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Publications

Publications by CESE

2021

Forecasting of Urban Public Transport Demand Based on Weather Conditions

Authors
Correia, R; Fontes, T; Borges, JL;

Publication
Advances in Intelligent Systems and Computing

Abstract
Weather conditions have a major impact on citizens’ daily mobility. Depending on weather conditions trips may be delayed, demand may be changed as well as the modal shift. These variations have a major impact on the use and operation of public transport, particularly in transport systems that operate close to capacity. However, the influence of weather conditions on transport demand is difficult to predict and quantify. For this purpose, an artificial neural network model – the Multilayer Perceptron – is used as a regression model to estimate the demand of urban public transport buses based on weather conditions. Transit bus ridership and weather conditions were collected along a year from a medium-size European metropolitan area (Oporto, Portugal) and linked under the assumption that individuals choose the travel mode based on the weather conditions that are observed during the departure hour, the hour before and two hours before. The transit ridership data were also labelled according to the hour, day of the week, month, and whether there was a strike and/or holiday or not. The results demonstrate that it is possible to predict the demand of public transport buses using the weather conditions observed two hours before with low error for the entire network (MAE = 143 and RMSE = 322). The use of weather conditions allow to decreases the error of the prediction by ~8% for the entire network. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

2021

Improving Order-picking Operations with Precedence Constraints through Efficient Storage Location Assignment

Authors
Trindade, MAM; Sousa, PSA; Moreira, MRA;

Publication
U.Porto Journal of Engineering

Abstract
This paper is inspired by a manual picking retail company where shape and weight constraints affect the order-picking process. We proposed an alternative clustering similarity index that considers the similarity, the weight and the shape of products. This similarity index was further incorporated in a storage allocation heuristic procedure to set the location of the products. We test the procedure in a retail company that supplies over 191 stores, in Northern Portugal. When comparing the strategy currently used in the company with this procedure, we found out that our approach enabled a reduction of up to 40% on the picking distance; a percentage of improvement that is 32% higher than the one achieved by applying the Jaccard index, a similarity index commonly used in the literature. This allows warehouses to save time and work faster.

2021

Mapping Enabling Technologies for Supply Chains with Future Scenarios

Authors
Senna, PP; Stute, M; Balech, S; Zangiacomi, A;

Publication
Lecture Notes in Management and Industrial Engineering - Next Generation Supply Chains

Abstract
AbstractDriven by the current digital transformation, European companies rely on accurate forecasting of future trends and prediction of most useful technologies in order to maintain their competitive edge. For this purpose, the mapping of enabling technologies to future scenarios becomes a valuable tool for practitioners and researchers alike, especially when considering the disruptive events that surround SCs design, implementation and management. This research sets forth to fill this gap by presenting a technology mapping of enabling technologies based on technology portfolio approach, expert elicitation and literature. The final outcome is the mapping of the enabling technologies to the characteristics of the future European SC scenarios.

2021

Urban travel behavior adaptation of temporary transnational residents

Authors
Monteiro, MM; Silva, JDE; Haustein, S; de Sousa, JP;

Publication
JOURNAL OF TRANSPORT GEOGRAPHY

Abstract
Temporary transnational relocation is a growing type of migration. However, travel behavior adaptation of highly skilled temporary residents and its urban impacts have largely been ignored. This study extends the knowledge of mobility biographies, mobility cultures, and mobility of millennials by examining how temporary residents adapt their intra-urban travel behavior in response to a transnational relocation. The data used here comes from semi-structured interviews with students and researchers of nine different nationalities, aged between 19 and 31 years, temporarily living in Portugal (Lisbon or Porto). We found supporting evidence for the occurrence of residential self-selection, although prior information on study/workplace combined with low knowledge on neighborhood-level make it somewhat specific. Given their shortterm perspective, temporary residents are more prone to rely on public transport and non-motorized modes, having a low likelihood of purchasing vehicles. Thus, measures aimed at improving and facilitating the use of active modes can have an immediate effect on this group's travel behavior and contribute to reaching critical mass for these sustainable alternatives. Temporary residents are also a potentially interesting market segment for public transportation operators for increases in revenues, as they tend to display a relatively higher travel intensity and a wider diversity of activities and destinations. Finally, technology usage was found to reduce the stress-related to traveling to unfamiliar places by increasing the perceived spatial orientation, having the downside of generating a feeling of confidence that decreases the internalization of information. Providing timely and persuasive information at the very beginning of temporary residents' stay can help induce their travel behavior decisions.

2021

The impact of supply chain fit on business and innovation performance in Brazilian companies

Authors
Zimmermann, R; Ferreira, LMDF; Moreira, AC; Barros, AC; Correa, HL;

Publication
International Journal of Logistics Management

Abstract
Purpose: This paper investigates the effect of the fit between supply and demand uncertainty (SDU) and supply chain responsiveness (SCR) (SC fit) on business and innovation performance in Brazilian companies. Design/methodology/approach: The study presented an analysis carried out on an empirical study based on a sample of 150 manufacturing companies. Business and innovation performance of companies with different types of SC fit (high–high and low–low fits) and misfit (positive and negative) are compared and discussed. Findings: The results indicated that SC fit had a positive effect on both business and innovation performance. Further analyses suggested that companies with SC fit present similar business performance, independent of the level of SDU that characterizes the environment where they compete, while companies in environments with higher levels of uncertainty tend to present superior innovation performance. Companies with positive and negative misfit present similar performance. Originality/value: An analysis of the literature showed that there is no consensus when it comes to the definitions and measurements of SC fit. The paper investigates the effects of SC fit on business and innovation performance, while previous empirical studies have mainly addressed its impact on financial performance. Moreover, this study compares the effects of two types of fit and two types of misfit and assesses SC fit in Brazilian manufacturing companies, analyzing the context of an under-researched reality. © 2020, Emerald Publishing Limited.

2021

Impact of Governmental Support for the Implementation of Industry 4.0 in Portugal

Authors
Faria, BS; Simões, AC; Rodrigues, JC;

Publication
Innovations in Industrial Engineering - Lecture Notes in Mechanical Engineering

Abstract

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