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CHAPTER 3 - DEVELOPMENT OF RESEARCH FRAMEWORK
3.1 Research Model
According to the Service Quality Model developed by Parasuraman et al. (1985), we propose that there is a fit between mobile service mobility design and customer expectation that could generate better service performance, as figure 3-1 shows.
Figure 3-1. Research Framework
In our study, we used the fit as moderation concept that illustrates that customers with certain characteristics tend to have higher expectations of services they receive, thus moderating the effect between mobile services design and service performance.
With regard to mobile service design, we used the extended mobility concept to focus on three types of mobility: spatial, temporal, and contextual mobility (Kakihara and Sorensen, 2001). Additionally, based on the customer variability framework (Frei 2006), we identified four individual differences as the antecedents of customer expectation.
Individual Difference
Personal Innovativeness
Need for Interaction
Self-Efficacy
Previous Experience
Mobile Service Mobility Design
Spatial Mobility
Temporal Mobility
Contextual Mobility
Service Performance
Relational Performance
Operational Performance
Service Experience Service
Design Expected
Service
Fit
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We measured service performance using three dimensions: operational, relational, and experiential. Goodhue (1995) has argued that TTF leads to higher operational performances such as utilization, accessibility, and compatibility. Pujari (2004) has worked on B2B (business-to-business) customer satisfaction in the service encounter and indicates that operational benefits such as improved speed, improved process efficiency, saved labor hours, technology reliability, real-time accessibility, convenience, and quick help are sources of satisfaction when adopting self-service technology. Besides operational performance, we also consider relational performance that measures the service firm’s closeness to customers and involves service providers who proactively seek to understand customers’ expectations and needs (Bhappu and Schultze, 2006; Stank et al., 1999). Gwinner et al. (1998) have specified that confidence benefits, social benefits, and special treatment benefits are the most important relational benefits. Moreover, we argue that service experience is another essential dimension of service performance. Pine II and Gilmore (1998) have suggested that with the rise of the experience economy service, providers should turn to offering and selling appealing experiences. Poulsson and Kale (2004) describe experience as sensations and feelings that include personal relevance, novelty, surprise, learning, and engagement. Consistent with the Service Quality Model, we believe that better mobile service design will reduce the gap between customer expectations and management’s perceptions of those expectations, which will have an impact on the customer's evaluation of service performance. A more detailed discussion follows.
3.2 Mobile Service Mobility Design 3.1.1 Spatial Mobility
Spatial mobility denotes the movement of objects (which could be anything from information, signals, symbols, or people to mediums such as Internet or mobile technology) without the limitations of space. Spatial mobility connects everyone within a virtual community (Kakihara and Sorensen, 2001), giving mobile workers greater flexibility so that that they can complete work anywhere. Because the traditional working space has been extended and the information influx via the Internet has changed how we acquire useful knowledge, we no longer depend on wired personal computers, networks, and paper systems. It is much more convenient for people to control the progress of work and exchange information rapidly; therefore, higher service performance is perceived. We develop the hypothesis H1a:
H1a: Higher spatial mobility is positively related to mobile service performance.
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3.1.2 Temporal Mobility
Temporal mobility grants people the ability to structure their activities and plan synchronously or asynchronously through the Internet or mobile technology instead of following the linear 'clock-time' perspective (Ciolfi et al., 2005; Kakihara and Sorensen, 2001). With temporal mobility, we are able to better manage several tasks simultaneously. In other words, we can do many tasks at the same time, and there are no obtrusive events we must react to immediately. Instead of needing to pay full attention and react instantly to service messages as they arrive, the real-time information and flexible work allocation allows us to work effectively and efficiently.
Precise and updated information exchanges lead to fewer errors of communication, and flexible task management accelerates working processes as well as saving time.
