HOW TO SATISFY MOBILE APPLICATION USERS AND INCREASE THEIR BRAND EQUITY PERCEPTION?

Year 2019, Volume: 41 Issue: 1, 126 - 144, 12.07.2019

Hüseyin Ekizler

https://doi.org/10.14780/muiibd.582314

Abstract

Nowadays, with the development of technology people’s lives have adapted to new situation and individuals have started to carry all the communication, socialization, banking, navigating and many other things they need through applications on their smart phones. The main purpose of this study is to examine the features of the mobile phone applications and the effects of these features on the brand value through users’ satisfaction. In this study, the utilitarian benefits, consist of application quality and application utility, hedonic benefits, consist of enjoyment and aesthetics, privacy risk, technicality, and perceived price were determined as the factors assume to have an impact on satisfaction directly, and brand equity correspondingly. All of the concepts used in this study were firstly analyzed with Exploratory Factor Analysis (EFA) and their reliability were measured. Afterwards, the model fit was tested with Confirmatory Factor Analysis (CFA) and path analysis. Out of 731 respondents, that were usable, 368 were selected for EFA and the remaining 363 were selected for CFA and path analysis, where dataset division was randomly performed with Bernoulli distribution. As a result, there were significant relationships between all concepts except the aesthetic dimension and privacy risk of the application.

Keywords

Mobile Applications, Customer Satisfaction, Brand Equity, Structural Equation Modeling

