看不見的因素：科技社群定住區位之鄰近性考量──以新竹地區為例

The Invisible Factors: Proximity Consideration for Residential Location of Science and Technology Social Workers - Hsinchu Case

本研究立基於社會、認同與認知鄰近性之觀點，探討科技社群是否經由購屋動機、資訊搜尋與定住區位選擇流程中，其購屋資訊學習在非正式互動、社會網絡建立與共同的學習文化下，而能直接評估居住環境。因此，研究目的著重於檢定個體鄰近性對於定住區位選擇產生影響的假說下，並進一步以迴歸分析探討相關個體鄰近性因子與空間鄰近性之關聯，期望能從中解析新竹地區空間發展變遷的背後涵義。研究發現，科技社群選擇住宅行為是經兩種不同的鄰近性路徑進行，其一是對於園區知識網絡、地方環境認同而依附於居住環境行為之內部鄰近性（社會、認同鄰近）；另一則是為了獲取住宅資訊學習之外部鄰近性（認知鄰近）。在個體鄰近性的作用下，其空間發展變遷所呈現的是，社會、認同鄰近必須在空間上彼此聚集鄰近在同一地區；而外部認知鄰近性雖非空間鄰近性之直接因子，但卻有助於科技人才社會鄰近性之互動。故此，個體鄰近性產生內生的拉力促使新竹地區之空間擴展逐漸趨於減緩。 Based on the viewpoint of social, identified and cognitive proximity, this study will discuss whether science and technology social workers are able to evaluate their living environment directly in the process of motivating housing purchase, searching for information, and making residential location decisions when they learn about housing purchase based on informal interactions, social networking, and common learning culture. This study uses regression analysis to explore the correlation between individual proximity factors and spatial proximity based on the hypothesis that individual proximity impacts residential location choices of science and technology social workers. Through this analysis, the authors hope to find explanation behind the spatial development transformation of Hsinchu District. The result of this study indicates that housing choice behaviors of science and technology social workers follow two different proximity paths. First, internal proximity factors (social and identified proximity) show that the groups identify with knowledge networks within HSIP and the local environment, and thus conform to residential environmental behaviors. Second, external proximity (cognitive proximity) refers to the acquisition of housing information. Under the influence of individual proximity, social and identified proximity require agglomeration in the same geographic area. Although external cognitive proximity does not lead directly to spatial proximity, it benefits science and technology professionals through social proximity interactions. As a result, the pulling force created by individual proximity slowed down the spatial expansion of Hsinchu District.

Based on the viewpoint of social, identified and cognitive proximity, this study will discuss whether science and technology social workers are able to evaluate their living environment directly in the process of motivating housing purchase, searching for information, and making residential location decisions when they learn about housing purchase based on informal interactions, social networking, and common learning culture. This study uses regression analysis to explore the correlation between individual proximity factors and spatial proximity based on the hypothesis that individual proximity impacts residential location choices of science and technology social workers. Through this analysis, the authors hope to find explanation behind the spatial development transformation of Hsinchu District. The result of this study indicates that housing choice behaviors of science and technology social workers follow two different proximity paths. First, internal proximity factors (social and identified proximity) show that the groups identify with knowledge networks within HSIP and the local environment, and thus conform to residential environmental behaviors. Second, external proximity (cognitive proximity) refers to the acquisition of housing information. Under the influence of individual proximity, social and identified proximity require agglomeration in the same geographic area. Although external cognitive proximity does not lead directly to spatial proximity, it benefits science and technology professionals through social proximity interactions. As a result, the pulling force created by individual proximity slowed down the spatial expansion of Hsinchu District.