Determinants of App Stores Continuance Behavior: A PLS Path Modelling Approach

References

• Akhter, S. H. 2014. Privacy concern and online transactions: The impact of Internet self-efficacy and Internet involvement. Journal of Consumer Marketing 31 (2):118–25. doi:10.1108/jcm-06-2013-0606.
   Google Scholar
• Al-Maghrabi, T., and C. Dennis. 2011. What drives consumers’ continuance intention to e-shopping? Conceptual framework and managerial implications in the case of Saudi Arabia. International Journal of Retail & Distribution Management 39 (12):899–926. doi:10.1108/09590551111183308.
   Google Scholar
• Anderson, J. C., and D. W. Gerbing. 1982. Some methods for respecifying measurement models to obtain unidimensional construct measurement. Journal of Marketing Research 19:453–60. doi:10.2307/3151719.
   Web of Science ®Google Scholar
• Babin, L. A., and A. C. Burns. 1998. A modified scale for the measurement of communication‐evoked mental imagery. Psychology & Marketing 15 (3):261–78. doi:10.1002/(sici)1520-6793(199805)15:3<261::aid-mar4>3.3.co;2-x.
   Web of Science ®Google Scholar
• Bagozzi, R. P., Y. Yi, and L. W. Phillips. 1991. Assessing construct validity in organizational research. Administrative Science Quarterly 36:421–58. doi:10.2307/2393203.
   Web of Science ®Google Scholar
• Bandura, A. 1986. Social foundations of thought and action. Englewood Cliffs, NJ: Prentice Hall.
   Google Scholar
• Bandura, A. 1997. Self-efficacy: The exercise of control. New York, NY: Macmillan.
   Google Scholar
• Bawden, D., and L. Robinson. 2009. The dark side of information: Overload, anxiety and other paradoxes and pathologies. Journal of Information Science 35 (2):180–91. doi:10.1177/0165551508095781.
   Web of Science ®Google Scholar
• Bellman, S., R. F. Potter, S. Treleaven-Hassard, J. A. Robinson, and D. Varan. 2011. The effectiveness of branded mobile phone apps. Journal of Interactive Marketing 25 (4):191–200. doi:10.1016/j.intmar.2011.06.001.
   Web of Science ®Google Scholar
• Bhattacherjee, A. 2001. Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly 25 (3):351–70. doi:10.2307/3250921.
   Web of Science ®Google Scholar
• Bhattacherjee, A., J. Perols, and C. Sanford. 2008. Information technology continuance: A theoretic extension and empirical test. Journal of Computer Information Systems 49 (1):17–26.
   Web of Science ®Google Scholar
• Bishop, B. W. 2012. Analysis of reference transactions to inform library applications (apps). Library & Information Science Research 34 (4):265–70. doi:10.1016/j.lisr.2012.06.001.
   Web of Science ®Google Scholar
• Bruner, G. C., P. J. Hensel, and K. E. James. 2001. Marketing scales handbook. Chicago: American Marketing Association.
   Google Scholar
• Budd, L., and T. Vorley. 2013. Airlines, apps, and business travel: A critical examination. Research in Transportation Business & Management 9:41–49. doi:10.1016/j.rtbm.2013.08.004.
   Google Scholar
• Chen, Y.-C., R.-A. Shang, and C.-Y. Kao. 2009. The effects of information overload on consumers’ subjective state towards buying decision in the Internet shopping environment. Electronic Commerce Research and Applications 8 (1):48–58.
   Web of Science ®Google Scholar
• Chin, W. 2010. How to write up and report PLS analyses. In Handbook of partial least squares, ed. V. Esposito Vinzi, W. W. Chin, J. Henseler, and H. Wang 655–90. Heidelberg, Berlin: Springer.
   Google Scholar
• Chin, W. W. 1998. Commentary: Issues and opinion on structural equation modeling. MIS Quarterly 22 (1):7–16.
   Web of Science ®Google Scholar
• Chin, W. W., B. L. Marcolin, and P. R. Newsted. 2003. A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research 14 (2):189–217. doi:10.1287/isre.14.2.189.16018.
