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Full-Text Articles in Computer Sciences

Lean Manufacturing Approach To Increase Packaging Efficiency, Lina Gozali, Irsandy Kurniawan, Aldo Salim, Iveline Anne Marie, Benny Tjahjono, Yun Chia Liang, Aldy Gunawan, Nnovia Hardjo Sie, Yuliani Suseno Aug 2023

Lean Manufacturing Approach To Increase Packaging Efficiency, Lina Gozali, Irsandy Kurniawan, Aldo Salim, Iveline Anne Marie, Benny Tjahjono, Yun Chia Liang, Aldy Gunawan, Nnovia Hardjo Sie, Yuliani Suseno

Research Collection School Of Computing and Information Systems

The company upon which this paper is based engages in flexible packaging production, especially pharmaceutical products with guaranteed quality, trusted by consumers. Its production process includes printing, laminating, and assembling processes. Production activities are done manually and automatically using machines, so various types of waste are often found in these processes, making the level of plant efficiency nonoptimal. This study aims to identify wastes occurring in the production process, especially the production of pollycelonium with three colour variants as the highest demand product, by applying lean manufacturing concepts. The Current Value Stream Mapping (CVSM) used to map the production process …

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Evolve Path Tracer: Early Detection Of Malicious Addresses In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu Aug 2023

Evolve Path Tracer: Early Detection Of Malicious Addresses In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu

Research Collection School Of Computing and Information Systems

With the boom of cryptocurrency and its concomitant financial risk concerns, detecting fraudulent behaviors and associated malicious addresses has been drawing significant research effort. Most existing studies, however, rely on the full history features or full-fledged address transaction networks, both of which are unavailable in the problem of early malicious address detection and therefore failing them for the task. To detect fraudulent behaviors of malicious addresses in the early stage, we present Evolve Path Tracer, which consists of Evolve Path Encoder LSTM, Evolve Path Graph GCN, and Hierarchical Survival Predictor. Specifically, in addition to the general address features, we propose …

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The Future Of Cryptocurrency And Blockchain Technology In Finance, Wanyi Wong, Alan @ Ali Madjelisi Megargel Aug 2023

The Future Of Cryptocurrency And Blockchain Technology In Finance, Wanyi Wong, Alan @ Ali Madjelisi Megargel

Research Collection School Of Computing and Information Systems

Cryptocurrencies have been all the rage in recent years, with many being drawn to their appeal as speculative investment assets. Its proponents also champion the secure and decentralised nature of the technology it is based on, called the blockchain. Given the secure nature of blockchain technology, the idea of adopting cryptocurrencies as legal tender currency has also been mooted and experimented with – with the most famous example being the Central American nation of El Salvador’s bold move to adopting the cryptocurrency Bitcoin as legal tender in September 2021. In theory, this would provide a solution to the high transaction …

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Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An Aug 2023

Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An

Research Collection School Of Computing and Information Systems

Quantitative stock investment is a fundamental financial task that highly relies on accurate prediction of market status and profitable investment decision making. Despite recent advances in deep learning (DL) have shown stellar performance on capturing trading opportunities in the stochastic stock market, the performance of existing DL methods is unstable with sensitivity to network initialization and hyperparameter selection. One major limitation of existing works is that investment decisions are made based on one individual neural network predictor with high uncertainty, which is inconsistent with the workflow in real-world trading firms. To tackle this limitation, we propose AlphaMix, a novel three-stage …

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Corporate Trade War Uncertainty And Patent Bubble, Xu Yang, Nan Hu, Peng Liang Aug 2023

Corporate Trade War Uncertainty And Patent Bubble, Xu Yang, Nan Hu, Peng Liang

Research Collection School Of Computing and Information Systems

This paper draws upon resource dependence theory and investigates how trade policy uncertainty affects firm strategic innovation management in China. Adopting a machine learning approach called Word2Vec from computational linguistics, we construct and validate a measure of firm-level managers’ perceived trade war uncertainty (TWU). We find that TWU has a positive effect on the number of total patent applications, but this positive effect is totally driven by low-quality patents instead of high-quality patents. Moreover, we document that firms have stronger incentives for such strategic innovation behavior when the underlying firms are more financially constrained, and/or when the management is more …

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How Technology May Be Used For Future Disease Predictions, Rich P. Manprisio Jul 2023

