prevails in this service sector vis-à-vis other service sectors. Also, implementation of ‘the mobile number portability’ in October 15, 2008 in Malaysia has made it easier to switch to other service providers. Thus, the following are hypothesized: H1: A high level of switching cost is less likely to make mobile phone users switch to other service providers; and H2: A high level of switching cost moderates the relationship between service satisfaction and service switching. This paper will discuss the results of these two hypotheses tested using linear and moderated regression analysis. Data was obtained using a sample of about 500 employees and students of five public universities and two private universities in Malaysia. Findings from this study will develop insights to better strategize and effectively implement loyalty programs and so, prevent their customers from switching. Keywords: switching behavior, service quality, consumer satisfaction, mobile phone service usage Field of research: consumer behavioral aspects of marketing, mobile phone service

SERVICE SWITCHING AND SWITCHING TELECOMMUNICATIONS INDUSTRY

COST

IN

THE

MOBILE

Although switching is a common scenario in most service industries (Griffin & Lowenstein, 2001), it is more prevalent in telecommunication services (Lee & Murphy 2005). For example, the annual switching rate ranges from 20% to 40% in most of the global telecommunication service companies (Berson et al., 1999; Madden et al., 1999). Until two years ago, mobile service users in Malaysia faced significant costs in switching from one service provider (SP) to another because it could cause the loss of phone number known by friends, relatives, acquaintances, and business associates. Therefore, majority of users tended to continue to use the same SP‘s services regardless of their satisfaction/dissatisfaction with the service. To lessen this switching barrier and to increase the competition, Mobile Number Portability (MNP) regulation has been introduced in Malaysian mobile market on October 15, 2008, hence allowing consumers to keep their mobile numbers when switching to another service provider. It is estimated that with the effect of MNP, 11.7% of subscribers will switch to a competing SP on yearly basis (IDC report, 2007). Past studies imply that the MNP will not only affect users‘ behavioural pattern. The telecommunication industry is also deemed to face significant transformation as the SP‘s compete even more fiercely in a very competitive environment (Eshghi et al., 2007). However, in South Korea (Kim et al., 2004) and in USA (Shin & Kim, 2008), it is found that introduction of MNP could not reduce the switching barrier. Hence, to study the effect of ‗switching cost‘ on switching in mobile service usage became the motivation of the present study. Switching cost plays a significant role in the satisfaction/dissatisfaction – switching link , as the present research contradicts previous findings that satisfied consumers tend to be loyal. Cost-benefit models suggest that when customers determine whether to retain with the existing provider, they employ the notion of ‗net utility‘, which is switching benefits minus switching costs (Yang & Peterson, 2004). Therefore, if the switching costs are greater than the increase in utility, consumers prefer not to switch (Lee et al., 2006a). Due to conflicting and thus confusing findings in telecommunication literature regarding the influence of dissatisfaction on switching, the present study
†

Corresponding author e-mail address: aliah@ukm.my

The 2nd International Research Symposium in Service Management Yogyakarta, INDONESIA, 26 – 30 July 2011

136

considers switching cost as the moderator to solve this conflict. More specifically, this study assumes that, although mobile service users are not satisfied with the service, they would stay with the existing provider due to the switching cost effect. However, in-spite of the importance of the moderating influence of switching cost on the satisfaction – switching relationship, to date, no studies have been found to examine this relationship. Following the above discussions, the present study examines the switching cost construct as a quasi moderator in its effect on service switching and on service satisfaction – switching link in the context of mobile service usage. It is expected that the results of this study may be helpful to both policy decision makers and telco‘s in providing information on the costs associated with switching SPs. In the next section, measurements of the study constructs are discussed followed by hypotheses and methodology. Then it describes the study findings and ends with discussion and conclusion, and future research directions.

DEVELOPMENT OF MEASURES FOR THE STUDY CONSTRUCTS
Relevant literature regarding the study constructs are synthesized in brief below, to gain insights about how the working definitions of each construct are developed.

