Research article of American Journal of Educational Research and Reviews
Use of item response theory in marketing research
Hyo Jin Eom1, John Hulland2, Jordan M. Wheeler2, Seock-Ho Kim2
1Korea University, 2University of Georgia
There are three purposes of this paper. The first is to present a brief introduction to item response theory in conjunction with marketing research. The second is to present a review of the current uses of item response theory in representative marketing research journals. The third is to present an example that illustrate and contrasts classical test theory and item response theory approaches to item and scale analysis. Several item response theory relevant papers were recently published in various marketing research journals. Because models under item response theory, from simple to complex, were used without any systematic introduction in marketing research, this paper briefly presents the main concepts in item response theory. A content analysis was done for the second purpose with 30 item response theory relevant articles in marketing research journals. Articles were sorted based on the taxonomy of item response theory models. Many articles reviewed relied on some type of unidimensional dichotomous item response theory models. Articles published recently within the past 10 years used more complicated item response theory models, both mathematically and statistically, than other previously published articles in marketing research journals. Lastly, data from a scale with three Likert-type items of four response categories were analysed using a traditional approach based on item statistics and coefficient alpha as well as using an item response theory approach by employing the graded response model. Main concepts of item response theory were explicated with figures.
Keywords: item response theory; marketing research; measurement issues; Rasch model
How to cite this article:
Hyo Jin Eom, John Hulland, Jordan M. Wheeler, Seock-Ho Kim. Use of item response theory in marketing research. American Journal of Educational Research and Reviews, 2021,6:87. DOI: 10.28933/ajerr-2021-09-2609
1. AERA, APA, & NCME (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education). (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.
2. Bacon, L., & Lenk, P. (2008). Breaking the binary model code. Marketing Research, 20(4), 6-10.
3. Bagozzi, R. P. (1994). Advanced methods of marketing research. Cambridge, MA: Blackwell.
4. Baker, F. B., & Kim, S.-H. (2004). Item response theory: Parameter estimation techniques (2nd ed.). New York, NY: Marcel Dekker.
5. Baker, F. B., & Kim, S.-H. (2017). The basics of item response theory using R. New York, NY: Springer.
6. Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of marketing scales: Multi-item measures for marketing and consumer behavior research (2nd ed.). Thousand Oaks, CA: Sage.
7. Bearden, W. O., Netemeyer, R. G., & Haws, K. L. (2011). Handbook of marketing scales: Multi-item measures for marketing and consumer behavior research (3rd edition.). Los Angeles, CA: Sage.
8. Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee’s ability. In F. M. Lord & M. R. Novick (Eds.), Statistical theories of mental test scores (pp. 395–479). Reading, MA: Addison-Wesley.
9. Bock, R. D. (1972). Estimating item parameters and latent ability when responses are scored in two or more nominal categories. Psychometrika, 37, 29-51.
10. Bock, R. D. (1997). A brief history of item response theory. Educational Measurement: Issues and Practice, 16(4), 21-32.
11. Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika, 46, 443–459; 47, 369 (Errata).
12. Brace, I. (2004). Questionnaire design: How to plan, structure and write survey material for effective market research (2nd ed.). London, England: Kogan Page.
13. Brzezinska, J. (2016). Latent variable modeling and item response theory analyses in marketing research. Folia Oeconomica Stetinensia, 163-174. DOI: 10.1515/foli-2016-0032
14. Burns, A. C., & Bush, R. F. (2006). Marketing research (5th ed.). Upper Saddle River, NJ: Pearson Education.
15. Carlson, L, & Grossbart, S. (1988). Parental style and consumer socialization of children. Journal of Consumer Research, 15, 77-94.
16. De Ayala, R. J. (2009). The theory and practice of item response theory. New York, NY: Guilford.
17. De Champlain, A. F. (2010). A primer on classical test theory and item response theory for assessment in medical education. Medical Education, 44, 109-117.
18. Engelhard, G., Jr. (2013). Invariant measurement: Using Rasch models in the social, behavioural, and health sciences. New York, NY: Routledge.
19. De Jong, M. G., Steenkamp, J.-B. E. M., & Fox, J.-P. (2007). Relaxing measurement invariance in cross-national consumer research using a hierarchical IRT model. Journal of Consumer Research, 34, 260-278.
