Apps in the world of Health Insurance: a healthy combination?
A critical examination of the value of offering services via mobile applications for customer retention of a health insurance organization in the Netherlands.
Master thesis, MscBA, specialization Business Development University of Groningen, Faculty of Economics and Business
August, 2013
T. Scholten
Apps in the world of Health Insurance: a healthy combination?
A critical examination of the value of offering services via mobile applications for customer retention of a health insurance organization in the Netherlands.
Master thesis, MscBA, specialization Business Development University of Groningen, Faculty of Economics and Business
August, 2013
Thomas Scholten
Student number: 1918834 Address: Hoornsediep 144 9725 HP Groningen, The Netherlands
Tel: 06-48770537
Email: thomasscholten1987@gmail.com
Supervisors University
Dr. ir. M.W. Hillen
Dr. M.A.G. van Offenbeek
ABSTRACT
Services offered via mobile applications is a new way to offer services nowadays. For example, banks offer mobile ways to transfer money. By offering the services via mobile applications they aim at an increase satisfaction of their customers and generate customer retention and prevent switching from service provider. Customer retention and the prevention of switching from service provider is something that is of great importance for almost every organization; therefore also for a health insurance company. The aim of this research is to consider if and how a health insurance company can utilize this new way of offering services to customers. We will consider which variables are expected to be important. The influence of two variables, perceived usefulness and perceived risk of safety, on switching intention is tested. The purpose of this research is to consider how and to which extent the perceived usefulness and perceived risk of services offered via mobile applications influence the switching intentions of customers of a health insurance organization. To find out if results are true for all respondents, two possible moderating variables, technological readiness and trust in the organization, are included. Finally, the variable age is added as a control variable to test if it influences the results.
The results show that perceived usefulness of the services offered via mobile applications significantly influences switching intentions, when services would be offered via mobile applications ,from customers of a health insurance industry. Technological readiness of customers does not influence the strength of the relation between perceived usefulness and customer retention. On the other hand, the age of customers does influence this relation. The strength of the relation between perceived usefulness and switching intentions is much stronger for younger customers than for customers above the age of 35. Thus, age plays a significant role. Furthermore, we can conclude that the relation between perceived risk of safety and switching intentions is not significant for all customers. The relation is not moderated by technological readiness but it is moderated by trust in the organization. For customers with a low level of trust the relation between perceived risk of safety and switching intentions of customers, when services would be offered via mobile applications, is significantly stronger than for customers with a higher level of trust in the organization. Age also strongly influences the relation between perceived risk of safety and the switching intentions. The relation is significant and much stronger for younger customers. Thus, perceived risk of safety is for them a more important factor in their decision to remain customer and not switch from services provider when services would be offered via mobile applications, when an organization offers mobile applications than for other age groups. The research was conducted at a large health insurance company in the Netherlands, Menzis.
Key words: Switching intentions, customer retention, perceived usefulness, perceived risk, technological readiness, trust, mobile applications, TBSS.
ACKNOWLEDGEMENT
I would like to thank several people who supported me complete this Master thesis. First of all I would like to thank my girlfriend Anne Kievitsbosch. Her support gave me more energy to complete this Master thesis. Furthermore I would also like to thank friends and family who assisted and supported me during this period. With special thanks to Jelmer Dijkstra for his help improving the level of English. Finally I would like to thank my supervisor, Mr Hillen, for his guidance with this thesis.
TABLE OF CONTENTS
ABSTRACT
AKNOWLEDGMENT
1 INTRODUCTION 3.
1.1 Research Context: The health insurance industry in the Netherlands 4.
1.2 Management Question and Research Goal 5.
1.3 Objective Statement and Research Question 6.
2. THEORETICAL FRAMEWORK 8.
2.1 Mobile applications 8.
2.2 Technology-Based Self-Service 10.
2.3 Customer Retention 11.
2.3.1 Trust 12.
2.3.2 Relationship commitment 12.
2.3.3 Overall Customer Satisfaction 13.
2.4 Modified objective research question 14.
2.5 Perceived Usefulness 16.
2.6 Perceived Risk of safety 18.
2.7 Moderating and control factors 19.
2.7.1 Technological Readiness 19.
2.7.2 Trust in organization 20.
2.7.3 Control variable: age 21.
2.8 Conceptual model 21.
3. METHODOLOGY 23.
3.1 Data collection method 23.
3.2 Research instrument 24.
3.3 Characteristics respondents and type of sampling 25.
3.4 Quality of the research 26.
3.4.1 Reliability 26.
3.4.2 Validity 27.
4. RESULTS 29.
4.1 Reliability test 29.
4.2 Results future use five mobile applications and comments 30.
4.2.1 Future use five mobile applications 30.
4.2.2 Comments questionnaire 31.
4.3 Statistical results 32.
4.3.1 Descriptive statistics and the Spearman’s rho 32.
4.3.2 Trust in the organization 33.
4.3.3 Age of respondents 34.
4.4 Statistical results smartphone users 35.
4.4.1 Smartphone users and non smartphone users 35.
4.4.2 Technological readiness – smartphone users 36.
4.4.3 Trust in organization – Smartphone users 38.
4.4.4 Age of respondents – Smartphone users 39.
5. CONCLUSION ON MANAGEMENT QUESTION 41.
6. CONCLUSION AND DISCUSSION ON RESEARCH QUESTION 44.
7. REFLECTION 48.
REFERENCELIST
APPENDIX A: Marketshare Menzis
B: Questionnaire and answers to questionnaire C: Results questionnaire future use of services D: Comments end of questionnaire
1 INTRODUCTION
Smartphones are becoming increasingly indispensable for people in the Netherlands (Jansen, 2012). A growing percentage of people living in the Netherlands are in possession of a smartphone, in the middle of 2011 42 percent of the inhabitants owned a smartphone (‘Smartphone-penetratie stijgt naar 42 procent in Nederland’, n.d.). Over 50 percent of the Netherlands owns a smartphone with internet connection via a mobile phone (CBS, 2011). An increasing number of people use their telephone for a wide range of goals through installing mobile applications. Mobile application software, also known as an application or an app, is computer software designed to help the user to perform singular or multiple related specific tasks (AKNLabs, n.d.). A smartphone is needed to use mobile applications.
The most used and downloaded mobile applications on smartphones are games or tasks done with fun as purpose. Examples are Wordfeud and Buienrader, the latter a weather forecast application (Hijink, 2011). TomTom has also offered a downloadable car navigation system besides its physical navigation systems (‘Autonavigatie’ n.d.). While the phones of a decade ago were only used for calling and text messaging, nowadays people use their (smart)phones more and more like a computer through the use of mobile applications.
