Funded Projects for APAEM Members.

Our research team strives to have societal impact with our projects. If your organization is interested in becoming one of our collaborators, please contact us at

Asian Economics

(Team members)

Monetary Policy and Subsidy Policy in a Global Economy with Innovation and Technology Transfer

Principal Investigator: Prof. Yibai YANG

This project explores the impacts of two policy regimes on innovation and technology transfer in a global economy. The policy regimes in consideration include monetary policy and subsidy policy. Therefore, this project will consist of two research topics, including how (a) monetary policy (in terms of inflation) and (b) subsidy policy (in terms of research subsidies) on innovation and technology transfer in multinational firms’ foreign direct investment (FDI).

Technological innovation becomes increasingly important to sustain long-run economic growth in an open economy, especially for Asian economies. Inflation generates an extra cost burden in manufacturing and research and development (R&D) investments, whereas subsidization is one crucial policy instrument affecting technological improvement and economic growth. Therefore, these policy tools play a crucial role in transferring multinationals’ technologies across countries. This project expects to make significant contributions in terms of theoretical exploration and policy implications.

This project will systematically describe phenomenal observations. Then it will analytically study the effects of two policy instruments on innovation and technology transfer by setting up dynamic general equilibrium frameworks with optimization and endogenous economic growth. Finally, this project will quantify the effects of policy instruments by calibrating theoretical models to realistic data.

Optimal Design for Concession Agreements 

Principal Investigator: Dr. Allen VONG

Motivated by casino concessions in Macau, this project examines the socially optimal design for concession agreements by governments. Concessionaires, namely firms that receive concessions, earn profits by operating but are expected to perform socially desirable activities during their operations. These firms might face little incentives to exert effort to perform these activities for several reasons. First, exerting effort is costly. Second, it is difficult for governments to monitor the firms’ efforts, as their efforts are typically unobservable; governments only partially infer their efforts via some observable outcomes. Finally, it can be difficult for governments to assess these observable outcomes because they might not be familiar with the firms’ private information, such as their operating costs.

Thus, the design for concession agreements that provides incentives for firms to reveal their private information and to exert efforts to perform socially desirable activities is of paramount importance. This project develops a game-theoretic analysis of such design, elucidating the optimal structure such as the number of concessions to grant and the length of concessions, and how governments should screen the concession applicants and decide the winning applicants. The results provide policy implications for concession agreements of casinos and other public utilities in Macau.

Tourism Development in the Greater Bay Area

Principal Investigator: Prof. Priscilla TAM

* Co-funded by Education Fund of the Macao SAR Government (2021-2022)

This project purports to study the course of tourism development in the Greater Bay Area from the economic perspective. It focuses on examining the spillover effects of tourism development among the regional cities so as to assess the extent of regional cooperation or competition with regards to their complementarity and substitutability. It also investigates the main determinants of regional tourism development for their implications on the regional allocation of resources. Results would provide insights into the current and future development and growth of the region’s tourism industry.

The Evolution of Productivity and Efficiency in the GD-HK-MO Greater Bay Area

Principal Investigator: Prof. Fung KWAN

Using official regional and prefecture-level data of the Guangdong- Hong Kong-Macao Greater Bay Area, we identify the sources of output growth and study the technical efficiency with its determinants across cities and sectors over time. Accordingly, implications for appropriate industrial policy, investment on human capital and R&D will be examined.

External Political Shocks and Corporate Innovation in China –Evidence from the 2016 US Presidential Election 

Principal Investigator: Prof. Brenda ZHANG

The unanticipated presidential election outcome in 2016 allows us a unique opportunity to estimate the effect of exogenous political shock in the US on the financial market and corporate strategy in China –its largest trade partner and creditor. We identify firms’ exposure to the shock by examining the stock market reaction and investigate the implication on corporate innovation among listed firms. Our results show that how the surprise victory of Donald Trump influences stock returns and its implications on firms’ innovation outcome. We further test if such relation continues to hold in a battery of robustness tests and is moderated by some firm level characters such as size and ownership. Our findings shed light on the broader implication on corporate innovation of US-China trade war.

The Effect of the U.S.–China Trade War on Chinese Corporate Innovation: A Curse or a Blessing?

