Study of the Cross-Border Family Mediation Mechanisms and Practices in the Greater Bay Area (China, Hong Kong SAR, and Macau SAR”) - Wong, Hang Si (University of Saint Joseph, 2024)
The dissertation is about the study on the usage of mediation as the dispute mechanism on the cross-border family dispute issue in the Guangdong -Hong Kong- Macau Greater Bay Area through a comparative law aspects. Under the background of the Country’s Policy in integrating the citizens of the two SARs into China. The citizens of different provinces in PRC and the two SARs have frequent contact such as in business, in personal affairs and so on, the more the contact the more the possibility disputes will arise. With three different jurisdictions and the backlogs from the Courts, to find out the possibility of using another dispute resolution is essential. The study found out the perspectives of the disputed / litigated parties, courts and legal practitioners in usage of mediation, the nature of mediation in use in GBA and the strengths and limitations on the usage of mediation. This research used a mixed methods including doctrinal legal research, comparative legal research method and empirical legal research method. It result from the finding that though there is no specialized legislation in usage of mediation in Macau SAR, there is practice in usage of family mediation. Besides that the judicial mediation in PRC is not the mediation we defined in the literature review, thus it is the conciliation. Whether the recent development in Hong Kong SAR on the procedures M-FDR and M-CDR are in conflict with the facilitative mediation which has all along been practiced in Hong Kong SAR. In conclusion, the perspectives in usage of mediation in PRC and Hong Kong SAR are higher than Macau SAR and the nature of mediation in usage are different in the three jurisdictions. Lastly, in the dissertation provided some reflections on the development of family mediation mechanism in Macau SAR and how to merge the different natures of mediation in GBA
Keywords: ADR; Alternative Dispute Resolution; GBA; Greater Bay Area; Mediation; Mediation Mechanism; Thesis and Dissertations Master of Lusophone and International Public Law(MLIPL); University of Saint Joseph

INFLUENCE OF ORGANIZATIONAL CULTURE ON WORK ENGAGEMENT: A MEDIATING ROLE OF JOB SATISFACTION IN MACAU SIX GAMING CONCESSIONAIRES - Wong, Ka Son (University of Saint Joseph, 2024)
The Macau six gaming concessionaires are encouraged to diversify their business activities beyond the gaming sector to promote a more balanced economy in Macau. It is worth noting that a substantial portion of the workforce within these organizations is employed in non-gaming sectors. Unlike previous studies that primarily concentrated on the gaming sector, this study aims to assess the extent of work engagement among all employees, encompassing both gaming and non-gaming employees, within the six gaming concessionaires of Macau. It also aims to explore the correlation between organizational culture and work engagement, as well as the mediating role of job satisfaction in this relationship. The survey design utilized convenience and referral sampling methods to select the sample. A quantitative approach was employed, and data was collected through an online self-response questionnaire with a total of 396 participants. The study findings reveal a positive correlation among all variables, with a particularly strong relationship observed between supportive organizational culture and various aspects of work engagement. Notably, the mediating variable of job satisfaction, specifically the nature of work, had a more significant impact than the direct effect of organizational culture on emotional and physical work engagement. These findings suggest that organizations should prioritize the development of a supportive organizational culture to enhance work engagement. Furthermore, it is crucial to provide employees with motivating and meaningful work that gives them a sense of accomplishment upon completion. Future studies could explore the relationship between organizational culture and work engagement by examining two distinct employee groups, such as local employees and expatriates
Keywords: Job Satisfaction; Macau Gaming Concessionaires; Nature of Work; Organizational Culture; Thesis and Dissertations Master of Organisational Psychology (MOP); University of Saint Joseph; Work Engagement

Impact of green finance on Asian economic development - Wong, Kuan Lam (University of Saint Joseph, 2024)
The development of green financial products like green bonds and industry financing has gained momentum, showing positive impacts on sustainable economic development, renewable energy investment, and greenhouse gas emission reduction. As the research problem is inadequately explored, this dissertation aims to fill the research gap to evaluate the impacts of green finance on economic development. Furthermore, this study assesses the differences between Asian and non-Asian economies in the impacts of green finance on economic development. Two empirical measures are analyzed in this study.Green finance is measured with the Global Green Finance Index (GGFI), a composite index that captures over 100 instrumental variables, covering the business environment, human capital, infrastructure, and sustainability aspects of a financial center. Growth rate of gross domestic product (GDP) per capita reflects economic development. The dataset encompasses 83 international financial centers from 2018 to 2022. The regression model finds a significant negative relationship between growth rates of GGFI and GDP per capita in the full sample, the Asian subgroup, and the non-Asian subgroup. GGFI growth is confirmed to have Granger caused GDP per capita growth, but GDP per capita growth did not Granger cause GGFI growth. Combined with the insights of the previous studies, this study justifies the findings as a short-term negative impact of green finance on economic growth. However, the Asian region, with many emerging economies, could transition faster, so the regression derives a less negative coefficients for Asian financial centers. The policy implication 5 is that continued government support to improve the effectiveness of green finance is necessary for the long-term benefit of green finance to be fully realized
Keywords: Thesis and Dissertations Master of Government Studies (MGS); University of Saint Joseph

初任教師在融合教育中教學困擾及因應策略: 以澳門某三所私立學校的初任教師為例 = TEACHING CHALLENGES OF NOVICE TEACHERS AND COPING STRATEGIES IN INCLUSIVE EDUCATION: A STUDY OF NOVICE TEACHERS IN THREE PRIVATE SCHOOLS IN MACAO - Wong, Man U. (University of Saint Joseph, 2024)
Keywords: Thesis and Dissertations Master of Education (MED); University of Saint Joseph; 初任教師; 因應策略; 教學困擾; 融合教育

THE VALUATION OF WALMART INC - Wong, Nga Man (University of Saint Joseph, 2024)
A world-class retailer, Walmart Inc. (WMT) operates in multiple formats, including physical and online stores. Walmart began operations in 1962 and currently owns 10,616 merchandise units around the world. Most of Walmart's revenue comes from the United States segment, 17% from the Walmart International segment, and 14% from the Sam's Club segment. Walmart offers many products, such as groceries, consumables, general merchandise, and health products. With its marketing strategy of low-cost products, Walmart has successfully navigated through economic prosperity and recessions in different periods. However, there is still intense competition in the retail industry, so we will analyze the company's internal factors across the economic climate and external factors and see how the company positioned itself to adapt to the trends in the industry to achieve the current intrinsic value. Three valuation models have been completed to determine Walmart’s intrinsic value. We will then compare that figure with WMT's stock price at the end of fiscal year 2022, which will benefit investors by providing valuable reference information
Keywords: Master of Business Administration; THE VALUATION OF WALMART INC; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph; VALUATION; Walmart

澳門教師的情緒智力、幸福感與教學效能之相關研究 =: AN EXPLORATORY STUDY ON THE RELATIONSHIP OF MACAU TEACHERS’ EMOTIONAL INTELLIGENCE, SENSE OF WELL-BEING AND TEACHER SELF-EFFICACY - Wong, Pou I. (University of Saint Joseph, 2024)
Keywords: Thesis and Dissertations Master of Education (MED); University of Saint Joseph; 幸褔感; 情緒智力; 教學效能

兩晉之際中原統治集團和江南豪族合作之探討 =: A Discussion on the Cooperation Between The Ruling Group in Middle China and the Jiangnan Indigenous Families Between Western and Eastern Jin Dynasties - Wong, Seong I. (University of Saint Joseph, 2024)
Keywords: Thesis and Dissertations Master of History & Heritage Studies (MHHS); University of Saint Joseph; 僑姓士族; 合作; 晉室; 江南豪族

The Study of Social Support and Stress Among Gambling Industry Workers in Macau - Wong, Sut Ieng (University of Saint Joseph, 2024)
This research explores the dynamics of stress and social support among professionals in Macao's gambling industry during the COVID-19 pandemic. The economic impact of the pandemic, coupled with the border restrictions, has severely affected Macao's gaming industry, leading to a 70% decrease in gaming revenue and a significant increase in unemployment rates among residents. As a result, many employees have faced downsizing or unpaid leave, posing significant challenges to their daily lives and raising concerns about mental health within the community. To gain a deeper understanding of these changes and the experiences of residents, this research utilized phenomenology as the methodology, employing qualitative interviews. During the recruitment of interviewees, three scales (PSS, MSPSS, and DASS21) were used as screening tools to assess the mental status of participants, allowing for the identification of various combinations of mental states. Through in-depth interviews, significant findings emerged. It was observed that interventions aimed at enhancing social support had a remarkable impact on reducing daily life stress among the interviewees. This included interventions focused on marital relationships, digital communication support, and positive personal beliefs with encouragement. In conclusion, by recognizing and proactively responding to these insights, the industry can create an ecosystem where professionals not only achieve professional excellence but also maintain robust mental and emotional well-being. Future studies should focus on developing holistic support systems within the gaming industry
Keywords: Thesis and Dissertations Master of Social Work (MSW); University of Saint Joseph

Comparative study of the implementation of the National Security Law in the SARs: A Case study of Hong Kong SAR and Macao SAR - Wu, Ka Seng (University of Saint Joseph, 2024)
The aim of this study is comparing the jurisdiction of the National Security Law in Hong Kong SAR and Macau SAR, also reviewing the practical implementation of the law in the two SARs, analyzing the Chinese government's participation in the governance of national security in two SARs, and exploring the future sustainability of National Security Law in two SARs
Keywords: Hong Kong; Macao; National Security; National Security Law; Thesis and Dissertations Master of Lusophone and International Public Law(MLIPL); University of Saint Joseph

STRATEGIES FOR DEFINING AND RESOLVING NON-PERFORMING ASSETS IN STATE-OWNED CHINESE BANKS - Wu, Xiao (University of Saint Joseph, 2024)
Given the rapid growth of China's economy and its maturing financial market, state-owned banks have played a crucial role in driving national economic growth and ensuring financial stability. However, this progress has been accompanied by a pressing challenge - the accumulation of non-performing assets (NPAs), which pose significant obstacles to both the banking industry and China's economic development. Therefore, it is imperative to comprehensively analyze strategies aimed at mitigating NPAs in state-owned commercial banks, with an emphasis on seeking more effective resolution mechanisms. This study delves into the institutional environment surrounding NPAs in state-owned banks, including improvements in laws and regulations as well as advancements in financial market structures and legal frameworks. The initial step involves analyzing the current status and manifestations of NPAs within state-owned banks to clarify their ambiguously defined areas. Furthermore, considering China's unique policy context and socio-economic landscape, this study conducts an analysis and comparison of diverse strategies for addressing NPAs from the perspectives of asset quality management, risk-profit equilibrium, and legal regulatory support system. Ultimately, several suggestions are proposed regarding the trajectory of NPA resolution
Keywords: Bank; NPA; NPL; Risk management; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph

A Study of Tesla's Marketing Strategy in the Chinese Market - Xian Wenhao (University of Saint Joseph, 2024)
This study assesses Tesla's marketing strategies and their effectiveness in the Chinese market. Given Tesla's leading position in the global electric vehicle sector and the importance of the Chinese market, this study aims to analyze in-depth how Tesla has succeeded in China with its unique marketing tactics, and to suggest improvements to enhance its competitiveness. By utilizing analytical tools such as PEST, Porter's Five Forces Model, SWOT, and STP, this study comprehensively evaluates Tesla's marketing environment and thoroughly analyzes its marketing mix of products, prices, channels, promotions, etc., combined with consumer feedback and market research data. The study reveals that the key factors for Tesla's success include innovative design, unique branding, effective marketing strategies and digital marketing applications. Nevertheless, Tesla still needs to face the challenges of localization, pricing strategy, channel adjustment and promotion innovation. In order to maintain its leading position, Tesla should continue to innovate, strengthen its localization strategy, improve service quality, and adapt to policy changes. The optimization suggestions proposed in this study will help Tesla overcome challenges and achieve sustained growth, and they will also provide valuable references for other new energy vehicle companies
Keywords: China; Marketing evaluation; Marketing strategy; Tesla; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph

The Role of the Country-of-Origin Effect in Driving Chinese EV Adoption: The Case of Portugal - Xian, Sitong; Lampo, Alessandro (PROCEEDINGS OF THE 18th INTERNATIONAL CONFERENCE OF THE AGBRP, 2024)
As environmental awareness grows, sustainable modes of transportation have garnered increasing importance. With the rising popularity of electric vehicles (EVs), a broader community now acknowledges their numerous advantages, such as lower noise levels, enhanced efficiency, and cost-effectiveness in comparison to traditional internal combustion engine vehicles. Furthermore, EVs significantly contribute to a more sustainable future by emitting fewer pollutants and reducing overall environmental impact. However, consumers' perceptions and expectations about the vehicle's country of origin - the nation where the vehicle is manufactured - remain unclear, particularly in the case of Chinese-manufactured EVs due to China's reputation for pollution and product safety concerns. This study employsa qualitative framework based on the Unified Theory of Acceptance and Use of Technology 2(UTAUT-2) to assess the acceptance of Chinese electric vehicles, and the influence of the Country-of-Origin Effect (COE) on a sample of Portuguese residents. Data was gathered through semi-structured interviews and analyzed using qualitative methods. The study's results shed light on the significance of the country of origin in shaping consumers' behavioral intentions to purchase Chinese electric vehicles, indicating a positive influence. This suggests that country of origin is a crucial factor when considering an individual's intention to adopt electric vehicles. Additionally, the research highlights the importance of various other factors such as performance expectancy, effort expectancy, social influence, facilitating conditions, price value, hedonic motivation, and habit in shaping consumers' attitudes and intentions. Our results underscore the complexity of consumer behavior toward electric vehicles, suggesting the need for a multifaceted approach to understanding andpromoting EV adoption. Research is needed to examine the COE in different cultural and geographic contexts to develop effective strategies to enhance the global adoption of electric vehicles, particularly from countries with varying environmental reputations

EFFCT OF EMPLOYEE PERFORMANCE MANAGEMENT ON EMPLOYEE INCENTIVE: A CASE STUDY OF N COMPANY - Xie, Yue Na (University of Saint Joseph, 2024)
With the comprehensive opening of the global economy, the intensification of market competition and the increasingly prominent value of human resources, all trades and professions are facing unprecedented challenges. In order to remain competitive in the market, human resource management plays an increasingly important role. As an important part of human resource management, enterprise performance management can be used as a key tool to drive the release of employees' potential, which has attracted more and more attention from enterprises. More and more performance management-related systems have been introduced into enterprises. However, in the system introduction and implementation process, there are different degrees of problems, such as ""mechanically copied"" and ""process"". Therefore, according to the specific situation of different enterprises, it is necessary to formulate the corresponding performance management system to maximize the role of motivating employees. This paper explores enterprise performance management's influence on the employee incentive effect. The implementation of enterprise performance management and its influence on employee incentive are analyzed through the literature review, case analysis and empirical analysis. Research has found that effective enterprise performance management can significantly improve the work enthusiasm and satisfaction of employees, thus enhancing the overall performance of enterprises and promoting all-round development. At the same time, this paper also discusses the key factors affecting the incentive effect of enterprise performance management, and puts forward the corresponding optimization suggestions
Keywords: TCA; Theses and Dissertations Master of Business Administration (MBA); University of Saint Joseph; performace management; performance incentive

FLOWING PATH: SPORTS CENTER AS SOCIAL CONNECTOR - Xin, Ziyan (University of Saint Joseph, 2024)
In the age of the information society, the prominence of internet communication and social media has meant that the role of face-to-face encounters in public life has been diminished. This trend has been exacerbated by public health concerns in the aftermath of the COVID pandemic. The social role of architecture and its contribution to the sustainability of interpersonal relationships has become a significant issue for architects. As a place to accommodate sporting activities and social space in the community, sports centers play an important role in promoting social cohesion and interaction. This is the focal topic of the present thesis. The principal tasks of this thesis are as follows: (1) This thesis collects and studies relevant literature on sports centers as social spaces. A special emphasis is placed on discussions of social spaces. The intention is to articulate design characteristics of community sports centers that merit further exploration. (2) This thesis selects three representative sports facilities as case studies and considers how they promote the formation of social bonds and interactions. The thesis offers a review of design ideas, planning strategies and specific methods of implementation. (3) This thesis takes the design project for a sports center in New District A in Macau as an example, and puts forward a design strategy of ""vertical intensification + shared application"". This strategy aims to promote the integration of the sports center with the urban environment, while creating a flexible public space that can adapt to the needs of spontaneous and social activities. The intention is to make the sports center a place that promotes community interaction and connectivity. Overall, this thesis argues that community sports centers can become important places to promote social interaction through well-designed architectural space. Specific design factors and strategies explored in this thesis provide useful points of reference for architects. Through on-going processes of optimization and innovation, sports centers can better serve the community of Macau
Keywords: Circulation strategies in architecture; Theses and Dissertations Master of Architecture (MARCH); University of Saint Joseph; integrated sports facilities; social connectors; sports centers

FACTORS INFLUENCING BRAND IMAGE AND BEHAVIOR OF CONSUMERS OF THE XIAMEN MARATHON - Xu Teng (University of Saint Joseph, 2024)
Many sports events have been reopened since the recovery from the global Covid19 epidemic. As countries work toward the third sustainable development goal of good health and well-being, sports events have received increasing support and investments. This study focuses on the Xiamen Marathon, which had reached the platinum level of sustainable development and is a benchmark marathon race in China. To assess the factors that influence the brand image and behavior of consumers of the Xiamen Marathon, this dissertation references the conceptual models in previous studies and hypothesizes that experience, brand image, loyalty, satisfaction, motivation, organization, quality, and trust are the direct influencing factors of brand image and indirect determinants of word of mouth, sport, and behavioral intention. This study surveyed participants of the Xiamen Marathon in 2024 and collected data from a sample of 285 participants. All the respondents were local residents and over 90% were contestants. The largest proportions were 36-to-55-year-old, married, highly educated, and employed, earning monthly income between ¥5000 to ¥15000 and spending over ¥1000 on marathon equipment. IBM SPSS and Amos were used for the quantitative analysis based on structural equation modeling techniques, including reliability test, validity test, and hypothesis testing. The questionnaire quality was good, the scale data were suitable for factor analysis, and the questionnaire data fitted well. However, quality and trust were excluded due to low significance. The results show that experience, loyalty, satisfaction, motivation, and organization have significant and positive impacts on brand image, which in turn has significant and positive impacts word of mouth, sport, and behavioral intention. The results support the eight hypotheses of direct effects and the 15 hypotheses of intermediate effects
Keywords: Brand experience; Brand image; Brand loyalty; China; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph

IMPACTS OF CARBON TRADING SYSTEM ON GREEN FINANCE: Ziyan Yin - Yin, Ziyan (University of Saint Joseph, 2024)
Against the backdrop of escalating global climate change and China being the world’s largest carbon emitter, this study explores the impact of the carbon trading system on green finance in Chinese power sector. This study uses a quantitative research method, namely a difference-in-differences (DID) model, to investigate power companies that participated or had the potential to participate in carbon trading in 2019 and 2022. The key finding is that companies that participated in carbon trading had significantly higher green finance than those that did not participate, indicating that the carbon trading system has a positive impact on promoting green finance. However, the impact does not significantly intensify after the national carbon trading scheme was implemented in mid-2021. The green finance of listed companies and state-owned enterprises were less affected by carbon trading, possibly because these companies rely on alternative financing options and government financial support. Due to the findings, this study recommends that policy makers should strengthen the promotion of the carbon trading scheme and provide more support for non-listed companies and non-state-owned enterprises. At the same time, the companies should actively participate in the carbon market to take advantage of the industrial policies to enhance green finance, and ultimately promote environmental protection and their own sustainable development
Keywords: Carbon trading scheme; Carbon trading system; China; DiD; Difference-in-difference; Green finance; Power companies; Power plants; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph

Study on Influencing Factors of University Students' entrepreneurial Intention: Greater Bay Area as an example - Yu, Yuan Bao (University of Saint Joseph, 2024)
Keywords: Macro level; Micro level; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph; college student; entrepreneurial Intention; entrepreneurship

Exploring Interactive Wearable: Enhancing Emotional Release and Expression in Modern Fashion Design - Zhai, Jingwen (University of Saint Joseph, 2024)
As technology evolves swiftly and consumers call for more customization, the study of interactive fashion design is increasingly emerging as a key topic within the fashion industry. The goal of this research is to investigate merging intelligent technology with apparel design, realizing functional enlargements and enriching the user experience by employing interactive design. Initially, this document examines key theories and ongoing studies in interaction design, intelligent textiles, and wearable tech, pinpointing the current research voids and difficulties. This section then presents a range of methodologies used in the study, encompassing literature review, case analysis, and interviews with experts, to thoroughly analyze and assess all facets of interactive apparel design. This document suggests a methodical design of interactive clothing, outlining the entire process from initial design to the creation of prototypes. The practicality and efficiency of the design methodology are proven by creating prototypes and conducting trials. Findings from the experiments indicate that interactive attire offers substantial benefits in terms of functionality, comfort, and user experience. The research offers both theoretical backing and pragmatic advice for designing interactive attire, while also highlighting paths for upcoming advancements in fashion technology. In conclusion, the document examines the shortcomings of the existing research and potential research paths, aiming to offer valuable guidance for advancing the development of clothing styling and wearable tech
Keywords: Fashion design; Thesis and Dissertations Master of Design (MDG); University of Saint Joseph; clothing interactive devices; emotion and perception; emotional user experience; interactive design

EXPERIENCING THE PRESENT AND EXPLORING THE FUTURE WITH IMMERSIVE TECHNOLOGIES CASE STUDY: " ST. LAZARUS CHURCH PEDESTRIAN STREET", MACAU - Zhou RenWei (University of Saint Joseph, 2024)
In the present world, many cities have historical and culturally rich districts, but protectionism or economic reasons have slowed their development. Therefore, how to generate more value for these areas is crucial for a city with a deep and complex history. Using immersive virtual reality technology can help solve this problem, and this paper takes Macau's famous historical district as an entry point and starts from the perspective of the general public to explore and design some of the existing buildings and public areas in the district. The focus of this study is to explore the future development possibilities of historical and cultural districts in cities and experience the current situation of the district. Specifically, by studying the historical background and human investigation of ST. LAZARUS CHURCH PEDESTRIAN STREET (Chinese official name: 疯堂斜巷), the study uses immersive virtual reality technology to first create a scene of the existing building group in the district as a stage of protection for historical buildings. Then, it creates and presents a future building group scene in the district, which includes completed buildings and public area facilities after renovation and sustainable design. This renovation does not destroy the protected historical buildings at all, but is a protective exploration. The researchers used 3D computer graphics software (Blender) and virtual tour software (Kuula) to create the design, and users can freely explore the scene by ""walking"" virtually. The design includes two groups of architectural scenes of the ST. LAZARUS CHURCH PEDESTRIAN STREET in the present and the future. After entering the scene, users can freely switch between the present and the future time points to experience the different architectural scene atmospheres. Users can enter some buildings and public areas, and interact with objects in the scene to generate visual or auditory introductions to the target. Users can see the rough outline of the future historical and cultural district after the protective development in the free exploration of the virtual reality environment, which can inspire further public thinking about the development of historical and cultural street areas in the city. Users can explore and experience the project using professional virtual reality equipment or directly on the web. By using immersive virtual reality technology, the public can have a more intuitive and comprehensive understanding of the future development of historical and cultural street areas, and urban planners, professional architects, and clients of architectural design can all benefit from this technology, especially in the initial conceptual design and prototype design of buildings
Keywords: Conservation of historical building; Exploratory design; Reconstruction of historic district; Thesis and Dissertations Master of Design (MDG); University of Saint Joseph; Virtual reality technology

