DETERMINANTS OF UTILITARIAN VALUE IN SMARTPHONE-BASED MOBILE COMMERCE

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1 Association for Information Systems AIS Electronic Library (AISeL) PACIS 2014 Proceedings Pacific Asia Conference on Information Systems (PACIS) 2014 DETERMINANTS OF UTILITARIAN VALUE IN SMARTPHONE-BASED MOBILE COMMERCE Sujeong Choi Chonnam National University, Kiju Cheong Chonnam National University, Beverly Somera Chonnam National University, Qiying Hao Chonnam National University, Follow this and additional works at: Recommended Citation Choi, Sujeong; Cheong, Kiju; Somera, Beverly; and Hao, Qiying, "DETERMINANTS OF UTILITARIAN VALUE IN SMARTPHONE-BASED MOBILE COMMERCE" (2014). PACIS 2014 Proceedings This material is brought to you by the Pacific Asia Conference on Information Systems (PACIS) at AIS Electronic Library (AISeL). It has been accepted for inclusion in PACIS 2014 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact

2 DETERMINANTS OF UTILITARIAN VALUE IN SMARTPHONE-BASED MOBILE COMMERCE Sujeong Choi, Free21+ e-service Team, Chonnam National University, Gwangju, Korea, Kiju Cheong, College of Business Administration, Chonnam National University, Gwangju, Korea, Beverly Somera, Free21+ e-service Team, Chonnam National University, Gwangju, Korea, Qiying Hao, Free21+ e-service Team, Chonnam National University, Gwangju, Korea, Abstract Given that smartphones are widely used as a key means for m-commerce, this study aims to provide in-depth understanding of smartphone-based m-commerce use. Drawing on TAM, we develop the basic framework of our research model with the three constructs namely, usefulness, ease of use, and m-commerce use. TAM has parsimony, robustness, and generalizability so that it can be widely applied to predict user behavior regardless of particular IT. However, due to these strengths, TAM cannot capture unique characteristics embedded in particular IT. Therefore, this study attempts to expand TAM by including mobile-specific characteristics (i.e., service ubiquity and LBS) and a SST (self-service technology) characteristic (i.e., user control). A total of 164 responses were collected on users having experience in m-commerce. The key findings are as follows: first, the results indicate that TAM is a very useful theoretical lens to predict user behavior in the context of m-commerce enabled by smartphones. Second, the results show that service ubiquity and LBS lead to increased usefulness of m-commerce. Finally, the results demonstrate that user control is positively associated with both usefulness and ease of use. Discussion and implications on the findings are provided. Keywords: TAM, Smartphone, Mobile Commerce, Service Ubiquity, Location-based Service, User Control

3 1. INTRODUCTION Given that smartphones are widely used as a key means for mobile (m-)commerce, this study aims to provide in-depth understanding of smartphone-based m-commerce use. Drawing on TAM (technology acceptance model) proposed by Davis (1989), we develop the basic framework of our research model with the three constructs namely, usefulness, ease of use, and smartphone-based m-commerce use. More specifically, we propose that usefulness and ease of use are main predictors of smartphone-based m-commerce use and ease of use is a determinant of usefulness. TAM has parsimony, robustness, and generalizability so that it can be widely applied to predict user behavior, regardless of a particular IT. However, due to these strengths, TAM cannot capture unique characteristics embedded in a particular IT. Therefore, this study attempts to expand TAM by including mobile-specific characteristics and a self-service technology (SST) characteristic. In this study, these factors are regarded as external variables that are associated with usefulness and ease of use. Smartphones are a typical mobile device widely used to deliver value-added service to customers in m-commerce (Mathwick et al., 2001). Although m-commerce is often conceptualized as an extension of electronic commerce, it is suitable that m- commerce is considered as a new channel that creates unique customer value (Balasubramanian et al., 2002). Recognizing this, traditional offline and/or online-based retailers attempt to develop mobile-specific services able to create new customer value (Kleijnen et al., 2007). Nevertheless, firms fail to obtain a substantial profit from m-commerce. One of the key reasons is that firms do not understand utilitarian value that customers want to obtain from smartphone-based m-commerce (Kleijnen et al., 2007). Thus, it is important to understand what factors involve utilitarian value. In the IS literature, usefulness suggested in TAM is frequently conceptualized as extrinsic motivation that lays emphasis on outcomes obtainable from using a particular IT rather than the use of IT itself (Davis et al., 1992). That is, usefulness represents utilitarian value that users seek to obtain from using a particular IT. Indeed, a majority of studies have focused on m-commerce use. However, little has been known about what factors involve the creation of utilitarian value in smartphone-based m-commerce settings. What are the unique characteristics embedded in smartphone-based m-commerce? From two perspectives, this study explains key determinants of usefulness (i.e., utilitarian value) in the context of smartphone-based m-commerce. To begin with, this study considers service ubiquity and location-based service (LBS) as mobile-specific characteristics. The two variables are further reinforced by the widespread of smartphones. Using smartphones, people can conduct m-commerce anytime and anywhere, irrespective of time and space, accessing to necessary information and service. That is, service ubiquity is realized by the use of smartphones (Lee et al., 2012; Tojib and Tsarenko, 2012). It has been reported that service ubiquity is the most influential factor among other variables, such as ease of use and enjoyment in enhancing users experiential value. Particularly, in the context of mobile service use, time convenience is regarded as a vital factor related to user value (Tojib and Tsarenko, 2012). Thus, this study explores service ubiquity as a key determinant of usefulness in smartphone-based m-commerce use. As another prominent characteristic of mobile devices, location-based service (LBS) has been received considerable attention (Dhar and Varshney 2011; Ho, 2012; Junglas et al., 2008; Lee and Jun, 2005; Li and Du, 2012). LBS refers to services offered based on user profiles (e.g., preferences and demographics) and context information (e.g., location, time, user activities, and weather) (Dhar and Varshney, 2011; Li and Du, 2012). LBS is becoming more widely available by the use of smartphones equipped with GPS (global positioning system). A typical example of LBS offered by smartphones is navigational services (Junglas et al., 2008). People frequently use navigational services to find the quickest route and to receive real-time information on traffic jams. Besides, people use LBS offered by smartphones to find the nearest and cheapest gas station or restaurants when necessary. Thus, LBS can represent a key feature of smartphone-based m-commerce. In this regard, this study examines LBS as another mobile-specific characteristic that influences usefulness. Next, we recognize smartphone-based m-commerce as a typical SST-involved service environment. In the context of SST use, perceived control plays a key role in adopting and using SST. Customers with greater control can determine service outcomes depending on their abilities, needs, and requirements instead of accepting standardized service provided by service employees, using the well-designed SST (Collier and Sherrell, 2010). Besides, SST allows customers to control the speed of transaction, to decide the level of interactivity needed to produce services, and to obtain service outcomes that they want (Dabholkar, 1996). One of the key reasons for choosing the SST-based transaction is that customers can obtain increased user control (Bateson, 1985; Langeard et al., 1981). Therefore, we consider and empirically test user control as one of the key external factors that influence usefulness (i.e., utilitarian value).

4 2. LITERATURE REVIEW 2.1 TAM TAM coined by Davis (1980) has been served as a dominant theoretical lends for a deeper understanding on the acceptance, use, and further continued use of a particular IT (Bhattacherjee, 2001; Venkatesh et al., 2003; 2012). TAM suggests that two beliefs about a particular IT (i.e., usefulness and ease of use) determine user behavior. Usefulness refers to the degree to which a person believes that using a particular system would enhance his or her job performance whereas ease of use refers to the degree to which a person believes that using a particular system would be free of effort. (Davis, 1989, p. 320). Usefulness is often conceptualized as the extrinsic motivation that lays emphasis on outcomes obtainable from using a particular IT rather than the use of IT itself (Davis et al., 1992). Thus, usefulness represents the utilitarian value that users seek to obtain from the use of a particular IT. Davis (1989) argued that usefulness is a more influential factor than ease of use in determining IT use in the workplace that the achievement of goals is highly valued. On the other hand, ease of use supports users to achieve utilitarian value from the use of IT (Davis et al., 1992). TAM is not confined to a particular IT so that it has been applied to predict user behavior in various settings. Although several issues are raised in the application of TAM, such as the exclusion of social factors (i.e., social influence), TAM is one of the most widely used theories to examine user acceptance and use of new IT (Brown and Dennis, 2010; Venkatesh et al., 2003). 2.2 Mobile commerce M-commerce is defined as electronic service transactions that are available due to wireless devices (Kleijnen et al., 2007). Although m-commerce is viewed as an extension of electronic commerce, it should be considered as a separate channel, considering that it can create a new value for customers (Kleijnen et al., 2007). It is important to understand unique characteristics that can create users utilitarian value from mobile services (Kleijnen et al., 2007). One of the most salient features of m-commerce is service ubiquity, which enables users to conduct m-commerce anytime and anywhere (Kleijnen et al., 2007; Nysveen et al., 2005). Regardless of temporal and spatial constraints, people can obtain necessary information on products and services and conduct transactions by accessing to the website with mobile