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Can digital technologies induce behavioral changes in transportation habits? Evidence based on User Experience with the SmartMoov Application
... La revue de littérature proposée par Blayac et al. (2020) complète ce premier éclairage sur les choix de transport et de mobilité. Les études de Brisbois (2010) et d' Innocenti et al. (2013) suggèrent là encore qu'il existe une inertie tenace et élevée concernant le maintien du choix du mode de transport. ...
Les nudges appliqués à la mobilité des individus alimentent un nombre croissant d’expérimentations de terrain. Le présent article présente le concept de nudge, puis propose un état de l’art de la bibliographie et une classification des principaux biais cognitifs sur lesquels les nudges s’appuient pour modifier une architecture de choix. La deuxième partie de l’article présente les conflits de rationalités et la négociation qui en résulte dans le fil de la conception d’un jeu de nudges dédié aux changements de comportements en termes de mobilité, jeu destiné à s’insérer dans une application de téléphone multifonctions.Au-delà des approches définitionnelles et de la production de nudges originaux, ce qui importe ici est de distinguer, en théorie et en pratique, les divers leviers à partir desquels une incitation peut se mettre en place, et comment les technologies de l’information et de la communication (TIC) peuvent être mobilisées pour tenter d’influer sur les comportements. Articulant les perspectives de l’économie comportementale, des sciences de l’information et de la communication et des sciences cognitives, la recherche s’inscrit dans une analyse technopolitique de fond.
Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter estimates and prediction accuracy. To this end, we estimate recursive models using data from an innovative data collection effort consisting of route choice observation data from GPS trackers, travel diaries and link travel times on the overall network. Though such combined data sets exist, these have not yet been used to investigate route choice behaviour. A dynamic network in which travel times change over time has been used for the estimation of both recursive logit and nested models. Prediction and estimation results are compared to those obtained for a static network. The interpretation of parameter estimates and prediction accuracy differ substantially between dynamic and static networks as well as between models with correlated and uncorrelated utilities. Contrary to the static results, for the dynamic, where travel times are modelled more accurately, travel information does not have a significant impact on route choice behaviour. However, having travel information increases the travel comfort, as interviews with participants have shown.
This study develops smartphone-app-based mobility management (MM) system using gamification. Our application has step counter and it introduces score and ranking function as gamification technique. A case study on university students reveals that we can increase the number of steps and change the behavior of some participants. Also, we examined the smartphone-app-based mobility management in the future.
This article develops the concept of ?smart velomobility? that is concerned with networked practices, systems and technologies of cycling. The concept draws on velomobility, Smart Mobility/Intelligent Transport Systems (ITS), Smart Cities and the Internet of Things (IoT). The article presents results from an empirical study, where 80 riders of a networked fleet of e-bikes discuss their experience of smart velomobility. The results show how digital and physical mobilities merge, the way riders of the networked fleet interact with the data, how they share the data and how they feel tracked (privacy). The conclusion sketches out future research of ?smart velomobilities? and also points out the policy and innovation potential of cycling as active, sustainable and networked mode of transport in the context of Smart Cities and the Internet of Things.
The increasing number of travelers in urban areas has led to new opportunities for local government and private mobility providers to offer new travel modes besides and in addition to traditional ones. Multimodal travel provides an especially promising opportunity. However, until now the underlying reasons why consumers choose specific alternatives have not been fully understood. Hence, the design of new travel modes is mainly driven by obvious criteria such as environmental friendliness, convenience etc. but might not consider consumers’ real or latent needs. To close this research gap, sixty in-depth interviews with urban travelers were conducted. To identify the perceptual differences of customers among different travel modes, the repertory grid technique as an innovative, structured interview method was applied. Our data show that urban travelers distinguish and select travel alternatives based on 28 perceptual determinants. While some determinants associated with private cars such as privacy, flexibility and autonomy are key indicators of travel mode choice, costs and time efficiency also play a major role. Furthermore, by comparing travel modes to an ideal category, we reveal that some perceptual determinants do not need to be maximized in order to fulfill customer needs optimally. A comparison of consumers’ perceptual assessments of alternative travel modes identifies specific advantages and disadvantages of all alternatives, and provides fruitful implications for government and private mobility providers.