基模教學對百分比問題之程序流暢程度的有效性研究 =: EFFECTIVENESS OF SCHEMA-BASED INSTRUCTION (SBI) ON PROCEDURAL FLUENCY WITH PERCENTAGES PROBLEMS - Zhou, Mingyan (University of Saint Joseph, 2024)
Research suggested that students struggle because of lacking understanding of basic concepts, formulas, and procedures in algebra, leading to inefficiency in logical thinking and problem-solving skills. (Julius et al., 2018; Jupri et al., 2021). Schemabased instruction (SBI) aims to enhance learning and problem-solving by activating and building upon students' prior knowledge structures, known as schemas (Powell et al., 2008). The common schemas include the total, difference, change, equal groups, comparison, ratios/proportions (Hughes & Cuevas, 2020). SBI has been found to be effective, particularly for students who struggle with mathematics word problems (Marshall, 2012; Hughes & Cuevas, 2020). Research related to SBI has not yet been conducted in Macau region. An early pre-test was administered by the researcher, thirty-one students were asked to solve 10 questions about percentages. The results showed that some students lacked the fundamental knowledge needed to investigate and explore the abstract ideas, patterns, and relationships in percentages problems. A daily schema-based instruction (SBI) as a part of an experimental intervention study was implemented, pre-test and post-tests were administered to investigate the effect of SBI on students' mathematical procedural fluency skills. Thirty-one students from the researcher’s class were invited to engaged in 40 minutes of daily SBI lessons for two weeks, 12 lessons in total. During each of the twelve 40-minute session, students practiced schemas to develop procedural fluency competencies, such as solid number sense and arithmetic operations, to solve percentages problems. Within-group descriptive and inferential statistics were adopted. The results indicated that after SBI, students can solve mathematical problems with greater procedural fluency. This research shares implications and provides suggestions regarding SBI and procedural fluency
Keywords: SBI; Thesis and Dissertations Master of Education (MED); University of Saint Joseph; mathematics; percentages problems; procedural fluency; schema-based instruction; secondary education

Factors Affecting Customer Satisfaction for Fitness Club: A Case Study of Noble Fitness Club in Zhongshan - Zhu, Junwen (University of Saint Joseph, 2024)
This paper selects Noble Fitness Club in Zhongshan as a research object, adopting a qualitative method and conducting in-depth interviews with its members to determine what factors affect customers’ choice of a fitness club. This study is important because it enriches the theoretical guidance framework of the fitness market. Moreover, it helps partitioners from the fitness industry realize what factors directly impact customer satisfaction, providing recommendations for them to foster sustainable development. In-depth interviewing is the primary method for data collection. And, the thematic content analysis (TCA) approach is used to analyze the data derived from interview transcripts. Existing research identified eight factors affecting customers’ choice of a fitness club. However, the author discovered three additional factors that also significantly influenced their selection of a fitness club: geographical location, group courses, and fitness atmosphere. The fitness industry has an issue of product homogenization. Attracting more customers while retaining existing members is a challenge many fitness clubs face nowadays. Therefore, operators should avoid engaging in a price war, reducing the profit margin to attract more customers at the expense of sacrificing service quality. Instead, they should prioritize customers’ practical needs and make the best effort to meet their expectations
Keywords: Case Study; Customer Satisfaction; Fitness Club; Thesis and Dissertations Master of Business Administration (MBA); University of Saint Joseph

The Impact of Personal Characteristics of Successors in Chinese Family Firms on Succession Based on Thematic Content Analysis - Zou, Zhuoneng; Phillips, Jenny O. L. (Proceedings of the SSEME Workshop on Economics and Management (SSEME-EM 2024), 2024)
Series Title: Advances in Economics, Business and Management Research

Exploring the learning effectiveness under the "formative assessment" reform of non-tertiary education in Macao: A Case Study =探討澳門非高等教育改革「形成性評核」下的學習成效－個案研究 - 何愛琴 (University of Saint Joseph, 2024)
Keywords: Thesis and Dissertations Master of Education (MED); University of Saint Joseph; 個案研究; 學習成效; 形成性評核; 教育改革

Teacher's Teaching Style and the Learning Attitude of Elementary School Students: A Macau Case Study = 小學生學習態度與教師教學風格現況之研究—以澳門某小學為例 - 洪麗 (University of Saint Joseph, 2024)
Keywords: Learning Attitude; Macau; Primary School; Teacher's Teaching Style; Thesis and Dissertations Master of Education (MED); University of Saint Joseph

基于价格检验的粤港澳大湾区经济一体化实证研究 - CNKI [Empirical Study on the Economic Integration of the Guangdong-Hong Kong-Macao Greater Bay Area Based on Price Assessment] - 王心如; 李颖芝 (产业创新研究, 2024)

探討澳門普通小學教師在融合教育背景下的工作相關壓力及有效應對策略 =: Exploring Work-Related Stress and Effective Coping Strategies in the Context of Inclusive Education Among Mainstream Primary Teachers in Macau - 黃家敏 (University of Saint Joseph, 2024)
Since 2006, the Government of Macau has been promoting inclusive education. This has now been ongoing for seventeen years. As education policies gradually improve, the focus has shifted from students in inclusive settings to the realm of teachers. With an increasing number of inclusive students, the corresponding work pressures faced by teachers has also increased. The aims of this study are to better understand the work-related stress, sources of stress, and subsequent coping strategies used by mainstreamteachers within the inclusive education sector of Macau. This study used qualitative research methods, interviewing twelve frontline teachers from eight different private primary educational institutions. Eight of these teachers work in schools practicing inclusive education, while four were employed in regular schools. However, all twelve participating teachers had experience in teaching inclusive students but also lacked any specialized background in special education. Following and obtaining and meticulously analyzing interview data, supported by relevant literature, the study findings are presented as follows: 1. Views and Attitudes of Regular Teachers in Inclusive Schools towards Inclusive Education The interviewed teachers support the concept of inclusive education but were concerned about student behaviors and their learning challenges. These concerns included inappropriate behaviors, learning disabilities, and the teachers’ own pedagogical demands. In managing student behaviors, teachers found it difficult to handle the emotional control of inclusive students, leading to disruptions in class. Regarding learning, teachers had to use additional and extra time on after-class tutoring, increasing their workload. Teaching inclusive students also complicated the instruction, requiring teachers to undergo additional training and preparation. 2. Work-Related Stress and its Sources among Regular Teachers within Inclusive Schools The participating teachers rated their stress-resilience as not low, but rather they experienced medium to high levels of work-related stress, mainly due to long working hours and extensive workloads. The study identifies four main sources of stress: （i） The nature of work, including extensive teaching and non-teaching tasks, including heavy class management, or multiple roles. （ii） Social relationships, where regular teachers lacked an understanding of resource teachers’ roles, leading to ineffective communication and an underutilization of resource teachers in schools. （iii） Organizational structure, where schools involved in inclusive education required improvements in facilities and teaching environments, particularly in the safety of sports areas. Additionally, not all mainstream teachers had access to inclusive education resources, and the instructional adjustments for inclusive students did not fully meet their needs. （iv） Social aspects, where the public did not fully understand the concepts of inclusive education, and expectations on teachers were excessively high. Furthermore, teachers were dissatisfied with their salaries and benefits, which they felt were not commensurate with their heavy workload. The study also found that female teachers faced additional stress from both work and family responsibilities, as they also bear the burden of caring for and educating their own children at home. 3. Responses and Coping Methods of Regular Teachers in Inclusive Schools to Work-Related Stress The study analyzed the negative impacts of work-related stress on teachers’ physical health, psychological state, and behavior. The impacts included poor sleep quality or insomnia and emotional states of worry and anxiety. In response to stress, teachers engaged in communication and social activities, exercise and rest, and dietary adjustments. However, these stress-relief methods did not effectively address the root causes of the stress, making long-term stress management a crucial issue for teachers. Based on the findings regarding stress perceptions, sources, and coping methods, the researcher proposes recommendations for teachers, educational institutions, and relevant government departments, with an aim to support and aid future policymaking in the area of inclusive education in Macau
Keywords: Thesis and Dissertations Master of Education (MED); University of Saint Joseph; 小學; 工作壓力; 應對策略; 普通教師; 融合教育

澳門普通小學教師職業幸福感：: 現況、影響因素及提升策略 = THE OCCUPATIONAL WELL-BEING OF MACAU PRIMARY SCHOOL TEACHERS：CURRENT STATUS, INFLUENCING FACTORS, AND ENHANCEMENT STRATEGIES - 黎嘉穎 (University of Saint Joseph, 2024)
Keywords: Thesis and Dissertations Master of Education (MED); University of Saint Joseph; 教師; 澳門小學; 職業幸福感

The Effect of Empathy on Relationship Satisfaction in Young Adult Lovers in Macau: The Role of Love Maintenance Behaviors - 黎志濠 (University of Saint Joseph, 2024)
The purpose of this study was to explore the correlation between empathy, love maintenance behaviors, relationship satisfaction in a convenience sample of young adult lovers in Macau. Participants were N = 183 (84 males, 99 females) recruited from the social media platform (e.g. Instagram, WeChat, Facebook). Firstly, young adult lovers who tended to have high relationship satisfaction and empathy are tended to use positive love maintenance behaviors but less likely to use negative love maintenance behaviors. Besides, there were differences found by gender in empathy (affective empathy & total empathy), some dimensions of positive love maintenance behaviors (openness & advice), and negative love maintenance behaviors (causing jealousy, destructive conflict & negative love maintenance behaviors in general). Lastly, the findings in this study supported the hypotheses that love maintenance behaviors mediated the relationship between relationship satisfaction and empathy among young adult lovers in Macau. It was revealed that there was higher satisfaction in younger adult lovers in younger group (18-24 years) compared to older groups (32-40 years). For empathy, it correlated positively with relationship satisfaction and most positive love maintenance behaviors, but also with certain negative love maintenance behaviors. Positive love maintenance behaviors mediate the relationship between relationship satisfaction and empathy, highlighting their critical role in maintaining healthy relationships
Keywords: Love maintenance behaviors; Thesis and Dissertations Master of Couselling and Psychotherapy (MCP); University of Saint Joseph; empathy; relationship satisfaction

Revenue Management in Airlines and External Factors Affecting Decisions: The Harmonic Oscillator Model - Arraut, Ivan; Rosado, Wilson; Leong, Victor (Mathematics, 2024)
The Revenue Management (RM) problem in airlines for a fixed capacity, single resource and two classes has been solved before by using a standard formalism. In this paper we propose a model for RM by using the semi-classical approach of the Quantum Harmonic Oscillator. We then extend the model to include external factors affecting the people’s decisions, particularly those where collective decisions emerge.
Number: 6 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: collective decisions; harmonic oscillator; revenue management; spontaneous symmetry breaking

Diffusion of Technologies: Delivering on the Promises of Battery Electric Vehicles - Lampo, Alessandro; Silva, Susana C. (Walking the Talk? MNEs Transitioning Towards a Sustainable World, 2024)
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.
Keywords: Air quality; Battery electric vehicles; Clean energy technology; Consumer behavior; Diffusion of innovations; Early adopters; International marketing

Machine learning-based cardiac activity non-linear analysis for discriminating COVID-19 patients with different degrees of severity - Ribeiro, Pedro; Marques, João Alexandre Lobo; Pordeus, Daniel; Zacarias, Laíla; Leite, Camila Ferreira; Sobreira-Neto, Manoel Alves; Peixoto, Arnaldo Aires; de Oliveira, Adriel; Madeiro, João Paulo do Vale; Rodrigues, Pedro Miguel (Biomedical Signal Processing and Control, 2024)
Objective: This study highlights the potential of an Electrocardiogram (ECG) as a powerful tool for early diagnosis of COVID-19 in critically ill patients with limited access to CT–Scan rooms. Methods: In this investigation, 3 categories of patient status were considered: Low, Moderate, and Severe. For each patient, 2 different body positions have been used to collect 2 ECG signals. Then, from each collected signal, 10 non-linear features (Energy, Approximate Entropy, Logarithmic Entropy, Shannon Entropy, Hurst Exponent, Lyapunov Exponent, Higuchi Fractal Dimension, Katz Fractal Dimension, Correlation Dimension and Detrended Fluctuation Analysis) were extracted every 1s ECG time-series length to serve as entries for 19 Machine learning classifiers within a leave-one-out cross-validation procedure. Four different classification scenarios were tested: Low vs. Moderate, Low vs. Severe, Moderate vs. Severe and one Multi-class comparison (All vs. All). Results: The classification report results were: (1) Low vs. Moderate - 100% of Accuracy and 100% of F1–Score; (2) Low vs. Severe - Accuracy of 91.67% and an F1–Score of 94.92%; (3) Moderate vs. Severe - Accuracy of 94.12% and an F1–Score of 96.43%; and (4) All vs All - 78.57% of Accuracy and 84.75% of F1–Score. Conclusion: The results indicate that the applied methodology could be considered a good tool for distinguishing COVID-19’s different severity stages using ECG signals. Significance: The findings highlight the potential of ECG as a fast and effective tool for COVID-19 examination. In comparison to previous studies using the same database, this study shows a 7.57% improvement in diagnostic accuracy for the All vs All comparison.
Keywords: Accuracy; COVID-19; ECG signals; Machine learning classifiers; Non-linear analysis; –