At present, the mobile application industry is a billion euro industry (Hijink, 2011). There are a lot of companies which offer additional services to their customers via mobile applications. One example is the Rabobank which offers an application to transfer money. Another example is the mobile application of the supermarket Albert Heijn, called ‘Appie’, which aims to make your shopping more efficient by providing you with the ideal walking route in their store (Klis, 2010).
Besides supermarkets and banks, the health insurance company Menzis has also started to offer services via mobile applications. The organization offers, via a budget brand Anderzorg, a mobile application, which makes it possible for their customers to claim their health costs by taking a picture of their declaration and send it to Anderzorg with their mobile phone (http://www.anderzorg.nl).
The above mentioned mobile applications can be divided into five types of mobile application (Fling, 2009). These types are: one where you can gain information at-a-glance (1), mobile applications which offer location-based information (2), mobile applications for content seeking (3), one that offer the opportunity to manage content (4) and a mobile applications for entertainment (5).
Organizations offer services via mobile applications in order to please their customers and bind them to the company as customer. In recent sales and marketing literature, customer retention is viewed as a significant issue (Morgan & Hunt, 1994). It is defined as the activity that a selling organization undertakes in order to reduce customer defection (Reicheld, 1996). Johnson, Barksdale and Boles (2001) emphasize that the importance of understanding customer retention is twofold:
firstly, ‘loyal’ customers are more profitable than newly acquired customers. The conventional wisdom in retail industry circles is that it costs significantly more to acquire new customers than to retain old ones. In fact, among financial-services companies, there is reliable evidence that it is five
times as expensive to acquire a new customer than to retain an existing one (Saubert, 2009). Secondly, the retention of customers can act as a competitive advantage (Friend, Hamwi & Rutherford, 2011).
An example is the increase in purchasing power towards suppliers. The expectation is that health insurance company customers are no exception to this. The goal of this study is to consider whether offering services via mobile applications have a positive influence on customer retention in the health insurance industry. First, the research context of the organization where this research is conducted, Menzis, will be discussed in more detail.
1.1 Research Context: The health insurance industry in the Netherlands
The Dutch health insurance system is based on a distinction between long-term care (covered by the AWBZ) and routine care. Until 2006, the routine care was covered by two parallel but separate systems (Rosenau & Lako, 2008). The first system was a model in which public funds provided insurance for persons with incomes below a given threshold and for those older than age 65 (Ziekenfondswet — ZFW); this was financed mainly from income -related proportional contributions.
The second system was a model in which voluntary private health insurance was provided for all others (from 1986 onwards, insurers were obliged to offer standard cover, the contents and price being set by the public authorities) (Turquet, 2012).
Since the late 1960’s the Dutch government became concerned about increases in health care costs. In the mid 1970’s the government has took measures to control prices and quantities of provided care. From 1992 onwards various elements of competition were gradually introduced into the ZFW system: the regional monopolies of the funds were abolished and the insured consumers became free to choose their insurance organization. The health insurance organizations were given permission to charge a nominal premium over and above the income-related proportional contributions already paid (Van de Ven & Schut, 2008).
Despite these efforts, there was relatively little mobility among the insured at that time and insurers failed to make use of the opportunity for selective contracting towards hospitals and other organizations that were offered to them. These measures nonetheless lead to numerous mergers between insurance organisations. Menzis was one of the outcomes of mergers in this time period.
Menzis Health Insurance was founded in 2006 as a result of a merger of Amicon, Geové and NVS (Menzis Kaders, 2012). The organization is active throughout the Netherlands, but has a so-called focus areas (Kerngebieden)1.
A new mandatory health insurance for routine care was introduced on the 1st of January 2006 which removed the distinction between public (Ziekenfonds) and private funds. All insurers are now allowed to make profit and pay dividends to their shareholders (Van Ginneken, Busse & Gericke, 2008). All residents and non-residents who are paying income tax on their earnings must subscribe to
health insurance for routine care. The government still finances the health coverage for children under the age of 18. Each year in November everyone receives a new offer from their health insurance company for the year to come. If you want to switch to a new health insurance company you have to cancel your health insurance policy before the first of January and choose a new health insurance policy before the first of February. This is the so-called ‘switching period’. Everyone who lives or works in the Netherlands is legally obliged to have a basic health insurance policy (basisverzekering), furthermore, they have the freedom to choose extra health insurance by means of additional health insurance policies (‘Zorgverzekering – Hoe kunt u overstappen?’, n.d.). The main aim of this reform was to introduce competition between health insurers (Rosenau & Lako, 2008).
The increase in competition, among other things, made Menzis aware of the importance of its customer base, resulting in 2011 in goals which focussed on customer retention for 2012. Through these goals, Menzis aims to commit customers to Menzis’ labels (Menzis Kaders, 2012).
1.2 Management Question and Research Goal
As described in the research context section (section 1.1), the increase in competition between health insurance companies made Menzis aware of the importance of its customer base. This resulted in 2011 in goals that focussed on customer retention for 2012 and beyond. Furthermore, Menzis noticed the increase in use of mobile applications from other organizations, such as banks, by its customers.
Menzis also noticed that 3.7 percent of the traffic on their website originated from smartphones.
Therefore, the organization is wondering if and how there is a combination possible of offering services via mobile application and their aims for customer retention.
The mobile applications do not yet exist but are explained to the respondents. This makes it impossible to measure actual retention. All the respondents explained their thoughts and expectations about the services and their intention to remain a customer or defect during the ‘switching period’ The five services which Menzis potentially want to offer via mobile applications are also offered via the internet. The five services are “My Declarations”, “Own Risk”, “My Polis Schedule”, “Health Finder” and “My Optimal Health insurance”. All five will now be discussed.
The services “My Declarations”, Own Risk” and “My Polis Schedule” are services which are offered to customers via a closed section on the Internet (http://www.Menzis.nl/mijnmenzis). “My Declarations” offers an overview of the submitted declarations, for example dentist costs and/or medicine costs with an overview of the declarations that are important to the consumer. “Own Risk“
offers an overview of the amount of health costs the customer has to pay themselves before the health insurance company starts to cover the costs. “My Polis Schedule” offers an overview of your polis schedule in which your agreements with the health insurance company are listed.