Principal Investigator: Prof. Jia YUAN

During 2018–2019, the Trump administration imposed unexpected punitive tariffs on China, raising the average U.S. tariff on Chinese products from 3.57% in early 2018 to 26.3% by the end of 2019. This triggered a series of retaliatory tariff actions from China. Although the tariff spikes most immediately impacted exporting activities and international trade configuration (Fajgelbaum et al., 2021), the core argument for the initial U.S. tariff escalations, as documented in its Section 301 investigation report, concerns the “technology transfer, intellectual property, and innovation” of Chinese entities (USTR, 2018a,b). It is therefore imperative to ask whether and how the U.S.–China trade war affects China’s innovation activities. Specifically, did the Trumpian tariffs discourage innovation by leading Chinese firms? In this research, we plan to use balanced panel data for publicly listed Chinese manufacturing companies to provide comprehensive evidence on the innovation responses of Chinese firms to the U.S.–China trade war by exploiting the tariff variations during the U.S.–China trade war. Moreover, we plan to use triple difference-in-differences and textual analysis to further explore the mechanisms behind.  Specifically, we aim to evaluate and provide evidence about how the market size effect, the induced-competition effect and the government intervention affect the innovation response of Chinese firms to the US-China trade war.

Monetary Policy and Wealth Inequality: Evidence from China

Principal Investigator: Prof. Brenda ZHANG

China has emphasized promoting common prosperity in recent years to narrow the wealth inequality. Based on channels identified by Auclert (2019), this project investigates the impact of China’s monetary policy on households’ wealth levels and wealth distribution using data from the China Family Panel Studies (CFPS) during 2012-2018. Analysis shows that: (1) household wealth is more affected by real interest rate adjustments than unexpected inflation; (2) the impacts of monetary policy loosening and tightening cycles on household wealth are not symmetric and a persistently accommodative interest rate policy may do more harm than good to social wealth; (3) financial development raises the sensitivity of household wealth to monetary policy adjustments with heterogeneous effect across different channels.

R&D Efficiency of the GD-HK-MO Greater Bay Area

Principal Investigator: Prof. Fung KWAN

Using official regional and prefecture-level data of the Guangdong-Hong Kong-Macao Greater Bay Area, the project studies the efficiency of R&D technical efficiency with its determinants across cities and sectors over time. Policy implications for appropriate industrial policy are examined. The objectives of the project include: (a) identifying the sources of innovation growth in GBA; (B) examining the R&D efficiency across the GBA cities; and (c) assessing the R&D efficiency change in GBA over time.

Moving Forward and with Confidence: Improving College Admissions and School Choice through Sequential Mechanisms

Principal Investigator: Prof. Inácio BÓ

Procedures used for many school choice programs and centralized college admissions require the participants to submit a ranking over all the schools or colleges. The widespread use of the Internet, however, allows for new methods for determining these assignments through the use of sequential mechanisms. In these, participants choose their desired outcome from the options available, which are updated accordingly, before a final matching is produced. This allows students to focus their applications away from institutions that will not accept them, given other students’ choices. In this project, we evaluate sequential mechanisms currently being used to match millions of students to universities and proposed alternatives, testing their theoretical and empirical properties and the extent to which they help students make better choices and improve assignments. We will also provide a new mechanism to be used in these problems, which combines contemporaneous choices with historical statistics to produce assignments.

Investigating the Co-existence of the Gambler’s Fallacy and the Lucky Store Effect and Its Theoretical Mechanism

Principal Investigator: Prof. Jia YUAN

The project aims to examine individual gambling behavior by investigating one important question: can the seemingly contradicting fallacies: Gambler’s Fallacy (GF) and the Lucky Store Effect co-exist in the same context? If so, what is the behavioral theory to reconcile these two seemingly contradicting phenomenon?

The project aims to explore this issue by exploiting a unique large peer-to-peer online lottery marketplace for the Chinese national lottery. The project wants to investigate whether lottery players exhibit Gambler’s Fallacy beliefs when picking lottery numbers and meanwhile whether they believe in ‘lucky stores’ when choosing which online lottery store to purchase their tickets from. More importantly, the project focuses the co-existence of these fallacies and if so, plans to propose a simple behavioral theory to reconcile these two seemingly contradicting phenomenon.

Career Incentives of Local Leaders and Firm Dynamics in China

Principal Investigator: Prof. Leona LI

This project aims to assess how the career incentives of local leaders in China impact the entry and exit dynamics of firms. Despite having relatively weak formal institutions, China has achieved impressive economic growth. Emerging studies suggest that this may be attributed to the existence of a second-best, informal institution setup, where local politicians in China, facing the regional decentralized tournament system, are incentivized to promote economic development to advance their personal careers. Through the lens of firm entry and exit, we investigate both the advantages and limitations of this special institutional arrangement, contribution to the important literature that explores the institution-development nexus.

An Econometric Anatomy of Global Tourism Development

Principal Investigator: Prof. Priscilla TAM

The tourism industry has been the largest and one of the fastest growing industry in the world. Tourism expansion has been actively sought by economies around the globe as an engine for economic development and growth. Yet, the restricted mobility of people cross borders during the novel coronavirus period has called for a near standstill of international tourist flows, thereby bringing colossal economic losses to the tourism industry. To devise strategies for reinventing the industry in the post-pandemic new normal, this project purports to examine the global tourism development dynamics and analyze the steady-state condition along the long-run growth trajectory. To this aim, global tourism demand growth will be decomposed into its structural and cyclical components, the region(s) of centroid for global tourism development will be identified, while the contributions of economic, social and political forces that drive international tourism demand will also be scrutinized.

The Effect of China Connect

Principal Investigator: Prof. Sili ZHOU

The Shanghai (Shenzhen) -Hong Kong “Stock Connect” program allows investors in mainland China and Hong Kong residents and foreign investors to trade eligible stocks listed on the other market, through the exchange and clearing houses in their home markets. This program, announced in April 2014 and begun in November 2014, is regarded as a major step toward internationalizing China’s security markets.

The project analyzes the effects on Chinese firms of the “China Connect” equity market liberalization. Because China is a capital abundant country, unlike typical emerging markets in the literature, the benefits and costs of liberalization are logically different. Nonetheless, the liberalization brought benefits: lower funding costs, higher stock prices, and more investment for connected firms compared to unconnected firms, despite a common negative effect on all firms from capital outflows. These benefits come from a new channel: reducing domestic credit misallocation between private- and state-owned enterprises. The project also documents costs: connected firms became more sensitive to external shocks than unconnected firms.

Effects of Monetary Policy and Subsidy Policy on Innovation and Economic Growth in a Data Economy

Principal Investigator: Prof. Yibai YANG

This project aims to explore the impacts of two policy instruments on innovation and economic growth in a data economy. The policy instruments in consideration include monetary policy and subsidy policy. Therefore, this project will consist of two research topics, including how (a) monetary policy (in terms of inflation) and (b) subsidy policy (in terms of research subsidies) on innovation and economic growth in a dynamic general equilibrium model with a data-provision process.

Data has become an important factor in the process of consumer behavior and knowledge accumulation, with the development of technologies in modern economies. Inflation places an extra cost burden in consumption, manufacturing, and research and development (R&D) investment, whereas subsidization is one crucial policy instrument that governments implement to steer the market economy. Therefore, it is important to explore how these policy tools affect the use of data, leading to implications on innovation, economic growth and social welfare. This project expects to make significant contributions in terms of theoretical exploration and policy implications.

Financial Innovation 

(Team members)

The Application of Robo-Advisor in Macau

Principal Investigator: Prof. Jinjuan REN

Industry Collaborator: BNU

Motivated by the urgent need for inclusive finance in Macau, we plan to develop a Robo-advisor system to provide Macau residents with low-threshold, low-cost, and effective investment advice and financial planning services. This system is based on big data and machine learning technologies. We plan to collect and analyze data on investors’ personal traits, assess their risk attitude, evaluate their portfolios, optimize portfolios based on modern asset pricing theory, and further provide comprehensive and whole-life financial planning for households. We will further utilize the advantage of university education and build in financial literacy and education into the system.

