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http://dx.doi.org/10.5850/JKSCT.2016.40.6.994

Impact of Review Characteristics on Female Consumer Perceptions of Review Usefulness and Patronage Intent of Online Stores Hosting the Reviews  

Hong, Heesook (Dept. of Clothing & Textiles, Jeju National University)
Kim, Hye-Shin (Dept. of Fashion and Apparel Studies, University of Delaware)
Publication Information
Journal of the Korean Society of Clothing and Textiles / v.40, no.6, 2016 , pp. 994-1009 More about this Journal
Abstract
Applying the S-O-R Model within an online context, a hypothesized model incorporates three review characteristics (perceived concreteness, exaggeration, and sufficient quantity of reviews) for apparel products in order to present their impact on consumer perceptions of review usefulness and consumer attitude toward and patronage intent for the online stores hosting the reviews. An online survey of Korean women (N=299) reported their experiences in purchasing apparel products online and reading apparel reviews on a regular basis. Testing of the hypothesized model showed the usefulness of reviews were determined by two review characteristics (S: perceived concreteness and sufficient quantity of reviews); however, the negative effect of exaggerated reviews were insignificant. In addition, the perceived usefulness of reviews (O-cognitive) hosted by an online store influenced online store attitude (O-affective) which subsequently led to online store patronage intent (R). This study systemically advances online retail literature by showing how the characteristics of online reviews (as a part of the online store environment) can influence attitude toward online stores and patronage intent for online stores. Long term relationships with consumers can be achieved through the building of mechanisms to enhance the perceived usefulness of reviews by employing the strategies of hosting concrete reviews and offering a sufficient quantity of reviews. This study addresses removes research gaps by testing an adapted the S-O-R Model that frames review information as an element of an online store environment using a large sample.
Keywords
Online reviews; Usefulness; Concreteness; Exaggeration; Quantity;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Lohse, G. L., & Spiller, P. (1999). Internet retail store design: How the user interface influences traffic and sales. Journal of Computer-Mediated Communication, 5(2). Retrieved May 28, 2015, from http://onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.1999.tb00339.x/full
2 Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: The MIT Press.
3 Mittal, B. (1989). Measuring purchase-decision involvement. Psychology and Marketing, 6(2), 147-162. doi:10.1002/mar.4220060206   DOI
4 Monroe, K. B., & Guiltinan, J. P. (1975). A path-analytic exploration of retail patronage influences. Journal of Consumer Research, 2(1), 19-28. doi:10.1086/208612   DOI
5 Mudambi, S. M., & Schuff, D. (2010). What makes a helpful online review? A study of customer reviews on Amazon. com. MIS Quarterly, 34(1), 185-200.   DOI
6 Mummalaneni, V. (2005). An empirical investigation of web site characteristics, consumer emotional states and online shopping behaviors. Journal of Business Research, 58(4), 526-532. doi:10.1016/S0148-2963(03)00143-7   DOI
7 Pan, Y., & Zinkhan, G. M. (2006). Determinants of retail patronage: A meta-analytical perspective. Journal of Retailing, 82(3), 229-243. doi:10.1016/j.jretai.2005.11.008   DOI
8 Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204. doi:10.1016/S0378-7206(01)00143-4   DOI
9 Babin, B. J., Hardesty, D. M., & Suter, T. A. (2003). Color and shopping intentions: The intervening effect of price fairness and perceived affect. Journal of Business Research, 56(7), 541-551. doi:10.1016/S0148-2963(01)00246-6   DOI
10 Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530-545. doi:10.1287/mnsc.29.5.530   DOI
11 Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum Associates.
