Abstract
Purpose: The purpose of this paper is to analyse consumer purchasing behaviour in different cultural settings by exploring the value of consumer reviews from various countries. Design/methodology/approach: This study uses online review mining technology to collect, process and analyse user review data from multiple countries. The main procedures of this research are data collection, data pre-processing, feature extraction and sentiment analysis. Online reviews from the American, British and Indian websites for the iPhone 5s are analysed. Findings: Every country has unique cultural characteristics, and these cultural differences affect consumers’ perceptions, attitudes and purchasing behaviours. The results show that consumers from different countries exhibit different levels of attention towards the same product and have different emotional inclinations for the same product feature. In addition, the study also identified the advantages and disadvantages of the product. Limitations implications: The user reviews provide abundant feedback information that serves as a good intelligence resource for companies. Under the premise of different language habits, this paper uses a universal approach to analyse consumer behaviour from online reviews in different countries, which can help reveal consumers’ emotional inclination towards each feature of a product. This approach can be extended to other brands of mobile phones or other industries. Practical implications: Multinational companies should analyse the cultural characteristics of target groups when proposing transnational development strategies. Companies can understand the perceptions of their products based on the consumer reviews and can formulate their marketing and product strategies by considering consumer purchasing behaviours arising from cultural differences. Originality/value: This study identifies differences in consumer behaviour in different cultural settings by using a data mining method, which can help companies understand consumer perceptions and the performance and quality of product features.
Original language | English |
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Pages (from-to) | 1242-1263 |
Number of pages | 22 |
Journal | Kybernetes |
Volume | 48 |
Issue number | 6 |
DOIs | |
Publication status | Published - 13 Jun 2019 |
Keywords
- Consumer behaviour
- Culture
- Data mining
- Online review
ASJC Scopus subject areas
- Theoretical Computer Science
- Control and Systems Engineering
- Computer Science (miscellaneous)
- Engineering (miscellaneous)
- Social Sciences (miscellaneous)