Measuring tourists’ meal experience by mining online user generated content about restaurants

ABSTRACT

Understanding restaurant customer satisfaction has been uneasy, especially in a Nordic tourism scenario. Fortunately, the availability of online user generated content, as well as text mining techniques, has offered a chance to complement traditional measurement scales or interview approaches. Against this background, this study uncovers and compares the satisfaction of restaurant tourist customers travelling in four Nordic countries by means of investigating their online ratings and reviews. Findings suggest that tourist diners discuss more about feeling, price, food, place, time, and service when commenting on their meal experience. Moreover, four factors have been identified as satisfactory to Nordic travellers, whereas other nine factors have been the opposite. Methodologically, user generated content analysis has been proved to be a cost-effective and meaningful supplement to existing meal experience measurement tools. Moreover, the approach is transferable from catering and tourism to other service or product industry to generate greater business insight.

KEYWORDS:

• Meal experience
• user generated content
• text mining
• Nordic

Disclosure statement

No potential conflict of interest was reported by the author.

ORCID

Susan (Sixue) Jia http://orcid.org/0000-0002-8623-5876

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number 71702107]; Shanghai International Studies University [grant number 2015114050].