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Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni Jun 2013

Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni

Research Collection School Of Computing and Information Systems

The Last Mile Problem (LMP) refers to the provision of travel service from thenearest public transportation node to a home or office. We study the supply side of thisproblem in a stochastic setting, with batch demands resulting from the arrival of groupsof passengers at rail stations or bus stops who request last-mile service. Closed-formbounds and approximations are derived for the performance of Last Mile TransportationsSystems as a function of the fundamental design parameters of such systems. An initialset of results is obtained for the case in which a fleet of vehicles of unit capacity providesthe Last Mile service and each …

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Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song Jun 2013

Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song

Research Collection School Of Computing and Information Systems

In this paper, we propose SocioPhone, a novel initiative to build a mobile platform for face-to-face interaction monitoring. Face-to-face interaction, especially conversation, is a fundamental part of everyday life. Interaction-aware applications aimed at facilitating group conversations have been proposed, but have not proliferated yet. Useful contexts to capture and support face-to-face interactions need to be explored more deeply. More important, recognizing delicate conversational contexts with commodity mobile devices requires solving a number of technical challenges. As a first step to address such challenges, we identify useful meta-linguistic contexts of conversation, such as turn-takings, prosodic features, a dominant participant, and pace. …

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A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery, Feida Zhu, Zequn Zhang, Qiang Qu Jun 2013

A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery, Feida Zhu, Zequn Zhang, Qiang Qu

Research Collection School Of Computing and Information Systems

Despite the wealth of research on frequent graph pattern mining, how to efficiently mine the complete set of those with constraints still poses a huge challenge to the existing algorithms mainly due to the inherent bottleneck in the mining paradigm. In essence, mining requests with explicitly-specified constraints cannot be handled in a way that is direct and precise. In this paper, we propose a direct mining framework to solve the problem and illustrate our ideas in the context of a particular type of constrained frequent patterns — the “skinny” patterns, which are graph patterns with a long backbone from which …

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A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang Jun 2013

A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang

Research Collection School Of Computing and Information Systems

Threaded discussion forums provide an important social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or stances on hot issues from forum threads is an important and useful task. In this paper, we propose a novel latent variable model for viewpoint discovery from threaded forum posts. Our model is a principled generative latent variable model which captures three important factors: viewpoint specific topic preference, user identity and user interactions. Evaluation results show that our model clearly outperforms a number of baseline models in terms of both clustering …

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Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang Jun 2013

Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang

Research Collection School Of Computing and Information Systems

Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to apply collaborative filtering through probabilistic matrix factorization to generalize and improve the opinion matrices extracted from forum posts. Experiments with two tasks show that the learned latent factor representation can give good performance on a relation polarity prediction task and improve the performance of a subgroup detection task.

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Think Twice Before You Share: Analyzing Privacy Leakage Under Privacy Control In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng Jun 2013

Think Twice Before You Share: Analyzing Privacy Leakage Under Privacy Control In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Online Social Networks (OSNs) have become one of the major platforms for social interactions. Privacy control is deployed in popular OSNs to protect user’s data. However, user’s sensitive information could still be leaked even when privacy rules are properly configured. We investigate the effectiveness of privacy control against privacy leakage from the perspective of information flow. Our analysis reveals that the existing privacy control mechanisms do not protect the flow of personal information effectively. By examining typical OSNs including Facebook, Google+, and Twitter, we discover a series of privacy exploits which are caused by the conflicts between privacy control and …

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Launching Generic Attacks On Ios With Approved Third-Party Applications, Jin Han, Mon Kywe Su, Qiang Yan, Feng Bao, Robert H. Deng, Debin Gao, Yingjiu Li, Jianying Zhou Jun 2013

Launching Generic Attacks On Ios With Approved Third-Party Applications, Jin Han, Mon Kywe Su, Qiang Yan, Feng Bao, Robert H. Deng, Debin Gao, Yingjiu Li, Jianying Zhou

