DISTRIXA: Design and Formalization of a Data-Intelligent Supply and Retail Transformation Framework for Resilient Distribution Networks

Itua Austin Omogiate

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 4, 1177-1206

Abstract: Retail and distribution networks increasingly depend on integrated data, analytics, digital systems, and adaptive operational processes to maintain product availability and service continuity under volatile demand and supply conditions. Existing research has separately examined artificial intelligence, demand forecasting, inventory optimization, digital supply-chain integration, omnichannel fulfillment, procurement digitalization, and resilient network design. However, these capabilities are frequently treated as distinct analytical or operational domains, limiting their use as an integrated mechanism for diagnosing and improving distribution performance. This paper introduces DISTRIXA, a Data-Intelligent Supply and Retail Transformation Framework designed to integrate these fragmented capabilities within a unified operational architecture. DISTRIXA organizes distribution transformation around four interdependent dimensions: DISTRIBUTE, OPTIMIZE, INTEGRATE, and EXECUTE (D.O.I.E.). The framework operationalizes these dimensions through four proposed analytical instruments: the Distribution Intelligence Index (DII), Fulfillment Efficiency Matrix (FEM), Operational Visibility and Adoption Score (OVAS), and Retail Execution Performance Index (REPI). Together, these instruments provide a structured mechanism for evaluating demand-to-distribution alignment, inventory and fulfillment efficiency, digital and cross-functional visibility, and the translation of operational capabilities into retail and commercial execution. The principal contribution of DISTRIXA is the formal integration of these dimensions into a closed-loop transformation architecture in which operational data are converted into diagnostic measures, decision priorities, interventions, and subsequent performance reassessment. Rather than treating artificial intelligence or digitalization as independent determinants of resilience, DISTRIXA positions analytical technologies within a broader socio-technical system incorporating operational processes, decision rights, information integration, physical network capabilities, and human governance. The paper develops the conceptual foundations, constructs, measurement logic, implementation procedure, and testable propositions of the framework. It further specifies an empirical validation agenda through which future studies can assess the reliability, validity, predictive capability, and generalizability of DISTRIXA across retail and distribution environments.

Keywords: supply-chain resilience; distribution intelligence; retail analytics; inventory optimization; digital transformation; fulfillment efficiency; operational visibility; retail execution; supply-chain analytics; DISTRIXA (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT261233041
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DOI: 10.32628/CSEIT261233041

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