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Digital transformation is one of the key concepts attached to the smart cities’ domain. The requirement to enhance strategically the way that business is delivered around different areas is a critical milestone for the digital transformation agenda and also for business performance management. In this short position chapter, we are focusing on the area of healthcare and we are providing key insights and lessons learned from Saudi Arabia. The main contribution of the chapter is a structured discussion on a digital healthcare strategy in the context of smart cities.

While considerable scholarly attention has been given to “millennials” (those born between 1981 and 1997), little is known of this generation’s ability to influence healthcare organizations and managerial roles in particular. This paper aims to clarify why millennials enter the healthcare management field and how their motivations correlate with preferences for working in various healthcare sectors and with various patient populations.

Survey data were collected from 107 millennials pursuing bachelor degrees in healthcare management by using a modified version of the multidimensional work motivation scale. Further data were collected on millennials’ preferences for working in various healthcare sectors and with various patient populations. Correlational analyses were conducted to examine the relationship between types of motivation and workplace preferences. Cross-cultural differences were also examined within this generational set.

Results indicate a significant positive relationship between intrinsic motivation and preferences for working on the payer side of the industry and within finance and IT functions. Findings also reveal a significant positive relationship between prosocial motivation and preferences for working with more vulnerable patient populations. Variance in work motivation among cultural sub-sets of millennials suggests different upbringings, or alternatively, cultural relativity of the motivational constructs themselves.

Despite offering key insights into the next generation of healthcare managers, this study is limited by a sample of millennials from one large, metropolitan university in the USA and thus may not represent the views of all millennials.

To select, retain and develop the next generation of healthcare managers, it is incumbent upon organizations to better understanding millennials’ motivations and preferences.

This study is the first of its kind to illuminate the motivations and preferences that underpin a key and growing segment of the healthcare workforce. Millennials, now the largest and most diverse generation on the planet, are poised to change the landscape of health care.

The goal of this article is to provide an overview of healthcare entrepreneurship, both in terms of its current trends and future directions.

The article engages in a systematic review of extant research on healthcare entrepreneurship using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) as the review protocol and bibliometrics or scientometrics analysis as the review method.

Healthcare entrepreneurship research has fared reasonably well in terms of publication productivity and impact, with diverse contributions coming from authors, institutions and countries, as well as a range of monetary and non-monetary support from funders and journals. The (eight) major themes of healthcare entrepreneurship research revolve around innovation and leadership, disruption and technology, entrepreneurship models, education and empowerment, systems and services, orientations and opportunities, choices and freedom and policy and impact.

The article establishes healthcare entrepreneurship as a promising field of academic research and professional practice that leverages the power of entrepreneurship to advance the state of healthcare.

The article offers a seminal state of the art of healthcare entrepreneurship research.

This chapter explores the transformative impact of artificial intelligence (AI) on higher education, particularly in the context of accelerating technological and societal changes. As higher education institutions face the need to offer more flexible, adapted and relevant academic programmes, AI presents significant opportunities and challenges. In the first part of this chapter, the authors elaborated on characteristic the evolution of AI including characterizing the emerging AI landscape. One of our contributions in this concluding chapter is to conceptualize the next areas of deployment of AI in higher education considering the novel, innovative services that will disrupt the entire market in the next few years. The strategic proposition for deployment of AI in higher education highlighted six pillars, namely large language models, research.AI, content creation.AI, personalised learning.AI, skill building assistants.AI and education out of the Box.AI. The authors presented opportunities to harness AI to enhance teaching, learning and research under each pillar, along with a detailed list of potential application areas and services. Universities are exploring innovative ways to use AI-driven solutions to improve research, teaching and learning experiences, and the authors also developed indicative scenarios for the use of AI in higher education based on the six pillars. One of the bold contributions in this chapter is the structured framework for understanding the evolution and use of AI in higher education, utilizing a matrix to map the intersection of market penetration and product development. Finally, the authors discuss future directions and strategies for Higher Education 2030 in light of advances in AI technology.

