Market Segmentation of Online Reviews: A Network Analysis Approach

2022 ◽  
pp. 147078532110590
Author(s):  
Hui-Ju Wang
Keyword(s):  
Network Analysis ◽  
Market Segmentation ◽  
Online Reviews ◽  
Analysis Approach ◽  
Online Review ◽  
Analysis Techniques ◽  
The Core ◽  
Segmentation Methods ◽  
Traditional Market ◽  
Complex Features

With the popularity of online reviews, brand managers have opportunities to segment their markets according to the reviews of their products or services by customers. Nonetheless, it has been suggested that traditional market segmentation methods are ineffective at analyzing online review data due to the complex features and large amount of this type of data; specifically, traditional methods fail to take into account the networked nature of interactive relationships among reviewers and brands across online review websites. Accordingly, this study proposes a network analysis approach for the market segmentation of online reviews. Collecting samples from Yelp via web scraping, this study demonstrates how network analysis techniques can be utilized to segment online reviewers through a four-step process. The results reveal the core and peripheral market segments, as well as the bridge segment in the core. The study contributes to offering marketing researchers and managers a new network structure analysis approach for the market segmentation of online reviews.

scholarly journals How consumers attend to online reviews: an eye-tracking and network analysis approach

2019 ◽  
Vol 39 (2) ◽  
pp. 282-306 ◽  
Author(s):  
Ewa Maslowska ◽  
Claire M. Segijn ◽  
Khadija Ali Vakeel ◽  
Vijay Viswanathan
Keyword(s):  
Network Analysis ◽  
Eye Tracking ◽  
Online Reviews ◽  
Analysis Approach

Typologies of Urban Cyclists: Review of Market Segmentation Methods for Planning Practice

2017 ◽  
Vol 2662 (1) ◽  
pp. 125-133 ◽  
Author(s):  
Rosa Félix ◽  
Filipe Moura ◽  
Kelly J. Clifton
Keyword(s):  
Multivariate Analysis ◽  
Market Segmentation ◽  
Infrastructure Development ◽  
Urban Mobility ◽  
Rule Based ◽  
Analysis Techniques ◽  
Trip Purpose ◽  
Segmentation Methods ◽  
Urban Cycling ◽  
Different Types

Following global guidelines, several cities are investing in urban cycling. Cities are in different stages of cycling development and have adopted different approaches and packages of policies that are likely to be most effective at each stage. Urban cycling plans include investment in infrastructure, promotion, and education supporting the adoption of active modes for urban mobility. Some investments aim to meet current cyclists’ needs and others those of potential bicycle adopters. With respect to urban cyclists, several studies propose typologies, usually related to frequency, trip purpose, or motivation. This paper compares a set of cyclist typologies and the corresponding categorization methods and reviews 20 studies that considered different cyclists’ profiles. Most studies relied on expert judgment approaches or rule-based decisions; five considered multivariate analysis techniques for clustering groups, on the basis of data from surveys. Despite the variety of group categorizations, commonalities were found in most cases and divided cyclists into three main types: current cyclists (typically more proficient riders), potential cyclists (willing but not convinced), and noncyclists (unaware of or unwilling to shift to cycling). Dividing the population of potential cyclists into different typologies can better inform the different stages of planning for cycling infrastructure development by targeting more accurately the needs and requirements of different types of users. This is a key element in the management of a cycling network and cycling infrastructure, which are intended to be built on the basis of effective solutions and decisions to achieve desirable bicycle modal shares of regular trips.

Motives for writing online reviews in post-vacation phase

2019 ◽  
Vol 13 (2) ◽  
pp. 244-256 ◽  
Author(s):  
Dusan Mladenovic ◽  
Anida Krajina ◽  
Ivana Milojevic
Keyword(s):  
Market Segmentation ◽  
Design Methodology ◽  
Online Reviews ◽  
Opinion Leaders ◽  
Online Review ◽  
Web Survey ◽  
Men And Women ◽  
Content Type ◽  
Tourism Marketing ◽  
Practical Implications

