The aim of the present study was to investigate the relation of technology, organizational culture and emotional intelligence with knowledge management using the mediators of organizational structure and empowerment. The methodology of the research was descriptive-correlational and the population of the study consisted of all the physical education instructors of Zanjan universities with three-year teaching record (61 people). The population size using the census sample criterion. Research tool included Stankosky and Baldanza’s technology, organizational culture and structure, Bar-On’s emotional intelligence inventory, Spreitzer and Mishra’s empowerment, Kordnaij et al. and Newman and Conrad’s knowledge management framework questionnaires. The structural equation modelling was used via Smart PLS 2 software for analyzing the data. The results showed that there is a negative and significant relation between technology and knowledge management. Also, there is significant relation between organizational culture and knowledge management, emotional intelligence and knowledge management, technology and organizational structure, organizational culture and organizational structure, technology and empowerment, organizational culture and empowerment, organizational structure and empowerment and empowerment and knowledge management; while the significance of relations between organizational structure and knowledge management and emotional intelligence and empowerment were not confirmed. The results of the present study can help the people in charge of education and research in the universities in order to produce, keep and use the needed knowledge related to proper time and place by making decisions and educating people.
Physical activity can contribute to societal health and prevent antisocial behaviors. This study explored the driving forces facilitating these goals in Iran’s socio-cultural context. Through a literature review, investigation of available political documents, interviews with experts and consensus of the research team, seventy-three driving forces were explored from different domains and then categorised via the STEEPV framework. This framework considers drivers from Social, Technological, Environmental, Economic, Political, and Value/Cultural dimensions. The “sport/sport sciences” domain was also considered as an additional domain. In the next step, a questionnaire with an answer scale of 1 to 7 was distributed among experts. The fuzzy Delphi method was used to analyse the collected data. Results showed eighteen drivers from five domains (social, environmental, economic, technological and sport/sports sciences) dramatically influenced leisure time physical activity (LTPA) in Iran. “Physical activity opportunities for vulnerable groups” was identified as the most important driver for participation in LTPA. Results suggest the need for a multidimensional and thorough consideration by organisations, leisure managers and policymakers to discover methods to promote health-related physical activities in the future.
The aims of this study were to adapt the Hungarian version of the Sport Commitment Questionnaire-2 and test an expanded Sport Commitment Model (SCM) with psychological variables.
Participants were 526 adolescent athletes (aged 14-18 years, 52.3% males). Applied scales were the following: Hungarian version of the Sport Commitment Questionnaire-2, Consideration of the Future Consequences Scale and Health Attitudes Scale. Exploratory, confirmatory, and path analysis were used for statistical analysis.
Our result showed adequate construct validity of the Hungarian version of Sport Commitment Questionnaire-2. We found several positive predictors of Enthusiastic Commitment and three positive predictors of Constrained Commitment. We found that Health Attitudes had positive relationship with Constrained Commitment and it was associated with future goals and plans; whereas Enthusiastic Commitment had a positive relationship, and Constrained Commitment had a negative relationship with Future Orientation.
Information about sport commitment provided by Sport Commitment Questionnaire may be useful as a tool to prevent dropout among young athletes.
European Research Council Executive Agency, (ERCEA), has the mission to encourage the highest quality research in Europe through competitive funding and to support investigator-driven frontier research across all field, on the basis of scientific excellence. In 2019, European Research Council (ERC) updates the Panel Structure in 3 areas: Social Sciences and Humanities SH, Physical Sciences and Engineering PE, Life Sciences LS, 25 panels and 333 sub-panels. Every UE countries are updating own academic body system to align to the ERC. In Italy, this alignment is not possible because Movement and sport science has been together place SH and LS as academic disciplines of Physical training and Sport sciences. This is the vexata quaestio that makes the Italian academic system different from the other EU countries with consequences on the development of Italian research in Europa. Historical review explains why this division exists and why it begun after the second great war and developed to nowadays, determining an atypical model than others European countries. Movement and sport science should to be reasonably placed in an unique scientific area or alignments coherently at the related subpanels according to the scientific evidences, even if they are placed in more ERC areas. Both options can be applied according to ERC thought to resolve the actual problem.
