Digital Commons Network^™

Handling Long And Richly Constrained Tasks Through Constrained Hierarchical Reinforcement Learning, Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Safety in goal directed Reinforcement Learning (RL) settings has typically been handled through constraints over trajectories and have demonstrated good performance in primarily short horizon tasks. In this paper, we are specifically interested in the problem of solving temporally extended decision making problems such as robots cleaning different areas in a house while avoiding slippery and unsafe areas (e.g., stairs) and retaining enough charge to move to a charging dock; in the presence of complex safety constraints. Our key contribution is a (safety) Constrained Search with Hierarchical Reinforcement Learning (CoSHRL) mechanism that combines an upper level constrained search agent (which …

Imitate The Good And Avoid The Bad: An Incremental Approach To Safe Reinforcement Learning, Minh Huy Hoang, Mai Anh Tien, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

A popular framework for enforcing safe actions in Reinforcement Learning (RL) is Constrained RL, where trajectory based constraints on expected cost (or other cost measures) are employed to enforce safety and more importantly these constraints are enforced while maximizing expected reward. Most recent approaches for solving Constrained RL convert the trajectory based cost constraint into a surrogate problem that can be solved using minor modifications to RL methods. A key drawback with such approaches is an over or underestimation of the cost constraint at each state. Therefore, we provide an approach that does not modify the trajectory based cost constraint …

Glop: Learning Global Partition And Local Construction For Solving Large-Scale Routing Problems In Real-Time, Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, Fanzhang Li

Research Collection School Of Computing and Information Systems

The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance. This paper proposes GLOP (Global and Local Optimization Policies), a unified hierarchical framework that efficiently scales toward large-scale routing problems. GLOP partitions large routing problems into Travelling Salesman Problems (TSPs) and TSPs into Shortest Hamiltonian Path Problems. For the first time, we hybridize non-autoregressive neural heuristics for coarse-grained problem partitions and autoregressive neural heuristics for fine-grained route constructions, leveraging the scalability of the former and the meticulousness of the latter. Experimental results show that GLOP achieves competitive and state-of-the-art real-time performance …

Simple Image-Level Classification Improves Open-Vocabulary Object Detection, Ruohuan Fang, Guansong Pang, Xiao Bai

Research Collection School Of Computing and Information Systems

Open-Vocabulary Object Detection (OVOD) aims to detect novel objects beyond a given set of base categories on which the detection model is trained. Recent OVOD methods focus on adapting the image-level pre-trained vision-language models (VLMs), such as CLIP, to a region-level object detection task via, eg., region-level knowledge distillation, regional prompt learning, or region-text pre-training, to expand the detection vocabulary. These methods have demonstrated remarkable performance in recognizing regional visual concepts, but they are weak in exploiting the VLMs' powerful global scene understanding ability learned from the billion-scale image-level text descriptions. This limits their capability in detecting hard objects of …

Earnhft: Efficient Hierarchical Reinforcement Learning For High Frequency Trading, Molei Qin, Shuo Sun, Wentao Zhang, Haochong Xia, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

High-frequency trading (HFT) is using computer algorithms to make trading decisions in short time scales (e.g., second-level), which is widely used in the Cryptocurrency (Crypto) market, (e.g., Bitcoin). Reinforcement learning (RL) in financial research has shown stellar performance on many quantitative trading tasks. However, most methods focus on low-frequency trading, e.g., day-level, which cannot be directly applied to HFT because of two challenges. First, RL for HFT involves dealing with extremely long trajectories (e.g., 2.4 million steps per month), which is hard to optimize and evaluate. Second, the dramatic price fluctuations and market trend changes of Crypto make existing algorithms …

Market-Gan: Adding Control To Financial Market Data Generation With Semantic Context, Haochong Xia, Shuo Sun, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financial market simulation methodologies, existing frameworks often struggle with adapting to specialized simulation context. We pinpoint the challenges as i) current financial datasets do not contain context labels; ii) current techniques are not designed to generate financial data with context as control, which demands greater precision compared to other modalities; iii) the inherent difficulties in generating context-aligned, high-fidelity data given the non-stationary, noisy nature of financial data. To address these challenges, our contributions are: i) we proposed the Contextual …

