IDEAS home Printed from https://ideas.repec.org/a/pal/jmarka/v4y2016i1d10.1057_jma.2016.4.html
   My bibliography  Save this article

A two-step item response theory procedure for a better measurement of marketing constructs

Author

Listed:
  • Salim Moussa

    (Institut Supérieur des Études Appliquées en Humanités)

Abstract

In order to broaden the set of methods for developing better multi-item marketing scales, this article proposes an item response theory (IRT) procedure that consists of two successive steps. The first exploratory step uses a non-parametric IRT model for dimensionality detection and scale purification. The second confirmatory step employs a parametric IRT model for evaluating, and likely refining, the resulting scale. This two-step IRT procedure also involves a wide range of new parametric and non-parametric IRT-based interpretive tools (that is, goodness-of-fit indices, scale-score reliability coefficients and item response/information functions) that allows scale developers and users to work in a highly informed manner. To illustrate the benefits of the proposed procedure, the article presents an extended application to the topical construct of emotional attachment.

Suggested Citation

  • Salim Moussa, 2016. "A two-step item response theory procedure for a better measurement of marketing constructs," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(1), pages 28-50, March.
    • Handle: RePEc:pal:jmarka:v:4:y:2016:i:1:d:10.1057_jma.2016.4
    DOI: 10.1057/jma.2016.4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jma.2016.4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1057/jma.2016.4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Laros, Fleur J.M. & Steenkamp, Jan-Benedict E.M., 2005. "Emotions in consumer behavior: a hierarchical approach," Journal of Business Research, Elsevier, vol. 58(10), pages 1437-1445, October.
    2. Lea Dunn & JoAndrea Hoegg, 2014. "The Impact of Fear on Emotional Brand Attachment," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 41(1), pages 152-168.
    3. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    4. R. Bock & Murray Aitkin, 1981. "Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 443-459, December.
    5. J. Straat & L. Ark & Klaas Sijtsma, 2013. "Comparing Optimization Algorithms for Item Selection in Mokken Scale Analysis," Journal of Classification, Springer;The Classification Society, vol. 30(1), pages 75-99, April.
    6. Maydeu-Olivares, Albert & Joe, Harry, 2005. "Limited- and Full-Information Estimation and Goodness-of-Fit Testing in 2n Contingency Tables: A Unified Framework," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1009-1020, September.
    7. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    8. Martijn G. de Jong & Jan-Benedict E. M. Steenkamp & Bernard P. Veldkamp, 2009. "A Model for the Construction of Country-Specific Yet Internationally Comparable Short-Form Marketing Scales," Marketing Science, INFORMS, vol. 28(4), pages 674-689, 07-08.
    9. R. Darrell Bock, 1972. "Estimating item parameters and latent ability when responses are scored in two or more nominal categories," Psychometrika, Springer;The Psychometric Society, vol. 37(1), pages 29-51, March.
    10. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    11. Smith, Anne M., 1999. "Some Problems When Adopting Churchill's Paradigm for the Development of Service Quality Measurement Scales," Journal of Business Research, Elsevier, vol. 46(2), pages 109-120, October.
    12. Melissa A. Z. Knoll & Carrie R. Houts, 2012. "The Financial Knowledge Scale: An Application of Item Response Theory to the Assessment of Financial Literacy," Journal of Consumer Affairs, Wiley Blackwell, vol. 46(3), pages 381-410, September.
    13. L. Ark & Wicher Bergsma, 2010. "A Note on Stochastic Ordering of the Latent Trait Using the Sum of Polytomous Item Scores," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 272-279, June.
    14. Wen-Hung Chen & David Thissen, 1997. "Local Dependence Indexes for Item Pairs Using Item Response Theory," Journal of Educational and Behavioral Statistics, , vol. 22(3), pages 265-289, September.
    15. Leonard Paas & Klaas Sijtsma, 2008. "Nonparametric item response theory for investigating dimensionality of marketing scales: A SERVQUAL application," Marketing Letters, Springer, vol. 19(2), pages 157-170, June.
    16. Singh, Jagdip, 2004. "Tackling measurement problems with Item Response Theory: Principles, characteristics, and assessment, with an illustrative example," Journal of Business Research, Elsevier, vol. 57(2), pages 184-208, February.
    17. Martijn G. de Jong & Donald R. Lehmann & Oded Netzer, 2012. "State-Dependence Effects in Surveys," Marketing Science, INFORMS, vol. 31(5), pages 838-854, September.
