Business Commons^™

The Role Of Shopping Orientations And Intrinsic Experiential Value In Consumer's Willingness To Follow Embodied-Ai's Advice In Fashion Shoe Stores, Christina Soyoung Song, Ji Young Lee, Dooyoung Choi

STEMPS Faculty Publications

This study employs a synthesis of Intrinsic Motivation Theory with three shopping orientations, namely “adventure,” “idea,” and “personalized” shopping, in order to examine their potential influence on individuals' motivation towards shopping. We proposed that consumers’ experiential value of intrinsic enjoyment is an indispensable mediator that affects their willingness to follow EAI’s advice. The study offers novel insights into the way that consumers’ characteristics of influencing others’ clothing consumption affect their shopping motivations to find adventure and stimulation, keep up with new fashion trends and products information, and their preference to patronize stores and interact with store staff on a personal …

Digitalization Of Railway Transportation Through Ai-Powered Services: Digital Twin Trains, Salih Sarp, Murat Kuzlu, Vukica Jovanovic, Zekeriya Polat, Ozgur Guler

Engineering Technology Faculty Publications

Digitalization is a key concept that transformed the various industries through technologies like Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin (DT). Although innovations provided by the advancement of digitalization have paved the way for more efficient operations and products for transportation, the rail transportation sector struggles to keep up with the rest of the transportation industry, since trains are designed to last for decades, and the insufficient infrastructure investment leads to multiple railroad derailments across the globe. Therefore, the primary aim is to transform current railway systems into human-centric, adaptable, sustainable and future-proof networks, aligning with Industry …

Ai Fairness In Action: A Human-Computer Perspective On Ai Fairness In Organizations And Society, David De Cremer, Jack Mcguire, Jack Mcguire

Research Collection Lee Kong Chian School Of Business

Artificial intelligence (AI) systems are being increasingly adopted by society, governments, and organizations in various decision-making contexts. For example, organizations use AI systems to decide whether applicants can be considered for a job, whether bonuses and other rewards should be allocated, or whether promotions and further training need to be invested in. In fact, as AI is seen as an important catalyst of economic growth, organizations today seem to know no boundaries in their AI adoption efforts, making employees and society more dependent on and thus also more vulnerable to the decisions made by or in partnership with AI (De …

Crossing The “Valley Of Death”: How Climate Technology Entrepreneurs Navigate Relationships With Venture Capital Investors, Allison Lucas

Wayne State University Dissertations

As the world faces the ongoing and intensifying impacts of climate change, a group of innovative changemakers known as climate tech entrepreneurs (CTEs) are working on climate adaptation, mitigation, and/or resilience efforts by brining innovative technologies to the global market (UNFCC, 2018; Endeavor 2022). To realize the full potential of these technologies—tools, techniques, specialized knowledge or skillsets—they must be developed, deployed, and implemented at scale (IPCC, 2000). To do this, CTEs require external funding support, especially during a crucial period of the start-up lifecycle known as the “valley of death”. In this period between development and commercialization, production costs and …

Regional Price Index 2023, Department Of Primary Industries And Regional Development, Western Australia

Statistics

The 2023 Regional Price Index (RPI) is the eleventh State Government Index contrasting the cost of a common basket of goods and services at a number of regional locations to the Perth metropolitan region. The RPI is used as the basis for the construction of the public sector district allowance, and by the private sector when considering remuneration packages for remotely located staff.

The RPI provides an insight into differences in regional consumer costs. The 2023 RPI basket of 185 goods and services was priced in 39 regional centres around Western Australia.

The 2023 RPI results show that, overall, prices …

Towards Algorithmic Justice: Human Centered Approaches To Artificial Intelligence Design To Support Fairness And Mitigate Bias In The Financial Services Sector, Jihyun Kim

CMC Senior Theses

Artificial Intelligence (AI) has positively transformed the Financial services sector but also introduced AI biases against protected groups, amplifying existing prejudices against marginalized communities. The financial decisions made by biased algorithms could cause life-changing ramifications in applications such as lending and credit scoring. Human Centered AI (HCAI) is an emerging concept where AI systems seek to augment, not replace human abilities while preserving human control to ensure transparency, equity and privacy. The evolving field of HCAI shares a common ground with and can be enhanced by the Human Centered Design principles in that they both put humans, the user, at …

