Recently the development of new technologies has produced an increase in the number of studies that try to evaluate consumer behavior towards the use of sports applications. The aim of this study is to perform a systematic review of the literature on the intention to use mobile applications (Apps) related to fitness and physical activity by consumers. This systematic review is a critical evaluation of the evidence from quantitative studies in the field of assessment of consumer behavior towards sport applications. A total of 13 studies are analyzed that propose models for evaluating the intentions to use fitness applications by sport consumers. The results revealed several key conclusions: (a) Technology Acceptance Model is the most widely used model; (b) the relationship between perceived utility and future intentions is the most analyzed; and (c) the most evaluated applications are diet/fitness. These findings could help technology managers to know the most important key elements to take into account in the development of future applications in sport organizations.

Purpose: The purpose of this paper is to understand how the nationality and the sport education system could affect the entrepreneurial intentions (EI) of undergraduate sport science students in two different countries. Design/methodology/approach: A total of 249 undergraduate sport sciences (SS) students from Spain and Lithuania were analysed. The EI questioner questionnaire by Liñán and Chen (2009) was used to compile the data during the 2016-2017 academic year. Findings: There are significant differences between the sport science students of Spain and Lithuania. The Lithuanian students have significantly higher means in the variables of EI, perceived behaviour control and professional attraction. Moreover, the variables that predict EI are different, and certain path coefficients of the variables are also significantly different. Research limitations/implications: The sample originates from one university in each country; therefore, these results may not be generalisable to the entire population. Practical implications: The SS degrees in Lithuania and Spain should follow different educational policies with the objective of fostering EI and increasing the number of entrepreneurs. Social implications: Creating adequate educational policies to foster entrepreneurship in sports across countries could improve the number of entrepreneurs in the sports sectors; thus, the youth unemployment rate will decrease. Originality/value: There has been no previous research that analyses the EI of sport science students across contexts through the theory of planned behaviour. Moreover, there are no studies that compare the EI of university students between Spain (Western Europe) and Lithuania (Eastern Europe).

Purpose: The number of familiarization sessions in fitness assessments seems to be critical and inconsistent. Therefore, the primary aim of this research was to determine the number of familiarization attempts that stabilize the results in particular physical fitness tests. The secondary aim was to establish the test reliability through familiarization sessions.Methods: Thirty-nine primary school children participated in this research (age: 10.8 years, body mass: 40.6 ± 8.9 kg, and body height: 145.3 ± 7.2 cm). During six sessions, with one session every third day, participants performed the following tests to assess explosive strength (vertical jump and standing long jump), coordination (polygon backward and polygon with turn) and flexibility (toe touch).Results: The results of repeated analysis of variance (ANOVA) showed that there were significant increases (p < .05) in the polygon backward and polygon with turn performances from the first to third familiarization session. The standard error of measurement decreased as sessions progressed, indicating little within subject variation between the coordination test results following a familiarization period. Statistically significant differences were identified in the vertical jump test from the fourth test session compared with the first session. On the other hand, statistically significant differences for the standing long jump test were only found in the final session compared with the initial session. In the toe touch test, there were no significant increases from the first to the final familiarization session. All tests showed high a reliability coefficients, ranging from 0.979 to 0.991.Conclusion: Polygon backward and polygon with turn performance may be a practical, reliable method to assess coordination in primary school-aged children. However, completion of at least 3 practice sessions is suggested for participants to obtain a stable score. In addition, both jump tests are feasible for assessing skill-related fitness in young children, although the scientific reliability of the two tests should be questioned and the tests should be tailored to fit the age group of the children.

This study aimed to investigate the relationship between health education and motives and barriers for university students’ engagement in leisure-time physical activity (PA). The research sample included 709 students (312 females and 397 males) in different years of study, ranging in age between 18-25 years. A questionnaire survey method revealed a significant positive relationship between fitness and health motives and students’ leisure-time PA. External barriers were negative predictors of students’ leisure-time PA, while more health education-related courses per week were positively associated with students’ leisure-time PA. Finally, we found that the number of health education-related courses per week moderated the relationship between fitness and health motives and students’ leisure-time PA. These findings suggest that university students’ fitness and health motives and external barriers to be physically active outweigh other motives and barriers in determining their leisure-time PA. In addition, health education in university studies can effectively increase students’ health-related motivation for PA.

One of the main objectives of fitness center managers is to obtain high levels of loyalty from the customers of these fitness centers. Within the existing literature on fitness center management, previous research has analyzed the importance of the management variables themselves to determine the behavioral intentions of their customers, ignoring other psychological and sociodemographic aspects and focusing on linear relationship models. Therefore, this study, which aims to analyze the impact of different management variables along with psychological (emotions and subjective well-being) and demographic variables (age and sex) on the satisfaction, perceived value (PV) and future intentions (FI) of 398 users (216 men, aged 18–75, Mean = 35.89 ± 14.53) of a fitness center, intends to fill this gap. In this study, two different methodologies are used, i.e., hierarchical regressions models (HRM) and qualitative comparative analysis (QCA). The data were obtained by means of a self-administered questionnaire composed of 69 items that collected different previously validated scales. Considering HRM, the different models proposed explain 52% of the satisfaction variance, 57% of perceived value and 59% of future intentions. In general, it seems that the management variables are better predictors than subjective well-being, emotions and age or gender since their inclusion does not greatly improve the model’s predictive capacity. As far as QCA analyses are concerned, it seems that none of the conditions are necessary for high or low levels of satisfaction, perceived value or future intentions. On the other hand, based on sufficiency analyses, there seem to be 8 pathways or combinations of conditions leading to high levels of satisfaction and 13 for low levels, 11 combinations leading to high levels of IF and 10 leading to low levels; however, there are 6 combinations of conditions leading to high levels of PV and 5 leading to low levels. In general, some of the pathways consider only the management variables, although many of them consider the importance not only of the management variables but also of the interactions that these may have with emotional aspects and, to a lesser extent, with age and well-being. When comparing both methodologies, it can be observed that the QCA models are more explanatory than the HRM models and that they take into account aspects that seem unimportant when observing linear models (such as emotions or age). However, both methodologies should be considered complementary and used simultaneously since, by focusing on different aspects, enriched results are obtained. The results obtained will enable managers to make more efficient use of available resources to increase user satisfaction.