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G-Trac: Graph-Textual Representations Alignment For Cold-Start Recommendations, Li Yang Chang, Yuan Fang, Ming Feng Tsai, Chuan Ju Wang Feb 2026

G-Trac: Graph-Textual Representations Alignment For Cold-Start Recommendations, Li Yang Chang, Yuan Fang, Ming Feng Tsai, Chuan Ju Wang

Research Collection School Of Computing and Information Systems

The cold-start problem remains a significant challenge in recommendation systems, particularly for new users or unseen items with little to no historical data. Existing methods, including graph neural networks, often struggle in such scenarios. Inspired by the success of transformer models in natural language processing, we propose G-TRAC (Graph-Textual Representations Alignment for Cold-start Recommendations), a novel approach that integrates transformer-based textual modeling with graph neural networks. By effectively leveraging both textual and structural information, G-TRAC addresses cold-start challenges more effectively. Extensive experiments demonstrate its ability to enhance recommendation quality and generalize well across diverse scenarios.

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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 Feb 2026

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, …

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Brand Switching Or Behavior Change: The 2023 Bud Light Boycott's Impact On Alcohol Purchases, Aljoscha Janssen Feb 2026

Brand Switching Or Behavior Change: The 2023 Bud Light Boycott's Impact On Alcohol Purchases, Aljoscha Janssen

Research Collection School Of Economics

I study how the 2023 Bud Light boycott affected overall alcohol demand using household-level panel data and a set of difference-in-differences designs. Focusing on households that, before April 2023, regularly purchased Bud Light, I find a large drop in Bud Light volume (34%–37%), partial switching into other beer (＋70 to ＋90 ounces per month), and a net decline in total ethanol purchases of about 3–4 fl-oz per month, or roughly 5.5%–7.5% of pre-boycott intake. I detect no compensatory increase in wine or spirits. Scaled nationally, the quantity response is equivalent to roughly 150 million standard drinks per year; using CDC …

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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 Feb 2026

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, …

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A Dynamic Inspection And Replacement Policy For Systems Subject To Degradation And Periodic Shocks, Jiawen Hu, Qiuzhuang Sun Feb 2026

A Dynamic Inspection And Replacement Policy For Systems Subject To Degradation And Periodic Shocks, Jiawen Hu, Qiuzhuang Sun

Research Collection College of Integrative Studies

Inspection is widely adopted to improve the maintenance efficiency. Most works predetermine a periodic inspection scheme and focus on optimizing the replacement threshold. However, it is reasonable to inspect less frequently when the degradation level of the system is low and to perform inspections more frequently as the degradation level increases. This work investigates a dynamic inspection and replacement policy for systems subject to regular degradation and periodic shocks. The regular degradation of the system is modeled as a Wiener process. Meanwhile, a periodic arrived shock will incur a random amount increment to the degradation, which is assumed to satisfy …

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The Affective Economy Of Toxic Atmospheres: Sensory Governance, Ecological Intelligences And The Performative Politics Of Urban Mosquito Management, Orlando Woods, Creighton Connolly Feb 2026

The Affective Economy Of Toxic Atmospheres: Sensory Governance, Ecological Intelligences And The Performative Politics Of Urban Mosquito Management, Orlando Woods, Creighton Connolly

Research Collection College of Integrative Studies

This paper considers how atmospheres can play a powerful role in troubling the management of nature in the multispecies city. It brings the cyclical nature of atmospheric effects, the affective values and il/logics that determine human responses to non-human threats, and the misguided and potentially deleterious health outcomes that ensue into one analytical frame. Drawing on the empirical case of urban mosquito management in Singapore, it considers how the creation of toxic atmospheres through fogging – blowing insecticides into the air in a bid to kill mosquitoes – is ineffective and sets in motion a cascading series of socio-environmental consequences. …

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Atmospheric Circulation Reconstructions Over The Earth (Acre) 2025: Climate Data Recovery, Fiona Williamson Feb 2026

Atmospheric Circulation Reconstructions Over The Earth (Acre) 2025: Climate Data Recovery, Fiona Williamson

