Toward an Integrated Decision-Making Model for Consumer Electronic

References

• Anderson EW, Fornell C, Lehmann DR. Customer satisfaction, market share, and profitability: Findings from Sweden. J Market. 1994;53–66.
   Google Scholar
• Anderson M. Shopping from smartphones, tablets boosts holiday sales. Available from http://www.dispatch.com/content/stories/business/2016/01/09/shopping-from-smartphones-tablets-boosts-holiday-sales.html.
   Google Scholar
• Armstrong JS, Overton TS. Estimating nonresponse bias in mail surveys. J Market Res. 1977;396–402.
   Google Scholar
• Beaudry A, Pinsonneault A. The other side of acceptance: Studying the direct and indirect effects of emotions on information technology use. MIS Q. 2010;34(4):689–710.
   Web of Science ®Google Scholar
• Beaudry A, Pinsonneault A. Understanding user responses to information technology: A coping model of user adaptation. MIS Q. 2005;493–524.
   Google Scholar
• Bhattacherjee A. An empirical analysis of the antecedents of electronic commerce service continuance. Decis Support Syst. 2001;32(2):201–214.
   Web of Science ®Google Scholar
• Bilbao-Osorio B, Dutta S, Lanvin B. The global information technology report. World Economy Forum; 2013. Available from http://www3.weforum.org/docs/WEF_GITR_Report_2013.pdf.
   Google Scholar
• Boakye KG. Factors influencing mobile data service (MDS) continuance intention: An empirical study. Comput Hum Behav. 2015;50:125–131.
   Web of Science ®Google Scholar
• Carbone LP, Haeckel SH. Engineering customer experiences. Market Manage. 1994;3(3):8.
   Google Scholar
• Carù A, Cova B. Revisiting consumption experience a more humble but complete view of the concept. Market Theory. 2003;3(2):267–286.
   Google Scholar
• Chang T-Z, Wildt AR. Price, product information, and purchase intention: An empirical study. J Acad Market Sci. 1994;22(1):16–27.
   Google Scholar
• Chen L-d, Gillenson ML, Sherrell DL. Enticing online consumers: an extended technology acceptance perspective. Inf Manage. 2002;39(8):705–719.
   Google Scholar
• Chin WW, Marcolin BL, Newsted PR. 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. Inf Syst Res. 2003;14(2):189–217.
   Web of Science ®Google Scholar
• Chordas L. A New Generation in the Cross Hairs, in Best’s Review. 2001, AM Best.
   Google Scholar
• Chow WS, Shi S. Investigating Customers’ Satisfaction with Brand Pages in Social Networking Sites. J Comput Inf Syst. 2015;55(2):48–58.
   Web of Science ®Google Scholar
• Corrêa H, et al. Customer choice of a car maintenance service provider: A model to identify the service attributes that determine choice. Int J Oper Prod Manage. 2007;27(5):464–481.
   Web of Science ®Google Scholar
• Dai H, Hu T, Zhang X. Continued use of mobile technology mediated services: A value perspective. J Comput Inf Syst. 2014;54(2):99–109.
   Web of Science ®Google Scholar
• Dai H, et al. Explaining consumer satisfaction of services: The role of innovativeness and emotion in an electronic mediated environment. Decis Support Syst. 2015;70:97–106.
   Web of Science ®Google Scholar
• Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;319–340.
   Google Scholar
• Davis FD, Bagozzi RP, Warshaw PR. Extrinsic and intrinsic motivation to use computers in the workplace1. J Appl Soc Psychol. 1992;22(14):1111–1132.
   Web of Science ®Google Scholar
• Davis FD, Bagozzi RP, Warshaw PR. User acceptance of computer technology: a comparison of two theoretical models. Manage Sci. 1989;35(8):982–1003.
   Web of Science ®Google Scholar
• Dodds WB, Monroe KB, Grewal D. Effects of price, brand, and store information on buyers’ product evaluations. J Market Res. 1991;307–319.
   Google Scholar
• Fishbein M, Ajzen I. Belief, Attitudes, Intention, and Behavior. An Introduction to Theory and Research. Boston (MA): Addison-Wesley; 1975.
   Google Scholar
• Fornell C, Larcker DF. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J Market Res. 1981;382–388.
   Google Scholar
• Frow P, Payne A. Towards the ‘perfect’customer experience. J Brand Manage. 2007;15(2):89–101.
   Google Scholar
• Garvin DA. Competing on the eight dimensions of quality. Harv Bus Rev. 1987;65(6):101–109.
   Web of Science ®Google Scholar
• Gentile C, Spiller N, Noci G. How to sustain the customer experience:: An overview of experience components that co-create value with the customer. Eur Manage J. 2007;25(5):395–410.
