 2005). However, the four main types of innovation fundamentally differ from each other. These characteristics and mutual differences will be discussed in this section.

(18)

2.2.3.1 Product innovation

A product innovation has to do with the final product that the customers buy: goods and services that companies offer (Varkey et al., 2008). Small adjustments or improvements to the current goods and services are incremental innovations. Most product innovations are incremental changes (Tushman & Nadler, 1986). These small changes are mostly introduced to improve quality in health care (Herzlinger, 2006). In the case of an incremental product innovation, it could be an adjustment, improvement or change in the goods or services that are currently offered. Radical product innovations consist of newly introduced goods or services in the market.

As shown in Figure 1, product innovations can be divided into 4 categories: product, service, hybrid and technical innovations. Product innovations are the implementation of new products or adjustments to the current ones (Varkey et al., 2008). Service innovations are the implementation of new services or adjustments to current services. There is also an innovation category in between them: hybrid innovations. Hybrid innovations consist of products that are coupled with services (Rowley et al., 2011). For example, a faster computer is a product innovation, offering new maintenance services coupled to that computer is a service innovation. A hybrid innovation would include both of them and would combine the product and the service into one innovation.

2.2.3.2 Process innovation

A process innovation has to do with the production or delivery process of the goods and services that are delivered. The customers do not directly pay for the process but it is necessary to deliver a product or service and to manage the relationship with the stakeholders (Omachonu & Einspruch, 2010; Varkey et al., 2008). A process innovation brings a change to the production or delivery of the product or service and increases the delivered value for one or more stakeholders (Varkey et al., 2008). While value for one stakeholder could mean a pain for the other, the most important value in health care is the health outcome delivered per euro spent (Porter, 2010). Values like accessibility, profitability, cost containment and patient satisfaction could be delivered by a process innovation. Process innovation is therefore important to improve internal capabilities (Johne & Davies, 2000) and conserve the quality that is delivered in hospitals (Johne, 1999).

Process innovations can be divided in 6 distinct categories: production, administrative, organisational structure, people, organisational and management innovations. For these

(19)

categories, two groups can be formed: technical and organisational innovations (Rowley et al., 2011). Process innovations can bring improvements to the administrative or organisational operations within a hospital. Process innovations could also bring improvements to the technical operations of the hospital. For example, an organisational process innovation could be a new patient waiting system. A technical process innovation could be a new patient data monitoring system.

2.2.3.3 Position innovation

Position innovation can be defined as the exploitation of new customer bases and markets with existing products, services or processes (Bessant & Tidd, 2007). A position innovation changes the customer's understanding or view of the products (Kim & Mauborgne, 1999). Positional innovation can also create markets that did not exist before or alter the characteristics of existing markets (Francis & Bessant, 2005). For example, baby shampoo has the characteristics that they don’t hurt the baby’s eyes. However, there could be more markets that demand shampoo that does not hurt their eyes. Elderly people that cannot wash themselves could be an example for that. Introducing the baby shampoo to elderly people can be seen as a position innovation because the position on the market of an existing product is changed to exploit a new market.

Applying position innovation to health care is a somewhat more difficult task. Because there are many regulations for innovations in health care (Herzlinger, 2006), it seems almost impossible to introduce a product, service or process in health care that has not been approved by regulatory instances. This regulatory mechanism for innovations in health care makes position innovations only possible from medical market to another medical market. For example, implementing a treatment that is being used in another department of the hospital could be seen as a position innovation, because a new market is served. On the other hand, innovations from outside the medical environment would need to pass strict regulatory tests before implementation in health care is allowed.

2.2.3.4 Paradigm innovation

By the nature of paradigm innovations in health care, they tend to be radical because they bring major changes to conventional methods of health care delivery (Varkey et al., 2008). Health care organizations derive their legitimacy, mostly from having care structures that are seen as appropriate by the stakeholders (Arndt & Bigelow, 2000). This perception of appropriate structures in health care is susceptible to change and transforms through the years by reacting to environmental and societal stimuli (Arndt & Bigelow, 2000; Starr, 1984; Stevens, 1986).

(20)

Therefore it is important for health care institutions to implement paradigm innovations to stay in line with the perception of appropriate health care delivery and conserve their legitimacy (Arndt & Bigelow, 2000).

