Digital Commons Network^™

Explorelah: Personalised And Smart Trip Planner For Mobile Tourism, Aldy Gunawan, Siu Loon Hoe, Xun Yi Lim, Linh Chi Tran, Dang Viet Anh Nguyen

Research Collection School Of Computing and Information Systems

Various recommender systems for mobile tourism have been developed over the years. However, most of these recommender systems tend to overwhelm users with too much information and may not be personalised to user preferences. In this paper, we introduce ExploreLah, a personalised and smart trip planner for exploring Point of Interests (POIs) in Singapore. The user preferences are categorised into five groups: shopping, art & culture, outdoor activity, adventure, and nightlife. The problem is considered as the Team Orienteering Problem with Time Windows. The algorithm is developed to generate itineraries. Simulated experiments using test cases were performed to evaluate and …

M2-Cnn: A Macro-Micro Model For Taxi Demand Prediction, Shih-Fen Cheng, Prabod Manuranga Rathnayaka Mudiyanselage

Research Collection School Of Computing and Information Systems

In this paper, we introduce a macro-micro model for predicting taxi demands. Our model is a composite deep learning model that integrates multiple views. Our network design specifically incorporates the spatial and temporal dependency of taxi or ride-hailing demand, unlike previous papers that also utilize deep learning models. In addition, we propose a hybrid of Long Short-Term Memory Networks and Temporal Convolutional Networks that incorporates real world time series with long sequences. Finally, we introduce a microscopic component that attempts to extract insights revealed by roaming vacant taxis. In our study, we demonstrate that our approach is competitive against a …

Interoperability In Blockchain: A Survey, Kunpeng Ren, Nhut-Minh Ho, Dumitrel Loghin, Thanh-Toan Nguyen, Beng Chin Ooi, Quang-Trung Ta, Feida Zhu

Research Collection School Of Computing and Information Systems

This paper presents a systematic and comprehensive survey on blockchain interoperability, where interoperability is defined as the ability of blockchains to flexibly transfer assets, share data, and invoke smart contracts across a mix of public, private, and consortium blockchains without any changes to the underlying blockchain systems. Analyzing the vast landscape of both research papers and industry projects, we classify the existing works into five categories, namely, (1) sidechains, (2) notary schemes, (3) hashed time lock contracts (HTLC), (4) relays, and (5) blockchain agnostic protocols. We analyze the existing works under a taxonomy that consists of system and safety characteristics, …

Data-Driven Optimization Approaches For Dynamic Urban Logistics Operational Problems, Jingfeng Yang

Dissertations and Theses Collection (Open Access)

Given the rapid pace of urbanization, there is a pressing need to optimize urban logistics delivery operations for enhanced capacity and efficiency. Over recent decades, a multitude of optimization approaches have been put forth to address urban logistics challenges, encompassing routing and scheduling within both static and dynamic contexts. In light of the rising computational capabilities and the widespread adoption of machine learning in recent times, there is a growing body of research aimed at elucidating the seamless integration of data and machine learning within conventional urban logistics optimization models. Additionally, the ubiquitous utilization of smartphones and internet innovations presents …

Modelling Sentiment And Trader Aggressiveness In Cryptocurrency Markets: An Empirical Analysis Of The Bitcoin Limit Order Book., Angelique Nicole Huei Yin Thang

Dissertations and Theses Collection (Open Access)

Cryptocurrency assets are inherently susceptible to social sentiment. Due to emotional contagion, extreme emotions influence and drive traders’ order execution behaviour. This study aims to empirically model the relationship between sentiment and trader aggressiveness for two types of traders: Whales and Retails. Additionally, I uncover the mediating roles of momentum, mean reversion, and market timing underpinning the dynamics of the off-chain Bitcoin market. Time series data collected from the Coinbase level 3 Bitcoin limit order book is first reconstructed to access its core structure. Next, sentiment data from Reddit is extracted and processed using an internal Natural Language Processing pipeline. …

Buffering The Negative Impacts Of Age Diversity On Company Performance And Innovation: The Roles Of Knowledge Transfer And Environmental Uncertainty, Tiecheng Xu

Dissertations and Theses Collection (Open Access)

The VUCA (Volatility, Uncertainty, Complexity, Ambiguity) era has resulted in significant uncertainty in the global economy, while deglobalization in international politics and economics, and the interweaving of old and new contradictions, have presented substantial challenges to businesses. On the other hand, aging is a crucial issue that China and the world at large are currently facing. It is essential to study the relationship between employee age structure and enterprise performance.

Different researchers have provided empirical analyses of the effects of age diversity on organizational performance and innovation, but the conclusions are not consistent. According to the research in this paper, …

The Determinants Of Creator Performance On Creative Content Platforms: Evidence From Xiaohongshu And Bilibili, Caijun Xu

Dissertations and Theses Collection (Open Access)

Content creation platforms, including Douyin, Kuaishou, Xiaohongshu, and Bilibili, have emerged as significant drivers of employment and economic growth within the digital economy. These platforms invigorate online engagement and offline consumption, serving as vital conduits that merge China’s digital and real economies. Currently, China boasts over 10 million active content creators on its leading platforms, although their earnings are markedly uneven. While some top-tier creators garner substantial profits, the majority in the mid to lower tiers grapple with profit generation and encounter challenges in enhancing their creative performance. Against this background, this study delves into the antecedents of creative performance. …

When Social Status Gets In The Way Of Mating: The Incompatibility Between Social Status And Reproductive Goals In Modern Contexts, Jose C. Yong, Amy J. Y. Lim, Norman P. Li

Research Collection School of Social Sciences

Low fertility is a growing concern in modern societies. While economic and structural explanations of reproductive hindrances have been informative to some extent, they do not address the fundamental motives that underlie reproductive decisions and are inadequate to explain why East Asian countries, in particular, have such low fertility rates. The current paper advances a novel account of low fertility in modern contexts by describing how modern environments produce a mismatch between our evolved mechanisms and the inputs they were designed to process, leading to preoccupations with social status that get in the way of mating and reproductive outcomes. We …

The Use Of Deception In Dementia-Care Robots: Should Robots Tell "White Lies" To Limit Emotional Distress?, Samuel R. Cox, Grace Cheong, Wei Tsang Ooi

ROSA Journal Articles and Publications

With projections of ageing populations and increasing rates of dementia, there is need for professional caregivers. Assistive robots have been proposed as a solution to this, as they can assist people both physically and socially. However, caregivers often need to use acts of deception (such as misdirection or white lies) in order to ensure necessary care is provided while limiting negative impacts on the cared-for such as emotional distress or loss of dignity. We discuss such use of deception, and contextualise their use within robotics.

Using Team Rewards And Individual Assessment To Incentivize Collaboration In Team Projects, Prasart Jongjaroenkamol

Research Collection School Of Accountancy

Team projects are commonly used in higher education across different disciplines to promote cooperation among students. However, achieving this objective can be challenging. To address this issue, educators have explored various strategies, such as implementing peer evaluation or having periodic consultations with teams. In this paper, I present a novel approach to team assessment that combines team rewards with individual assessment. In this assessment, each team member independently takes a quiz, and the team's score is determined by the average performance of its members. Consequently, the team reward becomes intricately tied to the individual learning outcomes of all team members. …

Greater Traditionalism Predicts Covid-19 Precautionary Behaviors Across 27 Societies, Theodore Samore, D. M. T. Fessler, A. M. Sparks, C. Holbrook, L. Aaroe, Norman P. Li, Kai Lin Lynn Tan, Et Al

Research Collection School of Social Sciences

People vary both in their embrace of their society’s traditions, and in their perception of hazards as salient and necessitating a response. Over evolutionary time, traditions have offered avenues for addressing hazards, plausibly resulting in linkages between orientations toward tradition and orientations toward danger. Emerging research documents connections between traditionalism and threat responsivity, including pathogen-avoidance motivations. Additionally, because hazard-mitigating behaviors can conflict with competing priorities, associations between traditionalism and pathogen avoidance may hinge on contextually contingent tradeoffs. The COVID-19 pandemic provides a real-world test of the posited relationship between traditionalism and hazard avoidance. Across 27 societies (N = 7844), we …

