Management Information Systems Commons^™

A Systematic Literature Review On Resilient Digital Transformation, Examining How Organizations Sustain Digital Capabilities, Thira Chavarnakul, Li Da Xu, Zhuming Bi, Achyut Shankar, Gaurav Dhiman, Wattana Viriyasitavat, Danupol Hoonsopon

Information Technology & Decision Sciences Faculty Publications

In an era marked by relentless technological shifts and market volatility, digital transformation (DT) alone is insufficient. Organizations must develop Resilient Digital Transformation (RDT)—the organizational capabilities required to sustain DT over a medium-term horizon—to navigate these challenges effectively. This study primarily aims to propose a guideline for fostering RDT. Drawing on the PRISMA guidelines and a systematic review of 77 peer-reviewed papers, this study identifies and synthesizes key targets and drivers across three core pillars: Technology, Organization, and External Environment. These elements collectively foster organizational resilience. Specifically, this study highlights how adaptability, innovation, and scalability form the technological underpinnings of …

2024-2025 Academic Year Annual Report, Collier Library

Collier Library and Information Services

No abstract provided.

Modeling Healthcare Managerial And It Sophistication, Gary Hackbarth, Teuta Cata

Journal of International Technology and Information Management

Sophisticated healthcare managers understand that managing information and selecting technology are two related but separate skill sets. Information Technology Governance (ITG) allows healthcare organizations to deal with complex issues, compete effectively, and support patient needs by integrating managerial and IT sophistication to improve business performance. An organizational model that merges IT and managerial sophistication by improving ITG to forecast business outcomes must grasp the intricacies of technology to acquire, manage, and utilize information technology in alignment with business strategies. The proposed model differentiates between internal and external IT management strategic thinking, emphasizing the critical need to govern IT effectively by …

A Bounded Custom Gpt Structures Operational Knowledge For Small-Industry Decision Support, Ikhwan Arief, Alizar Hasan, Nilda Tri Putri, Hafiz Rahmann

Knowledge Engineering and Data Science

Small manufacturing and craft-based firms increasingly use Generative Artificial Intelligence (GenAI) through public chat interfaces, low-cost tools, and informal experimentation. However, these firms often make operational decisions with incomplete records, tacit owner knowledge, fragmented spreadsheets, and limited managerial capacity. Under such conditions, open-ended chatbots may generate fluent but unsafe recommendations by overlooking missing information, contradictory evidence, feasibility constraints, and implementation constraints. This study presents Asisten Cerdas Industri Kecil as a bounded Custom GPT artifact for operational diagnosis, priority selection, and short-horizon action planning in small industries. Using a Design Science Research approach, the study develops a documented artifact corpus comprising …

Predicting Crises On The African Frontier Stock Markets With Investor Sentiment Indicators: A Machine Learning Approach, David Korsah, Lord Mensah

Journal of International Technology and Information Management

This study examined the predictive ability of machine learning algorithms in identifying crises within African stock markets. The study employed seven distinct machine-learning models, analyzing historical stock prices from eight stock markets, three major sentiment indicators, and the exchange rates of local currencies against the US dollar, with each data spanning from May 1, 2007, to April 1, 2023. Extreme Gradient Boosting (XGBoost) emerged as the most effective algorithm for predicting crises. Historical stock prices and exchange rates were identified as the most critical features for prediction. On the sentiment side, investors’ perceptions of potential volatility on the S&P 500, …

A Conceptual View Of Data For Decision-Oriented Databases: A Knowledge-Driven Approach, Sung-Kwan Kim, Wenjun Wang, Seunghyun Kim

Journal of International Technology and Information Management

Typical database design goes through three levels of data modeling: conceptual modeling, logical modeling, and physical modeling. In particular, conceptual modeling is important since it captures and documents user data requirements. Conceptual modeling serves as a blueprint for designing a database by defining information content to be included in a database. Presently, decision-oriented databases have no well-accepted conceptual modeling approach to apply. While some use conceptual modeling approaches for transaction-oriented databases such as the ER (Entity-Relationship) model, they are not well-suited for decision-oriented databases. It is hard to map from the ER Model to decision-oriented data models. Others attempt to …

Preventive Health Care Information Seeking Behaviors Among Baby Boomers In Taiwan, Alexander N. Chen, Michael J. Rubach, Tracy Suter, Hsin Ke Lu, Mark E. Mcmurtrey

