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The use of e-health applications has remained popular during pandemic for medical treatments. Nevertheless, adoption of e-health applications among individuals is considerably low in post-COVID-19 world. To address this issue, the current research integrates three renowned theories, namely unified theory of acceptance and use of technology model, diffusion of innovation and DeLone and McLean model and investigates individual intention to adopt e-health application.

Research design is grounded in quantitative and cross-sectional methods and uses a survey questionnaire. Survey questionnaire is administered toward smartphone users. Overall, 238 valid responses were analyzed with structural equation modeling approach.

Results indicate that altogether performance expectancy, effort expectancy, information quality, system quality, service quality, facilitating condition and social influence explained substantial variance (R² = 76.5%) in user intention to adopt e-health applications. Similarly, effect size analysis has revealed substantial impact of social influence on user intention to adopt e-health applications. Geiser and Stone’s Q² analysis discloses that research model has substantial power to predict user intention to adopt e-health applications.

This study integrates three known information system models to investigate individual behavior toward adoption of e-health applications. In practice, it suggests that managers should pay attention in improving performance expectancy, social influence, facilitating condition, system quality, service quality and information quality which develop positive behavior and encourage smartphone users to adopt e-health applications.

This study is original as it integrates three models and investigates individual intention to adopt e-health applications. To the best of the author’s knowledge, this is the first study to test the moderating impact of patient health value between user intention to adopt and actual use of e-health applications. It has established that compatibility and innovativeness are essential antecedents of performance and effort expectancy and hence make this research more unique and valuable.

Today, e-government (electronic government) applications have extended to the frontiers of health-care delivery. E-Nabız contains personal health records of health services received, whether public or private. The use of the application by patients and physicians has provided efficiency and cost advantages. The success of e-Nabız depends on the level of technology acceptance of health-care service providers and recipients. While there is a large research literature on the technology acceptance of service recipients in health-care services, there is a limited number of studies on physicians providing services. This study aims to determine the level of influence of trust and privacy variables in addition to performance expectancy, effort expectancy, social influence and facilitating factors in the unified theory of acceptance and use of technology (UTAUT) model on the intention and behavior of using e-Nabız application.

The population of the study consisted of general practitioners and specialist physicians actively working in any health facility in Turkey. Data were collected cross-sectionally from 236 physicians on a voluntary basis through a questionnaire. The response rate of data collection was calculated as 47.20%. Data were collected cross-sectionally from 236 physicians through a questionnaire. Descriptive statistics, correlation analysis and structural equation modeling were used to analyze the data.

The study found that performance expectancy, effort expectancy, trust and perceived privacy had a significant effect on physicians’ behavioral intentions to adopt the e-Nabız system. In addition, facilitating conditions and behavioral intention were determinants of usage behavior (p < 0.05). However, no significant relationship was found between social influence and behavioral intention (p > 0.05).

This study confirms that the UTAUT model provides an appropriate framework for predicting factors influencing physicians’ behaviors and intention to use e-Nabız. In addition, the empirical findings show that trust and perceived privacy, which are additionally considered in the model, are also influential.

This paper aims to develop a digital transformation model in hospitals. This study proposes a digital transformation model in hospitals by formulating dimensions and sub-dimensions. The proposed hospital digital transformation model outlines why and how each of dimensions and sub-dimensions are important in the hospital digital transformation model.

This study chose the type of qualitative research using a phenomenology approach. This study used observation techniques and in-depth interviews with 11 informants and conducted group discussion forums with information technology governance experts, a hospital information technology department manager who has an information technology background, and doctor representatives. The data were documented and analyzed using triangulation techniques.

This research provides empirical insights into the dimensions and sub-dimensions of hospital digital transformation models. The findings of the digital transformation dimension in hospitals are 7 dimensions and 37 sub-dimensions, namely, the governance and management dimension which has 8 sub-dimensions; the person has 9 sub-dimensions; strategy dimension which has 5 sub-dimensions; information technology capability has 3 sub-dimensions; the data interoperability dimension has 3 sub-dimensions; the data analytics dimension has 5 sub-dimensions; patient dimensions have 4 sub-dimensions; the findings of the sub-dimensions involved in the digital transformation dimension of the hospital can provide input on the accuracy of the indicators measuring the hospital’s digital transformation.

