Evaluating the Performance of Systemic Innovation Problems of the IoT in Manufacturing Industries by Novel MCDM Methods

Yu-Sheng Kao, Kazumitsu Nawata and Chi-Yo Huang
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Yu-Sheng Kao: Department of Technology Management for Innovation, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Kazumitsu Nawata: Department of Technology Management for Innovation, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Chi-Yo Huang: Department of Industrial Education, National Taiwan Normal University, Taipei 106, Taiwan

Sustainability, 2019, vol. 11, issue 18, 1-33

Abstract: The Internet of Things (IoT) is an important technological innovation that can enhance industrial competitiveness and sustainability. Thus, governments need to carefully construct an innovation portfolio that promotes sustainable IoT development. To help define an accurate innovation policy and promote development of the IoT industries, potential problems in terms of systemic perspectives should be examined. Such problems, so-called “systemic innovation problems”, influence and block sustainable development of IoT technology as well as the IoT industry. However, past studies that explored systemic innovation problems in IoT-related industries are limited. Thus, this research aims to explore systemic innovation problems related to configuring an IoT innovation policy portfolio. A hybrid Bayesian rough based evaluation model was used to derive the most feasible policy instruments. The modified Delphi, Bayesian Rough Decision-Making Trial and Evaluation Laboratory Based Network Procedures (BR-DNP), and the modified Bayesian rough Vlse Kriterijumska Optimizacija I Kompromisno Resenje (MBR-VIKOR) were introduced. Gaps in performance corresponding to each systemic innovation problem can thus be assessed based on the features of technological innovation systems. The applicability of the proposed model for promoting industrial sustainability of IoT in the Taiwanese smart manufacturing industry (based on the opinions provided by Taiwanese experts) was verified by an empirical study. Eleven systemic innovation problems that influence the development of the IoT for the smart manufacturing industry were compared and ranked. Based on the results of the empirical study, the performance-gap ratio of “low level of interdisciplinary collaboration” problem is the lowest, as compared to other systemic innovation problems. In addition, the systemic functions of entrepreneurial activities and knowledge development are relatively more important than other systemic functions. The empirical results can serve as a basis for planning an IoT innovation policy portfolio definition and roadmap. Moreover, suggestions for enhancing current systemic innovation problems are provided for policy makers and industrial researchers, according to the results of the evaluation.

Keywords: systemic innovation problems; innovation policy; Multiple Criteria Decision Making (MCDM); Bayesian Rough MCDM Model; Decision Making Trial and Evaluation Laboratory based Network Process (DNP); VlšeKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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