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Electronic government is increasingly dominant in the study of public administration. In analysing people's behavioural factors towards the adoption of e-services, most previous studies targeted the adult population, while those on government employees are minimal. Government employees have an essential function in the process of government operation; they can be regarded as the principal medium of communication between the service provider (government) and the end-users (citizens). This study was designed to understand the government employees' behavioural factors on their intentions towards adopting e-government services. A set of semi-structured interview questions was developed based on the prior literature on the Theory of Planned Behaviour (TPB) and e-government studies. Ten in-depth interviews were conducted in Macao SAR (Special Administrative Region). In addition to analysing the three primary constructs of TPB, the factor of Trust and some enablers and hindrances were identified. Significant findings were yielded while investigating how the government employees perceived the e-services and how they regarded the general public's perception of this issue. This contextualisation would help policymakers look at this issue from different perspectives and design feasible interventions according to group alignment strategies.
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In any physical system, when we move from short to large scales, new spacetime symmetries emerge which help us to simplify the dynamics of the system. In this letter we demonstrate that certain variations on the symmetries of general relativity at large scales generate the effects equivalent to dark matter ones. In particular, we reproduce the Tully-Fisher law, consistent with the predictions proposed by MOND. Additionally, we demonstrate that the dark matter effects derived in this way are consistent with the predictions suggested by MOND, without modifying gravity.
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Monitoring signals such as fetal heart rate (FHR) are important indicators of fetal well-being. Computer-assisted analysis of FHR patterns has been successfully used as a decision support tool. However, the absence of a gold standard for the building blocks decision-making in the systems design process impairs the development of new solutions. Here we propose a prognostic model based on advanced signal processing techniques and machine learning algorithms for the fetal state assessment within a comprehensive evaluation process. Feature-engineering-based and time-series-based machine learning classifiers were modeled into three data segmentation schemas for CTU-UHB, HUFA, and DB-TRIUM datasets and the generalization performance was assessed by a two-way cross-dataset evaluation. It has been shown that the feature-based algorithms outperformed the time-series ones on data-limited scenarios. The Support Vector Machines (SVM) obtained the best results on the datasets individually: specificity (85.6% ) and sensitivity (67.5%). On the other hand, the most effective generalization results were achieved by the Multi-layer perceptron (MLP) with a specificity of 71.6% and sensitivity of 61.7%. The overall process provided a combination of techniques and methods that increased the final prognostic model performance, achieving relevant results and requiring a smaller amount of data when compared to the state-of-the-art fetal status assessment solutions.
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Family business are the dominant form of business in the world, and Chinese family business (CFB) is a unique type of family business that relies on collective action to survive. This paper argues that in CFBs, entrepreneurial actions are transgenerational collective endeavors, and successors are groomed as stewards of the family legacy. Work-life relationship in CFBs is about synergy and not balance because the family identity is the business identity, and vice-versa. Using five in-depth case studies, this research introduces an alternative understanding of CFBs and proposes a model of work-life synergy in transgenerational entrepreneurship based on discussion of five theory-based propositions. This model explains that through emphasizing on the business family's shared value and entrepreneurial legacy, elements of trust, shared identity and stewardship of family members are enhanced which leads to collective action and goal of the business family, resulting in transgenerational entrepreneurship. Limitations and future research are presented.
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Academic Units
- Faculty of Arts and Humanities (1)
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Faculty of Business and Law
- Alessandro Lampo (6)
- Alexandre Lobo (33)
- Angelo Rafael (2)
- Douty Diakite (8)
- Florence Lei (3)
- Ivan Arraut (8)
- Jenny Phillips (9)
- Sergio Gomes (1)
Resource type
United Nations SDGs
- 01 - No Poverty (1)
- 02 - Zero Hunger (1)
- 03 - Good Health and Well-being (8)
- 07 - Affordable and Clean Energy (1)
- 08 - Decent Work and Economic Growth (1)
- 09 - Industry, Innovation and Infrastructure (11)
- 11 - Sustainable Cities and Communities (2)
- 13 - Climate Action (2)
- 16 - Peace, Justice and Strong Institutions (1)
Publication year
- Between 2000 and 2024 (85)
- Unknown (1)