Antonio Accetturo, Mattia Borsati (p), Michele Cascarano

László Lőrincz

See extended abstract

Sergey Nikitenko (p), Elena Goosen

Mattia Borsati

Coal is a traditional energy resource that is quite common in many countries of the world and plays a significant role in the global energy balance. With the transition to renewable energy sources (solar, wind, bioenergy, etc.) and the beginning of the development of alternative energy, the role of coal as an energy source began to decline, the coal industry faced instability in world markets, extreme volatility in coal prices, and the formation of a "seller's market" oriented to coal with strictly specified properties. Everything set the task of choosing between the closure of some companies and the transition of the industry to a new stress-resistant development model.
The purpose of the article is to identify segments of the coal industry with the help of the stress resistance index and evaluate their prospects for the transition to a new development model.
The object of analysis was 92 companies that operated in Russia during the period 2011-2020 and "survived" two deep "stresses" in 2015 and 2020. The study is based on the concept of resilience adapted to the conditions of the coal industry. It involves the division of the coal industry into separate segments depending on the level of stress resistance and the type of value chains that have developed in the segment. Based on the analysis of the sequence of stages of value creation and the nature of intra- and inter-company interactions within the value chains, the authors identified the strengths and weaknesses of each of the segments and assessed the prospects for a potential upgrade of VC in the direction of flexibility and stress resistance.

Virág Ilyés (p), Rebeka O. Szabo(p), László Lőrincz (p)

Sergey Nikitenko

Obtaining a job requires complex efforts from jobseekers. Several studies have reported on the importance of cultural signaling as a form of impression management in the selection process. It implies that jobseekers cannot merely rely on their skills, credentials, and expertise, but need to engage in a convincing self-presentation when one can give an account of their cultural capital, signal their status, group membership, style, character traits, etc. This cultural component is a well-documented mechanism in the process of social allocation, and as such, in hiring decisions. Although there are studies investigating how self-presentation affects hiring outcomes, only a handful of research has dealt with this topic in online platforms despite their increasing importance in job seeking. In this work, we address this gap by making a systematic analysis of the facets of self-presentation and their impact on successful job applications in Freelancer, one of the biggest online labor markets. Besides investigating skills, credentials, geographic distance, job category, gender and ethnicity, we seek to understand the role of impression management in online hiring outcomes. Addressing these matters, we use natural language processing, image recognition and fixed effect regression models to analyze more than 100000 job seeker applications. Relying on scraped, online data and conducting a systematic exploration of these complex mechanisms, our work provides valuable insight on the functioning of online labor markets and hiring outcomes.