scholarly journals Numbers Speak Where Words Fail: Exploring the Effect of Online Consumer Reviews on Consumer Decision Making

Author(s):  
Fei Liu
2021 ◽  
Vol 13 (4) ◽  
pp. 2024
Author(s):  
Do-Hyung Park

Today, consumer-created information such as online consumer reviews have become important and popular, playing a key role in consumer decision making. Compared with expert-created information, each piece of information is less powerful or persuasive, but their aggregation can be more credible and acceptable. This concept is called collective intelligence knowledge. This study focuses on the persuasive effect on consumer product attitudes of consumer-created information compared to expert-created information. Using source credibility and familiarity theory, the study reveals how prior brand attitudes can play a moderating role in the persuasive effect of consumer-created information and expert-created information. Specifically, this study shows how consumer-created information is more persuasive when consumers have more favorable prior brand attitudes, while expert-created information is more persuasive when consumers have less favorable prior brand attitudes. Based on the results, this study proposes practical strategies for information structure, curation, and presentation. If a company has a good-quality brand evaluation of its products, it should increase the weight of consumer-created information such as online consumer reviews. Otherwise, the company needs to first improve brand evaluation through expert-created information such as third-parties or power-blogger reviews.


2017 ◽  
Vol 29 (2) ◽  
pp. 762-783 ◽  
Author(s):  
Minwoo Lee ◽  
Miyoung Jeong ◽  
Jongseo Lee

Purpose This paper aims to explore how emotional expressions embedded in online hotel reviews influence consumers’ helpfulness perceptions. In particular, this study develops and tests hypotheses analyzing empirical data with a text-mining method in the context of hotels to investigate how review valence influences the perceived helpfulness of online hotel reviews and to examine the role of negative emotional expressions embedded in online consumer reviews with respect to perceived helpfulness. Design/methodology/approach This study collected 520,668 online reviews involving 488 hotels in New York City (NYC) on Tripadvisor.com. Of these reviews, 69,202 reviews (13.29 per cent) that had received helpfulness votes were analyzed by a text mining method and negative binomial regression. Findings This study demonstrates that negative reviews are considered more helpful than positive reviews when potential customers read online hotel reviews for their future stay. However, when intensively negative emotions were expressed, the degree of helpfulness regarding negative reviews was diminished. Originality/value While emotional expressions prevail in online consumer reviews, surprisingly little attention has been devoted to the consequences of emotional expressions in consumers’ information processing and decision-making. Due to the nature of service, given the inseparability of production and consumption, which often hinders the execution of flawless service, consumers tend to be more dependent on reviews to minimize any potential failures they may encounter later on. Therefore, this study fills a gap by demonstrating that negative reviews and emotional expressions play a more crucial role in consumers’ information processing and decision-making.


Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 432
Author(s):  
Aziz Khan ◽  
Shougi S. Abosuliman ◽  
Saleem Abdullah ◽  
Muhammad Ayaz

Spherical hesitant fuzzy sets have recently become more popular in various fields. It was proposed as a generalization of picture hesitant fuzzy sets and Pythagorean hesitant fuzzy sets in order to deal with uncertainty and fuzziness information. Technique of Aggregation is one of the beneficial tools to aggregate the information. It has many crucial application areas such as decision-making, data mining, medical diagnosis, and pattern recognition. Keeping in view the importance of logarithmic function and aggregation operators, we proposed a novel algorithm to tackle the multi-attribute decision-making (MADM) problems. First, novel logarithmic operational laws are developed based on the logarithmic, t-norm, and t-conorm functions. Using these operational laws, we developed a list of logarithmic spherical hesitant fuzzy weighted averaging/geometric aggregation operators to aggregate the spherical hesitant fuzzy information. Furthermore, we developed the spherical hesitant fuzzy entropy to determine the unknown attribute weight information. Finally, the design principles for the spherical hesitant fuzzy decision-making have been developed, and a practical case study of hotel recommendation based on the online consumer reviews has been taken to illustrate the validity and superiority of presented approach. Besides this, a validity test is conducted to reveal the advantages and effectiveness of developed approach. Results indicate that the proposed method is suitable and effective for the decision process to evaluate their best alternative.


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