Impact of Online Review Grouping on Consumers' System Usage Behavior

2016 ◽  
Vol 24 (4) ◽  
pp. 45-66 ◽  
Author(s):  
Jia Li ◽  
Xinmiao Li ◽  
David C. Yen ◽  
Pengzhu Zhang

Information overload is one of the major challenges for online shoppers. One possible solution to this aforementioned problem is to take advantage of the interactive decision aids (IDAs). Prior studies on IDAs have mainly focused on information overload problems caused by the products (e.g., recommendation agents) and hence, have overlooked the information overload problems related to online reviews. However, online reviews are becoming more popular and turning into a major information source in consumer purchase decisions. To bridge this gap, this study investigates the effect of message grouping, an IDA approach supporting review browsing, onto the consumer's information processing and system usage intention. An experiment with a one-factor, three-level design was conducted to test the proposed research model. It is noted that grouping customer reviews into task-related categories significantly increases users' perceived usefulness, system satisfaction and intention to use the system next time. However, grouping customer reviews into task-distracting categories may significantly decrease users' perceived usefulness, system satisfaction and intention to use the system.

Author(s):  
Filipe Sengo Furtado ◽  
Thomas Reutterer ◽  
Nadine Schröder

AbstractWith increasing volumes of customer reviews, ‘helpfulness’ features have been established by many online platforms as decision-aids for consumers to cope with potential information overload. In this study, we offer a differentiated perspective on the drivers of review helpfulness. Using a hurdle regression setup for both helpfulness and unhelpfulness voting behavior, we aim to disentangle the differential effects of what drives reviews to receive any votes, how many votes they receive and whether these effects differ for helpful against unhelpful review voting behavior. As potential driving factors we include reviews’ star rating deviations from the average rating (as a proxy for confirmation bias), the level of controversy among reviews and review sentiment (consistency of review content), as well as pricing information in our analysis. Albeit with opposite effect signs, we find that revealed review un-/helpfulness is consistently guided by the tonality (i.e., the sentiment of review texts) and that reviewers tend to be less critical for lower priced products. However, we find only partial support for a confirmation bias with differential effects for the level of controversy on helpfulness versus unhelpfulness review votings. We conclude that the effects of voting disagreement are more complex than previous literature suggests and discuss implications for research and management practice.


2021 ◽  
Vol 29 (6) ◽  
pp. 0-0

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.


Author(s):  
Ming Wang

The enormous amount of commercial information available on the Internet makes online shoppers overwhelmed and it difficult to find relevant information. The recent development of shopping agents (bots) has offered a practical solution for this information overload problem. From the customer’s point of view, a shopping agent reduces search complexity, increases search efficiency, and supports user mobility. It has been proposed that the availability of agent Web sites is one of the reasons why e-markets should be more efficient (Mougayar, 1998). Shopping bots are created with agent software that assists online shoppers by automatically gathering shopping information from the Internet. In this comparative shopping environment, shopping agents can provide the customer with comparative prices for a searched product, customer reviews of the product, and reviews of the corresponding merchants. The agent will first locate the merchants’ Web sites selling the searched product. Then, the agent will collect information about the prices of the product and its features from these merchants. Once a customer selects a product with a merchant, the individual merchant Web site will process the purchase order and the delivery details. The shopping agent receives a commission on each sale made by a visitor to its site from the merchant selling the product on the Internet. Some auction agent Web sites provide a negotiation service through intelligent agent functions. Agents will represent both buyers and sellers. Once a buyer identifies a seller, the agent can negotiate the transaction. The agents will negotiate a price and then execute the transaction for their respective owners. The buyer’s agent will use a credit card account number to pay for the product. The seller’s agent will accept the payment and transmit the proper instructions to deliver the item under the terms agreed upon by the agent.