What Difference Do The New Factor Models Make In Portfolio Allocation?, Frank J. Fabozzi, Dashan Huang, Fuwei Jiang, Jiexun Wang

Research Collection Lee Kong Chian School Of Business

This paper compares the Hou-Xue-Zhang four-factor model with the Fama-French five-factor model from an investing perspective both in- and out-of-sample. Without margin requirements and model uncertainty, the Hou-Xue-Zhang model outperforms the Fama-French model. However, the outperformance could become negligible if an investor is subject to margin requirements and model uncertainty. The Hou-Xue-Zhang model shows similar power as the Fama-French model in describing the covariance matrix of asset returns. Overall, the two models do not make a difference for investing in a realistic setting.

Learning From Machines: How Negative Feedback From Machines Improves Learning Between Humans, Tengjian Zou, Gokhan Ertug, Thomas Roulet

Research Collection Lee Kong Chian School Of Business

Prior studies on learning from failure primarily focus on how individuals learn from failure feedback given by other individuals. It is unclear whether and how the advent of machine feedback may influence individuals’ learning from failures. We suggest that failure feedback provided by machines facilitates learning in two ways. First, it focuses individuals’ attention on their failures, leading them to learn from these failures. Second, it serves as a catalyzer, motivating individuals to learn more from failure feedback given to them by other individuals as well. In addition, this catalyzing effect is stronger if the failure feedback from machines and …

Navigating Geopolitical Crises For Energy Security: Evaluating Optimal Subsidy Policies Via A Markov Switching Dsge Model, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao

Sim Kee Boon Institute for Financial Economics

This paper aims to provide insights on the design of optimal subsidy policies to enhance energy security amidst energy disruptions triggered by geopolitical conflicts. We introduce a novel Markov switching dynamic stochastic general equilibrium (MS-DSGE) model to address the limitations of existing integrated assessment models in environmental evaluation. These models often fail to adequately consider the environmental and economic impacts of geopolitical conflicts and do not prioritize energy security sufficiently in policymaking. Our application of the MS-DSGE model to the Russia–Ukraine conflict reveals significant decreases in output, social welfare, and energy consumption during disruptions. The mere anticipation of an energy …

Local Institutional Investors And Corporate Monitoring: Evidence From Cross-Listed Korean Stocks In The Us Market, Changhwan Choi, Chune Young Chung, Jun Myung Song

Sim Kee Boon Institute for Financial Economics

Using Korean firms that are cross-listed in the US market, this paper investigates whether there are standalone effects of geographic and market proximity of institutional investors on monitoring performance. We find that Korean institutional ownership is negatively associated with earnings management while the US institutional ownership has no impact on earnings management. This suggests that there is the geographic proximity advantage over the market proximity advantage in the emerging markets. Furthermore, we also show that the impact of geographic proximity is stronger for firms with high informational opacity

Belt And Road Initiative: Legal Mechanism To Recover Stolen Assets, Veltrice Tan

Singapore International Dispute Resolution Academy

Purpose: This paper aims to determine the types of legal mechanisms that authorities can use to recover stolen assets for and from China. Design/methodology/approach: Newspaper articles and books are examined as are relevant reports by various regulatory authorities and academic institutions. Findings: The effectiveness of legal mechanisms in the recovery of stolen assets may be affected by issues such as the difficulties in tracing illicit funds, the ambiguous nature of “value” as well as the rise in technology. Research limitations/implications: There are limited data available in relation to the prevalence of corrupt officials along the Belt and Road Initiative and …

Smu Launches Urban Institute Focused On The Study Of Asian Cities, Singapore Management University

SMU Press Releases and News

As Asian cities urbanise at an unprecedented rate, urban policy-makers face the increasingly complex and pressing challenge of balancing urban growth with resilience and sustainability. With migration and the rapid flow of ideas online, old and new city-making practices have become uncomfortably entwined, resulting in contestation for space, resources, and municipal services. In response to megatrends that underscore the critical need to prioritise urban research, Singapore Management University (SMU) today launched the SMU Urban Institute (UI), a new research institute dedicated to multi- and inter-disciplinary research on cities in Asia. SMU UI will look beyond the development of infrastructure, and …

The Belt And Road Initiative: Conflict Of Laws And Dispute Resolution, Veltrice Tan