Becoming A Father, Staying A Father: An Examination Of The Cumulative Fatherhood Wage Premium To U.S. Residential Fathers, Ohjae Gowen

Research Collection School of Social Sciences

The instability of fathers’ co-residence with children has become an increasingly prevalent experience for U.S. families. Despite long-standing scholarship examining the relationship between fatherhood and wage advantages, few studies have investigated how variation in fathers’ stable co-residence with a child may produce temporal changes in the wage premium over the life course. Building on prior explanations of the fatherhood wage premium, I test if the wage premium grows with time since the birth of a resident child and if the premium depends on fathers’ co-residence with a child. I use marginal structural models with repeated outcome measures and data from …

Cross-Period Impatience: Subjective Financial Periods Explain Time-Inconsistent Choices, Minkwang Jang, Oleg Urminsky

Research Collection Lee Kong Chian School Of Business

Inconsistency in consumer time preferences has been well established and used to explain seemingly short-sighted behaviors (e.g., failures of self-control). However, prior research has conflated time-inconsistent preferences (discount rates that vary over time) with present bias (greater discounting when outcomes are delayed specifically from the present, as opposed to from a future time). This research shows that time-inconsistent preferences are reliably observed only when choices are substantially delayed (e.g., months into the future), which cannot be explained by present bias. This seeming puzzle is explained by a novel cross-period discounting framework, which predicts that consumers are more impatient when choosing …

Maintaining Consistent Sustainability Performance Through Peaks In Last Mile Logistics: What Factors Most Influence The Maintenance Of Consistent Social And Environmental Sustainability Performance In Last Mile Logistics During Peak Periods? How Do These Factors Exercise This Influence?, Prashant Saran

Dissertations and Theses Collection (Open Access)

Last Mile Logistics (LML) is the final leg of the supply chain that gets the product to the chosen destination point of the end consumer. LML has been witnessing unprecedented growth driven by increasing urbanization and growth in e-commerce retail sales. The impact of the rapid growth of LML is being witnessed both in the social and environmental dimensions, making social and environmental sustainability (S&ES) of LML an impactful area of research. LML deliveries driven by e-commerce also experience multiple demand peaks where the number of packages to be delivered spikes significantly over a short period of a few days …

Weakly-Supervised Semantic Segmentation, Zhaozheng Chen

Dissertations and Theses Collection (Open Access)

Semantic segmentation is a fundamental task in computer vision that assigns a label to every pixel in an image based on the semantic meaning of the objects present. It demands a large amount of pixel-level labeled images for training deep models. Weakly-supervised semantic segmentation (WSSS) is a more feasible approach that uses only weak annotations to learn the segmentation task. Image-level label based WSSS is the most challenging and popular, where only the class label for the entire image is provided as supervision. To address this challenge, Class Activation Map (CAM) has emerged as a powerful technique in WSSS. CAM …

Supporting Software Engineers With Large Language Model-Based Automation, Ting Zhang

Dissertations and Theses Collection (Open Access)

In recent years, software engineering (SE) has witnessed significant growth, leading to the creation and sharing of an abundance of software artifacts such as source code, bug reports, and pull requests. Analyzing these artifacts is crucial for comprehending the sentiments of software developers and automating various SE tasks, ultimately leading to more human-centered automated SE and enhancing software development efficiency. However, the diverse and unstructured nature of software text poses a significant challenge to this analysis. In response, researchers have investigated a variety of approaches, including the utilization of natural language processing techniques. The advent of large language models (LLMs), …

Towards Securing Smart Contracts Systematically, Duy Tai Nguyen

Dissertations and Theses Collection (Open Access)

