Electronic Commerce Research

, Volume 16, Issue 3, pp 297–333 | Cite as

Eyeing the web interface: the influence of price, product, and personal involvement

Article

Abstract

Although Internet retailing has become part of mainstream commerce, there is still lack of research related to web interface design as a function of product price, product complexity, and personal involvement of consumer with the product. Different types of products require different aspects of information and environment as demanded by consumers; thus, it is imperative for retailers to appropriately tailor their online presentation of products. Drawing from the elaboration likelihood model and media richness theory, we investigate the effectiveness of peripheral cue-dominated interfaces, balanced cue-dominated interfaces, and central cue-dominated interfaces on consumer purchase intention. Nearly 1000 subjects participated in this study over a period of 2 years. Our analyses provide support for the contention that the role of website cues (peripheral and central) on the consumer varies by the type of product. Our findings have implications for research and practice.

Keywords

Elaboration likelihood model (ELM) Media richness theory (MRT) Peripheral cues Central cues Web interface design Structural equation modeling 

Supplementary material

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Supplementary material 1 (DOCX 394 kb)
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Supplementary material 2 (DOCX 69 kb)
10660_2015_9200_MOESM3_ESM.docx (1.4 mb)
Supplementary material 3 (DOCX 1438 kb)

References

  1. 1.
    Agarwal, R., & Venkatesh, V. (2002). Assessing a firm’s web presence: A heuristic evaluation procedure for the measurement of usability. Information Systems Research, 13(2), 168–186.CrossRefGoogle Scholar
  2. 2.
    Andrews, J. C., & Durvasula, S. (1991). Suggestions for manipulating and measuring involvement in advertising message content. In R. H. Holman & M. R. Solomon (Eds.), Advances in consumer research. UT: Association for Consumer Research, Provo.Google Scholar
  3. 3.
    Bakos, J. Y. (1998). The emerging role of EM on the Internet. Communications of the ACM, 41(8), 35–42.CrossRefGoogle Scholar
  4. 4.
    Bansal, G., Zahedi, F. M., & Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49, 138–150.CrossRefGoogle Scholar
  5. 5.
    Bauer, R. A. (1960). Consumer behavior as risk-taking. In R. S. Hancock (Ed.), Dynamic marketing for a changing world (pp. 389–398). Chicago: American Marketing Association.Google Scholar
  6. 6.
    Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805–825.Google Scholar
  7. 7.
    Blasco-Arcas, L., Hernandez-Ortega, B., & Jimenez-Martinez, J. (2013). Adopting television as a new channel for e-commerce. The influence of interactive technologies on consumer behavior. Electronic Commerce Research, 13, 457–475.CrossRefGoogle Scholar
  8. 8.
    Boulding, W., & Kirmani, A. (1993). A consumer-side experimental examination of signaling theory: Do consumers perceive warranties as signals of quality? Journal of Consumer Research, 20, 111–123.CrossRefGoogle Scholar
  9. 9.
    Briñol, P., Petty, R. E., & Barden, J. (2007). Happiness versus sadness as a determinant of thought confidence in persuasion: A self-validation analysis. Journal of Personality and Social Psychology, 93(5), 711–727.CrossRefGoogle Scholar
  10. 10.
    Brynjolfsson, E., & Smith, M. (2000). Frictionless commerce? A comparison of Internet and conventional retailers. Management Science, 46, 563–585.CrossRefGoogle Scholar
  11. 11.
    Burke, R. R. (1995). Virtual shopping. OR/MS Today, 22(4), 28–34.Google Scholar
  12. 12.
    Cambell, D. J. (1988). Task complexity: A review and analysis. The Academy of Management Review, 13(1), 40–53.Google Scholar