This research is limited to the qualitative type of phenomenology approach so that future research can test empirically with quantitative methods with techniques through surveys of dimensional and sub-dimensional relationships to hospital digital transformation. The researchers also recommend further assessing the findings of this paper which can develop as a model for measuring the maturity of hospital digital transformation.

This paper covers the implications of developing a hospital digital transformation model that can be used to organize and manage hospital digital transformation.

This paper can be used as a guideline for hospital stakeholders when carrying out digital transformation. This paper can be used as a reference for further research to find, study and develop dimensions and sub-dimensions of digital transformation models.

Business models (BMs) are becoming increasingly crucial for value creation in the healthcare sector. The study explores the conceptualization and application of BM concepts within the healthcare sector and investigates their evolution in emerging economies (EEs) and developed economies (DEs). This study aims to uncover these two contexts' shared characteristics and unique variances through a comparative analysis.

The paper systematically investigates and consolidates the literature on healthcare by employing the antecedents, decisions and outcomes (ADO) framework and finally examines 71 shortlisted articles published between 2003 and 2022.

The recognition of the BM within healthcare is increasing, both in EEs and DEs. EEs prioritize value creation and capture through cost efficiency, while DEs focus on innovation. Key theories employed include a resource-based view, the network theory and the theory of innovation. Case studies are commonly used as a methodology. Further research is needed to explore the decisions and outcomes of BMs.

The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

Beyond comparing and highlighting gaps in BMs between EEs and DEs, benchmarking DE's healthcare business models (HBMs) helps healthcare organizations in EEs align their practices, mitigate risks and establish efficient healthcare systems tailored to their specific contexts. The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

The study analyzes HBMs using an SLR framework perspective and provides practical implications for academicians and practitioners to enhance their decision-making.

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study aims to establish a Greenness of Construction Technologies (GCT) evaluation model using the method of analytic network process (ANP).

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study establishes a GCT evaluation model using the method of ANP.

Among the four formwork technologies of plastic, steel, plywood and wooden formwork, the plastic formwork exhibits the best performance in terms of environmental friendliness, economic and social effects, while facing issues like material wastage and low static strength. The results align with practical observations which validates the model’s applicability.

This research contributes to the field by introducing the concept of greenness into construction technology evaluation for the first time. The establishment of the GCT evaluation model promotes the adoption of green construction technologies and advances sustainable practices in the construction industry.

Disasters and pandemics pose challenges to health-care provision. Accordingly, the need for adopting innovative approach is required in providing care to patient. Therefore, the purpose of this study is to present telehealth as an innovative approach for providing care to patients and reducing spread of the infection and advocates for the adoption of telehealth for digitalized treatment of patients.

An integrative review methodology of existing evidence was conducted to provide implications for integration of telehealth for digitalized treatment of patients. This paper draws on Technology Organization Environment (TOE) framework to develop a model and propositions to investigate the factors that influence telehealth adoption from the perspective of the supply side and the demand side of medical services.

Findings from this study discuss applications adopted for telehealth and recommendations on how telehealth can be adopted for medical-care delivery. More importantly, the findings and propositions of this study can act as a roadmap to potential research opportunities within and beyond the pandemic. In addition, findings from this study help provide guidelines on how health practitioners can rapidly integrate telehealth into practice for public health emergencies.

This study identifies the social, technological and organizational factors that influence telehealth adoption, and opportunities of adopting telehealth during the public health emergencies. This study concludes that specific policy changes to improve integration of interoperable solutions; data security; better physical infrastructures; broadband access; better transition and workflow balance; availability of funding and remuneration; regulations and reimbursement; awareness; and training will improve telehealth adoption during public health emergencies.

Patient safety is a top priority globally. A robust healthcare system requires strategic collaboration between research and development. The author analysed over 300 cases from seven hospitals using the failure modes, effects, and criticality analysis (FMECA) tool to understand the underlying causes of medical errors.

The author studied seven hospitals and 300 cases using FMECA to prioritise activities. The findings showed that high-priority events occurred less frequently but had the potential to cause the most harm. Team members evaluated independently to ensure unbiased evaluations. This approach is useful for setting priorities or assessing difficulties.

