رضا حیدری

Background: Sport heritage is increasingly being recognized as a potent instigator of tourism. The convergence of heritage, sport and tourism involves many different and diverse fields, including sport tourism, heritage tourism, sport management. Aim: The purpose of this study was to identify the effective factors on the development of heritage sports tourism with an interpretive structural modeling approach (ISM). Materials and Methods: The present research is applied, qualitative and analytical in terms of nature and purpose, data retrieval, and data analysis method, respectively based on interpretive structural modeling. Data collection tools in this study were library studies, interview and questionnaire based on interpretive structural modeling. In order to identify the factors affecting the development of heritage sports tourism, with the collective agreement of experts and reviewing the research literature, 16 factors affecting the development of heritage sports tourism were identified. Results: According to the third step of the ISM method, the effective factors on the development of heritage sports tourism were classified into 7 levels and the political and governmental dimensions along with the rule of law were at the lowest level of the model (seventh level); these are prioritized in terms of implementation over other dimensions. As a result, officials and managers in the field of tourism and sports tourism should pay special attention to these dimensions in order to provide the ground for the emergence and realization of other dimensions at higher levels of the model. Finally, based on the analysis matrix of influence and dependence, it was determined that the political and governmental dimensions, rule of law, management and supportive factors are among the influence factors; economic dimensions, socio-cultural factors, infrastructure and welfare services, education and research, specialized human resources, technology, heritage sports tourism attractions, heritage, marketing and information and international relations are among the linking factors; and the dimensions of safety and security, complementary attractions and sporting events are among the dependent factors in this research. Conclusion: According to the results of the model, for the development of heritage sports tourism, there must be a serious determination. In this regard, the policies of a nation must be progressive, and in the first step, government with a decisive role must provide the infrastructure.

The purpose of this study is to explore the effective factors on the productivity of human capital via an interpretive structural modeling (ISM) in General office of Sports and Youth in Khorasan Razavi Province. The present study is a qualitative research with an analytical nature and it is also an applied one that was conducted via interpretive structural modeling. Literature review, interviews and ISM questionnaires were used for data collection. The research population included professors and experts in sports management, managers, deputies and staff of the General office of Sports and Youth in Khorasan Razavi, of which 35 people were totally selected through purposeful sampling in three stages of this study. According to the research findings, 59 effective indicators were identified under seven major dimensions playing role in improving the productivity of human capital, which were classified into five levels. Motivational factors, organizational culture and work environment, the relationship between managers and employees along with individual factors, the quality of labor force, and finally the technology factor were identified under five levels of the model. Finally, it can be concluded that managers in sports organizations should pay special attention to the technology factor and its indicators, which have been identified as the foundation of improving employees’ productivity, which then provides the ground for exploiting other dimensions at higher levels.

In recent years, the fluctuation in agricultural commodity prices in Iran is increased and thus, accurate forecasting of price change is necessary. In this article, a flexible combined method in modeling monthly prices of beef, lamb and chicken from April 2001 to March 2021, was proposed. In this new method, three different approaches namely simple averaging, discounted and shrinkage methods were effectively used to combine the forecasting outputs of three hybrid methods (MLPANN-GA, MLPANN-PSO and MLPANN-ICA) together. In implementation stage of hybrid methods, based on test and error method, the optimal MLPANN structure was found with 3/2/4–6–1 architectures and the controlling parameters are carefully assigned. The results obtained from three hybrid methods indicate that, based on the RMSE statistical index, the MLPANN-ICA method performs the best when forecasting prices for beef, lamb, and chicken. The outputs of three combination approaches show that the shrinkage method, with a parameter value of K=0.25, achieves the highest prediction accuracy when forecasting prices for these three meats. In summary, the proposed method outperforms the other three hybrid methods overall.