حجت الله صادقی

The geographic information system, by combining decision-making models, can be effective in various areas of spatial development, including tourism capacities. Due to their characteristics and spatial differences, peri-urban tourism villages operate differently from other rural areas in the service sector. Due to these conditions, the required tourism services of these villages are also different. Izeh city has various suburban villages, some of which have tourist attractions. Due to these capacities and the geographical location of the villages in relation to the city of Izeh, these villages have become very important over time. As such, today we are witnessing the growth of the population, as well as the increase in the price of land and the change of land use in suburban villages. The touristic nature of some of these villages is another important factor that shows the importance of paying attention to the management, planning and development of services in them; Because the spatial distribution of services and the level of accessibility at the level of suburban villages should be done according to their capacities and geographical location, based on logical principles and criteria. The geographic information system and spatial decision-making models can be effective in this field and provide a prioritization of tourism services needed in peri-urban villages and determine the spatial distribution of services. Therefore, in this research, the aim is to evaluate the services needed for tourism development in peri-urban villages through the VIKOR model and analyzing their spatial distribution in the GIS environment.

The research method is descriptive-analytical and based on the applied goal. Two methods of library-document studies and survey studies are used to collect information. Field studies are based on common techniques, namely questionnaires. The number of 5 Pirasheri villages with tourism capabilities, including Kohbad, Kolfarah, Abrak, Noorabad, and Kell Infern, have been emphasized in this study. The statistical population of the research is made up of visitors who entered the villages. The sample size for each village was determined as 20 people and a total of 100 visitors were questioned. Further, after collecting the data, through the VIKOR model, villages were analyzed and prioritized, as well as the required services. Also, AHP method and algorithms available in GIS including central location, hot-cold spots and clustering of spatial statistics were used.

The results showed that, in general, the most important needed and important services were accommodation services with an importance coefficient of 0.389. In addition, transportation services are known with an importance factor of 0.186. Two types of health services with a weight of 0.146 and catering services with a score of 0.099 are also recognized in the third and fourth ranks. The lowest weights of criteria in the field of services required for tourism development in Urban-Peripheral villages are related to two technology services with a weight of 0.052 and shopping services with a weight of 0.055. The rate of compatibility of values and pairwise comparison of data is also equal to 0.05, which is less than 0.1 and therefore acceptable.Based on the results of Vikor model, Noorabad village has received the first rank in the field of required tourism services with a weight of 0.857. In fact, this village has more weaknesses in the field of tourism services compared to other villages, and it is necessary to create and expand various services, including accommodation and hospitality services in this village. After that, the village of Kolfarah with a value of 0.813 is recognized as the second most needed tourist service. Kohbad village is ranked third with a weight of 0.767 and this village also needs to plan and create various tourism services.Based on the results of the central location algorithm in GIS and applying the calculated price weight, Kolfarah village is known as the central village in terms of services required by tourism; Because this village has had an acceptable weight in calculations, and secondly, compared to other villages, it needs more promotion and attention in terms of tourism resources and existing attractions.Examining the spatial autocorrelation index shows that this index is equal to -0.367787. Since this value is close to negative (-1), it can be concluded that the data do not have spatial autocorrelation and are scattered. Also, by referring to the standard value of z, which is equal to -0.822, the hypothesis of autocorrelation in spatial distribution can be rejected, and as a result, the random pattern in the field of tourism services can be confirmed. In fact, Urban-Peripheral villages have had a random pattern in terms of tourism services. Therefore, the randomness of services and the existence of spatial differences between urban tourism villages are confirmed and based on this situation, planning and prioritization of services in villages should be done.

In general, according to the results, it can be concluded that the Urban-Peripheral villages are not at the same level in terms of tourism services. Another point is that despite the geographical location and proximity to cities, many weaknesses in terms of services can be seen in them. This is the context. In addition, the result of the research indicates the lack of concentration of services in a single village. In other words, the services are scattered in all the villages and this issue has made it difficult for tourists to access all kinds of services in the shortest time and at the lowest cost. The innovation of the research, firstly, in terms of methodology, is the integration of Vikor model and spatial algorithms in the GIS environment, and secondly, the use of spatial statistics algorithms in the survey of rural tourism services, which has received less attention.

With the increasing volume of information and the complexity of financial markets, investors are increasingly seeking innovative financial tools to make more informed decisions. These tools should help investors choose the right stocks and achieve better returns. In this regard, stock recommendation systems are becoming increasingly important. Stock recommendation systems can assist investors in achieving superior returns by selecting the right stocks. However, traditional stock recommendation systems often lack the necessary accuracy and efficiency. This research aims to develop a novel approach called Stock-based Collaborative Filtering to design a stock recommendation system for the Tehran Stock Exchange. This method is founded on two key assumptions: first, market inefficiency, meaning the stock market does not completely and accurately reflect all available information; and second, the presence of hidden information in stock movements, indicating that these movements contain valuable insights that can influence the prices of other stocks in the market. In this research, assuming the existence of the transmission effect on the Tehran Stock Exchange, we used the collaborative filtering technique, a common algorithm in recommender systems, to design a stock recommender system. The purpose is to help investors select the best-performing stocks to outperform the market.

This study uses historical stock price data of 145 firms listed on the Tehran Stock Exchange from 2012 to 2021. The collaborative filtering algorithm was implemented in two stages: training and testing. In the training stage, the algorithm was trained using data from 2012 to 2016, and in the testing stage, its performance was evaluated on data from 2016 to 2021. Following, buy and sell signals were generated using the stock-based collaborative filtering algorithm during the same period. Finally, the strategy was evaluated.

The algorithm was tested as an investment strategy in both in-sample and out-of-sample periods. The results obtained from the algorithm for the out-of-sample periods show that this strategy can achieve a 25-fold return. The overall index returned 16 times during this period, indicating the excellent performance of the strategy over time. Additionally, the value at risk (VaR) for the selected method during the study period stood at -12.8%, indicating the lower risk of this method.

