Mapping brand similarities: Comparing consumer online comments versus survey data

2018 ◽  
Vol 61 (2) ◽  
pp. 130-139 ◽  
Author(s):  
Marco Vriens ◽  
Song Chen ◽  
Chad Vidden
Keyword(s):  
Hierarchical Clustering ◽  
Online Forums ◽  
Online Data ◽  
Online Consumer Behavior ◽  
Similarity Data ◽  
Scaling Methods ◽  
Additive Trees ◽  
Online Consumer ◽  
The Cost ◽  
Brand Similarity

Online consumer behavior has become a valuable and viable source of consumer insights. Consumer comments in online forums, or discussion groups, have proven useful as a source to extract brand similarity data from. Apart from the cost and speed advantages, such data can be captured easily over different time periods. Both online consumer-generated data (CGD) and surveys have their pros and cons. To date, little is known as to how these two data sources compare in terms of brand insights. In this study, we discuss the results from analyzing survey and consumer-generated online data pertaining to the U.S. skincare market. Our study included 57 brands, and we used multidimensional scaling (MDS), t-stochastic neighbor embedding (t-SNE; an alternative to MDS), hierarchical clustering, and additive similarity trees (an extension of hierarchical clustering) to analyze the data. We show that the outcomes vary between CGD and surveys. As an additional insight, we show that, rather than the spatial scaling methods, additive trees result in a much better fit of brand similarity data in cases where we have many brands.

scholarly journals Research on the Balanced Relationship between Online Consumer Behavior and E-Commerce Service Quality Based on 5G Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yuna Si
Keyword(s):  
Statistical Analysis ◽  
Consumer Behavior ◽  
Service Quality ◽  
Qualitative Interviews ◽  
Online Consumer Behavior ◽  
Service Quality Evaluation ◽  
Online Consumer ◽  
The Cost ◽  
Consumption Habits

In order to better explore the consumer psychology activities of consumers and reduce the cost control risks of enterprises, this article aims to explore the relationship between online consumer behavior and e-commerce service quality and hopes to study e-commerce by dividing online consumer groups. This article uses 5G technology to track consumer consumption habits and consumption costs. First, according to the existing literature and qualitative interviews with online consumers, it is determined that the e-commerce service quality evaluation factors are the core service quality-related system reliability, efficiency, guarantee and completion, and the quality of after-sales service. Then, based on the data obtained from the questionnaire, SPSS statistical analysis software was used to analyze the reliability of the sample variables, thereby improving the quality of the sample data. We perform descriptive statistical analysis on these measurement items. Each attribute calculates the importance of each dimension. Through the analysis of experimental cases, it can be seen that the use of 5G technology can well match consumers’ consumption habits and message needs and can evaluate the quality of e-commerce services more accurately and scientifically.

scholarly journals Research Jungle on Online Consumer Behaviour in the Context of Web 2.0: Traceability, Frontiers and Perspectives in the Post-Pandemic Era

2021 ◽  
Vol 16 (5) ◽  
pp. 1740-1767
Author(s):  
Xi Zhang ◽  
Hongda Liu ◽  
Pinbo Yao
Keyword(s):  
Consumer Behavior ◽  
Web 2.0 ◽  
Research Network ◽  
Analysis Model ◽  
Economic Changes ◽  
Consumption Behavior ◽  
Online Consumer Behavior ◽  
Traditional Research ◽  
Online Consumer ◽  
Development Paths

In recent years, the study of online consumption behavior has gradually formed its research system and analysis model based on the inheritance of traditional research paradigms, focusing on the inner mechanism of consumption models explained by consumption activities. Online consumption is based on the research scenario of social e-commerce and forms a broad research network through the extension of consumer objects, consumer psychology, and consumer concepts. Although the theoretical constructs of online consumer behavior continue to improve, the relevant studies still do not fully grasp the research frontiers due to the lagging research nature. In the context of Web 2.0, it is impossible to run through the latest developments in online consumption research. Moreover, the study of online consumer behavior has shown a trend of diversification and multiple schools of thought, and a research jungle has emerged, which in essence is the perfection and new height of the study of consumerism. This paper analyses the origins, frontiers, and prospects of online consumer behavior research to clarify the formation principles, development paths, and future directions of the online consumer behavior research jungle. Ultimately based on the economic changes in the post-pandemic context, this paper integrates and proposes an evolving mechanism for studying online consumption behavior, intending to achieve a peek into and reveal the jungle of online consumption research.

