Digital Commons Network^™

The Compatibility Of The Substance Over Form Doctrine With Tax And Investment Treaties: A Case Study Of Lone Star V The Republic Of Korea, Blazej Kuzniacki

Research Collection School Of Accountancy

In late August 2022, the Lone Star tribunal concluded one of the latest awards in tax-related investment treaty disputes (the tax-related claims account for almost USD 1.5 billion of the total of almost USD 4.7 billion claimed in compensation). It also is the first award in which the tribunal dealt with the application of the substance over form doctrine (SOFD) by tax authorities and courts of the host state to prevent the abuse of a double tax treaty (DTT), and the impact of the refusal to accord the claimants the benefits under the DTT via a domestic (Korean) SOFD on …

Alternative Agrifood Systems And The Economic Sustainability Of Farmers' Cooperatives: The Chinese Experience, Zhanping Hu, Qian Forrest Zhang

Research Collection School of Social Sciences

Most registered farmers' cooperatives in China are de facto private enterprises; while many bring economic gains to farmers, they do not function as cooperatives. Among the small minority that started as authentic cooperatives, however, most struggled to provide economic benefits to members, unable to achieve economic sustainability. The failure of true farmers' cooperatives in China has been widely studied; the success of the few that did become economically sustainable, however, remains poorly understood. Using a sample of 70 farmers' cooperatives across the country and comparing three “extreme cases”—cooperatives that are both authentic and economically successful—with the rest, this study argues …

Using Simulations Of Future Extreme Weather Events To Escape The Resilience Trap: Experimental Evidence From Hong Kong, Terry Van Gevelt, J. Yang, K. N. Chan, L. Li, Fiona Williamson, B. G. Mcadoo, A. D. Switzer

Research Collection College of Integrative Studies

Hong Kong is a hyper-dense coastal city that has long learned to live with a potentially disastrous extreme weather event: tropical cyclones. This was largely a reactionary process, with investments in soft and hard infrastructure made in the aftermath of devastating tropical cyclones. While the experiences of devastating tropical cyclones remain strong in the collective memory of the city, Hong Kong's present-day resilience has led to complacency, especially among the general public. We suggest that Hong Kong may be caught in a resilience trap, where previous success in building resilience may be hindering the city's ability to adapt to the …

Sorry Not Sorry: Presentational Strategies And The Electoral Punishment Of Corruption, Dean C. Dulay, Seulki Lee

Research Collection School of Social Sciences

A growing literature has explored various factors that hamper the electoral punishment of corruption. Most studies have focused on how voters react to a corruption allegation, but this focus leaves out an important, common aspect of corruption allegations that voters also encounter: politicians' blame avoidance strategies. This study examines how politicians' presentational strategies in response to corruption allegations affect voter sanctioning. Employing an online survey experiment on a sample of 3531 U.S. citizens, we find that politicians' action-oriented strategies, such as denying allegations, acknowledging a problem but denying responsibility, or acknowledging a problem and taking responsibility, are more effective than …

Computer Use Frequency And Cardiovascular Health In Middle-Aged And Older Adults, Meilan Hu, Shu Fen Diong, K. T. A. Sandeeshwara Kasturiratna, Andree Hartanto

Research Collection School of Social Sciences

With increased computer usage amongst midlife and older adults, concerns are emerging with regards to the potential adverse health effects of computer use given the sedentary habits it may encourage. The current study aims to investigate the relationship between computer use and cardiovascular risk in midlife and older adults. From the National Survey of Midlife Development in the United States II: Biomarker Project (2004–2009) and the National Survey of Midlife Development in the United States (MIDUS II), 2004–2006, we examined five cardiovascular risk biomarkers—high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides, interleukin-6, and C-reactive protein—in relation to self-reported general …

Factor Structure Of The Ces-D-20 Scale In Young Adults In Singapore: An Examination Of Six Alternative Structures And Measurement Invariance By Sex, Nadyanna M. Majeed, K. T. A. Sandeeshwara Kasturiratna, Nicole Ruiying Chen, Andree Hartanto

