Product design opportunity identification through mining the critical minority of customer online reviews

Yupeng Li (), Yanan Dong (), Yu Wang () and Na Zhang ()
Additional contact information
Yupeng Li: China University of Mining and Technology
Yanan Dong: China University of Mining and Technology
Yu Wang: China University of Mining and Technology
Na Zhang: China University of Mining and Technology

Electronic Commerce Research, 2025, vol. 25, issue 1, No 8, 239 pages

Abstract: Abstract Online reviews that contain customer requirements and expectations are valuable for product design opportunity identification (PDOI) in customer-centric design. As most reviews are non-informative and repetitive, the existing approaches may not be effective for PDOI. Besides, online reviews containing design opportunities tend to be the critical minority, which can be characterized as outliers in a review dataset (RDT). Motivated by this observation, this study develops an online review mining approach based on outlier detection technique to identify the critical minority of online reviews for PDOI. First, unstructured online reviews are modelled as a RDT from a product improvement perspective, and the metadata and information attributes of review are involved. Then, a non-parametric weighted neighborhood information network (WNIN)-based outlier detection method is investigated to determine outlier reviews. Finally, a real case study of the PDOI for Mi 10 is implemented to elaborate the feasibility and effectiveness of the proposed methodology.

Keywords: Product design opportunity identification; Customer online reviews; Non-parametric outlier detection; Dataset with mixed-valued attributes; Weighted neighborhood information network (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10660-023-09683-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:25:y:2025:i:1:d:10.1007_s10660-023-09683-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-023-09683-8

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().