TY - JOUR
T1 - Cruise passengers’ internal reactions to onboard environmental attributes
AU - Akter, Sabina
AU - Romanoff, Jani
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/9/1
Y1 - 2024/9/1
N2 - This paper presents a method to analyse cruise passengers' internal responses through onboard environmental attributes. The internal responses are defined as cognitive, affective, physiological, and behavioural, while the environmental qualities are described as ambience, layout/design, social, product/service, and onboard enjoyment factors. A generic method to extract engineering attributes from written customer reviews is derived based on text mining, sentiment analysis, and metrics that characterise the success of the cruise experience in terms of customer reviews. The developed framework is demonstrated through open-source customer review data, with a sample size of 172. Even though, being a small sample, the amount of text data signifies the role of automatic data extraction. The method enables the managers and practitioners to a) improve the ship design, b) enhance the ship operations and c) to identify the issues in which both design and operations are intervened. Based on the connection between onboard environmental factors and internal responses, a key performance indicator (KPI) is derived, which is based on the absolute net score and the alignment of the sentiment.
AB - This paper presents a method to analyse cruise passengers' internal responses through onboard environmental attributes. The internal responses are defined as cognitive, affective, physiological, and behavioural, while the environmental qualities are described as ambience, layout/design, social, product/service, and onboard enjoyment factors. A generic method to extract engineering attributes from written customer reviews is derived based on text mining, sentiment analysis, and metrics that characterise the success of the cruise experience in terms of customer reviews. The developed framework is demonstrated through open-source customer review data, with a sample size of 172. Even though, being a small sample, the amount of text data signifies the role of automatic data extraction. The method enables the managers and practitioners to a) improve the ship design, b) enhance the ship operations and c) to identify the issues in which both design and operations are intervened. Based on the connection between onboard environmental factors and internal responses, a key performance indicator (KPI) is derived, which is based on the absolute net score and the alignment of the sentiment.
KW - Decision-making processes
KW - Human/data variables to behaviour
KW - Internal responses
KW - Onboard environmental attributes
KW - Processes
KW - Purchase decision
UR - http://www.scopus.com/inward/record.url?scp=85192792409&partnerID=8YFLogxK
U2 - 10.1016/j.oceaneng.2024.118112
DO - 10.1016/j.oceaneng.2024.118112
M3 - Article
AN - SCOPUS:85192792409
SN - 0029-8018
VL - 307
JO - Ocean Engineering
JF - Ocean Engineering
M1 - 118112
ER -