   Web of Science ®Google Scholar
• Chong, A. Y.-L. 2013. Predicting m-commerce adoption determinants: A neural network approach. Expert Systems with Applications 40 (2):523–30. doi:10.1016/j.eswa.2012.07.068.
   Web of Science ®Google Scholar
• Crabbe, M., C. Standing, S. Standing, and H. Karjaluoto. 2009. An adoption model for mobile banking in Ghana. International Journal of Mobile Communications 7 (5):515–43. doi:10.1504/ijmc.2009.024391.
   Web of Science ®Google Scholar
• Currás-Pérez, R., C. Ruiz-Mafé, and S. Sanz-Blas. 2013. Social network loyalty: Evaluating the role of attitude, perceived risk and satisfaction. Online Information Review 37 (1):61–82. doi:10.1108/14684521311311630.
   Web of Science ®Google Scholar
• Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13:319–40. doi:10.2307/249008.
   Web of Science ®Google Scholar
• Flavián, C., M. Guinalíu, and R. Gurrea. 2006. The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & Management 43 (1):1–14. doi:10.1016/j.im.2005.01.002.
   Web of Science ®Google Scholar
• Fornell, C., and D. F. Larcker. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18:39–50. doi:10.2307/3151312.
   Web of Science ®Google Scholar
• Gefen, D., D. W. Straub, and M.-C. Boudreau. 2000. Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems: CiteSeer.
   Google Scholar
• Gorla, N., and T. M. Somers. 2014. The impact of IT outsourcing on information systems success. Information & Management 51 (3):320–35. doi:10.1016/j.im.2013.12.002.
   Web of Science ®Google Scholar
• Graham, J. W., S. M. Hofer, S. I. Donaldson, D. P. MacKinnon, and J. L. Schafer. 1997. Analysis with missing data in prevention research. In The science of prevention: Methodological advances from alcohol and substance abuse research, ed. K. J. Bryant, M. Windle, and S. G. West, 325–366. Washington, DC: American Psychological Association.
   Google Scholar
• Grewal, D., A. L. Roggeveen, L. D. Compeau, and M. Levy. 2012. Retail value-based pricing strategies: New times, new technologies, new consumers. Journal of Retailing 88 (1):1–6. doi:10.1016/j.jretai.2011.12.001.
   Web of Science ®Google Scholar
• Hair, J. F., G. T. M. Hult, C. Ringle, and M. Sarstedt. 2013. A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, CA: Sage Publications.
   Google Scholar
• Hair, J. F., C. M. Ringle, and M. Sarstedt. 2011. PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice 19 (2):139–51.
   Google Scholar
• Hair, J. F., M. Sarstedt, C. M. Ringle, and J. A. Mena. 2012. An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science 40:414–33. doi:10.1007/s11747-011-0261-6.
   Web of Science ®Google Scholar
• Hardesty, D. M., and W. O. Bearden. 2004. The use of expert judges in scale development: Implications for improving face validity of measures of unobservable constructs. Journal of Business Research 57 (2):98–107. doi:10.1016/s0148-2963(01)00295-8.
   Web of Science ®Google Scholar
• Harman, H. H. 1976. Modern factor analysis. Chicago, IL: University of Chicago Press.
   Google Scholar
• Haynes, S. N., D. Richard, and E. S. Kubany. 1995. Content validity in psychological assessment: A functional approach to concepts and methods. Psychological Assessment 7 (3):238–47. doi:10.1037//1040-3590.7.3.238.
   Web of Science ®Google Scholar
• Henseler, J. 2010. On the convergence of the partial least squares path modeling algorithm. Computational Statistics 25 (1):107–20. doi:10.1007/s00180-009-0164-x.
   Web of Science ®Google Scholar
• Henseler, J., and W. W. Chin. 2010. A comparison of approaches for the analysis of interaction effects between latent variables using partial least squares path modeling. Structural Equation Modeling 17 (1):82–109. doi:10.1080/10705510903439003.
   Web of Science ®Google Scholar
• Henseler, J., T. K. Dijkstra, M. Sarstedt, C. M. Ringle, A. Diamantopoulos, D. W. Straub, D. J. Ketchen, J. F. Hair, G. T. M. Hult, and R. J. Calantone. 2014. Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods 17:182–209. doi:10.1177/1094428114526928.
   Web of Science ®Google Scholar
• Henseler, J., C. M. Ringle, and R. R. Sinkovics. 2009. The use of partial least squares path modeling in international marketing. In Advances in international marketing, ed. R. R. Sinkovics and P. N. Ghauri vol. 20, 277–320. Bingley: Emerald.
   Google Scholar
• Hill, W. W., S. E. Beatty, and G. Walsh. 2013. A segmentation of adolescent online users and shoppers. Journal of Services Marketing 27 (5):347–60. doi:10.1108/jsm-10-2011-0157.
   Web of Science ®Google Scholar
• Hossain, M. A., and M. Quaddus. 2011. The adoption and continued usage intention of RFID: An integrated framework. Information Technology & People 24 (3):236–56. doi:10.1108/09593841111158365.
   Web of Science ®Google Scholar
• Hsiao, M.-H. 2009. Shopping mode choice: Physical store shopping versus e-shopping. Transportation Research Part E: Logistics and Transportation Review 45 (1):86–95. doi:10.1016/j.tre.2008.06.002.
   Web of Science ®Google Scholar
• Hsu, C.-L., and J. C.-C. Lin. 2014. What drives purchase intention for paid mobile apps? An expectation confirmation model with perceived value. Electronic Commerce Research and Applications 14:46–57. doi:10.1016/j.elerap.2014.11.003.
   Web of Science ®Google Scholar
• Hsu, M. H., C. M. Chiu, and T. L. Ju. 2004. Determinants of continued use of the WWW: An integration of two theoretical models. Industrial Management & Data Systems 104 (9): 766–75. doi:10.1108/02635570410567757.
   Web of Science ®Google Scholar
• Hu, P. J. H., S. A. Brown, J. Y. Thong, F. K. Chan, and K. Y. Tam. 2009. Determinants of service quality and continuance intention of online services: The case of eTax. Journal of the American Society for Information Science and Technology 60 (2):292–306. doi:10.1002/asi.20956.
   Web of Science ®Google Scholar
• Hung, S.-Y., C.-M. Chang, and T.-J. Yu. 2006. Determinants of user acceptance of the e-government services: The case of online tax filing and payment system. Government Information Quarterly 23 (1):97–122. doi:10.1016/j.giq.2005.11.005.
   Web of Science ®Google Scholar
• Hung, S.-Y., C.-Y. Ku, and C.-M. Chang. 2003. Critical factors of WAP services adoption: An empirical study. Electronic Commerce Research and Applications 2 (1):42–60. doi:10.1016/s1567-4223(03)00008-5.
   Google Scholar
• Igbaria, M., and J. Iivari. 1995. The effects of self-efficacy on computer usage. Omega 23 (6):587–605. doi:10.1016/0305-0483(95)00035-6.
   Web of Science ®Google Scholar
• Jacoby, J. 1984. Perspectives on information overload. Journal of Consumer Research 10:432–35. doi:10.1086/208981.
   Web of Science ®Google Scholar
• Jacoby, J., D. E. Speller, and C. A. Kohn. 1974. Brand choice behavior as a function of information load. Journal of Marketing Research 11 (1):63–69. doi:10.2307/3150994.
   Web of Science ®Google Scholar
• Jöreskog, K. G. 1970. A general method for analysis of covariance structures. Biometrika 57 (2):239–51. doi:10.2307/2334833.
   Web of Science ®Google Scholar
• Kang, J.-Y. M., J. M. Mun, and K. K. Johnson. 2015. In-store mobile usage: Downloading and usage intention toward mobile location-based retail apps. Computers in Human Behavior 46:210–17. doi:10.1016/j.chb.2015.01.012.
   Web of Science ®Google Scholar
• Kang, Y. J., and W. J. Lee. 2014. Self-customization of online service environments by users and its effect on their continuance intention. Service Business 9:1–22. doi:10.1007/s11628-014-0229-y.
   Web of Science ®Google Scholar
• Kang, Y. S., and H. Lee. 2010. Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior 26 (3):353–64. doi:10.1016/j.chb.2009.11.006.
   Web of Science ®Google Scholar
• Karani, K. S., K. Fraccastoro, and J. Shelton. 2013. The effect of order of prices on customers’ confidence levels. Journal of Management & Marketing Research 13:1–10.
   Google Scholar
• Kasper, H., J. Bloemer, and P. H. Driessen. 2010. Coping with confusion: The case of the Dutch mobile phone market. Managing Service Quality 20 (2):140–60. doi:10.1108/09604521011027570.
   Google Scholar
• Kauffman, R. J., and E. A. Walden. 2001. Economics and electronic commerce: Survey and directions for research. International Journal of Electronic Commerce 5:5–116.
   Web of Science ®Google Scholar
• Kim, J. B. 2013. Understanding the repurchase abandonment process of consumers in the online environment: Integrating dissatisfaction and distrust. Journal of Internet Commerce 12 (2):154–94. doi:10.1080/15332861.2013.817863.
   Google Scholar
• Kim, Y., and M. Glassman. 2013. Beyond search and communication: Development and validation of the Internet self-efficacy Scale (ISS). Computers in Human Behavior 29 (4):1421–29. doi:10.1016/j.chb.2013.01.018.
   Web of Science ®Google Scholar
• Klausegger, C., R. R. Sinkovics, and H. “Joy” Zou. 2007. Information overload: A cross-national investigation of influence factors and effects. Marketing Intelligence & Planning 25 (7):691–718.
   Google Scholar
• Kuo, Y.-C., A. E. Walker, K. E. Schroder, and B. R. Belland. 2014. Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education 20:35–50. doi:10.1016/j.iheduc.2013.10.001.
   Web of Science ®Google Scholar
• Lee, B. K., and W. N. Lee. 2004. The effect of information overload on consumer choice quality in an on‐line environment. Psychology & Marketing 21 (3):159–83. doi:10.1002/mar.20000.
   Web of Science ®Google Scholar
• Lee, J., M. S. Cha, and C. Cho. 2012. Online service quality in social commerce websites contemporary research on E-business technology and strategy, 335–51. Berlin, Germany: Springer.
   Google Scholar
• Lewis, E. F., M. Hardy, and B. Snaith. 2013. An analysis of survey reporting in the imaging professions: Is the issue of non-response bias being adequately addressed? Radiography 19 (3):240–45. doi:10.1016/j.radi.2013.02.003.
   Google Scholar
• Liang, T.-P., H.-J. Lai, and Y.-C. Ku. 2006. Personalized content recommendation and user satisfaction: Theoretical synthesis and empirical findings. Journal of Management Information Systems 23 (3):45–70. doi:10.2753/mis0742-1222230303.
   Web of Science ®Google Scholar
• Limayem, M., S. G. Hirt, and C. M. Cheung. 2007. How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly 31 (4):705–37.
   Web of Science ®Google Scholar
• Limayem, M., M. Khalifa, and A. Frini. 2000. What makes consumers buy from Internet? A longitudinal study of online shopping. IEEE Transactions on Systems, Man, and Cybernetics - Part A 30 (4):421–32. doi:10.1109/3468.852436.
   Web of Science ®Google Scholar
• Lin, H.-F., and C.-H. Chen. 2013. An intelligent embedded marketing service system based on TV apps: Design and implementation through product placement in idol dramas. Expert Systems with Applications 40 (10):4127–36. doi:10.1016/j.eswa.2013.01.034.
   Web of Science ®Google Scholar
• Lin, I.-F., and N. C. Schaeffer. 1995. Using survey participants to estimate the impact of nonparticipation. Public Opinion Quarterly 59 (2):236–58. doi:10.1086/269471.