How Technology May Be Used For Future Disease Predictions, Rich P. Manprisio

Journal of Applied Disciplines

Exasperated by the ongoing global pandemic, the healthcare system is grappling with the formidable challenges posed by proper and effective disease treatments. Nevertheless, amidst these growing difficulties, the healthcare field has witnessed significant technological advancements, offering promising avenues for disease prediction. Notably, a positive correlation exists between the utilization of technologies and their potential to serve as valuable tools for disease prediction. As our reliance on technological sophistication continues progressing, current research highlights numerous viable options to augment the healthcare sector. This review explores the current state of utilizing technologies and their potential to enhance healthcare, shedding light on their …

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Using Machine Learning Techniques To Model Encoder/Decoder Pair For Non-Invasive Electroencephalographic Wireless Signal Transmission, Ernst Fanfan Jul 2023

Using Machine Learning Techniques To Model Encoder/Decoder Pair For Non-Invasive Electroencephalographic Wireless Signal Transmission, Ernst Fanfan

Master of Science in Computer Science Theses

This study investigated the application and enhancement of Non-Invasive Brain-Computer Interfaces (NI-BCIs), focused on enhancing the efficiency and effectiveness of this technology for individuals with severe physical limitations. The core research goal was to improve current limitations associated with wires, noise, and invasive procedures often associated with BCI technology. The key discussed solution involves developing an optimized Encoder/Decoder (E/D) pair using machine learning techniques, particularly those borrowed from Generative Adversarial Networks (GAN) and other Deep Neural Networks, to minimize data transmission and ensure robustness against data degradation. The study highlighted the crucial role of machine learning in self-adjusting and isolating …

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On Teaching Multi-Criteria Decision Making With A Robot Assistant, Chen Zhang, Hakan Saraoglu, David A. Louton Jul 2023

On Teaching Multi-Criteria Decision Making With A Robot Assistant, Chen Zhang, Hakan Saraoglu, David A. Louton

Information Systems and Analytics Department Faculty Conference Proceedings

We propose a system and method for a robot assistant for teaching multi-attribute decision making (MCDM). Through questions and answers in natural language, the robot assistant learns the user’s preferences on multiple criteria involving a selection decision and makes recommendations using data on each criterion and the learned user preferences. It will include a use-case demonstration where NAO the robot will assist a human in forming a simple portfolio of mutual funds. Presenters will illustrate the architecture of the robot assisted MCDM and describe a method that is extensively used to structure complex decision problems and has been applied to …

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Examination Of Cybersecurity Technologies, Practices, Challenges, And Wish List In K-12 School Districts, Florence Martin, Julie Bacak, Erik Jon Byker, Weichao Wang, Jonathan Wagner, Lynn Ahlgrim-Delzell Jul 2023

Examination Of Cybersecurity Technologies, Practices, Challenges, And Wish List In K-12 School Districts, Florence Martin, Julie Bacak, Erik Jon Byker, Weichao Wang, Jonathan Wagner, Lynn Ahlgrim-Delzell

Journal of Cybersecurity Education, Research and Practice

With the growth in digital teaching and learning, there has been a sharp rise in the number of cybersecurity attacks on K-12 school networks. This has demonstrated a need for security technologies and cybersecurity education. This study examined security technologies used, effective security practices, challenges, concerns, and wish list of technology leaders in K-12 settings. Data collected from 23 district websites and from interviews with 12 district technology leaders were analyzed. Top security practices included cloud-based technologies, segregated network/V-LAN, two-factor authentication, limiting access, and use of Clever or Class Link. Top challenges included keeping users informed, lack of buy-in from …

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Cyberbullying: Senior Prospective Teachers’ Coping Knowledge And Strategies, Kürşat Arslan, İnan Aydın Jul 2023

Cyberbullying: Senior Prospective Teachers’ Coping Knowledge And Strategies, Kürşat Arslan, İnan Aydın

Journal of Cybersecurity Education, Research and Practice

This study aimed to determine senior prospective teachers’ coping knowledge and strategies for cyberbullying in terms of demographic variables. The sample consisted of 471 prospective teachers (324 female and 147 male) studying in the 4th grade in Dokuz Eylül University Buca Education Faculty in Izmir in the 2019-2020 academic year. It was a quantitative study using a causal-comparative research design to find out whether prospective teachers’ coping knowledge differed by independent variables. The "Coping with Cyberbullying Scale" developed by Koç et al. (2016) was employed to discover prospective teachers’ coping strategies for cyberbullying. A "Personal Information" form was also prepared …

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A Systematic Mapping Study On Gamification Applications For Undergraduate Cybersecurity Education, Sherri Weitl-Harms, Adam Spanier, John Hastings, Matthew Rokusek Jul 2023

A Systematic Mapping Study On Gamification Applications For Undergraduate Cybersecurity Education, Sherri Weitl-Harms, Adam Spanier, John Hastings, Matthew Rokusek

Journal of Cybersecurity Education, Research and Practice

Gamification in education presents a number of benefits that can theoretically facilitate higher engagement and motivation among students when learning complex, technical concepts. As an innovative, high-potential educational tool, many educators and researchers are attempting to implement more effective gamification into undergraduate coursework. Cyber Security Operations (CSO) education is no exception. CSO education traditionally requires comprehension of complex concepts requiring a high level of technical and abstract thinking. By properly applying gamification to complex CSO concepts, engagement in students should see an increase. While an increase is expected, no comprehensive study of CSO gamification applications (GA) has yet been undertaken …

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Editorial - 2023 - 1, Hossain Shahriar, Herbert J. Mattord, Michael E. Whitman Jul 2023

Editorial - 2023 - 1, Hossain Shahriar, Herbert J. Mattord, Michael E. Whitman

Journal of Cybersecurity Education, Research and Practice

No abstract provided.

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Sociocultural Barriers For Female Participation In Stem: A Case Of Saudi Women In Cybersecurity, Alanoud Aljuaid, Xiang Michelle Liu Jul 2023

Sociocultural Barriers For Female Participation In Stem: A Case Of Saudi Women In Cybersecurity, Alanoud Aljuaid, Xiang Michelle Liu

Journal of Cybersecurity Education, Research and Practice

The participation of women in Science, Technology, Engineering, and Mathematics (STEM) workforces is overwhelmingly low as compared to their male counterparts. The low uptake of cybersecurity careers has been documented in the previous studies conducted in the contexts of the West and Eastern worlds. However, most of the past studies mainly covered the Western world leaving more knowledge gaps in the context of Middle Eastern countries such as Saudi Arabia. Thus, to fill the existing knowledge gaps, the current study focused on women in Saudi Arabia. The aim of the study was to investigate the factors behind the underrepresentation of …

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Compete To Learn: Toward Cybersecurity As A Sport, Tj Oconnor, Dane Brown, Jasmine Jackson, Bryson Payne, Suzanna Schmeelk Jul 2023

Compete To Learn: Toward Cybersecurity As A Sport, Tj Oconnor, Dane Brown, Jasmine Jackson, Bryson Payne, Suzanna Schmeelk

Journal of Cybersecurity Education, Research and Practice

To support the workforce gap of skilled cybersecurity professionals, gamified pedagogical approaches for teaching cybersecurity have exponentially grown over the last two decades. During this same period, e-sports developed into a multi-billion dollar industry and became a staple on college campuses. In this work, we explore the opportunity to integrate e-sports and gamified cybersecurity approaches into the inaugural US Cyber Games Team. During this tenure, we learned many lessons about recruiting, assessing, and training cybersecurity teams. We share our approach, materials, and lessons learned to serve as a model for fielding amateur cybersecurity teams for future competition.

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How Effective Are Seta Programs Anyway: Learning And Forgetting In Security Awareness Training, David Sikolia, David Biros, Tianjian Zhang Jul 2023

How Effective Are Seta Programs Anyway: Learning And Forgetting In Security Awareness Training, David Sikolia, David Biros, Tianjian Zhang

Journal of Cybersecurity Education, Research and Practice

Prevalent security threats caused by human errors necessitate security education, training, and awareness (SETA) programs in organizations. Despite strong theoretical foundations in behavioral cybersecurity, field evidence on the effectiveness of SETA programs in mitigating actual threats is scarce. Specifically, with a broad range of cybersecurity knowledge crammed into in a single SETA session, it is unclear how effective different types of knowledge are in mitigating human errors in a longitudinal setting. his study investigates how knowledge gained through SETA programs affects human errors in cybersecurity to fill the longitudinal void. In a baseline experiment, we establish that SETA programs reduce …

