Revealing the dual importance and Kano type of attributes through customer review analytics. (January 2022)
- Record Type:
- Journal Article
- Title:
- Revealing the dual importance and Kano type of attributes through customer review analytics. (January 2022)
- Main Title:
- Revealing the dual importance and Kano type of attributes through customer review analytics
- Authors:
- Lee, Seoyoon
Park, Sohyun
Kwak, Minjung - Abstract:
- Abstract: Identifying which attributes of a product are important to customers and clarifying how the attributes affect customer satisfaction are critical for a firm to survive and succeed in the market. To assist in characterizing the impacts of various attributes and prioritizing the attributes for design and marketing purposes, this paper proposes a novel review-analytics framework, called importance-Kano (I-Kano) analysis. I-Kano analysis holistically assesses the impacts of various attributes from three different perspectives that potentially may conflict with each other, i.e., appearance (stated importance), significance (derived importance), and Kano type. By fusing term-frequency and sentiment analyses of online reviews with conjoint analysis, the I-Kano analysis simultaneously identifies the dual importance (appearance and significance) and Kano type of an attribute. As the final deliverable of the I-Kano analysis, a new visualization scheme, called the I-Kano matrix, is proposed, which is the first attempt to integrate the dual importance and Kano type of multiple attributes in a single chart. The I-Kano matrix facilitates an intuitive interpretation of the multidimensional impacts of various attributes and supports the aggregation and comparison of the results from different market segments. Through the I-Kano analysis, the attributes of great importance in a market segment, which are useful for developing products and planning marketing promotions, can beAbstract: Identifying which attributes of a product are important to customers and clarifying how the attributes affect customer satisfaction are critical for a firm to survive and succeed in the market. To assist in characterizing the impacts of various attributes and prioritizing the attributes for design and marketing purposes, this paper proposes a novel review-analytics framework, called importance-Kano (I-Kano) analysis. I-Kano analysis holistically assesses the impacts of various attributes from three different perspectives that potentially may conflict with each other, i.e., appearance (stated importance), significance (derived importance), and Kano type. By fusing term-frequency and sentiment analyses of online reviews with conjoint analysis, the I-Kano analysis simultaneously identifies the dual importance (appearance and significance) and Kano type of an attribute. As the final deliverable of the I-Kano analysis, a new visualization scheme, called the I-Kano matrix, is proposed, which is the first attempt to integrate the dual importance and Kano type of multiple attributes in a single chart. The I-Kano matrix facilitates an intuitive interpretation of the multidimensional impacts of various attributes and supports the aggregation and comparison of the results from different market segments. Through the I-Kano analysis, the attributes of great importance in a market segment, which are useful for developing products and planning marketing promotions, can be identified. In addition, the I-Kano analysis can identify the segments of the market in which a certain attribute has greater relative importance, which is helpful in the design differentiation, targeting, and differentiated marketing of products. To demonstrate and validate the I-Kano analysis, an illustrative case study is described with an example of online hotel reviews. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 51(2022)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 51(2022)
- Issue Display:
- Volume 51, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 51
- Issue:
- 2022
- Issue Sort Value:
- 2022-0051-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-01
- Subjects:
- Online review -- Analytics -- Sentiment analysis -- Kano model -- Conjoint analysis -- Hospitality industry
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2022.101533 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 20994.xml