Title: Identification of a technological chance in product-service system using KeyGraph and text mining on business method patents

Authors: Sora Lee; Moon-soo Kim; Yongtae Park; Chulhyun Kim

Addresses: Technology Strategy Team, Samsung SDS, Samsung SDS Tower, 125 Olympic-ro 35-gil, Songpa-gu, Seoul 138-240, Korea ' Department of Industrial and Management Engineering, Hankuk University of Foreign Studies, San 89, Wangsan-ri, Mohyeon-myun, Yongin-si, Kyungki-do 447-791, Republic of Korea ' Department of Industrial Engineering, School of Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea ' Department of Technology and Systems Management, Induk University, Choansan-ro 12, Nowon-gu, Seoul 139-749, Republic of Korea

Abstract: Notwithstanding the prevailing trend towards a product-service system (PSS), literature has not fully supported a company's PSS innovation due to an absence of available data and a lack of quantitative methodology. In particular, despite the importance of technology in PSS, literature has paid little attention to technology as an innovation source of PSS. In order to fill this academic and practical lacuna, this study proposes a database-centred approach for the identification of technological chances in PSS as an innovation source. For analysing PSS innovation, business method (BM) patents are utilised as a data source; further, the complementary pair of KeyGraph for chance discovery and text mining for knowledge discovery is systematically applied as a quantitative methodology. To illustrate the utility of the proposed approach, the case study of PSS in the mobile area is presented.

Keywords: product-service systems; technological chance; KeyGraph; text mining; business methods; patents; BM patents; chance identification; chance discovery; database-centred approach; PSS innovation; mobile industry.

DOI: 10.1504/IJTM.2016.075884

International Journal of Technology Management, 2016 Vol.70 No.4, pp.239 - 256

Accepted: 02 Apr 2015
Published online: 12 Apr 2016 *

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