Concentration factors of manufacturing companies in the State of Guanajuato: A cluster analysis

Authors

DOI:

https://doi.org/10.29057/jas.v6i12.13495

Keywords:

Manufacturing companies, Cluster, Guanajuato, Ward's hierarchical method

Abstract

The geolocation of enterprises is an alternative for the regional development of small economies (Alegría et al., 1995). This research aims to group the cities of the State of Guanajuato into clusters based on the agglomeration factors that manufacturing companies have in common and to generate a business profile in this context. The research will be non-experimental, analyzing variables of the manufacturing sector such as Companies, Employment, Gross Value Added Census GCVA, transport costs, innovation, wages, daily hours worked, investment in gross fixed capital formation, economies of scale, Total Gross Production TGP, schooling and population by cities. The analysis technique is the hierarchical cluster using the Ward method to determine the essential factors in the business agglomeration based on the Euclidean distance, structuring a dendrogram with the resulting clusters. The results identify the agglomeration of cities in three clusters. The first cluster includes 28 cities whose business profile stands out for the economies of scale and the low level of schooling to which they have access. The second cluster includes 11 cities that have a medium-high educational level in common and whose companies are interested in accessing innovation. The third cluster includes seven cities in which manufacturing company salaries are not competitive. In conclusion, it is necessary to manage the factors used by manufacturing companies in Guanajuato to promote a decent development environment because family income from salaries improves people's well-being, quality of life, and regional economic growth.

Downloads

Download data is not yet available.

Publication Facts

Metric
This article
Other articles
Peer reviewers 
0
2.4

Reviewer profiles  N/A

Author statements

Author statements
This article
Other articles
Data availability 
N/A
16%
External funding 
No
32%
Competing interests 
N/A
11%
Metric
This journal
Other journals
Articles accepted 
67%
33%
Days to publication 
150
145

Indexed in

Editor & editorial board
profiles
Academic society 
N/A
Publisher 
Universidad Autónoma del Estado de Hidalgo

Author Biographies

Alejandra López Salazar, Universidad de Guanajuato, México

Research Professor, Department of Finance and Administration, Division of Social and Administrative Sciences, Campus Celaya Salvatierra, at the University of Guanajuato.

Jesús Ernesto Rocha Ibarra, Universidad de Guanajuato, México

Research Professor, Department of Art and Business, Division of Engineering, Campus Irapuato Salamanca, University of Guanajuato.

References

Alegría, T., Carrillo, J. and Alonso, J. (1995). Productive restructuring and territorial change in northern Mexico: consolidation of a second industrialization axis. Paper presented at the International Seminar "Territorial Impacts of Restructuring Processes", Santiago de Chile, Institute of Urban Studies, July 12-14.

Corrales, C. (2007). The importance of the cluster in current regional development. Northern border, 19(37), 173-201.

Pinto, M. R., Salume, P. K., Barbosa, M. W., & de Sousa, P. R. (2023). The path to digital maturity: A cluster analysis of the retail industry in an emerging economy. Technology in Society, 72, 102191. https://doi.org/10.1016/j.techsoc.2022.102191

Bouchra, N. H., & Hassan, R. S. (2023). Application of Porter's diamond model: A case study of tourism cluster in UAE. In Industry Clusters and Innovation in the Arab World (pp. 129-156). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80262-871-520231007

Mungaray, A., Machain, G., & Medina, E. (2001). Especialización industrial y desencadenamientos regionales en Nayarit. Región y sociedad, 13(22), 49-71.

Xu, R., Wu, J., Gu, J., & Raza-Ullah, T. (2023). How inter-firm cooperation and conflicts in industrial clusters influence new product development performance? The role of firm innovation capability. Industrial Marketing Management, 111, 229-241. https://doi.org/10.1016/j.indmarman.2023.04.009

Porter, M. (1991): The competitive advantage of nations, Plaza and Janés Editores, Barcelona.

Yoyo, T., Hanitha, V., & Hendra, H. (2023). Developing The Competitiveness Model of The Palm Oil-Based Fatty Acid and Fatty Alcohol Industry in Indonesia Using Porter’s Diamond Cluster Competitiveness Model. Primanomics: Jurnal Ekonomi & Bisnis, 21(1), 13-23. https://doi.org/10.31253/pe.v21i1.1537

Barajas, M.R. (2019). Los cambios en el proceso de relocalización industrial de la industria Bovin, P. (Ed.), Las fronteras del istmo: Fronteras y sociedades entre el sur de México y América Central. Centro de estudios mexicanos y centroamericanos. Doi https//doi.org/10.4000/books.cemca.659

Hernández, I. (2019). Liberalización Comercial y Localización Industrial en México. Departamento de Economía. Universidad de Barcelona.

Krugman, P (1992). Geography and Trade. Publisher Antoni Bosch, Barcelona, Spain

Ascani, A., Crescenzi, R., and Lammarino, S. (2021). New economic geography and economic integration: a review. WP Search, 1(02), 1-24. Doi https://doi.org/10.1111/pirs.12275

O’Leary, D., Doran, J., & Power, B. (2023). Urbanisation, concentration and diversification as determinants of firm births and deaths. Regional Studies, Regional Science, 10(1), 506-528. https://doi.org/10.1080/21681376.2023.2204143

Perroux, F. (1962). La Comunidad Económica Europea. Investigación Económica, 22(87), 709-727.

