Julian Michael Hodson

Connecting Brand Identity and Consumer-Based Brand Equity for Tourism Destinations (eBook, PDF)

A Structural Model of Leisure Visitors’ Destination Brand Associations

• Format: PDF

Produktbeschreibung

The study proposes and empirically validates an integrated model of leisure visitors’ destination brand associations that can guide destination marketing and branding activities for both, the brand identity and the consumer-based brand equity (CBBE) perspective. A ten-phase empirical research design is established and data is collected from a sample of German leisure visitors to the Balearic Island of Mallorca, Spain. Structural equation modeling (SEM) provides empirical evidence of construct validity and reveals strong support for the validity of the proposed structural theory of leisure visitors’ destination brand associations. Results also demonstrate that the structural model possesses excellent levels of predictive power and validity. Importantly, the model performs very well in the overall prediction of consumers’ destination brand attitudes and loyalty.

Produktdetails

• Verlag: Springer Fachmedien Wiesbaden
• Erscheinungstermin: 23. April 2021
• Englisch
• ISBN-13: 9783658330576
• Artikelnr.: 61629422

Autorenporträt

Julian Michael Hodson earned a Ph.D. at the Chair of Tourism Management, Prof. Edgar Kreilkamp, Leuphana University of Lueneburg. He graduated with degrees in media and business administration, focusing on marketing management and consumer behavior. The author gained international practical experience working for Destination Marketing and Management Organizations (DMOs). His research interests include destination marketing & branding, visitor/host community perceptions & attitudes, visitor destination loyalty, as well as destination planning, development, and management.

Inhaltsangabe

Introduction.- Literature Review.- Research Methodology.- Data Analysis & Empirical Results.- Discussion & Conclusion.

---

Introduction.- Literature Review.- Research Methodology.- Data Analysis & Empirical Results.- Discussion & Conclusion.