浅谈我国企业的股权筹资偏好

分析了我国企业的资金结构现状,介绍了我国企业股权筹资偏好的主要表现,分析了我国企业偏好股权筹资的原因,并指出了股权筹资偏好的不利影响。     

自适应路径规划系统研究

针对目前的路径规划系统普遍采用距离最短或时间最少等单一指标,不能自动识别驾驶员路径选择习惯,为驾驶员自适应地提供符合驾驶员偏好的诱导路径的问题,设计了自适应路径规划系统的框架,提出了一种基于驾驶员路径选择偏好的自适应路径规划算法。算法中设计了基于驾驶员路径选择偏好的多目标路阻函数、基于主成分分析和加权评分分析的评价指标确定方法以及驾驶员路径选择偏好权重的确定方法。最后,利用Mapx、VisualC＋＋和Access数据库联合开发出了自适应路径规划系统,并用长春市驾驶员的实例数据验证了系统的有效性和算法模型的正确性。     

综合管廊投资运营模式选择模型构建研究

为从当前国内常用的投资运营模式中遴选出与综合管廊项目特征契合的模式,保障综合管廊实现成功运营,通过对国内常用的几种投资运营模式进行分析,建立以项目特征、工作效能、社会效益、经济效益和项目风险为准则层、包含18个指标的综合管廊投资运营模式选择指标体系,选择逼近理想解对指标进行量化计算。运用层次分析法与逼近理想解相结合的方法克服逼近理想解无法确定指标权重的缺点,并引入云模型对层次分析法和逼近理想解分别加以改进,充分考虑模式选择过程中专家评价语言的不确定性,构建基于云模型改进AHP-TOPSIS的综合管廊投资运营模式选择模型,同时以西安市某综合管廊PPP项目Ⅰ标段为案例,验证了该模式选择模型具有较高的拟合度。     

基于偏好函数与深度信念网络的自动化码头AGV实时调度算法

为提高自动化集装箱码头岸桥作业效率、降低自动导引车(Automated Guided Vehicle,AGV)空载行驶距离,以偏好函数和深度信念网络(Deep Belief Network,DBN)为核心设计AGV实时调度算法,完成AGV任务分配指派,优化AGV作业任务序列。利用偏好函数为处于待分配状态的AGV筛选最优集装箱,产生训练样本并更新训练集,通过DBN实时更新集装箱的偏好函数,重复该过程直至集装箱作业完毕。算例分析表明:同两种现行调度规则对比,AGV空载距离和岸桥作业时间显著下降;与人工神经网络(Artificial Neural Network,ANN)相比,DBN可有效提高算法精度与求解效率;算法针对环境动态变化实时分配集装箱,为自动化码头提高效率和降低能耗提供依据。     

User preferences regarding autonomous vehicles

This study gains insight into individual motivations for choosing to own and use autonomous vehicles and develops a model for autonomous vehicle long-term choice decisions. A stated preference questionnaire is distributed to 721 individuals living across Israel and North America. Based on the characteristics of their current commutes, individuals are presented with various scenarios and asked to choose the car they would use for their commute. A vehicle choice model which includes three options is estimated:

• (1)Continue to commute using a regular car that you have in your possession.
• (2)Buy and shift to commuting using a privately-owned autonomous vehicle (PAV).
• (3)Shift to using a shared-autonomous vehicle (SAV), from a fleet of on-demand cars for your commute.

A factor analysis determined five relevant latent variables describing the individuals’ attitudes: technology interest, environmental concern, enjoy driving, public transit attitude, and pro-AV sentiments. The effects that the characteristics of the individual and the autonomous vehicle have on use and acceptance are quantified through random utility models including logit kernel model taking into account panel effects.Currently, large overall hesitations towards autonomous vehicle adoption exist, with 44% of choice decisions remaining regular vehicles. Early AV adopters will likely be young, students, more educated, and spend more time in vehicles. Even if the SAV service were to be completely free, only 75% of individuals would currently be willing to use SAVs. The study also found various differences regarding the preferences of individuals in Israel and North America, namely that Israelis are overall more likely to shift to autonomous vehicles.Methods to encourage SAV use include increasing the costs for regular cars as well as educating the public about the benefits of shared autonomous vehicles.     

