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pp.98-107
For efficient development of rural facilities, choice of their optimum locations would be an important issue, however, existing research works concentrated much more an allocation policy of urban industrial complex and public facilities than rural ones. In this study, because agricultural-cum-industrial complex has been the most widely developed representative one of rural facilities, it was selected as a case study facility. As a pre-study to system development, existing governmental location-decision system was checked and interviewing survey carried out to find out on-spot problems. And, being based on literature review and survey analysis results, 4-step optimum locational decision model was developed , formulation of locational goal system, ranking tabulation on components, determination of significance values of components, calculation of component scores. Finally, through the case study works on 3 sites, system applicability was checked, Considering together the simplicity problem of existing guidelines and the interviewing survey results favoring the diversified viewpoints, it would be necessary to develop multifaceted support system for locational decision making. 3-tier classification steps from the higher, middle to lower one were used and their underpinning viewpoints were sorted as on regional development, entrepreneurship, spatial rationality, from which a tentative locational goal system was formulated. Through the expert group checking, final locational goal system was determined having 3 of the higher classification items, 7 of the middle ones, 23 of the lower ogles. For ranking tabulation, 3 types of ranking criteria were arranged which were based on statistical analysis using mean and standard deviation(Type I ), its existence or not 1 good or not(Type E ), and the others(Type E ). From the significance evaluation results, regional development and entrepreneurship aspects were valued much higher than spatial rationality aspect. And, in the middle step, items as spread effects of regional economy, accessibility and social potentialities were highly valued while infrastructural development level and natural condition being low. The application results of the system to 3 case study total. However, the detailed ones differed among study the influencing effects on regional economy, and contrast greater the infrastructural development level. Conclusively, final evaluation values well represented the characteristics of each area. If this system be complemented and applied comprehensively by the successive studies, it would be developed to a general model of locational decision supporting system for rural facilities.