   Web of Science ®Google Scholar
• Lin, K.-M. 2011. E-learning continuance intention: Moderating effects of user e-learning experience. Computers & Education 56 (2):515–26. doi:10.1016/j.compedu.2010.09.017.
   Web of Science ®Google Scholar
• Lin, W.-S. 2011. Perceived fit and satisfaction on online learning performance: An empirical study Edutainment Technologies. In Educational games and virtual reality/augmented reality applications, ed. M. Chang, W.-Y. Hwang, M.-P. Chen, and W. Müller, 139–46. Berlin, Germany: Springer.
   Google Scholar
• Lin, K.-M., N.-S. Chen, and K. Fang. 2011. Understanding e-learning continuance intention: A negative critical incidents perspective. Behaviour & Information Technology 30 (1):77–89. doi:10.1080/01449291003752948.
   Web of Science ®Google Scholar
• Little, R. J. A. 1988. Missing-data adjustments in large surveys. Journal of Business & Economic Statistics 6 (3):287–96. doi:10.1080/07350015.1988.10509663.
   Web of Science ®Google Scholar
• Liu, C., and S. Forsythe. 2011. Examining drivers of online purchase intensity: Moderating role of adoption duration in sustaining post-adoption online shopping. Journal of Retailing and Consumer Services 18 (1):101–09.
   Google Scholar
• Lohmöller, J.-B. 1989. Latent variable path modeling with partial least squares. Heidelberg: Physica-Verlag.
   Google Scholar
• Lu, J. 2014. Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Research 24 (2):134–59. doi:10.1108/intr-05-2012-0100.
   Web of Science ®Google Scholar
• Lueg, C. P. 2014. Characteristics of human perception and their relevance when studying information behavior. Journal of Documentation 70 (4):562–74. doi:10.1108/jd-05-2012-0064.
   Web of Science ®Google Scholar
• MacKenzie, S. B., and P. M. Podsakoff. 2012. Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of Retailing 88:542–55. doi:10.1016/j.jretai.2012.08.001.
   Web of Science ®Google Scholar
• Marston, S., Z. Li, S. Bandyopadhyay, J. Zhang, and A. Ghalsasi. 2011. Cloud computing – The business perspective. Decision Support Systems 51 (1):176–89.
   Web of Science ®Google Scholar
• Mettler, T. 2012. Post-acceptance of electronic medical records: Evidence from a longitudinal field study. Orlando, FL: ICIS.
   Google Scholar
• Nagar, K. 2016. Drivers of E-store patronage intentions: Choice overload, internet shopping anxiety, and impulse purchase tendency. Journal of Internet Commerce 15 (2):97–124. doi:10.1080/15332861.2016.1148971.
   Web of Science ®Google Scholar
• Oliveira, T., M. Thomas, and M. Espadanal. 2014. Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & Management 51 (5):497–510. doi:10.1016/j.im.2014.03.006.
   Web of Science ®Google Scholar
• Oliver, R. L. 1977. Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. Journal of Applied Psychology 62 (4):480–86. doi:10.1037//0021-9010.62.4.480.
   Web of Science ®Google Scholar
• Oliver, R. L. 1980. A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research 17:460–69. doi:10.2307/3150499.
   Web of Science ®Google Scholar
• Pallud, J., and D. W. Straub. 2014. Effective website design for experience-influenced environments: The case of high culture museums. Information & Management 51 (3):359–73. doi:10.1016/j.im.2014.02.010.
   Web of Science ®Google Scholar
• Peng, L., and L. Lai. 2014. A service innovation evaluation framework for tourism e-commerce in China based on BP neural network. Electronic Markets 24 (1):37–46. doi:10.1007/s12525-013-0148-0.
   Web of Science ®Google Scholar
• Pentina, I., and M. Tarafdar. 2014. From “information” to “knowing”: Exploring the role of social media in contemporary news consumption. Computers in Human Behavior 35:211–23. doi:10.1016/j.chb.2014.02.045.
   Web of Science ®Google Scholar
• Podsakoff, P. M., S. B. MacKenzie, L. Jeong-Yeon, and N. P. Podsakoff. 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88 (5):879–903. doi:10.1037/0021-9010.88.5.879.
