Digital Commons Network^™

From Catching Up To Surpassing—A Multi-Case Study Of Chinese Latecomer Technology Firms, Baohua Chen

Dissertations and Theses Collection (Open Access)

In recent years, a number of Chinese latecomer technology firms have grown rapidly and, in some cases, have even moved into leading positions in global competition. As global competition is being reshaped, technologies are evolving more rapidly, and traditional catch-up paths are becoming less viable, how these Chinese latecomer technology firms catch up with leading incumbents has become an important issue in strategic management research. Drawing on the theoretical lens of asymmetrical competition, resource orchestration, and dynamic capabilities, this study adopts an Eisenhardt-style multiple-case design to conduct a longitudinal comparative analysis of six firms—Insta360, Dreame, DJI, Unitree, Transsion, and Royole—and …

Essays On Money Search Models, Fangfang Gong

Dissertations and Theses Collection (Open Access)

This dissertation comprises three papers that use money search models to revisit the distributional welfare costs of inflation, study the optimal design of a central bank digital currency (CBDC), and investigate the role of liquidity and monetary policy in initial investment and capital reallocation in secondary markets.

The second chapter develops a micro-founded general equilibrium model of payments to revisit the distributional welfare costs of inflation. We consider different cost structures incurred by merchants when accepting cash and deposits. In equilibrium, there exists a cutoff for buyers’ money holdings, above which card payments are accepted by merchants. We calibrate the …

Uncertainty, Information, And Major Choice: Evidence From Chinese Gaokao, Sikun Dou

Dissertations and Theses Collection (Open Access)

An unresolved background risk makes people more averse to other, independent  risks—most of all when a high-stakes, irreversible choice must be made under that risk. College major choice is such a setting. In China, students are admitted directly into a major they cannot easily change, and in the early 2000s they had to commit before learning their exam scores, bearing a field’s academic risk on top of an unresolved admission risk. Because STEM fields carry more academic risk and women are on average more risk-averse, this burden falls hardest on women’s entry into STEM. Exploiting a reform that moved application …

The Effect Of A 14-Day Digital Nudge-Based Sleep Hygiene Intervention On Behavioural, Cognitive, And Emotional Well-Being In College Students: An Experimental Approach, Tracy X. Chen, Chi-Ying Cheng, Michelle Koay, Chin Boon Soh, Andree Hartanto

Research Collection School of Social Sciences

Sleep is essential for one's cognitive, psychological, and physical health. Yet, college students often face sleep deprivation due to academic demands, social obligations, and extracurricular commitments. This study implemented a 14-day Digital Nudge-Based Sleep Hygiene Intervention, delivered via a digital platform, to encourage healthier sleep practices among college students. Grounded in nudge theory, the digital intervention used subtle behavioural prompts to improve participants' sleep hygiene without imposing restrictions, demonstrating high adherence and scalability. Participants were guided through daily tasks to enhance autonomy and motivation, such as creating calming bedtime routines. The digital intervention led to positive outcomes across four domains: …

Outcomes Associated With Childhood Parental Divorce: An Umbrella Review Of Meta-Analyses, Gabriel Xing Da Tan, Andree Hartanto, Ysabel Thereze Ang Guevarra, Angel K. M. P. Lee, Jing Jie Kenneth Koh, K Tennakoon Appuhamillage Sandeeshwara Kasturiratna

Research Collection School of Social Sciences

Background: Childhood parental divorce has been consistently associated with a host of negative outcomes across multiple domains, such as socioemotional, behavioural, academic, and physical health, which can persist into adulthood. Despite extensive research on childhood parental divorce, the current literature lacks a systematic, integrated synthesis that clarifies which child outcomes are most consistently associated with parental divorce, as well as the potential moderators influencing these associations. Therefore, we conducted an umbrella review of meta-analyses to bridge this gap by consolidating the existing research and providing an exhaustive overview. Methods: Systematic searches were conducted across various databases and following a two-stage …

The Smallholder’S Dilemma In Agroecological Transitions: The Diseconomy Of Agroecology For Small Farmers In Industrial Agriculture, Qian Forrest Zhang

Research Collection School of Social Sciences

A scalar contradiction exists between agroecology's three goals: while ecological sustainability is best pursued at the landscape scale, social equity and livelihood goals often require organizing production at the small scale of family farms. In China's ‘industrial agriculture of small farmers’, ecological farming practices became economically unviable at small farmers' minuscule scales. Agroecological transitions almost always first go through a scale expansion, a process fraught with tension. The empirical analysis focuses on three ‘ecological farms’ that enjoyed favorable conditions unattainable to smallholders. Yet, lock-ins across five dimensions have either made their operations economically unsustainable or forced compromises in agroecological principles.

