Complied by Belief Consistency: The Cognitive-Information Lens of User-Generated Persuasion
2. Theoretical Foundation
2.1. The Cognitive-Information Lens
|A trade-off between perceived costs and perceived benefits of information searching.||Review extremity and review count.|
Products types: search versus experience products.
|Review materials: online reviews of 6 products (3 experience and 3 search) on the Amazon website.|
Experience products: a music CD, an MP3 player, and a video game.
Search products: a digital camera, a cell phone, and a laser printer.
|Product type moderates the effect of review extremity on review helpfulness.|
Extreme ratings are less helpful than moderate ratings in the review evaluation of experience products.
Regarding the evaluation of review helpfulness, review count is better for examining search products than examining experience products.
|Explanatory and predictive models based on machine learning.||Review subjectivity features and review readability features.|
|Text mining and sentimental analysis.|
Review materials: a review set of selected products (e.g., audio and video players, digital cameras, and DVDs).
Context: Amazon website and its voting systems.
Measures of review helpfulness = [number of helpful votes/number of total votes] for a review.
|Reviews that mixed subjective with objective messages are perceived as more helpful.|||
|Dual process theories—elaboration likelihood model, heuristic systematic model.||Central cues: word count and the percentage of negative words.|
Peripheral cues: rating consistency, reviewer ranking, reviewer real name.
Product type: search versus experience, high-price versus low-price.
|Web data mining of reviews and reviewers from the 28 product categories on the Amazon website.||Two peripheral cues (e.g., rating consistency and reviewer credibility) and one central cue (e.g., review content) affect the helpfulness of reviews.|
Central cues are better to judge the review helpfulness of search and high-price products.
Peripheral cues are better to judge the review helpfulness of experience and low-price products.
|Bach’s (1967) helping behavior model.||Source-based review features.|
Content-based review features.
Review helpfulness is a formative construct
that is measured in terms of source credibility, content diagnosticity, and vicarious expression.
|A 2×2 factorial experiment.|
Context: An online shopping website uses scenario-based surveys of making purchase decisions under two information types—product features and product reviews from either experts or customers.
|Source- and content-based review features determine review helpfulness.|
Customer-generated reviews are perceived as more helpful than expert-generated reviews.
A concrete product review is perceived as more helpful than an abstract one.
The interaction between source- and context-based review features can shape review helpfulness.
|The emotion-cognition information processing model.||Emotions (e.g., anxiety and anger) embedded in product reviews.|
Perceived cognitive efforts.
|Two lab experiments and one field study using archival data from the Yahoo!Shopping website.||Anxiety-embedded reviews are perceived more helpful than anger-embedded reviews.|
The effects of negative emotions on review helpfulness are better explained by the beliefs of reviewers’ cognitive effort.
|The search-experience paradigm.|
|Product type: search versus experience.|
Source factors: reviewer rank, the disclosure of reviewer identity.
Context factor: number of reviews for a product.
Content factors: review extremity, review depth.
|A total of over 28,000 product reviews across 10 product types were collected from Amazon.com (Korea).||Positive determinants of review helpfulness: reviewer reputation, review depth.|
The number of reviews and the disclosure of reviewer identity have a stronger effect on perceived review helpfulness for experience products.
Reviewer reputation, review extremity, and review depth have a stronger effect on perceived review helpfulness for search products.
|Dual-process theory||Informational influence:|
two-sided reviews, source trustworthiness, source credibility, source homophily.
Normative influence: e-retailer’s, recommendation, service popularity.
|Context: Hong Kong International Airport.|
Materials: Customer reviews about accommodation and restaurants.
|Two-sided reviews are perceived as more helpful.|
Reviews from source expertise are perceived as more helpful.
Reviews of service popularity are perceived as more helpful.
|Source factors: reviewer experience, reviewer expertise.|
Content factors: review extremity, review inconsistency, review depth.
Context factors: product intangibility, product satisfaction, product popularity, product variety.
|A total of 14 million review data across 10 product types were collected on Amazon.com.||Positive effects on review helpfulness: review extremity, review depth, reviewer expertise. Negative effects on review helpfulness: review inconsistency, product intangibility, product satisfaction, product popularity, product variety, reviewer experience.|
Review extremity and review depth determine review helpfulness, depending on product intangibility.
2.2. Research Model and Hypothesis Development
2.2.1. Belief Consistency
2.2.2. Argument Quality
2.2.3. Positive and Negative Confirmation
3.1. The Instrument
3.2. Data Collection
4.1. Reliability, Validity, and Common Method Variance
4.2. Hypothesis Testing
5.1. Implications for Theory
5.2. Implications for Practice
6. Conclusions and Limitations
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A. The Measurement Items
|1||“iPhone is so expensive and iOS is a close system. While Android is not difficult to use, and it has more freedom of options and no function difference compared with iPhone. Why so many people like iPhone, just because of lost in fashion?”|
|2||“I use Sony (mobile phone), whereas my younger brother uses iPhone. I feel the choice of mobile phones depends on your budget. I will choose Sony Xperia Active Sport because this type of mobile phone is unique with small panel. I choose it because of my personal needs in sport, and it provides anti-water, anti-dust, and anti-friction functions. Moreover, it supports with sport-used sensors, and also provides step-counting and music functions. I have no special needs in videos and games. The price indeed suits my personal needs. I never take iPhone into account.”|
|3||“I feel iPhone is more valuable because it provides effective and efficient APPs.”|
|4||“iPhone is easy to use, and so fashion and attractive. But its APPs are not so cheap.”|
Appendix B. Common Method Variance
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Shih, H.-P.; Lai, K.-h.; Cheng, T.C.E. Complied by Belief Consistency: The Cognitive-Information Lens of User-Generated Persuasion. J. Theor. Appl. Electron. Commer. Res. 2023, 18, 372-393. https://doi.org/10.3390/jtaer18010020
Shih H-P, Lai K-h, Cheng TCE. Complied by Belief Consistency: The Cognitive-Information Lens of User-Generated Persuasion. Journal of Theoretical and Applied Electronic Commerce Research. 2023; 18(1):372-393. https://doi.org/10.3390/jtaer18010020Chicago/Turabian Style
Shih, Hung-Pin, Kee-hung Lai, and T. C. E. Cheng. 2023. "Complied by Belief Consistency: The Cognitive-Information Lens of User-Generated Persuasion" Journal of Theoretical and Applied Electronic Commerce Research 18, no. 1: 372-393. https://doi.org/10.3390/jtaer18010020