Digital Commons Network^™

Do Supplier Ceo's National Cultural Origins Affect Supplier-Customer Relationships?, Peng Liang, Hasan Cavusoglu, Nan Hu

Research Collection School Of Computing and Information Systems

This study investigates how the national cultural origins of supplier chief executive officers (CEOs), as characterized by Hofstede’s cross-cultural dimensions, influence the duration of supplier–customer relationships. By analyzing the cultural origins of supplier CEOs from 20 countries over a 25-year period, we find that supplier CEOs with high long-term orientation (LTO) and high uncertainty avoidance (UNA) are associated with longer lasting supplier–customer relationships, while those with high individualism (IND) are associated with shorter relationship durations. These findings are robust to several alternative explanations of customer and supplier CEO variables. To address potential endogeneity—specifically, the concern that CEOs with certain cultural …

Wa-Fdnet: A Unified Weight Adaptation Network For Multimodal Image Fusion And Object Detection, Yanyin Guo, Ying Luo, Junwei Li, Zhiyuan Zhang

Research Collection School Of Computing and Information Systems

Multimodal image fusion and object detection are critical tasks in computer vision, particularly in scenarios requiring robust perception under low illumination conditions. Existing approaches that attempt to combine these tasks often rely on cascaded or loosely coupled designs, which can result in suboptimal performance due to gradient conflicts and task imbalance. In this paper, we propose WA-FDNet, a novel Weight Adaptation Fusion Detection Network that unifies multimodal image fusion and object detection into a single end-to-end framework. WA-FDNet adopts a shared encoder–private decoder architecture, enabling efficient feature sharing while preserving task-specific characteristics. The image fusion branch employs a spatial attention-based …

Mindfulness And Entrepreneurship: Looking Back And Moving Forward, Eva Katharina Peters

Dissertations and Theses Collection (Open Access)

This dissertation spans three chapters covering the topics of mindfulness and entrepreneurship. The first chapter is a literature review summarizing the existing literature on mindfulness in entrepreneurship. The review provides an organizing framework for structuring the knowledge of mindfulness in entrepreneurship, along with an integrative framework and a detailed agenda for future research. Building on the insights generated through the literature review, the following two chapters provide empirical evidence for the role of mindfulness in entrepreneurship. The second chapter is an empirical study exploring how mindfulness relates to entrepreneurial well-being via its relation to co-founding team relationship quality and team …

Modeling Multiple Tasks In Recommendation Systems, Dinh Hieu Do

Dissertations and Theses Collection (Open Access)

Traditional research in recommendation systems has largely centered on the static offline supervised learning setting. In this paradigm, all available user-item interaction data is collected and partitioned into fixed training, validation, and test sets. Models are developed and evaluated in this controlled environment, where the underlying data distribution is assumed to remain unchanged. This approach offers clear advantages: it simplifies experimentation, enables reproducible benchmarking, and allows for straightforward comparisons between algorithms.

However, this static offline setting does not reflect the realities faced by modern recommendation systems. In real-world applications, data is dynamic and ever-evolving, where new users and items are …

From Sparse Feedback To Sequential Decision-Making: Learning Safety Constraints With Weak Supervision, Siow Meng Low

Dissertations and Theses Collection (Open Access)

Real-world decision-making often involves safety constraints that are implicit, non-Markovian, or difficult to specify directly. Standard reinforcement learning (RL) approaches typically assume access to fully specified cost functions and constraint budgets—assumptions that limit their applicability in domains where such structure must instead be inferred from data. This dissertation develops a sequence of methods for learning safety-relevant structure from weak supervision, such as sparse binary feedback on trajectory segments, and using these signals to guide planning and policy optimization.

The first part of the dissertation introduces a sample-efficient method for planning in continuous Markov Decision Processes (MDPs) using deep reactive policies. …

Calibrated Structures Of Feeling: Cultural Citizenship And The Reproduction Of The Military In Singapore, John Lowe, George Wong

Research Collection School of Social Sciences

This article discusses the nexus between Raymond Williams’ structure of feelings and the reproduction of military masculinity as cultural citizenship. By placing the gaze upon National Service in the Singapore Armed Forces as a rite of passage into manhood, this work uses representations of the military in popular culture and souvenirs/ephemera to elucidate how structures of feeling are calibrated as masculinity the state wants its citizenry to internalize. These render military masculinity emergent for Singaporean male bodies. With the male body functioning as an important edifice of the military, emotions toward military service are the connective tissue between enactments of …

