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The Black-Scholes equation is famous for predicting values for the prices of Options inside the stock market scenario. However, it has the limitation of depending on the estimated value for the volatility. On the other hand, several Machine learning techniques have been employed for predicting the values of the same quantity. In this paper we analyze some fundamental properties of the Black-Scholes equation and we then propose a way to train its free-parameters, the volatility in particular. This with the purpose of using this parameter as the fundamental one to be learned by a Machine Learning system and then improve the predictions in the stock market.

Digital inclusion in Macao is in the very beginning stage, and disability inclusion practice on social media in producing and promoting accessible social media content and needs is hard to find. This study aims to analyse the factors that influence communication staff's practice of disability inclusion on social media by using the combined employee behaviour and communication process model to provide suggestions to management who wants to promote disability inclusion practice on social media.The Service Centre for the Deaf of the Macau Deaf Association (MDA) was selected as the object for this case study. The online social media used for MDA's communication was analysed, and semi-structured in-depth interviews with members of the Association were conducted. The research findings showed that, except for the reward structure, factors examined from the work environment in terms of organisation, supervision and co-workers; communication staff themselves; outcomes of accessible social media communication; audience and feedbacks show relations with disability inclusion practices on social media. The delivery of inclusive culture, the influential power of disability stakeholders and the positioning of social media platforms are the key influencing factors.The interesting part of this study is that people without disabilities seem to be excluded from the disability inclusion practice carried out on MDA's Facebook. Their social media content is highly accessible to deaf and hard-of-hearing audiences yet seems not to involve the general public. The study object is a good model for producing accessible content, yet the optimisation of promoting social media accessibility needs further exploration.

This paper aimed to build up the theorical and conceptual understanding of future forecasting study of Macau’s GDP and Gross Gaming Revenue (GGR) by co-movement of economic indicators. Macau GDP and GGR showed co-movements with a number of time series economic indicators, including China’s exports and imports, China’s manufacturing PMI, non-manufacturing PMI, China's electricity production growth, share price of some Macau’s gaming operators, etc. These time series data can be found in statistics departments of China, Macau and Hong Kong, stock exchanges, and international organizations such as the International Monetary Fund (IMF), the World Bank, the World Trade Organization (WTO). Burns and Mitchell’s study in 1946 identified co-movements between economic indicators and being further carried out and developed leading, coincident and lagging indicators, which is essential for future econometric models and nowcasting techniques developments to study these co-movements. In particular, with the proper application of nowcasting techniques, future studies can exploit the data of leading and coincident economic indicators to forecast Macau’s GDP and GGR within an acceptable level of error. Since Macau is a “monotown,” where the gaming revenue makes a significant contribution to the economy. The forecasting of gaming revenue is crucial as it aids the gambling and tourism industries in preparing supply and provides information to policymakers to plan for the near future. This research also contributes to understand Macau’s economy by investigating its internal and external economic variables.

Human resources are essential to the survival, success, and long-term growth of a company. Hotel is an industry requiring a high level of human resources for delivering high-quality personal service to the hotel guests to maintain its competitiveness in the business environment. With the rapid economic growth in Macao started in 2002, all the industries have been growing fast and competing fiercely for the limited manpower in Macao. However, the Macao hotel industry has been losing its attractiveness in the Macao labor market and needs to rely on non-local workers with a limited stay in Macao. The management team of the Macao hotel industry is looking for a solution to maintain a stable workforce. Therefore, a study has been conducted on the effectiveness of its employee retention strategies. A questionnaire was designed to collect the preferences of the employees and interviews were conducted to understand the perspective of the management team toward the employee retention strategies. The study shows the employee strategies are focused on key employees’ interests such as career development and prospect. However, the communication between the management team and employees failed and led to employee turnover.

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.

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.