Research Collection School Of Computing and Information Systems

iOS is Apple’s mobile operating system, which is used on iPhone, iPad and iPod touch. Any third-party applications developed for iOS devices are required to go through Apple’s application vetting process and appear on the official iTunes App Store upon approval.When an application is downloaded from the store and installed on an iOS device, it is given a limited set of privileges, which are enforced by iOS application sandbox. Although details of the vetting process and the sandbox are kept as black box by Apple, it was generally believed that these iOS security mechanisms are effective in defending against malwares. …

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T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni Jun 2013

T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni

Research Collection School Of Computing and Information Systems

Nowadays, big cities are suffering from severe traffic congestion as a result of the continuing increase in vehicles. Taxis equipped with GPS can be viewed as sensors of the traffic situation in city. However, trajectory data generated by taxi’s GPS traces are often high-dimensional and contain large spatial and temporal attributes, which pose challenges for analysts. In this paper, based on taxi trajectory data, we present an interactive visual analytics system, T-Watcher, for monitoring and analyzing complex traffic situations in big cities. Users are able to use a carefully designed interface to monitor and inspect data interactively from three levels …

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Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan Jun 2013

Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

The execution of an agent's complex activities, comprising sequences of simpler actions, sometimes leads to the clash of conflicting functions that must be optimized. These functions represent satisfaction, short-term as well as long-term objectives, costs and individual preferences. The way that these functions are weighted is usually unknown even to the decision maker. But if we were able to understand the individual motivations and compare such motivations among individuals, then we would be able to actively change the environment so as to increase satisfaction and/or improve performance. In this work, we approach the problem of providing highlevel and intelligible descriptions …

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Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong Jun 2013

Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Discrete Time Markov Chains (DTMCs) are widely used to model probabilistic systems in many domains, such as biology, network and communication protocols. There are two main approaches for probability reachability analysis of DTMCs, i.e., solving linear equations or using value iteration. However, both approaches have drawbacks. On one hand, solving linear equations can generate accurate results, but it can be only applied to relatively small models. On the other hand, value iteration is more scalable, but often suffers from slow convergence. Furthermore, it is unclear how to parallelize (i.e., taking advantage of multi-cores or distributed computers) these two approaches. In …

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A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong Jun 2013

A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong

Research Collection School Of Computing and Information Systems

UML is a widely used notation, and formalizing its semantics is an important issue. Here, we concentrate on formalizing UML state machines, used to express the dynamic behaviour of software systems. We propose a formal operational semantics covering all features of the latest version (2.4.1) of UML state machines specification. We use labelled transition systems as the semantic model, so as to use automatic verification techniques like model checking. Furthermore, our proposed semantics includes synchronous and asynchronous communications between state machines. We implement our approach in USM2C, a model checker supporting editing, simulation and automatic verification of UML state machines. …

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Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang Jun 2013

Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang

Research Collection School Of Computing and Information Systems

No abstract provided.

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A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang Jun 2013

A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang

Research Collection School Of Computing and Information Systems

No abstract provided.

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Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston Jun 2013

Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

Cybersecurity is a national priority in this big data era. Because of negative externalities and the resulting lack of economic incentives, companies often underinvest in security controls, despite government and industry recommendations. Although many existing studies on security have explored technical solutions, only a few have looked at the economic motivations. To fill the gap, we propose an approach to increase the incentives of organizations to address security problems. Specifically, we utilize and process existing security vulnerability data, derive explicit security performance information, and disclose the information as feedback to organizations and the public. We regularly release information on the …

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Mitigating Access-Driven Timing Channels In Clouds Using Stopwatch, Peng Li, Debin Gao, Michael K. Reiter Jun 2013

Mitigating Access-Driven Timing Channels In Clouds Using Stopwatch, Peng Li, Debin Gao, Michael K. Reiter

