Identifying Causal Relationships in a Strategy Map Using ANP and Multi-Objective Integer Optimization Model

Luis E. Quezada (), Héctor López-Ospina, Miguel à ngel González (), Astrid Oddershede () and Pedro Palominos ()
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Luis E. Quezada: Department of Industrial Engineering, Universidad de Santiago de Chile, (USACH) Avenida Ecuador 3769, Santiago 9170124, Chile
Héctor López-Ospina: ��Faculty of Engineering and Applied Sciences, Universidad de los Andes, Chile
Miguel à ngel González: ��Department of Industrial Engineering, Universidad Autónoma de Chile, Pedro de Valdivia 425, Santiago 7500912, Chile
Astrid Oddershede: Department of Industrial Engineering, Universidad de Santiago de Chile, (USACH) Avenida Ecuador 3769, Santiago 9170124, Chile
Pedro Palominos: Department of Industrial Engineering, Universidad de Santiago de Chile, (USACH) Avenida Ecuador 3769, Santiago 9170124, Chile

International Journal of Information Technology & Decision Making (IJITDM), 2024, vol. 23, issue 03, 1261-1299

Abstract: This paper presents a method for identifying causal relationships between strategic objectives within a strategy map of a Balanced Scorecard. Strategy maps are modeled as a network of strategic objectives (nodes) and causal relationships (directed arcs). The nodes are also grouped into clusters that represent the perspectives of a Balanced Scorecard: (a) Finances, Clients, Internal Processes and Growth and Learning. The method uses the Analytic Network Process (ANP) to establish the importance of every relationship and uses a multi-objective integer linear programming model to select the relationships to be included within a strategy map of a company. The method provides a method that optimizes the selection of the relationships to be included in a strategy map. An illustration of the application of the method in a manufacturing company is presented.

Keywords: Balanced scorecard; strategy map; analytic network process; multi-objective integer linear programming (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219622023500396

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