Browsing by Issue Date, starting with "2024-10-17"
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- Brand placement disclosure on Instagram posts : the impact on behaviors towards the featured productPublication . Bicudo, Catarina Silva de Almeida; Romeiro, PauloThis research seeks to determine whether it's more worth it to pay for sponsored endorsements, or to promote organic ones (e.g., send products to potential endorsers and hope they make content out of it), and therefore help marketers in their budget allocation decisions. Accordingly, an experimental study was conducted to investigate if the absence or presence of a sponsorship disclosure on Instagram posts impacts the post's credibility, and subsequently behaviors towards the product featured, such as value perception and purchase intention. Surprisingly, findings show that disclosure does not have a significant direct effect on either post credibility, product value perception or product purchase intention. Despite this, survey results reveal that post credibility significantly affects value perception and purchase intention, and value perception considerably influences purchase intention.
- The management consulting paradigm : a case study comparing two consulting approachesPublication . Livério, José Maria; Rajsingh, Peter V.The management consulting industry has been estimated to be worth around $250 billion per annum and is growing consistently year over year. In the competitive landscape of consulting, various approaches exist whereby firms seek to differentiate themselves from their peers. This thesis aims to understand differences in problem-solving between the engineering approach versus a management orientation within the consulting industry. To capture the differences three forms of data were analysed. We surveyed 150 individuals with participants ranging from India to Mexico, as well as Europe, and the United States. We then interviewed 14 individuals with at least two years and a half of consulting experience and then 5 senior consultants. These sources allowed us to have an overview of differences between engineering and management and its long-term impacts on a consultant’s approach to problemsolving. The major differences found were that individuals with a management background demonstrated a wider perspective when solving business problems, even with only two and a half years of consulting experience. On the other hand, individuals with an engineering background demonstrated more attentiveness to details. The particularities of an educational background, which contours the form of thinking associated with problem-solving, was found to have an impact over a longer-term on consulting practise. The study creates a fertile ground for future research on different topics, for example if differences identified are indeed indicators of top performance.
- Artificial intelligence & digital ecosystems and their role in shaping the future of automotive aftersalesPublication . Raudies, Mona; Lancastre, FilipaThis thesis examines the role of artificial intelligence (AI) and digital ecosystems (DEs) in shaping the future of the automotive aftersales domain. This research addresses a gap in the existing literature, which has predominantly focused on broader digital transformation trends, thereby leaving the specific implications for aftersales services underexplored. By employing a qualitative approach based on 11 semi-structured interviews with experts from the automotive and consulting sectors, the study identifies key use cases for AI and DE integration, including personalized customer experiences, AI-driven customer support chatbots, and predictive maintenance. Additionally, it explores the strategic role of aftersales DEs in enhancing the competitiveness of original equipment manufacturers (OEMs) by improving customer relationships, leveraging external skills and knowledge, and establishing entry barriers. Furthermore, the research identifies significant challenges in the integration process, including the harmonization of technology, data management and regulatory compliance. The study concludes with lessons learned for OEMs, emphasizing the importance of a holistic approach, workforce education and the need to balance technological innovation with humancentric strategies. Overall, the findings contribute both to the academic discourse and provide actionable recommendations for industry practitioners aiming to leverage AI and DEs in the rapidly evolving automotive aftersales sector.
- Exploring generation Z's use of AI advice in business decision-makingPublication . Correia, Inês Monteiro Saraiva; Lettl, Christopher; Kommol, ErikThere is an increasing number of companies employing AI in business decision-making. Companies are composed by a diverse workforce with different experiences and backgrounds thus, it becomes imperative to understand if generations rely differently on AI. This thesis aims to understand the differences between Generation Z and Generation X regarding their reliance on AI advice and explore how this relationship is affected by trust. Additionally, it assesses the moderating effect of confidence in own judgement. To collect the data, a quantitative betweensubjects survey was employed, where participants from both generations were presented with two hypothetical decision-making scenarios to evaluate their reliance on AI advice. Findings reveal that Gen Z relies more on AI advice compared to Gen X. Interestingly, no significant differences were found in dispositional trust in AI between the two generations. However, a strong positive correlation was identified between dispositional and situational trust, with situational trust significantly enhancing reliance on AI advice. This indicates that higher levels of situational trust are correlated with greater reliance on AI. Surprisingly, the moderating effect of confidence in own judgment was not confirmed. Exploratory analysis suggests that familiarity with AI might mediate the relationship between generational differences and reliance on AI advice. Additionally, it was found that higher confidence in own judgement negatively impacts reliance on AI advice. These insights underscore the complexity of understanding how trust affects reliance on AI across generational cohorts and highlight the importance of considering this factor in order to foster effective AI integration strategies within companies.
- The role of large language models in mental health : a scoping reviewPublication . Gomes, Tiago; Martins, HenriqueMental health disorders affect nearly one billion individuals worldwide, with a growing prevalence over year, caused in part due to stigma and lack of treatment causing a high burden for healthcare systems. In this context, Large Language Models (LLMs), such as GPT-4, have emerged as transformative tools with the potential to improve mental health care. This master thesis conducts a scoping review of research published from 2023 onwards to explore the current applications of LLMs within the realm of mental health, with the objective of offering a thorough overview of their existing and prospective applications in clinical practices and data analysis. While LLMs hold promise in improving mental healthcare through early diagnosis, treatment planning, and the communication between patients and clinicians, this review has also pointed out the limitations the current models have, such as the high-risk mental health crisis, an inability to understand emotional subtleties which are crucial in the treatment of mental health, and concerns about ethics and data privacy in relation to the inherent biases of the training data. For future research, key areas include enhancing LLMs' skills in recognizing crises, creating tailored models for mental health for higher sensibility, and addressing significant ethical issues like bias and data privacy, which are essential for the gradual integration into the mental health field. LLMs integration in the mental health sector require a careful integration in order ensure patient safety and maintaining trust. It is imperative to have human oversight while using these tools, especially in high-risk clinical environments.
- Um estudo de viabilidade sobre o uso combinado de neurofeedback e fNIRS na ansiedade musical de performance musicalPublication . Santos, Henrique Gomes; Silva, Clédna Patrícia de OliveiraA ansiedade de performance musical é um fenómeno que afeta os músicos em situações nas quais o seu desempenho musical é ou pode ser avaliado, podendo trazer prejuízos para a própria performance. Este estudo de viabilidade procura contribuir para a preparação de futuros protocolos de investigação mais extensos e que utilizem a mesma tecnologia e abordagem, fornecendo dados críticos para o refinamento de metodologias. Com efeito, foi formulado e aplicado um protocolo de Neurofeedback associado a fNIRS (functional Near-Infrared Spectroscopy) a 13 músicos portugueses, amadores e profissionais, com idades entre 18 e os 29 anos. O protocolo consistia, numa primeira fase, na realização de uma tarefa de linha de base, onde era pedido aos participantes que procurassem relaxar antes da primeira atuação. Ambas as atuações contavam com a presença de um júri virtual. De seguida, deu-se início à sessão de Neurofeedback, que compreendia a realização de três tarefas com diferentes intuitos e dificuldades, acompanhadas por um termómetro emocional, que os participantes tinham de manter dentro dos parâmetros indicados na imagem. Por fim, os músicos foram convidados a realizar uma segunda atuação, também na presença do mesmo júri virtual, mas com uma nuance diferente, as camaras dos júris encontravam-se desligadas. Apesar dos resultados não se mostrarem significativos devido à reduzida amostra, que impede a sua generalização, os mesmos poderão ser tidos em conta para fornecer insights valiosos no desenvolvimento de intervenções eficazes com a mesma técnica. O presente estudo não só abre novas portas para a melhor compreensão do Neurofeedback associado a fNIRS, como contribui para otimizar futuras intervenções que utilizem a mesma abordagem na ansiedade de performance musical.
- Equity valuation : A.P. Møller - Mærsk A/SPublication . Vieira, Vítor Hugo Freitas; Martins, José Carlos TudelaIn this dissertation, the object of study was to determine A.P. Møller – Mærsk A/S’s fair value, as of 31st December 2024, through intrinsic and comparative valuation methods, to determine an investment recommendation, ranging from buy to sell, in comparison to the market price. To this end, different valuation methods were studied and presented and the DCF model was considered the most adequate for the valuation of Maersk. Nevertheless, comparative valuation methods were generated as model adjuster for the price estimation. From this, it was possible to determine a share price of 12.069 DKK. APMM has two different shares traded with different voting rights, however, their price difference is very low. Therefore, comparing the estimated price with the MAERSKb.CO share value of 9.622 DKK, as of 1st March 2024, it was able to determine an existence of potential upside. Hence, it was issued an Outperform recommendation. Finally, the assumptions and estimates supporting this thesis were tested and compared in two different periods with various investment reports. The first period was on 3rd November 2023, with comparisons of reports from SEB and ABG, where it allowed to understand that the intrinsic valuation for that period was determining an underperformance of the share, while the comparative method was determining Hold position, as with the investment reports. As for the second period of 1st March of 2024, comparing with information available from MarketScreener, it was determined that the model price was near the average of the recommendations available.
- AI in negotiations : the perspective of procurement managersPublication . Schurer, Jordin Aaron; Lancastre, FilipaThis study explores the adoption and impact of artificial intelligence (AI) in negotiations through qualitative interviews with 22 procurement managers and negotiation experts. Using the Technology Acceptance Model, the research investigates AI adoption, perception, and influencing factors in negotiation processes. Findings reveal early-stage AI adoption with growing interest. AI is perceived as beneficial for efficiency, data analysis, and communication, particularly in more straightforward standardized negotiations. Key adoption factors include negotiation frequency and complexity, data quality, security concerns, and the perceived value of human skills. Despite its advantages, professionals express concerns about AI's limitations in creativity, interpreting subtle signals, and potential impact on supplier relationships. There is a preference for using AI as a support tool rather than for full automation. The study recommends gradual AI implementation through low-risk pilot projects. It highlights the need for professionals to communicate the use of AI transparently to suppliers and evaluate AI tools thoroughly prior adoption. Further research is needed on integrating AI with human skills, evaluating AI effectiveness across negotiation phases, and exploring ethical implications, especially regarding supplier relationships.
- Equity valuation : Amgen Inc.Publication . Soares, Diogo Jorge Ruivo; Martins, José Carlos TudelaThe main purpose of this dissertation is to determine the target share-price for Amgen Inc., a biopharmaceutical company based in United States of America and listed on New York Stock Exchange (NYSE). For the valuation, an analysis was conducted on the company’s structure, their business model, the primary sources of revenues, the risks associated and the dynamics of the market and competitors. This research offered a clearer insight into the possible future cash flows of the company and through the Discounted Cash Flow method we were able to determine the target valuation for each share of Amgen. In addition, the Relative Valuation was used to compare the target share price. Our research recommends a Hold investment, with a target share price of 323.10 USD, 13.64% above the share price at 28th of March 2024.
- Consumer acceptance of the usage of artificial intelligence in the banking sectorPublication . Hidas, Réka Emma; Lancastre, FilipaIn the past years, artificial intelligence (AI) technologies have become rapidly integrated into the banking sector, thus understanding the factors that influence customers to accept the usage of these innovations is crucial for financial institutions. AI offers huge transformative potential, as it can enhance operational efficiency, improve consumer service, or strengthen security. However, there is limited research on how consumers perceive and adopt these technologies, especially from a customer experience (CX) perspective. This gap in understanding presents a challenge for banks that are trying to fully leverage AI in their customer-facing services. This study aims to investigate the key factors that are influencing consumer acceptance of AI technologies in banking, with a focus on awareness, trust in electronic security, customer experience, and demographic factors, specifically age. The results revealed that the most significant driver for adoption is the perceived trust towards electronic security. Age also has a huge influence, as younger customers appeared to be more inclined to embrace AI services compared to older generations. Contrary to expectations, neither customers’ awareness of using AI technologies nor customer experience had a statistically significant impact on AI acceptance.