We develop the hypothesis H1b:
H1b: Higher temporal mobility is positively related to mobile service performance
3.1.3 Contextual Mobility
Contextual mobility refers to the situation and environment in which people perform their activities. It provides an understanding of in what way and under what circumstances the activity is being performed via the Internet or mobile technology (Basole, 2004; Ciolfi et al., 2005). People with different backgrounds in different locations have various resources and constraints. Contextual mobility focuses on satisfying these different requirements in the mobile service context. Many service providers embrace contextual mobility in an attempt to bring customers unique value and higher satisfaction. Mobile services with high contextual mobility offer customers tailor-made information, notification, or configuration in different contexts according to customers’ habits and preferences. With contextual mobility, customers no longer receive a mass of useless information; furthermore, customized information and utilities not only adapt to the different constraints and situations but also save time and improve work efficiency. Therefore, we develop the hypothesis H1c:
H1c: Higher contextual mobility is positively related to mobile service performance
3.3 Individual Difference
In the previous chapter, we have shown how individual differences create customer variability in the service encounter. In the following section, we explain how these individual differences act as moderators between mobility design and service performance.
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3.2.1 Personal Innovativeness
Agarwal and Prasad (1998) have defined personal innovativeness as the willingness of an individual to try out any new information technology from the perspective of domain-specific innovativeness. Personal innovativeness includes several component behaviors such as seeking novelty, seeking an optimal stimulation level, seeking variety, and having exploratory tendencies (Yang, 2005). It means that customers are willing to take risks and be active seekers of new ideas or innovativeness. Some researchers postulate that individuals with higher levels of innovativeness are expected to develop more positive perceptions about intentions to use innovative IT (Lu et al., 2008). The result is similar when applied to the mobile context. For example, Yang (2005) conducted a survey of 866 Singaporean students, examining their decision-making processes when adopting M-commerce. The results indicated that personal innovativeness had significantly positive effects on perceived usefulness and perceived ease of use. Because people with higher personal innovativeness look forward to innovative services and have positive intention toward using mobile services, these people may feel the service even more useful when it incorporates a high degree of mobility. That is, customers cannot only use multiple mobile services at the same time but can also experience various interaction styles and highly customized utilities. We expect that such innovative designs can fulfill the needs of individuals with high innovativeness; therefore, we hypothesize:
H2：Higher levels of mobility design will be more positively related to mobile service performance when users are those who request high levels of innovativeness
3.2.2 Need for Interaction
The need for interaction with service employees highlights the importance of human interaction to the customer in service encounters (Dabholkar, 1996). Many customers evaluate the quality of the services by human contact in a service delivery instead of using machines that dehumanizes the interaction (Dabholkar, 1996; Dabholkar and Bagozzi, 2002). While Curran and Meuter (2005) point out there is no evidence to support that need for interaction is negatively related to attitude toward self-service technology (SST), Meuter et al. (2005) find out that need for interaction have negative effects on consumer readiness to try SST. Derived from this finding, we can expect that while people with a high need for interaction lack the motivation to adopt mobile services, they probably indulge in mobile services with more interactive and fluid communication design, highly adaptive functions that offer real-time interaction, and
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a friendly and unimpeded user experience (thus improving their work performance and satisfaction). We therefore hypothesize:
H3: Higher levels of mobility design will be more positively related to mobile service performance when users are those who need high levels of interaction
3.2.3 Self-Efficacy
Self-efficacy is an individual’s assessment or confidence of his/her capabilities in dealing with any situation (Dabholkar and Bagozzi, 2002; Oyedele and Simpson, 2007). Dabholkar and Bagozzi (2002) found that people with higher self-efficacy attenuated the relationship between ease of use and their attitude toward using a technology-based self-service. Lee et al. (2007) have also mentioned that computer self-efficacy is the major factor impacting the task–technology fit of applying PDA technology. We can expect that users with a higher computer self-efficacy have a greater willingness to use new computer technology to assist with tasks. As a result, they are more likely to be interested in mobile services with higher mobility because they can expend less effort in dealing with the potentially more complicated operations and quickly get used to doing work with the mobility functions provided.
Thus, the following hypothesized is set forth
H4: Higher levels of mobility design will be more positively related to mobile service performance when users are those who have high levels of self-efficacy
3.2.4 Previous Experience
Zeithaml et al. (1993) proposed that customers’ previous exposure to certain services that they had used has a positive impact on their expected services. Previous experience with mobile services can shorten the learning curve because people are familiar with the service operation. Armed with more relevant knowledge and less dependent on assistance, people who have had previous service experience can properly execute mobile services with high mobility and generate better performance.
Hence, we put forward the following hypothesis:
H5: Higher levels of mobility design will be more positively related to mobile service performance when users are those who have high levels of past experience