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Toward the Automatic Construction of Strategic Plans Based on Ontologies

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Abstract

In this paper, the authors propose an approach toward the automatic construction of Strategic Plans based on Ontologies. Transnational corporations have units located in different geographical regions with a set of multiple nationalities. Aligning the targets and values to the global vision and mission of the company is an activity that needs constant update. However, it is possible that the strategists from different places will interpret the objectives differently and the alignment will not be close to the original. As a consequence, the image and profits of the organization could deteriorate. Verifying automatically the alignment of the goals of the organization to the global organization is important because it saves time, money, and the whole team could move in the same direction. This approach is based on ontologies where the knowledge and information about the plans are structured on class, concepts and data. It is also composed of a set of data retrieval and manipulation operations, which allow the approach itself to identify a set of patterns in the group of the strategic plans. Finally, the evaluation is carried out by performing a series of tests to determine the level of adherence to the proposed approach.

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Acknowledgements

We are grateful to the Sciences Research Council (CONACYT) for funding this research project.

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Correspondence to Liliana Ibeth Barbosa-Santillán .

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Barbosa-Santillán, L.I., Nuño-de-la-Parra, J.P., Sánchez-Escobar, J.J., Vega-Lebrun, C.A. (2015). Toward the Automatic Construction of Strategic Plans Based on Ontologies. In: Sobh, T., Elleithy, K. (eds) Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering. Lecture Notes in Electrical Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-319-06773-5_74

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  • DOI: https://doi.org/10.1007/978-3-319-06773-5_74

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06772-8

  • Online ISBN: 978-3-319-06773-5

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