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This paper is motivated by two observations in the large civil aircraft (LCA) industry. (1) Boeing and Airbus are significantly different in the degree of offshoring. (2) The degree of offshoring also changes among different aircraft models. To offer an explanation, this paper focuses on issues related to fragmentation. Existing literature has established the tie between fragmented technology and offshoring. However, it is assumed that production can be fragmented readily and at no cost; and only exogenous global economic factors have impact on the degree of fragmentation. This model distinguishes itself from others by incorporating endogeneity in fragmentation. A final-good firm can spend on R&D specifically for its own fragmented technology. As a result, the final-good firm can optimally choose the portion of components to be offshored. A strategic trade policy model is used to show that the degree of offshoring depends on the firm's own cost of production, the host country's cost of production, the global state of technology as well as the government trade policies. In particular, export subsidy and subsidy on R&D of fragmented technology are shown to be policy substitutes. Keywords: Fragmentation; Offshoring; Outsourcing; Aircraft; Export subsidy; R&D subsidy; Boeing; Airbus JEL classification: F12; F13; F23; L13
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The adoption of project management techniques is a crucial decision for corporate governance in construction companies since the management of areas such as risk, cost, and communications is essential for the success or failure of an endeavor. Nevertheless, different frameworks based on traditional or agile methodologies are available with several approaches, which may create several ways to manage projects. The primary purpose of this work is to investigate the adequate project management methodology for the construction industry from a general perspective and consider a case study from Macau. The methodology considered semi-structured interviews and a survey comparing international and local project managers from the construction industry. The interviews indicate that most construction project managers still follow empirical methods with no specific methodology but consider the adoption of traditional waterfall approaches. In contrast, according to the survey, most project managers and construction managers agree that the project's efficacy needs to increase, namely in planning, waste minimization, communication increase, and focus on the Client's feedback. In addition, there seems to be a clear indication that agile methodology could be implemented in several types of projects, including hospitality development projects. A hybrid development approach based on the Waterfall and Agile methodologies as a tool for the project management area may provide a more suitable methodology for project managers to follow.
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The Guangdong-Hong Kong-Macau Greater Bay Area (GBA) was first conceptualized in 2016, which aimed to facilitate trade and finance liberalization among the three regions. The trade and financial environment of the GBA is unique. Due to the “one country, two systems” principle, Mainland China, Hong Kong and Macau are considered to be trading partners bounded by WTO rule, but bilateral free trade agreements have been signed between Mainland China and Hong Kong, and between Mainland China and Macau, but not between Hong Kong and Macau. Furthermore, each of the three regions circulates a local currency subject to its own exchange rate policy, with Hong Kong Dollar and Macau Pataca currently pegged to the US Dollar. These affect the mobility of trade and capital flows in the area. Hence, this paper applies the widely-used price-based approach due to Cheung et al. [5] to analyze the degrees of real and financial integration in the GBA based on interest rates, exchange rates, and price indexes data from January, 2016 to November, 2021. The real interest differential (RID), uncovered interest differential (UID) and the deviation from purchasing power parity (PPD) between each regional pair have means that are statistically and economically close to zero, implying high real and financial integration in the GBA. The unit root tests for stationarity also confirm that the time series are mean-reverting, so the economic integration in the GBA in the long run is foreseeable.
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The degree of economic integration in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), as reflected in the mobility of trade and capital flows, has been strengthened by free trade agreements, but obstacles including border effects, capital controls, differences of exchange rate systems and inadequate cross-regional coordination remain. Digital renminbi (e-CNY) has been tested in Shenzhen, a core GBA city since April 2020. If e-CNY is adopted in the GBA, the area will effectively become a single currency zone. Whether the GBA constitutes an “optimum currency area” (OCA) depends on its degree of economic integration. This paper computes real interest rate differential (RID), uncovered interest rate differential (UID) and deviation from purchasing power parity (PPD) of each regional pair based on data of interest rates, exchange rates and price indexes from 2016M2 to 2022M7. All UID, PPD and RID series have means within about 1 percent point from 0, indicating high degrees of financial integration, real integration and economic integration. With the exception of Guangdong-Macau RID, all series are stationary, implying mean-reverting behavior. Hence, the parities are expected to hold both in the short run and in the long run, which is a condition for an OCA in the GBA. Furthermore, the regression analysis finds that the test launch of e-CNY in Shenzhen (adjusted for the COVID-19 outbreak) has significant impacts on all RIDs, Guangdong-Macau PPD and Hong Kong-Macau PPD. With merely two and a half years of test launch, the introduction of e-CNY already had impacts on overall economic integration in the GBA.
