As a killer application of the mobile Internet, location-based services (LBS) have been popular among users. However, due to the collection and utilization of users’ location information, LBS have raised users’ privacy concern, which may negatively affect their usage. From the perspective of perceived justice, this research examined LBS users’ privacy concern and continuance usage. Perceived justice includes three dimensions: distributive justice, procedural justice and interactional justice. The results indicated that perceived justice has significant effects on privacy concern, satisfaction and flow. These three factors determine continuance usage. The results imply that service providers need to improve users’ perceived justice in order to mitigate their privacy concern and facilitate their continuance usage of LBS.
AndersonJCGerbingDW (1988) Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin103(3): 411–423.
2.
AngstCMAgarwalR (2009) Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly33(2): 339–370.
3.
BhattacherjeeA (2001) Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly25(3): 351–370.
4.
ChaiSDasSRaoHR (2011) Factors affecting bloggers’ knowledge sharing: An investigation across gender. Journal of Management Information Systems28(3): 309–341.
5.
China Internet Network Information Center (2015) 36th Statistical Survey Report on the Internet Development in China. China Internet Network Information Center.
6.
ColquittJAConlonDEWessonMJPorterCOLHNgKY (2001) Justice at the millennium: A meta-analytic review of 25 years of organizational justice research. Journal of Applied Psychology86(3): 425–445.
7.
CsikszentmihalyiMCsikszentmihalyiIS (1988) Optimal Experience: Psychological studies of flow in consciousness. Cambridge, Cambridge University Press.
8.
DinevTHartP (2006) An extended privacy calculus model for e-commerce transactions. Information Systems Research17(1): 61–80.
9.
FodorMBremA (2015) Do privacy concerns matter for millennials? Results from an empirical analysis of location-based services adoption in Germany. Computers in Human Behavior53: 344–353.
10.
GefenDKarahannaEStraubDW (2003) Trust and TAM in online shopping: An integrated model. MIS Quarterly27(1): 51–90.
11.
GefenDStraubDWBoudreauMC (2000) Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems4(7): 1–70.
12.
GoelLJohnsonNJunglasIIvesB (2013) Predicting users’ return to virtual worlds: A social perspective. Information Systems Journal23(1): 35–63.
13.
GuoYMPooleMS (2009) Antecedents of flow in online shopping: A test of alternative models. Information Systems Journal19(4): 369–390.
14.
HaIYoonYChoiM (2007) Determinants of adoption of mobile games under mobile broadband wireless access environment. Information and Management44(3): 276–286.
15.
HausmanAVSiekpeJS (2009) The effect of web interface features on consumer online purchase intentions. Journal of Business Research62(1): 5–13.
16.
HoL-AKuoT-H (2010) How can one amplify the effect of e-learning? An examination of high-tech employees’ computer attitude and flow experience. Computers in Human Behavior26(1): 23–31.
17.
HoffmanDLNovakTP (1996) Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing60(3): 50–68.
18.
HongWThongJYL (2013) Internet privacy concerns: An integrated conceptualization and four empirical studies. MIS Quarterly37(1): 275–298.
19.
JungYPerez-MiraBWiley-PattonS (2009) Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior25(1): 123–129.
20.
JunglasIAWatsonRT (2008) Location-based services. Communications of the ACM51(3): 65–69.
21.
KoufarisM (2002) Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research13(2): 205–223.
22.
KumarNMohanKHolowczakR (2008) Locking the door but leaving the computer vulnerable: Factors inhibiting home users’ adoption of software firewalls. Decision Support Systems46(1): 254–264.
23.
LeeKCKangIWMcKnightDH (2007) Transfer from offline trust to key online perceptions: An empirical study. IEEE Transactions on Engineering Management54(4): 729–741.
24.
LiY (2012) Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems54(1): 471–481.
25.
LinTHLuHPHsiaoKLHsuHH (2014) Continuance intention of Facebook check-in service users: An integrated model. Social Behavior and Personality42(10): 1745–1760.
26.
