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Project Management Journal, Vol. 45, No. 2, 83–97
© 2014 by the Project Management Institute
Published online in Wiley Online Library
(wileyonlinelibrary.com). DOI: 10.1002/pmj.21404
Metaphors used and views expressed in all articles published in the Journal are the author’s alone and do not re ect PMI’s perspective.
83
PAPERS
ABSTRACT ■
Project selection problems are inherently complex
problems with multiple and often conflicting objec-
tives. The complexity of project selection problems
is due to the high number of projects from which
a subset (portfolio) has to be chosen. Various ana-
lytical methods, ranging from the simple weighted
sum to complex mathematical programming have
been proposed to solving these problems. We
propose an integrated approach for strategic and
sustainable project portfolio selection, which is
composed of two distinct but interrelated modules.
In the first module, we use the strategic planning
and sustainability concepts to select a set of prom-
ising projects. In the second module, we use a proj-
ect portfolio selection procedure to choose among
the promising projects identified in the first mod-
ule. Astructural equation model is used to analyze
and explain the relationships among different fac-
tors in the proposed framework. More specifically,
we investigate the effects of: (1) strategic level
performance on sustainability, post-implementa-
tion, and overall performance; (2) implementation
performance on post-implementation and overall
performance; (3) portfolio selection performance
on implementation and overall performance; and
(4) post-implementation performance on overall
performance. A case study in investment banking
is presented to demonstrate the applicability of
the proposed model and exhibit the efficacy of the
procedures and algorithms.
KEYWORDS: project portfolio selection;
structural equation modeling; sustainability;
strategic planning; financial service
A Comprehensive Framework
for Sustainable Project Portfolio
Selection Based on Structural
Equation Modeling
Kaveh Khalili-Damghani, Department of Industrial Engineering, Faculty of Industrial
Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
Madjid Tavana, Business Systems and Analytics Department, Lindback Distinguished Chair of
Information Systems and Decision Sciences, La Salle University, Philadelphia, PA, USA; Business
Information Systems Department, Faculty of Business Administration and Economics, University
of Paderborn, Paderborn, Germany
INTRODUCTION ■
The project selection problem is an important and recurring problem in
many organizations, and establishing a systematic and comprehensive
selection model is an important concern. However, project selec-
tion problems are inherently complex problems with multiple and
often conflicting quantitative and qualitative factors, such as business goals,
financial costs and benefits, and limitations in available resources. In spite
of the importance of project selection problem research, a framework that
integrates the strategic themes of the organization with the portfolio selection
procedure has rarely been presented in the project selection literature.
Selecting projects and optimizing the project portfolio that best aligns
with the organization’s strategic priorities is the essential focus of project
portfolio selection. Morris and Jamieson (2004) and Dey (2006) argue that
project portfolio management is a “bridge between strategy and opera-
tion” and enables organizations to transform the organization’s vision into
realities or successfully implement their corporate strategies. Iamratanakul,
Patanakul, and Milosevic (2008) have summarized the project selection
problem models into several groups, including: scoring methods, economic
methods (i.e., payback period, net present value, and internal rate of return),
simulation and heuristics models, mathematical programming methods,
and real options, among others. They reported that each methodology alone
does not address all of the aspects of project portfolio selection because each
method has its own advantages and disadvantages.
For example, although scoring methods are simple and easy to use, they
assume that scores are precise, which is not always the case. The economic
methods also have their own drawbacks. Payback period does not take time
value of money into consideration or net present value, and internal rate of
return requires data that may not be readily available or easy to estimate.
Simulation models are well-suited for selecting projects in dynamic orga-
nizations; however, they are not suitable for organizations that do not have
well-established standards and flow of information. Mathematical program-
ming models are widely used in the literature but they are not suitable for
alignment problems that are based on the central tendency approach. The