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Determinants of CSR importance in employer attractiveness
No full textThis study examines what impacts the importance of CSR in employer attractiveness among
younger generations. A moderated moderation model with four constructs based on individuals’
identities connected to CSR and employer attractiveness was tested in a survey with 107
respondents. The analyses suggest that the perceived importance of CSR in employer
attractiveness is directly influenced by attitudes towards CSR and this effect is stronger for
strong personal CSR norms. The economic dimension does not significantly moderate the
moderation effect. Individuals with strong attitudes and norms towards CSR highly value CSR
in employer attractiveness, the economic dimension does not diminish this
Identification of critical areas in the water supply network using multicriteria decision analysis
No full textDissertation presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and Science, specialization in Geospatial Data ScienceIt is critical to ensure the efficient management of water supply networks to reduce water
losses caused by cracks and ruptures in the underground infrastructure. These issues have an
impact on environmental sustainability, resource efficiency, and operational costs. This issue
is especially important in aging infrastructure, where unbilled water losses frequently exceed
acceptable limits.
The study's main goal is to identify critical areas within Albufeira's water supply network, which
experiences 23% annual unbilled water losses. The study uses a multi-criteria analysis
methodology based on the Analytical Hierarchy Process and Geographic Information Systems.
The study looked at environmental, physical, and operational factors to create predictive maps.
The data were transformed into a hierarchical model, with weights assigned based on expert
contributions reported in scientific articles. The model was validated using techniques such as
acoustic geophones and thermal drones.
The findings show that the proposed methodology significantly improves the efficient
management of water resources by reducing losses and costs while promoting sustainability.
High-risk areas were identified, allowing for prioritization of maintenance interventions.
Applying the Analytical Hierarchy Process model reduced failures from 35% to 40%, detecting
leaks efficiently. It is concluded that integrating and Geographic Information Systems,
Multicriterial Decision Analysis, and Analytical Hierarchy Process improves water supply
network management by reducing water losses, operational costs, and environmental
impacts
Ltp labs - business model evolution: implementation and strategic impact
No full textLTPlabs, a leading analytics consultancy, blends advanced analytics with business expertise,
driving remarkable performance for clients. Their success lies in tailored, ready-to-use products
and a commitment to innovation. LTP values its team - analytical experts united in pursuing
excellence, teamwork, and tangible outcomes. This thesis aims to critically analyse LTP's
model, pinpointing gaps in the evolving analytics landscape. It proposes a robust business
model catering to these gaps, enhancing organizational value. It includes developing a change
management plan and a market strategy for implementation. Lastly, the thesis explores Industry
4.0 and how LTP can integrate physical digitization into consultancy projects
Crm at Borussia Dortmund: internationalization strategies leveraging on digital platforms - optimizing sports Crm: Borussia Dortmund´s Usa strategy
No full textThis research explores the convergence of Customer Relationship
Management (CRM), using Borussia Dortmund's presence in the
USA as a case study. Delving into CRM's definition and relevance
in sports, the study examines the club's status, social media impact,
and merchandise sales. Market analysis, competitive comparisons,
and digital platform evaluations inform targeted strategies. The
research concludes with recommendations for improving loyalty
programs and capitalizing on reach, providing a comprehensive
guide for sports organizations navigating the dynamic landscape of
CRM and digital strategies in the global market
How to create a breakthrough in consumer-based energy communities in Portugal: segmentation, targeting and poditioning, process, and people
No full textIn Portugal, Energy Communities are becoming increasingly relevant. Greenvolt Comunidades
is a new player in the energy market that focuses on energy management. This report presents
a comprehensive marketing strategy for the new service proposed “Poupança Unida”. The
report includes four additional sub-reports that deeper explore the following topics:
Segmentation, Targeting and Positioning, People and Process; Communication Plan; Brand
Identity, Service and Physical Evidence; and the Pricing Strategy tied with the Distribution
Channel choices. The objective of the report is to create a breakthrough in consumer-based
Energy Communities for Greenvolt Comunidades in Portugal
Building an effective managerial sales dashboard - application on the Iberian market for clams
No full textData-driven pricing and demand forecasting gained
popularity with increasing data availability. Start-ups
encounter high uncertainty due to a lack of internal data
before market entry. For the market entry in the Iberian
Peninsula of Oceano Fresco, a sustainable seafood start up, the market of clams with its demand and supply
factors are analyzed based on a publicly available
database. Demand is forecasted with an ARIMA model,
and monthly profit is maximized with a Newsvendor
Model. Two managerial Excel dashboards are created to
illustrate the latest developments on the clam market and
offer a monthly production planning tool
Becoming Muié - prototyping
Get PDFThe present Work Project aims to deliver an overview on Muié’s journey, a lingerie start-up
for women who had breast cancer. Resorting to the Lean Startup framework, an analysis is
conducted on the problematic to be tackled, on the development of the Business Model Canvas,
on the bra prototyping, as well as on the start-up’s expected social impact. To validate the
concept, a quantitative and qualitative research was performed, including a questionnaire and
interviewsto patients, health professionals, and breast cancer-related associations. To conclude,
the reader is expected to comprehend the effect of breast cancer on women’s self-esteem and
sexualit
Ai-driven decision support in the automotive industry: designing a user-centric ai chatbot using large language models and the double diamond approach
No full textCompanies are confronted with a paradoxical situation: although data is abundant, its
volume complicates rather than facilitates decision-making. This thesis explores how large language
models (LLMs) can address this challenge with a user-centered approach. Based on the specific
needs and challenges of decision-makers in the automotive industry, identified through user
interviews and content analysis, a chatbot was developed and evaluated. The findings demonstrate
the potential of LLMs to streamline decision-making by efficiently processing complex data and
generating insights. This research showcases the feasibility of user-centered AI tools in enhancing
decision-making processes and provides a comprehensive framework for future research
The impact of three-month libor rate changes on gold and S&P 500 returns: a machine learning forecasting approach
No full textThis study examines the dynamics of the U.S. three-month LIBOR rate and its influence on
financial markets, specifically focusing on its impact on the returns of financial assets such as the
S&P 500 and gold, from 1990 to 2024. Employing machine learning models, regression and
LSTM, the research aims to predict future asset returns under different economic conditions. The
research focuses on two different scenarios: falling rates from October 2008 to October 2009, and
rising rates from January 2023 to March 2024, comparing the predictive capabilities and
constraints of both models in these contexts
Data-Driven Customer Segmentation for Optimized Marketing and Strategic Business Growth
No full textDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsIn the competitive landscape of vehicle renting and fleet management, understanding and
classifying customer behaviour is paramount for businesses that specialize in financing and
managing full-service car fleets and mobility solutions. This study explores the critical role of
client segmentation in a service-oriented sector, particularly in distinguishing customers based
on renting preferences, kilometres consumption, and specific vehicle characteristics. Drawing
from literature on customer segmentation techniques in analogous industries, this study
emphasizes the importance of data-driven strategies in identifying patterns within customer
data. Such segmentation is essential for tailoring products and services effectively. For
example, differentiating between larger companies that require more mileage, longer duration
contracts, and a comprehensive fleet solution. As for smaller companies that look for contracts
with lower mileage, is crucial for targeted service delivery. Empirical studies indicate that
effective client segmentation profoundly impacts business strategies by enabling more precise
marketing, enhancing service delivery, and boosting customer satisfaction. By understanding
the unique needs and preferences of each segment, companies can devise focused strategies that
foster customer loyalty and drive revenue growth