Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research

2019-09-23
Sedera, D., & Atapattu, M. (2019). Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research. Australasian Journal of Information Systems, 23. doi:http://dx.doi.org/10.3127/ajis.v23i0.1966 Abstract Information systems (IS) studies regularly assume linearity of the variables and often disregard the potential non-linear theoretical interrelationships among the variables. The application of polynomial regression and response surface methodology can observe such non-linear theoretical assumptions among variables. This methodology enables to examine the extent to which two predictor variables relate to an outcome variable simultaneously. This paper utilizes the expectation confirmation theory as an example and provides a methodological commentary that illustrates a step-wise process for conducting a polynomial regression and response surface methodology. Keywords Quantitative analysis; Polynomial regression; Response surface methodology; Non-linearity