IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v163y2021ics0040162520312439.html
   My bibliography  Save this article

Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective

Author

Listed:
  • Yu, Wantao
  • Zhao, Gen
  • Liu, Qi
  • Song, Yongtao

Abstract

Despite increasing research interest in big data analytics, exploring its important role in implementing supply chain management practices in healthcare organisations is still one of the major challenges for both academics and practitioners. We propose a research model theoretically grounded on organizational information processing theory (OIPT) to investigate the roles of big data analytics capability (BDAC) in developing hospital supply chain integration (SCI) and operational flexibility. The results from our analysis of survey data from a sample of 105 senior executives from the Chinese hospitals reveal that BDAC has a significant impact on three dimensions of hospital SCI: inter-functional integration, hospital-patient integration, and hospital-supplier integration; and that hospital-patient integration and hospital-supplier integration fully mediate the relationship between inter-functional integration and operational flexibility. These findings extend and validate OIPT within the context of big data-driven hospital supply chains, while also providing useful and timely guidance to healthcare practitioners in developing data-driven SCI for better operational flexibility, especially to respond to the unprecedented disruption caused by the COVID-19 outbreak.

Suggested Citation

  • Yu, Wantao & Zhao, Gen & Liu, Qi & Song, Yongtao, 2021. "Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    • Handle: RePEc:eee:tefoso:v:163:y:2021:i:c:s0040162520312439
    DOI: 10.1016/j.techfore.2020.120417
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162520312439
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2020.120417?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. He, Alex Jingwei & Qian, Jiwei, 2016. "Explaining medical disputes in Chinese public hospitals: the doctor–patient relationship and its implications for health policy reforms," Health Economics, Policy and Law, Cambridge University Press, vol. 11(4), pages 359-378, October.
    3. Ward, Michael J. & Marsolo, Keith A. & Froehle, Craig M., 2014. "Applications of business analytics in healthcare," Business Horizons, Elsevier, vol. 57(5), pages 571-582.
    4. Wang, Yichuan & Kung, LeeAnn & Byrd, Terry Anthony, 2018. "Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 3-13.
    5. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    6. Jay R. Galbraith, 1974. "Organization Design: An Information Processing View," Interfaces, INFORMS, vol. 4(3), pages 28-36, May.
    7. Ravi Srinivasan & Morgan Swink, 2018. "An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1849-1867, October.
    8. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    9. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
    10. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    11. Wang, Yichuan & Hajli, Nick, 2017. "Exploring the path to big data analytics success in healthcare," Journal of Business Research, Elsevier, vol. 70(C), pages 287-299.
    12. Yu, Wantao & Jacobs, Mark A. & Salisbury, W. David & Enns, Harvey, 2013. "The effects of supply chain integration on customer satisfaction and financial performance: An organizational learning perspective," International Journal of Production Economics, Elsevier, vol. 146(1), pages 346-358.
    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. Yu, Wantao & Wong, Chee Yew & Chavez, Roberto & Jacobs, Mark A., 2021. "Integrating big data analytics into supply chain finance: The roles of information processing and data-driven culture," International Journal of Production Economics, Elsevier, vol. 236(C).
    2. El Baz, Jamal & Ruel, Salomée, 2021. "Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era," International Journal of Production Economics, Elsevier, vol. 233(C).
    3. Li, Huanli & Wu, Yun & Cao, Dongmei & Wang, Yichuan, 2021. "Organizational mindfulness towards digital transformation as a prerequisite of information processing capability to achieve market agility," Journal of Business Research, Elsevier, vol. 122(C), pages 700-712.
    4. Benzidia, Smail & Makaoui, Naouel & Bentahar, Omar, 2021. "The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    5. Li Cui & Hao Wu & Lin Wu & Ajay Kumar & Kim Hua Tan, 2023. "Investigating the relationship between digital technologies, supply chain integration and firm resilience in the context of COVID-19," Annals of Operations Research, Springer, vol. 327(2), pages 825-853, August.
    6. Korayim, Diana & Chotia, Varun & Jain, Girish & Hassan, Sharfa & Paolone, Francesco, 2024. "How big data analytics can create competitive advantage in high-stake decision forecasting? The mediating role of organizational innovation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    7. Jingsi Zhang & Liangqun Qi, 2021. "Crisis Preparedness of Healthcare Manufacturing Firms during the COVID-19 Outbreak: Digitalization and Servitization," IJERPH, MDPI, vol. 18(10), pages 1-23, May.
    8. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    9. Papanagnou, Christos & Seiler, Andreas & Spanaki, Konstantina & Papadopoulos, Thanos & Bourlakis, Michael, 2022. "Data-driven digital transformation for emergency situations: The case of the UK retail sector," International Journal of Production Economics, Elsevier, vol. 250(C).
    10. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    11. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Gary Graham & Mihalis Giannakis & Deepa Bhatt Mishra, 2022. "Agility in humanitarian supply chain: an organizational information processing perspective and relational view," Annals of Operations Research, Springer, vol. 319(1), pages 559-579, December.
    12. Basile, L.J. & Carbonara, N. & Panniello, U. & Pellegrino, R., 2024. "The role of big data analytics in improving the quality of healthcare services in the Italian context: The mediating role of risk management," Technovation, Elsevier, vol. 133(C).
    13. Sundarakani, Balan & Ajaykumar, Aneesh & Gunasekaran, Angappa, 2021. "Big data driven supply chain design and applications for blockchain: An action research using case study approach," Omega, Elsevier, vol. 102(C).
    14. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    15. 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.
    16. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    17. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
    18. Nan Wang & Baolian Chen & Liya Wang & Zhenzhong Ma & Shan Pan, 2024. "Big data analytics capability and social innovation: the mediating role of knowledge exploration and exploitation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    19. Kalaitzi, Dimitra & Tsolakis, Naoum, 2022. "Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage," International Journal of Production Economics, Elsevier, vol. 248(C).
    20. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.

    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:eee:tefoso:v:163:y:2021:i:c:s0040162520312439. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.