IDEAS home Printed from https://ideas.repec.org/a/eee/ijrema/v40y2023i3p552-569.html
   My bibliography  Save this article

Estimating the effect of brand beliefs on brand evaluations when beliefs are measured with error

Author

Listed:
  • Sonnier, Garrett P.
  • Rutz, Oliver J.
  • Ward, Adrian F.

Abstract

We consider the internal validity of estimates of the effects of brand beliefs on brand evaluations when beliefs are measured with error. Consumer research suggests numerous errors that may impact belief measures. However, the literature has not determined precisely why and how myriad types of error matter for the evaluation-belief relationship. Furthermore, the literature has not explicitly considered what is necessary and sufficient to control for different types of belief error when using the latent general factor approach. We show that the important distinction for empirical research is not the origin of the error per se but its relationship to affective evaluation. Error related to brand evaluation has an inflationary effect on estimates of the evaluation-belief relationship while error unrelated to brand evaluation has an attenuating effect. We use a bifactor structural equations model to decompose belief measures into general and specific dimensions. The model uses bias free variation in specific beliefs to identify effects on brand evaluation while controlling for a general belief dimension correlated with evaluation. Compared to models that do not adjust for the bias, estimates of the bias corrected marginal effects are smaller but positive and significant.

Suggested Citation

  • Sonnier, Garrett P. & Rutz, Oliver J. & Ward, Adrian F., 2023. "Estimating the effect of brand beliefs on brand evaluations when beliefs are measured with error," International Journal of Research in Marketing, Elsevier, vol. 40(3), pages 552-569.
  • Handle: RePEc:eee:ijrema:v:40:y:2023:i:3:p:552-569
    DOI: 10.1016/j.ijresmar.2023.02.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167811623000137
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijresmar.2023.02.002?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. Yiu-Fai Yung & David Thissen & Lori McLeod, 1999. "On the relationship between the higher-order factor model and the hierarchical factor model," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 113-128, June.
    2. Jan-Benedict E.M. Steenkamp & Alberto Maydeu-Olivares, 2021. "An updated paradigm for evaluating measurement invariance incorporating common method variance and its assessment," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 5-29, January.
    3. Robert Gibbons & Donald Hedeker, 1992. "Full-information item bi-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 423-436, September.
    4. Nakanishi, Masao & Bettman, James R, 1974. "Attitude Models Revisited: An Individual Level Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 1(3), pages 16-21, December.
    5. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    6. Rajdeep Grewal & Joseph A. Cote & Hans Baumgartner, 2004. "Multicollinearity and Measurement Error in Structural Equation Models: Implications for Theory Testing," Marketing Science, INFORMS, vol. 23(4), pages 519-529, June.
    7. Reibstein, David J & Lovelock, Christopher H & Dobson, Ricardo de P, 1980. "The Direction of Causality between Perceptions, Affect, and Behavior: An Application to Travel Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 6(4), pages 370-376, March.
    8. Slovic, Paul & Finucane, Melissa L. & Peters, Ellen & MacGregor, Donald G., 2007. "The affect heuristic," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1333-1352, March.
    9. Marc Vanhuele & Shuba Srinivasan & Koen Pauwels, 2010. "Mindset Metrics in Market Response Models: An Integrative Approach," Post-Print hal-00528411, HAL.
    Full references (including those not matched with items on IDEAS)

    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. repec:jss:jstsof:34:i03 is not listed on IDEAS
    2. Sridhar, Shrihari & Naik, Prasad A. & Kelkar, Ajay, 2017. "Metrics unreliability and marketing overspending," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 761-779.
    3. Chun Wang & Steven W. Nydick, 2020. "On Longitudinal Item Response Theory Models: A Didactic," Journal of Educational and Behavioral Statistics, , vol. 45(3), pages 339-368, June.
    4. Laine Bradshaw & Jonathan Templin, 2014. "Combining Item Response Theory and Diagnostic Classification Models: A Psychometric Model for Scaling Ability and Diagnosing Misconceptions," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 403-425, July.
    5. Leigh McAlister & Garrett Sonnier & Tom Shively, 2012. "The relationship between online chatter and firm value," Marketing Letters, Springer, vol. 23(1), pages 1-12, March.
    6. Li Cai, 2015. "Lord–Wingersky Algorithm Version 2.0 for Hierarchical Item Factor Models with Applications in Test Scoring, Scale Alignment, and Model Fit Testing," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 535-559, June.
    7. Yi-Jen (Ian) Ho & Sanjeev Dewan & Yi-Chun (Chad) Ho, 2020. "Distance and Local Competition in Mobile Geofencing," Information Systems Research, INFORMS, vol. 31(4), pages 1421-1442, December.
    8. Frank Rijmen & Minjeong Jeon & Matthias von Davier & Sophia Rabe-Hesketh, 2014. "A Third-Order Item Response Theory Model for Modeling the Effects of Domains and Subdomains in Large-Scale Educational Assessment Surveys," Journal of Educational and Behavioral Statistics, , vol. 39(4), pages 235-256, August.
    9. Sayed H. Kadhem & Aristidis K. Nikoloulopoulos, 2023. "Bi-factor and Second-Order Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 132-157, March.
    10. Claudia García-García & Catalina B. García-García & Román Salmerón, 2021. "Confronting collinearity in environmental regression models: evidence from world data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 895-926, September.
    11. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    12. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    13. Jesse Elliott & Zemin Bai & Shu-Ching Hsieh & Shannon E Kelly & Li Chen & Becky Skidmore & Said Yousef & Carine Zheng & David J Stewart & George A Wells, 2020. "ALK inhibitors for non-small cell lung cancer: A systematic review and network meta-analysis," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-18, February.
    14. Christina Leuker & Thorsten Pachur & Ralph Hertwig & Timothy J. Pleskac, 2019. "Do people exploit risk–reward structures to simplify information processing in risky choice?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 76-94, August.
    15. Francois Olivier & Laval Guillaume, 2011. "Deviance Information Criteria for Model Selection in Approximate Bayesian Computation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-25, July.
    16. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
    17. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    18. Rubio, F.J. & Steel, M.F.J., 2011. "Inference for grouped data with a truncated skew-Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3218-3231, December.
    19. Vicente Martínez-Tur & Vicente Peñarroja & Miguel A Serrano & Vanesa Hidalgo & Carolina Moliner & Alicia Salvador & Adrián Alacreu-Crespo & Esther Gracia & Agustín Molina, 2014. "Intergroup Conflict and Rational Decision Making," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-17, December.
    20. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.

    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:eee:ijrema:v:40:y:2023:i:3:p:552-569. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-research-in-marketing/ .

    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.