A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems
dc.contributor.author | Zhou, Feng | |
dc.contributor.author | Ayoub, Jackie | |
dc.contributor.author | Yang, X. Jessie | |
dc.contributor.author | Xu, Qianli | |
dc.date.accessioned | 2020-02-25T20:06:43Z | |
dc.date.available | 2020-02-25T20:06:43Z | |
dc.date.issued | 2019-10-03 | |
dc.identifier.issn | 1528-9001 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/153965 | |
dc.description.abstract | Creating product ecosystems has been one of the strategic ways to enhance user experience and business advantages. Among many, customer needs analysis for product ecosystems is one of the most challenging tasks in creating a successful product ecosystem from both the perspectives of marketing research and product development. In this paper, we propose a machine-learning approach to customer needs analysis for product ecosystems by examining a large amount of online user-generated product reviews within a product ecosystem. First, we filtered out uninformative reviews from the informative reviews using a fastText technique. Then, we extract a variety of topics with regard to customer needs using a topic modeling technique named latent Dirichlet allocation. In addition, we applied a rule-based sentiment analysis method to predict not only the sentiment of the reviews but also their sentiment intensity values. Finally, we categorized customer needs related to different topics extracted using an analytic Kano model based on the dissatisfaction-satisfaction pair from the sentiment analysis. A case example of the Amazon product ecosystem was used to illustrate the potential and feasibility of the proposed method. | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | MD-19-1275 | en_US |
dc.subject | machine learning, customer needs analysis, product ecosystems, kano model, design automation, design for X, design theory and methodology, product design | en_US |
dc.title | A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Industrial and Operations Engineering | |
dc.subject.hlbtoplevel | Engineering | |
dc.contributor.affiliationumcampus | Dearborn | en_US |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/153965/1/A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems.pdf | |
dc.identifier.source | ASME | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-6071-0387 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-6123-073X | en_US |
dc.identifier.orcid | https://orcid.org/0000-0003-0274-492X | en_US |
dc.identifier.name-orcid | Yang, X. Jessie; 0000-0001-6071-0387 | en_US |
dc.identifier.name-orcid | Zhou, Feng; 0000-0001-6123-073X | en_US |
dc.identifier.name-orcid | Ayoub, Jackie; 0000-0003-0274-492X | en_US |
dc.owningcollname | Industrial and Manufacturing Systems Engineering (IMSE, UM-Dearborn) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.