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

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...

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Main Authors: Darshana Sedera, Maura Atapattu
Format: Article
Language:English
Published: Australasian Association for Information Systems 2019-09-01
Series:Australasian Journal of Information Systems
Subjects:
Online Access:https://journal.acs.org.au/index.php/ajis/article/view/1966
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spelling doaj-0d527903344d4b789c79ce01b26cf5af2021-08-02T09:01:23ZengAustralasian Association for Information SystemsAustralasian Journal of Information Systems1449-86181449-86182019-09-0123010.3127/ajis.v23i0.1966761Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems ResearchDarshana Sedera0Maura Atapattu1Swinburne University of TechnologyUniversity of QueenslandInformation 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.https://journal.acs.org.au/index.php/ajis/article/view/1966Quantitative analysisPolynomial regressionResponse surface methodologyNon-linearity
collection DOAJ
language English
format Article
sources DOAJ
author Darshana Sedera
Maura Atapattu
spellingShingle Darshana Sedera
Maura Atapattu
Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research
Australasian Journal of Information Systems
Quantitative analysis
Polynomial regression
Response surface methodology
Non-linearity
author_facet Darshana Sedera
Maura Atapattu
author_sort Darshana Sedera
title Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research
title_short Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research
title_full Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research
title_fullStr Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research
title_full_unstemmed Polynomial Regression and Response Surface Methodology: Theoretical Non-Linearity, Tutorial and Applications for Information Systems Research
title_sort polynomial regression and response surface methodology: theoretical non-linearity, tutorial and applications for information systems research
publisher Australasian Association for Information Systems
series Australasian Journal of Information Systems
issn 1449-8618
1449-8618
publishDate 2019-09-01
description 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.
topic Quantitative analysis
Polynomial regression
Response surface methodology
Non-linearity
url https://journal.acs.org.au/index.php/ajis/article/view/1966
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AT mauraatapattu polynomialregressionandresponsesurfacemethodologytheoreticalnonlinearitytutorialandapplicationsforinformationsystemsresearch
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