Journal of International Technology and Information Management

Preventive health care is widely acknowledged as one of the most effective ways to reduce medical costs and enhance people's health. Preventive health care information (PHCI) is a crucial component. This study examines the PHCI-seeking behaviors of Taiwanese baby boomers. The study found some support for the idea that the preferred media used influenced the likelihood of Information seeking behavior. People with good health conditions were found to be more likely to seek PHCI, while people with greater health care needs sought out PHCI less frequently. The study examined social influences, which were found to be important. Three different types …

Pedagogy In The Age Of Ai: Exploring Generative Ai For Higher Education, Alison Munsch Phd

Journal of International Technology and Information Management

Generative Artificial Intelligence (AI) presents transformative opportunities for higher education, enabling personalized learning, enhanced student engagement, and efficient pedagogical practices. This tutorial-style article guides educators in integrating generative AI into their classrooms through hands-on activities, practical strategies, and reflective exercises. It explores the capabilities of AI tools such as ChatGPT, their applications across disciplines, and the ethical considerations for their use. By cultivating critical thinking and fostering student readiness for AI-driven futures, this article underscores the transformative potential of generative AI in higher education with an emphasis on the academic areas of business analytics, information systems, and computer science.

Surviving And Thriving In The Hybrid Cloud: A Review Of The Current Cloud Computing Landscape, Peter Munsch, Alison Munsch

Journal of International Technology and Information Management

Background and Purpose

Both academic and industry institutions have increasingly migrated essential services to public cloud providers (e.g., Microsoft, AWS, Google) with mixed outcomes. Some industry leaders attempted to fully replace their on-premises data centers with public cloud services, a move not advised without thorough performance and cost analyses (Potel, 2023). Despite some organizations pulling back from the “Cloud First” strategy, the public cloud services market continued to grow, with revenue increasing by approximately 20% year-over-year since 2020 and surpassing half a trillion dollars in 2022 (IDC Worldwide Semiannual Public Cloud Services Tracker, 2H 2022). Cloud technologists suggested that hybrid …

Predicting Global Healthcare Supply Chain Delays: A Machine Learning Approach Leveraging Country-Level Logistics Metrics, Jeevan Sai Gali, Nima Molavi, Sepideh Alavi

Journal of International Technology and Information Management

In global healthcare logistics, ensuring the timely delivery of medical commodities is critical, particularly in low- and middle-income countries characterized by infrastructural limitations and operational uncertainties. This research introduces an advanced, data-driven predictive framework designed to forecast delivery delays by synthesizing granular, internal shipment-level data from the USAID Global Health Supply Chain Program (GHSC-PSM) with external country-level logistics capabilities indicators derived from the World Bank’s Logistics Performance Index (LPI). Rather than relying on retrospective trend analyses, this study employs machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP) to detect …

Interactive Visualization Workflows For Mitigating Analytical Uncertainty, Kaustav Bhattacharjee

Dissertations

This dissertation takes a process-centric and stakeholder-first perspective for handling analytical uncertainty: the form of uncertainty that confronts data analysts' insight-generation processes in high-consequence decision-making scenarios. The cost of an incorrect decision when data is used for movie recommendations as opposed to when personal data is used to drive insights or when data-driven modeling is used to drive real-time decisions for maintaining the health of a grid are vastly different in terms of consequences. This dissertation looks at analytical uncertainty in two real-world scenarios: i) how sensitive information leakage can be prevented during the open data release process with data …

Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang

Journal of Cybersecurity Education, Research and Practice

Additive manufacturing (AM) has been applied to automotive, aerospace, medical sectors, etc., but there are still challenges such as parts’ porosity, cracks, surface roughness, intrinsic anisotropy, and residual stress because of the high level of thermal gradient. It is significant to conduct the modeling and simulation of the AM process and achieve quality products. Digital Twin (DT) can help AM with forecasting defects/errors through simulation and real-time process monitoring. DT is a concept of Industry 4.0, and its digital structure reflects the real-time behaviors of a cyber-physical or physical system. This paper introduces the progress of DT applications in AM, …

Volume 7 (2024) Artificial Intelligence And Responsibility, Arwa Alnajashi, Danielle Derise, Philip L. Frana, David Mcgraw, Amanda Sawyer, Tatjana Titareva, Raafat Zaini, Allie Zombron

International Journal on Responsibility

The seventh volume of the International Journal on Responsibility (IJR) arrives at a crucial moment in the evolution of artificial intelligence and its integration into our academic and social fabric. As we witness the rapid advancement and deployment of AI systems across various domains, this special issue examines the multifaceted dimensions of responsibility surrounding AI technology, with a particular focus on its role in higher education and broader societal implications.

The articles in this volume contribute to our understanding of responsibility through diverse lenses, from classroom implementation to ethical design considerations. Together, they fulfill IJR’s central mission of exploring “Who …

Imagining The Future Of Records Management: An Analysis Of The Srikandi In Indonesia Through Documentation Studies, Suprayitno Suprayitno, Rahmi Rahmi, Zulfatun Sofiyani

Proceedings from the Document Academy

The SRIKANDI application, a cornerstone of Indonesia's digital records management initiative, embodies the nation's commitment to modernizing governance through electronic systems. This study employs Niels Windfeld Lund’s Complementary Documentation Analysis Model to dissect SRIKANDI'S evolution (diachronic analysis) and its current state (synchronic analysis), offering a comprehensive understanding of its role in Indonesia's e-government landscape. Diachronically, SRIKANDI'S development reflects a strategic shift from fragmented, standalone applications towards a unified, interoperable platform, as mandated by Presidential Regulation No. 95 of 2018. This transition aims to streamline government processes, reduce redundancy, and enhance budget efficiency. Synchronically, SRIKANDI is evaluated as a digital platform …

Potential Impact Of Artificial Intelligence On Small And Medium Enterprises Innovation In The Eu: A Perspective From Poland, Malgorzata Wilczynska, Alina Walenia, Artur Dabek, Daniel Salabura, Halina Kot

Markets, Globalization & Development Review

The development of small and medium-sized enterprises is a complex process that requires the use of all approaches to achieve success. In this regard, finding opportunities to use artificial intelligence in such companies is of great importance. The study aims to assess how this technology affects the innovation and financial performance of small and medium-sized enterprises. To draw the main conclusions, the implementation of artificial intelligence at Polish enterprises, including in the context of their financial performance, namely the level of return on assets and the level of debt, was analysed. The study showed that the introduction of artificial intelligence …

Evaluating The Perceived Benefits Of Education In Revenue Cycle Management And The Impact On Medical Claims Reimbursement, Jessica L. Miller

Student Dissertations

Efficient Revenue Cycle Management (RCM) is essential for healthcare organizations to ensure timely and accurate reimbursement for medical claims. The research problem was the significant inadequacies in RCM process in medical billing that has resulted in financial burdens imposed on providers, patients, and the organizations that provide medical services. There are clearly identified educational gaps in RCM that contribute to claim denials, delays, and revenue loss, underscoring the need for robust training programs. The purpose of this study was to explore the perceived impact of education in RCM on medical claim reimbursement outcomes within the U.S. healthcare system. The study …

Esg Ratings In The Mining Industry: Factors And Implications, Mahelet G. Fikru, Jennifer Brodmann, Lili Eng, J. Andrew Grant

Economics Faculty Research & Creative Works

While previous research explores the relationship between ESG ratings, firm size, and financial outcomes, there is a lack of comprehensive analysis comparing multiple ESG ratings within the mining industry. This gap is crucial given the increasing focus on ESG in mining operations and its potential impact on company performance. Based on proprietary financial and ESG ratings data from 200 mining companies, this study investigates the relationship between two different ESG ratings and firm characteristics. We compare ESG-rated firms with unrated firms in terms of firm size, and financial performance indicators, and explore country-level patterns in ESG ratings. Findings reveal that …

Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey

All Theses

This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …

The Practical Adoption And Application Of Blockchain Technology Within The Beverage Industry, Alexander Adams Jr

Electronic Theses, Projects, and Dissertations

Abstract

The beverage industry is facing heightened scrutiny as the demand for transparency and accountability reaches new heights. In the age of information technology, companies must prioritize enhanced traceability to ensure product safety, comply with government regulations, maintain customer trust, and protect brand integrity. This thesis explores the potential of blockchain technology as a solution to these challenges, focusing on its ability to decentralize data, improve traceability, and expedite response times during safety recalls. The research provides an overview of the evolution of food safety regulations, beginning with the first establishment by Upland Sinclair, and examines current traceability practices and …

Flexible Vs. Dedicated Technology Choice In The Presence Of Multiproduct Subscription Programs, Liling Lu, Onur Boyabatli, Sarah Yini Gao

Research Collection Lee Kong Chian School Of Business

Recently, automotive manufacturers have started offering multi-car subscription programs that give customers access to a menu of car models with possibility of switching between the models. The maintenance and depreciation costs during the program are borne by the manufacturers before the cars are sold in the pre-owned market. This paper studies how offering such a subscription program shapes the firm’s flexible versus dedicated technology choice and capacity investment decisions. We consider a two-product firm that makes these decisions under uncertain demand in a single subscription period. The firm faces two types of demand based on which product is requested at …