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Regulating Personal Data Usage In Covid-19 Control Conditions, Mark Findlay, Nydia Remolina May 2020

Regulating Personal Data Usage In Covid-19 Control Conditions, Mark Findlay, Nydia Remolina

Centre for AI & Data Governance (2019-2025)

As the COVID-19 health pandemic ebbs and flows world-wide, governments and private companies across the globe are utilising AI-assisted surveillance, reporting, mapping and tracing technologies with the intention of slowing the spread of the virus. These technologies have capacity to amass and share personal data for community control and citizen safety motivations that empower state agencies and inveigle citizen co-operation which could only be imagined outside times of real and present personal danger. While not cavilling with the short-term necessity for these technologies and the data they control, process and share in the health regulation mission (provided that the technology …

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Spillover Effects From Unintended Trials On Attitude And Behavior: Promoting New Products Through Access-Based Services, Adrian Lehr, Marion Buettgen, Sabine Benoit, Katrin Merfeld May 2020

Spillover Effects From Unintended Trials On Attitude And Behavior: Promoting New Products Through Access-Based Services, Adrian Lehr, Marion Buettgen, Sabine Benoit, Katrin Merfeld

Research Collection Lee Kong Chian School Of Business

Access-based services (ABS) provide an opportunity for brands to promote their new products by enabling (unintended) trials. However, the mechanisms and impact of consumer exposure to products in ABS and the subsequent potential spillover effects on both the brand and the product perception are largely unknown. Our hypotheses are derived from the information integration theory (IIT) and subsequently tested. Study 1 is a field study investigating an unintended trial moderated by involvement and positive experience. The results indicate the positive effects of the unintended trial on product and brand attitudes, brand purchase intention, and word of mouth. In line with …

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Customer Satisfaction And Its Impact On The Future Costs Of Selling, Leon Gim Lim, Kapil R. Tuli, Rajdeep Grewal May 2020

Customer Satisfaction And Its Impact On The Future Costs Of Selling, Leon Gim Lim, Kapil R. Tuli, Rajdeep Grewal

Research Collection Lee Kong Chian School Of Business

Although scholars have established that customer satisfaction affects different dimensions of firm financial performance, a managerially important but overlooked aspect is its effect on a firm’s future cost of selling (COS), that is, expenditures associated with persuading customers and providing convenience to them. Accordingly, this study presents the first empirical and theoretical examination of the impact of customer satisfaction on future COS. The authors propose that while higher customer satisfaction can lower future COS, the degree to which a firm realizes this benefit depends on its strategy and operating environment. Analyzing almost two decades of data from 128 firms, the …

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Assistance For Target Selection In Mobile Augmented Reality, Vinod Asokan, Scott Bateman, Anthony Tang May 2020

Assistance For Target Selection In Mobile Augmented Reality, Vinod Asokan, Scott Bateman, Anthony Tang

Research Collection School Of Computing and Information Systems

Mobile augmented reality - where a mobile device is used to view and interact with virtual objects displayed in the real world - is becoming more common. Target selection is the main method of interaction in mobile AR, but is particularly difficult because targets in AR can have challenging characteristics such as being moving or occluded (by digital or real world objects). Because target selection is particularly difficult and error prone in mobile AR, we conduct a comparative study of target assistance techniques. We compared four different cursor-based selection techniques against the standard touch-to-select interaction, finding that a newly adapted …

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Learning Discriminative Neural Sentiment Units For Semi-Supervised Target-Level Sentiment Classification, Jingjing Zhao, Yao Yang, Guansong Pang, Lei Lv, Hong Shang, Zhongqian Sun, Wei Yang May 2020

Learning Discriminative Neural Sentiment Units For Semi-Supervised Target-Level Sentiment Classification, Jingjing Zhao, Yao Yang, Guansong Pang, Lei Lv, Hong Shang, Zhongqian Sun, Wei Yang

Research Collection School Of Computing and Information Systems

Target-level sentiment classification aims at assigning sentiment polarities to opinion targets in a sentence, for which it is significantly more challenging to obtain large-scale labeled data than sentence/document-level sentiment classification due to the intricate contexts and relations of the target words. To address this challenge, we propose a novel semi-supervised approach to learn sentiment-aware representations from easily accessible unlabeled data specifically for the finegrained sentiment learning. This is very different from current popular semi-supervised solutions that use the unlabeled data via pretraining to generate generic representations for various types of downstream tasks. Particularly, we show for the first time that …

