Abstract
This paper analyses how the harmonization between supply and demand uncertainty and supply chain responsiveness (SC fit) impacts business performance. The study analyses data obtained from a sample of 179 manufacturing companies from Portugal. The business performance of companies with different types of SC fit (high-high fit and low-low fit) and misfit (positive and negative) were analyzed and discussed. The results indicate that SC fit is positively related to business performance, economic and productivity, and commercial performance separately. This study advances the literature as the results indicate that SC fit positively affects both commercial and economic, and productivity performance. In contrast, previous empirical studies have mainly addressed the impact only on financial and operational performance. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Subgroup discovery (SD) aims at finding significant subgroups of a given population of individuals characterized by statistically unusual properties of interest. SD on event logs provides insight into particular behaviors of processes, which may be a valuable complement to the traditional process analysis techniques, especially for low -structured processes. This paper proposes a scalable and efficient method to search significant SD rules on frequent sequences of events, exploiting their multidimensional nature. With this method, it is intended to identify significant subsequences of events where the distribution of values of some target aspect is significantly different than the same distribution for the entire event log. A publicly available real -life event log of a Dutch hospital is used as a running example to demonstrate the applicability of our method. The proposed approach was applied on a real -life case study based on the public transport of a medium size European city (Porto, Portugal), for which the event data consists of 133 million smartcard travel validations from buses, trams and trains. The results include a characterization of mobility flows over multiple aspects, as well as the identification of unexpected behaviors in the flow of commuters (public transport). The generated knowledge provided a useful insight into the behavior of travelers, which can be applied at operational, tactical and strategic business levels, enhancing the current view of the transport services to transport authorities and operators.

Abstract
This work was developed to improve the costing process of new products within the Product Development Department of a furniture manufacturer. It consisted of creating a parametric cost estimation model based on applying simple and multiple linear regressions, considering the existing data of the products produced and their respective costs. The proposed model considers the cost estimation of creating a product that covers the materials and operations costs. The suitability of the different independent variables was studied by applying simple and multiple linear regressions. A set of functions that return an estimate of the cost as a function of these predictor variables was obtained. The model built with the functions obtained provides the materials and operations cost estimation. The results indicated that 75% of the tests performed show an estimation error of less than 2% in the total cost of a product. Incorporating this model in a tool with the purpose of cost estimation brings the ability to predict prices faster, improving the internal process of obtaining costing and enhancing the analytical capacity of the team in the relentless pursuit of cost minimization and value creation. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Sectorization consists of grouping the basic units of a large territory to deal with a complex problem involving different criteria. Resectorization rearranges a current sectorization avoiding substantial changes, given a set of conditions. The paper considers the case of the distribution of geographic areas of fire brigades in the north of Portugal so that they can protect and rescue the population surrounding the fire stations. Starting from a current sectorization, assuming the geographic and population characteristics of the areas and the fire brigades’ response capacity, we provide an optimized resectorization considering two objectives: to reduce the rescue time by maximizing the compactness criterion, and to avoid overload situations by maximizing the equilibrium criterion. The solution method is based on the Non-dominated Sorting Genetic Algorithm (NSGA-II). Finally, computational results are presented and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract

Abstract
Sectorization is the division of a large area, territory or network into smaller parts considering one or more objectives. Dynamic sectorization deals with situations where it is convenient to discretize the time horizon in a certain number of periods. The decisions will not be isolated, and they will consider the past. The application areas are diverse and increasing due to uncertain times. This work proposes a conceptualization of dynamic sectorization and applies it to a distribution problem with variable demand. Furthermore, Genetic Algorithm is used to obtain solutions for the problem since it has several criteria; Analytical Hierarchy Process is used for the weighting procedure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.