scholarly journals Minimum description length and psychological clustering models

2019 ◽  
Author(s):  
Michael David Lee ◽  
Danielle Navarro
Keyword(s):  
Data Analysis ◽  
Goodness Of Fit ◽  
Minimum Description Length ◽  
Additive Clustering ◽  
Similarity Data ◽  
Additive Trees ◽  
Using Data

Clustering is one of the most basic and useful methods of data analysis. This chapter describes a number of powerful clustering models, developed in psychology, for representing objects using data that measure the similarities between pairs of objects. These models place few restrictions on how objects are assigned to clusters,and allow for very general measures of the similarities between objects and clusters.Geometric Complexity Criteria (GCC) are derived for these models, and are used to fit the models to similarity data in a way that balances goodness-of-fit with complexity. Complexity analyses, based on the GCC, are presented for the two most widely used psychological clustering models, known as “additive clustering”and “additive trees”

SOCIAL AND POLITICAL EFFECTS OF THE COVID-19 PANDEMIC IN RUSSIA: RESULTS OF A STUDY WITHIN THE FRAMEWORK OF THE "WORLD INTERNET PROJECT - 2021"

2021 ◽  
Vol 4 (1) ◽  
pp. 3-13
Author(s):  
I.A. Batanina ◽  
◽  
E.V. Brodovskaya ◽  
A.Y. Dombrovskaya ◽  
R.V. Parma ◽  
...  
Keyword(s):  
Well Being ◽  
Behavioral Characteristics ◽  
Negative Consequences ◽  
Online Retail ◽  
Online Consumer Behavior ◽  
The Social ◽  
Political Effects ◽  
Coronavirus Infection ◽  
Online Consumer ◽  
Digital Gap

The results of the All-Russian survey on the social well-being of citizens in the con-text of the spread of the COVID-19 pandemic are presented. The baseline results were con-clusions about changes in Russians 'offline and online consumer behavior, social expecta-tions, fears and citizens' perception of universal vaccination as a measure to combat the COVID-19 pandemic. The study showed that three types of fears prevail among Russians: coronavirus infection of relatives and friends, their own illness when they do not receive the necessary medical care, and a drop in income (worsening living conditions) amid an uncon-trollably spreading pandemic. The analysis of the survey database showed the activation of digital behavior of citizens in the context of the pandemic, which became a favorable factor in the development of online retail. Against the background of the spread of the COVID-19 vi-rus, the age structure of the Russian national audience is changing, and the digital gap be-tween generations is gradually being bridged. The pandemic triggered the involvement of older people in the digital space. Cluster analysis of the research data made it possible to segment Russians into three groups in relation to the pandemic and measures to overcome it: covid-pessimists, who suffered the most from the restrictions of the corona virus and did not adapt to life under conditions of covid-restrictions; covid-optimists who have successfully adapted to new circumstances in connection with the spread of the COVID-19 virus; covid-realists focused on constructively overcoming the negative consequences of restrictive pandemic measures. Their socio-demographic and behavioral characteristics have been ana-lyzed, and the specificity of the civic position of representatives of various clusters of Rus-sians has been established.

Understanding the Reasons for Gender Difference in Online Information Processing of Consumers

2019 ◽  
pp. 230-252
Author(s):  
Ceyda Tanrikulu
Keyword(s):  
Gender Differences ◽  
Information Processing ◽  
Consumer Behavior ◽  
Gender Difference ◽  
Theoretical Perspective ◽  
Future Research ◽  
Online Information ◽  
Strategic Decisions ◽  
Online Consumer Behavior ◽  
Online Consumer

This chapter aims to provide proposals about understanding the gender difference in online information processing that have been developed based on the theories and the findings of the current research. Major findings in the literature indicate the gender difference in online information processing. This chapter can be used to help gain insight about the online consumer behavior based on gender approach by presenting theoretical perspective, providing basis for future research, enrich the understanding about gender differences in online information processing, and to give suggestion for implications requiring strategic decisions.

