Discrete Choice Approach Research Articles

Modeling route choice criteria from home to major streets: A discrete choice approach

Abstract A discrete choice model that consists of three sub-models was developed to investigates the route choice criteria of drivers who travel from their homes in the morning to the access point along the major streets that bound the Traffic Analysis Zones (TAZs). The first sub-model is a Nested Logit Model (NLM) that estimates the probability of a driver has or has no multiple routes, and if the driver has multiple routes, the route selection criteria are based on the access point’s intersection control type or other factors. The second sub-model is a Mixed Logit (MXL) model. It estimates the probabilities of the type of intersection control preferred by a driver. The third sub-model is a NLM that estimates the probabilities of a driver selecting his/her route for its shortest travel time or to avoid pedestrian, and if the aim is to take the fastest route, the decision criteria is based on the shortest distance or minimum stops and turns. Data gathered in a questionnaire survey were used to estimate the sub-models. The attributes of the utility functions of the sub-models are the driver’s demographic and trip characteristics. The model provides a means for transportation planners to distribute the total number of home-based trips generated within a TAZ to the access points along the major streets that bound the TAZ.

Do consumers care about European food labels? An empirical evaluation using best-worst method

Purpose The purpose of this paper is to investigate Spanish consumer preferences for several food-labelling schemes on semi-cured, pasteurised sheep milk cheese. In particular, the authors used three labels regulated by the European Union regulation (European organic logo, protected denomination of origin (PDO) and nutritional fat content), and the remaining four have been introduced to the European food market by private initiatives (local, carbon footprint, food miles and animal welfare). Design/methodology/approach A Best-Worst Discrete Choice approach was applied in Spain during Fall 2011 by administrating a survey to 549 consumers. Findings The results suggest that the most valued labels are the PDO, followed by the organic logo and the nutritional panel. The least valued are food-miles labelling and carbon foodprint labels, while local-origin labels and animal welfare are in the middle position. Originality/value This study is the first to value consumer preferences for cheese products bearing several public and private European food-labelling schemes since literature on consumer preferences for food labels has only dealt with a comparison of a few (two or at most three) food-labelling schemes. In addition, the added value of this paper is also the use of the BWC approach that has the advantage of providing the best way to discriminate the degree of importance given by respondents to each food labels by overcoming the problem of bias caused by differences in the use of rating scales.

What factors affect physicians' labour supply: Comparing structural discrete choice and reduced-form approaches.

Little is known about the response of physicians to changes in compensation: Do increases in compensation increase or decrease labour supply? In this paper, we estimate wage elasticities for physicians. We apply both a structural discrete choice approach and a reduced-form approach to examine how these different approaches affect wage elasticities at the intensive margin. Using uniquely rich data collected from a large sample of general practitioners (GPs) and specialists in Australia, we estimate 3 alternative utility specifications (quadratic, translog, and box-cox utility functions) in the structural approach, as well as a reduced-form specification, separately for men and women. Australian data is particularly suited for this analysis due to a lack of regulation of physicians' fees leading to variation in earnings. All models predict small negative wage elasticities for male and female GPs and specialists passing several sensitivity checks. For this high-income and long-working-hours population, the translog and box-cox utility functions outperform the quadratic utility function. Simulating the effects of 5% and 10% wage increases at the intensive margin slightly reduces the full-time equivalent supply of male GPs, and to a lesser extent of male specialists and female GPs.

Discrete choice approach for assessing deprivation cost in humanitarian relief operations

One of the key objectives of humanitarian logistics is to guarantee the timely delivery of supplies to people affected by disasters during the response phase. In this regard, it is fundamental to design appropriate models to minimize the social costs of response operations to distribute essential supplies to populations in need. In addition to merely cover logistics cost, social costs include deprivations costs, which are an increasing function of deprivation time, derived from the human suffering caused by the lack of access to a good or a service. This research uses the theory of discrete choices to assess deprivation costs due to the time spent waiting for the delivery of a basket of basic supplies, defined as the changes in the welfare of people affected by disasters. To this end, we designed a stated choice survey, applied to people living in areas affected by floods and earthquakes in Colombia. The estimated models consider the influence of individual's socioeconomic characteristics and random effects on the deprivation cost functions. The functions have a nonlinear structure, strictly increasing, and convex on the deprivation time. The results are useful for estimating the social costs of humanitarian relief operations.

Stability Assessment of Reference Genes for Reliable Analysis of Silver Nanoparticles Cytotoxicity in HepG2 Cell Line

In spite of many reports on the toxicity of silver nanoparticles (AgNPs), the mechanisms underlying the toxicity are far from clear. For many years, evaluation of gene expression levels by reverse transcription real-time quantitative PCR (RT-qPCR) has been the discrete choice approach for discovering nanotoxicity-associated alterations and related mechanisms. The appropriate selection of reference genes is critical step for accurate data interpretation in RT-qPCR. In this study, five reference genes including GAPDH, YWHAZ, ACTB, TBP and 18s rRNA were evaluated to determine the most stable genes in a HepG2 cells under various AgNPs treatment conditions. Analysis by geNorm program ranked ACTB and YWHAZ in HepG2 cells as the most stable reference genes, While TBP was assessed as the most stable one by NormFinder, implying the importance of the employed algorithm in comparative interpretation of the data. 18s rRNA exhibited the least stable expression in this study using both algorithms. Cumulative data suggested the use of two reference genes (ACTB and TBP) for RT-qPCR data normalization under AgNPs treatment. Here, the selection of superior reference genes for RT-qPCR in HepG2 cells under different AgNPs treatment conditions was firstly investigated, and will be considered in future studies on mechanisms underlying nanosilver exposure.

Exploring place image from visitors' expected and lived experiences: A discrete choice approach

Exploring place image from visitors' expected and lived experiences: A discrete choice approach

Human Dimensions Approach towards Integrating Sustainable Transportation and Urban Planning Policies: A Decision Support System (DSS) Based on Stated Preferences Data

While a lot of progress has been made in Germany to reduce CO2 emissions in the past years in almost all sectors of economy, however, the sector of transportation shows increasing CO2 emissions in the same period of time. Likewise, sustainability objectives of German land use policies have not been met so far, especially with regard of the continuously high rate of greenfield land used up for new housing development. In this paper, it is argued that environmental issues of both sectors have to be addressed by integrating urban housing development and transportation infrastructure planning policies. The paper reports on a stated preferences survey among house buyers in Germany, using a discrete choice approach, where parameters of sustainable urban design and sustainable transport are both integrated into one model. Building on concepts of behavioral economics, preferences are elicited for sub-samples of different “environmental awareness”. Results show differences in tastes for higher building densities to reduce land consumption as well as differences in tastes for transport infrastructure development and frequency of public transport parameters. In addition, a decision support system is developed to analyze the impact of individual parameters on choosing one alternative over the other. Form this, conclusions on potential market shares for sustainable housing and transport development are drawn and recommendations are given to implement integrated urban design and transportation infrastructure policies.

Dynamics of Activity Time-of-Day Choice

This study explored travelers’ decision behavior in selecting activity start times. The study examined the problem in the context of the Agent-based Dynamic Activity Planning and Travel Simulation (ADAPTS) activity-based travel demand model for the Chicago, Illinois, metropolitan area. A unique feature of the ADAPTS framework is its consideration of planning horizons for various activity attributes. Naturally, the various attributes of an activity—such as start time, duration, location, party involvement, and mode of travel—can be planned in different time horizons. An attribute that is planned affects the choice of other activity attributes. Therefore, developing a true behavioral time-of-day choice model would not be possible unless the planning order of activity attributes and the dynamics of travelers’ decision-making processes are taken into account. Similarly, it can be argued that there should be fundamental differences in the time-of-day decision process when other attributes of the activity are not yet planned but are to be decided at a later time. The presented time-of-day model aims to capture the dynamics of this decision process by considering the planning time horizons of other attributes of the activity, as well as the outcomes of the decisions. The study adopted the discrete choice approach to model activity timing decisions and a hybrid utility maximization and developed a regret minimization model to account for the heterogeneity of decision rules across choice variables. Analysis of the estimation results and parameter elasticities indicates that higher expected travel time, variations in travel time, and schedule occupancy rates for different time choices can significantly increase the regret value of the corresponding choice and therefore affect the time-of-day choice.

