Next Article in Journal
Paradoxes of the Italian Historic Centres between Underutilisation and Planning Policies for Sustainability
Next Article in Special Issue
Is Gastronomy A Relevant Factor for Sustainable Tourism? An Empirical Analysis of Spain Country Brand
Previous Article in Journal
The Multi-Risk Assessment Approach as a Basis for the Territorial Resilience
Previous Article in Special Issue
Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend
Article

Exploring the Determinants of Hot Spring Tourism Customer Satisfaction: Causal Relationships Analysis Using ISM

1
College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
Program in Management, Dayeh University, Changhua 51591, Taiwan
3
Department of Information Management, Da-Yeh University, Changhua 51591, Taiwan
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(9), 2613; https://doi.org/10.3390/su11092613
Received: 7 April 2019 / Revised: 20 April 2019 / Accepted: 1 May 2019 / Published: 7 May 2019
(This article belongs to the Special Issue Marketing for Sustainable Tourism)
To stand out in the hot spring tourism industry, customer satisfaction has become the crucial issue for competitiveness. A company cannot implement several customer satisfaction improvement practices altogether with limited resources. Researchers advocate that companies should evaluate the relationships among success factors and explore determinants for their improvement implementation. However, such a relationship evaluation has not yet been adequately performed. This paper intends to explore the determinants for improving hot spring customer satisfaction. Adopting grounded theory (GT) and using data collected from websites, Ctrip and Qunar, the first 12 key factors for customer satisfaction were identified. Then, their interrelationships were assessed by 15 experts, and interpretive structural modeling (ISM) was employed to analyze the interrelationships and the driving and dependence power among key factors. The results show that “Environment Quality”, “Special Resource”, “Convenience”, “Food”, Service Quality”, and “Facilities” were the decisive factors affecting customer satisfaction. The findings offer important implications for hot spring management and practice. The contribution of this study is using a novel approach to establish a hierarchical structural model for comprehensive understanding of factor relationships that influence hot spring tourists’ satisfaction and to explore decisive factors which can help hot spring practitioners to better plan and design effective improvement strategies to attract potential new consumers and retain their current consumers, especially with limited resources. View Full-Text
Keywords: hot spring; customer satisfaction; interpretive structural modeling; decisive factors; grounded theory hot spring; customer satisfaction; interpretive structural modeling; decisive factors; grounded theory
Show Figures

Figure 1

MDPI and ACS Style

Mi, C.; Chen, Y.; Cheng, C.-S.; Uwanyirigira, J.L.; Lin, C.-T. Exploring the Determinants of Hot Spring Tourism Customer Satisfaction: Causal Relationships Analysis Using ISM. Sustainability 2019, 11, 2613. https://doi.org/10.3390/su11092613

AMA Style

Mi C, Chen Y, Cheng C-S, Uwanyirigira JL, Lin C-T. Exploring the Determinants of Hot Spring Tourism Customer Satisfaction: Causal Relationships Analysis Using ISM. Sustainability. 2019; 11(9):2613. https://doi.org/10.3390/su11092613

Chicago/Turabian Style

Mi, Chuanmin, Yetian Chen, Chiung-Shu Cheng, Joselyne L. Uwanyirigira, and Ching-Torng Lin. 2019. "Exploring the Determinants of Hot Spring Tourism Customer Satisfaction: Causal Relationships Analysis Using ISM" Sustainability 11, no. 9: 2613. https://doi.org/10.3390/su11092613

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop