Can continuous improvement lead to satisfied customers? Evidence from the services industry

Abstract

Purpose: To achieve higher customer satisfaction (CS), companies implement continuous improvement (CI) programs, regardless of the growing evidence of their failure to achieve declared goals. The purpose of this paper is twofold: first, to identify whether companies are able to improve CS through the application of CI; and, second, to identify what organizational practices are able to facilitate the impact of CI on CS. Design/methodology/approach: To test the developed assumptions, the study uses the structural equation modeling technique. The data for analysis were collected from 304 service companies via a custom web-survey. Findings: The research confirms the direct positive impact of CI on CS. Further, the study demonstrates that management commitment and rewards system that encourages employees to participate in CI play the major facilitating role in improving CS through CI. These practices accompanied by quality-oriented culture and employee training in the improvement tools provide necessary infrastructure to sustain CI in the companies over time. Additionally, regardless of the vital role of goal setting for CI established in previous research, the proposed study finds a limited ability of goal setting, as compared to other organizational practices, to facilitate CI–CS relationship. Originality/value: The study contributes to the scarce field of research on CI implementation in the services environment. Further, the research assesses CS as a variable of interest, as opposite to the previous studies, considering CS as a part of the composite variable. The research assesses the impact of the training in CI methodology on the CI–CS relationship, while previous research focuses on the general, work-related training. The findings provide an important basis for further academic work in the area of quality management. The identified practices can serve as guidance for managers, implementing CI in their companies due to the high fit of the proposed model. © 2018, Emerald Publishing Limited.