Poor communication and lack of coordination among staff in a healthcare organisation caused misunderstandings, ineffective decision-making, delays in patient care, and medical errors. Implementation of effective communication and coordination protocols can help avoid these problems.

The study recommends using FMECA to identify and prioritise failures and conducting in-depth analyses to understand their root causes. It also highlights the importance of interdisciplinary knowledge and soft skills for healthcare staff.

This study reveals the significance of FMECA in healthcare risk management and benchmarking. FMECA helps identify system failures, develop prevention strategies, and evaluate effectiveness against industry benchmarks. It offers healthcare professionals a valuable tool to enhance patient safety and improve healthcare quality.

This study delves into how perceived ease of use and perceived usefulness impacts consumer attitude and intention to adopt digital technologies in Ghana.

We utilized covariance-based structural equation modeling with a dataset consisting of 204 respondents to evaluate the model. The analysis was conducted using R (version 0.6–12).

The results confirm that both perceived ease of use and perceived usefulness are key predictors of the intention to adopt technology. Additionally, factors such as attitude, subjective norms and perceived behavioral control also play a significant role in influencing adoption intent. Notably, the research indicates that perceived ease of use not only impacts peer influence among consumers, but also shapes their confidence in effectively using the technology. Furthermore, in contrast to previous studies, this investigation suggests that while perceived behavioral control impacts behavioral intent, it does not predict attitude in the Ghanaian context. The study advocates for development of user-centric technologies, promotion of digital literacy and cultivation of a digital culture.

Our use of a single country data restricts generalizability of the study. For a more comprehensive and profound understanding, we recommend a broader study across multiple sub-Saharan African countries with a mixed method or qualitative approach.

The significance of this research lies in its original contribution to the field in providing crucial insights for governments and industry players. It sheds light on factors influencing user readiness to adopt technology and makes a substantial contribution to the ongoing discussion on digital technology adoption in literature.

The success of an Electronic Health Record (EHR) system is determined by the numerous facilitators and obstacles that influence physicians' intentions toward using these technologies. This study examines physicians' intentions to use EHR by applying the extended technology readiness and acceptance model (TRAM) factors, the result demonstrability, colleagues' opinions, perception of external control, and organizational support.

Convenience sampling was used to collect data from physicians in Egypt (n = 520). To evaluate the model's hypotheses, this study used the partial least squares structural equation modeling (PLS-SEM) method with WarpPLS.7.

The results revealed that positive TR factors (innovativeness and optimism) positively affect perceived usefulness and ease of use, while negative TR factors (discomfort and insecurity) negatively impact perceived usefulness and ease of use. Furthermore, the result demonstrability and colleagues' opinions positively influence perceived usefulness, while the perception of external control and organizational support positively influence perceived ease of use. In addition, significant relationships between perceived ease of use and usefulness and adoption intention were identified.

This is the first study to apply the TRAM to understand physicians' adoption intentions to use EHR systems. Moreover, this study determined the different roles of positive and negative TR affecting physicians' cognition regarding using EHR systems.

This study aims to present a comprehensive investigation into users’ behavioural intentions to use e-pharmacies through the lens of the privacy calculus model. The present study also investigates the effects of perceived benefit, perceived privacy risk, timeliness and perceived app quality on e-pharmacy usage through the mediating role of trustworthiness.

The study used a deductive approach and collected data from 338 respondents using the purposive sampling technique. partial least squares structural equation modelling was applied to analyse the data.

The findings of the study indicate that perceived benefit, perceived privacy risk, timeliness and perceived app quality do not directly impact users’ behavioural intentions towards e-pharmacy adoption. Instead, it demonstrated that perceived benefit, perceived privacy risk, timeliness and perceived app quality influenced behavioural intention indirectly through the mediating role of trustworthiness

This study offers valuable insights to entrepreneurs, marketers and policymakers, enabling them to develop regulations, guidelines and policies that cultivate trust, safeguard privacy, ensure prompt services and create an enabling environment for the adoption of e-pharmacies. The present study also contributes to the existing literature by extending the privacy calculus model with the integration of timeliness and perceived app quality to explain users’ adoption behaviour towards e-pharmacy.