Decision-making for high-involvement products: Topic modelling using online reviews
High-involvement products require a complex decision-making process. Automobiles require time and effort and a financial budget to purchase, requiring the consideration of diverse characteristics of the vehicle before purchase. Research in this area has focused primarily on finding the most signific...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2020
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| Online Access: | https://eprints.nottingham.ac.uk/61780/ |
| _version_ | 1848799907242049536 |
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| author | Lee, Chanyoung |
| author_facet | Lee, Chanyoung |
| author_sort | Lee, Chanyoung |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | High-involvement products require a complex decision-making process. Automobiles require time and effort and a financial budget to purchase, requiring the consideration of diverse characteristics of the vehicle before purchase. Research in this area has focused primarily on finding the most significant features when purchasing an automobile using the traditional statistical method with surveys. However, advanced linguistic technique analysis provides an opportunity to extract meaning from the diverse comments provided by owners. In this paper, the author identifies the key topics of the customer decision-making process from electric automobile owners using a topic modelling approach with a latent Dirichlet allocation (LDA) model combined with natural language processing techniques. The dataset includes 956 free-text customer online reviews for Tesla. In an exploratory analysis involving electric automobiles, LDA uncovered 10 comprehensive lists of topics discussed by customers. Topics are key for electric automobile companies to manage their interactions with customers by understanding the primary interests and features in terms of the decision-making process of current and future customers. The proposed approach and findings are beneficial to support understanding customer perceptions. Through this method, the marketing and business strategy can be improved to maintain current customers and attract future customers. |
| first_indexed | 2025-11-14T20:43:07Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-61780 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:43:07Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-617802022-12-14T10:03:41Z https://eprints.nottingham.ac.uk/61780/ Decision-making for high-involvement products: Topic modelling using online reviews Lee, Chanyoung High-involvement products require a complex decision-making process. Automobiles require time and effort and a financial budget to purchase, requiring the consideration of diverse characteristics of the vehicle before purchase. Research in this area has focused primarily on finding the most significant features when purchasing an automobile using the traditional statistical method with surveys. However, advanced linguistic technique analysis provides an opportunity to extract meaning from the diverse comments provided by owners. In this paper, the author identifies the key topics of the customer decision-making process from electric automobile owners using a topic modelling approach with a latent Dirichlet allocation (LDA) model combined with natural language processing techniques. The dataset includes 956 free-text customer online reviews for Tesla. In an exploratory analysis involving electric automobiles, LDA uncovered 10 comprehensive lists of topics discussed by customers. Topics are key for electric automobile companies to manage their interactions with customers by understanding the primary interests and features in terms of the decision-making process of current and future customers. The proposed approach and findings are beneficial to support understanding customer perceptions. Through this method, the marketing and business strategy can be improved to maintain current customers and attract future customers. 2020-12-01 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/61780/1/20171924_BUSI4374%20UNUK_Dissertation.pdf Lee, Chanyoung (2020) Decision-making for high-involvement products: Topic modelling using online reviews. [Dissertation (University of Nottingham only)] |
| spellingShingle | Lee, Chanyoung Decision-making for high-involvement products: Topic modelling using online reviews |
| title | Decision-making for high-involvement products: Topic modelling using online reviews |
| title_full | Decision-making for high-involvement products: Topic modelling using online reviews |
| title_fullStr | Decision-making for high-involvement products: Topic modelling using online reviews |
| title_full_unstemmed | Decision-making for high-involvement products: Topic modelling using online reviews |
| title_short | Decision-making for high-involvement products: Topic modelling using online reviews |
| title_sort | decision-making for high-involvement products: topic modelling using online reviews |
| url | https://eprints.nottingham.ac.uk/61780/ |