Lobo, Carla Azevedo

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Lobo

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Carla Azevedo

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Carla Azevedo Lobo

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Carla Azevedo Lobo é doutorada em Gestão pela Universidade Portucalense. É Professora Auxiliar da Universidade Portucalense e leciona em cursos de Licenciatura, Mestrado e Doutoramento, na área das Ciências Empresariais. É também Coordenadora do Curso de Licenciatura em Gestão, desde 2010. É investigadora do REMIT (Research on Economics, Management and Information Technologies). Foi a Investigadora Responsável do Projeto de Investigação ("IEcPBI”) na área dos Negócios Internacionais, financiado pelo COMPETE 2020, FEDER e FCT, entre 2018 - 2022. Afiliação: Investigadora do REMIT - Research on Economics, Management and Information Technologies (departamento: DEG)

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REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura. Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture. Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations: - the understanding of local, national and international environment; - the development of activities oriented to professional practice, namely in the business world.

Search Results

Now showing 1 - 2 of 2
  • PublicationOpen Access
    The interplay of innovation and internationalisation in the foreign market entry mode and international market selection process of SMEs
    2023-12-15 - Azevedo, Mónica; Lobo, Carla Azevedo; Santos-Pereira, Carla; Durão, Natércia; Gerschewski, Stephan
    In an interconnected, globalised world where the success of companies increasingly relies on internationalisation, innovation has emerged as a crucial strategic decision for firm’s strong development and competitiveness. While there tends to be a consensus in the literature regarding the growing significance of internationalisation and innovation, certain questions arise regarding the relationship between innovation and entry modes with lower market commitment as well as destination markets with lower risks. This study aims to investigate whether a discernible pattern of relationship exists between internationalisation modes, destination markets, and innovation among small and medium-sized Portuguese firms. To accomplish this research objective, we developed and distributed an online questionnaire survey and collected empirical data from Portuguese SMEs. The final dataset consisted of 310 valid responses, which were subjected to statistical analysis using IBM SPSS 27.0 Statistics software. Considering the categorical nature of the data (measured on a nominal or ordinal scale), we applied robust quantitative analysis techniques. More specifically, we employed exploratory statistical analyses, including univariate and multivariate exploratory factorial analysis (EFA), as well as inferential analysis (e.g., Spearman's correlation and Chi-square test for correlation analysis, and Mann-Whitney nonparametric test). Our findings provide empirical evidence that companies employing internationalisation modes requiring greater commitment, along with those targeting geographically and psycho-logically distant destination markets, tend to attach greater importance to innovation as a determinant of internationalisation. Our study carries important theoretical and practical implications.
  • PublicationRestricted Access
    Balancing innovation and integrity: Faculty perceptions of AI and generative AI in assessment
    2025-12-10 - Santos-Pereira, Carla; Moreira, Fernando; Lobo, Carla Azevedo; Azevedo, Mónica
    The integration of Artificial Intelligence (AI) and Generative AI (GAI) into higher education assessment is reshaping debates, especially in business education, in teaching and learning. While AI supports data analysis, pattern recognition, and predictive modelling, GAI extends these capabilities to the automated generation of texts and assessment materials. Yet their role remains contested, raising questions of efficiency, ethics, and academic integrity. This study investigates faculty perceptions and practices regarding AI/GAI in assessment, with a focus on business disciplines. A national survey yielded 111 responses across institutions; 46.8% were social sciences faculty. The questionnaire examined current uses, perceived benefits and risks, and expectations for future adoption. Overall, 53.2% report using AI/GAI for assessment. Among adopters, applications include plagiarism detection (63.3%) and content generation (37.6%). Benefits include time efficiency (66.1%), greater objectivity (48.6%), and improved feedback quality (42.2%). However, concerns persist about reliability (62.4%), ethical implications (52.3%), loss of the human element (51.4%), and insufficient training (50.5%). Faculty remains divided on permissibility: 44.0% support conditional integration, 43.1% favor selective use, and 5.6% advocate complete prohibition. These patterns indicate cautious optimism. While faculty recognize AI/GAI’s transformative potential, training deficits, technical limitations, and unresolved ethical challenges impede widespread adoption. Business educators emphasize the tension between efficiency gains and safeguarding critical thinking, creativity, and fairness. This article offers one of the first empirical portraits of Portuguese assessment practices involving AI/GAI. It underscores the need for targeted training, ethical frameworks, and institutional policies that balance innovation and integrity, enabling responsible and effective assessment in higher education.