The aim of this paper is to analyze the real impact of ICT (Information and Communications Technology) skills mismatch on SME’s (small and medium enterprises) sustainable competitiveness in the presence of a guaranteed minimum wage. As part of public policies—the minimum wage needs to maintain a balance between increasing employment and not being a burden for the companies, leading them to bankruptcies, especially in times of disruptive change, in which economies have to be more resilient. The rapid progress in information and communication technologies has dramatically redefined rising unemployment as a result of skills mismatch. This paper aims to understand, on the one hand, whether there is a match between the supply demand of ICT skills, and how increasingly powerful digital technologies affect the skills, jobs, and demand for human labor. On the other hand, it aims to understand whether increasing productivity and a fair minimum wage could be an integrated approach for stimulating SME’s in increasing sustainable competitiveness.

The effectiveness of vocational education and training (VET) depends on the quality of interactions between the actors from the education and employment systems, which ensure the correspondence of skills supply and demand. This paper develops an instrument to measure education-employment linkage (EEL) by capturing EEL in each sub-process where these actors can and should interact. Surveying VET experts from 18 countries suggests that countries with dual VET have the highest EEL, while the included Asian countries score lowest in terms of EEL. The analysis further reveals that the three most important sub-processes are employer involvement in the definition of qualification standards; employer involvement in deciding the timing of curriculum updates; and the combination of workplace training with classroom education.

No published abstract

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when automating prediction leads to automating decisions versus enhancing decision-making by humans.

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a small summer workshop at Dartmouth College in 1956. Since then, AI applications made possible by machine learning (ML), an AI subdiscipline, include Internet searches, e-commerce sites, goods and services recommender systems, image and speech recognition, sensor technologies, robotic devices, and cognitive decision support systems (DSSs). As more applications are integrated into everyday life, AI is predicted to have a globally transformative influence on economic and social structures similar to the effect that other general-purpose technologies, such as steam engines, railroads, electricity, electronics, and the Internet, have had. Novel AI applications in the workplace of the future raise important issues for occupational safety and health. This commentary reviews the origins of AI, use of ML methods, and emerging AI applications embedded in physical objects like sensor technologies, robotic devices, or operationalized in intelligent DSSs. Selected implications on the future of work arising from the use of AI applications, including job displacement from automation and management of human-machine interactions, are also reviewed. Engaging in strategic foresight about AI workplace applications will shift occupational research and practice from a reactive posture to a proactive one. Understanding the possibilities and challenges of AI for the future of work will help mitigate the unfavorable effects of AI on worker safety, health, and well-being.

Unemployment data and a fast-changing environment have elicited reflections about the skills and personal traits required to face the increasing complexity brought by the 'glocal, liquid and networked' world in which workers operate. Several definitions and categorisations of the 'soft skills' are present in the literature, but there is a lack of scientific research on the topic and very few studies have been able to contribute significantly to the discussion on the practitioners' side. A literature review addressing and structuring this issue is presented in this article and the authors propose a preliminary list of relevant soft skills to enter the job market in order to lay the foundations for a comprehensive conceptual study. As a first step, a pilot study was carried out to validate the list of 22 soft skills. It was ranked and validated by a panel of Italian HR managers. Results confirmed that the development of soft skills is a top priority on the agenda of Italian HR managers and, in particular, teamwork, communication, results orientation, and learning skills (9%) are felt to be primary skills when assessing young graduates.

The media and popular business press often invoke narratives that reflect widespread anxiety that robots may be rendering humans obsolete in the workplace. However, upon closer examination, many argue that automation, including robotics and artificial intelligence, is spreading unevenly throughout the labor market, such that middle-skill occupations that do not require a college degree are more likely to be affected adversely because they are easier to automate than high-skill occupations. In this article, the author examines the effect of industrial robots on occupations in the United States in 2010 and 2015. Results from regression models indicate that an increase in industrial robots is associated with increases in high-skill and some middle-skill occupations but not for other types of occupations. These findings may indicate the ushering in of a new era in which robots are more technologically advanced and able to collaborate better with human employees.

This article investigates how educational level, job-related skills and employers' support for competence development jointly determine Norwegian employees' expectations of maintaining employment and career advancement. The data were collected in 2010 and 2013, and they comprise a representative sample of Norwegian employees. In contrast to previous research on self-perceived employability, this study divides expectations of advancement and continued employment. The results show that these are different measures of labour market success. While education is significantly correlated with both measures, the employer's support for competence development is important for expectations of career advancement, especially among the highly educated, whereas the job-skills match is most relevant for the expectation of maintaining employment.

This paper examines the effectiveness of active labour market policies (ALMPs) in improving labour market outcomes, especially of low-skilled individuals, by means of a pooled cross-country and time series database for 31 advanced countries during the period 1985-2010. The analysis includes aspects of the delivery system to see how the performance of ALMPs is affected by different implementation characteristics. Among the notable results, the paper finds that ALMPs matter at the aggregate level, but mostly through an appropriate management and implementation. In this regard, sufficient allocation of resources to programme administration and policy continuity appear to be particularly important. Moreover, start-up incentives and measures aimed at vulnerable populations are more effective than other ALMPs in terms of reducing unemployment and increasing employment. Interestingly, the positive effects of these policies seem to be particularly beneficial for the low skilled., The ILO Research Department released a working paper by this author, 'Are active labour market policies effective in activating and integrating low-skilled individuals?: an international comparison', in 2015.