Impact of CSR perceptions on workers’ innovative behaviour: exploring the social exchange process and the role of perceived external prestige

The study aims to show how organisational corporate social responsibility (CSR) can influence workers’ attitudes, especially in terms of innovative behaviour (IB). A second aim is to explore the social exchange process that may underlie this relationship, by examining the mediating role of organisational trust (OT), affective commitment (AC) and happiness (HAP), and the moderating role of perceived external prestige (PEP). The authors employ structural equation modelling based on survey data obtained from 315 Portuguese individuals. The findings show that perceptions of CSR predict IB through a social exchange process which involves the mediating role of OT, AC and HAP and the moderating process of PEP. They suggest that managers should implement CSR practices because these can contribute towards fostering IB, but that they should also invest in communication and in the process of upgrading corporate image. This study enriches the existing knowledge about social exchange relationships in organisational contexts, and responds to the need to understand underlying mechanisms linking CSR with workers’ organisational outcomes, by analysing CSR practices from a holistic stakeholder perspective.info:eu-repo/semantics/publishedVersio

Ubiquitous model for wireless sensor networks monitoring

Wireless Sensor Networks (WSNs) belongs to a new technology trend where tiny and resource constrained devices are wirelessly interconnected and are able to interact with the surrounding environment by collecting data, such as temperature and humidity. Recently, due to the huge growth of mobile devices usage with Internet connection, smartphones are becoming the center of future ubiquitous wireless networks allowing users to access data network services, anytime and anywhere. According to the Internet of Things vision, interconnecting WSNs with smartphones and the Internet is a big challenge. Then, due to the heterogeneity of these devices new architectures are required. This dissertation focuses on the design and construction of a ubiquitous architecture for WSNs monitoring based on Web services, a relational database, and an Android mobile application. This architecture allows mobile users accessing real-time or historical data in a ubiquitous environment using smartphones. Besides that, a push notification system to alert mobile users when a sensor parameter overcomes a given threshold was created. The entire solution was evaluated and demonstrated using a laboratory WSN testbed, and is ready for use.As redes de sensores sem fios fazem parte de uma nova tendência tecnológica na qual pequenos dispositivos com recursos limitados comunicam entre si, sem fios, e interagem com o ambiente envolvente recolhendo uma grande diversidade de dados, tais como a temperatura e a humidade. Recentemente, devido ao enorme crescimento no uso de dispositivos móveis com ligação à Internet, os smartphones estão a tornar-se o centro das futuras redes sem fios ubíquas permitindo aos utilizadores aceder a dados, a qualquer hora e em qualquer lugar. De acordo com a visão da Internet of Things, interligar redes de sensores sem fios e smartphones usando a Internet é um grande desafio e novas arquitecturas são necessárias devido à heterogeneidade destes dispositivos. Esta dissertação centra-se na proposta e construção de uma arquitectura ubíqua para a monitorização de redes de sensores sem fios, baseada em serviços Web, apoiada numa base de dados relacional e uma aplicação móvel para o sistema operative Android. Esta arquitectura permite que os utilizadores móveis acedam a dados em tempo real e também a dados históricos, num ambiente móvel, usando smartphones. Além disso, foi desenvolvido um sistema de notificações push que alerta o utilizador quando um dado parâmetro de um sensor ultrapassa um limiar pré-definido. A solução construída foi testada e demonstrada utilizando uma testbed laboratorial e está pronta para utilização