devices (Kleijnen et al., 2007; Lee et al., 2009; Yoo et al., 2012). Thus, the ubiquitous service contributes to the creation of users extrinsic value in m-commerce (Nysveen et al., 2005). With the advanced mobile technologies, firms can timely deliver personalized, customized, and location-based service and maintain a seamless relationship with customers for 24 hours (Tojib and Tsarenko, 2012). Likewise, in the context of m-commerce, ubiquitous and instant connectivity is regarded as a main source of creating user value. Service ubiquity has been reinforced by the spread of smartphones. Service ubiquity due to smartphones allows firms to create new values for customers, and thereby influencing customer behavior, such as m-commerce use. In the context of mobile services including mobile , mobile chat, mobile games, and mobile banking, Tojib and Tsarenko (2012) verified that service ubiquity is positively associated with enjoyment, ease of use, time convenience, and experiential value leading to increased customer satisfaction and actual service use. Additionally, they found the result that time convenience due to service ubiquity is the most influential factor than ease of use and enjoyment in enhancing users experiential value. As such, in the use of mobile services, time is considered as an important factor. Nysveen et al. (2005) argued that advanced mobile technologies enable firms to provide customers with ubiquitous access to relevant information and service and to exchange personalized information with customers, and to create new business opportunities. Lee et al. (2009) developed a measurement instrument for mobile internet service quality considering ubiquitous connectivity. Likewise, service ubiquity enabled by the use of smartphones can be considered as an important factor as far as mobile services are concerned. As another prominent characteristic of mobile devices, location-based service (LBS) has been received considerable attention (Dhar and Varshney 2011; Ho, 2012; Junglas et al., 2008; Lee and Jun, 2005; Li and Du, 2012). LBS refers to services offered based on user profiles (e.g., preferences and demographics) and context information (e.g., location, time, user activities, and weather) (Dhar and Varshney, 2011; Li and Du, 2012). The goal of LBS is to offer personalized mobile transactions to customers by using user information at a certain time and place (Li and Du, 2012). LBS is becoming more widely available by the use of smartphones equipped with GPS (global positioning system). A typical example of LBS offered by smartphones is navigational services (Junglas et al., 2008). People frequently use navigational services to find the quickest route and to receive real-time information on traffic jams. Besides, people use LBS offered by smartphones to find

5 the nearest and cheapest gas station or restaurants when necessary. Thus, LBS enabled by smartphones can represent a key feature of m-commerce. There is a growing body of research and evidence of LBS in the context of m-commerce. Li and Du (2012) asserted that LBS facilitates effective mobile advertising by enabling firms to offer customized, personalized information to targeted customers. Using advanced mobile technology (e.g., location recognition systems), firms easily obtain the context information of customers who access to their mobile services via smartphones so that they use the information for mobile advertising. Applying motivation theory, Ho (2012) verified that individuals intention to use mobile services is determined by intrinsic and extrinsic motivations due to location personalization provided by smartphones. Drawing on task-technology fit model, Junglas et al. (2008) contended that when individuals use LBS for location sensitive tasks (e.g., real-time traffic conditions on route to the airport and coupon announcements when approached retail stores), they can achieve better performance from using LBS. On the other hand, when individuals use LBS for location insensitive tasks, such as wireless stock order and wireless access to digital library, the effect of LBS on individual performance is insignificant. Thus, they concluded that it is important to consider both task characteristics and technology characteristics (i.e., mobility and locatability). Pura (2005) argued that the use of LBS is influenced by various perceived value, such as social value, emotional value, conditional value, monetary value, and convenience value. To predict individuals intention to use LBS, Zhou (2012) drew key determinants (i.e., performance expectancy, effort expectancy, social influence, and facilitating conditions) from UTAUT (unified theory of acceptance and use of technology) by Venkatesh et al. (2003) and expanded it by including privacy concern, perceived risk, and trust. The results showed that effort expectancy and privacy concern were insignificant. 