868
Views
15
CrossRef citations to date
0
Altmetric
Original Articles

Antecedents of Global Brand Purchase Likelihood: Exploring the Mediating Effect of Quality, Prestige and Familiarity

&
Pages 288-303 | Published online: 17 May 2018
 

ABSTRACT

This article examines the drivers of global brand purchase likelihood and delineates theoretical and practical implications for marketers. A distinctive model is developed based on theoretical and empirical foundations in the branding and consumer behavior research and the constructs used are well grounded in literature. The model proposes that perceived brand globalness and country of origin have an impact on perceived brand quality, brand prestige and brand familiarity that in turn affect brand purchase likelihood. Additionally, both perceived brand globalness and country of origin are expected to have direct relationships with brand purchase likelihood. The proposed model is testified drawing on the results of empirical work in the form of a large-scale survey conducted on a convenience sample of generation Y consumers in Saudi Arabia. Data collection resulted in 319 usable questionnaires. Data were analyzed using structural equation modeling. Results indicate that brand perceived globalness and country of origin are important determinants of perceived brand quality, prestige, and brand familiarity. Additionally, perceived brand globalness, quality, and prestige are important determinants of brand purchase likelihood.

Additional information

Notes on contributors

Rania Hussein

Dr. Rania S. Hussein is an Assistant Professor of Marketing at the Business School in The American University in Cairo, and Cairo University. She was awarded her MBA degree from Georgia State University, USA in 2001 and her PhD degree from The University of Nottingham, UK in 2010. She is a Fulbright scholar and has conducted joint research with George Washington University in 2014. Her research interests include internet marketing, social media and innovation adoption. She has published a book on Adoption of Web-based Marketing in the travel industry with Lambert Academic Publishing in 2011. Her research appears in journals such as Journal of Business and Industrial Marketing, Online Information Review, the International Journal of Marketing and Management Research and the International Journal of Customer Relationship Marketing and Management.

Salah Hassan

Dr. Salah S. Hassan is Professor of Marketing at the School of Business and affiliate faculty of the Institute for Middle East Studies, Elliott School of International Affairs, The George Washington University and has been a professor at GW School of Business since 1988 and served as Department Chair for 6 years. He received his PhD from The Ohio State University. Dr. Hassan's research and writings appeared in leading refereed journals such as Journal of Business Research, Journal of Macromarketing, Journal of Consumer Marketing, Journal of Travel Research, Journal of Product and Brand Management, International Journal of Consumer Marketing, and International Journal of Bank Marketing. He was granted the “Highly Commended” paper award by the Journal of Consumer Marketing twice in 2004 and 2013. In a 1991 article published with The Academy of Marketing Science, Dr. Hassan coined and defined the concept of “Intermarket Segmentation.” He published books on Globalization of Consumer Markets and Global Marketing Perspectives & Cases. Also, Dr. Hassan co-authored an Arab World Edition of the widely acclaimed Marketing Management, by Philip Kotler & Kevin Keller, Pearson Education, 2012.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 413.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.