An example of a of paradigm innovations in health care could be a change in the way hospitals operate: more robots instead of humans. Another example could be the role that a patient gets in the decision-making of treatments: the development of the internet has made patients more aware of diseases, their underlying mechanisms and their treatments (Varkey et al., 2008). Allowing the patients to participate in the decision-making of which treatments to use, is a paradigm innovation that could be implemented in our modern society. This would not be possible a couple of decades ago because the societal and technical environments were not ready yet (Stevens, 1986). This shows that paradigm innovations, like all innovations, depend on what is technically possible, but also on what is perceived as an appropriate care structure (Arndt & Bigelow, 2000).

2.3 Innovation adoption in hospitals

To understand the influences of innovation types on the adoption decision, various innovation types have been discussed in the previous section. This section will look into the literature of the innovation adoption decision and which criteria influence this decision.

Innovation is undoubtedly one of the factors that contributes to quality improvement in health care (Varkey et al., 2008). But innovation has also a big impact on the rising health care costs (Bodenheimer, 2005). Increasing demands of cost-effectiveness on innovations has resulted in a limited number of innovations that can be implemented in hospitals (Emanuel & Emanuel, 1996). However, cost-effectiveness is only one of the requirements set by health care regulating instances (Herzlinger, 2006). These regulating instances are influencing the behaviour of decision makers in hospitals, for instance, whether or not to adopt the newest imaging technology or not (Lehoux, Williams-Jones, Miller, Urbach, & Tailliez, 2008). The next section will be about these different innovation adoption criteria that are being considered when deciding about the adoption of an innovation.

2.3.1 Innovation adoption criteria

When deciding whether to adopt an innovation or not, there are several factors that are being considered in this decision process. The literature on innovation adoption criteria is very broad and consists of innovation adoption criteria for various disciplines. A meta-analysis of

(21)

innovation adoption predictors shows that the innovation adoption criteria differ per discipline but are based on similar principles (Tornatzky & Klein, 1982). Tornnatzky & Klein suggest that innovations are more easily adopted if they are more similar to current practices, offer a relative advantage to current practices, easy to try, easy to use, low-cost, profitable, socially acceptable and their advantage is easy to observe (1982). These are very general predictors and could be used for every discipline. However, some disciplines need more specific innovation adoption criteria because the general innovation adoption criteria do not cover every important aspect for the innovations in that discipline. For example, IT innovations can have slightly different adoption criteria because it is a new discipline with a massive amount of sub-disciplines (Hollenstein, 2004). Also, the innovation discipline is not the only determinant that affects the need for varying innovation adoption criteria. For example, the innovation adoption criteria of IT innovations in governments differ from IT innovation adoption criteria in profit-based companies (Kamal, 2013). Therefore, it is important to look at the specific discipline and environment in which innovations take place and test them with the corresponding innovation adoption criteria.

Because the focus of this study is innovation in hospitals, we will further look into the innovation adoption criteria in health care organizations. Innovation in health care is a complex and multidimensional phenomenon (Paul E Plsek, 2003). Fleuren et al. suggest 4 categories that affect the adoption of an innovation:

• The socio-political context

• The organisation and its characteristics that make or break the innovative environment • The persons that are adopting the innovation

• The innovation itself and its characteristics

The socio-political context resembles the characteristics of the patients and the effect of regulations and legislation (Varkey et al., 2008). The organization and its characteristics can be seen as the hospital and the decision-making process in a hospital that innovations go through when they are considered for adoption. The adopting persons are the health care professionals with their knowledge, skills and their own perspective on innovations and what should be adopted or not (Varkey et al., 2008). The innovation itself includes the characteristics of the innovation and the advantages that it offers to the hospital. Looking at these 4 categories, we can see that the first 3 categories do not have anything to do with the innovation itself. Therefore, we can state that the innovation itself is not the only important factor that determines whether an innovation will be adopted or not.