Artificial Insights Or Historical Fidelity? Crafting An Ethical Framework For The Use Of Genai In The Restoration, Reconstruction And Recreation Of Movable Cultural Heritage, David Ocón, Chunzhi Yin, Jose Luna

Research Collection School of Social Sciences

This article explores the ethical considerations surrounding using Generative Artificial Intelligence (GenAI) in preserving movable cultural heritage, focusing specifically on its application in restoration, reconstruction, and recreation. While GenAI offers innovative methods for preserving and recreating cultural heritage, it also presents significant ethical challenges. The article reviews current studies on the role of GenAI in heritage preservation alongside relevant ethical guidelines and proposes a tailored ethical framework for its application in movable heritage. The framework addresses several critical ethical concerns, including cultural integrity and sensitivity, accuracy and authenticity, intellectual property rights, sustainability and social impact, and governance and ethical accountability. …

Singapore At 60: Home Truly Is An Idea That Never Stands Still, Lily Kong

Research Collection School of Social Sciences

There are many new stories to embrace but also quiet distances between us that we must bridge.

In a National Day op-ed published in The Straits Times, SMU President Professor Lily Kong reflects on what ‘home’ means as Singapore marks its 60th year of independence — and how that meaning continues to evolve across generations. Prompted by a walk through a familiar playground now transformed, Prof Kong considers how Singapore’s changing physical and social landscape mirrors shifts in national identity. While progress and policy evolution signal a society in transition, she also notes the emergence of quieter divides – between …

Analyzing Google Maps As A Data Source For Urban Research In Dhaka, Xinyi Du

Dissertations and Theses Collection (Open Access)

This paper investigates how mass transit infrastructure shapes urban economic activity by examining the impact of Dhaka's first metro line using novel Google Maps data. Leveraging the opening of Metro Line 6 on December 2022, we employ a difference-in-differences framework to analyze changes in business establishment density around metro stations. Our estimates show that every 1% reduction in distance to the nearest metro station adds, on average, about 0.092–0.111 establishments per 40 m × 40 m grid cell—that is, roughly 57 – 69 additional businesses per square kilometer. The effect is even more pronounced for dining: about 1 – 4 …

Machine Learning For Digital Biomarker-Based Detection Of Cognitive Decline, Seng Khoon The

Dissertations and Theses Collection (Open Access)

Dementia is a neurodegenerative disease with a prevalence rate expected to triple by 2050, posing a significant challenge for health services. To impede the increasing prevalence, medical professionals and scientists are actively investigating technology to detect cognitive decline at a reversible stage known as Mild Cognitive Impairment (MCI). Digital biomarker technology is an emerging pragmatic approach to permit objective, ecologically valid, and long-term continuous measurement of cognitive health status, rendering it as one of the promising technologies for early MCI detection. Despite its potential, it is nontrivial to encode, extract and combine predictive information from these digital biomarker technologies; advanced …

The Rising Returns To R&D: Ideas Are Not Getting Harder To Find, Yoshiki Ando, James Bessen, Xiupeng Wang

Research Collection School Of Economics

R&D has grown robustly, yet aggregate productivity growth has stagnated. Is this because “ideas are getting harder to find”? Using microdata from the US Census Bureau this paper estimates R&D effectiveness in the manufacturing sector from 1976 to 2018. We find that the marginal effect of R&D on output and the gross marginal returns to R&D have risen sharply. But rivals’ R&D has also gotten more effective, raising expected obsolescence. But firm productivity growth rises with growth in the R&D stock. Higher obsolescence slows the accumulation of R&D capital, reducing the contribution to productivity growth and shortening innovation lives.

Evaluating Chatgpt To Answer Multi-Modal Exercises In Computer Science Education, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo, Benjamin Gan

Research Collection School Of Computing and Information Systems

This study investigates ChatGPT-4o's ability to answer multi-modal assessment exercises in computer science (CS) courses. While the use of large language models (LLMs) to answer text-based exercises are extensively researched, their ability to answer exercises involving artifacts of other modalities remains underexplored. To close this gap, we evaluate ChatGPT-4o's answers to 120 multi-modal CS exercises in programming, software design, human-computer interaction, statistical analysis, process analysis, and simulation. The multi-modal artifacts in these exercises include class diagrams, sequence diagrams, user interface images, analytical charts, workflow diagrams and object-flow diagrams. Our comparisons to the expected answers of these exercises show that ChatGPT-4o …

An On-The-Fly Synthesis Framework For Ltl Over Finite Traces, Shengping Xiao, Yongkang Li, Shufang Zhu, Jun Sun, Jianwen Li, Geguang Pu, Moshe Vardi

Research Collection School Of Computing and Information Systems

We present an on-the-fly synthesis framework for Linear Temporal Logic over finite traces (LTLf) based on top-down deterministic automata construction. Existing approaches rely on constructing a complete Deterministic Finite Automaton (DFA) corresponding to the LTLf specification, a process with doubly exponential complexity relative to formula size in the worst case. In this case, the synthesis cannot be conducted until the entire DFA is constructed. This inefficiency is the main bottleneck of existing approaches. To address this challenge, we first present a method for converting LTLf into Transition-based DFA (TDFA) by directly leveraging LTLf semantics, incorporating intermediate results as direct components …

Query Understanding In Llm-Based Conversational Information Seeking, Yifei Yuan, Zahra Abbasiantaeb, Mohammad Aliannejadi, Yang Deng

Research Collection School Of Computing and Information Systems

Query understanding in CIS involves accurately interpreting user intent through context-aware interactions. This includes resolving ambiguities, refining queries, and adapting to evolving information needs. LLM enhance this process by interpreting nuanced language and adapting dynamically, improving the relevance and precision of search results in real-time. In this tutorial, we explore advanced techniques to enhance query understanding in LLM-based CIS systems. We delve into LLM-driven methods for developing robust evaluation metrics to assess query understanding quality in multi-turn interactions, strategies for building more interactive systems, and applications like proactive query management and query reformulation. We also discuss key challenges in integrating …

The Aggregate Welfare And Trade Implications Of Contracting Frictions In Global Sourcing, Davin Chor, Lin Ma

Research Collection School Of Economics

How much do contracting frictions between global firms and their suppliers impact country welfare and trade? We answer this by developing a model of global sourcing under partial contractibility, where firm-supplier relationships are exposed to a bilateral holdup problem. Sourcing decisions aggregate into a gravity equation for trade flows by organizational mode (intrafirm vs. arm’s length), which we take to structural estimation. We can then evaluate welfare changes with an extended Arkolakis, Costinot and Rodriguez-Clare (2012) formula that incorporates these contracting frictions. Our counterfactual analysis reveals a sizeable average country welfare gain of 9.2% from eliminating contracting frictions in global …

High Frequency Factor Analysis With Partially Observable Factors, Dachuan Chen, Wenqi Lu, Siyu Xie

Research Collection School Of Economics

This paper considers a novel factor structure – Partially Observable Factor Model – where both observable factors and latent factors exist in the model simultaneously. Such factor structure can make sure both interpretability and goodness-of-fit at the same time. Necessary estimation methodologies for this partially observable factor model are developed in this paper for the high frequency data. The proposed estimation methodology is robust to jumps, microstructure noise and asynchronous observation times simultaneously.When the observable factors are exogenous, we provide the estimation theory for the integrated eigenvalues of the residual covariance matrix, which including the bias-corrected estimator, central limit theorem …

The Role Of Private Law In Promoting Building Safety: The Case Of Singapore, Edward S. W. Ti

Research Collection Yong Pung How School Of Law

Singapore is a tiny granite rock situated just north of the equator. Lacking land, and indeed any kind of natural resource, means that the trend for urban development in the city-state will always be densifi cation; 96 per cent of residents in Singapore already live in multi-owned housing, ie high-rise apartments. 1 Singapore is also a rapidly greying nation. 2 It has been observed that persons over 70 years old are four times more vulnerable in the event of a fi re, 3 and fi re safety is a critical aspect of building safety. Safety features and measures in the …

Digital Economy Innovation In The Indo-Pacific: Towards A 'Singapore Effect'?, J.G. Allen, Qiu Xu Martin Liao

Research Collection Yong Pung How School Of Law

This paper examines the rise of Digital Economy Agreements (DEAs) in the Indo-Pacific as a strategic response to digital trade fragmentation and great power competition. Focusing on Singapore’s leadership, we introduce the ‘Singapore Effect’ – a model of regulatory influence distinct from others, such as the ‘Brussels Effect’ and ‘Beijing Effect.’ Unlike market-driven regulatory diffusion, the Singapore Effect emphasizes interoperability, norm entrepreneurship, and mini-lateralism, enabling middle powers to shape digital trade governance. We analyze DEA formation, implementation challenges in national law, and Singapore’s role as a bridge between diverse regulatory regimes. DEAs’ flexible, modular structure allows for incremental regulatory alignment …

Operationalising The Social Licence To Operate Along The Belt And Road: The Case For A Mediation-Focused Approach, Mark Mclaughlin

Research Collection Yong Pung How School Of Law

This article examines the intricate dynamics of community representation and stakeholder influence in the realm of international investment law. More specifically, it considers the most effective method by which to operationalise the concept of the ‘social licence to operate’ when attempting to resolve investor-state disputes. By utilising disputes relating to China’s Belt and Road Initiative as a case study, it is shown that the social impact of foreign investment projects is often a catalyst for arbitration claims. Community interests are insufficiently represented at the stage of procurement or admission of investment, which has led to violent clashes between investors and …

Wild Hogs In The Water: Contested Infrastructural Ecologies Of Reservoir Storage In Texas, Sayd Randle

Research Collection College of Integrative Studies

Reservoirs are developed to store water in reserve for future use. But once built, reservoir sites inevitably hold more than just water, often serving as a key habitat for a range of species. This paper examines how one such animal has transformed water storage facilities and nearby landscapes into contested ground in urbanising areas of Texas, USA. Living around the reservoirs, feral hogs complicate the process of urbanisation by degrading the stockpiled water and infrastructure at the storage sites themselves and by damaging private property throughout the surrounding landscape. Tracking local efforts to manage the hogs, the case study illustrates …

Political Ecologies Of Storage For The 21st Century, Sayd Randle, Matthew Archer

Research Collection College of Integrative Studies

New resource storage arrangements are proliferating rapidly both in terms of physical infrastructures-for the storage of things like "clean" energy, nuclear waste, carbon dioxide, fresh water, and data-and as part of a set of discursive moves that reinforce a vision of a near future world in which problems of climate change mitigation and adaptation in particular (but also issues like energy security, water security, industry growth, etc.) are solved through eco-modernist techno-fixes. This Symposium sketches the contours of a framework we term political ecologies of storage. In doing so, we treat storage as both a potent imaginary and a concrete …

Sensor Lag Adjustments On A Mobile Meteorological Cart In Tropical Environments: A Case Study From An Urban Park In Singapore, Moshe Eliezer Mandelmilch, Sin Kang Yik, Beatrice H. Ho, Graces N. Y. Ching, Peter J. Crank, Winston T. L. Chow

Research Collection College of Integrative Studies

This study adds to the growing literature on mobile platforms by examining the performance of the Singapore MaRTy (SMaRTy) in conducting mobile micrometeorological measurements along a designated route in an urban park in Singapore, reflecting a pedestrian walking experience. The main objective of the study was to calculate the sensor lag for the mobile climate measurements: Air Temperature (TA), and Relative Humidity (RH) of SMaRTy along a designated route in an urban park in Singapore based on data from fixed stations (HOBO sensors) in two significant synoptic meteorological periods during the Northeast and Southwest monsoons. Statistically significant regression models were …

A New City For A New Era: Xiong'an As Showcase Of China's Evolving Urban Ideology, Andrew Stokols

Research Collection College of Integrative Studies

Cities have long been expressions of political ideology in China and elsewhere. During China’s rapid urbanization over the past few decades, “new areas” became popular strategies to promote urban growth, following the success of Shenzhen, widely regarded as China’s first special economic zone. Today under Xi, Xiong’an New Area has become the latest “new area of national significance.” But unlike previous new areas in China, Xiong’an has become wedded to a distinct vision of the urban in Xi Jinping’s China, one in which the excesses of reform-era urbanization are controlled through new forms of affordable housing and finance, new ecological …

An Incentive Mechanism For Privacy Preserved Data Trading With Verifiable Data Disturbance, Man Zhang, Xinghua Li, Bin Luo, Yanbing Ren, Yinbin Miao, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

To motivate data owners’ (DOs’) trading willingness, the existing incentive mechanisms allow DOs to independently disturb data following data consumer's (DC’s) availability requirement. However, they cannot motivate DOs’ honest disturbance, which is attributed to DOs’ independent disturbance without any supervision. Thus, we implement an incentive mechanism for privacy preserved data trading with verifiable data disturbance where an honest-but-curious disturbance generator (DG) is additionally introduced to supervise DOs’ local disturbance and assist disturbance verification between DOs and DC. Specifically, DG generates the disturbance strategies and secretly distributes to DOs following private information retrieval, guaranteeing DOs's local disturbance's privacy and verifiability with …

An Exponential Cone Integer Programming And Piece-Wise Linear Approximation Approach For 0-1 Fractional Programming, Hoang Giang Pham, Thuy Anh Ta, Tien Mai

