Employee well-being and innovativeness: A multi-level conceptual framework based on citation network analysis and data mining techniques

This study proposes a multilevel conceptual framework for a deeper understanding of the relationship between employee well-being and innovativeness. We overview 49 years of well-being research [1972-2021] and 54 years of research on innovativeness [1967-2021] to uncover 24 dominant themes in well-being and ten primary topics in innovativeness research. Citation network analysis and text semantic similarity were used to develop a conceptual framework featuring 21 components and three levels: individual, organizational, and market. These components consist of constructs, domains, and factors that can influence or be influenced by employee well-being and innovativeness either directly or indirectly. This is the first study to use citation network analysis and data mining techniques to investigate the relationship between employee well-being and innovativeness. This novel framework can aid organizations in identifying more holistic and efficient strategies for fostering innovativeness and enhancing the well-being of their workforce. It can also assist in developing new theories and serve as a roadmap for future research. We discuss the research limitations and theoretical and practical implications and propose three research themes that future studies may address.

Creativity as a key competence in advertising industry: Knowledge management and creative potential stimulation

The study purpose is to investigate the development of creativity in the process of knowledge management in the advertising industry. The novelty of the research is in the study of creativity and social intelligence management as key competencies of this industry. The study is motivated by the high need for continuous improvement in the quality of training of employees in the advertising industry. The respondents group for the online study was formed by simple randomisation from representatives of the advertising industry in the Russian Federation (42 people) and China (45 people). The training methodology consisted of several online exercises in the form of situational tasks aimed at stimulating creativity as well as the development of communicative, image qualities and social intelligence. Statistical analysis was performed using STATISTICA 13.3 software (StatSoft Inc.). To compare quantitative data in the group of respondents before and after the training, a paired Student’s t-test was used to test the null hypothesis about the absence of statistically significant differences in the results of tests of creativity and other significant variables for pre- and post-test after applying the training methodology. The null hypothesis was rejected. The research has shown the possibilities of stimulation of creative potential and development of active thinking, its fluency and flexibility by means of training sessions.

Assessing Algorithmic Thinking Skills in Relation to Age in Early Childhood STEM Education

In the modern digital era, intensive efforts are made to inject computational thinking (CT) across science, technology, engineering, and mathematics (STEM) fields, aiming at formulating a well-trained citizenry and workforce capable of confronting intricate problems that would not be solvable unless exercising CT skills. Focusing on contributing to the research area of CT assessment in the first two years of primary school, we investigated the correlation of algorithmic thinking skills, as a fundamental CT competency, with students’ age in early childhood settings. This article reports a relevant research study, which we implemented under the umbrella of quantitative methodology, employing an innovative assessment tool we constructed for serving the needs of our study. The research was conducted within the context of the environmental study course, adding to the efforts of infusing CT into STEM fields. The study results shed light on the correlation between algorithmic thinking skills and age in early childhood, revealing that age is a predictor factor for algorithmic thinking and, therefore, for CT.

Psychedelic Cognition—The Unreached Frontier of Psychedelic Science

Psychedelic compounds hold the promise of changing the face of neuroscience and psychiatry as we know it. There have been numerous proposals to use them to treat a range of neuropsychiatric conditions such as depression, anxiety, addiction and PTSD; and trials to date have delivered positive results in favor of the novel therapeutics. Further to the medical use, the wider healthy population is gaining interest in these compounds. We see a surge in personal use of psychedelic drugs for reasons not limited to spiritual enhancement, improved productivity, aiding the management of non-pathological anxiety and depression, and recreational interests. Notably, microdosing—the practice of taking subacute doses of psychedelic compounds—is on the rise. Our knowledge about the effects of psychedelic compounds, however, especially in naturalistic settings, is still fairly limited. In particular, one of the largest gaps concerns the acute effects on cognition caused by psychedelics. Studies carried out to date are riddled with limitations such as having disparate paradigms, small sample sizes, and insufficient breadth of testing on both unhealthy and healthy volunteers. Moreover, the studies are majoritarily limited to laboratory settings and do not assess the effects at multiple dosages within the same paradigm nor at various points throughout the psychedelic experience. This review aims to summarize the studies to date in relation to how psychedelics acutely affect different domains of cognition. In the pursuit of illuminating the current limitations and offering long-term, forward-thinking solutions, this review compares and contrasts findings related to how psychedelics impact memory, attention, reasoning, social cognition, and creativity.