scholarly journals THE DYNAMIC EFFECTS OF ONLINE PRODUCT REVIEWS ON PURCHASE DECISIONS

2018 ◽  
Vol 24 (5) ◽  
pp. 2045-2064 ◽  
Author(s):  
Jia Chen ◽  
Gang Kou ◽  
Yi Peng
Keyword(s):  
Decision Process ◽  
Online Reviews ◽  
Online Review ◽  
Purchase Decision ◽  
Product Reviews ◽  
Purchase Decisions ◽  
Dynamic Effects ◽  
Initial Opinion ◽  
Initial Impressions ◽  
Potential Customers

Previous studies have demonstrated that online reviews play an important role in the purchase decision process. Though the effects of positive and negative reviews to consumers’ purchase decisions have been analyzed, they were examined statically and separately. In reality, online review community allows everyone to express and receive opinions and individuals can reexamine their opinions after receiving messages from others. The goal of this paper is to study how potential customers form their opinions dynamically under the effects of both positive and negative reviews using a numerical simulation. The results show that consumers with different membership levels have different information sensitivities to online reviews. Consumers at low and medium membership levels are often persuaded by online reviews, regardless of their initial opinion about a product. On the other hand, online reviews have less effect on consumers at higher membership levels, who often make purchase decisions based on their initial impressions of a product.

scholarly journals Using Customer Review Systems to Support Purchase Decisions

2021 ◽  
Vol 29 (6) ◽  
pp. 0-0
Keyword(s):  
Structural Equation ◽  
Online Reviews ◽  
Equation Modeling ◽  
Online Review ◽  
Purchase Decision ◽  
Intention To Use ◽  
Purchase Decisions ◽  
Sources Of Information ◽  
User Attitudes ◽  
Significant Difference

Online reviews have emerged as influential sources of information which greatly affect customers’ pre-purchase decision. Some studies have found that culture impacts online reviews, but many aspects of online review usage are still not well-understood. This study seeks to understand: What factors influence the usage of online reviews and consumers’ intention to use online reviews influenced by culture? This study collects data from U.S. and Thai consumers to examine what factors affect user attitudes and intentions. Structural Equation Modeling is used to analyze the data and the findings reveal that most of the proposed factors influence online review adoption for these two nationalities. One significant difference was found between the respondents of the two countries. The results should help online businesses gain a better understanding of these factors, and thus direct their efforts to develop features which positively influence online review usage.

scholarly journals Using Customer Review Systems to Support Purchase Decisions

2021 ◽  
Vol 29 (6) ◽  
pp. 1-24
Author(s):  
Chuleeporn Changchit ◽  
Timothy Klaus ◽  
Alicha Treerotchananon
Keyword(s):  
Structural Equation ◽  
Online Reviews ◽  
Equation Modeling ◽  
Online Review ◽  
Purchase Decision ◽  
Intention To Use ◽  
Purchase Decisions ◽  
Sources Of Information ◽  
User Attitudes ◽  
Significant Difference

Online reviews have emerged as influential sources of information which greatly affect customers’ pre-purchase decision. Some studies have found that culture impacts online reviews, but many aspects of online review usage are still not well-understood. This study seeks to understand: What factors influence the usage of online reviews and consumers’ intention to use online reviews influenced by culture? This study collects data from U.S. and Thai consumers to examine what factors affect user attitudes and intentions. Structural Equation Modeling is used to analyze the data and the findings reveal that most of the proposed factors influence online review adoption for these two nationalities. One significant difference was found between the respondents of the two countries. The results should help online businesses gain a better understanding of these factors, and thus direct their efforts to develop features which positively influence online review usage.

Business Data Analytics Applications to Online Product Reviews and Nationalism

2021 ◽  
Vol 2 (2) ◽  
pp. 27-39
Author(s):  
Charles C. Willow
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Smart Phone ◽  
Consumer Preference ◽  
Online Reviews ◽  
Global Market ◽  
Product Reviews ◽  
Purchase Decisions ◽  
Control Factors

This paper investigates the data analytics between consumer purchase decisions relative to the on-line reviews. The multi-attributes associated with purchase decisions are comprised of nationalism and consumer preference to be correlated with online reviews using big data analytics. By far, a small fraction of meaningful studies have sought to correlate nationalism and ethnocentrism with big data analytics to date. Globally accepted generic products are selected to expedite the process of data engineering. Two sets were arranged: passenger automobiles for transportation with an estimated $9 trillion global market and the smart phone, boosting its market size of approximately $5 billion. Both products provide minimized cultural, linguistic, gender, age, and/or custom barriers of entry for prospective digital consumers, thereby allowing relatively unrestricted engagement with online reviews and purchases. A series of hypothesis tests indicate that there is a positive correlation between nationalism and automobiles. As to smart cell phones, however, nationalism had nominal control factors. Multi-variate analytics were performed by using R and Tableau Public.

Tourist Social Media Engagement

2022 ◽  
pp. 192-212
Author(s):  
Rayane Ruas ◽  
Belem Barbosa
Keyword(s):  
Social Media ◽  
Literature Review ◽  
Decision Process ◽  
Secondary Data ◽  
Purchase Decision ◽  
Purchase Decisions ◽  
Four Dimensions ◽  
Tourist Destinations ◽  
Search For Information ◽  
Method Approach

Social media are transforming relationships with customers for all sectors, including tourism. Since the search for information is a critical aspect of tourist purchase decision process, the importance of social media for tourism is evident. However, the presence of tourism brands in social media is not enough to have an impact on tourist purchase decisions: it is necessary to generate engagement. This chapter aims to conceptualize tourist engagement on social media and identify tourist engagement indicators. Tourist engagement was conceptualized through a literature review that identified four dimensions of engagement: popularity, commitment, virality, and post engagement. A set of indicators is proposed to measure tourist engagement in each of these dimensions. The proposed TSM engagement framework was validated through a mixed-method approach, using secondary data and interviews carried out with Brazilian tourist destinations.

The impact of monetary rewards for online reviews

2019 ◽  
Vol 31 (5) ◽  
pp. 1486-1515 ◽  
Author(s):  
Yongrui Duan ◽  
Chen Chen ◽  
Jiazhen Huo
Keyword(s):  
Analytical Framework ◽  
Online Reviews ◽  
Monetary Reward ◽  
Product Reviews ◽  
Purchase Decisions ◽  
Content Type ◽  
Second Stage ◽  
Monetary Rewards ◽  
Stage 1 ◽  
The Impact

Purpose To encourage buyers to contribute product reviews, some online sellers offer monetary rewards. The purpose of this paper is to investigate the impact of monetary rewards on buyers’ purchase decisions and review contributions, as well as the impact on the seller’s price decisions and profit. Design/methodology/approach The authors consider an online seller in a two-stage setting. Prior to Stage 1, the profit-maximizing seller sets the price and decides whether to offer a monetary reward secretly to motivate online reviews. Then, a continuum of buyers arrives and makes purchase decisions at the beginning of each stage. First-stage buyers may contribute reviews if they are satisfied, which will affect demand in the second stage. Using this analytical framework, the authors analyze the impact of monetary rewards. Findings If the monetary reward is small, it decreases the seller’s profit and fails to generate more reviews. It also increases price, leading to a decline in total demand. Thus, when the reward is lower than a certain threshold, all buyers are worse off. Only when the reward exceeds the threshold are buyers who contribute reviews better off. Profit and total demand both increase in review quality, while the price may either increase or decrease in it. Originality/value To the best of the authors’ knowledge, this paper is the first to analyze theoretically the impact of monetary rewards on buyers’ purchase decisions, review contributions and on online sellers’ decisions.

scholarly journals May we buy your love? psychological effects of incentives on writing likelihood and valence of online product reviews

2020 ◽  
Vol 30 (4) ◽  
pp. 805-820
Author(s):  
Ina Garnefeld ◽  
Sabrina Helm ◽  
Ann-Kathrin Grötschel
Keyword(s):  
Experimental Studies ◽  
Online Reviews ◽  
Psychological Effects ◽  
Online Review ◽  
Product Reviews ◽  
Monetary Rewards ◽  
Online Product Reviews ◽  
The Impact

AbstractAcknowledging the impact on their sales, companies strive to increase the number of positive online reviews of their products. A recently popular practice for stimulating online reviews is offering monetary rewards to customers in return for writing an online review. However, it is unclear whether such practices succeed in fulfilling two main objectives, namely, increasing the number and the valence of online reviews. With one pilot and two experimental studies, this research shows that offering incentives indeed increases the likelihood of review writing. However, the effect on review valence is mixed, due to contradictory psychological effects: Incentive recipients intend to reciprocate by writing favorable reviews but also perceive a need to resist marketers’ influence, which negatively affects their review valence. Finally, recipients who are less satisfied with the product are particularly prone to psychological costs and decrease the positivity of their online reviews. Consequently, incentives should be applied carefully.

scholarly journals An Affordance-Based Online Review Analysis Framework

2019 ◽  
Vol 1 (1) ◽  
pp. 2457-2466
Author(s):  
Tianjun Hou ◽  
Bernard Yannou ◽  
Yann Leroy ◽  
Emilie Poirson
Keyword(s):  
Opinion Mining ◽  
Online Reviews ◽  
User Preferences ◽  
Data Driven ◽  
Online Review ◽  
Product Reviews ◽  
Analysis Framework ◽  
Review Analysis ◽  
Classical Models ◽  
Feedback Data

AbstractOne of the main tasks of today's data-driven design is to learn customers' concerns from the feedback data posted on the internet, to drive smarter and more profitable decisions during product development. Feature-based opinion mining was first performed by the computer and design scientists to analyse online product reviews. In order to provide more sophisticated customer feedback analyses and to understand in a deeper way customer concerns about products, the authors propose an affordance-based online review analysis framework. This framework allows understanding how and in what condition customers use their products, how user preferences change over years and how customers use the product innovatively. An empirical case study using the proposed approach is conducted with the online reviews of Kindle e-readers downloaded from amazon.com. A set of innovation leads and redesign paths are provided for the design of next-generation e-reader. This study suggests that bridging data analytics with classical models and methods in design engineering can bring success for data-driven design.

scholarly journals Understanding the Dark Side of Online Reviews on Consumers' Purchase Intentions in E-Commerce: Evidence From a Consumer Experiment in China

2021 ◽  
Vol 12 ◽  
Author(s):  
Junbin Wang ◽  
Xiaojun Fan ◽  
Xiangdong Shen ◽  
Yurong Gao
Keyword(s):  
Purchase Intention ◽  
Word Of Mouth ◽  
Critical Role ◽  
Online Reviews ◽  
Purchase Intentions ◽  
Dark Side ◽  
Online Review ◽  
Purchase Decision ◽  
Subject Design ◽  
Main Effects

Background: Online review, as an important way of electronic word-of-mouth (eWOM) communication, plays an important role in e-commerce. However, few studies have examined the dark side of online reviews and their effect on consumers' purchase intentions. Information inconsistency is one of the dark sides that plays a critical role in influencing consumers' purchase intentions through online reviews.Methods: Using a 2*2 between-subject design that explores the main effects of the type of information inconsistency (vertical- vs. horizontal-attribute inconsistency) on purchase intention and the moderating effect of product type (search vs. experience product).Results: This study examines whether and how the type of information inconsistency between online recommendations and reviews influences consumer purchase decision-making.Conclusions: The findings show that vertical-attribute inconsistency leads to a lower purchase intention for search products; moreover, both vertical- and horizontal-attribute inconsistencies have no significant effect on purchase intention for experience products.

Identifying the Opinion Orientation of Online Product Reviews at Feature Level

2017 ◽  
Vol 8 (2) ◽  
pp. 92-111
Author(s):  
Nilanshi Chauhan ◽  
Pardeep Singh
Keyword(s):  
Sentiment Analysis ◽  
Present Article ◽  
Online Shopping ◽  
Service Providers ◽  
Online Reviews ◽  
Product Reviews ◽  
Striking Increase ◽  
Feature Based ◽  
Potential Customers ◽  
Pruning Methods

This article describes how e-commerce has become so vast that almost every product and service can be purchased online, to be delivered at our doorsteps. This has led to a striking increase in the number of online customers. In an attempt to make the online shopping more appealing and transparent to the online customers, the e-retailers allow their customers to express their opinion about the purchased products and services. Recently, analysis of such online reviews has become an active topic of research. This is because it is of immense concern to various stakeholders vs. online merchants, potential customers and the manufacturers of the particular product or service providers. The present article addresses the problem of summarization of such opinions expressed online and aims to create an organized feature-based summary as a solution. The proposed system depends on the frequency of occurrences of the potential features. A number of pruning methods are applied in order to obtain the final feature set and sentiment analysis has been done for each such feature.

A Method for Ranking Products Through Online Reviews Based on Sentiment Classification and Interval-Valued Intuitionistic Fuzzy TOPSIS

2017 ◽  
Vol 16 (06) ◽  
pp. 1497-1522 ◽  
Author(s):  
Yang Liu ◽  
Jian-Wu Bi ◽  
Zhi-Ping Fan
Keyword(s):  
Fuzzy Topsis ◽  
Online Reviews ◽  
Sentiment Classification ◽  
Support Vector ◽  
Product Reviews ◽  
Purchase Decisions ◽  
Intuitionistic Fuzzy ◽  
Online Product Reviews ◽  
Intuitionistic Fuzzy Topsis ◽  
Interval Valued

Studies have shown that online product reviews significantly affect consumer purchase decisions. However, it is difficult for the consumer to read online product reviews one by one because the number of online reviews is very large. Thus, to facilitate consumer purchase decisions, how to rank products through online reviews is a valuable research topic. This paper proposes a method for ranking products through online reviews based on sentiment classification and the interval-valued intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The method consists of two parts: (1) identifying sentiment orientations of the online reviews based on sentiment classification and (2) ranking alternative products based on interval-valued intuitionistic fuzzy TOPSIS. In the first part, the online reviews of the alternative products concerning multiple attributes are preprocessed, and an algorithm based on support vector machine and one-versus-one strategy is developed for classifying the sentiment orientations of online reviews into three categories: positive, neutral, and negative. In the second part, based on the percentages of the online reviews with different sentiment orientations and the numbers of online reviews of different products crawled from the website, an interval-valued intuitionistic fuzzy number is constructed to represent the performance of an alternative product with respect to the product attribute. Additionally, the interval-valued intuitionistic fuzzy TOPSIS method is employed to determine a ranking of the alternative products. Finally, a case analysis is provided to illustrate the application of the proposed method.

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