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The main purpose of this paper is to assess the degree of complementarity between cognitive skills and non-cognitive skills, and to evaluate their joint impact on individual wages.

The author uses a survey representative of the Polish working-age population with well-established measures of cognitive and non-cognitive skills.

Non-cognitive skills are important in the labour market, not only as separate factors that influence wages, but as complements to cognitive skills. Specifically, the analysis showed that the more neurotic an individual is, the lower his or her returns to cognitive skills are. Social skills were not shown to be complementary to cognitive skills in Poland unlike the recent results in the United States.

To the best of author's knowledge, this is the first study to provide evidence that neurotic individuals have lower returns to cognitive skills. It also tests the existence of the complementarity between social and cognitive skills.

Purpose – The purpose of this research is to provide empirical evidence on the relationships among new technologies, innovative work practices and upskilling in the Spanish case. Design/methodology/approach – Using detailed plant‐level data from a survey of Spanish manufacturing firms, we apply estimation methods, such as tobit and ordered probit models, to test the hypothesis that the use of ICT, AMT, and innovative work practices is positively related to upskilling. Findings – As available empirical evidence shows for other countries, we have found that AMT, ICT and innovative work practices are positively related to skills, although they have different effects on workforce composition and training. We have also found several significant effects of the interactive terms of the three technologies and work practices considered on the selected variables of upskilling. Research limitations/implications – The main limitation is the lack of time series data. Cross‐sectional data do not allow the use of lagged variables and make it impossible to analyse the evolution of the adoption of new technologies and work practices by firms and their dynamic effects on skills, or to study causalities among variables. In addition, the study relates only to manufacturing industries. Further research should consider expanding the analysis to the service sector and studying possible complementarities between technology and work practices, in terms of labor cost savings. Originality/value – This paper offers empirical evidence for Spain on the relationship between new technologies, innovative work practices and upskilling considered jointly. It analyses two different technologies: ICT and AMT. The paper also focuses on different dimensions of upskilling.

The technological revolution is creating new goods and services and altering how and where they are produced. One of the principal issues for all countries is how these new technologies will affect employment and the composition of skills demand. Surveys the literature to attempt to answer three main questions: to what degree are the new technologies becoming diffused around the world? How much do they reduce, or increase employment? And do they reduce, or increase, the skills required in the labour force? Touches briefly on implications for educational policy. The survey suggests that because of new technologies, new organizations of production, changing employment conditions and the development of new sectors of production, the complementarity of general, formal schooling, in‐plant training and learning‐by‐doing to capital investment are increasing over time and that general schooling plus on‐the‐job training is more complementary to new technologies than is vocational schooling. The former combination is more likely to give workers the flexibility they need in such changing conditions.

In this chapter we study job design. Do organizations plan precisely how the job is to be done ex ante, or ask workers to determine the process as they go? We first model this decision and predict complementarity among these following job attributes: multitasking, discretion, skills, and interdependence of tasks. We argue that characteristics of the firm and industry (e.g., product and technology, organizational change) can explain observed patterns and trends in job design. We then use novel data on these job attributes to examine these issues. As predicted, job designs tend to be “coherent” across these attributes within the same job. Job designs also tend to follow similar patterns across jobs in the same firm, and especially in the same establishment: when one job is optimized ex ante, others are more likely to be also. There is evidence that firms segregate different types of job designs across different establishments. At the industry level, both computer usage and R&D spending are related to job design decisions.

The purpose of this paper is to investigate self-competence—the ability to act responsibly on one's own—and likely nonlinear wage returns across different levels of self-competence as part of training curricula.

The authors identify the teaching of self-competence at the occupational level by applying machine-learning methods to the texts of occupational training curricula. Defining three levels of self-competence (high, medium, and low) and using individual labor market data, the authors examine nonlinearities in wage returns to different levels of self-competence.

The authors find nonlinear returns to teaching self-competence: a medium level of self-competence taught in an occupation has the largest wage returns compared to low or high levels. However, in occupations with a high cognitive requirement profile, a high level of self-competence generates positive wage returns.