Promoting the use of public transportation and Intelligent Transport Systems, as well as improving transit accessibility for all citizens, may help in decreasing traffic congestion and air pollution in urban areas. In general, poor information to customers is one of the main issues in public transportation services, which is an important reason for allocating substantial efforts to implement a powerful and easy to use and access information tool. This paper focuses on the design and development of a real time mobility information system for the management of unexpected events, delays and service disruptions concerning public transportation in the city of Milan. Exploiting the information on the status of urban mobility and on the location of citizens, commuters and tourists, the system is able to reschedule in real time their movements. The service proposed stems from the state of the art in the field of travel planners for public transportation, available for Milan. Peculiarly, we built a representation of the city transit based on a time-expanded graph that considers the interconnections among all the stops of the rides offered during the day. The structure distinguishes the physical stations and the get on/get off stops of each ride, representing them with two different types of nodes. Such structure allows, with regard to the main focus of the project, to model a wide range of service disruptions, much more meaningful than those possible with approaches currently proposed by transit agencies. One of the most interesting point lies in the expressive capability in describing the different disruptions: with our model it is possible, for instance, to selectively inhibit getting on and/or off at a particular station, avoid specific rides, and model temporary deviations.
The rise of smartphones and mobile applications (apps) is of major importance to multiple recent innovations in sustainable urban mobility, including car sharing schemes and real-time information provision in public transport, as well as the recent surge in urban cycling. Yet, exactly how apps feature in these innovations and trends remains largely unclear. This paper argues that this lack of understanding reflects not only the rapid pace of developments in apps and their technical functionalities but also gaps in academics’ conceptualization of the nature of apps and their effects. Too easily and often are apps seen as mere instruments for the realisation of human-centred goals and intentions, or are their capacities and effects assumed to emerge from the webs of relations in which apps and smartphones are enmeshed. An alternative conceptualisation is therefore proposed, one that is informed principally by the object-oriented approach developed by philosopher Graham Harman. After summarising some of Harman’s original concepts and developing his account of power, the paper elaborates a series of ideas and recommendations about how the developed conceptual framework can be deployed in empirical research on the interactions between apps and physical mobility in the city.
Innovation in information and communication technologies (ICTs) is providing us with a myriad of travel information sources. Knowledge on the influence of information on human travel behaviour (mainly route and mode choice) and their implications on network levels of service remains fragmented. We distinguish between experiential, descriptive, and prescriptive information sources. We draw on recently developed theoretical concepts in behavioural and cognitive sciences to examine the state of the knowledge on information and travel behaviour. Key theoretical concepts used to explore the relationship between information and travel behaviour include: reinforced learning; framing; risk and loss aversion; probability weighting; affect; anchoring and ambiguity aversion; and regret aversion. We review studies focusing on individual travel behaviour as well as network studies involving collective behaviours. While information seems to assist individual travellers in coping with uncertainty, the impacts relating to collective behaviour on networks remain unclear. Many open questions remain, yet research provides important insights and suggests that ICTs will enable the design of persuasive information systems that motivate cooperative and efficient use of the transportation network beyond what is possible today.
The smartphone penetrates many facets of everyday life, including travel. As such, this article argues that since travel can be considered a special stage of technology use, understanding how the smartphone shapes the tourist experience cannot be separated from the way it is used in one’s everyday life. On the basis of a study of American travelers, this study uses adaptive structuration theory as a lens to identify a number of spillover effects from smartphone use in everyday life into travel. The results of this study offer several important implications for both research and practice as well as future directions for the study of mobile technology in tourism.
In this introduction to the special issue on habitual travel choice, we provide a brief account of the role of habit in travel behaviour, discuss more generally what habitual choice is, and briefly review the issues addressed in the solicited papers. These issues include how habitual travel behaviour should be measured, how to model the learning process that makes travel choice habitual, and how to break and replace car-use habits.
Cette thèse envisage le problème du report modal sous l'angle des lacunes existant dans le modèle classique de compréhension des choix de mobilité. Trois grandes dimensions, propres au comportement individuel, sont étudiées au moyen de trois études sur les résidents de la région de Paris, en France. L'approche des explications naïves (étude 1), permet d'abord d'envisager les raisons des déterminants du choix modal pour 307 personnes aux pratiques modales diverses. Les résultats montrent qu'au point de vue des usagers, les choix modaux sont principalement fondés par les caractéristiques instrumentales des modes, la préférence individuelle pour le bénéfice temporel ne distingue cependant pas les usagers de la voiture des usagers des modes collectifs ferrés. L'importance relative des paramètres symboliques est envisagée par une manipulation de deux contextes hypothétiques auprès de 200 participants (étude 2). Les résultats montrent qu'un paramètre instrumental (le temps de trajet) et un paramètre symbolique (la mixité sociale) ont des impacts du même ordre sur les choix. La nécessité de considérer les dimensions cognitives de la décision est abordée au moyen d'une manipulation de l'attention portée par 438 individus à l'évaluation de leur liberté de choix (étude 3). Les résultats montrent que le sentiment de liberté de choix tend à être moins extrême en traitement central qu'en traitement périphérique. Cette thèse montre en outre, dans une visée critique, certains effets des variables sociodémographiques. Ces travaux soulignent dans l'ensemble la nécessité de prendre en compte les comportements individuels pour pouvoir espérer réaliser une promotion du report modal efficace.
The opening of the replacement for the I-35W Mississippi River Bridge bridge on September 18th, 2008 provides a unique opportunity to evaluate the impacts generated by this additional link on network performance, and thus empirically test whether a Braess Paradox occurred. Using detailed GPS data to estimate travel times on links and for origin-destination pairs, this research �nds that while on average travel time improved with the reopening of the bridge, the subsequent restoration of parts of the rest of the network to their pre-collapse con�guration worsened travel times signi�cantly on average. In all cases, the distribution of winners and losers indicates clear spatial patterns associated with these network changes. While no Braess paradox was found in this case, the research provides a method for measuring such phenomena.
The increase in connected devices in the internet of things (IoT) is leading to an exponential increase in the data that an organization is required to manage. To successfully utilize IoT in businesses, big data analytics are necessary in order to efficiently sort through the increased data. The combination of big data and IoT can thus enable new monitoring services and powerful processing of sensory data streams.
The Handbook of Research on Big Data and the IoT is a pivotal reference source that provides vital research on emerging trends and recent innovative applications of big data and IoT, challenges facing organizations and the implications of these technologies on society, and best practices for their implementation. While highlighting topics such as bootstrapping, data fusion, and graph mining, this publication is ideally designed for IT specialists, managers, policymakers, analysts, software engineers, academicians, and researchers.
Recently, it has become common practice for transit operators to provide real-time information (RTI) to passengers about the location or predicted arrival times of transit vehicles. Accompanying this is a growing body of literature that aims to assess the impacts of RTI on transit passenger behaviour and perceptions. The main objective of this research is to compile a literature review of studies that assess the passenger benefits of RTI provision. The results suggest that the primary behavioural changes associated with providing RTI to passengers pertain to decreased wait times, reductions in overall travel time due to changes in path choice, and increased use of transit. RTI may also be associated with increased satisfaction with transit service and increases in the perception of personal security when riding transit. A second objective of this review was to identify areas for future research based on remaining gaps in the literature; two keys areas that were identified are assessing actual behavioural changes of path choice of transit riders and conducting cost–benefit analyses post implementation of RTI systems. The results of this study have immediate implications for public transit operators considering implementation or expansion of RTI systems and researchers seeking topics for future investigation.
Control strategies have been widely used in the literature to counteract the effects of bus bunching in passenger's waiting times and its variability. These strategies have only been studied for the case of a single bus line in a corridor. However, in many real cases this assumption does not hold. Indeed, there are many transit corridors with multiple bus lines interacting, and this interaction affects the efficiency of the implemented control mechanism. This work develops an optimization model capable of executing a control scheme based on holding strategy for a corridor with multiple bus lines. We analyzed the benefits in the level of service of the public transport system when considering a central operator who wants to maximize the level of service for users of all the bus lines, versus scenarios where each bus line operates independently. A simulation was carried out considering two medium frequency bus lines that serve a set of stops and where these two bus lines coexist in a given subset of stops. In the simulation we compared the existence of a central operator, using the optimization model we developed, against the independent operation of each line. In the simulations the central operator showed a greater reduction in the overall waiting time of the passengers of 55% compared to a no control scenario. It also provided a balanced load of the buses along the corridor, and a lower variability of the bus headways in the subset of stops where the lines coexist, thus obtaining better reliability for all types of passengers present in the public transport system.
