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Investigating the barriers towards adoption and implementation of open innovation in healthcare

Author

Listed:
  • Kumari, Pooja
  • Shankar, Amit
  • Behl, Abhishek
  • Pereira, Vijay
  • Yahiaoui, Dorra
  • Laker, Benjamin
  • Gupta, Brij B.
  • Arya, Varsha

Abstract

Open innovation, characterized by collaborative approaches and knowledge-sharing across organizational boundaries, holds great promise for transforming healthcare practices. However, the complexities of the healthcare landscape introduce unique challenges that impede the widespread adoption of open innovation initiatives and warrant an enquiry into barriers associated with one of the open innovation initiatives, i.e. digital clinic. Hence, this study investigates medical professionals' resistance towards digital clinics in emerging markets. Using innovation resistance theory (IRT) as underpinning theory, the study investigates the effects of performance barriers, value barriers, risk barriers, legal barriers, tradition barriers, and image barriers. This study also examined how the effects of barriers on inertia vary at different levels of medical professionals' personal innovativeness. The structural equation modelling and Process Macro are used to analyze the collected data. The findings indicate that value barriers, risk barriers, legal barriers, and tradition barriers play crucial roles in framing resistance intention towards digital clinics. The study uniquely enriches the emerging literature related to digital clinics by investigating the role of different barriers and inertia in digital clinic adoption. The study helps hospitals understand different barriers towards digital clinic adoption intention.

Suggested Citation

  • Kumari, Pooja & Shankar, Amit & Behl, Abhishek & Pereira, Vijay & Yahiaoui, Dorra & Laker, Benjamin & Gupta, Brij B. & Arya, Varsha, 2024. "Investigating the barriers towards adoption and implementation of open innovation in healthcare," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523007850
    DOI: 10.1016/j.techfore.2023.123100
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