A model to improve user acceptance of e-services in healthcare systems based on technology acceptance model: an empirical study

Nazari-Shirkouhi, Salman; Badizadeh, Ali; Dashtpeyma, Mosayeb; Ghodsi, Reza

doi:10.1007/s12652-023-04601-0

Cited by 5 publications

(2 citation statements)

References 63 publications

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“…Reliability was evaluated through composite reliability and Cronbach's alpha coefficient. Values above 0.7 for each construct demonstrate satisfactory reliability [93]. Table 2 displays the factor loadings, composite reliability, and AVE of the variables, indicating robust validity and reliability across the constructs.…”

Section: Resultsmentioning

confidence: 87%

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Lean, Agile, Resilient, Green, and Sustainable (LARGS) Supplier Selection Using Multi-Criteria Structural Equation Modeling under Fuzzy Environments

Ghazvinian,

Feng,

Feng

et al. 2024

Sustainability

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This study aims to propose an integrated approach for supplier selection based on the lean, agile, resilience, green, and sustainable (LARGS) paradigm. This approach was validated using structural equation modelling (SEM) and the intuitionistic fuzzy TOPSIS method. A comprehensive literature review was conducted, identifying twenty-six criteria, which were then consolidated into five main criteria. A questionnaire was distributed to 237 individuals from manufacturing companies listed on the Tehran Stock Exchange, and the collected data were analyzed using third-order factor analysis and the partial least squares method. Subsequently, the proposed integrated approach was applied to evaluate four suppliers in an intuitionistic fuzzy environment, utilizing expert opinions and a case study on the automotive industry. The results demonstrate the effectiveness and practicality of the proposed approach in terms of prioritizing and selecting suitable suppliers according to LARGS criteria. In conclusion, this study contributes to the existing literature by proposing an integrated approach that addresses the decision-making challenges in supplier selection. This approach offers a practical tool for managers seeking to enhance sustainable supply chain performance from the LARGS perspective.

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Section: Resultsmentioning

confidence: 87%

“…To delve into the validation process, we assessed construct validity by examining the factor loadings in the confirmatory factor analysis. A factor loading exceeding 0.6 for each indicator with its construct indicates that each item adequately represents said construct [92,93]. The factor loadings are presented in Table 2.…”

Section: Resultsmentioning

confidence: 99%

Lean, Agile, Resilient, Green, and Sustainable (LARGS) Supplier Selection Using Multi-Criteria Structural Equation Modeling under Fuzzy Environments

Ghazvinian,

Feng,

Feng

et al. 2024

Sustainability

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Perceptions and attitudes of nurse practitioners toward artificial intelligence adoption in health care

Rony,

Numan,

Johra

et al. 2024

Health Science Reports

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BackgroundWith the ever‐increasing integration of artificial intelligence (AI) into health care, it becomes imperative to gain an in‐depth understanding of how health care professionals, specifically nurse practitioners, perceive and approach this transformative technology.ObjectivesThis study aimed to gain insights into nurse practitioners' perceptions and attitudes toward AI adoption in health care.MethodsThis qualitative research employed a descriptive and phenomenological approach using in‐depth interviews. Data were collected through a semi‐structured questionnaire with 37 nurse practitioners selected through purposive sampling, specifically Maximum Variation Sampling and Expert Sampling techniques, to ensure diversity in characteristics. Trustworthiness of the research was maintained through member checking and peer debriefing. Thematic analysis was employed to uncover recurring themes and patterns in the data.ResultsThe thematic analysis revealed nine main themes that encapsulated nurse practitioners' perceptions and attitudes toward AI adoption in health care. These included nurse practitioners' perceptions of AI implementation, attitudes toward AI adoption, patient‐centered care and AI, quality of health care delivery and AI, ethical and regulatory aspects of AI, education and training needs, collaboration and interdisciplinary relationships, obstacles in integrating AI, and AI and health care policy. While this study found that nurse practitioners held a wide range of perspectives, with many viewings AI as a tool to enhance patient care.ConclusionsThis research provides a valuable contribution to the evolving discourse surrounding AI adoption in health care. The findings underscore the necessity for comprehensive education and training in AI, accompanied by clear and robust ethical and regulatory guidelines to ensure the responsible integration of AI in health care practice. Furthermore, fostering collaboration and interdisciplinary relationships is pivotal for the successful incorporation of AI in health care. Policymakers should also address the challenges and opportunities that AI presents in the health care sector. This study enhances the ongoing conversation on AI adoption in health care by shedding light on the perspectives of nurses, thereby shaping future strategies for AI integration.

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The issue of interconnections and mutual influence of digital transformation in international trade: How digitization affects customer satisfaction?

Wang

2024

Heliyon

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A model to improve user acceptance of e-services in healthcare systems based on technology acceptance model: an empirical study

Cited by 5 publications

References 63 publications

Lean, Agile, Resilient, Green, and Sustainable (LARGS) Supplier Selection Using Multi-Criteria Structural Equation Modeling under Fuzzy Environments

Lean, Agile, Resilient, Green, and Sustainable (LARGS) Supplier Selection Using Multi-Criteria Structural Equation Modeling under Fuzzy Environments

Perceptions and attitudes of nurse practitioners toward artificial intelligence adoption in health care

The issue of interconnections and mutual influence of digital transformation in international trade: How digitization affects customer satisfaction?

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