This paper first adds to research on the importance of teaching noncognitive skills for economic outcomes, which recently—in addition to personality traits research—has primarily focused on social skills by introducing self-competence as another largely unexplored but important noncognitive skill. Second, the paper studies not only average but also nonlinear wage returns, showing that the right level of self-competence is crucial, i.e. neither teaching too little nor too much self-competence provides favorable returns because of trade-offs with other skills (e.g. technical or professional skills). Third, the paper also examines complementarities between cognitive skills and noncognitive skills, again pointing toward nonlinear returns, i.e. only in occupations with a high cognitive requirement profile, high levels of self-competence generate positive wage returns.

Supply chain (SC) professionals are increasingly working alongside business partners of diverse backgrounds, which has been argued to engender both innovation and creativity but also found as potentially detrimental to SC relationships and performance. To reconcile these views, this study explores two mechanisms – supplementary (similarity) and complementary fits – at the surface (observable traits) and deep (unobservable characteristics) levels and their impact on a focal firm representative’s perception of a SC partner’s trustworthiness.

Model was tested using survey data from 285 managers involved in interorganizational SC relationships.

Results indicate that a focal firm representative’s perception of supplementary and complementary fits with a SC partner positively impacts their perception of the partner’s trustworthiness. However, the effects of similarity at both surface and deep levels and complementarity weaken each other.

Understanding the mechanisms of diversity in SC relationships is crucial for fostering trustworthiness and achieving organizational objectives. Firms should evaluate both supplementary and complementary fits when hiring or assigning roles. Embracing a complementary fit not only promotes diversity but also mitigates the negative impact of similarity bias, ultimately strengthening trustworthiness within the organization's SC ecosystem.

By simultaneously examining individual and combined effects of two unique mechanisms of supplementarity and complementarity at the surface and deep levels, this study sheds light on inconsistent findings of the effects of diversity in the SCM literature.

Due to greater returns to high skill and desirable amenities, high-skilled workers are increasingly agglomerating in metropolitan areas and form path dependence. This chapter explores whether the land supply policy of China constraining big cities' urban construction land quota strengthens the spatial divergence of human capital. Using city-level land supply data, population census data, and land transaction micro data, we find that the higher the degree of a city's land supply lagging behind land demand, the greater the enlargement effect of the initial share of population with college degrees on the increase in share of population with college degrees. Further research reveals that the main mechanism causing this phenomenon is the rapidly rising housing prices hindering low-skill labor flows to big cities.

This paper investigates, theoretically and empirically, differences between blacks and whites in the United States concerning the intergenerational transmission of occupational skills and the effects on sons’ earnings. The father–son skill correlation is measured by the correlation coefficient (or cosine of the angle) between the father’s skill vector and the son’s skill vector. The skill vector comprises an individual’s occupational characteristics from the Dictionary of Occupational Titles (DOT). According to data from the U.S. National Longitudinal Survey of Youth (NLSY79), white sons earn higher wages in occupations that require skills similar to those of their fathers, whereas black sons in such circumstances incur a wage loss. A large portion of the racial wage gap is explained by the father–son skill correlation. However, a significant unexplained racial wage gap remains at the lower tail of the wage distribution.

The purpose of this paper is to reveal the smart collaborative learning service. This concept aims to build teams of learners based on the complementarity of their skills, allowing flexible participation and offering interdisciplinary collaboration opportunities for all the learners. The success of this environment is related to predict efficient collaboration between the different teammates, allowing a smartly sharing knowledge in the Smart University environment.

A random forest (RF) approach is proposed, which is based on semantic modelization of the learner and the problem-solving allowing multidisciplinary collaboration, and heuristic completeness processing to build complementary teams. To achieve that, this paper established a Konstanz Information Miner workflow that integrates the main steps for building and evaluating the RF classifier, this workflow is divided into: extracting knowledge from the smart collaborative learning ontology, calculating the completeness using a novel heuristic and building the RF classifier.

The smart collaborative learning service enables efficient collaboration and democratized sharing of knowledge between learners, by using a semantic support decision support system. This service solves a frequent issue related to the composition of learning groups to serve pedagogical perspectives.

The present study harmonizes the integration of ontology, a new heuristic processing and supervised machine learning algorithm aiming at building an intelligent collaborative learning service that includes a qualified classifier of complementary teams of learners.