The service “Health-finder” is offered via an open section on the Internet (http://www.menziszorgvinder.nl). This service gives the user the ability to find a pharmacist or a physiotherapist in their neighbourhood. In the case of “Top Health-finder” the ability is offered to find
a Menzis contracted physiotherapist. “My optimal Health insurance” is based on the payments comparison tool which is also offered online (‘Vergoedingen vergelijken’, n.d.). The tool advices the customer of Menzis, based on their own expectations and wishes, which Menzis’ health Insurance is most suitable for the customer.
When the services are also offered via mobile applications, the customer can consult their declarations, own risk, the polis schedule, the health finder and payment comparison tool at all time on a smartphone. The goal of this research is to consider whether and how the organization should invest in mobile applications and if that results in an increase in retention. Therefore the management question can be defined as follows:
How and to what extent will services offered via mobile applications influence the customer retention at Menzis?
In this study a quantitative research is conducted to find answers to the research question. In order to find a direction for the research, a literature research has first been conducted. The literature research focuses on the characteristics of mobile applications and factors important to customer retention.
Thereafter, a questionnaire is set out among customers of Menzis to gather their opinions about the mobile applications in combination with customer retention. Results are analysed which lead to an answer to the management question in the conclusion.
1.3 Objective Statement and Research Question
Services offered via mobile applications may have some advantages such as offering location-based information (Fling, 2009). However, it is unknown if customers of a health insurance organization would value these advantages for their services. Furthermore it is unknown if, when customers do value these advantages, if these would lead to an increase in customer retention. The objective of this research is to find out if offering services via mobile applications by a health insurance company will positively influences customer retention. In this research Menzis is used as a case study.
The importance of this study lies in the combination of this relatively young technology with a health insurance company. Unique characteristics of this industry are that it is mandatory for customers to have an insurance and that they are only allowed to switch once a year. Mobile applications are relatively new and have unique characteristics as well. It is therefore unknown if the information about on- and offline self-service technologies and services, such as ATM’s, can be used in the same way for this technology in this specific industry. This research can help to better understand and increase the knowledge of the process of customer evaluation of self-service mobile applications in the health insurance industry.
This leads to the following objective research question:
How and to what extent will services offered via mobile applications influence customer retention within a health insurance company?
In the next chapters we will try to find answers to the management question, simultaneously with the research question. First, a literature research is conducted where customer retention and an overview of its antecedents will be given (ch2). Next, there will be an explanation of the antecedents that are tested in this research (ch2). Thereafter, the methodology of this study is described (ch3). Besides the literature research, a questionnaire has been distributed among customers of Menzis. Answers of this questionnaire will analyzed in chapter four. There will be given an answer to the management and research questions in the conclusion (ch 5 & ch6). Limitations of this research and recommendations for future research will be given at the end (ch7).
2. THEORETICAL FRAMEWORK
In this chapter the hypotheses are set up which will be used to answer the research question. The hypotheses will be based on scientific literature about mobile applications, technology-based self services (TBSS) and services. This approach is used because no literature exists about a combination of mobile applications and customer retention. When there is no literature available about mobile applications, which is preferable, literate about TBSS is used. When there is also no literature available about TBSS, literature about services will be used about services in general. This logic is illustrated also shown in figure 2.1. This figure shows that mobile applications are a form of technology-based self-services and technology-based self services are a form of services offerings.
Figure 2.1 Focus used literature
Available literature about mobile applications is discussed first. Because there is little information available about mobile applications and customers retention, information in this thesis is mostly based on literature concerned with mobile applications. Secondly, information about technology-based self- services will be discussed. Aspects, of technology-based self services which are expected to be important for customer retention are found here. Finally, the information found about services in general is combined with the information known about mobile applications and technology-based self services. This will result in a list of characteristics of the mobile applications that may influence customer retention. At the end of this chapter the conceptual model is defined by visually showing the described relations between customer retention and the chosen antecedents.
2.1 Mobile applications
A smartphone is a relatively young medium. It is the first truly personal, always present and carried- with-you-mass-medium, with a built-in payment channel and it gives consumers the ability to create and distribute content at the moment the mood strikes you to do so (Fling, 2009). As explained earlier, mobile application software, also known as an application or an app, is computer software designed to
Service (3) TBSS (2)
Mob App (1)
help the user to perform singular or multiple related specific tasks (AKNLabs, n.d.). A smartphone is needed to use mobile applications.
According to Fling (2009), there are five types of mobile applications which have their own characteristics. Therefore, the context in which it is used is assumed to be different, as can be seen in the table below (Table 2.1).
Table 2.1 Type of mobile applications
Mobile appli- User experience Task Type Task duration Can be combined with cation type type
Utility At-a-glance Information recall Very Short Immersive
Local Location-based Contextual Quick Immersive
information
Informative Content-based Seek information Quick Local Productivity Task-based Content management Long Utility Immersive Full screen Entertainment Long Utility, local
Utility is a simple user experience metaphor that is meant to address short, task-based scenarios.
Information is meant to be presented in a minimal fashion, often using as little user input as possible.
An example is the Time Timer application with which you can easily see how much time is left on the clock you have set (‘Time Timer’, n.d.). Local is used for location-based applications, applications which might contain a dynamic map, and which possibly lists multiple location-based points of interest (Fling, 2009). An example is the runner or so called hardloop application, which automatically measures the time and distance you ran (‘Gratis Looptijden.nl app voor iPhone’, n.d.). Informative is an application context in which the one and only goal of the application is to provide information. The key task of the user is to read and understand; it is not necessary to interact (Fling, 2009). An example is the mobile application from nu.nl with which you can read the latest news articles (‘NU op de iPhone’, n.d.). Productivity is used for content and services which are heavily task-based and meant to increase the users’ sense of efficiency. With these types of applications, we can assume that the users are more committed to accomplishing a particular goal, like managing content such as messages, contacts, or media, but we should still assume that they are doing so during idle periods (Fling, 2009).
An example is the mobile application from Marktplaats (‘Marktplaats Mobiel’, n.d.). Immersive is meant to consume the user’s focus, often doing so by filling the entire screen, and leaving no trace of the device-user-interface to distract the user (Fling, 2009). A game such as Angrybirds is an example of an immersive mobile application (‘Angry Birds’, n.d.).
Another important factor for mobile applications is the context in which the mobile app is used. Context is defined as how the users will derive value from something they are currently doing,
or in other words, the understanding of circumstances in which the mobile application is used. Each context will dictate how someone accesses information and, therefore, how someone derives value from it (Fling, 2009). Anckar and D’Incau (2002) found that there are five different settings or contexts in which wireless services can provide mobile value: time-critical needs and arrangements (1), spontaneous needs and decisions (2), entertainment needs (3), efficiency needs and ambitions (using ‘dead spots’ in the day) (4) and mobility-related needs (needs that arise when away from home) (5).
