Management Information Systems Commons^™

Responsible Ai: Applications And Ethical Considerations, Emuesiri Oduaran, Skye Ese Oduaran

Communications of the IIMA

As artificial intelligence (AI) rapidly transforms industries and societies, its applications present both immense opportunities and significant ethical challenges. This paper explores the concept of Responsible AI, emphasizing the importance of integrating ethical considerations into AI development and deployment. It examines a range of AI applications, from healthcare and finance to autonomous systems, highlighting their potential to drive innovation while also raising concerns about bias, privacy, accountability, and job displacement. The paper evaluates the ethical principles that should guide AI design, including transparency, fairness, privacy protection, and human oversight. Furthermore, it critically analyzes the current landscape of AI governance, identifying …

Enhancing Sarcasm Detection With Contextual Factors For Improved Model Robustness Based On Bmlrf, Walter O. Yodah, Alice S. Mataruse, Never O. Kangara

Communications of the IIMA

Detecting sarcasm in text remains a critical yet challenging task in natural language processing (NLP). Despite significant advances through deep learning, particularly the use of transformer-based architecture like BERT, sarcasm detection models still face challenges in achieving high accuracy. A major limitation lies in their insufficient incorporation of contextual awareness, including conversational history, social inter- actions, emotional cues, and cultural factors. To address this, this paper proposes the BERT with Meta-Feature Logistic Regression Fusion (BMLRF) model, which in- tegrates sentence-level embeddings from a pre-trained transformer with meta-features capturing social, emotional, and cultural contexts. The model also leverages multi-turn dialogue history …

Adoption Of Blockchain Technology In Beverage Supply Chains: Drivers, Benefits, And Challenges In The Coca-Cola And Bodyarmor Sport Water Recall Case, Alexander Adams Jr., Nima Molavi

Communications of the IIMA

The beverage industry faces growing scrutiny as demands for transparency and accountability intensify. In today’s digital landscape, companies must prioritize enhanced traceability to ensure product safety, comply with regulations, maintain consumer trust, and safeguard brand reputation. This research investigates blockchain technology as a potential solution to these challenges, emphasizing its capacity to decentralize data, improve traceability, and accelerate response times during safety recalls.

The study traces the evolution of food safety regulations and analyzes current traceability practices and technological innovations within the beverage sector. Using the Coca-Cola and BODYARMOR Sport Water recall as a case study, this study examines drivers, …

An Empirical Investigation Into The Effect Of Brain Drain “Japa Syndrome” On Agile Practitioners Developing Healthcare Information Systems Software In Nigeria, Yazidu Buba Salihu, Julian M. Bass, Gloria E. Iyawa

Communications of the IIMA

Within the software engineering context, agile approaches encourage customer collaboration, iterative development, and flexibility. However, the mass exodus of highly skilled professionals, known as the “brain drain” or "Japa Syndrome," has emerged as a significant challenge, especially in Nigeria. This phenomenon has particularly impacted agile software development practitioners by undermining project continuity, knowledge transfer, and team dynamics. This study empirically examines the effect of brain drain, “Japa Syndrome,” on agile practitioners developing healthcare information systems software in Nigeria. It employed a qualitative, multi-method approach to gather empirical data from 13 agile practitioners in Nigeria’s healthcare information systems sector. The study …

Exploring Ai Corporate Governance Through The Lens Of Dynamic Capabilities, Albert Samigullin, Paul Dooley

Communications of the IIMA

As AI technologies evolve, organizations must continuously adapt their governance structures to address emerging challenges related to transparency, ethics, and regulatory compliance. Given the rapid pace of AI advancements, traditional governance approaches may not be sufficient to ensure responsible AI oversight while maintaining competitiveness. This research examines AI corporate governance through the lens of Dynamic Capability (DC) Theory, focusing on how organizations can develop the capacity to sense technological and regulatory shifts, seize opportunities, and reconfigure governance mechanisms to align with AI-driven transformation. Through a literature review and the development of an AI Corporate Governance Framework grounded in DC Theory, …

Sustainable Enterprise Architecture: Embedding Circular Economy And Lifecycle Thinking In It Strategy, Sai Chandrahas Kaveripakam, Frank Lin

Communications of the IIMA

This paper explores the integration of sustainability into traditional Enterprise Architecture (EA), proposing a novel Sustainable Enterprise Architecture (SEA) model, and uses the fashion industry to illustrate the efficacy of the proposed model. The SEA framework systematically embeds environmental, social, and economic sustainability principles into corporate strategy and operational practices. This research also addresses the significant intention-action gaps among consumers and organizations in sustainability practice. Through vivid case examples, such as MUD Jeans' leasing model and Pact's affordable circular apparel, this research highlights practical pathways for operationalizing sustainability. By leveraging Circular Economy (CE) and Product Life Cycle (PLC) concepts, SEA …