Singapore International Dispute Resolution Academy

Purpose: This paper aims to determine the adaptability of China’s legal system in recognizing and enforcing foreign judgements in China. Design/methodology/approach: Academic articles, case law and books are examined as are relevant reports by various regulatory authorities and organizations. Findings: Historically, Chinese courts have strictly adhered to “de facto reciprocity”, which made it difficult for foreign judgements to be recognized and enforced in China. Fortunately, Chinese courts have since abandoned their rigid adherence to de facto reciprocity, and have instead, used flexible tests of reciprocity such as de jure reciprocity, reciprocal commitment and reciprocal understand/consensus. Accordingly, this would facilitate the …

Singapore Management University Report To Stakeholders 2023/24, Singapore Management University

Report to Stakeholders

The past year has been one of significant growth and achievement for Singapore Management University. As we navigated an increasingly complex and challenging world, SMU remained committed to doing the best by our students, harnessing the collective brain trust that our faculty represent, and the professional expertise of our staff, to deliver impact on our community, country, and region. Our focus on nurturing the next generation of leaders, thinkers, and change-makers continues to be at the heart of our educational mission, and our dedication to the highest quality research for academic and societal impact remains our commitment.

Key Success Factors Of Strategic Transformation For Sino-French Cooperation In The Development Of Third-Party Markets In Africa, Bin Wang

Dissertations and Theses Collection (Open Access)

The most popular form of third-party market cooperation is an innovative international economic and trade cooperation model initiated by China under the context of the “Belt and Road” initiative nowadays. Although China and France, as non-state actors, have actively promoted trilateral cooperation and improved various agreements, the trilateral countries have not achieved effective resource complementarity due to differences in political and economic systems and goals, resulting in high complexity in the cooperation process.

Therefore, the research topic of this study is dedicated to addressing this pain point and assisting Chinese enterprises in leveraging third-party markets to expand overseas business under …

Smu Welcomes Two New Members To Its Board Of Trustees, Singapore Management University

SMU Press Releases and News

The Singapore Management University is pleased to announce the appointment of two new members to its Board of Trustees with effect from 12 January 2024. Their appointment will be for an initial term of three years. The new members are: (1) Dr Andrew David Hamilton – President Emeritus, New York University, (2) Mr Don Lam – Chief Executive Officer & Founding Partner, VinaCapital Group.

Managing The Personalized Order-Holding Problem In Online Retailing, Shouchang Chen, Zhenzhen Yan, Yun Fong Lim

Research Collection Lee Kong Chian School Of Business

Problem definition: A significant percentage of online consumers place consecutive orders within a short duration. To reduce the total order arrangement cost, an online retailer may consolidate consecutive orders from the same consumer. We investigate how long the retailer should hold the consumer’s orders before sending them to a third-party logistics provider (3PL) for processing. In this order-holding problem, we optimize the holding time to balance the total order arrangement cost and the potential delay in delivery. Methodology/results: We model the order-holding problem as a Markov Decision Process. We show that the optimal order-holding decisions follow a threshold-type policy that …

Climate Change Concerns And Mortgage Lending, Tinghua Duan, Frank Weikai Li

Research Collection Lee Kong Chian School Of Business

We examine whether beliefs about climate change affect loan officers’ mortgage lending decisions. We show that abnormally high local temperature leads to elevated attention to and belief in climate change in a region. Loan officers approve fewer mortgage applications and originate lower amounts of loans in abnormally warm weather. This effect is stronger among counties heavily exposed to the risk of sea-level rise, during periods of heightened public attention to climate change, and for loans originated by small lenders. Additional tests suggest that the negative relation between temperature and approval rate is not fully explained by changes in local economic …

Shadow Bank, Risk-Taking, And Real Estate Financing: Evidence From The Online Loan Market, Xiaoying Deng, Chong Liu, Eng Seow Ong

Research Collection Lee Kong Chian School Of Business

This paper examines whether and how individual risk-taking behavior affects real estate financing through shadow banks. Using the loan data from an online platform in China, we show that riskier households tend to employ online loans to meet the increasing down-payment in their home purchase. Individual investors are likely to fund riskier real estate loans with higher expected returns. Real estate loans experience higher ex-post default rates than other types of loans. The effect is more pronounced during the period of credit constraints.