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Semantic Understanding Of Smart Contracts: Executable Operational Semantics Of Solidity, Jiao Jiao, Shuanglong Kan, Shang Wei Lin, David Sanan, Yang Liu, Jun Sun May 2020

Semantic Understanding Of Smart Contracts: Executable Operational Semantics Of Solidity, Jiao Jiao, Shuanglong Kan, Shang Wei Lin, David Sanan, Yang Liu, Jun Sun

Research Collection School Of Computing and Information Systems

Bitcoin has been a popular research topic recently. Ethereum (ETH), a second generation of cryptocurrency, extends Bitcoin's design by offering a Turing-complete programming language called Solidity to develop smart contracts. Smart contracts allow creditable execution of contracts on EVM (Ethereum Virtual Machine) without third parties. Developing correct and secure smart contracts is challenging due to the decentralized computation nature of the blockchain. Buggy smart contracts may lead to huge financial loss. Furthermore, smart contracts are very hard, if not impossible, to patch once they are deployed. Thus, there is a recent surge of interest in analyzing and verifying smart contracts. …

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Symbolic Verification Of Message Passing Interface Programs, Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun, Chun Huang, Wei Dong May 2020

Symbolic Verification Of Message Passing Interface Programs, Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun, Chun Huang, Wei Dong

Research Collection School Of Computing and Information Systems

Message passing is the standard paradigm of programming in high-performance computing. However, verifying Message Passing Interface (MPI) programs is challenging, due to the complex program features (such as non-determinism and non-blocking operations). In this work, we present MPI symbolic verifier (MPI-SV), the first symbolic execution based tool for automatically verifying MPI programs with non-blocking operations. MPI-SV combines symbolic execution and model checking in a synergistic way to tackle the challenges in MPI program verification. The synergy improves the scalability and enlarges the scope of verifiable properties. We have implemented MPI-SV and evaluated it with 111 real-world MPI verification tasks. The …

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Beyond Physical Entrainment: Competitive And Cooperative Mental Stances During Identical Joint-Action Tasks Differently Affect Inter-Subjective Neural Synchrony And Judgments Of Agency, Philip S. Cho, Nicolas Escoffier, Yinan Mao, Christopher Green, Richard C. Davis May 2020

Beyond Physical Entrainment: Competitive And Cooperative Mental Stances During Identical Joint-Action Tasks Differently Affect Inter-Subjective Neural Synchrony And Judgments Of Agency, Philip S. Cho, Nicolas Escoffier, Yinan Mao, Christopher Green, Richard C. Davis

Research Collection School Of Computing and Information Systems

Little work has examined how mental stance alone, apart from physical entrainment, affects between-participant neural synchrony during joint social interaction. We report the first findings on how cooperative and competitive mental stances, even during identical visuomotor joint-action tasks, result in distinct neural oscillatory signatures in low beta and theta band between-participant phase synchrony. Two participants jointly controlled a cursor and were instructed to either compete or cooperate to move it to one of three targets. The visuomotor output was identical for both the compete and cooperate conditions because participants were privately given the same target for experimental trials. Cooperation enhanced …

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A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu May 2020

A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu

Research Collection School Of Computing and Information Systems

The proliferation of various mobile devices equipped with cameras results in an exponential growth of the amount of images. Recent advances in the deep learning with convolutional neural networks (CNN) have made CNN feature extraction become an effective way to process these images. However, it is still a challenging task to deploy the CNN model on the mobile sensors, which are typically resource-constrained in terms of the storage space, the computing capacity, and the battery life. Although cloud computing has become a popular solution, data security and response latency are always the key issues. Therefore, in this paper, we propose …

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“Trust Me, I Have A Ph.D.”: A Propensity Score Analysis On The Halo Effect Of Disclosing One's Offline Social Status In Online Communities, Kunwoo Park, Haewoon Kwak, Hyunho Song, Meeyoung. Cha May 2020

“Trust Me, I Have A Ph.D.”: A Propensity Score Analysis On The Halo Effect Of Disclosing One's Offline Social Status In Online Communities, Kunwoo Park, Haewoon Kwak, Hyunho Song, Meeyoung. Cha

