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The Promises And Perils Of Insurtech, Lin Lin, Christopher C. H. Chen Jul 2020

The Promises And Perils Of Insurtech, Lin Lin, Christopher C. H. Chen

Research Collection Yong Pung How School Of Law

The insurance sector, in riding the wave of the FinTech phenomenon, has been rapidly expanding, with a slew of firms having emerged to provide so-called “InsurTech” services. These services incorporate concepts such as blockchain, artificial intelligence, digitalisation and the sharing economy to various aspects of the insurance industry. This profusion of technology brings with it the promise of various benefits including increasing efficiency and lowering costs for not only insurers and intermediaries, but also businesses or consumers as end-users of insurance. However, the development of InsurTech comes with corresponding risks and regulatory concerns not currently accounted for by the traditional …

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Revisiting The Automation Tax Debate In Light Of Covid-19 And Resulting Structural Unemployment, Vincent Ooi Jul 2020

Revisiting The Automation Tax Debate In Light Of Covid-19 And Resulting Structural Unemployment, Vincent Ooi

Research Collection Yong Pung How School Of Law

As lockdowns ease around the globe and businesses reopen, the threat of jobs being automated by machines and workers being displaced as a result has significantly increased. Businesses must keep the number of workers on site to a minimum to comply with safe distancing measures. Under these constraints while social distancing remains the norm, automation might be the way forward for companies that still want to continue production while minimising human contact. The threat of a workforce being replaced by robots and automation, a threat that has already alarmed the labour movement, is heightened with Covid-19. There will be considerable …

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Tort Law, Amirthalingam Kumaralingam, Gary Kok Yew Chan Jul 2020

Tort Law, Amirthalingam Kumaralingam, Gary Kok Yew Chan

Research Collection Yong Pung How School Of Law

This review examines the ten most significant decisions in tort law for 2020. It was an interesting year for the range of significant decisions in tort law handed down by the courts on matters including limitation period, medical negligence, the scope of duty in negligence, breach of confidence, conspiracy, and defamation.

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Quantile Treatment Effects And Bootstrap Inference Under Covariate-Adaptive Randomization, Yichong Zhang, Xin Zheng Jul 2020

Quantile Treatment Effects And Bootstrap Inference Under Covariate-Adaptive Randomization, Yichong Zhang, Xin Zheng

Research Collection School Of Economics

In this paper, we study the estimation and inference of the quantile treatment effect under covariate‐adaptive randomization. We propose two estimation methods: (1) the simple quantile regression and (2) the inverse propensity score weighted quantile regression. For the two estimators, we derive their asymptotic distributions uniformly over a compact set of quantile indexes, and show that, when the treatment assignment rule does not achieve strong balance, the inverse propensity score weighted estimator has a smaller asymptotic variance than the simple quantile regression estimator. For the inference of method (1), we show that the Wald test using a weighted bootstrap standard …

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Security Analysts And Capital Market Anomalies, Li Guo, Frank Weikai Li, K.C. John Wei Jul 2020

Security Analysts And Capital Market Anomalies, Li Guo, Frank Weikai Li, K.C. John Wei

Research Collection Lee Kong Chian School Of Business

We examine whether analysts use information in well-known stock return anomalies when making recommendations. We find results contrary to the common view that analysts are sophisticated information intermediaries who help improve market efficiency. Specifically, when analysts make more favorable recommendations to stocks classified as overvalued, these stocks tend to have particularly large negative abnormal returns ex post. Moreover, analysts whose recommendations are more aligned with anomaly signals are more skilled and elicit greater recommendation announcement returns. Our results suggest that analysts' biased recommendations could be a source of market frictions that impede the efficient correction of mispricing.

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Individuals Responses To Economic Cycles: Organizational Relevance And A Multilevel Theoretical Integration, Nina Sirola Jul 2020

Individuals Responses To Economic Cycles: Organizational Relevance And A Multilevel Theoretical Integration, Nina Sirola

Research Collection Lee Kong Chian School Of Business

The state of the economy represents a concern for individuals and shapes their behavior in profound ways. The current review of studies on how individuals respond to economic cycles reveals that organizational relevance of such responses has often not been considered, and the literature is characterized by a variety of seemingly disconnected explanations for how and why individuals respond to the perceived state of the economy. I develop a theoretical framework that systematizes the literature and accounts for the seemingly disparate findings, highlighting the underlying functionality of such responses for individuals. I then integrate the literature on individual responses to …

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Negative Reviews, Positive Impact: Consumer Empathetic Responding To Unfair Word Of Mouth, Thomas Allard, Lea H. Dunn, Katherine White Jul 2020

Negative Reviews, Positive Impact: Consumer Empathetic Responding To Unfair Word Of Mouth, Thomas Allard, Lea H. Dunn, Katherine White

Research Collection Lee Kong Chian School Of Business

This research documents how negative reviews, when perceived as unfair, can activate feelings of empathy toward firms that have been wronged. Six studies and four supplemental experiments provide converging evidence that this experienced empathy for the firm motivates supportive consumer responses such as paying higher purchase prices and reporting increased patronage intentions. Importantly, this research highlights factors that can increase or decrease empathy toward a firm. For instance, adopting the reviewer's perspective when evaluating an unfair negative review can reduce positive consumer responses to a firm, whereas conditions that enhance the ability to experience empathy-such as when reviews are highly …

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Stock Market Information And Security Prices, Haoyuan Li Jun 2020

Stock Market Information And Security Prices, Haoyuan Li

Dissertations and Theses Collection (Open Access)

Chapter 1: Analyst report content and stock market anomalies A series of recent papers document that security analyst recommendations tend to contradict stock-mispricing signals. This seems at odds with the large prior literature on the investment value of analyst recommendations. What justifications do analysts make when they write reports on mispriced stocks? I use the latest techniques in machine learning and textual analysis to categorize the qualitative information in a large sample of analyst reports. I find that report content can be intuitively classified into five categories or topics: 1) Growth, 2) Earnings, 3) New developments, 4) Management transactions, and …

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Essays On Time Series And Financial Econometrics, Yijie Fei Jun 2020

Essays On Time Series And Financial Econometrics, Yijie Fei

Dissertations and Theses Collection (Open Access)

This dissertation contains four essays in financial econometrics. In the first essay, some asymptotic results are derived for first-order autoregression with a root moderately deviating from unity and a nonzero drift. It is shown that the drift changes drastically the large sample properties of the least-squares (LS) estimator. The second essay is concerned with the joint test of predictability and stability in the context of predictive regression. The null hypothesis under investigation is that the potential predictors exhibit no predictability and incur no structural break during the sample period. We first show that the IVX estimator provides better finite sample …

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Transparency And Fairness In Organizational Decisions: An Experimental Investigation Using The Paired Ultimatum Game, Jared Nai, Reddi Kotha, Phanish Puranam Jun 2020

Transparency And Fairness In Organizational Decisions: An Experimental Investigation Using The Paired Ultimatum Game, Jared Nai, Reddi Kotha, Phanish Puranam

Research Collection Lee Kong Chian School Of Business

Organizations often keep secret their decisions about what employees receive (e.g., salary, budgets, benefits) to manage fairness concerns. We propose that this can be counterproductive because of a mechanism we call the “escalation of deservingness under secrecy”, where the existence of peers can inflate one’s own sense of deservingness, even when the actual allocations to peers are unknown. Building on the ultimatum game, we developed a Paired Ultimatum Game (PUG) in which a player and a peer respondent engage with the same offeror simultaneously but with no direct competition between respondents. Across three experiments- a live interaction study as well …

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Removing Situation Descriptions From Situational Judgment Test Items: Does The Impact Differ For Video-Based Versus Text-Based Formats?, Philipp Schäpers, Filip Lievens, Jan-Philipp Freudenstein, Joachim Hüffmeier, Cornelius J. König, Stefan Krumm Jun 2020

Removing Situation Descriptions From Situational Judgment Test Items: Does The Impact Differ For Video-Based Versus Text-Based Formats?, Philipp Schäpers, Filip Lievens, Jan-Philipp Freudenstein, Joachim Hüffmeier, Cornelius J. König, Stefan Krumm

Research Collection Lee Kong Chian School Of Business

Recent research has shown that many text-based situational judgment test (SJT) items can be solved even when the situational descriptions in the item stems are not presented to test takers. This finding challenges the traditional view of SJTs as low-fidelity simulations that rely on ‘situational’ (context-dependent) judgment. However, media richness theory and construal level theory suggest that situation descriptions presented in a richer and more concrete format (video format) will reduce uncertainty about inherent requirements and facilitate the perception that the situation is taking place in the here and now. Therefore, we hypothesized that situational judgment would be more important …

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Learning From Digital Failures? The Effectiveness Of Firms’ Divestiture And Management Turnover Responses To Data Breaches, Gui-Deng Say, Gurneeta Vasudeva Jun 2020

Learning From Digital Failures? The Effectiveness Of Firms’ Divestiture And Management Turnover Responses To Data Breaches, Gui-Deng Say, Gurneeta Vasudeva

Research Collection Lee Kong Chian School Of Business

We examine whether firms learn from digital technology failures in the form of data breach events, based on the effectiveness of their failure responses. We argue that firms experiencing such technological failures interpret them broadly as organizational problems, and undertake unrelated divestitures and top management turnover to achieve better standardization and to remove dysfunctional routines. We test our hypotheses on unrelated subsidiary divestitures and chief technology officer (CTO) turnovers undertaken by 8,760 publicly traded U.S. firms that were at risk of experiencing data breaches in- volving the loss of personally identifiable information during the period 2005–2016. We find that data …

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A Simple New Scoring System For Predicting The Mortality Of Severe Acute Pancreatitis: A Retrospective Clinical Study, Lei Wang, Yan-Bo Zeng, Jia-Yun Chen, Qian Luo, Rowan Wang, Ruijie Zhang, Zhichao Zheng, Yuan-Hang Dong, Wen-Bin Zou, Xiaoqing Xie, Yi-Qi Du, Zhao-Shen Li Jun 2020

A Simple New Scoring System For Predicting The Mortality Of Severe Acute Pancreatitis: A Retrospective Clinical Study, Lei Wang, Yan-Bo Zeng, Jia-Yun Chen, Qian Luo, Rowan Wang, Ruijie Zhang, Zhichao Zheng, Yuan-Hang Dong, Wen-Bin Zou, Xiaoqing Xie, Yi-Qi Du, Zhao-Shen Li

Research Collection Lee Kong Chian School Of Business

It is critical to accurately identify patients with severe acute pancreatitis (SAP) in a timely manner. This study aimed to develop a new simplified AP scoring system based on data from Chinese population.We retrospectively analyzed a consecutive series of 585 patients diagnosed with SAP at the Changhai hospital between 2009 and 2017. The new Chinese simple scoring system (CSSS) was derived using logistic regression analysis and was validated in comparison to 4 existing systems using receiver operating characteristic curves.Six variables were selected for incorporation into CSSS, including serum creatinine, blood glucose, lactate dehydrogenase, heart rate, C-reactive protein, and extent of …

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Hyperbolic Visual Embedding Learning For Zero-Shot Recognition, Shaoteng Liu, Jingjing Chen, Liangming Pan, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang Jun 2020

Hyperbolic Visual Embedding Learning For Zero-Shot Recognition, Shaoteng Liu, Jingjing Chen, Liangming Pan, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

This paper proposes a Hyperbolic Visual Embedding Learning Network for zero-shot recognition. The network learns image embeddings in hyperbolic space, which is capable of preserving the hierarchical structure of semantic classes in low dimensions. Comparing with existing zeroshot learning approaches, the network is more robust because the embedding feature in hyperbolic space better represents class hierarchy and thereby avoid misleading resulted from unrelated siblings. Our network outperforms exiting baselines under hierarchical evaluation with an extremely challenging setting, i.e., learning only from 1,000 categories to recognize 20,841 unseen categories. While under flat evaluation, it has competitive performance as state-of-the-art methods but …

