Empirical Framework for Tackling Recurring Project Management Challenges Using Knowledge Management Mechanisms

The construction industry is termed as a highly risky industry, considering the alarming rate of recurring challenges and its negative impact on the economy, man, and his environment. This study aimed to develop a framework using knowledge management in tackling recurring problems in the Nigerian construction industry. The data instrument was a well-designed questionnaire directed at construction professionals. Out of the 80 questionnaires distributed, the study used 78 (97.5%) questionnaires for analysis. The study identified corruption, inadequate planning measures, and reduced government policies as the main factors influencing recurring project management challenges in the Nigerian construction industry. The study revealed significant knowledge management strategies used by Nigerian construction professionals, which include the use of emails, face-to-face interactions, and brainstorming sessions. The knowledge management strategies are further classified into data mining based, traditional based, and mobile technology-based knowledge management strategies in the construction sector. The primary benefits associated with knowledge management mechanisms in the construction industry include high growth performance, aid decision making, and innovation in the construction sector. Further classification showed that these benefits are mainly performancebased and collaboration and learning-based benefits. The study proposed a knowledge management framework for tackling recurring challenges in the Nigerian construction industry. Some recommendations drawn from the findings and conclusions can be found in this study

Built environment life cycle process and climate change

In order to design and realise an efficient built environment life cycle with focus on climate change mitigation and adaptation, it is necessary to carry out exhaustive investigations of all the decision and processes that form it. The efficiency level of the considered built environment life cycle depends on a great many micro, meso and macro factors. The authors of this paper participated in the different EU projects related with built environment and climate change [Linking European, Africa and Asian Academic Networks on Climate Change (LEAN CC), etc.]. One of the LEAN CC project’s goals was to develop a Model and Intelligent System of Built Environment Life Cycle Process for Climate Change Mitigation and Adaptation. The presented Model and Intelligent System enables one to form up to 100 million alternative versions. Intelligent system allows one to determine the strongest and weakest points of each project and its constituent parts. In order to demonstrate the micro, meso and macro factors that influence the efficiency of the built environment in climate change mitigation and adaptation processes, the Model and Intelligent System will be considered as an example.(undefined