Property Appraisal Platform

This document focuses on the internship in the company DeepNeuronic as part of the project ”Property Appraisal Platform”. This project’s main objective was to develop machine learning models capable of inferring real estate prices using machine learning models and a limited set of features capable of describing a property. In order to achieve the objective, the project was divided into two major phases. In the first phase the state of the art was studied and a dataset collection was put together with the aim of creating a comprehensive representation of the real estate market all across the globe. With this dataset collection available, a set of features was chosen according to their relevancy for the main problem. The second phase consisted of the major practical developments, such as the model creation and dataset improvements. With this in mind, the most relevant metrics were chosen and the models were evaluated in the chosen datasets, creating a set of baseline results to improve upon. Afterwards, multiple other experiments were done, tackling different areas of interest that could potentially improve upon the performance of the models. In total, four different models were evaluated and all the experiments improved upon the baseline results. As an highlight, in the last experiment we propose the transformation of the target label from the property price to the ”Coefficient of the price per square meter compared to the suburb average”. Using this new target label, the results obtained were considerably better. All of these experiments were redone in a new more complex dataset, with all of the experiments improving upon the baseline results obtained in this dataset, reinforcing the idea that these experiments can be used even in more complex datasets.Este documento foi criado no âmbito do estágio realizado na empresa DeepNeuronic como parte do projeto ”Plataforma de Avaliação de Propriedades”. O objetivo do mesmo foi desenvolver modelos de aprendizagem automática capazes de avaliar preços do mercado imobiliário usando modelos inteligentes e um conjunto limitado de características capazes de descrever uma propriedade. Para atingir este objetivo o projeto foi dividido em duas partes principais. Na primeira parte foi feito um estudo intensivo do estado da arte, e criada uma coleção de bancos de dados extensiva, representante do mercado imobiliário no mundo inteiro. Com esta coleção disponível, um conjunto de características foram escolhidas de acordo com a sua relevância para o problema em questão. A segunda fase consistiu nos desenvolvimentos práticos principais, envolvendo a criação de modelos e melhorias nos bancos de dados. Para isso foram escolhidas as métricas mais relevantes, e foram avaliados os modelos nos bancos de dados iniciais, criando assim um conjunto de resultados base. Seguidamente, múltiplas experiências foram feitas, abordando diferentes áreas de interesse que podiam potencialmente melhorar os resultados base. No total quatro modelos diferentes foram avaliados e as experiências realizadas todas melhoraram os resultados base obtidos. De especial relevância, na última experiência propomos a transformação do preço da propriedade para uma variável objetivo que pode ser descrita como o ”Coeficiente do preço por metro de área quadrado comparado à média do subúrbio”. Usando esta variável os resultados obtidos foram consideravelmente melhores, estas experiências foram refeitas em um novo banco de dados consideravelmente mais complexo, verificando-se também que todas estas experiências melhoram os resultados obtidos inicialmente, reforçando a ideia que estas experiências podem ser usadas mesmo em bancos de dados mais complexos

Towards an investigation on the determinants for effectiveness and efficiency of reverse logistics systems (RLS)

This article deals with the influence of economies of scale and postponement on the efficiency and effectiveness of reverse logistics systems (RLSs). In a global way, it aims to provide an understanding of RLSs to generate knowledge of practical and theoretical character. Starting from a generic model of circular flow of materials, the system studied is positioned between the final consumer and the traditional or direct supply chain. It is a qualitative approach over two case studies carried out in Portugal and Brazil dealing with scraptires. One deals with management system while the other deals with the reverse logistics system. As conclusions, the efficiency of RLSs is aided by economies of scale. Postponement has positive effects on efficiency by increasing the system capacity reducing logistics costs which indirectly leads to economies of scale, having a positive influence on the effectiveness of RLSs. According to what has been stated in this paper, the coordination between the direct and reverse flow is a typical case of a closed circuit

A Computer-Aided Drug Design Approach to Predict Marine Drug-Like Leads for SARS-CoV-2 Main Protease Inhibition

UIDB/50006/2020 UIDB/04378/2020 Norma transitória DL 57/2016The investigation of marine natural products (MNPs) as key resources for the discovery of drugs to mitigate the COVID-19 pandemic is a developing field. In this work, computer-aided drug design (CADD) approaches comprising ligand- and structure-based methods were explored for predicting SARS-CoV-2 main protease (Mpro) inhibitors. The CADD ligand-based method used a quantitative structure–activity relationship (QSAR) classification model that was built using 5276 organic molecules extracted from the ChEMBL database with SARS-CoV-2 screening data. The best model achieved an overall predictive accuracy of up to 67% for an external and internal validation using test and training sets. Moreover, based on the best QSAR model, a virtual screening campaign was carried out using 11,162 MNPs retrieved from the Reaxys® database, 7 in-house MNPs obtained from marine-derived actinomycetes by the team, and 14 MNPs that are currently in the clinical pipeline. All the MNPs from the virtual screening libraries that were predicted as belonging to class A were selected for the CADD structure-based method. In the CADD structure-based approach, the 494 MNPs selected by the QSAR approach were screened by molecular docking against Mpro enzyme. A list of virtual screening hits comprising fifteen MNPs was assented by establishing several limits in this CADD approach, and five MNPs were proposed as the most promising marine drug-like leads as SARS-CoV-2 Mpro inhibitors, a benzo[f]pyrano[4,3-b]chromene, notoamide I, emindole SB beta-mannoside, and two bromoindole derivatives.publishersversionpublishe