Research Collection College of Integrative Studies

On 15-16 September 2025, Singapore Management University hosted the annual Atmospheric Circulation Reconstructions over the Earth (ACRE, www.met-acre.net/) workshop, ’ACRE 2025: Climate Data Recovery’, chaired by Fiona Williamson, Rob Allan and Praveen Teleti. The 2-day event took place at the College of Integrative Studies and saw around 30 participants from multi-disciplinary backgrounds all working in meteorological data rescue (DaRe, www.community.wmo.int/en/data-rescue-projects-and-initiatives-dare) sharing their latest work and discoveries. Speakers were a mix of climate scientists and historians, archivists and historical climatologists from across the globe. ACRE has been operating for 18 years under Professor Rob Allan, formerly of the UK Meteorological Office …

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Geopolitical Ecologies Of Cloud Capitalism: Territorial Restructuring And The Making Of National Computing Power In The Us And China, Justin Kollar, Sol Andrew Stokols Feb 2026

Geopolitical Ecologies Of Cloud Capitalism: Territorial Restructuring And The Making Of National Computing Power In The Us And China, Justin Kollar, Sol Andrew Stokols

Research Collection College of Integrative Studies

As computing power becomes central to geopolitical rivalry, cloud infrastructure is increasingly framed as critical to national security, economic resilience and technological sovereignty. Current debates often focus on global competition – especially between the U.S. and China – highlighting strategic investments, export controls and infrastructure diplomacy abroad. Yet far less attention has been paid to the domestic territorial transformations that make such geopolitical projection possible. This paper argues that national strategies for AI and cloud dominance depend on the reorganization of land, energy and regulatory systems to sustain large-scale computation. Using a geopolitical ecology framework, we examine how the U.S. …

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Vercation: Precise Vulnerable Open-Source Software Version Identification Based On Static Analysis And Llm, Yiran Cheng, Ting Zhang, Lwin Khin Shar, Shouguo Yang, Chaopeng Dong, David Lo, Shichao Lv, Zhiqiang Shi, Limin Sun Feb 2026

Vercation: Precise Vulnerable Open-Source Software Version Identification Based On Static Analysis And Llm, Yiran Cheng, Ting Zhang, Lwin Khin Shar, Shouguo Yang, Chaopeng Dong, David Lo, Shichao Lv, Zhiqiang Shi, Limin Sun

Research Collection School Of Computing and Information Systems

Open-source software (OSS) has experienced a surge in popularity, attributed to its collaborative development model and cost-effective nature. However, the adoption of specific software versions in development projects may introduce security risks when these versions bring along vulnerabilities. Current methods of identifying vulnerable versions typically analyze and extract the code features involved in vulnerability patches using static analysis with pre-defined rules. They then use code clone detection to identify the vulnerable versions. These methods are hindered by imprecision due to (1) the exclusion of vulnerability- irrelevant code in the analysis and (2) the inadequacy of code clone detection. This paper …

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Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang Feb 2026

Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Function calling is a fundamental capability of today's large language models, but sequential function calling posed efficiency problems. Recent studies have proposed to request function calls with parallelism support in order to alleviate this issue. However, they either delegate the concurrent function calls to users for execution which are conversely executed sequentially, or overlook the relations among various function calls, rending limited efficiency. This paper introduces LLMOrch, an advanced framework for automated, parallel function calling in large language models. The key principle behind LLMOrch is to identify an available processor to execute a function call while preventing any single processor …

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Exploring Jvm Garbage Collector Testing With Event-Coverage, Kai Zheng, Yingquan Zhao, Junjie Chen, Hanmo You, Haoyu Wang, Haoyu Wang, Tianchang Gao Feb 2026

Exploring Jvm Garbage Collector Testing With Event-Coverage, Kai Zheng, Yingquan Zhao, Junjie Chen, Hanmo You, Haoyu Wang, Haoyu Wang, Tianchang Gao

Research Collection School Of Computing and Information Systems

Garbage Collection (GC) in the Java Virtual Machine (JVM) serves as an automatic memory management mechanism, efficiently reclaiming unused memory space in different production scenarios. To optimize JVM performance, developers typically fine-tune the garbage collector by identifying an optimal set of GC configurations for specific scenarios. Despite the sophisticated design of garbage collectors, they still have the potential for bugs in different settings, and these bugs can result in more severe consequences. Hence, comprehensive testing of these garbage collectors is imperative before their release. Code coverage criteria are typically employed to assess the comprehensiveness of a test suite. However, traditional …

