IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i18p4970-d266361.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "Evaluating the Performance of Systemic Innovation Problems of the IoT in Manufacturing Industries by Novel MCDM Methods," Sustainability, MDPI, vol. 11(18), pages 1-33, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:4970-:d:266361
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/18/4970/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/18/4970/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charles Edquist, 2011. "Design of innovation policy through diagnostic analysis: identification of systemic problems (or failures)," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(6), pages 1725-1753, December.
    2. Edquist, Charles, 2011. "Innovation Policy Design: Identification of Systemic Problems," Papers in Innovation Studies 2011/6, Lund University, CIRCLE - Centre for Innovation Research.
    3. Kebede, Kassahun Y. & Mitsufuji, Toshio, 2017. "Technological innovation system building for diffusion of renewable energy technology: A case of solar PV systems in Ethiopia," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 242-253.
    4. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    5. Tigabu, Aschalew D. & Berkhout, Frans & van Beukering, Pieter, 2015. "Technology innovation systems and technology diffusion: Adoption of bio-digestion in an emerging innovation system in Rwanda," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 318-330.
    6. Anna J. Wieczorek & Marko P. Hekkert, 2012. "Corrigendum to 'Systemic instruments for systemic innovation problems: A framework for policy makers and innovation scholars'," Science and Public Policy, Oxford University Press, vol. 39(6), pages 842-842, December.
    7. Mohamed Hanine & Omar Boutkhoum & Tarik Agouti & Abdessadek Tikniouine, 0. "A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection," Information Systems and e-Business Management, Springer, vol. 0, pages 1-29.
    8. Tigabu, Aschalew Demeke & Berkhout, Frans & van Beukering, Pieter, 2015. "The diffusion of a renewable energy technology and innovation system functioning: Comparing bio-digestion in Kenya and Rwanda," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 331-345.
    9. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry," Sustainability, MDPI, vol. 11(8), pages 1-34, April.
    10. Rajagopal, 2012. "Decision Making," Palgrave Macmillan Books, in: Darwinian Fitness in the Global Marketplace, chapter 7, pages 191-224, Palgrave Macmillan.
    11. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2007. "Extended VIKOR method in comparison with outranking methods," European Journal of Operational Research, Elsevier, vol. 178(2), pages 514-529, April.
    12. Liu, Chui-Hua & Tzeng, Gwo-Hshiung & Lee, Ming-Huei, 2012. "Improving tourism policy implementation – The use of hybrid MCDM models," Tourism Management, Elsevier, vol. 33(2), pages 413-426.
    13. Gao, Ruxing & Nam, Hyo On & Ko, Won Il & Jang, Hong, 2018. "Integrated system evaluation of nuclear fuel cycle options in China combined with an analytical MCDM framework," Energy Policy, Elsevier, vol. 114(C), pages 221-233.
    14. Mohamed Hanine & Omar Boutkhoum & Tarik Agouti & Abdessadek Tikniouine, 2017. "A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection," Information Systems and e-Business Management, Springer, vol. 15(4), pages 897-925, November.
    15. Kivimaa, Paula & Kern, Florian, 2016. "Creative destruction or mere niche support? Innovation policy mixes for sustainability transitions," Research Policy, Elsevier, vol. 45(1), pages 205-217.
    16. Anna J. Wieczorek & Marko P. Hekkert, 2012. "Systemic instruments for systemic innovation problems: A framework for policy makers and innovation scholars," Science and Public Policy, Oxford University Press, vol. 39(1), pages 74-87, February.
    17. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    18. Reichardt, Kristin & Negro, Simona O. & Rogge, Karoline S. & Hekkert, Marko P., 2016. "Analyzing interdependencies between policy mixes and technological innovation systems: The case of offshore wind in Germany," Technological Forecasting and Social Change, Elsevier, vol. 106(C), pages 11-21.
    19. Bergek, Anna & Jacobsson, Staffan & Carlsson, Bo & Lindmark, Sven & Rickne, Annika, 2008. "Analyzing the functional dynamics of technological innovation systems: A scheme of analysis," Research Policy, Elsevier, vol. 37(3), pages 407-429, April.
    20. Chen, Xiafei & Liu, Zhiying & Zhu, Qingyuan, 2018. "Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain," Technovation, Elsevier, vol. 74, pages 42-53.
    21. R Rajagopal & E del Castillo, 2007. "A Bayesian approach for multiple criteria decision making with applications in Design for Six Sigma," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 779-790, June.
    22. Flavio Tonelli & Steve Evans & Paolo Taticchi, 2013. "Industrial sustainability: challenges, perspectives, actions," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 7(2), pages 143-163.
    23. Hermans, Frans & Geerling-Eiff, Floor & Potters, Jorieke & Klerkx, Laurens, 2019. "Public-private partnerships as systemic agricultural innovation policy instruments – Assessing their contribution to innovation system function dynamics," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 88, pages 76-95.
    24. Söderholm, Patrik & Hellsmark, Hans & Frishammar, Johan & Hansson, Julia & Mossberg, Johanna & Sandström, Annica, 2019. "Technological development for sustainability: The role of network management in the innovation policy mix," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 309-323.
    25. Jeng, Don Jyh-Fu & Huang, Kuo-Hsin, 2015. "Strategic project portfolio selection for national research institutes," Journal of Business Research, Elsevier, vol. 68(11), pages 2305-2311.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chi-Yo Huang & Min-Jen Yang & Jeen-Fong Li & Hueiling Chen, 2021. "A DANP-Based NDEA-MOP Approach to Evaluating the Patent Commercialization Performance of Industry–Academic Collaborations," Mathematics, MDPI, vol. 9(18), pages 1-26, September.
