2007
DOI: 10.1108/03090560710737598
|View full text |Cite
|
Sign up to set email alerts
|

Where does the logistic regression analysis stand in marketing literature?

Abstract: Purpose -The objective of this article is to determine the usage and application of logistic regression analysis in the marketing literature by comparing the market positioning of prominent marketing journals. Design/methodology/approach -In order to identify the logistic regression applications, those journals having "marketing" term in their titles and indexed by the social citation index (SSCI) were included. As a result, the target population consisted of 12 journals fulfilling the criteria set. However, o… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
9
0

Year Published

2012
2012
2023
2023

Publication Types

Select...
5
3
1

Relationship

0
9

Authors

Journals

citations
Cited by 45 publications
(9 citation statements)
references
References 92 publications
0
9
0
Order By: Relevance
“…The two models were evaluated using two logistic regressions. This method is suitable for classifying a dichotomous dependent variable (the presence or absence of attitudinal loyalty toward Magazine X) based on a set of criterion variables and “appears to be a very useful technique for the modelling and discrimination problems in marketing” (Akinci, Kaynak, Atilgan, & Aksoy, , p. 538). Before running the regression, the interaction term was centered (Menard, ).…”
Section: Resultsmentioning
confidence: 99%
“…The two models were evaluated using two logistic regressions. This method is suitable for classifying a dichotomous dependent variable (the presence or absence of attitudinal loyalty toward Magazine X) based on a set of criterion variables and “appears to be a very useful technique for the modelling and discrimination problems in marketing” (Akinci, Kaynak, Atilgan, & Aksoy, , p. 538). Before running the regression, the interaction term was centered (Menard, ).…”
Section: Resultsmentioning
confidence: 99%
“…Since real world data often described by not always having a linear pattern, this technique is quite satisfying for most researchers. For instance, in marketing, Akinci et al (2007) indicates that logistic regression can generates more appropriate and correct findings in terms of model fit and correctness of the analysis.…”
Section: Logistic Regression For Analysismentioning
confidence: 99%
“…Multinomial logistic regression is robust for revealing violations of assumptions of multivariate normality and covariance equality of groups. Furthermore, multinomial logistic regression does not assume a linear relationship between the dependent and independent variables (Akinci et al, 2007).…”
Section: Table 2 Mean Scores Of Indicatorsmentioning
confidence: 99%