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The extent of citizens' trust in government determines the success or failure of e-government initiatives. Nevertheless, the idiosyncrasies of the concept and the broad spectrum of its approach still present relevant challenges. This work presents a systematic literature review on e-government trust while elaborating and summarizing a conceptual analysis of trust, introducing evaluation methods for government trust, and compiling relevant research on e-government trust and intentional behavior. A total of 26 key factors that constitute trust have been identified and classified into six categories: Government trust, Trust in Internet and technology (TiIT), Trust in e-government (TiEG), Personal Beliefs, Trustworthiness, and Trust of intermediary (ToI). The value added of this work consists of developing a conceptual framework of TiEG to provide a significant reference for future in-depth studies and research on e-government trust.

This dissertation identifies factors driving consumer shopping behavior within the realm of live-streaming commerce, an area fast emerging in the e-commerce domain. Live-streaming shopping or commerce involves real-time interaction and entertainment with traditional online shopping, forming a unique endogenous environment where consumers can contact sellers or influencers directly. The study employed quantitative surveys that identified some of the main determining factors of consumer behavior within this context. The findings show that the significant factors in determining consumer behavior are trust and engagement, which are strongly influenced by the credibility and authenticity of the live streamer. Another significant finding is the role of social interaction and community building in providing consumers with a sense of belonging and validation, enhancing their confidence and purchase intention. Moreover, it highlights how marketing strategies of flash sales, limited-time offers, and partnerships with influencers make their way into the system to help invoke engagement and impulsive buying behavior among consumers. The implications of these findings extend to e-commerce platforms and marketers. Any improvements in features leading to trust, engagement, and interactivity within the community would drive higher customer satisfaction and sales. According to researchers, working partnerships with believable influencers and more extensive integrations of real-time marketing might further activate live-streaming commerce. This study thus fills a gap in the existing body of literature by detailing the drivers of consumer behavior toward live-stream commerce. It also identifies areas of future research on the current studies, including developing technologies and the cultural variances in the impact of live-stream commerce, including ethical considerations. These results are principle for guiding work on potential live-stream commerce in the digital age for anybody from workers to academicians

In the wave of digital transformation, Chinese banks have taken digital and scenario-based finance as primary strategic goals. The goal is to revolutionize the mobile banking experience and encourage frequent use of mobile banking services. However, assessing customer satisfaction with the various financial and contextual services mobile banking provides is crucial. The main objective of this study is to propose a model based on users' perception of financial usage in mobile banking scenarios and how the development of mobile banking finance and scenarios affects users' choice motivations. The study examined the interview records of 12 mobile banking users through qualitative in-depth interviews and utilized Nvivo qualitative analysis software to analyze the interview content. Through repeated thinking, sorting, and differentiating the data, nine core coding categories were formed. The coding was further refined and deepened to include Financial professionalism, Security, Marketing Stimulation, Innovative Products, Use Experience, Strong Relationship, Trust, Perceived usefulness, and Willingness to use. Based on these categories, a theoretical model of user willingness in the financial scenario of mobile banking has been proposed by referring to the optimized TAM model. The results may provide support to the banking industry in Macau in understanding customers' needs and fostering the positive development of mobile finance and the scene field in Macau

With the rapid development of digital media, internet celebrity live streaming has become a key factor in influencing the consumer decision-making of adolescents, presenting unique regional characteristics in different socio-cultural and economic contexts. This study investigates the differences in consumption habits among adolescents in Macau and Mainland China and their impact on the innovation and reform of the commercial model of internet celebrity live streaming. The methodology employs a questionnaire survey and data analysis to systematically compare the consumption behavior of adolescents in Macao and mainland China, collecting live streaming consumption habits of adolescents in both regions. Statistical methods are used to compare and analyze the consumption patterns within the regions. The analysis indicates that influencers, as internet celebrities with a large number of fans on social media, have a significant impact on adolescents' consumption decisions through their recommendations and evaluations. Firstly, the convenience and diversity of e-commerce platforms provide adolescents with a wealth of consumption choices, such as characteristics and usage effects of products. Secondly, the recommendations and evaluations of influencers have become an important reference for adolescents' consumption. Results show that adolescents in Macau tend to seek entertainment and interaction in their consumption of internet celebrity live streaming, whereas those in Mainland China place greater emphasis on the practicality of the live streaming content and the cost-effectiveness of the products. Moreover, the study reveals the roles of socio-cultural and economic levels in the differences in consumption between the two regions. Based on these insights, it is recommended that live streaming platforms should advance the innovation and reform of their business models to cater to different market characteristics—such as optimizing content recommendation algorithms, enhancing interactive elements, and improving the integration of e-commerce features, thereby promoting business sustainability and economic benefits

