---

Human impact on the environment are increasingly of urban life arises that this is due to human population growth is partly a result of technological progress. Cities as the center of attraction of population with multiple and various environmental problems such as air pollution, noise, waste, and water pollution this leads to increasing pressure on the environment and therefore the incidence of environmental pollution. The study aimed to measure and evaluating the quality of the urban residential environment with cross-sectional approach in urban settlements Ardabil province. To achieve the goal of is evaluated 5 environmental factors (environment, energy, environment, social, cultural, recreational and employment) in the form 30 Index. Rate the importance of each of the variables were determined using the Shannon entropy. Models used to analyze the data is Visual PROMETHEE PROMETHEE and GAIA software. The results show that urban settlements Kosar city with a score of 2,674 / 0 has favorable conditions, Bilesuar, Namin, Sareyn, as well as the privileges 1281/0, 1147/0, 0994/0, 0924/0 has favorable conditions, Meshkin with a score of 0369/0 in relatively good condition, Warmth, anklets and Ardebil with 0704 votes / 0-, 1359 / 0- and 2098 / 0- of adverse conditions And Pars Abad city with 3228 negative rating / -0 in last place and the situation is quite unsatisfactory. Based on the analysis of the 30 indicators used PARSABAD Gaia city status this research indicates that only in the ratio of active branches of sewage into the urban population in the state is ideal. Overall results show that environmental situation in cities far worse that the urban population is more urban counties that have less.

---

The purpose of the present study was modeling villagers’ intention to adopt e-marketing and rural provincial clustering. The data was collected from 988 villages with ICT offices from 31 provinces of Iran. The results showed that the rate of agricultural income in villages with ICT offices was desirable but income of handicrafts and tourism was lower than the average. Also, rural access to city and ICT users were acceptable. In designing the research model, the “theory of planned behavior” (TPB) was developed. In this regard, a new factor called rural economic geography was added having five new variables such as rural access, rural tourism, agriculture, rural handicrafts, and population. Thus, the “Geographic Model of Planned Behavior” (GeoTPB) was presented. In the new model, the impact of geographic factor on behavioral factor was examined using structural equation modeling approach. In general, the rural economic geography had a direct impact (64%) on behavioral factors and in the next step, the behavioral factor (as full mediation) affected the intention. The Geographic Model of Planned Behavior predicted villagers' intention to e-marketing adoption up to 75%. In addition, the K-means clustering indicated that Iran rural regions can be placed in six clusters due to economical and behavioral factors. In most clusters, rural economic geography was effective on behavioral factor. The interesting finding was that Sistan and Baluchestan, Hormozgan, and Khuzestan provinces in cluster 1 were the leading regions in e-marketing adoptions. These regions were recorded as less-developed villages in the reports of the statistics center indicating that the development of technology was significantly effective on the digital literacy of the inhabitants of these regions. The findings emphasized the significance of considering behavioral factors in geographic studies to provide realistic solutions for rural development.