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Worldwide academia is going through a major transformation because of Open Science and Recognition and Rewards movements that are linked to big societal challenges such as climate change, digitalization, growing inequality, migration, political instability, democracies under threat and combinations of these challenges. The transformations affect the human resource management (HRM) and talent management of universities. The main focus of this chapter is on collaborative innovation and the way universities participate in coalitions and strategic alliances on national and international levels. These platforms not only discuss the transformations and support the academic changes but also act as talent pools and talent exchange. This chapter provides an overview of the current state of affairs with respect to Open Science and Recognition and Rewards in academia. Next, a theoretical foundation is presented on the concepts of collaborative innovation, coopetition and HRM innovation in general. The leaders or leading organizations in the HRM innovation models often can’t make it happen on their own, in particular in highly institutionalized contexts such as academia. The legitimacy of transformations requires coalitions of the willing and therefore strategic alliances on different levels. The coalitions in academia can also contribute to academic talent management through sectoral transformations (see Recognition and Rewards) and through the way these coalitions operate.

The purpose of the article is to examine the concepts of knowledge management strategies, innovation and service quality in information technology companies that have research and development (R&D) departments in the technoparks of research universities.

The research was carried out in information technology companies with R&D departments in the technoparks of universities. Due to the “innovation” focus of the research, 302 engineers were selected by random sampling from engineers working in information technology companies in technoparks, and the prepared scale was sent to them via e-mail. In total, 302 units of data were subjected to path analysis and mediation effect analysis using the SmartPLS program.

In the research, it is supported by hypotheses that both knowledge management strategies and organizational innovation have a positive effect on the success of service quality and product innovation in information technology companies with R&D departments. At the same time, it can be explained as a result of analysis that innovation capability has both an independent and an intermediary variable effect.

Considering the limitations of the research, it is not correct to generalize the results of the analysis because the research was conducted only in information technology companies located in technoparks, and the data were collected from engineers working in these companies. For this reason, it is recommended that similar studies that are planned to be conducted in the future should do their research by taking this situation into account. At the same time, it is recommended to carry out future studies in different sectors and to bring the results obtained to the literature by comparing them.

The importance of information is increasing in technology-oriented companies where competition is increasing. Companies that cannot go beyond imitation or offer similar products and/or services cannot compete with their competitors in a competitive environment. The fact that companies can be successful in a competitive environment is supported by hypotheses as a result of the analysis that they need to develop organizational innovation and knowledge, as well as develop innovation capability at the same time.

The research is an original study in terms of examining the R&D departments of information technology companies operating in the technoparks of universities. Innovation and knowledge management strategies are examined within the scope of the research model by collecting data from information technology companies with R&D departments.

The purpose of this study is to test the hypotheses proposed by Konadu et al. (2023) for the first time and provide empirical insight on the subject. Corruption concerns affect all economies, but those attempting to avoid foreign grants are especially vulnerable. Stakeholders in these economies have pushed for more honest public sector (PS) workers and better oversight of public funds in an effort to build a more trustworthy and efficient government to improve PS performance. Just as the mechanisms through which employee integrity (EI) influences work performance (WP) have not been proven empirically, neither has the effect of EI on WP in African economies. Also, how purposeful leadership (PL) interacts with EI to boost WP is yet to be empirically examined in the integrity literature.

This paper surveyed and analysed the responses of 875 workers across the three most corrupt large PS organisations in Ghana using Smart PLS 4. Perceived organisational support and contract fulfilment functioned as control factors influencing job satisfaction (JS, a mediator). Psychological need satisfaction and perceived procedural justice serve as control factors for organisational identification (OI, an additional mediator). Education, tenure, job position, sex and age were used as control variables in WP. Product indicator and variance accounted for (VAF) methods were used to estimate the impacts of moderation and mediation, respectively. A 5% level of significance was determined.

As hypothesised, this study found that EI and WP had a significantly positive connection (ß = 0.119, p = 0.026), and both JS (VAF = 25.16%) and OI (VAF = 39.59%) partially mediated this connection. Moreover, PL positively moderated the EI–JS (ß = 0.155, p = 0.000) and EI–OI (ß = 0.095, p = 0.000) connections.

This paper affords empirical insight on the EI–WP relationship, how this relationship is mediated and how the EI–JS and EI–OI relationships are amplified. In this context, it sheds light on new ways in which EI and WP in the PS are improved. In addition, this paper provides a roadmap for forthcoming academics to test the hypotheses in diverse PS contexts globally to triangulate the results.

Leadership in PS organisations must maintain a “values-grounded approach” to all parts of human resource (HR) practices, including hiring, performance reviews, leadership enhancement programmes, training and promotions, if they are to attract, develop and retain employees who stand for the sector’s ethics and beliefs.

This research gives African nations proof that enhancing EI in the PS is important, and it lays out the many ways in which EI transforms into WP. It also draws attention to the challenges that purposeful leaders may help alleviate and the opportunities that they may present.

