Women’s mode and trip structure choices in daily activity-travel: a developing country perspective

ABSTRACT

In this paper, we analyze the travel patterns of Iranian women, where typical patriarchal views and specific social and cultural norms may differ from the patterns of those in western societies. In addition to inherent psycho-physical gender differences, women in Iran can face special constraints forcing them not to be involved in all activity-travel patterns that people in developed countries usually undertake. We pay special attention to the role of marital and employment status on women’s activity-travel patterns. To this end, we develop a joint mode and daily activity pattern (DAP) discrete choice model, which is a two-level mixed nested Logit. The upper nest of the proposed model embodies women’s DAP choices, and the lower nest belongs to the mode choices. In this paper, we try to show how different factors in a patriarchal Muslim society like Iran affect or restrict women’s type and structure of activity-travel patterns.     

旅客购票模式与渠道关联选择行为的建模分析

为分析多元化售票渠道下旅客购票选择行为的影响因素及交互特征，解析了多渠道情境下旅客购票过程的 3个阶段，辨识了旅客购票的 3类典型模式；运用协同进化分析思想，建立了购票模式与渠道关联选择的协同进化 Logit模型；基于道路客运联网售票信息系统数据，进行了模型的实证应用，分析了特征变量对旅客购票选择行为的影响，揭示了渠道与模式间关联选择行为特征.研究表明：性别，年龄，提前购票时间，出行时间，出行里程，发车频率等因素对旅客购票行为有显著影响；旅客购票模式和渠道选择间存在相关性，某一决策选择受另一决策结果的影响；考虑两者的交互作用有助于提高分析预测精度，2类决策模型的精度分别提高了5.98%和5.72%.     

Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars

Recently, policy makers’ expectations about the role of electric cars in reducing emissions have risen substantially. In parallel, academic research on purchase intentions has dramatically increased. Originally, most studies have focused on utility attributes and price. More recently, several hybrid choice models have been estimated to include the impact of attitudes on choice probabilities. In addition, a few studies have caught the attention to social influence. In contributing to this line of research, this paper reports the results of an expanded hybrid choice, which simultaneously estimated all these different effects in a single integrated model of purchase intention. Results indicate that the model performs well. Costs considerations contribute most to the utility of electric cars. Social influence is less important, but there is also evidence that people tend to take it into consideration when there are positive public opinions about electric cars and the market share becomes almost half of friends of their social network. The intention to purchase an electric car is also influenced by attitudes about environmental concerns and technology acceptance.     

Dynamic diurnal social taxonomy of urban environments using data from a geocoded time use activity-travel diary and point-based business establishment inventory

In this paper, we explore the diurnal dynamics of joint activity participation in a small city in Pennsylvania, USA, using behavioral data and an inventory of business establishments. We account for the variation caused by the collective impact of social, temporal and spatial choices of individuals to produce predicted space–time visualizations of activity participation. The focus is on how social contexts of an activity impact the temporal and spatial decisions regarding the activity locations and how this impact varies depending on activity types. A comparison across activity types and social interaction types is made among spatial patterns during a day. The CentreSIM dataset, which is a household-based activity diary survey collected in Centre County (Pennsylvania, USA) in 2003, provides very detailed social interaction information enabling the analysis of social, spatial and temporal aspects of activity participation. In this paper we use this information to develop a spatio-temporal interpolation method and demonstration based on kriging. In this way, we extract the dynamic social taxonomy of places from the behavioral information in the dataset and suggest how urban and transportation models can be informed from the dynamics of places by observing “what is taking place” (activities being pursued in the context of this paper) combined with “what exists” (business establishments) or “what is available” (businesses that are open). The method here can also be used to improve the design of urban environments (e.g., filling gaps in desired activity locations), manage specific places (e.g., extending the opening and closing times of businesses), study transportation policies that are sensitive to time of day (e.g., pricing of parking to discourage crowding and traffic congestion), and modeling of spatio-temporal decisions of social activities in travel demand models (e.g., to guide the development of model specification and representation of the space in which behavioral models are applied).     

A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area

Airport choice is an important air travel-related decision in multiple airport regions. This paper proposes the use of a probabilistic choice set multinomial logit (PCMNL) model for airport choice that generalizes the multinomial logit model used in all earlier airport choice studies. The paper discusses the properties of the PCMNL model, and applies it to examine airport choice of business travelers residing in the San Francisco Bay Area. Substantive policy implications of the results are discussed. Overall, the results indicate that it is important to analyze the choice (consideration) set formation of travelers. Failure to recognize consideration effects of air travelers can lead to biased model parameters, misleading evaluation of the effects of policy action, and a diminished data fit.     

Adapting interactive stated response techniques to a self-completion survey

We report here on how we adapted Interactive Stated Response Methods to use in a self-completion survey of 454 California households to measure the market for electric vehicles in California. Electric vehicles are a novel product and have many features unfamiliar to consumers, in particular their home recharging capability and limited range. Reflexive techniques were designed to draw households into a deeper exploration of the lifestyle implications of electric vehicles than can be done in more typical self-completion surveys, and to stimulate key decision processes previously observed in detailed gaming interviews with 51 households. Reflexive self-completion techniques provide a middle course between typical large sample quantitative surveys and small sample, detailed gaming interviews. One of the benefits of the more intensive techniques was that participants reported finding the surveys interesting and return rates were high for a self-completion approach – over sixty percent. We review previous transportation and sociological methods which inspired our design, describe the design goals and features of our research, and summarize research results pertinent to testing the validity of our approach.     

A practical assessment of stated preferences methods

Stated preferences data in the form of rankings, ratings and choices were collected in Santiago and discrete choice models estimated with them. The models were compared in terms of accuracy v/s the cost of obtaining the information and models. All methods produced reasonable but different models and fairly close subjective values of time. In terms of production costs the ranking method was a clear looser although the experimental design was slightly biased against it. Finally, the use of computerised interviews is highly recommended particularly for dealing with low income people.     

Bayesian estimation of multinomial probit models of work trip choice

In this paper, we estimate a multinomial probit model of work trip mode choice in Seoul, Korea, using the Bayesian approach with Gibbs sampling. This method constructs a Markov chain Gibbs sampler that can be used to draw directly from the exact posterior distribution and perform finite sample likelihood inference. We estimate direct and cross-elasticities with respect to travel cost and the value of time. Our results show that travel demands are more sensitive to travel time than travel cost. The cross-elasticity results show that the bus has a greater substitute relation to the subway than the auto (and vice versa) and that an increase in the cost of an auto will increase the demand for bus transport more so than that of the subway.     

Urban form,travel time,and cost relationships with tour complexity and mode choice

The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.