20. De Jong, M. G., Steenkamp, J.-E. E. M., Fox, J.-P., & Baumgartner, H. (2008). Using item response theory to measure extreme response style in marketing research: A global investigation. Journal of Marketing Research, 45, 104-115.
21. De Jong, M. G., Steenkamp, J.-B. E. M., & Veldkamp, B. P. (2009). A model for the construction of country-specific yet internationally comparable short-form marketing scales. Marketing Science, 28, 476-689.
22. DeVellis, R. F. (1991). Scale development: Theory and applications. Newbury Park, CA: Sage.
23. Emerson, J. D., & Colditz, G. A. (1986). Use of statistical analysis in the New England Journal of Medicine. In J. C. Bailar III & F. Mosteller (Eds.), Medical use of statistics (pp. 27-38). Waltham, MA: MEJM Books.
24. Farris, P. W., Bendle, N. T., Pfeifer, P. E., & Reibstein, D. J. (2010). Marketing metrics: The definitive guide to measuring marketing performance (2nd ed.). Upper Saddle River, NJ: Pearson Education.
25. Frances, P. H., & Paap, R. (2001). Quantitative models in marketing research. New York, NY: Cambridge University Press.
26. Gable, R. K., & Wolf, M. B. (1993). Instrument development in the affective domain: Measuring attitudes and values in corporate and school settings (2nd ed.). Boston, MA:Kluwer Academic Publishers.
27. Ganglmair, A., & Lawson, R. (2003). Advantages of Rasch modeling for the development of a scale to measure affective response to consumption. In D. Turley & S. Brown (Eds.), European advances in consumer research (Vol. 6; pp. 162-167). Provo, UT: Association for Consumer Research.
28. Green, B. F. (1954). Attitude measurement. In G. Lindzey (Ed.), Handbook of social psychology (pp. 355-369). Cambridge, MA: Addison-Wesley.
29. Green, B. F., Bock, R. D., Humphreys, L. G., Linn, R. L., & Reckase, M. D. (1984). Technical guidelines for assessing computerized adaptive tests. Journal of Educational Measurement, 21, 347-360.
30. Green, P. E., & Wind, Y. (1985). Marketing, Statistics in. In S. Kotz & N. L. Johnson (Eds.), Encyclopedia of Statistical Sciences (Vol. 5, 227-247). New York, NY: John Wiley & Sons.
31. Haertel, E. H. (2006). Reliability. In R. L. Brennan (Ed.), Educational measurement (4th ed.) (pp. 65-110). Westport, CT: Praeger.
32. Hague, P., Hague, N., & Morgan, C.-A. (2004). Market research in practice: A guide to the basics. London, United Kingdom: Kogan Page.
33. Hair, J. F., Jr., Wolfinbarger Celsi, M., Money, A. H., Samouel, P., & Page, M. J. (2011). Essentials of business research methods (2nd ed.). Mrmonk, NY: M. E. Sharpe.
34. Hambleton, R. K., Swaminathan, H., & Roger, H. J. (1991). Fundamentals of item response theory. Newbury Park, CA: Sage.
35. He, Y., Merz, M. A., & Alden, D. L. (2008). Diffusion of measurement invariance assessment in cross-national empirical market research: Perspectives from the literature and a survey of researchers. Journal of International Marketing, 16(2), 64-83.
36. Iacobucci, D. (2013). Marketing models: Multivariate statistics and marketing analytics. Mason, OH: South-Western.
37. Kamakura, W., & Srivastava, R. R. (1982). Latent trait theory and attitude scaling: The use of information functions for item selection. In A. Mitchell (Ed.), Advances in consumer research (Vol. 9; pp. 251-256). Ann Arbor, MI: Association for Consumer Research.
38. Kane, M. T. (2006). Validation. In R. L. Brennan (Ed.), Educational measurement (6th ed.). Westport, CT: Praeger.
39. Kim, S.-H. (2015). Item response theory. In J. M. Spector (Ed.), The SAGE encyclopedia of educational technology (pp. 428-430). Thousand Oaks, CA: Sage.
40. King, C. W., & Summers, J. O. (1970). Overlap of opinion leadership across product categories. Journal of Marketing Research, 7, 43-50.
41. Leonard, M. (2000). Marketing literature review. Journal of Marketing, 64, 91-103.
42. Li, C., Peng, L., & Cui, G. (2017). Picking winners: New product concept testing with item response theory. International Journal of Market Research, 59, 335-353.
