Management Information Systems Commons^™

Managerial Mindset And Ai Adoption In Smes. A Systematic Review Of Cognitive, Behavioural, And Institutional Foundations, Shabin Muzibbhai Shaikh, Shivkanya Birla

European Management Studies

Purpose: This study examines how managerial mindset shapes the adoption of artificial intelligence (AI) in small and medium‑sized enterprises (SMEs). While existing research often highlights resource or capability constraints, this review shows that deeper cognitive, behavioral, and institutional foundations strongly influence how managers interpret AI and decide whether to engage with it.

Design, Methodology, and Approach: A systematic literature review (SLR) was conducted using established protocols. Thirty influential studies across managerial cognition, behavioral strategy, institutional theory, and technology adoption were identified, screened, and synthesized. Their insights were integrated into a multilayered conceptual model explaining how mindset shapes AI adoption in …

Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen

Honors College Theses

This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …

Large Language Models As A Detector For Political Deepfakes, Gracie L. Roberts

Honors Theses

The advancement of generative artificial intelligence has allowed for the creation of highly realistic political deepfakes, posing significant threats to democratic integrity and trust in governmental institutions. This study investigates the effectiveness of Large Language Models (LLMs) as detectors for political deepfakes, specifically exploring their ability to address the transferability, interpretability, and robustness limitations inherent in traditional detection systems.

The research was conducted in four steps including data collection, model selection, experimental testing, and evaluation. Two datasets were used in this study. The first dataset uses 833 fake images from the Political Deepfake Incidents Database (PDID) and 833 real images …

Investigating Machine Learning As An Anomaly Detection Tool In College Basketball, Eli G. Whitaker

Honors College Theses

Artificial Intelligence (AI) and Machine Learning (ML) are more commonly becoming tools that organizations use to prevent, detect, and deter fraud. Like other organizations, the amount of fraud that the National Collegiate Athletic Association (NCAA) faces is growing at an alarming rate. The primary issue involves athletes that undermine the integrity of their sport by purposefully playing below their true potential as participants in broader betting-related schemes. This thesis focused on Division 1 Men’s Basketball evaluates the viability of using supervised ML to detect anomalies in team performance over games in recent seasons. Anomalies, like red flags in the context …

Examining Digital Transformation In Maritime Logistics: A Big Data Perspective, Jiyoon An

Atlantic Marketing Association Proceedings

No abstract provided.

Exploration Of Dimensionality In Nfts, Blockchain, And Cryptocurrencies, George D. Shows

Atlantic Marketing Association Proceedings

No abstract provided.

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Business Process Redesign For Reducing Undelivered Product Return Losses In E-Commerce – An Explainable Ai Approach, Venkataraghavan Krishnaswamy, Deepa R, Himanshu Sharma

Journal of International Technology and Information Management

Product returns in e-commerce affect the profitability of the e-tailer. We adopt a two-stage approach to reduce undelivered product returns in an e-commerce firm. First, we develop and compare machine learning techniques—logistic regression, decision trees, Naïve Bayes, random forest, adaptive boosting, gradient boosting, stochastic gradient boosting, and deep neural networks—on their ability to predict undelivered returns. Next, we use explainable methods, such as relative importance and Shapley values, to develop insights from the best-performing machine learning model. Finally, we use these insights and the predictive model to redesign the firm’s order fulfillment and return processes. A Post-implementation evaluation of the …

Early Stem Impressions, Student Engagement, And Readiness For Digitalization, Myron Sheu

Journal of International Technology and Information Management

This study examines how early impressions of science, technology, engineering, and mathematics (STEM) shape business students’ learning behaviors and, ultimately, their readiness for organizational digitalization. Focusing on gender differences, subgroup identities, and perceived obstacles, the analysis uses survey data processed through correlation matrices, regression models, and subgroup heatmaps to trace the relationship between initial attitudes toward STEM and subsequent engagement patterns. The findings reveal consistent links between positive early impressions and active participation in structured STEM activities, along with gender-based distinctions in action preferences. Subgroup analyses further uncover nuanced patterns where stereotypes or perceived barriers correspond with reduced engagement. Collectively, …

The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …

Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu

Journal of International Technology and Information Management

While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …

Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati

Journal of International Technology and Information Management

With the power of social media transforming the way people connect and interact with each other, the dynamics of community formation on platforms such as X during major events are of crucial importance. While social media is an increasingly key driver in determining interactions, little is known about the online influence forming and developing fan communities in high-stakes events. This study looks into the development of user communities for datasets drawn from Kaggle on two of the world’s largest sporting events: the FIFA World Cup 2022, or football, and the T20 World Cup 2022, or cricket, with the aim of …

Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar

Journal of International Technology and Information Management

Blockchain technology has gained increasing attention as a digital infrastructure capable of improving transparency, trust, and coordination in complex, multi-organizational project environments. However, existing research on blockchain-enabled project management remains fragmented and industry-focused, providing limited guidance for organizational adoption and integration. This study addresses this gap through a systematic literature review of 29 peer-reviewed studies, following PRISMA guidelines, to examine how blockchain capabilities are incorporated into project management practices across industries and maturity stages.

Grounded in Resource-Based View and Coordination Theory, the analysis employs a feature-to-process mapping approach to link six core blockchain capabilities—decentralization, transparency, immutability, smart contracts, traceability, and …

The Value Of Personal Data Ecosystems: A Flemish Media Sector Case Study, Maarten De Mildt, Melanie Verstraete, Sofie Verbrugge, Didier Colle

Journal of International Technology and Information Management

Personal Data Stores (PDSs) have been proposed as a privacy-preserving approach to data sharing that increases individual control over personal data while enabling new forms of cross-organizational collaboration. This collaboration leads to the emergence of Personal Data Ecosystems (PDEs). Despite growing interest in PDEs, limited research has examined how the organizational and economic barriers identified in prior studies manifest in practice. This paper investigates these challenges through a case study of the Flemish media sector within the Solid4Media project, which explores the use of PDSs to support data sharing and personalization across media organizations. Using a qualitative research design, data …

Responsible People Analytics For Remote-Work Decisions: A Machine-Learning Benchmark For Classifying Perceived Productivity, Ruth Menjivar, Nima Molavi, Narges Mashhadi Nejad

Journal of International Technology and Information Management

This study examines whether employee-perception survey data can support responsible people-analytics decisions about remote-work productivity. Using the public New South Wales (NSW) Remote Working Survey 2021 (N=1,512), the study benchmarks statistical and machine-learning classifiers for self-reported perceived productivity classes (same, less, or more productive when working remotely relative to onsite work), not objective output, under default, class-weighted, and resampling protocols. Main evidence comes from 5×5 repeated stratified cross-validation using macro F1 and balanced accuracy with fixed model specifications. Class-balanced separability is modest. Random Forest, CatBoost, and LightGBM form a leading cluster with overlapping confidence intervals (macro F1 ≈0.51–0.52). Affective/well-being items, …

Towards Developing A Career Technology Fit Framework And Analyzing Its Influence On Work-Related Outcomes Among It Professionals, Gunjan Tomer

Journal of International Technology and Information Management

With growing attrition rate and significant demand for skilled IT professionals, the importance of studying their behaviour has become important for both academia and industry. Despite ample amount of research, there is still a gap between theory and practice. Based on our qualitative study conducted on Indian IT professionals we propose that technology allocation might contribute in understanding the behaviour of IT professionals. We found that IT professionals evaluate the technology allocated to them based on their individual career motives. This evaluation, either positive or negative, influences their job outcomes. Further, we explored the factors that make a technology preferable …

High Technology And The Developing State: The Arrival Of Supercomputers In India, Ramesh Subramanian

Journal of International Technology and Information Management

While India has made vast strides in information technology in the last few decades, its success is mainly attributed to its software, rather than its hardware sector. In fact, India’s attempts at developing computer hardware that can match international standards have largely been unsuccessful. A notable exception is its development of a series of supercomputers that match and exceed many international standards. This paper looks at an interesting period in India’s computing history – namely the 1980s and 1990s – focusing on its development of an indigenous supercomputer. During that period, supercomputers were thought to be the sole privy of …

An Active Learning Simulation For Teaching Hadoop In An Undergraduate Business Curriculum, Ruben A. Mendoza Ph.D., Liyuan Liu Ph.D.

International Journal for Business Education

This paper shows the effectiveness of an experiential learning activity for teaching core Hadoop concepts to undergraduate business students across all majors (Finance, Marketing, etc.). The complexity of Hadoop, with its distributed computing model and deep technical requirements, presents significant challenges in educational settings. The simulation was developed for an introductory course in a Business Intelligence & Analytics (BI&A) curriculum and adapted for use in a Database Management (DB) course. Results show significantly higher performance on questions centered on the topic in an online test preparation game with a total of 236 students in 11 different offerings of the course. …

Evolution Of A New Strategic Orientation In The Ai Era: Exploring The Determinants Of Ai Orientation, Sreelakshmy Geethakumari

Dissertations

The field of AI has undergone significant evolution over the past few decades. While AI is heralded as one of the most transformative technologies, scholars caution that its strategic impact may still not be fully realized. Given the strategic importance of AI in today's firms, it is essential to consider AI as a strategic orientation and understand its determinants in detail. Our study examines AI Orientation, defined as a firm's deliberate application of AI technologies to achieve its strategic objectives. Drawing on multiple theoretical perspectives, this study investigates the determinants that shape a firm’s AI orientation. This study employs a …

