عنوان مقاله [English]
City old areas, which one day created a suitable living space for their dwellers, due to technological improvements and changes occurred in environmental, social and economic needs, can no longer have the same performance as they once did. Once, these old areas were the heart of wealth and power of cities, but under current conditions (in almost all cities) and because of having poor infrastructures and urban services, and also from a physical point of view, they are considered as disorganized. Study on and restoration of the historical centers of cities, or in other words, improvement of urban decays, the tangible need of which has attracted officials’ attention, is caused by different inferences drawn from insight, culture, tradition, art and architecture, and in a sense, life styles during three late centuries. During the last century, the Iranian life style has undergone fundamental changes in such a way that nowadays the effect of past long culture and rich civilization is no longer felt. Different studies conducted on old areas of Iran cities show that most dealing with these areas have been based on mere conservation and repair of valuable monuments while little attention has been directed toward certain planning for revitalization and restoration of social-economic and cultural life in these areas. In Iran, experience in urban management and planning for restoration of old areas of cities dates back to 1921 up to now. In early 1971, the role and significance of historical areas increased through holding seminars and introducing scientific books and articles. After the Islamic Revolution, attempts in this regard decreased. Since 1985 up to now, by conducting research projects, publishing scientific books and articles, holding seminars, activities in the field expedited. So, current study seeks to investigate the role of public contribution in restoration of Jahrom city urban decay.
Current study is conducted with an applied-developmental aim using research theoretical foundations with a library method. Moreover, data collection is done through field observation and questionnaire. After developing the questionnaire, it is completed utilizing random sampling. Study geographical area is consisted of the city old region with a population and size of (104) and (22375), respectively. Sample size is calculated using Cochrane formula. Moreover, using SPSS and Excel software, data is analyzed in statistical descriptive methods (Tables of Frequency Distribution), and inferential statistics (Factor Analysis, Pearson).
Results and discussion
Research findings are recorded in two parts: at first, individual characteristics of the respondents and data are analyzed, and also prioritization of indexes is determined making use of Factor and Heuristic analyses. The four physical (Eight Items), social (Six Items), economic (Five Items), and environmental (Four Items) indexes are investigated. For prioritizing variable, the use is made of Factor-Heuristic analysis. According to research findings, initial variable becoming the superior factor is because of Varimax rotation. In order to conduct a satisfactory Factor Analysis the value of KMO should be larger than 0.5. As Table 1 shows, results obtained from the test is larger than 0.5 and significance level is 0.00. Therefore, correlation between variables can be proved by 99 per cent likelihood.
Table 1- KMO and Bartlett’s Tests
Bartletts Test of Sphericity Chi-Square 876/425
Results obtained from analysis and value of every factor
Indexes which are loaded in each factor, and are higher than 0.5 constitute a factor while indexes which cannot be added to these factors, form other ones. Moreover, the sum of variance of four mentioned factors is 66.154 per cent, the largest of which with 17.798 per cent is in the first factor. The variance value of 66.154 per cent shows that the results analysis is satisfactory. Results show that in this analysis, 17.798 per cent of the variance is defined by the first factor. Second, third, and fourth factors calculate 17.689, 16.252, and 14.145 per cent of the variance, respectively. According to research findings and above tables, physical factor, or more obviously physical problems, and social problems such as social disorders present at the mentioned old area, are considered as the most affecting issues. Therefore, for organizing the region, mentioned factor can be helpful in region improvement planning.
Also, in order to investigate the degree of contribution and satisfaction, the use is made of Pearson Coefficient Correlation. Findings show that considering value of Pearson Correlation Coefficient (0.632), with Confidence of 0.99 and error level of lower than 0.01, there is a meaningful statistical relationship between the two degree of contribution and trust variables. That is, the more the trust in government officials become, so does the contribution.
Results obtained from Factor Analysis conducted on four public contribution variables prove helpful and effective in restoring urban decay. More than 91 per cent of dwellers in overall level of urban decay region are contributive. It is so in such a way that if dwellers’ contribution to urban decay restoration and improvement become organized, its effect will be doubled. Investigation done in overall level of urban decay region shows that 31.09 per cent of dwellers is organized as region councils and associations. Moreover, dwellers’ opinions show that in case facilities and motivating policies are provided, about 72.42 per cent of them willingly welcome the restoration and improvement of residential buildings. For instance, according to the first factor with variance values of 3.738, 17.798, the most important factor in Factor Analysis, physical factor has the most significance in urban decay. Second significant factor is social one which is placed after the first factor. Economic and environmental factors are in the next stage. Results of the hypothesis testing show that according to Pearson Correlation Coefficient (0.168), Confidence (0.99), and error level lower than 0.01, there is a meaningful statistical relationship between two variables of contribution and trust. That is, the more people trust in government officials, the more increase in contribution will result.