Integration of a text mining approach in the strategic planning process of small and medium-sized enterprises
Abstract
Purpose
Strategic planning (SP) enables enterprises to plan management and operations activities efficiently in the medium and large term. During its implementation, many processes and methods are manually applied and may be time consuming. The purpose of this paper is to introduce an automatic method to define strategic plans by using text mining (TM) algorithms within a generic SP model especially suited for small- and medium-sized enterprises (SMEs).
Design/methodology/approach
Textual feedbacks were collected through a SWOT matrix during the implementation of a SP model in a company dedicated to the local distribution of food. A four-step TM process (performing acquisition, pre-processing, processing, and validation tasks) is applied via a framework developed under the cloud computer paradigm in order to determine the strategic plans.
Findings
The use of categorization and clustering algorithms show that unstructured textual information produced during the SP can be efficiently processed and capitalized. Collected evidence reveals the potential to enhance the strategic plans creation with less effort and time, improving the relevance, and producing new technological resources accessible to SMEs.
Originality/value
An innovative framework especially suited for the SMEs based on the synergy assumption of the coupling between TM and a generic SP model.
Keywords
Acknowledgements
This research work was supported by a faculty research grant from the Consejo Nacional de Ciencia y Tecnología (Conacyt) of Mexico, and the Tecnológico Nacional de México (5392.14-P). The authors also thank roprin.org for supporting this work.
Citation
Vásquez Rojas, C., Roldán Reyes, E., Aguirre y Hernández, F. and Cortés Robles, G. (2018), "Integration of a text mining approach in the strategic planning process of small and medium-sized enterprises", Industrial Management & Data Systems, Vol. 118 No. 4, pp. 745-764. https://doi.org/10.1108/IMDS-01-2017-0029
Publisher
:Emerald Publishing Limited
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