The objective of this study was the investigation of travel behavioral effects of the reduction in traffic capacity resulting from the construction of the West LRT (Light Rail Transit) line in the city of Calgary, Alberta, Canada. Travelers’ responses to real-time information providing traffic updates and advisory detours due to lane/road closures were also examined. The West LRT alignment extends approximately 8.2 km from downtown into the city’s southwest. Many road closures took place in the vicinity of the LRT line construction zones, inducing significant delays to traffic. Data on travelers’ behavioral responses and responses to real-time information were obtained by conducting a survey on a sample of users of the main road affected by the construction. The survey also investigated the effects of West LRT line construction on drivers’ daily commutes, including increases in travel times, mode choices, alternate route choices, and selection of sources of information on traffic conditions. A significant change in the selection of transportation mode was caused by West LRT construction. Throughout the construction period, there was a decrease in the percentage of respondents who reported private vehicles as their first choice and an increase in the percentage of respondents who preferred public transit as their first and second choices. Radio was found to be the most preferred source for traffic updates and detour advice, followed by variable message signs (VMS). The findings of the en-route information model showed that driving experience, employment status, travel time and purpose, and desire for pre-trip information had significant effects on traveler’s rerouting decisions after getting en-route information through VMS. The results from this study are of interest for understanding behavioral changes for the purposes of traffic management, mitigation schemes and design of advanced traveler information systems in response to network disruptions.
Most of the world’s cities have significant traffic problems involving peak hour congestion and pollution. Information supplied to potential users via the internet and phone systems can improve transport effectiveness in two major ways. The first is to inform travellers of integrated public transport options using real time accurate information. Travellers can then accurately choose their public transport route. Second, since most cars are occupied by a driver only, a market can be set up for potential drivers to meet potential passengers in an effective ridesharing scheme, in which authentication, micro-payments and effective coordination can be executed using real time hub and mobile phone technology. This paper outlines the form of these systems and presents a market research study which demonstrates that such services would be popular. Benefits of such services would accrue to many stakeholders: governments would avoid future capital expenditures on expensive road capacity, citizens would be able to travel faster due to reduced congestion, and the environment would suffer from less carbon and other forms of pollution due to reduced and faster flowing traffic volumes.
In the present study, we investigate the impact of real-time traffic information on traveller behaviour by using repeated day-to-day revealed-preference (RP) observations from a reward experiment. We estimate a trip scheduling model of morning peak behaviour that allows us to determine the impact of traffic information on travel behaviour. Specifically, we distinguish between the marginal impact of expected travel times versus that of deviations from this expectation upon user behaviour. We find that participants to the experiment who were given access to a smart-phone displaying real-time traffic information react to the daily variations in travel times stronger than they had done in the pre-trial period. This we interpret as evidence that provision of traffic information indeed affects behaviour. However, we also find that participants who were not given the smart-phone also respond to daily variations in travel times – suggesting that these drivers use other sources of information to help their trip planning, or were better capable of processing information available into travel time predictions.
A computer-aided survey was designed and conducted face-to-face with freeway drivers in Taiwan to gauge the demand for and reasonable pricing of customized real-time traffic information in the event of three different traffic conditions. Bivariate ordered probit models were estimated to investigate factors that significantly influence the demand for traffic information both for main freeways and secondary alternative routes. The results indicated that the demand for traffic information for non-recurring conditions was the strongest of the factors investigated. Basic information was the main type of information requested for normal and recurring conditions, whereas dynamic travel time prediction was the main type of information requested for non-recurring conditions. The estimation results from bivariate ordered probit models showed that by providing node-to-node information and encouraging a greater willingness to pay for information the demand for traffic information about main freeways and secondary alternative routes will increase. Finally, the significant and positive correlations of models imply that the greater the demand for traffic information about main freeways, the greater the demand for information about secondary alternative routes.
We conduct a laboratory experiment to investigate the factors determining travel mode choice. Two different scenarios are considered. In the first scenario, subjects have to decide whether to commute by car or by metro. Metro costs are fixed, while car costs are uncertain and determined by the joint effect of casual events and traffic congestion. In the second scenario, subjects have to decide whether to travel by car or by bus, whose costs are determined by a different combination of chance and traffic congestion. Subjects receive feedback information on the actual travel times of both modes. We find that individuals show a marked preference for cars, are inclined to confirm their first choice and exhibit travel mode stickiness. We conclude that travel mode choice is subject to cognitive heuristics and biases leading to robust deviations from rational behaviour.