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Battery electric vehicles (BEVs) are living up to their claims as consumers choose them more frequently. The increasing demand for sustainable vehicles translates into the global need for specific components, materials, and infrastructures and drives the regulatory frameworks in each country. While BEVs offer environmental benefits and global business opportunities, the technology has not yet gained mainstream acceptance. Thus, this work aims to investigate the characteristics of BEV users and their role in the diffusion of products to larger segments, as this may vary from country to country. For this purpose, a survey based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) (Venkatesh et al., 2012) framework and structural equation modeling (SmartPLS) was adopted. The results indicated that, except for the constructs of effort expectancy (EE) and social influence (SI), the predictors in the model performed well in this context. Current users are satisfied with their vehicles and are supportive of BEVs in the future. The analysis also revealed that in addition to the availability of financial resources, early adopters are attracted by new technologies in a way that leads them to make decisions outside of the traditional influence of the other members of society. It is suggested to leverage the perceived benefits of status, differentiation, or uniqueness motives, to appeal to those seeking to appear trendy and tech-savvy in society. Companies and policymakers should acknowledge the peculiarities of early customers in their communication strategies to reach a wider audience around the globe and encourage the adoption of BEV technology.
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info:eu-repo/semantics/publishedVersion
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This review article is among the first to examine the new junket regulations in the Macau gaming industry. Particular emphasis is on the legal and regulatory framework governing the junket activity of gaming promoters and their associates. The recent changes to Macau gaming laws have resulted in stronger licensing requirements for local junket participants and precipitated the collapse of the VIP room system in casinos. Furthermore, this article highlights the policy and managerial implications of the current junket environment for the gaming industry in Macau and possibly other regional gaming jurisdictions. The effects of the new legal environment for Macau junkets could also provide insights into the implementation of similar legislation in other jurisdictions.
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Crowdsensing exploits the sensing abilities offered by smart phones and users' mobility. Users can mutually help each other as a community with the aid of crowdsensing. The potential of crowdsensing has yet to be fully realized for improving public health. A protocol based on gamification to encoura...
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This study analyzes the green marketing strategies with specific reference to the hotel industry. The concept of green marketing in this sector is crucial due to the growing expected importance of tourism in the future of global economy and its potential impact on social and economic development; this is true particularly in areas with relevant volumes of tourist arrivals. In this sense, we carried out an exploratory research in the hotel industry of the Special Administrative Region (SAR) of Macao in order to: highlight the primary motivations that underlie interventions geared towards the eco-sustainability of hotels, the services they offer and point out the problems, issues, and future prospects in the development of green marketing, as well as explore the role of eco-sustainable values in hotels’ online communication policies. In order to reach these aims a qualitative research was carried out with a semi-structured questionnaire (face-to-face interviews) to a group of hotels. The research was finished by an analysis of their websites, in order to verify possible references to the steps taken to protect the environment.
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Objective: As a world tourist destination, Macao is inevitably under the impact of the COVID-19 pandemic. However, the market of integrated resorts in Macao are shared by only a few casino concessionaries, together forming an oligopoly. While the firms attempted to adjust price, quantity and quality of their hotel services in response to the pandemic, they could not overlook the strategic interactions with other players in the market. Hence, this paper aims to investigate the possible impact of the pandemic on the oligopolistic strategies in the integrated resort market in Macao. Methodology: Application of a theoretical model of differentiated oligopoly to this six-firm case shows that price differences across firms depend on their quality differentiation. In order to analyze these price differences empirically, this paper collects data of hotel room rates of the integrated resorts from November, 2019 to mid-August, 2020, covering the periods before and after the outbreak of COVID-19. Originality: In the existing literature, there is a lack of studies of the oligopoly in the hospitality industry of Macao. Furthermore, the effect of COVID-19 is still ongoing, so this present paper is one of the first to perform such analysis. Results: The regression of each of the hotel price differentials on the COVID-19 dummy variable shows that COVID-19 has statistically significant impacts on almost all the price differentials. Intuitively, MGM and Wynn were in the high-price segment before and after the outbreak, while other firms switched positions in the low-price segment during the pandemic. One obvious downstream movement was by Conrad. According to the proposition derived from the theory, these imply that COVID-19 should have significant impact on the quality differentiation of the firms. Practical implications: The results are in line with the observations that the integrated resorts have rolled out staycation packages according to preferences of local residents. These quality adjustments observed in Macao’s hospitality industry currently only involved variable inputs rather than fixed inputs of production; therefore, the impact of COVID-19 should be seen as short-term effects. Keywords: Covid-19; Differentiated oligopoly; Hospitality industry; Hotel room rate; Oligopolistic market structure; Pricing strategy.
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Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.
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The gold standard to detect SARS-CoV-2 infection considers testing methods based on Polymerase Chain Reaction (PCR). Still, the time necessary to confirm patient infection can be lengthy, and the process is expensive. In parallel, X-Ray and CT scans play an important role in the diagnosis and treatment processes. Hence, a trusted automated technique for identifying and quantifying the infected lung regions would be advantageous. Chest X-rays are two-dimensional images of the patient’s chest and provide lung morphological information and other characteristics, like ground-glass opacities (GGO), horizontal linear opacities, or consolidations, which are typical characteristics of pneumonia caused by COVID-19. This chapter presents an AI-based system using multiple Transfer Learning models for COVID-19 classification using Chest X-Rays. In our experimental design, all the classifiers demonstrated satisfactory accuracy, precision, recall, and specificity performance. On the one hand, the Mobilenet architecture outperformed the other CNNs, achieving excellent results for the evaluated metrics. On the other hand, Squeezenet presented a regular result in terms of recall. In medical diagnosis, false negatives can be particularly harmful because a false negative can lead to patients being incorrectly diagnosed as healthy. These results suggest that our Deep Learning classifiers can accurately classify X-ray exams as normal or indicative of COVID-19 with high confidence.