2019 ◽  
Vol 3 (1) ◽  
pp. 54-72 ◽  
Author(s):  
Laura A. Book ◽  
Sarah Tanford

Purpose The purpose of this paper is to develop a scale to measure normative and informational influence in online traveler reviews. Design/methodology/approach Through proper scale development techniques and a two-sample validation process, the resulting 2-factor, 11-item scale yields a valid and reliable measure of social influence. Findings The resultant scale provides a tool for researchers to investigate the process whereby different characteristics of online reviews influence travel decisions. Originality/value Customer reviews are prevalent and powerful sources of influence on travel decisions. However, it is unclear how social influence manifests in today’s online purchasing environment. For several decades, the domain of social influence has played an important role in the advancements of consumer behavior and hospitality/tourism research. In particular, normative and informational influences are applicable, since online reviews contain numerous informational and normative cues. These principles were formulated under much different conditions than today’s purchasing environment. This research provides a way to measure normative and informational influence in the online review environment, thus enhancing the understanding of how reviews influence purchase decisions.


Author(s):  
Hsiaoping Yeh ◽  
◽  
Tsung-Sheng Chang ◽  
Fenghung Kuo

Recommender systems solve the current information overload problem in the online world. By predicting and presenting relevant information, web users do not need to waste time searching and browsing for contents that they are interested in. However, in addition to the accurate contents, slogans associated catching the customers’ eyes are worthy of exploration. This study aims to discover the effects of various recommender slogans. Two categories of slogans were designed in the study: slogans associated with customer inputs and slogans associated with price promotion. Actual customers’ webpage clickstreams and purchase decisions were collected from a Taiwanese retail shopping Website. The effects of recommender slogans on product categories are different. Customers generally were drawn by the slogans associated with price promotion. This study brought to light the effects of different slogans on online shoppers. With the empirical findings, this study provides online retailers important guidelines regarding online customers’ behaviors towards the employment of recommender slogans.


Author(s):  
Anuradha Jagadeesan ◽  
Amit Patil

With the increased interest of online users in E-commerce, the web has become an excellent source for buying and selling of products online. Customer reviews on the web help potential customers to make purchase decisions, and for manufacturers to incorporate improvements in their product or develop new marketing strategies. The increase in customer reviews of a product influence the popularity and the sale rate of the product. This lead to a very important question about the analysis of the sentiments (opinions) expressed in the reviews. As such internet does not have any quality control over customer reviews and it could vary in terms of its quality. Also the trustworthiness of the online reviews is debatable. Sentiment Analysis (SA) or Opinion Mining is the computational analysis of opinions, sentiments, emotions and subjectivity of text. In this chapter, we take a look at the various research challenges and a new dimension involved in sentiment analysis using fuzzy sets and rough sets.


Author(s):  
Siyu Peng ◽  
Nicholas Su Miew Sing

As e-commerce continues to become an integral part of our lives, more and more purchase decisions are being made online. A significant contribution leading to such purchases stem from a few key factors, one of which, is customer reviews. Reviews are based on consumer experience and are increasingly necessary on e-commerce sites and platforms. Another key factor is the role brands play in influencing purchase decisions. A brand is an intangible asset of a company where brand value reflects the degree of differentiation a brand has over competitors. Most consumers judge the quality of an online product based on reviews and brands. This paper explores the question of how online product reviews and brands affect product sales on travel websites, using Ctrip.com as a case study. The study uses the user recommendation rate, the total score, the total number of reviews and brand strength to draw a relationship that suggests online reviews and brand strength impact product sales. The results demonstrate that there is a positive impact on product sales for high review scores on weak-branded inns; and the sales volume of strongbranded inns are more prominently affected by the number of comments and user recommendation rate.


2020 ◽  
Vol 12 (13) ◽  
pp. 5408 ◽  
Author(s):  
Jooa Baek ◽  
Yeongbae Choe

Online customer reviews increasingly influence customer purchase decisions. Indeed, many customers have highlighted the significance of online reviews as an influential source of information. This study reports an investigation of the differential effects of online reviews, such as valence and volume, on the customer share of visits. Our findings suggest that valence (i.e., star rating) had more effect, giving a higher average check size to restaurants on the share of visits, while number reviews (volume) did not drive the share of visits to restaurants regardless of the average check size. Therefore, the ideal for casual dining restaurant brands would be to manage highly positive ratings to retain their customers.


