헤어미용서비스 소비자가 지각하는 인적서비스품질이 전환비용 및 충성도에 미치는 영향

Abstract

Hairbeauty industry is a field which is highly dependent upon human services. This study attempted to investigate the influence of the quality of hairdressing services on switching costs and customer loyalty to help beauty salons overcome current crisis by preventing customer churn. For this purpose, this study collected and analyzed 338 questionnaire data from experienced men and women who visited hair salons in Gwangju. The questionnaire survey was performed with the following measuring tools by referring to previous studies: ‘reliability’, ‘professionalism’, ‘authenticity’, ‘switching costs’, ‘cognitive loyalty’, ‘affective loyalty’. The collected data were analyzed by multiple regression analysis, using SPSS 26.0, and the results found the followings: First, ‘reliability’, ‘professionalism’ and ‘authenticity’ had a positive influence on ‘switching costs’ with statistical significance. Second, ‘reliability’, ‘professionalism’ and ‘authenticity’ revealed a positive effect on ‘cognitive loyalty’ with statistical significance. Third, ‘reliability’, ‘professionalism’ and ‘authenticity’ showed a positive influence on ‘affective loyalty’ with statistical significance.
 Fourth, ‘switching costs’ had a positive effect on ‘cognitive loyalty’ with statistical significance. Fifth, ‘switching costs’ revealed a positive influence on ‘affective loyalty’ with statistical significance. The above results confirm that switching costs are recognized by the quality of services and that high switching costs enhance customer loyalty.
 Therefore, there is a need to create and supplement new services compared to other hair salons such as development of service manuals suitable for hair salons and efforts to maintain good relationships. With differentiated switching costs, it would be possible to enhance customer loyalty by reducing customer churn, anticipating creation of new consumers. significant influence was observed in ‘personnel’, ‘reward’ and ‘business factor’ (p<.001). In predicting social cognitive factors, ‘personnel’, ‘reward’ and ‘business factor’ demonstrated the explanatory power of 11.4%.