According to Anckar and D’Incau (2002), the mobile value is the value arising from the mobility of the new medium, i.e. making use of electronic services while ‘on the road,’ and mobile- commerce has, in fact, been defined as ‘e-commerce for users on the move’ (Vittet-Philippe &
Navarro 2000; Kalakota & Robinson, 2001). The distinctive feature of mobile commerce is the significance of the user’s location, his situation and his mission (May, 2001).
Dickinger, Arami and Meyer (2008) suggest that the most powerful determinant of attitudes and intentions of using services on a mobile phone is the enjoyment of that service rather than its usefulness in a context. This is supported by the most downloaded mobile applications in 2011 which all fall in the following categories: games, entertainment, music & photography, social programs, on the go (i.e. Weather Channel) and lifestyle (i.e. Amazon) (http://www.apple.com). Furthermore, it may be possible that it is more useful to receive enjoying services on a smartphone than via the computer.
The weather channel is, for example, more useful when you are sheltering outside and want to know when it stops raining than when you are inside your house.
The different types of mobile applications in combination with the context makes that a mobile application offer some advantages in comparison with other service offering possibilities. For example, when you are in the waiting room of a dentist, wondering if you have to pay for this consult.
A smartphone offers the advantage that you can check your own risk etc. wherever you are. In this situation that would be the waiting room of a dentist. In the next chapter information about other technologies and customer retention will be explained.
2.2 Technology-Based Self-Service (TBSS)
Self service technologies (SST’s) are technological interfaces that allow customers to produce a service independent of direct service employee involvement (Meuter, Ostrom, Roundtree & Bitner, 2000). According to Curran, Meuter and Suprenant (2003) examples of SST’s include internet based services such as online check-in at an airline company, automated hotel checkout, automated teller machines or services offered via mobile applications.
There is disagreement about the term SST. Reinders, Dabholkar and Frambach (2008) state that Technology-based self-service (TBSS) is a more accurate term than self-service technology (SST) for most of this literature because the majority of studies examine different types of self-services based
services offered via the mobile applications are inquired as well, not solely mobile applications.
Therefore the term TBSS will be used in this research. Technology-Based Self Service includes “on- site” options, such as touch screens in department stores, information kiosks at hotels, as well as self- scanning options in grocery stores and libraries. It also includes “off-site” options such as telephone and online banking and shopping on the internet (Reinders et al., 2008) as well as also applications on smartphones. Much of the literature used in this thesis is based on research about TBSS. According to Meuter et al. (2000) and Blumberg (1994), to optimize an organizations’ performance and generate savings organizations are increasingly using TBSS. Anitsal and Schumann (2007) claim that customers actually contribute to a firm's productivity and profitability by using TBSS and thereby decreasing the firm's labour costs. Customers who are adapted at using technologies might experience increased efficiency and satisfaction while customers who are not as technologically educated might be frustrated by the technological possibilities in service settings. Besides generating savings by an increase in performance, offering services via mobile application may also influence customer retention, according to Hedge (2011). He states: “mobile banking customers are twelve and a half percent less likely to leave their current provider than customers in general” (p16). The relation between mobile applications, TBSS and customer retention will be more thoroughly clarified in the coming chapter.
2.3 Customer Retention
As said in the previous chapter, some authors state that TBSS, and in this research mobile applications, may influence customer retention. Important to know is how customer retention ‘occurs’
and which underlying variables of customer retention are important. Villanueva and Hanssens (2007) state that there are several reasons why customers decide to be loyal to a specific company. Some may be easily affected by a company, while others may not. According to Villanueva and Hanssens (2007) customer satisfaction can be seen as a determinant of customer retention. Miguel-Davila, Cabeza- Garcia, Valdunciel and Florez (2010) suggest that it is very likely that when customers are satisfied with the institution they remain loyal and continue their relationship with it. Walsh, Groth and Wiedmann (2005) have shown in their research that customer satisfaction had a significant effect on switching intentions of customers in the energy industry. Gustafsson, Johnson and Roos (2005) found that customer satisfaction and commitment are drivers of customer retention. Finally, by showing that customers who are committed to their relationship with their online bank are likely to continue the services offered by that bank, Vatanasombut, Igbaria Stylianou and Rodgers (2008) have found that commitment as well as trust in the service and company is an important factor for customer retention.
Customers who trust their online bank are likely to continue using the services offered by that bank.
Garbarino and Johnson (1999) found that for theatres, satisfaction is a good predictor of future intentions for low relational customers (customers looking for a transaction). Whereas for high relational customers (customers looking for a relation), trust and commitment, rather than satisfaction,
are the important factors. This suggests that there may be differences between customers who remain customer. Furthermore it suggest that satisfaction, relationship commitment and trust can not explain the complete customer retention by themselves but are interrelated.
Based on the above literature, the hypothesis is that satisfaction, relationship commitment and trust are important factors for customer retention in health insurance industry because the studies are conducted at various industries, including banks and a energy company. Both industries share many characteristics the health insurance industry, such as long-term contracts and mandatory products. The following section explains which factors influence trust, relationship commitment and satisfaction.
2.3.1 Trust
According to Turel, Yuan and Connelly (2008), many studies have demonstrated the importance of trust in an online service provider as a predictor of behavioural outcomes of customers. In services marketing, Berry and Parasuraman (1991) found that “customer-company relationships require trust“
(p. 144). Effective service marketing depends on the management of trust because “the customer typically must buy a service before experiencing it (p. 107).” Trust can be defined as a group of beliefs held by a person derived from his or her perceptions about certain attributes; in marketing this involves the brand, products or services (Flavián, Guinalíu & Gurrea, 2006). Morgan and Hunt (1994) further specify these beliefs by defining trust as existing when one party has confidence in an exchange partner’s reliability and integrity. Flavián et al. (2006) define trust slightly different by considering it a multidimensional construct that differentiates between honesty and benevolence perceived in the behaviour of the other party (Flavián et al., 2006). Honesty is the belief that another person will keep his or her word, fulfil promises and be sincere (Gundlach & Murphy, 1993).
Benevolence is the belief that one of the parties is interested in the well-being of the other without intention of opportunistic behaviour (Larzelere & Huston, 1980) and motivated by a search for a mutually beneficial relationship (Doney & Cannon, 1997). When services offered via a mobile application influence the trust in a health insurance company, it is expected that they do so via a change in feeling of honesty and or benevolence about the brand or the service.