The emergence of blockchain technology in 2008 marked a significant milestone in the evolution of digital currencies, paving the way for the emergence of cryptocurrencies such as Bitcoin. Since then, blockchain has undergone four generations of development, expanding its applications across various sectors. In particular, the integration of blockchain into accounting and auditing practices has garnered significant attention due to its potential to transform traditional methods. However, there's a lack of clear understanding of how blockchain impacts traditional auditing practices and finance recordkeeping and the implications for audit quality. Significant challenges and uncertainties hinder its widespread adoption, including technical hurdles, regulatory complexities, and practical barriers. This dissertation aims to determine the transformative impact of blockchain technology on auditing practices and finance recordkeeping. In order to fully understand the impact of blockchain on auditing practices and finance recordkeeping, the dissertation utilizes a mixed sequential research approach that is divided into three phases. The first approach involves gathering qualitative data through interviews with blockchain experts. The second approach involves collecting secondary qualitative data through a systematic literature review to determine the changes that blockchain has brought to traditional auditing practices and finance recordkeeping. This is followed by a bibliometric analysis to identify current trends in blockchain research related to auditing practices and finance recordkeeping. The third approach involves gathering data through an online-focused survey distributed to finance and other industry professionals to determine the challenges organizations face in implementing blockchain technology in auditing practices and finance recordkeeping. Additionally, in phase three, case studies will be conducted based on the survey responses to examine the hindrances and challenges faced by organizations in implementing blockchain and its impact on auditing practices in different regions and among different demographic groups. As the findings indicate, Integrating blockchain technology into accounting and auditing practices can bring about significant improvements in transparency, efficiency, and fraud prevention. However, there are several challenges that must be overcome for successful implementation, such as technical difficulties, regulatory uncertainties, and privacy concerns. To overcome these hurdles, it is necessary to establish clear regulatory frameworks and innovative solutions. Although smart contracts offer automation, they also pose security risks that need to be addressed. Despite these challenges, blockchain has the potential to revolutionize auditing by enabling real-time auditing and enhancing integrity verification. To ensure audit quality, auditors must adapt to new responsibilities and stay up-to-date with emerging trends. Collaboration among stakeholders and continuous education and training programs are key to driving the successful adoption of blockchain technology

As the world becomes more globalized, it is now more important than ever for brands and advertisers to find effective ways to engage with consumers of different cultural backgrounds. Developing marketing that targets people of different cultural backgrounds, or multicultural marketing, carries specific nuances and complexities that may make traditional methods fall short. With this being said, there is still a lack of studies that explore the correlation between consumer's cultural background and their overall brand perception. Neuromarketing has proven to be an effective tool to understanding consumer behavior, by utilizing neuroscience tools. To employ a more sophisticated and in-depth understanding of consumer perception, the current research study makes use of neuroscience tools and aims to study the influence of cultural background in brand perception, while in a controlled environment. Using physiological neuroscience tools, namely, facial expression analysis (FEA), electrodermal activity (EDA), and eye-tracking (ET), a total of thirty-eight individuals, with ages between 19 and 50 years old, from 12 different countries and regions, participated in this research study. Findings suggest that participants of different cultural backgrounds perceive multicultural commercials as more favorable than monocultural commercials. However, future research should be done with a larger sample size, as well as include a wider variety of commercials. Research would also benefit from adopting a statistical analysis to help determine the significance of the results obtained

Since early times, the effects of a booming sector in other sectors of a small economy have been of interest to scholars. There is a general perception that the booming Gaming sector has contributed to the overall growth in Macau through the trickle-down effect, passing on the benefits of growth to other sectors. After the liberalization of the gaming industry in 2002, this booming sector experienced several years of exponential growth, becoming the driving industry for Macao’s economy. Several scholars and researchers have dedicated their studies to the effects of the casino gaming industry as a booming sector in such a small economy. However, there is a gap in what concerns measuring the influence of the Gaming sector as a driving industry for several other sectors or following industries of Macau’s economy. The purpose of this research study is to investigate in what measure the Gaming sector in Macao leveraged the other economic sectors and how related or correlated are the different industries of Macao’s Economy. A protocol-driven understanding of the state of the art on the interrelations between economic sectors and different techniques used to study those inter-relations was conducted through a systematic literature review. Given the limited available data on the Gross Value Added (GVA), or Gross Domestic Product (GDP) on the supply side, as a central measure of economic activity in the different sectors, several possible interpolation models using auxiliary high-frequency data (indicators) were compared, to achieve the optimal model for interpolation of each variable. Several forecasts for the future performance of Macau's four major economic sectors were presented based on different regression techniques. Autoregressive Integrated Moving Average (ARIMA) models were developed to assess the dependence of the future performance of a sector’s GVA on its past performance. Optimal Vector Autoregressive (VAR) models were created to identify the explanatory power of some sectors of Macau’s economy in others. Based on available auxiliary data in high-frequency (quarterly) it was possible to interpolate the quarterly GVA per economic sector, available only in low-frequency (annually), for the major sectors of Macao’s economy. Some sectors have a considerable explanatory power on the performance of other sectors, however, the proposed regression models did not identify a clear relation between the performance of the Gaming sector and the performance of other major sectors from Macao’s economy

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.