To the best of the authors’ knowledge, the hypotheses put forward in the conceptual research by Konadu et al. (2023) are tested empirically for the first time in this study. It also adds to the empirical literature that already exists on EI, JS, OI, WP and PL in the PS. This contributes to the disciplines of integrity, performance and leadership by enhancing theoretical frameworks and expanding upon existing knowledge.

In order to meet the different quality of service (QoS) requirements of vehicle-to-infrastructure (V2I) and multiple vehicle-to-vehicle (V2V) links in vehicle networks, an efficient V2V spectrum access mechanism is proposed in this paper.

A long-short-term-memory-based multi-agent hybrid proximal policy optimization (LSTM-H-PPO) algorithm is proposed, through which the distributed spectrum access and continuous power control of V2V link are realized.

Simulation results show that compared with the baseline algorithm, the proposed algorithm has significant advantages in terms of total system capacity, payload delivery success rate of V2V link and convergence speed.

The LSTM layer uses the time sequence information to estimate the accurate system state, which ensures the choice of V2V spectrum access based on local observation effective. The hybrid PPO framework shares training parameters among agents which speeds up the entire training process. The proposed algorithm adopts the mode of centralized training and distributed execution, so that the agent can achieve the optimal spectrum access based on local observation information with less signaling overhead.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

The purpose of this paper is to understand how those involved in executive pay determination in large publicly quoted UK businesses see the role of diversity within remuneration committees (Remcos) as enabling the input of different perspectives, which can enhance their decision-making and potentially improve pay outcomes.

Qualitative, semi-structured interviews were undertaken with 18 high-profile major-enterprise decision-makers and their advisers, i.e. non-executive directors (NEDs) serving Remcos, institutional investors, executive pay consultants and internal human resources (HR) reward specialists, together with data from three focus groups with 10 further reward management practitioners.

Remco members recognise the benefits of social category/demographic diversity but say the likelihood of increasing this is low, given talent pipeline issues. The widening of value diversity is considered problematic for Remcos’ functioning. Informational diversity is used as a proxy for social category/demographic diversity to improve Remcos’ decision-making on executive pay. While the inclusion of members from wider social networks is recognised as potentially bringing a different informational perspective, the social character of Remcos, reflecting their elite nature and experience of wealth, appears ingrained.

Our original contribution is to extend the application of upper echelons theory in the context of Remco decision-making to explain why members do not welcome widening informational diversity by appointing people from different social networks who lack value similarity. Instead, by drawing views from employees, HR acts as a proxy for social network informational diversity. The elite, upper-echelons nature of Remco appointments remains unchanged and team functioning is not disrupted.

This paper investigates how gender, ethnicity, and network membership interact to influence how small and medium-sized enterprise (SME) owner-managers become aware of finance support programmes developed by government policy and/or support schemes advanced by the banking industry.

Drawing on expectation states theory (EST), we develop eight sets of hypotheses and employ the UK SME Finance Monitor data to test them using bivariate probit regression analysis.

In general, network membership increases awareness, but more so for government programmes. We also find no differences between female and male owner-managers when in networks. However, we identify in-network and out-network differences by ethnicity, with minority females seemingly better off than minority males.

Business networks are better for disseminating government programmes than industry-led programmes. For native White women, network membership can enhance policy awareness advantage further, whilst for minorities, networks significantly offset the big policy awareness deficits minorities inherently face. However, policy and practice need to address intersectional inequalities that remain in access to networks themselves, information access within networks, and the significant out-network deficits in awareness of support programmes afflicting minorities.

This study provides one of the first large-scale empirical examinations of intersectional mechanisms in awareness of government and industry-led enterprise programmes. Our novel and nuanced findings advance our understanding of the ways in which gender and ethnicity interact with network dynamics in entrepreneurship.

This study aims to investigate the influence of inventors’ abilities to acquire external knowledge, provide broad and professional knowledge and patenting output (i.e. different types of inventors) on the formation of structural holes.

The authors collected 59,798 patents applied for and granted in the USA by 33 of the largest firms worldwide in the pharmaceutical industry between 1975 and 2014. A random-effects tobit model was used to test the hypotheses.

The inventors’ ability to acquire external knowledge contributes to the formation of structural holes. While inventors’ ability to provide broad knowledge positively affects the formation of structural holes, their ability to provide professional knowledge works otherwise. In addition, key inventors and industrious inventors are more likely to form structural holes than talents.

The results identify individual factors that affect the formation of structural holes and improve the understanding of structural hole theory. This study is unique in that most scholars have studied the consequences of structural hole formation rather than their antecedents. Studies on the origin of structural holes neglect the effect of inventors’ knowledge abilities and patenting output. By addressing this gap, this study contributes to a more comprehensive theoretical understanding of structural holes. The results can guide managers in managing structural holes in accordance with inventors’ knowledge abilities and patenting outputs, which optimize the allocation of network resources.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.