Computer Sciences Commons^™

Establishing The Importance Of Co-Creation And Self-Efficacy In Creative Collaboration With Artificial Intelligence, Jack Mcguire, David De Cremer, Tim Van De Cruys

Research Collection Lee Kong Chian School Of Business

The emergence of generative AI technologies has led to an increasing number of people collaborating with AI to produce creative works. Across two experimental studies, in which we carefully designed and programmed state-of-the-art human–AI interfaces, we examine how the design of generative AI systems influences human creativity (poetry writing). First, we find that people were most creative when writing a poem on their own, compared to first receiving a poem generated by an AI system and using sophisticated tools to edit it (Study 1). Following this, we demonstrate that this creativity deficit dissipates when people co-create with—not edit—AI and establish …

Decoding Gpt Mania In Chinese Stock Market, Yan Ma, Nan Hu, Shuyang Jia

Research Collection School Of Computing and Information Systems

This study investigates the impact of investor attention on stock market reactions to ChatGPT using dialogues on the Chinese interactive investor platforms (IIPs). We measure investor attention by the number of investors’ questions toward ChatGPT on the IIPs and categorize the firms’ answers as Investing, Speculative, and Absent. The research reveals positive and statistically significant market reactions surrounding the initial questions that occur before firm responses. Positive abnormal returns are also observed around the initial answer dates, with Investing firms evoking the highest market response, followed by Speculative firms, and Absent firms exhibiting the lowest reactions. Our results suggest that …

Exponential Qubit Reduction In Optimization For Financial Transaction Settlement, Elias X. Huber, Benjamin Y. L. Tan, Paul Robert Griffin, Dimitris G. Angelakis

Research Collection School Of Computing and Information Systems

We extend the qubit-efficient encoding presented in (Tan et al. in Quantum 5:454, 2021) and apply it to instances of the financial transaction settlement problem constructed from data provided by a regulated financial exchange. Our methods are directly applicable to any QUBO problem with linear inequality constraints. Our extension of previously proposed methods consists of a simplification in varying the number of qubits used to encode correlations as well as a new class of variational circuits which incorporate symmetries thereby reducing sampling overhead, improving numerical stability and recovering the expression of the cost objective as a Hermitian observable. We also …

Gamification In Erp Systems: A Study On Intrinsic Motivation And User Behavioral Intentions, Esi Adeborna, Fiona Fui-Hoon Nah, Luvai Motiwalla

Research Collection School Of Computing and Information Systems

In the evolving landscape of Enterprise Resource Planning (ERP) systems, integrating gamification shows promise for enhancing user training and education. However, empirical research on gamification's effect on intrinsic motivation in using ERP is limited. Hence, we examined the intrinsic motivational effects of a gamified ERP environment in this research. We created a Gamified Web Application linked to SAP ERP to investigate how gamification affects users' behavioral intention. Leveraging self-determination theory, we examined the influence of perceived competence, autonomy, and relatedness on usage intent. In a controlled experiment with 63 participants, data collected via survey revealed that gamification enhances perceived competence, …

Macrohft : Memory Augmented Context-Aware Reinforcement Learning On High Frequency Trading, Chuqiao Zong, Chaojie Wang, Molei Qin, Lei Feng, Xinrun Wang, Xinrun Wang

Research Collection School Of Computing and Information Systems

High-frequency trading (HFT) that executes algorithmic trading in short time scales, has recently occupied the majority of cryptocurrency market. Besides traditional quantitative trading methods, reinforcement learning (RL) has become another appealing approach for HFT due to its terrific ability of handling high-dimensional financial data and solving sophisticated sequential decision-making problems, e.g., hierarchical reinforcement learning (HRL) has shown its promising performance on second-level HFT by training a router to select only one sub-agent from the agent pool to execute the current transaction. However, existing RL methods for HFT still have some defects: 1) standard RL-based trading agents suffer from the overfitting …

Maximizing Generative Ai Benefits With Task Creativity And Human Validation, Charu Sinha, Veselina P. Vracheva, Cristina Nistor

