Business Intelligence Commons^™

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 …

Fasttree-Guided Genetic Algorithm For Credit Scoring Feature Selection, Rashed Bahlool, Nabil Hewahi Prof., Youssef Harrath Dr.

Research & Publications

Feature selection is pivotal in enhancing the efficiency of credit scoring predictions, where misclassifications are critical because they can result in financial losses for lenders and exclusion of eligible borrowers. While traditional feature selection methods can improve accuracy and class separation, they often struggle to maintain consistent performance aligned with institutional preferences across datasets of varying size and imbalance. This study introduces a FastTree-Guided Genetic Algorithm (FT-GA) that combines gradient-boosted learning with evolutionary optimization to prioritize class separability and minimize falserisk exposure. In contrast to traditional approaches, FT-GA provides fine-grained search guidance by acknowledging that false positives and false negatives …

Decentralized Multi-Hop Federated Reinforcement Learning For Energy-Efficient And Secure Routing In Lorawan-Based Smart City Infrastructure, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

This paper proposes a decentralized hybrid framework that integrates Federated Learning (FL) and Reinforcement Learning (RL) to enable energy-efficient and secure multi-hop routing in LoRaWAN-based smart city networks. The method allows local model training at gateways and relay nodes, combining real-time routing decisions with privacy-preserving federated aggregation. Key metrics such as residual energy, link quality, and node trust levels are embedded into the reward function, and lightweight encryption plus differential privacy safeguard routing metadata. Simulation results demonstrate substantial gains in packet-delivery ratio, latency, network lifetime and resilience to adversarial attacks when compared to traditional routing protocols.

Faids: Artificial Intelligence Developmental Systems Framework For Predicting And Preventing Cyberattacks In Supply Chain Networks, Lordt Becklines

Research & Publications

Cyber threats and attacks disrupt and damages supply chain networks (SCNs), which are complex and interlinked. Current methods to predict and prevent cyberattacks are inadequate and ineffective. This research proposes an AI developmental systems framework (FAIDS) to protect SCNs from cyberattacks. The framework has four components: (1) an AI threat intelligence system; (2) an AI risk assessment system; (3) an AI decision support system; and (4) an AI learning and adaptation system. The framework is tested on a simulated retail SCN. The results show that the framework can predict and prevent cyberattacks and improve the network's resilience and security. The …

Using Social Media For Customer Knowledge Management In Developing Economies: A Systematic Review, Martinson Ofori, Omar El-Gayar

Research & Publications

Knowledge Management (KM) research has theorized that KM activities lead to better firm performance. The current view that there is more external knowledge than exists within organizations has resulted in a preference for customercentric approaches over traditional KM activities. Recent advances in technology has resulted in social media use as an avenue for knowledge creation from the social interaction between brands and their customers. Most research however explore social media’s impact on organizational knowledge in developed economies with little attention to developing economies where KM could be conceptualized differently. In this research, we analyze the extent to which social media …