Abstract
Nowadays, fraudsters are continually trying to explore technical gaps in telecom companies to get some profit. The high cost of international termination rates in Telecom Companies, and mainly because of their high asymmetry property, attracts the attention of fraudsters. In this paper, we explore the application of three deterministic algorithms and one probabilistic, that combined can help to identify possible abnormal behaviors. Interconnect Bypass Fraud (IBF) is on the top three (worldwide), most common frauds in the telecommunication domain. Typically, the Telecom Companies can detect IBF by the occurrence of bursts of calls, repetitions, and mirror behaviors from specific numbers. The goal of our work is to discover as soon as possible numbers with abnormal behaviors and based on this assumption we developed: ( i ) the lossy count algorithm with fast forgetting technique; and ( ii ) the single-pass hierarchical heavy hitter algorithm that also contains a forgetting technique; as well as the application of the HyperLogLog sketches, and the application of sticky sampling algorithm. We applied the four algorithms in two real datasets and did a parameter sensitivity analysis. The results show that our two proposals (Lossy Counting with fast forgetting and the Hierarchical Heavy Hitters) can capture the most recent abnormal behaviors, faster than the baseline algorithms. Nonetheless, these four algorithms combined can make the fraud task more difficult and can complement the techniques used by the Telecom Company.

Abstract
Recent studies have shown that the coverage of Scopus and Web of Science (WoS) databases differs substantially. Consequently, the citation counts of a paper are different depending on the database used, making it difficult to apply both together. To address this problem, this paper aims to examine whether the percentile- and stochastic-based approach is effective for converting citation counts between two databases while guaranteeing its time-normalization. For this analysis, we collected a dataset of 326,345 papers, published in 1987-2017 in the top 10% source titles of the following fields: Industrial and Manufacturing Engineering, Aquatic Science, Social Psychology and Archaeology. First, we applied the linear regression model to the citation percentiles of indexed papers in both databases. Secondly, we used the predicted results of this linear dependence, combined with the Monte Carlo simulations, to obtain the probability density function of a percentile from papers in the database in which they are missing. The results indicate that, with the method proposed in this paper, it is possible to convert the citation counts of articles between Scopus and WoS. In addition, it also predicts the citation impact of a missing paper on one of those databases, based on the citation impact on the other database. Tests on subsamples, using Lin's concordance coefficient, suggest substantial agreement between estimated and real citation values. This allows the combined use of the citation counts of two databases, improving the coverage and accuracy of both bibliometric studies and bibliometric indicators.

Abstract
The automotive industry faces major megatrends such as climate change and emissions control, digital transformation, and increased customer power, resulting in more intensive competition, and higher sophisticated vehicles. The application of QFD (Quality Function Deployment) can be particularly valuable to link customer expectations with the technical characteristics of the product. In the case of products, such as batteries for electric vehicles, where technology is not yet mature, and the technical requirements (e.g., autonomy) are continuously more demanding, this is particularly relevant. The QFD customer-oriented product development technique is applied to a cover of a battery pack, to improve the negotiation process with the car manufacturer, the automotive industry battery components supplier company and its suppliers, to ensure market success once the product is released. The application of the HoQ revealed that Product Design and Tolerancing are the main technical requirements with the most impact over the battery cover development, followed the Leakage ratio. This research confirms that the voice of the customer could be quite generic, and it is critical that these requirements are translated into engineering requirements, which, in turn, can be translated into items that can be measured quantitatively and actionable within the company. The application of the affinity diagram was found to be quite valuable to address the significant amount of subjective information, and it is also relevant that OEMs have a desire to standardize the electric vehicle platforms at least on fewer and general sizes, hinting the need for more collaborative team approaches. © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the FAIM 2021.

Abstract
The popularity of electric and hybrid cars has been growing worldwide, and Portugal is no exception. Companies have been offered incentives as a way to promote the transition to more sustainable transportation systems and supply chains. Celebrities and influencers are endorsing the new technology, and consumer preferences are changing. However, in Portugal, there are still consumers with misconceptions about the autonomy, cost and reliability of electric cars, which may favour the choice of a conventional car, in a new car purchase decision-making process. In this study, we analyse whether purchase intention in the near future of an electric car varies with a pro-environmental lifestyle, perceived symbolic value of the electric car, mobility patterns, age, and place of residence, (perfor-mance, social, financial and externalities) risk avoidance, consumer perceptions, knowledge about the cost, the autonomy and the existing infrastructures. A sample of 308 Portuguese consumers was collected with an online survey. Results from survey subsample analysis of 170 consumers who unequivocally claim that would opt for an electric vehicle or not show a positive relationship between the purchase intention of an electric car, the fuel cost increase, the proximity of convenient charging places and battery lifetime perception. It was also found that age, knowledge and perceived symbolic value of the electric car, in general, have a positive influence on consumers’ choice of an electric car. A negative relationship was found between the purchase intention, social and financial risk avoidance, perceived symbolic value of the electric car in particular and the number of cars each family has. © 2020 Emerald Publishing Limited.

Abstract
Purpose This study aims to address the topic of ethics, responsibility and sustainability (ERS) orientation of students enrolled in schools of economics and management master's degrees. It examines the effect of educational background and gender on Portuguese students' orientation towards ERS, as well as the extent to which there is a relation between the scientific area of the master degree in which the student is enrolled and his/her ERS orientation. Design/methodology/approach The authors used a sample of 201 students from several master degrees offered by the School of Economics and Management of a large public Portuguese university and analysed their ERS orientation using a survey by questionnaire. Findings Findings suggest that there are differences in orientation across gender, with female students valuing ERS more than their male counterparts. Educational background has minimal effects on the responses. It was also found some sort of selection effect in terms of the scientific area of the master degree and ERS orientation. Originality/value This study contributes to the literature by analysing the issue of whether students with an educational background in economics and management present different ERS orientation than their counterparts, as well as by examining whether there is some sort of self-selection into the study of disciplines in which ERS orientation is likely to be a week. As far as the authors are aware, this is the first study analysing this type of issue regarding ERS.

Abstract
In a recent paper (10.1007/s11192-020-03386-9) we proposed a model to estimate the citations of an article in a database (Scopus/Web of Science) in which it is not indexed using the percentile rank of the database (Web of Science/Scopus) in which it is indexed. In this study we supplement the previous work with three advances: (1) by using 15 different research fields, corresponding to over 1 million papers, since we previously used only four fields; (2) by measuring the agreement between the percentile ranks in both databases using Lin's concordance correlation coefficient, since this coefficient has not been used previously to measure this agreement, but as a test with a sample of 15,400 papers to compare the actual and estimated number of citations; and (3) by using a robust data cleaning procedure. The results revealed a substantial concordance between percentile ranks of papers indexed in these two databases in all the research fields studied, and that this concordance is even stronger for high percentile values. This level of concordance suggests that we can consider the percentile of a paper in a database in which it is not indexed as being equal to the percentile of this paper in a database in which it is indexed. In other words, we increased the reliability of our previous conclusions that the percentile rank can be used as a citation database-normalization. The results of this study contribute to improve the use of citation counts in bibliometric studies, and to calculate research indicators when we need to use both bibliographic databases.