Research Collection School Of Computing and Information Systems

Online communities adopt various reputation schemes to measure content quality. This study analyzes the effect of a new reputation scheme that exposes one's offline social status, such as an education degree, within an online community. We study two Reddit communities that adopted this scheme, whereby posts include tags identifying education status referred to as flairs, and we examine how the “transferred” social status affects the interactions among the users. We computed propensity scores to test whether flairs give ad-hoc authority to the adopters while minimizing the effects of confounding variables such as topics of content. The results show that exposing …

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Jplink: On Linking Jobs To Vocational Interest Types, Amila Silva, Pei Chi Lo, Ee-Peng Lim May 2020

Jplink: On Linking Jobs To Vocational Interest Types, Amila Silva, Pei Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Linking job seekers with relevant jobs requires matching based on not only skills, but also personality types. Although the Holland Code also known as RIASEC has frequently been used to group people by their suitability for six different categories of occupations, the RIASEC category labels of individual jobs are often not found in job posts. This is attributed to significant manual efforts required for assigning job posts with RIASEC labels. To cope with assigning massive number of jobs with RIASEC labels, we propose JPLink, a machine learning approach using the text content in job titles and job descriptions. JPLink exploits …

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Posit: Simultaneously Tagging Natural And Programming Languages, Profir-Petru Pârțachi, Santanu Dash, Christoph Treude, Earl T. Barr May 2020

Posit: Simultaneously Tagging Natural And Programming Languages, Profir-Petru Pârțachi, Santanu Dash, Christoph Treude, Earl T. Barr

Research Collection School Of Computing and Information Systems

Software developers use a mix of source code and natural language text to communicate with each other: Stack Overflow and Developer mailing lists abound with this mixed text. Tagging this mixed text is essential for making progress on two seminal software engineering problems — traceability, and reuse via precise extraction of code snippets from mixed text. In this paper, we borrow code-switching techniques from Natural Language Processing and adapt them to apply to mixed text to solve two problems: language identification and token tagging. Our technique, POSIT, simultaneously provides abstract syntax tree tags for source code tokens, part-of-speech tags for …

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Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan May 2020

Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan

Research Collection School Of Computing and Information Systems

Sleepiness or sleep deprivation creates a serious hazard or obstacle to task execution and performance. Sleep deprivation can be life-threating (e.g., when driving or executing attention-critical tasks). We are interested to examine if eye-tracking technology can be used to assess and detect sleepiness in an online environment. In this research proposal, we will focus on examining the relationships between sleepiness and parameters involving pupil size, blinks, and saccades.

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Non-Autoregressive Dialog State Tracking, Hung Le, Richard Socher, Steven C. H. Hoi May 2020

Non-Autoregressive Dialog State Tracking, Hung Le, Richard Socher, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Recent efforts in Dialogue State Tracking (DST) for task-oriented dialogues have progressed toward open-vocabulary or generation-based approaches where the models can generate slot value candidates from the dialogue history itself. These approaches have shown good performance gain, especially in complicated dialogue domains with dynamic slot values. However, they fall short in two aspects: (1) they do not allow models to explicitly learn signals across domains and slots to detect potential dependencies among (domain, slot) pairs; and (2) existing models follow auto-regressive approaches which incur high time cost when the dialogue evolves over multiple domains and multiple turns. In this paper, …

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Automated Identification Of Libraries From Vulnerability Data, Chen Yang, Andrew Santosa, Asankhaya Sharma, David Lo May 2020

Automated Identification Of Libraries From Vulnerability Data, Chen Yang, Andrew Santosa, Asankhaya Sharma, David Lo

Research Collection School Of Computing and Information Systems

Software Composition Analysis (SCA) has gained traction in recent years with a number of commercial offerings from various companies. SCA involves vulnerability curation process where a group of security researchers, using various data sources, populate a database of open-source library vulnerabilities, which is used by a scanner to inform the end users of vulnerable libraries used by their applications. One of the data sources used is the National Vulnerability Database (NVD). The key challenge faced by the security researchers here is in figuring out which libraries are related to each of the reported vulnerability in NVD. In this article, we …

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Essays On Heterogeneous Large Panel Data Models, Ke Miao May 2020

Essays On Heterogeneous Large Panel Data Models, Ke Miao

Dissertations and Theses Collection (Open Access)

