User acceptance of location-based social networking services An extended perspective of perceived value

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1 The current issue and full text archive of this journal is available at User acceptance of location-based social networking services An extended perspective of perceived value Jieun Yu, Hangjung Zo and Mun Kee Choi Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea, and Andrew P. Ciganek University of Wisconsin Whitewater, Whitewater, Wisconsin, USA Location-based social networking 711 Received 12 December 2011 First revision accepted 15 July 2012 Abstract Purpose The purpose of this paper is to develop a research model examining users perceived value of a location-based social networking service (LB-SNS) through hedonic, utilitarian, and social values. This study investigates the impact for each type of perceived value on user satisfaction, behavioural intention to use, and word-of-mouth for LB-SNS. Design/methodology/approach Data were collected from 172 Korean smartphone users with experience using LB-SNS. This study employed PLS to test the proposed model and corresponding hypotheses. Findings A positive influence exists for each type of perceived value on satisfaction with hedonic value having the strongest relationship. Hedonic value is positively correlated with behavioural intention to use LB-SNS and positive word-of-mouth while social value affects positive word-of-mouth. Utilitarian value did not influence either behavioural intention to use LB-SNS or positive word-of-mouth. User satisfaction has a significant influence on both behavioural intention to use LB-SNS and positive word-of-mouth. Research limitations/implications This study is at the forefront of research focused on LB-SNS adoption, extending beyond the utilitarian-hedonic value dichotomy to include a social dimension. This study confirmed that perceived value is an antecedent of satisfaction, which leads to behavioural intentions. Practical implications The advantages and benefits of LB-SNS should be emphasised to increase users perceived value. LB-SNS providers can improve user satisfaction by increasing the hedonic, utilitarian, and social value of their services. Organisations should seek out and explore the possibilities of marketing campaigns through LB-SNS. Originality/value This study is the first empirical study examining user acceptance of LB-SNS incorporating users perceived value satisfaction and behavioural intentions Keywords Perceived value, Hedonic value, Location-based social networking services, Social value, Utilitarian value, Word-of-mouth Paper type Research paper Introduction The market for location-based services (LBS) has been slow to take off (Ince, 2007). A number of signs indicate that LBS are on the verge of tremendous growth. Gartner predicts that LBS will be one of the most disruptive technologies in the next few years Online Information Review Vol. 37 No. 5, 2013 pp q Emerald Group Publishing Limited DOI /OIR

2 OIR 37,5 712 (Shen et al., 2009). The users of LBS in the world are expected to grow from 96 million in 2009 to almost 800 million by the end of 2012 while revenue generated by consumer LBS is forecast to reach $13.5 billion in 2015 (Gartner, 2012). Smartphones are becoming more prevalent and is a key to the growth in LBS. The location-based social networking service (LB-SNS), a type of mobile social networking service (SNS), represents the integration of location-based information and social networking and has emerged as one of the killer applications for smartphones. LB-SNS capture social structures in a new way by documenting a physical history of events and interests in common with others inferred from location-tagged data (Zheng, 2011). LB-SNS are a mix of location-awareness, a recommendation engine driven by crowdsourcing, a game-like rewards system, and a location-based mobile advertising revenue model. LB-SNS provide game elements, competition and an incentive mechanism to stimulate users and increase service usage. A strong social component drives usage of LB-SNS, which may not be adequately captured in existing research models. Three types of LB-SNS providers exist including traditional SNS (e.g. Facebook and Twitter), web service providers (e.g. Yahoo and Google), and specialised LBS providers (e.g. Foursquare and Gowalla). Users may want to flaunt location information with their friends when they visit prestigious venues such as famous places and expensive restaurants. Users can also leave feedback, receive benefits, and obtain information from local businesses. Foursquare users gain points when they check-in to an existing location, add new locations, or provide tips to others about a location. Users are automatically notified of user-generated tips or prizes for nearby locations whenever they check-in. Shops target consumers in the vicinity of their businesses by pushing promotional messages. Researchers have examined SNS in the context of user adoption, user satisfaction, and users perceived value. This study builds upon previous research, which primarily examines hedonic and utilitarian value, by incorporating social value. The objectives of this study are: to examine user perceived value of LB-SNS through hedonic and utilitarian values as well as through social values; and to investigate the impact of each perceived type of value (hedonic, utilitarian, and social) on user satisfaction, behavioural intention to use, and word-of-mouth for LB-SNS. Literature review Perceived value Perceived value is an important concept for understanding user behaviours such as service adoption or shopping behaviour. Perceived value is difficult to define and measure but the most common definition is a ratio or trade-off between quality and price, i.e. value for money. Zeithaml (1988) defined perceived value as the consumer s overall assessment of the utility of a product (or service) based on perceptions of what is received and what is given. Value represents a trade-off between the salient get and give components though what is received (volume/quality/convenience) and what is given (money/time/effort) varies across consumers. Prior studies have proposed several types of perceived value, which is a multi-dimensional construct. Sheth et al. (1991) created an extensive framework viewing perceived value as having social, emotional, functional, epistemic and conditional dimensions. Babin et al. (1994) regarded perceived value as comprising