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.

Healthcare education is a huge industry with a significant social footprint and resilient impact on well-being and on the quality of life. It integrates diverse scientific domains and needs to continuously update its value proposition to reflect the need for preparing top-quality health professionals. It also has to support professional development and to manage effectively the accreditation of programs and the certification of skills and knowledge. In this chapter, the authors expand a theoretical framework about Active and Transformative Learning (ATL) that has introduced in the volume of ATL for STEAM disciplines and also discussed how artificial intelligent (AI) tools, such as OPENAI Chat GPT, can serve as transformers and value carriers for the implementation of ATL activities and use cases in healthcare education.

This paper explores how healthcare administration students perceive the integration of Artificial Intelligence (AI) in healthcare leadership, mainly focusing on the sustainability aspects involved. It aims to identify gaps in current educational curricula and suggests enhancements to better prepare future healthcare professionals for the evolving demands of AI-driven healthcare environments.

This study utilized a cross-sectional survey design to understand healthcare administration students' perceptions regarding integrating AI in healthcare leadership. An online questionnaire, developed from an extensive literature review covering fundamental AI knowledge and its role in sustainable leadership, was distributed to students majoring and minoring in healthcare administration. This methodological approach garnered participation from 62 students, providing insights and perspectives crucial for the study’s objectives.

The research revealed that while a significant majority of healthcare administration students (70%) recognize the potential of AI in fostering sustainable leadership in healthcare, only 30% feel adequately prepared to work in AI-integrated environments. Additionally, students were interested in learning more about AI applications in healthcare and the role of AI in sustainable leadership, underscoring the need for comprehensive AI-focused education in their curriculum.

The research is limited by its focus on a single academic institution, which may not fully represent the diversity of perspectives in healthcare administration.

This study highlights the need for healthcare administration curricula to incorporate AI education, aligning theoretical knowledge with practical applications, to effectively prepare future professionals for the evolving demands of AI-integrated healthcare environments.

This research paper presents insights into healthcare administration students' readiness and perspectives toward AI integration in healthcare leadership, filling a critical gap in understanding the educational needs in the evolving landscape of AI-driven healthcare.

Digital transformation in nursing education is crucial for enhancing pedagogical practices and preparing future healthcare professionals for the rapidly evolving healthcare landscape. This chapter explores how the integration of digital technologies in higher education has revolutionising teaching methodologies and offered new opportunities to enhance learning experiences. It identifies gaps in digital learning modalities for undergraduate and postgraduate nursing students and discusses strategies to strengthen online literacy preparation and transition into the healthcare sector's digital transformation landscape and the 4th industrial era economy. The chapter examines best practices and challenges in digital transformation in nursing education such as blended learning environments, simulation and virtual reality, mobile learning applications and gamification strategies. Additionally, it addresses challenges in curriculum development including insufficient technological infrastructure, faculty training and development, assessment strategies and resistance to change among faculty and students. This chapter aims to provide insights and recommendations for educators, curriculum developers and policymakers in implementing successful digital transformation in nursing education.

This paper explores innovation adoption in inter-organizational healthcare networks. The authors develop theoretical speculations to investigate better the role of artificial intelligence (AI) as an innovative tool to improve buyer-supplier relationships, creating better performance outcomes.

The research is based on a theoretical investigation aiming at exploring the role of AI-based solutions for managing buyer-supplier relationships. The conceptual approach allows us to identify some research streams (e.g. co-working collaborations in supply chain management) by proposing a matrix that helps clarify the analysis's directions.

The results show the importance of AI that can help the operator in accessing supplier information, including current prices, available stocks, and delivery status, thereby reducing the risk of information asymmetry. AI is intended not only as a technology tool but also as an innovative solution to promote business relationships and support vertical alliances through the value chain between buyer and supplier.

This paper can help healthcare actors examine the choices behind their operational strategies by providing transparency of the activities and availability of information in real-time. Finally, our study reflects the future directions to enhance the cooperation and innovation adoption among healthcare operators.