Research Collection School Of Computing and Information Systems

This paper presents StopWatch , a system that defends against timing-based side-channel attacks that arise from coresidency of victims and attackers in infrastructure-as-a-service clouds. StopWatchtriplicates each cloud-resident guest virtual machine (VM) and places replicas so that the three replicas of a guest VM are coresident with nonoverlapping sets of (replicas of) other VMs. StopWatch uses thetiming of I/O events at a VM's replicas collectively to determine the timings observed by each one or by an external observer, so that observable timing behaviors are similarly likely in the absence of any other individual, coresident VM. We detail the design and implementation …

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When Do Consumers Purchase Online?: Based On Inter-Purchase Time, Youngsoo Kim Jun 2013

When Do Consumers Purchase Online?: Based On Inter-Purchase Time, Youngsoo Kim

Research Collection School Of Computing and Information Systems

This study is motivated by the premise that online consumers can make a purchase at any time of day if they have even a tiny time slot along with Internet access. To identify the increased shopping time flexibility, we first characterize the patterns of online purchase timing in comparison to those in the offline market. The results show (1) the breakdown of purchase timing regularity and (2) the change of weekly spike purchase occurrence. Second, we build online inter-purchase time model and estimate it with the data collected from one of the premier online vendors in Korea. We verify new …

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Converting Houses Into Churches: The Mobility, Fission, And Sacred Networks Of Evangelical House Churches In Sri Lanka, Orlando Woods Jun 2013

Converting Houses Into Churches: The Mobility, Fission, And Sacred Networks Of Evangelical House Churches In Sri Lanka, Orlando Woods

Research Collection School of Social Sciences

In this paper I examine the processes and politics associated with the formation of evangelical house churches in Sri Lanka. In doing so, I show how the sacred space of the house church is constructed through the development of sacred networks, which emerge when a group of Christians assemble for prayer and worship. Sacred networks grant the house church an important degree of mobility, but they also encourage church fission. Whilst the house church enables evangelical groups to grow in hostile environments like that of Sri Lanka, it is often a superficial form of growth that is unsustainable in the …

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Validating Estimates Of Latent Traits From Textual Data Using Human Judgment As A Benchmark, Will Lowe, Kenneth Benoit Jun 2013

Validating Estimates Of Latent Traits From Textual Data Using Human Judgment As A Benchmark, Will Lowe, Kenneth Benoit

Research Collection School of Social Sciences

Automated and statistical methods for estimating latent political traits and classes from textual data hold great promise, because virtually every political act involves the production of text. Statistical models of natural language features, however, are heavily laden with unrealistic assumptions about the process that generates these data, including the stochastic process of text generation, the functional link between political variables and observed text, and the nature of the variables (and dimensions) on which observed text should be conditioned. While acknowledging statistical models of latent traits to be "wrong," political scientists nonetheless treat their results as sufficiently valid to be useful. …

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David-Hillel Ruben’S 'Traditions And True Successors': A Critical Reply, John N. Williams Jun 2013

David-Hillel Ruben’S 'Traditions And True Successors': A Critical Reply, John N. Williams

Research Collection School of Social Sciences

No abstract provided.

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A Note-Restructuring Intervention Increases Students’ Exam Scores, Dov Cohen, Emily Kim, Jacinth J. X. Tan, Mary-Ann Winkelmes Jun 2013

A Note-Restructuring Intervention Increases Students’ Exam Scores, Dov Cohen, Emily Kim, Jacinth J. X. Tan, Mary-Ann Winkelmes

Research Collection School of Social Sciences

It was hypothesized that students’ learning would be enhanced by an intervention getting them to elaborate on and restructure the notes they had taken in lecture. Students in a research methods course were randomly assigned to weeks in which they would turn in a copy of their restructured lecture notes along with a very brief summary of the class. This intervention required students to spend quality time-on-task. Subsequently, results of exam questions from weeks in which students completed the intervention were compared to weeks they did not do so. The intervention improved student performance by a full class grade (11 …