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Anonymity And Gender Effects On Online Trolling And Cybervictimization, Gang Lee, Annalyssia Soonah Jul 2023

Anonymity And Gender Effects On Online Trolling And Cybervictimization, Gang Lee, Annalyssia Soonah

Journal of Cybersecurity Education, Research and Practice

The purpose of this study was to investigate the effects of the anonymity of the internet and gender differences in online trolling and cybervictimization. A sample of 151 college students attending a southeastern university completed a survey to assess their internet activities and online trolling and cybervictimization. Multivariate analyses of logistic regression and ordinary least squares regression were used to analyze online trolling and cybervictimization. The results indicated that the anonymity measure was not a significant predictor of online trolling and cybervictimization. Female students were less likely than male students to engage in online trolling, but there was no gender …

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Case Study: The Impact Of Emerging Technologies On Cybersecurity Education And Workforces, Austin Cusak Jul 2023

Case Study: The Impact Of Emerging Technologies On Cybersecurity Education And Workforces, Austin Cusak

Journal of Cybersecurity Education, Research and Practice

A qualitative case study focused on understanding what steps are needed to prepare the cybersecurity workforces of 2026-2028 to work with and against emerging technologies such as Artificial Intelligence and Machine Learning. Conducted through a workshop held in two parts at a cybersecurity education conference, findings came both from a semi-structured interview with a panel of experts as well as small workgroups of professionals answering seven scenario-based questions. Data was thematically analyzed, with major findings emerging about the need to refocus cybersecurity STEM at the middle school level with problem-based learning, the disconnects between workforce operations and cybersecurity operators, the …

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Managing The Creative Frontier Of Generative Ai: The Novelty-Usefulness Tradeoff, Anirban. Mukherjee, Hannah H. Chang Jul 2023

Managing The Creative Frontier Of Generative Ai: The Novelty-Usefulness Tradeoff, Anirban. Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

In this paper, drawing inspiration from the human creativity literature, we explore the optimal balance between novelty and usefulness in generative Artificial Intelligence (AI) systems. We posit that overemphasizing either aspect can lead to limitations such as hallucinations and memorization. Hallucinations, characterized by AI responses containing random inaccuracies or falsehoods, emerge when models prioritize novelty over usefulness. Memorization, where AI models reproduce content from their training data, results from an excessive focus on usefulness, potentially limiting creativity. To address these challenges, we propose a framework that includes domain-specific analysis, data and transfer learning, user preferences and customization, custom evaluation metrics, …

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Beyond Anthropomorphism: Unraveling The True Priorities Of Chatbot Usage In Smes, Tamas Makany, Sungjong Roh, Kotaro Hara, Jie Min Hua, Felicia Si Ying Goh, Wilson Yang Jie Teh Jul 2023

Beyond Anthropomorphism: Unraveling The True Priorities Of Chatbot Usage In Smes, Tamas Makany, Sungjong Roh, Kotaro Hara, Jie Min Hua, Felicia Si Ying Goh, Wilson Yang Jie Teh

Research Collection Lee Kong Chian School Of Business

This study examined business communication practices with chatbots among various Small and Medium Enterprise (SME) stakeholders in Singapore, including business owners/employees, customers, and developers. Through qualitative interviews and chatbot transcript analysis, we investigated two research questions: (1) How do the expectations of SME stakeholders compare to the conversational design of SME chatbots? and (2) What are the business reasons for SMEs to add human-like features to their chatbots? Our findings revealed that functionality is more crucial than anthropomorphic characteristics, such as personality and name. Stakeholders preferred chatbots that explicitly identified themselves as machines to set appropriate expectations. Customers prioritized efficiency, …

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Reducing Spatial Labeling Redundancy For Active Semi-Supervised Crowd Counting, Yongtuo Liu, Sucheng Ren, Liangyu Chai, Hanjie Wu, Dan Xu, Jing Qin, Shengfeng He Jul 2023

Reducing Spatial Labeling Redundancy For Active Semi-Supervised Crowd Counting, Yongtuo Liu, Sucheng Ren, Liangyu Chai, Hanjie Wu, Dan Xu, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Labeling is onerous for crowd counting as it should annotate each individual in crowd images. Recently, several methods have been proposed for semi-supervised crowd counting to reduce the labeling efforts. Given a limited labeling budget, they typically select a few crowd images and densely label all individuals in each of them. Despite the promising results, we argue the None-or-All labeling strategy is suboptimal as the densely labeled individuals in each crowd image usually appear similar while the massive unlabeled crowd images may contain entirely diverse individuals. To this end, we propose to break the labeling chain of previous methods and …

