Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Design | en_US |
| dc.contributor.advisor | de Bont, Cees (SD) | - |
| dc.contributor.advisor | Liu, Sylvia (SD) | - |
| dc.creator | Zhang, Mengting | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/9681 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Towards a comprehensive and integrated framework that serves as a basis to describe, stimulate and analyze innovation in intelligent products | en_US |
| dcterms.abstract | After breakthroughs in machine learning and the commercialisation of artificial intelligence technology, products have become more 'intelligent'. New features were developed, like decision-making, natural language processing, or intuitive interaction (e.g., Feil-Seifer & Mataric, 2009; Kiritsis, 2011; Leitao et al., 2015), which give products relative autonomy. Although intelligent products are still in the earliest stages of development, the influence that they will wield over everyday life will be revolutionary. In the near future, it is safe to forecast that these products may reshape most, if not all, aspects of human life. As a result, industries, companies, and product development teams need to rethink and redefine their strategy towards this change. To equip them to take part in this new arena, this research aims to generate and structure knowledge and insights to facilitate the innovation of intelligent products across industries and society. The challenge is that effective innovations are not easily fashioned -they can only be achieved through careful design (Morris et al., 2014). As studies of intelligent product are still an emerging domain, very little research has sought to develop frameworks for understanding innovation in consumer-oriented intelligent products, especially considering its specific requirements, such as multi-sourced inspiration, dynamic agenda or complexity of characteristics. This research gap motivates the present attempt to explore, build, describe and test a conceptual framework, which can be used to describe, stimulate and analyse innovation of intelligent products. The framework was built based on systematic literature review of 376 theoretical and empirical studies from multiple disciplines were reviewed, including design, engineering, information technology, computer science, marketing, and economics; and 202 in-depth expert interviews with experts and researchers from various disciplinary backgrounds, positions, locations, and nationalities to collect diversified insights. The framework was then tested through an in-depth expert interview to improve its usability and flexibility; a workshop with senior high school students for its capability to stimulate innovation in intelligent products; and a case study of an intelligent unmanned automatic vehicle to demonstrate how it can be used to describe and analyse the innovation pattern, strength and weakness, or opportunities for product development. The research contributes to the current understanding of intelligent product innovation and can be beneficial for both academic researchers and business practitioners in the following ways: - To describe and analyse innovation pattern of products; - To diagnose product strength and weakness; - To discover and forecast product evolutionary path and trend; - To ideate a product at early stage; - To facilitate multidisciplinary and cross-department communication and collaboration; - To translate company's insights and strategies into actionable task. - To transform traditional product into intelligent product types. The research also shares a vision of intelligent product innovation in the future, which can be exploited by policy makers for industry-upgrade and transformation. | en_US |
| dcterms.extent | x, 197 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2018 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.LCSH | Product design | en_US |
| dcterms.LCSH | New products | en_US |
| dcterms.LCSH | Artificial intelligence -- Industrial applications | en_US |
| dcterms.accessRights | open access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022168758603411.pdf | For All Users | 3.64 MB | Adobe PDF | View/Open |
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