Information and communications technologies (ICTs) are permeating modern lifestyles, shaping and colouring the undertaking of activities and travel. This article reports on a qualitative diary and interview study that explored the ways in which ICTs are being used by students aged 18–28 and part-time working mums. Study participants were selected on the basis of being ‘informal experts’ – reflecting their affinity for engagement with ICTs. Through an exploration of the interview findings, it becomes clear that relatively new technological devices and applications have quickly become embedded into the participants’ everyday travel and communications. Changes in social practice at the level of the individuals are not visibly dramatic, but at the same time, there is evidence of a cumulative influence of ICTs on their daily lives. Technologies are enabling the participants to better accommodate the uncertainties in activity and travel scheduling and yet also contributing to a ‘fluidity’ in time–space co-ordination of activities. They are also allowing the juggling of life roles in time and space leading to apparent fragmenting of activities. The article reflects upon the travel behaviour consequences of ICTs in their influence on everyday life.
The question of the relationship between the spread of communication tools and the physical mobility of individuals is not new and arose with the arrival of the fixed telephone and, more recently, the development of the Internet and especially e-commerce. The extraordinary spread of individual, especially portable, communication tools like the mobile phone, has recently generated new interest in this topic in the fields of transportation economics, geography and sociology. This article discusses the main topics that have been explored, from the debate between complementarity and substitution to analyses in terms of interactions with the spatiotemporal organization of daily activities, the size and maintenance of social networks, and, finally, perception of travel and spaces. We then identify several issues that we think merit further exploration.
This quantitative study provides more insight into the relative strength of various factors affecting the use and non-use of pre-trip Public Transport (PT) information for business and leisure trips. It also illuminates comparing car with public transport and its consequences for mode choice. The factors affecting PT information use most strongly are travel behaviour and sociodemographics, but travel attitudes, information factors, and social surrounding also play a role. Public transport use and PT information use are closely connected, with travel behaviour having a stronger impact on information use than vice versa. Information service providers are recommended to market PT information simultaneously with public transport use.
When considering mode choice criterion, departing air passengers allow a period of time, additional to the time allowance predicted for their ground access to airports. This additional time is commonly known as a “safety margin”. The safety margin allowance increases the possibility of arriving at the airport no later than passengers' preferred arrival times. This study is the first to assess the magnitude of safety margin allowed for airport ground access trips. With the use of revealed preference survey data, the effects of safety margin allowances on ground access mode choices to Hong Kong International Airport (HKIA) are quantified by a multinomial logit-type mode choice model. The model results indicated that, when compared to non-business air passengers, business air passengers place a significantly higher value on both travel time and safety margin for their ground access to HKIA. The findings of this study provide valuable information to various transport operators for their design and improvement on airport related traffic.
The standard method to estimate valuations of travel time variability for use in appraisal is to estimate the parameters of a reduced-form utility function, where some measure of travel time variability (such as the standard deviation) is included. A recently discovered problem with this approach is that the obtained valuation will in general depend on the standardized travel time distribution, and hence cannot be transferred from one context to another. Instead, we test another recently suggested approach: estimating a scheduling model and then deriving an implied reduced-form expression, which can be used for appraisal. The valuations implied by the scheduling model turn out to deviate substantially from a reduced-form model estimated on the same sample. We conclude that the scheduling model – in the way it is usually interpreted and estimated – is not able to capture the entire disutility of travel time variability. Hence, although it can be shown that scheduling and reduced-form models are "theoretically equivalent", they are apparently not "empirically equivalent". We hypothesize that the derivation of reduced-form models from an underlying scheduling model omits two essential features: first, the notion of an exogenously fixed "preferred arrival time" neglects the fact that most activities can be rescheduled given full information about the travel times in advance, and second, disutility may be derived from uncertainty as such, in the form of anxiety, decisions costs or costs for having contingency plans. Finally, we report our best estimates of the valuation of travel time variability for public transit trips, for use in applied appraisal.
In order to attract more choice riders, transit service must not only have a high level of service in terms of frequency and travel time but also must be reliable. Although transit agencies continuously work to improve on-time performance, such efforts often come at a substantial cost. One inexpensive way to combat the perception of unreliability from the user perspective is real-time transit information. The OneBusAway transit traveler information system provides real-time next bus countdown information for riders of King County Metro via website, telephone, text-messaging, and smart phone applications. Although previous studies have looked at traveler response to real-time information, few have addressed real-time information via devices other than public display signs. For this study, researchers observed riders arriving at Seattle-area bus stops to measure their wait time while asking a series of questions, including how long they perceived that they had waited.
Even where unreliability has been recognised as a significant component in the generalised cost of trip-making, few attempts have been made to quantify it in the evaluation of transport improvements. This neglect is perhaps explained by the difficulty of observing a suitable “trade-off” situation in which transport users can trade money directly or indirectly for improved reliability of their transport modes.
