Mohammad Ali Sahebkaran; Motahare salehi nasab; Mahmood Sangari
Abstract
The purpose of this research is to identify the factors affecting the use of artificial intelligence in the marketing of sports equipment and goods. The present study was a field research study in terms of its applied purpose and in terms of the method of data collection. Considering the research topic, ...
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The purpose of this research is to identify the factors affecting the use of artificial intelligence in the marketing of sports equipment and goods. The present study was a field research study in terms of its applied purpose and in terms of the method of data collection. Considering the research topic, the present study used a qualitative research method using the grounded theory method and a systematic method. The statistical population of the study was all managers and experts who were knowledgeable and knowledgeable in the field of artificial intelligence and sports marketing, totaling 14 people, which continued until theoretical saturation was reached. The researcher's indicators for sampling from the statistical population were: people familiar with the literature on artificial intelligence and sports marketing; people who have written scientific and research books and articles; people with teaching experience and work experience in any of the above fields, who were selected using two methods of purposive sampling and snowball sampling. The coding method was used in three stages of open, axial, and selective coding. The results of the research showed that quality and comprehensive data, systems integration, technology infrastructure, customer behavior analysis, algorithm optimization, smart inventory management (causal factors); environmental factors, organizational factors, human factors, geographical factors, economic factors (contextual factors); human errors, transparency in facilitating laws, digital literacy, culture building, process and data modeling (intervening factors); knowledge development and intelligence, development of improvement strategies and business intelligence,
Xolamreza Ebrahemi; mir hasan seyed ameri
Abstract
The aim of the study was to explain the antecedents and consequences of fear of accepting artificial intelligence with an emphasis on the role of organizational syndromes and the perception of globalization among employees of sports and youth departments in northwest Iran. The study was applied in terms ...
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The aim of the study was to explain the antecedents and consequences of fear of accepting artificial intelligence with an emphasis on the role of organizational syndromes and the perception of globalization among employees of sports and youth departments in northwest Iran. The study was applied in terms of purpose and descriptive-correlational in nature, and was conducted with a quantitative approach and field implementation. The statistical population was 653 employees of selected general departments in the years 1402-1403, of which 263 were selected by stratified-proportional random method according to the Krejci and Morgan table. Content validity was confirmed by experts and reliability was confirmed by Cronbach's alpha and CR and AVE indices. Data analysis was performed with descriptive statistics, correlation coefficient, regression, and structural equation modeling in SPSS and SmartPLS software. The results showed that demographic variables (age, gender, education, and service experience) have no significant relationship with AI acceptance, while organizational syndromes, fear of acceptance, and perception of globalization all have significant relationships with AI acceptance, and the proposed model has a good statistical fit. Based on these findings, AI acceptance is more dependent on the quality of organizational health, psychological state, and level of understanding of globalization requirements than on the apparent characteristics of employees. Therefore, strengthening the supportive environment, reducing organizational syndromes, managing technological fear, and consciously orienting to confront global trends are key prerequisites for the success of digital transformation programs in government sports organizations.
mehran haghparast; mohammad soltanhoseini; Davoud Nasr esfahani
Abstract
The main goal of this research was to develop financial management in sports organizations using artificial intelligence language models. The methodology of this research was qualitative. Data was collected through interviews with language models ChatGPT, Command-R, Claude, Google Gemini, Mistral, and ...
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The main goal of this research was to develop financial management in sports organizations using artificial intelligence language models. The methodology of this research was qualitative. Data was collected through interviews with language models ChatGPT, Command-R, Claude, Google Gemini, Mistral, and LLaMA, and initial coding was done using AI TalkBot. Then, to validate the codes, researchers re-encoded the extracted codes and then analyzed them using a Charmaz constructivist approach. The validity and reliability of the research were confirmed using triangulation method, re-coding by a financial expert in sports, and Cohens Kappa coefficient. As a result, 240 initial codes were identified, which were reduced to 28 focused codes in later stages, and finally to 10 core codes. The findings include financial health and accountability, improvement in disclosure in financial reports, operational budget planning, financial data analysis based on commitment, financial risk management, cash flow management, cost management and process improvement, human capital, investment and financial supporters, and the use of advanced financial technologies on blockchain platform. These axes are interconnected and each axis helps strengthen other axes. The proposed model contributes to improving transparency, accuracy in budget planning, and financial risk management in sports organizations, and implementing this model can lead to long-term financial sustainability and growth of sports organizations.
