Supply chain operations of construction industry including road projects in disaster regions
results in exceeding project budget and timelines. In road construction projects, supply chain with
poor performance can affect efficiency and completion time of the project. This is also the case of
the road projects in disaster areas. Disaster areas consider both natural and man-made
disasters. Few examples of disaster zones are; Pakistan, Afghanistan, Iraq, Sri Lanka, India,
Japan, Haiti and many other countries with similar environments. The key factors affecting
project performance and execution are insecurity, uncertainties in demand and supply, poor
communication and technology, poor infrastructure, lack of political and government will,
unmotivated organizational staff, restricted accessibility to construction materials, legal hitches,
multiple challenges of hiring labour force and exponential construction rates due to high risk
environment along with multiple other factors. The managers at all tiers are facing challenges of
overrunning time and budget of supply chain operations during planning as well as execution
phase of development projects.
The aim of research is to develop a Multiple Linear Regression Model (MLRM) and a Rule Based
Decision Support System by incorporating various factors affecting supply chain management of
road projects in disaster areas in the order of importance. This knowledge base (KB)
(importance / coefficient of each factor) will assist infrastructure managers (road projects) and
practitioners in disaster regions in decision making to minimize the effect of each factor which will
further help them in project improvement. Conduct of Literature Review in the fields of disaster
areas, supply chain operational environments of road project, statistical techniques, Artificial
Intelligence (AI) and types of research approaches has provided deep insights to the
researchers. An initial questionnaire was developed and distributed amongst participants as pilot
project and consequently results were analysed. The results’ analysis enabled the researcher to
extract key variables impacting supply chain performance of road project. The results of
questionnaire analysis will facilitate development of Multiple Linear Regression Model, which will
eventually be verified and validated with real data from actual environments. The development of
Multiple Linear Regression Model and Rule Based Decision Support System incorporating all
factors which affect supply chain performance of road projects in disastrous regions is the most
vital contribution to the research. The significance and novelty of this research is the
methodology developed that is the integration of those different methods which will be employed
to measure the SCM performance of road projects in disaster areas.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19403 |
| Date | January 2019 |
| Creators | Anwar, Waqas |
| Contributors | Not named |
| Publisher | University of Bradford, Faculty of Engineering and Informatics |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Thesis, doctoral, PhD |
| Rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. |
Page generated in 0.0019 seconds