(22)

Because this study focuses on the characteristics of innovations, we will further discuss the fourth category that affects the adoption of innovations: characteristics of innovations. As discussed earlier in this chapter, there are many disciplines in which innovations have different characteristics that are of importance. Tornatzky and Klein suggest that there are 10 general innovation criteria that are important for every discipline. These are: compatibility, relative advantage, complexity, costs, communicability, divisibility, profitability, social approval,

trialability, and observability (Tornatzky & Klein, 1982). These innovation criteria are broadly stated and will not be useful for health care innovations without interpreting these criteria in a different way. For example, relative advantage has to be interpreted in a different way for health care professionals and in a different way for car manufacturers. For health care professionals the relative advantage of an innovation could mean better health outcomes for the patients. A relative advantage for a car manufacturer could mean a more fuel-efficient engine. Therefore, it is important to look at discipline-specific innovation criteria.

Omachonu and Einspruch have proposed 5 criteria that are being considered by health care professionals when deciding whether or not to adopt an innovation. These characteristics are: efficiency, costs, quality of care, health outcomes and safety, also showed in Figure 2. In the literature there are examples of criteria that describe the consequences of innovations. Fleuren et al. have designed a framework of categories that affect the adoption of innovations (2004). But Omachonu and Einspruch were the only researchers that suggested health care-specific innovation adoption criteria that are directly related with the characteristics of the innovation itself. The criteria are showed in Figure 2.

Figure 2: Characteristics of innovations: quality of care, costs, safety, efficiency and health outcomes are being considered during the innovation adoption decision.

(23)

3. Research method

3.1 Research design

To obtain meaningful results, it is crucial that the research design is in line with the nature of the research questions. Due to the fact that the research questions are phrased in a descriptive matter, this study requires the use of a descriptive research design. The study is conducted with quantitative research methodologies.

The purpose of this study is to explore the difference in willingness to adopt an innovation among innovation types. In order to describe the differences in willingness to adopt an innovation, I decided to conduct a descriptive study with quantitative methodologies. Describing known phenomena often illuminates knowledge that we might not otherwise notice or even encounter (Kothari, 2004). Descriptive research designs are often used to describe associations between phenomena (Kothari, 2004). By using a descriptive research design in this study, it is determined whether the type of an innovation is associated with the willingness to adopt innovations.

The research domain of this study consists of the general hospitals in The Netherlands. This domain is specifically chosen because the innovation environment in hospitals has interesting characteristics that differ from most industries. There are regulatory instances that influence the innovation environment and various stakeholders that have different agendas and therefore could have different views on innovation adoption (Herzlinger, 2006).

To describe whether the willingness to adopt an innovation is associated with the innovation type I wanted to research the view of heads of medical departments. To provide insights on the view of the heads of the hospitals’ medical departments I have looked into the willingness of them to adopt innovations among various innovation types. This has been done by conducting a survey about the willingness to adopt different innovation types.

To further understand how the adoption decision is taken by the heads of medical departments the importance of various innovation adoption criteria have been measured for every innovation type. By measuring the importance of these criteria for every innovation type, we can say something about the considerations hospitals have to make when deciding about the adoption of an innovation. This might propose new insights about how hospitals decide about the adoption of innovations.

(24)

The research strategy has been an online survey. With the online survey strategy I collected data and analyzed them quantitatively with descriptive and inferential statistics. An online survey has some advantages compared to paper questionnaires, especially the costs, speed, appearance and user-friendliness (Lumsden, 2007). The survey has been designed on the website of Qualtrics and has also been distributed via the website of Qualtrics. The survey has been purposely designed to be short and narrow, with an average time of filling of approximately five minutes, to obtain a dropout rate as low as possible (Appendix A). The average filling time is automatically calculated by Qualtrics.

3.2 Sample

This section describes the sample that has been used in the survey.

In The Netherlands there are a total of 134 health institutions that are qualified as hospitals (Dutch Hospital Data, 2014). Within these 134 hospitals there are 20 revalidation clinics and 23 categorical hospitals. These only offer health care services for very specific groups and are not relevant for this study because the aim is to sketch a view of the general hospitals in The Netherlands. There are 85 general hospitals. Within the 85 general hospitals there are 8 university medical centres that function as a general hospital. These will be part of the sample because they offer health care services that are similar to the general hospitals nationwide. From the non-university hospitals, 36 are small, 17 are medium and 24 are big. There will be no difference made between the different hospitals in terms of data collection. They will all be treated equally because they all have the same decision-making mechanism for innovation adoption: a head of department that takes the final decision. The head of departments of these hospitals are the population of this study. Because the population is small, the whole population will be studied as a sample. The reason that the heads of departments are chosen is because the final decision to adopt an innovation is made by the heads of medical departments.

