Showing papers in "ERIM report series research in management Erasmus Research Institute of Management in 2019"

Railway timetabling with integrated passenger distribution

Abstract: textTimetabling for railway services often aims at optimizing travel times for passengers. At the same time, restricting assumptions on passenger behavior and passenger modeling are made. While research has shown that passenger distribution on routes can be modeled with a discrete choice model, this has not been considered in timetabling yet. We investigate how a passenger distribution can be integrated into an optimization framework for timetabling and present two mixed-integer linear programs for this problem. Both approaches design timetables and simultaneously find a corresponding passenger distribution on available routes. One model uses a linear distribution model to estimate passenger route choices, the other model uses an integrated simulation framework to approximate a passenger distribution according to the logit model, a commonly used route choice model. We compare both new approaches with three state-of-the-art timetabling methods and a heuristic approach on a set of artificial instances and a partial network of Netherlands Railways (NS).

A good or a bad timetable: Do different evaluation functions agree?

Abstract: text We compare different evaluation functions that are all designed to mea- sure the quality of a timetable from passengers’ perspective. Already in small examples fundamentally different timetables can be preferred by evaluation functions that seem to be similar. To investigate this effect in practice, we design a set of evaluation functions as representatives for a wide range of commonly used evaluation functions in optimization models, evaluation applications, or choice models. These functions are compared by analyzing their evaluation values of multiple timetables in three case studies. To investigate to what extent these evaluation functions agree on a good or a bad timetable, we apply cluster analysis as well as a novel methodology to quantify the similarity of pairs of evaluation functions based on the values they yield on different timetables. We empirically show that the choice of the evaluation function can have a significant impact on the assessed quality of timetables, and thus also on which timetable is considered optimal, even though all evaluation functions are meant to evaluate the same - the quality of a timetable from passengers’ perspective. Due to the structure of the designed evaluation functions, it is further possible to identify which components of the func- tions influence the results of an evaluation and under which conditions they this is most pronounced. This can be very beneficial when designing timetable evaluation functions for passengers.

Economic Cross-Efficiency

Abstract: This paper is concerned with introducing a series of new concepts under the name of Economic Cross-Efficiency, which is rendered operational through Data Envelopment Analysis (DEA) techniques. To achieve this goal, from a theoretical perspective, we connect two key topics in the efficiency literature that have been unrelated until now: economic efficiency and cross-efficiency. In particular, it is shown that, under input (output) homotheticity, the traditional bilateral notion of input (output) cross-efficiency for unit l, when the weights of an alternative counterpart k are used in the evaluation, coincides with the well-known Farrell notion of cost (revenue) efficiency for evaluated unit l when the weights of k are used as market prices. This motivates the introduction of the concept of Farrell Cross-Efficiency (FCE) based upon Farrell’s notion of cost efficiency. One advantage of the FCE is that it is well defined under Variable Returns to Scale (VRS), yielding scores between zero and one in a natural way, and thereby improving upon its standard cross-efficiency counterpart. To complete the analysis we extend the FCE to the notion of Nerlovian cross-inefficiency (NCI), based on the dual relationship between profit inefficiency and the directional distance function. Finally, we illustrate the new models with a recently compiled dataset of European warehouses.

Simultaneous customer interaction in online booking systems for attended home delivery

Abstract: text In many delivery and service settings, the customer must be home when the provider arrives. If the customer is not at home, the delivery or service fails and the provider may have to return at a later point, needlessly creating additional vehicle miles and emission. To prevent such missed deliveries, it is increasingly common for providers to let customers choose from a menu of narrow time slots in which the delivery or service will take place. An important decision problem in this setting is which time slots to offer to maximize the expected number of placed orders while guaranteeing a feasible delivery schedule. In this paper, we particularly identify the occurrence of multiple customers simultaneously interact with a booking system. Indeed, customers might arrive while the system is still processing a previous customer, and customers might arrive while another customer is still deciding on his or her preferred time slot. Such simultaneous interactions lead to additional waiting time and invalid service offers, as we demonstrate in this paper. We argue that state-of- the-art procedures are not yet equipped to deal with this and present new approaches for this purpose. We illustrate their performance using real-time experiments with thousands of customers arriving over a small period of time. Our findings provide insights that may help to improve the design of current online booking systems, and opens up new areas of research.

Choice Architecture for Healthier Insurance Choices: Ordering and Partitioning Can Improve Decisions

Abstract: textHealth insurance decisions are a challenge for many consumers and influence welfare, health outcomes, and longevity. Two choice architecture tools are examined that can improve these decisions: informed ordering of options (from best to worst) and choice set partitioning. It is hypothesized that these tools can improve choices by changing: (1) decision focus: the options in a set on which consumers focus their attention, and (2) decision strategy: how consumers integrate the different attributes that make up the options. The first experiment focuses on the mediating role of the hypothesized decision processes on consumer decision outcomes. The outcome results are validated further in a field study of over 40,000 consumers making actual health insurance choices and in two additional experiments. The results show that informed ordering and partitioning can reduce consumers’ mistakes by hundreds of dollars per year. They suggest that wise choice architecture interventions depend upon two factors: The quality of the user model possessed by the firm to predict consumers’ best choice and possible interactions among the ensemble of choice architecture tools.

The Decompositions of Cost Variation

Abstract: In this paper a number of meaningful and empirically implementable decom- positions of the cost variation (in difference and ratio form) are developed. The components distinguished are price level change, technical efficiency change, allocative efficiency change, technological change, scale of activity change, and price structure change. Given data from a (balanced) panel of produc- tion units, all the necessary ingredients for the computation of the various decompositions can be obtained by using linear programming techniques. An application is provided.