醫療設施區位具有不同的空間特性,包括:1.就醫便利性,屬於區位正面的「迎毗效果」,2.設施對環境所產生「或多或少」之「鄰避效果」,例如救護車的進出會產生噪音的干擾(特別在深夜時刻,民眾的感受愈加深刻)、就醫民眾所產生的交通量造成附近交通擁擠或停車問題、當爆發大規模傳染病(例如2003的SARS)時會有被傳染或被阻隔的風險等,導致對當地的居住環境產生潛在的風險,使得居民產生對該設施接受意願的不確定性態度。本研究選擇屬醫學中心之「國立成功大學醫學院附設醫院」為研究標的,並以周邊五百公尺範圍內之居民為對象,進行結構性問卷調查,期能深入探討大型醫院對於附近居民住宅環境所帶來的各種影響,首先採用因素分析方法,萃取五大重要因素,分別為住宅區寧適因素、健康風險因素、住宅區安全因素、醫療服務因素及距離認知因素。然後藉由資訊整合理論(Information Integration Theory, IIT),以前述抽查樣本中選擇自願者,進一步分析居民(群體與個體)對於成大醫院所產生之外部性的選擇決策,提供較為客觀之「行為與決策」間的連結。研究結果如下: 一、就群體分析而言 (一)居民群體對「距離-住宅區寧適」之資訊整合模式為相加模式,意謂居民群體以距離與住宅區寧適資訊進行決策時,此兩項資訊間彼此獨立互不影響,且決策者如採用相加模式會將所有屬性之正面資訊主觀值相加,以形成對整體居住環境接受程度的滿意度。 (二)居民群體對「距離-健康風險」之資訊整合模式為不等權重平均模式,意謂居民群體在面對距離與健康風險資訊以考量居住環境的接受程度時,傾向將距離與健康風險資訊加以平均,主觀上會同時考慮兩者並給予不同的權重比例,以形成對整體居住環境接受程度的滿意度。 (三)居民群體對「距離-住宅區安全」之資訊整合模式為不等權重平均模式,意謂居民群體在面對距離與住宅區安全資訊以考量居住環境的接受程度時,傾向將距離與住宅區安全資訊加以平均,主觀上會同時考慮兩者並給予不同的權重比例,以形成對整體居住環境接受程度的滿意度。 (四)居民群體對「距離-醫療服務」之資訊整合模式為不等權重平均模式,意謂居民群體在面對距離與醫療服務資訊以考量居住環境的接受程度時,傾向將距離與醫療服務訊息程度加以平均,主觀上會同時考慮兩者並給予不同的權重比例,以形成對整體居住環境接受程度的滿意度。 二、就個體分析而言,居民個體對「距離-住宅區寧適」、「距離-健康風險」、「距離-住宅區安全」與「距離-醫療服務」之資訊整合模式,多採用不等權重平均模式,意謂居民在面對相關資訊以考量居住環境之接受程度時,傾向將相關資訊加以平均,主觀上會同時考慮兩者並給予不同的權重比例,以形成居住環境接受程度之決策。
Medical facility location considers different spatial characteristics including. 1. Accessibility of medical service is a positive effect of YIMBY; 2. Semi-obnoxious ex. ambulance noise (especially in late night), traffic congestion in service hours, SARS like case quarantined or infected which is negative effect of NIMBY. This study selected NCKU affiliated hospital (medical center) as target and 500 meters range residents as samples. Then structure questionnaires were conducted for several effecting factors in terms of housing environment. The Factor analysis was used to extract 5 important factors: (1) neighborhood amenity, (2) health risk, (3) neighborhood safety, (4) accepted distance, (5) medical service. Then we further designed Information Integration Theory questionnaire and selected the samples from above residences to explain the choice decision from the externality of a large-scale hospital. The result shows: 1. In group analysis (1)“distance-neighborhood amenity” represented adding model, it meant residents regarded these variables as independent and decision maker would add the positive value as comprehensive satisfaction degree. (2)“distance-health risk” represented different-weight averaging model, it meant residents regarded these variables different weights. Decision maker would average the value as comprehensive satisfaction degree. (3)“distance-neighborhood safety” represented different-weight averaging model, it meant residents regarded these variables different weights. Decision maker would average the value as comprehensive satisfaction degree. (4) “distance-medical service” represented different-weight averaging model, it meant residents regarded these variables different weights. Decision maker would average the value as comprehensive satisfaction degree. 2. In individual analysis results represented different weights averaging model, the information integration of the individual in “distance-neighborhood” “distance-health risk” “distance-neighborhood safety” “distance-medical service” would average the value as comprehensive satisfaction degree.