Investigating The Relationship Between Noun Classes And Plant Folk Taxonomy In Chasu Language Of Kilimanjaro Region In Tanzania, Peter Rabson Mziray

Journal of Humanities and Social Sciences

The current study investigates the relationship between noun classes and plant folk taxonomy in Chasu (G 22). The study focuses on two objectives: the first objective is to describe the plant folk taxonomy in Chasu and the second objective is to determine the relationship between noun classes and plant folk taxonomy in Chasu. Data were collected from rural villages in Same and Mwanga districts by using free listing, field interviews (jungle-walk-and-identify), and written texts containing Chasu plant names. The findings reveal that Chasu folk taxonomy reflects different ethnobotanical categories; including a unique beginner which is mmea/mimea ‘plant(s)’, and three life …

Skill Evolution In The Age Of Ai-Utilizing Text Analytics For Skill Gap Analysis To Prepare Women For Leadership Roles, Blenda G. Mutuma, Marcelline Ouma, Beth Kanyiri

Communications of the IIMA

ABSTRACT
The rapid advancement of Artificial Intelligence (AI) is transforming the global workforce, presenting both opportunities and challenges for leadership development, particularly for women. As AI automates routine tasks and redefines skill requirements, there is a growing demand for uniquely human capabilities such as emotional intelligence, creativity, and strategic thinking, qualities that are inherently strong and often highly associated with women. Research indicates that women typically score higher in emotional intelligence, particularly in areas such as empathy and relationship management, which are critical for effective leadership (Goleman, 2020). Furthermore, studies by McKinsey & Company (2022) highlight that gender-diverse leadership teams, …

Organizational Metamorphosis: When Artificial Intelligence Transforms Companies Into New Economic Life Forms, Allan M. Glass

All Dissertations

Traditional theories of organizational change fall short in explaining how artificial intelligence (AI) transforms organizations. This grounded theory study, based on interviews with 34 organizational leaders, identifies a novel phenomenon: organizational metamorphosis - the irreversible transformation of organizations into fundamentally new entities through deep integration with AI as a cognitive partner.

The metamorphosis process unfolds in three phases. Individual Awakening occurs when leaders experience powerful interactions with AI, prompting a rapid shift from skepticism to advocacy. Once a critical mass of leaders undergo this shift, it initiates Organizational Restructuring, characterized by reimagined work design, boundary dissolution, and altered temporal rhythms. …

Book Review: Building A God, Carl Lee Tolbert

The Journal of Values-Based Leadership

No abstract provided.

Case Study & Lessons Learned: Creation And Pilot Of A Regional Small Business Accelerator And Cybersecurity Assessment Program, Stanley Mierzwa, Randall D. Pinkett, Willie Mae Veasey, Debra Price

Center for Cybersecurity

Startup companies and originated small businesses are an essential aspect of our nation’s economy, contributing to many organizations that aim, in some cases, to become larger enterprises. As a small business is in the mode of sustaining and growth, minimizing cybersecurity and business resilience threats may not be front and center on the minds of these entities. This paper will provide a case study background about a project and effort – the New Jersey Cybersecurity Regional Cluster (NJCRC) - that has contributed significant outreach to New Jersey small businesses to provide free cybersecurity risk assessments to help small businesses prepare …

Perceptions Of Artificial Intelligence In Healthcare: A Qualitative Study Among Physicians And Nurses In Florida, Aaron Miri

MUSC Theses and Dissertations

This investigation will leverage participant focus group interviews with 32 clinicians (16 nurses / 16 physicians) to study what, if anything, is inhibiting AI adoption across the hospital. Specific physicians will be sourced across the key service lines of primary care, oncology, cardiology, behavioral health, and emergency department medicine, as these tend to be patient volume driven and thus have the maximum amount of potential for positive impact leveraging AI. Nurses in these same departments will be assessed to analyze if there is a similarity or difference between the nursing and physician AI adoption barriers.

Understanding The Determinants Of Blockchain Adoption: An Empirical Study, Amarpreet Kohli, Nihar Kumthekar, Piyush Shah, Rebecca Jauch

Journal of International Technology and Information Management

Blockchain technology (BT) has the potential to enhance security and robustness of transactions through a distributed ledger bookkeeping process. This study employs technology-organization-environment (TOE) framework and threat-rigidity theory (TRT) to examine whether perceived disruption caused by COVID-19 pandemic significantly impacted the adoption of BT, and inclination to adopt BT in the US. The COVID-19 pandemic provided a unique backdrop, as it affected businesses across all industries, sizes, and geographies. Results show a non-significant effect of perceived pandemic disruption on the current stage of BT adoption and intention to adopt BT. However, disruption readiness positively influences the current stage of BT …

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 …

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.