Digital Commons Network^™

A Closer Look At The Innovator: The Interplay Between Divergent And Convergent Processes Of Self-Regulation, Ronald Bledow, Hye Jung Eun, Lien Vossaert

Research Collection Lee Kong Chian School Of Business

Creativity and innovation are essential for modern organizations. While abundant research has helped to better understand creativity in everyday work life, considerably less attention has been paid to how individuals achieve creative performance during the implementation of innovation projects. We articulate a dialectical interplay between divergent and convergent processes of self-regulation that supports creative performance in innovation projects. We propose that a divergent exploration orientation contributes to creative performance by inducing a broad search for novelty and by stimulating iteration—repeated cycles of experimentation and refinement. Convergent processes of self-regulation—outcome focus and planning—strengthen the relationship between divergent processes and creative performance. …

Global Value Chains And Economic Inequality, Vivek Soundararajan, Ari Van Assche, Hari Bapuji, Gokhan Ertug

Research Collection Lee Kong Chian School Of Business

In their inaugural editorial, Van Assche and De Marchi (2024) argued that meaningful progress in international business policy requires a more fine-grained understanding of how private international business practices intersect with public policy objectives. This editorial builds on that insight by applying it to a critical yet still underexplored issue – one on which we hope to see more research in this journal: the role of multinational enterprises (MNEs) and global value chains (GVCs) in shaping economic inequality within developing economies. Decisions related to sourcing, contracting, and GVC governance are inherently distributional rather than neutral, with important implications for how …

Collaborative Work Management Technologies And Managerial Intensity In U.S. Corporations: An Examination, Piyush Gulati, Arianna Marchetti, Phanish Puranam

Research Collection Lee Kong Chian School Of Business

Do digital technologies reinforce managerial hierarchies or, instead, make them less relevant? We propose that the answer to this question depends on the nature of the technology: specifically, its relative impact on managers' capacity to supervise and on subordinates' need for supervision. Applying this framework to collaborative work management (CWM) technologies that facilitate real-time collaboration, communication, and task coordination, we predict that the adoption of such technologies should reduce managerial intensity and increase decentralization in organizations. To test this prediction, we use a difference-in-differences design on a novel data set built from over 26 million job listings (Lightcast) and over …

The Smu Trade Dashboard: Tracking And Quantifying The Trump Ii Tariffs, Pao-Li Chang, Ruoqing Chen, Lin Ma

Research Collection School Of Economics

The SMU Trade Dashboard (https://economics.smu.edu.sg/soetrade/tr ade-dashboard), developed by the SMU Center for Research on International Trade, consists of Tariff Tracker and Trade Simulation functions. The Tariff Tracker allows users to track the tariff applicable to an HS 6-digit product or an ISIC 2-digit sector bymarkets and country origins. The Trade Simulation presents quantitative simulation results of the effects of Trump II tariffs (and the associated tariff responses by its trading partners) on trade flows, welfare, and wages. This companion paper documents the methodologies underlying the tariff data collection protocol and the structuralsimulation designs.

Opencil: Benchmarking Out-Of-Distribution Detection In Class Incremental Learning, Wenjun Miao, Guansong Pang, Trong-Tung Nguyen, Ruohuan Fang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Class incremental learning (CIL) aims to learn a model that can not only incrementally accommodate new classes, but also maintain the learned knowledge of old classes. Out-of-distribution (OOD) detection in CIL is to retain this incremental learning ability, while being able to reject unknown samples that are drawn from different distributions of the learned classes. This capability is crucial to the safety of deploying CIL models in open worlds. However, despite remarkable advancements in the respective CIL and OOD detection, there lacks a systematic and large-scale benchmark to assess the capability of advanced CIL models in detecting OOD samples. To …

Improving Credit Card Transaction Fraud Detection Using Cvqboosting, Bethel Hui Ting Loke, Nirvik Sahoo, Bingyan Guan, Minrui Xu, Dev Verma, Paul R. Griffin

