In today’s rapidly evolving world, the ability to translate knowledge into innovative actions is not merely a desirable feature but a fundamental driver of progress to create value among all the players and stakeholders (Dalkir, 2017).
This translation requires the implementation of a Knowledge Management System (KMS), generally recognized and applied to define disciplined actions useful to align people, data, processes, and technologies to drive organizational performance. In healthcare setting, adopting a systematic approach, information and needs could be integrated, enhancing, and improving performance, potentially impacting the quality of patients’ care (El Morr et al., 2010). This is gaining pivotal importance with the availability of massive, various, and complex healthcare data deriving from different sources that can be exploited in the development of new organizational models, disruptive technological solutions, and more demand‐oriented healthcare systems. A healthcare organization’s Knowledge Management (KM) initiatives could embrace a range of social and technology-oriented actions, including, but not limited to, developing an information network that could connect final users, providers, payers, and professionals, adopting the ecosystem’s logic, and defining knowledge transfer programs. A knowledge transfer process, in particular, is defined as the transfer of scientific findings, skills, knowledge, technologies, methods of manufacturing, and facilities among different entities, such as governments, universities, and other institutions with the aim of ensuring that scientific and technological developments are accessible to a wider range of users who can then further develop and exploit them into new products, processes, applications, materials, or services. Although technology transfer in healthcare faces numerous challenges, such as intellectual property rights, regulatory barriers, ethical issues, market failures, standardization requirements and cultural differences. This process is considered as crucial to foster innovation and improve health outcomes for all the actors involved in the healthcare value chain, enabling the diffusion of new medical devices, diagnostics, drugs, vaccines, and ground-breaking therapies across different settings and contexts (Sheng et al., 2013).
Thus, knowledge, including medical research, discovery and development of new drugs, clinical expertise, data analytics, knowledge workers’ and patient insights, serves as the foundation of healthcare innovation. The relevance of knowledge is connected to the priority for the healthcare industry and healthcare facilities to drive innovation at any level as innovations plays a pivotal role in improving patient outcomes, enhancing healthcare delivery, and addressing global health challenges. Understanding how this knowledge is connected and transformed into innovation is crucial for healthcare organizations, researchers, policymakers, and clinicians aiming to drive advancements that positively impact human health.
In this context, digitalization serves as a catalyst in this process, harnessing cutting-edge technologies and sophisticated platforms to seamlessly integrate and manage such knowledge components. Digitalization not only amplifies the efficiency of existing processes but also affords a multitude of opportunities for process innovation within the healthcare landscape (Biancone et al., 2021).
Primarily, digitalization fuels the generation of data-driven insights, unveiling a treasure trove of actionable knowledge hidden within vast and complex datasets (Wang and Byrd, 2017; Wowak et al., 2023). Such data-driven insights not only inform medical decision-making but also pave the way for ground-breaking approaches, including personalized medicine, treatment optimization, and proactive disease prevention (Wowak et al., 2023). Moreover, digitalization assumes the role of a facilitator, fostering instantaneous, cross-border knowledge sharing and support for more transparent decision-making among healthcare professionals. This collaborative dynamic, underpinned by adept KM practices, entails the cultivation of learning and organizational competencies, the mitigation of errors, and the continual enhancement of healthcare services that considers also the social and environmental impacts of operations. It fosters heightened teamwork collaboration, enabling the acquisition of substantial technical resources, the provision of elevated support structures, and the achievement of cost optimization (Cerchione et al., 2017; Myllärniemi et al., 2012; Kessel et al., 2012).
Furthermore, focusing on operations, KM approaches, in the hospitals, in the healthcare industries, and within the local healthcare contexts, could support the operational excellence due to an in-depth examination of how knowledge management strategies can be leveraged to optimize various aspects, considering process improvement and re-engineering, resource allocation and cost reduction, driven by well-managed knowledge resources (Wickramasinghe et al., 2009). In this regard, the role of data and management science methodologies – and their integration and interface with KM approaches – emerge as relevant for decision-making. Indeed, in the current scenario characterized by ongoing crises and the pervasive phenomenon of digital transformation, the debate around users’ accessibility to services is regaining momentum. As such, policymakers are asked to strategically redesign traditional models and networks for healthcare services provision toward more inclusive, effective, and efficient solutions, strengthening territorial cohesion and reducing disparities (e.g., novel models of territorial medicine/primary care), while fostering a more transparent, traceable, and well-coordinated healthcare supply chain thanks to the better knowledge management among all the supply chain actors (manufacturers, logistics service providers/wholesalers, healthcare service providers and retailers). To this end, quantitative methodologies – both predictive (e.g., machine learning and deep learning) and prescriptive (e.g., spatial analysis, optimization, and simulation) – are becoming fundamental support tools to seek solutions ensuring social/user-oriented objectives, environmental targets, and economic goals. Their implementation, which is, in fact, organizational and process innovation in practice, cannot neglect an eco-systemic view and, hence, adequate KM initiatives in healthcare.
