Artificial intelligence (AI) is revolutionizing healthcare by introducing novel treatments and applications, thereby transforming the sector. However, the complexity, ambiguity, and inherent risks associated with AI can create tensions for healthcare workers that may result in stress, anxiety, and discomfort when they make decisions. These tensions are paradoxical in nature as they may present conflicting demands that can persist over time and develop into seemingly irrational situations. Understanding how these paradoxical tensions affect healthcare workers' responses to AI is crucial in addressing their concerns. This study investigates the role of paradoxical tensions and the paradoxical mindset in shaping healthcare workers' responses to AI. The study examines how these two factors influence individuals' intention to adopt AI systems and tools and evaluates the users' satisfaction with them. Using a quantitative survey design, data were collected from 357 healthcare workers. The results, based on regression analysis, indicate that paradoxical tensions positively influence both individuals' intention to adopt AI systems and tools and their satisfaction with the current use of AI systems and tools. The results also indicate that the paradoxical mindset positively mediates these relationships. © 2024 The Authors

Purpose: The utilization of virtual agents, particularly chatbots, within healthcare and medical contexts is witnessing exponential growth owing to their capacity to provide comprehensive support to patients throughout their healthcare journey, by reshaping the healthcare business processes. Such transformation in healthcare service delivery processes is enabled by those digital entities able to offer a preliminary screening and consultation platform, facilitating patients’ interactions with real medical professionals. However, when redesigning processes through the integration of new technologies, particular attention to the reactions of end users cannot be neglected. Thus, the purpose of this paper is investigating how both chatbots' features and patients' individual differences may shape a redesigned/renewed service in the healthcare sector.

Design/methodology/approach: Through two experimental studies (Study 1 and Study 2), we examined the impact of chatbot tone of voice (formal vs unformal) on patients’ behavioral responses, particularly their intention to use.

Findings: Our investigation shed light on chatbots’ characteristics in terms of perceived warmth, denoting the friendliness and empathy conveyed by the chatbot, and competence, reflecting its effectiveness in addressing user queries or tasks, when used to reshape the service delivery process; Moreover, we also shed light on the moderating role of emotional receptivity seeking, indicating that the emotionality and non-verbal communication between doctor and patient, cannot be overlooked even in innovative digital environments.

Practical implications: Managers and marketers could leverage insights from this study to tailor chatbot interactions, optimizing tone of voice to enhance patient engagement and satisfaction. By focusing on perceived warmth and competence, they can design more effective digital health solutions. Additionally, recognizing the role of emotional receptivity can guide strategies for integrating chatbots in a way that maintains a human touch in patient communications.

Social implications: Findings importantly underscore the relevance of chatbot in improving patient care, making digital interactions more empathetic and responsive. This relevance extends to business process management by demonstrating how integrating emotionally intelligent chatbots may contribute to better service delivery on the basis of personalized and effective healthcare experiences.

Originality/value: The originality of this paper is about the relevance of considering chatbots’ and final users’ characteristics to strategically plan healthcare services process redesign. Indeed, it examines chatbots' perceived warmth and competence in reshaping service delivery processes. Additionally, it highlights the moderating role of emotional receptivity seeking, emphasizing the importance of emotional communication in digital healthcare environments. © 2025, Emerald Publishing Limited.

Background: The purpose of this paper is to explore on the main barriers related to the Internet of Things devices adoption in healthcare, with specific concern to developing countries.

Methods: A qualitative research approach with the systematic combination method has been adopted, considering an Indian hospital as a research setting. Semi-structured interviews were carried out as part of the data collection process

Results: The study helped us identify some of the main factors affecting IoT adoption in the hospital, categorised under three different sections: 1) technological barriers, 2) organisational barriers, and 3) environmental barriers. Findings suggest that IoT adoption barriers in hospitals are related to adoption challenges mainly focused on technological acceptance, complexity, organisational behaviour, lack of expertise and infrastructure, lack of stringent regulations and standards, and finally, security and privacy concerns.

Conclusion: Thus, this research makes a unique contribution for researchers and hospital managers in developing countries to understand the common barriers behind the IoT adoption process and to understand the steps to be taken to overcome these barriers. © 2025, Journal of Health Informatics in Developing Countries.

