درخت حوزه‌های تخصصی

This research aims to identify the factors that influence the growth of cultural tourism in Iran and propose a corresponding model. Following the identification of these factors, a scenario is written to optimize their utilization. The research employs a combination of qualitative and quantitative methods to achieve its objectives and finalize the factors. Semi-structured interviews are conducted with experts in the field. In the second phase, after the formal validity of the factors is confirmed, their fuzzy cognitive mapping and scenario are designed using the FCMapper and Pajek software programs. As the results show, the factor of “creating investment opportunities and attracting financial resources in the field of cultural tourism” is the most influential, while the factor of “providing diverse and creative services in Iran’s cultural tourism” is the most impressionable for the development of cultural tourism in Iran. In the task of scenario writing, it has been discovered that, by focusing on attracting financial resources, managers can enhance the infrastructure, create a context for interaction with other countries, identify new target markets, and offer creative services to Iranian cultural tourists through diverse tours. The findings can help stakeholders, managers, and policymakers in Iran’s tourism industry design and develop plans and strategies for the growth of Iran’s cultural tourism

In this paper, first, the stochastic differential equations are introduced as well as the definition and basic theories about Monte Carlo and quasi-Monte Carlo and Sobel and Halton sequences are expressed. Indeed, we introduce and use simulations under these methods to compare the efficiency of the solutions, which the results show that the approximation of the resulting Sobel sequence is much better than other stochastic methods. The comparison of the efficiency of random and quasi-random methods, the geometric Brownian movement and the price index of Tehran stock (equal weight and weight-value) is studied. The results show that the quasi-Monte Carlo method is better than other methods.

With the rapid advancement of information and communication technology (ICT), public administration has adopted the concept of e-government. The academic literature produced many studies in the field of E-government (E-GOV) services, however, there is limited research on such services from the perspective of bibliometric and Network analysis. Therefore, this study aims to present a bibliometric and network analysis of the E-government services literature review obtained from the Scopus database, published between 2011 to 2021. This study uses a five-step method including (1) defining keywords, (2) initializing search outcomes, (3) inclusion and exclusion of some elements of the initial result, (4) compiling initial data statistics, and (5) undertaking analysis of data. The analysis starts by identifying more than 4,880 published articles related to E-government services published between 2011 and 2021. The study findings revealed that the highest number of publications on the E-government Service was in 2019 (102 articles), the top contributing affiliation was Brunel University London, the leading influential country was the USA, and the top contributing Source was Electronic Government. Furthermore, Lu J. occupied the first rank in the list of the most influential authors in terms of citations, while Weerakkody V. occupied the list of the top authors with high publications 20 papers. Likewise, this study showed that there is a collaboration among some authors. This research identified four research clusters by which researchers could be encouraged to widen the research of E-government services in the future. The bibliometric and network analysis of E-government services helps to graphically display the publication's assessment over time and identify domains of current studies' interests and potential directions for further studies. Finally, this research draws a roadmap for future investigation into E-government services.