2.3.2 Relationship commitment
There is another potential driver of customer retention: relationship commitment (Bendapudi & Berry 1997; Morgan & Hunt, 1994). Morgan and Hunt (1994) define relationship commitment as: “(…) an exchange partners believe that an ongoing relationship with another is so important as to warrant maximum efforts at maintaining it; that is, the committed party believes the relationship is worth working on to ensure that it endures indefinitely”(p. 23).
According to Reichfeld (1996), a high level of commitment is crucial for business success and can offer a competitive advantage. There are two major dimensions of relationship commitment:
the ‘hotter’, or more emotional, factor that develops through the degree of reciprocity or personal involvement that a customer has with a company, which results in a higher level of trust and commitment (Garbarino & Johnson 1999; Morgan & Hunt 1994). Calculative commitment is in contrast to affective commitment the colder, more rational economic-based, dependence on product benefits due to a lack of choice or because of switching costs (Anderson & Weitz, 1992; Dwyer, Schurr & Oh, 1987; Heide & John, 1992; Morgan & Hunt, 1994). When services offered via a mobile application can lead to an increase in relationship commitment with a health insurance company, it is expected that it does so via an increase in calculative commitment and/or affective commitment.
2.3.3 Overall Customer Satisfaction
Different research findings in this area suggests, at least, the link between satisfaction and retention could be established as an empirical generalization (Villanueva & Hanssens, 2007). Although previous empirical evidence does not totally support it, Arasli, Katircioglu and Mehtap-Smadi (2005) and Karatepe,Yavas and Babakus (2005) conclude that it is very probable for customers who are satisfied with the company to remain loyal and continue their relationship with it. According to Heskett,Jones, Loveman, Sasser and Schlesinger (1994), overall satisfaction is also the key determinant of customer commitment. This means that an increase in satisfaction, according to the authors, would, most likely, lead to an increase in retention and in commitment. In general terms Flavián et al. (2006) define satisfaction as: “an affective consumer condition that results from a global evaluation of all the aspects that make up the consumer relationship (p. 4)”. Johnson and Fornell (1991) define customer satisfaction as a customer’s overall evaluation of the performance of an offering to date.
It has also been shown that in highly competitive markets (e.g., automobiles) only very satisfied customers are loyal. In non-competitive markets, even companies with low levels of satisfaction have high levels of loyalty (Jones & Sasser, 1995). Important to note is that the authors place loyalty on a par with customer retention. So the level of satisfaction needed to gain an increase in retention can differ between branches.
Important underlying factors of satisfaction are perceived service quality and perceived customer value (Miguel-Davila et al., 2010). Customers who perceive service quality will be satisfied with the institution (Miguel-Dávila et al., 2010). As an overall evaluation that is built up over time, satisfaction typically mediates the effects of product quality, service quality, and price or payment equity on loyalty (Bolton & Lemon, 1999). Sweeney, Soutar and Johnson (1999) studied the effect of perceived risk on customer value. There was found that perceived risk had a more powerful, direct effect on perceived value than its traditional antecedents, like perceived relative price or perceived product quality. These findings have found further support in literature suggesting that the greater the perceived risk, the smaller the, by the customer perceived, value (Lee & Allaway, 2002; Snoj, Korda
& Mumel, 2004). In the study of Sweeney et al. (1999) perceived risk was defined as financial and performance risk.
Meuter et al. (2000) found that if a technology performs as expected, it provides advantages over interpersonal service and/or helps consumers in difficult situations, consumers are likely to evaluate the TBSS favourably and, as a result, be satisfied. When a TBSS is favourable it is therefore expected to positively influence the satisfaction of consumers and, therefore, follow the same path towards retention as a ‘normal’ or non technology-based self-service.
In line with this, there are several aspects that are important for a positive evaluation of a mobile application. Zhou (2011) found in his study about mobile services that the perceived usefulness affect users’ satisfaction of that service. It is important to note that the satisfaction here is the satisfaction that with the mobile service, which in this study would be a part of the overall customer satisfaction. The perceived usefulness also directly influences the continuance intention of customers to use the mobile services. Because the perceived usefulness was shown to be important for the continuance intention, they suggest that organizations need to attach great importance to the perceived usefulness. In the research of Zhou (2011) it is, furthermore, shown that for mobile services the perceived ease of use has an effect on users’ satisfaction of the mobile service. No relation was found between the perceived ease of use and the continuance intention of the consumers. In the research of Thong, Hong and Tam (2006) a relationship between perceived ease of use and satisfaction was found.
In addition, perceived enjoyment is also found to affect mobile internet users’ continuance intention (Thong et al., 2006). In their research the perceived enjoyment had a direct positive effect on the satisfaction with the service.
When services offered via mobile applications lead to an increase in satisfaction, it is expected they do so via several variables. First, it may be possible that it does so via an increase in perceived service quality and customer value. Perceived risk is hereby expected to be an important underlying factor that influences the customer value. Secondly, the perceived usefulness, perceived ease of use and perceived enjoyment may influence the satisfaction, of the services offered via mobile applications, which are part of the overall customer satisfaction.
2.4 Modified objective research question
The previous paragraphs have shown which variables are expected to be important to find how the implementation of service via mobile application influence the customer retention. To find if and how offering services via mobile applications could lead to an increase in customer retention, all previous variables and their relation towards customer retention should be investigated. Due to the time and size of this research it is not possible to test all variables and their relation towards customer retention. A selection from all the possible researchable variables has been made. First, all the variables that could be researched in this paper are described. It is explained how they are expected to influence the customer retention, based on several previous conducted and discussed studies. Thereafter, it is explained which variables will be studied in this paper, with a modified research question as result.
In several studies it has been found that to influence the customer retention three underlying variables (satisfaction, relationship commitment and trust) are important. Therefore, the expectation is that services offered via mobile applications should positively influence the trust in, the relationship commitment with, and satisfaction with the organization which should result in an increase of customer retention.
The important underlying variables for trust are benevolence and honesty. Therefore, offering services via mobile applications should increase the feeling of benevolence and/or honesty towards the organization which should lead to an increase in trust and most likely customer retention.
The important underlying factors of relationship commitment are the variables affective and calculative commitment. Therefore, services offered via mobile applications could lead to an increase in the feeling of affective and/or calculative commitment towards the organization which should lead to an increase in relationship commitment of the customer. This increase in relationship commitment will then most likely lead to an increase in customer retention.
For overall customer satisfaction the underlying variables are perceived service quality and customer value. Perceived risk is an important negative factor on the customer value. The services via mobile application should have advantages that will make customers want to use them and view them as favourable, which will lead to a more overall customer satisfaction. The aspects that are important for a positive evaluation of the mobile application are perceived usefulness, perceived ease of use and perceived enjoyment. It is unknown if offering services via mobile applications will have influence on all these variables and if it therefore can lead to an increase in customer retention.
The fact that the services offered via mobile applications do not yet exist makes it hard to test if whether they increase the trust in and relationship commitment to a health insurance company.
These two variables should be tested when services are available and customers have used these for a while, because it is hard for customers to say in advance if it would influence the trust in the organization or commitment towards a organization. The important variables which increase the overall customer satisfaction are the service quality and the customer value with perceived risk as an important negative factor and perceived usefulness, perceived ease of use and perceived enjoyment as positive factors. Because the perceived ease of use and perceived enjoyment are based on using the mobile application and the application does not yet exist, this should be tested in the future when the applications do exist.
In this research the perceived risk and perceived usefulness in relation of the services offered via mobile applications to customer retention are going to be studied. Perceived risk, based on expectations previous to using the service, can be measured. The perceived usefulness can also be measured because people can express their feelings about the usefulness of the services previous to using the services, because the services can be explained in detail. The perceived risk and perceived usefulness are also expected to be the most important factors while there has been found that perceived risk had a more powerful, direct effect on customer value than the other variables (Sweeney et al.,
1999) and perceived usefulness was also important for the intention of continuing the use of the service (Zhou, 2011).
As mentioned above, a unique characteristic of the health insurance industry in the Netherlands is that it is mandatory for customers to have an insurance. Also, they are only allowed to switch between insurances companies once, at the end of the year. ‘Remaining customer’ is therefore defined as a customer that does not switch during that period. As mentioned earlier: an increase in satisfaction often has a negative effect on customer switching intentions (Walsh et al., 2005).
According to Antón, Camarero and Carrero (2007) satisfaction is a mediating variable between organization initiatives and switching intentions. This is similar to the expectation that satisfaction mediates between organization initiatives and customer retention. Because of the lack of actual services offered by mobile applications, only the expected customer satisfaction and intention to switch can be measured. Doing so by asking customers about a hypothetical situation in which that services would be offered via mobile application. Therefore, instead of measuring the satisfaction and customer retention, the intention not to switch from health insurance organization will be tested.
Perceived usefulness and perceived risk will be directly tested on customers’ switching intentions in a scenario in which services would be offered by mobile applications. This led to the following modified objective research question:
How and to which extent will the perceived usefulness and perceived risk of safety of services offered via mobile applications, influence customers’ intention to not switch from health insurance organization, when services would be offered via mobile applications?
In the next paragraph the relation between perceived usefulness, perceived risk and switching intention will be explained more extensively and hypotheses will be given. For these hypotheses will be made use of literature about customer retention, because it is closely related to switching intentions.
Thereafter potentially moderating factors are explained. Finally, the conceptual model will be given.
2.5 Perceived Usefulness
Perceived usefulness is an important determinant of attitude in the technology acceptance model (TAM) (see figure 3) and is important for the acceptance of a technology (Davis, 1986). Perceived usefulness can be defined as: “People’s salient beliefs that using the technology will enhance his or her job performance“ (Davis, Bagozzi & Warshaw, 1989). The basic concept underlying the acceptance of technology can be found in figure 2.2.
Figure 2.2 Technology acceptance model (Davis, 1986)
The perceived usefulness is expected to influence the attitude towards using a service. The individual reactions to using a technology influence its intention towards using it and ultimately it influences the actual use (Venkatesh, Morris, Davis & Davis, 2003). Based on the literature of Davis (1986) the expectation is that some customers, before using the service, may find it a good idea to be able to receive the services via mobile applications. Their idea about the usefulness, influences their intention to use the services offered via mobile applications and this influences the actual use of the services via mobile applications.
Bhattacherjee (2001) found in his research about satisfaction and continuance use of online banking that the perceived usefulness was an important determinant for both variables. The perceived usefulness was measured via the perceived improvement in performance, productivity and effectiveness of measuring personal finances and perceived overall usefulness. Besides this, Oghazi, Mostaghel, Hultman and Parida (2012) also found that perceived usefulness of a TBSS was important for the intention of using the TBSS. In his research perceived usefulness was measured via the perceived increase in easiness of borrowing books, the perceived improvement in procedure of borrowing books, the perceived reduced time, perceived increase in control and the perceived expectation that customers will sooner re-use the TBSS and they perceive the TBSS as more useful.
As previously mentioned, according to Villanueva Hanssens (2007) and Gustafsson et al.
(2005) customer satisfaction is a determinant of customer retention. Zhou (2011) also showed in his research that an increase in perceived usefulness positively influences the satisfaction of the services for online banking. Though there was no research found that directly measures the perceived usefulness on the increase in customer retention for another TBSS, it would be interesting to find out if the perceived usefulness of the services offered via mobile applications directly positively influences the customer retention in the health insurance industry. While there is known that for other TBSS’ in other industries the increase in perceived usefulness positively influences the satisfaction and satisfaction in turn positively influences the intention to switch, the expectation is that the perceived usefulness of the services via mobile applications also influences the switching intention. This leads to the following hypothesis:
H1: Increase in perceived usefulness of services offered via mobile applications positively influences customers’ intention to not switch from health insurance organization, when services would be offered via mobile applications?
2.6 Perceived risk of safety
Perceived risk is an old concept introduced by Bauer (1960). Bauer stated that “consumer behaviour involves risk in the sense that any action of a consumer will produce consequences which he cannot anticipate with anything approximating certainty, and some of which are likely to be unpleasant”
Bauer, 1960, p24. Bauer refers to service offering in general, in the case of customers of a health insurance company who think about using mobile applications it may be unknown how the organization makes sure their privacy is secured. Perceived risk could also be defined as “the subjective expectation of a loss or as a subjective anticipation or loss of some degree” (Sweeney et al., 1999, p81. There are two aspects of that loss of some degree: the consequences and/or importance of a loss and the likelihood of unfavourable outcomes Shamdasani, Muhkerjee and Malhotra (2008).
According to these authors there are several categories of loss which impact on overall perceived risk.
These include: financial, safety, performance, psychological, social and time/opportunity risks.
We believe that the new aspects in this study are the mobile applications; therefore, the focus of the perceived risk will be on safety. Sweeney et al. (1999) studied the effect of perceived risk on customer value. In that study, perceived risk was defined as consisting of financial and performance risk. As previously mentioned, there was found that perceived risk had a more powerful, direct effect on perceived value as its traditional antecedents, like perceived relative price or perceived product quality. These findings have found further support in literature which argues that the greater the perceived risk, the less is the value perceived by the customer (Lee & Allaway, 2002; Snoj et al., 2004).
A customer’s perception about the risks of a technology can negatively influence the opinion about that technology (Black, Locket, Winklhofer & Ennew, 2001), in this case mobile applications.
According to Black et al., (2001), perceived risk is the risk of error and the level of security compared to the system currently used by the customers. Perceived security is defined as the perception that interactions are safe and secure. In this research that means that the mobile applications are safe and secure. As mentioned above, the focus of perceived risk will be on safety; therefore, the definition of Black et al. (2001) is used in this research; perceived risk of safety is the opinion about the safety and security of the mobile applications.
The research of Wessels and Drennan (2011) shows that perceived risk negatively influences the attitude towards mobile banking. Vatanasombut et al. (2008) found that the aspect of perceived security was important for the increase in trust and, as earlier mentioned, trust was important for the increase in customer retention. This leads to the following hypothesis:
H2: Increase in perceived risk of safety of services offered via mobile applications negatively influence customers’ intention to not switch from health insurance organization, when services would be offered via mobile applications?
2.7 Moderating and control variables
The relation between perceived risk of safety, perceived usefulness and switching intentions may be influenced by two variables; ‘technological readiness’ and ‘trust in the organization’. Both are explained in the coming paragraphs. After that, age is included as a control variable.
2.7.1 Technological Readiness
The technological readiness concept can be viewed as an overall state of mind resulting from a gestalt of mental enablers and inhibitors that collectively determine a person’s predisposition towards technologies (Parasuraman, 2000). The construct is based on four dimensions: optimism (1), innovativeness (2), discomfort (3) and insecurity (4). Optimism can be defined as: “A positive view of technology (belief in increased control, flexibility and efficiency in life due to technology)“
(Parasuraman, 2000, p311). Innovativeness can be defined as: “A tendency to be the first using a new technology (a tendency to be a technology pioneer and thought leader)” (Parasuraman, 2000, p311).
Discomfort can be defined as: “Distrusting of technology and scepticism about its ability to work properly” (Parasuraman, 2000, p311). Insecurity can be defined as: “A perception of lack of control over technology and a feeling of being overwhelmed by it” (Parasuraman, 2000, p311). Optimism and innovativeness are the positive drivers of technological readiness, encouraging customers to use technological products and/or services and to hold a positive attitude towards technology, while discomfort and insecurity are negative drivers, making customers reluctant to use technology (Lin &
Hsihe, 2006). In the research of Chen, Chen and Chen (2009) covering a wide range of TBSS’ it was shown that optimism and innovativeness both positively influence the satisfaction of customers.
However, there was no significant relation found for the influence of discomfort and insecurity on satisfaction.
The positive dimensions are used in this research to see if they serve as a moderator in the relation between perceived usefulness, perceived risk of safety and switching intentions. The negative dimensions of technological readiness are closely related to the perceived risk of safety. With both the risk of using mobile applications can be measured. When the technology readiness is higher the influence of perceived risk of safety is assumed to decrease. Because the amount of questions in this questionnaire would become too much for the respondents, the negative dimensions are not included.
Besides a direct influence of technological readiness on perceived usefulness (Chen et al., 2009), technological readiness also, perhaps, moderates the effect of perceived usefulness on switching intentions. As mentioned earlier, Oghazi (2012) found that perceived usefulness of a TBSS was important for the intention of using the TBSS. In his research perceived usefulness was measured
via the perceived increase in easiness of borrowing books, the perceived improvement in the procedure of borrowing books, the perceived reduced time, the perceived increase in control and the perceived expectation that customers will quicker re-use the TBSS and if the TBSS is perceived as useful. It is possible that there are differences between customers in perceived usefulness. Customers who are adept at using technologies, and in this study mobile applications, might experience increased efficiency/usefulness and satisfaction, while customers who are not as technologically educated might be frustrated by the technological possibilities in service settings (Anitsal & Schumann, 2007). The expectation is that mobile applications do not frustrate customers who prefer to use other service options because they are not forced to use it. When a customer does not want to use the mobile applications other service options are available. Therefore, the expectation is therefore that the relation will be stronger for customers who are technological ready. This leads to the following hypothesis:
H3: Technology readiness positively moderates the effect of the perceived usefulness on customers intention to not switch from health insurance organization when services would be offered via mobile applications.
It may also be interesting to measure the influence of technological readiness on the relation between perceived risk of safety on switching intentions. In this way can be measured if customers perceive risk for these particular applications of Menzis and/or if they perceive this risk for all apps. It is also interesting to find out if a high level of technological readiness results in lower level of perceived risk of safety. If this is true, the expectation is that the overall perceived risk of safety will be lower in the future because it is expected that more consumers then will have a high level of technological readiness. The expectation is that technological readiness may moderate the perceived risks influences on the decrease in customer retention. This lead to the following hypothesis:
H4: Technology readiness negatively moderates the effect of the perceived risk of safety on customers intention to not switch from health insurance organization when services would be offered via mobile applications.
2.7.2 Trust in organization
The perceived risk of safety of a mobile application may be influenced by the trust in the organization.
As mentioned earlier, trust is usually considered as a multidimensional construct that differentiates between honesty and benevolence perceived in the behaviour of the other party (Flavián et al., 2006).
Firms with a good reputation are perceived to be reluctant to jeopardize their reputation by acting in an opportunistic manner (Chiles & McMackin, 1996). Thus, when an organization has customers who trust them the expectation is that customers expect future actions, such as introducing services via
technology. In the research of Vatanasombut et al. (2008) it is shown that the aspect of perceived security, an element of perceived risk of safety, was important for the increase in customer retention via the increase in trust. Where the increase in perceived risk of safety is directly tested in relation to the increase in switching intentions, trust in the company may be an important moderating factor. The expectation is that when customers trust the organization the perceived risk of safety has less influence on the intention not to switch. This leads to the following hypothesis:
H5: Trust in the organization negatively moderates the effect of perceived risk of safety on customers intention to not switch from health insurance organization when services would be offered via mobile applications.
2.7.3 Control variable: age
Besides moderating variables there are also control variables. Control variables are utilized to test whether outcomes of the study are true for all the customers or that a variable influences this relation.
