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Table 3. Model Summary of Multiple Regression
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Table 3. Model Summary of Multiple Regression
Model
R R²
Adjusted R²
Std. Error of the Estimate Change Statistics Durbin-
Watson
R² Change
F Change df1 df2 Sig. F Change
1 .539(a) .290 .288
.977 .290 153.402 1 375 .000
2 .836(b) .700 .698
.636 .409 509.763 1 374 .000
3 .822(c) .675 .674
.661 -.025
30.831 1 374
.000 1.725
Notes : a Predictors: (Constant), Service Quality b Predictors: (Constant), Service Quality, Customer Satisfaction c Predictors: (Constant), Customer Satisfaction d Dependent Variable: Re-patronage Intentions
Table 4. Coefficients Analysis Model
Variable Unstandardized Coefficients Standardized Coefficients t Sig.
B Std.
Error Beta
1 (Constant) 3.282
.051
64.783 .000 Service Quality .935 .075
.539 12.386 .000 2 (Constant) -.071 .152
-.468 .640
Service Quality .313 .056
.180 5.553 .000
Customer Satisfaction .974 .043
.733 22.578 .000 3 (Constant) -.493 .137
-3.596 .000
Customer Satisfaction 1.091 .039
.822 27.902 .000 Note: Dependent Variable: Re-patronage Intentions
In summary, all the hypotheses were strongly supported and the proposed framework of the present study was able to demonstrate strong explanatory power. Notably, this study provides evidence for the direct effect of service quality and satisfaction on repatronage intention as suggested by the literature and satisfaction emerged as a stronger predictor of repatronage intentions in the restaurant settings. A number of marketing implications can be drawn from this study. The descriptive result reveals that patrons’ perception towards service quality level provided was consistently lower than their expectation. This implies that more effort is needed to improve the service quality level of the restaurant. The frontline staff may well be trained to be more responsive and sensitive to customer needs, thus providing services that are more efficient and effective. In addition, the restaurant atmosphere can also be improved by ensuring cleanliness and favourable ambience with appropriate music and lighting. Customer satisfaction is also very crucial for marketing
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planning since satisfaction does influence customers’ intention to repatronage the restaurant in future. Hence, marketers should look into the factors that would affect customer satisfaction level. In addition, as customer expectations are changing over time, practitioners are advised to measure their customer expectation and satisfaction regularly and handle complaints timely and effectively.
The present study has a number of limitations. Firstly, the nature of sampling unit under study cannot be generalized to a larger population as only one restaurant was examined and the use of single-item measurement for satisfaction construct has low reliability (Churchill, 1979). Secondly, the causal relationship between service quality and satisfaction was not addressed in the present study. Thirdly, the use of cross-sectional data in a single industry also limits some of the conclusions obtained.
In view of the limitations, future study should use different sampling units which are more generalizable and conduct the study nationwide. The proposed model can also be extended to other service industries or other types of restaurants. In terms of measurement issues, future research may use multiple items to strengthen the reliability of satisfaction construct. Also, the structural relationships among the three constructs should be examined. Additional constructs may also be added into this model, based on the literature, and be tested empirically.
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Kivela, J., Inbakaran, R., and Reece, J. (1999a). Consumer Research in the Restaurant Environment, Download 119.99 Kb. Do'stlaringiz bilan baham: |
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