Modeling Key Readiness Factors of Hospitals for E-procurement System Using Fuzzy Cognitive Map (Case Study: A Specialty Hospital in Tehran) - Alireza Ahmadnezhad; Mohamad Sadegh Sangari; Ali Bozorgi-Amiri (Tehran University of Medical Sciences, 2018)
Background and Aim: Nowadays, e-procurement systems have provided many opportunities to improve supply and procurement activities in healthcare industry through Internet-based electronic communications for supplier-buyer interactions. Considering the fact that the implementation of these systems is not successful in many cases, extensive preparation in relevant areas is necessary before implementation. This paper aims to present a framework of key readiness factors of hospitals for the adoption of e-procurement system. Materials and Methods: This study was an applied descriptive survey. The framework of readiness factors was developed based on an extensive review of literature and e-readiness models as well as opinions of experts in the field of information technology, procurement, and healthcare systems. The proposed framework was applied in a case study of a specialty hospital located in Tehran in 2016. The data were collected using a questionnaire, and Fuzzy Cognitive Map (FCM) method was used for modeling and analysis of the identified factors. Results: In this research, a comprehensive framework of critical readiness factors of hospitals for e-procurement adoption was developed comprising five main components: management, technology, process, human resource, and environment. Environmental and managerial factors were identified as the most important readiness determinants of the case hospital, and among various factors, managerschr('39') expertise in IT, IT infrastructures of hospital, and continuous monitoring of systemchr('39')s performance are of higher priority. Conclusion: This paper provides guidance for more accurate planning to improve readiness and successful adoption of e-procurement systems in hospitals by identifying the most important influential readiness factors.