Süpermarket Müşterilerinin Hizmet ve Ürün Kalitesi Algılarıyla Birinci ve İkinci Mertebe Doğrulayıcı Faktör Modelleri: Deneysel Bir Araştırma

Year 2016, , 115 - 146, 08.12.2016

Gülhayat Gölbaşı Şimşek

https://doi.org/10.17093/alphanumeric.277738

Abstract

Pazarlama literatüründe müşterilerin hizmet kalitesi algılarının kavramsallaştırılması ve ölçülmesi için önerilen birçok model bulunmaktadır. Bu çalışmada, bağımsız küme faktör modeli (korelasyonlu faktör modeli) ve ikinci mertebe (hiyerarşik) faktör modeli gibi çok-boyutlu faktör modelleri geliştirilerek ve tahmin edilerek, Türkiye perakende sektöründe faaliyet gösteren zincir süpermarketlerin müşterilerinin hizmet kalitesi algılarının modellenmesi için ampirik bir değerlendirme yapılmıştır. Bu amaçla kurulan hiyerarşik faktör modelinde, etkileşim kalitesi, fiziksel özellikler ve güvenilirlik faktörleri, ikinci mertebeden hizmet kalitesi faktörünün birinci mertebe faktörleri olarak ele alınmıştır. Bununla beraber, süpermarketler söz konusu olduğunda, müşterilerin kalite algılarının anlamak ve ölçmek için sadece hizmet kalitesinin değerlendirilmesi yeterli olmadığından, ürün kalitesi algıları da modellere dahil edilerek hizmet kalitesi ile birlikte değerlendirilmişlerdir. Müşteriler tarafından algılanan ürün kalitesi ve süpermarketlerdeki ürün politikası faktörlerinin hem birinci mertebe korelasyonlu faktör modelinde hem de hizmet kalitesinin ikinci mertebe faktör olduğu hiyerarşik modelde, hizmet kalitesi boyutları ile korelasyonlu olmasına izin verilerek kurulan modellerin doğrulayıcı faktör analizleri sonuçlarına göre, geçerli ve güvenilir ölçümleri ile beş faktörlü birinci mertebeden korelasyonlu faktör modeli, ikinci mertebeden hizmet kalitesi içeren modelden daha iyi uyum göstermiştir.

Keywords

Hizmet kalitesi, etkileşim kalitesi, fiziksel özellikler, güvenilirlik, algılanan ürün kalitesi, ürün politikası, doğrulayıcı faktör analizi, ikinci mertebe faktör

First and Second Order Confirmatory Factor Models With Service And Product Quality Perceptions of Supermarket Customers: An Empirical Investigation

Abstract

There are various models proposed for conceptualization and measurement of customers’ perceptions of service quality in the marketing literature. This study presents an empirical evaluation of customers’ perceptions of service quality in the chain supermarkets within the Turkish retail sector through developing and estimating multidimensional factor models such as independent clusters factor model (correlated factor model) and second order (hierarchical) factor model. For this purpose, interaction quality, physical aspects and reliability dimensions of service quality were conceptualized as first order factors of a superordinate second order factor of service quality in the hierarchical model. However, product quality perceptions were also considered because service quality alone is not enough to explain quality in all respects for supermarkets. With considering customer perceived product quality and product policy as product quality dimensions correlated with first and second order service quality factors, confirmatory analyses indicated that the first-order model consisting of five correlated factors −for which valid and reliable measures are provided− has better fit than the model with  the second order service quality factor.

Keywords

confirmatory factor analysis, interaction quality, perceived product quality, physical aspects, product policy, reliability, second order factor, Service quality

References

• Akter, S., D’Ambra, J., & Ray, P. (2010). Service quality of mHealth platforms: Development and validation of a hierarchical model using PLS. Electron Markets, 20(3), 209-227.
• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
• Arrindell, W. A., & van der Ende, J. (1985). An empirical test of the utility of the observations-to-variables ratio in factor and components analysis. Applied Psychological Measurement, 9, 165 - 178.
• Bentler, P.M., & Bonnet, D.C. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88 (3), 588-606.
• Brady, M. K., & Cronin, J. J. (2001). Some new thoughts on conceptualizing perceived service quality: A hierarchical approach. Journal of Marketing, 65(3), 34-49.
• Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum Associates.
• Chahal, H., & Kumari, N. (2010). Development of multidimensional scale for healthcare service quality (HCSQ) in Indian context. Journal of Indian Business Research, 2(4), 230-255.
• Child, D. (2006). The essentials of factor analysis. (3rd ed.). New York, NY: Continuum International Publishing Group.
• Comrey, A.L., & Lee, H.B. (1992). A first course in factor analysis (2nd edition). Hillsdale,NJ: Lawrence Erlbaum Associates.
• Cronin, J. J., & Taylor, S. A. (1992). Measuring service quality - A reexamination and extension. Journal of Marketing, 56(3), 55-68.
• Dabholkar, P. A., Thorp, D. I., & Rentz, J. O. (1996). A measure of service quality for retail stores: Scale development and validation. Journal of the Academy of Marketing Science, 24(1), 3-16.
• Dagger, T. S., Sweeney, J. C., & Johnson, L. W. (2007). A hierarchical model of health service quality: Scale development and investigation of an integrated model. Journal of Service Research, 10(2), 123-142.
• Diamantopoulos, A. & Siguaw, J.A. (2000). Introducing LISREL. London: Sage Publications.
• Field, A. (2009). Discovering Statistics using SPSS. London: Sage Publications.
• Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1), 39-50.
• Garvin, D. A. (1987). Competing on the eight dimensions of quality. Harvard Business Review, 65(6), 101–109.
• Grönroos, C. (1984). A service quality model and its marketing implications. European Journal of Marketing, 18(4), 36-44.
• Hair, Jr., J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.) Upper Saddle River, NJ: Pearson Prentice Hall.
• Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
• Horn, J.L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179–185.
• Hu, L.T., & Bentler, P.M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural Equation Modeling. Concepts, Issues, and Applications (pp. 76-99). London: Sage.
• Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6 (1), 1-55.
• Hutcheson, G., & Sofroniou, N. (1999). The multivariate social scientist: Introductory statistics using generalized linear models. Thousand Oaks, CA: Sage Publications.
• Kline, R. B. (2011). Principles and practice of structural equation modeling. Third Edition, New York: The Guilford Press.
• Lei, M., & Lomax, R. G. (2005). The effect of varying degrees of nonnormality in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 12, 1-27.
• MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological methods, 4(1), 84.
• MacCallum, R.C., Browne, M.W., & Sugawara, H.M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1 (2), 130-49.
• McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah NJ: Erlbaum.
• Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
• Osborne, J.W., & Fitzpatrick, D.C. (2012). Replication analysis in exploratory factor analysis: What it is and why it makes your analysis better. Practical Assessment, Research & Evaluation, 17(15), (http://pareonline.net/getvn.asp?v=17&n=15).
• Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). Servqual: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.
• Rust, R. T., & Oliver, R. L. (1994). Service quality: Insights and manegerial implications from the frontier. In R. T. Rust & R. L. Oliver (Eds.), Service Quality: New Directions in Theory and Practice (pp. 1-19). Thousand Oaks, CA: Sage Publication.
• Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures, Methods of Psychological Research-Online, 8, 23-74.
• Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Upper Saddle River, NJ: Pearson Allyn & Bacon.
• Wheaton, B., Muthen, B., Alwin, D., F., & Summers, G. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8 (1), 84-136.
• Torlak, Ö., Uzkurt, C., & Özmen, M.,Dimensions of service quality in grocery retailing: a case from Turkey,413- 422,2010,33