The Effects Of Language-Related Misunderstanding At Work, John Fiset, Devasheesh P. Bhave, Nilotpal Jha

Research Collection Lee Kong Chian School Of Business

Demographic, technological, and global trends have brought the language used at the workplace to the forefront. A growing body of research reveals that language could result in misunderstanding at work, and influence employees' performance and attitudinal outcomes. Language at work encompasses standard language (e.g., English) as well as several hybrid forms of language (non-native accents, code-switching, and jargon). We delineate how these forms of language could result in misunderstanding. We then identify relational, affective, and informational mechanisms that underlie the relationship between language-related misunderstanding and employees' performance and attitudinal outcomes, and highlight key boundary conditions. In doing so, we uncover …

R&D Project Portfolio Collaboration: How To Structure The Strategic Alliance, Guiyun Feng, Pascale Crama, Wenqi Lian

Research Collection Lee Kong Chian School Of Business

Incumbent companies target innovative firms with promising research and development (R&D) projects to rejuvenate their product portfolio. Such strategic alliances create value by combining the innovator’s research expertise with the partner firm’s superior marketing capability. The partner firm chooses the timing and payment terms of the strategic alliance, accounting for the innovator's budget and marketing capability, and the project portfolio's market interaction and revenue variability. The partner firm may prefer delayed alliances post R&D completion for innovator firms with high marketing capability when the innovator has sufficient budget or when market interaction is weak. Upfront alliances - prior to the …

Fairness Perceptions Of Artificial Intelligence: A Review And Path Forward, Devesh Narayanan, Mahak Nagpal, Jack Mcguire, Shane Schweitzer, David De Cremer

Research Collection Lee Kong Chian School Of Business

A key insight from research on organizational justice is that fairness is in the eye of the beholder. With increasing discussions–especially among computer scientists and policymakers–about the potential biases and unfairness of decisions made by Artificial Intelligence (AI) systems, there is a critical need to consider how decision-subjects perceive the fairness of AI-led decision-making. Drawing upon theoretical and empirical perspectives on perceived fairness in organizational justice scholarship, this review categorizes and analyzes perceptions of AI fairness as they impact the effective implementation of AI in workplaces and beyond. Specifically, we review existing empirical research on AI fairness according to distinct …

The Dark Side Of Category Expansion: Will Existing Ones Pay The Price?, Qi Yu, Ron Berman, Eric Bradlow

Research Collection Lee Kong Chian School Of Business

Many retailers that manage product assortments believe that “more is better”. We challenge this conventional wisdom by demonstrating that a retailer may face more price-sensitive demand for existing categories after a category expansion. While introducing a new category to a store may increase the demand for the existing ones, this increase sometimes suggests a movement towards the steeper part of the demand curve and an increase in price sensitivity. We build a model of multi-category purchases with transportation costs and generate a series of theoretical predictions of the changes in price sensitivity after category expansion. We then estimate the model …

Why The Ethical Use Of Ai Matters For Your Career, Jack Mcguire, David De Cremer, Yorck Hesselbarth, Leander De Schutter

Research Collection Lee Kong Chian School Of Business

In the contemporary digital era, innovations such as artificial intelligence (AI) are profoundly transforming the business landscape (De Cremer, 2020). The buzz surrounding ChatGPT, coupled with recent assertions about the sentience of Google’s LaMDA, a large language model, underscore the prominence of chatbot technology in these advancements (Adamopoulou & Moussiades, 2020; Ryu & Lee, 2018; Tiku, 2022). Customer-oriented chatbots, an emergent application of this tech, offer unparalleled efficiency and cost-effectiveness, operating ceaselessly and responding to client inquiries in real time (Salesforce, Research, 2019). Yet, amidst these advantages lies an ethical conundrum. Customers cherish genuine human interaction and can become quickly …

Do Real-Time Strategy Video Gamers Have Better Attentional Control?, Mengxin He, Lin-Xuan Xu, Chiang-Shan R. Li, Zihan Liu, Jiaqi Hu, Xiangyi Guo, Hongyun Liu, Jin-Tao Zhang

Research Collection Lee Kong Chian School Of Business

Objective: Do real-time strategy (RTS) video gamers have better attentional control? To examine this issue, we tested experienced versus inexperienced RTS video gamers on multi-object tracking tasks (MOT) and dual-MOT tasks with visual or auditory secondary tasks (dMOT). We employed a street-crossing task with a visual working memory task as a secondary task in a virtual reality (VR) environment to examine any generalized attentional advantage. Background: Similar to action video games, RTS video games require players to switch attention between multiple visual objects and views. However, whether the attentional control advantage is limited by sensory modalities or generalizes to real-life …

Strategic Diplomacy: The Singapore Case, Country Report For The Project On ‘Strategic Diplomacy For 21st Century Defence And Statecraft’, Evelyn Goh, Wee-Kiat Lim

CCX Research

How does Singapore conduct strategic diplomacy despite being a small and constrained state? This report first identifies the major long-term drivers affecting Singapore’s security, both at the domestic level (rapidly ageing population, immigrant assimilation, and growing societal fault-lines) and at the international or systemic level (changing global order, power of technology, slow collective action on climate change). Then it analyses how Singapore strategists deal with two of their most prominent problem-sets: (i) positioning Singapore in relation to the US-China rivalry and the changing international order; and (ii) tackling climate change as a collective action problem. Both problem-sets illustrate how Singapore …

Impact Of A Covid-19 Related Lockdown On The Experience Of Informal Caregiving In Singapore, Vicky Mengqi Qin, Abhijit Visaria, Rahul Malhotra

ROSA Journal Articles and Publications

Introduction: Lockdowns, while limiting COVID-19 transmission, can affect provision of care by informal caregivers and their caregiving experience. We assessed, among informal caregivers in Singapore, (a) the perceived impact of a 2-month (April to May 2020) nationwide lockdown on their care provision, (b) correlates of different perceptions of the impact of the lockdown on care provision, and (c) association of different perceptions of the impact with negative and positive experiences of caregiving. Methods: In the August 2020 wave of the Singapore Life Panel (SLP; nationally representative, longitudinal monthly survey of Singapore citizens and permanent residents aged 50-70 years at baseline), …

Politics Speak Louder Than Skills: Political Similarity Effects In Hireability Judgments In Multiparty Contexts And The Role Of Political Interest, Franz W. Moenke, Filip Lievens, Ursula Hess, Philipp Schaepers

Research Collection Lee Kong Chian School Of Business

Recruiters increasingly cybervet job applicants by checking their social media profiles. Theory (i.e., the political affiliation model, PAM) and research show that during cybervetting, recruiters are exposed to job-unrelated information such as political affiliation, which might trigger similarity-attraction effects and bias hireability judgments. However, as the PAM was developed in a more polarized two-party political system, it is pivotal to test and refine the PAM in a multiparty context. Therefore, we asked working professionals from the United States (two-party context, N = 266) and Germany (multiparty context, N = 747) to rate an applicant’s hireability after cybervetting a LinkedIn profile …

Steering The Intangible Wheel: Chief Executive Officer Effect On Corporate Cultural Change, Xina Li, Guoli Chen, Rui Shen

Research Collection Lee Kong Chian School Of Business

We provide large-scale empirical evidence of how much chief executive officers (CEOs) change corporate culture. To do this, we use employee reviews to measure corporate cultural change in S&P 1500 firms. In a variance decomposition analysis, we find a modest effect of CEOs on corporate cultural change. The effect of CEOs on cultural change is larger than industry effect but smaller than firm effect. Regression analysis in the context of CEO succession further shows consistent evidence of a modest effect of CEO succession on corporate cultural change. In addition, the relationship between CEOs and cultural change is not likely to …

Ai Fairness In Action: A Human-Computer Perspective On Ai Fairness In Organizations And Society, David De Cremer, Jack Mcguire, Jack Mcguire

Research Collection Lee Kong Chian School Of Business

Artificial intelligence (AI) systems are being increasingly adopted by society, governments, and organizations in various decision-making contexts. For example, organizations use AI systems to decide whether applicants can be considered for a job, whether bonuses and other rewards should be allocated, or whether promotions and further training need to be invested in. In fact, as AI is seen as an important catalyst of economic growth, organizations today seem to know no boundaries in their AI adoption efforts, making employees and society more dependent on and thus also more vulnerable to the decisions made by or in partnership with AI (De …