Research Collection School of Social Sciences

Building on past research that has indicated cultural variations in the factor structure of the 20-item Center for Epidemiologic Studies Depression Scale (CES-D-20), as well as several limitations validating the CES-D-20 within a Singapore context, this study investigated the CES-D-20's factor structure and sex-based measurement invariance in Singapore. A large young adult sample in Singapore (N = 1008) was utilised, and the original CES-D-20 was administered to all participants. The findings confirmed the four-factor model's robustness over five other alternative models (RMSEA = .05, SRMR = .04), where each of the 20 items loaded significantly onto its respective factor (all …

Us Or Them: How Covid-19 Vaccine Priority Influences Perceptions Of Local-Migrant Worker Relations, Tengjiao Huang, Haochen Zhou, Liz Jones, Chin Wen Cong

Research Collection School of Social Sciences

The COVID-19 pandemic laid bare pre-existing societal fault lines, placing immense strain on intergroup relations and giving rise to xenophobic sentiments. Drawing on Realistic Conflict Theory (RCT) and Social Identity Approach (SIA), our study examined how the public allocation of COVID-19 variant vaccines could influence the dynamics between local citizens and migrant workers, and under what conditions. One key idea is that valued resource distribution that favour migrant workers may produce increased perceptions of realistic threats among local citizens which could lead to exacerbated negative attitudes and behaviours of high-status local citizens towards low-status migrants, whereas higher fairness perceptions of …

Longitudinal Bidirectional Relation Between Fear Of Missing Out And Risky Loot Box Consumption: Evidence For Fomo-Driven Loot Boxes Spiral Hypothesis, Andree Hartanto, K Tennakoon Appuhamillage Sandeeshwara Kasturiratna

Research Collection School of Social Sciences

Background: The integration of loot boxes has emerged as a significant factor contributing to the increasing revenue in the video gaming industry. However, this integration has also led to widespread engagement in risky loot box consumption. To understand the mechanism that drives and sustains such maladaptive behavior, we propose the FoMO-Driven Loot Boxes Spiral Hypothesis – positing that fear of missing out (FoMO) not only triggers initial engagement in risky loot box consumption but also perpetuates a self-reinforcing cycle, where such engagement intensifies subsequent FoMO, leading to further risky loot box consumption. Method and results: We conducted a 13-week longitudinal …

Positive And Negative Affect Differentially Predict Individual Differences And Intra-Individual Changes In Daily Cognitive Failures In Younger And Older Adults, Ysabel A. Guevarra, Nadyanna M. Majeed, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

(1) Background: Cognitive failures, including lapses in attention, memory, and executive functioning, can negatively affect daily performance and well-being. Negative and positive affectivity have been implicated in cognitive functioning, yet their relationship with cognitive failures remains underexplored. This study investigates the impact of positive and negative affect on cognitive failures, using daily diary methods to examine both within-person and between-person associations in a sample of younger adults from Singapore and adults across the lifespan from the United States (US). (2) Methods: Participants (Singapore: N = 253, US: N = 1726) completed daily diaries over seven (Singapore) or eight (US) consecutive …

Advances In Research On Anthropogenic Drivers Of Climate Change, Andrew Jorgenson, Hassan El Tinay, Jared Fitzgerald, Jennifer Givens, Taekyeong Goh, Xiaorui Huang, Orla Kelly, Annika Marie Rieger, Ryan P. Thombs

Research Collection School of Social Sciences

This chapter provides an overview of advances in social science research on the anthropogenic drivers of climate change. Anthropogenic drivers refer to the social systems and human actions causing GHG emissions, and societal factors shaping and conditioning those actions. The authors summarize the contemporary drivers research literature on (1) economic growth, (2) income and wealth inequality, (3) environmental load displacement and ecologically unequal exchange, (4) militarization, and (5) corporations. In addition to summarizing recent work, the authors identify future directions for each of these areas of research, as well as ways in which they can be better integrated.