Relationships among critical thinking disposition components of Chinese undergraduates: A moderated mediating effect analysis - Zhao, Yangyintao; Liu, Yong; Wu, Hao (International Journal of Educational Research, 2024)
Critical thinking (CT), as a form of higher-order thinking, is intended to help individuals form reasonable reflection and judgment to deal with increasingly severe employment situations. As the primary workforce in the labor market, undergraduates must possess a strong critical thinking disposition (CTD) to make better use of CT. Despite extensive research on components of CTD from the perspective of educational practices, there is limited emphasis on investigating the components and their relationships of CTD in the labor market and the impact of gender differences. Therefore, this study presented an analysis of 1535 Chinese undergraduates (Mage = 20.89; SD = 1.43) using the Employer-Employee-Supported Critical Thinking Disposition Inventory (2ES-CTDI), aiming to explore the CTD that undergraduates should possess before entering the labor market. The relationships among the components were examined using SmartPLS4.0 in conjunction with Partial Least Squares Structural Equation Modeling (PLS-SEM). Additionally, a multigroup analysis (PLS-MGA) with a measurement invariance (MI) test was conducted to validate the moderating effects of gender. The findings indicate that (a) self-efficacy has a significant negative effect on habitual truth-digging, and boys are more affected than girls, instant judgment plays a competitive partial mediating role in this relationship; (b) self-efficacy has a significant positive effect on instant judgment, and boys are more likely to make instant judgments than girls; (c) instant judgment significantly positively affects habitual truth-digging. These findings highlight the dynamic equilibrium among the internal components of CTD in the labor market and call for increased attention from educators to the importance of gender differences in the cultivation process.
Keywords: Critical thinking disposition; Labor Market; Moderated mediation; Undergraduates

Impact of Education on Green Fintech Adoption in a Smart City: Evidence from the Newly Developed Sub-city Center of Beijing. - Lei, Weng Chi; An, Boyang (2024)
Integrating financial technologies with green initiatives is critical to the sustainable development agenda. This is particularly true for newly developed smart cities like Tongzhou, the sub-city center of Beijing. To assess the adoption of green fintech in Tongzhou, this paper extends the EnergyAugmented Technology Acceptance Model (EA-TAM) to incorporate two green factors – environmental awareness and green knowledge. This paper applies structural equation modeling techniques to analyze data from 403 respondents who live, work, or study in Tongzhou and finds allhypothesized constructs significant. Since green knowledge is significant to the adoption of green fintech, this paper further divides the sample into a high-education group (162 respondents with university-or-above degrees) and a low-education group (251 respondents with post-secondary-orlower degrees) to evaluate the impact of education. All the hypothesized factors are significant to the high-education group,but environmental awareness and perceived usefulness are insignificant to the low- education group. Hence, the results provide evidence that people in the newly developed smart city adopt green fintech due to their environmental sensitivity. The adoption of green fintech is more environmentally sensitive for people with high education levels.

Enforcement of arbitral awards in Macau - Diakite, Ansoumane Douty (LexisNexis, 2024)
Under Macau Arbitration Law (MAL, art 64.1), an award shall be made in writing and shall be signed by the arbitrator or arbitrators. Furthermore, the law provides that in case of arbitral proceedings with more than one arbitrator, the signatures of the majority of all members of the arbitral tribunal shall suffice, provided that the reason for any omitted signature is stated (MAL, art 64.2).
Publisher: LexisNexis

ECG Forecasting System Based on Long Short-Term Memory - Zacarias, Henriques; Marques, João Alexandre Lôbo; Felizardo, Virginie; Pourvahab, Mehran; Garcia, Nuno M. (Bioengineering, 2024)
Worldwide, cardiovascular diseases are some of the primary causes of death; yet the early detection and diagnosis of such diseases have the potential to save many lives. Technological means of detection are becoming increasingly essential and numerous techniques have been created for this purpose, such as forecasting. Of these techniques, the time series forecasting technique seeks to predict future events. The long-term time series forecasting of physiological data could assist medical professionals in predicting and treating patients based on very early diagnosis. This article presents a model that utilizes a deep learning technique to predict long-term ECG signals. The forecasting model can learn signals’ nonlinearity, nonstationarity, and complexity based on a long short-term memory architecture. However, this is not a trivial task as the correct forecasting of a signal that closely resembles the original complex signal’s structure and behavior while minimizing any differences in amplitude continues to pose challenges. To achieve this goal, we used a dataset available on the Physio net database, called MIT-BIH, with 48 ECG recordings of 30 min each. The developed model starts with pre-processing to reduce interference in the original signals, then applies a deep learning algorithm, based on a long short-term memory (LTSM) neural network with two hidden layers. Next, we applied the root mean square error (RMSE) and mean absolute error (MAE) metrics to evaluate the performance of the model and obtained an average RMSE of 0.0070±0.0028 and an average MAE of 0.0522±0.0098 across all simulations. The results indicate that the proposed LSTM model is a promising technique for ECG forecasting, considering the trends of the changes in the original data series, most notably in R-peak amplitude. Given the model’s accuracy and the features of the physiological signals, the system could be used to improve existing predictive healthcare systems for cardiovascular monitoring.
Publisher: MDPI AG

Mini-programs in mobile payment to access eGovernment in China’s Greater Bay Area - exploring the determinants and mechanism from self-determination and motivation theory - Patrick, Lai ChiMeng; Lobo Marques, Joao Alexandre (Cogent Social Sciences, 2024)
Government service mini-programs (GSMPs) in mobile payment have become integral to the eGovernment in China’s Greater Bay Area (GBA). The ubiquitous nature of WeChat and Alipay provides excellent flexibility for accessing public e-services. Yet, the determinants and mechanisms of adoption have not been identified. A convenience sample was collected from GBA core cities for statistical and SEM analysis. The findings suggest that service quality, trust in eGovernment, ubiquity, and social influence constitute the determinants. A structural model grounded on Self-Determination and Motivation theory is verified, where perceived value and intention contribute a high explanatory power. Benevolence, integrity, and competence are crucial indicators of trust, while social influence amplifies risk perception. Surprisingly, government support negatively moderates the impact of determinants on intention, indicating that over-intervention leads to inhibition. The mechanism illustrates the beneficial impact of GSMPs as the smart government channel and provides insights into addressing service homogeneity and policy applicability. Relevant theoretical and managerial implications are instructive to policymakers and practitioners of smart city innovation and in-depth integration in GBA.
Publisher: Informa UK Limited

Life Is not a Walk across a Field - Morrison, Keith (2024)

Stock market prediction using artificial intelligence: A systematic review of systematic reviews - Lin, Chin Yang; Lobo Marques, Joao Alexandre (Social Sciences & Humanities Open, 2024)
There are many systematic reviews on predicting stock. However, each reveals a different portion of the hybrid AI analysis and stock prediction puzzle. The principal objective of this research was to systematically review the existing systematic reviews on Artificial Intelligence (AI) models applied to stock market prediction to provide valuable inputs for the development of strategies in stock market investments. Keywords that would fall under the broad headings of AI and stock prediction were looked up in Scopus and Web of Science databases. We screened 69 titles and read 43 systematic reviews, including more than 379 studies, before retaining 10 for the final dataset. This work revealed that support vector machines (SVM), long short-term memory (LSTM), and artificial neural networks (ANN) are the most popular AI methods for stock market prediction. In addition, the time series of historical closing stock prices are the most commonly used data source, and accuracy is the most employed performance metric of the predictive models. We also identified several research gaps and directions for future studies. Specifically, we indicate that future research could benefit from exploring different data sources and combinations, while we also suggest comparing different AI methods and techniques, as each may have specific advantages and applicable scenarios. Lastly, we recommend better evaluating different prediction indicators and standards to reflect prediction models’ actual value and impact.
Publisher: Elsevier BV

Fintech Adoption: A Study of Users in the Guangdong-Macao In-Depth Cooperation Zone in Hengqin (China) - Weng, Chi Lei; Lampo, Alessandro (INTI JOURNAL, 2024)
Intended as an economic and development hub, the Hengqin Cooperation Zone aims to foster collaboration and integration between mainland China, Hong Kong, and Macao, serving as a platform for economic development and innovation among the three regions. The zone's development has increased demand for financial services, often offered through fintech. There is, however, a lack of interoperability between the fintech services currently used in Macao and Hengqin. This may hinder Macao users' adoption of the technology. Thus, our research objective is to identify the factors determining Macao residents' adoption of fintech services in the area and provide insights for service providers, developers, and policymakers. A framework based on the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) was used for this purpose. The responses of 103 Macao residents provided evidence that ease of use significantly and positively impacts the usefulness of the technology. This in turn influences attitudes towards fintech usage. Subjective norms and perceived behavioral control positively impact fintech adoption intentions. The fintech industry and the governments of Macao and Hengqin can work on improving technology's ease of use and usefulness. They can also promote them to Macao users, and provide the resources required for better access to fintech in the zone
Number: 02 Publisher: INTI International University

Alignment, fitness for purpose, and fidelity in planning, conducting, and reporting research - Morrison, Keith (2024)

Hawking Radiation as a Manifestation of Spontaneous Symmetry Breaking - Arraut, Ivan (Symmetry, 2024)
We demonstrate that black hole evaporation can be modeled as a process where one symmetry of the system is spontaneously broken continuously. We then identify three free parameters of the system. The sign of one of the free parameters governs whether the particles emitted by the black hole are fermions or bosons. The present model explains why the black hole evaporation process is so universal. Interestingly, this universality emerges naturally inside certain modifications of gravity.
Number: 5 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Hawking radiation; black holes; spontaneous symmetry breaking

Digital and Sustainable Trade Facilitation in Western Balkans Countries - Toshevska-Trpchevska, Katerina; Lei, Weng Chi (Florence); Stojkoski, Viktor (European Scientific Journal, ESJ, 2024)
After the Covid-19 Pandemic crisis in international economic relations it became evident that climate-smart aspects should be considered when re-establishing a new international trade order. International organizations have proclaimed that this momentum should be used to include climate-smart trade and investment provisions to enable sustainable development. It has been acknowledged that trade has an important role to play in the global response to climate change, providing economies with tools to draw on in their efforts to mitigate climate change and to adapt to its consequences. In this paper we focus the analysis on investigating the digital and sustainable component of trade facilitation measures applied in Western Balkans countries. To evaluate the importance of trade facilitation measures and their digital and sustainable components we apply standard gravity model with the data from UN Global Survey on digital and sustainable trade facilitation. The results show that trade facilitation measures are important for improving and increasing trade among the Western Balkans countries. Especially, measures connected to improving transparency procedures in trade and measures for alleviating trade formalities are most significant for increasing bilateral trade among Western Balkans countries. With a lower level of importance are the measures for improving cross-border paperless trade between these countries.
Keywords: Digital and sustainable trade facilitation; UN Global Survey on Digital and Sustainable Trade Facilitation; Western Balkans countries; gravity model

Remote Learning's Impact on Students' Cognitive Development: Evidence from Time Series Assessment [Conference presentation] - Wu, Hao; Molnár, Gyöngyvér (2024)
Remote Learning's Impact on Students' Cognitive Development: Evidence from Time Series Assessment [Conference presentation]

The neutrino mass: A triangular formulation - Arraut, Ivan (arXiv.org, 2024)
We demonstrate that the flavor oscillation when a neutrino travels through spacetime, is equivalent to permanent changes on the vacuum state condition perceived by the same particle. This can be visualized via the Quantum Yang Baxter equations (QYBE). From this perspective, the neutrino never breaks the symmetry of the ground state because it never selects an specific vacuum condition. Then naturally the Higgs mechanism cannot be the generator of the neutrino masses. The constraints emerging from this model predict a normal mass hierarchy and some specific values for the mass eigenvalues once we fix the mixing angles. Interestingly, the model suggests that the sum of the mix angles is equal to $\pi/2$.

