Despite the extensive adoption of radio-frequency identification (RFID) technology across many industry supply chains, the extent of adoption in healthcare is far behind the earlier expectation. The purpose of this study is to better understand the current RFID adoption in healthcare by looking beyond the existing body of work using both the task-technology fit (TTF) framework and network externalities theories.
A survey is employed in this study, and the structural equation modeling (SEM) technique is used to test the hypotheses of the proposed model.
The findings are twofold. First, both TTF and network externalities exert a positive impact on the RFID adoption in the healthcare sector; and second, no synergistic effect can be found between these two for further increasing the adoption. This is different from what the extant research found on other technology adoptions across various supply chains.
This paper provides contributions to both researchers and practitioners. For researchers, this study enriches the body of knowledge of RFID adoption by being the first to apply the network externalities and TTF theories to predict the adoption of RFID in healthcare. For healthcare practitioners, to make the RFID adoption easier and more effective, any initial applications of RFID tools should be centered on those for which there is a more natural application. Further, for those who propose an RFID adoption should start with a product that has a sizable adoption community; this may help persuade senior management to make the adoption decision.
Gu, V. and Black, K. (2020), "Integration of TTF and network externalities for RFID adoption in healthcare industry", International Journal of Productivity and Performance Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJPPM-11-2018-0418Download as .RIS
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