Studies of the connections between transportation and subjective well-being (SWB) require a clear understanding of the conceptual composition of travel-related SWB as well as psychometric instruments to measure these complex topics. Well-established psychological scales for measuring general SWB—including both hedonic (affective and cognitive) and eudaimonic aspects—are difficult to adapt or have yet to be tested in the travel domain. Existing measures of travel liking and travel satisfaction are somewhat inadequate for these purposes, especially for representing eudaimonia. Using a questionnaire survey of 680 commuters in the Portland, Oregon, region, exploratory and confirmatory factor analyses examined responses to a total of 42 items. Results suggested four-factor measurement models of both travel affect (Enjoyment, Attentiveness, Distress, and Fear) and travel eudaimonia (Health, Competence, Autonomy, and Security). Despite some limitations and opportunities for enhancements, these models show promise as ways of measuring affective and eudaimonic SWB in the travel domain for future studies and travel surveys.
基于宁波市公共自行车刷卡数据、POI(Point of Interest)数据、气象和空气质量等数据，从数据驱动视角，深入挖掘公共自行车使用的时空特征及站点租还车需求预测。在时间上，采用KMeans算法，将站点聚为5类，探讨各类站点的时变需求规律及影响因素；在空间上，提出基于POI 数据的站点用地类型识别方法，将站点分为居住类、交通设施类、办公类和商业休闲类。构建以 15，30，60 min 为间隔，以租还车需求为目标变量的随机森林预测模型，并与常用的 BP (Back Propagation)神经网络、K最近邻方法进行比较。结果表明，随机森林模型的精度更高，适用性更强。以30 min为间隔的站点租还车需求预测精度最高，考虑站点土地利用类型后能有效提高模型的预测精度。本文结果可作为未来站点平衡调度的依据并推广应用于共享单车系统，为改善服务水平提供技术和理论支撑。 相似文献
ABSTRACTThis study estimated the external cost of air pollution from shipping by means of a meta-regression analysis, which has not been made before. Three pollutants, which were included in most of the primary studies, were considered: nitrogen oxides (NOx), sulphur dioxides (SO2) and particulate matters with a diameter of max 2.5 micrometres (PM2.5). All primary studies included damages of health and a majority added impacts on agriculture and estimated the cost of air pollutants by transferring cost estimates from studies on costs of air emissions from transports in Europe. Different regression models and estimators were used and robust results were found of statistically significant emission elasticities of below one, i.e. total external costs increase by less than 1% when emissions increase by 1%. There was a small variation between the pollutants, with the highest elasticity for PM2.5 and lowest for NOx. Calculations of the marginal external cost of the pollutants showed the same pattern, with this cost being approximately six times higher for PM2.5 than for the other pollutants. Common to all pollutants was that the marginal external cost decreases when emission increases. Another robust result was a significant increase in the cost of studies published in journals compared with other publication outlets. These findings point out some caution when transferring constant external unit cost of air pollutant from shipping, which is much applied in the literature, and the cost functions estimated in this study could thus provide a complementary transfer mechanism. 相似文献