Smart contracts are a groundbreaking technique that allows users to programmatically modify the state of the blockchain. They are essentially self-enforcing programs that are deployed and executed on top of the blockchain. In recent years, we have witnessed various smart contract incidents that led to substantial financial losses and even business closures. These incidents mainly arise from design flaws in Solidity, a dominant programming language for writing smart contracts, which complicates the process of detecting and repairing vulnerabilities. Furthermore, there is a growing interest in attacking smart contracts by the attackers. This thesis is dedicated to developing effective methods to …

The Relationship Between Reits Industry Characteristics And Project Performance: The Moderating Role Of Macroeconomic Fluctuations, Ying Cai

Dissertations and Theses Collection (Open Access)

As a distinct investment vehicle, Publicly Listed Real Estate Investment Trusts (REITs) projects enable real estate projects to be listed on the stock market. This study begins with the industry attributes of the underlying assets of Publicly Listed REITs projects. Using econometric methods, it analyzes the variances in market performance between growth and defensive REITs, based on annual data from 1,674 REITs products in the United States from 2005 to 2022 and 27 listed REITs in China from Q3 2021 to Q1 2023. The study also leverages the data from China to explore the moderating effects of macroeconomic factors such …

Technical Maturity And Network Effects Of Xf Artificial Intelligence Open Platform, Tao Jiang

Dissertations and Theses Collection (Open Access)

Studying the impact mechanism of the commercial value of artificial intelligence open technology platforms has theoretical and practical significance. This article aims to enrich and expand the theoretical research on technology maturity, value co creation, and network effects on open technology platforms at home and abroad through empirical research on artificial intelligence open technology platforms and ecology. This study takes XF's open technology platform case as the research object, and based on technology maturity theory, value co creation, and network effects theory, examines the network effect value creation mechanism of open technology platforms driven by technology maturity in three development …

Gender Divergence In Premarket Skill Acquisition And Wage Inequality, Sunha Myong

Research Collection School Of Economics

I study the changes in premarket skills and the evolution of the wage distribution across two cohorts using the NLSY79 and NLSY97. To estimate the relative importance of changes in premarket skills and changes in skill prices in explaining the evolution of the wage distribution, I apply the DiNardo, Fortin, and Lemieux decomposition method (DiNardo et al. 1996). I find a substantial gender divergence in premarket skill acquisition and wage gain across the two cohorts. Women's wage gain associated with changes in premarket skills is greater than that of men's at all levels of the wage distribution. Changes in premarket …

Market For Patents, Monopoly, And Misallocation, Shang-Jin Wei, Jianhuan Xu, Ge Yin, Xiaobo Zhang

Research Collection School Of Economics

The paper studies a possible “dark side” of patent trade in enhancing the market power of monopolists. We explore the different effects of China’s 2008 tax reform on patent innovations and sales across industries. In particular, although easier patent trade leads to more patent creation, the new patents are disproportionately connected to existing monopolists and are more likely to be acquired by them. Using an endogenous growth model with patent trade, we show that subsidizing patent trade could skew investors’ research to appeal to the monopolists, increase the latter’s monopoly power, and reduce social welfare. An optimal subsidy policy for …

The Depth Of Preferential Trade Agreements, Pao-Li Chang, Wei Jin, Kefang Yao

Research Collection School Of Economics

Preferential trade agreements (PTAs) have increased rapidly in number since the 1990s, and have extended their traditional focus on tariff reduction to include deeper integration in policy areas such as competition policy, intellectual property rights, investments, and movement of capital. This paper uses a comprehensive dataset on the content of PTAs to quantify the impacts of the depth of trade agreements on bilateral trade flows and national welfare across the world for the period 1980–2015. The results indicate that agreements that are deeper (by different definitions) contribute to larger trade growth and welfare gains. Furthermore, the results imply that the …

Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …

Dynamic Factor Copula Models With Estimated Cluster Assignments, Dong Hwan Oh, Andrew John Patton

