| Kong et al. (14) | 2021 | Examining the acceptance of AI in e-commerce in the healthcare industry | Questionnaire and TOE framework | Data transparency, cost pressure, relative benefits, laws, and regulations | The effectiveness of the identified factors in the TOE framework was confirmed. |
| Bedoya Reina et al. (15) | 2021 | A review of haven healthcare center’s disruption of the US healthcare system | A review of measures taken in haven | Identifying strategies for reducing healthcare costs and promoting patient satisfaction in the US | They confirmed Amazon Inc.’s specialty and capability in e-commerce, e.g., logistics, supply, and large-scale data management, supporting haven's efforts to resolve healthcare inefficiencies. |
| Fedushko et al. (16) | 2021 | A review of e-commerce, eHealth strategies, and administrative activities in the UK | A review of e-commerce measures in the UK | Identifying secondary specialties such as blockchain, IT health, virtual and augmented reality, sensors, personal genomics, telemedicine, big data, eHealth, mobile health, electronic medical/health records, AI, and machine learning | Presenting governmental and private sector investment levels in the UK healthcare domain and mentioning the 93.89 billion USD market of e-commerce, and in the UK, e-commerce constituted 30% of the country’s economy. E-commerce also had a 6.1% share of the gross domestic product (GDP) of the UK. |
| Shahzad et al. (4) | 2020 | Examining the effect of COVID-19 on the use of e-commerce in the Malaysian healthcare industry | The TOE framework and a questionnaire | Organizational preparedness; having e-commerce knowledge; supply chain integration; technological infrastructure; External pressure | Organizational preparedness, knowledge of e-commerce, and supply chain integration have significant positive effects. On the other hand, IT infrastructure and external pressure have negligible effects on the use of e-commerce. |
| Rajak and Shaw (17) | 2019 | Evaluation and selection of mHealth apps | AHP and fuzzy TOPSIS techniques | User satisfaction; performance; ease of use and learning; quality of information | “User satisfaction”, “performance”, “ease of use and learning”, and “quality of information” were the most critical factors in the evaluation and selection of mHealth apps. |
| Nilashi et al. (18) | 2016 | Identifying the factors affecting or hindering the acceptance of HIS in Malaysia | AHP technique | Environmental; human-related; organizational; technological | Technological factor (weight: 0.467) was identified as the most crucial factor in accepting HIS. This factor was followed by environmental (0.277), organizational (0.160), and human-related (0.095) factors, respectively, as the major factors in HIS acceptance, according to experts. |
| Chao et al. (19) | 2014 | Proposing a B2B evaluation management model to assess the organizational factors in hospitals and identify the relationships between B2B benefits | Mixed methods: qualitative (content analysis) and quantitative (questionnaire) | IT maturity; IT investment evaluation methods; IT evaluation resource allocation; user information needs an assessment process; B2B benefits | IT maturity positively and significantly affected the acceptance of IT investment evaluation methods, and the precise and complete user information need assessment positively and significantly affected IT evaluation and resource allocation. These factors, in turn, markedly and positively affected the realization of B2B benefits. The results also revealed that the IT maturity level relatively affects hospitals’ ability to allocate IT evaluation resources. |
| Lin et al. (20) | 2011 | Compatibility between organizational B2B policy, IT maturity, and evaluation methods on B2B performance in Australian healthcare organizations | Qualitative content analysis | Organizational B2B strategy and policy; organizational IT maturity; IEM; BRM; B2B benefits; B2B satisfaction | There is a positive relationship between organizational B2B strategy and policy, organizational IT maturity, effective use of IEM and BRM, B2B benefits, and satisfaction level |
| Peikari and Rezazadeh (21) | 2021 | Determining the relationship between professional errors and UTAUT factors for using the electronic prescription system of the Social Security Organization by pharmacists in Isfahan (Iran) via the UTAUT model | Descriptive-correlational | Expect effort; reduction of professional errors; pharmacists’ expected performance; facilitators; social factors; Intention to accept technology | The expected effort and a reduction in professional errors affected the expected performance of pharmacists (P < 0.001). The expected performance, effort, facilitators, and social factors significantly shaped the intention to accept (P < 0.001). The intention to accept and facilitators significantly influenced the acceptance of the system (P < 0.001). |
| Motallebzadeh et al. (8) | 2019 | Evaluating the influence of factors affecting the acceptance of electronic health services from the viewpoints of social security insurance employees | Descriptive-correlational | Systemic factors; perceived benefit; perceived simplicity; attitude toward the application; the behavioral decision for use | Significant relationships existed between systemic factors and perceived benefits; systemic factors and perceived simplicity; perceived simplicity and perceived benefit; perceived benefit and attitude towards the application; perceived simplicity and attitude towards the application; perceived benefit and behavioral decision for use; and attitude towards the application and behavioral decision for use |
| | | | | |