Research Collection School Of Computing and Information Systems

This paper introduces a novel hybrid quantum-classical approach to credit card fraud detection using CVQBoost, a hybrid quantum-classical boosting algorithm executed on the photonic Dirac-3 processor from Quantum Computing Inc. (QCi). By integrating a diverse set of weak classifiers, which includes K-nearest neighbours (KNN), linear discriminant analysis, logistic regression, and XGBoost, within a hybrid quantum-classical ensemble, the proposed method demonstrates significant improvements over the latest published classical benchmarks. Experiments on a Kaggle credit card fraud dataset show that the quantum-enhanced model achieves a mean AUC-PR score of over 0.8, corresponding to an approximately 9% relative improvement over the best published …

Navigation Beyond Wayfinding: Robots Collaborating With Visually Impaired Users For Environmental Interactions, Shaojun Cai, Nuwan Janaka, Ashwin Ram, Janidu Shehan, Yingjia Wan, Kotaro Hara, David Hsu

Research Collection School Of Computing and Information Systems

Robotic guidance systems have shown promise in supporting blind and visually impaired (BVI) individuals with wayfinding and obstacle avoidance. However, most existing systems assume a clear path and do not support a critical aspect of navigation—environmental interactions that require manipulating objects to enable movement. These interactions are challenging for a human–robot pair because they demand (i) precise localization and manipulation of interaction targets (e.g., pressing elevator buttons) and (ii) dynamic coordination between the user’s and robot’s movements (e.g., pulling out a chair to sit). We present a collaborative human–robot approach that combines our robotic guide dog’s precise sensing and localization …

Compositions Of Variant Experts For Integrating Short-Term And Long-Term Preferences, Dinh Hieu Do, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In the online digital realm, recommendation systems are ubiquitous and play a crucial role in enhancing user experience. These systems leverage user preferences to provide personalized recommendations, thereby helping users navigate through the paradox of choice. This work focuses on personalized sequential recommendation, where the system considers not only a user’s immediate, evolving session context, but also their cumulative historical behavior to provide highly relevant and timely recommendations. Through an empirical study conducted on diverse real-world datasets, we have observed and quantified the existence and impact of both short-term (immediate and transient) and long-term (enduring and stable) preferences on users’ …

Addressing Graph Heterogeneity And Heterophily From A Spectral Perspective, Kangkang Lu, Yanhua Yu, Ruopei Guo, Nan Cheng, Zhiyong Huang, Yunshan Ma, Meiyu Liang, Yuling Wang, Xiting Qin, Yimeng Ren, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) face two key challenges, heterogeneity and heterophily, which often degrade performance. Existing approaches either focus narrowly on specific meta-paths, limiting their expressiveness, or are expressive but cannot effectively leverage higher-order neighbors. In this paper, we propose the Heterogeneous Heterophilic Spectral Graph Neural Network (H2SGNN), which combines local independent filtering to adaptively handle meta-path subgraphs with varying homophily ratios, and global hybrid filtering to capture high-order neighbor interactions with linear computational complexity. On five heterogeneous graph benchmarks—DBLP, ACM, IMDB, AMiner, and Yelp—H2SGNN consistently outperforms strong baselines, for example, achieving +1.0% Macro-F1 and +1.3% Micro-F1 on IMDB. It …

Using Large Language Models To Analyze Political Texts Through Natural Language Understanding, Kenneth Benoit, Scott De Marchi, Conor Laver, Michael Laver, Jinshuai Ma

Research Collection School of Social Sciences

Large language models (LLMs) offer scalable alternatives to human experts when analyzing political texts for meaning, using natural language understanding (NLU). Qualitative NLU methods relying on human experts are severely limited by cost and scalability. Statistical text-as-data methods are scalable but rely on strong and often unrealistic assumptions. We propose a systematic, scalable, and replicable method that can extend existing qualitative and quantitative approaches by using LLMs to interpret texts meaningfully rather than as mere data. Our ensemble means of LLM-generated estimates of party positions on six key issue dimensions correlate highly with equivalent mean ratings by country specialists. When …

