Digital Commons Network^™

Techno-Geopolitics And Semi-Conductor Chokepoints: Beyond The Us-China Wto Dispute, Han-Wei Liu, Ching-Fu Lin

Research Collection Yong Pung How School Of Law

Much ink has been spilled on the US-China tech and trade war, particularly the role of US export controls in containing China and preserving America’s tech dominance. Less attention, however, has been paid to other critical nodes in the global semiconductor supply chain – Taiwan, South Korea, Japan, and the Netherlands – which we coin as ‘chokepoint economies’. Taiwan alone produces over 90% of the world’s most advanced chips, vital to the digital age and the future of AI in the Indo-Pacific and beyond. Using Taiwan as a case study, this paper shows how chokepoint economies navigate competing pressures amid …

On Sgx’S Voyage To Corporate Sustainability: Exploring Emerging Topics In Multi-Industry Corpora, Xinwen Ni, Min Bin Lin, Simon J.D. Schillebeeckx, Wolfgang Karl Hardle

Research Collection Lee Kong Chian School Of Business

Topic modeling and LDA (Latent Dirichlet Allocation) have proven valuable in various fields as an innovative approach to studying areas of interest and identifying topics in a dynamic content. The underlying assumption is that techniques like LDA can swiftly capture emerging topics in textual documents compared to other categorization tools. These unsupervised approaches have been used to identify new industries and technological domains. However, our study on the nascent topic of “sustainability” within the corpora of SGX-listed companies highlights clear limitations in employing techniques like LDA on sparse data. The dynamic LDA approach, also called DTM (Dynamic Topic Modelling),based on …

The Gender Effects Of Covid: Evidence From Equity Analysts, Frank Weikai Li, Baolian Wang

Research Collection Lee Kong Chian School Of Business

We use COVID-19 and sell-side analysts as an experiment to study the effects of gender on labor productivity. We find that the forecast accuracy of female analysts declined more than that of male analysts, especially when schools were closed and among analysts who were more likely to have young children, were inexperienced, were busier, or lived in southern states of the US. Relative to male analysts, females also reduced their forecast timeliness and resorted to more heuristic forecasts but did not reduce coverage or updating frequency. Relative to pre pandemic, female analysts’ careers were more negatively affected than male analysts’. …

Capacity Investment In The Presence Of Correlated Demand And Production Resource Uncertainties And Its Implications For Financial Hedging, Onur Boyabatli, Guiyun Feng

Research Collection Lee Kong Chian School Of Business

In manufacturing firms, besides demand uncertainty, capacity investment decisions may also be subject to uncertainty in the availability of a production resource (e.g., budget or commodity component) which may become constraining for manufacturing. When the production resource uncertainty is tied to a financial index (e.g., asset or commodity price), the firm can enter into financial hedging contracts at the time of capacity investment to engineer this uncertainty. Our paper characterizes the optimal capacity investment and hedging decisions and examines how production resource uncertainty impacts the firm’s decisions, profitability, and the value of hedging. We identify three key drivers of these …

The Pricing Of Green Bonds And The Determinants Of The Green Bond Premium In The Asia-Pacific And European Markets, Parath Wongaree, Chiyachantana N. Chiraphol, Kuan Yong David Ding, Pattarawan Prasarnphanich, Wasin Siwasarit

Research Collection Lee Kong Chian School Of Business

This study examines the sources of capital for sustainable development and investigates the existence of a green bond premium in both primary and secondary bond markets across the Asia-Pacific and European regions. Utilizing the robust Coarsened Exact Matching (CEM) method in conjunction with the Synthetic Minority Oversampling Technique (SMOTE), our analysis reveals a significant disparity in yields between green bonds and conventional bonds within the Asia-Pacific markets, indicating the existence of a green bond premium. In contrast, this distinction is not observed in Europe. These findings suggest that investors in the Asia-Pacific region display a willingness to accept lower yields …

Business Schools And The External Environment: Where Are They Now?, Kai Peters, Howard Thomas, Michael Thomas

Research Collection Lee Kong Chian School Of Business

The article, the first of a two-part series, takes a look at the external environment facing business schools today. Major factors considered include the global landscape and related populism, funding shortfalls, increasing regulatory burdens, increased competition, and artificial intelligence. This combination of challenges, together with factors that are internal to business schools and universities and will be examined in an article later in the year, means that it is not an easy time to be the dean of a business school. Protecting present income streams, developing new sources of funds, and being agile are all paramount.