43. Likert, R. (1932). Technique for the measurement of attitudes. Archives of Psychology, Serial No. 140.
44. Lord, F. M. (1980). Applications of item response theory in practical testing problems. Hillsdale, NJ: Lawrence Erlbaum Associates.
45. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley.
46. Lou, Y.-C. (1995). An application of item response theory to consumer judgment. In K. Grant & I. Walker (Eds.), Proceedings of the 1995 World Marketing Congress (pp. 364-368). Melbourne, Australia.
47. Malhotra, N., Agarwal, J., & Peterson, M. (1996). Methodological issues in cross-cultural marketing research: A state-of-the-art review. International Marketing Review, 13, 7-43.
48. Malhotra, N. K. (2004). Marketing research: An applied orientation (4th ed.). Upper Saddle River, NJ: Pearson Education.
49. Moussa, S. (2016). A two-step item response theory procedure for a better measurement of marketing constructs. Journal of Marketing Analytics, 4, 28-50.
50. Nering, M. L., & Ostini, R. (2010). Handbook of polytomous item response theory models. New York, NY: Routledge.
51. Nunnally, J. C. (1967). Psychometric theory. New York, NY: McGraw-Hill.
52. Ostini, R., Nering, M. L. (2010). New perspectives and applications. In M. L. Nering & R. Ostini (Eds.), Handbook of polytomous item response theory models. New York, NY: Routledge.
53. Popham, W. J. (1993). Educational testing in America: What’s right, what’s wrong? A criterion referenced perspective. Educational Measurement: Issues and Practice, 12(1), 11-14.
54. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen, Denmark: Nielsen & Lydiche.
55. Raykov, T., & Calantone, R. J. (2014). The utility of item response modeling in marketing research. Journal of the Academy of Marketing Science, 42, 337-360.
56. Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin, 114, 552-566.
57. Rossiter, J. R. (1977). Reliability of a short test measuring children’s attitudes toward TV commercials. Journal of Consumer Research, 3, 179-184.
58. Rusch, T., Mair, P., & Hatzinger, R. (2013). Psychometrics with R: A review of CRAN packages for item response theory. Vienna, Austria: Vienna University of Economics and Business, Center for Empirical Research Methods.
59. Samajima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, No. 17.
60. Salzberger, T., & Koller, M. (2013). Towards a new paradigm of measurement in marketing. Journal of Business Research, 66, 1307-1317.
61. Silver, L., Stevens, R., Wrenn, B., & Loudon, D. (2013). The essentials of marketing research (3rd ed.). New York, NY: Routledge.
62. Singh, J. (2004). Tackling measurement problems with item response theory: Principles, characteristics, and assessment, with an illustrative example. Journal of Business Research, 57, 184-208.
63. Snyder, M. (1974). Self-monitoring of expressive behavior. Journal of Personality and Social Psychology, 30, 526-537.
64. Tarka, P. (2013). Construction of the measurement scale for consumer’s attitudes in the frame of one-parametric Rasch model. Folia Oeconomica, 286, 333-340.
65. Thissen, D. (1991). MULTILOG user’s guide. Chicago, IL: Scientific Software.
66. Thissen, D., & Steinberg, L. (1986). A taxonomy of item response models. Psychometrika, 51, 567-577.
67. Thissen, D., Nelson, L., & Swygert, K. A. (2001). Item response theory applied to combinations of multiple-choice and constructed-response items—Approximation methods for scale scores. In D. Thissen & H. Wainer (Eds.), Test scoring (pp. 293-341). Mahwah, NJ: Lawrence Erlbaum Associates.
68. Thissen, D., & Wainer, H. (2001). Test scoring. Mahwah, NJ: Lawrence Erlbaum Associates.
69. Torgerson, W. S. (1958). Theory and methods of scaling. New York, NY: Wiley.
70. Van der Linden, W. J. (Ed.). (2016a). Handbook of item response theory, Volume 1: Models. Boca Raton, FL: CRC Press.
71. Van der Linden, W. J. (Ed.). (2016b). Handbook of item response theory, Volume 3: Applications. Boca Raton, FL: CRC Press.
72. Wright, B. D., & Stone, M. H. (1979). Best test design. Chicago, IL: MESA Press.
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