While talent management (TM) continues to attract significant attention, research exploring TM practices within emerging markets and small and medium-sized enterprises (SMEs) remains limited. This qualitative study investigates how TM is practiced and talent is conceptualized in Turkish SMEs and large organizations, drawing on the strategy-as-practice (SAP) and HRM-as-practice perspectives. The findings reveal significant contextual variation: SMEs predominantly adopt informal, relational, and strategically adaptive TM practices, such as culturally embedded festive bonuses, apprenticeship-based training, and informal recognition, reflecting the local economic constraints and cultural norms. In contrast, large organizations utilize formalized TM practices, including structured career models, universal leadership development, and performance evaluations (for example, Nine-Box Grid), though these are actively adapted to local cultural expectations emphasizing inclusivity and collectivism. Talent conceptualization also diverges notably, with SMEs emphasizing loyalty, trust, and critical operational skills (exclusive-stable approach), whereas large firms prioritize broader, development-oriented views of talent (inclusive-developable approach). By demonstrating these nuanced, practice-based variations, the study challenges prevailing assumptions in TM literature derived predominantly from large Western enterprises, highlighting the critical influence of local institutional contexts and cultural factors. The study contributes theoretically by offering an integrative, practice-based perspective on TM and talent, calling for a more dynamic understanding of TM as socially constructed and contextually embedded. © 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.

Purpose – The purpose of this paper isto contribute to a grounded understanding of how mobility impactstalentdesignation and with what consequences.

Design/methodology/approach – An exploratory qualitative case study was conducted of a global medicaltechnology corporation, based on interviews with HR managers, line managers and non-managerial employees.

Findings – The findings illustrate that mobility plays a significant role in how employees are assigned talentstatus, and that mobility manifests and impacts talent designation through two types – geographical and lateralmobility. Mobility is not determined based on abilities and competencies, but rather on an employee’s overallpersonal situation, including age, family status and relationship status. Two main practices emerged throughwhich these determinants were decided: direct questioning and guesswork. The consequences that follow arethat individuals are left with little room to influence their own talent situation, and that there is a risk ofdiscriminatory and exclusionary consequences arising.

Originality/value – The study makes two main contributions. First, it provides a more nuanced understandingof how talent designation unfolds in practice, showing that performance and potential alone cannot explain theprocess and emphasizing the consequential role of mobility. Second, it contributes with knowledge about theconsequences of basing talent designation heavily on mobility. Individual employees are left with significantlyless room for enacting agency and playing active roles in relation to TM than has been suggested. Added to thisare the potential discriminatory and exclusionary consequences.

While important insights have been provided into the role of HR managers in performing change in the workplace, still little is known about how HR managers themselves are shaped by change, in particular in relation to those changes triggered by radical or disruptive shock events and crisis situations, and in the public sector context. In this study, we aim to address this, using an exploratory qualitative interview study to explore how the serious and profound COVID-19 pandemic triggered boundary work among HR managers in public sector municipalities. Our findings illustrate that COVID-19 triggered HR managers to engage in boundary work in two main ways: either by defending their boundaries (through the two practices of counteracting dumping and counteracting shirking) or by expanding them (through the two practices of facilitating self-fulfillment and facilitating status-enhancement). We discuss how this variation is related to whether the HR managers experienced and made sense of the pandemic mainly as a threat—of being forced into unwanted responsibility—or if they experienced and made sense of it mainly as an opportunity to take advantage of the situation. In showing this, the study makes a number of important contributions to both theory and practice. © The Author(s) 2023.

Background: Hard-to-heal wounds pose a significant challenge to healthcare systems globally. While person-centred care (PCC) has been proposed as a means to improve wound management, there is a scarcity of research examining its practical application in healthcare. An increased understanding of healthcare professionals' perceptions of PCC in wound management and the challenges associated with its application is thus warranted. Such an understanding can facilitate the implementation of PCC and, consequently, enhance the quality of care. Aim: To explore healthcare professionals' perceptions of PCC in wound management in primary care services. Method: The study had an explorative abductive design involving semi-structured interviews with 23 healthcare professionals in primary care working with wound management. An abductive qualitative content analysis was conducted using the PCC framework, incorporating three routines related to, respectively, initiation, working, and safeguarding the partnership. Results: The findings illustrated healthcare professionals' perceptions regarding initiating, practising, and safeguarding PCC in wound management. Initiating such care entailed having a holistic perspective, considering both the patient and the underlying causes of the wound, using the patient's goals and preferences to establish wound management, and motivating them to commit to the care. Practising PCC in wound management involved establishing a relationship of trust with the patient, tailoring wound management to her/his needs and circumstances, and minimising symptoms that had a negative impact on everyday life. Safeguarding PCC in wound management involved documenting continuously, keeping updated on patient medical records, and facilitating the exchange of information between healthcare professionals. Conclusion: Healthcare professionals acknowledge the significance of PCC in wound management. The findings also highlight challenges, particularly in practising shared decision-making, ensuring closeness and continuity of wound management, and documenting person-centred care. These findings offer insights into key factors that support the implementation of PCC. © 2025 The Author(s). Scandinavian Journal of Caring Sciences published by John Wiley & Sons Ltd on behalf of Nordic College of Caring Science.

