Percepción de la calidad de servicio técnico en distribución eléctrica: un análisis multi-grupo entre clientes residenciales urbanos y suburbanos
Perception of technical service quality in electrical distribution systems: a multi-group analysis of urban and suburban residential customers
DOI:
https://doi.org/10.56712/latam.v5i6.3190Palabras clave:
sistema de distribución de energía eléctrica, ecuaciones estructurales CB-SEM, calidad de servicio técnico, invarianza de medida, análisis multi-grupoResumen
El presente trabajo evalúa la percepción de la calidad del servicio técnico en sistemas de distribución eléctrica, centrándose en clientes residenciales de zonas urbanas y suburbanas. Utilizando un modelo de ecuaciones estructurales (CB-SEM) con análisis multi-grupo, se evalúa la existencia de diferencias significativas en las percepciones de ambos grupos. Se estudian dos constructos independientes: ‘Frecuencia y Tiempo de Fallas’ y "Atención a Reclamos ante interrupciones no programadas del servicio", en relación con el constructo dependiente "Calidad de Servicio Técnico". La investigación contrasta hipótesis de moderación que suponen mayor sensibilidad en clientes urbanos, justificando prácticas empresariales que priorizan su atención. Los resultados, sin embargo, rechazan ambas hipótesis, mostrando que no hay diferencias estadísticamente significativas entre los dos grupos. Este hallazgo cuestiona ciertas prácticas de algunas empresas distribuidoras, remarcando la necesidad de políticas regulatorias más equitativas sobre la calidad del servicio técnico que deben recibir los clientes. El estudio se basa en datos de una encuesta realizada en Bariloche, Argentina, durante 2023.
Descargas
Citas
Abreu, P., Martins, A.G. (2021). Evaluation of service quality of distribution systems with critically located generators. International Transactions on Electrical Energy Systems. 31, e12852. https://doi.org/10.1002/2050-7038.12852
Aldás, J., Uriel, E. (2017). Análisis Multivariante Aplicado con R. 2da Edición. Paraninfo.
Anderson, J. C., Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), pp. 411–423. https://doi.org/10.1037/0033-2909.103.3.411
Bagozzi, R.P., YI, Y. (1998). On the Evaluation of Structural Equation Models. JAMS 16, pp. 74–94.
Barrera, R. B., García, A. N., & Moreno, M. R. (2014). Evaluation of the e-service quality in service encounters with incidents: Differences according to the socio-demographic profile of the online consumer. Revista Europea de Dirección y Economía de la Empresa, 23(4), pp. 184-193. https://doi.org/10.1016/j.redee.2014.09.001
Barrera-Barrera, R., Navarro-García, A., & Peris-Ortiz, M. (2015). Evaluation of quality in different electronic services: A multigroup analysis. The International Journal of Management Science and Information Technology (IJMSIT), (15), pp. 5-27.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, pp. 238–246. https://doi.org/10.1037/0033-2909.107.2.238
Bentler, P.M., Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, pp. 588–606. https://doi.org/10.1037/0033-2909.88.3.588
Bentler, P. M., & Chou, C.-P. (1987). Practical Issues in Structural Modeling. Sociological Methods & Research, 16(1), pp. 78-117. https://doi.org/10.1177/0049124187016001004
Brown, T. A. (2015). Confirmatory factor analysis for applied research. Guilford publications.
Browne, M. W., Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen and J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
Byrne, B. M. (2012). Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming. New York, NY: Routledge.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464-504. https://doi.org/10.1080/10705510701301834
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), pp. 233–255. https://doi.org/10.1207/S15328007SEM0902_5
Clifton, J. D. W. (2020). Managing Validity versus Reliability Trade-offs in Scale Building Decisions. Psychological Methods, 25(2), pp. 259–270. https://doi.org/10.1037/met0000226
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika. 16 (3): pp. 297-334.
Cronin Jr, J. J., Taylor, S. A. (1992). Measuring Service Quality: A Reexamination and Extension. Journal of Marketing, 56 (3), pp. 55-68.
Cronin Jr, J. J., Taylor, S. A. (1994). SERVPERF versus SERVQUAL: reconciling performance-based and perceptions-minus-expectations measurement of service quality. Journal of marketing, 58 (1), pp. 125-131.
Davidov, E., Meuleman, B., Cieciuch, J., Schmidt, P., & Billiet, J. (2014). Measurement equivalence in cross-national research. Annual review of sociology, 40(1), pp. 55-75. https://doi.org/10.1146/annurev-soc-071913-043137
Davidov, E., Schmidt, P., & Billiet, J. (Eds.). (2011). Cross-Cultural Analysis: Methods and Applications. Routledge.