Research Collection School Of Computing and Information Systems

We study a class of binary fractional programs commonly encountered in important application domains such as assortment optimization and facility location. These problems are known to be NP-hard to approximate within any constant factor, and existing solution approaches typically rely on mixed-integer linear programming or second-order cone programming reformulations. These methods often utilize linearization techniques (e.g., big-M or McCormick inequalities), which can result in weak continuous relaxations. In this work, we propose a novel approach based on an exponential cone reformulation combined with piecewise linear approximation. This allows the problem to be solved efficiently using standard cutting-plane or branch-and-cut procedures. …

Crow: Eliminating Backdoors From Large Language Models Via Internal Consistency Regularization, Nay Myat Min, Long H. Pham, Yige Li, Jun Sun

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) are vulnerable to backdoor attacks that manipulate outputs via hidden triggers. Existing defense methods—designed for vision/text classification tasks—fail for text generation. We propose Internal Consistency Regularization (CROW), a defense leveraging the observation that backdoored models exhibit unstable layer-wise hidden representations when triggered, while clean models show smooth transitions. CROW enforces consistency across layers via adversarial perturbations and regularization during finetuning, neutralizing backdoors without requiring clean reference models or trigger knowledge—only a small clean dataset. Experiments across Llama-2 (7B, 13B), CodeLlama (7B, 13B), and Mistral-7B demonstrate CROW’s effectiveness: it achieves significant reductions in attack success rates across …

Position: Trustworthy Ai Agents Require The Integration Of Large Language Models And Formal Methods, Yedi Zhang, Yufan Cai, Xinyue Zuo, Xiaokun Luan, Kailong Wang, Zhe Hou, Yifan Zhang, Zhiyuan Wei, Meng Sun, Jun Sun, Jing Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing broad aspects of daily life. Despite their remarkable performance, LLMs exhibit a fundamental limitation: hallucination—the tendency to produce misleading outputs that appear plausible. This inherent unreliability poses significant risks, particularly in high-stakes domains where trustworthiness is essential. On the other hand, Formal Methods (FMs), which share foundations with symbolic AI, provide mathematically rigorous techniques for modeling, specifying, reasoning, and verifying the correctness of systems. These methods have been widely employed in mission-critical domains such as aerospace, defense, and cybersecurity. However, the broader adoption of FMs remains constrained …

Llmscan: Causal Scan For Llm Misbehavior Detection, Mengdi Zhang, Kai Kiat Goh, Peixin Zhang, Jun Sun, Lin Xin Rose, Hongyu Zhang

Research Collection School Of Computing and Information Systems

Despite the success of Large Language Models (LLMs) across various fields, their potential to generate untruthful and harmful responses poses significant risks, particularly in critical applications. This highlights the urgent need for systematic methods to detect and prevent such misbehavior. While existing approaches target specific issues such as harmful responses, this work introduces LLMSCAN, an innovative LLM monitoring technique based on causality analysis, offering a comprehensive solution. LLMSCAN systematically monitors the inner workings of an LLM through the lens of causal inference, operating on the premise that the LLM’s ‘brain’ behaves differently when generating harmful or untruthful responses. By analyzing …

Hps: Hard Preference Sampling For Human Preference Alignment, Xiandong Zou, Wanyu Lin, Yuchen Li, Pan Zhou

Research Collection School Of Computing and Information Systems

Aligning Large Language Model (LLM) responses with human preferences is vital for building safe and controllable AI systems. While preference optimization methods based on PlackettLuce (PL) and Bradley-Terry (BT) models have shown promise, they face challenges such as poor handling of harmful content, inefficient use of dispreferred responses, and, specifically for PL, high computational costs. To address these issues, we propose Hard Preference Sampling (HPS), a novel framework for robust and efficient human preference alignment. HPS introduces a training loss that prioritizes the most preferred response while rejecting all dispreferred and harmful ones. It emphasizes “hard” dispreferred responses — those …

Repairing Adversarial Texts Through Perturbation, Guoliang Dong, Jingyi Wang, Jun Sun, Sudipta Chattopadhyay, Xinyu Wang, Ting Dai, Jie Shi, Jin Song Dong

Research Collection School Of Computing and Information Systems

It is known that neural networks are subject to attacks through adversarial perturbations. Worse yet, such attacks are impossible to eliminate, i.e., the adversarial perturbation is still possible after applying mitigation methods such as adversarial training. Multiple approaches have been developed to detect and reject such adversarial inputs. Rejecting suspicious inputs however may not be always feasible or ideal. First, normal inputs may be rejected due to false alarms generated by the detection algorithm. Second, denial-of-service attacks may be conducted by feeding such systems with adversarial inputs. To address this, in this work, we focus on the text domain and …