Stock-based collaborative filtering is an active investment strategy. This intelligent algorithm aims to identify undervalued stocks and achieve higher returns than the market. This algorithm can serve as a valuable tool for active investors seeking to identify valuable stocks and achieve higher returns than the market. Therefore, further research is necessary to examine the performance of this algorithm in different markets and diverse economic conditions. Also, it is recommended to implement risk control strategies and optimize the system's efficacy further.

In the realm of rural tourism, the duration of tourist stays is one of the important indicators of sustainability. Rural tourism becomes sustainable when it can significantly contribute to job creation, increase incomes, enhance cultural exchanges, and more. In essence, tourists can have positive outcomes for an area when their stay is prolonged, allowing them to utilize existing facilities and generate economic revenue for the geographic location. Various economic, social, infrastructural, and environmental factors can influence the improvement of tourist stay durations. Identifying these factors can illuminate barriers and limitations to tourism development and enhance the duration of tourist stays. One major and noteworthy factor in this context is the environment. Unlike previous research that emphasized the impact of tourism on the environment, this study focuses on the effect of the environment on tourism. In this research, Sheyvand village in Dezpart County, Khuzestan Province, has been selected as the study area. This study aims to examine and explain this issue. Thus, the primary research question is formulated as follows: Do the travel characteristics and environmental features of tourist villages (specifically Sheyvand village) influence the duration of tourist stays, and in what ways do these influences manifest?

This research is descriptive-analytical and exploratory in nature, based on the analysis of survey data. The data were collected using a researcher-designed questionnaire. The data analysis method is quantitative, relying on statistical tests and structural equation modeling. The statistical population of the research consists of tourists who visited Sheyvand village during the summer of 2023, selected randomly. The actual population of the study is not specified; however, given the researcher’s access to the statistical population and existing limitations, a sample size of 250 individuals was determined and surveyed. The validity was confirmed through expert review, and the reliability of the instrument was established with a Cronbach’s alpha coefficient of 0.790 overall. Ultimately, the data were analyzed using SPSS and AMOS statistical software. Data analysis was conducted using appropriate statistical tests as well as structural equation modeling.

An analysis of the results of the binary test regarding the impact of travel characteristics on the duration of tourists’ stay in rural areas indicates that factors such as the gender of tourists (0.184), transportation and accessibility to the village (0.950), the quality and price of rural accommodations (0.411), infrastructure facilities (water, electricity, gas) in the village (0.114), the hospitality of the local people (0.066), and local festivals and programs (0.146) were not significant at the 0.05 level. Examining the means of these characteristics shows that the travel characteristic of gender, with a value of 3.336, has a moderate impact on tourists’ length of stay. Additionally, transportation and accessibility to the village, with a mean of 3.432, infrastructure facilities with a mean of 3.492, and local festivals and programs with a mean of 3.564 also demonstrate a moderate influence on the duration of tourists’ stays, classifying them as situational and objective variables of travel. The analysis of the results from the binary test showed that other travel characteristics were significant at a level less than 0.05. The significance indicates that age and income, as background variables, have a moderate impact on the duration of tourists’ stay. Additionally, the price and cost of services, with a mean of 3.696, the location and distance of the village with a mean of 4.028, and access to the internet in the village with a mean of 3.672 are recognized as other important factors that affect the duration of tourists' stays in rural areas.
The overall model regarding the impact of the environmental characteristics of the village on the duration of tourists’ stays indicated that the role of environmental characteristics was statistically significant at a 99% confidence level. A higher critical ratio estimated at 2.58 (a critical ratio above 2.58 indicates the significance of the effect) also demonstrates the significance of the independent variable of the study (characteristics) on the dependent variable (tourists’ length of stay). In summary, the 18 examined characteristics, including the village's landscapes and beauty, cleanliness of the environment, diverse attractions (historical, natural, etc.), proper sewage disposal, the pristine nature surrounding the village, effective waste management, availability of diverse aquatic attractions (rivers, springs, etc.), diversity in agricultural production (pomegranate orchards, rice, etc.), the plant cover of oak trees, low pollution levels in the village, waste separation in the village, etc., can influence the duration of tourists’ stays in rural areas. The analysis of the impact of the 18 influential factors shows a total effect of 0.91, indicating that these examined factors can explain approximately 91% of the variance in the positive role and effects on the duration of tourists’ stays. According to the results of this model, the greatest impact comes from the local residents’ attention and sensitivity to the village’s environment, with an effect size of 0.81, which actually has the most significant influence on tourists’ length of stay. Effective waste management in the village, with an effect size of 0.79, and the presence of environmentally compatible accommodations in the village, with an effect size of 0.78, are recognized as the second and third most influential characteristics affecting the duration of tourists’ stays. Overall, the 18 characteristics examined as the environmental features of the village have been influential on the duration of tourists’ stays.

The results of this research indicated that the rural environment, as a significant indicator, can influence the length of tourists’ stay in rural areas. This influence can be achieved through various environmental (natural and human) actions and characteristics. It is recommended that considering the impact of the environment on the length of tourists’ stay, an effective operational program should be emphasized to strengthen the environmental indicators of target tourism villages, such as Sheyvand village.