(In)Visible China: Understanding Chinese Global Orders, Hassan Karrar, William A. Callahan, Carwyn Morris, Stephen Whiteman

Research Collection School of Social Sciences

Where is China going? What does its alternative global order look like? We hear a lot about China’s grand projects like the Belt and Road Initiative, but how are they experienced on the ground in Africa, South America, and Asia?The Chinese Global Orders project brings together twenty-two scholars from five continents to explore these questions. As these four commentaries show, it seeks to pluralize the discussion by exploring “Chinese” beyond the PRC nation-state, “Global” as a space beyond the international, and “Orders” as a plural set of norms.The project seeks to do more than just describe Global China’s material impact, …

Reevo: Large Language Models As Hyper-Heuristics With Reflective Evolution, Haoran Ye, Jiarui Wang, Zhiguang Cao, Federico Berto, Chuanbo Hua, Haeyeon Kim, Jinkyoo Park, Guojie Song

Research Collection School Of Computing and Information Systems

The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design process. The long-standing endeavor of design automation has gained new momentum with the rise of large language models (LLMs). This paper introduces Language Hyper-Heuristics (LHHs), an emerging variant of Hyper-Heuristics that leverages LLMs for heuristic generation, featuring minimal manual intervention and open-ended heuristic spaces. To empower LHHs, we present Reflective Evolution (ReEvo), a generic searching framework that emulates the reflective design approach of human experts while far surpassing human capabilities with its scalable LLM inference, Internet-scale domain knowledge, and powerful evolutionary search. Evaluations …

Competency Model For General Managers Of Chain Independent Clinical Laboratory (Icl) Subsidiaries, Haiyan Wen

Dissertations and Theses Collection (Open Access)

An independent clinical laboratory (ICL) is a medical institution that has received approval from health authorities, holds independent legal status, and specializes in medical testing or pathological diagnostics, assuming responsibility independently. It is also referred to as a third-party medical testing laboratory. During in-depth research on the enterprises, it was found that while the chain ICL industry is rapidly growing, the issues of uncertainty and difficulty in selecting subsidiary general managers have become a common concern and pain point among senior managers.

The study combines theoretical and data analysis to identify distinct and important competency characteristics of general managers of …

Research On The Impact Of Firms' Perception Of Economic Policy Uncertainty On Their Digital Transformation, Fanwei Meng

Dissertations and Theses Collection (Open Access)

In an era characterized by globalization and digital advancement, economic policies play a critical role in the governmental regulation of economic activities. These policies are characterized by uncertainty due to a variety of internal and external factors, including international politics, economic cycles, and market fluctuations. The way firms, as microeconomic entities, perceive economic policy uncertainty (EPU) has a direct impact on their investment decisions and innovation activities. Nowadays, digital transformation has emerged as a vital strategy for firms seeking to enhance their competitiveness and adapt to evolving markets. However, digital transformation often comes with challenges, such as high input costs …

The Research On The Impact Of Listing Regime On Innovation For The Biotech Industry: Inspiration And Experience From Mb Rules 18a Published By Hkex, Yueying Dong

Dissertations and Theses Collection (Open Access)

The development of the Biotech Industry is not only connected to the national economy and livelihood of the people, but also affects the technology development, economy growth and national security of the country. The development depends on the technology innovation, with the essence for the continuous process of financial ecology guiding and technology refresh driving. For high-tech intensive industries of biotech companies, the development of the equity market is an important support for promoting the technology innovation. The capital market in guiding resource allocation has the responsibility of optimizing the listing regime, providing more external financing channels and promoting the …

Impact Of Project Simulation Shareholding Incentive On Team Performance: Research Based On The Construction Industry, Jian Zhou

Dissertations and Theses Collection (Open Access)

China's construction industry is vast and possesses a wide market; however, it faces challenges such as unclear stratification and low concentration levels. Construction enterprises face significant constraints in key areas such as financial strength, team stability, and technological advancement, while also bearing substantial costs related to supervision and accountability. The project simulation shareholding mode enhances employees' sense of belonging and responsibility through a collaborative approach characterized by joint management, shared risks, and shared benefits. This improves project execution efficiency and quality, ultimately strengthening the core competitiveness of the enterprise. In the construction industry, projects often involve substantial investments and long-term …

Correlation And Causation Analysis For Cross-Sectional And Panel Data, Barry Nuqoba

Dissertations and Theses Collection (Open Access)

This dissertation investigates how data, algorithms, and expert knowledge can be harnessed to better understand human behavior and enhance well-being. It emphasizes the critical importance of interdisciplinary collaboration to bridge knowledge gaps and foster insights that support preventive care, causal theory advancement, and policy development.