A Generalized Dynamic Discrete Choice Model for Green Vehicle Adoption

Abstract: Much is happening in the automotive industry and new models are in the market or are expected to be available soon. At the same time, environmental awareness, new regulations for increased fuel efficiency, and the need to diminish greenhouse gas emissions make small vehicles and alternative fuel vehicles more competitive. As a consequence, vehicle characteristics and consumer decisions will change rapidly in the short and medium run. Accounting for the dynamic of the problem is important to correctly forecast green vehicle acceptance and to evaluate eco-friendly policies. This paper proposes a generalized dynamic discrete choice approach that models purchase behavior and forecasts future preferences in a finite time horizon setting. The framework allows one-time purchases, repeated purchases, univariate and multivariate diffusion processes that capture the evolution of vehicle characteristics and dynamics in the market conditions. The models proposed are estimated using stated preference data collected in Maryland. Results show that the formulation with repeated purchases successfully captures changes in the market shares, and that the multivariate diffusion process adopted to model the evolution of fuel prices further improves both model fit and the ability to recover peaks in demand. The estimated coefficients have been applied to test different policy scenarios, including changes in fuel prices, vehicle purchase prices, and improvements of car characteristics. These policies have a high impact on the adoption of electric cars and on their diffusion in the marketplace.

Examining patient preferences in the treatment of rheumatoid arthritis using a discrete-choice approach.

BackgroundBiological disease-modifying antirheumatic drugs (bDMARDs) used in second-line treatment of rheumatoid arthritis (RA) are administered parenterally. However, so-called targeted synthetic DMARDs (tsDMARDs) – developed more recently – offer alternative (ie, oral) administration forms in second-line treatment. Since bDMARDs and tsDMARDs can be regarded as equal in terms of efficacy, the present study examines whether such characteristics as route of administration drive RA patients’ treatment choice. This may ultimately suggest superiority of some second-line DMARDs over equally effective options, at least according to RA-patient preferences.ObjectiveThe current study assessed the importance of oral administration among other treatment characteristics differing between available second-line DMARDs for RA patients’ preferences using a discrete-choice experiment (DCE).Materials and methodsThe DCE involved scenarios of three hypothetical treatment options in a d-efficient design with varying levels of key attributes (route and frequency of administration, time till onset of drug effect, combination therapy, possible side effects), as defined by focus groups. Further patient characteristics were recorded by an accompanying questionnaire. In the DCE, patients were asked to choose best and worst options (best–worst scaling). Results were analyzed by count analysis and adjusted regression analysis.ResultsA total of 1,588 subjects completed the DCE and were eligible for final analyses. Across all characteristics included in the DCE, “oral administration” was most desired and “intravenous infusion” was most strongly rejected. This was followed by “no combination with methotrexate” being strongly preferred and “intake every 1–2 weeks” being strongly rejected. On average, levels of route of administration showed strongest influences on patients’ decisions in post hoc bootstrapping analysis.ConclusionAccording to the results, an oral DMARD that does not have to be combined with methotrexate and is not administered (only) every 1–2 weeks appears a highly favorable treatment option for patients with RA. DMARDs meeting these preferences may increase compliance and adherence in RA treatment.

Itchy feet vs cool heads: Flow of funds in an agent-based financial market

Investors tend to move funds when they are unhappy with their current portfolio managers׳ performance. We study the effect of the size of this flow of funds in an agent-based model of the financial market. The model combines the discrete choice approach from agent-based modelling, where all capital is mobile, with the evolutionary finance framework where all growth is endogenous. Our results show that, if investors exhibit recency bias in evaluating portfolio managers׳ performance, even a small amount of freely flowing capital has a huge impact on the market dynamics and the survival of noise traders. We also find that investors׳ intensity of choice is a driving force for excess volatility and extreme price movements when the size of the flow of funds is large.

Attitudes in China about Crops and Foods Developed by Biotechnology.

