Análisis de los principales aspectos que afectan a la decisión de selección y planificación de cartera de proyectos.

  1. Fernández Carazo, Ana
  2. Gómez Núñez, Trinidad
  3. Pérez García, Fátima
Revista:
Rect@: Revista Electrónica de Comunicaciones y Trabajos de ASEPUMA

ISSN: 1575-605X

Año de publicación: 2011

Volumen: 12

Número: 1

Páginas: 123-140

Tipo: Artículo

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Otras publicaciones en: Rect@: Revista Electrónica de Comunicaciones y Trabajos de ASEPUMA

Resumen

Investment activities play an important role in any economic organization. That is why the problem of project portfolio and scheduling is one of the most important managerial tasks necessary to ensure the survival of any organization. In order to make a good selection or distribution of resources among a set of candidate projects in accordance with existing budget constraints, the decision process has to take into account several aspects, such as the multiplicity of objectives and constraints, the time factor, and the different relationships among projects (dependences, synergies, precedence, complementarities, etc.). In this study, we review in depth and separately the most important contributions made by the main authors in the field of project portfolio selection, describing the development of the approaches to address those aspects and highlighting their advantages and disadvantages. This paper concludes with the presentation of our own proposal: a flexible model that considers all those aspects simultaneously and solves the project portfolio selection and scheduling problem for any given time horizon and for any type of organization.