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Even with more than 12 billion vaccine doses administered globally, the Covid-19 pandemic has caused several global economic, social, environmental, and healthcare impacts. Computer Aided Diagnostic (CAD) systems can serve as a complementary method to aid doctors in identifying regions of interest in images and help detect diseases. In addition, these systems can help doctors analyze the status of the disease and check for their progress or regression. To analyze the viability of using CNNs for differentiating Covid-19 CT positive images from Covid-19 CT negative images, we used a dataset collected by Union Hospital (HUST-UH) and Liyuan Hospital (HUST-LH) and made available at the Kaggle platform. The main objective of this chapter is to present results from applying two state-of-the-art CNNs on a Covid-19 CT Scan images database to evaluate the possibility of differentiating images with imaging features associated with Covid-19 pneumonia from images with imaging features irrelevant to Covid-19 pneumonia. Two pre-trained neural networks, ResNet50 and MobileNet, were fine-tuned for the datasets under analysis. Both CNNs obtained promising results, with the ResNet50 network achieving a Precision of 0.97, a Recall of 0.96, an F1-score of 0.96, and 39 false negatives. The MobileNet classifier obtained a Precision of 0.94, a Recall of 0.94, an F1-score of 0.94, and a total of 20 false negatives.
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This paper starts to address the affect and side-effects of social media on people’s live in a pure contemplation perspective. Social networks are revised and some issues regarding its impact on education was not forgotten such as the teacher role in the digital classroom, formal versus informal learning or Web 2.0 tools use. Since Moodle is the first Learning Management System whilst Facebook is the first social network in the world, a survey was accomplished with two independent classes of e-business students at University of Saint Joseph, Macao, China, on their attitudes toward both online services in a learning framework. In general, the results confirms to a certain extent others previous studies on the question of whether using Facebook as an educational tool is more effective than Moodle.
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Molecular Chinese Medicine (MCM) is a recent method of manufacturing and dosing prescriptions that brings several advantages when compared with Traditional Chinese Medicine (TCM). For instance, MCM is highly dissoluble, tastes better than the usual decoction, and the active principles are easily absorbed. Also, the manufacturing process is subject to better quality control. In spite of these benefits, consumers' intentions remain unclear due to the novelty of this technique. Therefore, an assessment of individuals' perceptions is relevant since molecular medicine is redefining how scientists understand and treat diseases, and it can be considered a medical innovation. To fill the research gap, the Value-based Acceptance Model (VAM) (Kim et al., 2007) is used to assess the individuals' perceptions of value and intention to accept MCM. Data from a sample of Macau residents are analyzed by means of structural equation modeling (SmartPLS). The results support the use of the model in our context, thus extending the applicability of the VAM to other settings. Except for 'technicality', the constructs of 'usefulness', 'enjoyment', and 'perceived fee' had a significant impact on the overall 'perceived value' of MCM, and in turn on the behavioral intention to use the innovation. To facilitate the diffusion of this dosage method in the marketplace, it is suggested that communications strategies consider the proposed sources of value when promoting MCM. To further explain the adoption process, it is recommended to include additional factors that may affect consumers' intention to adopt the innovation and extend the analysis to the actual usage.
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University students in Macao are required to attend computer literacy courses to raise their basic skills levels and knowledge as part of their literacy foundation. Still, teachers frequently complain about the weak IT skills of many students, suggesting that most of them may not be benefiting sufficiently from their computer literacy courses. This research proposes an enhanced framework based on constructivist principles by using peer-tutoring to increase cost effectiveness and to improve student outcomes. Essential to this proposed model is the training of former course graduates as peer-instructors to achieve high quality learning results. At Instituto de Formação Turistica (IFT), a case study was used to evaluate its effectiveness using a qualitative analysis. In Macao, most students have a Confucian Heritage Cultural (CHC) background and the current findings demonstrate that students share more easily their learning difficulties within their group as their interpersonal relationships improve. It is suggested that since CHC cooperative learning is primarily based on bonds, students involved in this 'relationship-first, learning-second' type shared a larger amount of knowledge and social skills, a dual positive outcome. Moreover, English language is a major barrier for the understanding of the teacher’s message to Chinese students. Meanwhile, the negative Western concept of plagiarism is replaced, under the CHC, as the ‘face giving’ and it is directly based on the relationship intensity to 'help friends'. At last, peer-tutors play a key role in the student increase internal motivation regarding the joy of the learning process.
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