Business Faculty Articles and Research

Much of the existing literature on generative AI applications is conflicting, with findings suggesting that investing in AI will lead to better organizational outcomes but also pointing out that incorporating AI may be a wasteful even counterproductive initiative. We develop a conceptual frame-work to characterize generative AI benefits based on the types of tasks that generative AI may be used for in management. Our work suggests that task creativity plays a key role in successful generative AI outcomes, but human validation - the extent to which a human engages in a supervisory role - is required to reap the benefits. …

Empowering Traditional Industries With Digital Intelligence For Transformation And Upgrading, Jiyuan Zang, Huanyong Ji, Qingxue Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Traditional industries are the basic support and driving force for the high-quality development of the economy. Digital intelligence is an important lever for traditional industries to achieve the transformation of old and new kinetic energy and the leapfrogging of the global value chain. This study firstly deconstructs the rich connotations of digital intelligence from the perspectives of digitalization, networkization, and intelligentization. Secondly, it analyzes the transformation mechanism and various pathways through which digital intelligence impacts traditional industries. Thirdly, it analyzes the barriers faced by traditional industries in the process of adopting digital intelligence technologies. Finally, this study puts forward four …

Strategic Study On Leading Construction Of Modern Agricultural System By Technology Innovation, Yan Yan, Xurong Mei, Xiudong Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Technology innovation is the fundamental solution to build a modern agricultural system, and it is also an important support for building the large base, large enterprise, and large industry of modern agriculture and achieving the modernization of material equipment, technology, management, agricultural informatization, and sustainable resource utilization of agriculture. This paper explains the scientific concepts and logical relationships of the agricultural production system, industrial system and management system, which are the main components of a modern agricultural system. It emphasizes that ensuring food security, promoting industrial integration and upgrading, and cultivating leading enterprises are current key tasks. Nevertheless, from the …

Using Gamification To Enhance Mastery Of Network Security Concepts, Kevin Hilliard, Xiaohong Yuan, Kelvin Bryant, Jinsheng Xu, Jinghua Zhang

Journal of Cybersecurity Education, Research and Practice

Gamification has proven to be effective in engaging and encouraging people to work towards and achieve goals. Many students struggle to focus on schoolwork, due to a lack of interest, lack of understanding, or other factors unique to the student. Applying gamification elements to education can help engage these students in learning their course material and help them excel academically. This study examines the effectiveness of using gamification techniques to enhance the learning experience in college Computer Science courses. A video game application is utilized to review and reinforce cybersecurity concepts that students have already been taught in class. Previous …

Introduction To Programming And Applied Analytics Using Python, Matt Brown

ATU Faculty OER Books and Materials

This open electronic textbook is a collection of lecture notes, assignments, and additional background material for a junior level analytics course targeted for business students, it is free to use and copy. The text assumes readers have not had prior programming or computing courses, but have had at least one analytics course. The textbook differs from other textbooks because it serves a dual purpose, to first introduce to students the Python programming language and secondly to introduce analytics programming in Python. It is not meant to be a comprehensive book on the Python language or data analytics, rather a semester’s …

Green Finance Growth Prediction Model Based On Time-Series Conditional Generative Adversarial Networks, Aya Salama Abdelhady, Nadia Dahmani, Lobna M. Abouel-Magd, Ashraf Darwish, Aboul Ella Hassanien

All Works

Climate change mitigation necessitates increased investment in green sectors. This study proposes a methodology to predict green finance growth across various countries, aiming to encourage such investments. Our approach leverages time-series Conditional Generative Adversarial Networks (CT-GANs) for data augmentation and Nonlinear Autoregressive Neural Networks (NARNNs) for prediction. The green finance growth predicting model was applied to datasets collected from forty countries across five continents. The Augmented Dickey-Fuller (ADF) test confirmed the non-stationary nature of the data, supporting the use of Nonlinear Autoregressive Neural Networks (NARNNs). CT-GANs were then employed to augment the data for improved prediction accuracy. Results demonstrate the …

Essays On Artificial Intelligence (Ai) In Management, Bowen Zhou

Dissertations and Theses Collection (Open Access)

This dissertation comprises three essays that investigate the transformative potential of Artificial Intelligence (AI) in business.