Background: Artificial intelligence (AI) is increasingly introduced into healthcare, promising improved efficiency and clinical decision-making. While research has mainly focused on AI in hospital settings and physician perspectives, less is known about how AI may challenge the values that guide nursing practices. This study explores nurses’ perceptions of wound care in municipal home healthcare and the opportunities and challenges with the integration of AI technologies into their practices.

Methods: An exploratory qualitative study using semi-structured interviews was conducted with 14 registered nurses from two municipalities in Sweden. Participants were recruited through purposive sampling, and data were collected through individual interviews, either in person or via video call. Interviews were transcribed verbatim and analyzed inductively, inspired by the Gioia methodology. This approach allowed themes to emerge from the data while maintaining close alignment with participants’ perspectives. In a subsequent phase, the data were interpreted through the lens of Mol’s Logic of Care to deepen understanding of the relational, embodied, and adaptive nature of wound care. Ethical approval was obtained, and the study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ).

Results: Three interconnected dimensions emerged from the data: relational, embodied, and adaptive practices. Nurses emphasized the importance of relational work in wound care, highlighting the trust and continuity necessary for effective wound care, which AI-driven automation might overlook. Embodied practices, such as sensory engagement through touch, sight, and smell, were central to wound care, raising nurses’ concerns about AI’s ability to replicate these nuanced judgments. Adaptive practices, including improvisation and situational awareness in non-standardized home environments, were presented as challenges for AI integration, as existing digital systems were perceived as rigid and often increased administrative burdens rather than streamlining care.

Conclusions: Home healthcare nurses’ perspectives highlight the complex interplay between technology and caregiving. While AI could support documentation and diagnostic processes, its current limitations in relational, sensory, and adaptive aspects raised the nurses’ concerns about its suitability for wound care in home settings. Successful AI integration should account for the realities of nursing practice, ensuring that technological tools enhance the embodied, relational, and adaptive dimensions of wound care. Applying Mol’s Logic of Care helps illuminate how good care emerges through ongoing, situated practices that resist full automation. Future research could further explore how AI aligns with professional nursing values and decision-making in real-world care settings.

 © The Author(s) 2025.

The increased use of advanced technologies generating new data and information, including algorithmic technologies and AI, has led to a renewed interest in the role of technologies in knowledge work. Some of these technologies act as epistemic technologies, a term derived from the work of Knorr Cetina on how sciences make knowledge. While previous studies provide important insights into how the outcomes of the technologies are used in expert work, the work needed to produce the outcomes in the first place is often overlooked and separated from use. The generation of new data and information is instead treated as both black-boxed and decontextualized. To highlight the work required to generate meaningful outcomes, and address the challenges posed by opaque algorithms, we present a longitudinal in-depth study of the medical imaging technologies of the Robotic X-ray and iMRI, used in combination with surgery. The study illustrates how technologies become epistemic through use: new data was produced by means of interactions within a relational and heterogeneous assemblage of people, technologies and devices. Through trained judgement, the experts made the data useful and possible to act upon in each specific situation. The study contributes to research into the use of algorithmic technologies in knowledge work by showing how opaque algorithms can be complemented by contextualized information, making it possible to interrogate and make trained judgements, in relation not only to outcomes, but also to their production. We conclude that epistemic technologies are involved in the ongoing construction of knowledge, during both the production and use of outcomes, and that enacting the technologies as epistemic includes a situational and material awareness. © The Author(s) 2025.