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Attribute-Based Access To Scalable Media In Cloud-Assisted Content Sharing, Yongdong Wu, Zhuo Wei, Robert H. Deng Jun 2013

Attribute-Based Access To Scalable Media In Cloud-Assisted Content Sharing, Yongdong Wu, Zhuo Wei, Robert H. Deng

Research Collection School Of Computing and Information Systems

This paper presents a novel Multi-message Ciphertext Policy Attribute-Based Encryption (MCP-ABE) technique, and employs the MCP-ABE to design an access control scheme for sharing scalable media based on data consumers’ attributes (e.g., age, nationality, gender) rather than an explicit list of the consumers’ names. The scheme is efficient and flexible because MCP-ABE allows a content provider to specify an access policy and encrypt multiple messages within one ciphertext such that only the users whose attributes satisfy the access policy can decrypt the ciphertext. Moreover, the paper shows how to support resource-limited mobile devices by offloading computational intensive perations to cloud …

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Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong Jun 2013

Adaptive Credit Scoring With Analytic Hierarchy Process, Kwang Yong Koh, Murphy Choy, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Credit risk assessment for consumers has been a cornerstone of risk management in financial institutions and constitutes a component of the three pillars of Basel II. Traditionally, the concept of 5 ‘C’s was widely adopted by financial institutions as the key basis for credit risk assessment for loan applications by prospective borrowers. With the evolution of the credit risk management practices, more quantitative methods such as credit scorecards have been developed, which is implemented through the use of logistic regression, decision trees and neural networks. However, such approaches proved to be inadequate with the validity and effectiveness of the approaches …

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A New Unpredictability-Based Rfid Privacy Model, Anjia Yang, Yunhui Zhuang, Duncan S. Wong, Guomin Yang Jun 2013

A New Unpredictability-Based Rfid Privacy Model, Anjia Yang, Yunhui Zhuang, Duncan S. Wong, Guomin Yang

Research Collection School Of Computing and Information Systems

Ind-privacy and unp-privacy, later refined to unp∗-privacy, are two different classes of privacy models for RFID authentication protocols. These models have captured the major anonymity and untraceability related attacks regarding RFID authentication protocols with privacy, and existing work indicates that unp∗-privacy seems to be a stronger notion when compared with ind-privacy. In this paper, we continue studying the RFID privacy models, and there are two folds regarding our results. First of all, we describe a new traceability attack and show that schemes proven secure in unp∗-privacy may not be secure against this new and practical type of traceability attacks. We …

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Introducing Programmers To Pair Programming: A Controlled Experiment, A. S. M. Sajeev, Subhajit Datta Jun 2013

Introducing Programmers To Pair Programming: A Controlled Experiment, A. S. M. Sajeev, Subhajit Datta

Research Collection School Of Computing and Information Systems

Pair programming is a key characteristic of the Extreme Programming (XP) method. Through a controlled experiment we investigate pair programming behaviour of programmers without prior experience in XP. The factors investigated are: (a) characteristics of pair programming that are less favored (b) perceptions of team effectiveness and how they relate to product quality, and (c) whether it is better to train a pair by giving routine tasks first or by giving complex tasks first. Our results show that: (a) the least liked aspects of pair programming were having to share the screen, keyboard and mouse, and having to switch between …

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Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li Jun 2013

Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li

Research Collection School Of Computing and Information Systems

Event detection has been an important task for a long time. When it comes to Twitter, new problems are presented. Twitter data is a huge temporal data flow with much noise and various kinds of topics. Traditional sophisticated methods with a high computational complexity aren’t designed to handle such data flow efficiently. In this paper, we propose a mixture Gaussian model for bursty word extraction in Twitter and then employ a novel time-dependent HDP model for new topic detection. Our model can grasp new events, the location and the time an event becomes bursty promptly and accurately. Experiments show the …

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Cameo: A Middleware For Mobile Advertisement Delivery, Azeem J. Khan, Kasthuri Jayarajah, Dongsu Han, Archan Misra, Rajesh Krishna Balan, Srinivasan Seshan Jun 2013

