Teresa Galvão Dias

Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis

This paper discusses different models that can be used to construct composite indicators with both desirable and undesirable output indicators. Two approaches are considered. The first is an indirect approach, based on a traditional Data Envelopment Analysis model, requiring a prior transformation in the measurement scale of the undesirable outputs. The second is a direct approach, based on a directional distance function model. The use of a directional distance function allows for the accommodation of undesirable indicators in their original form. The main limitations of these approaches are discussed related to the data transformation in the case of the indirect approach and the possibility to obtain negative margin rates of substitution between the desirable and undesirable outputs in the case of the direct approach. These issues lead to the proposal of a new composite indicator model based on a directional distance function that overcomes the limitations associated with the existing approaches. The incorporation of information on the relative importance of individual indicators using weight restrictions is discussed. Proposed here is an enhanced formulation of weight restrictions, in the form of assurance regions type I, that reflects the relative importance of the indicators in percentage terms. The models are illustrated in the assessment of Brazilian hydropower plants and are suitable for any assessment involving the aggregation of key performance indicators whenever undesirable outputs are present.

Genetic algorithms for the bus driver scheduling problem: a case study

This paper describes an application of genetic algorithms to the bus driver scheduling problem. The application of genetic algorithms extends the traditional approach of Set Covering/Set Partitioning formulations, allowing the simultaneous consideration of several complex criteria. The genetic algorithm is integrated in a DSS but can be used as a very interactive tool or a stand-alone application. It incorporates the users knowledge in a quite natural way and produces solutions that are almost directly implemented by the transport companies in their operational planning processes. Computational results with airline and bus crew scheduling problems from real world companies are presented and discussed.

Benchmarking Countries’ Environmental Performance

Environmental performance assessments are often conducted using environmental indicators. Although these indicators provide a starting point for performance assessments, they do not provide guidelines that countries should follow to improve performance. This paper develops an enhanced Data Envelopment Analysis (DEA) model that provides a single summary measure of countries’ environmental performance, based on the aggregation of the indicators that underlie the estimation of the Environmental Performance Index (EPI). The DEA model used is based on a novel specification of weight restrictions. The main contribution of the methodology used in this paper is to enable benchmarking in such a way that it becomes possible to identify the strengths and weaknesses of each country, as well as the peers with similar features to the country under assessment. These peers provide examples of good environmental practices that countries with worse performance should follow to improve performance.

Passenger Journey Destination Estimation From Automated Fare Collection System Data Using Spatial Validation

A methodology for estimating the destination of passenger journeys from automated fare collection (AFC) system data is described. It proposes new spatial validation features to increase the accuracy of destination inference results and to verify key assumptions present in previous origin-destination estimation literature. The methodology applies to entry-only system configurations combined with distance-based fare structures, and it aims to enhance raw AFC system data with the destination of individual journeys. This paper describes an algorithm developed to implement the methodology and the results from its application to bus service data from Porto. The data relate to an AFC system integrated with an automatic vehicle location system that records a transaction for each passenger boarding a bus, containing attributes regarding the route, the vehicle, and the travel card used, along with the time and the location where the journey began. Some of these are recorded for the purpose of allowing onboard ticket inspection but additionally enable innovative spatial validation features introduced by the methodology. The results led to the conclusion that the methodology is effective for estimating journey destinations at the disaggregate level and identifies false positives reliably.

The assessment of cities’ livability integrating human wellbeing and environmental impact

This study develops a tool to assess livability in European cities covering two components of livability: human wellbeing and environmental impact. First, we propose a conceptual model to assess cities’ livability, that extends the concept of urban livability to include a component related to environmental sustainability. Second, we address the measurement of cities’ livability. For this purpose, a new composite indicator was constructed based on a data envelopment analysis model specified using a directional distance function. In addition to assigning a summary measure of performance for each city, the composite indicator can be used to guide improvements concerning different livability objectives. One of the innovative features of the model proposed is to enable, by the specification of different directional vectors, focusing separately on each component of livability (e.g., human wellbeing and environmental impact) or alternatively considering cities’ potential for improvement in all indicators simultaneously. In addition, it is possible to incorporate a new type of weight restrictions, specified as assurance regions type I, that reflect the relative importance of both desirable and undesirable outputs in percentage terms. Finally, this paper approached the assessment of the evolution of cities’ performance over time using the Luenberger productivity indicator.

