Abstract
Technological evolution has led to a significant transformation in tourism organizations, particularly in those who focus their activities on particular themes or segments, such as wine tourism. This can be transposed to Portuguese wine tourism organizations because the majority lack the necessary information and communication technologies (and inherent technologies) to become globally competitive. As highlighted in the literature, for a tourism experience to become memorable it must be emotional and immersive in such a way that the tourist becomes fully involved with the existing surroundings. This leads to the notion of using virtual reality experiences as triggers for the development of wine tourism. Considering the relevance of Portugal's Douro Valley to the country's wine tourism segment, a theoretical model that supports the implementation of multisensory (hence more immersive) virtual wine tourism experiences is developed. While considering the international success of Port wine tourism, this paper also presents a conceptualization of a multisensory virtual Port wine experience that includes a conceptual perspective and a technological solution proposal.

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Abstract
E-commerce website owners rely heavily on analysing and summarising the behaviour of costumers, making efforts to influence user actions and optimize success metrics. Machine learning and data mining techniques have been applied in this field, greatly influencing the Internet marketing activities. When faced with a new e-commerce website, the data scientist starts a process of collecting real-time and historical data about it, analysing and transforming this data in order to get a grasp into the website and its users. Data scientists commonly resort to tracking domain-specific events, requiring code modification of the web pages. This paper proposes an alternative approach to retrieve information from a given e-commerce website, collecting data from the site's structure, retrieving semantic information in predefined locations and analysing user's access logs, thus enabling the development of accurate models for predicting users' future behaviour. This is accomplished by the application of a web mining process, comprehending the site's structure, content and usage in a pipeline, resulting in a web graph of the website, complemented with a categorization of each page and the website's archetypical user profiles. 1877-0509 (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
In order to increase sales and profits, it is common that e-commerce website owners resort to several marketing and advertising techniques, attempting to influence user actions. Summarizing and analysing user behaviour is a complex task since it is hard to extrapolate patterns that never occurred before and the causality aspects of the system are not usually taken into consideration. There has been studies about characterizing user behaviour and interactions in e-commerce websites that could be used to improve this process. This paper presents an agent-based framework for simulating models of user behaviour created through data mining processes within an e-commerce context. The purpose of framework is to study the reaction of user to stimuli that influence their actions while navigating the website. Furthermore a scalability analysis is performed on a case-study. © Springer International Publishing AG 2018.

Abstract
Research management promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of a higher education institutions' research information assets. These assets may include databases, documents, policies and procedures. Conceptually linked, knowledge and research assume critical relevance as an essential tool to insuring Higher Education institutions quality. Institutions are challenged to develop robust (internal) quality assurance systems in which information about scientific production, research projects, staff curricula are considered as relevant indicators. This commitment with science and research is also visible by the opportunities promoted by institutions for the academic development of their staff. Accordingly, the assessment of research and science indicators becomes an essential step for the definition of research development programmes in HE institutions. Based on this framework, it was developed an online questionnaire to be answered by academic staff, trying to assess some science and research indicators. Trying to measure the research potential of all faculty staff, this assessment tool is organized in distinctive four dimensions, namely researcher's (i) biographic data, (ii) scientific identification, scientific outputs (books, Books' chapters, scientific paper indexed and proceedings), (iii) research project with competitive funding and (iv) suggestions to improve research production. In what concerns to the application, all faculty staff members (teachers and researchers) were invited to contribute. The results were presented and discussed personally and collectively with all academic community. These results also provide relevant Key Performance Indicators, also known as KPIs or Key Success Indicators (KSIs), that could help managers and researchers gauge the effectiveness of various functions and processes important to achieving organizational goals. If scientific research is a strategic priority to higher education institutions, this kind of KPIs could be used to help academic managers to assess whether they or their faculty/research staff are on or off target towards those goals.

Abstract