Cognitive Strategic Model applied to a Port System


1 Faculty of Engineering, University Finis Terrae, Avda. Pedro de Valdivia 1509, Providencia, Santiago, Chile.

2 Faculty of Engineering, Universidad Tecnológica Metropolitana, Dieciocho 161, Santiago, Región Metropolitana, Chile.

3 Department of Mathematics and Computer Science, Universidad de Santiago de Chile, Avda. Ecuador 3769, Estación Central, Santiago, Chile.



Port organizations have focused their efforts on physical or tangible assets, generating profitability and value. However, it is recognized that the greatest sustainable competitive advantage is the creation of knowledge using the intangible assets of the organization. The Balanced ScoreCard, as a performance tool, has incorporated intangible assets such as intellectual, structural and social capital into management. In this way, the port community can count on new forms of managing innovation, strengthening organizational practices, and increasing collaborative work teams. In this study, the concepts from analysis of the cognitive SWOT are applied to diagnose the port activity and its community. In workshops with experts and from the vision, mission, cognitive SWOT and strategies, a cognitive strategic map considering strategic objectives and indicators is designed in the customer, processes, and learning and growth axis for the port and port community. Causal relationships between objectives, associated indicators and incidence factors are established in a forward way from learning and growth axis to customer axis. Then, the incidence matrix is developed and the direct and indirect effects between factors are analyzed, which allows recommending the future course of the port and its community.

[1] Micco A. Clark X., Dollar D. Port efficiency, maritime transport costs, and bilateral trade. Journal of development economics, 75(2):417–450, 2004.
[2] Luan W. Zhong M., Wu Y. Model of synergy degree between port logistics and urban economy. Journal of Dalian Maritime University, 37(1):80–82, 2011.
[3] Ervural B. Kabak Ö. Multiple attribute group decision making: A generic conceptual framework and a classification scheme. Knowledge-Based Systems, 123:13–30, 2017.
[4] Vargas L. G. Saaty T., L. The seven pillars of the analytic hierarchy process. Models, Methods, Concepts & Applications of the Analytic Hierarchy Process, 175:23–40, 2012.
[5] Rida M. Modeling and optimization of decisionmaking process during loading and unloading operations at container port. Arabian Journal for Science and Engineering, 39(11):8395–8408, 2014.
[6] Bell M. G. Angeloudis P. A review of container terminal simulation models. Maritime Policy & Management, 38(5):523–540, 2011.
[7] Norton D. P. Kaplan R. S. Using the balanced scorecard as a strategic management system. Harvard Business Review, 74:75–85, 1996.
[8] D. Norton R. Kaplan. Strategy maps: Converting intangible assets into tangible outcomes. Harvard Business Review, Harvard Business School Press, Boston, MA, USA., 2004.
[9] Norton D. P. Kaplan R. S. Linking the balanced scorecard to strategy. California Management Review, 39(1):53–79, 2006.
[10] Palominos F.E. Córdova F.M., Durán C.A. Dynamic evaluation of balanced scorecard using knowledge based representation. 7th Int. Conf. on Computers Communications and Control (ICCCC). Oradea, Rumania, IEEE Catalog Number CFP18E84-ART:52–57, 2018.
[11] Gutiérrez F. A. Córdova F. M. Knowledge management system in service companies. Procedia Computer Science, 139:392–400, 2018.
[12] Kyaw N.A. Aggarwal R. Internal capital networks as a source of mnc competitive advantage: Evidence from foreign subsidiary capital structure decisions. Research in International Business and Finance, 22 (3):409–439, 2008.
[13] Chin-Tsang Ho. The relationship between knowledge management enablers and performance. Industrial
Management & Data Systems, 109(1):98–117, 2009.
[14] Galindo R. Córdova F.M., Durán C.A. Evaluation of intangible assets and best practices in a medium sized port community. Procedia Computer Science, 91:75 – 84, 2016.
[15] Sepúlveda J. Durán C., Carrasco R. Model of decision for the management of technology and risk in a port community. Decision Science Letters, 7(3):211–224, 2018.