A growing and aging population provides challenges for the healthcare sector, generating higher healthcare costs, and ineffective work process that results in long patient queues and problems with recruiting and retaining healthcare professionals. Artificial intelligence (AI) is considered as one means to provide efficient processes for healthcare professionals, e.g. in diagnostics and treatment recommendations. However, research has shown that there are many obstacles to successfully introducing and using AI applications in healthcare, especially by focusing on the organizational level. However, individual healthcare professionals have an important role to play in the transition towards information driven healthcare. 

Therefore, we address the healthcare professionals' perception of the usefulness and value of AI applications, as well as challenges and considerations of this new technology. 

The study is based on an exploratory approach with more than 350 healthcare professionals in Sweden, carried out beginning of 2024. The questionnaire includes perceptions of the use of AI and identifies potential challenges that need to be addressed. The respondents include doctors (92%) and nurses (8%). The sample consists of answers from 221 (62%) male and 136 (38%) female respondents. Most of the respondents work in public hospitals (54%) and health centers (20% public and 14% private). Several AI applications are used by healthcare professionals, spanning from administrative work reduction to new insights in the analysis of complex cases.

Thematic analysis is conducted to create a model of perception of usefulness, values and problems (barriers). The analysis includes a stepwise analysis to identify patterns and themes.

The  results from the project provide insights into how the introduction of AI applications in healthcare changes the work of healthcare professionals and the perceived challenges that need to be addressed to improve their work by using AI. To some extent, implementation and use is based on healthcare professionals’ interest in using new advanced technology but for others the decision to adopt AI is primarily based on formal decisions within the organization. Respondents that have been using AI for at least six months, indicate AI supports decision making, with the main benefit consisting of a more effective and faster work process, while other respondents do not perceive any changes. A surprising result is that healthcare professionals have identified the possibility to test and evaluate new ideas and more complex cases. One interpretation is that AI has made the workload easier, which may allow for more innovative work. Another interpretation is that their experience-based knowledge is augmented by AI, and this makes it possible for them to handle more complex cases.   However, others experience a learning paradox – challenging to find time and learn how to use the technology, while at the same time adopting by testing AI applications.

Conclusions drawn from the ongoing study provide insights on the transformation phase towards implementing and using AI applications in healthcare.

Background: Healthcare is undergoing a digital transformation as advanced analytics, artificial intelligence (AI), and connected devices revolutionize clinical decision-making, care delivery, and patient outcomes. Digital technologies, particularly AI, have created unprecedented opportunities for value creation through improved diagnostics, automated workflows, and data-driven care. Despite this potential, the adoption of digital technologies in healthcare remains slower than in other industries. Multiple factors contribute to this gap, with value creation emerging as central to adoption decisions. While individual factors - such as healthcare professionals' responses to new technologies - significantly influence adoption, medical technology (MedTech) firms play an essential role in facilitating value creation through digitalization. Previous research has largely overlooked this complexity, particularly the interplay between healthcare professionals' adoption decisions and MedTech firms' capabilities. 

Purpose: The purpose of this doctoral thesis is to explore how healthcare professionals adopt digital technologies and how MedTech firms acquire capabilities to facilitate digitalization and value creation in healthcare. 

Method: To fulfill the overall purpose of this thesis, five independent papers were developed. The papers comprise one qualitative descriptive study, one sys- tematic literature review, one exploratory qualitative study, one embedded case study, and one survey. The data collection is based on exploratory and semi-structured interviews, workshops, observation, and questionnaires. The data analysis follows a thematic analysis technique and linear regression analysis. 

Findings: The findings of this thesis indicate that digitalization and value creation in healthcare emerge through dynamic interactions between healthcare professionals and MedTech firms. Healthcare professionals, as technology adopters, evaluate multiple value dimensions (cost-sacrifice, instrumental, hedonic, and symbolic) that shape their attitudes toward digital technologies. They engage in facilitation activities to manage resistance to change and develop paradoxical mindsets to navigate tensions arising from technological transitions. MedTech firms acquire the necessary capabilities through formal, vii semi-formal, and informal mechanisms to facilitate digitalization. These capabilities - health-related, data-driven, and social capabilities - are primarily accessed through external actors. Value co-creation occurs through structured encounters between healthcare professionals and MedTech firms, where they share resources and knowledge, align expectations, and collaborate to enhance technology adoption and value realization. This interplay creates a foundation for successful healthcare digitalization while ensuring technologies meet clinical needs and create sustainable value. 