   Google Scholar
• Gordon R. Forecast Alert: IT Spending, Worldwide, 2008–2015, 4Q11 Update. Stamford (CT): Gartner; January 3, 2012
   Google Scholar
• Ha S, Stoel L. Consumer e-shopping acceptance: Antecedents in a technology acceptance model. J Bus Res. 2009;62(5):565–571.
   Web of Science ®Google Scholar
• Helkkula A, Kelleher C, Pihlström M. Characterizing value as an experience: implications for service researchers and managers. J Serv Res. 2012;1094670511426897.
   Web of Science ®Google Scholar
• Hoffman DL, Novak TP, Venkatesh A. Has the Internet become indispensable? Commun ACM. 2004;47(7):37–42.
   Web of Science ®Google Scholar
• Hong S, Thong JY, Tam KY. Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decis Support Syst. 2006;42(3):1819–1834.
   Web of Science ®Google Scholar
• GSMA Intelligence Report. The mobile economy 2014. 2014. Available from http://www.gsmamobileeconomy.com/GSMA_ME_Report_2014_R2_WEB.pdf.
   Google Scholar
• Kim DJ, Ferrin DL, Rao HR. Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Inf Syst Res. 2009;20(2):237–257.
   Web of Science ®Google Scholar
• Kim H-W, Chan HC, Gupta S. Value-based adoption of mobile internet: an empirical investigation. Decis Support Syst. 2007;43(1):111–126.
   Web of Science ®Google Scholar
• Kim H-W, Gupta S, Koh J. Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Inf Manage. 2011;48(6):228–234.
   Web of Science ®Google Scholar
• Kim H-W, Xu Y, Gupta S. Which is more important in Internet shopping, perceived price or trust? Electron Commerce Res Appl. 2012;11(3):241–252.
   Web of Science ®Google Scholar
• Kuo Y-F, Wu C-M, Deng W-J. The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Comput Hum Behav. 2009;25(4):887–896.
   Web of Science ®Google Scholar
• Lemke F, Clark M, Wilson H. Customer experience quality: an exploration in business and consumer contexts using repertory grid technique. J Acad Market Sci. 2011;39(6):846–869.
   Web of Science ®Google Scholar
• Lin S, Zimmer JC, Lee V. Decoupling software from hardware in technology acceptance research. J Comput Inf Syst. 2014;54(2):77–86.
   Web of Science ®Google Scholar
• Lin T-C, et al. The integration of value-based adoption and expectation–confirmation models: An example of IPTV continuance intention. Decis Support Syst. 2012;54(1):63–75.
   Web of Science ®Google Scholar
• Lu J, et al. Determinants of accepting wireless mobile data services in China. Inf Manage. 2008;45(1):52–64.
   Web of Science ®Google Scholar
• Martensen A. Tweens’ satisfaction and brand loyalty in the mobile phone market. Young Consumers. 2007;8(2):108–116.
   Google Scholar
• Mathwick C, Malhotra N, Rigdon E. Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment. J Retail. 2001;77(1):39–56.
   Web of Science ®Google Scholar
• Meyer C, Schwager A. Understanding customer experience. Harv Bus Rev. 2007;85(2):116.
   PubMed Web of Science ®Google Scholar
• Mook DG. In defense of external invalidity. Am Psychol. 1983;38(4):379.
   Web of Science ®Google Scholar
• Oakes W. External validity and the use of real people as subjects. Am Psychol. 1972;27(10):959.
   Web of Science ®Google Scholar
• Oliver RL. Measurement and evaluation of satisfaction processes in retail settings. J Retail. 1981.
   Web of Science ®Google Scholar
• Parasuraman A, Zeithaml VA, Berry LL. Servqual. J Retail. 1988;64(1):12–40.
   Web of Science ®Google Scholar
• Payne AF, Storbacka K, Frow P. Managing the co-creation of value. J Acad Market Sci. 2008;36(1):3–96.
   Web of Science ®Google Scholar
• Pedraja Iglesias M, Jesus Yagüe Guillén M. Perceived quality and price: their impact on the satisfaction of restaurant customers. Int J Contemp Hospitality Manage. 2004;16(6):373–379.
   Google Scholar
• Peterson RA, Merunka DR. Convenience samples of college students and research reproducibility. J Bus Res. 2014;67(5):1035–1041.
   Web of Science ®Google Scholar
• Petrick JF. Development of a multi-dimensional scale for measuring the perceived value of a service. J Leisure Res. 2002;34(2):119.
   Web of Science ®Google Scholar
• Pine BJ, Gilmore JH. The Experience Economy: Work is Theatre & Every Business a Stage. Harvard Business Press; 1999.
   Google Scholar
• Ringle CM, Wende S, Becker J-M. SmartPLS 3. Hambrug: SmartPLS; 2015.