Referencias bibliográficas

  • J.P. Martino, Research and development project selection (Wiley Series in Engineering & Technology Management, New York, 1995).
  • A.D. Henriksen and A.J. Traynor, A practical R&D project selection scoring tool, IEEE Transactions on Engineering Management 46, 2 (1999) 158-170.
  • M.W. Dickinson, A.C. Thornton and S. Graves, Technology portfolio management: optimizing interdependent projects over multiple time periods, IEEE Transactions on Engineering Management 48, 4 (2001) 518-527.
  • A.F. Carazo, T. Gómez, F. Guerrero and R. Caballero, Evaluación y clasificación de las técnicas utilizadas por las organizaciones, en las últimas décadas, para seleccionar proyectos, Revista de Métodos Cuantitativos para la economía y la empresa 5 (2008) 67-115.
  • N.P. Archer and F. Ghasemzadeh, An integrated framework for project selection, International Journal of Project Management 17, 4 (1999) 207-216.
  • R.G. Cooper, S.J. Edgett and E.J. Kleinschmidt, New product portfolio management: practices and performance, The Journal of Product Innovation Management 16, 4 (1999) 333-350.
  • L.D. Dye and J.S. Pennypacker, An introduction to project portfolio management, in Project Portfolio Management: selecting and prioritizing projects for competitive advantage, eds. L.D. Dye and J.S. Pennypacker, (West Chester, PA, USA: Center for Business Practices, XI-XVI, 1999).
  • C. Chien, A portfolio-evaluation framework for selecting R&D projects, R&D Management 32, 4 (2002) 359-368.
  • N.P. Archer and F. Ghasemzadeh, Project portfolio selection techniques: a review and suggested integrated approach, in Project Portfolio Management: selecting and prioritizing projects for competitive advantage, eds. L.D. and J.S. Pennypacker (West Chester, PA, USA: Center for Business, 1999), pp. 207-237.
  • A.F. Carazo, T. Gómez, J. Molina, J. Hernández-Díaz, F. Guerrero and R. Caballero, Solving a Comprehensive Model for Multi-Objective Project Portfolio Selection, Computers and Operations Research 37, 4 (2010) 630-639.
  • A.F. Carazo, Un estudio Holístico de la selección y planificación temporal de carteras de proyectos, Rect@ 9, 1 (2008) 5-45.
  • N.R. Baker, R&D project selection models: an assessment, IEEE Transactions on Engineering Management, EM-21, 4 (1974) 165-171.
  • F. Ghasemzadeh, N. Archer and P. Iyogun, A zero-one model for project portfolio selection and scheduling, Journal of the Operational Research Society 50, 7 (1999) 745-755.
  • S.B. Graves and J.L. Ringuest, Models & methods for project selection: concepts from management science, finance and information technology (Kluwer Academic Publishers, Boston, 2003).
  • J.H. Lorie and L.J. Savage, Three problems in capital rationing, Journal of Business 28 (1955) 229- 239.
  • H.M. Weingartner, Mathematical programming and the analysis of capital budgeting problems (Prentice-Hall, Englewood Cliffs, New York, 1963).
  • S.C. Myers, A note on linear programming and capital budgeting, Journal of Finance 27 (1972) 89- 92.
  • A.F. Czajkowski and S. Jones, Selecting interrelated R&D projects in space technology planning, IEEE Transactions on Engineering Management, EM-33, 1 (1986) 17-24.
  • J.L. Ringuest and S.B. Graves, The linear multi-objetive R&D project selection problem, IEEE Transactions on Engineering Management 36, 1 (1989) 54-57.
  • M.J. Schniederjans and R.L. Wilson, Using the analytic hierarchy process and goal programming for information system project selection, Information & Management 20, 5 (1991) 333-342.
  • R. Santhanam and J. Kyparisis, A multiple criteria decision model for information system project selection, Computers and Operations Research 22, 8 (1995) 807-818.
  • J.W. Lee and S.H. Kim, An integrated approach for interdependent information system project selection, International Journal of Project Management 19, 2, (2001) 111-118.
  • M.A. Badri, D. Davis and D. Davis, A comprehensive 0-1 goal programming model for project selection, International Journal of Project Management 19, 4 (2001) 243-252.
  • J. Klapka and P. Piños, Decision support system for multicriterial R&D and information systems projects selection, European Journal of Operational Research 140, 2 (2002) 434-446.
  • C. Stummer and K. Heidenberger, Interactive R&D portfolio analysis with project interdependencies and time profiles of multiple objectives, IEEE Transactions on Engineering Management 50, 2 (2003) 175-183.
  • A.L. Medaglia, D. Hueth, J.C. Mendieta and J.A. Sefair, A multiobjetive model for the selections and timing of public enterprise projects, Socio-Economic Planning Sciences 42, 1 (2008) 31-45.
  • J. Gaytán and J. García, Multicriteria decision on interdependent infrastructure transportation projects using an evolutionary-based framework, Applied Soft Computing 9 (2009) 512-526.
  • R. Santhanam and J. Kyparisis, A decision model for interdependent information system project selection, European Journal of Operational Research 89, 2 (1996) 380-399.
  • G.E Fox, N.R. Baker and J.L. Bryant, Economic Models for R and D Project Selection in the Presence of Interactions, Management Science 30, 7 (1984) 890-902.
  • S. Reiter, Choosing an investment program among interdependent projects, Review of Economic Studies 30, 82 (1963) 32-36.
  • A. Reisman, A capital budgeting approach for interrelated projects, Journal of Industry Engineering 26, (1965) 59-64.
  • H.M. Weingartner, Capital budgeting of interrelated projects: survey and synthesis, Management Science 12 (1966) 485-516.
