European Journal of Science, Innovation and Technology

Organizational Models for Managing Parallel Construction Projects in Regional Development

2026-11-10T20:59:27+02:00

This article addresses the problem of managing parallel construction projects within the context of regional development. The study was conducted as a systematic review of scientific publications and aims to identify organizational mechanisms that ensure the coordinated implementation of a large number of interrelated construction projects. Particular attention is given to the transformation of management challenges when moving from individual projects to construction programs and project portfolios. A comprehensive analysis of contemporary approaches to resource coordination, project management office organization, portfolio management, and digital integration of construction processes was carried out. The findings indicate that as the number of simultaneously implemented projects increases, the primary management challenge gradually shifts from the level of individual projects to the level of inter-project coordination. It is demonstrated that neither complete project autonomy nor rigid centralized control can fully address the complexities of a multi-project environment. Based on the analysis, the author developed the Hybrid Multi-Site Construction Management Model, which combines centralized construction portfolio coordination, autonomous site-level management, and a unified information environment. The proposed model extends existing perspectives on organizational principles for multi-project construction management and may be applied in the planning and implementation of regional development programs. The article may be of interest to construction company executives, project management professionals, regional development program managers, and researchers in the field of construction management.

An Investigation of the Phonemic Articulation Errors Committed by Grade Three Regular Learners with Kikamba Reading Difficulties

2026-11-10T21:01:36+02:00

This research sought to investigate the phonemic mis-articulation errors committed by grade three regular learners with Kikamba reading difficulties. A grade three learner who is considered a typical reader should not commit major articulation errors while reading written work. Unfortunately, there are regular grade three learners who make serious articulation errors during reading of written materials, such learners require to be identified and aided so that they can advance with their studies. This paper was guided by the objective: to investigate the phonemic mis-articulation errors committed by grade three regular learners with Kikamba reading difficulties. The study employed the Phonological Awareness theory, was cross-sectional and utilized a descriptive research design. A sample of purposively selected 25 grade three learners was used in this research. The investigation employed purposive sampling method to select the sample. The data was collected by tape recording articulations of the participants and later analyzed to determine the phonemic articulation errors they were committing while reading Kikamba language. Descriptive statistics which entail measures of central tendency and correlation were used to describe and summarize the data.

Methodological Foundations of AI Readiness in Enterprise Operations and Analytics Functions

2026-11-10T21:03:28+02:00

The article examines AI readiness as a methodological issue for enterprise operations and analytics functions. Its relevance follows from the gap between AI adoption ambitions and the organizational conditions required for reliable decision support, operational intelligence, and governed automation. The aim is to define the foundations that make enterprise AI usable beyond isolated pilots. The study applies comparative analysis, source analysis, conceptual synthesis, typologization, and analytical generalization to ten recent academic sources on AI readiness, AI capability, governance, data governance, and business value. The analytical part identifies three connected foundations: data and infrastructure reliability, organizational and process maturity, and decision-oriented governance. The article proposes an implementation logic that treats readiness as a managed operating condition measured through data quality, model lifecycle control, adoption behavior, accountability, and feedback loops. The results are applicable to enterprises preparing AI-enabled analytics, anomaly detection, forecasting, and operational decision support.