In this study it is tested if the influence from perceived usefulness and perceived risk of safety on switching intentions is true for all age categories. Whether or not age shall be of importance in this research is unknown. Gil-Saura, Ruiz-Molina and Calderon (2010) described in their article several previously conducted researches where some did found and some did not found age to be a moderating or control variable in the adoption of a TBSS. Age was not a control variable or moderating variable in their research (Gil-Saura et al., 2010). Where in the research of Morris, Venkatesh and Ackerman (2005) age did influence the results. The logic behind this was that older customers may perceive fewer advantages in the use of new technologies (Morris et al., 2005).
2.8 Conceptual model
In this theoretical framework the relation between perceived usefulness, perceived risk of safety, perceived enjoyment, ease of use, honesty, benevolence, affective commitment, calculative commitment, trust, relationship commitment, satisfaction and customer retention are set out, illustrated in a model, based on scientific literature. In this study, we have chosen to narrow the research. The relation between perceived usefulness and perceived risk of safety and switching intentions will be tested. Technological readiness and trust in organization are added as a moderator because these are expected to be important factors influencing the relation. The factors are all important for Menzis to decrease the uncertainty about offering services via mobile applications. All the variables, and their relations influence on each other each other, are combined in one conceptual model (figure 2.3). As one can see in figure 2.3, the relation between perceived usefulness and intention not to switch is expected to be positive (H1). The relation between perceived risk of safety and intention to not switch from health insurance organization is expected to be negative (H2). ‘Technological readiness’ is expected to positively influence the relation between perceived usefulness and intention to not switch
from health insurance organization (H4). Finally, ‘technological readiness’ and ‘trust in the organization’ are both expected to negatively influence the relation between perceived risk of safety and intention to not switch from health insurance organization (H3&H5).
Figure 2.3 Conceptual model Perceived
usefulness
Intention to not switch health insurance organization
Perceived risk of safety
Technological Readiness
+ H1
- H3 - H2
Trust in organization + H4
-
H5
Age
3. METHODOLOGY
In this chapter the methodology used in this research is described. First will be explained which data collection method is used (section 3.1). Second, the research instrument will be described (section 3.2). Third, customer characteristics and type of sampling will be explained (section 3.3). Finally will be described how there will be assured that the quality of this research will be at an acceptable level (section 3.4).
3.1 Data collection method
In this research a quantitative method is used to test the hypotheses. The interesting elements or characteristics are tested via mostly known, standardized, measuring instruments with a large number of data points. Statistical criteria are used to calculate if the results confirm or reject the hypotheses (Boeije, 2005).
Customer behaviour is best measured by using observation (Baarda & De Goede, 2001).
According to Baarda and De Goede (2001) customers may be aware what they do or have done. This could also be true for the actual perceived usefulness and perceived risk of safety of the services and expected increase in intention not to switch health organization. As the services offered via mobile applications are not yet available, the actual behaviour can not be measured. Therefore, a questionnaire has been used in this research. According to Baarda & De Goede (2001) a questionnaire is a good way to gain the customers’ knowledge, attitude towards or opinion about a subject. Some customers may possess knowledge about receiving services on their smartphone because they make use of other services on their smartphone. Furthermore, customers may possess knowledge about the services as well, as they may already make use of the five earlier explained services via a computer with Internet. Therefore, the expectation is that it is possible to gain the customers’ knowledge, attitude and opinion about the mobile applications.
In this research an online questionnaire is used. In this way customers of Menzis are asked through email to fill in the online questionnaire. The reason to use an online questionnaire is because it has a lower cost per unit in comparison with calling or visiting customers. Furthermore, the mail survey’s ability to cover a wide geographic area with little additional costs for respondents at a distance allows this research to be conducted with a larger group of persons (Bourque & Fielder, 2003). The method also has the advantage that respondents who do not want to make a commitment to an interviewer to be available at an appointed and specific length of time now may be more willing to do an interview, because they have the luxury to do it at their own leisure (Bourque & Fielder, 2003).
Blumburg, Cooper and Schindler (2008) also came up with several advantages which are important reasons which were important reasons in the decision to use this type of questionnaire. These advantages are that there is a quick turnaround of the results, results are tallied as respondents’
complete the questionnaire and respondents may appreciate the more anonymous nature of the approach.
There are also disadvantages of an online questionnaire. Large samples of data cannot automatically be generalized because characteristics of the larger population are not known.
Furthermore is a large and accurate list of the population of interest needed (Bourque & Fielder, 2003;
Blumburg et al. 2008); in contrast of using telephone and mail sample frames. Blumburg et al. (2008) also found that using web-based surveys can be expensive. Furthermore, it takes technical as well as research skills to prepare an online questionnaire. Of the customers of Menzis, to which the email was send, age, gender and email address are known. Luckily, the technical skills to set up an online questionnaire were in-house available. Therefore, some of the disadvantages of an online questionnaire were neutralized.
3.2 Research instrument
As explained in the previous paragraph, a questionnaire has been chosen as research instrument.
Because no standardized questionnaire is available for the topic with which we are concerned here, the questionnaire has been put together based on seven previously published questionnaires closely related to the research topic. Most questionnaires are previously used for other types of TBSS’s.
The questionnaires of Oghazi (2012) and Bhattacherjee (2001) were used to measure perceived usefulness. Perceived usefulness is the degree to which a person believes that using a particular system would enhance his or her (job) performance (Davis et al., 1989). Both authors measured the perceived usefulness of a TBSS. The research from Oghazi (2012) was about at a self- checkout option in a library and; the research of Bhattacherjee (2001) was about online banking. A combination of their questions has been made to measure the perceived usefulness of possible mobile applications from the health insurance company.
As mentioned earlier perceived risk of safety is the risk of error and the level of security compared to the system currently used by the customers (Black et al., 2001). In the article of Vatanasombut et al. (2008), the perceived security was measured as part of the perceived risk of safety for internet banking. Black et al. 2001) found that the expectation that things could go wrong was an important indicator for online financial services. Shamdasani et al. (2008) found that a negative influence on privacy online is an important indicator of the perceived risk of safety of online services.
In our questionnaire, Some of their questions have been combined to measure the perceived risk of safety of mobile applications.
Questions to measure intentions not to switch have been based on the article of Burnham, Frels, and Mahajan (2003). The questions have been slightly amended because the mobile services with which our questionnaire is concerned do not yet exist. Respondents now had to answer questions which addressed their future intentions to stay customer and switch from health insurance organization