基于面板数据的乘用车购买偏好分析

基于2009-2019年中国乘用车销售面板数据,结合车辆特性构建Logit模型,分析车辆特性衍变对消费者需求的响应,对比中国和瑞士乘用车的消费偏好.研究结果显示:发动机燃油效率更高,功率更大的乘用车市场份额占比更高;重型车比轻型车更受中国消费者青睐;燃油效率的边际值在大功率汽车细分市场中较小,即最可能产生更多污染排放的...     

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公共交通出行者ATIS信息选择行为对ATIS实际实施效果存在显著影响。本文以大连市公共交通出行信息需求专项调查为基础,通过因子分析方法提取并定义ATIS信息因子,对公共交通相关ATIS信息进行合理分类,同时引入公共交通出行者年龄、职业、先进通讯技术使用情况等个人特征变量,建立公共交通出行者ATIS信息选择Binary Logit 模型,对公共交通出行者ATIS信息选择行为影响因素进行研究。研究结果显示公共交通出行者个人特征与ATIS信息内容特性对公共交通出行者ATIS信息选择行为存在不同程度的影响,城市交通信息服务系统的建设与运营应进一步面向公共交通出行者实现“以人为本”。     

基于SP调查的天津市居民出行行为时间价值

为揭示天津市居民出行行为时间价值的一般规律,采用SP调查中的卡片式面谈调查法,运用市场细分法确定调查规模及抽样率,采用计算包容性检查矩阵等数据处理手段,估算天津市居民出行行为时间价值。比较了出行行为时间价值与单位工作时间价值之间的关系,并分析了不同出行方式、出行目的、出行时段的时间价值,研究了出行收入与时间价值的变化规律。得出现阶段天津市居民出行行为时间价值的分布,表明大部分出行者不愿为出行支付较高费用,但随着收入增加,出行行为时间价值将会快速增长,使个体机动化出行方式的需求增大,城市出行方式结构可能出现拐点。     

考虑用户偏好的有轨电车景观研究

从道路使用者的角度出发,研究有轨电车建设中的道路景观问题。采用问卷调查法与模拟评价法相结合,分析不同年龄、性别、社会背景的群体对道路景观的重视程度以及对道路景观的偏好。结果表明：在有轨电车建设中,使用者最重视的是污染问题,对道路景观的改善重视程度并不高,尤其是男性;道路绿化是影响景观的首要因素,而有轨电车供电接触网、轨道对景观的影响并不大;道路绿化形式中,使用者偏向于行道树＋草坪的形式;雕塑小品形式中,园艺景观小品最受欢迎;有轨电车供电接触网和地面铺装形式中,最受欢迎的是没有供电接触网且为草地铺装。     

Nature of influence of out‐of‐vehicle time‐related attributes on transit attractiveness: a random parameters logit model analysis

This paper describes the nature of the impacts of walking distances and waiting time on transit use. The relative trade‐offs of walking and transfer components with other transit service attributes are also discussed. A total of 449 completed stated‐preference interviews were collected; with six observations from each respondent, the total number of observations was 2694. This data set was used to estimate the coefficients in different utility functions using a random parameters logit model. The results demonstrated that walking distances to and from transit stops have important and significant nonlinear negative influences on the attractiveness of transit. Transfer waiting time was also shown to have a significant nonlinear negative impact on transit attractiveness. The random parameters logit model had a better model fit than the standard logit model. Some of the findings obtained here are novel, while others are consistent with previous works. These findings have implications for both theory and practice. Copyright © 2014 John Wiley & Sons, Ltd.