Knowing the areas prone to tourism development, including nomadic tourism, can be a platform for planning and development. Kohrang region in Chaharmahal and Bakhtiari province has a favorable capacity for the development of nomadic tourism due to the nomadic community. Considering this capacity, proper planning should be done according to its land use. The aim of this research is to evaluate the land suitability of Kohrang region for nomadic tourism planning in the geographic information system (GIS). The descriptive-analytical research method is based on the spatial data of the country's mapping organization in 2012. The analysis was done based on the fuzzy AHP method in Arc GIS software. The data were fuzzified and standardized in the software environment. In order to compare the criteria and sub-criteria, the opinion of 10 experts was used for comparison in the Expert Choice software. Finally, the maps related to each criterion were prepared and finally, the land suitability map was compiled for regional tourism planning. The results showed that eight criteria can be used in evaluating land suitability for nomadic tourism planning. Three criteria of proximity to water resources with a weight of 0.268, land cover with a weight of 0.237 and proximity to the road with a weight of 0.145 were recognized as the most important criteria in evaluating the suitability of land for nomadic tourism. The results showed that the most suitable land for nomadic tourism was 258.471 square kilometers, which is equivalent to 12.80% of the area of the region. Also, relatively suitable lands for the planning of nomadic tourism have been allocated 27.57% of the lands of the region. The analysis of Moran's algorithm in the field of the pattern of distribution of lands susceptible to nomadic tourism shows that the identified lands are distributed in clusters and the most concentration of susceptible lands is located in the northwestern and eastern parts of the region. In general, the region has suitable lands for planning and developing nomadic tourism.

Rural settlements have been formed under the influence of different environmental indicators. Today, planning for rural areas requires a correct recognition of the available natural opportunities and the use of optimal decisions. Spatial or environmental data play an important role in this context. Accordingly, in this research, the goal is to know the effective environmental data on rural issues and then analyze these data in the formation of rural settlements and prioritize them in terms of settlement in geographical areas. The descriptive-analytical research method is based on the spatial data of the country's mapping organization. In this research, 13 indicators, or spatial data, were used. The data standardization method was the fuzzy AHP method. The method of data analysis was using different algorithms in Arc GIS software, including interpolation (IDW and Kriging), the weighted sum overlay algorithm, and weighting in the model (IO). For weighting and comparison of criteria, experts' views were used as a panel (10 people) based on the AHP method in Expert Choice software. The result of the research showed that the geomorphology index of 0.455, the land cover index of 0.263, the distance from hazards index of 0.141, and the climate index of 0.141 played an important role in the establishment of rural settlements, respectively. The overlapping analysis confirmed that more than 121 rural points (10.38%) are in poor condition, 334 village (28.6%) have been evaluated in average condition and 713 villages (60.89%) in good condition.

Recognizing customers` requests and offering them personal investment suggestions is an essential aspect of a useful and effective consulting strategy. Many households trust financial advisors for investment guidance. Intelligent data analysis is one of the fields of artificial intelligence that solves the problem of learning automated systems without an explicit program. Financial companies have found that they need to adapt quickly to the environment and use automated systems to save money on the cost and accuracy of financial advice to investors. In recent years, a type of technology-based counseling has been introduced as an alternative to Robo Advisors. Robo Advisors is a financial advisor who can assist through machine learning algorithms to automatically analyze the financial product risk level and provide portfolio advice. Robo Advisors are digital platforms that offer algorithm-based and automated financial planning services such as investing. In this study, a systematic review of the empirical studies done on Robo Advisors is given and at the end, a proposed framework for designing Robo Advisors is presented.

Tourism as a vital economic sector necessitates infrastructure development. Within this context, provision of tourist accommodation stands out as a crucial service for sectoral growth, requiring optimal siting based on diverse regional indicators and capacities.

This study aimed to identify potential areas for establishing tourist accommodation in Dezpart Region in Khuzestan Province. Additionally, it conducted a comparative analysis of fuzzy overlay models to assess their respective outcomes.

The research employed a descriptive-analytical approach based on spatial data. Fuzzy logic analysis was conducted using ArcGIS software, involving data standardization, fuzzification using established algorithms, and application of the Analytic Hierarchy Process (AHP) model to derive criteria weights. The fuzzy overlay methods were then utilized to generate the final map.

The results indicated that, among the 9 criteria examined, the distance from tourism sources (with a final weight of 0.290) and the distance from fault lines (with a weight of 0.192) were the most influential in identifying areas suitable for tourist accommodation. Furthermore, analysis of the fuzzy overlay models confirmed that the Gamma model was more stringent and pessimistic compared to the Sum model. According to the Sum fuzzy model, over 39.41% of the area was deemed suitable, whereas the Gamma model identified only 10.3% as suitable for accommodating tourism services. The overall quality assessment also supported the superiority of the Sum model in delineating potential areas for tourist accommodation. Examination of the spatial distribution of the final maps revealed a greater concentration of suitable areas in the central and northern regions.

Establishment of tourist accommodation facilities at the regional level is an indisputably significant matter. However, determining the optimal siting of these services necessitates the utilization of various methods and amalgamation of diverse criteria, a task well-suited for the capabilities of a Geographic Information System (GIS) environment. Dezpart Region in Khuzestan Province, which was designated as a new city in 1401, possessed multifaceted potential for tourism development, alongside its agricultural sector. The region boasts a rich array of tourism resources and attractions, encompassing historical, natural, rural, and cultural elements and thus underscoring the imperative for strategic planning in this area. A pivotal aspect of this planning involves identifying the most suitable locations for establishing tourist accommodation centers. This endeavor not only contributes to the fundamental advancement of tourism, but also aids in attracting tourists over the medium and long terms. Consequently, this research aimed to identify potential areas for establishing tourist accommodation in Dezpart Region in Khuzestan Province, while also conducting a comparative assessment of fuzzy overlay models to discern the most effective approach. 

The research methodology employed in this study was descriptive-analytical and practical in nature. Data collection and analysis were conducted using documentary and organizational methods. The primary data utilized for map preparation consisted of the spatial data obtained from the country's mapping organization. To process the spatial data, operations, such as equalization, data formatting, ground referencing, and data adaptation, were performed. The criteria considered in this research encompassed elevation, slope, land use, distance from communication roads, distance from urban and rural settlements, proximity to tourism attractions, proximity to water sources (rivers), and distance from fault lines. Subsequently, the data underwent standardization and fuzzy logic analysis within the ArcGIS software. Weighting the criteria was done by using Expert Choice software and the Analytic Hierarchy Process (AHP) method. Consequently, the weights of the influential criteria for locating tourist accommodation centers were established. Finally, employing various fuzzy models or operators, including Gamma and Sum, a map was generated to identify potential areas for establishing accommodation-tourism centers. 