Service Switching
As persistent consumer defection has a devastating impact on a service company‘s performance, the switching phenomenon has got the centre of research interest in past literature (Lee & Cunningham, 2001). However, compared to the goods literature, service literature are less numerous focusing on this issue (Dube & Shoemaker, 2000). In the context of services, switching refers to replacing the current service provider with another. Keaveney and Parthasarathy (2001: 374) defined switching more clearly as ―… where customers continue to use the service category (e.g., online service) but switch from one service provider (e.g., Prodigy) to another (e.g., AOL)‖. On the contrary, another stream of research has defined service switching by regarding the attitudinal component as ‗switching intention‘ (Anton et al., 2007; Lin, 2010; Shin & Kim, 2008). This school of thought assumes that consumers may have the possibility to switch to other brands or suppliers in the future (Lin, 2010). Therefore, the present study operationally defines service switching as the situation where the mobile service users have the intention to switch their present service provider and/or have switched from one service provider but continuing to use the same service. From the above definition, service switching is operationalised to comprise seven items. These items are measured using a five-point Likert interval scale of 1=strongly agree through 5=strongly disagree. A pilot study (n=103) generated an accepted level of internal consistency among these items (α = 0.713). The following Table 1 lists the seven items developed to measure ‗service switching‘:Table 1. The measurement items of ‘service switching’ construct developed & their sources I often switch from one SP to another. I enjoy switching from one SP to another. I am happy with the decision to switch from my previous SP. Though I am used to this SP, I can still stop using it. I often think to switch from XYZ SP. I would not continue to have service from my current service provider. I will switch to another SP if I experience a problem with the 7 XYZ SP‘s service. Note: XYZ refers to the SP that the user uses most.

No. 1 2 3 4 5 6

Items to measure ‗service switching‘

Source(s) Odin et al., 2001 Odin et al., 2001 Self constructed Self constructed Self constructed Shin and Kim, 2008 Zeithaml et al., 1996

Switching Cost
According to Bendapudi and Berry (1997), consumers maintain the relationship with their existing SPs for one of two reasons: switching cost (due to the constraints) or loyalty. Due to the importance of switching cost in maintaining or terminating any relationship, the Economics, Psychology and

The 2nd International Research Symposium in Service Management Yogyakarta, INDONESIA, 26 – 30 July 2011

137

Employee Relations as well as Marketing disciplines have given priority to this construct to be studied in-depth (Lin & Chou, 2004). Switching cost refers to financial, social and psychological losses faced by a consumer when switching to a new SP (Fornell, 1992), whereas, Dick and Basu (1994) defined it as the cost incurred when switching, including time, money and psychological cost. In addition to this, Murray (1991) has considered it as perceived risk, insofar as there are potential losses perceived by consumers when switching providers, such as losses of a financial, performance-related, social, psychological, and safety-related nature. However, in the presence of MNP, different switching costs exist in the telecommunication service industry, such as perception of loss in benefits and performance associated with the switching of service from an existing SP, perception of cost of adaptation, associated with switching to a new SP, and perception of economic cost involved in switching to a new SP (Kim et al., 2004). Therefore, this study has operationalized switching cost as the one-time costs that mobile phone service users associate with the process of switching from one provider to another, which is the combination of loss cost, adaptation cost and move-in cost. From the above definition, switching cost is deemed to comprise seven items. These items are measured using a five-point Likert interval scale of 1=strongly disagree through 5=strongly agree. A pilot study (n=103) shows that the Cronbach‘s alpha coefficient is 0.812 which is above the recommended level by Nunnally (1978). The following Table 2 lists the seven items developed to measure ‗switching cost‘:Table 2. Sources of the measurement items of ‘switching cost’ construct Items to measure ‗service switching‘ If I switch to a new SP, I would lose loyalty points, bonus Ringeets etc. that I have gained with my current SP. 2 If I switch to a new SP, with technology upgrade, I could not use some services (MMS, GPRS, WAP etc.) until I learn to use the new phone and services effectively (different SP). 3 If I switch to a new SMART phone offer, I could not use some services (MMS, GPRS, WAP etc.) until I learn to use the new phone and services effectively (same SP) 4 I should compare all operators‘ attractive alternatives (coverage area, billing etc.). 5 Comparing information regarding all SP‘s offerings with one another takes a lot of energy, time and effort. 6 The monetary cost of closing the account in my current SP is high. 7 The subscription fee for the new membership to a new SP is high. Note: XYZ refers to the SP that the user uses most. No. 1 Source(s) Kim et al., 2004; Aydin and Ozer, 1995b Aydin and Ozer, 2005b; Kim et al., 2004 Self-constructed

Aydin and Ozer, 2005b; Kim et al., 2004 Aydin and Ozer, 2005b; Kim et al., 2004 Aydin and Ozer, 2005b; Kim et al., 2004 Self constructed

Service Satisfaction
Since its inception, satisfaction has become an important construct for marketing scholars (McQuitty et al., 2000) and an important goal to achieve for marketing practitioners due to its numerous benefits (Erevelles & Leavitt, 1992). Some of these advantages include reducing sensitivity to price by lessening price elasticity (Anderson, 1996; Garvin, 1988), minimizing customer loss from fluctuations in service quality in the short term (Fornell, 1992), helping to obtain and sustain advantage in the intensely competitive business environment and enhance customer loyalty (e.g. Brady & Robertson, 2001; Eklo¨f & Cassel, 2001; Edvardsson et al., 2000; Hackl et al., 2000). Hence, it is often assumed that service satisfaction can reduce switching in services. In a seminal work, Oliver (1997: 13) has defined satisfaction as ―…the consumer‘s fulfilment response. It is a judgment that a product or service feature, or the product or service itself, provided (or is providing) a pleasurable level of consumption-related fulfilment, including levels of under or over-fulfilment…‖. Later, Olsen (2007) has elaborated it by stating that it is a consumer‘s personal overall evaluation of satisfaction and pleasure with a given product category – and as a cumulative rather than a transaction-specific construct.
The 2nd International Research Symposium in Service Management Yogyakarta, INDONESIA, 26 – 30 July 2011