2.3 Self-service Technology (SST) Smartphone-based m-commerce can be considered as a new type of SST. SST refers to technology-based service encounters where customers produce necessary services by themselves without interaction with employees (Meuter et al., 2000). SST includes automated teller machines at the bank, ticketing kiosks, and online shopping and banking. Given that customers create and consume services electronically independent of employee involvement, convenience has been emphasized as a key determinant of SST use (Collier and Sherrell, 2010; Meuter et al., 2000). Convenience denotes the degree of time and effort required to select and use necessary service (Collier and Sherrell, 2010) and includes contextual factors supporting customers from the beginning of the transaction to the completion of it. Berry et al. (2001) highlighted that access convenience, such as location proximity and operating hours determines customers effort to use SST. Meuter et al. (2000) argued that SST satisfaction is dependent on SST ability to handle immediately customer service requests, relative advantages obtainable from the SST use, and its ability of performing services, based on the results of a critical incident study. Collier and Sherrell (2010) asserted that perceived convenience of time and location access is a starting point to facilitate customers SST use. Thus, this study regards smartphone-based m-commerce as one of the typical SSTs in that customers begin and complete the transaction by themselves without contact with service employees. Studies of SST suggest an important factor associated with user value creation and behavior intention in m-ecommerce. It is user control that refers to a belief that users have the ability to manage the whole processes and outcomes of service (Dabholkar, 1996; Kleijnen et al., 2007; Nysveen et al., 2005). Kleijnen et al. (2007) argued that perceived control enhances perceived value of mobile services and thus increases individuals intention to use mobile services. Collier and Sherrell (2010) considered perceived control and perceived convenience as starting points of SST use, and contended that perceived control is associated with various variables, such as speed of transaction, exploration, trust in service provider, and intention to use SST. According to the theory of planned behavior (TPB), perceived control is one of the key predictors along with attitude toward the behavior and subjective norm in predicting individual intention and behavior (Ajzen, 1991). Ajzen (1991) defines perceived behavioral control as people s perception of the ease or difficulty of performing the behavior of interest (p. 183). When people believe that their outcomes are determined by their behavior, they can create better performance. In the context of SST use, perceived control plays a key role in adopting and using SST. Customers can determine service outcomes depending on their abilities, needs, and requirements instead of accepting standardized service provided by service employees, using the well-designed SST (Collier and Sherrell, 2010). Besides, SST allows customers to control the speed of transaction, to decide the level of interactivity needed to produce services, and to obtain service outcomes that they want (Dabholkar, 1996). On the other hand, such SST characteristics impede the adoption and use of SST (Dabholkar et al., 2003). That is, customers are reluctant to use SST when they feel lack of ability to control service generation processes and outcomes using SST. This makes customers frustrated. Likewise, the paradox of self-service experience exists (Collier and Sherrell, 2010). Nevertheless, one of the key reasons for choosing the SST-based transaction is that customers can obtain

6 increased user control (Bateson, 1987). Bateson (1987) argued that people choose the SST-based transaction not because of financial benefits, but because of perceived control. Thus, it is expected that firms promote the use of smartphone-based m- commerce as a type of SST by enhancing user control. 3. RESEARCH MODEL AND HYPOTHESES 3.1 Research Model TAM provides a theoretical foundation for our research model of smartphone-based m-commerce use. In addition, this study attempts to expand TAM by considering mobile-specific and SST characteristics as external variables that influence the two constructs of TAM (i.e., usefulness and ease of use). In other words, we suggest that the use of smartphone-based m- commerce can be better understood when the three different perspectives (i.e., TAM, mobile technology, and SST) are simultaneously considered. Previous researchers have suggested many different types of external variables associated with the two constructs of TAM (Venkatesh, 2000; Venkatesh and Davis, 2000). Venkatesh (2000) shed light on determinants of ease of use upon considering that it is the first obstacle of users to overcome, and classified them into two dimensions: anchor and adjustment dimensions. While the anchor dimension refers to general beliefs about computers and computer and includes computer self-efficacy, external control, and computer anxiety, the adjustment one refers to beliefs that are formed by direct experience with the certain systems and includes enjoyment and objective usability. Venkatesh and Davis (2000) expanded TAM by including determinants of usefulness, such as subjective norm (as a social factor), image, job relevance, output quality, and result demonstrability. The expanded TAM which is called TAM2 considered the moderating effects of voluntariness the relationship between subjective norm and intention to use. That is, they incorporated usage contexts, such as mandatory or voluntary usages, into TAM. They also verified the moderating effect of experience on the relationship between