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.
The back squat is widely used in strength training programs. Alternatively, the belt squat has been gaining popularity since it loads the weight on the hips, as opposed to the shoulders and spine. The purpose of this study was to determine whether using a belt squat would result in less lumbar extensor activation while providing similar excitation of other prime mover and stabilizer musculature. Ten participants (9 males, 1 female; age 29.3 ± 4.9 years; body mass 96.2 ± 17.8 kg) who regularly trained both belt squats and back squats performed three sets of 5 repetitions with 100% bodyweight for each exercise. Peak and integrated muscle activity was calculated and normalized to a maximum voluntary isometric contraction. A one-way ANOVA (p < 0.05) was used to compare conditions. Belt squatting decreased lumbar erector impulse (45.4%) and peak (52.0%) activation as compared to the back squat. Belt squatting did not alter activation of the lower extremities except for a decrease in the gluteus maximus (35.2% impulse and 32.1% peak), gluteus medius (54.1% impulse and 55.2% peak). Furthermore, belt squatting reduced activation of the rectus abdominus (44.3% impulse; 31.1% peak), and external obliques (45.8% impulse; 53.7% peak) as compared to back squatting. Our results suggest belt squatting provides similar muscular demands for the quadriceps, hamstrings, and plantar flexors, but is less demanding of trunk stabilizers, and gluteual muscles. Belt squats may be a suitable alternative to back squats in order to avoid stressing low back or trunk musculature.
This randomized cross-over study examined the effects of typical static and dynamic stretching warm-up protocols on repeated-sprint performance. Thirteen young female handball players performed a 5 min aerobic warm-up followed by one of three stretching protocols for the lower limbs: (1) static stretching, (2) dynamic-ballistic stretching, and (3) no stretching before performing five all-out sprints on a cycle ergometer. Each protocol was performed on a different occasion, separated by 2-3 days. Range of movement (ROM) was also measured before and after the warm-up protocols with a sit-and-reach test. Fixed and random effects of each stretching protocol on repeated sprint performance were estimated with mixed linear modeling and data were evaluated via standardization and magnitude-based inferences. In comparison to no stretching, there were small increases in ROM after dynamic stretching (12.7%, ±0.7%; mean, ±90% confidence limits) and static stretching (19.2%, ±0.9%). There were small increases in the average power across all sprints with dynamic stretching relative to static stretching (3.3%, ±2.4%) and no stretching (3.0%, ±2.4%) and trivial to small increases in the average power in the 1st and 5th trials with dynamic stretching compared to static stretching (3.9%, ±2.6%; 2.6%, ±2.6%, respectively) and no stretching (2.0%, ±2.7%; 4.1%, ±2.8%, respectively). There were also trivial and small decreases in power across all sprints with static relative to dynamic stretching (-1.3%, ±2.8%) and no stretching (-3.5%, ±2.9%). Dynamic stretching improved repeated-sprint performance to a greater extent than static stretching and no stretching.
Personality traits, especially in sport are modulatory factors of athletes’ behavior – his/ her conscientiousness, the will to achieve an aim, perseverance and motivation of activity. Not only are biological predispositions related to anatomical or biochemical traits of success, but they are also largely determined by personality traits that result from genetic factors. In our research we joined tests of athlete’s personality in correlation with genotypes of the dopamine transporter (DAT1) gene polymorphism. The selection of this polymorphism was based on previous reports connecting the influence of dopamine with motivation and numerous arguments supporting its correlation with human behavior. We observed significant differences among polymorphisms DAT 9/9, 9/10, 10/10 in terms of proportion of particular genotypes between athletes and the control group. We also found significant differences in the NEO FFI sten scale for conscientiousness. We noticed that anxiety was related with genotypic variants of DAT1, specifically the 9/10 VNTR variant, which conditioned lower levels of anxiety in the group of tested athletes. By contrast, the lower sten value of agreeability was statistically significant for the group of athletes that were carriers of the 10/10 VNTR genotype. Heterozygous 9/10 VNTR among athletes showed lower levels of anxiety in comparison with the control group, whereas agreeability determined using the NEO FFI scale represented a lower value among athletes that had the 10/10 polymorphism. We may thus conclude that the presence of polymorphic variants of the dopamine transporter gene corresponds to athletes’ personality traits.
This study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4–19.8, 19.8–25.1 and ≥25.2 km·h-1, and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80–100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably.