Understanding users' continuance intention in online ...

1 downloads 0 Views 168KB Size Report
Abstract—This study explores users' continuance intention in online social network by synthesizing Bhattacherjee's IS continuance theory as basis with flow ...
Understanding users’ continuance intention in online social networks Yuan SUN School of Business Administration, Zhejiang Gongshang University Hangzhou, China [email protected]

Xinmin PENG School of Law, Zhejiang Wanli University Ningbo, China [email protected]

ZHU Ya-li Hangzhou Institute of Commerce, Zhejiang Gongshang University Hangzhou, P.R. China [email protected]

Klaus Boehnke Bremen International Graduate School of Social Sciences, Jacobs University Bremen Bremen, Germany [email protected]

Abstract—This study explores users’ continuance intention in online social network by synthesizing Bhattacherjee’s IS continuance theory as basis with flow theory, the unified theory of acceptance and use of technology (UTAUT), and social capital theory. The integrated model was empirically tested with 260 online social network users. The results indicate that all hypothesized paths are supported by our data. Based on the research findings, we offer discussions. Keywords-component; Online social network; continuance intention

I.

INTRODUCTION

Lately, online social network sites (SNS) have increasingly been integrated into people’s daily life [1]. A recent report from Nielsen Online indicates that two-thirds of the world’s internet population visit a social network or blogging site and the sector now accounts for almost 10% of all internet time [2]. Online SNS users spent more time between December 2007 and December 2008 with the growth rate of 18 %[2]. Thus, an important research question has more or less naturally arisen: Why do online SNS users continue to use these websites? To understand the reasons for users’ continuance in the use of an information system (IS) is critical for the long-term viability and the eventual success of the information system [3]. Although there are several comprehensive previous studies on IS continuance in other online contexts (e.g., online game [4]), online SNS differ from other online information systems in that they enable users to articulate and make visible their social network and let users enjoy the online social activity voluntarily [1]. To the knowledge of the authors, there is no study, which systematically assesses the impact of the unique features of online SNS on users’ continuance that has both strong theoretical foundations and empirically validates the critical influential factors. This paper attempts to bridge this gap by synthesizing IS continuance theory as basis with flow theory, the unified theory of acceptance and use of technology (UTAUT), and social capital theory.

This research is supported by start-up research grant from Zhejiang Gongshang University

978-1-4244-8694-6/11/$26.00 ©2011 IEEE

II.

LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT

A. IS continuance theory Based on expectation-confirmation theory (ECT), Bhattacherjee established the IS continuance theory which ascertains that perceived usefulness and user’s satisfaction are two basic and pivotal predictors of IS usage continuance [3]. Furthermore, the theory postulates user-perceived usefulness of IT as having a positive effect on satisfaction with IT [3]. Perceived usefulness, which was first conceptualized and validated by Davis et al. (1989) in IS research [5], is also referred to as performance expectancy in the so-called unified theory of acceptance and use of technology (UTAUT). It is defined as the degree to which an individual believes that using the system will help him or her to attain gains [6]. Online social network users sense usefulness since they can get information and knowledge from other users or the SNS system and through online social activities. Satisfaction is defined as an overall psychological state resulting when the emotion surrounding disconfirmed expectations is coupled with the consumer's prior feelings about the consumption experience [7]. Studies on post-adoption behavior have verified the IS continuance theory in online context, e.g., the online brokerage context [8]. Therefore, we hypothesize accordingly as follows: H1: Users’ perceived usefulness of online SNS use positively influences their continuance intention. H2: Users’ perceived usefulness of online SNS use positively influences their satisfaction with social network website. H3: Users’ satisfaction with online SNS use positively influences their continuance intention. B. Flow theory Csikszentmihalyi’s flow theory ascertains that people seek a flow experience primarily for themselves and will feel a decrease of self-consciousness when gaining hedonic

experience [9]. Researchers adapted this theory into the IS field and pointed out that perceived enjoyment is a key characteristic of the flow experience [9, 10]. Perceived enjoyment refers to the extent to which the activity of using the online SNS is perceived as being enjoyable in its own right, apart from any performance consequences that may be anticipated [11]. In online SNS, users can play online games with their friends, express themselves by uploading photos and writing blogs, interact with friends through embedded instant messaging, or explore other people’s profile, etc. [1]. They can, thus, temporarily escape from their mundane world and immerse in online SNS [12], consequently develop user satisfaction vis-àvis the online SNS [11] which in turn has an influence on user continuance intentions [10]. The hypotheses are thus derived as follows.

trust, which refers to the belief in good intent, competence, and reliability of other online SNS users regarding their activities and those of the online SNS service provider [17]. The more the user trusts other users and the online SNS service provider, the more the user will continue to use the social network. Shared norms represent a degree of consensus in the social system and reflect the commonalities among online SNS members [18]. Shared norms shape online SNS members’ thinking and behavior; they generate propositional attitudes that affect the users’ continuance intention. Tie strength represents the extent and frequency of the interaction and the closeness between ego user and other online SNS members [19]. Strong ties are more accessible and can usually encourage users to keep the ties in online SNS. Thus, the following hypotheses are proposed.

