Change of Scale and Forecasting with the Control-Function Method in Logit Models

Endogeneity is a model misspecification that precludes the consistent estimation of the model parameters. The control-function method is the most suitable tool to address endogeneity for several discrete choice models that are relevant in transportation research. However, the estimators obtained with the control-function method are consistent only up to a scale. In this paper, we first depict the determinants of this change of scale by adapting an existing result for omitted orthogonal attributes in logit models. Then, we study the problem of forecasting under these circumstances. We show that a procedure proposed in previous literature may lead to significant biases, and we suggest novel alternatives to be used with synthetic populations. We use Monte Carlo experimentation and real data on residential location choice to illustrate these results. The paper finishes by summarizing the findings of this investigation and suggesting future lines of research in this area.MIT-Portugal Progra

Spatial accessibility and social inclusion: The impact of Portugal's last health reform

Health policies seek to promote access to health care and should provide appropriate geographical accessibility to each demographical functional group. The dispersal demand of health‐careservices and the provision for such services atfixed locations contribute to the growth of inequality intheir access. Therefore, the optimal distribution of health facilities over the space/area can lead toaccessibility improvements and to the mitigation of the social exclusion of the groups considered mostvulnerable. Requiring for such, the use of planning practices joined with accessibility measures. However,the capacities of Geographic Information Systems in determining and evaluating spatial accessibility inhealth system planning have not yet been fully exploited. This paper focuses on health‐care services planningbased on accessibility measures grounded on the network analysis. The case study hinges on mainlandPortugal. Different scenarios were developed to measure and compare impact on the population'saccessibility. It distinguishes itself from other studies of accessibility measures by integrating network data ina spatial accessibility measure: the enhanced two‐stepfloating catchment area. The convenient location forhealth‐care facilities can increase the accessibility standards of the population and consequently reducethe economic and social costs incurred. Recently, the Portuguese government implemented a reform thataimed to improve, namely, the access and equity in meeting with the most urgent patients. It envisaged,in terms of equity, the allocation of 89 emergency network points that ensured more than 90% of thepopulation be within 30 min from any one point in the network. Consequently, several emergency serviceswere closed, namely, in rural areas. This reform highlighted the need to improve the quality of the emergencycare, accessibility to each care facility, and equity in their access. Hence, accessibility measures becomean efficient decision‐making tool, despite its absence in effective practice planning. According to anapplication of this type of measure, it was possible to verify which levels of accessibility were decreased,including the most disadvantaged people, with a larger time of dislocation of 12 min between 2001 and 2011

Modelling long-distance route choice using mobile phone call detail record data: A case study of Senegal

The growing mobile phone penetration rates have led to the emergence of large-scale call detail records (CDRs) that could serve as a low-cost data source for travel behaviour modelling. However, to the best of our knowledge, there is no previous study evaluating the potential of CDR data in the context of route choice behaviour modelling. Being event-driven, the data are discontinuous and only able to yield partial trajectories, thus presenting serious challenges for route identification. This paper proposes techniques for inferring the users' chosen routes or subsets of their likely routes from partial CDR trajectories, as well as data fusion with external sources of information such as route costs, and then adapts the broad choice framework to the current modelling scenario. The model results show that CDR data can capture the expected travel behaviour and the derived values of travel time are found to be realistic for the study area

Choice-Based Demand Management and Vehicle Routing in E-Fulfillment

Attended home delivery services face the challenge of providing narrow delivery time slots to ensure customer satisfaction, while keeping the significant delivery costs under control. To that end, a firm can try to influence customers when they are booking their delivery time slot so as to steer them toward choosing slots that are expected to result in cost-effective schedules. We estimate a multinomial logit customer choice model from historic booking data and demonstrate that this can be calibrated well on a genuine e-grocer data set. We propose dynamic pricing policies based on this choice model to determine which and how much incentive (discount or charge) to offer for each time slot at the time a customer intends to make a booking. A crucial role in these dynamic pricing problems is played by the delivery cost, which is also estimated dynamically. We show in a simulation study based on real data that anticipating the likely future delivery cost of an additional order in a given location can lead to significantly increased profit as compared with current industry practice

Modelling Preferences for Smart Modes and Services: A Case Study in Lisbon

In this research, we investigate the acceptability of three new and emerging smart mobility options and quantify the associated willingness-to-pay values in the context of Lisbon using a comprehensive stated preferences (SP) survey. The smart mobility options include shared taxi, one-way car rental, and a novel combination of park-and-ride and school bus facilities. While previous surveys on smart mobility options had investigated limited number of alternatives in isolation, the SP survey used in this research presents the smart mobility options alongside the existing options and their traditional variants like congestion pricing and improved public transport systems. Further, the choice of mode, departure time and occupancy are investigated in a multidimensional framework. This resulted a large choice set (with 9 modes, 5 departure times, and 2 occupancy levels leading to 135 alternatives in total) and required a novel survey design. The main survey administered over the internet and computer aided personal interviews included 2372 valid SP observations from 1248 respondents. Multi-dimensional mixed logit models were used to capture the complex correlations introduced due to the non-traditional survey design. Results indicate a significant preference of one-way car rental and shared taxi for non-commute trips. For commute trips, improved versions of traditional public transport modes are favoured over smart mobility options. These findings, as well as the novel data collection and modelling approach, are expected to provide important information to transportation planners and policy makers working to implement smart mobility options in Lisbon as well as in other cities

SOCIAL DESIRABILITY AND CYNICISM: BRIDGING THE ATTITUDE-BEHAVIOR GAP IN CSR SURVEYS

Many consumer-focused corporate social responsibility (CSR) studies suggest a positive link between the responsibility demonstrated by a company and consumers’ intention to favor the company in their purchases. Yet an analogous causal effect between corporate social and financial performances is not evident. This chapter conceptualizes how social desirability and cynicism contribute to the discrepancy between consumers’ attitudes and their actual purchase behavior, and analyzes why consumer choices indicated in surveys do not consistently convert into actions