Application of Blockchain Technology in Macau International Commercial Arbitration

Principal Investigator: Prof. Guangjian TU

As a platform for economic and trade cooperation between China and Portuguese-speaking countries, Macau takes a unique position in the field of international commercial dispute resolution. According to the long-term policy of the SAR government, Macau is intended to be built up as an international arbitration center for resolving commercial disputes between enterprises from China and Portuguese-speaking countries (Brazil, Portugal, Mozambique, Angola, Sao Tome and Principe, Guinea-Bissau, Cape Verde, and East Timor). In the internet age, a lot of information has to be transmitted, stored and handled electronically. In the case of arbitration, on the one hand, arbitration institutions need to extract, store and make use of electronic data; on the other hand, they need to prevent cyber attacks and ensure the security of data. Unfortunately, arbitral institutions has so far rarely utilized advanced technology such as Blockchain. They also can take advantage of the advanced technology for their case management and trials. Through analyzing the application of Blockchain technology, this project will identify how Blockchain can really help arbitration institutions in Macau e.g. in ensuring cyber security and data confidentiality and managing cases so as to promote Macau to become a popular arbitration center.

Augmentation of Digital Economy and Governance Through Deployment and Legal Recognition of Distributed Ledger Technology Applications in Macao SAR and Greater Bay Area

Principal Investigator: Prof. Guangjian TU

The scope and potential of Distributed Ledger Technologies (DLTs) including the Block Chain in the enhancement of economic development and effective governance are increasingly realized in various countries and markets around the world. The nature of the technology, warranting the development and use of different nodes of a network that could span across various borders, creates numerous technological and legal challenges, which needs to be comprehensively addressed in order to ensure the adoption of any transparent, reliable and efficient DLT applications. The proposed interdisciplinary project intends to

  1. assess the potential of specific DLT applications for enhancement of economic development and effective governance,
  2. identify relevant technological and legal challenges facing its prospective deployment in Macau SAR and Greater Bay Area (GBA) and
  3. propose relevant remedial and facilitation measures for wider adoption of the technology. Firstly, the project will systematically study the technology, infrastructure and legal environment necessary for the potential deployment DLT applications in various facets of the economy and public governance in Macau SAR in a comparative assessment with China, Hong Kong and other relevant jurisdictions. Secondly, the project will explore specific cross-border technological and legal cooperation/harmonization measures essential for facilitating economic transactions in the GBA region.

High-Speed Financial Asset Movement Forecasting System

Principal Investigator: Prof. Jerome YEN

This project integrates top research teams and professors in Mathematics and Computer Science of FST and Finance of FBA in UM to develop a very high-speed asset movement forecasting system with Independent Intellectual Property Rights (IIPRs), which focus on the future demand of financial industry in Greater Bay Area, supporting market benchmark, commodities, foreign exchanges, high-speed trading strategy selection and pricing for financial products. The innovative idea of the project is that to develop the implied volatility calculation model, with the scope of integration of traditional numerical analysis and artificial intelligence calculation by parallel processing on CPU and on hardware accelerator with high energy computing environment (e.g. GPU, ASIC, FPGA), to forecast asset movement.

Problems and Opportunities of Fintech as Sources and Platform of Financing

Principal Investigator: Prof. Rose Neng LAI

Financial Technology (Fintech) has brought in swift evolution to the financial system, and Fintech finance has grown rapidly to become new sources of funding, which distinguishes from traditional banking by using a lot more information through, for example, Big Data, particularly on credit checks of borrowers, while allowing small investors new choices of flexible and attractive investments. On the payment side, Fintech has facilitated financial inclusion that allows people in even remote areas to be able to use sources of funding as well as change consumption behaviour. This powerful source is however not without downside. When Fintech finance is offered outside of the banking sector, it becomes a new source of shadow banking beyond the scrutiny of the macroprudential banking system, creating a new source of financial fragility. This project attempts to include a collection of studies that analyze issues of Fintech. The first study covers theoretical and empirical analyses on the potential financial risks that Fintech can create to the financial system. The second is an analysis of the opportunities and risks created by the P2P platforms. The third one is to analyze the impact of Fintech financing and online payment platforms on patterns of consumption.

