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The purpose of this paper is to examine patient engagement in remote consultation services, an increasingly important issue facing Healthcare Operations Management (HOM) given the significant expansion in this and other forms of telehealth worldwide over the last decade. We use our analysis of the literature to develop a comprehensive framework that incorporates the patient journey, multidimensionality, antecedents and consequences, interventions and improvement options, as well as the cyclic nature of patient engagement. We also propose measures suitable for empirical assessment of different aspects of our framework.

We undertook a comprehensive review of the extant literature using a systematic review approach. We identified and analysed 63 articles published in peer-reviewed scientific journals between 2003 and 2022.

We conceptualise patient engagement with remote consultation across three key aspects: dimensions, process, and the antecedents and consequences of engagement. We identify nine contextual categories that influence such engagement. We propose several possible metrics for measuring patient engagement during three stages (before service, at/during service and after service) of remote consultation, as well as interventions and possible options for improving patient engagement therein.

The primary contribution of our research is the development of a comprehensive framework for patient engagement in remote consultation that draws on insights from literature in several disciplines. In addition, we have linked the three dimensions of engagement with the clinical process to create a structure for future engagement assessment. Furthermore, we have identified impact factors and outcomes of engagement in remote consultation by understanding which can help to improve levels of adoption, application and satisfaction, and reduce healthcare inequality. Finally, we have adopted a “cyclic” perspective and identified potential interventions that can be combined to further improve patient engagement in remote consultation.

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.

An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s needs throughout the service journey. This article envisions the idea of AI concierges and discusses how to leverage AI concierges in the customer journey.

This article takes a conceptual approach and draws insights from literature in service management, marketing, psychology, human-computer interaction and ethics.

This article delineates the fundamental forms of AI concierges: dialog interface (no embodiment), virtual avatar (embodiment in the virtual world), holographic projection (projection in the physical world) and tangible service robot (embodiment in the physical world). Key attributes of AI concierges are the ability to exhibit semantic understanding of auditory and visual inputs, maintain an emotional connection with the customer, demonstrate proactivity in refining the customer’s experience and ensure omnipresence through continuous availability in various forms to attend to service throughout the customer journey. Furthermore, the article explores the multifaceted roles that AI concierges can play across the pre-encounter, encounter and post-encounter stages of the customer journey and explores the opportunities and challenges associated with AI concierges.

This paper provides insights for professionals in hospitality, retail, travel, and healthcare on leveraging AI concierges to enhance the customer experience. By broadening AI concierge services, organizations can deliver personalized assistance and refined services across the entire customer journey.

This article is the first to introduce the concept of the AI concierge. It offers a novel perspective by defining AI concierges’ fundamental forms, key attributes and exploring their diverse roles in the customer journey. Additionally, it lays out a research agenda aimed at further advancing this domain.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

By following the “employee-centric” approach, this study aims at identifying the impact of high-performance work systems (HPWS) on specific employee attitudinal outcomes such as work engagement, job satisfaction and affective commitment in the Indian healthcare industry.

The target population for this study includes the nurses working in large private multi-specialty tertiary care hospitals in India. Partial Least Squares Structural Equation Modelling (PLS-SEM) techniques are used on a sample of 152 nurses working in two large specialty hospitals.

In the Indian healthcare industry context, the nurse's perception of HPWS has shown a significant positive effect on their attitudinal variables such as work engagement, job satisfaction and affective commitment. When checked for mediation of work engagement and job satisfaction variables in HPWS – affective commitment relationship, nurse's job satisfaction partially mediated the relationship, but nurse's work engagement has shown no mediation effect.

This is one of the pioneering studies conducted in the Indian healthcare industry context, especially on the nurse's sample in identifying the impact of high-performance work systems on their attitudinal outcomes. Underscoring the paucity of HPWS research in the Indian healthcare industry, this study's findings will be an addition to the HPWS literature and also to the nursing research in the Indian healthcare settings.

This article aims to elucidate the effect of transformational leadership on commitment to change, assuming the existence of mediating variables (Leader–Member Exchange) influencing this relationship.

Data was collected through a survey based on a sample of 240 observations (Tunisian context with respondents from the healthcare sector). These findings were processed using SPSS and AMOS 23 software, employing exploratory factor analysis and structural equation modeling.

Research results affirm that leader–member exchange plays a mediating role between leadership styles and commitment to change.

Methodologically, the sample choice lacked diversity. Only hospitals were encompassed in this study. Hence, the generalizability of the results might be questioned. It is crucial to acknowledge that outcomes could vary based on culture and organizational type (Yu et al., 2002; Hechanova and Cementina-Olpoc, 2013). Moreover, our assessment of commitment to change relies on a unidimensional measurement scale focused on affective commitment. However, a multidimensional approach (Herscovitch and Meyer, 2002) could provide a more detailed understanding of the relationship between transformational leadership and different dimensions of commitment to change, including affective, normative and continuance commitment.

On a practical level, the outcomes of this study hold significance for the healthcare domain, especially concerning change management and leadership within healthcare institutions. Grasping how transformational leadership can positively influence commitment to change through leader–member exchange offers healthcare managers concrete strategies to foster employee adherence to change initiatives. This understanding can be particularly crucial in a constantly evolving environment, where practices and protocols need adaptation to meet new requirements and medical advancements.

