The Tissues of the city is considered one of the elements of the urban form effective on the occurrence of theft crimes. Therefore, the current research seeks to investigate the effect of urban context on spatial-temporal patterns of robbery crimes in Mashhad. The research method is descriptive-analytical and based on spatial analysis models. The statistical population includes theft crimes in Mashhad in the period of 1390-1400. In order to analyze the data, Geoda and ArcGIS software and spatial-statistical models such as Moran's spatial autocorrelation and spatial-temporal cube model were used. The results of the research indicate that 58.9 percent of theft crimes have occurred in fine fabrics. In fact, uses with an area of 50-75 square meters have the highest amount of theft crimes. Investigating the effect of urban context classification on theft crimes showed that 60.43% of the thefts occurred in peripheral contexts (marginal areas of Mashhad city, areas 4, 5, 7, 15, 16 and parts of area 13). Also, 19/2% of crimes are in checkered patterns (localities located in the west of Mashhad), 14/6% in star patterns (the central part of the city and around the holy shrine of Razavi) and 5/7% in middle patterns (area 1 and parts of the region 2) has taken place. Investigating the spatial-temporal cube patterns of theft crimes in Mashhad city showed that in the peripheral contexts the pattern of theft crimes is of the type of new and scattered hot spots, which indicates the intensity of theft crimes in these areas, but in the checkered contexts, the pattern of crimes is of the type of cold spots is an increase that shows that theft crimes in these areas are increasing in recent years.

The effect of the city’s form on the emergence of crime anomie is logically discussed in the sense that the  form and the social order of the city, cannot be separated. Rather, they develop in parallel and mutually inspire each other. For this purpose, the present study was conducted with the aim of investigating the effect of urban form on the occurrence of theft crimes in Mashhad. The research method is descriptive-analytical and it is done based on spatial analysis models. The statistical population includes theft crimes in Mashhad in the period of years 1390-1400. In order to analyze the data, ArcGIS, Geoda and Depth map software were used. The results of the research indicate that 58.9 percent of theft crimes have occurred in fine-grained textures. In fact, the regions with the area of ​​51-75 square meters have the highest amount of theft crimes. Investigating the effect of texture classification on theft crimes showed that 60.43 percent of the thefts occurred in peripheral textures (marginal areas of Mashhad, districts 4, 5, 7, 15, 16 and parts of district 13). Also, 19.2 percent of theft crimes occurred in checkered areas (western neighborhoods of Mashhad), 14.6 percent in star areas (the central part of the city and around the holy shrine of Razavi), and 5.7 percent of theft crimes were also committed in middle areas (Region 1 and parts of Region 2). The results of the research indicate that the more land is used, the less amount of theft crimes will occur, so that only 22% of theft crimes occurred in areas with high land-use mix. Investigating the correlation between macro interconnection and theft crimes in Mashhad, showed a positive and significant relationship (correlation coefficient equal to 0.878) between them, which indicates that increasing the interconnection and permeability of the road network, causes the amount of theft crimes to increase. Finally, investigating the effect of urban form on the occurrence of theft crimes, showed that the scattered form pattern with 56.76 percent has a greater effect on theft crimes than the compact form pattern.

The growing trend of committing crimes such as robbery in the country is a function of economic conditions, especially unemployment. Unemployment is one of the most chronic complications that is not pleasing to any economic system and is one of the main factors in increasing theft crimes in society. Given the importance of the issue of theft crimes, the present study has investigated the relationship between unemployment and theft in the country.The research method in this study is based on descriptive-analytical methods and the use of quantitative methods. In this research, the relationship between unemployment and robbery crimes in Iran in the period (2016-2017) has been investigated using a bivariate Moran spatial-correlational model. ArcGIS and GeoDa software were used to analyze the data as well as draw the maps. The required data and information have been obtained from the general population and housing censuses of the years (2006, 2011 and 2016) as well as the judicial affairs section of the statistical yearbooks of the country (2006-2017).The results of the research indicate that theft crimes in the country during 2016 compared to 2011 has increased by about (34.4) percent and compared to (2006) by about (208) percent. The results of the model of spatial autocorrelation between unemployment and robbery in the country indicated that the provinces of Tehran, Khorasan Razavi, Isfahan, Qom and Semnan in the H-H cluster (indicating the high rate of unemployment and robbery in these provinces). As well as neighboring provinces and the provinces of East Azerbaijan, Zanjan and West Azerbaijan are in the LL cluster (indicating low unemployment and theft in these provinces as well as neighboring provinces); Therefore, the results indicated that there is a positive and significant relationship between unemployment and theft in the country.

Nowadays, theft -especially residential burglary-is considered as one of the most common and frequent crimes in many countries of the world, including Iran. As such, it has become a pervasive and serious problem with various social, economic, and security-related aspects. Investigating geographical dimensions of this crime facilitates the process of exploring this phenomenon. Space and its special features play an important and undeniable role in crime commitment, because space has always been considered as one of the most important factors in commitment of financial crimes such as residential burglary. Spatial analysis and geographical investigation of crimes seek to provide a spatial presentation of criminal actions, crime dispersion, and crime hotspots. This type of crime analysis basically aims to provide a model for decreasing crime commitment in urban spaces. Accordingly, the present research seeks tomodel spatial diffusion of residential burglary crimes in MashhadusingHogstrand’s spatial diffusion theory.

The present study is performed based on descriptive-analytic and qualitative methods. The research sample includes cases of residential burglary committed in Mashhad in the 2011-2017period. Data analysis was performed using ArcGIS software. Case study area includes Mashhad, with an area of about 35187 hectares, a population of more than 3057679, and a population density of 87 people per hectare.

Police reports in Mashhad suggest that the highest crime rates belong to the 2nd and 3thdistricts, and the lowest rates belong toSamen (around Razavi Shrine), the 12th, and 8thdistricts. 70% of crimes in Mashhad are committed in informal settlements including the 2nd, 3th, 4th, 5th, 6th, 7th, and 10thdistricts. However, only 10.6% of the city area and 29.3% of its population belong to these districts. Furthermore, the highest crime rates have been reported in 2017. In 2011, only two major crime hotspots were observed in Mashahd (in the 2nd and 3thdistricts). Results suggest that crimes have spread from one place to anotherin Mashhad, which indicates a close relationship between crime and distance factor. In other words, proximity to a crime hotspothas resulted in rapid spread of crimes, and due to the short distance, nearby places have been affected more quickly. Informal settlements of Mashhad are located in eastern, northern, and northeastern districts,which contain 99% of crime hotspots. This indicates that spatial autocorrelation of crimes in informal settlements of Mashhad is relatively high, which has led to formation of crime hotspots in these districts. However, moving from marginalized areas towards southern districts of Mashhad (more prosperous regions), spatial correlation of crimes decreases, and lead to formation of 99% of cold spots.

The present research has investigated the spatial diffusion pattern of crimes in Mashhad in 2011-2017period.To reach this end, crime hotspots were investigated by quantitative methods such as Kernel density, Moran coefficient, and crime hotspot analysis. Results suggest that the highest crime rates are reported in the 2nd and 3thdistricts, while the lowest rates are reported in Samen (around Razavi Shrine), the 12th, and 8th regions. In fact, 70% of crimes in Mashhad are committed in informal settlements including the 2nd, 3th, 4th, 5th, 6th, 7th, and 10thdistricts. Moreover, statistics indicate that for every100000 people,anaverage of 75/2 cases of crimes have been reported in the 2011-2017period.Results of Moran coefficient for spatial diffusion of crimes indicated the presence of a cluster distribution of crimes in Mashhad. Meanwhile, spatial diffusion pattern of crimes in Mashhad suggests that the first crime hotspots were formed in northern, eastern, and northeastern districtsof Mashhad, and crimes have spread from these to other districts (more central and prosperous regions such as the 8th and 9thdistricts). In fact, investigations suggest that crimes are spreading from informal settlements to other regionsof Mashhad, and acompatible spatial diffusion pattern of crimes exists in this city.