12 Chang, H. H., & Chen, S. W. (2008). The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review, 32(6), 818-841. doi:10.1108/14684520810923953   DOI
13 Cheung, C. M. K., Lee, M. K. O., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18(3), 229-247. doi:10.1108/10662240810883290   DOI
14 Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13(4), 9-38. doi:10.2753/JEC1086-4415130402   DOI
15 Corbitt, B. J., Thanasankit, T., & Yi, H. (2003). Trust and e-commerce: A study of consumer perceptions. Electronic Commerce Research and Applications, 2(3), 203-215. doi:10.1016/S1567-4223(03)00024-3   DOI
16 Petty, R. E., & Cacioppo, J. T. (1984). The effects of involvement on responses to argument quantity and quality: Central and peripheral routes to persuasion. Journal of Personality and Social Psychology, 46(1), 69-81. doi: 10.1037/0022-3514.46.1.69   DOI
17 Park, D. H., & Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399-410. doi: 10.1016/j.elerap.2007.12.001   DOI
18 Park, D. H., & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electronic Commerce Research and Applications, 7(4), 386-398. doi:10.1016/j.elerap.2007.11.004   DOI
19 Park, D. H., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125-148. doi:10.27 53/JEC1086-4415110405   DOI
20 Retail Everywhere: Omni-Channel Apparel Shopping. (2013, June 17). Lifestyle Monitor. Retrieved May 28, 2015, from http://lifestylemonitor.cottoninc.com/retail-everywhereomni-channel-apparel-shopping
21 Richard, M. O. (2005). Modeling the impact of internet atmospherics on surfer behavior. Journal of Business Research, 58(12), 1632-1642. doi:10.1016/j.jbusres.2004.07.009   DOI
22 Schindler, R. M., & Bickart, B. B. (2002). Characteristics of online consumer comments valued for hedonic and utilitarian shopping tasks. In S. M. Broniarczyk & K. Nakamoto (Eds.), Advances in Consumer Research, Vol. 29 (pp. 428-430). Valdosta, GA: Association for Consumer Research.
23 Eagley, A. H., & Chaiken, S. (2007). The advantages of an inclusive definition of attitude. Social Cognition, 25(5), 582-602. doi:10.1521/soco.2007.25.5.582   DOI
24 Dabholkar, P. (2006). Factors influencing consumer choice of a "Rating Web Site": An experimental investigation of an online interactive decision aid. Journal of Marketing Theory and Practice, 14(4), 259-273. doi:10.2753/ MTP1069-6679140401   DOI
25 Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi:10.2307/249008   DOI
26 Dizen, M., & Berenbaum, H. (2008). Extreme outcome expectations and affect intensity. Cognition & Emotion, 22 (6), 1130-1148. doi:10.1080/02699930701665010   DOI
27 Donovan, R. J., & Rossiter, J. R. (1982). Store atmosphere: An environmental psychology approach. Journal of Retailing, 58(1), 34-57.
28 Donovan, R. J., Rossiter, J. R., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing behavior. Journal of Retailing, 70(3), 283-294. doi:10.1016/0022-4359(94)90037-X   DOI
29 Eastlick, M. A., & Liu, M. (1997). The Influence of store attitudes and other nonstore shopping patterns on patronage of television shopping programs. Journal of Interactive Marketing, 11(3), 14-24. doi:10.1002/(SICI)1522-7138(199722)11:3<14::AID-DIR4>3.0.CO;2-#   DOI
30 Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2001). Atmospheric qualities of online retailing: A conceptual model and implications. Journal of Business Research, 54(2), 177-184. doi:10.1016/S0148-2963(99)00087-9   DOI
31 Shim, S., & Kotsiopulos, A. (1992). Patronage behavior of apparel shopping: Part II. Testing patronage model of consumer behavior. Clothing and Textiles Research Journal, 10(2), 59-64. doi:10.1177/0887302X9201000209   DOI
32 Schindler, R. M., & Bickart, B. B. (2005). Published word of mouth: Referable, consumer-generated information on the internet. In C. P. Haugtvedt, K. A. Machleit, & R. Yalch (Eds.), Online consumer psychology: Understanding and influencing consumer behavior in the virtual world (1st ed., pp. 35-62). Mahwah, NJ: Lawrence Erlbaum Associates.
