@article{(International Science Index):https://publications.waset.org/pdf/10003073,
	  title     = {Using Analytic Hierarchy Process as a Decision-Making Tool in Project Portfolio Management},
	  author    = {D. Danesh and  M. J. Ryan and  A. Abbasi},
	  country	= {},
	  institution	= {},
	  abstract     = {Project Portfolio Management (PPM) is an essential
component of an organisation’s strategic procedures, which requires
attention of several factors to envisage a range of long-term outcomes
to support strategic project portfolio decisions. To evaluate overall
efficiency at the portfolio level, it is essential to identify the
functionality of specific projects as well as to aggregate those
findings in a mathematically meaningful manner that indicates the
strategic significance of the associated projects at a number of levels
of abstraction. PPM success is directly associated with the quality of
decisions made and poor judgment increases portfolio costs. Hence,
various Multi-Criteria Decision Making (MCDM) techniques have
been designed and employed to support the decision-making
functions. This paper reviews possible options to enhance the
decision-making outcomes in organisational portfolio management
processes using the Analytic Hierarchy Process (AHP) both from
academic and practical perspectives and will examine the usability,
certainty and quality of the technique. The results of the study will
also provide insight into the technical risk associated with current
decision-making model to underpin initiative tracking and strategic
portfolio management.},
	    journal   = {International Journal of Economics and Management Engineering},
	  volume    = {9},
	  number    = {12},
	  year      = {2015},
	  pages     = {4194 - 4204},
	  ee        = {https://publications.waset.org/pdf/10003073},
	  url   	= {https://publications.waset.org/vol/108},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {International Science Index 108, 2015},
	}