Mendi, P. (2023). Concentration of innovation investments along the business cycle. Journal of the Knowledge Economy, 1-18. https://doi.org/10.1007/s13132-023-01267-z

Del Olmo-García, F., Domínguez-Fabián, I., Crecente-Romero, F. J., & del Val-Núñez, M. T. (2023). Determinant factors for the development of rural entrepreneurship. Technological Forecasting and Social Change, 191, 122487. https://doi.org/10.1016/j.techfore.2023.122487

Moreno Codina, T., López Flores, N., & de la Barrera Medina, M. S. (2020). Análisis de los instrumentos de gestión pública para administrar y gestionar los parques industriales.

Sistema para la Consulta de Información Censal SCINCE (a) (2020). Censo de Población y vivienda. https://gaia.inegi.org.mx/scince2020/

Secretaría de Economía (2020). Población Económicamente Activa. https://www.gob.mx/se

Sistema Automatizado de Información Censal SAIC (a) (2019). Número de empresas. https://www.inegi.org.mx/app/saic/

Sistema Automatizado de Información Censal SAIC (b) (2019). Ventas por internet. https://www.inegi.org.mx/app/saic/

Sánchez Juárez, Isaac Leobardo, & Moreno Brid, Juan Carlos. (2016). El Reto Del Crecimiento Económico En México: Industrias Manufactureras Y Política Industrial. Revista Finanzas y Política Económica, 8(2), 271-299. https://doi.org/10.14718/revfinanzpolitecon.2016.8.2.4

Sanchez Juarez, I. L. (2024). Desindustrialización prematura e informalidad laboral en América Latina. Instituto de Ciencias Sociales y Administración.

Gómez-Zaldívar, Fernando, & Gómez-Zaldívar, Manuel. (2023). Evolución manufacturera de Guanajuato: complejidad económica y estrategias industriales municipales. Problemas del desarrollo, 54(213), 73-102. Epub 07 de noviembre de 2023.https://doi.org/10.22201/iiec.20078951e.2023.213.69951

López Castro, E. (2016). Aglomeraciones económicas del sector industria manufacturera en México y su vínculo al desarrollo humano.

Sistema Automatizado de Información Censal SAIC (c) (2019). Empresas manufactureras. https://www.inegi.org.mx/app/saic/

Sistema Automatizado de Información Censal SAIC (d) (2019). Empleo subsector 31-33. https://www.inegi.org.mx/app/saic/

Sistema Automatizado de Información Censal SAIC (e) (2019). Remuneraciones. https://www.inegi.org.mx/app/saic/

Sistema para la Consulta de Información Censal SCINCE (b) (2020). Censo de Población y vivienda por municipio. https://gaia.inegi.org.mx/scince2020/

Sistema Automatizado de Información Censal SAIC (f) (2019). Producción Bruta Total. https://www.inegi.org.mx/app/saic/

Sistema Automatizado de Información Censal SAIC (g) (2019). Valor Agregado Censal Bruto. https://www.inegi.org.mx/app/saic/

Banco de Información Económica BIE (2019). Indicadores. https://inegi.org.mx/app/indicadores/?tm=0&t=10000215

Comisión Reguladora de Energía (2019). Precio del diésel 2018. https://www.gob.mx/cre

Instituto Nacional de Estadística y Geografía INEGI (2019). Finanzas públicas. https://www.inegi.org.mx/programas/finanzas/

Sistema para la Consulta de Información Censal SCINCE (c) (2020). Educación. https://gaia.inegi.org.mx/scince2020/

Sistema Automatizado de Información Censal SAIC (h) (2019). Inversión en Formación Bruta de Capital Fijo. https://www.inegi.org.mx/app/saic/

Instituto Mexicano de Propiedad Industrial (2020). Patentes Guanajuato. https://www.gob.mx/impi

Consejo Nacional de Población (2019) (a). Guanajuato https://www.gob.mx/conapo

Sistema Automatizado de Información Censal SAIC (i) (2019). Horas diarias trabajadas. https://www.inegi.org.mx/app/saic/

Flores-llhuicatzi, U., & Medina-Conde, A. (2018). Aceptación del concepto de Economía Social e identificación de grupos homogéneos en países de Latinoamérica y Europa. CienciaUAT, 12(2), 104-126.

Gere, A. (2023). Recommendations for validating hierarchical clustering in consumer sensory projects. Current Research in Food Science, 6, 100522.

Hirose, K., Miura, K., & Koie, A. (2023). Hierarchical clustered multiclass discriminant analysis via cross-validation. Computational Statistics & Data Analysis, 178, https://doi.org/10.1016/j.csda.2022.107613

Consejo Nacional de Población (2019). Bienestar y calidad de vida https://www.gob.mx/conapo

Downloads

Published

2025-01-05

How to Cite

Rodríguez, C. A., López Salazar, A. ., & Rocha Ibarra, J. E. (2025). Concentration factors of manufacturing companies in the State of Guanajuato: A cluster analysis. Journal of Administrative Science, 6(12), 10–18. https://doi.org/10.29057/jas.v6i12.13495