Eficiencia de los sistemas productivos de las pequeñas y medianas empresas
Autores/as
- José Morelos-Gómez https://orcid.org/0000-0002-0334-0575
- Roberto Gómez-Fernández https://orcid.org/0000-0002-0333-1089
- Jaime Acevedo-Chedid https://orcid.org/0000-0001-8318-2636
DOI:
https://doi.org/10.18041/2382-3240/saber.2022v17n2.9298Palabras clave:
Eficiencia, Pymes, Análisis envolvente de Datos, productividadResumen
Esta investigación tiene como objetivo evaluar la eficiencia en los sistemas productivos de bienes y servicios de las pequeñas y medianas empresas (Pymes) en el Departamento de Bolívar-Colombia. Para este propósito se utilizó la técnica de Análisis Envolvente de Datos (DEA), en la cual se determinó las eficiencias técnicas de las 120 Pymes formalmente registradas en la Cámara de Comercio de Cartagena para los años 2017 a 2020. Se contrasta con otros estudios cuya técnica no paramétrica fue aplicada en sectores productivos similares que, el grupo de pequeñas y medianas empresas evaluadas mostraron resultados análogos en sus procesos operacionales. Se concluye que las Pymes evaluadas presentaron un desempeño productivo exiguo en sus actividades operacionales debido a factores relacionados con el bajo aplacamiento financiero y deficiente gestión de la innovación.
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Referencias
Amin, G. R., Emrouznejad, A., & Gattoufi, S. (2017). Minor and major consolidations in inverse DEA: Definition and determination. Computers & Industrial Engineering, 103, 193-200. https://doi.org/10.1016/j.cie.2016.11.029
Andersen, A. L., Brunoe, T. D., Nielsen, K., & Rösiö, C. (2017). Towards a generic design method for reconfigurable manufacturing systems: Analysis and synthesis of current design methods and evaluation of supportive tools. Journal of Manufacturing Systems, 42, 179-195. https://doi.org/10.1016/j.jmsy.2016.11.006
Awan, U., Khattak, A., & Kraslawski, A. (2019). Corporate Social Responsibility (CSR) Priorities in the Small and Medium Enterprises (SMEs) of the Industrial Sector of Sialkot, Pakistan. In Corporate Social Responsibility in the Manufacturing and Services Sectors 1(1) ,267-278. https://doi.org/10.1007/978-3-642-33851-9_15
Brunswicker, S., & Vanhaverbeke, W. (2015). Open innovation in small and medium‐sized enterprises (SMEs): External knowledge sourcing strategies and internal organizational facilitators. Journal of Small Business Management, 53(4), 1241-1263.https://doi.org/10.1111/jsbm.12120
Caldas, P., Ferreira, D., Dollery, B., & Marques, R. (2019). Are there scale economies in urban waste and wastewater municipal services? A non-radial input-oriented model applied to the Portuguese local government. Journal of Cleaner Production, 219, 531-539. https://doi.org/10.1016/j.jclepro.2019.02.076
Cerchione, R., Esposito, E., & Spadaro, M. R. (2016). A literature review on knowledge management in SMEs. Knowledge Management Research & Practice, 14(2), 169-177. https://doi.org/10.1057/kmrp.2015.12
Costa, E., Soares, A. L., & De Sousa, J. P. (2016). Information, knowledge and collaboration management in the internationalisation of SMEs: A systematic literature review. International Journal of Information Management, 36(4), 557-569. https://doi.org/10.1016/j.ijinfomgt.2016.03.007
Chen, J. C., Chen, T. L., & Harianto, H. (2017). Capacity planning for packaging industry. Journal of manufacturing systems, 42, 153-169. https://doi.org/10.1016/j.jmsy.2016.12.007
