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This paper attempts to evaluate how the Italian tourism industry has been affected by the COVID-19 outbreak in February and March 2020. Using monthly data, a mathematical model is proposed to calculate the effects of the COVID-19 outbreak.

The paper calculates three metrics: the number of tourist arrivals, the tourist spending and the income. Each metric deals with two types of data: normal behavior and outbreak behavior. Data on normal behavior regarding the whole of Italy are used to calculate what would have been the trend of a given metric if the COVID-19 outbreak had not occurred. Data on outbreak behavior regarding a small part of Italy contains information about the COVID-19 outbreak. These data are used as a sample to infer the whole population of Italy. In all the cases, data are modeled as a variable sinusoid, where maximum and minimum peaks are calculated through linear or polynomial regression. The proposed model is compared with a classical model, i.e. the SARIMA model.

Results reveal that the COVID-19 outbreak significantly impacted the total number of tourist arrivals and total income, reducing tourist arrivals by 18.27% in February and 91.75% in March.

This paper illustrates an alternative methodology to represent historical data related to tourism and their prediction trend for the future.

Ship route prediction (SRP) is a quite complicated task, which enables the determination of the next position of a ship after a given period of time, given its current position. This paper aims to describe a study, which compares five families of multiclass classification algorithms to perform SRP.

Tested algorithm families include: Naive Bayes (NB), nearest neighbors, decision trees, linear algorithms and extension from binary. A common structure for all the algorithm families was implemented and adapted to the specific case, according to the test to be done. The tests were done on one month of real data extracted from automatic identification system messages, collected around the island of Malta.

Experiments show that K-nearest neighbors and decision trees algorithms outperform all the other algorithms. Experiments also demonstrate that linear algorithms and NB have a very poor performance.

This study is limited to the area surrounding Malta. Thus, findings cannot be generalized to every context. However, the methodology presented is general and can help other researchers in this area to choose appropriate methods for their problems.

The results of this study can be exploited by applications for maritime surveillance to build decision support systems to monitor and predict ship routes in a given area. For example, to protect the marine environment, the use of SRP techniques could be used to protect areas at risk such as marine protected areas, from illegal fishing.

The paper proposes a solid methodology to perform tests on SRP, based on a series of important machine learning algorithms for the prediction.

This paper aims to describe Tourpedia, a website about tourism, built on open data provided by official government agencies. Tourpedia provides data under a public license.

Tourpedia is built upon a modular architecture, which allows a developer to add a new source of data easily. This is achieved through a simple mapping language, namely, Tourpedia mapping language, which maps the original open data set model to the Tourpedia data model.

Tourpedia contains more than 70.000 accommodations, downloaded from open data provided by Italian, French and Spanish regions.

Tourpedia presents some limitations. First, extracted data are not homogeneous and often they are incomplete or wrong. Second, Tourpedia contains only accommodations. Finally, at the moment Tourpedia covers only some Italian, French and Spanish regions.

The most important implication of Tourpedia concerns the construction of a single access point for all Italian, French and Spanish open data about accommodations. In addition, a simple mechanism for the integration of new sources of open data is defined.

The current version of Tourpedia opens also the road to three new possible social scenarios. First, Tourpedia could be transformed into an open source of updated information about tourism. Second, Tourpedia could be empowered to support tours, which include some tourist attractions and/or events and suggest the nearest accommodations. Finally, Tourpedia may help tourists to discover unknown places.

Tourpedia constitutes an access point for data sets providers, application developers and tourists because it provides a unique website.

本论文介绍了Tourpedia, 一种以政府提供的开放数据为基础建立的旅游网站。Tourpedia通过公共执照来提供数据。

Tourpedia采用模块型结构建设而成, 方便开放商增加新数据源。这种设计通过简单映射语言, 即Tourpedia Mapping Language（TML）, 使得原开放数据模型映射到Tourpedia Data Model（TDM）。

Tourpedia包含70,000多家住宿服务, 可从意大利、法国、和西班牙国家区域提供的开放数据中下载。

Tourpedia有一些限制。首先, 其数据并非均质而且很多情况下不完整或者错误。第二, Tourpedia只包含住宿业数据。最后, 目前Tourpedia只包含一些意大利、法国、和西班牙国家区域的数据。

Tourpedia最重要的实践启示就是其通过单一信息渠道以涵盖所有意大利、法国、和西班牙国家区域关于住宿业的开放数据。此外, 新源开放数据的整合机制简单。

当前Tourpedia版本展开了三种社会场景的可能。首先, Tourpedia可以被改造成更新版的旅游信息开放数据源。第二, Tourpedia可以被用来支撑旅游活动, 包括提供一些游客景点和/或活动和就近住宿信息等。最后, Tourpedia可以帮助游客探索未知旅游目的地。

Tourpedia是一个独特的网站, 作为数据源, 为数据提供者、应用程序开发者、和游客提供便利。

The purpose of this paper is to analyze if the composition and activity of the appointment and remuneration committee have a significant effect in the remunerations of the members of the board of directors.

To achieve the paper's objective the authors proposed four hypotheses in order to analyze the repercussions of independent, institutional and executive directors in the Appointment and Retribution Committee (ARC) and its activity in the directors’ remunerations.