   Google Scholar
• Sarker S, et al. Managing employees’ use of mobile technologies to minimize work-life balance impacts. MIS Q Executive. 2012;11(4).
   Web of Science ®Google Scholar
• Schultz DP. The human subject in psychological research. Psychol Bull. 1969;72(3):214.
   PubMed Web of Science ®Google Scholar
• Sheela L, Hemamalini R, Rejendran M. Cell phone the primary personal mobile computing devices. Int J Comput Trends Technol. 2011;1:87–90.
   Google Scholar
• Sheth JN, Newman BI, Gross BL. Why we buy what we buy: a theory of consumption values. J Bus Res. 1991;22(2):159–170.
   Web of Science ®Google Scholar
• Sinha I, DeSarbo WS. An integrated approach toward the spatial modeling of perceived customer value. J Market Res. 1998;236–249.
   Google Scholar
• Statista. Statistics and facts about e-commerce in the United States. Available from: https://www.statista.com/topics/2443/us-ecommerce/.
   Google Scholar
• Sweeney JC, Soutar GN. Consumer perceived value: The development of a multiple item scale. J Retail. 2001;77(2):203–220.
   Web of Science ®Google Scholar
• Szymanski DM, Henard DH. Customer satisfaction: A meta-analysis of the empirical evidence. J Acad Market Sci. 2001;29(1):16–35.
   Web of Science ®Google Scholar
• Taylor DG, Strutton D. Has e-marketing come of age? Modeling historical influences on post-adoption era Internet consumer behaviors. J Bus Res. 2010;63(9):950–956.
   Web of Science ®Google Scholar
• Taylor S, Todd PA Understanding information technology usage: A test of competing models. Inf Syst Res. 1995;6(2):144–176.
   Web of Science ®Google Scholar
• Torres R, Johnson V, Imhonde B. The impact of content type and availability on ebook reader adoption. J Comput Inf Syst. 2014;54(4):42–51.
   Web of Science ®Google Scholar
• Van der Heijden H. User acceptance of hedonic information systems. MIS Q. 2004;695–704.
   Google Scholar
• Venkatesh V, Morris MG. Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Q. 2000;115–139.
   Google Scholar
• Verhoef PC, et al. Customer experience creation: Determinants, dynamics and management strategies. J Retail. 2009;85(1):31–41.
   Web of Science ®Google Scholar
• Vijayasarathy LR. Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Inf Manage. 2004;41(6):747–762.
   Web of Science ®Google Scholar
• Wamba SF, et al. Exploring the impact of RFID technology and the EPC network on mobile B2B eCommerce: A case study in the retail industry. Int J Prod Econ. 2008;112(2):614–629.
   Web of Science ®Google Scholar
• Wen C, Prybutok VR, Xu C. An integrated model for customer online repurchase intention. J Comput Inf Syst. 2011;52(1):14–23.
   Web of Science ®Google Scholar
• Wen C, et al. The role of E-quality within the consumer decision making process. Int J Oper Prod Manage. 2014;34(12):1506–1536.
   Web of Science ®Google Scholar
• Whitten D, Hightower R, Sayeed L. Mobile device adaptation efforts: the impact of hedonic and utilitarian value. J Comput Inf Syst. 2014;55(1):48–58.
   Web of Science ®Google Scholar
• Williams MD, Slade EL, Dwivedi YK. Consumers’ intentions to use e-readers. J Comput Inf Syst. 2014;54(2):66–76.
   Web of Science ®Google Scholar
• Xu C, Peak D, Prybutok V. A customer value, satisfaction, and loyalty perspective of mobile application recommendations. Decis Support Syst. 2015;79:171–183.
   Web of Science ®Google Scholar
• Zeithaml VA. Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. J Market. 1988;2–22.
   Google Scholar
• Zhao L, et al. Assessing the effects of service quality and justice on customer satisfaction and the continuance intention of mobile value-added services: An empirical test of a multidimensional model. Decis Support Syst. 2012;52(3):645–656.
   Web of Science ®Google Scholar
• Zhong B. From smartphones to iPad: Power users’ disposition toward mobile media devices. Comput Hum Behav. 2013;29(4):1742–1748.
   Web of Science ®Google Scholar
• Zhou T. An empirical examination of continuance intention of mobile payment services. Decis Support Syst. 2013;54(2):1085–1091.
   Web of Science ®Google Scholar
• Zhu K. The complementarity of information technology infrastructure and e-commerce capability: A resource-based assessment of their business value. J Manage Inf Syst. 2004;21(1):167–202.
   Web of Science ®Google Scholar
• Zviran M, Pliskin N, Levin R. Measuring user satisfaction and perceived usefulness in the ERP context. J Comput Inf Syst. 2005;45(3):43–52.
   Web of Science ®Google Scholar