Table Of Contents, Ciima 2024 Proceedings

Communications of the IIMA

Table of Contents IIMA conference proceedings 2024

Ethical Dilemmas And Solutions In The Adoption Of Ai Technologies In Supply Chain, Mohammad Reza Sadeghi Moghadam, Taha Mansouri, Iman Ghasemian Sahebi

Communications of the IIMA

As organizations increasingly adopt artificial intelligence (AI) technologies to optimize their supply chain operations, they face a growing set of ethical challenges that demand careful consideration. This study explores the key ethical dilemmas and potential solutions in implementing AI within the supply chain context, drawing insights from in-depth interviews with a diverse group of experts. The thematic analysis of the interview data revealed four primary ethical dilemmas: algorithmic bias and discrimination, lack of transparency and explainability, privacy and data ethics issues, and the socioeconomic impacts of AI-driven automation. To address the dilemmas, this study identified various mitigation strategies, including techniques …

Integrating Values In Dutch Music Copyright: A Q Methodology Study, Nerko Hadziarapovic, Pascal Ravesteyn, Marlies Van Steenbergen

Communications of the IIMA

This research investigates the integration of stakeholders' values into the digital frameworks of Collective Management Organizations (CMOs) within the Dutch music copyright system. Utilizing Q methodology, the study captures diverse perspectives from composers, lyricists, publishers, and CMO representatives on values, value tensions, norms, and system requirements. A pilot study with four experts tested data collection methods and refined the study design for a larger, follow-up study involving 30 participants. Preliminary findings, based on factor analysis of participant rankings of 30 statements, reveal two distinct perspectives: one focused on "Fairness and Accountability," emphasizing trust-building and equitable treatment, and the other on …

A Non-Invasive Mental Health Risk Predictor Using Machine Learning Models Utilising Music Listening Habits

Communications of the IIMA

Globally, there has been a rise in mental health issues such as insomnia, anxiety, and depression. However, the stigma that is associated with such a diagnosis makes individuals not want to seek help. Recent research has explored the relationship between music listening habits and mental health status, offering promising insights into the potential of leveraging this data for predictive modelling. This research proposes a non-invasive approach that integrates features extracted from music listening patterns including demographic and lifestyle data to build machine learning models that detect mental health conditions such as insomnia, depression and anxiety levels The results show that …

Are Emojis The New Words? A Sentiment Analysis Of Social Media Brand Conversations, Yashodhan Karulkar, Dev T. Vora, Siddharth Vaddepalli, Yash Thakur

Journal of International Technology and Information Management

Emojis have become an increasingly important aspect of consumer-brand interactions in the Indian subcontinent. However, the impact of emoji use on brand image and mental health remains underexplored, particularly in emerging economies like India, where structured research on this topic is limited. To address this gap, the present study analyzes over 4,600 consumer tweets related to 19 prominent brands across eleven industries. Using VADER sentiment analysis, the research develops a metric to assess consumer sentiment and brand engagement in relation to emoji usage. The findings indicate that effective integration of emojis contributes to positive consumer sentiment and enhanced brand engagement. …

On Legislating Cybercrime: Nigerian, South African, And United Kingdom Perspectives, Sagwadi Mabunda, Roland Akindele

Communications of the IIMA

Cybercrime has evolved to be a menacing challenge to all the countries of the globe. Consequently, it has become necessary for effective laws and policies to be enacted and implemented globally. This paper aims to review the cybercrime legislation of three jurisdictions: Nigeria, South Africa, and the United Kingdom (UK), to examine how each country has conceptualised and legislated cybercrime. The paper begins with a discussion on the definitional considerations necessary for legislating cybercrime. It draws from the Council of Europe Convention on Cybercrime (Budapest Convention) as the primary international convention on cybercrimes, to analyse some of the specific provisions …

Augmenting Legal Expertise: The Role Of Ai In Enhancing Human Capabilities In Legal Services

Communications of the IIMA

This study explores the dynamics of digital transformation within the legal services

industry, focusing on the integration of artificial intelligence (AI) to augment

human capabilities. By examining the interplay between institutional norms and

technological innovations, this research aims to understand how AI disrupts

traditional legal practices while maintaining ethical standards and promoting

equitable access to justice. Employing a qualitative content analysis, this research

analyzes data from international news sources spanning April 2011 to March 2021.

The study examines the roles of key industry actors, identifies barriers to digital

adoption, and explores the implications of digitalization for competition within the

legal …

The Intricate Dance Between Stars And Words: A Review Of Customer Reviews In Tourism

Communications of the IIMA

Travel and tourism industries rely heavily on customer reviews from past travelers as an invaluable source for informing potential travelers’ decisions. Thanks to the internet, reviews are an invaluable source for both quantitative star ratings as well as qualitative text comments that evaluate travel experiences. In this paper we analyse this complex relationship between text comments and their associated star ratings; using existing literature we highlight their interplay to give an overall picture of customer satisfaction. Factors that influence ratings and comments include both intrinsic (service quality, staff behavior) and extrinsic aspects such as location or price. Sentiment analysis through …