LowryPBCaoJEverardA (2011) Privacy concerns versus desire for interpersonal awareness in driving the use of self-disclosure technologies: The case of instant messaging in two cultures. Journal of Management Information Systems27(4): 163–200.
27.
LuarnPYangJCChiuYP (2015) Why people check in to social network sites. International Journal of Electronic Commerce19(4): 21–46.
28.
MalhotraNKKimSSAgarwalJ (2004) Internet users’ information privacy concerns (IUIPC): the construct, the scale, and a causal model. Information Systems Research15(4): 336–355.
29.
MalhotraNKKimSSPatilA (2006) Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Science52(12): 1865–1883.
30.
MoonYJKimWGArmstrongDJ (2014) Exploring neuroticism and extraversion in flow and user generated content consumption. Information & Management51(3): 347–358.
31.
NunnallyJC (1978) Psychometric Theory. New York, McGraw-Hill.
32.
O’CassACarlsonJ (2010) Examining the effects of website induced flow in professional sporting team websites. Internet Research20(2): 115–134.
PodsakoffPMOrganDW (1986) Self-reports in organizational research: Problems and prospects. Journal of Management12(4): 531–544.
35.
ReichheldFFSchefterP (2000) E-loyalty: Your secret weapon on the Web. Harvard Business Review78(4): 105–113.
36.
SlykeCVShimJTJohnsonRJiangJ (2006) Concern for information privacy and online consumer purchasing. Journal of the AIS7(6): 415–444.
37.
SmithHJMilbergSJBurkeSJ (1996) Information privacy: Measuring individuals’ concerns about organizational practices. MIS Quarterly20(2): 167–196.
38.
SonJ-YKimSS (2008) Internet users’ information privacy-protective responses: A taxonomy and a nomological model. MIS Quarterly32(3): 503–529.
39.
StraubDBoudreauM-CGefenD (2004) Validation guidelines for IS positivist research. Communications of the Association for Information Systems13(1): 380–427.
40.
TurelOYuanYFConnellyCE (2008) In justice we trust: Predicting user acceptance of e-customer services. Journal of Management Information Systems24(4): 123–151.
41.
WangY-SWuS-CLinH-HWangY-Y (2011) The relationship of service failure severity, service recovery justice and perceived switching costs with customer loyalty in the context of e-tailing. International Journal of Information Management31(4): 350–359.
42.
XuFMichaelKChenX (2013) Factors affecting privacy disclosure on social network sites: An integrated model. Electronic Commerce Research13(2): 151–168.
43.
XuHDinevTSmithJHartP (2011) Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems12(12): 798–824.
44.
XuHGuptaS (2009) The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services. Electronic Markets19(2-3): 137–149.
45.
XuHTeoH-HTanBCYAgarwalR (2009) The role of push--pull technology in privacy calculus: The case of location-based services. Journal of Management Information Systems (3): 135–173.
46.
XuHTeoH-HTanBCYAgarwalR (2012) Effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: A study of location-based services. Information Systems Research23(4): 1342–1363.
47.
YuJZoHChoiMKCiganekAP (2013) User acceptance of location-based social networking services An extended perspective of perceived value. Online Information Review37(5): 711–730.
48.
YunHHanDLeeCC (2013) Understanding the use of location-based service applications: Do privacy concerns matter?Journal of Electronic Commerce Research14(3): 215–230.
49.
ZamanMAnandarajanMDaiQ (2010) Experiencing flow with instant messaging and its facilitating role on creative behaviors. Computers in Human Behavior26(5): 1009–1018.
50.
ZhaoLLuYBGuptaS (2012) Disclosure intention of location-related information in location-based social network services. International Journal of Electronic Commerce16(4): 53–89.
51.
ZhouT (2012) Examining location-based services usage from the perspectives of unified theory of acceptance and use of technology and privacy risk. Journal of Electronic Commerce Research13(2): 135–144.
52.
ZhuDHChangYPLuoJJLiX (2014) Understanding the adoption of location-based recommendation agents among active users of social networking sites. Information Processing & Management50(5): 675–682.
