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The aim of this study is to comprehend the behavioural intention of females' perception toward smart healthcare technology. The study also examines the moderation effect of social influences between perceived smart healthcare technology and perceived usefulness among female users.

To test the model, this study collected data from female respondents (n = 913) responses. The data were analyzed by structural equation modeling (SEM) using Smart-PLS 3.2. To complement the findings from structural equation modeling, the study also conducted a post-hoc test via experimental research design. The authors also applied a t-test and PROCESS macro analysis to re-confirm the relationship mentioned above.

The findings revealed that perceived ease of use significantly mediates the relationship between females' perceived smart healthcare technology and intention to use. The findings also show that social influence moderates between smart healthcare technology and the perceived usefulness relationship.

Social influence is one of the major issues while adopting smart healthcare technology because the respondents perceived that they are accustomed to the technologies related to smart health once their surroundings and social environment influence them.

The current study is a pioneer in the context of a developing country and unique in that it makes two contributions: it extends previous research on smart health technology adoption in the healthcare business by considering females, and it gives a broad knowledge of the female healthcare consumers from emerging nations which can be useful for developing technology-driven healthcare services strategies.

The purpose of this paper is to investigate the role of emerging technologies in the promotion of health and well-being at the urban, domestic and bodily scale, through the systematic examination of technologies such as physical sensing systems and physiological data monitoring, that are currently explored as drivers for achieving sustainable healthcare within a multi-scalar approach.

A comprehensive study of the various technologies associated with smart healthcare is provided, first investigating smart cities, physical sensing systems and geospatial data as potential enablers of public health. Then the discourse shifts towards exploring Smart Home technologies for healthcare, first reviewing strategies of enhancing the home environment with multisensory components, and then discussing the emergence of physiological monitoring devices and their interconnection with the domestic and urban environment.

While the implementation of Internet of Things, physical sensing systems and geospatial analytics in extracting and analyzing the multiple information layers of the urban, the domestic and the bodily environment, has been widely explored, there is little consideration on the transition from the domestic to the urban level, and while within each of the different scales, the need for a multi-componential approach is addressed, there is minimal effort towards its materialization.

The major contribution of this study therefore lies in laying the ground for further research towards a multi-scalar relational approach that views smart healthcare as a trajectory, binding the bodily, to the domestic and the urban fabric.

The COVID-19 pandemic has affected around 216 countries and territories worldwide and more than 2000 cities in India, alone. The smart cities mission (SCM) in India started in 2015 and 100 smart cities were selected to be initiated with a total project cost of INR 2031.72 billion. Smart city strategies play an important role in implementing the measures adopted by the government such as the issuance of social distancing regulations and other COVID-19 mitigation strategies. However, there is no research reported on the role of smart cities strategies in managing the COVID-19 outbreak in developing countries.

This paper aims to address the research gap in smart cities, technology and healthcare management through a review of the literature and primary data collected using semi-structured interviews.

Each city is unique and has different challenges, the study revealed six key findings on how smart cities in India managed the COVID-19 outbreak. They used: Integrated Command and Control Centres, Artificial Intelligence and Innovative Application-based Solutions, Smart Waste Management Solutions, Smart Healthcare Management, Smart Data Management and Smart Surveillance.

This paper contributes to informing policymakers of key lessons learnt from the management of COVID-19 in developing countries like India from a smart cities’ perspective. This paper draws on the six Cs for the implications directed to leaders and decision-makers to rethink and act on COVID-19. The six Cs are: Crisis management leadership, Credible communication, Collaboration, Creative governance, Capturing knowledge and Capacity building.

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.

Prior literature lacks concrete and systematic review of the current blockchain application in smart sustainable city that covered to the full extent of various components. Thus, this study explores the integration of blockchain technology in making the city smarter, safer and sustainable.

This study conducted a systematic literature review of 49 publications published globally. Data were analysed by coding of the publications whereby the codes were generated based on frequency of appearance (n).

The results showed that smart sustainable city could leverage blockchain technology in several areas such as governance, mobility, asset, utility, healthcare and logistics. Blockchain technology could also aid smart sustainable city in achieving social, environmental and economic sustainability.

This study proposes a smart sustainable city with blockchain technology framework: guiding city planners and policymakers by deploying blockchain that supports technology within smart sustainable city framework. This facilitates the digital transformation of a city towards smart and sustainable through the use of blockchain.

Rural communities around the world are searching for solutions to upkeep, restore and improve local services that are deteriorating. They are exploring the potential of a digital transition along with the opportunities and threats created by new patterns of mobility and closer links with urban areas. The expansion of information and communication technologies (ICT)-enhanced applications enables rural communities to improve their quality of life. The concept of smart village is primarily about how rural communities make the best use of both ICT and social innovation by responding to the ongoing and emerging challenges. Therefore, the aim of this paper is to investigate strategies for adoption of smart villages along with the challenges faced.

A quantitative research methodology was adopted in this research. A web-based questionnaire survey was conducted to collect data. In total, 110 fully completed and useable questionnaires were received. Statistical analyses were undertaken using the Statistical Package for Social Sciences (SPSS).

The results indicate that lack of budget, lack of clear strategies for development of sustainable “smart villages”, lack of collaboration between stakeholders and lack of knowledge related to “smart villages” are the most debated challenges for implementing smart village agenda. Whereas smart energy, smart healthcare, smart transport, smart education and smart water are the top five most important smart village strategies.

Despite the novel insights provided by this study, it has some limitations. Given that the research reported in this paper is based on literature review and small-scale survey, results presented are only tentative and not generalisable. The findings of this paper are limited to the UK context only. Although generalisability outside of this context may be limited, the authors infer that the results are relevant to other comparable developed countries.

Research on smart village development is rare. This paper presents a theoretical basis on the concept of smart villages. It adds to the rich insight that goes into the understanding and awareness of the current smart village strategies along with the key challenges organisations encounter when implementing smart village initiatives. This research has implications towards informing professionals and policymakers on key lessons learnt during the implementation of smart village strategies. Also, this paper contributes to the academic debate on smart village development and provides useful recommendations to both policymakers and practitioners.

The utilization of artificial intelligence (AI) in the solution of many problems encountered in healthcare in recent years is rapidly becoming widespread. Understanding of the use and importance of efficiency, security and accessible healthcare to everyone and providing value-based services for healthcare decision-makers is essential. The special uses of machine learning, natural language processing and smart voice assistants, which have developed as sub-branches of AI, for healthcare services, the contributions of these techniques to the digital transformation of healthcare services and how all these will help decision-making processes in healthcare services, will be discussed in this chapter. And also, FDA-approved algorithms that are a kind of AI tool will be explained.

As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

Tremendous measure of data lakes with the exponential mounting rate is produced by the present healthcare sector. The information from differing sources like electronic wellbeing record, clinical information, streaming information from sensors, biomedical image data, biomedical signal information, lab data, and so on brand it substantial as well as mind-boggling as far as changing information positions, which have stressed the abilities of prevailing regular database frameworks in terms of scalability, storage of unstructured data, concurrency, and cost. Big data solutions step in the picture by harnessing these colossal, assorted, and multipart data indexes to accomplish progressively important and learned patterns. The reconciliation of multimodal information seeking after removing the relationship among the unstructured information types is a hotly debated issue these days. Big data energizes in triumphing the bits of knowledge from these immense expanses of information. Big data is a term which is required to take care of the issues of volume, velocity, and variety generally seated in the medicinal services data. This work plans to exhibit a survey of the writing of big data arrangements in the medicinal services part, the potential changes, challenges, and accessible stages and philosophies to execute enormous information investigation in the healthcare sector. The work categories the big healthcare data (BHD) applications in five broad categories, followed by a prolific review of each sphere, and also offers some practical available real-life applications of BHD solutions.

This paper proposes the adoption of Industry 4.0 (I4) technologies and lean techniques for improving operational performance in the healthcare sector.

The research adopted a systematic literature review and feedback of healthcare professionals to identify the inefficiencies in the current healthcare system. A questionnaire was used to get feedback from the patients and the hospital staff about the current practices and issues, and the expected impact of technology on existing practices. Data were analysed using descriptive statistics, correlation analysis and multiple regression analysis.

The results indicate that I4 technologies lead to the improvement of the operational performance, and the perceptions about I4 technologies are made through the pre-medical diagnosis. However, a weak correlation between lean practices and healthcare operational performance compared to that of I4 technologies and operational performance indicate that lean practices are not fully implemented in the Sri Lankan healthcare sector to their full potential.

This study is limited to two government hospitals, with insights from only the doctors and nurses in Sri Lanka. Furthermore, the study is limited to only selected aspects of I4 technologies (big data, cloud computing and IoT) and lean concepts (value stream mapping and 5S). Therefore, recommendations on the adoption of I4 technologies in the healthcare sector need to be made within the scope of the study investigation.

The implementation of I4 technologies needs careful consideration of process improvement as part of the overall plan for achieving the maximum benefits of technology adoption.

The findings of the research can be used as a benchmark/guide for other hospitals to explore the adoption of I4 technologies, and how process improvement from lean concepts could influence the overall operational performance.