Graph-Partitioning Entity Resolution For Resolving Noisy Product Names In Ocr Scans Of Retail Receipts, Jose Ramon Ilagan, Joseph Benjamin R. Ilagan

Quantitative Methods and Information Technology Faculty Publications

In business intelligence for retail, it is critical to ensure consistent and unambiguous product dimension information. This is challenging, especially if an organization does not have full control over the source of either transaction or master data. Such lack of control is the case when brands rely on data provided directly by consumers through images of receipts. Product name strings obtained from the digitization of receipts often contain substitution, insertion, and deletion errors. These errors prevent product names from serving as a useful dimension for further analysis. This paper proposes a clustering-based approach to link error-laden product names to underlying …

Unlv Title Iii Aanapisi & Mcnair Scholars Institute Research Journal 2024, Jesica Godinez-Paredes, Kian Hassankhan, Apia Hickman, Robin Ruth Kee, Kevin Ayala Pineda, Briana Melendez, Kalli Ramos, Saturn L. Reyes, Fabian Leija, Selena Pepe, Silva Topchyan, Celeste Ainsley, Mayra Arzate, Jessica Balistreri, Zantana Ephrem, Mirella Jasso, Karl Panou, Nichole Pelaez, Miklo Alcala, Akshay Dave, Mey Mey Heng, Michael Finkle, Janessa Montenegro, Reynafe Naol Aniga, Victor Mejia, Angelica G. Diaz, Anayeli Flores-Garibay, Kari Lee Joe Goold, Samantha Hernandez, Lianelys Cabrera Martinez, Caitlin Reynolds, Kimberly N. Usbeck, Abdulrahman Alahdal, Angelica Diaz, Willaine Mae Kahano, Raquel Jackson, Cecia Ruiz-Hernandez, Kers Ung-Watson, Yessenia Henriquez, Vanessa Marie Booth, Alexia Brown, Darlyn Magana, Bianca Navarro, Nicholas Pereira, Gia Renemae Calip, Lucky Heng, Ralph Sagun, Lucas Abreu, Alexandra Maria Acosta, Tristan Benally, Cosset Hernandez Pena, Adrian Montenegro, Cierra Paaaina-Daquioag, Nicole Torosian, Tracy Fuentes, Julissa Martinez, Medina Mcallister, Michal Newhouse-Van Vlerin, Tiria Carr, Nima Abkenar, Isabella Aceituno, Yuhan Bi, Victoria Campos, Melika Cummings, Zachary J. Johnigan, Alexis Sotolongo-Marin

McNair Journal

Journal articles based on research conducted by undergraduate students in the AANAPISI, LSAMP, and McNair Scholars Program.

Table of Contents

About AANAPISI

Dr. Chris Heavey, Interim President

Dr. Keith Rogers, Vice President for Student Affairs

Ms. Zhanna Aronov, Associate Vice President for Retention & Outreach

Optimizing Sports Outcome Prediction Through Feature Engineering And Machine Learning, Vitor S. Freitas

Graduate Theses/Dissertations

The challenge of predicting the outcome of a team game lies in the high complexity and dynamics of the sports data. This thesis focuses on the aspect of using feature engineering and the genetic algorithm to predict the winner and the score of various sports events. Generally, it deals with how machine learning algorithms are combined with state-of-the-art feature engineering techniques in sports datasets derived from various sports disciplines. In this thesis, five different machine learning models have been applied, classification and regression trees (CART), random forest (RF), stochastic gradient boosting (SGB), eXtreme gradient boosting (XGBoost), and extreme learning machine …

A Tale Of Two Working Landscapes, Sage C. Sutcliffe

Graduate Student Theses, Dissertations, & Professional Papers

No abstract provided.

