Book Review: Muhammad Faishal Ibrahim and Peter J. Goldrick: Shopping Choices with Public Transport Options

This book has been motivated by the observation that by and large studies of spatial shopping behaviour have not taken into account transport mode, while most transport studies ignored the attributes of shopping centres. The study, described in this book represents an attempt to bridge this gap. To that effect, the authors try to identify and analyse the importance of different factors, which are taken into account by shoppers in their shopping centre choice in regions with a wide choice of public transport. In addition, they analyse shoppers' perceptions of transport modes in the context of shopping trips. They start however with a review of trends of retail decentralisation and transport planning

Relevance of Prospect Theory to Transport Choice Modeling: a Rejoinder

I was pleased to see that van de Kaa spelled out my comments on prospect theory and must have spent quite some time tracing back the references and conducting some additional qualitative research. The very purpose of my contribution to the workshop and the paper was to stimulate discussion and it seems to have succeeded in that regard

PUMA - a multi-agent model of urban systems

It is increasingly recognised that land use change processes are the outcome of decisions made by individual actors, such as land owners, authorities, firms and households. As multi-agent models provide a natural framework for modelling urban processes on the level of individual actors, Utrecht University, Eindhoven University of Technology and RIVM are developing PUMA (Predicting Urbanisation with Multi-Agents), a full fledged multi-agent system of urban processes. PUMA consists of various modules, representing the behaviours of specific actors. The land conversion module describes farmers', authorities', investors' and developers' decisions to sell or buy land and develop it into other uses. The households module describes households' housing careers in relation to life cycle events (marriage, child birth, aging, job change etc.). The firms module includes firms' demography and their related demand for production facilities leading to location choice processes. The daily activity pattern module describes the trips made and locations visited by individuals to carry out certain tasks. This module generates aggregated effects of individual behaviours (congestion, pollution, noise), affecting households' or firms' longer term location decisions. The paper describes the model system architecture and the interactions between the modules. Particular attention is devoted to the households module that includes a behaviourally sophisticated model of households' process of awakening (deciding to actively search for another dwelling), search and acceptance of an offered dwelling. This model was calibrated on the Dutch Housing Preferences Survey. Based on the disaggregate housing search and acceptance model, the households module describes housing market dynamics and indicates the demand for new dwellings per region. The paper describes the model specification and calibration in detail. The households module was implemented and tested for the Northwing of the Dutch Randstad, including about 1.5 million households and 1.6 million dwellings. The paper describes the implementation and the first model results.

Firm dynamic productivity and economic growth

This paper examines the dynamics of firms and their productivity growth in Kuala Lumpur during period 1990 to 2007. Using a dataset of Kuala Lumpur firms, proximity and area analysis are conduct to examine the location of firms within five transportation feature (highways, major roads, rail networks, rail stations, and terminals) and in the CBD area. The result of empirical analyses shows that most of these firms are in Financing, Insurance, Real Estate, Investment and Business Services. We also find that most of the firms are located proximate to major roads, highways and in the CBD area.</p

What is smart for retailing?

AbstractWhile the last decade has seen increasing interest in the smart city phenomenon from both scholars and practitioners, little attention has been paid to what extent retailing might be considered as part of smart cities, with benefits for all the actors involved in the process. In fact, retailing is subject to a radical innovation force that makes available several technologies that can be successfully applied. The extensive use of advanced systems gives rise to new questions concerning the smart use of technologies. Moreover, the application of advanced technologies is part of a trend towards the creation of smart cities for a better urban society. In this scenario, the idea of smartness goes beyond the concept of application of new technologies by also including more important dimensions, such as organizational structure. Hence, our work aims at identifying what can be considered smart for retailing, in terms of features of smart technology for retailing, and the challenges emerging from the adoption of such smart technologies

Synchronization of home departure and arrival times in dual earner households with children:panel regression model of time gaps

Organizing schedules and allocating time to different activities is always a challenge in dual-earner households, especially when they have children. Parents may need to link their schedule to those of their children to allow them escorting their children to school or to take care or be with their children at home. This paper reports the results of an analysis of the degree of synchronization of home departure and arrival times in dual earner households with children, where the degree of synchronization is defined as the gap between departure and arrival times of a parent and child. Using activity-travel diary data of different household members, a random parameters regression model is estimated to examine differences in time gaps in home departure and arrival times between parents and children as a function of gender, day of the week, age of the youngest child, and other socio-demographic characteristics. The results of the analysis provide insight into factors influencing the degree of synchronization and coordination of double activity-travel scheduling decisions in households with children. Findings indicate that gender, number of children in the household, age of the youngest child, travel within or outside peak hours, day of the week, transport mode used for the work commute and household income level significantly affect time gaps, especially arrival time gaps.</p

Using ensembles of decision trees to predict transport mode choice decisions: Effects on predictive success and uncertainty estimates

The application of activity-based models of travel demand to planning practice has triggered interest in issues that potentially improve the accuracy and/or usefulness of model forecasts. The limited knowledge of uncertainty propagation in complex stochastic model systems has put uncertainty analysis high on the research agenda to differentiate between simulation error and policy effects. Focusing on transport mode choice, this paper draws attention to the use of model ensembles, which has hardly been explored in travel demand forecasting. Prior studies predicting transport mode choice has typically relied on a single equation, relating observed transport mode choices to a set of personal and contextual variables. The estimated single model is then assumed to apply to all individuals. This paper explores the idea of replacing a single equation/representation with an ensemble of model predictions, using the decision tree formalism. Potentially, ensembles better capture the notion that travellers may use different heuristics in their transport mode decisions. The aim of the study is to investigate whether the use of a model ensemble of different decision heuristics will reduce the error/uncertainty in predicting transport mode decisions. Results of the study, conducted in the Rotterdam region, The Netherlands, suggest that the accuracy of predicting transport mode choice is improved, albeit non-monotonically, with increasing ensemble size. Simultaneously, the uncertainty related to these predictions is decreasing. Finally, it is shown that the importance of the selected explanatory variables co-varies with ensemble size. Estimation results tend to become stable in this study with an ensemble size of approximately 20 decision trees

Photocathodes for a post-processed imaging array

Preliminary results of a photon detector combining a Micromegas like multiplier coated with a UV-sensitive CsI photocathode are described. The multiplier is made in the CMOS compatible InGrid technology, which allows to post-process it directly on the surface of an imaging IC. This method is aimed at building light-sensitive imaging detectors where all elements are monolithically integrated. We show that the CsI photocathode deposited in the InGrid mesh does not alter the device performance. Maximum gains of ~6000 were reached in a singlegrid element operated in Ar/CH4, with a 2% Ion Back Flow fraction returning to the photocathode