Knowledge Of Lifespan And Healthspan And Interest In Healthy Longevity Medicine Among The General Population In Singapore: The Singapore Healthy Longevity (Helo) Survey, Jonas John Posko Amalaraj, Belinda Wang, Anna Szucs, Louis Island, Laureen Yi-Ting Wang, Liz J. Horberg, Paul A. O'Keefe, Sonny Rosenthal, Yap-Seng Chong, Johannes J. Meij, Andrea B. Maier

Research Collection College of Integrative Studies

Given the growing global interest in Healthy Longevity Medicine (HLM), the field lacks understanding about public knowledge and interest, which are crucial for any public health intervention relying on HLM. This study presents findings from the Healthy Longevity (HELO) survey conducted in Singapore, assessing public knowledge regarding lifespan (number of years a person is alive), healthspan (number of years a person spends in good health), and interest in HLM. This nationwide cross-sectional survey, conducted between June and August 2024, involved 3034 participants. Main domains including questions on demographics, living arrangements, medical information, health behaviours, income and financial status were tested …

Compensation For Victims Of Crimes: Should Victims’ Financial Means And Insurance Coverage Matter? — Criminal Procedure Code 2010, S 359(1); Public Prosecutor V Ong Eng Siew [2025] Sghc 55, Benjamin Joshua Ong

Research Collection Yong Pung How School Of Law

Under s 359(1) of the Criminal Procedure Code 2010, the court can order an offender to compensate the victim with a sum which the victim would have been able to recover in a civil claim in tort against the offender. The courts have used this useful power extensively, though problems remain. One such problem is seen in Ong Eng Siew, where the court declined to make a compensation order. Given the purpose of the compensation system, the court was not correct to hold – in effect – that the purpose of s 359(1) is to benefit only impecunious victims, and …

Living Well: The Built, Lived, And Social Determinants Of Well-Being, Yi Wen Tan, Zidane Tiew, Emi Loh, Shania Go, Wensi Lim

ROSA Research Briefs

As Singapore transitions into a super-aged society, it becomes imperative for us to develop sustainable, inclusive, and effective models of care. In recent years, there has been growing emphasis on embedding healthcare, social services, and everyday amenities within the community. During this year’s National Day Rally, the Government introduced Age Well Neighbourhoods, a new scheme that builds on existing efforts from the Age Well SG initiative. Age Well Neighbourhoods seeks to expand active ageing centre networks, bring healthcare closer to homes with the establishment of community health posts, and provide greater home personal care services, further cementing its focus on …

Obstructive Sleep Apnea Prediction: A Comprehensive Review And Comparative Study, Thi Khanh Chi Huynh, Amonae Dabbs-Brown, Anna Jurek-Loughrey, James Mulhall, Tuan Dung Pham, Ngoc Phu Doan, Viet Hung Tran, Zichi Zhang, Xuan Hoang Nguyen, Yimeng An, Peixin Li, Phi Hung Nguyen, Thi Linh Hoang, Xinming Shi, Hans Vandierendonck, Sebastien Bailly, Jean-Louis Pépin, Thai Son Mai

Research Collection School Of Computing and Information Systems

Obstructive Sleep Apnea (OSA) is a highly prevalent sleep disorder linked to considerable public health burdens and comorbidities. However, its heterogeneous presentation and the limited accessibility of traditional diagnostic tools such as polysomnography (PSG) lead to widespread underdiagnosis. As a result, artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL) models, have attracted attention as an alternative pathway to detection. This paper first provides a comprehensive review of AI-driven OSA diagnosis, covering different diagnosis problems, input-data types, data biases, pre-processing techniques, and model performance. We then leverage the largest clinical dataset used in OSA prediction to date, …

Quantum Chebyshev Transform-Based Graph Neural Networks For Financial Fraud Detection, Minrui Xu, Bingyan Guan, Bethel Hui Ting Loke, Paul R. Griffin

