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This research aims to explore whether or how organizations adopt people analytics (PA), its value and potential socio-technical factors that can enable or hinder PA projects by disrupting and reshaping human resource management. We do this by focusing on the Italian context.

We conduct a scoping review of data collected between 2018 and 2022 via Google Alerts (GA), a content change detection and notification service that is gaining popularity in scholarly research.

Our findings suggest that the diffusion of PA applications in Italy, especially those of a descriptive nature, is growing. Most of the existing PA applications are positioned in a positive technocratic light, envisioning the value of PA for both employees and organizations. The value for the latter appears to be direct, while the value for employees is realized through organizational initiatives. The findings also suggest that while enablers can vary between PA application types, the barriers, especially technological and environmental, are generic for both descriptive and predictive/prescriptive PA applications.

Theoretically, we propose a framework for analyzing PA applications, their values, enablers and barriers. Methodologically, we present and describe in detail a novel approach, drawing on GA that can be used to study PA in specific contexts. Practically, our study serves as a helpful point of reference for managers planning or implementing PA in Italy, for benchmarking PA in Italy over time and for comparative international studies.

This study aims to explore the effects of intellectual capital (IC) on the occurrence of a modified audit opinion decision. The authors expect that high IC intensive firms are positively associated with the occurrence of a modified audit opinion since they are associated with an increased business risk and are more likely to exhibit issues concerning their financial health and stability.

Using a data sample of 423 listed firms from Greece, Italy, Spain and Portugal over a 10-year period, the authors estimated a logistic regression model to examine the effects of IC on the probability that a modified audit opinion is issued. The authors used organizational capital as a measure of a firm’s intensity on IC.

Empirical findings indicate a significant and positive relationship between the IC and the likelihood of a firm receiving a modified audit opinion decision.

This study expands prior literature by exploring the predictive ability of IC on the likelihood of a firm receiving a modified audit opinion decision.

The study seeks to understand the possible opportunities that Industry 5.0 might offer for various aspects of inclusive sustainability. The study aims to discuss existing perspectives on the classification of Industry 5.0 technologies and their underlying role in materializing the sustainability values of this agenda.

The study systematically reviewed Industry 5.0 literature based on the PRISMA protocol. The study further employed a detailed content-centric review of eligible documents and conducted evidence mapping to fulfill the research objectives.

The advancement of Industry 5.0 is currently underway, with noteworthy initial contributions enriching its knowledge base. Although a unanimous definition remains lacking, diverse viewpoints emerge concerning the recognition of fundamental technologies and the potential for yielding sustainable outcomes. The expected contribution of Industry 5.0 to sustainability varies significantly depending on the context and the nature of underlying technologies.

Industry 5.0 holds the potential for advancing sustainability at both the firm and supply chain levels. It is envisioned to contribute proportionately to the three sustainability dimensions. However, the current discourse primarily dwells in theoretical and conceptual domains, lacking empirical exploration of its practical implications.

This study comprehensively explores diverse perspectives on Industry 5.0 technologies and their potential contributions to economic, environmental and social sustainability. Despite its promise, the practical evidence supporting the effectiveness of Industry 5.0 remains limited. Certain conditions are necessary to realize the benefits of Industry 5.0 fully, yet the mechanisms behind these conditions require further investigation. In this regard, the study suggests several potential areas for future research.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

Despite growing emphasis on green skills, innovation, and sustainable livelihoods, research remains limited in the informal economy, particularly in developing countries. This study investigates gaps in green skills training, innovations and livelihoods among informal metal fabricators, shedding light on the challenges and opportunities within this sector. Specifically, the study critically assesses the potential for upskilling informal metal fabricators through Technical and Vocational Education and Training (TVET) institutions and university innovation hubs.

Employing a qualitative interpretive methodology, we conducted 40 key informant interviews with small-scale informal metal fabricators operating in Magaba and Gaza home industries, two of Harare’s largest home industries in Zimbabwe. Subsequent key informant interviews were held with TVET educators and innovation hub lecturers. Observations were carried out over a period of three months to comprehensively explore the issues under investigation.

