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Top1. Introduction
Maximizing an organization’s benefits is important in every business. Most decision makers invest in a project or activity that can pay back their investment. There are two types of benefits for investments, namely, monetary and non-monetary benefits. Usually, decision makers focus on the monetary benefits and neglect the non-monetary benefits because the non-monetary benefits are not easy to quantify, and it is complicated to integrate both monetary and non-monetary benefits for investment decisions. The most widely used indicator to measure the non-monetary benefits is the customer satisfaction (CSAT) score. The CSAT score can also be used to measure the satisfaction of employees of the company.
In large organizations, for example, banks or financial institutions, there are many investment projects to be evaluated and selected. This leads to the problem of Project Portfolio Selection (PPS). The project portfolio is a collection of projects where some are independent, mutually exclusive, and contingent projects. Many research works involve project portfolio evaluation and selection. Gutjahr and Reiter (2010) formulated a bi-objective project portfolio selection model under uncertainty which considers economic and strategic gains, and total overtime cost. Kornfeld and Kara (2011) proposed that project portfolio selection is a continuous improvement process. Nikkhahnasab and Najafi (2013) applied the net present value (NPV) to the PPS problem, which is solved by a metaheuristic algorithm. Orłowski et al. (2014) presented a project framework for the selection of methods and tools of project management in an IT support organization.
There are a number of financial techniques for investment decisions, for example, the net present value (NPV), internal rate of return (IRR), and benefit-cost ratio (BCR). When an objective of a decision is to optimize a financial indicator, the NPV is easier to use since the mathematical model has linear functions. In contrast, the IRR and BCR require nonlinear functions, and the mathematical model is more difficult to solve. To the best of the authors’ knowledge, there are no (or very limited) research works that explicitly and simultaneously consider both financial and non-financial indicators for PPS problems.
This research considers improvement-project portfolio selection in Thai Military Bank (TMB) Co., Ltd, which is a medium-sized bank in Thailand. Each year, TMB has more than 60 improvement projects, proposed by various sections. The characteristics of the project portfolio selection problem at TMB are summarized as follows:
- 1.
Projects are independent but not contingent. The selection of a project does not affect the selection of other projects;
- 2.
Some projects can generate significant financial benefits. These projects have positive NPV and a BCR that is greater than one;
- 3.
Some projects can generate non-financial benefits, which are employee satisfaction and/or customer satisfaction;
- 4.
Some projects can generate both financial and non-financial benefits;
- 5.
Investment, salvage value, benefits, operational and maintenance costs, MARR, and investment budget are uncertain and can be represented by triangular fuzzy numbers;
- 6.
Customer satisfaction and employee satisfaction are uncertain and can be represented by triangular fuzzy numbers;
- 7.
TMB has targets for customer satisfaction and employee satisfaction, to be achieved by the selected projects;
- 8.
TMB is interested in the NPV and BCR techniques for economic analysis of the projects;
- 9.
Since the data are fuzzy, fuzzy NPV and fuzzy BCR of each project can be calculated;
- 10.
TMB wishes to reduce the risk of having poor NPV and BCR of the entire project portfolio under uncertain situations.
Based on the characteristics of the PPS problem of TMB, this paper has the following objectives: