آسیب ‏شناسی کاربرد تحلیل عاملی اکتشافی در پژوهش ‏های گردشگری و میهمان‏ نوازی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کاندیدای دکتری، سنجش و اندازه گیری (روان‌سنجی)، دانشکده روانشناسی و علوم تربیتی، دانشگاه علامه طباطبائی، تهران، ایران.

2 کاندیدای دکتری، گردشگری، گروه مدیریت جهانگردی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران.

چکیده

زمینه و هدف: تحلیل عاملی اکتشافی (EFA)، به یکی از پرکاربردترین روش‌های آماری چندمتغیره در پژوهش های کاربردی در بسیاری از حوزه‌ها از جمله گردشگری و میهمان نوازی تبدیل ‌شده است. هدف مطالعه حاضر، شناسایی دلایل کاربست EFA، خطاهای رایج و به طور کلی آسیب شناسی استفاده از این روش در مطالعات گردشگری و میهمان نوازی می باشد.
روش شناسی: روش پژوهش حاضر بر مبنای هدف، اکتشافی-توصیفی بوده است. حجم نمونه، 66 مقاله منتشر شده از 7 نشریه علمی گردشگری بودند. بررسی مقالات از طریق تحلیل توصیفی (فراوانی و درصد) با استفاده از نرم افزار SPSS26 و Excel انجام پذیرفت.
یافته‌ها: بررسی ها نشان داد، در حدود 4% از پژوهش های منتشر شده در نشریات گردشگری از EFA استفاده می کنند و بیشترین گرایش تخصصی پژوهشگران جغرافیا است. از میان مراحل 5گانه ی انجام EFA، به ترتیب بیشتر به کمتر، مراحل حفظ عامل، استخراج عامل، چرخش عامل، غربالگری و کیفیت داده ها، و تفسیر-نامگذاری، گزارش نشده، نادیده گرفته شده و یا انجام نمی شوند.
نتیجه گیری و پیشنهادات: علیرغم سهولت انجام EFA به دلیل وجود نرم‌افزارهای مختلف، مراحل و مفروضات اساسی EFA، به طور منظم و دقیق در پژوهش های گردشگری و میهمان نوازی گزارش نمی شود یا نادیده گرفته می شود که قطع به یقین می تواند تضمین اعتبار پژوهش های گردشگری را زیر سوال ببرد.
نوآوری و اصالت: ضمن اینکه پژوهش برای اولین بار در حوزه ی پژوهش های گردشگری انجام شده است، بر اساس یافته ها و نتایج، یک جعبه ی ابزار با عنوان "فهرست نظارت" در سه فاز پیش‌تحلیل، تحلیل و پساتحلیل برای اطمینان از انجام و گزارش مراحل EFA برای پژوهشگران و ارزیابان پژوهش ها، طراحی و پیشنهاد گردید.