  13. 13.
    Carlson, J. R., & Zmud, R. W. (1999). Channel expansion theory and the experiential nature of media perceptions. Academy of Management Journal, 42, 153–170.CrossRefGoogle Scholar
  14. 14.
    Chau, P. Y. K., Au, G., & Tam, K. Y. (2000). Impact of information presentation modes on online shopping: An empirical evaluation of a broadband interactive shopping service. Journal of Organizational Computing and Electronic Commerce, 10, 1–22.CrossRefGoogle Scholar
  15. 15.
    Chebat, J., Charlebois, M., & Gelinas-Chebat, C. (2001). What makes open vs. closed conclusion advertisements more persuasive? The moderating role of prior knowledge and involvement. Journal of Business Research, 53, 93–102.CrossRefGoogle Scholar
  16. 16.
    Chen, Y. H., & Barnes, S. (2007). Initial trust and online buyer behavior. Industrial Management Data Systems, 107(1), 21–36.CrossRefGoogle Scholar
  17. 17.
    Chen, M., & Ryu, Y. U. (2013). Facilitating effective user navigation through website structure improvement. IEEE Transactions on Knowledge and Data Engineering, 25(3), 571–588.CrossRefGoogle Scholar
  18. 18.
    Chen, Q., & Well, W. D. (1999). Attitude toward the site. Journal of Advertising Research, 5, 27–37.Google Scholar
  19. 19.
    Cho, C.-H. (1999). How advertising works on the WWW: Modified elaboration likelihood model. Journal of Current Issues and Research in Advertising, 21(1), 33–50.CrossRefGoogle Scholar
  20. 20.
    Collier, J. E., & Bienstock, C. C. (2006). Measuring service quality in E-Retailing. Journal of Service Research, 8(3), 260–275.CrossRefGoogle Scholar
  21. 21.
    Copeland, M. T. (1923). Relation of consumer’s buying habits to marketing method. Harvard Business Review, 1, 282–289.Google Scholar
  22. 22.
    Daft, R., & Lengel, R. (1986). Organizational information requirements, media richness, and structural design. Management Science, 32(5), 554–571.CrossRefGoogle Scholar
  23. 23.
    De Figueriredo, J. M. (2000). Finding sustainable profitability in electronic commerce. Sloan Management Review, 41(4), 41–52.Google Scholar
  24. 24.
    Edell, J. A., & Staelin, R. (1983). The information processing of pictures in print advertisements. Journal of Consumer Research, 10, 45–61.CrossRefGoogle Scholar
  25. 25.
    Elliott, M. T., & Speck, P. S. (2005). Factors that affect attitude toward a retail web site. Journal of Marketing Theory and Practice, 13(1), 40–51.CrossRefGoogle Scholar
  26. 26.
    Everard, A., & Galletta, D. F. (2005). How presentation flaws affect perceived site quality, trust, and intention to purchase from an online store. Journal of Management Information Systems, 22(3), 55–95.Google Scholar
  27. 27.
    Fang, X., & Holsapple, C. (2007). An empirical study of web site navigation structures’ impacts on web site usability. Decision Support Systems, 43, 476–491.CrossRefGoogle Scholar
  28. 28.
    Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 1(1), 39–50.CrossRefGoogle Scholar
  29. 29.
    Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.Google Scholar
  30. 30.
    Gregg, D. G., & Walczak, S. (2008). Dressing your online auction business for success: An experiment comparing two eBay businesses. MIS Quarterly, 32(3), 653–670.Google Scholar
  31. 31.
    Grewal, D., Gotlieb, J., & Marmorstein, H. (1994). The moderating effects of message framing and source credibility on the price-perceived risk relationship. Journal of Consumer Research, 21(June), 145–153.CrossRefGoogle Scholar
  32. 32.
    Grewal, D., Iyer, G., & Levy, M. (2004). Internet retailing: Enablers, limiters and market consequences. Journal of Business Research, 57(7), 703–713.CrossRefGoogle Scholar
  33. 33.