2012 ◽  
Vol 2 (2) ◽  
pp. 25-43
Author(s):  
Yanbin Tu ◽  
Min Lu

The understanding of digital music consumer behavior and determinants of online digital music evaluation helps music retailers implement online digital music marketing strategies. In this study, the authors investigate the profiles of music consumers on the Internet and explore how consumers use product sampling and customer reviews for online music evaluation. The authors find most people use free radio as their main music source, piracy and digital music remains a problem. The authors also find consumers still depend on traditional word of mouth for their music evaluation. This study shows that many consumers are more likely to trust online sampling than online reviews, and online sampling plays a more important role than online reviews in their music evaluation. The authors also investigate post-sampling results including the music evaluation, willingness to pay (WTP), free rider, enjoyable sampling process, perceived usefulness of online sampling, knowing the true music value, further reading online reviews, using other music evaluation channels, and writing customer reviews after sampling. The authors also conduct coefficient correlation analysis for post-sampling results and provide managerial interpretations.


2017 ◽  
Author(s):  
◽  
Bunmi Yemisi Folarinde

Background: Advance directives (ADs) are documents that allow competent individuals to set forth their medical treatment wishes and/or to name a proxy in the event that they lose the capacity to communicate these decisions in the future. Technology has remained an important driver of change for centuries; the electronic health record (EHR) has evolved as an important facilitator in patient care processes and the implementation of electronic ADs in an EHR is no exception. The integration of ADs into EHRs is one of the means that has been improvised to improve instant accessibility of AD documents for healthcare providers. Although healthcare providers' perception of electronic ADs in EHRs can greatly impact its usability, little or no study has been conducted using Technology Acceptance Model constructs to explore perceptions of providers' use of electronic ADs. Aim: The aim of this study is to explore the perception of healthcare providers' use of electronic AD forms in the EHR in terms of perceived usefulness, perceived ease of use, and behavioral intention to use, and to measure impact on actual system usage. This study also examined existing relationships among the participants' demographics and the research variables described. Methods: This study was guided by the Technology Acceptance Model (TAM) using a survey adapted from the TAM literature. A cross-sectional, correlational quantitative design was utilized. The study was conducted in six departments at a public, academic healthcare system in the southern United States. Results: Of the 165 surveys distributed, a total of 151 participants (92 percent) responded: 67 percent female (n = 101), 33 percent male (n = 50). Participants included physicians (n=78); staff nurses (n=57); nurse practitioners (n=4); social workers/case managers (n=6); administrators (n=1); and others (n=5). There was a moderately strong positive correlation between Perceived Usefulness and Actual System Usage (r=0.70, p is less than 0.0001). Likewise, Perceived Ease of Use and Actual System Usage had a moderately strong positive correlation (r=00.70, p is less than 0.0001). In contrast, the strength of the relationship between Behavioral Intention to Use and Actual System Usage was more modest (r=0.22, p is less than 0.004). In addition, the results of the Kruskal-Wallis H test found there was a statistically significant differences in the Actual System Usage of the electronic ADs between the 6 departments [symbol]2(5) = 79.325, p is less than 0.000. Specifically, the Primary Care Clinics are highly significant with p=0.0004 for Behavioral Intention to Use and p is less than 0.0001 for Perceived Usefulness and Perceived Ease of Use. There were not significant relationships between the participants' demographics and the research variables. Conclusion: The relationships among primary TAM constructs found in this research are largely consistent with those typical in previous TAM research, with the exception of the Behavioral Intention to Use, which is slightly lower. These data suggest that the healthcare providers' perception has great influence on the usage of the electronics ADs. However, this study lacks generalization because it was conducted in few departments at a single hospital. Therefore, it is recommended that the future researchers conduct a similar study in a larger scale and, if possible, across different types of EHRs.


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