138

Taking these two views together, and considering overall satisfaction rather than transactional, the present study defines service satisfaction as a consumer‘s personal overall evaluation of ‗pleasure‘ with the mobile phone‘s service provider and viewing it as a cumulative experience. Moreover, it is the extent to which the mobile phone service user is happy with the overall service provider experience and purchase decision, and whether the experience meets/exceeds his/her expectations. From the above conceptualisation of service satisfaction contextualised for mobile phone service setting, six items are developed. Conducting the pilot study (n=103), resulted in the reliability coefficient of this scale to yield a Cronbach‘s alpha of 0.942, that indicates a high internal consistency among the items. The six items are listed below in Table 3. Table 3. Sources of the measurement items of ‘service satisfaction’ construct Items to measure ‗service satisfaction‘ I am satisfied with my decision to purchase/patronize XYZ SP‘s network service. 2 My choice to use mobile service from XYZ was a wise one. 3 I am fully satisfied with XYZ SP. 4 When I have experienced unforeseen or critical situations, XYZ SP has managed these in a satisfactory manner. 5 This SP meets my pre-purchase expectations. 6 I am happy with the efforts this SP is making towards regular consumers like me. Note: XYZ refers to the SP that the user uses most. No. 1 Source(s) Lim et al., 2006 Lim et al., 2006 Aydin and Ozer, 2005b Leverin and Liljander, 2006 Aydin and Ozer, 2005b DeWolf et al. 2001

Service Switching and Switching Cost
Switching costs are non-utilities that consumers would rather not incur (Burnham et al. 2003). There are theoretical and empirical support found to consider switching cost as the antecedent of service switching (Lee & Cunningham 2001). Table 4 summarizes the relevant literature in the field of service switching and switching cost. Table 4. Summary table that shows past studies relating to service switching and switching cost (arranged by year)
Name of the author (s) and year of publication Bansal, & Taylor, 1999 Lin & Chou 2004 Research context Objective/research question Methodology used in the study Findings

Canada Mortgage services Taiwan Mobile phone services

To develop a model of SP switching To develop and to modify the framework in terms of antecedents and consequences of switching costs in Taiwan. To investigate determinants of customer churn in the Korean mobile telecom service market. To investigate the factors that influence subscribers to stay or migrate.

N=416, Survey, Used EFA, CFA, SEM N=117/ 1215 Convenience sampling, Mail survey

Factors deemed responsible for switching behavior, along with switching intentions. Relational and perceived both SCs affect switching

Ahn, Han, & Lee 2006

Korean Mobile telecom services

N=5789, Secondary data, Used 3 logistic regressions

Accumulated loyalty points (SC) are associated with customer churn probability, whereas, loyalty program membership (SC) is not. Subscribers‘ satisfaction, SC, and habit strength negatively influence switching intentions.

Chuang 2011

Taiwan Mobile phone services

N=873, Telephone survey, Used binary logit mode

The 2nd International Research Symposium in Service Management Yogyakarta, INDONESIA, 26 – 30 July 2011