In this study, the criteria of distance from communication roads, rural and urban settlements, and proximity to tourism sources were assigned a value and membership of 1 for locations with shorter distances. This was because, for instance, closer proximity to communication roads or tourism resources signified greater suitability for accommodation-tourism services, making closer areas more pertinent for the research objective. A linear function was employed to fuzzify the map for these criteria.Utilizing the Gaussian function, a threshold limit was established such that any deviation beyond this threshold, whether an increase or decrease, would result in a value of zero for the areas or locations. For instance, a threshold limit of 3 km was set to assess the distance from water sources with values approaching zero for deviations from this threshold.Additionally, a small function was utilized to fuzzify the elevation and slope criteria with respective threshold limits of 1700 m and 25%. Consequently, areas with lower slope or elevation were assigned a membership grade of 1. Conversely, a large function was employed to fuzzify the distance from fault lines (with a threshold limit of 10 km) and land use (with a threshold limit of 4), resulting in areas with greater distance or value being assigned a membership grade of 1, thus denoting their suitability.The results revealed that among the 9 criteria examined, the distance from tourism sources (with a final weight of 0.290) and the distance from fault lines (with a weight of 0.192) were the most influential in identifying areas suitable for accommodation-tourism services. A comparison of the proposed maps indicated that the Sum overlay method identified more potential areas for accommodation-tourism services in the region compared to the Gamma method. Furthermore, the Sum method encompassed the central, western, and eastern areas, while the Gamma method suggested a narrow line in the central area for tourist accommodation. Notably, the proposed area deemed highly suitable for creating accommodation-tourism places covering 39.27 km2, which was equivalent to over 3.10% of the region's area, in the Gamma overlay method. In contrast, the Sum method identified 499.72 km2, representing 39.41% of the region's area as highly suitable for accommodation-tourism services. 

Analyses of the fuzzy overlay models revealed that the Gamma model was more stringent and pessimistic compared to the Sum model. According to the Sum fuzzy model, over 39.41% of the area was deemed suitable for creating accommodation-tourism services, whereas the Gamma model identified only 10.3% as suitable. The overall quality assessment also confirmed the superiority of the Sum model in delineating potential areas for accommodation-tourism services. Examination of the spatial distribution of the final maps further indicated that the susceptible areas were more prevalent in the central and northern geographical regions.

Today, tourists visit many areas due to branding. Hospitality is known as an intangible source of tourism development in Iran, which is less introduced to tourists and proper planning has not been done in this field. Therefore, the aim of the research is to identify the effective factors in the branding of hospitality culture in Iranian tourism.

Design/methodology/approach: 

The descriptive-analytical research method is based on field data collection. Both qualitative and quantitative methods were used in this research. In the interview section, 11 people and 75 experts in the field of tourism were studied in the questionnaire. Analysis was done by content analysis and statistical tests.

The results showed that 15 factors are effective in branding hospitality culture in Iranian tourism. The test showed that the most important factor is the registration and introduction of hospitality culture as a tourism brand of Iran with an average of 4.493. The two factors of reducing foreign political disputes with an average of 4.213 and improving the security index of foreign tourists with an average of 4.173 are known in the next ranks. Modeling confirmed that the effective factors of hospitality culture branding have a total effect of 0.54 d. In this context, the most influential factor was related to advertising and introducing intangible attractions with an explanation of 0.871.

All in all, various factors are influential in the branding of hospitality culture, and these factors can also lead to the growth of Iran's tourism. It is suggested that different aspects of hospitality culture should be studied for branding.

Originality/value:

 The innovation of the research is that little research has been done in the field of hospitality culture branding in Iran.​

The stock market, as a prominent financial domain, presents a formidable challenge in comprehending and evaluating an extensive array of stocks employing centrality measurements to portray the key variables within a network, companies' stocks can be visualized and comprehended. The utilization of stock network analysis facilitates a comprehensive understanding of the entire network through diverse visualization techniques. This study delves into the data of the top 50 companies listed on the Tehran Securities Exchange during the period from January 1, 2019, to July 6, 2021. Employing unsupervised machine learning tools such as Community Detection algorithms and network analysis methods like Louvain and Girvan-Newman, we construct a stock network. Subsequently, we compute five Centrality Metrics, including Degree Centrality, Closeness Centrality, Eigen Centrality, Betweenness Centrality, and PageRank, for these companies. By formulating a similarity matrix based on these criteria for the remaining stocks in the network, we determine a portfolio of 25 stocks suitable for investment, derived from the ranking of stocks according to the Centrality Metrics

Security is one of the important categories of sustainable development, which is influenced by various factors. Some effective factors in this field are known as social factors. Each region has its own social, cultural and economic conditions, and these differences show the necessity of knowing the social factors in each region. The purpose of this research is to investigate social factors affecting sustainable security in Izeh county and to provide solutions to improve it. The research method is descriptive-analytical and based on the collection of field data (survey). The data collection tool was a questionnaire. The statistical population of the research was formed by experts, and 85 people were determined as the sample size using the snowball method. The validity of the questionnaire was confirmed through elites and the reliability was also confirmed with Cronbach's alpha greater than 0.70. The result of the research showed that all social factors affecting sustainable security were significant at a level less than 0.05 and equal to 0.000. According to the results, the highest average is related to the factor of preventing discrimination with a value of 3.058 and the lowest average is related to the factor of creating employment for young people with a value of 1.411. Therefore, comparing the minimum and maximum average of social factors shows that there is an unfavorable situation. Among other social factors affecting stable security, they have a weak status: equal opportunities (2.435), management of moral and social networks (2.564), regional tourism development (1.788) and social identity in the region. (2/400) pointed out. The result confirmed that the promotion of social factors can be effective in improving the sustainable security of the region. In this context, the factor of improving the social identity of the region with a beta value of 0.694;