Log Off To Level Up: The Effect Of Social Media Hiatus On Goal Pursuit, Nekysha L. Y. Jalil, Yong Han Tan, Andree Hartanto, Eddie M. W. Tong

Research Collection School of Social Sciences

Concerns are growing that social media, with its constant notifications and attention-grabbing content, may distract individuals and hinder progress toward important goals. Despite its pervasive presence in our lives, the impact of social media on goal achievement has not been thoroughly studied. This within-subject experimental study aims to investigate the effects of social media hiatus (SMH), a short abstinence from social media usage, on goal pursuit processes. Participants (N= 107) completed daily diaries over three consecutive days of SMH and three days of regular social media use. SMH was manipulated by blocking participants’ access to multiple social media platforms. The …

Sevoauth: Secure Voiceprint Authentication With Hash-Based Feature Transformation, Rui Zhang, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

While voiceprint authentication offers convenient user authentication and access control through voice feature recognition, a critical research gap remains: existing voiceprint authentication systems fail to simultaneously achieve sound security against replay, spoofing, and adversarial attacks, preserve voice privacy leakage, and satisfy usability demand. Previous efforts have struggled to balance these issues comprehensively. To bridge this gap, we present SeVoAuth, a cloud-based Voiceprint Authentication as a Service (VAaaS) system designed to provide privacy preservation, robust security, and enhanced usability. SeVoAuth stores a synthesized voiceprint of a user in the cloud during user registration, thereby safeguarding the privacy of the real voiceprint …

Synthesis And Evaluation Of Long-Term History-Aware Medical Dialogue, Hebin Hu, Renke Dai, Ah-Hwee Tan, Yilin Kang

Research Collection School Of Computing and Information Systems

An effective healthcare agent must be able to recall and reason over a patient’s longitudinal medical history. However, the absence of datasets with realistic long-term dialogue timelines limits systematic evaluation. Real clinical text is constrained by privacy and ethics, while existing benchmarks focus on isolated interactions, failing to capture cross-session reasoning. We introduce a framework for synthesizing high-quality, long-term medical dialogues with LLMs. Our approach entails a knowledge-guided decomposition into three stages: constructing synthetic patient profiles with diverse disease and complication trajectories, generating multiturn dialogues per encounter, and integrating them into a coherent longitudinal history dataset, MediLongChat. We establish three …

Open Source Software Development Tool Installation: Challenges And Strategies For Novice Developers, Larissa Salerno, Christoph Treude, Patanamon Thongtanunam

Research Collection School Of Computing and Information Systems

As the world of technology advances, so do the tools that software developers use to create new programs. In recent years, software development tools have become more popular, allowing developers to work more efficiently and produce higher-quality software. Still, installing such tools can be challenging for novice developers at the early stage of their careers, as they may face issues such as compatibility problems (e.g., with operating systems) and unclear instructions. Therefore, this work aims to investigate the challenges novice developers face when installing software development tools and the strategies they employ to overcome them. To investigate these, we conducted …

Generation Of Elaborated, Targeted And Effective Feedback For Novice Programmers Using Llm, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Programming errors and misconceptions are pervasive in novice programmers which causes difficulty in the learning of computer programming. Large Language Models (LLMs), with their ability to comprehend and generate programming codes have shown promising results in the automatic identification of errors. This can potentially benefit student programmers by providing them with timely formative feedback at efficiencies and scale that were not attainable previously. In this study, we leveraged an LLM - OpenAI o4-mini for the generation of elaborated, targeted feedback for novice programmers across PHP and JavaScript exercises. We contend that the feedback needs to be effective and targeted other …

Fighting Against Recruitment Scams: Theory-Driven Supervised Learning And Empirical Analysis For Digital Fraudulent Recruitment Posting Behavior, Tom (Tianteng) Wang, David (Jingjun) Xu, Keng Siau, Zhongju (John) Zhang

Research Collection School Of Computing and Information Systems

The number of recruitment postings on digital recruitment hiring platforms has increased since the COVID-19 pandemic. However, the weak surveillance and operations of these platforms, combined with the fact that most job seekers have relatively low vigilance and a strong desire for recruitment offers, enable scammers to easily deceive job seekers for their money and confidential information. In this work, we combine prevailing text mining techniques (i.e., ChatGPT with prompting engineering and supervised machine learning) with interpersonal deception theory (IDT) from social science to design an interpretable IT system to predict fraudulent recruitment postings on digital recruitment-hiring platforms. We compare …