(25)

Total hospitals 85 Hospitals participated 21 Of which: Small hospitals 36 8 Medium hospitals 17 6 Big hospitals 24 4 University medical centres 8 3

(26)

Figure 4: Names of the hospitals that are part of the sample. UMC are university medical centres. STZ are the big hospitals, OVA are the medium hospitals and SAZ are the small hospitals (Dutch Hospital Data, 2014).

(27)

3.3 Data collection

In this section, the methods of data collection are discussed.

3.3.1 Survey

The survey is conducted to measure whether the willingness to adopt an innovation differed among innovation types and if there is a difference in the prioritization of innovation adoption criteria among innovation types.

All hospitals that were part of the sample have been mailed a link to the survey and are asked if they could distribute the survey internally to all heads of the medical departments. These heads of departments decide whether an innovation is adopted in their department or not. A total of 21 hospitals have participated in the survey. However, from the hospitals that received an e-mail, only 6 hospitals responded that they wanted to participate in the study. 13 hospitals have responded that they do not want to participate in the study. Also, 4 hospitals were not operational anymore because they closed or fused with another hospital. 64 hospitals did not respond via e-mail whether they would participate or not. However, some participants were from the hospitals that did not respond. There were also 14 participants that did not finish the survey, those were discarded

The participants were motivated in the e-mail by telling that insights of this study could contribute to the improvement of health care in general and also that they would help me out with graduating. Still, only 21 heads of departments responded to the survey. It is known that accessibility of research in health care institutions is relatively low. It requires strategic planning and also pure luck (Bryman, 2016; Cunliffe & Alcadipani, 2016). All hospitals have received 3 e-mails but still only 6 of them responded that they wanted to participate. The fact that the sample consisted of the heads of departments of hospitals made it even more difficult to reach them. They are mostly busy and have tight schedules. Also, it was regularly seen in the rejection e-mails that the hospitals do not participate in surveys/interviews of students anymore because they get a lot of requests and that it takes too much time.

3.3.1.1 Willingness to adopt among innovation types

To measure whether the willingness to adopt innovations differed among innovation types, the participants were asked to rate how likely they would adopt an innovation on a 10-point Likert scale (Norman, 2010). The innovations that were rated are based on the 4 innovation types

(28)

proposed by Bessant & Tidd (2007), suggested in the universal innovation type model by Rowley et al (2011). A total of 20 innovations have been rated on the willingness to adopt them, 5 from each innovation type. These innovation types are product, process, position and paradigm innovations. These innovation types are chosen because they include every innovation type that is described in the literature and therefore offer a complete framework for innovation types (Rowley et al., 2011). The goal of this study is to offer a complete overview of the willingness to adopt innovation types, therefore no innovation type could be missed out. The reason to include 5 innovations from each type was because it is desirable to have as much innovations per type as possible to make the data more reliable, without making the survey too long. Long surveys tend to drastically influence the response rate negatively (Jepson, Asch, Hershey, & Ubel, 2005). The aim was therefore to have an estimated average filling time of 5 minutes calculated by Qualtrics.

3.3.1.3 Prioritization of innovation adoption criteria among innovation types

To measure whether there is a difference in the prioritization of innovation adoption criteria between innovation types, participants were asked to rate the importance of innovation adoption criteria for every innovation type separately. The innovations were again based on the universal model suggested by Bessant and Tidd (2007). One innovation was used for product, process, position and paradigm innovations each. The innovation adoption criteria that were asked to rate are proposed by Greenhalgh et al (2004). The criteria are: efficiency, costs, safety, health outcomes and quality of care. These adoption criteria were chosen because Greenhalgh et al. have found these criteria to be applicable in research on innovations in hospitals. Also, other adoption criteria that were proposed were not specifically designed for health care innovations and would therefore unsuitable for this research.