Security is one of the important indicators for the development of the tourism industry. This index can affect various variables, the most important of which is the length of stay of tourists. The length of stay of tourists plays an essential role in the economic and social development of tourist areas. The purpose of this study is to investigate the role and effects of security indicators from different aspects on the length of stay of tourists in Chaharmahal and Bakhtiari province. The research method was descriptive -analytical and based on data collection through a survey method using a questionnaire. The validity of the questionnaire was performed and the reliability was confirmed with Cronbach's alpha greater than 0.70. The statistical population of the study consisted of tourists in six areas, including the city of Chelgard and the villages of Dimeh, Sheikh Alikhan, Sar Aghasid, Benovastaki and Qaleh Tabarak, but no statistics were available on their number. The sample size of 250 tourists was determined. The result showed that 17 factors affect the length of stay of tourists at a significant level less than 0.05. The most influential factor is related to the price and cost of services with an average of 3.99 and then the factor of accommodation with an average of 3.89. The results of one -sample t -test showed that the three indicators of socio -cultural security, economic security and security indicators of tourist resorts, at a level of less than 0.05, affect the length of stay of tourists. Also, the regression result indicates the effect of 32% economic security index, 25% social and cultural security index and 21% security of tourist accommodation index on the variable of tourists' stay. Assessing the status of the security component in tourist areas with a significance level of less than 0.05 and an average of 3.29 confirms that the status of the security component is moderate .

Network analysis is one of the methods of attention of analysts to analyze complex relationships in data in an intuitive way. One of the applications of network analysis is illustrating the relationships between different classes of assets. Identifying stock market dynamics is essential for actors, investors, and financial policymakers. The stock market is considered a complex system that shows its complex dynamics. The complexity of the stock market can have several reasons that the interdependence of stocks can be one of the most prominent of these factors. One of the most important concerns of people in the capital market is finding a way to present and analyze stock data of different companies. There are different companies in the stock market and portfolio managers and investors, in choosing the right stock portfolio, need to consider the best way to form a stock portfolio. This article discusses the formation of diverse and non-diverse portfolios through network theory. To conduct this research, the adjusted final price of 138 listed companies for the period 2017-01-01 to 2021-07-06, equivalent to 1648 trading days, has been used. To describe the effect between stocks, the Adjacency Matrix is used and using the optimal threshold, diverse and non-diverse portfolios are obtained. We implement the results of selected stocks for the portfolio using the Hierarchical Risk Parity (HRP) approach based on clustering methods and the results with three methods of Minimum Variance (MVP), Uniform Distribution (UNIF), and Risk Parity (RP) for both in-sample and out-of-sample periods are compared for both diverse and non-diversified portfolios. Finally, the results have been compared using the four criteria of Sortino, Sharpe, Maximum DD, and Calmar. The results show the superiority of the non-diversified portfolio approach in market downturns and the superiority of the diversified portfolio approach in other periods.

The development of tourism in rural areas depends on various indicators including services. In fact, services are one of the most important needs to attract tourism and continue its sustainability in rural areas. Therefore, it is undeniable that villages have various services for the development of tourism. In this research, the aim is to investigate the state of tourism development services in the target rural areas and then formulate the optimal strategies in this field. In this study, Shayvand village in Dezpart county of Khuzestan province has been selected as a target village for tourism. The research method is descriptive-analytical and based on survey data. The statistical population of the research is made up of tourists, 160 of whom were randomly questioned. The validity of the questionnaire was confirmed through elites and the reliability was also confirmed with Cronbach's coefficient equal to 0.802. The result showed that the types of tourism services were quantitatively and qualitatively significant at the level of less than 0.05. Quantitatively, the average of the test was equal to 3.128, and as a result, the quantitative status of the service was evaluated as average. In this field, the services related to visiting attractions have the best status with an average of 4.437. In terms of service quality, the average equal to 2.245 confirms that the quality of tourism services is evaluated poorly. In order to improve the quality and quantity of tourism services, 4 strategies are presented, including expanding the quality of services (37.059), improving social capital (25.374), protecting and improving the quality of the environment (9.524) and emphasizing local capacity (7.959) has been.

Nowadays, nomadic tourism has become very important due to its connection with nature and local culture. The construction of nomadic tourism ecocamps is a clear example of planning in this field. In this regard, planning for its growth and development is essential.Purpose of the research: The purpose of this research is to identify and locate potential areas for nomadic tourism ecocamps in Chaharmahal and Bakhtiari region.

The descriptive-analytical research method is based on spatial data and a questionnaire using the paired comparison method. The statistical community is made up of experts related to the subject, 30 of whom were selected to compare pairs of indicators using the AHP method. Algorithms in GIS were also used to draw maps and to locate areas prone to the construction of nomadic ecocamps. The research indicators are height, slope, soil, land use and cover, proximity to water sources, distance from protected areas, distance from fault line, distance from landslide, average annual temperature, average annual precipitation, proximity to communication road, Proximity to the city, proximity to the village, population density.Geographical area: The geographical area of the research is the nomadic areas of Chaharmahal and Bakhtiari province.Findings and

The most important criterion for the establishment of a tourism ecocamp is proximity to water sources with an importance factor of 0.148. After that, indicators of proximity to the communication road with an importance factor of 0.130; Land use with a weight of 0.109 and distance from landslides with a score of 0.096 are known.

The results showed that 10 ecocamps including Chelgerd, Shermak, Hirgan, Sheikh Alikhan, Shaleel, Samsami, Barz, Qala Madrasa, Maze Sokhte and Keri Beniche can be designed and planned for the development of nomadic tourism in this region.