subjective norm and usefulness. In line with these efforts to find external variables, we propose that considering mobile-specific and SST characteristics embedded in smartphone-based m-commerce use is one of the useful ways to expand TAM. Figure 1. Research model 3.2 Service ubiquity and usefulness In a retail setting, the speed of transaction and time efficiency have been regarded as important benefits that customers seek to obtain from using SST (Roulac, 2001). It is asserted that m-commerce contributes to the enhancement of user value by providing customers with real-time and on-demand access to products and services (Kleijnen et al., 2007). In the context of mobile service, customers expect to receive personalized, relationship-based, and time and location-based service (Lee et al., 2007). Nowadays, smartphones are a key means to realize service ubiquity. Smartphones allows firms to maintain constant

7 interactivity with customers 24 hours a day and thus can satisfy their values on time saving and convenience in m-commerce (Tojib and Tsarenko, 2012). Thus, the success of smartphones-based m-commerce lies in customers fingertips. Using handheld smartphones, customers conduct m-commerce anytime and anywhere when needed, which will enhance their utilitarian values. Service ubiquity due to smartphone-based m-commerce strengthens user value because smartphones enable firms to provide constant connectivity with their mobile services along with the localization and customization of service (Hong and Tam, 2006; Kannan et al., 2001). Usefulness represents the extrinsic, utilitarian value that customers seek to obtain from using IT (Davis et al., 1992). Service ubiquity enhanced by the use of smartphones will increase the speed of transaction, which contributes to the creation of user value of time efficiency (Tojib and Tsarenko, 2012). Tojib and Tsarenko (2012) found that service ubiquity greatly increases users experiential value. Smartphone-based m-commerce allows customers to save their time to make a purchase. Collier and Sherrell (2010) argued that access convenience independent of time and place is a key benefit that customers expect to obtain from using SST, such as m-commerce. Kleijnen et al. (2007) verified that time convenience is a core factor leading to increased user value in the use of mobile services. As such, providing customers with service in an efficient and timely manner greatly increases their utilitarian value (Childers et al., 2001). Service ubiquity due to smartphones would enhance usefulness by enabling customers to conduct m-commerce anytime and anywhere irrespective of time and space. In this regard, we set the following hypothesis: H1. Service ubiquity will be positively associated with usefulness. 3.3 Location-based service (LBS) and usefulness Another distinguished m-commerce characteristic that is enabled by the use of smartphones is LBS (Dhar and Varshney 2011; Ho, 2012; Junglas et al., 2008; Lee and Jun, 2005; Li and Du, 2012). That is, LBS is one of the key reasons that people choose smartphone-based m-commerce. Using smartphones equipped with GPS, customers can obtain relevant information based on location and contexts for m-commerce when needed. In m-commerce settings, when firms timely provide location and context-specific services customers feel the services more useful (Lee et al., 2009). For example, when firms offer discounted mobile coupons for restaurants based on location and proximity at lunch time or dinner time, customers perceive that the mobile service more is usefulness (Lee and Jun, 2005). Thus, we assume the positive relationship between LBS and usefulness: H2. Location-based service will be positively associated with usefulness. 3.4 Influence of user control In m-commerce settings, customers should generate and use necessary service by accessing to mobile services without interaction with service employees. Thus, m-commerce can be considered as a typical service using SST. In SST settings, researchers have emphasized user control, which means the ability of managing service processes and outcomes, as a key predictor of value creation (Kleijnen et al., 2007; Nysveen et al., 2005). Besides, researchers have found that to obtain increased user control, people choose to use SST instead of accepting the typical service delivered by service employees (Collier and Sherrell, 2010). With increased user control, customers can determine the level of interactivity with firms and conduct m-commerce when needed. User control is closely related to the speed of transaction in SST settings. When customers understand and take steps involving m-commerce, customers can complete m-commerce successfully and quickly (Collier and Sherrell, 2010). User control would enhance customers perception on usefulness by influencing the goal achievement process (Bateson and Hui, 1987). Kleijnen et al. (2007) found that user control increases experiential value and thus influences intention to use mobile services. That is, when customers have more control on the processes and outcomes of service, they can complete the transaction and obtain desired performance. Therefore, this study proposes that when customers have more control on m- commerce using smartphones, obtainable benefits would be increased. H3a. User control will be positively associated with usefulness.

8 Previous research has noted the positive relationship between user control and ease of use. According to TPB (Ajzen, 1991), user control is suggested a construct drawn from self-efficacy (Bandura, 1977) which refers to the belief that one can successfully conduct their behavior required to obtain certain outcomes. TAM is developed based on TRA (the Theory of Reasoned Action) (Fishbein and Ajzen 1975) so that user control is not considered. Venkatesh (2000) incorporated perceived control into TAM as a predictor of ease of use. Taylor and Todd (1995) defined perceived control as a concept including selfefficacy, technology facilitating conditions, and resource facilitating conditions. Venkatesh (2000) classified user control into two dimensions, such as internal control (computer self-efficacy) and external control (facilitating conditions) and argued that they influence the perception of ease of use. Accordingly, it can be understood that user control closely involves self-efficacy. IS researchers have verified the positive influence of computer self-efficacy on ease of use (Compeau and Higgins 1995; Venkatesh and Davis, 1996). Based on the above discussion, we suggest the following hypothesis: H3b. User control will be positively associated with ease of use. 3.5 Ease of Use and Usefulness Based on TAM (Davis, 1989) and TAM-expanded theories (Venkatesh, 2000; Venkatesh and Davis, 2000), we establish the following three hypotheses (H4, H5a, and H5b). Ease of use has been verified as a predictor of usefulness (Davis, 1989; Venkatesh, 2000; Venkatesh and Davis, 2000). Individuals will give up using a particular IT despite its many benefits when they feel difficulties in understanding and using a particular IT. Accordingly, IS researchers emphasized that IT should be designed for individuals to use easily. In the context of mobile service use, it is found that ease of use determines experiential value (i.e., usefulness) (Nysveen et al., 2005; Tojib and Tsarenko, 2012). Similarly, Kleijnen et al. (2007) verified the negative effect of cognitive effort on experiential value. In other words, when people feel difficulties in the use of m-commerce, the value created from m- commerce would be evaluated to be low. In this regard, we set the following hypothesis: H4. Ease of use will be positively associated with usefulness. 3.6 Usefulness, ease of use, and smartphone-based m-commerce use The two constructs of TAM (usefulness and ease of use) have been verified as key determinants of intention to use, actual use, and further continued use (Bhattacherjee, 2001; Brown and Dennis, 2010; Davis et al., 1989; Venkatesh, 2000; Venkatesh and Davis, 2000). Moreover, IS researchers have found that the effects of the two constructs on user behavior vary depending on IT-used contexts. For example, Davis (1989) argued that usefulness is more influential than ease of use in predicting intention to use in the situation that the achievement of goals is emphasized. On the other hand, van der Heijden (2004) asserted that ease of use is more important than usefulness in determining intention to use in the context of hedonic IS use. This study suggests that both usefulness and ease of use influence actual use. As m-commerce is the situation that customers seek to obtain certain outcomes from m-commerce, usefulness would be considered to be an important determinant of actual use. At the same time, as m-commerce is the SST-enabled situation, customers conduct m-commerce by themselves without service employee involvement so that ease of use would be also considered as to be an important determinant of actual use. Hence, we set the following hypotheses: H5a. Usefulness will be positively associated with smartphone-based m-commerce use. H5b. Ease of use will be positively associated with smartphone-based m-commerce use. 4. METHODS 4.1 Data Collection and Sample To empirically test the proposed research model and hypotheses, we conducted a survey using a self-reported questionnaire method on graduate and undergraduate students in the department of business administration with experience in mobile

9 transaction services, such as mobile banking, mobile shopping, and mobile ticketing, using smartphones. We collected a total of 196 responses. Excluding thirty-two responses with incomplete and missing data, we used a total of 164 responses for the analysis. Female users accounted for 71.3% of the sample. In terms of age, respondents in their twenties accounted for 90.9% of the sample. For types of Smartphone-based m-commerce, 45.2% of respondents are using mobile banking and 40.8% of them are using mobile shopping. The details of the sample are presented in Table 1. Gender Age Duration of Smartphone Usage Types of Smartphone-based M-commerce Category Frequency (%) Male 47(28.7) Female 117(71.3) Twenties 149(90.9) Thirties 9(5.5) Over Forties 6(3.7) Less than one year 15(9.1) One year to less than two years 43(26.2) Two years to less than three years 67(40.9) More than three years 39(23.8) Mobile Banking 71(45.2) Mobile Ticketing 22(14.0) Mobile Shopping 64(40.8) Table 1. Demographics 4.2 Measures We adapted measures from prior research and modified these for a call center setting. All items were measured using a seven-point Likert scale ranging from 1 point (very strongly disagree) to 7 points (very strongly agree). The details of measures are presented in Table 2. Service ubiquity is defined as the extent to which users conduct smartphone-based m-commerce anytime and anywhere, irrespective of time and space, accessing to necessary information and service, and measured with four items drawn from Lee et al. (2012) and Tojib and Tsarenko (2012). Location-based services (LBS) is defined as the extent to which users obtain relevant information based on location and contexts via smartphones and is measured using three items drawn from Lee et al. (2009) and Lee and Jun (2005). User control is defined as the extent to which users are able to determine the details (such as pace of the m-commerce or nature of the information flow) of smartphone-based m-commerce on my own, and measured using four items come from Collier and Sherrell (2010) and Kleijnen et al. (2007). Applying TAM (Davis, 1989), we defined perceived usefulness as users perception of the expected benefits of m-commerce use and perceived ease of use as the degree to which users believe that using m-commerce would be free of effort. Usefulness is measured using three items adapted from Limayem et al. (2007) and ease of use is measured using four items adapted from Venkatesh (2000). Smartphone-based m-commerce use is defined as the extent to which users conduct smartphone-based m-commerce and measured using two items adapted from Brown et al. (2010) 4.3 Assessment of Measurement Model and Common Method Variance We employed the partial least squares (PLS) method with Smart PLS 2.0 to assess the measurement structural models. This method is widely used in IS research for theory testing and can be used to test the relationship between a latent variable and its indicators as well as the structural model. The PLS method imposes minimal constraints on measurement scales, sample sizes, and residual distributions. Therefore, we employed this method because of this study s small sample size.

