Rural-urban mobility in Thailand: a decision-making approach

Abstract

This paper has analyzed a theoretical model of mobility decision-making. The model relies entirely on individual-level factors rather than macro-level factors as determinants of migration decision-making. The individual-level variables included in the model are: recent mobility history, urban social contacts, information about urban areas, evaluations of different locations, migration plans, and actual movements in the period subsequent to an initial interview. The empirical results indicate that with some exceptions there are relatively strong links of the type suggested in the model among these variables. The model was evaluated separately for two groups of villages for movement to Bangkok and for movement to Northeast Thai towns. Thus, four submodels were estimated, providing an opportunity to observe how robust the model is with respect to varying destinations and origins. Although certain differences are found among the four submodels, the overwhelming feature is their similarity. Where differences do exist, they generally reflect differences in the effectiveness of prior mobility as a predictor of other variables in the process. Clearly, a villager's previous history of movement is a key factor affecting subsequent movement and the entire decision-making process. The primary effect of having friends and relatives in a particular urban center is to increase the amount of information a villager has about that urban center. Information has a significant effect on evaluations and plans. Except in one submodel, evaluations have a significant effect on plans; and the existence of plans--which to some extent represent a culmination of social contacts, information, and evaluations--is the only factor other than previous mobility which has a significant direct effect on subsequent movement. Thai policy makers are searching for ways to stimulate the growth of regional urban growth centers and reduce the growth of Bangkok. From the standpoint of intervention, a key variable in this process would appear to be information. Not only is information level related to evaluations of an urban area and mobility plans, but, compared to other variables in the model, it appears to be relatively amenable to modification by inputs deriving from a source external to the village itself. It appears difficult to modify evaluations or migration plans directly, though both could be indirectly influenced by informational inputs. Movement history would be difficult, if not impossible, to manipulate; while villagers could be sponsored for short trips to town, this is not likely to produce much long-range effect.(ABSTRACT TRUNCATED AT 400 WORDS)