The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Factors that affect consumer trust in product quality: a focus on online reviews and shopping platforms
Open accessAbstract
The growing popularity of online shopping means that consumers must determine product quality after they make a purchase decision and receive the product, a situation that is directly related to the issue of consumers’ trust toward retailers. This study analyzes the marginal willingness to pay for attributes that influence consumer trust and purchasing decisions regarding products whose quality can only be determined after they are purchased. We select six attributes that influence trust in online shopping: (1) price, (2) number of reviews, (3) “star” rating, (4) review type (i.e., text, picture, and video), (5) length of text reviews, and (6) shopping platform. We conduct a conjoint survey by categorizing brands as famous and nonfamous and analyze the survey data using a multinominal logit model. The results reveal that consumers prefer high star ratings, a large number of reviews, and a trustworthy shopping platform, even if other similar products are less expensive. Additionally, feeling confident about a product’s quality is more difficult for consumers in the case of nonfamous brands, which they have not experienced, compared with famous brands. The findings indicate that when consumers purchase products from nonfamous brands they are willing to pay more for all six attributes. These results can help retailers establish pricing strategies based on the value of trust by considering customer experience.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A New Approach to Consumer Theory
Lancaster, K. J. (1966) · Journal of Political Economy · doi:10.1086/259131 · Cited by 8,471
Consumer trust in an Internet store
Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000) · Information Technology and Management · doi:10.1023/a:1019104520776 · Cited by 2,577
Hong, I. B., & Cho, H. (2011) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2011.02.001 · Cited by 590
Flagged first, then by citations
Research works printed but not linked: 42
- Abedin E, Mendoza A & Karunasekera S (2019) What makes a review credible? Heuristic and systematic factors for the credibility of online reviews. In: Australasian conference on information systems
- Agrawal SR, Mittal D (2022) Optimizing customer engagement content strategy in retail and E-tail: available on online product review videos. J Retail Consum Serv 67:102966 · DOI
- Alba J, Lynch J, Weitz B, Janiszewski C, Lutz R, Sawyer A, Wood S (1997) Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. J Market 61(3):38–53 · DOI
- Bei LT, Chen EY, Widdows R (2004) Consumers’ online information search behavior and the phenomenon of search vs. experience products. J Fam Econ Issues 25(4):449–467
- Cao Q, Duan W, Gan Q (2011) Exploring determinants of voting for the “helpfulness” of online user reviews: a text mining approach. Decis Support Syst 50(2):511–521 · DOI
- Duan Y, Chen C, Huo J (2019) The impact of monetary rewards for online reviews. Asia Pac J Market Logist 31(5):1486–1515 · DOI
- Duan Y, Liu T, Mao Z (2022) How online reviews and coupons affect sales and pricing: An empirical study based on e-commerce platform. J Retail Consum Serv 65:102846 · DOI
- Fernandes S, Venkatesh VG, Panda R, Shi Y (2021) Measurement of factors influencing online shopper buying decisions: a scale development and validation. J Retail Consum Serv 59:102394 · DOI
- Flanagin AJ, Metzger MJ, Pure R, Markov A, Hartsell E (2014) Mitigating risk in ecommerce transactions: perceptions of information credibility and the role of user-generated ratings in product quality and purchase intention. Electron Commer Res 14(1):1–23 · DOI
- Grabner-Kraeuter S (2002) The role of consumers’ trust in online-shopping. J Bus Ethics 39(1):43–50 · DOI
- Green PE, Srinivasan V (1978) Conjoint analysis in consumer research: issues and outlook. J Consum Res 5(2):103–123 · DOI
- Guo S, Wang M & Leskovec J (2011) The role of social networks in online shopping: information passing, price of trust, and consumer choice. In: Proceedings of the 12th ACM Conference on Electronic Commerce. pp 157–166 · DOI
- Ho-Dac NN, Carson SJ, Moore WL (2013) The effects of positive and negative online customer reviews: do brand strength and category maturity matter? J Market 77(6):37–53 · DOI
- Hong S, Pittman M (2020) eWOM anatomy of online product reviews: interaction effects of review number, valence, and star ratings on perceived credibility. Int J Advert 39(7):892–920 · DOI
- Hu N, Liu L, Zhang JJ (2008) Do online reviews affect product sales? The role of reviewer characteristics and temporal effects. Inf Technol Manag 9:201–214 · DOI
- Huang P, Lurie NH, Mitra S (2009) Searching for experience on the web: an empirical examination of consumer behavior for search and experience goods. J Market 73(2):55–69 · DOI
