درخت حوزه‌های تخصصی

Purpose: The purpose of this research was to provide a model for predicting time series of financial information based on the Lyapunov representation of information using chaos theory.Method: This research is applied in its purpose, which is conducted using a quantitative approach. The research ranks as descriptive-causal accounting research based on actual information in companies' financial statements. The research method is the "post-event" type and was carried out using chaos theory and Saida's method based on the Lyapunov view.Findings: The findings showed that during the ADF test, the null hypothesis was rejected at a level of less than 5% type 1 error and 95% confidence, and it shows that the data is not static. During the substitution analysis test and its significance level, the behavior of the time series of the main financial information is significantly different compared to their substitutes. The obtained value was calculated to describe the production process of all data sets for μ = 2, ApEnMax equal to 0.65 and rMax equal to 0.32, and for μ = 3, ApEnMax equal to 0.6 and rMax equal to 0.44. The value of the Lyapunov profile in stability at a certain point is less than zero and in the limited cycle of stability is equal to zero and in chaos, it is greater than zero and smaller than ∞, and in noise it is equal to ∞.Conclusion: The results show that higher returns, encourage investors to invest and increase the flow of capital. It is believed that companies' stock returns are a function of systematic risk, and systematic risk represents the changes in the return rate of a share compared to the changes in the return rate of the entire stock market.

Purpose: The purpose of this research was to provide a model for Validating and Presenting Brand-Customer Interaction Model in Digital Platform in the Cosmetics Industry.Method: This research was applied in its purpose and utilized a mixed approach (qualitative and quantitative). In this regard, this study was conducted with the aim of presenting and validating the brand-customer interaction model in Instagram Platform. The present study is a descriptive survey in terms of its practical-developmental purpose and data collection method. The statistical population in the qualitative section includes marketing professors and cosmetics industry managers, 20 of whom were selected by purposive sampling. The statistical population in the quantitative section also includes customers of cosmetics and health products, 384 participants were selected using the convenience sampling. The data collection tools were a semi-structured interview and a researcher-made questionnaire. First, thematic analysis method was used to analyze the expert interviews. Next, the identified pattern was validated using partial least squares method. Thematic analysis and partial least squares were done with MaxQDA software and Smart PLS software, respectively.Findings: The criterion to achieve data saturation has been to achieve repetition in extracting codes. 235 codes were identified in the open coding stage. Finally, three overarching themes, eight organizing themes, and 49 basic themes were obtained through axial coding. Based on the structural equation model, the proposed model was fitted and confirmed.Conclusion: Based on the results, effective marketing and digital content marketing are the basic elements of the model, which increase brand recognition and brand identity among customers by increasing interaction with customers. Brand recognition and identity contribute to positive word-of-mouth marketing, which in turn affects brand positioning on Instagram. Finally, in this way, it is possible to create a constructive and interactive brand-customer relationship.

Purpose: The purpose of this study was to prioritize the factors affecting consumer-buying behavior in online social media marketing.Method: The analysis and validation of indicators were conducted using the mixed method of structural equation modeling and partial least squares. Additionally, the IPMA matrix was utilized to determine the importance and type of performance of each factor. The research data were influenced by consumer information, predominantly consisting of women with a master's degree aged between 36 and 50 years. The study employed a non-probability sampling method common for online surveys, and 466 individuals were examined using Cohen's effect size formula.Findings: The research findings indicated that consumer engagement was the most important factor, and ease of use exhibited the highest level of performance in the overall social media model. Furthermore, consumer engagement was identified as the most important factor, while electronic word-of-mouth (EWOM) demonstrated the highest performance level on Instagram. Conversely, EWOM was deemed the most important factor, with consumer engagement displaying the highest performance level on Telegram. These results can be utilized by marketers to influence consumer purchasing behavior and craft online marketing strategies accordingly.Conclusion: Companies utilizing online social media platforms are advised to enhance consumer engagement and performance by implementing short-term techniques and effective strategies, such as incorporating online chat functionalities in the user environment. Instagram, being the most widely used social media platform and an online shopping hub for consumers, showcased acceptable performance in terms of consumer engagement. Hence, companies need to take measures to elevate performance levels to match their importance. In the case of Telegram, EWOM emerged as the most crucial factor among others, with a commendable performance rating. Businesses can bolster their Customer Relationship Management (CRM) units and enhance WOM initiatives to the fullest extent possible.