This research clarifies how transformational leadership influences commitment to change through leader–member exchange. Furthermore, this study guides organizations toward cultivating transformational leaders. The strength of transformational leadership lies in its ability to channel and transform energies to evoke enthusiastic motivation for achieving anticipated goals (Bass, 1985). However, it's pivotal to recognize that transitioning from a manager-directed approach to an empowerment approach presents inherent challenges (Manz et al., 1990). Investing in leadership development, as underscored by this study, can yield tangible enhancements in commitment to change.

This study investigates how federated learning (FL) and human–robot collaboration (HRC) can be used to manage diverse industrial environments effectively. We aim to demonstrate how these technologies not only improve cooperation between humans and robots but also significantly enhance productivity and innovation within industrial settings. Our research proposes a new framework that integrates these advancements, paving the way for smarter and more efficient factories.

This paper looks into the difficulties of handling diverse industrial setups and explores how combining FL and HRC in the mark of Industry 5.0 paradigm could help. A literature review is conducted to explore the theoretical insights, methods and applications of these technologies that justify our proposal. Based on this, a conceptual framework is proposed that integrates these technologies to manage heterogeneous industrial environments.

The findings drawn from the literature review performed, demonstrate that personalized FL can empower robots to evolve into intelligent collaborators capable of seamlessly aligning their actions and responses with the intricacies of factory environments and the preferences of human workers. This enhanced adaptability results in more efficient, harmonious and context-sensitive collaborations, ultimately enhancing productivity and adaptability in industrial operations.

This research underscores the innovative potential of personalized FL in reshaping the HRC landscape for manage heterogeneous industrial environments, marking a transformative shift from traditional automation to intelligent collaboration. It lays the foundation for a future where human–robot interactions are not only more efficient but also more harmonious and contextually aware, offering significant value to the industrial sector.

Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.

Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).

The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.

Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.

This paper aims to objectively present the research dynamics of China in the field of information behavior and its development trends. Firstly, it incorporates China’s research in the field of information behavior into the global research network of information behavior, analyzing the changes in the status of Chinese scholars and their research institutions in the global research network from 1991 to 2022, the trends in publication volume and the cooperation relationships with other countries. Then, it conducts a detailed analysis of China’s research categories, groups, theoretical models and hot topics in different information contexts in the past five years (2018–2022).

The study retrieved research literature related to information behavior in China from 1991 to 2022 in the Web of Science database. It then utilized a national/institutional cooperation network map to analyze the changes in the status of Chinese scholars/institutions in the global research network during this period, publication volume trends and cooperation relationships with other countries. Furthermore, it employed keyword co-occurrence network maps to analyze the key categories, groups, theories and models of China’s research in different information contexts in the past five years. Based on this, it used keyword clustering network maps to analyze the hot topics of China’s research in different information contexts in the past five years.

(1) China’s research in the field of information behavior started relatively late, but the volume of publications has grown rapidly since 2004, currently ranking second globally in cumulative publication quantity. However, the influence of the literature published by China is limited, and there is a lack of research institutions with global influence. (2) In the last five years, China has conducted extensive research in various information contexts. Among these, most research was conducted in work contexts, followed by healthcare contexts, especially studies related to epidemics. (3) Current research on information behavior in China is characterized by expanded and refined research groups, diversified research categories, continuous expansion and enrichment of research contexts, increased interdisciplinary nature of research and continuous innovation in research methods and theoretical models.

This study, utilizing a scientific knowledge map, elucidates China’s position in global information behavior research, with a specific emphasis on analyzing China’s research hot topics and trends in this field over the past five years. It aims to provide valuable resources for scholars interested in understanding the status of information behavior research in China and to offer some guidance for scholars currently or intending to engage in information behavior research.

This chapter examines how innovation and research are essential to the advancement of science, the economy, and society. We examine the current status of scientific research in Saudi Arabia, highlighting issues like financial limitations and a lack of skilled researchers. We emphasize how important it is to develop the next generation of scientists in order to transform existing practices and improve the state of scientific research in the country.

Proficiency in research and innovation is crucial for expanding the frontiers of knowledge, empowering scientists to tackle intricate problems, and advancing scientific rigor. These abilities also support the use of evidence in decision-making, enabling researchers to provide empirical data that inform practices and policies in a variety of industries. Sustained growth requires the formation of future leaders, who promote knowledge exchange and multidisciplinary collaboration.

Despite Saudi Arabia’s significant spending on science, problems still exist. Addressing governance deficiencies is demonstrated by the establishment of the Research, Development, and Innovation Authority in 2021. The nation has grown in the world’s scientific rankings, drawing eminent specialists and fostering cross-border cooperation. Still, there is room for improvement, especially when it comes to fostering a culture of research, improving financing sources, and encouraging international collaboration. It is imperative that these problems are resolved in order to avoid stagnation, guarantee ongoing innovation, and take advantage of chances for society’s progress.

The chapter ends with a call to action that highlights how quickly improvements must be made. Failing to do so runs the risk of stifling the advancement of science, preventing the creation of new technologies, and prolonging complicated issues. To lower risks, seize opportunities, and ensure that research and innovation continue to advance for the good of society, immediate action is necessary.