3 hedonic and utilitarian value while Teke et al. (2010) considered the functional, emotional, and social dimensions of perceived value. Sweeney and Soutar (2001) found that multiple value dimensions emotional, social, quality/performance, and price/value for money explain consumer choice better both statistically and qualitatively. Batra and Ahtola (1990, p. 159) stated that consumers purchase goods and services and perform consumption behaviours for two basic reasons: (1) consummatory affective (hedonic) gratification (from sensory attributes) and (2) instrumental, utilitarian reasons. Individuals adopt information technology (IT) as they perceive the value of obtaining the utility it brings and gain enjoyment from it (Lin and Lu, 2011). Both intrinsic and extrinsic factors influence perceived value and behavioural intentions (Rogers, 1995). Hedonic and utilitarian values are commonly discussed in the literature while social value is much less frequently addressed as a perceived value dimension (Sheth et al., 1991; Holbrook, 1999; Sweeney and Soutar, 2001; Pura, 2005; Turel et al., 2007, 2010; Lu and Hsiao, 2010; Hsiao, 2011). Perceived value is defined as a multidimensional construct consisting of hedonic, utilitarian, and social value, which differs from the generally used Sweeney and Soutar (2001) definition. Location-based social networking 713 Consumer satisfaction and word-of-mouth Satisfaction is a post-consumption evaluation based on a comparison between the pre-consumption expected value and the post-consumption value after the purchase or use of a service or product (Oliver, 1981). Performance-specific expectation and expectancy disconfirmation are two important factors in satisfaction decisions (Oliver, 1977; LaTour and Peat, 1979; Oliver, 1981, 1993). Consumers compare their expectations to their perceptions of consuming a product or service. A positive disconfirmation and satisfaction exists if perceptions exceed a consumer s expectations. Satisfaction also influences positive future behavioural intentions (Oliver, 1981). Intention to repurchase, word-of-mouth, and willingness-to-pay behaviours are components of a multidimensional measure of behavioural intentions (Zeithaml et al., 1996) and behavioural intentions are consequences of perceived value (Zeithaml, 1988). This study focuses on behavioural intention to use continuously and word-of-mouth as specific forms of behavioural intentions. Willingness-to-pay was not considered as a component of behavioural intention since LB-SNS are generally free services. Word-of-mouth (WOM) is an activity which may require consumers to engage in attribution analysis, recall, and interpretations of events as well as communication and the sharing of meaningful information with others (Weiner, 1985). WOM is a consequence of emotional responses to consumption situations (Swan and Oliver, 1989) and could be positive, neutral, or negative (Anderson, 1998). WOM is a credible and powerful source of information in the marketing field. Motivation to engage in positive WOM behaviour may differ from individual to individual. Some individuals engage in WOM for self-enhancement and others to gain social status (Pihlström and Brush, 2008). WOM communication operates based on social networking and depends on the families, friends, and others in a person s social network ( Jansen et al., 2009).