Improving Portfolio Performance based on Robust Hedge Regression

Principal Investigator: Prof. Lianjian SHU

Motivated from the hedge relationships revealed by the inverse conveyance matrix of asset recturns, the graphical least absolute shrinkage and selection operator (Glasso) has been proposed by Goto and Xu (2015) to estimate a sparse inverse covariance matrix for improving portfolio performance in high-dimensional settings. The Glasso approach achieves significant risk reduction and boosts certainty-equivalent returns (CER) by overcoming the multicollinearity issue of highly correlated assets in hedge regressions. However, the sample covariance matrix is used as input for Glasso analysis, which is susceptible to data outliers that can make the Glasso polluted by estimation error and become numerically unstable. Owing to its computational efficiency and portfolio allocation properties, this project employs robust treatment with Glasso strategy for portfolio selection in high dimensions. In particular, we replace the traditional sample covariance matrix with a cellwise robust estimator of covariance matrix as input tor the Glasso.

Research Proposal on Constructing the “Cross-Border Data Circulation Base” in Hengqin In-depth Cooperation Zone

Principal Investigator: Prof. Guangjian TU

Differences exist in the laws between Mainland China and Macau SAR on cross-border data flow. To ensure the legal compliance of cross-border data flow has become a prominent issue faced by businessmen in mainland China and Macau SAR in their business transactions. In this case, by seizing the opportunity of developing the Hengqin In-depth Cooperation Zone, it will be an effective solution to establish a data circulation base in Hengqin to enable businesses to exchange their data. The establishment of such a base must be dependent on the laws of the two sides. The legal system in Macau has strong historic origin of and high similarities with Portuguese-speaking countries. Therefore, before studying the cross-border data flow regulation between Mainland China and Macau SAR, it is necessary to make an understanding of the relevant legislations of Portuguese-speaking countries. At the same time, data legislations in the European Union, the United States and some other countries, are earlier than that of China, and have certain international influential power. Their mature experiences in data legislation can also provide a reference for the research of this project.

Criminal Liability of Arbitrators: Law and Practice in China

Principal Investigator: Dr. Zhe MA

Arbitrators are generally obliged to perform their duty to solve commercial disputes independently and impartially. When they fail to comply with this duty they may be legally liable for their misconduct. This liability usually assumes the nature of contractual or tort liability. By comparison, criminal liability of arbitrators is rarer, at least at the practical level. In this aspect, China stands as an outlier, not only having established a set of criminal provisions to regulate arbitrators, including specific provisions regarding bribery of arbitrators and a crime named “perversion of law” in 2006, but indeed there have been a number of cases where defendants have been convicted as a result of these provisions. This approach was received with skepticism by some Chinese and foreign legal practitioners who warned that this approach could discourage the usage of arbitrators in China and that it would give police and court authorities overbroad powers to intervene in arbitral proceedings.

Considering the importance of arbitration in China and world trade, this research will focus on reviewing the application of the aforementioned legislation in the period 2006-2023. A combination of data analysis and judgement content analysis is performed to discover how arbitrators in China are criminalized, including an identification of key players in prosecuted cases, crime patterns and punishments. Based on the data, the study offers insights into the impacts of criminal legislation on arbitrators and to what extent, if at all, this legislation has been used to disrupt arbitral proceedings.

In Search of IPO Peers Using Textual Approach

Principal Investigator: Prof. Jinjuan REN

Valuations in Initial Public Offering (IPO) are notoriously difficult, and the related literature is controversial regarding the initial mispricing and long-run performance. Finding comparable peers is critical in solving the disputes. Traditional peers matched by industry, size, and profitability have two limitations. First, the traditional industry classifications fail to classify firms with innovative business or covering multiple industries. Second, due to the high growth potential and high uncertainty of IPO firms, the current profitability fails to reflect the future prospects, which are critical in the forward-looking financial valuation.

This project applies the text-based approach of Hoberg and Phillips (2016) to identify peers matched by the business scope. The text-based peers can accommodate new-technology business, capture cross-industry relatedness, and does not rely on historical financial information. The project plans to explore the performance of various peers in IPO valuations. Preliminary evidence shows that the text-based peers have the highest aftermarket return correlations with IPO firms. The project plans to further investigate IPO pricing and long-run performance using the text-based peers as the benchmark. The results are expected to make important contributions to the IPO valuation literature and provide references to investment bankers in IPO underwriting.

