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

Accessibility appraisal of integrated land-use-transport strategies: methodology and case study for the Netherlands Randstad area

Conventional approaches to measuring accessibility benefits are not capable of fully measuring the total accessibility benefits of integrated land-use-transport strategies, in which both land-use and transport changes form part of the policy strategy. In this paper a comprehensive methodology for analysing accessibility impacts and accessibility benefits, which is based on location-based and utility-based accessibility measures within an integrated land-use-transport interaction modelling framework, is described and applied in a case study. The case study examines the accessibility benefits and related user benefits of intensive mixed-use strategies aimed at increasing the density and diversity of activities around railway stations for the Randstad area of the Netherlands for the 1996-2030 period. A heavy concentration of activities near railway stations is shown to result in decreasing marginal returns for public-transport users and disbenefits for car users. © 2006 a Pion publication printed in Great Britain

Pattern Recognition Based Speed Forecasting Methodology for Urban Traffic Network

A full methodology of short-term traffic prediction is proposed for urban road traffic network via Artificial Neural Network (ANN). The goal of the forecasting is to provide speed estimation forward by 5, 15 and 30 min. Unlike similar research results in this field, the investigated method aims to predict traffic speed for signalized urban road links and not for highway or arterial roads. The methodology contains an efficient feature selection algorithm in order to determine the appropriate input parameters required for neural network training. As another contribution of the paper, a built-in incomplete data handling is provided as input data (originating from traffic sensors or Floating Car Data (FCD)) might be absent or biased in practice. Therefore, input data handling can assure a robust operation of speed forecasting also in case of missing data. The proposed algorithm is trained, tested and analysed in a test network built-up in a microscopic traffic simulator by using daily course of real-world traffic