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Asnaashari, E (2011) A holistic conceptual model for managing construction logistics in building projects: the case of Iran, Unpublished PhD Thesis, School of Science and Technology, Nottingham Trent University.
- Type: Thesis
- Keywords: complexity; construction method; information management; interview; Iran; logistics; material management; purchasing; scheduling; site layout
- URL: http://irep.ntu.ac.uk/id/eprint/342/
Logistics, as a factor that affects the total cost of a product, has attracted attention in many industries. However, construction is behind other industries, such as manufacturing and food, in terms of obtaining value through application of effective logistics management. Some specific characteristics of the construction industry, such as fragmented supply chain, indirect employment, temporary location and matchless products, have prevented organisations utilising logistic management in their projects. In construction, logistics is about the mobilisation of different types of resources to feed the project with the required materials and components at the right time, in the right place, right quantity and right quality. To do so, a new approach to construction logistics should be undertaken that respects the special characteristics of this industry. This research aims to develop a conceptual model based on the current practice of construction logistics in building projects. This model, in addition to complying with the special characteristics of the construction industry, is also adapted to the economic, cultural, technological and environmental specifications of the building sector in Iran. The complexity mindset is adopted in this research which allows considering a construction logistics system as a whole and the system may assert an aggregate behaviour. This approach is called holism and investigates the performance of complex adaptive systems. The study is focused on the Iranian construction industry as the main source of data collection. To achieve the aim and objectives of the research, a literature review was followed by qualitative and quantitative data collection. This research adopted the complementarity approach that uses qualitative and quantitative strategies in a way that complement each other. In the qualitative phase, twenty four open-ended interviews were conducted with construction practitioners who work in the building sector in Iran. Gathered data was analysed using NVivo. This involves codifying the textual data to find themes, categories and relationships. The results of the first phase were rich and exploratory and explained opinions, norms and attitudes. Based on the results of the first phase, a questionnaire with ten sections was designed to investigate different aspects of construction logistics from wider perspectives by conducting a survey on a large sample. The data gathered from the second phase were analysed in a descriptive manner to provide statistical information about the present practice of construction logistics in the Iranian building sector. The final product of this research is a holistic conceptual model that has four subsystems: (a) environmental factors (b) operational factors, (c) commercial factors, and (d) managerial factors. Each subsystem has several agents that are different functions of logistics in a building project. The environmental factors include project size and location, peak working seasons, resource conservation and weather conditions. The operational factors discuss technological matters, construction methods, new materials, waste and transportation. The commercial factors encompass the supply chain, finance, economic conditions, material costs, estimation, supplier selection, packaging, purchasing, inspection, and material quality. The managerial factors cover material management, warehousing, material handling, information management, scheduling, delivery, organisation, personnel, knowledge, culture and site layout designing. All of these functions are integrated under the topic of construction logistics model. The model also illustrates the relationships among agents of the system. The developed model, in addition to technical factors, has paid attention to soft factors such as culture, economy and knowledge. The model is adaptable to changing environments and elements may be added or deleted from the system whenever required.