    Harrington, N. G., Lane, D. R., Donohew, L., & Zimmerman, R. S. (2006). An extension of the Activation model of information exposure: The addition of a cognitive variable to a model of attention. Media Psychology, 8, 139–164.CrossRefGoogle Scholar
  34. 34.
    Hassan, S., & Li, F. (2005). Evaluating the usability and content usefulness of web sites: A benchmarking approach. Journal of Electronic Commerce in Organizations, 3(2), 46–67.CrossRefGoogle Scholar
  35. 35.
    Hoque, A. Y., & Lohse, G. L. (1999). An information search cost perspective for designing interface for electronic commerce. Journal of Marketing Research, 36(3), 387–394.CrossRefGoogle Scholar
  36. 36.
    Huang, K.-L., Rust, C., & Press, M. (2003). Packaging design for e-commerce: Identifying new challenges and opportunities for online packaging. Working Paper. Sheffield Hallam University, Art and Design Research Centre, Sheffield.Google Scholar
  37. 37.
    Jahng, J., Jain, H., & Ramamurthy, K. (2001). The impact of electronic commerce environment on user behavior. E-service Journal, 1(1), 41–53.CrossRefGoogle Scholar
  38. 38.
    Jarvenpaa, S., & Dickson, G. W. (1988). Graphics and managerial decision-making: Research based guidelines. Communications of the ACM, 31(6), 764–774.CrossRefGoogle Scholar
  39. 39.
    Jarvenpaa, S. L., & Todd, P. A. (1997). Consumer reactions to electronic shopping on the World Wide Web. Journal of Electronic Commerce, 1(2), 59–88.CrossRefGoogle Scholar
  40. 40.
    Jarvenpaa, S. L., Tractinsky, N., Saarinen, L., & Vitale, M. (1999). Consumer trust in an Internet store: A cross-cultural validation. Journal of Computer Mediated Communication, 5(2), 1–37.Google Scholar
  41. 41.
    Jiang, Z., & Benbasat, I. (2007). The Effects of presentation formats and task complexity on online consumers’ product understanding. MIS Quarterly, 3(3), 475–500.Google Scholar
  42. 42.
    Johnson, E. J., & Payne, J. W. (1985). Effort and accuracy in choice. Management Science, 31(4), 395–414.CrossRefGoogle Scholar
  43. 43.
    Keng, C. J., Liao, T. H., & Yang, Y. I. (2012). The effects of sequential combinations of virtual experience, direct experience, and indirect experience: The moderating roles of need for touch and product involvement. Electronic Commerce Research, 12(2), 177–199.CrossRefGoogle Scholar
  44. 44.
    Kim, D., & Benbasat, I. (2003). Trust-Related arguments in Internet stores: A framework for evaluation. Journal of Electronic Commerce Research, 4(2), 49–64.Google Scholar
  45. 45.
    Kim, H.-W., Xu, Y., & Koh, J. (2004). A comparison of online trust building factors between potential customers and repeat customers. Journal of the Association for Information Systems, 5(10), 392–420.Google Scholar
  46. 46.
    Kirmani, A., & Rao, A. R. (2000). No pain, no gain: A critical review of the literature on signaling unobservable product quality. Journal of Marketing, 64, 66–80.CrossRefGoogle Scholar
  47. 47.
    Kotha, S., Rajgopal, S., & Venkatachalam, M. (2004). The role of online buying experience as a competitive advantage: Evidence from third party ratings for ecommerce firms. The Journal of Business, 77(S2), 109–113.CrossRefGoogle Scholar
  48. 48.
    Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–224.CrossRefGoogle Scholar
  49. 49.
    Kumar, N., & Benbasat, I. (2001). Shopping as experience and website as a social actor: web interface design and para-social presence. In ICIS 2001 Proceedings. Paper 54.Google Scholar
  50. 50.
    Kung, C.-Y., Wang, C.-M., & Lin, H.-J. (2006). The Effect of customers’ purchase willingness by applying adaptive sales interactive model. Journal of American Academy of Business, 8(1), 277–281.Google Scholar
  51. 51.
    Kurosu, M., & Kashimura, K. (1995). Apparent usability vs. inherent usability. In CHI’95 conference companion (pp. 292–293).Google Scholar
  52. 52.
    Kwon, O. B., Kim, C., & Lee, E. J. (2002). Impact of website information design factors on consumer ratings of web-based auction sites. Behavior & Information Technology, 21(6), 387–402.CrossRefGoogle Scholar
  53. 53.
    Lee, Y., & Kozar, K. (2006). Investigating the effect of website quality on e-business success: An analytic hierarchy process (AHP) approach. Decision Support System, 42, 1383–1401.CrossRefGoogle Scholar
  54. 54.
    Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You have 50 milliseconds to make a good first impression. Behaviour & Information Technology, 25(2), 115–126.CrossRefGoogle Scholar
  55. 55.
    Loiacono, E., Watson, R., & Goodhue, D. (2007). Webqual: An instrument for consumer evaluation of web sites. International Journal of Electronic Commerce, 11(3), 51–87.CrossRefGoogle Scholar
  56. 56.
    Lowengart, O., & Tractinsky, N. (2001). Differential effect of product category on shoppers selection of web-based store: Probablistic modeling approach. Journal of Electronic Commerce Research, 2(4), 12–26.Google Scholar
  57. 57.
    Lowry, P. B., Vance, A., Moody, G., Beckman, B., & Read, A. (2008). Explaining and predicting the impact of branding alliances and web site quality on initial consumer trust of e-commerce web sites. Journal of Management Information Systems, 24(4), 199–224.CrossRefGoogle Scholar
  58. 58.
    Lynch, J. G., Jr., & Ariely, D. (2000). Wine online: Search cost and competition on price, quality, and distribution. Marketing Science, 19(winter), 83–103.CrossRefGoogle Scholar
  59. 59.
    McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359.CrossRefGoogle Scholar
  60. 60.
    McMillan, S. J., Jang-Sun, H., & Guiohk, L. (2003). Effects of structural and perceptual factors on attitudes toward the website. Journal of Advertising Research, 43(4), 400–409.CrossRefGoogle Scholar
  61. 61.
    Melnik, M. I., & Alm, J. (2002). Does a seller’s ecommerce reputation matter? Evidence from eBay auctions. Journal of Industrial Economics, 50(3), 337–349.CrossRefGoogle Scholar
  62. 62.
    Montoya-Weiss, M., Voss, G. B., & Grewal, D. (2003). Determinants of online channel use and overall satisfaction with a relational, multichannel service provider. Journal of the Academy of Marketing Science, 31(4), 448–458.CrossRefGoogle Scholar
  63. 63.
    Morris, J. D., Woo, C. M., & Singh, A. J. (2005). Elaboration likelihood model: A missing intrinsic emotional implication. Journal of Targeting, Measurement, and Analysis for Marketing, 14(1), 79–98.CrossRefGoogle Scholar
  64. 64.
    Murphy, P. E., & Enis, M. (1986). Classifying product strategically. Journal of Marketing, 50(July), 24–42.CrossRefGoogle Scholar
  65. 65.
    Nadkarni, S., & Gupta, R. (2007). A task-based model of perceived website complexity. MIS Quarterly, 31(3), 501–524.Google Scholar
  66. 66.
    Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78, 311–329.CrossRefGoogle Scholar
  67. 67.
    Nicolaou, A. I., Ibrahim, M., & Van Heck, E. (2013). Information quality, trust, and risk perceptions in electronic data exchanges. Decision Support Systems, 54(2), 986–996.CrossRefGoogle Scholar
  68. 68.
    Nunnally, J. (1978). Psychomeric theory. New York: McGraw-Hill.Google Scholar
  69. 69.
    Palmer, J. W., & Griffith, D. A. (1998). An emerging model of web site design for marketing. Communications of the ACM, 41(March), 44–51.CrossRefGoogle Scholar
  70. 70.
    Park, C. W., & Mittal, B. (1985). A theory of involvement in consumer behavior: Problems and issues. Research in Consumer Behavior, 1, 201–231.Google Scholar
  71. 71.
    Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 69–103.Google Scholar
