ISSN 1995-459X print E-ISSN 2312-9972 online ISSN 2500-2597 online English
Editor-in-chief Leonid Gokhberg
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2022. vol. 16. No. 2
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6–14
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The work investigates the effects that a specific science industry collaboration scheme, joint research, generates in three areas, such as: production of academic activities, scientific knowledge commercialization and society at large. It is an in-depth work on joint research in a developing country that covers three different types of effects. The work highlights the specific industrial contributions that make it possible such effects to be verified, with special attention to societal effects, an aspect rarely present in the literature. Based on some dimensions that recent literature has identified and where more empirical evidence is needed, a multiple case study has been carried out through the selection of three public private collaborations in Argentine biopharmaceutical sector responding to joint research characteristics. Among the main findings, the identification of the different ways in which relationship with industry allows science: to intensify its publication activity, by having more resources and identifying new thematic niches to publish; to improve teaching, using co-generated knowledge and shared equipment; to expand its research agenda both towards applied topics and towards more basic ones. Likewise, relationship with industry allows knowledge generation that, in addition to being central in the creation of start-ups and patents, also contribute to perform new services of commercial nature. Finally, joint research generates effects that benefit society in general, through cheaper domestic diagnostic or therapeutic solutions improving public health. |
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15–30
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Modern Universities play increasingly important role in contemporary society, advancing frontiers of science and transforming regional economies. As funding models of modern universities change, they adopt some features of a business organization. While their ability to attract funding becomes vitally important for universities, especially from private sources (industry), a balance between fundamental and applied research becomes vital. The current research investigates 5-years of activities of the Skolkovo Institute of Science and Technology (Skoltech) and particularly its research portfolio. It is based on the theory and practice of the Research Domain Portfolio Matrix (RDPM) approach considering a University to be a portfolio of R&D technologies in diverse scientific areas and at various stages of technology maturity. It is of utmost importance for Universities to find a balance between basic and applied research while making decisions on launching new projects/programs or modifying the existing projects/programs. The proposed RDPM approach helps to leverage limited resources, establish priorities, monitor risks, and influence outcomes in the short and long-term horizons. |
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32–41
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This article investigates the link between human capital depreciation and job tasks, with an emphasis on potential differences between education levels. Using data from the German Socio-Economic Panel, fixed effects panel regression is applied to estimate an extended Mincer equation based on Neumann and Weiss’s model. Human capital gained from higher education levels depreciates at a faster rate than other human capital. The depreciation rate is also higher for specific skills compared to general skills. Moreover, the productivity-enhancing value of education diminishes faster in jobs with a high share of non-routine interactive, non-routine manual, and routine cognitive tasks. These jobs are characterized by greater technology complementarity or more frequent changes in core-skill or technology-skill requirements. The presented results point to the urgency of elaborating combined labor market and educational and lifelong learning policies to counteract the depreciation of skills. Education should focus on equipping workers with more general skills in all education levels and adapt educational programs to take into account the rapid upgrade of production technologies and changing competency requirements. |
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42–51
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Information technologies are rapidly transforming the field of human resource management in organizations. The digital transformation of human resource management has become specifically important in the context of the COVID-19 pandemic, which has significantly accelerated the pace of digitalization of HR processes. Companies that are able to quickly take advantage of the opportunities of the implemented digital HRM technologies are in a better position than those in which digitalization was paid less attention. At the same time, the factors and consequences of digitalization of human resource management, as well as its relationship with various characteristics of firms, remain unclear today. This article provides an attempt to shed light on the key components of HRM digitalization analyzed against significant characteristics of organizations (size, personnel structure, staff turnover, performance) using personal data of 449 small, medium and large businesses operating in the Russian market. The collected data indicate the presence of two key components of digitalization: quantitative (reach or breadth) and qualitative (effectiveness of digital practices). We found that the combination of wide reach and high efficiency has not always been a sign of more successful and functional companies. |
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52–64
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With the growing interest in e-education, particularly in the context of the pandemic, more scientific studies have been undertaken recently to analyze and identify factors influencing e-learning acceptance. Indeed, e-learning acceptance depends on many different factors, but no consensus has been reached on factors that contribute most to the acceptance of e-learning solutions. Consequently, this article ascertains the factors and their relationships behind the satisfaction and the future intention to use e-learning among Polish university students. From among the factors analyzed in the literature, the author examined the relationship between computer self-efficacy (CSE), facilitating conditions (FC), satisfaction (S) and the future intention to use e-learning (FI). Data were gathered using structured questionnaires and computer-assisted web interviewing (CAWI). Students at Bialystok University of Technology (Poland) were sent an electronic link to the questionnaires using the internal e-mail system. Eight hundred three forms were returned fully filled out. Aiming to ascertain the extent to which measured variables describe the number of constructs, the author made the Confirmatory Factor Analysis (CFA). The Generalized Least Squares (GLS) estimator was used to calculate the values of model parameters.The results confirmed that higher computer self-efficacy and better facilitation conditions result in greater user satisfaction with e-learning. However, facilitating conditions impact user satisfaction more than computer self-efficacy construct variables. Based on the findings, user satisfaction is a strong anticedents of the future intention to use e-learning. |
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65–78
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Knowledge intensive business services (KIBS) act as bridges of innovation in the productive fabric. Given this growing importance, the occupational structure and demand of skills in KIBS activities need to be reflected on. This paper examines the occupational structures of KIBS, looks at the role that vocational training profiles can play within them. The focus of this analysis is the case of the Basque Country, to which the mismatch approach was applied. Beyond merely understanding the current role of vocational education workers, this approach makes it possible to explore the potential of VET graduates in KIBS. Three types of mismatches are studied here: vertical mismatch, horizontal mismatch, and skills mismatch. Results show that the relevance of VET workers varies within the different types of KIBS, being particularly important in T-KIBS. This leads to the conclusion that VET graduates can play a key role in digital transformation processes, both in manufacturing and services companies. |
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80–89
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With an increase of population density and contacts between people, the emergence of new biological viruses, the threat of various epidemics is growing. Countering these threats involves the implementation of large-scale preventive, therapeutic and other measures, both before the start and during the epidemic. Epidemiological informing of the population plays an important role in such counteraction. The currently used models of epidemiological informing the population of cities largely do not meet the needs of practice. This negatively affects the effectiveness of the response to epidemics. The purpose of the study is to develop new models and justify their applicability for understanding the processes in public health, the impact of epidemics on the economy and business. For the quantitative substantiation of programs (scenarios), such epidemiological informing, a method based on new models of epidemic development in related cities is proposed. The method is characterized by a new objective function that links economic efficiency with the state of health of the population in an epidemic. The models differ from the known solutions both in the space of the selected states of the processes under study and in the connections between them.Using the developed method, seven possible programs of epidemiological informing the population of related cities were analyzed and the best of them was found for specific conditions. New regularities have been established between the parameters of the programs being implemented and the results of the impact on the health and performance capability of the population. It is shown how an epidemic can develop in cities that are differently connected to each other by vehicles. The proposed method allows quickly find the best epidemiological informing programs for the population. The models underlying this method make it possible to predict public health and the impact of epidemics on the economy and business, depending on the planned measures to counteract epidemics. They are also applicable to determine the sources and time of infections’ onset. The obtained simulation results are in good agreement with the known facts. The method can be applied in advanced information systems to support the adoption of far-sighted decisions to counteract epidemics. |
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