4 OIR 37,5 714 Research model and hypothesis development A theoretical model is presented in Figure 1. A comprehensive framework is proposed to examine the influence of perceived value on user satisfaction and ultimately behavioural intentions. Perceived value is composed of three value components; hedonic, utilitarian, and social. Satisfaction and behavioural intention Prior studies in the marketing and IS fields found that user satisfaction positively affects the consumer s decision to repurchase products or continuously use services, including mobile internet services. Bhattacherjee (2001) proposed an expectation confirmation model of IT continuance and showed that user satisfaction with initial IS use was positively related to IS continuance intention. Thong et al. (2006) expanded Bhattacherjee s model and confirmed that satisfaction had a significant effect on mobile internet service users continuance intention. Lin and Shih (2008) developed a model of m-commerce continuance intention and confirmed a significant positive relationship between satisfaction and continuance intention. Ng and Kwahk (2010) examined the determinants of mobile internet service continuance and verified user satisfaction as one of the determinants of perceived value. Individual degree of satisfaction with service experience is the key antecedent of WOM (Anderson, 1998) and satisfied consumers generate positive WOM (Bitner, 1990). Zeithaml et al. (1996) found that customers who were pleased with the service were likely to spread favourable WOM communication. Anderson (1998) developed a utility-based model of the relationship between customer satisfaction and WOM. Babin et al. (2005) explained positive effects between Korean restaurant consumers Figure 1. Research model

5 satisfaction and positive WOM. Yang and Peterson (2004) investigated the relationship among online banking service users perceived value, satisfaction, and loyalty, finding that loyal customers were inclined to disseminate positive WOM to others. Users satisfied with LB-SNS will develop stronger behavioural intentions to use them and positive WOM given a positive value assessment of LB-SNS. This study hypothesises that: H1a. H1b. User satisfaction will positively influence behavioural intention to use LB-SNS. User satisfaction will positively influence positive word-of-mouth of LB-SNS. Location-based social networking 715 Hedonic value Hedonic value is an individual affective and emotional response and results from fun and playfulness (Babin et al., 1994). Emotion is important in the overall value of service contexts (Mathwick et al., 2001; Turel et al., 2007). Hedonic value can be derived from the interaction with technology itself (Sherman et al., 1997). Seeking pleasurable and joyful experiences is recognised as a basic personal desire (Rokeach, 1973). Perceived enjoyment is an intrinsic motivation for adopting IT (Davis et al., 1992; Van der Heijden, 2004; Venkatesh, 2000; Hong and Tam, 2006; Sledgianowski and Kulviwat, 2009; Lin and Bhattacherjee, 2010) and is the extent to which the activity of using a specific IT system or product is perceived to be enjoyable in its own right, aside from any performance consequences resulting from the system or product use (Venkatesh, 2000). Enjoyment and fun seeking are motives for users to use mobile services (Leung and Wei, 2000; Pagani, 2004; Nysveen et al., 2005). Van der Heijden (2004) found that perceived enjoyment was a strong predictor of usage intentions in an entertainment context. Gibson and Cory (2005) found that convenience and enjoyment were the primary drivers for consumers to use mobile LBS. Users who find LB-SNS fun and enjoyable will be satisfied with the service and will continue to use the service in the future. Users that gain higher hedonic value through an enjoyable experience are more motivated to share their experiences with others and encourage friends and family to use the service (Babin et al., 2005). This study hypothesises that: H2a. The hedonic value of a LB-SNS will positively influence overall satisfaction with the service. H2b. The hedonic value of LB-SNS will positively influence behavioural intention to use LB-SNS. H2c. The hedonic value of LB-SNS will positively influence positive word-of-mouth. Utilitarian value Utilitarian value comes from instrumental and functional benefits (Hirschman and Holbrook, 1982). Utilitarian value is related to the task-specific, efficient, and economical aspects of products or services. Utilitarian value incorporates cognitive aspects of attitude, such as the economic value for money and judgements of convenience and time savings (Ha and Jang, 2010). Convenience and task fulfilment are major enticements to use mobile services (Pura, 2005). Perceived usefulness is an