  72. 72.
    Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115–143.Google Scholar
  73. 73.
    Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105–136.Google Scholar
  74. 74.
    Peracchio, L. A., & Meyers-Levy, J. (2005). Using stylistic properties of ad pictures to communicate with consumers. Journal of Consumer Research, 32, 29–40.CrossRefGoogle Scholar
  75. 75.
    Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: Classic and contemporary approaches. Dubuque, IA: William C. Brown.Google Scholar
  76. 76.
    Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 19, pp. 123–205). San Diego: Academic Press.Google Scholar
  77. 77.
    Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. New York: Springer.CrossRefGoogle Scholar
  78. 78.
    Petty, R. E., Cacioppo, J. T., & Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of Personality and Social Psychology, 41, 847–855.CrossRefGoogle Scholar
  79. 79.
    Piccoli, G. M., Brohman, K., Watson, R. T., & Parasuraman, A. (2004). Net-based customer service systems: Evolution and revolution in web site functionalities. Decision Sciences, 35(3), 423–455.CrossRefGoogle Scholar
  80. 80.
    Pinsonneault, A., Li, S., & Ouyang, Z. (2002). A study of the effects of Web site richness on learning about products and browsing satisfaction. Working Paper. McGill University, Montreal.Google Scholar
  81. 81.
    Rao, A. R., & Monroe, K. B. (1989). The effect of price, brand name, and store name on buyers perceptions of product quality: An integrative review. Journal of Marketing Research, 26, 351–357.CrossRefGoogle Scholar
  82. 82.
    Rao, A. R., Qu, L., & Ruekert, R. W. (1999). Signaling unobservable product quality through a brand ally. Journal of Marketing Research, 36(2), 258–268.CrossRefGoogle Scholar
  83. 83.
    Richard, M. O., & Chandra, R. (2005). A model of consumer web navigational behavior: conceptual development and application. Journal of Business Research, 58(8), 1019–1029.CrossRefGoogle Scholar
  84. 84.
    Richardson, P. S., Dick, A. S., & Jain, A. K. (1994). Extrinsic and intrinsic cue effects on perceptions of store brand quality. Journal of Marketing, 58(4), 28–36.CrossRefGoogle Scholar
  85. 85.
    Riedl, R., Hubert, M., & Kenning, P. (2010). Are there neural gender differences in online trust? An fMRI study on the perceived trustworthiness of eBay offers. MIS Quarterly, 34(2), 397–428.Google Scholar
  86. 86.
    Rose, G., Meuter, M., & Curran, J. (2005). On-Line waiting: The role of download time and other important predictors on attitude toward e-retailers. Psychology and Marketing, 22(2), 127–151.CrossRefGoogle Scholar
  87. 87.
    Rosen, K. T., & Howard, A. L. (2000). E-retail: Gold rush or fool’s gold? California Management Review, 42(3), 72–101.CrossRefGoogle Scholar
  88. 88.
    Schlosser, R. W., Wendt, O., Bhavnani, S., & Nail-Chiwetalu, B. J. (2006). The use of information seeking strategies in evidence-based practice: The case of pearl growing. International Journal of Language and Communication Disorders, 41, 567–582.CrossRefGoogle Scholar
  89. 89.
    Segars, A. H. (1997). Assessing the unidimensionality of measurement: A paradigm and illustration within the context of information systems research. Omega, 25(1), 107–121.CrossRefGoogle Scholar
  90. 90.
    Simon, S. J., & Peppas, S. C. (2004). An examination of media richness theory in product Web site design: An empirical study. Emerald Publishing Info, 6(4), 270–281.Google Scholar
  91. 91.
    Song, J., & Zahedi, F. M. (2005). A theoretical approach to Web design in e-commerce: A belief reinforcement model. Management Science, 51(8), 1219–1235.CrossRefGoogle Scholar
  92. 92.
    Strader, T. J., & Shaw, M. J. (1997). Characteristics of electronic markets. Decision Support Systems, 21, 185–198.CrossRefGoogle Scholar
  93. 93.
    Suh, K. S. (1999). Impact of communication medium on task performance and satisfaction: An examination of media-richness theory. Information & Management, 35, 295–312.CrossRefGoogle Scholar
  94. 94.
    Suki, N. M. (2013). Consumer shopping behaviour on the Internet: Insights from Malaysia. Electronic Commerce Research, 13(4), 1–15.CrossRefGoogle Scholar
  95. 95.
    Sweeny, 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, 77–105.CrossRefGoogle Scholar
  96. 96.
    Talia, L., & Tractinsky, N. (2004). Assessing dimensions of perceived visual aesthetics of web sites. International Journal of Human-Computer Studies, 60(3), 269–298.CrossRefGoogle Scholar
  97. 97.
    Tam, K. Y., & Ho, S. Y. (2005). Web personalization as a persuasion strategy: An elaboration likelihood model perspective. Information Systems Research, 16(3), 271–291.CrossRefGoogle Scholar
  98. 98.
    Teas, R. K., & Agarwal, S. (2000). The effects of extrinsic product cues on consumer perceptions of quality, sacrifice, and value. Journal of Academy of Marketing Science, 28(2), 278–290.CrossRefGoogle Scholar
  99. 99.
    Tractinsky, N., Katz, A. S., & Ikar, D. (2000). What is beautiful is usable. Interacting with Computers, 13, 127–145.CrossRefGoogle Scholar
  100. 100.
    Trevino, L., Lengel, R., & Daft, R. (1987). Media symbolism, media richness, and media choice in organizations. Communications Research, 14(5), 553–574.CrossRefGoogle Scholar
  101. 101.
    Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12(1), 41–48.CrossRefGoogle Scholar
  102. 102.
    Venkatesan, M., & Anderson, B. B. (1985). Time budgets and consumer services. In T. M. Bloch, G. D. Upah, & V. A. Zeithaml (Eds.), Services marketing in a changing environment proceedings. Chicago: American Marketing Association.Google Scholar
  103. 103.
    Venkatesh, V., & Morris, M. G. (2000). Why don’’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115–139.CrossRefGoogle Scholar
  104. 104.
    Voss, J., & Blackwell, R. (1979). The role of time resources in consumer behavior. Paper presented at the special educators’ theory conference of the American Marketing Association, Phoenix, AZ.Google Scholar
  105. 105.
    Wells, J. D., Valacich, J. S., & Hess, T. J. (2011). What signals are you sending? How website quality influences perceptions of product quality and purchase intentions. MIS Quarterly, 35(2), 373–396.Google Scholar
  106. 106.
    Westland, J. C. (2010). Lower bounds on sample size in structural equation modeling. Electronic Commerce Research and Applications, 9(6), 476–487.CrossRefGoogle Scholar
  107. 107.
    Westland, J. C. (2015). Structural equation models: From paths to networks. New York: Springer International Publishing. doi: 10.1007/978-3-319-16507-3.CrossRefGoogle Scholar
  108. 108.
    Wright, A. A., & Lynch, J. G., Jr. (1995). Communication effects of advertising versus direct experience when both search and experience attributes are present. Journal of Consumer Research, 21, 708–718.CrossRefGoogle Scholar
  109. 109.
    Yang, Z., & Jun, M. (2002). Consumer perception of e-service quality: From Internet purchaser and non-purchaser perspectives. Journal of Business Strategies, 19(1), 19–41.Google Scholar
  110. 110.
    Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(December), 341–352.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Dauch College of Business and EconomicsAshland UniversityAshlandUSA
  2. 2.Sheldon B. Lubar School of BusinessUniversity of Wisconsin-MilwaukeeMilwaukeeUSA
  3. 3.Department of Kinesiology, College of Health SciencesUniversity of Wisconsin-MilwaukeeMilwaukeeUSA

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