Measuring employee-tourist encounter experience value: A big data analytics approach. (15th September 2020)

• Record Type: Journal Article
• Authors: Barnes, Stuart J.; Mattsson, Jan; Sørensen, Flemming; Jensen, Jens Friis
• Is Part Of: Expert systems with applications. Volume 154(2020)
• Publication Date: 2020-09-15
• Subjects: Employee-tourist encounter -- Model -- Big data analytics -- Dictionary -- Text analytics; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113450
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Tests a conceptual model of experience value in tourist-employee encounters. Text analytics approach using combined conceptual dictionaries and big data. The five concepts significantly determine hotel customer satisfaction outcomes. Approach provides low cost solution for continuous measurement from reviews. Abstract: This paper takes a text analytics approach to measuring dimensions of employee-visitor encounters that impact on visitor outcomes. A conceptual model measuring dimensions of employee-tourist encounters is implemented using a big data analytics approach more suited to large-scale online review data than the traditional, limited survey approach. Using a dictionary-based measurement approach and a large sample of reviews for hotels ( n = 265, 016), we test the model and the importance of the factors for leveraging perceptions of satisfaction, service and value. The results demonstrate the importance of the different dimensions of experiential value in employee-tourist encounters in creating positive tourist perceptions. This knowledge is crucial for tourism companies aiming to create experiential value for visitors, rather than simply delivering service quality.