China growing awareness of sustainability has brought out relevant aspects to move towards a green environment. Since its subscription in 2016, China has been committed to implementing the Paris Agreement, and the Greater Bay Area (GBA) development plan prioritizes ecology and pursuing green development. The primary purpose of this research is to perceive the companies' insights concerning the implementation of sustainable buildings’ projects in Macau. For this multi-case study analysis, primary data was gathered from interviews with two groups involved in the construction projects’ lifecycle: Consultants and Contractors, to analyze different perceptions and concerns. The interviews considered two different themes about the main topic: (1) Perception on Companies’ Experience in Sustainable Projects; (2) Key Drivers towards Sustainable Buildings’ Projects’ Implementation. In conclusion, according to the analyzed data, it is essential to notice that companies’ background and the market particularities affect their corporate performance specially connected to the green construction frameworks. The data also indicate that it is necessary to move towards regulations and policies to change corporate and people's mindset.

Citizens' trust in eGovernment is crucial for the successful implementation of new electronic services. This relationship in the Greater Bay Area (GBA) plays an essential role since the Government services rely on mobile mini-programs This study investigates the trust towards government service mini-programs in WeChat and Alipay. A user feedback questionnaire was designed, and a total of 609 valid samples were collected from Shenzhen, Guangzhou, Hong Kong, and Macau. The findings imply that competence, integrity, and benevolence are the key components of trust in e-government (TIEG). TIEG positively influences perceived value (PV), which positively affects citizens' Intention to adopt service mini-programs. PV significantly mediates the relationship between TIEG and Intention. Although TIEG does not effectively reduce perceived risk (PR), risk issues cannot be ignored in the adoption process. Finally, this article proposes relevant implications and suggestions for the GBA government agents and policy makers.

The decision to accept and use technology innovations has long been a source of debate across disciplines due to the complexity involved in predicting behavior. Recognizing that the subject is vast and fragmented, this paper examines the mainstream technology works to assist researchers to understand, conceptualize and select the most appropriate theoretical framework for their study. Starting with the pioneering effort on Diffusion of Innovations (DOI/IDT), the analysis considers the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM/TAM-2/TAM-3), the Value-based Acceptance Model (VAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT/UTAUT-2) among the most important. A review of the key literature is vital to assessing and identifying research trends, as well as contributing to the discussion of emerging technologies such as Artificial Intelligence (AI), Augmented Reality (AR), Blockchain, Cloud Computing, Internet of Things (IoT), Mobile Apps, etc. Suggestions for future research paths are also provided.

The UTAUT-2 offers the most comprehensive assessment of individual acceptance and use of technology to date. In particular, the theoretical additions of “hedonic motivation”, “price value”, and “habit”, made the model suitable for studying technology in a consumer context. However, a review of the literature revealed that the construct of habit has been dropped from a large number of studies. There are several reasons for this, including that the technologies examined were relatively new for the respondents to form a routine behavior. Therefore, this study aims to explore whether the construct can be used as a key predictor of future intention to use an innovation rather than an acquired practice among technology users. For this purpose, a conceptual model based on the theoretical additions to the UTAUT-2 is proposed and analyzed with structural equation modeling (SmartPLS). Our results showed significant relationships between the predictors and the behavioral intention to use battery electric vehicles (BEV) technology, and, in particular, depicted the construct of habit as the strongest factor in the decision to adopt the technology. In light of our findings, the construct of habit (HT) should be used in research together with the other UTAUT-2 predictors to assess individuals’ perceptions of possible future habitual behaviors.

A growing number of people are becoming aware of the environmental footprint that our actions have on the environment. Research indicates that a key factor leading to the adoption of an electric vehicle is consumers’ high environmental concern. Indeed, the environmental concern (EC) construct is commonly associated with the purchase of sustainable and eco-friendly products in literature. Our study challenges this assumption. We examined how the environmental factor influenced the behavioral intention of Macau residents to adopt battery-electric vehicle (BEV) technology. For this purpose, we conducted a study based on the UTAUT-2 framework and used structural equation modeling (SmartPLS) to analyze the data. As a result, the choice of vehicles did not depend on the consumers’ level of concern. It appeared that consumers strongly perceived the benefits of a cleaner environment, however, when it comes to technology, environmental benefits are nice to have, rather than the primary incentive to purchase BEVs. Researchers should consider the role of environmental concern as a background factor in technology acceptance models, rather than a direct predictor of behavior. It is also recommended that marketers correctly consider this element when developing their product communications strategies, to appeal to the desired segment of customers.

