Effect of brand familiarity, experience and information on online apparel purchase
Abstract
Purpose: The purpose of this study is to examine the effect of brand familiarity, the number of pieces of product information presented on a web site, and previous online apparel shopping experience on perceived risk and purchase intention. Design/methodology/approach: The experiment was 2 (brand familiarity)×2 (information availability) factorial design and 166 students participated in this study. Findings: Multivariate and univariate analyses found a significant effect of brand familiarity and previous experience on perceived risk and purchase intention, and no effect of amount of information on perceived risk and purchase intention. Research limitations/implications: Participants may not have carefully considered the product information because the experiment was not an actual purchase situation, although a scenario was given. In future studies, creating an actual purchase situation may be necessary to investigate the effect of the amount of information available on the web sites on perceived risk and decision making. Practical implications: The present study suggests that internet retailers should capitalize on the power of their brand names. Multi‐channel retailers may be able to derive significant advantages from brand familiarity among their customers. Orginality/value: This study has added to the in‐home shopping literature by extending findings of previous research to internet shopping. Findings suggest that internal information, specifically familiarity with brands offered online and previous experience of shopping online, influence perceptions of risk associated with shopping online, as well as intentions to purchase online.
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Brand familiarity reduces perceived risk in consumer purchases of online clothes and intimate purchases.
“For instance, brand familiarity reduces perceived risk in consumer purchases of online clothes [53] and intimate purchases [54].”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [53]
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“(Woodruff et al., 1983; Flint et al., 1997; Park and Stoel, 2005; Felcher et al., 2001).”
BackgroundAssessing customers' attitude towards online apparel shopping: A three-way interaction model
Patel, A. K., Singh, A., Rana, N. P., Parayitam, S., Dwivedi, Y. K., & Dutot, V. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113917 · Cited by 47 · see citing works
Pilgrimage: What drives pilgrim experiential supportive intentions?
Wu, H., Chang, Y.-Y., & Wu, T. (2018) · Journal of Hospitality and Tourism Management · doi:10.1016/j.jhtm.2018.11.001 · Cited by 45 · see citing works
Jo, W., Kim, J., & Choi, J. (2020) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-05-2019-0317 · Cited by 45 · see citing works
Koronaki, E., Vlachvei, A., & Panopoulos, A. (2023) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2023.101242 · Cited by 44 · see citing works
What makes services customers say “buy it with a mobile phone”?
Gutiérrez, S. S. M., Prodanova, J., & López‐Catalán, B. (2016) · Journal of Services Marketing · doi:10.1108/jsm-02-2015-0081 · Cited by 44 · see citing works
Understanding of online hotel booking process: A multiple method approach
Park, S., Yin, Y., & Son, B. (2018) · Journal Of Vacation Marketing · doi:10.1177/1356766718778879 · Cited by 44 · see citing works
“The arbitrary decision makers were likely to possess higher levels of knowledge about the travel destination and online booking experiences than the standard decision makers and the comprehensive decision makers in the same lines with Park and Stoel (2005).”
BackgroundA matter of value? Predicting channel preference and multichannel behaviors in retail
Acquila-Natale, E., & Iglesías-Pradas, S. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120401 · Cited by 44 · see citing works
Bapat, D. M. (2021) · International Journal of Bank Marketing · doi:10.1108/ijbm-12-2020-0575 · Cited by 42 · see citing works
More Personalized, More Useful? Reinvestigating Recommendation Mechanisms in E-Commerce
Nguyen, T. K., & Hsu, P. (2022) · International Journal of Electronic Commerce · doi:10.1080/10864415.2021.2010006 · Cited by 42 · see citing works
“Resources from external searches are also available from reference groups (e.g., friends, experts) and/or other marketplaces (e.g., product descriptions, sales performance) [47].”
BackgroundLee, S., & Han, H. (2022) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2022.103292 · Cited by 42 · see citing works
Toufaily, É., & Pons, F. (2016) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.09.011 · Cited by 42 · see citing works
When do high prices lead to purchase intention? Testing two layers of moderation effects
Son, J., & Jin, B. E. (2019) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-07-2018-0271 · Cited by 42 · see citing works
Factors Influencing Italian Consumers’ Willingness to Pay for Eggs Enriched with Omega-3-Fatty Acids
Palmieri, N., Stefanoni, W., Latterini, F., & Pari, L. (2022) · Foods · doi:10.3390/foods11040545 · Cited by 42 · see citing works
Asante, I. O., Jiang, Y., & Miao, M. (2023) · Psychology and Marketing · doi:10.1002/mar.21881 · Cited by 41 · see citing works
Zhang, B., Ritchie, B. W., Mair, J., & Driml, S. (2019) · Journal of Sustainable Tourism · doi:10.1080/09669582.2019.1629448 · Cited by 41 · see citing works
“Given the higher risk and uncertainty of online purchases, past purchase experience could help reduce the uncertainty and perceived risk of the product, and consumers’ purchase intention (Jihye & Leslie, 2005; Shim & Drake, 1990).”