From Data To Discovery: Empowering Research With Comprehensive Library Services At Smu Libraries, Redzuan Abdullah

Research Collection Library

Academic libraries face increasing challenges in supporting complex research data needs across multiple financial and business databases. These challenges are amplified by the diverse nature of data sources, the intricacy of data extraction processes, and the varying levels of research support required by different user groups. While data quality issues persist, commercial databases in finance, accounting, and economics remain of significant interest for academic research (Liu et al., 2024; Reiter, 2020).

This presentation presents SMU Libraries’ comprehensive research & data services, particularly our specialized Data Discovery support, which emphasizes three distinctive offerings: expert guidance on data navigation and retrieval across …

Shareholder Satisfaction Or Societal Benefit? Coalition Support And Goal Prioritization, Man Zhang, Helen Hu, Toru Yoshikawa

Research Collection Lee Kong Chian School Of Business

Research on the behavioral theory of the firm has established that the profitability goal triggers various firm actions, but it has yet to thoroughly explore which other goals may gain prominence in directing firm resources if the profitability goal has been achieved. We identify shareholder satisfaction and societal benefit as two additional organizational goals and predict that when firms have achieved their profitability aspirations, the financial resources allocated to pursue these goals depend on the dominance of coalitions supporting or opposing them. Drawing on the coalition theory within the behavioral theory of the firm, we theorize that the prioritization and …

Tba Trading And Security Issuance In The Agency Mbs Market, Yu An, Wei Li, Zhaogang Song

Research Collection Lee Kong Chian School Of Business

In addition to the standard individual-security-based specified pool (SP) contract, agency mortgage-backed securities (MBS) are actively traded via the to-be-announced (TBA) contract that sets a uniform price for a cohort of heterogeneous securities. We provide empirical support for the economic impact of TBA trading on MBS issuers' security design: issuers pick low-quality loans and pool them together into few TBA MBS. We then conduct a quantitative analysis and show that TBA-trading-induced strategic MBS design increases issuers' selling revenue by about 55% of the SP transaction costs. Finally, we show that smaller issuers are less able to package low-quality loans separately …

Toward Whole-Person Fit Assessment: Integrating Interests, Values, Skills, Knowledge, And Personality Using The Occupational Information Network (O*Net), Zihan Liu, Kevin A. Hoff, Chu Chu, Frederick L. Oswald, James Rounds

Research Collection Lee Kong Chian School Of Business

Measuring person–occupation fit serves many important purposes, from helping young people explore majors and careers to helping jobseekers assess fit with available jobs. However, most existing fit measures are limited in that they focus on single individual difference domains without considering how fit may differ across multiple domains. For example, a jobseeker might be highly interested in a job, yet not possess the requisite skills or knowledge to perform the job well. The current research addresses this issue by evaluating an integrative set of person–occupation fit assessments that measure 88 fit dimensions across five domains: vocational interests, work values, knowledge, …

Sensors And Sensibilities: Exploring Interactions For Habitat Comfort With An Environmental-Physiological Sensing Eyewear In The Wild, Sailin Zhong, Patrick Chwalek, Nathan Perry, David Ramsay, Clayton Miller, Denis Lalanne, S. Hamed Alavi, A. Joseph Paradiso

Research Collection College of Integrative Studies

Buildings increasingly incorporate sensing and actuation techniques to automate the regulation of temperature, lighting, ventilation, and more. This trend seeks to minimize human intervention, justified by the promise of enhancing energy optimization. However, it has been widely acknowledged that loss of control over environmental conditions can lead to a diminished perception of comfort and compromised long-term user awareness and satisfaction. How can we envision building systems that can interact with building inhabitants and engage them at the “right” time and place? In this work, we address this challenge through three key contributions: 1) AirSpecs, a novel smart glasses-based system that …

Educating Indians, Learning ‘Indianness’: Navigating Pluralistic Educational Infrastructures In Diasporic Singapore, Emma Grimley, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