This article investigates the characteristics of a possible trade-off which might be made by commuters — the allowance of extra time for travelling in order to avoid unpredictable lateness at destination. The form of the costs of a response to unreliability of this nature is considered within a more general framework of the allocation of time under uncertainty or risk conditions.
Certain other approaches to the evaluation of travel unreliability are reviewed and a brief outline is given to a current research project which attempts to test the applicability of the “safety margin” in London commuters' timing of the trips that they take to work.
The purpose of this article is to question the presumption that route guidance and information systems necessarily reduce traffic congestion, and to point out the need to consider the general equilibrium effects of information. A simple model of the morning rush hour is adopted in which commuters choose a departure time and one of two routes to work, the capacities of which are stochastic. While expected travel costs are reduced by perfectly informing all drivers about route capacities, this is not necessarily the case if imperfect information is provided. A heuristic explanation is that, absent tolls, congestion is an uninternalized externality. Information can cause drivers to change their departure times in such a way as to exacerbate congestion.
A negative effect of congestion that tends to be overlooked is travel time uncertainty. Travel time uncertainty causes scheduling costs due to early or late arrival. The negative effects of travel time uncertainty can be reduced by providing travellers with travel time information, which improves their estimate of the expected travel time, thereby reducing scheduling costs. In order to assess the negative effects of uncertainty and the benefits of travel time information, this paper proposes a conceptual model of departure time choice under travel time uncertainty and information. The model is based on expected utility theory, and includes the variation in travel time, the quality of travel time information and travellers’ perception of the travel time. The model is illustrated by an application to the case of the A2 motorway between Beesd and Utrecht in the Netherlands.
In this paper we analyse the impact of both radio traffic information and variable message sign information on route choice behaviour. The empirical analysis is based on an extensive survey held among road users in the Amsterdam corridor in July 1994. The data is stemming from the EC DRIVE II project BATT. To analyse the factors that influence route choice behaviour, several types of discrete choice models (ordered probit, multiple logit and bivariate ordered probit) have been estimated. Bivariate models are needed to model the (endogenous) dependency of the use of radio traffic information and variable message sign information. The results confirm earlier findings that women are less likely to be influenced by traffic information. New is the finding that commuters are less likely to be influenced, and that the level of satisfaction with alternative routes is strongly related to the type and distance of the alternative road. The analysis also reveals that the impacts of radio traffic information and variable message sign information on route choice behaviour are very similar, and that route choice adaptations based on radio traffic information are positively related to route choice adaptations based on variable message sign information. An interesting issue is the willingness-to-pay for having in-vehicle dynamic traffic information. As expected, the willingness-to-pay is relatively large for male drivers on business trips. Another important new finding is that the results suggest that there is a positive correlation between the use of radio traffic information and variable message sign information.
This paper analyzes the results of a commuter behavior survey conducted in Austin, TX. Commuters' preferred arrival times at the workplace, use of traffic information and switching propensity (for both route and departure time) are discussed. Mathematical models are developed for each of these aspects relating them to three types of factors: traffic system characteristics, workplace conditions and individual attributes. The preferred arrival time at the workplace is modeled as a Poisson regression model, use of information as a binary logit function and switching decision as multinomial logit choice models. Comparisons are drawn between this sample and similar studies conducted in Seattle, WA.
We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows different weighting functions for gains and for losses. Two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting functions. A review of the experimental evidence and the results of a new experiment confirm a distinctive fourfold pattern of risk: risk aversion for gains and risk seeking for losses of high probability; risk seeking for gains and risk aversion for losses of low probability. Copyright 1992 by Kluwer Academic Publishers
The theory of precautionary saving is shown to be isomorphic to the Arrow-Pratt theory of risk aversion, making possible the application of a large body of knowledge about risk aversion to precautionary saving--and more generally, to the theory of optimal choice under risk. In particular, a measure of the strength of the precautionary saving motive analogous to the Arrow-Pratt measure of risk aversion is used to establish a number of new propositions about precautionary saving and to give a new interpretation of the Dreze-Modigliani substitution effect. Copyright 1990 by The Econometric Society.
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Guiding cities to pursue a smart mobility paradigm: An example from vehicle routing guidance and its traffic and operational effects
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« Le numérique au service de la mobilité urbaine durable
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Gender and Generation effects on Perception of value of Travel Time and Mode Choice
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