Perception Of Socioeconomic Status: A Meta-Analysis Of Manipulations, Jacinth Jia Xin Tan, Yong En Amos Tai

Research Collection School of Social Sciences

The causal effects of one’s socioeconomic status (SES) on outcomes are typically examined by experimentally manipulating SES self-perceptions based on one of three SES dimensions—absolute resource, relative resource, and general social position. We investigated the efficacy of these manipulations by systematically meta-analyzing their effects on SES self-perceptions. Based on 107 eligible samples (N = 26,203), manipulations of SES self-perceptions across the three SES dimensions were effective overall (g = 0.56–0.95). Explicit priming of absolute resource and relative resource manipulations comparing high versus low SES were consistently effective—although bias-corrected effects were attenuated—suggesting the importance of salient SES information and social comparisons. …

Financial Technology And Household Wealth, Rongbo Zhou

Dissertations and Theses Collection (Open Access)

With the spread of mobile payment platforms in China, the micro-foundations of household financial behaviour have been reshaped, and this change is increasingly reflected in household property income. Based on microdata from the China Household Finance Survey (CHFS) for 2015, 2017, 2019, and 2021, this dissertation examines how mobile payment use affects household property income, through which channels this effect is transmitted, and how its impact differs across household groups, regional conditions, and macro-financial environments.

The empirical results show a positive association between the use of mobile payment platforms and household property income. This conclusion remains robust after controlling for …

An Empirical Study On The Impact Of Eco-Friendly Selling Points On The Purchase Intention Of Young Chinese Consumers, Yang Liu

Dissertations and Theses Collection (Open Access)

Industry consumer research widely portrays Generation Z as an identity-driven cohort that enacts sustainability values through consumption. This narrative is often generalized across cultural contexts, assuming that Western-developed green consumption frameworks can be directly transferred without structural modification. Yet Chinese Gen Z’s e-commerce purchase patterns depart notably from this depiction, raising core questions: Can Western green consumption frameworks be applied to Chinese Gen Z? If so, what theoretical and structural adaptations are necessary?

This dissertation develops and tests an integrated three-pathway model to explain green purchase intention among Chinese Gen Z consumers. The model places utilitarian benefits, self-expression benefits, and …

Securing Cloud-Native Systems: From Vulnerability Analysis To External And Insider Threat Detection, Jiongchi Yu

Dissertations and Theses Collection (Open Access)

Cloud-native systems have become the backbone of modern software infrastructure. However, their dynamic resource orchestration and complex configurability introduce a large attack surface and intricate security challenges. Adversaries can externally exploit vulnerabilities in cloud components or perform insider movement within cloud environments to launch attacks. As these systems increasingly support critical services, security breaches can lead to severe operational and economic consequences.

Despite extensive efforts in vulnerability detection and attack monitoring, existing approaches struggle to remain effective in cloud-native environments characterized by rapid evolution and inherent heterogeneity. In particular, they exhibit three fundamental limitations: (1) Insufficient understanding of defect patterns …

Childlessness And Advance Care Planning In Midlife And Late Adulthood: A Mixed-Methods Study In Singapore, Bussarawan Teerawichitchainan, Dahye Kim, Pearlyn Hui Min Hui, Christine Ho

Research Collection School Of Economics

Advance care planning (ACP) is critical for ensuring high-quality, cost-effective end-of-life care and is typically facilitated by spouses and adult children. Yet, the growing number of older adults without children has been overlooked in ACP research. This study employs a mixed-methods approach to examine ACP practices and perceptions among childless adults aged 50+ in Singapore, a rapidly aging society with one of the world's highest childlessness rates. Quantitative analyses draw on nationwide survey data (N = 1,500), complemented by interviews with childless respondents (N = 26). We examine multiple dimensions of ACP: formal ACP (e.g., living wills, Lasting Power of …

From Trees To Treewidth: Inventory Management In Complex Supply Chain Networks, Philippe Blaettchen, Andre Calmon, Georgina Hall, Mohit Tawarmalani

Research Collection Lee Kong Chian School Of Business

We propose an exact solution approach to the Guaranteed Service Model (GSM), one of the most widely applied models for optimizing safety stock placement in supply chain networks. Based on linear programming (LP), our approach handles any directed acyclic network and any cost function that depends on a stage's incoming and outgoing service times. It scales polynomially in the number of nodes n in the network, and exponentially in its treewidth, which quantifies how "tree-like" a network is, and can be much smaller than n. This contrasts with existing approaches, which scale exponentially in n. The proof of exactness of …