   PubMed Web of Science ®Google Scholar
• Polit, D. F., and C. T. Beck. 2006. The content validity index: Are you sure you know what’s being reported? Critique and recommendations. Research in Nursing & Health 29 (5): 489–97. doi:10.1002/nur.20147.
   PubMed Web of Science ®Google Scholar
• Reinartz, W. J., M. Haenlein, and J. Henseler. 2009. An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of Research in Marketing 26 (4):332–44. doi:10.1016/j.ijresmar.2009.08.001.
   Web of Science ®Google Scholar
• Rezaei, S. 2015. Segmenting consumer decision-making styles (CDMS) toward marketing practice: A partial least squares (PLS) path modeling approach. Journal of Retailing and Consumer Services 22:1–15. doi:10.1016/j.jretconser.2014.09.001.
   Web of Science ®Google Scholar
• Rezaei, S., and S. S. Ghodsi. 2014. Does value matters in playing online game? An empirical study among massively multiplayer online role-playing games (MMORPGs). Computers in Human Behavior 35:252–66. doi:10.1016/j.chb.2014.03.002.
   Web of Science ®Google Scholar
• Ringle, C. M., S. Wende, and A. Will. 2005. SmartPLS 2.0. www.smartpls.de.
   Google Scholar
• Riquelme, I. P., and S. Román. 2014. The influence of consumers’ cognitive and psychographic traits on perceived deception: A comparison between online and offline retailing contexts. Journal of Business Ethics 119 (3):405–22. doi:10.1007/s10551-013-1628-z.
   Web of Science ®Google Scholar
• Rosen, L. D., K. R. Karwan, and L. L. Scribner. 2003. Service quality measurement and the disconfirmation model: Taking care in interpretation. Total Quality Management and Business Excellence 14 (1):3–14. doi:10.1080/14783360309703.
   Web of Science ®Google Scholar
• Rosenbloom, B. 2013. Functions and institutions: The roots and the future of marketing channels. Journal of Marketing Channels 20 (3–4):191–203. doi:10.1080/1046669x.2013.803423.
   Google Scholar
• Salanova, M., R. M. Grau, E. Cifre, and S. Llorens. 2000. Computer training, frequency of usage and burnout: The moderating role of computer self-efficacy. Computers in Human Behavior 16 (6):575–90. doi:10.1016/s0747-5632(00)00028-5.
   Web of Science ®Google Scholar
• Sarstedt, M. 2008. A review of recent approaches for capturing heterogeneity in partial least squares path modelling. Journal of Modelling in Management 3 (2):140–61. doi:10.1108/17465660810890126.
   Google Scholar
• Schafer, J. L., and M. K. Olsen. 1998. Multiple imputation for multivariate missing-data problems: A data analyst’s perspective. Multivariate Behavioral Research 33 (4):545–71. doi:10.1207/s15327906mbr3304_5.
   PubMed Web of Science ®Google Scholar
• Shang, R.-A., Y.-C. Chen, and S.-Y. Chen. 2013. The effects of the number of alternative products and the way they are presented on the consumers’ subjective statuses in online travel sites. Behaviour & Information Technology 32 (7):630–43. doi:10.1080/0144929x.2011.572185.
   Web of Science ®Google Scholar
• Shank, D. B., and S. R. Cotten. 2014. Does technology empower urban youth? The relationship of technology use to self-efficacy. Computers & Education 70:184–93. doi:10.1016/j.compedu.2013.08.018.
   Web of Science ®Google Scholar
• Sipior, J. C., B. T. Ward, and L. Volonino. 2014. Privacy concerns associated with smartphone use. Journal of Internet Commerce 13 (3–4):177–93. doi:10.1080/15332861.2014.947902.
   Google Scholar
• Sivadas, E., and J. L. Baker-Prewitt. 2000. An examination of the relationship between service quality, customer satisfaction, and store loyalty. International Journal of Retail & Distribution Management 28 (2):73–82. doi:10.1108/09590550010315223.