The impact of monetary policy and its surprises on bank’s risk-taking

The latest financial crisis accentuated the importance of understanding bank risk and its ties to financial stability. This paper looks to investigate the impact of monetary policy in the risk-taking behaviour of Euro Area banks, when taking unconventional monetary policy into account. Looking further into this relationship, the impact of unanticipated monetary policy shocks is also analysed. Using both fixed effects and a system GMM model, sufficient statistical evidence was found to claim that looser monetary policy leads to increased risk-taking behaviour from banks. This effect, however, is mitigated in case banks and/or the market originally anticipated an even looser stance by the central bank

The influence of consumption vocabulary on the encoding and retrieval of haptic information

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and EconomicsSensory stimuli are often ambiguous, which makes it difficult for consumers to encode and retrieve them, and to construct their preferences. This project studies whether, in a prepurchase context, consumption vocabulary can help consumers to perceive what products are superior on haptic attributes. In an experiment with bed pillows, participants provided with evaluative criteria preferred the pillow with superior haptic attributes more often and to a larger extent than participants who had no evaluative criteria, which suggests the provision of criteria has a positive influence on preference construction. Improvements in memory for haptic attributes and disconnection from incongruent market information derived from that provision were not confirmed

Profiles of ageing in the South of Portugal: education and cognitive functioning in elderly persons living in institutionalized and community contexts

The region of the Algarve shows huge differences between the coastline where population in the urban areas grows, and the inland rural areas, in some cases very isolated, which frequently have high ageing indexes. This general scenario, with an elderly population with very different economic and social conditions, frames the ongoing PhD research designed as a cross-sectional study of an intentional sample of elderly persons. The basic theoretical framework departs from the perspective of developmental psychology of life-span and the model of selection, optimisation and compensation for optimal ageing (Baltes & Baltes, 1990; Freund & Baltes, 2002). The present study is a first step in the analysis of empirical data collected in the PhD sample (N=156; age range 65 to 97 years; M = 80.4 years; SD = 7.2 years). Its purpose is to assess the cognitive functioning of participants, screening for cognitive impairment and examine the relations between the cognitive status of the subjects and a number of selected variables including educational level, age, physical activity and living contexts of the subjects. We accessed the cognitive status of the participants with the Portuguese version of Mini Mental State Examination (MMSE) finding a 10.3% prevalence of positive cases with cognitive impairment. The results also show significant relationships between the cognitive status accessed by the MMSE and educational level, professional qualification, age, living arrangement and activity level of the participants. The relationship verified between educational level and cognitive status of the participants was the largest correlation found in the study with the variability in educational level accounting for 44.8% of the variability in MMSE score. This results points in the same direction of several lines of research that corroborate the strong intercorrelation between education and cognitive functioning in old age

The interaction process between medical students and families in a context of community health promotion: the case “one student, one family” at Lúrio University (Napula)

This work aims to address the main features of communication used by students from Lúrio University (Nampula, Mozambique) in the family health promotion process under the project "one student, one family". Therefore, reflections on interpersonal communication were made, based on the analysis of verbal and nonverbal language, and the relationship/interaction between medical student and family during their conversation. This is a qualitative exploratory study using observation by video recording during the meetings between medical student and family. For data analysis, conversation analysis was used. For the research, we used as scenario, the Muatala community where the Unilúrio project took place, and the families are composed of several members living in the same house. And therefore, we worked with 10 medical students who attend different courses and different semester. From the results found it is necessary to highlight the relevance that medicine student and the environment exert in their interaction to the visited families; It was clear enough that there is an insecurity for the student of what he is going to speak in the meeting. It has been in a pacific way he sits down each one accept his mistakes. As a result of that it was concluded that it is worth noting to look at the necessity of developing a work that can make the students be aware of the importance that an effective communication has in the process of interaction between students and the households of Muatala quarter