The first study, part of the SHINESeniors project, shed light on the potential usefulness of passive, unobtrusive sensors for detecting nocturia and poor sleep quality, symptoms commonly observed in chronic diseases, thereby enabling live-alone older adults to age in place. Utilizing machine learning techniques on sensor-derived features, the study can identify nocturia and poor sleep …

Causality Analysis For Neural Network Security, Bing Sun

Dissertations and Theses Collection (Open Access)

While neural networks are demonstrating excellent performance in a wide range of applications, there has been a growing concern on their reliability and dependability.Similar to traditional decision-making programs, neural networks inevitably have defects that need to be identified and mitigated at times. Neural networks are usually inherently black-boxes and do not provide explanations on how and why decisions are made. As a result, these defects are more ``hidden" and more challenging to eliminate. It is thus crucial to develop systematic approaches to identify and mitigate defects in a neural network in a rigorous way.

In this dissertation, we focus on …

Robust Learning With Probabilistic Relaxation Using Hypothesis-Test-Based Sampling, Zilin Wang

Dissertations and Theses Collection (Open Access)

In recent years, deep learning has been a vital tool in various tasks. The performance of a neural network is usually evaluated by empirical risk minimization. However, robustness issues have gained great concern which can be fatal in safety-critical applications. Adversarial training can mitigate the issue by minimizing the loss of worst-case perturbations of data. It is effective in improving the robustness of the model, but it is too conservative, and the plain performance of the model can be unsatisfying. Probabilistic Robust Learning (PRL) empirically balances the average- and worst-case performance while the robustness of the model is not provable …

Towards Robust, Secure, And Privacy-Aware Large Language Models Of Code, Zhou Yang

Dissertations and Theses Collection (Open Access)

The field of software engineering has witnessed a surge in large language models specifically tailored to understand and process code, which we call large language models for code (LLM4Code). The increasing popularity of LLM4Code is inseparable from three key factors: the availability of extensive datasets compiled from diverse data sources, the advancements in deep learning algorithms and computational power that facilitate the training of these powerful models, and the active engagement and collaboration within the research community fostering innovation and the rapid exchange of ideas and methodologies. As evidenced by a series of studies, LLM4Code has been experiencing rapid development …

Manufacturing Enterprises' Gross Margins And Performance: A Study On The Moderating Effect Of Management Expenses And R&D Expenses, Jiuliu Zhang

Dissertations and Theses Collection (Open Access)

In the context of globalization, manufacturing enterprises are integral to national economies, with their financial stability closely related to increasingly fierce market competition. Among various financial metrics, gross margin stands out as a key indicator of product profitability, significantly impacting production decisions, cost control, and pricing strategies. Understanding the relationship between the gross margins of manufacturing enterprises and their performance is essential for optimizing their financial structures and enhancing their market competitiveness. The study aims to investigate the correlation between gross margin and enterprise performance by developing complex, scientifically sound models and utilizing big data analysis technology. Additionally, it examines …

On The Decomposability Of Fractional Allocations, Shurojit Chatterji, Peng Liu

Research Collection School Of Economics

A common practice in dealing with the allocation of indivisible objects is to treat them as infinitely divisible and specify a fractional allocation, which is then implemented as a lottery on integer allocations that are feasible. The question we study is whether an arbitrary fractional allocation can be decomposed as a lottery on an arbitrary set of feasible integer allocations. The main result is a characterization of decomposable fractional allocations, that is obtained by transforming the decomposability problem into a maximum flow problem. We also provide a separate necessary condition for decomposability.

A Data-Driven Approach For Automated Multi-Site Competitive Facility Location, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper addresses the challenge of optimal retail expansion in competitive urban environments through a novel approach to the Competitive Facility Location (CFL) problem. Traditional methods for solving CFL problems often struggle with large-scale scenarios, relying on manual pre-selection of candidate sites and imposing limitations on the number of new locations. Our approach leverages Adaptive Large Neighborhood Search (ALNS) enhanced with data enrichment techniques, including community detection on road networks and population weighting based on mobility data. We developed two ALNS variants: Community Geometric Centroid (CGC-ALNS) and Population Weighted Centroid (PWC-ALNS). These methods automate site selection, eliminating manual pre-selection while …