H4: Users’ perceived enjoyment of online SNS use positively influences their satisfaction with online SNS.

H8: Trust positively influences online SNS continuance intention.

H5: Users’ perceived enjoyment of online SNS positively influences their continuance intention.

H9: Shared norms positively influence online SNS continuance intention.

C. The unified theory of acceptance and use of technology (UTAUT) UTAUT, so far considered to be the most comprehensive IT adoption theory, posits constructs of effort expectancy (similar to perceived ease of use), performance expectancy (similar to perceived usefulness), social influence (similar to subjective user norms), and facilitating conditions as the antecedents of the user’s behavioral intention [6]. Considering that facilitating conditions have not been found to directly and significantly affect behavioral intention in UTAUT, we adopt the first three constructs in our study. Effort expectancy is the degree of ease associated with the use of the online SNS by individual users[6]. Online SNS continuance intention could be discouraged when users perceive high levels of effort and obligation as being required for online social activities [13]. Social influence is defined as the degree to which an individual perceives that important others believe he or she should use online SNS [6]. Users who intend to quit the online SNS would be influenced by their friends’ or relatives’ usage continuance pressure. Prior studies have shown that social influence is a significant predictor of the intention to use system (e.g. [14]). Therefore, we propose as follows: H6: Effort expectancy positively influences online SNS continuance intention. H7: Social influence positively influences online SNS continuance intention. D. Social capital theory Nahapiet and Ghoshal (1998) define social capital as “The sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit” [15]. Online social networks provide a typical environment for the capital to be mobilized through the network, offering trust (relational dimension), shared norms (cognitive dimension), and tie strength (structural dimension), three key aspects of social capital [16]. Trust here is conceptualized as generalized

H10: Tie strength positively influences online SNS continuance intention. III.

METHODOLOGY

A. Subjects To test the proposed research model, we conducted a field survey of online SNS users who used the popular social network websites including Facebook.com, Myspace.com, Xiaonei.com, kaixin001.com, and 51.com (The last three are Chinese domestic SNS websites). In total, 260 users responded and filled in the entire questionnaire instrument. Of the respondents, 120 (46.2%) were male and 140 (53.8%) were female. Sixty nine percent of the respondents were 20–29 years old, indicating the relatively young online SNS user group in China at the time the survey was conducted. In terms of profession, about 74 percent of the respondents were university students. In addition, about half of the respondents used online SNS services every day. Finally, we attempted an estimation of the non-response bias by comparing responses from earlycompleting versus late-completing respondents, and the result indicated that our sample was not influenced to any substantial degree by a non-response bias. Construct Operationalization All instruments were adapted from previously published research. Constructs were measured via a multiple-item, sevenpoint either Likert or semantic differential scale, and then were refined by expert judges and in a pilot test. A back-translation between Chinese and English versions was employed to ensure an appropriate translation. In the final version of the questionnaire, we randomly sequenced all items to reduce potential ceiling (or floor) effects as well as order effects that can lead to a response bias of subjects.

B.

We measured continuance intention with three items and satisfaction with four items modified from Bhattacherjee [3]. Perceived usefulness was assess using four items from

Venkatesh et al. [6]. Perceived enjoyment with three items were adapted from Davis et al. [11]. Effort expectancy with four items and social influence with four items were extended from Venkatesh et al. [6]. The three items were employed to measure the trust based on previous studies [17, 20]. Shared norm was assess using three items [18, 21]. Tie strength with three items was modified from Levin and Cross by embedding the feature of the online SNS into the items [19]. DATA ANALYSIS AND RESULTS

IV.

The empirical data was analyzed in PLS Graph 3.00 via the Partial Least Squares (PLS) technique by two stages. In the first stage, all measurement scales were examined for their psychometric properties, then hypotheses testing and model analyses were performed in the second stage. Raw data was used as input to the PLS program, and path significances were estimated using a bootstrapping resampling technique with 100 sub-samples. We evaluated the reliability, convergent validity and discriminant validity of all our measurement scales in the first stage. All Cronbach’s alpha coefficients exceeded .70 and composite reliability exceeded .80, indicating good reliability for our measurement scales [22]. In addition, square roots of the average variance extracted (AVE) exceeded .71, i.e., their AVE values exceeded .50, and factor loadings of all items were significantly higher than .70 at p