The purpose of the present investigation was to develop and initial validation of a measure for assessing the athletes perceptions of coaches’ behaviors that promote fairplay behaviors. A three-step procedure was undertaken to develop the questionnaire. In the initial step, the literature review provided theoretical and empirical perspectives on how youth sport coaches can influence athletes’ fairplay behaviors. In step 2, a pool of 191 items worded and content validity was assessed. In the final step, 252 teenage male athletes (age range 14-19; mean age =15. 88± 1. 34 years) who were participating in a variety of team sports (i. e., volleyball, basketball, soccer, futsal) completed a revised 164-item questionnaire. Principal components analyses further reduced the number of items to 30 and suggested a four-factor structure (i. e., modeling, instruction, pressure, and dialogue dimensions). The results revealed that the final 30-item version of the Coaching Fairplay Behaviors Inventory possesses a good psychometric basis with adequate internal consistency and which explain 57. 80% of the total variance. Collectively, this study provides a new valid and reliable instrument for assessing the specific mechanisms by which coaches promote fairplay behaviors among teenagers, although more investigations are needed to validate this tool.

The emergence of information and communication technologies (ICT), especially the Internet, has created a new concept in human resource management, which is called electronic Coaching or e-Coaching. According to the numerous advantages of eCoaching, the aim of this study is to provide an e-Coaching model for IT service providers companies by applying comparative study and measuring the factors related to acceptance of the provided model. The population consists of 258 coaches in the field of information technology in Tehran, which has led to 104 fully answered questionnaires. For validity, the opinions of faculty members and experts in the field were examined. The reliability of the questionnaire also was measured by Cronbach's alpha, led to the ratio between 0.74 and 0.91 for various factors. For data analysis, structural equation modeling, descriptive statistics and inferential statistics (analysis of variance (ANOVA) and t-test) were used. The results showed that the relative advantage, complexity, visibility, individual innovation, gender, age, education, computer skills and perceptual barriers predict the process of e- Coaching acceptance.