Published: 2026-02-17

Determinantes del éxito en la implementación de Lean Manufacturing en maquiladoras mexicanas Determinants of Success in the Implementation of Lean Manufacturing in Mexican Maquiladoras

Main Article Content

How to Cite

Alvarado Lagunas, E., & Torres Herrera, E. (2026). Determinants of Success in the Implementation of Lean Manufacturing in Mexican Maquiladoras. Administración & Desarrollo, 56(1), e-1240. https://doi.org/10.22431/25005227.1240

Problemática: la alta competencia global y la presión por elevar la productividad obligan a las pequeñas y medianas empresas maquiladoras a optimizar sus procesos sin comprometer la calidad ni la sostenibilidad. Objetivo: analizar los factores organizacionales que inciden en el éxito de la implementación del modelo Lean Manufacturing (LM) en empresas de Reynosa, Tamaulipas, México. Metodología: se utilizó un enfoque cuantitativo con aplicación de encuestas a 84 líderes estratégicos de empresas maquiladoras. Se empleó un modelo de regresión lineal múltiple para evaluar el impacto de cinco variables independientes: compromiso de la alta dirección, capacitación del personal, liderazgo transformacional, enfoque al cliente y colaboración con proveedores. Resultados: se encuentra que el liderazgo transformacional, el compromiso de la alta dirección, la capacitación y el enfoque al cliente influyen en el éxito de la implementación del modelo LM. En cambio, la colaboración con proveedores no mostró un efecto estadísticamente significativo en este contexto. Conclusión: el éxito en la implementación del modelo LM depende de factores internos, especialmente del liderazgo y el compromiso directivo. La adopción de herramientas LM debe ir acompañada de una cultura organizacional adecuada. El estudio aporta evidencia empírica desde el contexto mexicano y propone un modelo replicable para industrias similares.

Keywords:
lean facturing, industria maquiladora, liderazgo transformacional, enfoque al cliente

Problem statement: High global competition and pressure to increase productivity are forcing small and medium-sized maquiladora companies to optimize their processes without compromising quality or sustainability.. Objective: To analyze the organizational factors that influence the successful implementation of the Lean Manufacturing (LM) model in companies in Reynosa, Tamaulipas, Mexico. Methodology: A quantitative approach was employed, applying surveys to 84 strategic leaders of maquiladora companies. Multiple linear regression analysis was used to assess the impact of five independent variables: top management commitment, employee training, transformational leadership, customer focus, and supplier collaboration. Results: The results show that transformational leadership, top management commitment, training, and customer focus significantly influence the successful implementation of the Lean Manufacturing model. In contrast, supplier collaboration did not show a statistically significant effect in this context. Conlcusion: Success in implementing the Lean Manufacturing model mainly depends on internal factors, especially leadership and top management commitment. The adoption of lean tools must be accompanied by an appropriate organizational culture. The study provides empirical evidence from the Mexican context and proposes a replicable model for similar industries.

Keywords:
lean manufacturing, maquiladora industry, transformational leadership, customer focus

Elias Alvarado Lagunas, Universidad Autónoma de Nuevo León

PhD in Social Sciences, with summa cum laude honors, from Universidad Autónoma de Nuevo León (UANL). Professor and researcher at the Faculty of Public Accounting and Administration (FACPYA) at UANL.

Evaristo Torres Herrera, Universidad Autónoma de Nuevo León

PhD candidate in Philosophy with a focus on Administration at the School of Public Accounting and Administration. He holds a degree in Electronic Systems Engineering from the Monterrey Institute of Technology and Higher Education (ITESM) and a Master's in Business Administration (MBA) from the same institution. 


Dimensions

PlumX

Downloads

Download data is not yet available.

Visitas

66

References

Adetunji, A. (2025). Type 1 error rate of some normality tests. Journal of Multidisciplinary Science: MIKAILALSYS, 3(1), 5234. https://doi.org/10.58578/mikailalsys.v3i1.5234

Adhikari, G. (2022). Interpreting the basic results of multiple linear regression. Scholars’ Journal, 5(1), 22-37. https://doi.org/10.3126/scholars.v5i1.55775

Alshammakhi, Y., Mohammed, A., Mazher, K., y Ghaithan, A. (2023). Integrated impact of circular economy, Industry 4.0, and lean manufacturing on sustainability performance of manufacturing firms. International Journal of Environmental Research and Public Health, 20. https://doi.org/10.3390/ijerph20065119