Tourism is one of the main drivers of rural development, which requires basic planning To actualize rural tourism, according to each region, the upcoming obstacles should be identified and suitable solutions should be adopted in line with them. The rural areas around Darian dam in Paveh county are known as one of the tourist areas which, in addition to natural capacities, hasspecial importance due to the creation of Darian dam and lake. The purpose of this research is to identify and analyze the challenges and strategies of tourism development in the rural areas around Darian Dam. The research method is applied in terms of purpose and in terms of the nature of data collection, it is a survey based on questionnaire and interview technique. The statistical population of the research is made up of the residents of three villages around the dam, including Hajij, Dariyan and Vera. Their population was equal to 1298 people and based on Cochran's formula, the sample size was calculated as 296 people. The validity of the questionnaire was confirmed through the elite community and the reliability was also confirmed through Cronbach's alpha with a coefficient of 0.79. The result of the T-Tech test of a sample confirmed that the changes in tourism in the villages with the construction of the dam were at a significant level of less than 0.05 and the average was 2.79, which indicates the poor condition and lack of influence of the dam in the development of tourism in the villages. In addition, the result showed that local people have pointed out more than 21 challenges in the field of rural tourism development, which using factor analysis in five challenges including infrastructure (31.820 percent), management (21.314 percent), education and Supportive (18.832 percent), financial (7.399 percent) and environmental (5.241 percent) are categorized. The most important tourism development strategies in order to solve the challenges were identified as including the development of services and infrastructure (31.608 percent), investment and prosperity of economic activities (27.033 percent), and cultural and media activities (8.925 percent).

Tourism, as a dynamic industry in the regional and territorial economy, can manage many social and economic challenges. In this regard, recognizing the obstacles ahead in the first stage and then presenting effective strategies in the second stage, can help the development of tourism in each region; Because each region, regardless of major tourism issues, has its own obstacles and strategies. Dezpart county was separated from the Izeh county  in 1400 and is known as a separate political area. Therefore, on the one hand, considering that this city has recently become administratively independent and planning for its development by managers and officials is very important and vital, and on the other hand, one of the programmable capacities for its development is tourism. Obstacles and strategies for the development of this industry can not only provide a proper knowledge to the authorities, but also can identify important obstacles and strategies for the development of tourism in the Despart region for optimal and sustainable planning. The purpose of this study is to identify obstacles to tourism development in the Dezpart County and then provide effective strategies to address these obstacles

Due to its descriptive-analytical nature, the research method is in-depth and applied in terms of purpose. It is also quantitative-survey based on method. The statistical population of the study is the population of Despart region in 2016 equal to 19,351 people. Based on the calculation of Cochran's formula, the sample size was calculated to be 377 people. There are 84 villages and one urban point in this area, and it was not possible to conduct interrogation operations in all of them. Based on this, the city center (Dehdez city) and rural areas over 400 people in this study were selected for questioning, the number of which was 7 villages. Therefore, Dehdez city and the villages of Shivand, Faleh, Kalimalek, Mallah, Chaman, Deh Kian and Mozarm were selected in this study. The data collection tool was a questionnaire whose validity was confirmed by the elite community and its reliability was confirmed by Cronbach's alpha with a coefficient of 0.74. SPSS software was used for data analysis.

The result of one-sample t-test at the level of indicators shows that all four indicators of environmental barriers, managerial barriers, socio-economic obstacles and infrastructure barriers are significant at the level of less than 0.05. In other words, the study of the results at the level of indicators shows that in order to develop tourism in the region, managerial, environmental, infrastructural and socio-economic obstacles play an important role. The study of the difference between the average of environmental index (0.111), socio-economic index (0.160), management index (0.965) and infrastructure index (1.012) also confirms this in all four dimensions in the field of tourism development. They have a great impact and action should be taken to remove these obstacles.The strength of effective obstacles (environmental, socio-economic, infrastructure and management) in the development of tourism in the region is not the same. Environmental barriers with a rate equal to 0.113 units predict the tourism development variable, which means predicting 11% of the changes in this variable. Also, managerial obstacles with a rate of 0.176 units, means a forecast of 17% of changes in tourism development. In other words, managerial barriers to the development of tourism in the region are 17% effective. Infrastructural obstacles with an amount of 0.231 units, ie 23% of the explanation has also been effective. Socio-economic barriers can also explain more than 13% of tourism development variables.

The analysis showed that environmental, socio-cultural, managerial and infrastructural obstacles have a great impact on the development of tourism in the Dezpart region. These obstacles are 65% effective, with infrastructure barriers with a coefficient of 0.231 having the most impact and environmental barriers with a coefficient of 0.113 having the least impact on tourism development in the region. In order to remove obstacles, six strategies of cultural planning, integrated management, improving services and facilities, capacity measurement and product supply, development-infrastructure development and improving tourism knowledge were presented.According to the results and strategies of tourism development in the region, it can be suggested that cultural planning, management reform, increasing knowledge and awareness of the local community about tourism and its effects, improving tourism technology, developing access and development of the region and finally improving Tourism services in the Dezpart region should be considered.

Tourism development in any region requires attention to certain indicators and their improvement. One of the most important elements related to tourism is cultural elements. This research aims to investigate the impact of cultural elements on the development of tourism in Dezpart County. The research method is based on the objective, descriptive-analytical and quantitative approach. The data collection tool was a questionnaire whose validity was confirmed by the elites of the society and its reliability was also confirmed using Cronbach's alpha test (0.79). The statistical population of the research was made up of experts from the administrative offices in Dezpart County. Exact statistics on the number of available experts were not available, but 50 experts were surveyed in this study. The findings showed that the tourism development indicators, except for two variables of historical-cultural attractions with an average of 3.66 and security with an average of 3.68, do not have a desirable status in the region. Pearson correlation indicates that there is a relationship between cultural elements and tourism development. It was found through regression analysis that the highest impact on regional tourism development is related to the variable of historical and cultural attractions with a coefficient of 0.163, followed by education and literacy with a coefficient of 0.132. Therefore, the cultural elements of the region have the potential to develop tourism and overcome existing challenges. Four cultural strategies are proposed for tourism development, including participation and community organizations, management and planning of services, education and skilled workforce, and empowerment of women.

