2023
Autores
Pereira, MJD; Cardoso, A; Canavarro, A; Figueiredo, J; Garcia, JE;
Publicação
SUSTAINABILITY
Abstract
Research into the role of digital influencers in marketing strategies is a rapidly developing area that has attracted the interest of researchers and organizations. In recent years, organizations have become increasingly interested in using digital influencers to promote their brands and disseminate advertising messages with a high impact on their target audience. Digital influencers are beginning to be used as models for sustainable consumption behavior (for example in the fashion, food, and health sectors) by promoting environmental and sustainable values. By promoting sustainable content and disseminating messages of environmental awareness, digital influencers can help achieve the Sustainable Development Goals (SDGs). This study aims to identify the attributes (attitude homophily, physical attractiveness, and social attractiveness) and perceived characterizations (trustworthiness, perceived expertise, and parasocial relationship) of digital influencers and their impact on purchase intention among a sample of Portuguese consumers. It also aims to identify the most relevant types of digital influencers according to their areas of influence (fashion, sports, beauty, and cinema/TV/music) and their impact on purchase intention. For data collection, an online questionnaire was developed and administered to a non-probabilistic convenience sample. Only respondents who had experience purchasing a product or service after watching a YouTuber's advertisement (screening question) or following or searching for a digital influencer could complete the questionnaire. A total of 243 valid questionnaires were received. The main findings are that the attributes and perceived characterizations of digital influencers have a positive and significant impact on purchase intention. It was also found that digital influencers can enhance shopping experience and credibility, which has a strong impact on consumers' purchase intentions. In terms of sector, the data show that the most important influencer in the 'Fashion' sector is Helena Coelho, in the 'Sports' sector is Cristiano Ronaldo, in the 'Beauty' sector is Sara Sampaio, and in the 'Music, TV, Cinema' sector is Ricardo Araujo Pereira. This study can help companies use digital influencers more effectively in their digital marketing strategies, as credibility, experience, and parasocial relationships have a strong impact on consumers' purchase intention.
2023
Autores
Mourão, RL; Gouveia, C; Sampaio, G; Retorta, F; Merckx, C; Benothman, F; Águas, A; Boto, P; Silva, CD; Milzer, G; Marzano, G; Dumont, C; Crucifix, P; Kaffash, M; Heylen, E;
Publicação
IET Conference Proceedings
Abstract
The EUniversal project, funded by the European Union, aims to establish a universal approach to the utilization of flexibility by Distribution System Operators (DSOs) and their engagement with new flexibility markets. To achieve this objective, the project team has focused on developing the Universal Market Enabling Interface (UMEI) concept. This paper presents an overview of the process of adapting grid core systems to interact with different market platforms and agents, which is a key aspect of the real-world demonstration set to take place in Portugal. © The Institution of Engineering and Technology 2023.
2023
Autores
de Queirós, RAP; Teixeira Pinto, MP;
Publicação
ICPEC
Abstract
2023
Autores
Neto, AT; Mamede, HS; dos Santos, VD;
Publicação
CENTERIS 2023 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2023, Porto, Portugal, November 8-10, 2023.
Abstract
Anomaly detection in the industrial context, identifying defective products and their categorization, is a prevalent task. It is aimed to acknowledge if training and testing multilabel classification models on textures to deploy on an MCU is possible. The focus is deploying lightweight models on MCUs, performing a multilabel classification on textures for industrial usage. For this purpose, a Systematic Literature Review was conducted, which allows knowing the commonly used machine learning models in industrial products anomaly detection and what methods are used to defect detection on textures. Through the Systematic Literature Review, was possible to understand the range of different and combined methods, the methods used in multilabel classification, the most common hyper-parametrizations and popular inferences engines to train machine-learning models to deploy on MCUs, and some techniques applied to overcome the restricted resources of memory and inference time associated with MCUs. © 2024 Elsevier B.V.. All rights reserved.
2023
Autores
Costa, Carolina; Fernandes, Sandra; Nakamura, Ingrid; Poínhos, Rui; Bruno M P M Oliveira;
Publicação
Abstract
2023
Autores
Carvalho, CL; Barbosa, B;
Publicação
International Journal of Sport Management and Marketing
Abstract
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