Research Collection School Of Economics

This paper proposes a dynamic multi-factor copula for use in high-dimensional time series applications. A novel feature of our model is that the assignment of individual variables to groups is estimated from the data, rather than being pre-assigned using SIC industry codes, market capitalization ranks, or other ad hoc methods. We adapt the k-means clustering algorithm for use in our application and show that it has excellent finite-sample properties. Applying the new model to returns on 110 US equities, we find around 20 clusters to be optimal. In out-of-sample forecasts, we find that a model with as few as five …

Assignment (Or Novation) Of Indemnity Policies, Chee Ho Tham

Research Collection Yong Pung How School Of Law

In this article Dr Chee Ho Tham suggests that terminological confusion has arisen over the use of the phrase “assignment” in connection with policies of non-marine indemnity insurance, where the “assignment” is made before the occurrence of the insured event which causes loss or damage to the subject-matter of the policy. An “assignment” of the contract of insurance entails a novation and should be referred to as such.

Criminal Law In Myanmar, Wing Cheong Chan, Mark Mcbride, Neil Morgan, Stanley Yeo

Research Collection Yong Pung How School Of Law

A commentary on the Myanmar Penal Code that describes and critically evaluates the general principles of criminal responsibility contained in the Code. This book was originally published in English in 2016. It was republished in Burmese in 2023.

"Takings" And "Givings" In Singapore: Land Law And Policy In The Search For Justice, Rachel Phang

Research Collection Yong Pung How School Of Law

In the United States and globally, cities are increasingly plagued by deepening housing crisis and widening economic inequality. In the face of these crises, this Article focuses on the potentially powerful role for land law and policy in the search for justice. Specifically, it does so by reference to two unusual yet illuminating choices of theory and application: the case study of Singapore, and the school of thought of Georgism, both of which accord inordinate and paramount importance to land. Singapore’s land law and policy have been characterized by extensive takings and givings of land. In consequence, the State owns …

Open Finance: Regulatory Challenges Of The Evolution Of Data Sharing Arrangements In The Financial Sector, Nydia Remolina Leon

Research Collection Yong Pung How School Of Law

In recent years, open banking has emerged as a new form of financial intermediation, allowing third party developers to build applications and services around financial institutions. By using the financial institution's data and infrastructure through open Application Programming Interfaces (APIs), a variety of actors-including fintech companies, Bigtechs, and the traditional players in the financial system-can develop new products and services that ultimately promote innovation, competition and financial inclusion while improving consumers' experiences. The concept of open banking evolved to open finance to illustrate the possibilities of adding to the picture all types of data-driven financial products. Focusing on the opportunities …

Exposure To Climate Change Information Predicts Public Support For Solar Geoengineering In Singapore And The United States, Sonny Rosenthal, Peter J. Irvine, Christopher L. Cummings, Shirley S. Ho

Research Collection College of Integrative Studies

Solar geoengineering is a controversial climate policy measure that could lower global temperature by increasing the amount of light reflected by the Earth. As scientists and policymakers increasingly consider this idea, an understanding of the level and drivers of public support for its research and potential deployment will be key. This study focuses on the role of climate change information in public support for research and deployment of stratospheric aerosol injection (SAI) in Singapore (n = 503) and the United States (n = 505). Findings were consistent with the idea that exposure to information underlies support for research and deployment. …

Forecasting Traffic Speed During Daytime From Google Street View Images Using Deep Learning, Junfeng Jiao, Huihai Wang

Research Collection College of Integrative Studies

Traffic forecasting plays an important role in urban planning. Deep learning methods outperform traditional traffic flow forecasting models because of their ability to capture spatiotemporal characteristics of traffic conditions. However, these methods require high-quality historical traffic data, which can be both difficult to acquire and non-comprehensive, making it hard to predict traffic flows at the city scale. To resolve this problem, we implemented a deep learning method, SceneGCN, to forecast traffic speed at the city scale. The model involves two steps: firstly, scene features are extracted from Google Street View (GSV) images for each road segment using pretrained Resnet18 models. …