   Google Scholar
• Song, J., J. Kim, D. R. Jones, J. Baker, and W. W. Chin. 2014. Application discoverability and user satisfaction in mobile application stores: An environmental psychology perspective. Decision Support Systems 59:37–51. doi:10.1016/j.dss.2013.10.004.
   Web of Science ®Google Scholar
• Soper, D. 2015. A-Priori Sample Size Calculator for Structural Equation Models [Software].
   Google Scholar
• Stanton, J. V., and D. M. Paolo. 2012. Information overload in the context of apparel: Effects on confidence, shopper orientation and leadership. Journal of Fashion Marketing and Management 16 (4):454–76. doi:10.1108/13612021211265854.
   Google Scholar
• Ström, R., M. Vendel, and J. Bredican. 2014. Mobile marketing: A literature review on its value for consumers and retailers. Journal of Retailing and Consumer Services 21:1001–02. doi:10.1016/j.jretconser.2013.12.003.
   Google Scholar
• Teo, T. S., and V. K. Lim. 2001. The effects of perceived justice on satisfaction and behavioral intentions: The case of computer purchase. International Journal of Retail & Distribution Management 29 (2):109–25. doi:10.1108/09590550110382039.
   Google Scholar
• Torkzadeh, G., J. C.-J. Chang, and D. Demirhan. 2006. A contingency model of computer and Internet self-efficacy. Information & Management 43 (4):541–50. doi:10.1016/j.im.2006.02.001.
   Web of Science ®Google Scholar
• Torkzadeh, G., and T. P. Van Dyke. 2002. Effects of training on Internet self-efficacy and computer user attitudes. Computers in Human Behavior 18 (5):479–94. doi:10.1016/s0747-5632(02)00010-9.
   Web of Science ®Google Scholar
• Vekiri, I., and A. Chronaki. 2008. Gender issues in technology use: Perceived social support, computer self-efficacy and value beliefs, and computer use beyond school. Computers & Education 51 (3):1392–404. doi:10.1016/j.compedu.2008.01.003.
   Web of Science ®Google Scholar
• Vinzi, V. E., L. Trinchera, and S. Amato. 2010. PLS path modeling: From foundations to recent developments and open issues for model assessment and improvement. In Handbook of partial least squares, ed. V. Esposito Vinzi, W. W. Chin, J. Henseler, and H. Wang, 47–82. Berlin, Germany: Springer.
   Google Scholar
• Wang, J.-C., and M.-J. Chiang. 2009. Social interaction and continuance intention in online auctions: A social capital perspective. Decision Support Systems 47 (4):466–76. doi:10.1016/j.dss.2009.04.013.
   Web of Science ®Google Scholar
• Wang, Q., and P. Shukla. 2013. Linking sources of consumer confusion to decision satisfaction: The role of choice goals. Psychology & Marketing 30 (4):295–304. doi:10.1002/mar.20606.
   Web of Science ®Google Scholar
• Wang, R. J.-H., E. C. Malthouse, and L. Krishnamurthi. 2015. On the go: How mobile shopping affects customer purchase behavior. Journal of Retailing 91:217–34. doi:10.1016/j.jretai.2015.01.002.
   Web of Science ®Google Scholar
• White, M. 2010. Information anywhere, any when: The role of the smartphone. Business Information Review 27 (4):242–47. doi:10.1177/0266382110390651.
   Google Scholar
• Wold, H. 1975. Path models with latent variables: The NIPALS approach. New York, NY: Academic Press.
   Google Scholar
• Zhang, L., T.-Q. Peng, Y.-P. Zhang, X.-H. Wang, and J. J. Zhu. 2014. Content or context: Which matters more in information processing on microblogging sites. Computers in Human Behavior 31:242–49. doi:10.1016/j.chb.2013.10.031.
   Web of Science ®Google Scholar
• Zwass, V. 1996. Electronic commerce: Structures and issues. International Journal of Electronic Commerce 1:3–23. doi:10.1080/10864415.1996.11518273.
   Google Scholar