Examining Country Image in Expert Electronic Word-of-Mouth: An Abstract

Experts guide consumers’ preferences and purchase decisions because they are often perceived as unbiased and trustworthy. Countries spend billions on marketing their agricultural industries to not only their own citizens but also foreign citizens all over the world, including these experts. The wine industry is a high-value agricultural industry from the standpoints of both the main raw agricultural products (i.e., grapes) and the value added in the finished products. This paper explores the role of country image in expert ratings and reviews (i.e., expert eWOM) using large data sets from the global wine industry and the automated text analysis DICTION. We find significant differences between countries regarding price, rating, and all of the DICTION content dimensions using ANOVA tests at p < 0.001. Furthermore, using regression analysis, we find significant effects for the price, all five review content dimensions, all major countries with the exception of Australia and France. The “France” variable was significant until we controlled for the influence of price. The Australia variable was nonsignificant in all regression analysis indicating that the Australian wine ratings were not statistically different than minor wine-producing countries. This paper makes several contributions to the expert eWOM and country image literatures. Producers in prestigious wine-producing countries (e.g., Italian or German) can extract a price premium related to the image of that country that is perceived by the experts as high quality. However, producers in less prestigious wine-producing countries (e.g., South African or Chilean) can signal quality through a higher price that can help them overcome their country image bias and aid the perception by experts of high quality. Producers can also manage expert eWOM by priming these reviewers to write reviews that use more active, certain, and optimistic language to increase quality ratings. Thus, governments and industry associations can build country images that encourage experts to write reviews with active, optimistic, and central language to influence quality ratings.