This dissertation consists of three papers which contribute to the estimation and inference theory of the heterogeneous large panel data models. The first chapter studies a panel threshold model with interactive fixed effects. The least-squares estimators in the shrinking-threshold-effect framework are explored. The inference theory on both slope coefficients and the threshold parameter is derived, and a test for the presence of the threshold effect is proposed. The second chapter considers the least-squares estimation of a panel structure threshold regression (PSTR) model, where parameters may exhibit latent group structures. Under some regularity conditions, the latent group structure can be correctly …

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Detecting Latent Communities In Network Formation Models, Shujie Ma, Liangjun Su, Yichong Zhang May 2020

Detecting Latent Communities In Network Formation Models, Shujie Ma, Liangjun Su, Yichong Zhang

Research Collection School Of Economics

This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed effects. We model the coefficients of observed characteristics to have a latent community structure and the edge-wise fixed effects to be of low rank. We propose a multi-step estimation procedure involving nuclear norm regularization, sample splitting, iterative logistic regression and spectral clustering to detect the latent communities. We show that the latent communities can be exactly recovered when the expected degree of the network is of order log n or higher, where n is the number …

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Econometric Methods And Data Science Techniques: A Review Of Two Strands Of Literature And An Introduction To Hybrid Methods, Tian Xie, Jun Yu, Tao Zeng May 2020

Econometric Methods And Data Science Techniques: A Review Of Two Strands Of Literature And An Introduction To Hybrid Methods, Tian Xie, Jun Yu, Tao Zeng

Research Collection School Of Economics

The data market has been growing at an exceptional pace. Consequently, more sophisticated strategies to conduct economic forecasts have been introduced with machine learning techniques. Does machine learning pose a threat to conventional econometric methods in terms of forecasting? Moreover, does machine learning present great opportunities to cross-fertilize the field of econometric forecasting? In this report, we develop a pedagogical framework that identifies complementarity and bridges between the two strands of literature. Existing econometric methods and machine learning techniques for economic forecasting are reviewed and compared. The advantages and disadvantages of these two classes of methods are discussed. A class …

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The Development Of Singapore Law: A Bicentennial Retrospective, Andrew Phang, Yihan Goh, Jerrold Soh May 2020

The Development Of Singapore Law: A Bicentennial Retrospective, Andrew Phang, Yihan Goh, Jerrold Soh

Research Collection Yong Pung How School Of Law

The present article reviews (in broad brushstrokes) the status of Singapore law during its bicentennial year. It is not only about origins but also about growth – in particular, the autochthonous or indigenous growth of the Singapore legal system (particularly since the independence of Singapore as a nation state on 9 August 1965). The analysis of this growth is divided into quantitative as well as qualitative parts. In particular, the former constitutes an empirical analysis which attempts – for the very first time − to tell the development of Singapore law through numbers, building on emerging techniques in data visualisation …

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Ethics, Ai, Mass Data And Pandemic Challenges: Responsible Data Use And Infrastructure Application For Surveillance And Pre-Emptive Tracing Post-Crisis, Mark Findlay, Jia Yuan Loke, Nydia Remolina Leon, Yum Yin, Benjamin (Tan Renyan) Tham May 2020

Ethics, Ai, Mass Data And Pandemic Challenges: Responsible Data Use And Infrastructure Application For Surveillance And Pre-Emptive Tracing Post-Crisis, Mark Findlay, Jia Yuan Loke, Nydia Remolina Leon, Yum Yin, Benjamin (Tan Renyan) Tham

Research Collection Yong Pung How School Of Law

As the COVID-19 health pandemic rages governments and private companies across the globe are utilising AI-assisted surveillance, reporting, mapping and tracing technologies with the intention of slowing the spread of the virus. These technologies have the capacity to amass personal data and share for community control and citizen safety motivations that empower state agencies and inveigle citizen co-operation which could only be imagined outside such times of real and present danger. While not cavilling with the short-term necessity for these technologies and the data they control, process and share in the health regulation mission, this paper argues that this infrastructure …

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Students’ Conceptions Of Bell Curve Grading Fairness In Relation To Goal Orientation And Motivation, Lynette Tan, Brenda Yuen, Wee Ling Loo, Christiaan Prinsloo, Mark Gan May 2020

