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With the increasing number of tourists coming to Macau after the three years of lockdown period, more quality services are expected. However, organisations are now facing a big challenge in maintaining sufficient employee, managing their employees’ performance and productivity. Employee engagement plays an important role because it will not only affect individual performance but also the performance of an organisation. This is the first study to provide evidence of the engagement level of general employees working in Macau, and of its relationships with job autonomy, organisational justice and organisational culture. The study results revealed that the levels of vigour, dedication and absorption of employees working full time in Macau were slightly above the mid-point value 3 of the scale, with about 30% of employees were found less engaged or disengaged. Criteria autonomy, method autonomy, schedule autonomy, organisational justice and collectivism culture were positively and significantly correlated with all three dimensions of employee engagement (i.e. vigour, dedication and absorption). There is no significant negative relationship between power distance culture and employee engagement. Method autonomy was the strongest positive predictor of all three dimensions of employee engagement, followed by organisational justice, while collectivism culture was a positive predictor for vigour and absorption. The implications for management will be discussed in terms of organisational support and communication

The increasing contribution of Generation Z (Gen Z) to Macao’s economy may be the driving force behind the recent changes in Macao’s consumption patterns. This dissertation analyzes how consumption patterns of Macao’s Gen Z differ from other generations. To investigate the types of goods and services consumed, the shopping modes, and the factors that influence the consumption decisions of different generations of Macao, this study conducts a survey to collect primary quantitative data from 296 Macao residents. This study found that the most Macao residents consumed 21%-60% of their income, showing a balance between consumption and saving. They spent most on food and non-alcoholic beverages, healthcare, and education. In terms of receiving information about new products, many Macao consumers learned from family and friends and social media, such as the Red Book and TikTok. Electronic payments have become increasingly popular, such as the local payment system, MPay. The t tests for statistically significant differences show that Gen Z was more likely to make online purchases when buying beauty products and electronic devices than other generations. Compared to other generations, Gen Z was more concerned with the level of fun of the brand, impacts on the environment, society, and local community of the product, personal preference and research, and the recommendations of online reviewers, influencers, and salesperson. Based on the findings of this study, businesses can develop up-to-date marketing strategies to introduce their products to different generations in Macao

China’s economy has entered a critical period of structural adjustment. The developing green industries and the transforming traditional industries have increasing demand for finance, making ""green finance"" increasingly essential. While China's green finance is in the development stage, some newly developed zones serve as pilots for the launch of green financial products. An example is Tongzhou District of Beijing, which aims to expand Beijing’s space, promote the coordinated development of Beijing-Tianjin-Hebei, and explore the optimal development mode of the densely populated economic areas. This thesis aims to study consumer acceptance of green financial technology (fintech) in the case of Tongzhou District. This thesis extended the commonly applied theoretical model for the problem of study, the Energy Augmented Technology Acceptance Model (EA-TAM), to analyze the impacts of perceived usefulness, perceived ease of use, attitude toward use, intention, usage intention, environmental awareness, and green knowledge on the acceptance of green fintech in Tongzhou District. The survey collected 403 valid responses from people that had been active in Tongzhou District. The quantitative analysis is based on structural equation modeling techniques, including reliability analysis, validity analysis, standard method deviation test, and hypothesis testing. The analytical results show that all the hypothesized factors are significant. In addition, the sample is divided into different gender groups and education groups, so that the impacts of the socio-demographic characteristics can be explored. Males’ environmental awareness and green knowledge are insignificant in determining their acceptance of green fintech. The low-educated group’s acceptance of green fintech does not significantly depend on environmental awareness and perceived usefulness

Macau, Macau Business, MAG, MB, MB Featured, Opinion | Despite the welcome optimism expressed at the government’s plans to resurrect Macau’s economy, its economic recovery will continue to suffer from having had the rug pulled from under its feet by the zero-Covid policy, however well intentioned.

Small and medium-sized enterprises (SMEs) can benefit significantly from open innovation by gaining access to a broader range of resources and expertise using absorptive capacitive, and increasing their visibility and reputation. Nevertheless, multiple barriers impact their capacity to absorb new technologies or adapt to develop them. This paper aims to perform an analysis of relevant topics and trends in Open Innovation (OI) and Absorptive Capacity (AC) in SMEs based on a bibliometric review identifying relevant authors and countries, and highlighting significant research themes and trends. The defined string query is submitted to the Web of Science database, and the bibliometric analysis using VOSviewer software. The results indicate that the number of scientific publications has consistently increased during the past decade, indicating a growing interest of the scientific community, reflecting the industry interest and possibly adoption of OI, considering Absorptive. This bibliometric analysis can provide insights on the most relevant regions the research areas are under intensive development.

Nowadays, the increasing number of medical diagnostic data and clinical data provide more complementary references for doctors to make diagnosis to patients. For example, with medical data, such as electrocardiography (ECG), machine learning algorithms can be used to identify and diagnose heart disease to reduce the workload of doctors. However, ECG data is always exposed to various kinds of noise and interference in reality, and medical diagnostics only based on one-dimensional ECG data is not trustable enough. By extracting new features from other types of medical data, we can implement enhanced recognition methods, called multimodal learning. Multimodal learning helps models to process data from a range of different sources, eliminate the requirement for training each single learning modality, and improve the robustness of models with the diversity of data. Growing number of articles in recent years have been devoted to investigating how to extract data from different sources and build accurate multimodal machine learning models, or deep learning models for medical diagnostics. This paper reviews and summarizes several recent papers that dealing with multimodal machine learning in disease detection, and identify topics for future research.