Despite the advances in modern medicine, the use of data-driven technologies (DDTs) to prevent surgical site infections (SSIs) remains a major challenge. Scholars recognise that data management is the next frontier in infection prevention, but many aspects related to the benefits and advantages of using DDTs to mitigate SSI risk factors remain unclear and underexplored in the literature. This study explores how DDTs enable value creation in the prevention of SSIs. This study follows a systematic literature review approach and the PRISMA statement to analyse peer-reviewed articles from seven databases. Fifty-nine articles were included in the review and were analysed through a descriptive and a thematic analysis. The findings suggest a growing interest in DDTs in SSI prevention in the last 5 years, and that machine learning and smartphone applications are widely used in SSI prevention. DDTs are mainly applied to prevent SSIs in clean and clean-contaminated surgeries and often used to manage patient-related data in the postoperative stage. DDTs enable the creation of nine categories of value that are classified in four dimensions: cost/sacrifice, functional/instrumental, experiential/hedonic, and symbolic/expressive. This study offers a unique and systematic overview of the value creation aspects enabled by DDT applications in SSI prevention and suggests that additional research is needed in four areas: value co-creation and product-service systems, DDTs in contaminated and dirty surgeries, data legitimation and explainability, and data-driven interventions. © 2023, The Author(s).

Num ambiente cada vez mais competitivo, a satisfação do consumidor se tornou um dos principaisobjetivos das organizações que desejam criar e manter vantagem competitiva. Nesse cenário, paraconquistar a satisfação e a lealdade do consumidor, é necessário avaliar sua percepção em relação aqualidade dos serviços ofertados. Assim sendo, este estudo objetiva avaliar a satisfação dos usuáriosde Uber e táxi no Brasil a partir da percepção de qualidade dos serviços. Um questionário online foidesenvolvido com base na escala Servqual e contou com a participação de 442 respondentes. Osresultados da pesquisa indicam que os usuários, tanto do Uber quanto de táxi, consideram-sesatisfeitos com a qualidade dos serviços oferecidos; sendo que para os usuários de Uber os atributosmais importantes estão relacionados à “Usabilidade”, enquanto para os usuários de táxi os aspectosmais relevantes para a satisfação referem-se a dimensão dos “Tangíveis”.

This study investigates the opportunities that smart mobility offers as a fundamental part of the transition to a smart city. The study comprises a case study of the city of Taranto, Italy. The data collection was based on semi-structured interviews with policymakers with expertise in transport systems. Findings confirm the relevance of smart mobility as a primary fundamental factor to accelerate and begin the transition to a smart city, and how this transition requires a joint effort by both public actors and companies involving coherent, coordinated, and advantageous territorial development strategies aimed to achieve environmental sustainability and distributive equity.

The use of artificial intelligence (AI) is changing how manufacturing firms create new value, shifting their business models from product suppliers toward product- service systems (PSS) providers. To create value for customers and users, firms need to internally develop or externally access new or modified capabilities to be integrated into the development of PSS value propositions. Currently, the PSS literature does not systematically show which capabilities are complementary to the focal firm’s capabilities and from which actors they are acquired. Therefore, this study characterizes and explains the necessary complementary capabilities for MedTech firms to diversify into PSS, identify external actors, and describe which business activities MedTech firms use to attract and integrate external complementary capabilities. The research design was an embedded case study of a multinational MedTech firm with four PSS innovation cases. The findings show that the complementary capabilities in PSS development by MedTech firms consist of 1) health-related capabilities; 2) data-driven capabilities; and 3) social capabilities. To attract and integrate these capabilities, MedTech firms rely on negotiations and formal contracts, additional benefits to current clients, after- sales contact and remote support, and exploration of partners’ networks and reputations. By drawing on the PSS, servitization, and capability-based views of the firm, the paper explains the limits to the internalization of complementary capabilities. 

Experts claim for more studies on Theory of Multiple Intelligences in higher education classrooms. There is a lack of information on the characteristics of multiple intelligence in universities in developing countries, such as Brazil, as they can assist in the education of students in a wide variety of fields. This study aims to analyze and compare the types of multiple intelligences among bachelor students of Business Administration programs in private universities. We conducted a quantitative study based on survey with students from two private universities in the southern Brazil. The results indicated that the academic profile of both programs has similarity in the average frequency of most of the identified intelligences. The intelligences identified that showed statistically significant differences between academics are: logical-mathematical, interpersonal, musical and naturalistic. In general, the most developed multiple intelligences are: logical mathematical, interpersonal, intrapersonal and bodily-kinesthetic. In addition, the least developed are: spatial, linguistic, musical and naturalistic.