Expanding Links Between Work Values And Occupations: Development Of The Occupational Values Inventory (Ovi), Nicholas F. Heimpel, Kevin Hoff, Zihan Liu, Federick L. Oswald, James Rounds

Research Collection Lee Kong Chian School Of Business

This research developed the Occupational Values Inventory (OVI), a 30-item measure that expands the content coverage of work values by linking into a broad range of O*NET occupational descriptors, including Work Activities and Work Contexts, along with salary data from the Bureau of Labor Statistics. The OVI assesses 11 work values—Interpersonal, Outdoor, Physical, Leadership, Salary, Prestige, Variety, Interest, Work Hours, Knowledge Utilization, and Autonomy—providing an updated and refined coverage of work values relevant to people and occupations in the modern labor market. Study 1 (N = 768) developed and refined the OVI’s scales using conceptual and psychometric criteria, also reporting …

International Business And Sustainability: Towards An Interdisciplinary Research Agenda, Jonathan Doh, Ans Kolk, Heli Wang

Research Collection Lee Kong Chian School Of Business

The relationship between international business (IB) and sustainability is a complex and multifaceted one. Multinational enterprises (MNEs) both affect and are affected by the social, economic, and ecological (green environment) context in which they are embedded.1 As such, the study of how IB activity influences sustainability and the way that sustainability, in turn, impacts IB, involves incorporating a wide range of drivers, actors, processes, and outcomes. At the same time, sustainability challenges, such as climate change, biodiversity loss, pollution, resource scarcity, economic and social inequality and others, are increasingly systemic, multilevel, and intertwined with geo economic, biophysical and governance dynamics …

Research: What Message Are Your Headphones Sending Your Coworkers?, Oguz Gencay, Michael Schaerer, Trevor A. Foulk

Research Collection Lee Kong Chian School Of Business

Walk into almost any modern office, and you will see it: earbuds in, playlists on, and heads down. For many employees, music is an essential tool for focusing, mood regulation, and stamina. For most managers, it is a non-issue as long as performance stays strong. If it helps people concentrate, let them listen to music. At worst, it is a harmless preference, such as drinking coffee or using a standing desk.

Rationalizable Incentives: Interim Rationalizable Implementation Of Correspondences, Takashi Kunimoto, Rene Saran, Roberto Serrano

Research Collection School Of Economics

Are there ways to enforce incentives free of equilibrium considerations? When the normative goals for a set of agents can be summarized in a set-valued rule and agents take actions that are rationalizable, a new theory of incentives emerges in which standard Bayesian incentive compatibility (BIC) is relaxed significantly. The paper studies the interim rationalizable implementation of social choice sets with a Cartesian product structure, a leading example thereof being ex-post efficiency. Setwise incentive compatibility (setwise IC), much weaker than BIC, is shown to be necessary for implementation. Setwise IC enforces incentives flexibly within the entire correspondence, instead of the …

Using Satellite-Observed Geospatial Inundation Data To Identify The Impacts Of Floods On Firm-Level Performance: The Case Of China During 2000–2009, Pao-Li Chang, Fan Zheng

Research Collection School Of Economics

This paper compiles high-resolution geospatial inundation areas of China for the period 2000–2009 based on satellite imagery repositories filtered by the Global Flood Database (GFD). In parallel, we geocode a comprehensive firm-level dataset of China and combine these two sets of geospatial data to identify the set of inundated firms in each year of flood events, as well as the distances of all non-inundated firms from the inundated areas. Given the high-resolution inundation data, we adopt a generalized dynamic-panel specification to estimate dynamic and spatial spillover effects of floods on firm-level production activities (including outputs, capital and labor inputs, and …

Improving Estimation Efficiency Via Regression-Adjustment In Covariate-Adaptive Randomizations With Imperfect Compliance, Liang Jiang, Oliver B. Linton, Haihan Tang, Yichong Zhang

Research Collection School Of Economics

We study how to improve efficiency via regression adjustments with additional covariates under covariate-adaptive randomizations (CARs) when subject compliance is imperfect. We first establish the semiparametric efficiency bound for the local average treatment effect (LATE) under CARs. Second, we develop a general regression-adjusted LATE estimator which allows for parametric, nonparametric, and regularized adjustments. Even when the adjustments are misspecified, our proposed estimator is still consistent and asymptotically normal, and their inference method still achieves the exact asymptotic size under the null. When the adjustments are correctly specified, our estimator achieves the semiparametric efficiency bound. Third, we derive the optimal linear …