6 OIR 37,5 716 extrinsic motivation for adopting IT (Davis et al., 1992; Venkatesh, 2000) as well as an important determinant for the adoption of mobile services (Pagani, 2004; Nysveen et al., 2005; Hong and Tam, 2006; Kim et al., 2007; Mallat et al., 2008). Utilitarian value increases when a task is completed more efficiently and effortlessly (Griffin et al., 2000). Users perceive utilitarian value from LB-SNS by acquiring useful information about places to visit from the comments of others. WOM is associated with cognitive processes such as perceptions of value (Swan and Oliver, 1989) and a relationship is possible between utilitarian value and positive WOM (Ha and Jang, 2010). This study hypothesises that: H3a. The utilitarian value of a LB-SNS will positively affect overall satisfaction with the service. H3b. The utilitarian value of LB-SNS will positively influence behavioural intention to use LB-SNS. H3c. The utilitarian value of LB-SNS will positively influence positive word-of-mouth. Social value Social aspects are accounted for in many ways, such as through social value, social influence, subjective norms, and social image. Social value is one component comprising overall perceived value. Sweeney and Soutar (2001, p. 211) defined social value as the utility derived from the product s ability to enhance social self-concept. Individuals enhance their self-concept if they use a product or service perceived as trendy and innovative, which can signal that the user belongs to a particular social class. Social influence is defined as the degree to which an individual perceives that important others believe he or she should use the new system (Venkatesh et al., 2003, p. 451). Social influence is represented by subjective norms and social factors (Thompson et al., 1991). Innovation diffusion theory posits that the desire to gain status or image is an important factor in innovation adoption (Rogers, 1995). Image is a predictor of utilitarian systems usage (Moore and Benbasat, 1991). Social image, derived from Rogers theory, is the extent to which users may derive respect and admiration from peers in their social network as a result of their IT usage (Lin and Bhattacherjee, 2010). Sweeney and Soutar s (2001) concept of social value is similar to the concept of social image because it stresses self-image as viewed by others. Social image is important where systems act as media for communication and social interaction (Venkatesh et al., 2003). Social image has a significantly greater effect than subjective norms in motivating hedonic system usage because power users (those who get high scores or at a higher gamer level) derive a substantial amount of reputation and prestige in their community due to their ability to help others use systems better (Lin and Bhattacherjee, 2010). Social image places an emphasis on being shown to others whereas social influence considers others opinions as important. Social value combines social image and social influence and is defined as the enhancement of a person s self-concept and gratification tied to the beliefs of salient others in one s social network. Prior studies of mobile services have not supported relationships with social value. Turel et al. (2010) identified three value drivers in the context of mobile phone

7 ringtones, finding that social value did not have an impact on overall value. Pihlström and Brush (2008) found a direct relationship between individual value dimensions including social value and post-purchase behaviour regarding a mobile entertainment service. Social value had a stronger effect on WOM but did not influence repurchase intentions. Pura (2005) did not find a significant relationship between social value and commitment to location-based mobile services. Mobile service users tend to express personality, status, and image in public contexts (Leung and Wei, 2000). LB-SNS are a new and innovative service so using LB-SNS may position individuals as trendsetting. The desire for social outcomes is more important for earlier adopters than later adopters (Venkatesh and Brown, 2001). Users develop and maintain personal or social relationships with others through SNS (Lin and Lu, 2011). LB-SNS enable users to identify their physical location and their opinion of locations to visit as well as share related information. The desire for social outcomes is fulfilled when people check-in to places and share that information with others using LB-SNS. People share information because they find it intrinsically satisfying. Individuals may gain indirect benefits from sharing information with others because it helps to solidify their social position (Walsh et al., 2004). People who have a sociable personality may provide information to others because they want to share their joy and experience positive feelings when utilising the service. Self-enhancement is an important motivator for engaging in positive WOM (Sundaram et al., 1998). Sharing location-tagged data with others may enhance the service experience and improve self-esteem ( Jones et al., 2006). This study hypothesises that: H4a. The social value of a LB-SNS will positively affect overall satisfaction with the service. H4b. The social value of LB-SNS will positively influence behavioural intention to use LB-SNS. H4c. The social value of LB-SNS will positively influence positive word-of-mouth. Location-based social networking 717 Research methodology Data collection The research model was verified and analysed with an online survey. The survey respondents consisted of 222 smartphone users with experience using LB-SNS. Individuals without LB-SNS experience were asked not to respond to the survey, as non-users usually have unrealistic perceptions of services (Pura, 2005). Respondents received a monetary coupon as an incentive for participating in the survey. A total of 172 responses were identified after data filtering to eliminate invalid responses. Table I lists the respondents demographic characteristics. The demographic characteristics resemble the Korean Wireless Internet Usage Survey (2010) results that indicate males (68.3 per cent) and the 20 to 39 age group (79.8 per cent) comprise the majority of smartphone users. Instrument development The measurement items were developed based on existing items that exhibited validity and reliability (see the Appendix). Six of the 28 measurement items were removed from

