{"id":12860,"date":"2022-09-05T14:36:05","date_gmt":"2022-09-05T12:36:05","guid":{"rendered":"https:\/\/ecobas.gal\/?post_type=mec-events&p=12860"},"modified":"2022-09-09T13:43:55","modified_gmt":"2022-09-09T11:43:55","slug":"msca-fellowships-review-of-applications-elena-shakina","status":"publish","type":"mec-events","link":"https:\/\/ecobas.gal\/en\/events\/msca-fellowships-review-of-applications-elena-shakina\/","title":{"rendered":"MSCA Fellowships: Review of applications – Elena Shakina"},"content":{"rendered":"

ABSTRACT<\/strong>:<\/p>\n

Worker-job match as one of the critical conditions of individual productivity and overall firm performance is far from being comprehensively studied. The vast majority of research endeavors fall into two categories: (1) on the macrolevel \u2013 structural unemployment conditioned by a temporary mismatch between qualifications of jobseekers and employers\u2019 demand and (2) on microlevel \u2013 a separation propensity or insufficient productivity of a particular worker due to its low fit to position requirements or management styles. A seminal paper by Jovanovic (1979) suggests a solid theoretical grounding of job match and associated turnover phenomena. This paper essentially shifted the frontier and was followed by numerous empirical tests like those by Fredriksson et al.<\/em> (2018); Kiyotaki & Lagos (2007); Sicilian (1995) demonstrating the economic antecedents and consequences of employee quits in light of so-called \u201cpermanent separations\u201d and incomplete information. Along with the literature on economic dimensions of job-matching,\u00a0organizational psychology has been developing theories on the behavioral fit between worker and management styles as well as perceiver expectations and motivation (McGregor, 2006). Originating from the work by Merton (1948), this theory suggests that both positive and negative perceiver expectations determine their performance. The behavioral perspective of job matching refers to self-fulfilling prophecies (so-called “Pygmalion” and” Golem” effects), psychological pressures, manifold discriminations, including gender gap. This continuum of behavioral responses draws up a substantive dimension of job match and mismatch.<\/p>\n

In this research project, we propose a comprehensive examination based on theoretical advancements, several empirical tests, and practical implications of job matching mechanisms in both dimensions. We are currently witnessing a dramatic transformation of the job market which translates into substantially shifting roles of agents \u2013 jobseekers, workers, employers, mediators, and regulators. The development of online job boards, open peer-review screening platforms, and professional social networks significantly reduce information asymmetry and transaction costs and potentiate market efficiency. Though it leads to higher worker mobility and knowledge spillovers. That ultimately requires the development of a fundamentally new institutional environment.<\/p>\n

The combination of economic and behavioral dimensions of job matching turns to the higher relevance due to the following reasons:<\/p>\n

(1) Higher job market efficiency evidently mitigates the dominance of purely economic factors and reinforces behavioral factors to predict and interpret job matching parameters<\/p>\n

(2) New wage-setting mechanisms occur as a response to structural shifts in the job market making specific skills and individual traits of jobseekers and their fit to employer identity significant drivers of job matching<\/p>\n

(3) Job matching becomes more industry- and firm-specific and allows elaborating ad hoc tools to account for these distinctions and making use of vast unstructured data, artificial intelligence (AI), and machine learning (ML) for data processing and prescriptive analytics.<\/p>\n

 <\/p>\n

The objectives of the project are accordingly developed to respond to these challenges:<\/p>\n

(1) to measure economic consequences of job match and mismatch and to investigate behavior factors (incl, self-fulfilling prophecies, psychological pressures, discriminative biases) on individual and firm performance<\/p>\n

(2) to explore alternative wage-setting mechanisms based on data published on major job boards:<\/p>\n

(2.1) predicting the value of the domain and non-domain skills from the demand and supply side,<\/p>\n

(2.2) discovering and interpreting behavior factors of gaps and market frictions<\/p>\n

(3) to examine and run comparative analytics for various contexts of job markets with presumably specific conditions and to suggest effective AI tools for better job matching outcomes<\/p>\n","protected":false},"excerpt":{"rendered":"

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