ASSESSING THE FACTORS CAUSING PROJECT COMPLETION DELAYS IN THE CONSTRUCTION SECTOR OF OMAN USING SEM-PLS

Purpose: The objectives of the study were to investigate the causes of the delays to analyze the factors causing the construction delay in Oman and to investigate the effects of such delays. Design/methodology/approach: To carry out this study 210 samples were collected through a well-defined questionnaire from the construction stakeholders viz. the consultants, contractors, and the clients who were selected on a random sampling basis. Smart PLS for Structural Equation Modeling (SEM) technique was used to analyze the data to obtain the formative measurement models, the structured model, and the goodness of fit. Findings: The results of the study reveal that the client-related factors, equipment-related factors, and material related factors have a significant impact on the completion delay in construction projects. The findings of the study also revealed that the Client related factors were – Delay in providing services, Delayed decision-making process, Allocation of insufficient time. Equipment related factors were – Existing low productive equipment, Unskillful Equipment operator, Breakdown of equipment and Outdated equipment; Material related factors were – Delay in supply of raw materials, Non-availability of materials, Change of materials during construction, Non-availability of accessories and Damaged materials. Research limitations/Implications: The present study covers the stakeholders of the construction projects from selected regions only. The future studies can be extended to other projects and other regions as well. Social implications: The study suggested that the clients’ cooperation especially in providing the contractors with the necessary equipment, facilities, and sufficient time will avoid such delays of the construction projects in Oman. Originality/Value: Only very few have examined the completion delay of the construction projects in Oman using SEM-PLS and it is a first-hand study of its kind and the results will be useful to the stakeholders.

Ontology Re-Engineering: A Case Study from the Automotive Industry

For over twenty-five years Ford Motor Company has been utilizing an AI-based system to manage process planning for vehicle assembly at its assembly plants around the world. The scope of the AI system, known originally as the Direct Labor Management System and now as the Global Study Process Allocation System (GSPAS), has increased over the years to include additional functionality on Ergonomics and Powertrain Assembly (Engines and Transmission plants). The knowledge about Ford’s manufacturing processes is contained in an ontology originally developed using the KL-ONE representation language and methodology. To preserve the viability of the GSPAS ontology and to make it easily usable for other applications within Ford, we needed to re-engineer and convert the KL-ONE ontology into a semantic web OWL/RDF format. In this article, we will discuss the process by which we re-engineered the existing GSPAS KL-ONE ontology and deployed semantic web technology in our application.