8 OIR 37,5 718 Table I. Respondent characteristics Respondents Characteristics n % Gender Male Female Age (years) þ Education Middle school High school College or university Advanced degree Monthly income ($) None Less than 1, ,000-2, ,000-3, ,000 þ Occupation Official worker Service worker Specialist Student Homemaker Other LB-SNS use per day Once times times Over Notes: n ¼ 172: Education: Highest level of education attained the analysis due to relatively low loadings on their designated factor. The measurement model included 22 items describing six latent constructs: (1) hedonic value; (2) utilitarian value; (3) social value; (4) satisfaction; (5) behavioural intention to use; and (6) word-of-mouth.

9 Items from Babin et al. (1994) for hedonic and utilitarian value were adopted. Social value was captured using items related to social image from Moore and Benbasat (1991) and social influence from Venkatesh et al. (2003). Items for satisfaction were adopted from Babin and Griffin (1998). Four items for behavioural intention to use were selected from Davis (1989). Three items for word-of-mouth were taken from Zeithaml et al. (1996). All items were measured using a seven-point Likert scale from strongly disagree to strongly agree. Location-based social networking 719 Data analysis and results Analysis Partial Least Squares (PLS) was employed to test the proposed model and corresponding hypothesis tests, which is appropriate given the sample size (n ¼ 172), the focus on each path coefficient, and the focus on variance explained rather than overall model fit (Chin et al., 2003). Measurement model Confirmatory factor analysis was conducted to test the convergent validity of each construct. Table II lists the cross-loadings of all items which loaded highest among their own factors. Measurement item and construct statistics are summarised in Table III. Convergent validity was assessed by examining the factor loadings for each item in the measurement model, the significance level for each loading, the reliability, and average variance extracted (AVE) for each construct. All factor loadings exceeded 0.60, the minimum required to assure convergent validity of constructs (Anderson and Measurement item Hedonic value Utilitarian value Social value Satisfaction Behavioural intention to use WOM HV HV HV HV UV UV UV UV SV SV SV SV SV SAT SAT BI BI BI BI WOM WOM WOM Table II. Construct cross-loadings

10 OIR 37,5 Construct Items Factor loading Std error t-value AVE (.0.5) Composite reliability (.0.6) Cronbach s alpha (.0.7) 720 Table III. Indicator variable loadings Hedonic value HV (HV) HV HV HV Utilitarian value UV (UV) UV UV UV Social value (SV) SV SV SV SV SV Satisfaction (SAT) SAT SAT Behavioural BI intentions to use BI (BI) BI BI Word-of-mouth WOM (WOM) WOM WOM Gerbing, 1988). Cronbach s alpha for all six constructs exceeded 0.70, which is a general requirement of reliability for research instruments. The AVE for each construct exceeded 0.50 (Fornell and Larcker, 1981), which established convergent validity. The inter-construct correlation matrix (Table IV) demonstrated that the square root of the average variance extracted (AVE) for each construct is higher than the corresponding inter-construct correlations. All of the diagonal values are greater than the off-diagonal correlations in the corresponding rows and columns, which demonstrates discriminant validity. Common method bias may occur when respondents are asked to provide retrospective accounts of their perceptions, attitudes, and behaviours (Podsakoff et al., 2003). Common method biases were assessed using a marker variable. The correlation between constructs and the marker HV UV SV SAT BI WOM Table IV. Construct correlations and square roots of AVE HV UV SV SAT BI WOM