Antony, J., Barclay, R., Shetty, S., y Cudney, E. (2021). Determining critical success factors for lean implementation. Total Quality Management & Business Excellence, 33, 818–832. https://doi.org/10.1080/14783363.2021.1894919

Azian, A., Ibrahim, D., Mamat, R., y Abu, F. (2025). Lean Manufacturing and Industry 4.0: Unveiling trends, applications, and global impacts in manufacturing through comprehensive literature review. Jurnal Kejuruteraan, 37(1). https://doi.org/10.17576/jkukm-2025-37(1)-10

Baez, Y., Tlapa, D., Limón, J., De La Vega, M., Macias, S., y Chávez, E. (2023). Modeling critical success factors of Lean strategy in the manufacturing industry. Systems, 11(10), 490. https://doi.org/10.3390/systems11100490

Bromsen, A. (2019). Condescending saviors: union substitution at Toyota Motor Manufacturing Kentucky (TMMK) [Tesis doctoral, Wayne State University]. ProQuest. https://www.proquest.com/openview/f849896468125e8c67e4f4e009dc1822/1?pq-origsite=gscholar&cbl=18750&diss=y

Buniya, M., Mewada, B., Qureshi, K., y Qureshi, M. (2023). Analyzing critical success factors of Lean 4.0 implementation in small and medium enterprises for sustainable manufacturing supply chain for Industry 4.0 using PLS-SEM. Sustainability, 15(6), 5528. https://doi.org/10.3390/su15065528

Cochran, W. G. (1977). Sampling techniques (3rd ed.). John Wiley & Sons.

Correa da Cunha, H., Singh, V., y Farrell, C. (2023). Host country cultural profile and the performance of foreign subsidiaries in Latin America. International Journal of Cross Cultural Management, 23(3), 531–555. https://doi.org/10.1177/14705958231204728

Credé, M., y Harms, P. D. (2021). Three cheers for descriptive statistics—and five more reasons why they matter. Industrial and Organizational Psychology, 14(4), 486–488. https://doi.org/10.1017/iop.2021.110

Creswell, J. W., y Hirose, M. (2019). Mixed methods and survey research in family medicine and community health. Family medicine and community health, 7(2), 1-6. https://doi.org/10.1136/fmch-2018-000086

Desai, T., y Parmar, P. (2020). Evaluating Sustainable Lean Six Sigma enablers using fuzzy DEMATEL: A case of an Indian manufacturing organization. Journal of Cleaner Production, 265, 121802. https://doi.org/10.1016/j.jclepro.2020.121802

Flores, D., Maldonado, A., Tlapa, D., Borbón, M., De La Vega, M., Limón, J., y Baez, Y. (2020). Lean Manufacturing critical success factors for the transportation equipment manufacturing industry in Mexico. IEEE Access, 8, 168534–168545. https://doi.org/10.1109/ACCESS.2020.3023633

Fortuny, J., Ruiz, P., Zubeltzu, E., y Luján, I. (2024). Lean manufacturing and environmental performance: A meta-analytic approach. International Journal of Lean Six Sigma. Advance online publication. https://doi.org/10.1108/IJLSS-11-2023-0190

Ganga, G., Filho, M., y Sasso, R. (2024). Synergizing lean management and circular economy: Pathways to sustainable manufacturing. Corporate Social Responsibility and Environmental Management. https://doi.org/10.1002/csr.2962

Gatell, I., y Avella, L. (2024a). Impact of Industry 4.0 and circular economy on lean culture and leadership: Assessing digital green lean as a new concept. European Research on Management and Business Economics. https://doi.org/10.1016/j.iedeen.2023.100232

Gatell, I., y Avella, L. (2024b). A maturity model for assessing digital green lean leadership and culture implementation in manufacturing companies. Total Quality Management & Business Excellence, 35, 860–897. https://doi.org/10.1080/14783363.2024.2347373

Habibzadeh, F. (2024). Data distribution: Normal or abnormal? Journal of Korean Medical Science, 39, e35. https://doi.org/10.3346/jkms.2024.39.e35

Hasiloglu, S., y Hasiloglu-Ciftciler, M. (2023). What should be the measure of conformity to normal distribution (normality) test in Likert type digital and face-to-face survey data? Journal of Internet Applications and Management, 14(1). https://doi.org/10.34231/iuyd.1346463

INEGI. (15 de febrero de 2025). Producto interno bruto por actividades secundarias. https://www.inegi.org.mx/app/indicadores/?t=87&ag=00#D87

Jankovic, S. (2022). The multivariate statistical analysis – Multiple linear regression. International Journal on Biomedicine and Healthcare, 10(4), 173–175. https://doi.org/10.5455/ijbh.2022.10.173-175

Kumar, A. S., Babu, R. V., Paranitharan, K. P., y Kumar, K. S. (2024). Lean implementation in manufacturing SMEs: A systematic review. AIP Conference Proceedings, 2935(1), 020010. https://doi.org/10.1063/5.0198915

Le, T., y Le, H. (2024). Linking smart manufacturing technologies and sustainable corporate performance: Evidence from emerging economy. Operations Management Research. https://doi.org/10.1007/s12063-024-00525-w

Ljungblom, M., y Lennerfors, T. T. (2021). The lean principle respect for people as respect for craftsmanship. International Journal of Lean Six Sigma, 12(6), 1209-1230. https://doi.org/10.1108/IJLSS-06-2020-0085

Li, Q. (2024). Discussion on the shortcomings and countermeasures of lean management in manufacturing industry in the Industry 4.0 era. Scientific Journal of Economics and Management Research, 6(9), 1-12. https://doi.org/10.54691/a91rts90

López, C. F., y Huamán, L. A. (2024). Cadena de valor: modelo de gestión para la formación inicial del profesorado. Formación universitaria, 17(2), 47-60. https://doi.org/10.4067/s0718-50062024000200047

Maqueira, J., Garcia, N., Romano, P., Molinaro, M., y Moyano, J. (2023). Strategic supplier performance in a competitive landscape: Enhancing organizational performance through lean supply chain management. BRQ Business Research Quarterly, 28, 474–490. https://doi.org/10.1177/23409444231210566

Manogaran, M., Abubakar, U., Aisami, A., y Shukor, M. (2021). Test for the presence of autocorrelation in the Morgan-Mercer-Flodin (MMF) model used for modelling the total number of COVID-19 cases for Brazil. Bulletin of Environmental Science and Sustainable Management, 5(1), 32-36. https://doi.org/10.54987/bessm.v5i1.589

Metwally, A., y Buhaya, M. (2024). The interplay between digital technologies and sustainable performance: Does lean manufacturing matter? Sustainability, 16(22), 10002. https://doi.org/10.3390/su162210002

Murphy, K. R. (2021). In praise of Table 1: The importance of making better use of descriptive statistics. Industrial and Organizational Psychology, 14(4), 461–477. https://doi.org/10.1017/iop.2021.90

O’Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673–690. https://doi.org/10.1007/s11135-006-9018-6

Oliveira, B., Alves, A. C., Carneiro, P., y Ferreira, A. C. (2018). Lean Production and Ergonomics: a synergy to improve productivity and working conditions. International Journal of Occupational and Environmental Safety, 2(2), 1–11. https://doi.org/10.24840/2184-0954_002.002_0001

Phanden, R., Kumar, S., Jayaraman, R., Swarnakar, V., Khanduja, D., y Antony, J. (2023). Analyzing critical success factors of Lean Six Sigma for implementation in Indian manufacturing MSMEs using best-worst method. Benchmarking: An International Journal, 31(9), 2960–2983. https://doi.org/10.1108/bij-08-2022-0540

Pineda, J. A. C. (2021). Adopción parcial e integral de las prácticas del sistema técnico de Lean en la industria maquiladora de manufactura en México. RECAI Revista de Estudios en Contaduría, Administración e Informática, 11(30), 28-50. https://doi.org/10.36677/recai.v11i30.16919

Piwowar, K. (2020). Pro-environmental organizational culture: Its essence and a concept for its operationalization. Sustainability, 12(10), 4197. https://doi.org/10.3390/su12104197

Qureshi, K., Qureshi, M., Mewada, B., y Kaur, S. (2023). Assessing Lean 4.0 for Industry 4.0 Readiness Using PLS-SEM towards Sustainable Manufacturing Supply Chain. Sustainability. https://www.mdpi.com/2071-1050/15/5/3950

Raktate, O., Jha, V. C., y Vanarotti, M. B. (2024). Productivity improvement in the manufacturing industry through the implementation of LM tools. AIP Conference Proceedings, 3178(1), 070003. https://doi.org/10.1063/5.0229539

Riepina, I. (2023). Using the lean manufacturing methodology to improve the quality of the enterprise’s business processes. Management, 37(1), 39–49. https://doi.org/10.30857/2415-3206.2023.1.4

Rojas, T., Mula, J., y Sanchis, R. (2023). Quantitative modelling approaches for lean manufacturing under uncertainty. International Journal of Production Research, 62(16), 5989–6015. https://doi.org/10.1080/00207543.2023.2293138

Rositas, J. (2014). Los tamaños de las muestras en encuestas de las ciencias sociales y su repercusión en la generación del conocimiento (Sample sizes for social science surveys and impact on knowledge generation). Innovaciones de negocios, 11(22), 235-268. http://eprints.uanl.mx/id/eprint/12605

Saraswat, P., Agrawal, R., y Rane, S. B. (2024). Technological integration of lean manufacturing with Industry 4.0 toward lean automation: Insights from the systematic review and further research directions. Benchmarking: An International Journal, 32(6), 1909–1941. https://doi.org/10.1108/BIJ-05-2023-0316

Saad, S., Bahadori, R., Bhovar, C., y Zhang, H. (2023). Industry 4.0 and Lean Manufacturing: A systematic review of the state-of-the-art literature and key recommendations for future research. International Journal of Lean Six Sigma, 15(5), 997–1024. https://doi.org/10.1108/IJLSS-02-2022-0021

Shichiyakh, R., Belova, N., Hajiyev, H., Bobrova, A., Vetrova, E., Bankova, N., Sergeeva, S., y Vaslavskaya, I. (2024). Implementation of lean manufacturing principles and fast structured logic methods in the organizational culture: Addressing challenges and maximizing efficiency. International Journal of Sustainable Development and Planning, 19(3), 963–970. https://doi.org/10.18280/ijsdp.190337

Shukor, M. (2021). Autocorrelation test for the residual data from the pseudo-1st order kinetic model of the brominated flame retardant 4-bromodiphenyl ether adsorption onto biochar-immobilized Sphingomonas sp. Journal of Environmental Bioremediation and Toxicology, 4(1), 35–39. https://doi.org/10.54987/jebat.v4i1.583

Singh, D., Kumar, P., Bhamu, J., y Goel, S. (2024). Interpretive structural modeling of Lean Six Sigma critical success factors in the context of Industry 4.0 for Indian manufacturing industries. International Journal of System Assurance Engineering and Management, 15, 3776–3793. https://doi.org/10.1007/s13198-024-02375-y

Templ, M. (2023). Leveraging Sankey diagrams for enhanced curriculum planning in higher education. The Curriculum Journal, 36(1). https://doi.org/10.1002/curj.299

Torres, E. y E. Alvarado (2023). Análisis sistemático de la relación de satisfacción laboral y liderazgo trasformacional. Innovaciones de Negocio, 20(39), 122-139. https://doi.org/10.29105/revin20.39-414

Turgay, S., Pirvan, S., y Cebeci, Ç. (2023). Lean Manufacturing Implementation for Process Improvement in the Cable Company: A Comprehensive Approach. Manufacturing and Service Operations Management, 4(5), 1–11. https://doi.org/10.23977/msom.2023.040501

United Nations statistics Division. (2025). International Trade. United Nations, Department of Economic and Social Affairs. https://unstats.un.org/unsd/snaama/Basic

Vargas, T., y Yagüe, R. M. (2024). Organizational culture and innovation: Exploring the “black box.” European Journal of Management and Business Economics, 33(2), 174–194. https://doi.org/10.1108/EJMBE-07-2021-0203

Ventura, J., y Peña, B. N. (2021). The world should not revolve around Cronbach’s alpha ≥ .70. Adicciones, 33(4), 369–372. https://doi.org/10.20882/adicciones.1576

Womack, J. P., y Jones, D. T. (1996). Lean thinking: Banish waste and create wealth in your corporation. Simon & Schuster.

Yang, K., Justin, T., y T. Chien (2019). Homoscedasticity: An overlooked critical assumption for linear regression. General Psychiatry, 32(5), e100148. https://doi.org/10.1136/gpsych-2019-100148

Yuik, C., Feng, C., y Perumal, P. (2020). Exploring critical success factors for the implementation of Lean Manufacturing in machinery and equipment SMEs. Engineering Management in Production and Services, 12, 77–91. https://doi.org/10.2478/emj-2020-0029

Zwinderman, A., y Cleophas, T. (2021). Analysis of variance (ANOVA). En Regression analysis in medical research (pp. 63–74). Springer. https://doi.org/10.1007/978-3-030-61394-5_7