Transgenic Bt cotton has been planted in China since 1997 and, in 2009, biosafety certificates for the commercial production of Bt rice and phytase corn were issued by the Chinese government. The public attitude in China toward agricultural biotechnology and genetically modified (GM) crops and foods has received considerable attention worldwide. We investigated the attitudes of consumers, Bt cotton farmers and scientists in China regarding GM crops and foods and the factors influencing their attitudes. Data were collected using interview surveys of consumer households, farmer households and scientists. A discrete choice approach was used to elicit the purchase intentions of the respondents. Two separate probit models were developed to examine the effect of various factors on the choices of the respondents. Bt cotton farmers had a very positive attitude because Bt cotton provided them with significant economic benefits. Chinese consumers from developed regions had a higher acceptance and willingness to pay for GM foods than consumers in other regions. The positive attitude toward GM foods by the scientific community will help to promote biotechnology in China in the future. Our survey emphasized that educational efforts made by government officials, the media and scientists can facilitate the acceptance of GM technology in China. Further educational efforts will be critical for influencing consumer attitudes and decisions of government agencies in the future. More effective educational efforts by government agencies and public media concerning the scientific facts and safety of GM foods would enhance the acceptance of GM crops in China.

Target Selection Models with Preference Variation Between Offenders

This study explores preference variation in location choice strategies of residential burglars. Applying a model of offender target selection that is grounded in assertions of the routine activity approach, rational choice perspective, crime pattern and social disorganization theories, it seeks to address the as yet untested assumption that crime location choice preferences are the same for all offenders. Analyzing detected residential burglaries from Brisbane, Australia, we apply a random effects variant of the discrete spatial choice model to estimate preference variation between offenders across six location choice characteristics. Furthermore, in attempting to understand the causes of this variation we estimate how offenders’ spatial target preferences might be affected by where they live and by their age. Findings of this analysis demonstrate that while in the aggregate the characteristics of location choice are consistent with the findings from previous studies, considerable preference variation is found between offenders. This research highlights that current understanding of choice outcomes is relatively poor and that existing applications of the discrete spatial choice approach may underestimate preference variation between offenders.

European Integration and Outward FDI from Central and Eastern Europe – Is There Any Evidence of Knowledge‐seeking?

AbstractThe European Union (EU) Member States in central and eastern Europe (CEE) witnessed a surge in outward foreign direct investment (OFDI) between 2000 and the start of the global financial crisis. This article investigates whether the European integration process altered the relative importance of host country location factors. In particular, we investigate to what extent knowledge‐seeking is a relevant investment motive, which has been documented as a key determinant for OFDI from other emerging economies. We apply a discrete choice approach to model foreign location choice of firms from CEE countries (CEECs) within the EU 27 (1996–2010). We find that the EU integration process is related with increasing importance of market access and less emphasis on labour cost advantages. We find heterogeneity in the valuation of foreign knowledge‐related assets. The location probability within the EU15 is positively associated with knowledge‐seeking. It also plays a role for technology‐intensive industries and larger firms.

A Comparison of Traditional and Discrete-Choice Approaches to the Analysis of Residential Mobility and Locational Attainment

This article contrasts traditional modeling approaches and discrete-choice models as methods to analyze locational attainment—how individual and household characteristics (such as race, socioeconomic status, age) influence the characteristics of neighborhoods of residence (such as racial composition and median income). Traditional models analyze attributes of a neighborhood as a function of the characteristics of the households within them; discrete-choice methods, on the other hand, are based on dyadic analysis of neighborhood attributes and household characteristics. I outline two problems with traditional approaches to residential mobility analysis that may be addressed through discrete-choice analysis. I also discuss disadvantages of the discrete-choice approach. Finally, I use data from the Panel Study of Income Dynamics to estimate residential mobility using traditional locational attainment and discrete-choice models; I show that these produce similar estimates but that the discrete-choice approach allows for estimates that examine how multiple place characteristics simultaneously guide migration. Substantively, these models reveal that the disproportionate migration of black households into lower-income tracts amounts to sorting of black households into black tracts, which on average are lower income.

Socio-economic status and enrollment in higher education: do costs matter?