139

HYPOTHESES AND METHODOLOGY
Although few studies have examined the influence of switching cost on service loyalty, little attention has been paid in relation to service switching. Moreover, in the telecommunication literature, this relationship has yielded mixed results. However, no studies have been found to prove this in the context of Malaysian service industries let alone in mobile service context. Hence, after launching the MNP in Malaysian market, it is deemed necessary to examine the switching cost effect on service switching in the Malaysian mobile market. Furthermore, due to the fact that 60% - 80% ‗satisfied‘ or ‗very satisfied‘ consumers were found to defect in most businesses (Reichheld, 1994), this study proposes switching cost to have a moderating effect on this satisfaction-switching link. Hence, the following hypotheses are developed to verify and refine these relationships: H1: A high level of switching cost is less likely to make mobile phone users switch to other service providers. H2: A high level of switching cost moderates the relationship between service satisfaction and service switching. To establish face validity, the survey instrument was given to ten respondents comprising students, academic and non-academic staff at a public university to gauge their reaction to the items in terms of the clarity of the instructions, understanding of the questions and understanding of the meaning of the words/sentences. The content validity of the questionnaire was established by requesting the opinion and suggestion of five academics who are active researchers and experts in the Marketing discipline (guided by Cavana et al., 2000). Hence, the initial questionnaire was pre-tested and then pilot tested to ensure high validity. The internal reliability consistency was proven above 0.7 for all constructs. Furthermore, to assure construct validity, confirmatory factor analysis was also performed for all study variables on the basis of final collected data. This study targeted post-paid users as the respondents due to three reasons. These are: (i) postpaid users are more committed and involved towards their SPs than prepaid users (Lee et al. 2006b); (ii) for the post paid users, it is required to be subscribed to the particular SP for a minimum range of duration as per the subscription contract (considers as switching cost) (Ranganathan et al. 2006), whereas, pre-paid users do not have such contract and switching SP is as easy as buying a SIM card from a local grocery store (Shmukler, 2009); and (iii) they exhibit high frequency of usage and pay comparatively high call charges, and thus are relevant as respondents for us to examine the loyalty versus switching issue (Shmukler, 2009). The data for analysis was collected in the May-July 2010 period via a structured questionnaire survey, using a sample of 535 employees and students of five public universities and two private universities located in Malaysia‘s multimedia super-corridor region. This yielded a 60.29% questionnaire response rate. The result of ‗hand phone user survey‘ conducted by Malaysian Communications and Multimedia Commission (MCMC) (2005; 2006; 2009) generated the idea that a major portion of the mobile phone users fall in two big categories: employed users (about 53%) and students (almost 25%) and the rest consisted of self-employed, employer and unemployed users (12.2%). Hence, present study tries to capture both categories of users i.e., students and employed persons as the subjects for this study; more specifically, academic and non-academic staff and the post-graduate students. In addition, post-graduate students were preferred since undergraduate students are known mostly to be pre-paid (i.e. not post- paid) mobile service users. For each university, permission was obtained from the dean/head of department of the respective faculties/offices, to conduct the survey. In the next stage, the researcher asked permission from the respective class lecturers to distribute the questionnaire in the post-graduate classes (MBA, Executive MBA, and PhD/DBA classes). Furthermore, questionnaires were given to an administrative officer/in-charge person in each business school and university library to assist in distributing the questionnaires to the prospective respondents and in gathering the completed questionnaires.

THE FINDINGS
A majority of the respondents (68.4%) has been using only one mobile phone SP‘s network whereas, 31.6% have been concurrently using more than one SPs‘ network. This result implies that although most of the users are sole-users, some multi-brand loyals also exist. This is supported by the fact that in Malaysia, about 24% of mobile phone users have multiple subscriptions (MCMC, 2009). Data from
The 2nd International Research Symposium in Service Management Yogyakarta, INDONESIA, 26 – 30 July 2011

140

this study reveal that most of the respondents (49.72%) are users of Maxis, followed by Celcom (37.94%), DiGi (12.15%) and U-mobile (0.2%). This ratio also represents the fact that as per 2009, the number of Maxis users is 42.1%, whereas, Celcom users are 32.5% and 25.4% are DiGi users (Aziz et al. 2009; Said & Adham 2009). In regards to the switching pattern, among 535 participants, majority are found to be loyal (55.3%) and the rest (44.7%) are switchers. Most of the switchers (63.59%) have switched one time from their previous SP, and some respondents (34.73%) have switched from Maxis pre-paid services. The reason most frequently cited for switching the past SP‘s network was ‗high call charges‘ (33.47%), followed by ‗attractive ad and offers of the other SP‘ (17.15%). In terms of gender, the sample indicates a balance somewhat between the males (40.2%) and females (59.8%). All of the respondents are above the age of 18, and most of the respondents (30.8%) fall in the range of 25 – 31 years and the least are 60 years and above (0.4%). On the basis of HPUS (2009), the 20-49 year age range from the frequent and heavy users of mobile phone service and this number is made up of 73.4%. With respect to the ethnic groups, majority are Malay (58.1%), 26.4% are Chinese, 10.1% are Indian and 5.4% are foreigners. These somewhat mirror the composition of the actual consumer mobile phone usage market in Malaysia. According to MCMC 2005, Malay subscribers are 53.9%, Chinese constitute of 32.4%, Indians are 6.3% and the rest are comprised of foreigners and other minorities. With regard to profession, this study‘s respondents are made up of 26.7% academic staff, 24.5% are full-time post-graduate students (24.5%) and the rest (48.8%) are non-academic staff (including administrative and managerial, clerical and technical jobs). It is supported by the fact that the majority of the mobile phone service users are students and employed persons (MCMC, 2005). With respect to monthly income, a majority of the post-paid mobile phone users sampled in this study fall within the range of RM 2,001 – RM3500, followed by RM 501RM2,000 and below RM 500. In this study, bivariate correlation was used to analyse the association among the variables (Diamantopoulos & Schlegelmilch, 1997). Table 5 exhibits the correlation with a two-tailed test of significance pa