This research aimed to investigate the moderating role of age and gender in the willingness to use IOT technology in sports, based on the Technology Acceptance Theory (TAM). This research utilized a survey of the correlation type, with the statistical population consisting of all athletes who have received sports insurance cards and were active this year. Using Morgan's table, a sample of 394 individuals was selected. Standard questionnaires of willingness to use new technologies were employed as tools. Data analysis was conducted using SPSS version 22 and Warp PLS version 8.The research findings indicated that the variables of perceived usefulness, perceived ease of use, and attitude have an impact on athletes' willingness to use IOT technology in sports. Additionally, in the Technology Acceptance Model, perceived ease of use was found to have a significant effect on perceived usefulness. The study also examined the moderating role of age and gender on the willingness to use IOT devices in sports, revealing that only the relationship between age and perceived usefulness did not reach an acceptable level of significance. Therefore, in order to utilize IOT technology in sports, it is crucial to consider these factors as the use of Internet of Things can lead to highly favorable outcomes.

This research seeks to investigate the influence of human resource practices on organizational effectiveness by considering the mediating role of internal customer satisfaction. It draws on data from a human resource department and its employees; a total of 294 valid questionnaires are obtained. Structural equation modeling is employed to examine the proposed model. The results of this research hypotheses test indicate that human resource practices have direct and significant effects on internal customer satisfaction and organizational effectiveness. What’s more, internal customer satisfaction has a mediating role in the relationship between human resource practices and organizational effectiveness.

The present study aimed to identify the factors influencing the implementation of sustainable development policies, with a specific focus on small wins in Iran. This applied and descriptive-survey study utilized a qualitative approach and employed the grounded theory method. Data collection involved interviews and the codification was conducted using the emerging (Glaserian) grounded-theory classical approach. the interview questions were meticulously developed based on a comprehensive review of the literature, and the collected data were coded using Strauss and Corbin’s (1998) paradigm model. The research population comprised specialists and experts who held influential roles in policy implementation, and they were selected using purposive and theoretical sampling. The sampling process continued until the data were theoretically saturated, ensuring a comprehensive understanding of the subject matter. the results of the study revealed the significant impact of various factors on the implementation of sustainable development policies. Notably, in line with the new concept of small wins and the principles of sustainable development, the study identified 36 indicators, which were categorized into drivers and inhibitors. Each main indicator encompassed six economic, social, cultural, strategic, environmental, and organizational factors, along with 18 sub-indicators. These findings underscore the importance of considering these indicators for formulating sustainable development policies and goals, particularly for developing countries like Iran, in order to achieve sustainable development on a global scale.

The proliferation of online stores in Iran has surged in recent years, yet a notable proportion of these ventures falter shortly after inception. Among the myriad challenges confronting Iranian online retailers, the discontinuity in customer purchases stands out prominently. To address this issue, this study delves into the influence of online store service quality antecedents, specifically perceived risk, service convenience, and website design, on both customer satisfaction and behavioral intentions. Data collection entailed administering a questionnaire, and the research model underwent scrutiny via structural equation modeling (SEM). Results indicate a significant positive association between website design and the quality of online store services. Moreover, service convenience and the quality of online store services emerged as robust determinants of customer satisfaction. Satisfaction, in turn, exhibited a substantial positive impact on customer behavioral intentions. Conversely, perceived risk exerted a negative and significant influence on the quality of online store services. Notably, the effects of service convenience on service quality and the impact of service quality on customer behavioral intentions were statistically insignificant at the 95% confidence level. However, the mediating variable of satisfaction significantly mediated the relationship between online store service quality and customer behavioral intentions.