Harnessing The Power Of Ai-Instructor Collaborative Grading Approach: Topic-Based Effective Grading For Semi Open-Ended Multipart Questions, Phyo Yi Win Myint, Siaw Ling Lo, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Semi open-ended multipart questions consist of multiple sub questions within a single question, requiring students to provide certain factual information while allowing them to express their opinion within a defined context. Human grading of such questions can be tedious, constrained by the marking scheme and susceptible to the subjective judgement of instructors. The emergence of large language models (LLMs) such as ChatGPT has significantly advanced the prospect of automatic grading in educational settings. This paper introduces a topic-based grading approach that harnesses LLM capabilities alongside a refined marking scheme to ensure fair and explainable assessment processes. The proposed approach involves …

Gtree: Gpu-Friendly Privacy-Preserving Decision Tree Training And Inference, Qifan Wang, Shujie Cui, Lei Zhou, Ye Dong, Jianli Bai, Yun Sing Koh, Giovanni Russello

Research Collection School Of Computing and Information Systems

Outsourcing Decision tree (DT) training and inference to cloud platforms raises privacy concerns. Recent Secure Multi-Party Computation (MPC)-based methods are hindered by heavy overhead. Few recent studies explored GPUs to improve MPC-protected deep learning, yet integrating GPUs into MPC-protected DT with massive data-dependent operations remains challenging, raising question: can MPC-protected DT training and inference fully leverage GPUs for optimal performance?We present GTree, the first scheme that exploits GPU to accelerate MPC-protected secure DT training and inference. GTree is built across 3 parties who jointly perform DT training and inference with GPUs. GTree is secure against semi-honest adversaries, ensuring that no …

Was 2024 A Good Year For You? Let’S Review Your Yardsticks…, Seow Hon Tan, Su Ching Lim

Research Collection Yong Pung How School Of Law

This op-ed encourages all to reflect on their year and examine whether they have lived meaningfully according to their yardstick of meaning, the legacy they want to leave behind, and whether their talents and credentials are empowering and enabling, rather than restricting them. It is written as part of a research project examining success and flourishing in Singapore.

Prevention Is Better Than Cure: Rethinking Court Behaviour And Design, De Maartje Visser

Research Collection Yong Pung How School Of Law

Using a relational dynamics perspective, this commentary considers how to buttress courts' ability to practice their role as guardians of the constitution. It suggests that we should pay more attention to empowering the general public to provide meaningful social support for courts through constitutional literacy efforts. Such literacy efforts should focus on the place of the court within the separation of powers and the value of judicial independence. At the same time, it may be prudent to redact the list of tasks given to constitutional courts and divest responsibility for some activities to other institutions.

The Case For Stronger Scrutiny Of The Deductibility Of Crypto Losses, Vincent Ooi

Research Collection Yong Pung How School Of Law

Crypto losses have the potential to adversely impact the tax base, particularly if they are deducted against income from other profitable sources. There is a key question of fairness as to whether crypto losses should be cross-subsidised by income from other sources that may have nothing to do with cryptoassets at all. This article argues for stronger scrutiny of the deductibility of crypto losses at the stage of determining whether such losses can be set off against income from other sources or at the stage of the shifting of the losses across time and between companies. It explains why crypto …

Disputing Personal Data In The Eu-China Comprehensive Agreement On Investment, Mark Mclaughlin

Research Collection Yong Pung How School Of Law

This chapter analyses the emerging data realms in China and the European Union against the backdrop of the Comprehensive Agreement on Investment (CAI). It examines the link between data protection and investment flows and undertakes a comparative analysis of the PIPL and GDPR. Moreover, this chapter will also analyse the Digital Silk Road in promoting China’s model of data sovereignty. While early trade and investment agreements did not consider data relevant for the regulation of cross-border commerce, modern treaties are increasingly cognisant of rules for data protection. As such, the data-related provisions of the CAI will be placed in the …

Personality Dynamics Turn Positive And Negative Mood Into Creativity, Ronald Bledow, Jana Kuhnel, Julius Kuhl

Research Collection Lee Kong Chian School Of Business

Introduction: Research on the link between affect and creativity rests on the assumption that creativity unfolds as a stimulus-driven response to affective states. We challenge this assumption and examine whether personality dynamics moderate the relationship of positive and negative mood with creativity. Theoretical Model: According to our model, personality dynamics that generate and maintain positive affect and down-regulate negative affect energize creativity. Based on this model, we expect high creativity in response to negative mood if people engage in self-motivation and achieve a reduction in negative mood. We further derive that individual differences in action versus state orientation moderate the …