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Enhancing knowledge transfer in tourism: an Elaboration Likelihood Model approach
Citation
Hardy, A and Vorobjovas-Pinta, O and Eccleston, R, Enhancing knowledge transfer in tourism: an Elaboration Likelihood Model approach, Journal of Hospitality and Tourism Management, 37 pp. 33-41. ISSN 1447-6770 (2018) [Refereed Article]
Copyright Statement
© 2018 Published by Elsevier Ltd on behalf of CAUTHE - COUNCIL FOR AUSTRALASIAN TOURISM AND HOSPITALITY EDUCATION
DOI: doi:10.1016/j.jhtm.2018.09.002
Abstract
It has been widely recognised that knowledge transfer between tourism academics and the tourism industry is inefficient and ineffective. This research responds to this challenge by applying the Elaboration Likelihood Model (ELM) as a framework to guide the design of knowledge transfer in tourism, from the early design of research through to the delivery of the data. The ELM model posits that messages can influence behaviour via both peripheral and central cues, yet surprisingly has scarcely been applied to knowledge transfer literature. The paper argues that new technology enables innovative, usable and credible visualisation of tourism data, thus maximising the opportunity to apply principles of ELM and ultimately the transfer of knowledge to an array of tourism stakeholders from different backgrounds. In doing so, it presents an opportunity to depart from traditional reporting formats, and as such, enhances the uptake of academic tourism research by the tourism industry.
Item Details
Item Type: | Refereed Article |
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Keywords: | knowledge transfer, Elaboration Likelihood Model (ELM), action research, tourism |
Research Division: | Commerce, Management, Tourism and Services |
Research Group: | Tourism |
Research Field: | Impacts of tourism |
Objective Division: | Commercial Services and Tourism |
Objective Group: | Tourism services |
Objective Field: | Tourism services not elsewhere classified |
UTAS Author: | Hardy, A (Associate Professor Anne Hardy) |
UTAS Author: | Vorobjovas-Pinta, O (Dr Oscar Vorobjovas-Pinta) |
UTAS Author: | Eccleston, R (Professor Richard Eccleston) |
ID Code: | 128339 |
Year Published: | 2018 |
Web of Science® Times Cited: | 18 |
Deposited By: | TSBE |
Deposited On: | 2018-09-14 |
Last Modified: | 2018-12-05 |
Downloads: | 0 |
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