The results put into evidence that the composition (independent, institutional and executive members) of the ARC is not associated with the variation of the directors remuneration mean, while the activity of the ARC influences positively this remuneration mean, contrary to what was expected.

The ARC in Spain is not effective in fixating the directors’ remunerations.

El objetivo de este artículo es analizar si la configuración y actividad de las comisiones de nombramientos y remuneraciones (CNR) tienen un efecto significativo en las remuneraciones de los miembros del consejo de administración.

Para alcanzar el objetivo del artículo hemos planteado cuatro hipótesis con la finalidad de analizar la repercusión de los consejeros independientes, dominicales y ejecutivos de las CNR y la actividad de las mismas en las remuneraciones de los consejeros.

Los resultados ponen de manifiesto que la composición (miembros independientes, dominicales y ejecutivos) de las CNR no se asocian con la variación de las remuneraciones medias de los consejeros, mientras que la actividad de las CNR influye de manera positiva, contrario a lo pronosticado, en las variaciones de las retribuciones medias de los consejeros.

Las CNR en España no son efectivas en la fijación de las retribuciones de los consejeros.

This case looks at the design and implementation of a risk management strategy. It reviews the early moves by Great Plains Energy (GPE) to establish a corporate-wide Enterprise Risk Management program. The corporate Chief Risk Officer is Andrea Bielsker. Andrea appointed Jana Utter to take charge of coordinating the design and implementation of the ERM program. Utter faces a number of challenges. She has had to first conceptualize the program given the charge by the Board of Directors, then design a process by which she identifies the risks that the corporation faces, assist in designing measures for the risks, and work with the various divisions and functional areas to put processes in place to mitigate the identified risks.

The aim of this paper is to develop a systematic literature review (SLR) aiming to identify reverse logistics (RL) concepts and practices applied to the end-of-life (EOL) and end-of-use (EOU) of pharmaceuticals and to identify and synthesize, through bibliometric indicators, research opportunities on RL, considering the analysis of publications in the periodical Supply Chain Management: An International Journal (SCMij).

The SLR followed two steps, namely, search for articles on the subject and content analysis of selected material and bibliometric analysis of publications using VOSviewer®.

The SLR allowed the compilation of evidences regarding pharmaceutical RL in the groups: environmental risk, the RL evolution and regulatory and stakeholder’s educational perspective. Despite the timid specific literature on pharmaceutical RL, it was also possible to point out research gaps and opportunities. Pharmaceutical RL seems to be influenced by studies from traditional RL including mathematical modeling, managerial strategies and technologies but prescind of a systemic solution. Besides reducing environmental impact, the motivation to implement pharmaceutical RL resides in its potential for revenue. Considering integrated logistics as a trend and an emerging issue, RL for the pharmaceutical industry needs to be addressed more thorough and broadly.

The limited number of papers returned in this SLR of pharmaceutical RL impaired the bibliometric analysis of them, leading to the inclusion of papers on general RL.

This study provides an overview of the evolution of RL in the pharmaceutical industry, it also clarifies concepts and EOL/EOU practices, particularly directed to the pharmaceutical industry RL.

The spatial development of urban areas affects the characteristics of landscape as well as people’s aesthetic perception of it. Specifically, sprawl results in an urban morphology which is diametrically opposed to the compact city model and which assumes several kinds of patterns: for example “striped”, “ribbon” or “leapfrogged” urban development. Assessing urban morphology in spatial terms is crucial to urban policy, while landscape metrics are the key to a comprehensive understanding of different urban development patterns. The purpose of this paper to design and test an urban morphology indicator (UMI) for the Lombardy Regional Landscape Plan.

The paper describes an UMI that can be used to identify the heterogeneity of built-up patterns according to urban porosity, fragmentation and patch shape. This UMI is a result of Esri ArcGIS 10.3 “grouping analysis” which works by applying a spatial statistical metric for clustering geometries in a given geographical area.

Morphological analysis was used in regional urban development policies with a view to minimising impact on surrounding ecosystems and preserving the natural environment and landscape. It defines 28 different urban morphology patterns in the region, which are divided into systems, polarities and urbanised units.

The proposed methodology differs from those traditionally used in qualitative/descriptive landscape planning and supports the identification of morphological features with quantitative statistical and spatial data, allowing a fine-scale assessment of complex metrics.

The purpose of this paper is to describe a methodology to deal with conformance checking through the implementation of computer-interpretable-clinical guidelines (CIGs), and present an application of the methodology to real-world data and a clinical pathway for radiotherapy-related oncological treatment.

This methodology is implemented by a software able to use the hospital electronic health record data to assess the adherence of the actual executed clinical processes to a clinical pathway, monitoring at the same time management-related efficiency and performance parameters, and ideally, suggesting ways to improve them.

Three use cases are presented, in which the results of conformance checking are used to compare different branches of the executed guidelines with respect to the adherence to ideal process, temporal distribution of state-to-state transitions, and overall treatment efficacy, in order to extract data-driven evidence that could be of interest for the hospital management.

This approach has the result of applying management-oriented data mining technique on sequential data, typical of process mining, to the result of a conformity check between the preliminary knowledge defined by clinicians and the real-world data, typical of CIGs.