    18. Martijn G. De Jong & Jan-Benedict E. M. Steenkamp & Jean-Paul Fox, 2007. "Relaxing Measurement Invariance in Cross-National Consumer Research Using a Hierarchical IRT Model," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(2), pages 260-278, June.
    19. van der Ark, L. Andries, 2012. "New Developments in Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i05).
    20. Seonghoon Kim, 2012. "A Note on the Reliability Coefficients for Item Response Model-Based Ability Estimates," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 153-162, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salim Moussa, 2021. "Measuring brand personality using emoji: findings from Mokken scaling," Journal of Brand Management, Palgrave Macmillan, vol. 28(2), pages 116-132, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ling Peng & Geng Cui & Yuho Chung & Chunyu Li, 2019. "A multi-facet item response theory approach to improve customer satisfaction using online product ratings," Journal of the Academy of Marketing Science, Springer, vol. 47(5), pages 960-976, September.
    2. Maud Dampérat & Ping Lei & Florence Jeannot, 2019. "IRT Approach for rating scales: applications for normal and non-normal distributions," Post-Print hal-04325043, HAL.
    3. Salim Moussa, 2021. "Measuring brand personality using emoji: findings from Mokken scaling," Journal of Brand Management, Palgrave Macmillan, vol. 28(2), pages 116-132, March.
    4. Alberto Maydeu-Olivares & Rosa Montaño, 2013. "How Should We Assess the Fit of Rasch-Type Models? Approximating the Power of Goodness-of-Fit Statistics in Categorical Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 116-133, January.
    5. Ick Hoon Jin & Minjeong Jeon, 2019. "A Doubly Latent Space Joint Model for Local Item and Person Dependence in the Analysis of Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 236-260, March.
    6. Li Cai, 2010. "A Two-Tier Full-Information Item Factor Analysis Model with Applications," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 581-612, December.
    7. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    8. de Jong, M.G., 2006. "Response bias in international marketing research," Other publications TiSEM 5d4031be-97b5-4db3-962b-2, Tilburg University, School of Economics and Management.
    9. Ji Seung Yang & Xiaying Zheng, 2018. "Item Response Data Analysis Using Stata Item Response Theory Package," Journal of Educational and Behavioral Statistics, , vol. 43(1), pages 116-129, February.
    10. Wang, Luming & Finn, Adam, 2013. "Dual-faceted multidimensional IRT models with hierarchical structure," Australasian marketing journal, Elsevier, vol. 21(2), pages 111-118.
    11. Nuo Xi & Michael W. Browne, 2014. "Contributions to the Underlying Bivariate Normal Method for Factor Analyzing Ordinal Data," Journal of Educational and Behavioral Statistics, , vol. 39(6), pages 583-611, December.
    12. Jules L. Ellis & Klaas Sijtsma, 2023. "A Test to Distinguish Monotone Homogeneity from Monotone Multifactor Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 387-412, June.
    13. Silvana Bortolotti & Rafael Tezza & Dalton Andrade & Antonio Bornia & Afonso Sousa Júnior, 2013. "Relevance and advantages of using the item response theory," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2341-2360, June.
    14. Mark Reiser & Silvia Cagnone & Junfei Zhu, 2023. "An Extended GFfit Statistic Defined on Orthogonal Components of Pearson’s Chi-Square," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 208-240, March.
    15. Javier Revuelta, 2010. "Estimating Difficulty from Polytomous Categorical Data," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 331-350, June.
    16. Yang Liu & Ji Seung Yang & Alberto Maydeu-Olivares, 2019. "Restricted Recalibration of Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 529-553, June.
    17. Molenaar, Dylan & Tuerlinckx, Francis & van der Maas, Han L. J., 2015. "Fitting Diffusion Item Response Theory Models for Responses and Response Times Using the R Package diffIRT," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 66(i04).
    18. Michael Brusco & J Dennis Cradit & Douglas Steinley, 2021. "A comparison of 71 binary similarity coefficients: The effect of base rates," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-19, April.
    19. Vassilis Vasdekis & Silvia Cagnone & Irini Moustaki, 2012. "A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 425-441, July.
    20. Chen, Yunxiao & Moustaki, Irini & Zhang, H, 2020. "A note on likelihood ratio tests for models with latent variables," LSE Research Online Documents on Economics 107490, London School of Economics and Political Science, LSE Library.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jmarka:v:4:y:2016:i:1:d:10.1057_jma.2016.4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.