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The rising of chronic illness and the continuous aging of the global population requires a re-organization of health care systems based on relations and exchange of information to address patient needs in the community. The re-organization of health care systems involves interconnected changes and the development of integrated health care information systems and novel eHealth services. In Crete, the Foundation for Research and Technology-Hellas has developed HYGEIAnet, a Regional Health Information Network (RHIN) to contribute to the re-organization of health care systems and information sharing. We present HYGEIAnet, some of the most critical and novel eHealth services developed and deployed, discuss the impact of an RHIN on health care processes, and explore innovative models and services for health delivery and the coordination of care. We then critically discuss lessons learned regarding the effective management of change to overcome organizational and cultural issues in such large-scale initiatives. The paper concludes with policy and practice recommendations for managing change processes in health care organizations.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

This study aims to understand the factors affecting the continuance usage intention (CUI) of mHealth among the rural elderly.

An integrated model was proposed with the constructs derived from multiple models such as the unified theory of acceptance and use of technology, information system success model and expectation confirmation model. Data were collected from 400 participants who had prior experiences with mHealth services in Bangladesh. The research model was tested using the partial least squares method based upon structural equation modelling.

The findings indicated that system quality, performance expectancy, facilitating conditions and social influence were significant to the degree of confirmation and ultimately affect satisfaction and CUI. Surprisingly, service quality and information quality were insignificant.

This study has added in the field of knowledge by contributing some new thoughts and interpretations of continuance usage modelling for mHealth services. The findings may become beneficial for the government agencies, policymakers, mHealth systems developers and service providers.

As limited research was found on CUI of mHealth in the integrated view of rural elderly’s value, this research contributes to the extant literature by categorizing key factors that might support to proliferate the continuance usage of this service. Moreover, the contextualization of the related variables and integration of the existing model is theoretically original. Furthermore, because of a generic approach, the findings could be easily modified to assist other developing countries in the planning and up-take of mHealth.

The purpose of this paper is to assess the correlations between mobile banking and inclusive development (poverty and inequality) in 93 developing countries for the year 2011.

Mobile banking entails the following: “mobile phones used to pay bills” and “mobile phones used to receive/send money”, while the modifying policy indicator includes the human development index (HDI). The data are decomposed into seven sub-panels based on two fundamental characteristics: regions (Latin America, Asia and the Pacific, Central and Eastern Europe, and Middle East and North Africa) and income levels (upper middle income, lower middle income and low income).

The results show that at certain thresholds of the HDI, mobile banking is positively linked to inclusive development. The following specific findings are established. First, the increased use of mobile phones to pay bills is negatively correlated with: poverty in lower-middle-income countries (LMIC), upper-middle-income countries (UMIC) and Latin American (LA) countries, respectively, at HDI thresholds of 0.725, 0.727 and 0.778 and inequality in UMIC and LA with HDI thresholds of, respectively, 0.646 and 0.761. Second, the increased use of mobile phones to send/receive money is negatively correlated with: poverty in LMIC, UMIC and Central and Eastern European (CEE) countries with corresponding HDI thresholds of 0.631, 0.750 and 0.750 and inequality in UMIC, CEE and LA at HDI thresholds of 0.665, 0.736 and 0.726, respectively.

The findings are discussed in the light of current policy challenges in the transition from the UN’s Millennium Development Goals to Sustainable Development Goals.

The authors have exploited the only macroeconomic data on mobile banking currently available.

This study investigated the underlying influence mechanism between mHealth service quality (SQ) and users' adoption intention and compared the differences of consumer individual decision-making behaviors between the pre-adoption stage and the post-adoption stages.

This study built the pre-adoption and post-adoption models based on the stimulus-organism-response (S-O-R) model. Besides, this study collected 14,221 independent samples from 40 studies of pre-adoption intention to use and 12,876 independent samples from 36 studies of post-adoption intention to continue using and used meta-analysis structural equation modeling (MASEM) method to explore the formation of mHealth service quality influence on consumers toward adoption intention.

The results showed that (1) service quality positively trigger users' cognition response (i.e. perceived usefulness, perceived ease of use and perceived trust) and further positively drove the adoption and continuance intention; (2) there are similarities and differences in the relative importance of users' cognitive response between service quality and adoption intention at pre-adoption and post-adoption stages; (3) perceived trust (PTRU) played the most significant mediator in predicting users' adoption intention in both two stages; (4) perceived usefulness had a stronger influence than perceived ease of use (PEOU) on the adoption intention in pre-adoption while the result was just opposite in post-adoption stage.

This study could help service providers effectively allocate their limited resources to improve user adoption intention.