Crime is an extremely important social and economic issue in our day. The considerable costs imposed by crime on victims and society greatly exceed the private benefits of crime (Becker, 1968). The economics of crime is an interdisciplinary topic that is intended to analyze crimes economically. Regarding the increase in crime rates in our country, a comprehensive study of the causes of crime, especially economic crimes such as robbery is necessary, because it is directly related to the economy and an accurate understanding of causal relationship between the two will help policymakers in planning for a better society. The causal relationship between crime and unemployment is an old-age question in the social science literature. There have been many studies of the relationship between crime and unemployment from a range of perspectives, but this research tries to produce clear evidence of a causal link between crime and inflation/unemployment rates. A large empirical literature investigating the link between macroeconomic conditions and aggregate crime rates has developed over the last thirty years. The majority of these studies focus on the relationship between unemployment and crime. As a result, the literature largely neglects the role of inflation as a potential determinant of crime. One of the most important side effects of economic policies in Iran has been an increase in inflation. This has led to different crimes especially economic crimes and robbery, by widening the gap between different social classes and income groups. As inflation and unemployment rates were the only variables used in this study, the results might not fully capture the criminal behavior. Results imply that inflation and unemployment rates cause crime rate, but there is no strong evidence of the reverse causality. An individual will engage in criminal activities because of their inability to maintain a particular level of living as a consequence of inflation and unemployment. Therefore unemployment is a shock effect that causes an individual to engage in criminal activities. Inflation causes the purchasing power to reduce while increasing the cost of living. As a result, crime rate may increase because an individual is unable to maintain their standard of living as before. However, this phenomenon does not happen immediately because it takes time for inflation to gradually reduce the individual's purchasing power. Crime rates rise as the inflation rate rises. Because of the lag between price and wage adjustments, inflation lowers the real income of low-skilled labor, but rewards property criminals due to the rising demand and subsequent high profits in the illegal market. Inflation destroys the confidence in the existing institution's arrangements, resulting in a loss of social control, and erodes the economic ability of communities to maintain real leverage for deterrence. Although the unemployment rate is a logical variable to include in an economic model of property crime, it suffers from three potential problems. First, unemployment varies substantially across regions, making it difficult to pin down its true effects using national data. Secondly, unemployment does not capture discouraged workers, who have ceased searching for jobs because they believe that it is a futile effort. Thirdly, unemployment is only partially connected to the manufacturing sector, which disproportionately effects the urban poor and, as a result, has been linked to crime rates. The downward pressure on purchasing power associated with periods of rising inflation affect low-income households more adversely. Since low-income groups commit a high proportion of crimes in Iran, one would expect periods of higher inflation to be concomitant with higher rates of crime, especially property crime. The low-income segment of society should find crime more attractive during inflationary periods, as wages generally do not adjust as freely as other prices (See Christiane et al. 2005). One can also think of inflation as a tax that generates a dominant income effect for “labor supply” in the underground sector of the economy. Using statistics of the past 20 years regarding Iranian annual reports of crimes in the field of non-creditable checks, we try to introduce a suitable model by employing econometric methods based on available statistics and auto-regressive distributed lag (ARDL). We investigate the long term relationships between different variables, and then in the second stage using error correction model (ECM), we look at the short term relationships between variables.Using the models mentioned above, we conclude that unemployment and inflation rate variables have a considerable effects on increase in robbery and non-creditable checks. Discussion of Results & Proper economic policies bring about social and moral effects besides economic implications. The Results of this study suggest that inflation and crime rates are co-integrated with a positive relationship and the causal link is from inflation and unemployment to crime. It appears that price stability contributes considerably to the reduction of property crimes. Also, the relationship between monetary policy and crime is considered according to the hypothesis by which the government emits money to finance its deficit. The result of the research shows that economic policies, which increase inflation, have a negative role in economic development and have a negative effect in social damage. These policies increase economic crimes and social deviances. Therefore, expansion and longtime planning to decrease inflation is necessary for controlling deviance and crimes. Since the social analysis of economic policies is very crucial, it is necessary that researchers consider the following topics: social impact of inflation, especially on social deviance such as perversion. Also, if the analysis of crime at "the economics of crime” will be considered with the sociological analysis at social patalogy, based on interdisciplinary approach, then we can better study this problem.

Spatial Analysis of Crimes at Different Hours of the Day, the Days of the Week, Month, and Seasons is an Effective Way to Control and Prevent Urban Crime. These analyzes give city management and other city safety officials, including law enforcement officials, the possibility to take preventive measures to eliminate or mitigate the effects of these factors in the city. The purpose of this study was to investigate the spatial analysis of theft crimes on a daily, weekly, monthly and seasonal basis in the 12th metropolitan area of Tehran. The research method in this article is descriptive-analytic. The comprehensive statistical data included the statistical blocks of 1390 in the neighborhoods of the 12th district of Tehran and the crimes related to theft in 2010. The most important statistical tests used are the Center-Medium and Oval-standard deviation tests, and from among the clustering tests, the nearest neighbor index is used to identify massive cores. The results of this study indicate that 446 crimes related to theft, Ferdowsi and Lalehzar neighborhoods, and Sachr('39')di Baharestani have the most crimes and minorities in Kosar and Mokhtari. The pattern of distribution of crimes in the 12th region is clustered and the most important crustal focal points are formed at the intervals of the Shemiran, Iran, Baharestan - Saadi, Ferdowsi -Laleh Zar, Arg Pamenar, Imamzadeh Yahya and the Cascade. The spatial analysis of stealing crimes also suggests that the direction and extent of theft is different at different times of the day, weekdays, and on a monthly basis.