33 Sen, S. (2008). Determinants of consumer trust of virtual word-of-mouth: An observation study from a retail website. The Journal of American Academy of Business, 14 (1), 30-35.
34 Sher, P. J., & Lee, S. H. (2009). Consumer skepticism and online reviews: An Elaboration Likelihood Model perspective. Social Behavior and Personality: An international Journal, 37(1), 137-144. doi:10.2224/sbp.2009.37.1.137   DOI
35 South Korea No. 1 in mobile web use. (2012, August 14). eMarketer. Retrieved May 28, 2015, from http://www.emarketer.com/Article/South-Korea-No-1-Mobile-Web-Use/1009262
36 Spiggle, S., & Sewall, M. A. (1987). A choice sets model of retail selection. Journal of Marketing, 51(2), 97-111. doi:10.2307/1251132   DOI
37 Srinivasan, S. S., Anderson, R., & Ponnavolu, K. (2002). Customer loyalty in e-commerce: An exploration of its antecedents and consequences. Journal of Retailing, 78 (1), 41-50. doi:10.1016/S0022-4359(01)00065-3   DOI
38 Statistics Korea. (2012, May 18). 2012년 1/4분기 가계동향 [2012 first quarter Korean household income and expenditure trend]. Statistics Korea. Retrieved July 20, 2013, from http://kostat.go.kr/portal/korea/kor_nw/2/4/1/index.board?bmode=read&aSeq=256098&pageNo=3&rowNum=10&amSeq=&sTarget=&sTxt=
39 Exaggerate. (n.d.). Merriam-Webster. Retrieved May 27, 2015, from http://www.merriam-webster.com/dictionary/exaggerate
40 Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2003). Empirical testing of a model of online store atmospherics and shopper responses. Psychology and Marketing, 20(2), 139-150. doi:10.1002/mar.10064   DOI
41 Flavian, C., Guinaliu, M., & Gurrea, R. (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   DOI
42 Gauri, D. K., Bhatnagar, A., & Rao, R. (2008). Role of word of mouth in online store loyalty. Communications of the ACM, 51(3), 89-91. doi:10.1145/1325555.1325572   DOI
43 Hong, H., & Jin, I. (2011). An exploratory study of important information on consumer reviews in internet shopping. Journal of the Korean Society of Clothing and Textiles, 35(7), 761-774. doi:10.5850/JKSCT.2011.35.7.761   DOI
44 Grimes, M. (2012, April 10). Nielsen: Global consumers' trust in 'earned' advertising grows in importance. nielsen. Retrieved May 27, 2015, from http://www.nielsen.com/us/en/press-room/2012/nielsen-global-consumers-trust-in-earned-advertising-grows.html
45 Ha, Y., & Lennon, S. J. (2010). Online visual merchandising (VMD) cues and consumer pleasure and arousal: Purchasing versus browsing situation. Psychology and Marketing, 27(2), 141-165. doi:10.1002/mar.20324   DOI
46 Hong, H. (2011). Classification of consumer review information based on satisfaction/dissatisfaction with availability/non-availability of information. Journal of the Korean Society of Clothing and Textiles, 35(9), 1099-1111. doi:10.5850/JKSCT.2011.35.9.1099   DOI
47 Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: An initial examination. Journal of Retailing, 76(3), 309-322. doi:10.1016/S0022-4359(00)00035-X   DOI
48 Statistics Korea. (2014, February 25). 2013년 연간 및 4/4분기 전자상거래 및 사이버쇼핑 동향 [2013 and 4th quarter sales trends in electronic commerce and cyber shopping]. Statistics Korea. Retrieved December 9, 2016, from http://kostat.go.kr/portal/korea/kor_nw/2/11/1/index.board?bmode=read&aSeq=311839
49 Summers, T. A., & Wozniak, P. J. (1990). Discount store patronage preferences of rural and urban woman. Clothing and Textiles Research Journal, 8(3), 1-6. doi:10.1177/0887302X9000800301   DOI
