With an increasing pace of digitalization, automatization, and robotization, firms need to quickly anticipate new consumer values, trends, and needs and adjust their production, thus requiring constant adaptation of competences and competence-based models. This review: (1) briefly outlines the development of competence-based models; (2) presents difficulties when defining and delineating differences between competences, skills, and abilities; (3) presents the main challenges of competence measurement; (4) presents recent findings of competence-based models in organizational and individual context; and (5) highlights challenges these models are likely to encounter in the future. To this end, a non-systematic literature review was carried out to summarize relevant published research studies and to define future research directions. Results show that further competence-based research should focus on generalizing the findings by looking at various groups of workers and industries, expanding the set of competences used in the analyses, using different definitions of key competences, and developing alternative models to assess their impact on performance. Such research would allow to better assess employees’ preparedness in terms of competence requirements, as well as to identify the most critical gaps and opportunities for the formal educational system and as part of on-the-job training.

Purpose: Industry 4.0 processes brought dramatic changes in skills and competences needed at the firm level. The purpose of this paper is: to identify and quantify key competences required for workers with economics-and-business background; to evaluate development level of those competences among the currently employed workforce; to investigate degree of match between required and currently developed competences; and finally to assess how this (mis)match translates to firm performance.Design/methodology/approach: This research is based on primary data, collected through questionnaires, and secondary data of firms’ financial and structural characteristics. Key competences were estimated using factor analysis and were then used as covariates in explaining differences in firms’ performance in both static and dynamic production function specifications using standard regression model, Heckman selection model and Arellano–Bond estimation.Findings: Results show that mismatches in competences basic algebra; collectedness, conflict resolution and presentation; and motivation and organization are all negatively associated in explaining the variation of firm performance, with motivation and organization having the most significant effect.Originality/value: This paper focuses on competence mismatch by including both sides of the labor market (employers and employees) in the analysis. This paper offers: a theoretical structure for understanding and investigating existing competence mismatches; a step-by-step industry-driven method for deriving key required competences, including an initial exploratory phase (combination of literature review, exploratory interviews and pilot study) followed by a descriptive and implementation phases (design, implementation and analysis of nationally representative survey); and finally, analysis phase (associating competence mismatches to firm performance).

This is a conceptual paper that aims to identify relevant approaches for assessing consumer resilience with regard to online privacy violation and to develop a research model suitable for subsequent empirical testing. Based on the relevant literature, we made a synthesis of theoretical approaches to individual resilience from diverse disciplines and in the next step we proposed a set of variables in the model to serve as determinants and behavioral consequences of consumer resilience with regard to online privacy violation. Finally, we offer the developed conceptual model for further scholarly debate and for future empirical verification from the research community.

This study examines the impact of regulation as an antecedent of online privacy concern. Previous research found that perceived effectiveness and enforcement of regulatory policies reduce online privacy concern; however, it does not explain what factors influence this relationship. Based on the survey data, the empirical analysis is conducted on a large sample of internet users in Croatia. Our methodology consists of two parts: first, we use confirmatory factor analysis to validate the latent constructs used in the main model; and then we proceed with model estimation using OLS and ordered probit techniques. This study fills the gap in the existing body of knowledge by analysing different perceptions of the existing legislation and government effort to protect online privacy in the context of sociodemographic characteristics of respondents, computer anxiety, individual desire to maintain control of personal information online, as well as intensity and diversity of online activities. Our results indicate that perceived effectiveness of government regulation reduces online privacy concern whereas computer anxiety has a major positive impact on online privacy concern. These findings might be useful for national policy-makers and for business strategies, especially in the context of the GDPR regulation introduced in 2018.