Once More with Feeling: The Debate Over Yalta Resurrected [Concluding Remarks] - Roberts, Priscilla (H-Diplo State of the Field Roundtable on the Eastern European Settlements during the Second World War: Making the Peace Amidst the War, 2024)

Automl-Based Eeg Signal Analysis in Neuro-Marketing Classification Using Biclustering Method - Albuquerque, Victor; Gois, Francisco Bernardo; Lobo Marques, Joao Alexandre; Silva, Bruno Riccelli dos Santos; Cortez, Paulo Cesar (2024)
Consumer neuroscience analyzes individuals’ preferences through the assessment of physiological data monitoring, considering brain activity or other bioinformation to assess purchase decisions. Traditional marketing tactics include customer surveys, product evaluations, and comments. For product or brand marketing and mass production, it is important to understand consumer neurological responses when seeing an ad or testing a product. In this work, we use the bi-clustering method to reduce EEG noise and automatic machine learning to classify brain responses. We analyze a neuromarketing EEG dataset that contains EEG data from product evaluations from 25 participants, collected with a 14 channel Emotiv Epoch + device, while examining consumer items. Four components comprised the research methodology. Initially, the Welch Transform was used to filter the EEG raw data. Second, the best converted signal biclusterings are used to train different classification models. Each biclustering is evaluated with a separate classifier, considering F1-Score. After that, the H2O.ai AutoML library is used to select the optimal biclustering and models. Instead of traditional procedures, two thresholds are used. First-threshold values indicate customer satisfaction. Low values of the second threshold reflect consumer dissatisfaction. Values between the first and second criteria are classified as uncertain values. We outperform the state of the art with a 0.95 F1-Score value.
Publisher: Elsevier BV

Teaching and learning with older adults: Research ethics, risk analysis, and covert research - Ní Bhroin, Áine; Morrison, Keith (Educational Gerontology, 2024)
This article reports a case study of older adults learning English in China. It indicates how, founded on consequentialist ethics, risk analysis, and safeguarding, it was decided to use covert research, drawing on the confluence of risk analysis, risk evaluation, risk management, safeguarding, research ethics, and important contextual and cultural features. Ethical principles of nonmaleficence, beneficence, safeguarding, and protection were addressed, and account was taken of the strength, likelihood, and consequences of risks, safeguards, and benefits, informed by Chinese cultural contexts, values, behaviors, and features of teaching and learning based on andragogy and geragogy. Implications are drawn for teaching and learning with older adults, advocating significant account to be taken of contextual factors.
Publisher: Routledge _eprint: https://doi.org/10.1080/03601277.2024.2377872

Integration of Blockchain Technology in Auditing Practices - Bibliometric Analysis - Almeida, Ermelinda Nazaré António de; Lobo Marques, Joao Alexandre (Proceedings of the 2024 15th International Conference on E-business, Management and Economics, 2024)
The potential of blockchain technology extends beyond cryptocurrencies and has the power to transform various sectors, including accounting and auditing. Its integration into auditing practices presents opportunities and challenges, and auditors must navigate new standards and engage with clients effectively. Blockchain technology provides tamper-proof record-keeping and fraud prevention, enhancing efficiency, transparency, and security in domains such as finance, insurance, healthcare, education, e-voting, and supply chain management. This paper conducts a bibliometric analysis of blockchain technology literature to gain insights into the current state and future directions of blockchain technology in auditing. The study identifies significant research themes and trends using keyword and citation analysis. The Vosviewer software was used to analyze the data and visualize the results. Findings reveal significant growth in blockchain research, particularly from 2021 onwards, with China emerging as a leading contributor, followed by the USA, India, and the UK. This study provides valuable insights into current trends, key contributors, and global patterns in blockchain technology research within auditing practices, and future research may explore thematic areas in greater depth.
Publisher: ACM

Emotion Detection from EEG Signals Using Machine Deep Learning Models - Fernandes, João Vitor Marques Rabelo; Alexandria, Auzuir Ripardo de; Lobo Marques, Joao Alexandre; Assis, Débora Ferreira de; Motta, Pedro Crosara; Silva, Bruno Riccelli dos Santos (Bioengineering, 2024)
Detecting emotions is a growing field aiming to comprehend and interpret human emotions from various data sources, including text, voice, and physiological signals. Electroencephalogram (EEG) is a unique and promising approach among these sources. EEG is a non-invasive monitoring technique that records the brain’s electrical activity through electrodes placed on the scalp’s surface. It is used in clinical and research contexts to explore how the human brain responds to emotions and cognitive stimuli. Recently, its use has gained interest in real-time emotion detection, offering a direct approach independent of facial expressions or voice. This is particularly useful in resource-limited scenarios, such as brain–computer interfaces supporting mental health. The objective of this work is to evaluate the classification of emotions (positive, negative, and neutral) in EEG signals using machine learning and deep learning, focusing on Graph Convolutional Neural Networks (GCNN), based on the analysis of critical attributes of the EEG signal (Differential Entropy (DE), Power Spectral Density (PSD), Differential Asymmetry (DASM), Rational Asymmetry (RASM), Asymmetry (ASM), Differential Causality (DCAU)). The electroencephalography dataset used in the research was the public SEED dataset (SJTU Emotion EEG Dataset), obtained through auditory and visual stimuli in segments from Chinese emotional movies. The experiment employed to evaluate the model results was “subject-dependent”. In this method, the Deep Neural Network (DNN) achieved an accuracy of 86.08%, surpassing SVM, albeit with significant processing time due to the optimization characteristics inherent to the algorithm. The GCNN algorithm achieved an average accuracy of 89.97% in the subject-dependent experiment. This work contributes to emotion detection in EEG, emphasizing the effectiveness of different models and underscoring the importance of selecting appropriate features and the ethical use of these technologies in practical applications. The GCNN emerges as the most promising methodology for future research.
Publisher: MDPI AG

Examining How "Technology Show-off" Affects the Acceptance of Innovations in the Battery Electric Vehicle Sector. - Lampo, Alessandro (Proceedings of the 2024 6th International Conference on Management Science and Industrial Engineering, 2024)
Theories and models try to describe the complexity of how people embrace and make use of innovations. The determinants of behavior concerning battery electric vehicles (BEVs) have traditionally revolved around factors such as vehicles’ price and range. Surprisingly, despite being small and one of the wealthiest territories in the world, Macau SAR faces challenges in BEV market penetration, underscoring the need to explore alternative causes of behavioral intention. To explain the adoption of technologies, this paper focuses on technology show-off (TS), which combines Rogers’ (2003) concepts of visibility and trialability of technology in a single construct as a determinant of behavioral intention. Therefore, when individuals perceive technology as more visible and available for trial, their behavioral intention to adopt it strengthens. Using structural equation modeling for quantitative analysis, this study examines the significance of TS in terms of the intention to adopt battery electric vehicles. The findings highlight the salience of the technology show-off construct in explaining behavioral intention, underscoring its significance in the context of modern society’s characteristics. This study contributes to advances in understanding technology acceptance and highlights the importance of incorporating experiential aspects (such as TS) into the traditional technology acceptance models.

Comparing Online Learning Experiences Between University Students With and Without Special Educational Needs During COVID-19 - Lim, Yun Ting; Nah, Yong-Hwee; Chen, Mo (ISSN: 2758-0962 The Paris Conference on Education 2024: Official Conference Proceedings, 2024)
The aim of this study is to examine the online learning experiences of university students with Special Educational Needs (SEN), and how their experiences might differ from their typically developing peers. Fifty typically developing students (mean age = 22; 29 females) and 31 students with SEN (mean age = 22; 15 females) from a local

Order parameter conditions from mutual information and symmetry conditions - Arraut, Ivan; Yu, Wing Chi (International Journal of Modern Physics B, 2024)
The mutual information method has demonstrated to be very useful for deriving the potential order parameter of a system. Although the method suggests some constraints which help to define this quantity, there is still some freedom in the definition. The method then results inefficient for cases where we have order parameters with a large number of constants in the expansion, which happens when we have many degenerate vacuums. Here, we introduce some additional constraints based on the existence of broken symmetries, which help us to reduce the arbitrariness in the definitions of the order parameter in the proposed mutual information method.
Publisher: World Scientific Publishing Co.
Keywords: Mutual information; order parameter; quantum phase transitions; spontaneous symmetry breaking

Understanding Policy Acceptance Through UTAUT-2: The Case of the Northbound Travel Policy for Macau Vehicles - Lampo, Alessandro; Diakite, Ansoumane D.; Ip, Emil C. H. (Journal of Global Business Research and Practice, 2024)

The cosmological constant emerging from a symmetry invariant - Arraut, Ivan (Modern Physics Letters A, 2024)
The cosmological constant is normally introduced as an additional term entering the Einstein–Hilbert (EH) action. In this letter, we demonstrate that, instead, it appears naturally from the standard EH action as an invariant term emerging from spacetime symmetries. We then demonstrate that the same constraint emerging from this invariant suppresses the short wavelength modes and it favors the long wavelength ones. In this way, inside the proposed formulation, the observed value for the vacuum energy density is obtained naturally from the zero-point quantum fluctuations.
Publisher: World Scientific Publishing Co.
Keywords: Dark energy; cosmological constant; zero point quantum fluctuations

Changing professional identities: a qualitative study of how Singapore allied educators managed their own resistance to change - Kit, Phey Ling; Ow Yeong, Wai Mang Elizabeth; Chen, Mo (Teacher Development, 2024)

Neutrino oscillations from the perspective of the quantum Yang-Baxter equations - Arraut, Ivan; Arrieta-Diaz, Enrique (arXiv, 2024)
The origins of neutrino masses is one of the biggest mysteries in modern physics since they are beyond the realm of the Standard Model. As massive particles, neutrinos undergo flavor oscillations throughout their propagation. In this paper we show that when a neutrino oscillates from a flavor state {\alpha} to a flavor state \b{eta}, it follows three possible paths consistent with the Quantum Yang- Baxter Equations. These trajectories define the transition probabilities of the oscillations. Moreover, we define a probability matrix for flavor transitions consistent with the Quantum Yang-Baxter Equations, and estimate the values of the three neutrino mass eigenvalues within the framework of the triangular formulation.
arXiv:2409.00560 [hep-ph]
Keywords: High Energy Physics - Phenomenology

Determining the relationships of employee resilience and organizational culture with levels of employee work engagement - Kuok, Angus; Taormina, Robert (2024)
The objective is to assess whether the extent to which employee resilience and organizational culture would be significantly related to and statistically predict the three facets of employee work engagement. Resilience was measured by four facets (Determination, Endurance, Adaptability, and Recuperability); and Organization Culture was measured for three types (Bureaucratic, Innovative, and Supportive). The dependent measures were the three facets of Work Engagement (Cognitive, Emotional, and Physical). This research by questionnaire was conducted in 2023. The questionnaires completed by 316 full-time workers revealed that all four facets of employee resilience had significant positive correlations with all three types of work engagement. Also, all three facets of work engagement were significantly higher in Innovative and Supportive cultures compared to Bureaucratic cultures. The regression analyses performed showed that the resilience factors of Determination and Adaptability were strong positive predictors of all three facets of work engagement. Furthermore, Innovative culture had additional positive effects on all three facets of work engagement; while Supportive culture had an additional positive effect on Emotional Work Engagement. The implications of the results for management are also discussed in this paper.

