Siyuan (Bruce) JIN 金思远

Research

The goal of behavioral-science research is truth. The goal of design-science research is utility. — MIS Quarterly, 2004

知之为知之，不知为不知，是知也。 — Confucius

Although I have not yet published in any of the top UTD 24 or FT 50 journals, I would like to share my research progress and contributions to the community. Here are works catergorized by my research agenda.

Research Agenda 1: Token-based Platforms

Token-based platforms are esential for the development of the digital asset economy in the complex Web 3.0 market. My research aims to provide better governance and regulation of token-based platforms.

Academic Papers

  1. S. Jin, A. Huang, Z Li, K. Tam. “Do Users of Blockchain IT Infrastructure Value Environmental Sustainability? Evidence from Environmental Impacts Disclosures”. Working paper. [Paper] [Slides]

    Abstract: While the environmental impact has become an important IT governance agenda in recent years, it is unclear whether its disclosure is valued by token holders of platforms based on blockchain IT infrastructure and how these platforms react to changing public awareness of their environmental impacts. We consider Elon Musk’s 2021 announcement that Tesla would suspend accepting Bitcoin as payment because of Bitcoin mining’s environmental impact as a shock that dramatically increases awareness of Bitcoin mining’s environmental impacts. We find that, subsequent to the shock, infrastructure platforms which have larger environmental impacts than application platforms, are more likely to disclose environmental impact information than application platforms and that their token market values grow at a slower rate, consistent with the increased awareness spills over to other token-based platforms. Furthermore, whereas pre-shock environmental impact disclosure by infrastructure platforms reduces token market value growth rates, post-shock disclosure has the opposite effect, consistent with green-costing and green-enhancing, respectively.

  2. S. Jin, Y. Cai, L. Qiu, K. Tam. “Operational Transparency in the Blockchain Era: Examining the Impact of Different Types and Levels on User Engagement”. Working paper.

  3. S. Jin, D. Lee, K. Kim, K. Tam. “When K-Pop Meets Blockchain: An Empirical Exploration of Voting Behavior via DAO”. Working paper.

Research Agenda 2: Regulated Digital Currencies

The designs of regulated digital currencies, like Central Bank Digital Currency (CBDC), are complex and involve a trade-off between system features. My research aims to provide solutions to CBDC implementation and their adoptions of consumers and merchants.

Academic Papers

  1. M. Dordal i Carreras, K. Kawaguchi, S. Jin, H. Guo. “Consumer Perceptions and Willingness to Adopt rCBDCs Before and After the e-HKD Pilot”. Working paper. [Paper]

  2. Joint with K. Kawaguchi and M. Dordal i Carreras. “Informational Experiment on Consumer’s Perception of Central Bank Digital Currency as Liquidity Assets”. Working paper.

Policy Papers

  1. Joint with HKUST School of Business and Management and HSBC Holdings plc (2023). “e-HKD Pilot Programme”. [Summary] [Hong Kong Monetary Authority Report].

  2. Y. Xia, S. Jin, B. Qu, Y. Liu, L Yang. Joint with HSBC Bank (Singapore) Limited and HSBC Holdings plc (2021). “Global CBDC Challenge Report”. Awarded as Global CBDC Challenge Finalist (Top 5% in over 300+ submissions from 50+ countries) [Monetary Authority of Singapore Report]

Research Agenda 3: IT Management

  1. S. Jin, Y. Xia, K. Tam. “Do Software Performance Measurement Systems Increase Code Productivity? Evidence from a Quasi-Experiment”. Working paper.

    • 2024 HKUST Business PhD Student Conference

  2. S. Jin, K. Tam, B. Zeng, Q Shao, Y Huang, Y. Xia, B Zhu, Z Li. “Can Analogical Principles Help Quantum Computing Adoption? Evidence from Quantum Monte Carlo Analysis”. Working paper.

  1. Y. Zhang, S. Jin, B. Zeng. “Quantum Tokens via Cloud: A Practical and Quantum-Resistant Digital Token Protocol”. Working paper.

Conferences

  1. S. Jin, Z Li, B. Chen, B. Zhu, Y. Xia (2023). “Software Code Quality Measurement: Implications from Metric Distributions”. 23rd IEEE International Conference on Software Quality, Reliability, and Security, Chiang Mai, Thailand. (QRS 2023). Short paper with oral presentaiton. Acceptance Rate: 21.47%. [Paper] [Slides] [IEEE]

    Abstract: Software code quality is a construct with three dimensions: maintainability, reliability, and functionality. Although many firms have incorporated code quality metrics in their operations, evaluating these metrics still lacks consistent standards. We categorized distinct metrics into two types: 1) monotonic metrics that consistently influence code quality; and 2) non-monotonic metrics that lack a consistent relationship with code quality. To consistently evaluate them, we proposed a distribution-based method to get metric scores. Our empirical analysis includes 36,460 high-quality open-source software (OSS) repositories and their raw metrics from SonarQube and CK. The evaluated scores demonstrate great explainability on software adoption. Our work contributes to the multi-dimensional construct of code quality and its metric measurements, which provides practical implications for consistent measurements on both monotonic and non-monotonic metrics.

  2. Y. Liu, C. Xu, S. Jin. “Reinforcement Learning for Continuous Control: A Quantum Normalized Advantage Function Approach”. IEEE Services - 4th International Conference on Quantum Software, Chicago, USA. (SERVICE 2023). Corresponding Author, Average Acceptance Rate: 21.50%. [Paper] [Code]

  3. S. Jin, B. Xu, P. Intallura, Y. Xia. “A UTXO-based Sharding Method for Stablecoin”. 4th IEEE International Conference on Blockchain Computing and Applications, San Antonio, USA. (BCCA 2022). Short Paper with Oral Presentation. [Paper] [Code]

    Abstract: We propose a UTXO-based sharding method to achieve horizontal scalability in a token-based system, including stablecoin. The critical challenge of the current sharding method is that introducing extra cross-shard transactions significantly impacts transaction latency. Previous solutions use account-based sharding to improve transaction volume, increasing latency. We propose a new method that improves transaction throughput linearly while keeping latency low by reducing cross-shard transactions. We were able to verify our solution through experiments.

Patent

  1. B. Zhu, Y. Xia, Z. Li, S. Jin. (2024). “Network Analysis using optical quantum computing”. International Bureau, World Intellectual Property Organization. Publication No. WO2024/007565 A1.

  2. S. Jin, Y. Xia. (2024). “Method for implementing network consensus algorithm”. International Bureau, World Intellectual Property Organization. Publication No. WO2024/007483 A1.

  3. S. Jin, Y. Xia. (2024). “Transaction security for multi-tier transaction networks”. International Bureau, World Intellectual Property Organization. Publication No. WO2024/007527 A1.

  4. S. Jin, Y. Xia. (2024). “Blockchain transaction sharding for improved transaction throughput.” International Bureau, World Intellectual Property Organization. Publication No. WO2024/011707 A1.

Supervising

  • 2024.02 ~ now: Jieliang Yin (research assistant for CBDC project).
  • 2022.10 ~ now: 7 Msc students on their year-level research projects (Co-supervised with Prof. Bei Zeng, Prof. Qiming Shao, Yuhan Huang and Yichi Zhang)
    • After their research projects, Chang Xu, Shiguang Zhang, and Jiahui Wu got Ph.D. offers.
    • Y. Liu received the Best Presentation Award of DDM 6980 Project Presentation.
    • [Details]

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