Derivation and consistency checking of models in early software product line engineering

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Strategic design of There App’s business model: From product to multi-sided platform

The following work project illustrates the strategic issues There App, a mobile application, faces regarding the opportunity to expand from its current state as a product to a multisided platform. Initially, a market analysis is performed to identify the ideal customer groups to be integrated in the platform. Strategic design issues are then discussed on how to best match its value proposition with the identified market opportunity. Suggestions on how the company should organize its resources and operational processes to best deliver on its value proposition complete the work.

Functional and molecular characterization of SR45, a plant-specific factor involved in sugar and stress signaling in Arabidopsis thaliana

Dissertation presented to obtain the Ph.D degree in Molecular Biology

Improvement of Lipton’s business model through wholesalers and traditional supermarkets channel

Field Lab in Entrepreneurial Innovative Ventures

An analog model for global macro investing

This study proposes a systematic model that is able to fit the Global Macro Investing universe. The Analog Model tests the possibility of capturing the likelihood of an optimal investment allocation based on similarity across different periods in history. Instead of observing Macroeconomic data, the model uses financial markets’ variables to classify unknown short-term regimes. This methodology is particularly relevant considering that asset classes and investment strategies react differently to specific macro environment shifts.

Fostering e-participation sustainability through a BPM-driven semantic model

According to a recent Eurobarometer survey (2014), 68% of Europeans tend not to trust national governments. As the increasing alienation of citizens from politics endangers democracy and welfare, governments, practitioners and researchers look for innovative means to engage citizens in policy matters. One of the measures intended to overcome the so-called democratic deficit is the promotion of civic participation. Digital media proliferation offers a set of novel characteristics related to interactivity, ubiquitous connectivity, social networking and inclusiveness that enable new forms of societal-wide collaboration with a potential impact on leveraging participative democracy. Following this trend, e-Participation is an emerging research area that consists in the use of Information and Communication Technologies to mediate and transform the relations among citizens and governments towards increasing citizens’ participation in public decision-making. However, despite the widespread efforts to implement e-Participation through research programs, new technologies and projects, exhaustive studies on the achieved outcomes reveal that it has not yet been successfully incorporated in institutional politics. Given the problems underlying e-Participation implementation, the present research suggested that, rather than project-oriented efforts, the cornerstone for successfully implementing e-Participation in public institutions as a sustainable added-value activity is a systematic organisational planning, embodying the principles of open-governance and open-engagement. It further suggested that BPM, as a management discipline, can act as a catalyst to enable the desired transformations towards value creation throughout the policy-making cycle, including political, organisational and, ultimately, citizen value. Following these findings, the primary objective of this research was to provide an instrumental model to foster e-Participation sustainability across Government and Public Administration towards a participatory, inclusive, collaborative and deliberative democracy. The developed artefact, consisting in an e-Participation Organisational Semantic Model (ePOSM) underpinned by a BPM-steered approach, introduces this vision. This approach to e-Participation was modelled through a semi-formal lightweight ontology stack structured in four sub-ontologies, namely e-Participation Strategy, Organisational Units, Functions and Roles. The ePOSM facilitates e-Participation sustainability by: (1) Promoting a common and cross-functional understanding of the concepts underlying e-Participation implementation and of their articulation that bridges the gap between technical and non-technical users; (2) Providing an organisational model which allows a centralised and consistent roll-out of strategy-driven e-Participation initiatives, supported by operational units dedicated to the execution of transformation projects and participatory processes; (3) Providing a standardised organisational structure, goals, functions and roles related to e-Participation processes that enhances process-level interoperability among government agencies; (4) Providing a representation usable in software development for business processes’ automation, which allows advanced querying using a reasoner or inference engine to retrieve concrete and specific information about the e-Participation processes in place. An evaluation of the achieved outcomes, as well a comparative analysis with existent models, suggested that this innovative approach tackling the organisational planning dimension can constitute a stepping stone to harness e-Participation value.

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

Growth hacking model for B2B saas startups

The following project introduces a model of Growth Hacking strategies for business-tobusiness Software-as-a-Service startups that was developed in collaboration with and applied to a Portuguese startup called Liquid. The work addresses digital marketing channels such as content marketing, email marketing, social marketing and selling. Further, the company’s product, pricing strategy, partnerships and website communication are examined. Applying best case practices, competitor benchmarks and interview insights from numerous industry influencers and experts, areas for improvement are deduced and procedures for each of those channels recommended.

The emergence of product certification systems as trade barriers

This paper addresses the growing difficulties automobile manufacturers face within their after sales business: an increasing number of trade obstacles set up by import countries discriminates against the foreign suppliers and impedes the international sales of genuine parts. The purpose of the study is to explore the emergence of trade restrictive product certification systems, which affect spare parts exports of automobile manufacturers. The methodology used includes review of the literature and an empirical study based on qualitative interviews with representatives of major stakeholders of the automotive after sales business. Relevant key drivers, which initiate the introduction of technical regulations in importing countries, are identified and analysed to evaluate their effect on the emerging trade policy. The analysis of the key drivers outlines that several interacting components, such as the global competitiveness of the country, macroeconomic and microeconomic factors, and certain country-specific variables induce trade restrictive product certification systems. The findings allow for an early detection of the emergence of product certification systems and provide a means to early recognise the risks and opportunities for the sales of automotive spare parts in the automakers’ target markets. This allows the manufacturers to react immediately and adapt in time to the upcoming changes.