کلیدواژه‌ها


Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716-723.
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(2), 165-178.
Bandalos, D. L., & Finney, S. J. (2010). Factor analysis. Exploratory and confirmatory. In Hancock, G. R., & Mueller, R. O. (Eds.) , The reviewer’s guide to quantitative methods in the social science (pp. 93–114). New York: Routledge.
Bartholomew, D. J. (2007). Three faces of factor analysis, in Factor Analysis at 100: Historical Developments and Future Directions, eds R. Cudeck and R. C. MacCallum (Mahwah, NJ: Lawrence Erlbaum Associates), 9-21.
Beavers, A. S., Lounsbury, J. W., Richards, J. K., Huck, S. W., Skolits, G. J., &  Esquivel, S. L. (2013). Practical considerations for using exploratory factor analysis in educational research. Practical Assessment, Research, and Evaluation, 18(1), 1-13.
Bollen, K. A. (1989). Structural equations with latent variables. John Wiley & Sons.
Braeken, J., & Van Assen, M. A. (2017). An empirical Kaiser criterion. Psychological methods, 22(3), 450-566.
Cattell, R. B. (1966). The scree test for the number of factors. Multivariate behavioral research, 1(2), 245-276.
Cattell, R. B. (1978). Fixing the number of factors: The most practicable psychometric procedures. The scientific use of factor analysis in behavioral and life sciences, 72-91.
Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological bulletin, 70(6), 426-443.
Comrey, A., & Lee, H. (1992). A first course in factor analysis (2nd edn.) Lawrence Earlbaum associates. Publishers: Hillsdale, New Jersey.
Conway, J. M., & Huffcutt, A. I. (2003). A Review and Evaluation of Exploratory Factor Analysis Practices in Organizational Research. Organizational Research Methods, 6(2), 147-168.
Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(1), 1-9.
Crawford, A. V., Green, S. B., Levy, R., Lo, W. J., Scott, L., Svetina, D., & Thompson, M. S. (2010). Evaluation of parallel analysis methods for determining the number of factors. Educational and Psychological Measurement, 70(6), 885-901.
Cudeck, R., & O’Dell, L. L. (1994). Applications of standard error estimation in unrestricted factor analysis: Significance tests for factor loadings and correlations. Psychological Bulletin, Vol. 115,475-487.
De Winter, J. C. F., & Dodou, D. (2012). Response to commentary on The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis. Journal of Safety Research, 43(1), 85-90.
Everitt, B. S. (1975). Multivariate analysis: The need for data, and other problems. The British Journal of Psychiatry, 126(3), 237-240.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272-299.
Fava, J. L., & Velicer, W. F. (1992). The effects of over-extraction on factor and component analysis. Multivariate Behavioral Research, 27(3), 387-415.
Ferguson, G. A. (1941). The factorial interpretation of test difficulty. Psychometrika, 6(5), 323-329.
Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modeling. Structural equation modeling: A second course, 10(6), 269-314.
Flora, D. B., LaBrish, C., & Chalmers, R. P. (2012). Old and new ideas for data screening and assumption testing for exploratory and confirmatory factor analysis. Frontiers in psychology, Vol. 3, 1-21.
Fokkema, M., & Greiff, S. (2017). How performing PCA and CFA on the same data equals trouble. European Journal of Psychological Assessment, 33(6), 399-402.
Ford, J. K., Maccallum, R. C., & Tait, M. (1986). The application of exploratory factor analysis in applied psychology: a critical review and analysis. Personal Psychology, 39(2), 291-314.
Gaskin, C. J., & Happell, B. (2014). On exploratory factor analysis: A review of recent evidence, an assessment of current practice, and recommendations for future use. International Journal of Nursing Studies, 51(3), 511-521.
Goretzko, D., Pham, T. T. H., & Bühner, M. (2021). Exploratory factor analysis: Current use, methodological developments and recommendations for good practice. Current Psychology, 40(7), 3510-3521.
Gorsuch, R. L. (1990). Common factor analysis versus component analysis: Some well and little known facts. Multivariate behavioral research, 25(1), 33-39.
Green, S. B., Akey, T. M., Fleming, K. K., Hershberger, S. L., & Marquis, J. G. (1997). Effect of the number of scale points on chi‐square fit indices in confirmatory factor analysis. Structural Equation Modeling: A Multidisciplinary Journal, 4(2), 108-120.
Green, S. B., Levy, R., Thompson, M. S., Lu, M., & Lo, W. J. (2012). A proposed solution to the problem with using completely random data to assess the number of factors with parallel analysis. Educational and Psychological Measurement, 72(3), 357-374.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2019). Multivariate data analysis. UK: Cengage.
Henson, R. K., & Roberts, J. K. (2006). Use of Exploratory Factor Analysis in Published Research: Common Errors and Some Comment on Improved Practice. Educational and Psychological Measurement, 66(3), 393-416.
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179-185.
Howard, M. C. (2016). A review of exploratory factor analysis decisions and overview of current practices: What we are doing and how can we improve? International Journal of Human-Computer Interaction, 32(1), 51-62.