Predicting consumer ad preferences: Leveraging a machinelearning approach for EDA and FEA neurophysiologicalmetrics - Lobo Marques, Joao Alexandre; Neto, Andreia C.; Silva, Susana C.; Bigne, Enrique (Psychology & Marketing, 2024)
Abstract This research unveils to predict consumer ad preferences by detecting seven basic emotions, attention and engagement triggered by advertising through the analysis of two specific physiological monitoring tools, electrodermal activity (EDA), and Facial Expression Analysis (FEA), applied to video advertising, offering a twofold contribution of significant value. First, to identify the most relevant physiological features for consumer preference prediction. We integrated a statistical module encompassing inferential and exploratory analysis tools, which identified emotions such as Joy, Disgust, and Surprise, enabling the statistical differentiation of preferences concerning various advertisements. Second, we present an artificial intelligence (AI) system founded on machine learning techniques, encompassing k‐Nearest Neighbors, Support Vector Machine, and Random Forest (RF). Our findings show that the RF technique emerged as the top performer, boasting an 81% Accuracy, 84% Precision, 79% Recall, and an F1‐score of 81% in predicting consumer preferences. In addition, our research proposes an eXplainable AI module based on feature importance, which discerned Attention, Engagement, Joy, and Disgust as the four most pivotal features influencing consumer ad preference prediction. The results indicate that computerized intelligent systems based on EDA and FEA data can be used to predict consumer ad preferences based on videos and effectively used as supporting tools for marketing specialists.
Publisher: Wiley

Trust in AI and Top Management Support in Generative-AI Adoption - Korzyński, Paweł; Silva, Susana Costa E; Górska, Anna Maria; Mazurek, Grzegorz (Journal of Computer Information Systems, 2024)

Analysis of deep learning algorithms for emotion classification based on facial expression recognition - Qian, Cheng; Lobo Marques, Joao Alexandre; Fong, Simon James (Proceedings of the 2024 8th International Conference on Big Data and Internet of Things, 2024)
Facial expression recognition (FER) is essential for discerning human emotions and is applied extensively in big data analytics, healthcare, security, and user experience enhancement. This paper presents an empirical study that evaluates four existing deep learning models—VGG16, DenseNet, ResNet50, and GoogLeNet—utilizing the Facial Expression Recognition 2013 (FER2013) dataset. The dataset contains seven distinct emotional expressions: angry, disgust, fear, happy, neutral, sad, and surprise. Each model underwent rigorous assessment based on metrics including test accuracy, training duration, and weight file size to test their effectiveness in FER tasks. ResNet50 emerged as the top performer with a test accuracy of 69.46%, leveraging its residual learning architecture to effectively address challenges inherent in training deep neural networks. Conversely, GoogLeNet exhibited the lowest test accuracy among the models, suggesting potential architectural constraints in FER applications. VGG16, while competitive in accuracy, demonstrated lengthier training times and a larger weight file size (512MB), highlighting the inherent balance between model complexity and computational efficiency.
Publisher: ACM

Enhancing Dynamic Hand Gesture Recognition through Optimized Feature Selection using Double Machine Learning - Yan, Keyue; Lam, Chi Fai; Fong, Simon; Lobo Marques, Joao Alexandre; Song, Qun; Qin, Huafeng (Proceedings of the 2024 8th International Conference on Big Data and Internet of Things, 2024)
Publisher: ACM

Post-Covid-19 Gender Inequality in Global Employment: A Difference-In-Difference Analysis - Lei, Weng Chi (Atlantis Press, 2024)
The fifth Sustainable Development Goal of the United Nations targets achieving gender equality by 2030, but recent progress has been sluggish. Gender inequalities in the labor markets may have been exacerbated by the Covid-19 recession. This paper aims to investigate the effects of the Covid-19 pandemic on gender inequalities in the labor markets by...
ISSN: 2352-5398

Understanding the dynamics of customer satisfaction and repurchase intentions in the era of platform service supply chain – a case study of Foodpanda in Pakistan - Choudhary, Waliha; Waqar Haider, Syed; Raza, Aamir; Silva, Susana C.; Carmo Dias, Joana (Journal of Foodservice Business Research, 2024)

Assessment of the post-acute COVID-19 syndrome cardiovascular effect through ECG analysis - Ribeiro, Pedro; de Souza, Clarice Cristina Cunha; Camerino, Cristine Mayara Cavalcante; Pordeus, Daniel; Leite, Camila Ferreira; Lobo Marques, Joao Alexandre; Madeiro, João Paulo; Rodrigues, Pedro Miguel (2024)
Introduction: SARS-CoV-2, a virus responsible for the emergence of the life-threatening disease known as COVID-19, exhibits a diverse range of clinical manifestations. The spectrum of symptoms varies widely, encompassing mild to severe presentations, while a considerable portion of the population remains asymptomatic. COVID-19, primarily a respiratory virus, has been linked to cardiovascular complications in some patients. Notably, cardiac issues can also arise after recovery, contributing to post-acute COVID-19 syndrome, a significant concern for patient health. The present study intends to evaluate the post-acute COVID-19 syndrome cardiovascular effect through ECG by comparing patients affected with cardiac diseases without COVID-19 diagnosis report (class 1) and patients with cardiac pathologies who present post-acute COVID-19 syndrome (class 2). Methods: From 2 body positions, a total of 10 non-linear features, extracted every 1 second under a multi-band analysis performed by Discrete Wavelet Transform (DWT), have been compressed by 6 statistical metrics to serve as inputs for an individual feature analysis by the means of Mann-Whitney U-test and XROC classification. Results and Discussion: 480 Mann-Whitney U-test statistical analyses and XROC discrimination approaches have been done. The percentage of statistical analysis with significant differences (p<0.05) was 30.42% (146 out of 480). The best overall results were obtained by approximating the feature Energy, with the data compressor Kurtosis in the body position Down. Those results were 83.33% of Accuracy, 83.33% of Sensitivity, 83.33% of Specificity and 87.50% of AUC. Conclusions: The results show that the applied methodology can be a way to show changes in cardiac behaviour provoked by post-acute COVID-19 syndrome.

Sharing towards cohesive community: the role of social capital in sharing economy - Lai, Michael (ResearchGate, 2024)
PDF | Purpose Whilst the majority of academic studies have focused on the for-profit business-to-consumer type of sharing economy, the community-based... | Find, read and cite all the research you need on ResearchGate

Impact of Education on Green Fintech Adoption: Evidence From the New Sub-Center of Beijing - Lei, Weng Chi; An, Boyang (Journal of Global Business Research and Practice, 2024)

Habermas, Honneth, Critical Theory, and Ideology Critique for Transformative Mixed Methods Research - Morrison, Keith (Journal of Mixed Methods Studies, 2024)
This article sets a theoretical foundation to transformative mixed methods research that is rooted in the critical theory of Habermas and Honneth. This addresses Habermas’s knowledge-constitutive interests and communicative action for redressing societal pathologies, and Honneth’s work on (mis)recognition, (dis)respect, and social justice. In doing so, the article argues for broadening the scope and embrace of mixed methods research, to go beyond being empirical research only or largely, and to include theorisation, critical theoretical discourse and its analysis, and ideology critique, as legitimate methods for (transformative) mixed methods research. The article makes a case for these methods as constituting important research methods in themselves in the portfolio of mixed methods research, moving the boundaries of mixed methods research beyond solely empirical studies, and providing emancipatory lenses and consciousness-raising in recognising that transformation takes many forms.

Beyond the myth: understanding women's impulsive retail footwear shopping - Duarte, Paulo; Silva, Susana C.; Magro, Margarida; Dias, Joana Carmo (International Journal of Retail & Distribution Management, 2024)
This research focuses on common misconceptions about the factors driving women to purchase footwear impulsively. Its primary objective is to explore how emotional and social triggers specifically influence women's purchasing decisions, contrasting with the traditionally rational consumer models.,An online questionnaire was administered to a sample of women, yielding 199 useable responses.,The findings reveal the key determinants of women's impulsive retail footwear purchases, which include self-regulation, hedonic motivations and the influence of the retail store environment. This research challenges the prevailing assumption that women's passion for shopping is driven solely by inherent characteristics and suggests that external factors substantially shape their impulsive buying behaviour. In summary, the stereotypical portrayal of women as compulsive retail footwear shoppers may result more from external stimuli and environmental factors rather than an intrinsic trait.,This study improves the existing knowledge of women’s impulsive buying behaviour by unveiling the determinants of women's impulsive footwear purchases and assessing whether prevailing stereotypes hold true.
Publisher: Emerald Publishing Limited

Using Machine Learning CART Decision Trees for Predicting the Causes of Delays in Projects from the Construction Industry - Lobo Marques, Joao Alexandre; Chun, Fung Ka; Riccelli, Bruno (2024)
Construction projects are complex endeavours, with potential obstacles that can cause delays which can have particularly profound implications potentially impacting on company's financial health, business continuity and reputation. It is becoming increasingly recognised that delays are context-specific and multifaceted, requiring more industry-oriented perceptions. This work proposes the exploratory use of Machine Learning based on Classification and Regression Trees (CART) Decision Trees (DT) to assess the predictive analysis of these approaches, considering surveys (primary data) collected from 100 specialists with different backgrounds and experiences in the construction industry. Survey responses are discussed, followed by the CART DTs, which are used as predictor for clarifying underneath relationship among different variables in a project environment. The major issue presented is related to Project Design, with "The firm is not allowed to apply for an extension of contract period", with two possible predictors, firstly, as the main factor it is found "Mistakes, inconsistencies, and ambiguities in specification and drawing", while other aspect highlights "Poor site supervision and management by the contractor". The results indicate that the correct use of Artificial Intelligence techniques with relevant data are potential tools to support the analysis of scenarios and avoidance of project delays in Project Management.

Artificial Intelligence and Deep Learning in Stock Prediction: A Bibliometric Review - Chin, Yang Lin; Lobo Marques, Joao Alexandre; Lin, Kun Chan (2024)
Artificial intelligence (AI) and deep learning (DL) are advancing in stock market prediction, attracting the attention of researchers in computer science and finance. This bibliometric review analyzes 525 articles published from 1991 to 2024 in Scopus-indexed journals, utilizing VOSviewer software to identify key research trends, influential contributors, and burgeoning themes. The bibliometric analysis encompasses a performance analysis of the most prominent scientific contributors and a network analysis of scientific mapping, which includes co-authorship, co-occurrence, citation, bibliographical coupling, and co-citation analyses enabled by the VOSviewer software. Among the 693 countries, significant hubs of knowledge production include China, the US, India, and the UK, highlighting the global relevance of the field. Various AI and DL technologies are increasingly employed in stock price predictions, with artificial neural networks (ANN) and other methods such as long short-term memory (LSTM), Random Forest, Sentiment Analysis, Support Vector Machine/Regression (SVM/SVR), among the 1399 keyword counts in publications. Influential studies such as LeBaron (1999) and Moghaddam (2016) have shaped foundational research in 8159 citations. This review offers original insights into the bibliometric landscape of AI and DL applications in finance by mapping global knowledge production and identifying critical AI methods advancing stock market prediction. It enables finance professionals to learn about technological developments and trends to enhance decision-making and gain market advantage.
Issue: 1

Optimization of Energy Storage Systems with Renewable Energy Generation and Consumption Data - Filho, Edmilson Moreira Lima; Silveira, Aêdo Braga; Ferreira, Alexandre Marques; Lobo Marques, Joao Alexandre; Batista, Josias Guimarães; Guimarães, Glendo De Freitas; Alexandria, Auzuir Ripardo De; Rodrigues, Joel José Puga Coelho (2024 IEEE 7th Student Conference on Electric Machines and Systems (SCEMS), 2024)
This work provides a comprehensive systematic review of optimization techniques using artificial intelligence (AI) for energy storage systems within renewable energy setups. The primary goals are to evaluate the latest technologies employed in forecasting models for renewable energy generation, load forecasting, and energy storage systems, alongside their construction parameters and optimization methods. The review highlights the progress achieved, identifies current challenges, and explores future research directions. Despite the extensive application of machine learning (ML) and deep learning (DL) in renewable energy generation, consumption patterns, and storage optimization, few studies integrate these three aspects simultaneously, underscoring the significance of this work. The review encompasses studies from Web of Science, Scopus, and Science Direct up to December 2023, including works scheduled for publication in 2024. Each study related to renewable energy storage was individually analyzed to assess its objectives, methodology, and results. The findings reveal useful insights for developing AI models aimed at optimizing storage systems. However, critical areas need further exploration, such as real-time forecasting, long-term storage predictions, hybrid neural networks for demand-based generation forecasting, and the evaluation of various storage scales and battery technologies. The review also notes a significant gap in research on large-scale storage systems in Brazil and Latin America. In conclusion, the study emphasizes the need for continued research and the development of new algorithms to address existing limitations in the field.