Chen, X., Fu, T. T., Juo, J. C., & Yu, M. M. (2019). A comparative analysis of profit inefficiency and productivity convergence between Taiwanese and Chinese banks. BRQ Business Research Quarterly. https://doi.org/10.1016/j.brq.2019.02.001
Departamento Administrativo Nacional de Estadística (2019), Boletín de Prensa: Micro-establecimientos Evolución 2018. Consultado 29/052020 en: https://www.dane.gov.co/index.php/estadisticas-por-tema/comercio-interno/microestablecimientos
Feenstra, R. C. (2018). Restoring the product variety and pro-competitive gains from trade with heterogeneous firms and bounded productivity. Journal of International Economics, 110, 16-27. https://doi.org/10.1016/j.jinteco.2017.10.003
Fontalvo, T. J., De La Hoz, E. J. y Morelos, J. (2018). La productividad y sus factores: incidencia en el mejoramiento organizacional. Dimensión empresarial, 16(1), 47-60. Consultado 15/02/2019 en: https://dialnet.unirioja.es/servlet/articulo?codigo=6233008
Fuentes, R., Molinos-Senante, M., Hernández-Sancho, F., & Sala-Garrido, R. (2020). Analysing the efficiency of wastewater treatment plants: The problem of the definition of desirable outputs and its solution. Journal of Cleaner Production, 267(10) https://doi.org/10.1016/j.jclepro.2020.121989
Garone, L. F., Villalba, P. A. L., Maffioli, A., & Ruzzier, C. A. (2020). Firm-level productivity in Latin America and the Caribbean. Research in Economics. https://doi.org/10.1016/j.rie.2020.04.004
Goel, V., Agrawal, R., & Sharma, V. (2017). Factors affecting labour productivity: an integrative synthesis and productivity modelling. Global Business and Economics Review, 19(3), 299-322. https://doi.org/10.1504/GBER.2017.083964
Gonnermann, C., & Reinhart, G. (2019). Automatized setup of process monitoring in cyber-physical systems. Procedia CIRP, 81, 636-640. https://doi.org/10.1016/j.procir.2019.03.168
Hariharan, S., Liu, T., & Shen, Z. J. M. (2020). Role of resource flexibility and responsive pricing in mitigating the uncertainties in production systems. European Journal of Operational Research284(2), 498-513. https://doi.org/10.1016/j.ejor.2019.12.040
Herman, E. (2020). Labour Productivity and Wages in the Romanian Manufacturing Sector. Procedia Manufacturing, 46, 313-321. https://doi.org/10.1016/j.promfg.2020.03.046
Hossain, M. and Kauranen, I. (2016) Open innovation in SMEs: a systematic literature review, Journal of Strategy and Management, 9(1), pp. 58-73. https://doi.org/10.1108/JSMA-08-2014-0072
Hu, W., Guo, Y., Tian, J., & Chen, L. (2019). Eco-efficiency of centralized wastewater treatment plants in industrial parks: A slack-based data envelopment analysis. Resources, Conservation and Recycling, 141, 176-186. https://doi.org/10.1016/j.resconrec.2018.10.020
Javid, N., Khalili-Damghani, K., Makui, A., & Abdi, F. (2020). Multi-objective flexibility-complexity trade-off problem in batch production systems using fuzzy goal programming. Expert Systems with Applications, 148(1). https://doi.org/10.1016/j.eswa.2020.113266
Jodlbauer, H., & Strasser, S. (2019). Capacity-driven production planning. Computers in Industry, 113, 103-126. https://doi.org/10.1016/j.compind.2019.103126
Joppen, R., von Enzberg, S., Kühn, I. A., & Dumitrescu, I. R. (2019). A practical framework for the optimization of production management processes. Procedia Manufacturing, 33, 406-413. https://doi.org/10.1016/j.promfg.2019.04.050
