This research studied the relationship between three input variables and outcomes related to the use of quality circles (QCC) in a Chinese manufacturing company. After a thorough review of the literature, three managerial input variables were identified, including goal clarity, goal difficulty, and management support. Five outcomes were measured, including attitude, motivation, skill, understanding of continuous improvement and QCC success. Further, models were built for each individual outcome variable to identify the most significant input variables.
A single site study was conducted to investigate the research hypotheses. Survey scales were developed based on previous research. A translated survey was developed for collecting data in the selected Chinese company. After initial data screening, principal component analysis was conducted, and Cronbach's alpha values were calculated. The results of these analyses were used to revise and validate the survey scales. In addition, ANOVA and ICC(1) were calculated to determine whether or not survey data collected from individual QCC members could be aggregated to the team-level.
Two different analyses were conducted to test the research hypotheses. First, a Pearson correlation coefficient analysis was conducted to test three out of eight hypotheses. These three hypotheses were developed to determine whether or not individual input variables had a direct relationship with each individual output variables. Second, five outcome variable models were developed using multiple regression. These models were built to test the remaining five hypotheses, which were designed to identify the most significant set of input variables for explaining the variation observed in each outcome variable.
Results from this research indicate that goal clarity and management support have a direct relationship with all outcome variables, while, goal difficulty exhibited a direct relationship only with attitude. Attitude was significantly affected by goal clarity and goal difficulty. Motivation and skill were both impacted by goal clarity. Understanding of continuous improvement was strongly affected by goal clarity and management support. Finally, QCC success was shown to be strongly affected by goal clarity and management support.
Implications from this research extend to both practitioners and to the governing body of knowledge on QCC management. Based on the findings from this study, engineering managers should work to ensure that QCC teams establish clear goals. Management support also is critical and will help ensure that organizations benefit from QCC projects. Difficult goals are also more attractive than easy goals to QCC teams. The findings from this study also support the need for researchers to further develop and understand the relationship between other potential factors and QCC outcomes and consequently implications on QCC management.