Leading Ai Adoption In Organizations: Introducing A Behavioral Human-Centered Approach, Shane Schweitzer, Devesh Narayan, Jack Mcguire, David De Cremer

Research Collection Lee Kong Chian School Of Business

Initiatives to implement AI technologies in organizations fail at an alarming rate. We argue that leading the adoption of AI is not a simple engineering exercise but rather represents a behavioral exercise where change management principles—the process by which organizations plan, implement, and embed changes in practices—are employed. However, many AI initiatives in business focus predominantly on the AI systems themselves, assuming humans will fall in line. To solve this, we integrate ideas from change management with scholarship on human-centered artificial intelligence to offer a behavioral approach that accounts for the impact of AI adoption on humans at all stages …

The Downside Of Generosity: How Rare Giving Fosters Stronger Social Connection, Minkwang Jang, Shereen J Chaudhry, Ayelet Fishbach

Research Collection Lee Kong Chian School Of Business

Giving serves not only to benefit others and society but also to foster social connections between givers and recipients. However, more giving is not necessarily merrier. This research finds that social connection depends not only on the act of giving but also on how many others receive the gesture from the same giver. Rare givers—those who give to fewer recipients—are perceived as more socially connected to each recipient than broad givers—those who give to many (the rare giving effect). This effect emerges across diverse contexts, including interpersonal gift exchanges in both new and existing relationships and corporate donations. As a …

Public Pool Usage As Adaptation Against Urban Heat, Stefan Borsky, Eric Fesselmeyer

Research Collection College of Integrative Studies

This paper examines the relationship between urban heat and outdoor public pool usage. Using attendance data from all 53 outdoor public pools in New York City, we analyze nonlinear effects of heat on pool usage across socioeconomic contexts. Pool attendance rises sharply with heat, especially in low-income neighborhoods where alternative coping options are likely limited. We also find that public pools reduce heat-related emergency medical service calls. Our findings highlight the need for equitable investment in blue infrastructure to enhance urban climate resilience and demonstrate how this type of adaptive infrastructure can play a critical role in managing urban heat.

Selective Concolic Testing, Guofeng Zhang, Zhenbang Chen, Ziqi Shuai, Jun Sun, Weijiang Hong, Yufeng Zhang, Ji Wang, Yang Liu

Research Collection School Of Computing and Information Systems

The principled combination of symbolic execution and random testing lacks a formal foundation, especially in deciding which inputs to symbolize. We propose selective concolic testing, a cost-aware framework that formulates this choice as an optimized policy problem of a MDP (Markov Decision Process). We model program exploration over a finite control-flow graph, where MDP states represent covered statements, actions partition path constraints into symbolic and random fragments, rewards reflect coverage gain, and costs account for SMT solving effort and sampling inefficiency. Our framework yields the first formal characterization of selective symbolization as policy synthesis in a probabilistic system. We prove …

Detecting Doubt In Reflective Learning: A Learning Analytics Study With Large And Small Language Models, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Reflective learning enhances understanding, especially when instructors promptly address difficulties raised in student reflections. Automated doubt detection can reduce time for instructors, yet existing classification approaches take substantial time for manual annotation and model training. This paper investigates whether large and small language models (LLMs, SLMs) can automate doubt detection without time-consuming training. Using a dataset of anonymized student reflections, we evaluate zeroshot, few-shot prompting, and multi-step reasoning against prior supervised classification baselines. We show that LLMs (GPT-4o, Claude-4, Gemini-2.5) surpass earlier F1 scores without prompting, while prompting further improves their performance. However, using proprietary LLMs can raise cost and …

Gencode: A Generic Data Augmentation Framework For Boosting Deep Learning-Based Code Understanding, Zeming Dong, Qiang Hu, Xiaofei Xie, Maxime Cordy, Mike Papadakis, Yves Le Traon, Jianjun Zhao

Research Collection School Of Computing and Information Systems

Pre-trained code models lead the era of code intelligence, with multiple models designed with impressive performance. However, one important problem, data augmentation for code data that automatically helps developers prepare training data lacks study in this field. In this paper, we introduce a generic data augmentation framework, GenCode, to enhance the training of code understanding models. Simply speaking, GenCode follows a generation-and-selection paradigm to prepare useful training code data. Specifically, it employs code augmentation techniques to generate new code candidates first and then identifies important ones as the training data by influence scores. To evaluate the effectiveness of GenCode, we …