Ricardo Pérez Martínez

Since time immemorial, the phenomenon of leadership and its understanding has attracted the attention of the business world because of its important role in human groups. Nevertheless, for years efforts to understand this concept have only been centred on people in leadership roles, thus overlooking an important aspect in its understanding: the necessary moral dimension which is implicit in the relationship between leader and follower. As an illustrative example of the importance of considering good morality in leadership, an empirical study is conducted in which a good performance of the "leader-follower" relationship is reflected when individuals perceive ethical leadership in higher hierarchical managerial levels. To be precise, findings of this study demonstrate that follower job response is improved through an ethics trickle-down partial effect from the Top Manager to the immediate supervisor, and also reveal both key aspects and managerial level on which the practice of ethical leadership should rest upon to have a stronger effect on the follower positive job response. Practical implications of these findings and directions for future research are finally presented

Three ethics program components, a code of ethics, ethics training initiatives and ethics-oriented performance appraisal content, were examined for their relationship to ethical intent using a sample of 525 employees from the Spanish financial services industry. As expected, all three components contributed to the prediction of ethical intent. Importantly, clusters of employees who reported experiencing distinct combinations of the program components were identified and compared for their level of ethical intent. Employees who perceived all three components to be strongly implemented reported significantly higher levels of ethical intent relative to those who viewed the components as either all weakly implemented or not present. Combinations including training initiatives plus one other element had a similar impact to the fully implemented approach. Contrary to expectations, ethics-oriented performance appraisal content did not relate more strongly to ethical intent than codes of ethics

Nowadays there is a growing interest in business ethics, both in academia and professionally. However, moral lapses continue to happen in business activities, leading academicians and professionals to rethink what is being done and reinventing new strategies to successfully manage ethics in business organisations. Thus, whereas efforts to promote ethics are basically oriented to using and developing explicit, written formal mechanisms, the literature suggests that other instruments are also useful and necessary to achieve this. Thus, studying the role of the Human Resource Management (hereafter, HRM) in promoting ethics is an emerging research topic due to the heavy influence that HRM practices are thought to have on employees. This paper is aimed at developing a thorough analysis of HRM's role in promoting ethics, and specifically at focusing on one of its practices, training. As an illustrative example of the utility of this practice, an empirical study was conducted on a range of Spanish banking companies in which an impact was found on the employees' ethical behaviour when ethics training was being provided inside the organisation. Finally, the practical implications of these findings and directions for future research are presented

Meeting 5G high bandwidth rates, ultra-low latencies, and high reliabilities requires of network infrastructures that automatically increase/decrease the resources based on their customers’ demand. An autonomous and dynamic management of a 5G network infrastructure represents a challenge, as any solution must account for the radio access network, data plane traffic, wavelength allocation, network slicing, and network functions’ orchestration. Furthermore, federation among administrative domains (ADs) must be considered in the network management. Given the increased dynamicity of 5G networks, artificial intelligence/machine learning (AI/ML) solutions are strong candidates able to learn, and take quick provisioning decisions upon fast changes in network conditions. Therefore, this chapter presents an analysis of the state-of-the-art solutions for 5G networks’ management, where AI/ML solutions are discussed and compared with traditional methods. Additionally, the chapter provides a technology overview of both standards, and existing solutions regarding the 5G network management, and directions toward the integration of AI/ML in 5G networks.