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This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a two-stage trajectory of exploration and development followed by dissemination and adoption. To illuminate the transition from the first to the second stage, we use prospect theory (PT) to offer insights into the effects of risk and uncertainty on individual decision-making, which potentially lead to partially irrational choices. The primary objective is to discern whether clinical decision support systems (CDSSs) can serve as effective means of “cognitive debiasing”, thus countering the perceived risks.

This study presents a comprehensive systematic literature review (SLR) of the adoption of clinical decision support systems (CDSSs) in healthcare. We selected English articles dated 2013–2023 from Scopus, Web of Science and PubMed, found using keywords such as “Artificial Intelligence,” “Healthcare” and “CDSS.” A bibliometric analysis was conducted to evaluate literature productivity and its impact on this topic.

Of 322 articles, 113 met the eligibility criteria. These pointed to a widespread reluctance among physicians to adopt AI systems, primarily due to trust-related issues. Although our systematic literature review underscores the positive effects of AI in healthcare, it barely addresses the associated risks.

This study has certain limitations, including potential concerns regarding generalizability, biases in the literature review and reliance on theoretical frameworks that lack empirical evidence.

The uniqueness of this study lies in its examination of healthcare professionals’ perceptions of the risks associated with implementing AI systems. Moreover, it addresses liability issues involving a range of stakeholders, including algorithm developers, Internet of Things (IoT) manufacturers, communication systems and cybersecurity providers.

Globally, co-production is of great significance in promoting neighborhood regeneration. However, in the Chinese context, characterized by a governance system with strong government discourse power and a tradition of passive public participation, co-production has faced significant challenges. To address issues, this paper aims to deeply understand the co-production behaviors and strategy choices of local governments and residents in the co-produced neighborhood regeneration.

An evolutionary game approach was utilized as the research method to analyze the interest interactions between the two parties, the differences and similarities in strategy choices and the influencing factors in government and resident-initiated project types, respectively. Chongqing was selected as the case area for empirical analysis, with data derived from project materials and in-depth interviews.

This study revealed dynamic interactions between local governments and residents, significant differences between the two project types regarding co-production levels, the positive role of residents' perceived loss and the effect of marginal benefits on critical influencing factors.

Drawing upon co-production theory, this paper elucidates how different levels of co-production are implemented and highlights the differences between the two types of neighborhood regeneration projects within governance systems characterized by strong state discourse power and a lack of public participation tradition. It addresses current issues and provides critical references for government policymakers and urban planners to make informed decisions and promote co-produced neighborhood rehabilitation projects.

Some firms excel at positively presenting their employer brand (talk), while others excel at effectively implementing human resource management (HRM) practices for the benefit of the employees (walk). Which approach is more effective? Focusing specifically on small and medium-sized hotels (SMHs), this study explores the relation of employer branding (EB) and HRM practices with organizational performance (OP).

Stratified sampling was used to identify 34 top management figures (owners, CEOs, and top HR managers) from SMHs across Greece. These individuals agreed to participate in in-depth, semi-structured, one-on-one interviews, focusing on their hotels’ HRM, EB, and organizational performance. The interviews were subjected to content analysis, further coupled with graphical exploration of the relations between the concepts under study.

The findings reveal a noteworthy pattern: high-performing SMHs tend to prioritize EB, particularly leveraging social media channels. This prioritization is further reinforced by the implementation of HRM practices, including extensive training and rewards. Clustering SMHs into four different levels based on their application of EB and HRM practices and the effect of these practices on OP, enables us to extend this study and gain valuable insights into the interplay of these factors.

This study highlights the need for practitioners to invest in HRM practices, especially in training and rewards, while giving due attention to EB, despite the potential resource limitations SMHs often face. Importantly, when basic levels of HRM are combined with high levels of EB, OP seems to be maximized.

Both HRM and EB deal with the employer – employee interaction, that’s why EB in most companies is the responsibility of the HRM department. Surprisingly, academic research has treated them as distinct fields, in isolation, ignoring their combined effects. This paper is the first to conceptualize EB as communication (“talk”) and HRM as practice (“walk”) and to thus propose that a complementarity relationship between these two dynamics may facilitate OP. Additionally, this study is the first to combine content analysis with a quantitative exploration to gain more holistic and valuable insights on the topic.