The participants were asked per innovation type to rate which innovation adoption criteria they found most important if they had to decide whether to adopt it. The participants were asked to rate the criteria from (1) most important to (5) least important. A ranking scale was chosen because the difference between innovation adoption criteria is relative. When measuring relative differences in importance between phenomena it is suggested that a ranking scale will give the most useful results (Saaty, 1993).

(29)

3.3.2 Operationalization

3.3.2.1 Willingness to adopt an innovation

To make the willingness to adopt an innovation quantifiable, the concept of willingness to adopt an innovation has been operationalized with a score for how likely participants would adopt an innovation. Participants were asked to answer how likely they would be adopting an innovation on a 10-point Likert scale. This Likert-scale functioned to measure the relative difference among the willingness to adopt an innovation among the innovation types. The variable that has been created is the ‘score of likeliness to adopt’, This operationalization made it possible to compare the scores between innovation types and say something about the relative difference in willingness to adopt among innovation types.

3.3.2.2 Prioritization of innovation adoption criteria

To make the prioritization of innovation adoption criteria quantifiable, the concept has been operationalized with a ranking for every innovation adoption criteria. Participants were asked to give a ranking to every innovation adoption criterium based on their importance during the adoption decision. Therefore, the variable that has been created for the prioritization of innovation adoption criteria is the ‘rank of innovation adoption criteria’. This ranking is also relative and does not offer any possibilities to observe absolute differences among innovation adoption criteria. With this operationalization we could compare the ranks of innovation adoption criteria and look whether there is an observable prioritization.

3.4 Data analysis

To make sense out of the raw data, statistical analyses have been done. In this section it is discussed how and why these methods are used.

In this research, two different kinds of data are analyzed. The data about the willingness to adopt different innovation types is Likert-scale data, and the data about the prioritization of innovation adoption criteria among innovation types is ranked-scale data.

3.3.1 Willingness to adopt innovation types

The data about the willingness to adopt innovation types consisted of scores between 1 and 10 for 20 innovations, 5 from each innovation type. The scores for every innovation that were from the same type were averaged. This gave a mean of ‘willingness to adopt’ for every innovation

(30)

type. A one-way ANOVA has been conducted to measure whether these means differed from each other. The null hypothesis of the one-way ANOVA is that the means of the willingness for every innovation type are equal. Rejecting this null-hypothesis would mean that at least one mean differs from the others (Christensen, 1987).

After rejecting the null-hypothesis, a Tukey test has been done to compare which means differed from each other. The Tukey test showed which means of willingness to adopt innovation types differed from each other at the 0,05 level. Means of willingness’ to adopt innovation types that differ from others at the 0,05 level are statistically different and can be seen as more/less important than other innovation types.

3.3.2 Prioritization of innovation adoption criteria

The data from the part of the survey that functioned to measure the importance of adoption criteria per innovation type was exported from Qualtrics to Excel. To reverse the scale of the data and recode it so that 1 corresponds with least important and 5 with most important, all data points were subtracted from 6. For example, the rating of 5 given by participants would mean that a criterium is the least important, subtracting 5 from 6 gives 1. That way, all data points were transformed to a new scale between 1 and 5.

After recoding the data, it was imported into SPSS. The statistical importance of the data has been tested with a non-parametrical procedure of the Friedman test. The Friedman test resulted in average ranks of the innovation adoption criteria. These average ranks made it possible to observe whether there is a prioritization of innovation adoption criteria. To assess whether these differences were statistically strong enough, the X2 and p-values of the Friedman test were examined. For calculating the critical value of X2_{, the methods of Johnson, Kotz and}

Balakrishnan were used (1994). For the p-value, a significance level of 0,05 has been used. With the critical value of X2 for every innovation type, it is separately assessed for which innovation type there is a prioritization of innovation adoption criteria during the adoption decision.

3.3.3 Difference in prioritization of adoption criteria among innovation types

After the prioritization of innovation adoption criteria for every innovation type has been mapped, we want to know whether there is a difference in prioritization among innovation

(31)

types. To find a statistical difference in prioritization among innovation types, one-way ANOVA procedures were conducted for every innovation type. The one-way ANOVA resulted in a X2 and p-value for every innovation type that showed how statistically strong the means of the rankings of innovation adoption criteria are.