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Beyond "Protected" And "Private": An Empirical Security Analysis Of Custom Function Modifiers In Smart Contracts, Yuzhou Fang, Daoyuan Wu, Xiao Yi, Shuai Wang, Yufan Chen, Mengjie Chen, Yang Liu, Lingxiao Jiang Jul 2023

Beyond "Protected" And "Private": An Empirical Security Analysis Of Custom Function Modifiers In Smart Contracts, Yuzhou Fang, Daoyuan Wu, Xiao Yi, Shuai Wang, Yufan Chen, Mengjie Chen, Yang Liu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

A smart contract is a piece of application-layer code running on blockchain ledgers and it provides programmatic logic via transaction-based execution of pre-defined functions. Smart contract functions are by default invokable by any party. To safeguard them, the mainstream smart contract language, i.e., Solidity of the popular Ethereum blockchain, proposed a unique language-level keyword called “modifier,” which allows developers to define custom function access control policies beyond the traditional “protected” and “private” modifiers in classic programming languages.In this paper, we aim to conduct a large-scale security analysis of the modifiers used in real-world Ethereum smart contracts. To achieve this, we …

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Augmenting Fake Content Detection In Online Platforms: A Domain Adaptive Transfer Learning Via Adversarial Training Approach, Ka Chung Ng, Ping Fan Ke, Mike K. P. So, Kar Yan Tam Jul 2023

Augmenting Fake Content Detection In Online Platforms: A Domain Adaptive Transfer Learning Via Adversarial Training Approach, Ka Chung Ng, Ping Fan Ke, Mike K. P. So, Kar Yan Tam

Research Collection School Of Computing and Information Systems

Online platforms are experimenting with interventions such as content screening to moderate the effects of fake, biased, and incensing content. Yet, online platforms face an operational challenge in implementing machine learning algorithms for managing online content due to the labeling problem, where labeled data used for model training are limited and costly to obtain. To address this issue, we propose a domain adaptive transfer learning via adversarial training approach to augment fake content detection with collective human intelligence. We first start with a source domain dataset containing deceptive and trustworthy general news constructed from a large collection of labeled news …

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Product Question Answering In E-Commerce: A Survey, Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam Jul 2023

Product Question Answering In E-Commerce: A Survey, Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam

Research Collection School Of Computing and Information Systems

Product question answering (PQA), aiming to automatically provide instant responses to customer’s questions in E-Commerce platforms, has drawn increasing attention in recent years. Compared with typical QA problems, PQA exhibits unique challenges such as the subjectivity and reliability of user-generated contents in E-commerce platforms. Therefore, various problem settings and novel methods have been proposed to capture these special characteristics. In this paper, we aim to systematically review existing research efforts on PQA. Specifically, we categorize PQA studies into four problem settings in terms of the form of provided answers. We analyze the pros and cons, as well as present existing …

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Theme Park Visitors Prefer Human-Like Robots In Customer Service Interactions, Ady Milman, Asli D.A. Tasci Jun 2023

Theme Park Visitors Prefer Human-Like Robots In Customer Service Interactions, Ady Milman, Asli D.A. Tasci

Rosen Research Review

Service robots are becoming increasingly popular in many industries and social settings, including education, childcare, elderly therapy centers, and even theme parks. Tourism and hospitality industries are adopting robots enthusiastically and are being closely studied to observe guest engagement and reaction to robotic services. Service robots are becoming increasingly popular in many industries and social settings, including education, childcare, elderly therapy centers, and even theme parks. Tourism and hospitality industries are adopting robots enthusiastically and are being closely studied to observe guest engagement and reaction to robotic services. UCF Rosen College of Hospitality Management researchers, Dr. Ady Milman and Dr. …

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The Power Of (Virtual) Convergence: The Unrealized Potential Of Pair Programming And Remote Work, Mikayla Maki Jun 2023

The Power Of (Virtual) Convergence: The Unrealized Potential Of Pair Programming And Remote Work, Mikayla Maki

University Honors Theses

Remote work is expensive. It can lead to isolation, miscommunications, and ossified organizations. These problems occur because of a synchronicity mismatch between how we need to communicate as humans, and what today's tools are capable of. This mismatch can be solved by the adoption of remote pair programming, as exemplified by the authors work at a startup (Zed). Pair programming provides the organic, synchronous, reciprocal interaction necessary to develop the sorts of relationships that remote firms currently lack.