- Keen C, Wetzels M, De Ruyter K, Feinberg R (2004) E-tailers versus retailers: which factors determine consumer preferences. J Bus Res 57(7):685–695 · DOI
- Kim BY, Kim J, Kan YY (2012) Analysis of consumer preferences for cosmetic essence-for-men via choice-based conjoint with new design of choice sets. Kor J Appl Stat 25(6):987–997 · DOI
- Kim HW, Xu Y, Gupta S (2012) Which is more important in Internet shopping, perceived price or trust? Electron Commer Res Appl 11(3):241–252 · DOI
- Kim S, Jones C (2009) Online shopping and moderating role of offline brand trust. Direct Market 3(4):282–300 · DOI
- Lackermair G, Kailer D, Kanmaz K (2013) Importance of online product reviews from a consumer’s perspective. Adv Econ Bus 1(1):1–5 · DOI
- Lau GT, Lee SH (1999) Consumers’ trust in a brand and the link to brand loyalty. J Mark Focused Manag 4:341–370 · DOI
- Liu H (2023) Comparative analysis of fresh food e-commerce brand attitudes based on STM theme model. PLoS ONE 18(3):e0282521 · DOI
- Liu Y, Du R (2019) The effects of image-based online reviews on customers’ perception across product type and gender. J Glob Inf Manag 27(3):139–158 · DOI
- Luan J, Yao Z, Zhao F, Liu H (2016) Search product and experience product online reviews: an eye-tracking study on consumers’ review search behavior. Comput Hum Behav 65:420–430 · DOI
- Mudambi SM, Schuff D (2010) Research note: what makes a helpful online review? A study of customer reviews on Amazon. com. MIS Q 34(1):185–200 · DOI
- Muslim M, Mubarok RR, Wijaya NHS (2019) The effect of brand image, brand trust and reference group on the buying decision of sneakers. Int J Financ Account Manag 1(2):105–118
- Nelson P (1970) Information and consumer behavior. J Polit Econ 78(2):311–329 · DOI
- Park M, Lennon SJ (2009) Brand name and promotion in online shopping contexts. J Fash Market Manag 13(2):149–160
- Pavlou PA, Liang H, Xue Y (2007) Understanding and mitigating uncertainty in online exchange relationships: a principal-agent perspective. MIS Q 31(1):105–136 · DOI · Paper page
- Qalati SA, Vela EG, Li W, Dakhan SA, Hong Thuy TT, Merani SH (2021) Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping. Cogent Bus Manag 8(1):1869363 · DOI
- Rha JY, Lee B, Nam Y, Yoon J (2021) COVID-19 and changes in Korean consumers’ dietary attitudes and behaviors. Nutr Res Pract 15(Suppl 1):S94–S109 · DOI
- Riasanow T, Ye HJ & Goswami S (2015). Generating trust in online consumer reviews through signaling: an experimental study. In: 2015 48th Hawaii international conference on system sciences. IEEE, p 3307–3316 · DOI
- Salehan M, Kim DJ (2016) Predicting the performance of online consumer reviews: a sentiment mining approach to big data analytics. Decis Support Syst 81:30–40 · DOI
- Sebastianelli R, Tamimi N (2018) E-tailer website attributes and trust: understanding the role of online reviews. Online Inf Rev 42(4):506–519 · DOI
- Tata SV, Prashar S, Gupta S (2020) An examination of the role of review valence and review source in varying consumption contexts on purchase decision. J Retail Consum Serv 52:101734 · DOI
- Wu TY, Lin CA (2017) Predicting the effects of eWOM and online brand messaging: source trust, bandwagon effect and innovation adoption factors. Telemat Inform 34(2):470–480 · DOI
- Wu J, Wu Y, Sun J, Yang Z (2013) User reviews and uncertainty assessment: a two stage model of consumers’ willingness-to-pay in online markets. Decis Support Syst 55(1):175–185 · DOI
- Xu P, Chen L, Santhanam R (2015) Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type. Decis Support Syst 73:85–96 · DOI
- Yi J, Oh YK (2021) The informational value of multi-attribute online consumer reviews: a text mining approach. J Retail Consum Serv 65:102519 · DOI
- Zhang X, Wang T (2021) Understanding purchase intention in o2o e-commerce: the effects of trust transfer and online contents. J Theor Appl Electron Commer Res 16(2):101–115 · DOI
- Zhu F, Zhang X (2010) Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J Market 74(2):133–148 · DOI
Cited by
Sorted by citations
Zhang, Y., Albattat, A., Rehman, A. U., & Azam, S. M. F. (2025) · Cogent Business & Management · doi:10.1080/23311975.2025.2582220 · Cited by 6
Metadata
- Authors
- Sung, E., Chung, W. Y., & Lee, D.
- Affiliations
- Sungkyunkwan University (KR)
- Corresponding author
- Chung, Won Young
- Venue
- Humanities and Social Sciences Communications
- Published
- 2023-11-01
- Volume
- 10
- Issue
- 1
- ISSN
- 2055-1045 (ISSN-L)
- 2662-9992
- OpenAlex
- W4388112622
- Cited by
- 61
- References
- 3
- Citations by year
- 2026: 21 · 2025: 23 · 2024: 17
- FWCI
- 16.11
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Humanities and Social Sciences Communications (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Keywords
- consumer trust, product quality, online reviews, e-commerce platforms, star ratings, review quantity, review types, price, famous brands, willingness to pay, purchase decision, customer experience, pricing strategy
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review