50 Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: an integrated approach to knowledge adoption. Information Systems Research, 14(1), 47-65. doi:10.1287/isre.14.1.47.14767   DOI
51 Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & Management, 41(6), 747-762. doi:10.1016/j.im.2003.08.011   DOI
52 Wagner, M. (2008, January 31). The power of customer reviews. Internet Retailer. Retrieved May 28, 2015, from http://www.internetretailer.com/2008/01/31/the-power-of-customer-reviews
53 Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102. doi:10.1287/isre.1050.0042   DOI
54 Kim, J., & Lennon, S. J. (2013). Effects of reputation and website quality on online consumers' emotion, perceived risk and purchase intention: Based on the stimulus-organism-response model. Journal of Research in Interactive Marketing, 7(1), 33-56. doi:10.1108/17505931311316734   DOI
55 Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. doi:10.1080/10705519909540118   DOI
56 Huang, E. (2008). Use and gratification in e-consumers. Internet Research, 18(4), 405-426. doi:10.1108/1066224 0810897817   DOI
57 Hulland, J., Chow, Y. H., & Lam, S. (1996). Use of causal models in marketing research: A review. International Journal of Research in Marketing, 13(2), 181-197. doi: 10.1016/0167-8116(96)00002-X   DOI
58 Kim, J. H., & Lennon, S. J. (2010). Information available on a web site: Effects on consumers' shopping outcomes. Journal of Fashion Marketing and Management: An International Journal, 14(2), 247-262. doi:10.1108/13612021011046093   DOI
59 Wolfinbarger, M., & Gilly, M. C. (2001). Shopping online for freedom, control and fun. California Management Review, 43(2), 34-55. doi:10.2307/41166074   DOI
60 Yun, Z. S., & Good, L. K. (2007). Developing customer loyalty from e-tail store image attributes. Managing Service Quality: An International Journal, 17(1), 4-22. doi: 10.1108/09604520710720647   DOI
61 Kim, J. H., Kim, M., & Lennon, S. J. (2009). Effects of web site atmospherics on consumer responses: Music and product presentation. Direct Marketing: An International Journal, 3(1), 4-19. doi:10.1108/17505930910945705   DOI
62 Kline, R. B. (2004). Principles and practice of structural equation modeling (2nd ed.). New York, NY: Guilford Press.
63 Koernig, S. K. (2003). E-scapes: The electronic physical environment and service tangibility. Psychology and Marketing, 20(2), 151-167. doi:10.1002/mar.10065   DOI
64 Lee, E. J., & Shim, W. S. (2007). A study on the behavior characteristics of point of purchase, post purchase and trust evaluation of internet shopping afternotes. The e-Business Studies, 8(3), 155-170.
65 Koo, S. M., & Ju, S. H. (2010). The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention. Computers in Human Behavior, 26(3), 377-388. doi.org/10.1016/j.chb.2009.11.009   DOI
66 Korea Internet and Security Agency. (2013, December). Survey on the internet usage. KISA ISIS. Retrieved August 4, 2014, from http://isis.kisa.or.kr/board/?pageId=060100&bbsId=7&itemId=800&pageIndex=
67 Korgaonkar, P. K., Lund, D., & Price, B. (1985). A structural equation approach toward examination of store attitude and store patronage behavior. Journal of Retailing, 61 (2), 39-60.
68 Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: a methodology for information quality assessment. Information & Management, 40(2), 133-146. doi: 10.1016/S0378-7206(02)00043-5   DOI
69 Lindner, M. (2016, January 29). Online sales will reach $523 billion by 2020 in the U.S. Internet Retailer. Retrieved December 9, 2016, from https://www.internetretailer.com/2016/01/29/online-sales-will-reach-523-billion-2020-us