    2. Parra-López, Carlos & Reina-Usuga, Liliana & Garcia-Garcia, Guillermo & Carmona-Torres, Carmen, 2024. "Functional analysis of technological innovation systems enabling digital transformation: A semi-quantitative multicriteria framework applied in the olive sector," Agricultural Systems, Elsevier, vol. 214(C).
    3. Blichfeldt, Henrik & Faullant, Rita, 2021. "Performance effects of digital technology adoption and product & service innovation – A process-industry perspective," Technovation, Elsevier, vol. 105(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry," Sustainability, MDPI, vol. 11(8), pages 1-34, April.
    2. Jhon Wilder Zartha Sossa & Oscar Hernán López Montoya & Julio Cesar Acosta Prado, 2021. "Determinants of a sustainable innovation system," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 1345-1356, February.
    3. Konstantinos Karanasios & Paul Parker, 2018. "Explaining the Diffusion of Renewable Electricity Technologies in Canadian Remote Indigenous Communities through the Technological Innovation System Approach," Sustainability, MDPI, vol. 10(11), pages 1-28, October.
    4. Edmondson, Duncan L. & Kern, Florian & Rogge, Karoline S., 2019. "The co-evolution of policy mixes and socio-technical systems: Towards a conceptual framework of policy mix feedback in sustainability transitions," Research Policy, Elsevier, vol. 48(10).
    5. Raven, Rob & Walrave, Bob, 2020. "Overcoming transformational failures through policy mixes in the dynamics of technological innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    6. Hu, Rui & Skea, Jim & Hannon, Matthew J., 2018. "Measuring the energy innovation process: An indicator framework and a case study of wind energy in China," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 227-244.
    7. De Oliveira, Luiz Gustavo Silva & Negro, Simona O., 2019. "Contextual structures and interaction dynamics in the Brazilian Biogas Innovation System," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 462-481.
    8. Borges, Cosme P. & Silberg, Timothy R. & Uriona-Maldonado, Mauricio & Vaz, Caroline R., 2023. "Scaling actors’ perspectives about innovation system functions: Diffusion of biogas in Brazil," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    9. Lashitew, Addisu A. & van Tulder, Rob & Liasse, Yann, 2019. "Mobile phones for financial inclusion: What explains the diffusion of mobile money innovations?," Research Policy, Elsevier, vol. 48(5), pages 1201-1215.
    10. Hoppmann, Joern & Huenteler, Joern & Girod, Bastien, 2014. "Compulsive policy-making—The evolution of the German feed-in tariff system for solar photovoltaic power," Research Policy, Elsevier, vol. 43(8), pages 1422-1441.
    11. Hornum, Sebastian Toft & Bolwig, Simon, 2021. "A functional analysis of the role of input suppliers in an agricultural innovation system: The case of small-scale irrigation in Kenya," Agricultural Systems, Elsevier, vol. 193(C).
    12. Torres-Avila, Angelica & Aguilar-Ávila, Jorge & Santoyo-Cortés, Vinicio Horacio & Martínez-González, Enrique Genaro & Aguilar-Gallegos, Norman, 2022. "Innovation in the pineapple value chain in Mexico: Explaining the global adoption process of the MD-2 hybrid," Agricultural Systems, Elsevier, vol. 198(C).
    13. Danish Ahmad Mir & Christopher N.H. Doll & Robert Lindner & Muhammad Tabish Parray, 2020. "Explaining the Diffusion of Energy-Efficient Lighting in India: A Technology Innovation Systems Approach," Energies, MDPI, vol. 13(21), pages 1-16, November.
    14. Reale, Filippo, 2019. "Governing innovation systems: A Parsonian social systems perspective," Technology in Society, Elsevier, vol. 59(C).
    15. Li, Chengjiang & Negnevitsky, Michael & Wang, Xiaolin & Yue, Wen Long & Zou, Xin, 2019. "Multi-criteria analysis of policies for implementing clean energy vehicles in China," Energy Policy, Elsevier, vol. 129(C), pages 826-840.
    16. Victoria Galan-Muros & Todd Davey, 2019. "The UBC ecosystem: putting together a comprehensive framework for university-business cooperation," The Journal of Technology Transfer, Springer, vol. 44(4), pages 1311-1346, August.
    17. Parra-López, Carlos & Reina-Usuga, Liliana & Garcia-Garcia, Guillermo & Carmona-Torres, Carmen, 2024. "Functional analysis of technological innovation systems enabling digital transformation: A semi-quantitative multicriteria framework applied in the olive sector," Agricultural Systems, Elsevier, vol. 214(C).
    18. Shu-Kung Hu & James J. H. Liou & Ming-Tsang Lu & Yen-Ching Chuang & Gwo-Hshiung Tzeng, 2018. "Improving NFC Technology Promotion for Creating the Sustainable Education Environment by Using a Hybrid Modified MADM Model," Sustainability, MDPI, vol. 10(5), pages 1-24, April.
    19. Krammer, Sorin M.S., 2015. "Science, technology and innovation for economic competitiveness: the role of smart specialization in less-developed countries," MPRA Paper 80203, University Library of Munich, Germany.
    20. Rogge, Karoline S. & Pfluger, Benjamin & Geels, Frank W., 2020. "Transformative policy mixes in socio-technical scenarios: The case of the low-carbon transition of the German electricity system (2010–2050)," Technological Forecasting and Social Change, Elsevier, vol. 151(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:4970-:d:266361. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.