Chapter 1 investigates the fundamental issue of how integrating AI within R&D activities influences a firm’s market value. We developed an "AI Index" using patent data and textual analysis. Interestingly, empirical results indicate a negative correlation between AI integration and market value. However, this does not suggest that AI is an unviable avenue for exploration. Further analysis of the boundary conditions reveals that complementary assets are crucial for successful commercialisation, highlighting that while AI adoption is costly, these assets significantly enhance its market value. …

Configurable Mirror Descent : Towards A Unification Of Decision Making, Pengdeng Li, Shuxin Li, Chang Yang, Xinrun Wang, Hau Chan, Bo An

Research Collection School Of Computing and Information Systems

Decision-making problems, categorized as single-agent, e.g., Atari, cooperative multi-agent, e.g., Hanabi, competitive multi-agent, e.g., Hold’em poker, and mixed cooperative and competitive, e.g., football, are ubiquitous in the real world. Although various methods have been proposed to address the specific decision-making categories, these methods typically evolve independently and cannot generalize to other categories. Therefore, a fundamental question for decision-making is: Can we develop a single algorithm to tackle ALL categories of decision-making problems? There are several main challenges to address this question: i) different decision-making categories involve different numbers of agents and different relationships between agents, ii) different categories have different …

The Confluence, Volume3, Issue 2, Full Issue

The Confluence

No abstract provided.

Large-Scale Research Infrastructure Empowers High-Quality Development Of Private Enterprises: Current Situation, Challenges, And Policy Recommendations, Lingling Zhang, Fuqiang Wang, Mingze Zhang, Zexia Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Private enterprises have become an important source of innovation in China’s economic development. Large-scale research infrastructure, as a crucial strategic support and innovation element for breaking through key technologies, provides a platform for the innovative development of private enterprises. At present, some large-scale research infrastructures in China, such as the China Spallation Neutron Source and the Shanghai Synchrotron Radiation Facility, have begun actively exploring mechanisms to serve private enterprises. These efforts have helped a number of private companies overcome critical technological bottlenecks and achieve original innovations. Nevertheless, in the current process of opening up large-scale research infrastructures to private enterprises …

Context-Driven: Logic And Pathway Of Industrial Intelligence To Accelerate Development Of New Quality Productive Forces, Ximing Yin, Yaxin Su, Tailun Chen, Jin Chen, Jiang Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The development of new productive forces hinges on industrial intelligence, which is driven by the deep integration of technological innovation and industrial innovation, and the accelerated construction of a modern industrial system. Industrial intelligence refers to the process of transforming traditional industrial development models and cultivating new pillar industries through the empowerment of intelligent technologies and data elements. It serves as a pivotal engine for promoting new industrialization and developing new productive forces. However, existing research has largely overlooked the critical theoretical and practical issues of how to leverage China’s ultra-large market and its vast contextual advantages to improve the …

Comparative Analysis And Insights Into R&D Mode Of Top Artificial Intelligence Companies In China And The Us, Xiyi Yang, Jia Jia, Xiaoyu Zhou, Shouyang Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) is currently one of the most prominent fields in the technology industry, with China and the US being two global centers for AI research and development. However, the two countries differ in their development levels of the AI industry. In particular, the emergence of ChatGPT in 2022 has sparked extensive discussions regarding the capabilities and competitiveness of Chinese AI companies. This study analyzes over 120 000 AI invention patents approved in the past five years in both China and the US. Firstly, it constructs a multidimensional index based on AI patent features to identify the top 10 …

Development Of Cyber Security Platform For Experiential Learning, Abhishek Vaish, Ravindra Kumar, Samo Bobek, Simona Sternad