Apps-Commerce in Emerging Markets

2017 ◽  
pp. 51-69 ◽  
Author(s):  
Sajad Rezaei ◽  
Maryam Emmi
Keyword(s):  
Information Technology ◽  
Consumer Behavior ◽  
Emerging Markets ◽  
Marketing Strategies ◽  
Current Understanding ◽  
The Internet ◽  
Online Consumer Behavior ◽  
Online Consumer ◽  
Flow Of Information ◽  
Large Flow

The Internet and Apps related technologies are considered as information “super highway” since they are able to connect people, computers, and data to one another. Because of them, a new communication medium has risen, which provides an access to the large flow of information across various broad extensions. As a consequence, there has been a need for understanding the behaviors of online consumers, since Information Technology and its usage have had a massive impact on shopping behaviors as well as the rate of market success. This chapter's aim will be to sanitize the current understanding of Apps/online consumer behavior to shape Apps marketing strategies and implementations.

A Review of Antecedents of Online Repurchase Behavior in Indian E-Commerce Paradigm Shift

2021 ◽  
pp. 1578-1597
Author(s):  
Syed Habeeb ◽  
K. Francis Sudhakar
Keyword(s):  
Systematic Review ◽  
Consumer Behavior ◽  
Customer Satisfaction ◽  
Marketing Research ◽  
Journal Articles ◽  
Exclusion Criteria ◽  
Repurchase Intentions ◽  
Online Consumer Behavior ◽  
Research Areas ◽  
Online Consumer

The purpose of this chapter is to highlight research areas of customer satisfaction and repurchase intentions and their antecedents in the Indian e-commerce industry. To retain, attract, and satisfy customers, e-retailers need to understand how and why online customers evaluate a web store. The relevant areas of consumer behavior and marketing research were derived to explain the possible gaps to study with respect to e-commerce in India. To do so, a systematic review of online consumer behavior literature is conducted. Following inclusion and exclusion criteria, a total of 109 journal articles are analyzed. The major finding of the chapter was that there is very less amount of research considering the areas of customer satisfaction, trust, loyalty along with repurchase behavior of the online customer in specific to the Indian context. Therefore, it is a need of the hour to extend the study to know the repurchase behavior of the online consumer in present time.

Online Consumer Behaviors Trigger Drastic Distribution Changes

2021 ◽  
pp. 303-321
Author(s):  
Mitsunori Hirogaki
Keyword(s):  
Consumer Behavior ◽  
Case Studies ◽  
Distribution Channel ◽  
Retail Market ◽  
Online Technology ◽  
Online Consumer Behavior ◽  
Channel Strategy ◽  
Retail Strategy ◽  
Online Consumer ◽  
The Impact

In this chapter, the author investigated the characteristics of online consumer behavior regarding the grocery retail market and their impact on retailers' distribution channel strategies. It examined the impact of recent innovations and the globalization of online technology on retail strategy. To achieve these goals, this study analyzed case studies of online consumer behavior in the Japanese online grocery market. Not only has there been a dramatic increase in sales over the last decade, but there have also been significant changes in both online technology and distribution channel strategy in this market. Underlying this transformation is the influence of Japan's characteristic online consumer behavior. Based on an empirical analysis of Japanese consumers and several case studies, this chapter predicts the future features of the online grocery market.

Developing a Research Framework to Assess Online Consumer Behaviour Using Netnography in India

2016 ◽  
pp. 154-167
Author(s):  
Gautam Deka ◽  
Sumangla Rathore ◽  
Avinash Panwar
Keyword(s):  
Research Method ◽  
Consumer Behaviour ◽  
Ethnographic Research ◽  
Online Consumer Behavior ◽  
Internet Users ◽  
Computer Mediated ◽  
Specialized Form ◽  
Online Consumer ◽  
Over Time ◽  
Online Consumer Behaviour

Netnography is a specialized form of ethnographic research that has been adapted to the unique contingencies of various types of computer-mediated social interaction. With the tremendous growth in the number of Internet users in India, the potential of utilizing netnography to study various aspects of management and business has also increased. Several e-Commerce companies have started operating in India since 2007. Over time, the number of online consumers has also increased in India. Therefore it is important to know the online consumer behaviour towards e-Commerce companies operating in India. Keeping the above facts in view, this chapter proposes Netnogrpahy as an effective research method to assess online consumer behavior. The chapter not only helps in providing future agenda for research, but also presents a framework that may be adopted to carry out Netnogrpahy of e-commerce related websites in India.

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