IDEAS home Printed from https://ideas.repec.org/a/eee/techno/v120y2023ics016649722100225x.html
   My bibliography  Save this article

Technology management maturity assessment model in healthcare research centers

Author

Listed:
  • Shaygan, Amir
  • Daim, Tugrul

Abstract

In the context of continuous learning in healthcare organizations, a mature system can be defined as a system that generates timely actions to the information that it derives from internal and external data to create meaningful measurement regarding system learning and increased efficacy and effectiveness in health outcomes. However, there is a lack of a model that provides managers and decision-makers with a systematic, multi-criteria, validated, quantifiable, and repeatable maturity model to assess and enhance health organizations' performance in continuous learning and technology management. This research proposes a multi-criteria model to assess technology management maturity and continuous learning in research centers within university hospitals by using Hierarchical Decision Model (HDM), validated and quantified by panels of healthcare subject matter experts. The model can help research centers with pinpointing their strengths and opportunities in terms of continuous learning from the data they have access to while giving them organizational self-awareness and guide them in setting their strategies and resource allocation. The model will serve as a much-needed technology management tool for healthcare organizations to assess their technology management maturity and continuous learning efforts and assist them in creating more effective roadmaps.

Suggested Citation

  • Shaygan, Amir & Daim, Tugrul, 2023. "Technology management maturity assessment model in healthcare research centers," Technovation, Elsevier, vol. 120(C).
  • Handle: RePEc:eee:techno:v:120:y:2023:i:c:s016649722100225x
    DOI: 10.1016/j.technovation.2021.102444
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016649722100225X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.technovation.2021.102444?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. Carvalho, João Vidal & Rocha, Álvaro & van de Wetering, Rogier & Abreu, António, 2019. "A Maturity model for hospital information systems," Journal of Business Research, Elsevier, vol. 94(C), pages 388-399.
    2. Brooks, Patti & El-Gayar, Omar & Sarnikar, Surendra, 2015. "A framework for developing a domain specific business intelligence maturity model: Application to healthcare," International Journal of Information Management, Elsevier, vol. 35(3), pages 337-345.
    3. Yan, Min & Filieri, Raffaele & Raguseo, Elisabetta & Gorton, Matthew, 2021. "Mobile apps for healthy living: Factors influencing continuance intention for health apps," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    4. Khodadad-Saryazdi, Ali, 2021. "Exploring the telemedicine implementation challenges through the process innovation approach: A case study research in the French healthcare sector," Technovation, Elsevier, vol. 107(C).
    5. Talukder, Md. Shamim & Sorwar, Golam & Bao, Yukun & Ahmed, Jashim Uddin & Palash, Md. Abu Saeed, 2020. "Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    6. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    7. Amir Shaygan, 2018. "Landscape Analysis: What Are the Forefronts of Change in the US Hospitals?," Innovation, Technology, and Knowledge Management, in: Tugrul U. Daim & Leong Chan & Judith Estep (ed.), Infrastructure and Technology Management, chapter 0, pages 213-243, Springer.
    8. Álvaro Rocha, 2011. "Evolution of Information Systems and Technologies Maturity in Healthcare," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 6(2), pages 28-36, April.
    9. Lee, Sang M. & Lee, DonHee, 2021. "Opportunities and challenges for contactless healthcare services in the post-COVID-19 Era," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    10. Lee, Sang Yup & Lee, Keeheon, 2018. "Factors that influence an individual's intention to adopt a wearable healthcare device: The case of a wearable fitness tracker," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 154-163.
    11. Abdel-Basset, Mohamed & Chang, Victor & Nabeeh, Nada A., 2021. "An intelligent framework using disruptive technologies for COVID-19 analysis," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    12. Carvalho, João Vidal & Rocha, Álvaro & Vasconcelos, José & Abreu, António, 2019. "A health data analytics maturity model for hospitals information systems," International Journal of Information Management, Elsevier, vol. 46(C), pages 278-285.
    13. Mike English & Grace Irimu & Ambrose Agweyu & David Gathara & Jacquie Oliwa & Philip Ayieko & Fred Were & Chris Paton & Sean Tunis & Christopher B Forrest, 2016. "Building Learning Health Systems to Accelerate Research and Improve Outcomes of Clinical Care in Low- and Middle-Income Countries," PLOS Medicine, Public Library of Science, vol. 13(4), pages 1-8, April.
    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. Salma Benchekroun & V. G. Venkatesh & Ilham Dkhissi & D. Jinil Persis & Arunmozhi Manimuthu & M. Suresh & V. Raja Sreedharan, 2023. "Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 424-447, January.
    2. Caselli, Mauro & Fracasso, Andrea & Traverso, Silvio, 2021. "Robots and risk of COVID-19 workplace contagion: Evidence from Italy," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    3. Olatunji A. Shobande & Lawrence Ogbeifun & Simplice A. Asongu, 2022. "Globalisation, technology and global health," Working Papers of the African Governance and Development Institute. 22/070, African Governance and Development Institute..
    4. Rubbio, Iacopo & Bruccoleri, Manfredi, 2023. "Unfolding the relationship between digital health and patient safety: The roles of absorptive capacity and healthcare resilience," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    5. Xiao Han & Menghan Zhang & Yixuan Hu & Yuan Huang, 2022. "Study on the Digital Transformation Capability of Cost Consultation Enterprises Based on Maturity Model," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    6. Baudier, Patricia & Kondrateva, Galina & Ammi, Chantal & Chang, Victor & Schiavone, Francesco, 2023. "Digital transformation of healthcare during the COVID-19 pandemic: Patients’ teleconsultation acceptance and trusting beliefs," Technovation, Elsevier, vol. 120(C).
    7. Talukder, Md. Shamim & Sorwar, Golam & Bao, Yukun & Ahmed, Jashim Uddin & Palash, Md. Abu Saeed, 2020. "Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    8. Basile, Luigi Jesus & Carbonara, Nunzia & Pellegrino, Roberta & Panniello, Umberto, 2023. "Business intelligence in the healthcare industry: The utilization of a data-driven approach to support clinical decision making," Technovation, Elsevier, vol. 120(C).
    9. Sami S. Binyamin & Md. Rakibul Hoque, 2020. "Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    10. Cannavacciuolo, Lorella & Capaldo, Guido & Ponsiglione, Cristina, 2023. "Digital innovation and organizational changes in the healthcare sector: Multiple case studies of telemedicine project implementation," Technovation, Elsevier, vol. 120(C).
    11. Chiang, Ai-Hsuan & Trimi, Silvana & Lo, Yu-Ju, 2022. "Emotion and service quality of anthropomorphic robots," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    12. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(C).
    13. Islam, A.K.M. Najmul & Laato, Samuli & Talukder, Shamim & Sutinen, Erkki, 2020. "Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive load perspective," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    14. Soon Goo Hong & DonHee Lee, 2023. "Development of a citizen participation public service innovation model based on smart governance," Service Business, Springer;Pan-Pacific Business Association, vol. 17(3), pages 669-694, September.
    15. Ayesha Amjad & Piotr Kordel & Gabriela Fernandes, 2023. "A Review on Innovation in Healthcare Sector (Telehealth) through Artificial Intelligence," Sustainability, MDPI, vol. 15(8), pages 1-24, April.
    16. Chiarello, Filippo & Fantoni, Gualtiero & Hogarth, Terence & Giordano, Vito & Baltina, Liga & Spada, Irene, 2021. "Towards ESCO 4.0 – Is the European classification of skills in line with Industry 4.0? A text mining approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Dang, Ngoc Bich & Bertrandias, Laurent, 2023. "Social robots as healing aids: How and why powerlessness influences the intention to adopt social robots," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    18. Ante, Lennart & Fiedler, Ingo & Strehle, Elias, 2021. "The impact of transparent money flows: Effects of stablecoin transfers on the returns and trading volume of Bitcoin," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    19. Caselli, Mauro & Fracasso, Andrea, 2021. "Covid-19 and Technology," GLO Discussion Paper Series 1001, Global Labor Organization (GLO).
    20. Madhavan, Naveen & White, Gareth R.T. & Jones, Paul, 2023. "Identifying the value of a clinical information system during the COVID-19 pandemic," Technovation, Elsevier, vol. 120(C).

    More about this item

    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:eee:techno:v:120:y:2023:i:c:s016649722100225x. 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/01664972 .

    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.