Assessing Performance Optimization Strategies In Cloud-Native Environments Through Containerization And Orchestration Analysis, Daniel E. Ukene

College of Graduate Studies: Theses & Dissertations

This thesis comprises three distinct, yet interconnected studies addressing critical aspects of web infrastructure management. We begin by studying containerization via Docker and its impact on web server performance, focusing on Apache and Nginx hosted on virtualized environments. Through meticulous load testing and analysis, we provide insights into the comparative performance of these servers, adding users of this technology know which webservers to leverage when hosting their webservice along alongside the infrastructure to host it on. Next, we expand our focus to examine the performance of caching systems, namely Redis and Memcached, across traditional VMs and Docker containers. By comparing …

Identifying Accessibility Improvement Opportunities For Global Environmental Communication Websites, Alicia Mason, Josh Compton, Sakshi Bhati

Faculty Submissions

Digital environmental information presented with low web accessibility reduces parti-cipation in environmental advocacy and information seeking behaviors for many people with disabilities, creating a consequential digital divide. We use WEB AIM computer automated analysis of web accessibility to assess the general accessibility of online environmental communication messages. Results show 95.3% of the popular websites in our sample had indicators of potentially critical accessibility errors. Our findings highlight the importance of addressing digital environmental information accessibility shortcomings so that educational, informational and persuasive environ-mental messages can increase environmental literacy of vulnerable populations and help to bridge the digital divide.

Why The Ethical Use Of Ai Matters For Your Career, Jack Mcguire, David De Cremer, Yorck Hesselbarth, Leander De Schutter

Research Collection Lee Kong Chian School Of Business

In the contemporary digital era, innovations such as artificial intelligence (AI) are profoundly transforming the business landscape (De Cremer, 2020). The buzz surrounding ChatGPT, coupled with recent assertions about the sentience of Google’s LaMDA, a large language model, underscore the prominence of chatbot technology in these advancements (Adamopoulou & Moussiades, 2020; Ryu & Lee, 2018; Tiku, 2022). Customer-oriented chatbots, an emergent application of this tech, offer unparalleled efficiency and cost-effectiveness, operating ceaselessly and responding to client inquiries in real time (Salesforce, Research, 2019). Yet, amidst these advantages lies an ethical conundrum. Customers cherish genuine human interaction and can become quickly …

Trust: The Feature That Vending Machines And Atms Share, But Simplygo Lacks, Sun Sun Lim

Research Collection College of Integrative Studies

The article discussed the intricacies of trust in the SimplyGo debacle and highlighted how the design of physical interfaces like vending machines and ATMs and digital interfaces from apps like Grab, Parking.sg and ShopBack have critical features to instil trust. People need to be reassured that their transactions have proceeded as they should, and thay have not been short-changed.

All In One Place: Ensuring Usable Access To Online Shopping Items For Blind Users, Yash Prakash, Akshay Kolgar Nayak, Mohan Sunkara, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Perusing web data items such as shopping products is a core online user activity. To prevent information overload, the content associated with data items is typically dispersed across multiple webpage sections over multiple web pages. However, such content distribution manifests an unintended side effect of significantly increasing the interaction burden for blind users, since navigating to-and-fro between different sections in different pages is tedious and cumbersome with their screen readers. While existing works have proposed methods for the context of a single webpage, solutions enabling usable access to content distributed across multiple webpages are few and far between. In this …

Archiving Digital Marketing: Examining Preservation Of Dynamic Content On The Web Through The Lens Of Online Advertisements, Christopher Rauch, Alex H. Poole, Travis Reid, Michele C. Weigle, Michael L. Nelson, Faryaneh Poursardar, Mat Kelly

Computer Science Faculty Publications

The transition to digital marketing has revolutionized advertising, reflecting and shaping societal norms and trends. The “Saving Ads” project addresses the challenges of preserving these ephemeral digital artifacts, essential for understanding the evolution of advertising and its socio-cultural impact. The initiative focuses on technical solutions for archiving dynamic online ads and enhancing access to these critical resources for future scholarship. By examining the preservation of online advertisements and suggesting improved approaches for archiving dynamic online content, this project contributes to the documentation of digital history.

Forecasting Crude Oil Price Using Multiple Factors, Hind Aldabagh, Xianrong Zheng, Mohammad Najand, Ravi Mukkamala

Computer Science Faculty Publications

In this paper, we predict crude oil price using various factors that may influence its price. The factors considered are physical market, financial, and trading market factors, including seven key factors and the dollar index. Firstly, we select the main factors that may greatly influence the prices. Then, we develop a hybrid model based on a convolutional neural network (CNN) and long short-term memory (LSTM) network to predict the prices. Lastly, we compare the CNN–LSTM model with other models, namely gradient boosting (GB), decision trees (DTs), random forests (RFs), neural networks (NNs), CNN, LSTM, and bidirectional LSTM (Bi–LSTM). The empirical …