Kamble, R., & Wankhade, L. (2017). Perspectives on productivity: identifying attributes influencing productivity in various industrial sectors. International Journal of Productivity and Quality Management, 22(4), 536-566. https://doi.org/10.1504/IJPQM.2017.087868
Karanikas, N., Melis, D. J., & Kourousis, K. I. (2018). The balance between safety and productivity and its relationship with human factors and safety awareness and communication in aircraft manufacturing. Safety and health at work, 9(3), 257-264. https://doi.org/10.1016/j.shaw.2017.09.001
Krüger, J., Wang, L., Verl, A., Bauernhansl, T., Carpanzano, E., Makris, S., ... & Pellegrinelli, S. (2017). Innovative control of assembly systems and lines. CIRP annals, 66(2), 707-730. https://doi.org/10.1016/j.cirp.2017.05.010
Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing letters, 3, 18-23. https://doi.org/10.1016/j.mfglet.2014.12.001
Li, T., Yang, W., Zhang, H., & Cao, X. (2016). Evaluating the impact of transport investment on the efficiency of regional integrated transport systems in China. Transport Policy, 45, 66-76. https://doi.org/10.1016/j.tranpol.2015.09.005
Ministerio de Comercio, Industria y Turismo ( 2016) ¿Cuáles son los programas y proyectos que se desarrollan para fortalecer a las Mipymes colombianas? MinCIT. Consultado 23/11/2016 en : http://www.mincit.gov.co/servicio-al-ciudadano/preguntas-frecuentes/mipymes
Mohammadian, I., & Rezaee, M. J. (2018). A new decomposition and interpretation of Hicks-Moorsteen productivity index for analysis of stock exchange companies: Case study on pharmaceutical industry. Socio-Economic Planning Sciences, 100674. https://doi.org/10.1016/j.seps.2018.12.001
Morelos, J. , Fontalvo, T. J., & Vergara, J. C. (2013). Incidencia de la certificación ISO 9001 en los indicadores de productividad y utilidad financiera de empresas de la zona industrial de Mamonal en Cartagena. Estudios Gerenciales, 29(126), 99-109. Consultado 4/0672017 en: https://www.redalyc.org/pdf/212/21228397012.pdf
Morelos, J. (2016). Análisis de la variación de la eficiencia en la producción de biocombustibles en América Latina. Estudios gerenciales, 32(139), 120-126. https://doi.org/10.1016/j.estger.2016.01.001
Morelos, J., & Nuñez, M. Á. (2017). Productividad de las empresas de la zona extractiva minera-energética y su incidencia en el desempeño financiero en Colombia. Estudios gerenciales, 33(145), 330-340. https://doi.org/10.1016/j.estger.2017.11.002
Nedaei, H., Naini, S. G. J., & Makui, A. (2020). A dynamic DEA model to measure the learning rates of efficient frontier and DMUs: An application to oil and gas wells drilling. Computers & Industrial Engineering, 144(1) 106434. https://doi.org/10.1016/j.cie.2020.106434
Nikolakis, N., Senington, R., Sipsas, K., Syberfeldt, A., & Makris, S. (2020). On a containerized approach for the dynamic planning and control of a cyber-physical production system. Robotics and Computer-Integrated Manufacturing, 64(1). https://doi.org/10.1016/j.rcim.2019.101919
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2017). Human resource management: Gaining a competitive advantage. New York, NY: McGraw-Hill Education.
OECD. (2015). The future of productivity. Joint Economics Department and the Directorate for Science, Technology and Innovation Policy Note.