This paper advances the idea of ‘educational infrastructures’ to explore the slippages created by national education frameworks and the everyday ways in which citizen-subjects learn to be part of an ethno-cultural community. In doing so, we tease apart the differences between education as a top-down process of citizen-making and learning as a poly-directional assemblage of behaviours and influences that permeate the socio-spatial landscapes of ethnic belonging. We illustrate these theoretical arguments through an analysis of Singapore’s diasporic Indian community and the collapse of linguistically and culturally complex community backgrounds under the Mother Tongue policy. This leads to a pluralisation of …

Shipnavisim: Data-Driven Simulation For Real-World Maritime Navigation, Quang Anh Pham, Janaka Chathuranga Brahmanage, Akshat Kumar

Research Collection School Of Computing and Information Systems

Maritime traffic management in busy ports faces growing challenges due to increased vessel traffic and complex waterway interactions. Strategies such as e-navigation by the International Maritime Organization aim to enhance navigation safety through traffic digitization. Maritime traffic simulation is essential for these systems, offering a virtual environment to model, analyze, and optimize traffic flows. Unlike road traffic, there are few simulators for maritime traffic, and they often lack realism and multi-ship interactions. In this paper, we (a) present ShipNaviSim, a data-driven maritime traffic simulator that utilizes a large-scale dataset over 2 years and electronic navigation charts to model vessel movements …

Few-Shot Learning On Graphs: From Meta-Learning To Llm-Empowered Pre-Training And Beyond, Yuan Fang, Yuxia Wu, Xingtong Yu, Shirui Pan

Research Collection School Of Computing and Information Systems

Graph representation learning has become central to many graph-based tasks, driving advancements in various domains such as web search, recommendation systems, and social network analysis. Traditionally, these methods rely on end-to-end supervised learning paradigms that require abundant labeled data, which can be costly and difficult to obtain. To address this limitation, few-shot learning on graphs has emerged as a promising approach, allowing models to generalize with minimal supervision and overcome data scarcity in real-world applications. This tutorial offers an in-depth exploration of recent advancements in few-shot learning for graphs, providing a comparative analysis of state-of-the-art methods and identifying future research …

“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono

Research Collection School Of Computing and Information Systems

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The …

Unlocking The Planning Capabilities Of Llms Through Maximum Diversity Fine-Tuning, Wenjun Li, Changyu Chen, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have demonstrated impressive task-solving capabilities through prompting techniques and system designs, including solving planning tasks (e.g., math proofs, basic travel planning) when sufficient data is available online and used during pre-training. However, for planning tasks with limited prior data (e.g., blocks world, advanced travel planning), the performance of LLMs, including proprietary models like GPT and Gemini, is poor. This paper investigates the impact of fine-tuning on the planning capabilities of LLMs, revealing that LLMs can achieve strong performance in planning through substantial (tens of thousands of specific examples) fine-tuning. Yet, this process incurs high economic, time, …

Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

There has been significant interest in the development of personalized and adaptive educational tools that cater to a student's individual learning progress. A crucial aspect in developing such tools is in exploring how mastery can be achieved across a diverse yet related range of content in an efficient manner. While Reinforcement Learning and Multi-armed Bandits have shown promise in educational settings, existing works often assume the independence of learning content, neglecting the prevalent interdependencies between such content. In response, we introduce Education Network Restless Multi-armed Bandits (EdNetRMABs), utilizing a network to represent the relationships between interdependent arms. Subsequently, we propose …

Government Guidance Funds And Corporate Innovation: An Empirical Examination Based On Hangzhou, Huaping Wang

Dissertations and Theses Collection (Open Access)

Since the establishment of China's first market-oriented government guidance fund in 2002, these funds have actively played a supportive role in addressing market failures and promoting the innovative development of technology enterprises by reducing information asymmetry in the primary equity market, releasing positive signals, and alleviating financing constraints. With the establishment and development of China's multi-tiered government guidance fund system, related research has gradually emerged. However, current studies primarily explore whether government guidance funds have fulfilled their role in fostering innovation from a macro perspective, with limited in-depth discussion from a micro-level on how these funds should conduct their investment …

Research On The Structural Antecedents And Contingencies Of Fluid Team Performance, Xiaodong Zhang

Dissertations and Theses Collection (Open Access)

In response to rapidly evolving markets and the pursuit of organizational agility, fluid teams—characterized by dynamic membership and flexible structures—have become prevalent as a key organizational form for addressing complex tasks and uncertainty. However, inherent challenges such as frequent member mobility and multiple project participation pose significant management difficulties and performance risks, including project delays and cost overruns, particularly evident in China's fintech sector. While existing research has begun examining fluid teams, systematic investigation into their structural antecedents and performance mechanisms—especially their contingencies across contexts—remains limited.

