Table 1.
CSFs of AI adoption in HSC.
| Major CSF | Sub-CSF | Description | References |
|---|---|---|---|
| Technological (TEC) | Technology sophistication (TEC1) | It refers to the maturity and diversity of technological hardware and software for addressing issues of latency, security, and throughput | Agrawal et al., 2018, Hoy, 2017, Büyüközkan and Göçer, 2019, Alrahbi et al., 2021 |
| Perceived benefits (TEC2) | It stipulates the anticipated advantages and positive impact accruing from technology adoption | Alrahbi et al., 2021, Dwivedi et al., 2019a, Sun et al., 2020, Yadegaridehkordi et al., 2018 | |
| Sustainable data quality and integrity (TEC3) | Data quality refers to usability in terms of determining the reliability of data, while data integrity refers to the trustworthiness of data in terms of its physical and logical validity | Li et al. (2020), Zhang et al. (2018b); Damoah et al., 2021 | |
| Technological testing and troubleshooting feasibility (TEC4) | It indicates the diverse and well-defined testing activities in terms of validation models, techniques, and tools to identify and overcome errors in software and achieve test requirements | Aboelmaged, 2014, Sun et al., 2020, Gardas, 2022 | |
| Interoperability (TEC5) | Data interoperability refers to the processing and interpretation of received data to facilitate smooth communication between different stakeholders | Wang et al., 2019, Dobrovnik et al., 2018, Orji et al., 2020 | |
| Organizational (ORG) | Organizational leadership and support (ORG1) | It draws an association to the dynamic leadership and support being extended by top management and managers towards the entire process, from commencement to full technology adoption | Gutierrez at al. (2015), Szalavetz, 2019, Singh et al., 2019, Alrahbi et al., 2021, Gardas, 2022 |
| Strategic alignment between business viability and AI adoption (ORG2) | It refers to creating an alignment between business goals, the viability of business, and technology adoption to have better management of risks and opportunities in business | Nguyen et al., 2015, Tallon et al., 2019, Gardas, 2022 | |
| Organizational readiness (ORG3) | It directs to the receptive attitude and preparedness of the business for AI adoption | Yang et al., 2015, Pacchini et al., 2019, Magistretti et al., 2020, Khanijahani et al., 2022 | |
| Firm size and organization structure (ORG4) | It refers to the size and organizational structure of the firm as a reflection of its ability to invest, mobilize human and financial resources and absorb risks while adopting the new business model | Janssen et al., 2020, Mathauer and Hofmann, 2019, Sun et al., 2020, Khanijahani et al., 2022 | |
| Competitive advantage (ORG5) | It pertains to technology adoption due to the existing competitive advantage achieved by firms | Chu et al. (2018); Saberi et al. (2019a), Pan et al., 2020, Beaulieu and Bentahar, 2021 | |
| Organizational culture (ORG6) | It refers to the pattern of shared values and beliefs that provide an understanding of organizational functioning and the norms for acceptable behavior witorganizationnisation | Ghadge et al., 2020, Xia et al., 2019, Khanijahani et al., 2022 | |
| Financial Resources (ORG7) | It refers to the availability of adequate finances to undertake technological adoption | Kiel et al., 2017, Kusi-Sarpong et al., 2019, Gardas, 2022 | |
| Institutional (INT) | Government support and policy framework (INT1) | It indicates government support in terms of credit availability, staff training, technical advice, support infrastructure, and conducive policy framework | Yadav et al., 2020, Tsai et al., 2019, Singh et al., 2019, Alrahbi et al., 2021 |
| Ecosystem management (INT2) | It lays down the approach toward complex interaction and integration amongst several domains and participants | Wong et al., 2020, Santoro et al., 2018, Clohessy and Acton, 2019 | |
| Effective collaboration with partners and stakeholders (INT3) | It ascribes effective collaboration with internal and external stakeholders | Kamble et al., 2019, Luthra et al., 2020; Balasubramanian et a., 2021 | |
| Competitive pressure (INT4) | It refers to the promptness towards adoption of technological innovation arising out of the pressure due to intense rivalry between industry players | Chu et al., 2018, Chang, 2020, Alrahbi et al., 2021 | |
| Demand volatility for health care supply chain sector (INT5) | It engulfs the various factors that impart volatility in demand for the healthcare supply chain | Polater and Demirdogen, 2018, Lawrence et al., 2020 | |
| Human (HUM) | User desirability at the implementation stage (HUM1) | It directs attention to the user's intention and desirability to adopt a new technology | Naszay et al., 2018, Cocosila and Turel, 2019, Roberts et al., 2019, Balasubramanian et al., 2021 |
| Customer acceptance and loyalty (HUM2) | For adoption to be successful, this dimension highlights customer acceptance in terms of continued use (post-adoption) and loyalty towards technology adoption. | Mathauer and Hofmann, 2019, Nysveen et al., 2020 | |
| Human resource team competence and training for AI integration (HUM3) | It refers to the availability of human capital with expertise in technical matters and technology management. It would also take into account the training facilities and opportunities being extended to existing team members | Tortorella et al., 2020, Sivathanu and Pillai, 2018, Gardas, 2022 | |
| Behavioral Intention (HUM4) | It refers to the formulation of conscious plans toward a specified future behavior | Holzmann et al., 2020, Sharma, 2019, Chopdar et al., 2018 | |
| Assurance of job security post-AI adoption (HUM5) | It directs attention to the technological unemployment and security of work as an outcome of AI adoption | Kamble et al. (2019b), Nam, 2019, Wang et al., 2019; |