Research Collection School Of Computing and Information Systems

Financial fraud detection is a critical challenge requiring accurate identification of anomalous patterns in complex transaction networks. Graph Neural Networks (GNNs) have emerged as powerful tools for fraud detection by capturing relational structures among entities. Meanwhile, quantum computing offers new possibilities to enhance machine learning through high-dimensional Hilbert spaces and parallelism. In this paper, we propose a hybrid classical-quantum model called QCTGNN (Quantum Chebyshev Transform-based Graph Neural Network) for financial fraud detection. The QCTGNN integrates a classical graph neural network component based on Simplified Graph Convolutions (SGConv) with a quantum component that performs a Chebyshev polynomial-based transform via variational quantum …

The Impact Of Innovation Belief On Strategic Product R&D, Yan Zhou

Dissertations and Theses Collection (Open Access)

In highly uncertain innovation scenarios characterized by long R&D cycles and high risks, how to continuously drive enterprises to develop market-competitive blockbuster products has become a critical issue of shared concern in both practice and academia. Existing research has mostly explained differences in blockbuster product R&D from perspectives such as resource allocation, organizational structure, or institutional incentives, while paying insufficient attention to cognitive and belief factors at the individual level. Based on this, this paper introduces the psychological and cognitive variable of "innovative belief" to systematically examine its impact mechanism on blockbuster product R&D capability.

Taking the R&D team of …

Derivation Of An Updated Brief Multivariable Prediction Model To Detect Panic-Related Anxiety In Emergency Department Patients With Cardiopulmonary Complaints, Sharon C. Sung, Felicia J. L. Ang, Arul Earnest, Leslie E. C. Lim, Shreshtha Jolly, Gilaine Rui Ng, A. John Rush, Marcus E. H. Ong

Research Collection School of Social Sciences

Background Patients with panic related-anxiety (i.e., panic attacks or panic disorder) frequently present to emergency departments (EDs) with cardiopulmonary complaints but are often undiagnosed, which can lead to recurrent visits and prolonged distress. This study aimed to derive a new symptom-based multivariable diagnostic prediction model to detect panic-related anxiety in ED patients with cardiopulmonary symptoms.Methods We conducted a single-blind prospective derivation study over 15 months in the ED of a major tertiary hospital in Singapore. Patients presenting with symptoms of palpitations, chest pain, dizziness, or difficulty breathing were assessed using the Structured Clinical Interview for DSM Disorders (SCID) to diagnose …

Examining The Effects Of Viewing Nature And Animal Smartphone Wallpapers On Affect, Behaviour, And Cognition: A Randomised Cross-Over Trial, Nadyanna M. Majeed, Nicole R. Y. Chen, Adalia Y. H. Goh, Meilan Hu, Kenneth J. J. Koh, Yuolmae H. G. Ang, Andree Hartanto

Research Collection School of Social Sciences

This study aims to investigate the effects of different smartphone lock screen wallpapers on weekly perceived well-being, procrastination, and productivity in young adults. Through a pre-registered within-subject experiment, 60 participants were exposed to three smartphone wallpaper conditions: nature, animal, and neutral (control). Each participant experienced each condition over three weeks, with the order of conditions counterbalanced. Using Frequentist and Bayesian analyses, we did not find any differences between conditions across the pre-registered confirmatory outcomes (i.e., life satisfaction, positive affect, negative affect, stress, productivity, and procrastination). Exploratory outcomes related to lock screen engagement, however, revealed some meaningful effects. Animal-themed smartphone wallpapers …

Less Is More: Docstring Compression In Code Generation, Guang Yang, Yu Zhou, Wei Cheng, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, Xin Zhou, Ke Liu, David Lo, Taolue Chen

Research Collection School Of Computing and Information Systems

The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code generation, LLMs are used to translate function/method signature and DocString to executable code. DocStrings, which capture user requirements for the code and are typically used as the prompt for LLMs, often contain redundant information. Recent advancements in prompt compression have shown promising results in Natural Language Processing (NLP), but their applicability to code generation remains uncertain. Our empirical study shows that the state-ofthe-art prompt compression methods achieve only about 10% reduction, as further reductions …

