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Response Surface Analysis: A Tutorial for Examining Linear and Curvilinear Effects

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  • Antonio Carlos Rodrigues

Abstract

Context: response surface analysis (RSA) is an approach that allows examining the extent to which combinations of two predictive variables relate to one outcome variable. The method is particularly interesting in cases where (in)congruence between the two predictive variables is a central consideration of the study. Objective: the purpose of this article is to provide a tutorial on applying RSA. Method: the method’s conceptual background and an illustrative example are provided so that the reader can understand some of the basic principles of the technique. This tutorial’s target audience is researchers who use mathematical modeling but are not yet familiar with the method. Results: the technique has the potential for application in various research questions in the field of Administration. Conclusions: besides providing a tutorial on how to use the investigated technique, the study demonstrates its relevance in the analysis of congruence and incongruence between the scores.

Suggested Citation

  • Antonio Carlos Rodrigues, 2021. "Response Surface Analysis: A Tutorial for Examining Linear and Curvilinear Effects," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 25(6), pages 200293-2002.
    • Handle: RePEc:abg:anprac:v:25:y:2021:i:6:1484
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    File URL: https://rac.anpad.org.br/index.php/rac/article/view/1484/1669
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    References listed on IDEAS

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    1. Renata P. Brito & Priscila L. S. Miguel, 2017. "Power, Governance, and Value in Collaboration: Differences between Buyer and Supplier Perspectives," Journal of Supply Chain Management, Institute for Supply Management, vol. 53(2), pages 61-87, April.
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    3. Lee, Kyootai & Woo, Han-Gyun & Joshi, Kailash, 2017. "Pro-innovation culture, ambidexterity and new product development performance: Polynomial regression and response surface analysis," European Management Journal, Elsevier, vol. 35(2), pages 249-260.
    4. Felix Reimann & David J. Ketchen Jr., 2017. "Power in Supply Chain Management," Journal of Supply Chain Management, Institute for Supply Management, vol. 53(2), pages 3-9, April.
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