The aim of the study was to evaluate the correlation between temperament and stress, to assess the stress level and perform comparative analysis of feeling of stress before and after the race. The test group consisted of 30 competitors from Mazovian cycling clubs between the ages of 15 and 16 (M = 15.5, SD = 0.50). Standard psychological questionnaires were used for the study. The level of stress was tested using the PSS 10 questionnaire by S. Cohen, T. Kamarck and R. Mermelstein. In addition, temperament was studied with Formal Characteristics of Behaviour – Temperament Inventory by Zawadzki and Strelau (1997). Measures were used to determine the constant predisposition of cyclists to feel the level of stress, as well as to show the intensity of stress during sports competitions (before and after the start). Statistical analyses carried out with the Wilcoxon test showed a significant difference between the initial and final value of the stress level as a condition in the subjects. It was found that in the same people, stress reached a higher average level after the race (M = 17.8, SD = 6) than before the performance (M = 11.83, SD = 5.9). The results show that the state of stress does not decrease after the start, as occurs with other variables (including emotional arousal). The results showed that stress measured before and after the start of a competition positively correlates with perseverance and emotional reactivity, while stress before the start negatively correlates with briskness. Observations from the analyses carried out may broaden the understanding of the phenomenon of stress, especially in aspects of sport competition and track cyclists.
While discussion and media coverage of esports (i.e., organized competitive video gaming) has dramatically increased since 2016, the use of esports by established consumer brands has not been emphasized in the sport marketing and sponsorship literature. Though appearing in limited sport management research, esports is a non-traditional sport form that generated just under $1.2 billion in revenue as an industry in 2019. However, many non-endemic traditional consumer brands have resisted capitalizing on esports brand-building opportunities. This paper provides a literature review of the past and current esports and sport marketing literature, resulting in the creation of a figure depicting the esports endemic and non-endemic company evolution of esports brand utilization. The evolution of the competitive video game market details how endemic companies are more apt to establish themselves in the esports space before non-endemic companies because of the way that the industry moves and has acceptance by gamers and non-gamers. Marketers and brand managers that have historically employed traditional sports may glean ideas on how to best enhance and extend their brand through the burgeoning esports industry. Moreover, ideas regarding when companies should enter the esports ecosystem is provided.
Betting odds are generally considered to represent accurate reflections of the underlying probabilities for the outcomes of sporting events. There are, however, known to be a number of inherent biases such as the favorite-longshot bias in which outsiders are generally priced with poorer value odds than favorites. Using data from European soccer matches, this paper demonstrates the existence of another bias in which the match odds overreact to favorable and unfavorable runs of results. A statistic is defined, called the Combined Odds Distribution (COD) statistic, which measures the performance of a team relative to expectations given their odds over previous matches. Teams that overperform expectations tend to have a high COD statistic and those that underperform tend to have a low COD statistic. Using data from twenty different leagues over twelve seasons, it is shown that teams with a low COD statistic tend to be assigned more generous odds by bookmakers. This can be exploited and a sustained and robust profit can be made. It is suggested that the bias in the odds can be explained in the context of the “hot hand fallacy”, in which gamblers overestimate variation in the ability of each team over time.
This work is concerned with the interpretation of the results produced by the well known Elo algorithm applied in various sport ratings. The interpretation consists in defining the probabilities of the game outcomes conditioned on the ratings of the players and should be based on the probabilistic rating-outcome model. Such a model is known in the binary games (win/loss), allowing us to interpret the rating results in terms of the win/loss probability. On the other hand, the model for the ternary outcomes (win/loss/draw) has not been yet shown even if the Elo algorithm has been used in ternary games from the very moment it was devised. Using the draw model proposed by Davidson in 1970, we derive a new Elo-Davidson algorithm, and show that the Elo algorithm is its particular instance. The parameters of the Elo-Davidson are then related to the frequency of draws which indicates that the Elo algorithm silently assumes games with 50% of draws. To remove this assumption, often unrealistic, the Elo-Davidson algorithm should be used as it improves the fit to the data. The behaviour of the algorithms is illustrated using the results from English Premier League.