Doctor Bone: treinamento de redes neurais para auxílio na identificação da idade óssea - Barbosa, Rodrigo Lages; Martins, Heitor de Castro Teixeira e; Barbosa, Felipe Cassiano; da Costa, Beatriz Torres; Matela, Rolf Freitas; Neto, José Fernando Rodrigues Ferreira; Fontes, Yuri Nekan Soares; Lobo Marques, Joao Alexandre; Duarte, João Batista Furlan; Neto, Joel Sotero da Cunha (2024)
Objetivo: Explorar a aplicação de inteligência artificial (IA) na predição da idade óssea a partir de imagens de raios-X. Método: Utilizou-se a Metodologia Interdisciplinar para o Desenvolvimento de Tecnologias em Saúde (MIDTS) para desenvolver uma ferramenta de predição. O treinamento foi realizado com redes neurais convolucionais (CNNs) usando um conjunto de dados de 14.036 imagens de raios-X. Resultados: A ferramenta alcançou um coeficiente de determinação (R²) de 0,94807 e um Erro Médio Absoluto (MAE) de 6,97, destacando sua precisão e potencial de aplicação clínica. Conclusão: O projeto demonstrou grande potencial para aprimorar a predição da idade óssea, com possibilidades de evolução conforme a base de dados aumenta e a IA se torna mais sofisticada.

Empowering Luxury: How Cause-Related Marketing Influences Gen Z and Millennials' Post-Purchase Guilt in China's High-End Retail Landscape - Dias, Joana Carmo; Silva, Susana; Martins, Carla; Casais, Beatriz (European Journal of Applied Business and Management, 2024)
Purpose: This study explores the emotional impact of post-purchase guilt on younger consumers in the Chinese luxury retail market, with a specific focus on the role of Cause-related Marketing (CrM) in mitigating negative emotions across luxury and non-luxury product categories.Design/Methodology/Approach: A quantitative experimental design was utilized, involving 326 respondents exposed to different advertising scenarios. The study tested the impact of CrM on post-purchase guilt in both luxury (high-priced) and non-luxury (moderately priced) product conditions, using a 2 × 2 factorial design. The data were analyzed using ANCOVA to assess the effects of CrM campaigns across conditions.Findings: The results demonstrate that CrM effectively reduces post-purchase guilt across both luxury and non-luxury product categories, providing a moral justification for purchases by linking them to a positive social cause. However, contrary to expectations, the impact of CrM was not significantly stronger in the luxury context compared to non-luxury. This suggests that CrM's influence on post-purchase guilt operates uniformly, regardless of product type.Originality: This research enhances understanding Millennial and Gen Z consumer behavior in the Chinese luxury market. The findings offer actionable insights for luxury brands, highlighting the effectiveness of CrM in addressing guilt-related concerns, thereby informing marketing strategies aimed at younger generations.Keywords: post-purchase guilt, Millennials, Gen Z, Chinese luxury retail industry, cause-related marketing.Acknowledgments: The first author would like to thank CEGE – Research Centre in Management and Economics, funded by The Multiannual Funding Programme of R&D Centres of FCT – Fundação para a Ciência e Tecnologia under the project UIDB/00731/2020. The fourth author would like to thank COMEGI funded by FCT – Fundação para a Ciência e Tecnologia under the project UIDB/04005/2020.DOI: https://doi.org/10.58869/EJABM10(3)/06
Number: 3

Consumers' Perception of Electric Aviation in Macao: An Exploratory Study Based on the Theory of Planned Behavior - Lampo, Alessandro (Proceedings of the 10th International Conference on Industrial and Business Engineering, 2024)
Battery Electric Aircraft (BEA) technology is gaining attention due to the potential to reduce carbon emissions and noise pollution, contributing to global environmental sustainability. Grounded in the Theory of Planned Behavior (TPB), this paper explores the determinants of attitude, social norm, behavioural control, and perceived risks related to the intention of Macau residents to use electric aeroplanes within the Greater Bay Area (GBA). This research uses a quantitative approach. Data is collected through structured surveys distributed to potential adopters. To assess the relationships between the determinants in our model, Structural Equation Modeling (SEM) is employed. The findings reveal that a favourable attitude and perceived behavioural control positively influence individuals’ intentions to adopt electric aeroplanes. However, perceived risks strongly impact adoption intentions, suggesting that addressing safety and reliability concerns is essential for promoting the technology within the region. The implications of this research extend beyond academic interests, as Macau’s unique position within the GBA offers the opportunity for electric aeroplanes’ adoption. Further, the reduced carbon emissions and noise pollution align with the city’s objectives and create a harmonious balance between economic prosperity and environmental preservation for future generations. This study offers important insights for integrating advanced computing technologies into BEA systems to enhance electric aeroplanes’ operational efficiency and safety to support their adoption. It also provides a path for policymakers and industry stakeholders toward sustainable economic development and integration of Macau within the GBA.

Macau Cultural Tapestry: Unravelling a City’s Visual Identity Through Its Patterns and Textures—Digital Archive and Mapping - Martins, Filipa; Seck, Mamadú; Pinheiro, Francisco; Estadieu, Gerald (Springer Series in Design and Innovation, 2024)
ISBN: 9783031761553

The Future of Digital Banking in Macau: Developing a Theoretical Model of User Willingness for Digital Banking Services - Lin, Jing-ying; Lobo Marques, Joao Alexandre; Neto, Andreia (Proceedings of the 2024 15th International Conference on E-business, Management and Economics, 2024)
In the wave of digital transformation, Chinese banks have prioritized digital banking services as key strategic goals, aiming to revolutionize the mobile banking experience. This study aims to assess the factors influencing the willingness to use the various financial and contextual services offered through digital banking. Specifically, it is proposed a model based on users' perceptions of mobile banking scenarios and examines how the development of digital banking services influences users' willingness to use them. The study involved qualitative in-depth interviews with 12 mobile banking users, with the interview content analyzed using Nvivo qualitative analysis software. The data analysis identified 9 core coding categories: Financial Professionalism, Security, Marketing Stimulation, Innovative Products, Use Experience, Strong Relationship, Trust, Perceived Usefulness, and Willingness to Use. These categories were further refined to construct a theoretical model of user willingness in digital banking services, drawing from the optimized Technology Acceptance Model (TAM). The findings provide valuable insights for the banking industry in Macau, aiding in understanding customer needs and supporting the positive development of mobile finance and contextual digital banking services in the region.
Publisher: ACM

Unveiling retail omnichannel challenges: developing an omnichannel obstacles scale - Radomska, Joanna; Kawa, Arkadiusz; Hajdas, Monika; Klimas, Patrycja; Silva, Susana C. (International Journal of Retail & Distribution Management, 2024)
Purpose Retail omnichannel implementation faces barriers hindering accurate and efficient integration across marketing channels. Our desk examination identified a need for a broader perspective in investigating these barriers, moving away from a dominant, narrow approach. This research aims to develop a comprehensive set of items to measure retail omnichannel obstacles, refine the scale and assess its reliability and validity for a robust measurement tool. Design/methodology/approach Our approach combines quantitative and qualitative methods, using data from primary and secondary sources to create and validate the omnichannel obstacles scale. Findings This study emphasises the inclusive nature of retail functional areas, departing from prior literature that examined them in isolation. Instead of focussing on separate domains where retail omnichannel obstacles may arise, we adopt a holistic perspective by integrating previously disconnected elements. Originality/value We assert that challenges in retail omnichannel operations encompass three distinct dimensions: operational efficiency, channel inefficiency, and strategy and organisational culture within retailing. In our final validated measurement model, we consolidate the channel inefficiency dimension and refine the omnichannel obstacles scale to emphasise two areas of consideration.

Unveiling the power of supplier-country image on B2B customers' perceptions: Beyond the product’s beauty - Crespo, Cátia Fernandes; Crespo, Nuno Fernandes; Silva, Susana C. (International Business Review, 2025)

是來時路，亦是前行燈：澳門教師的使命與歸屬 - Ge, Rochelle (2025)

Predicting consumer ad preferences: Leveraging a machine learning approach for EDA and FEA neurophysiological metrics - Marques, João Alexandre Lobo; Neto, Andreia C.; Silva, Susana C.; Bigne, Enrique (Psychology & Marketing, 2025)
This research unveils to predict consumer ad preferences by detecting seven basic emotions, attention and engagement triggered by advertising through the analysis of two specific physiological monitoring tools, electrodermal activity (EDA), and Facial Expression Analysis (FEA), applied to video advertising, offering a twofold contribution of significant value. First, to identify the most relevant physiological features for consumer preference prediction. We integrated a statistical module encompassing inferential and exploratory analysis tools, which identified emotions such as Joy, Disgust, and Surprise, enabling the statistical differentiation of preferences concerning various advertisements. Second, we present an artificial intelligence (AI) system founded on machine learning techniques, encompassing k-Nearest Neighbors, Support Vector Machine, and Random Forest (RF). Our findings show that the RF technique emerged as the top performer, boasting an 81% Accuracy, 84% Precision, 79% Recall, and an F1-score of 81% in predicting consumer preferences. In addition, our research proposes an eXplainable AI module based on feature importance, which discerned Attention, Engagement, Joy, and Disgust as the four most pivotal features influencing consumer ad preference prediction. The results indicate that computerized intelligent systems based on EDA and FEA data can be used to predict consumer ad preferences based on videos and effectively used as supporting tools for marketing specialists.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/mar.22118
Keywords: advertising; consumer ad preferences; consumer neuroscience; emotions; explainable artificial intelligence; machine learning

Beyond the myth: understanding women's impulsive retail footwear shopping - Duarte, Paulo; Silva, Susana C.; Magro, Margarida; Dias, Joana Carmo (International Journal of Retail & Distribution Management, 2025)
Purpose This research focuses on common misconceptions about the factors driving women to purchase footwear impulsively. Its primary objective is to explore how emotional and social triggers specifically influence women's purchasing decisions, contrasting with the traditionally rational consumer models. Design/methodology/approach An online questionnaire was administered to a sample of women, yielding 199 useable responses. Findings The findings reveal the key determinants of women's impulsive retail footwear purchases, which include self-regulation, hedonic motivations and the influence of the retail store environment. This research challenges the prevailing assumption that women's passion for shopping is driven solely by inherent characteristics and suggests that external factors substantially shape their impulsive buying behaviour. In summary, the stereotypical portrayal of women as compulsive retail footwear shoppers may result more from external stimuli and environmental factors rather than an intrinsic trait. Originality/value This study improves the existing knowledge of women’s impulsive buying behaviour by unveiling the determinants of women's impulsive footwear purchases and assessing whether prevailing stereotypes hold true.

The shifting landscape of Chinese student mobility to Thailand - Lertpusit, Sivarin; Ge, Rochelle; Ho, Kong Chong (Asian Population Studies, 2025)
This paper examines the evolving trends in Chinese student mobility to Thailand, highlighting three distinct phases shaped by changes in the higher education: the dominance of Thai language programmes (1990–2010), the rise of business and international programmes (2010–2020), and the increasing preference for graduate studies (2020 onwards). By analysing the economic, cultural, and institutional factors facilitating these shifts, this paper positions Thailand as an emerging alternative study destination for Chinese students. It highlights the significance of this migration within the context of Thailand’s declining fertility rate and labour shortages, focusing on how Thai universities have adapted through active recruitment strategies targeting Chinese students. This paper also addresses the push and pull factors underpinning this migration and the pursuit of alternative educational pathways among Chinese youth. Additionally, it explores the strategic role of Sino-Thai collaborations under the BRI and their broader implications for educational mobility and economic ties.
Publisher: Informa UK Limited

Action research on circular economy strategies in fashion retail - Silva, Susana C.; Neiva, Carolina Rocha; Dias, Joana Carmo (International Journal of Retail & Distribution Management, 2025)
Purpose The aim of this study is to explore the role and impact of action research in the adoption of circular economy strategies by a fashion retail brand. This exploration is motivated by the need to address the underutilization of action research in management studies, despite its potential to foster a deep understanding of organizational processes and to drive positive transformations. The study seeks to illustrate how action research can contribute to the practical implementation of sustainability initiatives, specifically within the context of new environmental legislation and growing demands for sustainable practices in retailing. Design/methodology/approach This research employs an action research methodology, particularly suited to the retail field, where understanding and influencing organizational processes are key. Through a detailed case study of a fashion retail brand, the study illustrates how action research facilitates the adoption of circular economy strategies. Findings The findings of this study underscore the effectiveness of action research in implementing circular economy strategies within the fashion retail industry. Specifically, it highlights how this approach has led to the successful reduction of waste and reintegration of products into their lifecycle. Originality/value The originality of this study lies in its thorough application of action research to measure and refine the outcomes of circular economy strategies in retailing. This novel approach provides substantial insights into the potential of the circular economy to drive practical innovations in business practices within retail.