Cameo: A Middleware For Mobile Advertisement Delivery, Azeem J. Khan, Kasthuri Jayarajah, Dongsu Han, Archan Misra, Rajesh Krishna Balan, Srinivasan Seshan

Research Collection School Of Computing and Information Systems

Advertisements are the de-facto currency of the Internet with many popular applications (e.g. Angry Birds) and online services (e.g., YouTube) relying on advertisement generated revenue. However, the current economic models and mechanisms for mobile advertising are fundamentally not sustainable and far from ideal. In particular, as we show, applications which use mobile advertising are capable of using significant amounts of a mobile users' critical resources without being controlled or held accountable. This paper seeks to redress this situation by enabling advertisement supported applications to become significantly more "user-friendly". To this end, we present the design and implementation of CAMEO, a …

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Affect As A Decision-Making System Of The Present, Hannah H. Chang, Michel Tuan Pham Jun 2013

Affect As A Decision-Making System Of The Present, Hannah H. Chang, Michel Tuan Pham

Research Collection Lee Kong Chian School Of Business

We review a variety of empirical findings consistent with the general thesis that the affective system of judgment and decision making is inherently anchored in the present. Building on this thesis, we advance the specific hypothesis that affective feelings are relied upon more (weighted more heavily) in judgments whose outcomes and targets are closer to the present than in those whose outcomes and targets are temporally more distant. Consistent with this hypothesis, results from five experiments show that temporal proximity (a) amplifies the relative preference for options that are affectively superior, and (b) increases the effects of incidental affect on …

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Designing Trustworthy Organizations, Robert F. Hurley, Nicole Gillespie, Donald L. Ferrin, Graham Dietz Jun 2013

Designing Trustworthy Organizations, Robert F. Hurley, Nicole Gillespie, Donald L. Ferrin, Graham Dietz

Research Collection Lee Kong Chian School Of Business

Companies often blame trust violations on ‘rogue employees', but these violations are predictable in organizations that allow dysfunctional, conflicting or incongruent activities to take root.

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The Influence Of Mindful Attention On Value Claiming In Distributive Negotiations: Evidence From Four Laboratory Experiments, Jochen Reb, Jayanth Narayanan Jun 2013

The Influence Of Mindful Attention On Value Claiming In Distributive Negotiations: Evidence From Four Laboratory Experiments, Jochen Reb, Jayanth Narayanan

Research Collection Lee Kong Chian School Of Business

We examined the effect of mindful attention on negotiation outcomes in distributive negotiations across four experiments. In Studies 1 and 2, participants who performed a short mindful attention exercise prior to the negotiation claimed a larger share of the bargaining zone than the control condition participants they negotiated with. Study 3 replicated this finding using a different manipulation of mindful attention. Study 4 again replicated this result and also found that mindful negotiators were more satisfied with both the outcome and the process of the negotiation. We discuss theoretical and practical implications, limitations, and future directions.

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Stock Picking, Industry Picking And Market Timing In Sell-Side Research, Ohad Kadan, Leonardo Madureira, Rong Wang, Tzachi Zach Jun 2013

Stock Picking, Industry Picking And Market Timing In Sell-Side Research, Ohad Kadan, Leonardo Madureira, Rong Wang, Tzachi Zach

Research Collection Lee Kong Chian School Of Business

Sell-side analysts employ different benchmarks when defining their stock recommendations. For example, a ‘buy’ for some brokers means the stock is expected to outperform its peers in the same sector (“industry benchmarkers”), while for other brokers it means the stock is expected to outperform the market (“market benchmarkers”), or just some absolute return (“total benchmarkers”). We use these benchmarks to analyze the role of stock picking, industry picking and market timing in contributing to the performance of stock recommendations. We are able to do so given that different benchmarks suggest the use of different sets of abilities. Analysis of the …

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