A new group-formation method for student projects

In BSc/MSc engineering programmes at Faculty of Engineering of the University of Porto (FEUP), the need to provide students with teamwork experiences close to a real world environment was identified as an important issue. A new group-formation method that aims to provide an enriching teamwork experience is proposed. Students are asked to answer a questionnaire to evaluate their teamwork profiles and are assigned to groups by an algorithm aiming to achieve maximum diversity within groups and homogeneity among groups. The profile diversity/complementarity within a group is an important factor to promote members’ commitment and coordination in order to achieve the proposed goals. The proposed method is compared to a standard self-selection method for three engineering programmes in three academic years. The results show that, with the new method, there are a higher number of medium ranked groups which surpass the expectation and that, contrary to some students’ beliefs, the method does not have a negative impact on the overall final marks.

Evaluating a DSS for operational planning in public transport systems: Ten years of experience with the GIST System

The GIST Decision Support System (DSS) has been specified and developed by a consortium of two University R & D groups and five public transport companies, aiming to support the operational planning processes of the latter. It has so far been implemented with unquestionable success in several companies, although it has been difficult to measure objectively the gains it directly introduced into their daily operations.

How to Encourage the Use of Public Transport? A Multiservice Approach Based on Mobile Technologies

It is crucial to promote the use of cleaner transport modes, and new technologies are key to achieve this goal. Most mobile-based solutions are focused on services related with the journey itself (mobile ticketing, real-time traffic information and trip planners). Adopting a holistic point of view, and considering every trip has a purpose (work, school, shopping and entertainment), a new service approach is considered. This paper presents a multiservice approach that links city services and public transport to encourage the use of sustainable transport modes. This multiservice approach is based on mobile technologies, which are a unique channel of interaction between service providers and customers. The conceptual model of this approach is materialized in a concrete example. This multiservice approach may represent a step towards a sustainable mobility, while improving the image and efficiency of Public Transport Operators (PTOs), boosting local businesses loyalty and sales and bringing convenience, better service quality and monetary savings to customers.

A Proposal for a Mobile Ticketing Solution for Metropolitan Area of Oporto Public Transport

The use of mobile phones to make payments is already a wide-spreading reality. While some mobile payment solutions achieved a considerable success and are already in use, others failed in the pilot phase. Nevertheless, there is an area where mobile payments have been quite successful: mobile ticketing in public transport. In fact, there are several advantages of mobile ticketing over traditional ticketing systems, such as queue avoidance, ubiquitous and remote access to payment, and the lack of need to carry coins and cash. This paper intends to propose a mobile payment system to be implemented in the Public Transport of Metropolitan Area of Oporto. After defining the payment ticketing model, a prototype was developed and tested by a sample of users. These tests allowed gathering some feedback about the feasibility of the system as well as useful insights about the concept, new in public transport in Portugal. The findings attained so far suggest that users considered the system extremely useful, since it is more convenient than traditional systems, improving the travelling process and experience. It was also clear that users valued the integration of additional and complementary services with mobile payments, such as real-time traffic information, maps and schedules. There are also several barriers to the adoption of such a system elicited by users, such as premium price, complex interfaces and perceived risks, such as security and privacy concerns.

Prediction of Journey Destination in Urban Public Transport

In the last decade, public transportation providers have focused on improving infrastructure efficiency as well as providing travellers with relevant information. Ubiquitous environments have enabled traveller information systems to collect detailed transport data and provide information. In this context, journey prediction becomes a pivotal component to anticipate and deliver relevant information to travellers. Thus, in this work, to achieve this goal, three steps were defined: (i) firstly, data from smart cards were collected from the public transport network in Porto, Portugal; (ii) secondly, four different traveller groups were defined, considering their travel patterns; (iii) finally, decision trees (J48), Naive Bayes (NB), and the Top-K algorithm (Top-K) were applied. The results show that the methods perform similarly overall, but are better suited for certain scenarios. Journey prediction varies according to several factors, including the level of past data, day of the week and mobility spatiotemporal patterns.