The present track is dedicated to delving into the multifaceted and evolving relationship between knowledge management and innovation development and dynamics in a digital context, within the healthcare setting, adopting a multidimensional approach and embracing several aspects such as strategic, managerial, organizational, and operational issues. The aim is to facilitate a comprehensive examination of the pivotal role that knowledge plays within the healthcare field, considering especially the innovation progress. It explores the pathways by which knowledge is acquired, refined, and applied to create innovative medical treatments, healthcare technologies, care delivery models, supply and service operations, and policies. Additionally, it investigates the broader societal implications of healthcare innovation, from improving patient care and population health to addressing healthcare disparities and advancing the global health agenda, also from a sustainable and resilient perspective.
Against the described backdrop, this track calls for further insights on challenges and solutions with a particular attention to the role of KM and knowledge assets in supporting the innovative transformation of healthcare systems. To stimulate the debate among attendees, this track welcomes empirical and conceptual contributions addressed, but not limited to, the following topics of interest:

• How could healthcare organizations effectively manage their knowledge to foster the development of innovative healthcare products and technologies?
• How does the acquisition of new knowledge influence the behaviour of healthcare organizations and the establishment of new governance models in healthcare, including aspects such as patient care, research, and healthcare policy?
• What organizational factors could either facilitate or hinder the transformation of knowledge into practical healthcare innovations?
• How could KM initiatives be efficiently applied within healthcare organizations to drive innovation and enhance sustainability in healthcare delivery?
• How can new knowledge support understanding patients’ needs and contribute to developing competitive healthcare innovations, treatments, and patient care approaches?
• How can the knowledge management improve the healthcare services, hospitals, and healthcare organisations, in terms of performance and value creation?
• What knowledge processes are crucial for transforming knowledge into healthcare innovations and improving also patient care?
• How does the translation of knowledge into healthcare innovation contribute to the development and refinement of critical theories within the healthcare field, such as dynamic healthcare capabilities, organizational learning, and resource- and competence-based views?
• How could be created a bridge for the gaps and conflicts between different organizational cultures, professional cultures, and national cultures that affect communication, collaboration, and trust among the entities involved in the technology transfer?
• How could be respected the dignity, privacy, and autonomy of the patients and participants involved in the technology development and transfer, as well as the social and cultural values of different communities and stakeholders?
• How should KM systems be designed for healthcare organizations to balance operational performance, availability of data and privacy?
• What are the determinants and barriers of technology transfer in healthcare, and how can they be measured and evaluated?
• How could digital technologies, and more in general the digitalization, assist healthcare organizations in capturing, storing, retrieving, and distributing knowledge for improved care and innovation development?
• What are the business process innovation opportunities unlocked through digitalization in healthcare?
• How could be defined a bridge between KM theories and their practical application within healthcare organizations, particularly concerning knowledge management goals, strategic execution, and alignment with healthcare challenges?
• What is the relationship between a healthcare organization’s ability to translate knowledge, defining networks and creating value for all the stakeholders?
• How could a knowledge management approach support the operations’ definition and optimization within the healthcare sector?
• How can KM initiatives and sharing activities between healthcare supply chain actors foster collaboration and transparency while meeting standardization requirements?
• How does entrepreneurship within the healthcare sector facilitate the transformation of knowledge into new-to-the-market healthcare innovations and advancements in medical solutions?
• To what extent could KM programs and data/management science approaches help reduce disparities in healthcare access, improving equity, quality, and continuity of care, also within the territorial medicine or the primary care setting?
• How can KM, data science, and management science approaches, support decision-making related to the territorial organization of health systems and/or the optimization of health logistics and processes?

Emanuela Foglia, Carlo Cattaneo – LIUC University, Italy
Elena Pessot, University of Siena, Italy
Antonio Diglio, University of Naples Federico II, Italy
Stefania Manetti, Politecnico di Milano, Italy
Elisabetta Benevento, University of Pisa, Italy