Is masculinity ruining the male skincare market? Comprehensive insights on consumer behavior in cosmetics - Duarte, Paulo; Silva, Susana; Carvalho, Maria Joana (Journal of Consumer Marketing, 2025)
This paper aims to investigate the factors influencing men’s purchase intentions for skincare products, particularly focusing on the evolving attitudes toward masculinity, grooming and self-care. The study seeks to identify dimensions such as self-image, health concerns, masculinity and perceptions regarding skincare, along with the impact of social media use on men’s skincare purchase intentions.,The research uses an online questionnaire to gather data from 178 valid responses. The collected data is analyzed using partial least squares structural equation modeling.,The results reveal that men’s skin health concerns significantly impact their purchase intention for skincare products. Self-image concerns and perceptions regarding skincare also emerge as influential determinants in shaping men’s purchasing decisions. Conversely, health concerns and social media platform use do not directly influence skincare purchase intention. Notably, self-image completely mediates the relationship between men’s social media usage and their intention to purchase skincare products.,The data is based on responses from an online questionnaire, which may introduce biases. In addition, the research focuses on specific personal variables and social media use, potentially overlooking other influential factors.,By recognizing the importance of men’s skin health concerns, self-image and perceptions regarding skincare, cosmetic companies can tailor marketing strategies to effectively target key dimensions to enhance sales of skincare products among men.,In a broader societal context, this research contributes to the ongoing evolution of attitudes. By identifying influential factors in men’s skincare purchase intention, the study sheds light on changing societal norms and perceptions. Acknowledging these shifts can lead to a more inclusive understanding of masculinity and contribute to breaking traditional stereotypes related to men’s grooming practices.,This research contributes to the understanding of men’s skincare purchase intention by exploring dimensions such as self-image, health concerns, masculinity and perceptions regarding skincare, in conjunction with the impact of social media use. The findings provide valuable insights, expanding on previous studies on men’s attitudes toward skincare products. The identification of self-image as a complete mediator is a novel contribution.
Publisher: Emerald Publishing Limited

A grounded theory study of Chinese female spouses of problem gamblers in Hong Kong: emergence of a multiple-paradigm coping model - Kwan, Edward Wood Kai; Jackson, Alun C.; Tse, Samson (Asia Pacific Journal of Counselling and Psychotherapy, 2025)

The role of environmental concern and technology show-off on electric vehicles adoption: the case of Macau - Lampo, Alessandro; Silva, Susana C.; Duarte, Paulo (International Journal of Emerging Markets, 2025)
Purpose Research on battery electric vehicles (BEVs) has typically considered environmental concern a key determinant of behavioral intention that leads individuals to prefer electric vehicles. This paper challenges this assumption and argues that technology frameworks may require new variables to capture consumers' preferences. A UTAUT2-based study has been developed to assess the role of environmental concern in the BEVs context and put forward the technology show-off (TS) concept to explain the technology's acceptance. Design/methodology/approach A quantitative and cross-sectional look at behavioral intention is adopted. The study uses structural equation modeling to analyze a sample of 236 Macau residents to determine the relevance of the factors behind the choice to adopt BEVs. Findings The findings indicate that environmental concern and price may be relevant to explain behavioral intention to adopt the BEVs technology. Furthermore, the UTAUT2 framework seems to benefit from adding new variables, with TS playing a pertinent role in explaining technology acceptance. Social implications The findings show that environmental concern fails to build an argument for the shift to full electric mobility and promote the desired behavioral change toward adopting BEVs. Herein lies the necessity to consider new variables that can better describe the characteristics of modern society. Originality/value This paper proposes the TS construct, combining visibility and trialability as significant determinants of behavioral intention to use technology. The study also stresses the need to reconsider the role of environmental concerns' impact on consumer decision-making.

A Novel Improvement of Feature Selection for Dynamic Hand Gesture Identification Based on Double Machine Learning - Yan, Keyue; Lam, Chi-Fai; Fong, Simon; Lobo Marques, Joao Alexandre; Millham, Richard Charles; Mohammed, Sabah (Sensors, 2025)
Causal machine learning is an approach that combines causal inference and machine learning to understand and utilize causal relationships in data. In current research and applications, traditional machine learning and deep learning models always focus on prediction and pattern recognition. In contrast, causal machine learning goes a step further by revealing causal relationships between different variables. We explore a novel concept called Double Machine Learning that embraces causal machine learning in this research. The core goal is to select independent variables from a gesture identification problem that are causally related to final gesture results. This selection allows us to classify and analyze gestures more efficiently, thereby improving models’ performance and interpretability. Compared to commonly used feature selection methods such as Variance Threshold, Select From Model, Principal Component Analysis, Least Absolute Shrinkage and Selection Operator, Artificial Neural Network, and TabNet, Double Machine Learning methods focus more on causal relationships between variables rather than correlations. Our research shows that variables selected using the Double Machine Learning method perform well under different classification models, with final results significantly better than those of traditional methods. This novel Double Machine Learning-based approach offers researchers a valuable perspective for feature selection and model construction. It enhances the model’s ability to uncover causal relationships within complex data. Variables with causal significance can be more informative than those with only correlative significance, thus improving overall prediction performance and reliability.
Publisher: MDPI AG

Application of Multiple Deep Learning Architectures for Emotion Classification Based on Facial Expressions - Qian, Cheng; Lobo Marques, Joao Alexandre; Alexandria, Auzuir Ripardo de; Fong, Simon James (Sensors, 2025)
Facial expression recognition (FER) is essential for discerning human emotions and is applied extensively in big data analytics, healthcare, security, and user experience enhancement. This study presents a comprehensive evaluation of ten state-of-the-art deep learning models—VGG16, VGG19, ResNet50, ResNet101, DenseNet, GoogLeNet V1, MobileNet V1, EfficientNet V2, ShuffleNet V2, and RepVGG—on the task of facial expression recognition using the FER2013 dataset. Key performance metrics, including test accuracy, training time, and weight file size, were analyzed to assess the learning efficiency, generalization capabilities, and architectural innovations of each model. EfficientNet V2 and ResNet50 emerged as top performers, achieving high accuracy and stable convergence using compound scaling and residual connections, enabling them to capture complex emotional features with minimal overfitting. DenseNet, GoogLeNet V1, and RepVGG also demonstrated strong performance, leveraging dense connectivity, inception modules, and re-parameterization techniques, though they exhibited slower initial convergence. In contrast, lightweight models such as MobileNet V1 and ShuffleNet V2, while excelling in computational efficiency, faced limitations in accuracy, particularly in challenging emotion categories like “fear” and “disgust”. The results highlight the critical trade-offs between computational efficiency and predictive accuracy, emphasizing the importance of selecting appropriate architecture based on application-specific requirements. This research contributes to ongoing advancements in deep learning, particularly in domains such as facial expression recognition, where capturing subtle and complex patterns is essential for high-performance outcomes.
Publisher: MDPI AG

A Possible Solution to the Black Hole Information Paradox - Arraut, Ivan (AppliedMath, 2025)
The information paradox suggests that the black hole loses information when it emits radiation. In this way, the spectrum of radiation corresponds to a mixed (non-pure) quantum state even if the internal state generating the black hole is expected to be pure in essence. In this paper we propose an argument solving this paradox by developing an understanding of the process by which spontaneous symmetry breaks when a black hole selects one of the many possible ground states and emits radiation as a consequence of it. Here, the particle operator number is the order parameter. This mechanism explains the connection between the density matrix, corresponding to the pure state describing the black hole state, and the density matrix describing the spectrum of radiation (mixed quantum state). From this perspective, we can recover black hole information from the superposition principle, applied to the different possible order parameters (particle number operators).
Number: 1 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Hawking radiation; black holes; information paradox; spontaneous symmetry breaking

Local Equivalence of the Black–Scholes and Merton–Garman Equations - Arraut, Ivan (2025)
It has been previously demonstrated that stochastic volatility emerges as the gauge field necessary to restore local symmetry under changes in stock prices in the Black–Scholes (BS) equation. When this occurs, a Merton–Garman-like equation emerges. From the perspective of manifolds, this means that the Black–Scholes and Merton–Garman (MG) equations can be considered locally equivalent. In this scenario, the MG Hamiltonian is a special case of a more general Hamiltonian, here referred to as the gauge Hamiltonian. We then show that the gauge character of volatility implies a specific functional relationship between stock prices and volatility. The connection between stock prices and volatility is a powerful tool for improving volatility estimations in the stock market, which is a key ingredient for investors to make good decisions. Finally, we define an extended version of the martingale condition, defined for the gauge Hamiltonian.

Real-time emotion recognition based on facial expressions using artificial intelligence techniques - A review and future directions - Cheng, Qian; Lobo Marques, Joao Alexandre; de Alexandria, Auzuir Ripardo (2025)

Solving the dark energy problem via symmetry constraints - Arraut, Ivan (The European Physical Journal C, 2025)
We derive the vacuum energy from the zero-point quantum fluctuations after imposing a natural constraint emerging from the rotational symmetry inside the de-Sitter metric. The constraint imposes a maximum azimuthal angle for each frequency mode emerging from the vacuum. In this way, the shorter the wavelength of the mode, the larger will be its suppression. The same result is derived subsequently by using the Friedmann–Lemaitre–Robertson–Walker (FLRW) metric. We then make a physical interpretation of the physical effects from the perspective of pair creations over the vacuum, where the mentioned constraint emerges, limiting then the maximum angle which each pair generated from the vacuum can rotate with respect to each other during their short existence.
Publisher: Springer Science and Business Media LLC

Non-thermodynamic Black Hole Evaporation - Arraut, Ivan; Mehta, Abhishek Kumar (arXiv, 2025)
In this paper, we investigate black hole evaporation from the path integral perspective. We demonstrate that besides the standard thermodynamic modes, there are non-thermodynamic modes of black hole evaporation which contain remnants. The pure thermodynamic process is recovered when the Gauss-Bonnet action is involved. This scenario opens a new window for analyzing the process of black-hole evaporation.
arXiv:2505.06859 [hep-th]
Keywords: High Energy Physics - Theory

Assessing critical thinking disposition through text analysis in traditional Chinese: An empirical study of tourism and gaming undergraduates in Macao - Siu Lam, Carlos; Liu, Yong; Zhang, Yinghong; Wu, Hao (Frontiers in Education, 2025)
Critical thinking disposition (CTD) is increasingly recognized as an important trait in education, reflecting the inclination and habits necessary for addressing complex challenges in today's world. This study assessed the CTD of students enrolled in a tourism and gaming management programme, focusing on two key dimensions: Analyticity and Open-Mindedness. This study was conducted at a university in Macao and involved 65 participants. The students were presented with an article relevant to their major, written in Traditional Chinese, and were asked to provide their opinions on each statement in the article. A rubric was designed to analyze their responses and assess their Analyticity and Open-Mindedness within the CTD framework. The results demonstrated high reliability (Cronbach's α = 0.91) and revealed an association between Analyticity and Open-Mindedness. Using Python programming, the study analyzed the frequency of parts of speech (POS) in students' responses, introducing a novel approach for evaluating CTD in Traditional Chinese. Regression modeling showed that parallel and adversative conjunctions significantly predicted Analyticity, while the frequency of conjunction use varied across Open-Mindedness classifications. These findings highlighted an innovative and objective method for assessing CTD through text analysis, offering promising applications for educational research in Traditional Chinese-speaking contexts.
Publisher: Frontiers
Keywords: critical thinking disposition; educational assessment; text analysis; tourism and gaming education; traditional Chinese