Green tourism can create new opportunities and play an important role in keeping cultural and local traditions alive. Kohrang region is an important ecotourism regions that attracts many tourists every year due to its pristine natural areas. The first step in the direction of tourism development in this region is to examine the status of green tourism indicators and then providing appropriate solutions.The research method is descriptive-analytical and based on survey data. The statistical population of the research consists of the population living in the rural areas of Kuhrang city totaling 35183 people, which was determined as 379 people .The validity of the questionnaire was confirmed by using elites and reliability with Cronbach's coefficient equal to 0.78. The result to measure the level of green tourism indicators in Kuhrang region is significant at a level of less than 0.05. Among the 21 examined indicators, the security index with an average of 4.03 is of good condition and the indicators of preserving cultural and local traditions (3.59), improving technology and the Internet (3.47) and managing waste and garbage (3.43) ) had an average status in Kuhrang region. Other indicators of green tourism have had a weak situation. Also, the result showed that 6 strategies include management and formulation of laws, culture building and educational, advisory and credit services, establishment of tourist accommodation and villages, local participation in environmental protection, development and distribution of tourism services and environmental protection based on existing capacities for the development of green tourism in the region.

The problem of securities optimization is a significant financial problem, and the issue of choosing the optimal stock portfolio has long occupied the minds of investment professionals. Under uncertain conditions, it is essential to determine asset allocation. The creation of a portfolio of investments is one of the most common financial challenges faced by investors. For them, building a portfolio of investments that yields the highest level of profit is imperative. Various methods have been introduced to construct a portfolio, the most famous of which is the Markowitz approach. There are numerous shortcomings with mean-variance theory due to its difficulty in estimating expected returns and covariances for different asset classes. The problem with the Markowitz variance-mean method, estimation errors, and inconsistencies led to the development of several other academics' attempts to find possible portfolio solutions that would lead to optimal asset allocation. To overcome this problem, Marcos Lopez de Prado was the first researcher to propose a hierarchical model for portfolio construction in his famous paper “Building Diversified Portfolios that outperform out-of-sample”, in 2016.

The present study is applied in terms of purpose, quantitative in terms of the implementation process, and retrospective and post-event in terms of time. This research focuses on the application of machine learning in selecting the optimal portfolio and its purpose is to find a stock portfolio optimization method that has superior performance in prototype simulation for the Tehran Stock Exchange. In this study, we use the Hierarchical Risk Parity (HRP) machine learning technique and compare the results with the minimum variance approach. The concept of HRP is based on graph theory and machine learning techniques and can be divided into three main stages including tree clustering, quasi-diagonalization, and recursive bisection. To conduct this research, the adjusted closing prices of 30 listed companies for 760 trading days from 2018 to 2020 were used. Missing values were filled by propagating the last valid observation forward

To evaluate portfolio performance, the Sharpe ratio was measured for both in-sample and out-of-sample periods. The results of in-sample and out-of-sample analyses showed that the Hierarchical Risk Parity approach performs better than the minimum variance approach.

In this study, the researchers employed a novel asset allocation method – Hierarchical Risk Parity (HRP) which has the most desirable diversification properties. HRP provides a meaningful alternative to traditional asset allocation approaches and an important risk management tool for investors. Therefore, portfolio managers should have an active approach in evaluating each method according to the conditions and situations in which they are.

Establishing an investment portfolio is one of the main concerns of managers and investors who are always looking for an effort to form the best investment basket so that they can achieve the most returns. So far, there have been many ways to form an investment basket, the most famous of which is Maritz's approach. The average theory of variance has many practical drawbacks due to the difficulty in estimating the expected returns and covariance for different asset classes. The purpose of this study is to maximize risk -adjusted return on the portfolio using PCA method in a data base of stock returns. The data base used for this case study is the daily data modified of 50 top stock and relevant stock index companies for the period 25/4/2016 to 7/2/2021 for 1027 trading days. We use a dimensional reduction algorithm (PCA) to allocate capital to different asset classes to maximize risk -adjusted returns and the results are compared with the equal weight allocation approach (1/N). There is also a post -test framework for evaluating the performance of the investment baskets provided. According to the results, the variance explained by the three main components can be an indicator for identifying the most important business risks.

The financial crisis of 2007-2008 has been the subject of research in different ways. The role of quantitative models and mathematical theories in the occurrence of this crisis and the other complications that such models cause in financial markets is the main theme of the book “Lecturing Birds on Flying”. By explaining the role of the educational system in creating a gap between theory and practice and the role of Quants in promoting and applying quantitative and computational models, the author gives a different account of the causes of financial crises. In this article, while examining the form and content of this work, by analyzing the theme as well as textual analysis techniques, the most important themes of this work as well as its foundations and place in the texts of financial knowledge are reviewed. Criticism of models such as value at risk, option pricing model, and copula functions has shown their contribution to bankruptcies and crises and has suggested that reform of the management and economics education system would make the financial models more realistic.

The clustering of cryptocurrencies as an emerging field in investment management is the main topic of this research. Applying the information-based distance matrices, we clustered the 30 most valuable cryptocurrencies. Then, we identified the most influential clustering by the concept of Minimum Spanning Tree (MST) and the centrality measures of graph theory. A second-order clustering, which is defined as the clustering of hierarchical clusterings, was applied to cluster 56 dendrograms. Using the most influential clustering, we identified the main clusters of cryptocurrencies and sub-clusters. The results showed that the clustering composition of cryptocurrencies changed at the period I (before COVID-19) and II (pandemic time).

With the development of science and technology, large volumes of structured, semi-structured, and unstructured data are generated daily at breakneck speeds from various sources. This data generated by different users share many common patterns that can be filtered and analyzed to make recommendations for a product, goods3, or service of interest to users. Recommender systems are software tools that are used to provide suggestions to users based on their needs. One of the critical issues in recommender systems is providing personalized advice that fits the users' mood.