BackgroundLiu, Y., Gao, Q., & Rau, P. P. (2021) · Travel Behaviour and Society · doi:10.1016/j.tbs.2021.10.009 · Cited by 41 · see citing works
Kim, D. H., & Song, D. (2018) · Journal of Brand Management · doi:10.1057/s41262-018-0134-0 · Cited by 40 · see citing works
Kadić‐Maglajlić, S., Arslanagić-Kalajdžić, M., Micevski, M., Michaelidou, N., & Nemkova, E. (2015) · Journal of Business Ethics · doi:10.1007/s10551-015-2755-5 · Cited by 39 · see citing works
“We also included several variables in our model to control for possible confounds (e.g. Christodoulides et al. 2013; Dao et al. 2014; Park and Stoel 2005), including education, income, Facebook use and previous experience with the brand.”
MethodShang, Q., Jin, J. K., & Qiu, J. (2019) · Neuroscience Letters · doi:10.1016/j.neulet.2019.134665 · Cited by 39 · see citing works
The Digital Transformation of the Retail Electricity Market in Spain
Chaparro-Peláez, J., Acquila-Natale, E., Hernández-García, Á., & Iglesías-Pradas, S. (2020) · Energies · doi:10.3390/en13082085 · Cited by 39 · see citing works
“Integrated promotion takes full advantage of the omnichannel store as a platform to entice consumers into using alternative channels [43,60,61], increase the reach of promotional actions and campaigns and reduce consumers’ perception of risk in channels with which they have no previous experience [62,63].”
BackgroundRural Consumers' Online Shopping for Food and Fiber Products as a Form of Outshopping
Lennon, S. J., Ha, Y., Johnson, K. K. P., Jasper, C. R., Damhorst, M. L., & Lyons, N. N. (2008) · Clothing and Textiles Research Journal · doi:10.1177/0887302x07313625 · Cited by 38 · see citing works
“Keywords: rural consumers, online shopping, clothing shopping, outshopping, satisfaction 3 4 Le n n o n e t a L. i n Cl o th i ng & te x t i l e s Re s e aR C h Jou R na l 27 (2009) Shifting demographic trends reveal increasing numbers of rural elderly with disabilities (DePoy & Gilson, 2003), a…”
BackgroundAlhabash, S., McAlister, A. R., Kim, W., Lou, C., Cunningham, C., Quilliam, E. T., & Richards, J. I. (2016) · Journal of Interactive Advertising · doi:10.1080/15252019.2016.1160330 · Cited by 37 · see citing works
Analysis of E-service Quality through Online Shopping
Al-Nasser, M., Islam, R., Abidin, I. S. Z., Azam, M., & Prabhakar, A. C. (2015) · Research Journal of Business Management · doi:10.3923/rjbm.2015.422.442 · Cited by 36 · see citing works
Barnes, L. (2013) · Textile Progress · doi:10.1080/00405167.2013.868677 · Cited by 36 · see citing works
Information components of apparel retail web sites: task relevance approach
Kim, J.-H., Kim, M., & Lennon, S. J. (2007) · Journal of Fashion Marketing and Management · doi:10.1108/13612020710824562 · Cited by 36 · see citing works
Successful SME web design through consumer focus groups
Boluda, I. K., & López, N. V. (2011) · International Journal of Quality & Reliability Management · doi:10.1108/02656711111101728 · Cited by 35 · see citing works
“Website content is important especially for reducing perceived risk and eliminating barriers to purchase ( Park and Stoel, 2005”
BackgroundA systematic review of consumer information search in online and offline environments
Haridasan, A. C., Fernando, A. G., & Saju, B. (2021) · RAUSP Management Journal · doi:10.1108/rausp-08-2019-0174 · Cited by 34 · see citing works
“…2001) Consumers with higher previous internet experience will use online sources for information search and purchase when compared to others (Park & Stoel, 2005) Presence of experience simulation and prior experiences increases the time spent on a website (Huang et al., 2009) Internet…”
BackgroundHussein, R., & Hassan, S. S. (2018) · Journal of International Consumer Marketing · doi:10.1080/08961530.2018.1455549 · Cited by 34 · see citing works
“Park and Stoel (2005) indicate that one of the strategies used to decrease perceived risk and to increase purchase intention is to promote brand familiarity.”
Background
- Authors
- Park, J., & Stoel, L.
- Affiliations
- Iowa State University (US)
- The Ohio State University (US)
- ORCID
- Park, Jihye
- Venue
- International Journal of Retail & Distribution Management
- Publisher
- Emerald
- Published
- 2005-02-01
- Volume
- 33
- Issue
- 2
- Pages
- 148-160
- ISSN
- 0959-0552 (ISSN-L)
- OpenAlex
- W2061503235
- Cited by
- 348
- References
- 31
- Citations by year
- 2026: 6 · 2025: 13 · 2024: 15 · 2023: 15 · 2022: 21 · 2021: 25 · 2020: 16 · 2019: 24 · 2018: 22 · 2017: 12 · 2016: 18 · 2015: 22 · 2014: 22 · 2013: 21 · 2012: 14
- FWCI
- 21.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Retail & Distribution Management (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Retail Behavior Studies
- Keywords
- brand familiarity, online clothing shopping, risk perception, purchase intention, online shopping experience, internet retailers, purchase decision
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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