中文摘要：

城市的旧城与新区由于街区尺度、居住密度和人群结构等方面的不同,居民的休闲步行行为需求也存在较大差异。选择上海市杨浦区鞍山新村和江湾新城作为旧城和新区的典型代表,以307份调查问卷为基础数据,应用叙述性偏好法,比较分析新旧城区居民休闲步行环境的关注要素和偏好程度,以此为基础构建休闲步行环境评价方法,并分别应用在案例地区。研究表明：旧城、新区居民对休闲步行环境的需求相似又相异,通过离散选择模型构建的休闲步行环境评价指标和权重也会有所不同,从侧面说明只调研一个地区就推论出广泛的评价指标和权重的做法是有缺陷的;应用该评价方法,鞍山新村和江湾新城休闲步行环境定量评价结果与日常生活经验相符。

英文摘要：

Walking environment is an important factor in public health and urban planning. To promote higher quality recreational walking environment, one issue requiring further attention is to what extent the walking environment factors are considered important by the pedestrians？ This paper aims to contribute to the methods of evaluating and improving walking environment by exploring the underlying mechanisms of pedestrians＇ route choice behavior in strolling activities. Stated preference （SP） method is used to reveal the influence of the environment factors on pedestrians＇ route choices. These environment factors are identified from an extensive literature review and a pilot survey. Hypothetical routes generated by orthogonal design are organized into route choice scenarios and illustrated in graphs. Respondents were required to select the route they prefer to stroll based on its environment factors of certain levels. The choice data are estimated using Discrete Choice Models （DCM） to derive the influence of each factor on the utility of a route. Two different practices are tried in the experiment design from conventional practices. The first is the use of factor level combinations for orthogonal design, which in theory improves the efficiency and effectiveness of the design because according to the nature of DCM, only factor differences matter for the calculation of choice probabilities. The second is the use of graphs in which factors are presented in more realistic and holistic manners for the questionnaire. Testified through internet-based experiments, choices using graphs facilitate respondents＇ cognition and display different model results from choices described using text only. Residents＇ walking environment demands differ between old and new built environments, owing to the difference in block scale, residence density and population structure. Data were collected in two selected neighborhoods in Shanghai, Anshan Village and Jiangwan Town as a typical example of old and new built environments