IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5154-d801367.html

A Study of the Competitiveness and Development Strategy of Korean Venture Companies in the Fourth Industrial Revolution Using SWOT/AHP

Author

Listed:
  • Dongik Lee

    (Industry University Cooperation Foundation, Kangnam University, Yongin 16979, Korea)

  • Sangsuk Lee

    (Department of Global Business Administration, Kangnam University, Yongin 16979, Korea)

Abstract

This study derives the SWOT (Strength, Weakness, Opportunity, Threat) factors and competitiveness index necessary for Korean venture companies to succeed in the fourth industrial revolution. It suggests a SWOT strategy as well as an action plan in which the government and related parties prepare to secure global competitiveness, along with a very basic and systematic analysis. A total of 21 SWOT sub-factors were selected through a literature review and report analysis and were evaluated by various industry, academics, and policy experts via a Delphi survey. The results of pairwise comparative analysis using the AHP (Analytic Hierarchy Process) technique showed that the importance of the 4 SWOT quadrants could be arranged in order as strength (48%) → opportunity (25%) → threat (16%) → weakness (11%). Looking at the competitiveness index according to industry, ‘Artificial intelligence·Intelligent Robots·Autonomous driving (a)’, ‘Blockchain·Fintech (d)’, ‘Bio-health (f)’, and ‘Big data·Cloud (c)’ possessed high competitiveness. The ‘Internet of Things·5G (b)’, ‘3D printing·Virtual reality (g)’, and ‘New materials·Energy (e)’ industries were the least competent industries. Optimal strategies derived through an analysis of the competitiveness index are as follows: the S-O (Strength-Opportunity) strategy was optimal for industries such as ‘Internet of things·5G (b)’, ‘Big data·Cloud (c)’, ‘Bio-health (f)’, the S-T (Strength-Threat) strategy was optimal for ‘Artificial intelligence·Intelligent Robots·Autonomous driving (a)’, ‘Blockchain·Fintech (d)’ and ‘New materials·Energy (e)’. Finally, the W-T (Weakness -Threat) strategy should be prioritized for the ‘3D printing·Virtual Reality (g)’ industry. The implication of the study outlined above is that policies supporting the strengths and weaknesses of a company must be established beforehand for Korean venture companies to secure competitiveness in the fourth industrial revolution. First, it is of the utmost importance to develop a business faster by utilizing the excellent ICT infrastructure of Korea. Second, the Korean government should take a leading role in mediating the sharing of the resources (manpower, technology, equipment, etc.) that are available from each university, company, and research institute. Third, the government should prepare a technology development roadmap for commercialization as well as source technology for the fourth industrial revolution.

Suggested Citation

  • Dongik Lee & Sangsuk Lee, 2022. "A Study of the Competitiveness and Development Strategy of Korean Venture Companies in the Fourth Industrial Revolution Using SWOT/AHP," Sustainability, MDPI, vol. 14(9), pages 1-22, April.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5154-:d:801367
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5154/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/9/5154/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kurttila, Mikko & Pesonen, Mauno & Kangas, Jyrki & Kajanus, Miika, 2000. "Utilizing the analytic hierarchy process (AHP) in SWOT analysis -- a hybrid method and its application to a forest-certification case," Forest Policy and Economics, Elsevier, vol. 1(1), pages 41-52, May.
    2. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    3. Thomas L. Saaty, 2013. "The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach," Operations Research, INFORMS, vol. 61(5), pages 1101-1118, October.
    4. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    5. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.
    Full references (including those not matched with items on IDEAS)

    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. Madjid Tavana & Mariya Sodenkamp & Leena Suhl, 2010. "A soft multi-criteria decision analysis model with application to the European Union enlargement," Annals of Operations Research, Springer, vol. 181(1), pages 393-421, December.
    2. Heidemann, Gerrit & Schmidt, Sascha L. & von der Gracht, Heiko A. & Beiderbeck, Daniel, 2024. "The impact of the metaverse on the future business of professional football clubs – A prospective study," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    3. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    4. Fritschy, Carolin & Spinler, Stefan, 2019. "The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    5. Geissler, Dominik & Beiderbeck, Daniel & Schmidt, Sascha L. & Schreyer, Dominik, 2024. "Emerging technologies and shifting consumer motives: Projecting the future of the top-tier sports media product," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    6. Junpai Chen & Yue Chen & Yitong Zhu & Mingyan Xiao & Hongfei Yang & Huaming Huang & Linli Li, 2023. "Assessing the Sustainability of Urban Community Renewal Projects in Southern China Based on a Hybrid MADM Approach," Sustainability, MDPI, vol. 15(4), pages 1-33, February.
    7. Santopuoli, Giovanni & Marchetti, Marco & Giongo, Marcos, 2016. "Supporting policy decision makers in the establishment of forest plantations, using SWOT analysis and AHPs analysis. A case study in Tocantins (Brazil)," Land Use Policy, Elsevier, vol. 54(C), pages 549-558.
    8. Javier Puente & Isabel Fernandez & Alberto Gomez & Paolo Priore, 2020. "Integrating Sustainability in the Quality Assessment of EHEA Institutions: A Hybrid FDEMATEL-ANP-FIS Model," Sustainability, MDPI, vol. 12(5), pages 1-22, February.
    9. Aguilar-Rivera, Noé, 2019. "A framework for the analysis of socioeconomic and geographic sugarcane agro industry sustainability," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 149-160.
    10. Abunawas Tjaija & Muhammad Nur Ali & Fadhliah & Effendy, 2022. "Development Strategy of Palu Bay Marine of Sustainable Tourism with the A'WOT Hybrid Method," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 11, January.
    11. Ernest Baba Ali & Ephraim Bonah Agyekum & Parise Adadi, 2021. "Agriculture for Sustainable Development: A SWOT-AHP Assessment of Ghana’s Planting for Food and Jobs Initiative," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    12. Rengarajan, Srinath & Moser, Roger & Narayanamurthy, Gopalakrishnan, 2021. "Strategy tools in dynamic environments – An expert-panel study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    13. Beiderbeck, Daniel & Frevel, Nicolas & von der Gracht, Heiko A. & Schmidt, Sascha L. & Schweitzer, Vera M., 2021. "The impact of COVID-19 on the European football ecosystem – A Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    14. Çağlar Kıvanç Kaymaz & Salih Birinci & Yusuf Kızılkan, 2022. "Sustainable development goals assessment of Erzurum province with SWOT-AHP analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 2986-3012, March.
    15. Tiberius, Victor & Gojowy, Robin & Dabić, Marina, 2022. "Forecasting the future of robo advisory: A three-stage Delphi study on economic, technological, and societal implications," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    16. Nermin Kişi, 2019. "A Strategic Approach to Sustainable Tourism Development Using the A’WOT Hybrid Method: A Case Study of Zonguldak, Turkey," Sustainability, MDPI, vol. 11(4), pages 1-19, February.
    17. Tahseen, Samiha & Karney, Bryan, 2017. "Opportunities for increased hydropower diversion at Niagara: An sSWOT analysis," Renewable Energy, Elsevier, vol. 101(C), pages 757-770.
    18. Liliane Moreira Nery & Darllan Collins Silva & Débora Zumkeller Sabonaro, 2024. "Agriculture technology transfer: A multicriteria analysis for decision making," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(6), pages 15515-15533, June.
    19. Guo, Jian & Luo, Cheng & Ma, Kaijiang, 2023. "Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    20. 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).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:14:y:2022:i:9:p:5154-:d:801367. 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.