Gender disparities persist within informal innovation spaces, with women making strides in the traditionally male-dominated field of metal fabrication. However, challenges such as prejudices, stigma, ridicule and abuse hinder women’s full participation in manufacturing processes, often relegating them to less physically demanding roles like customer engagement and product marketing. Inequities in support for green skills training were evident, with the innovation hub model primarily catering to formally educated youth in universities, neglecting the active involvement of notable informal innovators with limited formal education. While a gradual shift toward renewable energy sources is observable in the informal economy, government-owned TVET institutions show minimal or no adjustments in course content to incorporate essential green skills. In light of the findings, the study proposes measures to ensure equitable green skills training, innovation and the promotion of sustainable livelihoods in the informal metal fabrication sector.

The findings of this study represent a novel contribution the gaps in green skills training in the informal economy and how these inform reforms for vocational learning and training practices and the incubation of innovations.

The proliferation of industry platforms has disrupted several industries. Firms adopting a platform business model have experienced a substantial expansion in size and scale, positioning themselves as the foremost valuable entities in market capitalization. Over the past two decades, there has been a substantial expansion in the body of literature dedicated to platforms, and different streams of research have emerged. Despite considerable efforts and the significant progress made in recent years toward a comprehensive understanding of industry platforms, there is still room for further harnessing the field’s diversity. As a result, the aim of this article is to examine the field’s structure, identify research concerns and provide suggestions for future research, thereby enhancing the overall understanding of industry platforms.

We conducted a thorough examination of 458 articles on the topic using bibliometric methods and systematic review techniques.

Through co-citation analysis, we identified five distinct clusters rooted in various bodies of literature: two-sided markets, industry platforms, digital platforms, innovation platforms and two-sided networks. Furthermore, the examination of these five clusters has revealed three key areas that demand further consideration: (1) terminologies, (2) classifications and (3) perspectives.

While previous reviews have provided valuable insights into the topic of industry platforms, none have explored the structure of the field so far. Consequently, as a first step toward advancing the field, we uncover the structure of the literature, identifying three major areas of concern. By addressing these concerns, our goal is to converge different clusters, thereby harnessing the diversity in the field and enhancing the overall understanding of industry platforms.

Studies of inter-organizational relationships have traditionally overlooked the human resource management (HRM) field, with most research focusing on collaborations in the technical domain. This study endeavors to explore the impact of organizational human resources (HR) collaborations on HR innovativeness, drawing on theories about organizational learning capabilities to explain this connection. By analyzing the synergies arising from inter-organizational HR collaborations, this study aims to seek to shed light on the potential for HRM to contribute to organizational performance and foster innovation.

The study is based on a quantitative survey conducted among 326 Dutch companies. The survey aims to find out whether these companies collaborate with other organizations on HR-related issues, the extent to which they renew their HRM function, and whether they apply organizational learning practices. The data collected for the survey are analyzed using Hayes PROCESS macro to investigate mediation effects.

As per the study, HR collaboration results in innovation. The research suggests that collaborating with HR across different organizations significantly contributes to HR innovation. This relationship can be explained by the inter-organizational learning practices that organizations adopt. Therefore, when organizations collaborate with each other, they learn from each other, which enhances their learning capabilities and ultimately leads to HR innovation.

This study delves into the extent to which organizations collaborate on HR-related issues, which is a relatively new field. Moreover, it contributes to the research on the connection between inter-organizational relationships and innovation by showing how much of it is explained by organizational learning.

This study applies the target similarity model to examine the effects of servant leadership on supervisor commitment and supervisor citizenship behavior. The mediating role of supervisory commitment is explored to determine the relationship between servant leadership and supervisor citizenship behavior. The difference in supervisor gender is examined in the linkage between servant leadership and supervisory commitment.

The data were collected through a survey of 478 salespeople in the retail industry. Structural equation modeling (SEM) techniques were used to verify the hypotheses of this study.

The findings showed significant support for the direct and indirect effects of servant leadership on supervisor commitment and supervisor citizenship behavior. Furthermore, the positive relationship between servant leadership and supervisory commitment was stronger among female supervisors than male supervisors.

Due to the scarcity of studies conducted on the linkages of servant leadership, supervisory commitment and supervisory citizenship behavior, this study theoretically and empirically contributes to the leadership literature as it is the first study to investigate these direct and indirect relationships. Similarly, this study examined gender differences in servant leadership to fill the gap in the research field.