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Analyzing Online Reviews in E-Retail...

Zhou, Zheng.

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Analyzing Online Reviews in E-Retailer Platforms: A Structural Equation Modeling Approach.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analyzing Online Reviews in E-Retailer Platforms: A Structural Equation Modeling Approach./
作者:	Zhou, Zheng.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	123 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-03, Section: A.
Contained By:	Dissertations Abstracts International82-03A.
標題:	Web studies. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28028017
ISBN:	9798664776959

Analyzing Online Reviews in E-Retailer Platforms: A Structural Equation Modeling Approach.
Zhou, Zheng.

Analyzing Online Reviews in E-Retailer Platforms: A Structural Equation Modeling Approach. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 123 p.

Source: Dissertations Abstracts International, Volume: 82-03, Section: A.

Thesis (Ph.D.)--Illinois Institute of Technology, 2020.

This item must not be sold to any third party vendors.

In recent years, the role of online shoppers has transformed from a passive information receiver into an active shopping experience sharer, which makes reading the reviews left by peer shoppers a very important factor in consumer purchase decisions. However, fake online reviews are flooding websites and consumers are gradually becoming aware of that. This encourages consumers' skepticism toward the credibility of online reviews. Using a structural equation modeling approach, this study analyzes the effect of consumers' perceptions of shopping platform characteristics and online review trustworthiness on their purchase intention. Conditional process analysis was used to study the moderation effect of consumers' skepticism during their shopping experience. A total of 1,004 valid responses were collected through an online survey administered by Qualtrics.Results indicate that consumers' perceived platform trustworthiness contributes to the trustworthiness of its online reviews, which in turn both directly and indirectly increases purchase intention. Most parts of the proposed conceptual model are supported by empirical results with a few exceptions: consumer's perceived review quantity is found to have a positive impact on perceived review quality and platform quality is found to be directly related to consumers' perceived risk. All re-specifications increase the model fit, followed by cross-validation that yields satisfactory model stability. With the establishment of measurement invariance, we discuss structural invariance across sub-groups and present some interesting findings. Results also show that all three dimensions of consumers' skepticism negatively moderate the direct effect of the review's trustworthiness on purchase intention. However, unlike the other two items (skepticism toward review trustworthiness and reviewer's motivation), consumers' skepticism toward the reviewer's identity does not moderate the indirect causal path between review trustworthiness and purchase intention through perceived risk. We also adopt a different approach using latent moderated structural equations to support our findings. From a research perspective, this study contributes to our understanding of how consumers absorb information from online reviews to develop appropriate responses (e.g., purchase intention). From a practice perspective, this study provides insights on how platform and seller should respond to and properly manage consumers' perceptions and skepticism toward online reviews.

ISBN: 9798664776959Subjects--Topical Terms:

2122754
Web studies.
Subjects--Index Terms:

Conditional process analysis

Analyzing Online Reviews in E-Retailer Platforms: A Structural Equation Modeling Approach.
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500 $a Source: Dissertations Abstracts International, Volume: 82-03, Section: A.
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520 $a In recent years, the role of online shoppers has transformed from a passive information receiver into an active shopping experience sharer, which makes reading the reviews left by peer shoppers a very important factor in consumer purchase decisions. However, fake online reviews are flooding websites and consumers are gradually becoming aware of that. This encourages consumers' skepticism toward the credibility of online reviews. Using a structural equation modeling approach, this study analyzes the effect of consumers' perceptions of shopping platform characteristics and online review trustworthiness on their purchase intention. Conditional process analysis was used to study the moderation effect of consumers' skepticism during their shopping experience. A total of 1,004 valid responses were collected through an online survey administered by Qualtrics.Results indicate that consumers' perceived platform trustworthiness contributes to the trustworthiness of its online reviews, which in turn both directly and indirectly increases purchase intention. Most parts of the proposed conceptual model are supported by empirical results with a few exceptions: consumer's perceived review quantity is found to have a positive impact on perceived review quality and platform quality is found to be directly related to consumers' perceived risk. All re-specifications increase the model fit, followed by cross-validation that yields satisfactory model stability. With the establishment of measurement invariance, we discuss structural invariance across sub-groups and present some interesting findings. Results also show that all three dimensions of consumers' skepticism negatively moderate the direct effect of the review's trustworthiness on purchase intention. However, unlike the other two items (skepticism toward review trustworthiness and reviewer's motivation), consumers' skepticism toward the reviewer's identity does not moderate the indirect causal path between review trustworthiness and purchase intention through perceived risk. We also adopt a different approach using latent moderated structural equations to support our findings. From a research perspective, this study contributes to our understanding of how consumers absorb information from online reviews to develop appropriate responses (e.g., purchase intention). From a practice perspective, this study provides insights on how platform and seller should respond to and properly manage consumers' perceptions and skepticism toward online reviews.
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