TY - JOUR
T1 - Farm tourism experiences in travel reviews
T2 - A cross-comparison of three alternative methods for data analysis
AU - Capriello, Antonella
AU - Mason, Peyton R.
AU - Davis, Boyd
AU - Crotts, John C.
PY - 2013/6
Y1 - 2013/6
N2 - This paper demonstrates three alternative approaches for mining consumer sentiment from large amounts of qualitative data found in online travel reviews. Manual content coding, corpus-based semantic analysis, and stance-shift analysis represent methods varying greatly in both process and output. For illustration purposes, they are applied in an exploratory study focused on consumers' reaction to farm stays in order to demonstrate how large volumes of qualitative data can be analyzed quantitatively in a relatively efficient and reliable way. A total of 800 narratives describing farm stay experiences and representing four national settings (Australia, Italy, UK, and USA) was collected. The results reveal that each method provides unique insights of what a farm stay vacation evokes, helpful to farm entrepreneurs wishing to develop a tourism business. The findings indicate universal values as recurrent key drivers of customer satisfaction closely relate to rural experiences. Comparing the national datasets, local differences are evident, highlighting regional variations in terms of service products and consumer preferences. From a methodological viewpoint, all three methods produce reliable results by evidence of the similarities across all three analyses. The current study shows manual content coding, corpus-based semantic method, and stance-shift analysis can capture the peculiarities of rural experiences in different national settings.
AB - This paper demonstrates three alternative approaches for mining consumer sentiment from large amounts of qualitative data found in online travel reviews. Manual content coding, corpus-based semantic analysis, and stance-shift analysis represent methods varying greatly in both process and output. For illustration purposes, they are applied in an exploratory study focused on consumers' reaction to farm stays in order to demonstrate how large volumes of qualitative data can be analyzed quantitatively in a relatively efficient and reliable way. A total of 800 narratives describing farm stay experiences and representing four national settings (Australia, Italy, UK, and USA) was collected. The results reveal that each method provides unique insights of what a farm stay vacation evokes, helpful to farm entrepreneurs wishing to develop a tourism business. The findings indicate universal values as recurrent key drivers of customer satisfaction closely relate to rural experiences. Comparing the national datasets, local differences are evident, highlighting regional variations in terms of service products and consumer preferences. From a methodological viewpoint, all three methods produce reliable results by evidence of the similarities across all three analyses. The current study shows manual content coding, corpus-based semantic method, and stance-shift analysis can capture the peculiarities of rural experiences in different national settings.
KW - Corpus-based semantic analysis
KW - Farm tourism
KW - Manual content coding
KW - Stance-shift analysis
KW - Travel review
UR - http://www.scopus.com/inward/record.url?scp=84875813556&partnerID=8YFLogxK
U2 - 10.1016/j.jbusres.2011.09.018
DO - 10.1016/j.jbusres.2011.09.018
M3 - Article
SN - 0148-2963
VL - 66
SP - 778
EP - 785
JO - Journal of Business Research
JF - Journal of Business Research
IS - 6
ER -