Online Consumer Typologies and Their Shopping Behaviors in B2C E-Commerce Platforms
Bibliographic Data
| ID | 4181845 |
|---|---|
| Authors | Farid Huseynov (0000-0002-9936-0596, Gebze Technical University, corresponding author), Sevgi Özkan Yıldırım, Sevgi Özkan (0000-0002-7603-3656, Middle East Technical University) |
| Year | 2019 |
| Volume | 9 |
| Issue | 2 |
| Publication date | 2019-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | SAGE Open (JOURNAL) |
| Journal identifiers | ISSN: 2158-2440 • E-ISSN: 2158-2440 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2158244019854639 |
| OpenAlex | W2948375769 |
| Language | EN |
| Citations received | 9 |
| References cited | 72 |
Consumer behavior in e-commerce platforms is one of the extensively researched area. Numerous studies in this field assessed consumer online shopping behavior from various aspects. However, literature review showed that most of the conducted studies do not carry out market segmentation analysis while accessing shopping behavior of online consumers. Therefore, the general conclusions made by these studies about consumer attitude, behavior, and decision-making process might not reflect actual behaviors of different consumer segments. In contrast to previous studies, this study initially carried out psychographic market segmentation analysis and found four different online consumer segments. Later, shopping behavior of each determined segment was assessed by using the developed behavior evaluation model. Findings of this study provide important information to e-retailers about the behavioral characteristics of each consumer segment. E-retailers can utilize this study findings to effectively allocate their marketing resources and design more successful marketing mix for each consumer segment
Advertising · Business · Consumer behaviour · E-commerce · Market segmentation · Psychographic · Segmentation · Computer Science · Consumer Retail Behavior Studies · Digital Marketing and Social Media · Technology Adoption and User Behaviour · Marketing
Social influence and UTAUT in predicting digital immigrants’ technology use
Social Distancing, Health Concerns, and Digitally Empowered Consumption Behavior Under Covid-19
Cultural factors that influence the adoption of e-commerce
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What Drives or Decelerates Generation Z? An Empirical Study Navigating Consumer Buying Intentions in Online Shopping
What People Talk About Multi-Channel Purchasing Behavior and What They Intend to do
The Effects of Environmental Policy and the Perception of Electric Motorcycles on the Acceptance of Electric Motorcycles
Exploring the Relationship between WeChat Usage and E-purchase Intention During the Covid-19 Pandemic Among University Students in China
Effect of Mobile Social Apps on Consumer's Purchase Attitude
Multivariate data analysis
Understanding customers' repeat purchase intentions in B2C e‐commerce
Consumer e-shopping acceptance
Predicting consumer intentions to use on-line shopping
Understanding Information Technology Usage
Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT)
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance
The theory of planned behavior
Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
Structural Equation Models with Unobservable Variables and Measurement Error
Structural Equations with Latent Variables
Online shoppers’ perceptions of e‐retailers’ ethics, cultural orientation, and loyalty
The theory of planned behavior and Internet purchasing
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| Unique citing works | 9 |
|---|---|
| Citations per year | 1,5 |
| Citation span | 2020 - 2024 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 8 |