Quantification Of Landside Congestion In Ports: An Analysis Based On Gps Data, Kumushini Thennakoon, Namal Bandaranayake, Senevi Kiridena, Asela K. Kulatunga

Computer Science Faculty Publications

Hinterland transport is a critical segment in maritime cross-border logistics, which links the end-users of global supply chains to the maritime segment. Truck-based hinterland transport is known to cause congestion in and around ports. This study aimed to quantify the congestion caused by trucks at the Port of Colombo, which has not been a subject of a systematic study. To this end, the study makes use of GPS data. In addition to revealing heavy congestion within the port, the study also reveals significant variations in congestion during different times of the day with the duration of journeys peaking from 1200hrs …

Investigating Inland Waterway Transport Through A Sustainable Development Perspective: A Case Study Of Magdalena River (Colombia), Natalia Calderón-Rivera

World Maritime University Ph.D. Dissertations

The development of transport systems significantly influences economies, growth, and welfare of populations. However, these systems can have negative consequences, such as water and air pollution, traffic congestion, noise, and biodiversity loss. To address these challenges, it is essential to implement strategies that mitigate negative effects while improving the environmental, social, and economic conditions of the population. In this regard, inland water transport (IWT) is globally recognized as a more sustainable transport alternative due to its high cargo load capacities and comparatively lower environmental and social impacts. In Colombia, the Magdalena River – the country’s most important river basin – …

Self-Exciting Point Processes In Real Estate, Ian Fraser

Theses and Dissertations (Comprehensive)

This thesis introduces a novel approach to analyzing residential property sales through the lens of stochastic processes by employing point processes. Herein, property sales are treated as point patterns, using self-exciting point process models and a variety of statistical tools to uncover underlying patterns in the data. Key findings include the identification and explanation of clustering in both space and time, and the efficacy of a temporal Hawkes process with a sinusoidal background in predicting home sale occurrences. The temporal analysis starts by employing the state of art techniques for time series data like regression, autoregressive, and autoregressive integrated moving …

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw

Faculty Publications

Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …

Expanding Australia's Defence Capabilities For Technological Asymmetric Advantage In Information, Cyber And Space In The Context Of Accelerating Regional Military Modernisation: A Systemic Design Approach, Pi-Shen Seet, Anton Klarin, Janice Jones, Michael N. Johnstone, Violetta Wilk, Stephanie Meek, Summer O'Brien

Research outputs 2022 to 2026

Introduction. The aim of the project was to conduct a systemic design study to evaluate Australia'sopportunities and barriers for achieving a technological advantage in light of regional military technological advancement. It focussed on the three domains of (1) cybersecurity technology, (2) information technology, and (3) space technology.

Research process. Employing a systemic design approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding of the interdisciplinary nature of defence technologies, identifying key areas for further exploration. The subsequent survey study, engaging 828 …

The Impact Of Environmental Policy On Renewable Energy Innovation: A Systematic Literature Review And Research Directions, Hiva Rastegar, Gabriel Eweje, Aymen Sajjad

Research outputs 2022 to 2026

Renewable energy innovations are imperative to tackle the climate change crisis. However, there is a gap in the literature regarding the effectiveness of environmental policies in promoting renewable energy innovations. To bridge this gap, we have adopted a systematic literature review process covering the period from 2005 to 2023. We identified and analysed 29 articles in our final sample. Further, we employ two levels of analysis (individual-policy and policy-mix levels) for analysing the extant research. Our findings show that fiscal incentives and emissions trading policies such as the European Union (EU) Emissions Trading System (ETS) consistently promote renewable energy innovations. …

Unleashing The Power Of Internet Of Things And Blockchain: A Comprehensive Analysis And Future Directions, Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Sandeep Jagtap, Mohammad Iranmanesh, Salem Alghamdi, Yaser Alhasawi, Yasanur Kayikci

Research outputs 2022 to 2026

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics …

Opportunities And Challenges Posed By Disruptive And Converging Information Technologies For Australia's Future Defence Capabilities: A Horizon Scan, Pi-Shen Seet, Anton Klarin, Janice Jones, Mike Johnstone, Helen Cripps, Jalleh Sharafizad, Violetta Wilk, David Suter, Tony Marceddo

Research outputs 2022 to 2026

Introduction: The research project's objective was to conduct a comprehensive horizon scan of Network Centric Warfare (NCW) technologies-specifically, Cyber, IoT/IoBT, AI, and Autonomous Systems. Recognised as pivotal force multipliers, these technologies are critical to reshaping the mission, design, structure, and operations of the Australian Defence Force (ADF), aligning with the Department of Defence (Defence)’s offset strategies and ensuring technological advantage, especially in the Indo-Pacific's competitive landscape.