Over time, criminologists have found that specific locations influence the occurrence of crime. As in the past few decades, spatial analysis theories in criminology have shifted from focusing on the motivation of criminals to study crime points. In fact, some locations have a greater chance of occurring due to the physical and environmental characteristics as well as the social, cultural, and economic features of the inhabitants; on the contrary, some places are a barrier to criminal opportunities. Therefore, it can be said that identifying the factors in the incidence of crime is the first step in combating social depravity, because by eliminating these factors or reducing their effects can prevent or at least reduce the level of delinquency in society. Pakdasht has been subject to rapid physical and demographic growth bans over the past few decades due to the growth of informal housing and disrupted urban development, and the physical characteristics of the city have had an impact on environmental quality in terms of crime. Therefore, the key question in the present study is as following: what is the relationship between the physical texture of the city and the patterns of robbery crimes occurrence in Pakdasht? For this purpose, to analyze the pattern, extent and distribution of urban crime, the relationship between the physical texture of the city and the pattern of robbery crimes has been investigated.

The research method of this study is descriptive-analytical and in terms of purpose is an applied one. Also is based on library and field studies. The statistical population of this study was 302 cases of robbery. Mapping Clusters toolkit from ArcGIS software was used for spatial distribution and spatial representation of hot and cold physical textures of Pakdasht. Also to explore the pattern trends affecting physical parameters (passages width, building life, construction quality, size of discrete components, passages lighting, passage coverage, presence of demolished buildings, physical quality and building materials) on crimes, GWR was used.

The distribution of the robbery crimes perpetration place in the city shows that they have a cluster pattern in the central part of the city. Accordingly, the pattern of delinquency in Pakdasht city and most of the crimes of robbery occurred near the main streets and the central part of the city and other areas of the city have a lower crime density than these neighborhoods, which is evidence of the accumulation of delinquency patterns in certain areas of the city. hotspots have also been formed from Shahid Motahari Street Clock Square to Mamazani Head. There is also a focal point behind the municipality (Elihiya), that one of the reasons could be the high level of burglary of residential homes. Another pattern is in the sand and branch area, which is the informal settlement area. In this regard, the Local R2 coefficient for the model of impact of physical indicators on crime occurrence in Pakdasht is between (0/39 – 0/00), which means that the correlation between the independent variable (physical indicators) and the dependent variable (crime) is high in red areas of the city and contrariwise. In fact, locally and spatially, it indicates that the extent of the influence of physical indicators on crime is greater. For example, in areas of the city with poor lighting, crime rates are also high. Therefore, the greatest impact of physical factors and the interdependence between the framework and the occurrence of crime are in the marginal areas of the city that constitute the old texture areas of the city, as well as in areas known as worn-out and informal settlement.

According to the physical indicators of Pakdasht informal settlements (passage width, construction life, construction quality, size of segments, lighting and passages, passage coverage, presence of demolished buildings, dominant physical quality in the neighborhood and building materials), physical factors are directly related to occurrence of a crime. As such, the greatest impact of physical factors and the relationship between framework and crime occurrence has taken place in the marginal areas (Elahiyeh Phase 2 and Ghoute and Jito crossroads) and near the worn-out and informal settlement of the city (Zeinabieh and Imamzadeh Ghoueh) and the central district is less correlated with the predisposing physical factors due to its location in the downtown area and to some extent the importance of safety issues in buildings. The coefficient (Local R2) on impact of physical indicators on crime occurrence model in Pakdasht shows in terms of  locally and spatially that the effect of physical indicators on crime occurrence is greater so that the most influence of physical factors and dependence between framework and crime occurrence has occurred in the suburbs near the worn-out texture and informal housing of the city due to the specific conditions of the turbulence and worn-out texture, and crime rates have been high in areas of the city where illumination and lighting are inadequate.

Crime imposes expenses on the society and puts the goverment in troublein implemnting economic policies.the present study aims at investigating the effect of poverty,unemployment and social factors on the theft and drug-related crimes.the present study is an applied one and questionnaire was used to collect the required data.prisonors of semnan central prison accused of theft and drug-related crimes formed the statistical population of the study. statistical sample was randomely selected. The findings demonstrated that unemployment exert different effects on theft and drug-related crimes.the findings also showed that the risk of crime has different effects on different types of crimes.