Influence of Electronic Word-Of-Mouth on Restaurant Choice Decisions: Does It Depend on Gender in the Millennial Generation?
Abstract
:1. Introduction
2. Theoretical Framework and Hypothesis
2.1. Effects of Motivations to Consult eWOM on Intention to Consult eWOM
2.2. Effect of Intention to Consult eWOM on Adoption of eWOM
2.3. Role of Gender in eWOM Consultations
3. Methodology
3.1. Measurement Scales and Data Collection
3.2. Data Analysis
4. Results
4.1. Measurement Model and Metric Invariance
4.2. Analysis of the Structural Model and Moderating Effect
5. Discussion
6. Conclusions
7. Implications
8. Limitations and Future Lines of Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Constructs | Items | Loadings | α | CR | AVE |
---|---|---|---|---|---|
Convenience motivation | 0.901 | 0.922 | 0.629 | ||
CM1—For quicker information on restaurants. | 0.726 *** | ||||
CM2—To save time before making a restaurant reservation. | 0.817 *** | ||||
CM 3—Why does it make it easier for me to search for restaurant information from home or work. | 0.823 *** | ||||
CM 4—Why is it the easiest way to obtain information. | 0.804 *** | ||||
CM 5—To be able to compare them with others. | 0.745 *** | ||||
CM 6—To find low prices. | 0.813 *** | ||||
CM 7—To get a better price. | 0.819 *** | ||||
Social motivation | 0.911 | 0.928 | 0.616 | ||
SM1—To verify if others perceive the same as me. | 0.794 *** | ||||
SM 2—Why do I like comparing my evaluation with others. | 0.793 *** | ||||
SM 3—To feel better by verifying that I’m not the only one having issues with the services. | 0.813 *** | ||||
SM 4—To feel part of a virtual community. | 0.740 *** | ||||
SM 5—To enjoy interacting with other people. | 0.783 *** | ||||
SM 6—To know if there are new things. | 0.749 *** | ||||
SM 7—To know what topics are being discussed about restaurants. | 0.829 *** | ||||
SM 8—To find solutions to the problems I encounter when booking a restaurant. | 0.777 *** | ||||
Risk reduction motivation | 0.805 | 0.911 | 0.836 | ||
RM1—To make the best decision about a restaurant | 0.917 *** | ||||
RM 2—To benefit from others’ experiences. | 0.912 *** | ||||
Intention to consult eWOM | 0.841 | 0.904 | 0.758 | ||
IC1—I often read recommendations from friends on products or services on social media. | 0.853 *** | ||||
IC2—I enjoy reading on social media about experiences other people had with products or services I’m interested in. | 0.884 *** | ||||
IC3—When I interact on social media, I’m open to receiving opinions from other people about interesting products or services. | 0.875 *** | ||||
Adoption of the consulted eWOM | 0.849 | 0.909 | 0.769 | ||
ACE1—I tend to agree with the opinions and comments of people who write about a restaurant. | 0.810 *** | ||||
ACE 2—Overall, I follow recommendations from comments and opinions about restaurants | 0.913 *** | ||||
ACE 3—The comments and opinions made about a restaurant motivate me to decide to book it. | 0.904 *** |
Convenience Motivation | Social Motivation | Risk Reduction Motivation | Intention to Consult eWOM | Adoption of the Consulted eWOM | |
---|---|---|---|---|---|
Convenience motivation | 0.793 | ||||
Social motivation | 0.726 | 0.785 | |||
Risk reduction motivation | 0.757 | 0.761 | 0.915 | ||
Intention to consult eWOM | 0.598 | 0.513 | 0.529 | 0.871 | |
Adoption of the consulted eWOM | 0.725 | 0.693 | 0.690 | 0.535 | 0.877 |
Convenience Motivation | Social Motivation | Risk Reduction Motivation | Intention to Consult eWOM | Adoption of the Consulted eWOM | |
---|---|---|---|---|---|
Convenience motivation | |||||
Social motivation | 0.789 | ||||