Technology research offers several theories and models to explain how individuals accept and use technology innovations. While these often focus on the technical aspects of the innovation, they tend to downplay the affective component of technology. Recognizing that the adoption of technology is also determined by what it means and represents to the users, this paper aims to fill the gap in the literature by studying the effects of social influence and image on the behavioral intention to adopt a technology. We used structural equation modeling (SmartPLS) to analyze data collected from 238 self-administrated surveys regarding the behavioral intention of Macau residents to use battery electric vehicles. The result showed significant relationships among the variables in the model and depicted the construct of image as a strong factor in the adoption decision. Our findings suggest that social influence may not exhibit substantial impact in the case of innovations in their initial phase and, more importantly, the construct of image could be included as a key predictor of behavioral intention in technology acceptance models, particularly in contexts where the choices that consumers make are public, and therefore subject to judgments from the members of the community.

Despite the general good intentions towards the environment, individuals tend to adopt traditional internal combustion vehicles. Drawing from technology research, this study focuses on the impact of society - in the form of subjective norm and image – on the behavioral intention to adopt a technology. More precisely, this study seeks to explore to which extent societal influences drive the behavioral intention to adopt battery electric vehicles (BEV) technology. A self-administered survey was used for this purpose. The analysis of the data from a sample of 111 respondents showed significant relationships between the predictors and the target behavioral outcome. The study also revealed that subjective norm and image are particularly significant factors for the segment of BEV owners. The findings suggest that marketers and practitioners incorporate social elements into their product communication strategies in order to encourage the uptake of environmentally-sound technologies.

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.

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.

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.

Stock price prediction has always been challenging due to its volatility and unpredictability. This paper performs a preliminary exploratory comparison that utilizes Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) algorithms to forecast the stock market in Hong Kong. It considers a public dataset publicly available and uses feature engineering to extract relevant features. Then, LSTM and SVM algorithms are applied to predict stock prices. Our results show that the proposed machine learning techniques can predict stock prices in Hong Kong's share market with the error metrics presented, and, for this purpose, LSTM achieved better results than SVM, with MSE = 0.0026, RMSE = 0.0508, MAE = 0.0406, and MAPE = 1.325.

Neuromarketing lies at the intersection of three main disciplines: psychology, neuroscience, and marketing, and it has been a successful neuroscientific approach for the study of real-life choices such as consumer behavior [1]. A current gap in the cosmetics field is the lack of published research studies, considering the marketing investment done yearly in this category. With the rapid economic expansion and the rise of social media in China, consumers' interest in beauty is growing. Even though the Chinese cosmetics sector is rapidly expanding, no studies have been done with Chinese consumers. This study aims to employ the same approach as previously done in consumer neuroscience studies to evaluate cosmetic brands' marketing strategy to understand better if immediate emotional responses can be measured using Electrodermal Activity (EDA). Here, we focus on cosmetics products advertisement as a model to understand consumer preference formation and choice. Eighteen Chinese female consumers were recruited between 19 and 37 years old. From the results obtained, it was understood that none of the participants have voted for the product advertisement for which they showed higher emotional arousal. However, it appears that the participants' preference is for the products for which the brand awareness is stronger since the product advertisements with more votes are the ones for the Korean brand used. The product advertisements with Asian faces were the ones with more votes, suggesting that Asian faces have engaged consumer preference. However, the product advertisements for the Brazilian brands, unknown to the Chinese public, were the ones with fewer votes, although, those product advertisements were the ones with more emotional arousal per minute. Those advertisements were also those with non-Asian faces, suggesting that this feature influenced voting decisions. From this study, it has been observed that Electrodermal Activity is a measure of emotional arousal that by itself cannot be translated into consumer engagement. Therefore, it is also proposed to evaluate brand awareness in future studies related to product advertisements. The physical features of the people included in the advertisements is also suggested to be further evaluated in future studies since a different cultural background seems to influence the consumers' engagement. Furthermore, using EDA to complement other neurophysiological tools like facial expression analysis is also suggested for future studies to have evidence about the nature of the emotions raised.