Hydrogen Energy Demand Growth Prediction and Assessment (2021–2050) Using a System Thinking and System Dynamics Approach

Adoption of hydrogen energy as an alternative to fossil fuels could be a major step towards decarbonising and fulfilling the needs of the energy sector. Hydrogen can be an ideal alternative for many fields compared with other alternatives. However, there are many potential environmental challenges that are not limited to production and distribution systems, but they also focus on how hydrogen is used through fuel cells and combustion pathways. The use of hydrogen has received little attention in research and policy, which may explain the widely claimed belief that nothing but water is released as a by-product when hydrogen energy is used. We adopt systems thinking and system dynamics approaches to construct a conceptual model for hydrogen energy, with a special focus on the pathways of hydrogen use, to assess the potential unintended consequences, and possible interventions; to highlight the possible growth of hydrogen energy by 2050. The results indicate that the combustion pathway may increase the risk of the adoption of hydrogen as a combustion fuel, as it produces NOx, which is a key air pollutant that causes environmental deterioration, which may limit the application of a combustion pathway if no intervention is made. The results indicate that the potential range of global hydrogen demand is rising, ranging from 73 to 158 Mt in 2030, 73 to 300 Mt in 2040, and 73 to 568 Mt in 2050, depending on the scenario presented.

The Effects of Employees’ Perceived Intrinsic Motivation on Knowledge Sharing and Creative Self-Efficacy

Knowledge sharing is the major driving force to maintain enterprises’ competitiveness. This study extends the current knowledge-sharing research by considering knowledge sharing as comprising four types: automatic response, rational reflection, ridiculed reflection, and deprived reflection, based on Kahneman’s (2011) types of system thinking. Drawing on the motivation-action-outcome model, this study explored how individuals’ intrinsic motivation can guide the action of knowledge sharing and reflect the outcome of creative self-efficacy in intelligent transportation jobs. By snowball sampling in intelligent transportation companies, a total of 232 effective questionnaires were collected, and confirmatory factor analysis with structural equation modeling was performed. The research results showed that: intrinsic motivation was positively related to the four types of knowledge sharing tendencies; automatic response was not significantly related to creative self-efficacy; rational reflection was positively associated with creative self-efficacy; but ridiculed and deprived reflection were negatively related to creative self-efficacy. These results can be applied to encourage employees to practice rational reflection in knowledge sharing to enhance their creative self-efficacy in intelligent transportation jobs.

Problems of Formation of System Thinking in Modern Russian Education

The construction of new, market-based economic relations in Russia in the early 90s of the last century was accompanied by a radical transformation of the education system to the Bologna standard. At the same time, Western scientists - teachers drew attention to the work on the cognitive development of the child by L.S. Vygotsky, the theory of developmental education by P.Ya. Galperin, the theory of inventive problem solving by G.S. Altshuller and the results of research by other scientists providing the formation of systems thinking in Soviet education. The article shows that the documents regulating the development of Russian education include the formation of systematic and critical thinking in students, but in practice this is not always implemented. The directions of transformation of the Russian education system since the beginning of building market relations in the 90s of the last century are identified as the cause of the current situation. The formation of systems thinking in higher education should consider the peculiarities of the age dynamics of adults. The most developed figurative and verbal thinking among students makes it possible to use the teaching methods of V.F. Shatalov, which reduces the time for studying educational materials by more than 30 times in comparison with classical teaching methods.

The emotional and social side of analytics professionals: an exploratory study of the behavioral profile of data scientists and data analysts

PurposeAnalytics technologies are profoundly changing the way in which organizations generate economic and social value from data. Consequently, the professional roles of data scientists and data analysts are in high demand in the labor market. Although the technical competencies expected for these roles are well known, their behavioral competencies have not been thoroughly investigated. Drawing on the competency-based theoretical framework, this study aims to address this gap, providing evidence of the emotional, social and cognitive competencies that data scientists and data analysts most frequently demonstrate when they effectively perform their jobs, and identifying those competencies that distinguish them.Design/methodology/approachThis study is exploratory in nature and adopts the competency-based methodology through the analysis of in-depth behavioral event interviews collected from a sample of 24 Italian data scientists and data analysts.FindingsThe findings empirically enrich the extant literature on the intangible dimensions of human capital that are relevant in analytics roles. Specifically, the results show that, in comparison to data analysts, data scientists more frequently use certain competencies related to self-awareness, teamwork, networking, flexibility, system thinking and lateral thinking.Research limitations/implicationsThe study was conducted in a small sample and in a specific geographical area, and this may reduce the analytic generalizability of the findings.Practical implicationsThe skills shortages that characterize these roles need to be addressed in a way that also considers the intangible dimensions of human capital. Educational institutions can design better curricula for entry-level data scientists and analysts who encompass the development of behavioral competencies. Organizations can effectively orient the recruitment and the training processes toward the most relevant competencies for those analytics roles.Originality/valueThis exploratory study advances our understanding of the competencies required by professionals who mostly contribute to the performance of data science teams. This article proposes a competency framework that can be adopted to assess a broader portfolio of the behaviors of big data professionals.