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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 Feb 2026

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 …

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Constrained Pricing In Logit-Based Revenue Management, Qian Shao, Tien Mai, Shih-Fen Cheng Feb 2026

Constrained Pricing In Logit-Based Revenue Management, Qian Shao, Tien Mai, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

We consider a dynamic pricing problem in network revenue management in which customer behavior is predicted by a choice model, that is, the multinomial logit model. The problem, even in the static setting (i.e., customer demand remains unchanged over time), is highly nonconcave in prices. Existing studies mostly rely on the observation that the objective function is concave in terms of purchasing probabilities, implying that the static pricing problem with linear constraints on purchasing probabilities can be efficiently solved. However, this approach is limited in handling constraints on prices, noting that such constraints could be highly relevant in some real …

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Fcghunter: Towards Evaluating Robustness Of Graph-Based Android Malware Detection, Shiwen Song, Xiaofei Xie, Ruitao Feng, Qi Guo, Sen Chen Feb 2026

Fcghunter: Towards Evaluating Robustness Of Graph-Based Android Malware Detection, Shiwen Song, Xiaofei Xie, Ruitao Feng, Qi Guo, Sen Chen

Research Collection School Of Computing and Information Systems

Graph-based detection methods leveraging Function Call Graph (FCG) have shown promise for Android malware detection (AMD) due to their semantic insights. However, the deployment of malware detectors in dynamic and hostile environments raises significant concerns about their robustness. While recent approaches evaluate the robustness of FCG-based detectors using adversarial attacks, their effectiveness is constrained by the vast perturbation space, particularly across diverse models and features. To address these challenges, we introduce FCGHunter, a novel robustness testing framework for FCG-based AMD systems. Specifically, FCGHunter employs innovative techniques to enhance exploration and exploitation within this huge search space. Initially, it identifies critical …

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Quantum Chebyshev Transform-Based Graph Neural Networks For Financial Fraud Detection, Minrui Xu, Bingyan Guan, Bethel Hui Ting Loke, Paul R. Griffin Feb 2026

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 …

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Lagrangian Motion Fields For Long-Term Motion Generation, Yifei Yang, Zikai Huang, Chenshu Xu, Shengfeng He Feb 2026

Lagrangian Motion Fields For Long-Term Motion Generation, Yifei Yang, Zikai Huang, Chenshu Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Long-term motion generation is a challenging task that requires producing coherent and realistic sequences over extended durations. Current methods primarily rely on framewise motion representations, which capture only static spatial details and overlook temporal dynamics. This approach leads to significant redundancy across the temporal dimension, complicating the generation of effective long-term motion. To overcome these limitations, we introduce the novel concept of Lagrangian Motion Fields, specifically designed for long-term motion generation. By treating each joint as a Lagrangian particle with uniform velocity over short intervals, our approach condenses motion representations into a series of "supermotions" (analogous to superpixels). This method …

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Zero-Shot Video Translation Via Token Warping, Haiming Zhu, Yangyang Xu, Jun Yu, Shengfeng He Feb 2026

Zero-Shot Video Translation Via Token Warping, Haiming Zhu, Yangyang Xu, Jun Yu, Shengfeng He

Research Collection School Of Computing and Information Systems

With the revolution of generative AI, video-related tasks have been widely studied. However, current state-of-the-art video models still lag behind image models in visual quality and user control over generated content. In this paper, we introduce TokenWarping, a novel framework for temporally coherent video translation. Existing diffusion-based video editing approaches rely solely on key and value patches in self-attention to ensure temporal consistency, often sacrificing the preservation of local and structural regions. Critically, these methods overlook the significance of the query patches in achieving accurate feature aggregation and temporal coherence. In contrast, TokenWarping leverages complementary token priors by constructing temporal …

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Light Cone Cancellation For Variational Quantum Eigensolver In Solving Noisy Max-Cut, Xinwei Lee, Xinjian Yan, Ningyi Xie, Yoshiyuki Saito, Leo Kurosawa, Nobuyoshi Asai, Dongsheng Cai, Hoong Chuin Lau Feb 2026

Light Cone Cancellation For Variational Quantum Eigensolver In Solving Noisy Max-Cut, Xinwei Lee, Xinjian Yan, Ningyi Xie, Yoshiyuki Saito, Leo Kurosawa, Nobuyoshi Asai, Dongsheng Cai, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Variational Quantum Eigensolver (VQE) is a quantum-classical hybrid algorithm used to estimate the ground energy of a given Hamiltonian. It consists of a parameterized quantum circuit, which the parameters are optimized using a classical optimizer. With the increasing need in solving large-scale problems in real-world applications, solving those large problems with fewer qubits and fewer gates becomes essential, so that we reduce the simulation difficulty and mitigate the effect of noise in real quantum hardware. In this study, we applied the Light Cone Cancellation (LCC) method to reduce the number of qubits and gates required in a two-local ansatz. LCC …

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Grounding Is All You Need? Dual Temporal Grounding For Video Dialog, You Qin, Wei Ji, Xinze Lan, Hao Fei, Xun Yang, Dan Guo, Roger Zimmermann, Lizi Liao Feb 2026

Grounding Is All You Need? Dual Temporal Grounding For Video Dialog, You Qin, Wei Ji, Xinze Lan, Hao Fei, Xun Yang, Dan Guo, Roger Zimmermann, Lizi Liao

Research Collection School Of Computing and Information Systems

In the realm of video dialog response generation, capturing both the essence of video content and the temporal nuances of conversation history is crucial. While some approaches rely on large-scale pretrained visual-language models, often neglecting temporal dynamics, others emphasize spatial-temporal relationships within videos but demand intricate object trajectory pre-extractions and overlook dialog temporal dynamics. This paper introduces the Dual Temporal Grounding-enhanced Video Dialog model (DTGVD), designed to bridge the gap between these two approaches. DTGVD uniquely integrates the strengths of both by emphasizing dual temporal relationships. It achieves this by predicting dialog turn-specific temporal regions, selectively filtering video content, and …

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Learnable Game-Theoretic Policy Optimization For Data-Centric Self-Explanation Rationalization, Yunxiao Zhao, Zhiqiang Wang, Xingtong Yu, Xiaoli Li, Jiye Liang, Ru Li Feb 2026

Learnable Game-Theoretic Policy Optimization For Data-Centric Self-Explanation Rationalization, Yunxiao Zhao, Zhiqiang Wang, Xingtong Yu, Xiaoli Li, Jiye Liang, Ru Li

Research Collection School Of Computing and Information Systems

Rationalization, a data-centric framework, aims to build self-explanatory models to explain the prediction outcome by generating a subset of human-intelligible pieces of the input data. It involves a cooperative game model where a generator generates the most human-intelligible parts of the input (i.e., rationales), followed by a predictor that makes predictions based on these generated rationales. Conventional rationalization methods typically impose constraints via regularization terms to calibrate or penalize undesired generation. However, these methods are suffering from a problem called mode collapse, in which the predictor produces correct predictions yet the generator consistently outputs rationales with collapsed patterns. Moreover, existing …

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The Gains Do Not Make Up For The Losses: A Comprehensive Evaluation For Safety Alignment Of Large Language Models Via Machine Unlearning, Weixiang Zhao, Yulin Hu, Xingyu Sui, Zhuojun Li, Yang Deng, Yanyan Zhao, Bing Qin, Wanxiang Che Feb 2026

The Gains Do Not Make Up For The Losses: A Comprehensive Evaluation For Safety Alignment Of Large Language Models Via Machine Unlearning, Weixiang Zhao, Yulin Hu, Xingyu Sui, Zhuojun Li, Yang Deng, Yanyan Zhao, Bing Qin, Wanxiang Che

Research Collection School Of Computing and Information Systems

Machine Unlearning (MU) has emerged as a promising technique for aligning large language models (LLMs) with safety requirements to steer them forgetting specific harmful contents. Despite the significant progress in previous studies, we argue that the current evaluation criteria, which solely focus on safety evaluation, are actually impractical and biased, leading to concerns about the true effectiveness of MU techniques. To address this, we propose to comprehensively evaluate LLMs after MU from three aspects: safety, over-safety, and general utility. Specifically, a novel benchmark MuBench with 18 related datasets is first constructed, where the safety is measured with both vanilla harmful …

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Perceptions Of Game-Based Assessments: The Role Of Test Takers' Occupational Background, Marie L. Ohlms, Klaus G. Melchers, Filip Lievens Feb 2026

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, …

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The Asymmetric Effects Of Posting An Online Review On Future Spending And The Dark Side Of Solicitations, Hulya Karaman Feb 2026

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 …

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Are Less Hierarchical Firms Organized Around Stronger Cultures? Evidence From Big Data, Arianna Marchetti, Phanish Puranam Feb 2026

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 …

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The Effects Of Linguistic Ostracism On Job Performance. A Replication And An Extension, John Fiset, Devasheesh P. Bhave Feb 2026

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: …

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Eliciting Supplier Cooperation For Value Chain Decarbonization: A Field Experiment With Smallholder Farmers In India, Sukti Ghosh, Jasjit Singh Feb 2026

Eliciting Supplier Cooperation For Value Chain Decarbonization: A Field Experiment With Smallholder Farmers In India, Sukti Ghosh, Jasjit Singh

Research Collection Lee Kong Chian School Of Business

Many firms are pledging to reduce greenhouse gas emissions across their value chains. However, this requires their suppliers to also adopt more climate-friendly practices for decarbonization. This can involve addressing gaps in not only the suppliers’ ability but also their willingness to adopt such practices, which can be challenging if the suppliers perceive the practices as risky or potentially detrimental to their economic well-being. We examine the effectiveness of relational investments to help mitigate this challenge, arguing that relational investments can serve as a signal of the firm’s commitment towards joint value creation. In a field experiment conducted with supplier …

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A Social Norm Perspective On Distorted Information In China, Zhe Li, Massimo Massa, Nianhang Xu, Hong Zhang Feb 2026

A Social Norm Perspective On Distorted Information In China, Zhe Li, Massimo Massa, Nianhang Xu, Hong Zhang

Research Collection Lee Kong Chian School Of Business

Can social norms give rise to distorted information in China? We observe that China’s leading social norm related to alcohol consumption and social drinking enhance earnings management. An analysis of toxic alcohol scandals supports a causal interpretation. Further evidence suggests that the influence of alcohol may come from the negative externality that it creates, which is propagated by corporate leaders and cannot be attenuated by market-oriented institutions. Our results reveal a social norm externality that may have important normative implications.

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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 Feb 2026

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), …

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The Distinctiveness Effect: How Cross-Country Dissimilarities Influence Governance Decisions, Ilya Cuypers, Gokhan Ertug, Niels G. Noorderhaven, Korcan Kavusan Feb 2026

The Distinctiveness Effect: How Cross-Country Dissimilarities Influence Governance Decisions, Ilya Cuypers, Gokhan Ertug, Niels G. Noorderhaven, Korcan Kavusan

Research Collection Lee Kong Chian School Of Business

Transaction cost theory is one of the most commonly used theories to explain how firms govern their economic activities. In the context of cross-border collaborations, transaction cost theory proposes that dissimilarities between the partners’ home countries, which constitute a key source of behavioral uncertainty, affect how collaborations are governed (i.e. whether firms opt for equity joint ventures or non-equity alliances). Although many firms are likely to face more than one dimension of dissimilarity—for example, in terms language and religion, as well as culture—studies in transaction cost theory typically focus on how each source of dissimilarity impacts governance choices independently, in …

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Agency Mbs As Safe Assets, Zhiguo He, Zhaogang Song Feb 2026

Agency Mbs As Safe Assets, Zhiguo He, Zhaogang Song

Research Collection Lee Kong Chian School Of Business

Measured as yield spreads against Treasury securities and AAA corporate bonds, the convenience premium of newly issued agency MBS averages more than half of the long-term Treasury convenience premium. The agency MBS convenience premium and issuance amount vary negatively with mortgage rate, consistent with a prepayment-driven channel. Placing agencies into conservatorship in 2008 and introducing liquidity regulations in 2013 significantly affected MBS convenience premium, consistent with government guarantee and regulatory treatment channels. Analyses of dispersion of dealers’ prepayment forecasts, seasoned MBS, and investors’ MBS holdings deliver further economic implications for agency MBS as safe assets.

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