Howard, M. C. (2023). A systematic literature review of exploratory factor analyses in management. Journal of Business Research, Vol. 164, 1-14.
Howard, M. C., & Henderson, J. (2023). A review of exploratory factor analysis in tourism and hospitality research: Identifying current practices and avenues for improvement, Journal of Business Research, Vol. 154, 1-14
Jöreskog, K. G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36(4), 409-426.
Kline, P. (2014). An easy guide to factor analysis. Routledge.
Knapp, T. R. (1978). Canonical correlation analysis: A general parametric significance-testing system. Psychological Bulletin, 85(2), 410-416.
Knekta E., Runyon, C., Eddy, S. (2019). One Size Doesn't Fit All: Using Factor Analysis to Gather Validity Evidence When Using Surveys in Your Research. CBE—Life Sciences Education, 18(1), 1-17.
Larsen, R., & Warne, R. T. (2010). Estimating confidence intervals for eigenvalues in exploratory factor analysis. Behavior Research Methods, 42(3), 871-876.
Ledesma, R. D., Ferrando, P. J., Trogolo, M. A., Poo, F. M., Tosi, J. D., & Castro, C. (2021). Exploratory factor analysis in transportation research: Current practices and recommendations. Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 78, 340-352.
Luo, L., Arizmendi, C., & Gates, K. M. (2019). Exploratory factor analysis (EFA) programs in R. Structural Equation Modeling: A Multidisciplinary Journal, 26(5), 819-826.
MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological methods, 4(1), 84-99.
Maskey, R., Fei, J., & Nguyen, H. O. (2018). Use of exploratory factor analysis in maritime research. The Asian Journal of Shipping and Logistics, 34(2), 91-111.
Meyers, L. S., Gamst, G., & Guarino, A. J. (2016). Applied multivariate research: Design and interpretation. Sage publications.
Osborne, J. W. (2015). What is rotating in exploratory factor analysis? Practical Assessment, Research, and Evaluation, 20(1), 1-7.
Park, H. S., Dailey, R., Lemus, D. (2006). The Use of Exploratory Factor Analysis and Principal Components Analysis in Communication Research. Human communication research, 28(4), 562-577.
Preacher, K. J., Zhang, G., Kim, C., & Mels, G. (2013). Choosing the optimal number of factors in exploratory factor analysis: A model selection perspective. Multivariate Behavioral Research, 48(1), 28-56.
Raîche, G., Walls, T. A., Magis, D., Riopel, M., & Blais, J. G. (2013). Non-graphical solutions for Cattell’s scree test. Methodology, 9(1), 23-29.
Reio, T. G., Jr, & Shuck, B. (2015). Exploratory factor analysis: Implications for theory, research, and practice. Advances in Developing Human Resources, 17(1), 12-25.
Roberson, R. B., Elliott, T. R., Chang, J. E., & Hill, J. N. (2014). Exploratory factor analysis in Rehabilitation Psychology: A content analysis. Rehabilitation Psychology, 59(4), 429-438.
Rummel, R. J. (1988). Applied factor analysis. Northwestern University Press.
Ruscio, J., & Roche, B. (2012). Determining the number of factors to retain in an exploratory factor analysis using comparison data of known factorial structure. Psychological assessment, 24(2), 282-292.
Sakaluk, J. K., & Short, S. D. (2017). A methodological review of exploratory factor analysis in sexuality research: Used practices, best practices, and data analysis resources. The Journal of Sex Research, 54(1), 1-9.
Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464.
Spearman, C. (1961). “General Intelligence” Objectively Determined and Measured. American journal of psychology. 15(2), 201-292.
Steiner, M. D., & Grieder, S. (2020). EFAtools: An R package with fast and flexible implementations of exploratory factor analysis tools. Journal of Open Source Software, 5(53), 1-4.
Stevens, J. (1996). Categorical data: The log linear model. Applied multivariate statistics for the social sciences (3rd ed., pp. 518-557). Mahwah, NJ: Lawrence Erlbaum Associates.
Tabachnick, B. G., Fidell, L. S. (2013). Using multivariate statistics. Boston, MA: pearson.
Thompson, B., & Daniel, L. G. (1996). Factor analytic evidence for the construct validity of scores: A historical overview and some guidelines. Educational and psychological measurement, 56(2), 197-208.
Timmerman, M. E., & Lorenzo-Seva, U. (2011). Evaluación de la dimensionalidad de elementos politómicos ordenados con análisis paralelo. Psychol Methods, 16(2), 209-220.
Velicer, W. F., & Fava, J. L. (1998). Affects of variable and subject sampling on factor pattern recovery. Psychological methods, 3(2), 231.
Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. D. Goffin & E. Helmes (Eds.) , Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (pp. 41–71).
Velicer, W. F., Peacock, A. C., & Jackson, D. N. (1982). A comparison of component and factor patterns: A Monte Carlo approach. Multivariate Behavioral Research, 17(3), 371-388.
Watkins, M. W. (2018). Exploratory Factor Analysis: A Guide to Best Practice. Journal of Black Psychology, 44(3), 219-246.
Watkins, M. W. (2021). A step-by-step guide to exploratory factor analysis with Stata. Routledge.
Yeomans, K. A., & Golder, P. A. (1982). The Guttman-Kaiser criterion as a predictor of the number of common factors. The Statistician, 31(3), 221-229.