11 variable was not significant (see Table V). Thus common method bias is not a serious concern. Hypotheses testing Structural equation modelling results are presented in Figure 2 and the hypothesis tests are summarised in Table VI. Of the 11 hypotheses, eight were supported. A bootstrapping re-sampling technique was employed to calculate the corresponding t-values for each hypothesised relationship. Satisfaction was a significant factor influencing both behavioural intentions to use LB-SNS (b ¼ 0.408, t-value ¼ 4.813, p, 0.01) and positive word-of-mouth of LB-SNS (b ¼ 0.425, t-value ¼ 5.082, p 0.01), supporting H1a and H1b. All perceived value constructs including hedonic value (b ¼ 0.372, t-value ¼ 5.018, p, 0.01), utilitarian value (b ¼ 0.319, t-value ¼ 3.657, p, 0.01), and social value (b ¼ 0.215, t-value ¼ 3.743, p, 0.01) significantly influence Location-based social networking 721 HV UV SV SAT BI WOM Marker variable HV 1 UV SV SAT BI WOM Marker variable Table V. Correlations with marker variable Figure 2. PLS results of the structural model

12 OIR 37,5 722 Table VI. Summary of hypotheses testing results Hypothesis Path coefficient Std error t-value Outcome H1a: SAT! BI Supported H1b: SAT! WOM Supported H2a: HV! SAT Supported H2b: HV! BI Supported H2c: HV! WOM Supported H3a: UV! SAT Supported H3b: UV! BI Rejected H3c: UV! WOM Rejected H4a: SV! SAT Supported H4b: SV! BI Rejected H4c: SV! WOM Supported user satisfaction, supporting H2a, H3a, and H4a, and explaining 66 per cent of the variance. Hedonic value was the strongest factor to affect satisfaction. Only hedonic value affected behavioural intention to use LB-SNS, supporting H2b (b ¼ 0.335, t-value ¼ 3.947, p, 0.01), while support for H3b and H4b was not statistically significant. Hedonic (b ¼ 0.221, t-value ¼ 2.698, p, 0.01) and social value (b ¼ 0.143, t-value ¼ 1.859, p, 0.05) affected positive word-of-mouth of LB-SNS, supporting H2c and H4c, while utilitarian value did not, rejecting H3c. Discussion Findings There are several findings resulting from this research. User satisfaction had a significant influence on both behavioural intention to use LB-SNS and positive WOM which is consistent with the generally accepted belief that user satisfaction is a key determinant of IS continuance intention and customer loyalty (Oliver, 1981; Bitner, 1990; Anderson, 1998; Bhattacherjee, 2001; Yang and Peterson, 2004; Babin et al., 2005; Thong et al., 2006; Lin and Shih, 2008; Ng and Kwahk, 2010). Individuals may not use LB-SNS and disseminate positive WOM in the future without being totally satisfied with the service. A positive relationship between each perceived value dimension and user satisfaction was found, which is consistent with previous research (Babin et al., 1994; Ravald and Grönroos, 1996; Jones et al., 2006; Ha and Jang, 2010; Kuo et al., 2009; Deng et al., 2010; Ng and Kwahk, 2010). LB-SNS provide users with high levels of perceived value and user satisfaction by satisfying a variety of needs from entertainment to productivity to social networking. Hedonic value had the strongest statistical relationship with user satisfaction, which indicates that users receive pleasure from elements of LB-SNS. Users may use LB-SNS more for fun and enjoyment rather than utilitarian and social objectives. Users also experience satisfaction when they record the places they visit and share this information with friends. LB-SNS are still in the early stages of overall diffusion, so users may feel satisfaction when considered an early adopter by others. Utilitarian value did not have a significant statistical relationship on either behavioural intention to use LB-SNS or a positive WOM. One possible reason for this finding is that although users are satisfied with the service s usefulness, such as documenting daily activities or being informed of a friend s location, these utilities are