Students’ Conceptions Of Bell Curve Grading Fairness In Relation To Goal Orientation And Motivation, Lynette Tan, Brenda Yuen, Wee Ling Loo, Christiaan Prinsloo, Mark Gan

Research Collection Yong Pung How School Of Law

The controversial bell curve has received considerable attention in recent years as a grade distribution tool where “norm-referenced grading involves comparing students’ performances with each other” rather than where they fall on a “predefined continuum of quality” (Brookhart, 2013, p. 258). Despite educators’ deep concern on the fairness of bell curve grading, there is little research done on students’ conceptions of that grading system in higher education. This correlational study uses open-ended questions and three instruments to measure students’ conceptions of the fairness of bell curve grading, their goal orientations, and motivation. Undergraduates from three universities participated in the survey …

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Starhopper: A Touch Interface For Remote Object-Centric Drone Navigation, Jiannan Li, Ravin Balakrishnan, Tovi Grossman May 2020

Starhopper: A Touch Interface For Remote Object-Centric Drone Navigation, Jiannan Li, Ravin Balakrishnan, Tovi Grossman

Research Collection School Of Computing and Information Systems

Camera drones, a rapidly emerging technology, offer people the ability to remotely inspect an environment with a high degree of mobility and agility. However, manual remote piloting of a drone is prone to errors. In contrast, autopilot systems can require a significant degree of environmental knowledge and are not necessarily designed to support flexible visual inspections. Inspired by camera manipulation techniques in interactive graphics, we designed StarHopper, a novel touch screen interface for efficient object-centric camera drone navigation, in which a user directly specifies the navigation of a drone camera relative to a specified object of interest. The system relies …

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Memlock: Memory Usage Guided Fuzzing, Cheng Wen, Haijun Wang, Yuekang Li, Shengchao Qin, Yang Liu, Zhiwu Xu, Hongxu Chen, Xiaofei Xie, Geguang Pu, Ting Liu May 2020

Memlock: Memory Usage Guided Fuzzing, Cheng Wen, Haijun Wang, Yuekang Li, Shengchao Qin, Yang Liu, Zhiwu Xu, Hongxu Chen, Xiaofei Xie, Geguang Pu, Ting Liu

Research Collection School Of Computing and Information Systems

Uncontrolled memory consumption is a kind of critical software security weaknesses. It can also become a security-critical vulnerability when attackers can take control of the input to consume a large amount of memory and launch a Denial-of-Service attack. However, detecting such vulnerability is challenging, as the state-of-the-art fuzzing techniques focus on the code coverage but not memory consumption. To this end, we propose a memory usage guided fuzzing technique, named MemLock, to generate the excessive memory consumption inputs and trigger uncontrolled memory consumption bugs. The fuzzing process is guided with memory consumption information so that our approach is general and …

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Towards Characterizing Adversarial Defects Of Deep Learning Software From The Lens Of Uncertainty, Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, Meng Sun May 2020

Towards Characterizing Adversarial Defects Of Deep Learning Software From The Lens Of Uncertainty, Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, Meng Sun

Research Collection School Of Computing and Information Systems

Over the past decade, deep learning (DL) has been successfully applied to many industrial domain-specific tasks. However, the current state-of-the-art DL software still suffers from quality issues, which raises great concern especially in the context of safety- and security-critical scenarios. Adversarial examples (AEs) represent a typical and important type of defects needed to be urgently addressed, on which a DL software makes incorrect decisions. Such defects occur through either intentional attack or physical-world noise perceived by input sensors, potentially hindering further industry deployment. The intrinsic uncertainty nature of deep learning decisions can be a fundamental reason for its incorrect behavior. …

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Competitive Ratios For Online Multi-Capacity Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet May 2020

Competitive Ratios For Online Multi-Capacity Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

In multi-capacity ridesharing, multiple requests (e.g., customers, food items, parcels) with different origin and destination pairs travel in one resource. In recent years, online multi-capacity ridesharing services (i.e., where assignments are made online) like Uber-pool, foodpanda, and on-demand shuttles have become hugely popular in transportation, food delivery, logistics and other domains. This is because multi-capacity ridesharing services benefit all parties involved – the customers (due to lower costs), the drivers (due to higher revenues) and the matching platforms (due to higher revenues per vehicle/resource). Most importantly these services can also help reduce carbon emissions (due to fewer vehicles on roads). …

