Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.     

Timetable-based operation in urban transport: Run-time optimisation and improvements in the operating process

Urban public transit provides an efficient means of mobility and helps support social development and environmental preservation. To avoid loss of ridership, transit authorities have focussed on improving the punctuality of routes that operate using timetables. This paper presents a new approach to generating run-time values that is based on analytical development and micro simulations. The work utilizes previous research (described herein) and the experience acquired by Transports Metropolitans de Barcelona (TMB) in operating bus routes based on timetables. Using a sample of historical data, the method used for generating run-time values consists of the following steps: purging and screening atypical trips, based on the consideration of confidence intervals for median trips; segmenting the day into time bands based on the introduction of a new hierarchical classification algorithm; creating initial run-time values based on criteria derived from statistical analysis; adjusting and validating initial run-time values using micro simulations; and evaluating incident-recovery times at the end of trips in order to guarantee the punctual departure of the next trip in the vehicle schedule. To favour service improvement, we also introduced certain indicators that can identify the root causes of non-compliance. As a final step, in order to ensure the applicability and use of the model, we promoted the development of our model within the framework of the HASTUS™ software solution.     

Seaport research: A structured literature review on methodological issues since the 1980s

This study aims to investigate how seaport research has been conducted from the methodological perspective. To this end, this study reviews published port literature for the last three decades (1980-2000s). The investigation primarily categorises the literature according to various methodological issues such as research paradigm, research strategy, base-disciplines, research methods and analysis techniques in order to provide meaningful implications on methodological evolution in seaport research for the period. This study suggests methodological bias in port research to a positivistic paradigm, following a quantitative trajectory moving from conceptual to empirical studies. In addition, the increased use of mathematical modelling and advanced statistical analysis methods is clearly observed. The introduction of advanced analytical tools used in other academic disciplines facilitates discussions in particular research area and amplifies the literature in those areas. This paper also suggests research gaps from the methodological perspective and implications for future port research.     

A network option portfolio management framework for adaptive transportation planning

A real option portfolio management framework is proposed to make use of an adaptive network design problem developed using stochastic dynamic programming methodologies. The framework is extended from Smit’s and Trigeorgis’ option portfolio framework to incorporate network synergies. The adaptive planning framework is defined and tested on a case study with time series origin-destination demand data. Historically, OD time series data is costly to obtain, and there has not been much need for it because most transportation models use a single time-invariant estimate based on deterministic forecasting of demand. Despite the high cost and institutional barriers of obtaining abundant OD time series data, we illustrate how having higher fidelity data along with an adaptive planning framework can result in a number of improved management strategies. An insertion heuristic is adopted to run the lower bound adaptive network design problem for a coarse Iran network with 834 nodes, 1121 links, and 10 years of time series data for 71,795 OD pairs.     

基于纸纤维改性的隧道工程透水砂浆性能研究北大核心CSCD

为提出一种适用于隧道初期支护基面找平并且具有一定透水性能的砂浆,将纸纤维加入砂浆试块中对其性能进行改性。通过分析纸纤维的降解原理,并将不同掺量的纸纤维加入砂浆试块中,对其体积密度、吸水率、抗压强度等基本性能指标及微观结构进行测试和分析。由试验结果可知:在碱性环境中,纸纤维具有可降解的性能特点;纸纤维可以使普通砂浆试块的吸水率提升2~3倍,同时也会造成砂浆试块的体积密度和抗压强度降低;对砂浆试块吸水率和抗压强度进行线性拟合后发现其吸水率和抗压强度呈现负相关关系。研究结果表明,通过纸纤维对砂浆进行透水性能的提升是可行的,但是纸纤维掺量对砂浆其他性能的影响还有待进一步研究。     

GPS-based optimization of plug-in hybrid electric vehicles’ power demands in a cold weather city

Using the WPG03 duty cycle developed from global positioning data collected in Winnipeg, Canada, real world energy demands and costs are modeled. Three types of plug-in hybrid electric vehicles, four temperatures and two charging scenarios are compared to a vehicle with an internal combustion engine. Cold temperatures are shown to greatly affect vehicle operation energy costs, which is an important consideration for cold weather cities such as Winnipeg. The largest energy cost savings are obtained for smaller-battery plug-in hybrids that had the opportunity to charge during the day.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.     

Implementing green supply chain practices: an empirical investigation in the shipbuilding industry

ABSTRACT

Environmental concerns have become important in the shipbuilding industry. Governmental expectations about environmental and social performance are much higher than in the past. Public authorities penalize companies that do not comply with the rules. Shipbuilding companies face these challenges by introducing new technologies into their business processes. They do not only start initiatives to green their own business processes but also those of their supply chain partners. This form of environmental management is called Green Supply Chain Management (GrSCM) and its importance is increasingly recognized. Although GrSCM is growing, companies are experiencing difficulties engaging suppliers in environmental activities.

This empirical study analyses drivers for supply chain participation of suppliers in the shipbuilding industry. We explain the participations of suppliers in GrSCM practice by investigating influencing factors including governmental involvement in greening the supply chain, customer requirements towards green issues, feeling of social responsibility, competitive advantage by going green, and GrSCM readiness. Hypotheses are tested with partial least squares, using survey data of 93 suppliers of two leading shipbuilding companies. We found GrSCM readiness, competitive advantage, and social responsibility to be significant drivers in supplier participation. No significant support was found for governmental involvement and customer requirements.     

A link-node complementarity model and solution algorithm for dynamic user equilibria with exact flow propagations

In this paper, we propose a link-node complementarity model for the basic deterministic dynamic user equilibrium (DUE) problem with single-user-class and fixed demands. The model complements link-path formulations that have been widely studied for dynamic user equilibria. Under various dynamic network constraints, especially the exact flow propagation constraints, we show that the continuous-time dynamic user equilibrium problem can be formulated as an infinite dimensional mixed complementarity model. The continuous-time model can be further discretized as a finite dimensional non-linear complementarity problem (NCP). The proposed discrete-time model captures the exact flow propagation constraints that were usually approximated in previous studies. By associating link inflow at the beginning of a time interval to travel times at the end of the interval, the resulting discrete-time model is predictive rather than reactive. The solution existence and compactness condition for the proposed model is established under mild assumptions. The model is solved by an iterative algorithm with a relaxed NCP solved at each iteration. Numerical examples are provided to illustrate the proposed model and solution approach. We particularly show why predictive DUE is preferable to reactive DUE from an algorithmic perspective.