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DECISION MATRIX FOR FUNCTIONAL EVALUATION OF PROJECT MANAGEMENT AUTOMATION
MOHANTY, SAMEER

2006, MS, University of Cincinnati, Engineering : Civil Engineering.
The construction industry is one of the largest and fastest growing industries in the USA as well as in most parts of the world. The US department of commerce reported that construction industry spending peaked all-time in the month of November 2005 with an annual spending of over $1160 billion. It presently employs over 10 million people. However, increasing demand for better services at lower costs resulting in greater market share, profits and client satisfaction compel the construction industry to focus on intangible parameters that affect its competitiveness. As a tool to aid construction management (CM) and other project activities it encompasses, scores of PM software applications have been written over the years. However, with increasing availability of a broad range of such applications, organizations are generally disoriented and uncertain with respect to which applications and tools are best suited to their business goals. Furthermore, with project management systems becoming more and more complex with time and encompassing sophisticated practices for better management and control, selection of such tools has become increasingly difficult. Amidst all of this technology development, investments and implementation towards CM efficiency, it is imperative that the project executives and senior management, who are also the primary users of such applications, be facilitated a simple decision support system that acts as a framework towards justifying investments, setup and installation, utilization and upgrade of project management applications. This study, through a broad preview of the past, current and futuristic CM application functioning, its developmental history and an industry-wide survey aims to demarcate current IT and software solutions trends in the US construction industry. Some of the pertinent issues addressed include critical business areas, investments, deployment, expenditures and work environment. Categories include computing, networking and telecommunications hardware and software, purchase, technology transfer and maintenance modalities, personnel, training and HR as well as preferences and globalization issues. Assimilated survey data has been analyzed to create a decision model that shall guide project personnel and owners step-by-step in understanding and evaluating their priorities and constraints, tasks and budgets, communications, networking and other stipulations in order to formulate a strategy that allows them to center upon software applications that functionally and financially best suit their enterprise and operations. Conclusions and recommendations that are elicited from such data analysis and the formulated decision matrix are based on statistical relevance of observed trends and logical inferences thereof.
Dr. Sam Salem (Advisor)
228 p.

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MOHANTY, S. (2006). DECISION MATRIX FOR FUNCTIONAL EVALUATION OF PROJECT MANAGEMENT AUTOMATION. (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

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MOHANTY, SAMEER. "DECISION MATRIX FOR FUNCTIONAL EVALUATION OF PROJECT MANAGEMENT AUTOMATION." Electronic Thesis or Dissertation. University of Cincinnati, 2006. OhioLINK Electronic Theses and Dissertations Center. 27 Apr 2015.

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MOHANTY, SAMEER "DECISION MATRIX FOR FUNCTIONAL EVALUATION OF PROJECT MANAGEMENT AUTOMATION." Electronic Thesis or Dissertation. University of Cincinnati, 2006. https://etd.ohiolink.edu/

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