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Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang May 2020

Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang

Research Collection School Of Computing and Information Systems

While decision-making task is critical in knowledge transfer, particularly from multi-source domains, existing knowledge transfer approaches are not generally designed to be privacy preserving. This has potential legal and financial implications, particularly in sensitive applications such as financial market forecasting. Therefore, in this paper, we propose a Privacy-preserving Multi-party Knowledge Transfer system (PMKT), based on decision trees, for financial market forecasting. Specifically, in PMKT, we leverage a cryptographic-based model sharing technique to securely outsource knowledge reflected in decision trees of multiple parties, and design a secure computation mechanism to facilitate privacy-preserving knowledge transfer. An encrypted user-submitted request from the target …

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Learning Expensive Coordination: An Event-Based Deep Rl Approach, Runsheng Yu, Xinrun Wang, Rundong Wang, Youzhi Zhang, Bo An, Zhen Yu Shi, Hanjiang Lai May 2020

Learning Expensive Coordination: An Event-Based Deep Rl Approach, Runsheng Yu, Xinrun Wang, Rundong Wang, Youzhi Zhang, Bo An, Zhen Yu Shi, Hanjiang Lai

Research Collection School Of Computing and Information Systems

Existing works in deep Multi-Agent Reinforcement Learning (MARL) mainly focus on coordinating cooperative agents to complete certain tasks jointly. However, in many cases of the real world, agents are self-interested such as employees in a company and clubs in a league. Therefore, the leader, i.e., the manager of the company or the league, needs to provide bonuses to followers for efficient coordination, which we call expensive coordination. The main difficulties of expensive coordination are that i) the leader has to consider the long-term effect and predict the followers’ behaviors when assigning bonuses, and ii) the complex interactions between followers make …

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Diversity Of Shareholder Stewardship In Asia: Faux Convergence, Gen Goto, Alan K. Koh, Dan W. Puchniak May 2020

Diversity Of Shareholder Stewardship In Asia: Faux Convergence, Gen Goto, Alan K. Koh, Dan W. Puchniak

Research Collection Yong Pung How School Of Law

Since the UK adopted the world's first stewardship code in 2010, stewardship codes have proliferated across Asia. Given the UK Code's prominence, it is tempting to assume that every other stewardship code performs the same function as the UK Code. This assumption belies the truth: all these codes--regardless of whether they have in fact drawn inspiration from the UK Code--have taken different trajectories due to each adopting its jurisdiction's distinctive institutional and legal context.Using empirical evidence and in-depth case studies of stewardship in Japan and Singapore, this Article reveals how any reception of United Kingdom-style stewardship concepts is only skin …

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Precedent Within The High Court, Kwan Ho Lau May 2020

Precedent Within The High Court, Kwan Ho Lau

Research Collection Yong Pung How School Of Law

A number of Masters and a Registrar have recently indicated that they, when exercising High Court jurisdiction, are not bound strictly to follow prior decisions made by Judges in the High Court. This represents a notable departure from the position established by and within the High Court, where since the Judicature Acts of 1873 and 1875 an unquestioning obeisance of the Master and Registrar towards such decisions has been generally expected and offered. Delving into questions of power, authority and jurisdiction, and examining relevant legislation such as the Civil Procedure Rules, this article constructs and analyses various arguments for and …

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Depletion Manipulations Decrease Openness To Dissent Via Increased Anger, Ming-Hong Tsai, Norman P. Li May 2020

Depletion Manipulations Decrease Openness To Dissent Via Increased Anger, Ming-Hong Tsai, Norman P. Li

Research Collection School of Social Sciences

We investigated a potential outcome of ego depletion manipulations and an importantfactor behind cooperative failure: a lack of openness to others’ dissenting opinions.Across five studies in a variety of task settings, we examined the effect of depletionmanipulations on openness to dissent and investigated two negative emotions as potentialmediators of this process: fatigue and anger. The results demonstrated a negative effect ofdepletion manipulations on openness to dissent through increased anger rather thanfatigue (Studies 1–5). In Studies 3 and 4, we also eliminated perceived trust towards a taskcounterpart as a significant mediator of the relationship between depletion manipulationsand openness to dissent. These …

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