In this research, with the bibliometrics approach using bibliometrix library in R software, all the researches done on the application of recommended systems in personalization is reviewed.

In this research, using the bibliometrics approach, while defining recommender systems and their types, an overview of the field of personalization is introduced, and different types of personalization are presented. It also discusses the process of personalization and describes recommender systems as an integral part of this process. The following are the challenges that exist for implementing recommendation systems, and finally, the areas in which the issue of personalization of recommendation systems can be raised.

The results of this study with a comprehensive review of all research in this field can help researchers in ideation and selection of appropriate methods in classifying and analyzing data as a toolbox for the use of recommender systems in personalization.

The tourism industry with a multidimensional nature, in addition to meeting the needs of tourists, causes major changes in the host community system. Therefore, the government is trying to provide the opportunity to benefit from the positive aspects of this industry by providing and valuing tourist attractions in areas with potential.Order and security are the main prerequisites for the development of tourism. In this context, ecological analysis of order and security can provide a general framework based on the capabilities and limitations available for rural tourism planning. Ecological analysis of order and security is one of the best practices and frameworks for better understanding of areas and planning for order and security in tourism; Because ecology is formed from the combination of natural and human factors, and if a plan is based on different canons, many of the problems in the field of order and security are also addressed.The purpose of this research is ecological analysis of order and security in rural tourism in Isfahan province.

The research method is descriptive-analytical in nature and based on field data. The data of this study are qualitative and collected through interviews. The method of data analysis is qualitative content analysis. The statistical population of the study consisted of experts related to tourism and rural development, which was 15 people according to the theoretical saturation stage and repetitive results. In fact, the snowball method was used to select the sample and due to the fact that the results of the interviews were close to each other and reached the repetition stage, so it was not necessary to continue interviewing more people. After collecting the interviews, coding and data analysis began. In order to analyze the data, the data were coded according to the collected findings. Then they were organized and the final results were obtained.

According to the ecological framework, which is based on natural and human factors and the relationship between the two, the study area was divided into three classes. Mountainous area, dry plain and arid-desert. The analysis of various experts on order and security in rural tourism in the mountainous region is included in 11 cases. In interviews with experts, these 11 factors in the field of order and security and its maintenance in the direction of rural development and ultimately rural tourism is considered effective, which is the reason for not using new methods in irrigation to reduce water issues as the most important factor. Experts' analysis of order and security in rural tourism in the dry plain area has been summarized in 12 cases. Accordingly, one of the most important factors that play a role as a threat to order and security in the villages of this area is the lack of proper management methods in the field of water resources. The issue of water in the villages of the province is becoming a problem, and in some cases, it has led to many security issues, and on the other hand, it has overshadowed the order and security of many villages. According to them, the lack of employment and economic activity in the villages of the desert area is one of the most important factors.Qualitative content analysis is based on the opinions of 15 experts related to rural development and tourism issues. The results were presented in two sections: natural and human factors. According to experts, the natural factors influencing the management of order and security of rural tourism can be summarized in ten key concepts. One of the most important of these concepts is water management. Also, in terms of human factors influencing the order and security of rural tourism in Isfahan province, diversification of the rural economy is one of the first key concepts inferred from interviews with experts.

The results showed that water management, drought management, development of natural tourism attraction, strengthening of desert tourism are from the most influential natural factors and diversification into rural economies, population stabilization and reduction of migration, strengthening of facilities, improving access roads and reducing unemployment the most important human factors Influencing the order and security of rural tourism. The eastern part of the province, which is mostly plain and desert, has more restrictions on the order and security of rural tourism. The most important requirements of security and order in rural tourism can be mentioned to remove blind spots desert, the development of clean energy, division of the province to tourism areas, population stabilization, Local community participation, the management of water resources and etc.In general, considering the natural and human structures of Isfahan province and in more detail its rural settlements, the model of order and security in rural development and tourism is defined and framed accordingly. In fact, the management challenges of rural tourism order and security in the province are not only due to human issues, but are mostly rooted in natural issues and lack of proper management in this area. Geographical algebra of the environment can be the best description in this field and this issue can not be ignored in the province, especially in the east. Based on this concept and in line with it, the model of order and security in rural tourism should be defined. In fact, the management and model that is implemented in the villages of the mountainous area can not be applied in the desert area; Because, first of all, the type of crimes and security problems are different in these two areas. Secondly, its natural and human structures are very different. Based on the prevailing natural and human structures and according to different ecosystems, the pattern of order and security of rural tourism should be redefined.

Tourism development can always play an important role in the development of different regions. But the development of this industry requires the improvement of various indicators, including increasing the length of stay of tourists. In this regard, there are various factors, including the security of tourist areas. One of the important aspects of tourism security is the component of economic security. In this study, the purpose of this study is to investigate the impact of economic security index on the length of stay of tourists as a case study in Koohrang County. The research method is descriptive-analytical and applied. The statistical population of the study is tourists, but there are no accurate statistics in this field. Due to cost, time and space constraints, 250 tourists were interviewed. Sampling was done randomly. The validity of the questionnaire was confirmed by the elites and the reliability was confirmed by Cronbach's gradient equal to 0.79. Analyzes were performed in SPSS software. The result of one-sample t-test showed that the economic security index was significant at the level of less than 0.05. The study of the mean of variables shows that the absence of an unemployed local community with an average of 3.93 is recognized as the most important factor of economic security affecting the length of stay of tourists. Also, the factor of the status of local community products with the amount of 3.83 and then the appropriate access of tourists to the shopping center with an average of 3.78 are in the third place. The result of ANOVA test also confirmed that there was no significant difference between the studied tourist areas in terms of economic security index at the level of more than 0.05 (equal to 0.901) and all areas have the same conditions.