10 Table 2 and Table 3 show the results for the measurement model. From the analysis results in terms of Cronbach s a, all the constructs used in this study exceeded 0.7, as suggested by Nunnally (1978). This verifies that our constructs have reliability. Moreover, the composite reliability was above 0.8 which exceeds the recommended threshold of 0.7, demonstrating satisfactory reliability. Regarding construct validity, all factor loadings exceeded 0.8 and every item showed the highest loading for its proposed factor, supporting the satisfactory convergent validity. In addition, the values of average variance extracted (AVE) for constructs were above the recommended value of 0.5 (Fornell and Lacker, 1981). Therefore, it can be said that measurement items used in this study had high representativeness for the constructs. Concerning discriminant validity, all the items have higher loadings on their corresponding constructs than any cross-loadings on any other constructs. Moreover, as shown in Table 3, the square root of the AVE exceeded all other cross-correlations, thus supporting the discriminant validity. The common method variance (CMV) was confirmed using a CFA because we used data collected via a self-report survey to measure both independent and dependent variables for a respondent. We compared the six-factor model with a single-factor model (or Harman s one-factor model) in which all indicators loaded on a single factor (Podsakoff et al., 2003). If CMV is substantial, than the single-factor model provides a better fit (Podsakoff et al., 2003). The result showed that the single factor model did not have a good fit (χ2 = , df = 170, GFI = 0.49, CFI = 0.82 and RMSEA = 0.236) when compared with our six-factor model (χ2 = , df = 155, GFI = 0.86, CFI = 0.98 and RMSEA = 0.069), thus providing evidence that CMV is not an issue for this study. Constructs Service Ubiquity Locationbased Services (LBS) User Control Usefulness Ease of Use Items 1. I use smartphone-based m-commerce anytime. 2. I use smartphone-based m-commerce while on the road. 3. I use smartphone-based m-commerce anywhere. 4. I expect that smartphone-based m-commerce would be available to use whenever I need it. 1. I obtain information on the current geographical location needed for m-commerce, using smartphones. 2. I obtain location-specific information based upon where I am, using smartphones. 3. Location-based information offered by smartphones enables me to conduct m-commerce more effectively. 1. Using smartphone-based m-commerce allows me to make a lot of decisions on my own. 2. I have a lot to say about what happens during the smartphonebased m-commerce. 3. I have flexibility when using smartphone-based m-commerce. 4. I have control over the smartphone-based m-commerce when using the mobile channel. 1. Smartphone-based m-commerce is of benefit to me. 2. The advantages of smartphone-based m-commerce outweigh the disadvantages. 3. Overall, using smartphone-based m-commerce is advantageous. 1. The way of using smartphone-based m-commerce is clear and understandable. 2. Using smartphone-based m-commerce does not require a lot of my mental effort. 3. I find smartphone-based m-commerce to ease to use. 4. I easily conduct smartphone-based m-commerce. 1. I widely use smartphone-based m-commerce. 2. I frequently use smartphone-based m-commerce. Factor Loadings SMU Note. All items were significant at the 0.01 level. SMU: Smartphone-based m-commerce use. Table 2. Measurement model assessment AVE Cronbach a Composite Reliability

11 Variables Mean SD Communality Redundancy A B C D E F A Service ubiquity NA B Location-based Service NA C User control NA D Usefulness E Ease of use F SMU Note. All constructs were significant at the 0.01 level. Values along the diagonal indicate the square root of the AVE. SD: Standard Deviation. SMU: Smartphone-based m-commerce use. Table 3. Correlation matrix 4.4 Research Model Assessment and Hypotheses Testing To estimate the statistical significance of path coefficients, we employed a bootstrap re-sampling procedure with 500 subsamples to estimate t-statistics. Figure 2 shows the results for the structural model. Concerning the criteria for assessing the structural model, previous studies have typically employed R 2 values for endogenous constructs. According to Chin (1998), an R 2 value of 0.15 indicates only weak explanatory power, whereas 0.35 and 0.67 are considered to be moderate and substantial, respectively. Therefore, this study s model showed moderate explanatory power: That is, the R 2 values were for usefulness, for ease of use, and for m-commerce use. Previous studies have employed Tenenhaus et al. s (2005) global goodness-of-fit (GoF) criterion as an index for assessing the