13 not enough to encourage users to continuously use and recommend others to use LB-SNS. LB-SNS are relatively new and functional benefits such as coupons and discounts from local businesses are not a popular practice. Utilitarian benefits must be increased as insufficient utilitarian value may diminish the intention to continuously use LB-SNS and result in negative WOM. Hedonic value had a positive relationship with behavioural intention to use LB-SNS and positive WOM through satisfaction. This result supports findings that emotional value plays an important role in technology-related service use (Novak et al., 2003) and that hedonic value is derived from the interaction with the technology itself (Sherman et al., 1997). LB-SNS can make users feel a sense of intimacy, pleasure, and interest when they share their location information with friends and communicate with each other about that place. Hedonic value was the most influential value in user satisfaction and the only value to affect behavioural intention to use. Hedonic value also had a stronger effect on positive WOM than social value. Hedonic value is the most significant value for LB-SNS users. Social value did not affect behavioural intention to use LB-SNS, but it had a relationship with positive WOM. This result resembles that of Pihlström and Brush (2008), who found no relationship between social value and repurchase intention in entertainment mobile services but did find a positive relationship between social value and positive WOM. A positive relationship exists because people tend to recommend others to use a new service after they perceive value in it. A person can make a significant impression on others by sharing information about the services that they use and value. The lack of a relationship between social value and behavioural intention to use LB-SNS suggests that trends and fads alone are not sufficient to significantly influence behavioural intentions. Location-based social networking 723 Theoretical contributions This research makes multiple theoretical contributions. This is the first empirical study examining user acceptance of LB-SNS focusing on user perceived value, satisfaction, and behavioural intentions. This study successfully extends the applicability of perceived value to the mobile internet service domain LB-SNS. LB-SNS are a new and innovative service that is expanding in importance with the propagation of the smartphone, but few studies have examined this phenomenon. Some research has focused on location-based services (Pura, 2005) while other research has examined SNS (Zhang, 2010; Zhou et al., 2010; Lu and Hsiao, 2010; Hsiao, 2011). This study is at the forefront of new research examining LB-SNS adoption. This study supports the expansion of the utilitarian-hedonic value dichotomy to include a social dimension. Social value had a positive influence on user satisfaction and positive WOM in the context of social networking services. Future studies related to perceived value or that examine mobile internet services should likewise examine social value, which encompasses both social image and social influence. This study also examined future behaviour incorporating both the behavioural intention to use LB-SNS and positive WOM. This is an important contribution due to the inherently social nature of LB-SNS. Finally, perceived value is a clear antecedent of satisfaction, which leads to behavioural intentions. This study investigated the direct relationship between perceived value dimensions and behavioural intentions despite the fact that this

14 OIR 37,5 724 relationship has received little attention. The necessity of capturing the multidimensional nature of value was supported by the differential value influences on behavioural intention to use LB-SNS and positive WOM. Practical implications The results offer two important recommendations for LB-SNS providers regarding how to satisfy their users with a service and retain them. The advantages and benefits of LB-SNS should be emphasised to increase users perceived value. LB-SNS providers can improve user satisfaction by increasing the hedonic, utilitarian, and social value of their services. LB-SNS providers should provide various strategies for enhancing user enjoyment, utility, and self-concept through the use of their services. More features that can increase user enjoyment should be continuously provided and emphasised as part of a marketing strategy as hedonic value was the most influential factor affecting satisfaction. A second recommendation is for organisations to seek out and explore the possibilities of marketing campaigns through LB-SNS. Local businesses can provide users with a special discount or a free service if a certain number of users check-in to specific locations; utilise user check-in records and behavioural responses in different geographical locations; and profile target consumers with this information to improve the degree and accuracy of their marketing initiatives. Conclusions, limitations and future research This study developed a new research model for perceived value using a new mobile internet service: LB-SNS. The research model offers a clear understanding of how perceived value influences user satisfaction and future behaviour. Hedonic value is the most influential value for a user s adoption of LB-SNS because it has the strongest relationship with user satisfaction and influences both behavioural intention to use and positive WOM. This study has limitations that future research may address. Most of the sample analysed consisted of people under 40 years old who were highly educated, as early adopters tend to be young and educated (Rogers, 1995). A second limitation is the focus on current users perceived value, satisfaction, and future behaviour as it pertained to LB-SNS. A study of perceived value of LB-SNS in prospective users may provide useful insights. Future research should redefine social value to incorporate value from interpersonal interactions through SNS. A longitudinal investigation after LB-SNS become a generally used service would also yield additional information. Utilitarian value is expected to increase after LB-SNS are combined with m-commerce. The degree of utilitarian value and its effect on satisfaction and future behaviour should be different from the study results. Future research should include variables specific to LB-SNS to better explain the perceived value of LB-SNS. Constructs such as mobility and social interactivity are appropriate to consider. Lastly, while this study focuses on LB-SNS, other types of mobile internet services and social services are popularly used by people. Additional empirical studies on perceived value, satisfaction, and future behaviour in various contexts will generate a more complete picture of the dynamics related to mobile internet services.

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