Next, we wanted to know if there are differences between the prioritization of innovation adoption criteria among innovation types. To assess whether there were differences, we conducted Tukey tests for every innovation type to map which innovation adoption criteria were statistically more or less important from each other at the 0,05 level. With the results of this analysis we could, for example, say whether costs are more important for process innovations than for product innovations. As stated before, these are relative differences and do not reflect the absolute differences between the importance of innovation adoption criteria.

3.5 Hypothesis

Before doing the research and collecting data, hypotheses have been phrased by studying the literature and anticipating on the results.

There are different types of innovations that are being introduced to hospitals. In the innovation literature there are a couple of innovation types defined. Although these innovation types have different characteristics, it is not expected that hospitals will be less likely to adopt one innovation type compared to the other. Innovations are not defined by their type but by other characteristics that make every innovation unique, even if they are from the same type. Therefore it is not expected that there will be a difference in the willingness to adopt an innovation among the innovation types. For the main research question the following hypothesis has been phrased:

H1: There is no difference in the willingness to adopt an innovation among the different innovation types.

There are also various innovation adoption criteria that are being considered when deciding whether or not to adopt an innovation. While there are multiple stakeholders that exert an influence on the innovation adoption decision, the final decision is made by the heads of medical departments. They take into consideration the various innovation adoption criteria like safety, efficiency and costs to come to a final decision. An innovation adoption decision that is

(32)

made by heads of medical departments is taken based on the innovation adoption policy of the hospital and their personal opinion. By the nature of health care and the strict safety regulations, it is expected that safety is the most important innovation adoption criterium. Also, due to the rising pressure on cost-effectiveness of hospitals, it is expected that costs will be the second most important innovation criterium during the adoption decision. For the other innovation adoption criteria, it is not expected that there is a general prioritization because it depends on the hospital’s policy and the opinion of the health professionals if they find efficiency more important than the quality of care. Therefore, the hypotheses phrased for the importance of innovation adoption criteria are:

H2: The safety of an innovation is the most important innovation adoption criterium. H3: The cost of an innovation is the second most important innovation adoption criterium. H4: There is no prioritization among other innovation types besides safety and costs.

After we know whether there is a prioritization of innovation adoption criteria when making the adoption decision, we want to know whether this prioritization differs among innovation types. Because hospitals and heads of departments do not look at innovations as part of an innovation type, but as unique innovations with their own characteristics, we do not expect that there will be a difference in prioritization among innovation types. Elaborating on this expectation, the following hypothesis has been phrased:

H5: There is no difference in the prioritization of innovation adoption criteria among the different innovation types during the innovation adoption decision.

(33)

4. Findings

4.1 Empirical analysis & Findings

In this section, the results of the survey and the empirical analysis are discussed.

Willingness of adoption

Mean Std Dev Min Max N

Product innovations 7,68 1,27 4,80 10,00 21 Process innovations 7,66 1,05 6,20 10,00 21 Position innovations 8,21 0,98 4,80 9,40 21 Paradigm innovations 5,59 2,20 2,20 9,80 21

Figure 5: Summary of the descriptive analysis

The results consist of 3 parts. In the first part, the relative differences in willingness to adopt innovations between innovation types have been measured. It has been found that the relative willingness to adopt innovations for product (x_{̅ =7,68 σ=1,27), process (x̅=7,66 σ=1,05) and} position (x_{̅ =8,21 σ=0,98) innovations are close to each other. However, the willingness to adopt} paradigm innovations is lower than the other innovation types (x_{̅ =5,59 σ=2,20). In the second} part, it has been measured whether there is a prioritization of innovation adoption criteria during the innovation adoption decision. It has been found that there is a prioritization of innovation adoption criteria for process (X2₌_{29,57, p<0,001)}_{and paradigm innovations (X}2_=11,79

p=0,019). With the third part, it has been measured whether there is a difference in the prioritization of innovation adoption criteria among innovation types. From the analysis of process and paradigm innovations we could observe that efficiency is found the most important innovation adoption criteria and safety is the least important. However, for the other innovation adoption criteria we could not observe whether there is a difference in prioritization among the innovation types.

Note: The data that has been analyzed originates from a sample with n=21, thereby we could not satisfy the assumption of normality. Therefore the results of this study cannot be presented as ‘statistically significant’. However, it is expected that the results have practical value and may provide insights for further research on the differences in the adoption of innovation types.

