Fuller T D, Lightfoot P, Kamnuansilpa P
Demography. 1985 Nov;22(4):565-79.
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)
本文分析了一个人口流动决策的理论模型。该模型完全依赖个体层面的因素,而非宏观层面的因素,作为迁移决策的决定因素。模型中包含的个体层面变量有:近期流动历史、城市社会关系、城市地区信息、对不同地点的评估、迁移计划,以及初次访谈后一段时间内的实际迁移情况。实证结果表明,除了一些例外情况,这些变量之间存在着模型所建议的那种较为紧密的联系。该模型针对两组村庄分别进行了评估,一组是向曼谷迁移的村庄,另一组是向泰国东北部城镇迁移的村庄。因此,估计了四个子模型,这提供了一个机会来观察该模型对于不同目的地和来源地的稳健程度。尽管在四个子模型之间发现了某些差异,但最显著的特征是它们的相似性。在存在差异的地方,它们通常反映出先前流动作为该过程中其他变量预测指标的有效性差异。显然,村民先前的流动历史是影响后续流动和整个决策过程的关键因素。在某个特定城市中心有朋友和亲戚的主要影响是增加村民对该城市中心的了解。信息对评估和计划有显著影响。除了一个子模型外,评估对计划有显著影响;而计划的存在——在某种程度上代表了社会关系、信息和评估的 culmination(此处未准确翻译的词,可根据上下文理解为某种综合结果)——是除先前流动之外,对后续流动有显著直接影响的唯一因素。泰国政策制定者正在寻找方法来刺激区域城市增长中心的发展,并减少曼谷的发展。从干预的角度来看,这个过程中的一个关键变量似乎是信息。不仅信息水平与对城市地区的评估和流动计划相关,而且与模型中的其他变量相比,它似乎相对更容易受到来自村庄自身外部来源的输入的影响而发生改变。直接修改评估或迁移计划似乎很困难,尽管两者都可能受到信息输入的间接影响。流动历史即使不是不可能,也很难操控;虽然可以资助村民短期进城旅行,但这不太可能产生太大的长期影响。(摘要截取自 400 字)