We study the impact of socio-economic status on enrollment and study decisions in higher education. We use a discrete choice approach to distinguish between three channels. First, students from disadvantaged backgrounds may be more sensitive to the costs of education. Second, they may have lower preferences for education. Third, they may have developed less academic ability during previous schooling and are therefore less likely to participate. We apply our analysis to Flanders, where tuition fees are low and all high school graduates have access to higher education. We control for unobserved heterogeneity and find that preferences and (acquired) ability are more important than cost sensitivity in explaining the lower enrollment of disadvantaged students. Finally, we use the cost sensitivity channel to simulate the impact of tuition fee increases. We find that a uniform tuition fee increase has a fairly small impact on total enrollment, but it especially reduces enrollment of socially disadvantaged students. An alternative discriminatory policy, which combines a higher tuition fee increase for advantaged students with a lower tuition fee increase for disadvantaged students, can be superior: it generates the same budgetary savings, has a lower impact on total enrollment and reduces the participation gap of disadvantaged students.

Socio-Economic Status and Enrollment in Higher Education: Do Costs Matter?

We study the impact of socio-economic status on enrollment and study decisions in higher education. We use a discrete choice approach to distinguish between three channels. First, students from disadvantaged backgrounds may be more sensitive to the costs of education. Second, they may have lower preferences for education. Third, they may have developed less academic ability during previous schooling and are therefore less likely to participate. We apply our analysis to Flanders, where tuition fees are low and all high school graduates have access to higher education. We control for unobserved heterogeneity and find that preference and (acquired) ability are more important than cost sensitivity in explaining the lower enrollment of disadvantaged students. Finally, we use the cost sensitivity channel to simulate the impact of tuition fee increases. We find that a uniform tuition fee increase has a fairly small impact on total enrollment, but it especially reduces enrollment of socially disadvantaged students. An alternative discriminatory policy, which combines a tuition fee increase with an extra subsidy to disadvantaged students, can be superior: it reduces the participation gap of disadvantaged students without decreasing total enrollment in higher education.

Monetary policy rule in inflation targeting emerging European countries: A discrete choice approach

The paper explores all six emerging European countries that target inflation, showing that a discrete choice model captures well the behavior of their central banks, both their monetary policy rule and operational behavior. As to the latter, our findings suggest that these central banks change their policy rates in discrete fashion, i.e. only when the deviation between its (unobservable) optimal rate and actual rate surpasses certain threshold values. Estimates of Taylor rule contain relevant economic variables, including real exchange rate. However, evidence is offered that in Romania, Serbia and Albania the exchange rate is a goal for itself, while in the Czech Republic, Poland and Hungary it is an instrument to achieve inflation target, and this is related to different features of these two sets of economies. The use of the nonstationary discrete choice approach is well motivated as some explanatory variables are nonstationary.

Aggregate sentiment dynamics: A canonical modelling approach and its pleasant nonlinearities

The paper is an attempt at an alternative to the rational expectations assumption in macroeconomic modelling. Emphasizing the concept of sentiment in contrast to the expectations of a single selected variable, it is meant to take an important step forward towards a canonical heterodox framework for the microfounded modelling of irreducible uncertainty and, specifically, herding. Referring to a large population of agents who repeatedly face a binary decision problem, two stylized approaches are considered to describe the aggregate sentiment dynamics: the transition probability and the discrete choice approach. After a slight modification of the latter, the two specifications are shown to give rise to essentially the same adjustment equations. In addition to these conceptual issues, a two-dimensional prototype model is put forward which can illustrate the rich potential of an inherent nonlinearity to generate scenarios with single and multiple (point and set) attractors.

Burglar Target Selection: A Cross-national Comparison.

Objectives:This study builds on research undertaken by Bernasco and Nieuwbeerta and explores the generalizability of a theoretically derived offender target selection model in three cross-national study regions.Methods:Taking a discrete spatial choice approach, we estimate the impact of both environment- and offender-level factors on residential burglary placement in the Netherlands, the United Kingdom, and Australia. Combining cleared burglary data from all study regions in a single statistical model, we make statistical comparisons between environments.Results:In all three study regions, the likelihood an offender selects an area for burglary is positively influenced by proximity to their home, the proportion of easily accessible targets, and the total number of targets available. Furthermore, in two of the three study regions, juvenile offenders under the legal driving age are significantly more influenced by target proximity than adult offenders. Post hoc tests indicate the magnitudes of these impacts vary significantly between study regions.Conclusions:While burglary target selection strategies are consistent with opportunity-based explanations of offending, the impact of environmental context is significant. As such, the approach undertaken in combining observations from multiple study regions may aid criminology scholars in assessing the generalizability of observed findings across multiple environments.