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Modeling Agglomeration Forces in Urban Dynamics : A Multi-Agent System Approach
Theo Arentze, Harry Timmermans 서울시립대학교 도시과학연구원 2003 International journal of urban sciences (IJUS) Vol. No.
Urban dynamics is driven by the location decisions of firms and households. The preferences of households and firms for a certain location generally depend on the presence of other households or firms at the same location. In this paper, we propose and illustrate a multi-agent model that takes such agglomeration effects into account. In the model, the households or firms that are potentially interested in a candidate site for (re-)development are individually represented as agents that can indicate their interest by making a bid. In compiling a proposal based on bids of individual agents, the model takes positive and negative synergies between agents into account. Planners and developers are also represented in the model as agents playing specific roles in the process. Simulations in the area of retailing demonstrate the model and show that agglomeration effects have an impact on generated proposals. It is argued that the model can be used as a location-decision component in dynamic multiagent, land-use systems for simulation or planning support.
Examining Temporal Effects of Lifecycle Events on Transport Mode Choice Decisions
Marloes Verhoeven, Theo Arentze, Harry Timmermans, Peter van der Waerden 서울시립대학교 도시과학연구원 2007 International journal of urban sciences (IJUS) Vol. No.
This paper describes the first results of a study on the impact of events on transport mode choice decisions. An Internet-based survey was designed to collect data concerning seven structural lifecycle events. In addition, respondents answered questions about personal and household characteristics, possession and availability of transport modes and their current travel behaviour. In total, 710 respondents completed the online survey. The complexity of transport mode choice is modelled using a Bayesian Decision Network. This paper focuses only on the time influence of events on transport mode choice decisions. We assume that people change or at least reconsider their behaviour after a structural lifecycle event, at times directly after experiencing a change and at times only after a period of time. We estimated a multinomial choice model to estimate the effect of these structural events, and in particular of the length of the time elapsed, on transport mode choice.
Soora Rasouli,Harry Timmermans,Gamze Dane,Anna Grigolon 서울시립대학교 도시과학연구원 2020 도시과학국제저널 Vol.24 No.3
In recent years, the importance of incorporating attribute uncertainty in models of spatial choice behaviour has been recognized in urban planning research. The majority of studies concerned with decision-making under uncertainty assume some a-priori probability distribution for discrete attribute levels or continuous attribute values. Consequently, it has been implicitly assumed that the decision maker perceives the uncertain attributes as reflected in the presumed discrete or continuous probability distributions. This assumption may, however, not be necessarily true. Capturing the shape of the probability distributions from the decision maker’s perspective likely increases the accuracy of models of decision-making under uncertainty. The aim of the current paper, therefore, is to develop an approach for measuring and modelling individuals’ subjective beliefs about uncertain attributes. The approach is illustrated using beliefs about future mortgage rates as an example. To understand the impact of trends in the data, we experimentally changed the trends in mortgage rates over 20 years with 5 years intervals and analysed the impact of such trends on subjective beliefs of anticipated future mortgages. More specifically, four patterns of the evolution of mortgage rates were created, i.e. monotonically increasing, monotonically decreasing, increasing for the first four intervals and then decreasing, and decreasing for the first four intervals and then increasing. Results suggest that the shape of the pattern (nature of the trend) significantly influences subjective probability assessments of future mortgage rates.
Soora Rasouli,Harry Timmermans 서울시립대학교 도시과학연구원 2013 도시과학국제저널 Vol.17 No.3
No previous studies seem to have examined uncertainty in forecasts of origin destination matrix (OD) tables, predicted by advanced activity-based models of travel demand. This paper documents the design and results of a study on the effects of model uncertainty of the Albatross model on predicted time-dependent OD matrices, for the Rotterdam area,the Netherlands, as a case study. The study involves 1000 runs of model system for a synthetic population of 41,668 individuals. Results indicate that the average uncertainty in the predicted OD matrices due to model uncertainty is 45%, and .13% for destination totals based on these simulation runs. In general, uncertainty is lower for the destinations with higher traffic volumes. Uncertainty in predicted traffic volumes, represented by the cells of the OD matrix, tends to be higher. Finally, for both types of indicators, there is evidence of spatial variability in coefficients of variation, capturing uncertainty in destination totals and traffic volumes. Generally, uncertainty is a non-linear function of the number of samples.