Fortifying The Seams Between C/C++ And Rust: Characterizing Bugs In Interop Tools, Xuemeng Cai, Jiakun Liu, Cunyang Liu, Lingfeng Bao, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Rust has become increasingly popular in recent years due to its safety and high performance. Despite these advantages, Rust projects rarely start from scratch in practice, and many Rust-based systems instead use hybrid programming, where Rust interoperates with existing C/C++ code. To reduce the manual effort involved in this interoperation (interop) process, several interop tools have been proposed to facilitate hybrid programming between Rust and C/C++. However, the challenges and limitations of these tools remain largely unexplored, leaving developers unclear about the future directions and users unclear about the appropriate usage scenarios. To fill the gap, we mined 320 bugs …

New Asymptotics Applied To Functional Coefficient Regression And Climate Sensitivity Analysis, Qiying Wang, Peter C. B. Phillips, Ying Wang

Research Collection School Of Economics

A general asymptotic theory is established for sample cross moments of nonstationary time series, allowing for long-range dependence and local unit roots. The theory provides a substantial extension of earlier results on nonparametric regression that include near-cointegrated nonparametric regression as well as spurious nonparametric regression. Many new models are covered by the limit theory, among which are functional coefficient regressions in which both regressors and the functional covariate are nonstationary. Simulations show finite sample performance matching well with the asymptotic theory and having broad relevance to applications, while revealing how dual nonstationarity in regressors and covariates raises sensitivity to bandwidth …

Situation Descriptions In Situational Judgment Tests: A Matter Of Including Trait-Relevant Situational Cues?, Philipp Schapers, Stefan Krumm, Filip Lievens, Jan-Philipp Freudenstein, Julian Schulze, Cornelius J. Konig

Research Collection Lee Kong Chian School Of Business

SJTs have traditionally been conceptualized as low-fidelity simulations of how respond to work-related situations. Yet, several studies demonstrated that situation descriptions were necessary to solve some SJT items, whereas they were not needed for other SJT items. So far, no solid support was found for various factors (e.g., item characteristics, presentation format, instructions, and content domain) that make some situation descriptions relevant and others irrelevant for responding to SJT items. Building on trait activation theory, we posit that trait-relevant situational cues serve as an ignored factor in SJT situation descriptions. Across two main studies (N-1 = 269, N-2 = 1,092), …

Are Less Hierarchical Firms Organized Around Stronger Cultures? Evidence From Big Data, Arianna Marchetti, Phanish Puranam

Research Collection Lee Kong Chian School Of Business

Research Summary: Are less hierarchical firms organized around stronger cultures instead? We analyze 1.5 million employee reviews on Glassdoor.com from 23,000 US-based firms, alongside data on managerial hierarchy estimated from 42 million professional social media profiles. Our findings confirm a negative association between managerial hierarchy and organizational culture strength. We explore two potential explanations for this association: Functional equivalence between the two, and culture fragmentation caused by managerial hierarchy. Multiple correlational tests show support for functional equivalence as a plausible explanation for the observed negative correlation. Our findings enhance our understanding of the complex relationships between organizational structure and culture …

The Effects Of Linguistic Ostracism On Job Performance. A Replication And An Extension, John Fiset, Devasheesh P. Bhave

Research Collection Lee Kong Chian School Of Business

We examined the phenomenon of linguistic ostracism—instances where a focal workgroup member perceives other members of their workgroup have rejected and/or excluded them by using a language they cannot comprehend. In a 2021 article, Fiset and Bhave observed that linguistic ostracism was related to two dimensions of job performance (interpersonal citizenship and deviance) and that disidentification served as an explanatory mechanism for the linguistic ostracism–job performance relationship. We constructively replicate and extend their work in several ways. First, we replicate prior effects on interpersonal citizenship and deviance and extend their work to focus on a third dimension of job performance: …

A General Limit Theory For Nonlinear Functionals Of Nonstationary Time Series, Qiying Wang, Peter C. B. Phillips

Research Collection School Of Economics

New limit theory is provided for a wide class of sample variance and covariance functionals involving both nonstationary and stationary time series. Sample functionals of this type commonly appear in regression applications and the asymptotics are particularly relevant to estimation and inference in nonlinear nonstationary regressions that involve unit root, local unit root, or fractional processes. The limit theory is unusually general in that it covers both parametric and nonparametric regressions. Self-normalized versions of these statistics are considered that are useful in inference. Numerical evidence reveals interesting strong bimodality in the finite sample distributions of conventional self-normalized statistics similar to …

Dynamic Spatial Panel Data Models With Interactive Fixed Effects: M-Estimation And Inference Under Fixed Or Relatively Small T, Liyao Li, Ke Miao, Zhenlin Yang

Research Collection School Of Economics

We propose an M-estimation method for dynamic spatial panel data models with interactive fixed effects based on (relatively) short panels. Unbiased estimating functions are constructed by adjusting the concentrated conditional quasi scores, given the initial values and with the factor loadings being concentrated out, to account for the effects of conditioning and concentration. Solving the estimating equations gives the M-estimators of the common parameters and common factors. Under fixed T, n-consistency and joint asymptotic normality of the M-estimators are established. Under T = o(n), the M-estimators of the common parameters are shown to be nT-consistent and asymptotically normal. For inference, …

Corrigendum To “Interim Rationalizable Implementation Of Functions” (Kunimoto T, Saran R, Serrano R (2024) Mathematics Of Operations Research 49(3):1791–1824), Takashi Kunimoto, Rene Saran, Roberto Serrano

Research Collection School Of Economics

This is the brief corrigendum to “Interim rationalizable implementation of functions” [Kunimoto T, Saran R, Serrano R (2024) Interim rationalizable implementation of functions. Math. Oper Res. 49(3):1791–1824].

The Asymmetric Effects Of Posting An Online Review On Future Spending And The Dark Side Of Solicitations, Hulya Karaman

Research Collection Lee Kong Chian School Of Business

Motivated by the prevalence of online review creation and solicitation, this paper examines whether posting an online review impacts the reviewer’s future spending on the reviewed brand. Identifying the causal effects of posting an online review is challenging because reviewers self-select into posting, making it an endogenous decision. I overcome this challenge by using randomized online review solicitations as an instrument for the endogenous treatment variable of posting an online review and establish that doing so decreases the average future spending by the reviewers on the reviewed brand. Additionally, I show that soliciting customers to post increases their propensity to …

Perceptions Of Game-Based Assessments: The Role Of Test Takers' Occupational Background, Marie L. Ohlms, Klaus G. Melchers, Filip Lievens

Research Collection Lee Kong Chian School Of Business

Game-based assessments (GBAs) have become increasingly popular in personnel selection. However, research on perceptions of GBAs has yielded mixed results, highlighting the need to explore variables that may shape perceptions of GBAs. Therefore, we examined whether test takers' occupational background and other person-related characteristics (i.e., gender, age, video game usage, openness to experience) are associated with their perceptions of GBAs. N = 179 individuals from technical and social occupational backgrounds rated their perceptions of GBAs and non-gamified tests. We found that GBAs were generally rated more positively than non-gamified tests in terms of organizational attractiveness, behavioral intentions toward the organization, …

Bridging Policy And Grassroots Action With Technology: A Framework For Civic Engagement In Environmental Sustainability, Mikhail Ola Adisa, Sonny Rosenthal, Shola Oyedeji, Ifeoma Adaji, Jari Porras

Research Collection College of Integrative Studies

Grassroots and civic organizations are increasingly recognized as “middle actors” in sustainability, leveraging ICT-driven solutions to bridge top-down policies with bottom-up citizen engagement and behavioral change. This study examines how civic organizations in Finland and Singapore integrate digital tools to support sustainable waste management practices aligned with Sustainable Development Goals 11, 12, and 17. Guided by a Design Science Research (DSR) approach and drawing on Middle-Out and multi-level governance theories, we developed and validated the Integrated Sustainability Engagement Framework (ISEF) based on interviews with 21 civic organizations and iterative feedback. Findings highlight the central roles of policy translation, localized practices, …