References

• Aaker, D.A., & Keller, K.L. (1990). Consumer evaluations of brand extensions. Journal of marketing, 54(1), 27-41.
• Ahmad, N. (2012). Utilitarian and Hedonic Values of Mobile Services: A Preliminary Analysis from the Users’ Perspective. Business & accounting review, (9), 69-83.
• Anderson, E.W. & Sullivan, M.W. (1993). The antecedents and consequences of customer satisfaction for firms, Marketing Science, 12 (2), 125–143.
• Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation – confirmation model, MIS Quarterly, 25 (3), 351–370.
• Chen L., Meservy, T.O. & Gillenson M. (2012). Understanding information systems continuance for information-oriented mobile applications, Communications of the Association for Information Systems, 30, 127–146.
• Chen, Z. & Dubinsky, A.J. (2003). A conceptual model of perceived customer value in ecommerce: a preliminary investigation, Psychology and Marketing, 20 (4), 323–347.
• Cho, D.Y., Kwon, H.J., & Lee, H.Y. (2007). Analysis of trust in internet and mobile commerce adoption. In Proceedings of the 40th Hawaii international conference on system science (HICSS), Waikoloa (pp. 1–10).
• Churchill Jr. G.A. & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction, Journal of Marketing Research, 19, 491–504.
• Cyr, D. Head, M., Larios, H., & Pan, B. (2009). Exploring human images in website design: a multi-method approach, MIS Quarterly, 33 (3), 539-566.
• Cyr, D., Head, M. & Ivanov, A. (2006). Design aesthetics leading to m-loyalty in mobile commerce, Information & Management, 43 (8), 950–963.
• Davis F. D., Bagozzi R.P., & Warshaw P.R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace, Journal of Applied Social Psychology, 22 (14), 1111–1132.
• Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13 (3), 319–340.
• Deloitte, (2011). So many apps so little to download. USA.
• Dennis, C., Papagiannidis, S., Alamanos, E., & Bourlakis, M. (2016). The role of brand attachment strength in higher education. Journal of Business Research, 69(8), 3049-3057.
• Dholakia, U.M., Bagozzi, R.P., & Pearo, L.K. (2004). A social influence model of consumer participation in network-and small-group-based virtual communities. International journal of research in marketing, 21(3), 241-263.
• Dinev, T. & Hart, P., (2006). An extended privacy calculus model for E-commerce transactions, Information Systems Research, 17 (1), 61–80.
• Dodds, W.B., Monroe, K.B. & Grewal, D. (1991), Effects of price, brand, and store information on buyers’ product evaluations, Journal of Marketing Research, 28 (3), 307–319.
• Durmus B., Yurtkoru S., & Cinko M. (2016). Sosyal Bilimlerde SPSS’le Veri Analizi. 6th ed. Beta Basim Yayim Dağıtım.
• Ghosh, A.K. & Swaminatha T.M. (2001). Software security and privacy risks in mobile ecommerce, Communications of the ACM, 44 (2), 51–57.
• Ha I., Yoon Y. & Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment, Information Management, 44 (3), 276–286.
• Hair, J.F.J., Anderson, R.E., Tatham, R.L., Black, W.C., (1998). Multivariate Data Analysis, 5th ed, Prentice
• Hall, Upper Saddle River, New Jersey.
• Harris, K.D. (2013), “Privacy On The Go: Recommendations For The Mobile Ecosystem”
• Harrison-Walker, L.J. (2001). The measurement of word-of-mouth communication and an investigation of service quality and customer commitment as potential antecedents, Journal of Service Research, 4 (1), 60–75.
• Hult, G.T.M., Sharma, P.N., Morgeson III, F.V., & Zhang, Y. (2018). Antecedents and Consequences of Customer Satisfaction: Do They Differ Across Online and Offline Purchases?. Journal of Retailing. (https://doi.org/10.1016/j.jretai.2018.10.003)
• Kayworth T., Whitten D. (2010) Effective information security requires a balance of social and technology factors. MIS Q Executive 9(3):163–175
• Keller, K.L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of marketing, 57(1), 1-22.
• Keller, K.L. (2003), Strategic Brand Management: Building, Measuring and Managing Brand Equity, 2nd ed., Prentice-Hall, Englewood Cliffs, NJ.
• Kim, D.J., Ferrin, D.L. & Rao, H.R. (2008). A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents, Decision Support Systems, 44 (2), 544–564.
• Kim, H.W., Chan H.C. & Gupta S., (2007). Value-based adoption of mobile internet: an empirical investigation, Decision Support Systems, 43 (1), 111–126.
• Kim, H.W., Gupta, S. & Koh, J., (2011). Investigating the intention to purchase digital items in social networking communities: a customer value perspective, Information Management, 48 (6), 228–234.
• Kim, K.H., Kim, K.S., Kim, D.Y., Kim, J.H., & Kang, S.H. (2008). Brand equity in hospital marketing. Journal of Business Research, 61(1), 75–82.
• Lam, S.Y., Shankar, V., Erramilli, M.K., & Murthy, B. (2004). Customer value, satisfaction, loyalty, and switching costs: an illustration from a business-to-business service context, Journal of the Academy of Marketing Science, 32 (3), 293–311.
• Lattin, J.M., Carroll, J.D., & Green, P.E. (2003). Analyzing multivariate data, Thomson Brooks/Cole, USA
• Lee, S., & Kim, D.Y. (2018). The effect of hedonic and utilitarian values on satisfaction and loyalty of Airbnb users. International Journal of Contemporary Hospitality Management, 30(3), 1332-1351.
• Lin, T.C., Wu, S., Hsu, J.S.C., & Chou, Y.C. (2012). The integration of value-based adoption and expectation– confirmation models: an example of IPTV continuance intention, Decision Support Systems, 54, 63–75.
• Netemeyer, R.G., Bearden, W.O., Sharma, S. (2003). Scaling Procedures: Issues and Applications, Sage Publications, Thousand Oaks.
• Petruzzellis, L. (2010). Mobile phone choice: technology versus marketing. The brand effect in the Italian market. European Journal of marketing, 44(5), 610-634.
• Sekeran U. & Bougie R. (2013). Research Methods for Business. 6th ed. John Wiley & Sons Ltd.
• Srivastava, R.K., & Shocker, A.D. (1991). Brand equity: a perspective on its meaning and measurement; technical working paper. na.
• Sweeney, J.C., Soutar, G.N. & Johnson, L.W. (1999). The role of perceived risk in the quality–value relationship: a study in a retail environment, Journal of Retailing, 75 (1), 77–105.
• Tractinsky, N., Katz, A.S. & Ikar, D. (2000). What is beautiful is usable, Interacting with Computers, 13 (2), 127–145.
• Van der Heijden, H. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands, Information Management, 40 (6), 541–549.
• Van der Heijden, H. (2004). User acceptance of hedonic information systems, MIS Quarterly, 28 (4), 695–704.
• Venkatesh V., Morris, M. G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: toward a unified view, MIS Quarterly, 27 (3), 425–478.
• Venkatesh V., Thong J.Y.L. & Xu X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Quarterly, 36 (1), 157–178.
• Wells, J.D., Valacich, J.S. & Hess T.J. (2011). What signal are you sending? How website quality influences perceptions of product quality and purchase intentions, MIS Quarterly, 35 (2), 373-396.
• Wixom B.H. & Todd P.A., (2005). A theoretical integration of user satisfaction and technology acceptance, Information Systems Research, 16 (1), 85–102.
• Xu C., Peak D., & Prybutok V., (2015). A customer value, satisfaction, and loyalty perspective of mobile application recommendations, Decision Support Systems, 79, 171–183.
• Yang, Z. & Peterson, R.T. (2004). Customer perceived value, satisfaction, and loyalty: the role of switching costs, Psychology and Marketing, 21 (10), 799–822.
• Yoo, B. & Donthu, N., (2001). Developing and validating a multidimensional consumer-based brand equity scale, Journal of Business Research, 52, 1-14.
• Zeithaml, V.A. (1982). Consumer response to in-store price information environments, Journal of Consumer Research, 8 (4), 357–369.
• Zeithaml, V.A., (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence, Journal of Marketing, 52 (3), 2–22.