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Interstice, Shravan Rao Jun 2023

Interstice, Shravan Rao

Masters Theses

When I was about three years old, I distinctly remember being too small to see what was on top of the table. A couple of years later, when I could see those objects, I thought the world around me had grown smaller. In a way, it did, as I experienced, lived, captured, remembered, and shared the space repeatedly. This sense of the world shrinking was exaggerated during the Covid-19 pandemic, allowing new behaviours and modes of interaction to emerge. Continually shaping our modern lives, virtual technologies redefine how we access and share information and stories or even explore new places. …

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Automatic Scoring Of Speeded Interpersonal Assessment Center Exercises Via Machine Learning: Initial Psychometric Evidence And Practical Guidelines, Louis Hickman, Christoph N. Herde, Filip Lievens, Louis Tay Jun 2023

Automatic Scoring Of Speeded Interpersonal Assessment Center Exercises Via Machine Learning: Initial Psychometric Evidence And Practical Guidelines, Louis Hickman, Christoph N. Herde, Filip Lievens, Louis Tay

Research Collection Lee Kong Chian School Of Business

Assessment center (AC) exercises such as role-plays have established themselves as valuable approaches for obtaining insights into interpersonal behavior, but they are often considered the “Rolls Royce” of personnel assessment due to their high costs. The observation and rating process comprises a substantial part of these costs. In an exploratory case study, we capitalize on recent advances in natural language processing (NLP) by developing NLP-based machine learning (ML) models to investigate the possibility of automatically scoring AC exercises. First, we compared the convergent-related validity and contamination with word count of ML scores based on models that used different NLP methods …

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Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey Jun 2023

Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey

CBN Journal of Applied Statistics (JAS)

This paper modifies the Bahl and Tuteja exponential ratio-type estimator for population median under simple random and stratified sampling schemes using calibration weight adjustment technique with supplementary information to vary the stratum weights. The bias and mean square error of the modified estimator were obtained up to the second-order approximation, which satisfies the necessary conditions for efficiency. The findings show that the new estimator surpasses existing estimators in efficiency gain. This suggests the appropriateness of calibration weight modification in boosting the efficiency of a population parameter estimator under stratified random sampling especially where the population parameter of the auxiliary variable …

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Privacy Please: Power Distance And People’S Responses To Data Breaches Across Countries, Shilpa Madan, Krishna Savani, Constantine S. Katsikeas Jun 2023

Privacy Please: Power Distance And People’S Responses To Data Breaches Across Countries, Shilpa Madan, Krishna Savani, Constantine S. Katsikeas

Research Collection Lee Kong Chian School Of Business

Information security and data breaches are perhaps the biggest challenges that global businesses face in the digital economy. Although data breaches can cause significant harm to users, businesses, and society, there is significant individual and national variation in people’s responses to data breaches across markets. This research investigates power distance as an antecedent of people’s divergent reactions to data breaches. Eight studies using archival, correlational, and experimental methods find that high power distance makes users more willing to continue patronizing a business after a data breach (Studies 1–3). This is because they are more likely to believe that the business, …

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Catching The Fast Payments Trend: Optimal Designs And Leadership Strategies Of Retail Payment And Settlement Systems, Zhiling Guo, Dan Ma Jun 2023

Catching The Fast Payments Trend: Optimal Designs And Leadership Strategies Of Retail Payment And Settlement Systems, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

Recent financial technologies have enabled fast payments and are reshaping retail payment and settlement systems globally. We developed an analytical model to study the optimal design of a new retail payment system in terms of settlement speed and system capability under both bank and fintech firm heterogeneous participation incentives. We found that three types of payment systems emerge as equilibrium outcomes: batch retail (BR), expedited retail (ER), and real-time retail (RR) payment systems. Although the base value of the payment service positively affects both settlement speed and system capability, the expected liquidity cost negatively impacts settlement speed, and total transaction …

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