Baking Dalarna's biking cake : Collaboration as a means for destination competitiveness, a case study of “Biking Dalarna"

In the contemporary tourism industry, the competitive game is between destinations. Tourism operations struggle to remain competitive on the international market and their success depends to a large extent on other complementary and competing tourism organizations at the destination. It is the sum of the total tourism offerings at the destination which determines its attractiveness. This research explores tourism collaboration process as a means of generating destination competitiveness. The focus of the research is on the enhancing factors which contribute to the success of the collaboration and to the development of quality tourism products. The research studies the case of Biking Dalarna, a collaboration of different organizations at five biking destinations in Dalarna, Sweden. Its purpose is to develop biking tourism in the region and to make Dalarna into Sweden’s leading biking destination. It is a qualitative research; the empirical data was collected through in depth interviews with representatives of six Biking Dalarna member organizations. The qualitative data collected from the participants provides inside look into the members reflections and experience of collaborating. The findings of this research demonstrate how collaboration has improved the biking product in Dalarna and promoted solutions to development problems. The research finds the good relationship between the collaborating actors and the involvement and leadership of the regional tourism management organization as the most contributing factors to the success of Biking Dalarna. The research also suggests that a third desired outcome of collaboration, improved marketing attributes was yet to be achieved in the case of Biking Dalarna.

From Pettson and Findus to Festus and Mercury...and Back Again: A Comparison of Four Translations of Sven Nordqvist's Picture Books

In order to examine how children's literature might be translated, two different English translations of two Swedish picture books have been analyzed. The original Swedish books are Rävjakten and Pannkakstårtan by Sven Nordqvist. Rävjakten was translated as The Fox Hunt in 1988 and as The Fox Hunt in 2000. Pannkakstårtan was translated as Pancake Pie in 1985 and as The Birthday Cake in 1999. Literary translation in general, specific translation issues for children's literature, and trends in international English style have been considered. Analysis of the four texts has been made, with consideration given to the following areas: changes in illustrations, layout, or format; text changes; lexical choices; and retention, deletion, or modification of names and culturally specific references. The analysis revealed that the following tendencies were true for the later translations: foreignization of the text, word-for-word translation of the text, and a neutral international English variety.

Big Data Analysis in Social Networks : Extracting Food Preferences of Vegans from Twitter

Market research is often conducted through conventional methods such as surveys, focus groups and interviews. But the drawbacks of these methods are that they can be costly and timeconsuming. This study develops a new method, based on a combination of standard techniques like sentiment analysis and normalisation, to conduct market research in a manner that is free and quick. The method can be used in many application-areas, but this study focuses mainly on the veganism market to identify vegan food preferences in the form of a profile. Several food words are identified, along with their distribution between positive and negative sentiments in the profile. Surprisingly, non-vegan foods such as cheese, cake, milk, pizza and chicken dominate the profile, indicating that there is a significant market for vegan-suitable alternatives for such foods. Meanwhile, vegan-suitable foods such as coconut, potato, blueberries, kale and tofu also make strong appearances in the profile. Validation is performed by using the method on Volkswagen vehicle data to identify positive and negative sentiment across five car models. Some results were found to be consistent with sales figures and expert reviews, while others were inconsistent. The reliability of the method is therefore questionable, so the results should be used with caution.