Background: Artificial intelligence (AI) holds significant promise for enhancing the efficiency and safety of medical history-taking and triage within primary care. However, there remains a dearth of knowledge concerning the practical implementation of AI systems for these purposes, particularly in the context of healthcare leadership. This study explores the experiences of healthcare leaders regarding the barriers to implementing an AI application for automating medical history-taking and triage in Swedish primary care, as well as the actions they took to overcome these barriers. Furthermore, the study seeks to provide insights that can inform the development of AI implementation strategies for healthcare.

Methods: We adopted an inductive qualitative approach, conducting semi-structured interviews with 13 healthcare leaders representing seven primary care units across three regions in Sweden. The collected data were subsequently analysed utilizing thematic analysis. Our study adhered to the Consolidated Criteria for Reporting Qualitative Research to ensure transparent and comprehensive reporting.

Results: The study identified implementation barriers encountered by healthcare leaders across three domains: (1) healthcare professionals, (2) organization, and (3) technology. The first domain involved professional scepticism and resistance, the second involved adapting traditional units for digital care, and the third inadequacies in AI application functionality and system integration. To navigate around these barriers, the leaders took steps to (1) address inexperience and fear and reduce professional scepticism, (2) align implementation with digital maturity and guide patients towards digital care, and (3) refine and improve the AI application and adapt to the current state of AI application development.

Conclusion: The study provides valuable empirical insights into the implementation of AI for automating medical history-taking and triage in primary care as experienced by healthcare leaders. It identifies the barriers to this implementation and how healthcare leaders aligned their actions to overcome them. While progress was evident in overcoming professional-related and organizational-related barriers, unresolved technical complexities highlight the importance of AI implementation strategies that consider how leaders handle AI implementation in situ based on practical wisdom and tacit understanding. This underscores the necessity of a holistic approach for the successful implementation of AI in healthcare. © The Author(s) 2024.

A digital transformation of Swedish healthcare is currently taking place, and artificial intelligence (AI) is meant to solve many of the healthcare sector's challenges. The objective of this paper is to describe and analyze how the boundaries around the physicians' work could change when AI is implemented in healthcare and what boundary work actors on different levels in a healthcare system conduct. We conducted 26 semi-structured interviews with healthcare leaders and 18 with healthcare managers and professionals. The result shows that the leaders, healthcare managers, and healthcare professionals describe different types of boundary work in regard to the implementation of AI. The implementation of AI in healthcare could change the boundaries around the healthcare professionals’ work and generate new kinds of boundary work that could affect the implementation. These findings can inform both practice and policy.

The promise behind many advanced digital technologies in healthcare is to provide novel and accurate information, aiding medical experts to navigate and, ultimately, decrease uncertainty in their clinical work. However, sociological studies have started to show that these technologies are not producing straightforward objective knowledge, but instead often become associated with new uncertainties arising in unanticipated places and situations. This study contributes to the body of work by presenting a qualitative study of an Artificial Intelligence (AI) algorithm designed to predict the risk of mortality in patients discharged to home from the emergency department (ED). Through in-depth interviews with physicians working at the ED of a Swedish hospital, we demonstrate that while the AI algorithm can reduce targeted uncertainty, it simultaneously introduces three new forms of uncertainty into clinical practice: epistemic uncertainty, actionable uncertainty and ethical uncertainty. These new uncertainties require deliberate management and control, marking a shift from the physicians' accustomed comfort with uncertainty in mortality prediction. Our study advances the understanding of the recursive nature and temporal dynamics of uncertainty in medical work, showing how new uncertainties emerge from attempts to manage existing ones. It also reveals that physicians’ attitudes towards, and management of, uncertainty vary depending on its form and underscores the intertwined role of digital technology in this process. By examining AI in emergency care, we provide valuable insights into how this epistemic technology reconfigures clinical uncertainty, offering significant theoretical and practical implications for the integration of AI in healthcare. © 2024 The Authors

A digital transformation of Swedish healthcare is currently taking place, and artificial intelligence (AI) is meant to solve many of the healthcare sector's challenges. The objective of this paper is to describe and analyze how the boundaries around the physicians' work could change when AI is implemented in healthcare and what boundary work actors on different levels in a healthcare system conduct. We conducted 26 semi-structured interviews with healthcare leaders and 18 with healthcare managers and professionals. The result shows that the leaders, healthcare managers, and healthcare professionals describe different types of boundary work in regard to the implementation of AI. The implementation of AI in healthcare could change the boundaries around the healthcare professionals’ work and generate new kinds of boundary work that could affect the implementation. These findings can inform both practice and policy.