Research process: Employing a two-pronged research approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding …

Outsourcing Voting To Ai: Can Chatgpt Advise Index Funds On Proxy Voting Decisions?, Chen Wang

Fordham Journal of Corporate & Financial Law

Released in November 2022, Chat Generative Pre-training Transformer (“ChatGPT”), has risen rapidly to prominence, and its versatile capabilities have already been shown in a variety of fields. Due to ChatGPT’s advanced features, such as extensive pre-training on diverse data, strong generalization ability, fine-tuning capabilities, and improved reasoning, the use of AI in the legal industry could experience a significant transformation. Since small passive funds with low-cost business models generally lack the financial resources to make informed proxy voting decisions that align with their shareholders’ interests, this Article considers the use of ChatGPT to assist small investment funds, particularly small passive …

Analyzing A Smartphone Battle Using Bass Competition Model, Maila Hallare, Alireza Hosseinkhan, Hasala Senpathy K. Gallolu Kankanamalage

CODEE Journal

Many examples of 2x2 nonlinear systems in a first-course in ODE or a mathematical modeling class come from physics or biology. We present an example that comes from the business or management sciences, namely, the Bass diffusion model. We believe that students will appreciate this model because it does not require a lot of background material and it is used to analyze sales data and serve as a guide in pricing decisions for a single product. In this project, we create a 2x2 ODE system that is inspired by the Bass diffusion model; we call the resulting system the Bass …

Molybdenum Versus Tungsten Based Polyoxometalates For Highly Effective Methylene Blue Removal, Roula Abi Saad, Ghassan Younes, Mohammad H. El- Dakdouki, Rami Al-Oweini

BAU Journal - Science and Technology

[SiW₁₂O₄₀]^4-(SiW₁₂) and [Mo₈O₂₆]^4- (Mo₈) were synthesized and characterized by Fourier Transform Infrared spectroscopy (FTIR). The prepared polyoxometalates were studied as potential adsorbents for the removal of methylene blue (MB) from an aqueous solution. Various operational parameters—contact time, adsorbent dose, initial dye concentration, pH, and temperature— were meticulously assessed by UV/Vis spectrophotometry to study its impact on the adsorption efficacy. An inverse relationship was observed between the percentage dye removal and the initial dye concentration, highlighting the complexes' superior adsorption capabilities under lower dye loads. The …

Optimization Of The Bio-Synthesis Of Magnesium Nanoparticles From Staphylococcus Haemolyticus: A Pilot Study, Mariam Bassam, Malak Mezher, Mahmoud Khalil

BAU Journal - Science and Technology

Nanotechnology is developing rapidly. This field has many influences in humans’ life. Nanoparticles (NPs) have many unique properties including the size, shape, morphology, and surface area. The synthesis of NPs could be achieved by three ways: physical, chemical, and biological. However, the biological synthesis of NPs has a priority on the other domains due to its safety and environmental friendship. In this regard, the main objective of this study was to synthesize magnesium (Mg) NPs from the bacterium S. haemolyticus which was isolated from the Lebanese wastewater. Different parameters were applied to detect the best conditions to produce the highest …

Volar V-Y Advancement Flaps In Reconstructing Fingertip Injuries, Sawsan Abiad

BAU Journal - Science and Technology

Fingertip injuries with exposed bones and joints require immediate or early closure for the preservation of function and avoidance of complications. The ideal procedure should maintain the length of the finger and cover the defect with non-tender, well-padded skin with normal sensation. The aim of this study was to evaluate the role of the different types of volar V-Y advancement flaps in reconstructing and resurfacing injuries of the fingertips at different levels and angles. Thirty patients (N=30) sustaining fingertip injuries of variable etiology and lost components, type III & IV according to Allen’s classification were divided into two groups (n=15) …