FNEGE MEDIAS

Pendant plus de 40 ans, une mauvaise gestion des déchets en Italie a permis à la Mafia de les éliminer illégalement, provoquant une crise sanitaire majeure et des taux de cancer en hausse. Malgré les interventions tardives de l’État, les choix économiques ont souvent prévalu sur la protection de l’environnement et des populations. Cette crise révèle que la gestion des déchets est avant tout une question de pouvoir et de justice sociale, touchant de manière inégale les communautés.

More organizations use AI in the hiring process than ever before, yet the perceived ethicality of such processes seems to be mixed. With such variation in our views of AI in hiring, we need to understand how these perceptions impact the organizations that use it. In two studies, we investigate how ethical perceptions of using AI in hiring are related to perceptions of organizational attractiveness and innovativeness. Our findings indicate that ethical perceptions of using AI in hiring are positively related to perceptions of organizational attractiveness, both directly and indirectly via perceptions of innovativeness, with variations depending on the type of hiring method used. For instance, we find that individuals who consider it ethical for organizations to use AI in ways often considered to be intrusive to privacy, such as analyzing social media content, view such organizations as both more innovative and attractive.

The aim of this paper is to explore how a number of processes combined to create the micro-level strategies and procedures that resulted in the deadliest and most tragic forest fire in Portuguese history.

Many start-ups do not survive the first few years of business. Previous studies suggest that networks play a role in start-ups’ success, but this positive effect has limits. The purpose of this paper is to answer the call for a better understanding of the dark side of networks and the variables that condition the likelihood of start-ups’ survival.

Artificial intelligence is already transforming lives and organizations. It brings a huge potential, for example, to achieve hyper-performance. Which is not about adding more trainings. But rather finding and removing obstacles from human minds. And artificial intelligence can facilitate that efficiently. It can help us to learn more about our own intelligence. Thus, giving us a unique chance to finally re-unite both intelligences.

It is a state of performance when all unnecessary human thought is minimized or completely suppressed. Such as bad judgments, distracting thoughts, subjective biases, bad decisions, etc. For example, employees may be reluctant to accept artificial intelligence. That means there’s something in their mind that stops them. That something is the root cause.

The existing literature has highlighted the relevance of collective intelligence to bring about successful collaboration between Artificial Intelligence (AI) tools and employees, and to bring about results that are valued by the organisation.

Circular Economy (CE) practices have the potential to increase the sustainable, societal and environmental performance of organisations and therefore contribute to meeting the United Nations Sustainable Development Goals. The objective of this research is to examine the adoption of sustainable practices by small and medium-sized enterprises (SMEs) and its impact on their environmental and societal performance.

Our goal was to understand the effectiveness of a company in attracting its customer targets. To do this, we have developed a model that links a company’s marketing activities to the mix of customers who buy from the company. Most marketing models simply ask how a company’s marketing activities influence the number of customers who buy the brand. We wondered how a company’s marketing activities influence the types of customers who buy the brand.

Not-for-profit organizations have long faced the challenge of balancing budgets when they simultaneously seek to retain and recruit new donors. In principle, existing donors can be targeted based on their previous donation data. However, for new donors, this data is not available or may be difficult to obtain from secondary sources. What should non-profit organizations do? We suggest 2 alternatives.