Online from: 1983
Subject Area: Marketing
Options: To add Favourites and Table of Contents Alerts please take a Emerald profile
|Title:||Interpreting interrelations across multiple levels in HGLM models: An application in international marketing research|
|Author(s):||Burcu Tasoluk, (Faculty of Management, Sabanci University, Istanbul, Turkey), Cornelia Dröge, (Department of Marketing, The Eli Broad Graduate School of Management, Michigan State University, East Lansing, Michigan, USA), Roger J. Calantone, (Department of Marketing, The Eli Broad Graduate School of Management, Michigan State University, East Lansing, Michigan, USA)|
|Citation:||Burcu Tasoluk, Cornelia Dröge, Roger J. Calantone, (2011) "Interpreting interrelations across multiple levels in HGLM models: An application in international marketing research", International Marketing Review, Vol. 28 Iss: 1, pp.34 - 56|
|Keywords:||International marketing, Marketing models, Multilevel marketing|
|Article type:||Technical paper|
|DOI:||10.1108/02651331111107099 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – Although the use of data from different levels is very common in international marketing research, the practice of employing multi-level analysis techniques is relatively new. The paper aims to provide an application of a specific case of multi-level modelling – where the dependent variable is dichotomous, which is often the case in marketing research (e.g. whether a consumer buys the brand or not, whether he/she is aware of the brand or not, etc.)
Design/methodology/approach – A hierarchical generalized linear model is employed.
Findings – Since this is a technical paper, the authors would like to emphasize the process rather than the empirical findings. In summary, the paper: provides a brief theoretical overview of Hierarchical Linear Modeling and Hierarchical Generalized Linear Modeling; illustrates the application of the method using the domains of consumers within countries and a dichotomous dependent variable; focuses on interpretation of log-odds results; and concludes with practical issues and research implications.
Originality/value – The main value of this research is to demonstrate how to employ multi-level models when the dependent variable is dichotomous. Multi-level techniques are quite new in international marketing research, although nested data structures are relatively common in our field. This is a technical paper that guides the researchers as to how to apply and interpret the results when modeling such data with a dichotomous dependent variable.
Existing customers: login
to access this document
To purchase this item please login or register.
Complete and print this form to request this document from your librarian