Purpose This quantitative study aims to examine background motives that navigate individuals to share their opinions, in the context of an individual’s post-vacation phase and its relation to the destination of Serbia, from the standpoint of age, gender and nationality. Design/methodology/approach The data were collected throughout six weeks via a self-administered Web survey. The survey was adopted and based on the scale developed by Bronner and de Hoog (2011). Findings Results indicate that the dominant driver to submit an online review after a trip is to help vacationers (altruism) and that men and women display differences in this, but not in other motives. Both age and nationality do not influence the particular motive to leave an online review. Research limitations/implications The main limitation of this study is the total number of answers. However, sampling was rather purposive, which gives us a good indicator of the population behavior. Practical implications Understanding these drivers is essential in formulating strategies for managing the interaction with opinion leaders. On a larger scale, the results can contribute the market segmentation and customer communication approaches in Serbian tourism marketing. Originality/value Motives that trigger individuals to compose an online review have not been investigated and thematic studies are still missing, in the case of Serbia in particular.

scholarly journals Influence of MOOC learners discussion forum social interactions on online reviews of MOOC

2021 ◽  
Author(s):  
Bing Wu
Keyword(s):  
Social Interactions ◽  
Regression Models ◽  
Online Courses ◽  
Online Reviews ◽  
Discussion Forum ◽  
Massive Open Online Courses ◽  
Online Review ◽  
Discussion Forums ◽  
Processing Data ◽  
Learning Progress

AbstractAlthough some studies have explored massive open online courses (MOOCs) discussion forums and MOOC online reviews separately, studies of both aspects are insufficient. Based on the theory of self-determination, this paper proposes research hypotheses that MOOC learning progress has a direct impact on MOOC online reviews and an indirect influence on MOOC online reviews through social interactions in discussion forums, as well. Coursera the largest MOOC platform, is selected as the empirical research object, and data from learners who participated in the MOOC discussion forum and provided MOOC online reviews from August 2016 to December 2019 are obtained from the most popular course, “Machine Learning”. After processing, data from 4376 learners are obtained. Then, according to research hypotheses, multi regression models are constructed accordingly. The results show that the length of MOOC online review text is affected by the MOOC learning progress, the number of discussion forum posts, the number of follow, the online review sentiment and MOOC rating. This study highlights the main factors that affect MOOC online reviews. As a result, some suggestions are put forward for the construction of MOOC.

Are Hotel Guests Altruistic? How Positive Review Disconfirmation Affects Consumers’ Online Review Behavior

2021 ◽  
pp. 109634802110303
Author(s):  
Hengyun Li ◽  
Fang Meng ◽  
Simon Hudson
Keyword(s):  
Social Influence ◽  
Experimental Research ◽  
Research Method ◽  
Online Reviews ◽  
Positive Deviance ◽  
Online Review ◽  
Altruistic Motivation ◽  
Prior Review ◽  
Concern For Others ◽  
Post Online

The research aims to examine how positive review disconfirmation (i.e., a positive deviance between a hotel consumer’s poststay evaluation and the average review rating by prior consumers) affects subsequent consumers’ willingness to post online reviews and their own review ratings. By employing an experimental research method, this study reveals that positive review disconfirmation increases hotel guests’ willingness to post online reviews, and increases their online review ratings through the mechanism of concern for others, demonstrating an act of altruism. In addition, comparatively the positive review disconfirmation effects are stronger when the variance of prior review ratings is smaller. This study enhances the online review social influence literature, and the consumer’s altruistic motivation of posting online reviews.

scholarly journals Quantitative Dynamics Effects of Belt and Road Economies Trade Using Structural Gravity and Neural Networks

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110326
Author(s):  
Koffi Dumor ◽  
Li Yao ◽  
Jean-Paul Ainam ◽  
Edem Koffi Amouzou ◽  
Williams Ayivi
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Analysis ◽  
Bilateral Trade ◽  
Belt And Road Initiative ◽  
Neural Network Analysis ◽  
Analysis Techniques ◽  
Belt And Road ◽  
The Impact ◽  
Trade Partners

Recent research suggests that China’s Belt and Road Initiative (BRI) would improve the bilateral trade between China and its partners. This article uses detailed bilateral export data from 1990 to 2017 to investigate the impact of China’s BRI on its trade partners using neural network analysis techniques and structural gravity model estimations. Our main findings suggest that the BRI countries would raise exports by a modest 5.053%. This indicates that export and network upgrades should be considered from economic and policy perspectives. The results also show that neural networks is more robust compared with structural gravity framework.

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