Journal of Cybersecurity Education, Research and Practice

The cyber security education market has grown-up exponentially, with a CAGR of 13.9 % as reported by Data Intelo. The report published by the World Economic Fo- rum 2023 indicates a shortfall of 2.27 million cyber security experts in 2021 across different roles and hence manifest that Skill-based cyber security education is the need of the hour. Cybersecurity as a field has evolved as a multi-discipline, multi-stakeholder and multi-role discipline. Therefore, the need to address formal education with an outcome-based philosophy is imperative to address for a wider audience with varied past training in their formal education. With the Internet …

Evaluating The Effect Of Domain-Specific Large Language Models On Question And Response, Phillip D. Crippen

Electronic Theses and Dissertations

Large Language Models have emerged to great fanfare in the Information Technology market. Business and Information Technology leaders are currently exploring ways to apply these models to assist their organizations in executing business processes and generating innovation. Software vendors, consultants, and academics promote various approaches to making Large Language Models work effectively for business. However, little academic literature is available today that quantifies the degree of improvement possible with these domain-specific approaches over the standard capabilities of generalized Large Language Models.

The study seeks to quantify the benefits of one approach, Retrieval Augmented Generation. The study uses a collection of …

Demystifying The "Social Media Algorithm": The Legacy Of Surveillance Advertising And Platformization, Garrett Crites

Honors Projects

Recently, more individuals are becoming aware that they are being served content on social media platforms by automated means. Due to the lack of transparency, a colloquial understanding of the “social media algorithm” has emerged in popular discourse. To shed light on the real–world phenomena that these ideas surround, I look at the rise of surveillance advertising and the platformization of the internet in conjunction with the automated platform operations employed by large social media platforms like Facebook, YouTube, TikTok, and X. In doing so I provide a clearer idea of the colloquial “social media algorithm” to encourage the reader …

Experimental Methods In Predicting Market Drift And Other Portfolio Optimization Factors Using Graph Theory, Perry Harrison Zhang

Computer Science Senior Theses

No abstract provided.

An Alternative Approach To Data Carving Portable Document Format (Pdf) Files, Kevin Hughes, Michael Black

Journal of Cybersecurity Education, Research and Practice

Traditional data carving relies on the successful identification of headers and trailers, unique hexadecimal signatures which are exclusive to specific file types. This can present a challenge for digital forensics examiners when pitted against modern anti-forensics techniques. The interest of this study is file signature obfuscation, a technique which alters headers and trailers. This research will focus on the development of a new, proof-of-concept algorithm that analyzes content in segments based on unique elements found within the body of a file. The file type being targeted is the Portable Document Format (PDF) and this research is built upon previously successful …

Does Generative Ai Facilitate Investor Trading? Evidence From Chatgpt Outages, Qiang Cheng, Pengkai Lin, Yue Zhao

Research Collection School Of Accountancy

In this paper, we use ChatGPT outages to investigate whether investors rely on generative artificial intelligence (GAI) to perform trading-related tasks and the associated impact on stock price informativeness. We first document a significant decline in stock trading volume during ChatGPT outages and find that the effect is stronger for firms with corporate news released immediately before or during the outages. We further document similar declines in the short-run price impact, return variance, and bid-ask spreads, consistent with a reduction in informed trading during the outage periods. Lastly, we use trading volume changes during outages to construct a firm-level measure …

Ai Competency Acquisition Online? Engaging Undergraduate Students In An Ai 101 Course Through A Chatbot Workshop, Thomas Menkhoff, Lydia Teo

Research Collection Lee Kong Chian School Of Business

In recent years, digital transformation has dominated industries at an unprecedented rate. Alongside the proliferation of Artificial ntelligence (AI) technologies in the workplace, institutions of higher learning are experiencing an unprecedented push to integrate AI into the education ecosystem (Popenici & Kerr, 2017; Renz & Hilbig, 2020). AI in education (AIED) has the propensity to enrich teaching and learning in higher education by personalising students’ learning courses, automating assessment tasks, or providing24/7 access to learning resources (Karandish, 2021). According to estimates by the AI Market in the US Education Report, the AIEDmarket will grow at a CAGR of 47.77% during …