Smart Tourism

(Team members)

A Smart Guided Tour Via VR for Historic Buildings

Principal Investigator: Prof. Alfred WONG

A part of the building’s cultural history preserved in oral form has disappeared recently. In this project, we build a smart guided tour platform to collect and share the models and introductions of many buildings with historical significance and characteristics. the real-world buildings are digitally recorded based on 3D modeling. The platform shows the 3D models, structural materials, and internal details with virtual reality (VR) technology.

A Custom Tour Itinerary Robot based on Deep Reinforcement Learning

Principal Investigator: Prof. Alfred WONG

Making a tour itinerary is an obstacle to visitors due to the unfamiliarity of the destination. This project aims to provide a custom tour itinerary robot using deep reinforcement learning. Tour itinerary is considered as the orienteering problem (OP) with search space. Therefore, we decide to train a graph model for predicting the route with reinforcement learning and create a mobile app for a custom tour itinerary in Macau.

Tourism Demand Forecasting for Multi-Destinations

Principal Investigator: Prof. Rob LAW

With the building of infrastructure for the region, such as new transportation, new flight routes, new highway and metro, the tourism demand of the region becomes more depending on nearby cities and countries. For example, the Hong Kong-Zhuhai-Macau bridge could connect Macao, Hong Kong, and Zhuhai, three major regions on the Pearl River Delta. The building on this bridge not only promotes economic development of the whole Pearl River Delta, but also creates a tourism clique with significant reducing on traveling time (Tian & Jiang, 2018). Accordingly, tourism demand of these three regions could be deeply changed and influenced by every city within the tourism clique, and existing tourism demand forecasting methods on single destination is insufficient to allow the public and private sectors to make the collective plan within the tourism clique. Hence, this project aims to explore the predictivity of tourism demand forecasting for the tourism clique, build the graph deep learning model to forecast the multi-destination tourism demand for the tourism clique and analysis the competitiveness circumstance within the tourism clique.

Detecting Fake Hospitality Reviews Using Linguistic Cues

Principal Investigator: Prof. Rob LAW

Online hospitality reviews provide peer opinions on hospitality and tourism products or services, which can assist reducing information asymmetry (Law et al., 2020). Consumers consider online reviews as trustworthy and useful in their decision-making process (Liang et al., 2019). In view of the commercial value of online reviews, fake reviews are often generated to manipulate consumers’ attitudes towards products and services (Huang et al., 2021). As an example, TripAdvisor recently found nearly one million fake reviews in 2020 (TripAdvisor, 2021). Fake hospitality reviews prevent the consumers from obtaining relevant or accurate information, which in turn, damage perceived credibility of reviews and constitute unfair competitions among businesses (Wang et al., 2021). To protect consumers and businesses from biased reviews, identification of fake reviews is crucial. Prior studies in hospitality research mainly focused on using algorithms to optimize the identification approach (Wu et al., 2020). To complement the algorithm development, this project aims to investigate the psychological process underlying review fabrication. Based on interpersonal deception theory, language usage in fake reviews can be different from authentic reviews (Li et al., 2020). Hence, this project is to detect fake reviews using linguistic cues. Specifically, the main objectives of this project include:

  • to analyze the linguistic divergences or differences between authentic and fake reviews;
  • to examine the interplay of linguistic cues to detect fake reviews; and
  • to compare the dynamics of linguistic cues by longitudinal design.

Estrangement Behavior in Post-COVID Travel and Tourism

Principal Investigator: Prof. Li MIAO

The presence of strangers, socially unrelated but physically near, is often an integral part of a travel and tourism experience. The COVID- 19 pandemic has abruptly and artificially changed the spatial relations among strangers. Mandatory and voluntary social distancing may lead to estrangement behavior in post-pandemic era travel and tourism such as distancing behavior, open hostility and micro-aggression towards travelers. Guided by the theoretical framework of strangership, this research examines the phenomenon of estrangement and tourism in the post- pandemic era through a socio-psychological lens. Using a sequential mixed method approach comprised of a quantitative study and a qualitative study, the objectives of this research are to evaluate the extent of estrangement in the post-COVID travel and tourism behavior in the aspects of emotional estrangement, self-estrangement and other-imposed estrangement and offer a phenomenological account of estrangement behavior in travel and tourism. Important theoretical and practical implications are also discussed.