PLS model globally. The GoF is computed as the geometric mean of average communality and R 2 values. For this study s model, the GoF was 0.612, indicating that the model provided a good fit to the data. Note. ** p < SPC means standardized path coefficient. Figure 3. Summary of hypothesis testing 5. DISCUSSION, IMPLICATION, AND LIMITATION Given that smartphones are widely used as a key means for m-commerce, this study aimed to provide in-depth understanding of m-commerce use. Drawing on TAM, we developed the basic frame of our research model with the three constructs namely, usefulness, ease of use, and m-commerce use. TAM has parsimony, robustness, and generalizability so that it can be widely applied to predict user behavior regardless of particular IT. However, due to these strengths, TAM cannot capture unique characteristics embedded in particular IT. Therefore, this study attempted to expand TAM by including mobile-specific

12 characteristics (i.e., service ubiquity and LBS) and a SST characteristic (i.e., user control). In our study, the three factors are considered as external variables that influence usefulness. Besides, this study considers user control as a determinant of ease of use. The key findings are discussed as follows: First of all, our results indicate that TAM is a very useful theoretical lens to predict user behavior in the context of smartphone-based m-commerce. That is, the results demonstrated that both usefulness and ease of use greatly increased the use of smartphone-based m-commerce. However, contrary to our expectation, the effect of ease of use on usefulness was insignificant. Instead, it is found that user control increases usefulness. These results imply that usefulness is determined more by user control than ease of use in smartphone-based m-commerce. In other words, in the SST-involved setting that customers conduct m-commerce by themselves without service employee involvement, user control is considered to be more influential than ease of use in predicting usefulness. In fact, firms provide the smartphone-specific interface only with very simple and essential functions needed to conduct m-commerce without complicated images and functions. In this sense, customers have no difficulties in using such simple functions provided by smartphones. Rather, customers expect to have more control so that they want to determine more about m-commerce use, such as the speed of transaction, the timing of transaction, and the level of interactivity with firms. Thus, it is important that firms provide customers with more opportunities to make decisions. Moreover, the results support the argument that user control is a key factor of creating utilitarian value that customers expect to obtain from using SST (Kleijnen et al., 2007). Second, the results show that service ubiquity and LBS considered as mobile-specific characteristics lead to increased usefulness of m-commerce. The main purpose of this study is to examine what factors determine utilitarian value (namely, usefulness) of smartphone-based m-commerce. Our results suggest two types of mobile-specific characteristics: service ubiquity and LBS. Due to service ubiquity, people can conduct m-commerce anytime and anywhere, irrespective of time and space, accessing to necessary information and service. Besides, due to LBS, people can obtain relevant information based on location and contexts. Service ubiquity and LBS are further reinforced by the widespread of smartphones. Thus, firms can facilitate usefulness of m-commerce by enhanced service ubiquity and LBS. Although the two factors have been received considerable attention as the typical features of mobile technologies, there is little empirical research on these factors. This study has an academic implication by verifying the effects of the two variables based on TAM, a dominant theoretical lends in the studies of IS adoption and use. Finally, our results show that user control considered as a typical feature involving SST use is positively associated with both usefulness and ease of use. As we discussed above, user control is a key determinant of usefulness and ease of use. Studies of SST have argued that people choose and use SST to have more control in the transaction (Bateson, 1985; Langeard et al., 1981). Smartphone-based m-commerce can allow more control to customers. Thus, it is important for firms to create more functions that allow customers to make decisions. Furthermore, we found the result that user control functions as a determinant of ease of use. When people believe that they have more control in m-commerce, they are likely to perceive ease of use that is directly related to m-commerce use. 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