Onkelinx, J., Manolova, T. S., & Edelman, L. F. (2016). The human factor: Investments in employee human capital, productivity, and SME internationalization. Journal of International Management, 22(4), 351-364. https://doi.org/10.1016/j.intman.2016.05.002
Ouyang, W., & Yang, J. B. (2020). The network energy and environment efficiency analysis of 27 OECD countries: A multiplicative network DEA model. Energy, 197(1) 117161. https://doi.org/10.1016/j.energy.2020.117161
Palominos, P., Quezada, L. E., & Gonzalez, M. A. (2019). Incorporating the voice of the client in establishing the flexibility requirement in a production system. International Journal of Production Economics, 211, 34-43. https://doi.org/10.1016/j.ijpe.2019.01.029
Pipitone, V., & Colloca, F. (2018). Recent trends in the productivity of the Italian trawl fishery: The importance of the socio-economic context and overexploitation. Marine Policy, 87, 135-140. https://doi.org/10.1016/j.marpol.2017.10.017
Putra, P. O. H., & Santoso, H. B. (2020). Contextual factors and performance impact of e-business use in Indonesian small and medium enterprises (SMEs). Heliyon, 6(3), e03568. https://doi.org/10.1016/j.heliyon.2020.e03568
Polotski, V., Kenné, J. P., & Gharbi, A. (2019). Production control of hybrid manufacturing–remanufacturing systems under demand and return variations. International Journal of Production Research, 57(1), 100-123. https://doi.org/10.1080/00207543.2018.1461272
Simon, P., Diehl, D., Glasschroeder, J., & Reinhart, G. (2019). Approach for the identification of influencing factors and their effects on energy flexible production systems. Procedia CIRP, 79, 239-244. https://doi.org/10.1016/j.procir.2019.02.057
Shao, X. F. (2019). What is the right production strategy for horizontally differentiated product: Standardization or mass customization?. International Journal of Production Economics, 223(1) https://doi.org/10.1016/j.ijpe.2019.107527
Shuai, S., & Fan, Z. (2020). Modeling the role of environmental regulations in regional green economy efficiency of China: Empirical evidence from super efficiency DEA-Tobit model. Journal of Environmental Management, 261, 110227. https://doi.org/10.1016/j.jenvman.2020.110227
Tamberi, M. (2020). Productivity differentials along the development process: A “MESO” approach. Structural Change and Economic Dynamics, 53, 99-107. https://doi.org/10.1016/j.strueco.2020.01.006
Tiammee, S., & Likasiri, C. (2020). Sustainability in corn production management: A multi-objective approach. Journal of Cleaner Production, 257(1). https://doi.org/10.1016/j.jclepro.2020.120855
Tsutsumi, D., Gyulai, D., Kovács, A., Tipary, B., Ueno, Y., Nonaka, Y., & Fujita, K. (2020). Joint optimization of product tolerance design, process plan, and production plan in high-precision multi-product assembly. Journal of Manufacturing Systems, 54, 336-347. https://doi.org/10.1016/j.jmsy.2020.01.004
Valdez, L. E., Solano-Rodríguez, O. J., & Martin, D. P. (2018). Modes of learning and profitability in Colombian and Mexican SMEs. The Journal of High Technology Management Research, 29(2), 193-203. https://doi.org/10.1016/j.hitech.2018.09.007
Wu, G., Hong, J., Li, D., & Wu, Z. (2019). Efficiency assessment of pollutants discharged in urban wastewater treatment: Evidence from 68 key cities in China. Journal of cleaner production, 233, 1437-1450. https://doi.org/10.1016/j.jclepro.2019.06.012
Yadav, A., & Jayswal, S. C. (2018). Modelling of flexible manufacturing system: a review. International Journal of Production Research, 56(7), 2464-2487. https://doi.org/10.1080/00207543.2017.1387302
Yan, Y., Liu, X., Wen, Y., & Ou, J. (2019). Quantitative analysis of the contributions of climatic and human factors to grassland productivity in northern China. Ecological indicators, 103, 542-553. https://doi.org/10.1016/j.ecolind.2019.04.020
Yan, J. (2019). Spatiotemporal analysis for investment efficiency of China’s rural water conservancy based on DEA model and Malmquist productivity index model. Sustainable Computing: Informatics and Systems, 21, 56-71. https://doi.org/10.1016/j.suscom.2018.11.004
Yu, D., & He, X. (2020). A bibliometric study for DEA applied to energy efficiency: Trends and future challenges. Applied Energy, 268. https://doi.org/10.1016/j.apenergy.2020.115048
Yu, F., Shi, Y., & Wang, T. (2020). R&D Investment and Chinese Manufacturing SMEs Corporate Social Responsibility: The Moderating Role of Regional Innovative Milieu. Journal of Cleaner Production, 258(1). https://doi.org/10.1016/j.jclepro.2020.120840
Zhang, R., Lu, C. C., Lee, J. H., Feng, Y., & Chiu, Y. H. (2019). Dynamic environmental efficiency assessment of industrial water pollution. Sustainability, 11(11), 1-12. https://doi.org/10.3390/su11113053
Zhang, G., & Cui, J. (2020). A general inverse DEA model for non-radial DEA. Computers & Industrial Engineering, 142 (1), 106368. https://doi.org/10.1016/j.cie.2020.106368
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