Using Smart Technology to Develop Medical Tourism in Macao

Principal Investigator: Prof. Yuanjia HU

Macao has a unique foundation for tourism development, and in response to the demand for moderate economic diversification, the Macao government is also vigorously promoting the development of a large health industry. Medical tourism is a useful exploration of the organic combination of the two for Macao. However, due to various constraints, Macao needs to overcome key bottlenecks with the help of smart technologies. However. Macao has less research in this area. and in this context, this project focuses on using smart technologies to develop medical tourism in Macao. The research aims to: 1) identify the factors and resources that affect the development of medical tourism in Macao, 2) explore the barriers that can be addressed through smart technologies, and 3) propose a pragmatic and actionable framework for the development of medical tourism in Macao. This study will use a combination of interviews, questionnaires, and comprehensive analysis to conduct a systematic study, with the expectation that it will inform and assist governmental decisions, industry development, and individual behavior in this field.

Smart Tourism Apps: Opportunities and Privacy Challenges

Principal Investigator: Prof. Li DU

Smart tourism has been adopted in many countries. However, despite the advantages of using digital tools for smart tourism, potential risks to privacy and data protection have raised increasing attentions. This paper analyses smart tourism-related mobile applications (apps) used in selected Asian countries, with a focused exploration on the following perspectives. 1) What services do they offer?; 2) How do they portray the services? 3) What benefits and risks of using smart tourism Apps are mentioned? 4) how do they address the informed consent issues? And 5) what strategies used to ensure the protection of users’ information? Based on the study findings, this study will then discuss potential privacy challenges for the adoption of smart tourism. It will make recommendations for regulatory improvements that meet the development of the smart tourism market and the increasing demand for privacy protection.

Decentralized Finance (DeFi): Laws and Regulations

Principal Investigator: Prof. Li DU

The financial activities in the metaverse are essentially the decentralized finance (DeFi), which is based on the blockchain system. The security of DeFi, therefore, is critical for the future development of metaverse-related economic industries, especially the metaverse tourism. However, by April 2022, a financial loss of more than $3.24 billion USD has been caused by a vulnerability in the smart contracts that make up financial apps. Blockchain companies who perform audits of DeFi applications can find smart contract logic flaws and interactions with other DeFi entities. However, the previous studies discovered that many accidents occurred on DeFi applications that had been audited, indicating that the quality of services provided by DeFi audit companies varies. This research aims to explore DeFi audit companies’ potential to resolve the loss in DeFi incidents and examine legal issues associated with using DeFi auditing services. This study will promote a safer cryptocurrency industry in the Asia-Pacific region, where virtual assets have been identified as key growing economies.

Metaverse and Tourism Destinations’ Sense of Place

Principal Investigator: Prof. Li MIAO

Sense of place, what a tourist thinks and feels about a geographically-defined region or community, has been a central concept of tourism. The traditional conceptualization of sense of place is based on the assumption that a constellation of place-related cognitions and affects is contained within the physical boundaries of a place. However, the advent of metaverse, a confluence of multiple advanced technologies, has challenged the long-held assumption of clear geographical demarcation of a place. Metaverse also extends the temporal, spatial and experiential dimensions of a place. In other words, what constitutes a place is being redefined. In addition, latest sensory technologies have significantly augmented our senses, redefining what constitutes senses. It is not a stretch to suggest that metaverse significantly alters and expands the meanings of place, sense, and sense of place. Given this context, this research attempts to explore how metaverse as a confluence of technologies and as a new paradigm is redefining sense of place. Specifically, the objectives of the research are to: (a) conceptually redefine sense of place in a metaverse realm; (b) identify key attributes of sense of place in a metaverse realm; and (c) empirically investigate sense of place in a metaverse context.

Hotel website evaluation: The case of the best 100 hotels in the Greater Bay Area

Principal Investigator: Prof. Rob LAW

To better understand this key online marketing channel of the hospitality industry, this project aims to investigate the top 100 hotel websites in the Guangdong-Hong Kong-Macao Greater Bay Area (hereafter known as GBA) in China and compare the development of websites across cities. There are three main objectives of this project:

  • to propose an updated hotel website evaluation framework;
  • to adopt the proposed framework to evaluate and compare the performance of the top 100 hotels in the GBA; and
  • to provide managerial implications for website designers and hospitality practitioners.