This study is the first one to open the black box of the underlying influence mechanisms between mHealth service quality and individual adoption intention in mHealth services and show differences in consumer decision-making according to the adoption stage. It provides a new perspective to the research in mHealth.

This study aimed to explore consumers' continuance intention to use a fitness and health app by applying two theoretical models: the expectation–confirmation model (ECM) and the investment model (IM).

An online survey was administered to consumers who are currently using fitness and health apps (N = 342). Structural equation modeling (SEM) was conducted using Amos 22.0 software to examine the hypothesized relationships in the research model.

Results revealed that users' continuance intention was significantly predicted by the two models. Within the ECM, the positive and significant relationships among variables were found. Moreover, users' satisfaction and investment size had positive impacts on their commitment, which, in turn, positively affected the intention. Also, confirmation of expectations had a positive impact on investment size.

The integrated model helps better understand fitness and health app users' decision-making process from the perspective of relationship commitment and suggests practical implications for health and fitness app providers.

Today, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects.

After a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS.

The results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies.

This paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region.

The purpose of this paper is to analyse the recent restructuring of the African mobile telecommunications sector, to examine how mobile telecommunications supports economic development and to assess how such development will be influenced by the restructuring.

An original database has been compiled and linked to recent merger and acquisition activity in the African telecommunications sector. The theoretical/case study literature on the link between mobile telecommunications and economic development is reviewed. This is then linked to the recent restructuring activity in Africa.

After something of a lull during the mid‐2000s, M&A activity has once again become frenetic over the past two years. It is too early to be certain of the eventual structure of the African mobile telecommunications sector, but in the medium term the reallocation of networks to well‐funded and efficient operators should provide a spur to renewed economic growth.

The structure of the sector is never in final equilibrium, so it is difficult to assess how long it will take for the benefits for economic growth to show through.

In the past, inadequately funded and managerially limited operators have expanded beyond their capabilities. Hopefully, this time around ambition will not outstrip capability.

Economic growth and societal development should be enhanced by recent M&A activity in the African mobile sector.

There are precious few completely up‐to‐date case studies on mobile telecommunications. This will help to fill the existing gap.

The purpose of this study is to investigate the determinants of behavioral intention to use smartphone diet applications within the emerging market. Specifically, it focuses on the Privacy Calculus Model constructs, encompassing perceived risk and perceived benefit, as well as the pivotal elements of trust and self-efficacy. It also explores the moderating influence of experience on the influencing factors and intention to use a diet application.

In a survey with 572 respondents, data analysis was conducted using partial least squares (PLS) structural equation modeling.

The findings reveal that perceived risk exerts a significant negative influence on behavioral intention. Conversely, perceived benefit, trust and self-efficacy exhibit a positive impact on behavioral intention. Moreover, the study delves into the moderating role of users' experience, which is found to significantly influence these relationships, suggesting that user experience plays a pivotal role in shaping the adoption dynamics of diet applications.

The limitations of this study may include the sample size and the specific focus on the emerging market of Saudi Arabia. The implications of the findings are relevant for scholars, developers, marketers, and policymakers seeking to promote the use of smartphone diet applications.

This study adds value by exploring the determinants of behavioral intention in the context of smartphone diet applications, and it is a first attempt to test the moderating role of users' experiences, providing valuable insights for various stakeholders in the field.

This paper aims to examine the global pattern of growth and development of eHealth research based on publication headcount, and analysis of the characteristics, of the keywords used by authors and indexers to represent their research content during 1945–2019.

This study adopted a bibliometric research design and a quantitative approach. The source of the data was Elsevier’s Scopus database. The search query involved multiple search terms because researchers’ choice of keywords varies very significantly. The search for eHealth research publications was limited to conference papers and research articles published before 2020.

eHealth originated in the late 1990s, but it has become an envelope term for describing much older terms such as telemedicine, and its variants that originated much earlier. The keywords were spread through the 27 Scopus Subject Areas, with medicine (44.04%), engineering (12.84%) and computer science (11.47%) leading, while by Scopus All Science Journal Classification Health Sciences accounted for 55.83% of the keywords. Physical sciences followed with 30.62%. The classifications social sciences and life sciences made only single-digit contributions. eHealth is about meeting health needs, but the work of engineers and computer scientists is very outstanding in achieving this goal.

This study demonstrates that eHealth is an unexplored aspect of health literature and highlights the nature of the accumulated literature in the area. It further demonstrates that eHealth is a multidisciplinary area that is attractive to researchers from all disciplines because of its sensitive focus on health, and therefore requires pooling and integration of human resources and expertise, methods and approaches.