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Leveraging Digital Technology To Transform Accounting Function: Case Study Of A Sme, Gary Pan, Benjamin Lee Jun 2020

Leveraging Digital Technology To Transform Accounting Function: Case Study Of A Sme, Gary Pan, Benjamin Lee

Research Collection School Of Accountancy

Digital transformation is taking hold of the processes and systems in accounting at a rapid pace and in a drastic way. With its emphasis on data and analysis, accounting entity is well suited to reap the benefits digital technologies have to offer. With the rapid infusion of digital technologies in accounting entity, the accounting literature has been calling for more empirical studies to examine the way accounting function leverages digital technology to enhance its analytical capabilities so as to obtain deeper business insights. This paper conducts an empirical study to examine the process of a SME's accounting function leveraging data …

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Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun Jun 2020

Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun

Research Collection School Of Computing and Information Systems

We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA. Given a set of detected object regions in an image (e.g., using Faster R-CNN), like any other unsupervised feature learning methods (e.g., word2vec), the proxy training objective of VC R-CNN is to predict the contextual objects of a region. However, they are fundamentally different: the prediction of VC R-CNN is by using causal intervention: P(Y|do(X)), while others are by using the conventional likelihood: P(Y|X). This is also …

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Maximum A Posteriori Estimation For Information Source Detection, Biao Chang, Enhong Chen, Feida Zhu, Qi Liu, Tong Xu Jun 2020

Maximum A Posteriori Estimation For Information Source Detection, Biao Chang, Enhong Chen, Feida Zhu, Qi Liu, Tong Xu

Research Collection School Of Computing and Information Systems

Information source detection is to identify nodes initiating the diffusion process in a network, which has a wide range of applications including epidemic outbreak prevention, Internet virus source identification, and rumor source tracing in social networks. Although it has attracted ever-increasing attention from research community in recent years, existing solutions still suffer from high time complexity and inadequate effectiveness, due to high dynamics of information diffusion and observing just a snapshot of the whole process. To this end, we present a comprehensive study for single information source detection in weighted graphs. Specifically, we first propose a maximum a posteriori (MAP) …

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Revisiting Supervised And Unsupervised Methods For Effort-Aware Cross-Project Defect Prediction, Chao Ni, Xin Xia, David Lo, Xiang Chen, Qing Gu Jun 2020

Revisiting Supervised And Unsupervised Methods For Effort-Aware Cross-Project Defect Prediction, Chao Ni, Xin Xia, David Lo, Xiang Chen, Qing Gu

Research Collection School Of Computing and Information Systems

Cross-project defect prediction (CPDP), aiming to apply defect prediction models built on source projects to a target project, has been an active research topic. A variety of supervised CPDP methods and some simple unsupervised CPDP methods have been proposed. In a recent study, Zhou et al. found that simple unsupervised CPDP methods (i.e., ManualDown and ManualUp) have a prediction performance comparable or even superior to complex supervised CPDP methods. Therefore, they suggested that the ManualDown should be treated as the baseline when considering non-effort-aware performance measures (NPMs) and the ManualUp should be treated as the baseline when considering effort-aware performance …

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Provably Robust Decisions Based On Potentially Malicious Sources Of Information, Tim Muller, Dongxia Wang, Jun Sun Jun 2020

Provably Robust Decisions Based On Potentially Malicious Sources Of Information, Tim Muller, Dongxia Wang, Jun Sun

Research Collection School Of Computing and Information Systems

Sometimes a security-critical decision must be made using information provided by peers. Think of routing messages, user reports, sensor data, navigational information, blockchain updates. Attackers manifest as peers that strategically report fake information. Trust models use the provided information, and attempt to suggest the correct decision. A model that appears accurate by empirical evaluation of attacks may still be susceptible to manipulation. For a security-critical decision, it is important to take the entire attack space into account. Therefore, we define the property of robustness: the probability of deciding correctly, regardless of what information attackers provide. We introduce the notion of …

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Empirical Evaluation Of Three Common Assumptions In Building Political Media Bias Datasets, Soumen Ganguly, Juhi Kulshrestha, Jisun An, Haewoon Kwak Jun 2020