Stock Market Volatility In The United Kingdom: Simulating Post-Covid-19 Recovery, Bala A. Dahiru, Mohammed Shuaibu, Najibullah Hassanov

CBN Journal of Applied Statistics (JAS)

This paper investigates the time it would take for the FTSE-100 index to reach its post-COVID-19 peak. The paper utilises an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model that accounts for leverage effect and asymmetries. The preferred models amongst competing variants was the Autoregressive Moving Average (ARMA)-EGARCH(2,1) specification and was used to predict daily FTSE-100 data from 5th January 2000 to 21st June 2024. The empirical exercise showed that the COVID-19-induced financial crisis negatively affected the United Kingdom’s stock market performance. The results show that the FTSE100 index could reach its post-pandemic peak around 27th August, 2024 (two months after …

Dappscan: Building Large-Scale Datasets For Smart Contract Weaknesses In Dapp Projects, Zibin Zheng, Jianzhong Su, Jiachi Chen, David Lo, Zhijie Zhong, Mingxi Ye

Research Collection School Of Computing and Information Systems

The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. Despite the SWC Registry not being updated with new entries since 2020, the sustained development of smart contract analysis tools for detecting SWC-listed weaknesses highlights their ongoing significance in the field. However, evaluating these tools has proven challenging due to the absence of a large, unbiased, real-world dataset. To address this problem, we aim to build a large-scale SWC weakness dataset from real-world DApp projects. We recruited 22 participants and spent 44 person-months analyzing 1,199 open-source audit reports …

The Next 'Deep' Thing In X To Z Marketing: An Artificial Intelligence Driven Approach, Vincent Charles, Nripendra Rana, Ilias O. Pappas, Morten Kamphaug, Keng Siau, Kenth Engo-Monsen

Research Collection School Of Computing and Information Systems

The existing body of literature indicates a growing interest in research pertaining to the influence of artificial intelligence (AI) on marketing strategies, processes, and practices. However, further studies are required to fully unravel its complete potential and the implications it holds for practical application. The aim of this special issue on “The Next ‘Deep’ Thing in X to Z Marketing: An Artificial Intelligence-Driven Approach” is to explore the next frontiers and delve into the various facets of AI-driven marketing, shedding light on cutting-edge research and practical insights that can shape the future of the field. It also focuses on novel …

Factors Affecting Online Consumers' Cultural Presence And Cultural Immersion Experiences In Live Streaming Shopping, Lifu Li, Kyeong Kang, Yafei Feng, Anqi Zhao

Research Collection School Of Computing and Information Systems

This paper conducts research on the interaction between ethnic minority group (EMG) live streamers and online consumers, aiming to present how EMG live streamers’ appearance and interaction factors affect online consumers’ cultural experience during live streaming shopping. Based on the social presence theory and the immersion theory, this paper explores how EMG live streamers impact online consumers’ cultural experience, and it designs personal EMG knowledge as a moderating variable under specific social and cultural backgrounds. Through analysing 325 online questionnaires based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the study results support that both …

To Protect Or To Hide: An Investigation On Corporate Redacted Disclosure Motives Under New Fast Act Regulation, Yan Ma, Qian Mao, Nan Hu

Research Collection School Of Computing and Information Systems

China adopted amendments allowing companies to redact filings without prior approval in 2016. Leveraging this change as a quasi-nature experiment, we explore whether managers utilize redacted information to withhold bad information in the more lenient regulatory environment. Our investigation uncovers a significant shift in managerial behavior: Since 2016, managers incline to employ redactions to obscure negative news rather than safeguarding proprietary data. Furthermore, we find that the poorer firm performance and a higher cost of equity are associated with the redacted disclosures after 2016, suggesting that investors perceive an increase in firm-specific risk attributed to withholding bad news through redactions.

Digital Transformation: Two Sides Of A Coin, Tze K Koh

Research Collection College of Integrative Studies

It is of paramount importance to examine the intersection of digital transformation and sustainability. At the same time, there is a growing imbalance between digitalisation within the workforce and the pace at which sustainability awareness is picking up. Addressing this gap is crucial.