Activity-based models of travel demand: promises, progress and prospects
Soora Rasouli,Harry Timmermans 서울시립대학교 도시과학연구원 2014 도시과학국제저널 Vol.18 No.1
Because two decades have almost passed since the introduction of activity-based modelsof travel demand, this seems the right time to evaluate progress made in the developmentand application of these models. This invited paper seeks to discuss the initial promisesof activity-based models as an alternative to four-step and tour-based models, summarizeprogress made and identify still unsolved issues that require further research.
IDENTIFYING SHOPPING STYLES: CLUSTER ANALYSIS OF SHOP VISIT PATTERNS IN AN INDONESIAN SHOPPING MALL
Widiyani,Aloys Borgers,Harry J.P. Timmermans 글로벌지식마케팅경영학회 2014 Global Marketing Conference Vol.2014 No.9
In 2005, Asia Pacific had the largest percentage of recreational shoppers in the world, while at the same time, Indonesia achieved the highest percentage for recreational shopping in Asia Pacific. (AC Nielsen, 2006). Shopping malls in Indonesia are growing rapidly and have currently increased in size, theme and location, and in the number of different types of shops. Given the rapid growth of malls, mall managers and retailers face the challenge to develop new strategies to survive in this highly competitive market. To gain greater insight into the relationship between shoppers and retailers, our aim is to explore shoppers’ behavior during their visit to the mall, specifically with respect to the type of shops visited. We will identify different shopping patterns and their characteristics based on 171 unobtrusive observations of shoppers using hierarchical clustering analysis. The results indicate that four shopping styles can be identified: fashion shoppers, basic shoppers, social shoppers, and entertainment seekers. Our results enhance an understanding of shopping styles. Mall managers and retailers could use this knowledge to decide the appropriate retail mix in the mall.
IDENTIFYING SHOPPING STYLES: CLUSTER ANALYSIS OF SHOP VISIT PATTERNS IN AN INDONESIAN SHOPPING MALL
Widiyani,Aloys Borgers,Harry J.P. Timmermans 글로벌지식마케팅경영학회 2014 Global Marketing Conference Vol.2014 No.7
In 2005, Asia Pacific had the largest percentage of recreational shoppers in the world, while at the same time, Indonesia achieved the highest percentage for recreational shopping in Asia Pacific. (AC Nielsen, 2006). Shopping malls in Indonesia are growing rapidly and have currently increased in size, theme and location, and in the number of different types of shops. Given the rapid growth of malls, mall managers and retailers face the challenge to develop new strategies to survive in this highly competitive market. To gain greater insight into the relationship between shoppers and retailers, our aim is to explore shoppers’ behavior during their visit to the mall, specifically with respect to the type of shops visited. We will identify different shopping patterns and their characteristics based on 171 unobtrusive observations of shoppers using hierarchical clustering analysis. The results indicate that four shopping styles can be identified: fashion shoppers, basic shoppers, social shoppers, and entertainment seekers. Our results enhance an understanding of shopping styles. Mall managers and retailers could use this knowledge to decide the appropriate retail mix in the mall.
Gustavo G. Manzato,Theo A. Arentze,Harry J. P. Timmermans,Dick Ettema 서울시립대학교 도시과학연구원 2010 도시과학국제저널 Vol.14 No.1
This paper addresses an exploratory study about the mediated influence of a set of location and accessibility attributes along with firm types and the effect on office firm closures. We use a proportional hazard modeling approach, examining the probability that an office firm will go out of business in any given year, conditional on the fact that it did not go out of business in the years prior. Variables include urbanization levels and regional effects; accessibility to airports, train stations, shopping centers and the roadway network; availability of parking facilities and schools; demographic and economic aspects; effects of agglomeration economies; rent price; and the type of economic activity of the office firm. Most of them presented significant information to assist in the explanation of the firm closure. Also, interaction effects between covariates and firm types brought a better understanding about the firm closure patterns in relation to urban characteristics. Assessing firm closures is an element of a firm demographic approach and overall dynamics. In turn, this is part of a multiagent system to simulate the co-evolution of firm dynamics and changes in activity-travel patterns.