Comparing Funders' Altruism Versus Self-Interest: Leveraging The Context Of Crisis, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

While reward-based crowdfunding has widespread popularity, the motivations driving funders, balancing self-interest and altruism, have remained puzzling. Prior research has been constrained by examination methods and produced mixed findings regarding the weight of altruism versus self-interest among funders. Our study takes a fresh perspective, delving into funder behavior amid a major crisis—the tumultuous backdrop of the COVID-19 pandemic. Our findings reveal that funders not only display an increased willingness to contribute but also significantly amplify their contributions, particularly to projects in crisis-affected regions, irrespective of external incentives like rewards. This underscores the prevalence of altruistic motives among funders in challenging …

Artificial Intelligence And Environmental Sustainability: Review And Research Directions, Troy Strader, Yu-Hsiang (John) Huang, Yu-Ju Tu

Journal of International Technology and Information Management

Environmental sustainability is one of the most important and complex issues currently facing our global society. One solution to some aspects of this problem could come from artificially intelligent systems and data analytics methods. The objective for this study is to identify the range of recently published research that addresses issues involving the convergence of artificial intelligence (AI) and environmental sustainability. A systematic literature review produced a sample of 62 journal articles from 2018-2024 that were each categorized into one of six research themes that included studies of AI and the ways in which it impacted natural resources, energy and …

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 …

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 …

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 …

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 …

How Can Researchers Be Influenced To Comply With Guidelines Of Research Data Management?, Rowena Van Houwelingen, Guido Ongena, Pascal Ravesteyn

Communications of the IIMA

How come Open Science is a well-shared vision among research communities, while the prerequisite practice of research data management (RDM) is lagging? This research sheds light on RDM adoption in the Dutch context of universities of applied sciences, by studying influencing technological, organizational, and environmental factors using the TOE-framework. A survey was sent out to researchers of universities of applied sciences in the Netherlands. The analyses thereof showed no significant relation between the influencing factors and the intention to comply with the RDM guidelines (p-value of ≤ .10 and a 90% confidence level). Results did show a significant influence of …

Risk Identification And Mitigation In Agile Software Re-Engineering: A Case Study, Chiara Fasching, Peggy Gregory, Nicholas Mitchell, Charlie Frowd

Communications of the IIMA

Legacy software is becoming increasingly common, and many companies nowadays are facing the challenges associated with this phenomenon. In certain circumstances, re-engineering is the only logical way to deal with legacy software. Such projects, by their very nature, are subject to a wide variety of risks. The aim of this study was to begin building the basis of a risk framework that will support future re-engineering projects within Agile (Scrum) environments. An interpretive case study approach has been followed, where the case study was the first phase of a re-engineering process, with the method of analysis being inductive and reflexive …

Enhancing Email Spam Detection Through Ensemble Machine Learning: A Comprehensive Evaluation Of Model Integration And Performance, Najah Al-Shanableh, Mazen S. Alzyoud, Eman Nashnush

Communications of the IIMA

Email spam detection and filtering are crucial security measures in all organizations. It is applied to filter unsolicited messages; most of the time, they comprise a large portion of harmful messages. Machine learning algorithms, specifically classification algorithms, are used to filter and detect if the email is spam or not spam. These algorithms entail training models on labelled data to predict whether an email is spam or not based on its features. In particular, traditional classification machine learning algorithms have been applied for decades but proved ineffective against fast-evolving spam emails. In this research, ensemble techniques by using the meta-learning …

Cyber Threat Intelligence Sharing In Nigeria, Muhammad Abubakar Nainna, Julian Bass, Lee Speakman

Communications of the IIMA

Cybersecurity challenges are common in Nigeria. Sharing cyber threat intelligence is essential in addressing the extensive challenges posed by cyber threats. It also helps in meeting regulatory compliance. There are a range of impediments that prevent cyber threat intelligence sharing. We hypothesise that we want to maximise this cyber threat intelligence sharing to resist malicious attackers. Therefore, this research investigates factors influencing threat intelligence sharing in Nigeria's cyber security practitioners. To achieve this aim, we conducted research interviews with 14 cyber security practitioners using a semi-structured, open-ended interview guide, which was recorded and transcribed. We analysed the data using an …

The Moderating Role Of Cost And Convenience On The Relationship In The Utaut Model To Adopt E- Payment Services, Essia Ries Ahmed, Brahim Zirari, Imane Tabet Derraz

Journal of International Technology and Information Management

Many emerging economies are on the brink of a major digital revolution as a result of the disruptive and game-changing wave of digitization that aims to create a financial ecosystem that will make the transition from a cash-based economy to a cashless (digital) economy the easiest way by making reliable and secure networks, Seamless payment solutions, ensuring large transactions at lightning speeds are a reality. Most studies using UTAUT are cross-sectional, capturing data at a single point in time. Longitudinal studies are needed to observe changes in behavioural intention and actual adoption of e-payment services over time, particularly in response …