  • S. Reiter and D.B. Rice, Discrete optimization solution procedures for linear and nonlinear integer programming problems, Management Science 12, (1966) 829-850.
  • Z. Ullmann, “Dynamic programming and the capital allocation problem”, Ph.D. thesis (The Johns Hopkins University, Baltimore, MD, 1967).
  • R.T. Schmidt, A model for R&D project selection with combined benefit, outcome a resource interactions, IEEE Transactions on Engineering management 40, 4 (1993) 403-410.
  • T.E. Gear and G.C. Cowie, A note on modeling project interdependence in research and development, Decision Sciences 2, 4 (1980) 738-748.
  • F.S. Hillier, Chance-constrained programming with 0-1 or bounded continuous decision variables, Management Science 14, 1 (1967) 34-51.
  • D. Verma and K.K. Sinha, Toward a theory of project interdependencies in high tech R&D environments, Journal of Operations Management 20, 51 (2002) 451-468.
  • C.T. Spradlin and D.M. Kutoloski, Action-oriented portfolio management, Research Technology Management 42, 2 (1999) 26-32.
  • J.W. Lee and S.H. Kim, Using analytic network process and goal programming for interdependent information system project selection, Computers & Operations Research 27, 4, (2000) 367-382.
  • K.F. Doerner, W.J. Gutjahr, R.F. Hartl, C. Strauss and C. Stummer, Pareto ant colony optimization: a metaheuristic approach to multiobjetive portfolio selection, Annals of Operations Research 131, 1-4 (2004) 79-99.
  • K.F. Doerner, W.J. Gutjahr, R.F. Hartl, C. Strauss and C. Stummer, Pareto ant colony optimization with ILP preprocessing in multiobjetivo project portfolio selection, European Journal of Operational Research 171, 3 (2006) 830-841.
  • P. Mild, “Multicriteria portfolio analysis for strategic resource allocation”, Ph.D. thesis (Helsinki University of Technology, 2005).
  • L.R. Ireland, Managing multiple projects in 21st century, in: Managing Multiple Projects: Panning, Scheduling and Allocating Resources for Competitive Advantage, eds. L.D. Dye and J.S. Pennypacker (New York, USA: Marcel Dekker Publishers, Centre for Business Practices 2002), pp. 21-33.
  • Y.H. Chun, Sequential decisions under uncertainty in the R&D project selection problem, IEEE Transactions on Engineering Management 41, 4 (1994) 404-413.
  • M.A. Coffin and B.W. Taylor, Multiple criteria R&D project selection and scheduling using fuzzy logic, Computers and Operations Research 23, 3 (1996) 207-220.
  • M.A. Coffin and B.W. Taylor, R&D project selection and scheduling with a filtered beam search approach, IIE Transactions 28, 2 (1996) 167-176.
  • H. Sun and T. Ma, A packing-multiple-boxes model for R&D project selection and scheduling, Technovation 25, 11 (2005) 1355-1361.
  • M. Rabbani, M. Aramoon and G. Khoshkhou, A multiple-objective particle swarm optimization for project selection problem. Expert Systems with Applications 37,1 (2010) 315-321.
  • A.D. Roy, Safety first and the holding of asset, Econometrics 20 (1952) 431-449.
  • F.W. McFarlan, Portfolio approach to information systems, Harvard Business Review 59, 5 (1981) 142-150.
  • S.B Graves and J.L. Ringuest, Evaluating a portfolio of R&D investment, The Journal of High Technology Management Research 7, 1 (1996) 53-60.
  • G.L. Tritle, E.F.V. Scriven and A.R. Fusfeld, Resolving uncertainty in R&D portfolios, Research Technology Management 43, 6 (2000) 47-55.
  • R. Carter and D. Edwards, Financial analysis extends management of R&D, Research Technology Management 44, 5 (2001) 47-57.
  • J.L. Ringuest, S.B. Graves and R.H. Case, Formulating R&D portfolios that account for risk, Research Technology Management 42, 6 (1999) 40-43.
  • J.L. Ringuest, S.B. Graves and R.H. Case, Conditional stochastic dominance in R&D portfolio selection, IEEE Transaction on Engineering Management 47, 4 (1999) 478-484.
  • J.L. Ringuest, S.B. Graves and R.H. Case, Mean-Gini analysis in R&D portfolio selection, European Journal of Operational Research 154, 1 (2004) 157-169.
  • R.M. Ghaeli, J. Vavrik and G. Nasvadi, Multicriteria project portfolio selection. Case study for intelligent transportation systems, Transportation Research Record 1848 (2003) 125-131.
  • C.Z. Rdulescu and M. Rdulescu, Project portfolio selection models and decision support, Studies in Informatics and Control 10, 4 (2001) 275-286.
  • H.M. Markowitz, Portfolio selection: efficient diversification of investments (Wiley, New York, 1959).
  • J.S. Pennypacker and L.D. Dye, Project portfolio management and managing multiple projects: two sides of the same coin, in Managing Multiple Projects: Panning, Scheduling and Allocating Resources for Competitive Advantage, eds. L.D. Dye and J.S. Pennypacker (New York, USA: Marcel Dekker Publishers, Centre for Business Practices, 2002), pp. 1-19.
  • R.G. Cooper and S.J. Edgett, Overcoming the crunch in resources for new product development, Research Technology Management 46, 3 (2003) 48-58.
  • M. Martinsuo and P. Lehtonen, Role of single-project management in achieving portfolio management efficiency, International Journal of Project Management 25 (2007) 56-65.
  • A.L. Medaglia, S.B. Graves and J.L. Ringuest, Multiobjective evolutionary approach for linearly constrained project selection under uncertainty, European Journal of Operational Research 179, 3 (2007) 869-894.
  • K.K. Damghani, S. Sadi-Nezhad and M.B. Aryanezhad, A modular Decision Support System for optimum investment selection in presence of uncertainty: Combination of fuzzy mathematical programming and fuzzy rule based system, Expert Systems with Applications 38, 1 (2011) 824-834.
Fuente de los datos: Dialnet