(34)

4.1.1 Willingness to adopt innovation types

4.1.1.1 One-way ANOVA results

In order to identify differences in the willingness to adopt among the innovation types, a way ANOVA followed by a post-hoc test using Tukey procedures was conducted. This one-way ANOVA was conducted to compare the willingness to adopt an innovation for product, process, position and paradigm innovations. Figure 6 shows the results of the one-way ANOVA for the four innovation types.

Sum of Squares df Mean Square F Sig

Between innovation types

84,371 3 28,124 13,225 <0,001

Within innovation types 170,126 80 2,127

Total 254,497 83

Figure 6: Results of the one-way ANOVA conducted on the willingness to adopt innovation types

There was an observable effect of the innovation type on the willingness of adoption at the p<0,05 level for the four innovation types [F(3,80) = 13,23, p < 0,001]. To assess which innovation types differ from each other, a Tukey test has been done. Figure 7 shows the results of the Tukey test. The Tukey test has showed that the willingness to adopt paradigm innovations is lower than for product, process and position innovations. However, there is no difference among the willingness of adoption among product, process and position innovations.

The hypothesis stated before was:

H1: There is no difference in the willingness to adopt an innovation among the different innovation types.

We can reject this hypothesis because the willingness to adopt paradigm innovations is lower than for product, process and position innovations. The rejection is strong with a p-value lower than ,001. However, because the hypothesis can only be rejected for paradigm innovations, it makes the practical significance less strong.

(35)

Innovation type (I) Innovation type (J) Mean difference (I-J) Standard error Sig Product Process ,01905 ,45003 1,000 Position -,53333 ,45003 ,638 Paradigm 2,08571* ,45003 <0,001 Process Product -,1905 ,45003 1,000 Position -,55238 ,45003 ,611 Paradigm 2,06667* ,45003 <0,001 Position Product ,53333 ,45003 ,638 Process ,55238 ,45003 ,611 Paradigm 2,61905* ,45003 <0,001 Paradigm Product -2,08571* ,45003 <0,001 Process -2,06667* ,45003 <0,001 Position -2,61905* ,45003 <0,001 * At the 0,05 level

(36)

4.1.2 Prioritization of innovation adoption criteria

4.1.2.1 Friedman test results

The second part of the survey functioned to measure if some criteria are more important than others when deciding about the adoption of an innovation. As described in the methods part, a Friedman test has been conducted to measure whether there are differences in the importance of innovation adoption criteria. First, the ranking that is given for the importance of every innovation adoption criteria has been averaged to get the means of the rankings. Figure 8 shows the means of the rankings for innovation adoption criteria among innovation types.

Product Process Position Paradigm

Efficiency 2,36 4,10 3,10 3,60

Costs 3,00 3,60 3,19 3,24

Safety 3,12 1,64 2,24 2,07

Health outcomes 3,50 2,74 3,55 3,26

Quality of care 3,02 2,93 2,93 2,83

Figure 8: The means of the ranks that the innovation adoption criteria have per innovation type on a scale from (1) least important to (5) most important

Then, the Friedman test has been done with the means of the rankings for every innovation type to assess whether these means differ from each other. As seen in Figure 9, there is only a prioritization at the 0,05 level for process and paradigm innovations. The prioritization of innovation adoption criteria for product and position innovations are not observable at the 0,05 level.

Friedman test n X2 Sig.

Product 21 5,83 0,212

Process 21 29,57 <0,001

Position 21 8,03 0,091

Paradigm 21 11,79 0,019

(37)

The differences in prioritization of innovation adoption criteria for product and position innovations are not observable at the 0,05 level and are therefore not statistically strong enough to mention.

Rank Product Process Position Paradigm

1 Health outcomes Efficiency* Health outcomes Efficiency*

2 Safety Costs* Costs Health outcomes*

3 Quality of care Quality of care* Efficiency Costs*

4 Costs Health outcomes* Quality of care Quality of care*

5 Efficiency Safety* Safety Safety*

*At the 0,05 level

Figure 10: Ranking of innovation adoption criteria among innovation types

The hypotheses for this part of the study were:

H2: The safety of an innovation is the most important innovation adoption criterium. H3: The cost of an innovation is the second most important innovation adoption criterium. H4: There is no prioritization among other innovation types besides safety and costs.

Because the results are only statistically strong enough for process and paradigm innovations, we will only test the hypotheses for those innovation types. With the Friedman test it became clear that some innovation adoption criteria are more important than others when adopting an innovation. With the results we can reject H2 because safety is the least important adoption criterium. H3 cannot be rejected for process and paradigm innovations because we cannot statistically say that costs are not the second important, the statistical power does not allow us to do that (Appendix B, Appendix C). We also found that safety is found the least important criterium. Therefore H4 can be rejected because it was expected that there would be no other prioritization than for safety and costs.

4.1.3 Differences in prioritization of innovation adoption criteria

After the prioritization of innovation adoption criteria has been mapped, the differences in prioritization among the innovation types has been measured. Consequently, in the third part of this study we looked at whether there are differences in the relative importance of innovation adoption

(38)

criteria among the innovation types. Because there is no observable prioritization for product and position innovations, we only looked at the differences between process and paradigm innovations.

4.1.3.1 One-way ANOVA results

After we have found that there is a prioritization of innovation adoption criteria for process and paradigm innovations, we looked at whether there were differences between these two types in the prioritization of criteria. To assess the prioritization of the criteria, a one-way ANOVA has been conducted with a post hoc Tukey test for both process and paradigm innovations.

Figure 10 shows the results of the ANOVA for paradigm innovations. There was an observable prioritization of innovation adoption criteria during the decision of innovation adoption at the p<0,05 level for paradigm innovations [F(4,100) = 3,74, p = 0,007].

Paradigm innovations Sum of Squares df Mean Square F Sig

Between innovation adoption criteria 28,133 4 7,033 3,739 ,007 Within innovation adoption criteria 188,095 100 1,881 Total 216,229 104

Figure 11: Results of the one-way ANOVA for paradigm innovations

To assess which innovation adoption criteria are more important for the adoption of paradigm innovations, a Tukey test has been done. The results of the Tukey test are showed in Appendix B. From the results of the Tukey test we can only see that for paradigm innovations, efficiency is found more important than costs and safety and that health outcomes are found more important than safety. Combining these findings results in the ranking showed in Figure 12.

Ranking Innovation adoption criteria

1 / 2 Efficiency / Health outcomes 3 / 4 Costs / Quality of care

5 Safety

(39)

The same one-way ANOVA and Tukey test have been conducted for process innovations. There was an observable prioritization of innovation adoption criteria during the decision of innovation adoption at the p<0,05 level for process innovations [F(4,100) = 12,54 p < 0,001]. Figure 11 shows the results of the ANOVA for process innovations.

Process innovations Sum of Squares df Mean Square F Sig

Between innovation adoption criteria 70,038 4 17,510 12,541 <,001 Within innovation adoption criteria 139,619 100 1,396 Total 209,657 104

Figure 13: Results of the one-way ANOVA for process innovations

To assess which innovation adoption criteria are more important for the adoption of process innovations, post hoc Tukey procedures have been conducted. The results of the Tukey test are showed in Appendix C. We can see that the differences in ranking of innovation adoption criteria for process innovations are bigger and also statistically stronger than for paradigm innovations. We can observe that efficiency is the most important adoption criterium. Also, costs are more important than

safety.

Ranking Innovation adoption criteria

1 Efficiency

2/3/4 Costs / Quality of care / Health outcomes

5 Safety

Figure 14: The interpretation of the ranking of innovation adoption criteria for process innovations based on the Tukey test The hypothesis stated earlier about the mutual differences in prioritization of innovation adoption criteria among innovation types is:

H5: There is no difference in the prioritization of innovation adoption criteria during the innovation adoption decision among the different innovation types.

We cannot reject this hypothesis because for both process and paradigm innovations, efficiency is found most important and safety is found the least important innovation adoption criteria. The ranks of other innovation adoption criteria do not differ enough from each other to call them statistically different. Therefore, we cannot say that there is a difference in prioritization among the innovation type

Difference in willingness of innovation adoption among innovation types in Dutch hospitals