De Mendonça, M. J. C., Pereira, A. O., Bellido, M. M. H., Medrano, L. A., & Pessanha, J. F. M. (2023). Service quality performance indicators for electricity distribution in Brazil. Utilities Policy, 80, 101481. https://doi.org/10.1016/j.jup.2022.101481
Flores, M., Waddams Price, C. (2018). The Role of Attitudes and Marketing in Consumer Behaviours in the British Retail Electricity Market. The Energy Journal, 39 (4), pp. 153-179.
Gomes, T. E. de O., Borniatti, A. R., Garcia, V. J., Santos, L. L. C. dos, Knak Neto, N., & Garcia, R. A. F. (2023). Clustering Electrical Customers with Source Power and Aggregation Constraints: A Reliability-Based Approach in Power Distribution Systems. Energies, 16(5), 2485. http://dx.doi.org/10.3390/en16052485
Fornell, C., Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39. https://doi.org/10/cwp
French, B. F., & Finch, H. W. (2006). Confirmatory factor analytic procedures for the determination of measurement invariance. Structural Equation Modeling, 13(3), pp. 378-402. https://doi.org/10.1207/s15328007sem1303_3
Hair, J., Anderson, R., Tatham, R. and Black, W. (1998). Multivariate data analysis. 5th Edition, Prentice Hall, New Jersey.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage.
He, J., & van de Vijver, F. J. R. (2012). Bias and equivalence in cross-cultural research. Online Readings in Psychology and Culture, 2(2), 8. https://doi.org/10.9707/2307-0919.1111
Henseler, J., Ringle, C.M. and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, Vol. 43 No. 1, pp. 115-135. https://doi.org/10.1007/s11747-014-0403-8
Hox, J. J., Moerbeek, M., & Van de Schoot, R. (2017). Multilevel Analysis: Techniques and Applications (3rd ed.). Routledge.
IEEE (2003). IEEE Guide for Electric Power Distrbution Realiability Indices. STD 1366TM.
Jain, T.K., Jain, N. (2021). Service Quality in the Energy Sector and Its Impact on Sustainability. In: Leal Filho, W., Marisa Azul, A., Brandli, L., Lange Salvia, A., Wall, T. (eds) Affordable and Clean Energy. Encyclopedia of the UN Sustainable Development Goals. Springer, Cham. https://doi.org/10.1007/978-3-319-95864-4_65
Jöreskog, K. G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36(4), pp. 409-426. https://doi.org/10.1007/BF02291366
Jöreskog, K. G., y Sörbom, D. (1981). LISREL V: Analysis of linear structural relationships by maximum likelihood and least squares methods (Research Report 81−8). Uppsala, Sweden: University of Uppsala, Department of Statistics.
Jou, Y.-T., Saflor, C. S., Mariñas, K. A., Young, M. N., Prasetyo, Y. T., & Persada, S. F. (2022). Assessing Service Quality and Customer Satisfaction of Electric Utility Provider’s Online Payment System during the COVID-19 Pandemic: A Structural Modeling Approach. Electronics, 11(22), 3646. http://dx.doi.org/10.3390/electronics11223646
Kaiser H. (1974). An index of factorial simplicity. Psychometrika, Vol. 39, pp 31–36.
Kenny, D. A., McCoach, D. B. (2003). Effect of the number of variables on measures of fit in structural equation modeling. Structural Equation Modeling, 10(3), pp. 333–351. https://doi.org/10.1207/S15328007SEM1003_1
Kline, R. B. (2023). Principles and Practice of Structural Equation Modeling (5th ed.). Guilford Press
Koufteros, X., & Marcoulides, G. A. (2006). Product development practices and performance: A structural equation modeling-based multi-group analysis. International Journal of Production Economics, 103(1), 286-307. https://doi.org/10.1016/j.ijpe.2005.08.004
Kyriazos, T. A. (2018). Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General. Psychology, 9, 2207-2230. https://doi.org/10.4236/psych.2018.98126
Marsh, H. W., Hau, K. T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11(3), pp. 320-341. https://doi.org/10.1207/s15328007sem1103_2
Martínez Ávila, M. (2021). Análise fatorial confirmatória: um modelo de gestão do conhecimento na universidade pública. RIDE. Revista Iberoamericana para la Investigación y el Desarrollo Educativo, 12(23). https://doi.org/10.23913/ride.v12i23.1103
Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93(3), pp. 568-592. https://doi.org/10.1037/0021-9010.93.3.568
Meitinger, K., Davidov, E., Schmidt, P., & Braun, M. (2020). Measurement invariance: Testing for it and explaining why it is absent. In Survey Research Methods. European Survey Research Association. Vol. 14, No. 4, pp. 345-349. https://doi.org/10.5167/uzh-192239
Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58(4), pp. 525–543. https://doi.org/10.1007/BF02294825
Meuleman, B., Żółtak, T., Pokropek, A., Davidov, E., Muthén, B., Oberski, D. L., ... & Schmidt, P. (2023). Why measurement invariance is important in comparative research. A response to Welzel et al. (2021). Sociological Methods & Research, 52(3), pp. 1401-1419.
Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge.
Millsap, R. E., & Meredith, W. (2007). Factorial invariance: Historical perspectives and new problems. In Factor analysis at 100 (pp. 145-166). Routledge.
Milfont, T. L., & Fischer, R. (2010). Testing measurement invariance across groups: Applications in cross-cultural research. International Journal of psychological research, 3(1), pp. 111-130. DOI: 10.21500/20112084.857
Muthén, B., & Asparouhov, T. (2012). Bayesian Structural Equation Modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), pp. 313–335. https://doi.org/10.1037/a0026802
Nigro H., González Císaro, S., Tripodi, G. (2014). Investigación Operativa, Año XXIIII, No. 36, pp. 81-99.
Lasker, J. (2024). Measurement Invariance Testing Works. Applied Psychological Measurement, 48(6), pp. 257-275. https://doi.org/10.1177/01466216241261708
Little, T. D. (2013). Longitudinal Structural Equation Modeling. Guilford Press.
Liu, F. M., Huang, Y. C., Ching, S. L., & Hu, Y. J. (2017). Discussion of the Measurement Invariance Across Gender in the Version of the Part of Responsiveness in Servqual Scale. In 2017 International Conference on Organizational Innovation (ICOI 2017) (pp. 56-58). Atlantis Press. https://doi.org/10.2991/icoi-17.2017.10
Luong, R., & Flake, J. K. (2023). Measurement invariance testing using confirmatory factor analysis and alignment optimization: A tutorial for transparent analysis planning and reporting. Psychological Methods, 28(4), pp. 905–924. https://doi.org/10.1037/met0000441
Olajuyin. E. A., Olulope, P. K., Fasina, E. T. (2022). An overview on reliability assessment in power systems using CI approaches. Archives of Electrical Engineering, Vol. 71(No 2), pp. 425-443. DOI:10.24425/aee.2022.140720
Parasuraman, A., Zeithaml, V., Berry, L. (1985). A Conceptual Model of Service Quality and Its Implications for Future Research. Journal of Marketing, Vol. 49, No. 4, pp. 41-50.
Parasuraman, A., Zeithaml, V., Berry, L. (1988). SERVQUAL: A multi-item scale for measuring consumer perceptions of the service quality. Journal of Retailing. Vol. 64, No. 1, pp. 12-40.
Parasuraman, A., Zeithaml, V., Berry, L. (1991). Refinement and Reassessment of the SERVQUAL Scale. Journal of Retailing, Vol. 67, No. 4, pp. 420-450.
Parasuraman, A., Zeithaml, V., Berry, L. (1994). Reassessment of Expectations as a Comparison Standard in Measuring Service Quality: Implications for Further Research. The Journal of Marketing, Vol. 58, issue 1, pp. 111-124.
Pavlov, G., Maydeu-Olivares, A., Shi, D. (2021). Using the Standardized Root Mean Squared Residual (SRMR) to Assess Exact Fit in Structural Equation Models. Educational and Psychological Measurement, 81(1), pp. 110–130. https://doi.org/10.1177/0013164420926231
Peña, D. (2002). Análisis de Datos Multivariantes. Mcgraw Hill Interamericana de España SL.
Protzko, J. (2022). Invariance: What Does Measurement Invariance Allow Us to Claim? Educational and Psychological Measurement, (0)0. https://doi.org/10.1177/00131644241282982
Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review, 41, 71-90. https://doi.org/10.1016/j.dr.2016.06.004
Rashid, S. (1985). Quality in Contestable Markets: ¿A Historical Problem? The Quarterly Journal of Economics, Vol. 103, No. 1, pp. 245-249.
Rutkowski, L., & Svetina, D. (2014). Assessing the hypothesis of measurement invariance in the context of large-scale international surveys. Educational and Psychological Measurement, 74(1), pp. 31-57. https://doi.org/10.1177/0013164413498257
Santos Neto, A. S., Reis, M. R., Coimbra, A. P., Soares, J. C., Calixto, W. P. (2022). Measure of customer satisfaction in the residential electricity distribution service using structural equation modeling. Energies, 15(3), 746. https://doi.org/10.3390/en15030746
Sarabia Sánchez, F. J. (2013). Métodos de Investigación Social y de la Empresa. Ediciones Pirámide.
Sass, D. A., & Schmitt, T. A. (2013). Testing measurement invariance using multigroup confirmatory factor analysis within a bifactor framework: A primer with Mplus and R. Frontiers in Psychology, 4, pp. 1-16. https://doi.org/10.3389/fpsyg.2013.00328
Satorra, A., Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Thousand Oaks, CA: Sage.
Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), pp. 507-514. https://doi.org/10.1007/BF02296192
Satorra, A., & Bentler, P. M. (2010). Ensuring positiveness of the scaled difference chi-square test statistic. Psychometrika, 75(2), pp. 243–248. https://doi.org/10.1007/s11336-009-9135-y
Schmitt, N., & Kuljanin, G. (2008). Measurement invariance: Review of practice and implications. Human Resource Management Review, 18(4), pp. 210-222. https://doi.org/10.1016/j.hrmr.2008.03.003
Schweickardt, G. (2023a). Percepción de la Calidad del Servicio Técnico en usuarios Residenciales de Sistemas de Distribución Eléctrica. LATAM Revista Latinoamericana De Ciencias Sociales Y Humanidades, 4(2), pp. 3885–3909. https://doi.org/10.56712/latam.v4i2.877
Schweickardt, G. (2023b). Percepción de la Calidad del Servicio Técnico en usuarios Residenciales de Sistemas de Distribución Eléctrica. LATAM Revista Latinoamericana De Ciencias Sociales Y Humanidades, 4(3), pp. 594–620. https://doi.org/10.56712/latam.v4i3.1100
Schweickardt, G. (2024). Costo de la calidad del servicio técnico desde la percepción de usuarios residenciales en sistemas de distribución eléctrica. LATAM Revista Latinoamericana De Ciencias Sociales Y Humanidades, 5(1), pp. 224 – 249. https://doi.org/10.56712/latam.v5i1.1584
Schweickardt, G., Pistonesi Castelli, H. (2008). Disputabilidad en los sistemas de redes de distribución eléctrica. un análisis desde los modelos de telecomunicaciones en el marco del paradigma económico neoclásico. Revista Energética, Nro. 39, pp. 11-23. Universidad Nacional de Colombia.
Sekhar, P. C., Deshpande, R. A., Sankar V. (2016). Evaluation and improvement of reliability indices of electrical power distribution system. 2016 National Power Systems Conference (NPSC), Bhubaneswar, India, 2016, pp. 1-6. DOI: 10.1109/NPSC.2016.7858838
Steenkamp, J.-B. E. M., & Baumgartner, H. (1998). Assessing measurement invariance in cross-national consumer research. Journal of Consumer Research, 25(1), pp. 78-90. https://doi.org/10.1086/209528
Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25, pp. 173–180.
Steiger, J. H., Lind, J. C. (1980). Statistically based tests for the number of common factors. Paper presented at the Annual Meeting of the Psychometric Society, Iowa City, IA.
Tucker, L. R., Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, pp. 1–10.
Van de Schoot, R., Lugtig, P., & Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9(4), pp. 486-492. https://doi.org/10.1080/17405629.2012.686740
Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), pp. 4-70. https://doi.org/10.1177/109442810031002
Welzel, C., Brunkert, L., Inglehart, R. F., & Kruse, S. (2019). Measurement equivalence? A tale of false obsessions and a cure. World Values Research, 11(3), pp. 54-84.
Welzel, C., Brunkert, L., Kruse, S., & Inglehart, R. F. (2021). Non-invariance? An overstated problem with misconceived causes. Sociological Methods & Research, 52(3), pp. 1368-1400. https://doi.org/10.1177/004912412199
Wheaton, B., Muthen, B., Alwin, D. F., Summers, G. (1977). Assessing Reliability and Stability in Panel Models. Sociological Methodology, 8 (1), pp. 84-136.
Widaman, K. F., Ferrer, E., & Conger, R. D. (2010). Factorial invariance within longitudinal structural equation models: Measuring the same construct across time. Child Development Perspectives, 4(1), pp. 10-18. https://doi.org/10.1111/j.1750-8606.2009.00110.x
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 73(6), pp. 913-934. doi: 10.1177/0013164413495237
Zhirkov, K & C. Welzel, C. (2022). Rethinking Measurement Equivalence: Why Non-Invariance Doesn’t Always Mean Non-Comparability. World Values Research, 14 (1), pp. 1-27.
