IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i13p5474-d381384.html
   My bibliography  Save this article

The Effect of Quality Management and Big Data Management on Customer Satisfaction in Korea’s Public Sector

Author

Listed:
  • Gye-Soo Kim

    (Business Department, Semyung University, Jecheon 27136, Korea)

Abstract

Data-driven decision making is needed in uncertain situations. Total quality management is the source of quality management activities and customer satisfaction. This study is related to the investigation into the application of total quality management based on big data management on the public sector in Korea. We developed a research model for total quality management, and investigated the role of moderating big data management between total quality management leadership and quality management. Moreover, this study has examined the relationships between the practices of the total quality management and using big data, including customer needs and wants. The research model is developed and tested to fit it is with the SEM (Structural Equation Model) analysis using data 250 samples in Korea’s public sector. The survey was conducted between 1 August and 30 August 2019. The results are as follow: Total quality leadership has significantly impacted total quality management. Customer satisfaction was found to be significantly affected by total quality management activities. In addition, the level of big data management has the moderation effect between total quality leadership and total quality management in Korea public sectors. It is necessary to systematically manage data management in a situation where the demand for improvement of public service is gradually increasing online in public sector.

Suggested Citation

  • Gye-Soo Kim, 2020. "The Effect of Quality Management and Big Data Management on Customer Satisfaction in Korea’s Public Sector," Sustainability, MDPI, vol. 12(13), pages 1-13, July.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:13:p:5474-:d:381384
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/13/5474/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/13/5474/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Frank, Alejandro G. & Mendes, Glauco H.S. & Ayala, Néstor F. & Ghezzi, Antonio, 2019. "Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 341-351.
    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. Yi-Yuan Liu & Shun-Hsing Chen & Jia-Xuan Zhang, 2021. "Applying Importance–Satisfaction Model to Evaluate Customer Satisfaction: An Empirical Study of Foodpanda," Sustainability, MDPI, vol. 13(19), pages 1-18, October.
    2. Boyao Zhang & Ubaldo Comite & Ali Gokhan Yucel & Xintao Liu & Mohammed Arshad Khan & Shahid Husain & Muhammad Safdar Sial & József Popp & Judit Oláh, 2021. "Unleashing the Importance of TQM and Knowledge Management for Organizational Sustainability in the Age of Circular Economy," Sustainability, MDPI, vol. 13(20), pages 1-18, October.
    3. Aawag Mohsen Alawag & Wesam Salah Alaloul & M. S. Liew & Abdullah O. Baarimah & Muhammad Ali Musarat & Al-Baraa Abdulrahman Al-Mekhlafi, 2023. "The Role of the Total-Quality-Management (TQM) Drivers in Overcoming the Challenges of Implementing TQM in Industrialized-Building-System (IBS) Projects in Malaysia: Experts’ Perspectives," Sustainability, MDPI, vol. 15(8), pages 1-21, April.

    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. Alkaraan, Fadi & Elmarzouky, Mahmoud & Hussainey, Khaled & Venkatesh, V.G., 2023. "Sustainable strategic investment decision-making practices in UK companies: The influence of governance mechanisms on synergy between industry 4.0 and circular economy," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    2. Paolo E. Giordani & Francesco Rullani, 2020. "The Digital Revolution and COVID-19," Working Papers 06, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    3. Hua Zhang & Qiwang Zhang, 2023. "How Does Digital Transformation Facilitate Enterprise Total Factor Productivity? The Multiple Mediators of Supplier Concentration and Customer Concentration," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    4. Tortorella, Guilherme Luz & Narayanamurthy, Gopalakrishnan & Thurer, Matthias, 2021. "Identifying pathways to a high-performing lean automation implementation: An empirical study in the manufacturing industry," International Journal of Production Economics, Elsevier, vol. 231(C).
    5. Morteza Ghobakhloo & Mohammad Iranmanesh & Andrius Grybauskas & Mantas Vilkas & Monika Petraitė, 2021. "Industry 4.0, innovation, and sustainable development: A systematic review and a roadmap to sustainable innovation," Business Strategy and the Environment, Wiley Blackwell, vol. 30(8), pages 4237-4257, December.
    6. Ancillai, Chiara & Sabatini, Andrea & Gatti, Marco & Perna, Andrea, 2023. "Digital technology and business model innovation: A systematic literature review and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    7. Jinkyo Shin & Md Alamgir Mollah & Jaehyeok Choi, 2023. "Sustainability and Organizational Performance in South Korea: The Effect of Digital Leadership on Digital Culture and Employees’ Digital Capabilities," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    8. Kohtamäki, Marko & Parida, Vinit & Patel, Pankaj C. & Gebauer, Heiko, 2020. "The relationship between digitalization and servitization: The role of servitization in capturing the financial potential of digitalization," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    9. Laudien, Sven M. & Reuter, Ute & Sendra Garcia, Francisco Javier & Botella-Carrubi, Dolores, 2024. "Digital advancement and its effect on business model design: Qualitative-empirical insights," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    10. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    11. Rongrong Zhou & Decai Tang & Dan Da & Wenya Chen & Lin Kong & Valentina Boamah, 2022. "Research on China’s Manufacturing Industry Moving towards the Middle and High-End of the GVC Driven by Digital Economy," Sustainability, MDPI, vol. 14(13), pages 1-30, June.
    12. Yuan, Sai & Zhou, Ran & Li, Mengna & Lv, Chengchao, 2023. "Investigating the influence of digital technology application on employee compensation," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    13. Zhihua Lai & Bifeng Wang & Xiang He, 2023. "Research on the Digital Transformation of Producer Services to Drive Manufacturing Technology Innovation," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    14. Hannah Bensussan, 2023. "Understanding the paradox of control and freedom of consumption under digital capitalism with Stafford Beer's cybernetic theory," Working Papers hal-04050331, HAL.
    15. Shen, Lei & Sun, Wanqin & Parida, Vinit, 2023. "Consolidating digital servitization research: A systematic review, integrative framework, and future research directions," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    16. Yüksel, Hilmi, 2020. "An empirical evaluation of industry 4.0 applications of companies in Turkey: The case of a developing country," Technology in Society, Elsevier, vol. 63(C).
    17. Guilherme F. Frederico, 2021. "From Supply Chain 4.0 to Supply Chain 5.0: Findings from a Systematic Literature Review and Research Directions," Logistics, MDPI, vol. 5(3), pages 1-21, July.
    18. Wu, Chih-Wen & Botella-Carrubi, Dolores & Blanco-González-Tejero, Cristina, 2024. "The empirical study of digital marketing strategy and performance in small and medium-sized enterprises (SMEs)," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    19. Bustinza, Oscar F. & Opazo-Basaez, Marco & Tarba, Shlomo, 2022. "Exploring the interplay between Smart Manufacturing and KIBS firms in configuring product-service innovation performance," Technovation, Elsevier, vol. 118(C).
    20. Gupta, Shivam & Justy, Théo & Kamboj, Shampy & Kumar, Ajay & Kristoffersen, Eivind, 2021. "Big data and firm marketing performance: Findings from knowledge-based view," Technological Forecasting and Social Change, Elsevier, vol. 171(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:12:y:2020:i:13:p:5474-:d:381384. 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.