The study examines structural antecedents and contingencies of fluid team performance through a mixed-methods …

Threads Of Time: A Lifespan Perspective On Temporal Simulations, Self-Continuity And Meaning In Life, Jonathan Louis Jie Sheng Chia

Dissertations and Theses Collection (Open Access)

This research investigates how temporal simulations—prospection and retrospection — influence meaning in life (MIL) through the mediating role of self-continuity, and whether these relationships vary with age. Across two studies, self-continuity mediated these associations, but the specific pathways appeared to be nuanced. In Study 1, using a correlational design, frequency of prospection and retrospection positively and negatively predicted MIL via self-continuity respectively. These indirect effects, however, became nonsignificant when accounting for personality and dispositional affect, suggesting the effects of temporal simulation frequency to be primarily driven by these individual differences. Study 2 experimentally manipulated temporal simulations. Prospection enhanced MIL through …

Generative Artificial Intelligence Dependency: Scale Development, Validation, And Its Motivational, Behavioral, And Psychological Correlates, Adalia Yin Hui Goh

Dissertations and Theses Collection (Open Access)

The growing integration of generative artificial intelligence (AI) into everyday life has raised questions about its potential psychological and behavioral consequences. The present research develops and validates the Generative AI Dependency Scale, a multidimensional tool developed to assess individual differences in dependency on generative AI systems. Across six studies involving 1,223 participants from the United States and Singapore, the Generative AI Dependency Scale demonstrated strong psychometric properties, including a stable three-factor structure (cognitive preoccupation, negative consequences, withdrawal) and good test-retest reliability (ICC = .85). Confirmatory factor analysis supported a higher-order dependency construct, and scalar measurement invariance was established across sex …

Diversity-Augmented Training For Generalizable Ai Agents, Wenjun Li

Dissertations and Theses Collection (Open Access)

Deep Reinforcement Learning (RL) has achieved remarkable success over the past decade, from superhuman performance in video games to real-world applications like robotics. However, RL models often lack generalization, making them unreliable when deployed in unfamiliar scenarios. For example, robots must adapt to varying terrains with different slopes and obstacles, yet standard RL training does not explicitly promote such adaptability. While various methods have been proposed to enhance RL robustness, achieving reliable generalization remains an open challenge.

This dissertation focuses on improving the generalization capability of agents in three major settings: infinite horizon RL agents, finite horizon RL agents, and …

To Mitigate Or Adapt? A Construal Level Perspective On Agenda Setting For Climate Action, Shu Tian Ng

Dissertations and Theses Collection (Open Access)

Climate change is no longer a distant threat, but a present crisis—making the question of how we act timelier than whether we act. This research investigates how people evaluate different approaches to climate action—specifically, mitigation (reducing emissions) and adaptation (coping with impacts)—through the lens of the Construal Level Theory (Liberman & Trope, 1998; Trope & Liberman, 2010). Across three studies, I examined how perceptions of desirability and feasibility influence preferences for different climate action strategies. Study 1 found that, to laypeople, mitigation was perceived as more desirable while adaptation was perceived as more feasible. Study 2 attempted to manipulate individuals’ …

Asia Pacific Business School Librarians Group Highlights, Sumita Govindan

Research Collection Library

Summary of new initiatives that have been undertaken, challenges faced and emerging opportunities from the APBSLG Member Institutions. This presentation is part of updates from the Chairs of the respective groups.

