Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks
Abstract
:1. Introduction
2. Literature Review
3. Methodology
3.1. Participants and Data Collection
3.2. Measurement Instruments
3.3. Analysis
4. Results
4.1. Linking SEM to BN
4.2. Network Validation and Robustness Test
4.3. Sensitivity Analysis
5. Scenario Analysis
5.1. Scenario 1: Effect of Customer Satisfaction
5.2. Scenario 2: Effect of Customer Trust
5.3. Scenario 3: Effect of Perceived Value
5.4. Scenario 4: Effect of Customer Satisfaction, Customer Trust, and Perceived Value
5.5. Scenario 5: Maximize Customer Loyalty
6. Discussion
6.1. Theoretical Contributions
6.2. Practical Implications
6.3. Limitation
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Variable | Measurement Items | SD | SK | KU | |
---|---|---|---|---|---|
Customer Loyalty (α = 0.910) | |||||
CL1 | Word of mouth | 5.70 | 0.88 | −0.43 | −0.20 |
CL2 | Identification | 5.50 | 1.02 | −0.79 | 1.33 |
CL3 | Repurchase | 5.70 | 0.91 | −0.60 | 0.40 |
Customer Satisfaction (α = 0.924) | |||||
CS1 | Happy to use this airline’s service | 5.63 | 1.00 | −0.56 | 0.33 |
CS2 | Overall satisfaction with airline’s service | 5.70 | 0.96 | −0.62 | 0.42 |
CS3 | Received service quality higher than expected | 5.63 | 1.03 | −0.62 | 0.44 |
CS4 | Received service quality was ideal | 5.55 | 1.11 | −0.86 | 1.35 |
Customer Trust (α = 0.937) | |||||
CT1 | Always trust this airline | 5.59 | 1.07 | −0.81 | 1.24 |
CT2 | The airline’s good handling achieved satisfaction | 5.62 | 1.06 | −0.73 | 0.87 |
CT3 | Reliability of the airline | 5.64 | 1.03 | −0.70 | 0.87 |
CT4 | This airline supplied the best service | 5.50 | 1.10 | −0.81 | 1.27 |
CT5 | This airline is stable and reliable | 5.62 | 1.05 | −0.75 | 0.92 |
Perceived Value (α = 0.910) | |||||
PV1 | The received service was worth its cost | 5.64 | 0.98 | −0.60 | 0.56 |
PV2 | Provided service was reasonable compared to its cost | 5.67 | 0.96 | −0.69 | 0.73 |
PV3 | Traveling with this airline was worth its cost | 5.65 | 0.98 | −0.72 | 0.72 |
Perceived Service Quality (α = 0.927) | |||||
PQ1 | Airline operation | 5.85 | 0.70 | −0.48 | 0.02 |
PQ2 | Ground services | 5.88 | 0.78 | −0.56 | 0.63 |
PQ3 | Information | 5.82 | 0.78 | −0.44 | −0.03 |
PQ4 | Flight attendants | 5.98 | 0.67 | −0.45 | −0.04 |
PQ5 | Airline tangible | 5.80 | 0.73 | −0.39 | 0.23 |
Customer Expectation (α = 0.944) | |||||
EQ1 | Airline operation | 6.07 | 0.70 | −0.50 | −0.37 |
EQ2 | Flight attendants | 6.15 | 0.68 | −0.59 | −0.42 |
EQ3 | Ground services | 6.09 | 0.75 | −0.50 | −0.55 |
EQ4 | Information | 6.03 | 0.73 | −0.43 | −0.46 |
EQ5 | Airline tangible | 6.08 | 0.72 | −0.60 | −0.24 |
Customer Commitment (α = 0.908) | |||||
CC1 | Better personal image when traveling with this airline | 5.32 | 1.17 | −0.52 | 0.09 |
CC2 | Concern about airline’s long-term success | 5.29 | 1.16 | −0.43 | −0.06 |
CC3 | Proud to use this airline | 5.25 | 1.17 | −0.32 | −0.21 |
Airline Image (α = 0.914) | |||||
AI1 | This airline has a good image in passengers’ minds | 5.78 | 0.95 | −0.69 | 0.19 |
AI2 | I am always very impressed with this airline | 5.75 | 0.96 | −0.56 | −0.14 |
AI3 | I trust that this airline has a better image than others | 5.63 | 1.02 | −0.84 | 1.10 |
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Actual from Responses | Predicted from the BN | ||
---|---|---|---|
Low | Medium | High | |
Low | 3 | 1 | 0 |
Medium | 0 | 30 | 4 |
High | 0 | 5 | 57 |
Total error rate = 10% |
Factor | Variance Reduction | Percent | Variance of Beliefs |
---|---|---|---|
Customer Satisfaction | 0.2306 | 15.2 | 0.0530 |
Customer Trust | 0.2034 | 13.4 | 0.0485 |
Perceived Value | 0.1758 | 11.6 | 0.0396 |
Perceived Service Quality | 0.0538 | 3.54 | 0.0111 |
Airline Image | 0.0191 | 1.25 | 0.0013 |
Customer Commitment | 0.0156 | 1.03 | 0.0028 |
Customer Expectation | 0.0135 | 0.88 | 0.0028 |
Factor | Mean Value | Change Rate (%) | |
---|---|---|---|
Prior | Posterior | ||
Customer Trust | 5.53 | 5.88 | 6.33 |
Customer Satisfaction | 5.62 | 5.97 | 6.23 |
Perceived Value | 5.61 | 5.91 | 5.35 |
Perceived Service Quality | 5.81 | 5.95 | 2.41 |
Customer Commitment | 5.29 | 5.38 | 1.70 |
Airline Image | 5.72 | 5.78 | 1.05 |
Customer Expectation | 5.93 | 5.99 | 1.01 |
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Chanpariyavatevong, K.; Wipulanusat, W.; Champahom, T.; Jomnonkwao, S.; Chonsalasin, D.; Ratanavaraha, V. Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks. Sustainability 2021, 13, 7046. https://doi.org/10.3390/su13137046
Chanpariyavatevong K, Wipulanusat W, Champahom T, Jomnonkwao S, Chonsalasin D, Ratanavaraha V. Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks. Sustainability. 2021; 13(13):7046. https://doi.org/10.3390/su13137046
Chicago/Turabian StyleChanpariyavatevong, Kattreeya, Warit Wipulanusat, Thanapong Champahom, Sajjakaj Jomnonkwao, Dissakoon Chonsalasin, and Vatanavongs Ratanavaraha. 2021. "Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks" Sustainability 13, no. 13: 7046. https://doi.org/10.3390/su13137046
APA StyleChanpariyavatevong, K., Wipulanusat, W., Champahom, T., Jomnonkwao, S., Chonsalasin, D., & Ratanavaraha, V. (2021). Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks. Sustainability, 13(13), 7046. https://doi.org/10.3390/su13137046