Empirical Evaluation Of Three Common Assumptions In Building Political Media Bias Datasets, Soumen Ganguly, Juhi Kulshrestha, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

In this work, we empirically validate three common assumptions in building political media bias datasets, which are (i) labelers' political leanings do not affect labeling tasks, (ii) news articles follow their source outlet's political leaning, and (iii) political leaning of a news outlet is stable across different topics. We build a ground-truth dataset of manually annotated article-level political leaning and validate the three assumptions. Our findings warn that the three assumptions could be invalid even for a small dataset. We hope that our work calls attention to the (in)validity of common assumptions in building political media bias datasets.

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Editing-Enabled Signatures: A New Tool For Editing Authenticated Data, Binanda Sengupta, Yingjiu Li, Yangguang Tian, Robert H. Deng Jun 2020

Editing-Enabled Signatures: A New Tool For Editing Authenticated Data, Binanda Sengupta, Yingjiu Li, Yangguang Tian, Robert H. Deng

Research Collection School Of Computing and Information Systems

Data authentication primarily serves as a tool to achieve data integrity and source authentication. However, traditional data authentication does not fit well where an intermediate entity (editor) is required to modify the authenticated data provided by the source/data owner before sending the data to other recipients. To ask the data owner for authenticating each modified data can lead to higher communication overhead. In this article, we introduce the notion of editing-enabled signatures where the data owner can choose any set of modification operations applicable on the data and still can restrict any possibly untrusted editor to authenticate the data modified …

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A New Framework For Privacy-Preserving Biometric-Based Remote User Authentication, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Pengfei Wu, Anyi Liu Jun 2020

A New Framework For Privacy-Preserving Biometric-Based Remote User Authentication, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Pengfei Wu, Anyi Liu

Research Collection School Of Computing and Information Systems

In this paper, we introduce the first general framework for strong privacy-preserving biometric-based remote user authentication based on oblivious RAM (ORAM) protocol and computational fuzzy extractors. We define formal security models for the general framework, and we prove that it can achieve user authenticity and strong privacy. In particular, the general framework ensures that: (1) a strong privacy and a log-linear time-complexity are achieved by using a new tree-based ORAM protocol; (2) a constant bandwidth cost is achieved by exploiting computational fuzzy extractors in the challenge-response phase of remote user authentications.

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Visual Commonsense Representation Learning Via Causal Inference, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun Jun 2020

Visual Commonsense Representation Learning Via Causal Inference, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun

Research Collection School Of Computing and Information Systems

We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA. Given a set of detected object regions in an image (e.g., using Faster R-CNN), like any other unsupervised feature learning methods (e.g., word2vec), the proxy training objective of VC R-CNN is to predict the con-textual objects of a region. However, they are fundamentally different: the prediction of VC R-CNN is by using causal intervention: P(Y|do(X)), while others are by using the conventional likelihood: P(Y|X). We extensively apply …

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A Machine Learning Approach For Vulnerability Curation, Yang Chen, Andrew E. Santosa, Ming Yi Ang, Abhishek Sharma, Asankhaya Sharma, David Lo Jun 2020

A Machine Learning Approach For Vulnerability Curation, Yang Chen, Andrew E. Santosa, Ming Yi Ang, Abhishek Sharma, Asankhaya Sharma, David Lo

Research Collection School Of Computing and Information Systems

Software composition analysis depends on database of open-source library vulerabilities, curated by security researchers using various sources, such as bug tracking systems, commits, and mailing lists. We report the design and implementation of a machine learning system to help the curation by by automatically predicting the vulnerability-relatedness of each data item. It supports a complete pipeline from data collection, model training and prediction, to the validation of new models before deployment. It is executed iteratively to generate better models as new input data become available. We use self-training to significantly and automatically increase the size of the training dataset, opportunistically …

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Online Spatio - Temporal Demand Supply Matching, Meghna Lowalekar Jun 2020

Online Spatio - Temporal Demand Supply Matching, Meghna Lowalekar

Dissertations and Theses Collection (Open Access)

The rapid growth of cities in developing world coupled with the increase in rural to urban migration have led to cities being identified as the key actor for any nation's economy. Shared mobility has become an integral part of life of people in cities as it improves efficiency and enhances transportation accessibility. As a result, the mismatch between the demand and supply of shared mobility resources has a direct impact on people's life. Thus, the goal of my dissertation is to develop solution strategies for these real-time (online) spatio-temporal demand supply matching problems for shared mobility resources which can enhance …

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A Virtualization Based System Infrastructure For Dynamic Program Analysis, Jiaqi Hong Jun 2020

A Virtualization Based System Infrastructure For Dynamic Program Analysis, Jiaqi Hong

Dissertations and Theses Collection (Open Access)

Dynamic malware analysis schemes either run the target program as is in an isolated environment assisted by additional hardware facilities or modify it with instrumentation code statically or dynamically. The hardware-assisted schemes usually trap the target during its execution to a more privileged environment based on the available hardware events. The more privileged environment is not accessible by the untrusted kernel, thus this approach is often applied for transparent and secure kernel analysis. Nevertheless, the isolated environment induces a virtual address gap between the analyzer and the target, which hinders effective and efficient memory introspection and undermines the correctness of …

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Skilful Reflection As A Master Virtue, Chienkuo Mi, Shane Ryan Jun 2020

Skilful Reflection As A Master Virtue, Chienkuo Mi, Shane Ryan

Research Collection School of Social Sciences

This paper advances the claim that skilful reflection is a master virtue in that skilful reflection shapes and corrects the other epistemic and intellectual virtues. We make the case that skilful reflection does this with both competence-based epistemic virtues and character-based intellectual virtues. In making the case that skilful reflection is a master virtue, we identify the roots of ideas central to our thesis in Confucian philosophy. In particular, we discuss the Confucian conception of reflection, as well as different levels of epistemic virtue. Next we set out the Dual Process Hypothesis of Reflection, which provides an explanation of the …

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Cfos Play Crucial Role In Surviving Covid-19 Crisis, Themin Suwardy Jun 2020

Cfos Play Crucial Role In Surviving Covid-19 Crisis, Themin Suwardy

Research Collection School Of Accountancy

In recent years, chief financial officers (CFOs) have been called upon to do many things. They have stepped beyond their traditional technical finance functions, embracing technology and innovations to partner chief executive officers (CEOs) and boards on strategic issues. But if asked at the end of 2019, probably no CFO would place "managing through a global pandemic and economic crisis at the same time" among their top five things to do in 2020. Like many others, CFOs are being asked to do even more in a very short timeframe.

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The Effect Of Endogenously-Determined Bullying On Test Scores, Hisham Bin Yacob Patel Jun 2020

The Effect Of Endogenously-Determined Bullying On Test Scores, Hisham Bin Yacob Patel

Dissertations and Theses Collection (Open Access)

The problem of bullying is one of the main sources of adverse school environment. In this dissertation, I explore the effect of bullying on test scores, under the assumption that bullying is endogenously determined. Comparing my estimates with that from traditional OLS, I find that estimates from OLS grossly underestimates the effect of bullying on short-term student outcomes. I also find significant evidence of heterogeneity across various sub-groups; for example, male students are found to be less affected by bullying as compared to their female peers. Furthermore, male students are also found to be less affected by physical bullying while …

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Attention, Entrainment, And Rules In High Reliability Organizations, Tingting Lang Jun 2020

Attention, Entrainment, And Rules In High Reliability Organizations, Tingting Lang

Dissertations and Theses Collection (Open Access)

Chapter 1: How institutions enhance mindfulness: interactions between external regulators and front-line operators around safety rules (with Ravi S. Kudesia and Jochen Reb) How is it that some organizations can maintain nearly error-free performance, despite trying conditions? Within research on such high-reliability organizations, mindful organizing has been offered as a key explanation. It entails interaction patterns among front-line operators that keep them attentive to potential failures—and relies on them having the expertise and autonomy to address any such failures. In this study, we extend the mindful organizing literature, which emphasizes local interactions among operators, by considering the broader institutional context …

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