To Lead Or Not To Lead? How Smu Libraries’ Ellssa Program Can Help Develop Leaders For The Future, Rajendra Munoo, Sumita Govindan

Research Collection Library

Digital libraries exist symbiotically with traditional physical libraries creating an ecosystem of hybrid services built around innovation and creativity. Leading the digital library requires the ambidexterity to keep up to date with trends and developments and be a catalyst to lead change management. With the pandemic, academic libraries learnt to become champions of agility in transforming their services to meet the new demands and needs of the community they serve. Libraries are now facing new challenges; the disbanding of the Institute of Museum and Library Services in the United States, the rising threats of censorship, and the gradual erosion of …

Evaluation Of Pre-Trained Vision Language Models In Challenging Contexts, Kankan Zhou

Dissertations and Theses Collection (Open Access)

The rapid advancement and proliferation of pre-trained vision-language models (VLMs) have heralded a new era in the realm of artificial intelligence (AI), opening up unprecedented opportunities and challenges alike. This dissertation sets forth on an ambitious and comprehensive journey to critically evaluate the performance and limitations of pre-trained VLMs, particularly in complex and challenging contexts that test the bounds of their capabilities. Our focus is twofold: to rigorously assess the extent of bias embedded in these models, and to meticulously scrutinize their reasoning abilities, highlighting parallels and disparities between machine and human cognition.

We initiate our exploration with a targeted …

Hdwsa2: A Secure Hierarchical Deterministic Wallet Supporting Stealth Address And Signature Aggregation, Xin Yin, Zhen Liu, Guomin Yang, Guoxing Chen, Haojin Zhu

Research Collection School Of Computing and Information Systems

Hierarchical Deterministic Wallet (HDW) and Stealth Address (SA) are widely used in cryptocurrency communities due to their functionality and security. In the preliminary version of this work (ESORICS 2022), we formally define the syntax and security models of Hierarchical Deterministic Wallet supporting Stealth Address (HDWSA), capturing the functionality and security requirements imposed by the practice in cryptocurrency. We propose a concrete HDWSA construction and prove its security in the random oracle model. Note that when applied in blockchain, in practice, signature aggregation could reduce the cost of computation, storage, and communication dramatically. In this full version, we develop HDWSA definition …

Rotation-Adaptive Point Cloud Domain Generalization Via Intricate Orientation Learning, Bangzhen Liu, Chenxi Zheng, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Shengfeng He

Research Collection School Of Computing and Information Systems

The vulnerability of 3D point cloud analysis to unpredictable rotations poses an open yet challenging problem: orientation-aware 3D domain generalization. Cross-domain robustness and adaptability of 3D representations are crucial but not easily achieved through rotation augmentation. Motivated by the inherent advantages of intricate orientations in enhancing generalizability, we propose an innovative rotation-adaptive domain generalization framework for 3D point cloud analysis. Our approach aims to alleviate orientational shifts by leveraging intricate samples in an iterative learning process. Specifically, we identify the most challenging rotation for each point cloud and construct an intricate orientation set by optimizing intricate orientations. Subsequently, we employ …

Enhancing Sub-Optimal Trajectory Stitching: Spatial Composition Rvs For Offline Rl, Sheng Zang, Zhiguang Cao, Bo An, Senthilnath Jayavelu, Xiaoli Li

Research Collection School Of Computing and Information Systems

Reinforcement learning via supervised learning (RvS) has been known as a burgeoning paradigm for offline reinforcement learning (RL). While return-conditioned RvS (RvS-R) predominates across a wide range of datasets pertaining to the offline RL tasks, recent findings suggest that goal-conditioned RvS (RvS-G) outperforms in specific sub-optimal datasets where trajectory stitching is crucial for achieving optimal performance. However, the underlying reasons for this superiority remain insufficiently explored. In this paper, employing didactic experiments and theoretical analysis, we reveal that the proficiency of RvS-G in stitching trajectories arises from its adeptness in generalizing to unknown goals during evaluation. Building on this insight, …

Three Essays On Robust Mechanism Design, Kexin Wang

Dissertations and Theses Collection (Open Access)

This dissertation consists of three chapters that study the mechanism design problems when the designer does not completely know the economic environments. In the first chapter, we study the design of contracts when the principal has limited statistical information about the output distributions induced by the agent’s actions. In the baseline model, we consider a principal who only knows the mean of the output distribution for each action. The mean restrictions allow for a large set of profiles of output distributions, including some extreme output distributions that can be used to establish the robust optimality of increasing affine contracts. Motivated …