Enhancing knowledge transfer in tourism: An Elaboration Likelihood Model approach

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.