Risk reduction motivation | 0.889 | 0.875 | |||
Intention to consult eWOM | 0.682 | 0.575 | 0.641 | ||
Adoption of the consulted eWOM | 0.827 | 0.782 | 0.828 | 0.628 |
Constructs | Step 1. | Step 2. | Partial Measurement Invariance? | Step 3a. | Step 3b. | Full Measurement Invariance? | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Configural Invariance? | Compositional Invariance | Equal Variances? | Equal Means? | ||||||||
C = 1 | Confidence Interval | Difference | Confidence Interval | Equal? | Difference | Confidence Interval | Equal? | ||||
Convenience motivation | Yes | 0.999 | (0.996; 1.000) | Yes | 0.072 | (−0.220; 0.212) | Yes | −0.053 | (−0.512; 0.486) | Yes | Yes |
Social motivation | Yes | 0.997 | (0.994; 1.000) | Yes | 0.053 | (−0.221; 0.215) | Yes | −0.079 | (−0.400; 0.382) | Yes | Yes |
Risk reduction motivation | Yes | 0.999 | (0.995; 1.000) | Yes | −0.044 | (−0.218; 0.215) | Yes | 0.047 | −0.450; 0.424 | Yes | Yes |
Intention to consult eWOM | Yes | 1.000 | (0.998; 1.000) | Yes | −0.086 | (−0.217; 0.211) | Yes | −0.034 | (−0.414; 0.39) | Yes | Yes |
Adoption of the consulted eWOM | Yes | 1.000 | (0.996; 1.000) | Yes | 0.017 | (−0.219; 0.213) | Yes | 0.123 | (−0.464; 0.419) | Yes | Yes |
Hypothesis | Path Coefficient | t-Value | p-Value | Result |
---|---|---|---|---|
H1: Convenience motivation → Intention to consult eWOM | 0.425 *** | 4.635 | 0.000 | Supported |
H2: Social motivation → Intention to consult eWOM | 0.110 ** | 1.671 | 0.047 | Supported |
H3: Risk reduction motivation → Intention to consult Ewom | 0.123 | 1.391 | 0.082 | Rejected |
H4: Intention to consult eWOM → Adoption of the consulted eWOM | 0.535 *** | 9.858 | 0.000 | Supported |
Hypothesis | Path Coefficient FEMALES | Path Coefficient MALES | Difference Paths | Henseler MGA | p-Value | Results |
---|---|---|---|---|---|---|
H5a: Convenience motivation → Intention to consult eWOM | 0.378 *** | 0.509 *** | 0.131 | 0.231 | 0.482 | Rejected |
H5b: Social motivation → Intention to consult eWOM | 0.048 | 0.217 ** | 0.169 | 0.112 | 0.249 | Rejected |
H5c: Risk reduction motivation → Intention to consult eWOM | 0.205 * | −0.012 | −0.217 | 0.119 | 0.222 | Rejected |
H5d: Intention to consult eWOM → Adoption of the consulted eWOM | 0.540 *** | 0.530 *** | −0.01 | 0.467 | 0.817 | Rejected |
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Haro-Sosa, G.; Moliner-Velázquez, B.; Gil-Saura, I.; Fuentes-Blasco, M. Influence of Electronic Word-Of-Mouth on Restaurant Choice Decisions: Does It Depend on Gender in the Millennial Generation? J. Theor. Appl. Electron. Commer. Res. 2024, 19, 615-632. https://doi.org/10.3390/jtaer19010033
Haro-Sosa G, Moliner-Velázquez B, Gil-Saura I, Fuentes-Blasco M. Influence of Electronic Word-Of-Mouth on Restaurant Choice Decisions: Does It Depend on Gender in the Millennial Generation? Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(1):615-632. https://doi.org/10.3390/jtaer19010033
Chicago/Turabian StyleHaro-Sosa, Giovanny, Beatriz Moliner-Velázquez, Irene Gil-Saura, and María Fuentes-Blasco. 2024. "Influence of Electronic Word-Of-Mouth on Restaurant Choice Decisions: Does It Depend on Gender in the Millennial Generation?" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 1: 615-632. https://doi.org/10.3390/jtaer19010033
APA StyleHaro-Sosa, G., Moliner-Velázquez, B., Gil-Saura, I., & Fuentes-Blasco, M. (2024). Influence of Electronic Word-Of-Mouth on Restaurant Choice Decisions: Does It Depend on Gender in the Millennial Generation? Journal of Theoretical and Applied Electronic Commerce Research, 19(1), 615-632. https://doi.org/10.3390/jtaer19010033