The business competitiveness of SMEs through mathematical modeling
Main Article Content
Abstract
The objective of this research is to propose a functional application model for small and medium-sized enterprises (SMEs), with the purpose of determining the optimal production preferences of your specific production system. The problematic that originates this research is the methodology of projection of the costs that practice this type of companies in the market ―which departs from a process of determination of the optimum batch of production―, which are based on models of mathematical determination. The applied methodology is of an analytical nature of a transversal type, the factorial study allows the application of descriptive statistics and the development of equations that determine variables of study of the ex ante model. The result of the research consists in the application to a scenario that represents the optimal level of transport costs of the SMEs products which interact in the market. It is concluded that mathematically it is possible use variables for determining the productivity and level of competitiveness.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Licensing Agreement
This journal provides free access to its content through its website following the principle that making research available free of charge to the public supports a larger exchange of global knowledge.
Web content of the journal is distributed under a Attribution-NonCommercial-ShareAlike 4.0 International.
Authors may adopt other non-exclusive license agreements for the distribution of the version of the published work, provided that the initial publication in this journal is indicated. Authors are allowed and recommended to disseminate their work through the internet before and during the submission process, which can produce interesting exchanges and increase citations of the published work.
References
Baykasoglu, A. and Kapanoglu, V. (2006). Developing a service costing system and an application for logistics companies. International Journal of Agile Manufacturing, 9(2), 13-18.
Bada, L., Rivas, L. & Littlewood, H. (2017). Modelo de asociatividad en la cadena productiva en las Mipymes agroindustriales. Contaduría y Administración, 62(4), 1100-1117.
De La Cruz, I., Morales, J. & Carrasco, G. (2006). Construcción de un instrumento de evaluación de capacidades en la empresa: una propuesta metodológica. In Memorias del X Congreso Anual de la Academia de Ciencias Administrativas A.C. (ACACIA), Oaxaca, México.
Hall, R. (1996). On the integration of production and distribution: Economic order and production quantity implications. Transportation Research Part B: Methodological, 30(5), 387-403.
Jaber, M., Bonney, M. and Moualek, I. (2009). An economic order quantity model for an imperfect production process with entropy cost. International Journal of Production Economics Volume, 118(1), 26-33.
Jamal, A., Sarker, R. and Mondal, S. (2004). Optimal manufacturing batch size with rework process at a single-stage production system. Computers & Industrial Engineering, 47(1), 77-89.
Mendoza, A. and Ventura, J. (2008). Incorporating quantity discounts to the EOQ model with transportation costs. International Journal of Production Economics, 113(2), 754-765.
Mora, E., Vera, M. & Melgarejo, Z. (2015). Planificación estratégica y niveles de competitividad de las Mipymes del sector comercio en Bogotá. Estudios Gerenciales, 31(134), 79-87.
Puu, T. and Norin, A. (2003). Cournot duopoly when the competitors operate under capacity constraints. Chaos, Solitons & Fractals, 18(3), 577-592.
Quiroga, D. (2003). Modelo matemático para determinar la competitividad de las Pyme’s. Revista Docencia Universitaria, 4(1), 1-16.
Rubio, A. & Aragón, A. (2006). Recursos estratégicos en la PYMEs. Revista Europea de Dirección y Economía de la Empresa, 17(1), 32-47.
Sánchez, J., Osorio, J. & Baena, E. (2007). Algunas aproximaciones al problema de financiamiento de las Pymes en Colombia. Scientia et technica, 1(34), 321-324.
Sarker, R. and Khan, L. (1999). An optimal batch size for a production system operating under periodic delivery policy. Computers & Industrial Engineering, 37(4), 711-730.
Solleiro, J. & Castañón, R. (2005). Competitividad y sistemas de innovación: los retos para la inserción de México en el contexto global. Revista Iberoamericana, 5(15), 165-197.
Tarziján, J. (2006). Organización industrial para la estrategia empresarial. Santiago de Chile, Chile: Pearson Educación.
Yuan, P. et al. (2011). Mathematical modeling for determining the replenishment policy for EMQ model with rework and multiple shipments. Mathematical and Computer Modelling, 54(9-10), 2165-2174.
Valencia, J., Lambán, M. & Royo, J. (2014). Modelo analítico para determinar lotes óptimos de producción considerando diversos factores productivos y logísticos. DYNA, 81(184), 62-70.
Vera-Colina, M. & Mora-Riapira, E. (2011). Líneas de investigación en micro, pequeñas y medianas empresas. Revisión documental y desarrollo en Colombia. Tendencias, 12(1), 213-226.
Vélez, D. et al. (2008). Dinámica de la empresa familiar Pyme: estudio exploratorio en Colombia. Tolima, Colombia: FUNDES.