TY - JOUR
T1 - Statistical thinking and its impact on operational performance in manufacturing companies
T2 - an empirical study
AU - Lizarelli, Fabiane Letícia
AU - Antony, Jiju
AU - Toledo, José Carlos
N1 - Funding Information:
Funding was provided by Fundação de Amparo à Pesquisa do Estado de São Paulo (Grant No. 2013/12910-1).
Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/12
Y1 - 2020/12
N2 - Statistical thinking (ST) is a concept that has been discussed in the literature as principles and concepts disseminated in companies to conduct a statistical approach and it is often associated with using continuous improvement programs (CIPs), such as Six Sigma and Lean Six Sigma since the 1990s. There is a lack of empirical studies in the literature that address this topic concerning the impacts generated by ST in operational performance (OP) of industrial companies, as well as the relationships between ST and CIPs. The paper proposes and tests the hypothesis that the use of ST principles is positively associated with OP in manufacturing companies in the context of CIPs. The empirical research was conducted in a sample of 243 manufacturing companies and used structural equation modelling—partial least squares for data analysis. Positive and statistically significant relationships between ST and OP were observed. ST principles can reduce non-conformities, lower production costs and increase the stability of the process. The findings also support that CIPs have a positive effect on the use of ST principles and a positive effect on OP. This indicates the managerial importance of implementing CIPs, including Six Sigma, Lean Six Sigma, lean and total quality management, and the emphasis on developing mechanisms that operationalize the understanding and practice of the ST principles and statistical techniques for better OP in the manufacturing environment.
AB - Statistical thinking (ST) is a concept that has been discussed in the literature as principles and concepts disseminated in companies to conduct a statistical approach and it is often associated with using continuous improvement programs (CIPs), such as Six Sigma and Lean Six Sigma since the 1990s. There is a lack of empirical studies in the literature that address this topic concerning the impacts generated by ST in operational performance (OP) of industrial companies, as well as the relationships between ST and CIPs. The paper proposes and tests the hypothesis that the use of ST principles is positively associated with OP in manufacturing companies in the context of CIPs. The empirical research was conducted in a sample of 243 manufacturing companies and used structural equation modelling—partial least squares for data analysis. Positive and statistically significant relationships between ST and OP were observed. ST principles can reduce non-conformities, lower production costs and increase the stability of the process. The findings also support that CIPs have a positive effect on the use of ST principles and a positive effect on OP. This indicates the managerial importance of implementing CIPs, including Six Sigma, Lean Six Sigma, lean and total quality management, and the emphasis on developing mechanisms that operationalize the understanding and practice of the ST principles and statistical techniques for better OP in the manufacturing environment.
KW - Improvement programs
KW - Manufacturing companies
KW - Operational performance
KW - Partial least squares
KW - Statistical techniques
KW - Statistical thinking
KW - Structural equation modelling
UR - http://www.scopus.com/inward/record.url?scp=85091454373&partnerID=8YFLogxK
U2 - 10.1007/s10479-020-03801-7
DO - 10.1007/s10479-020-03801-7
M3 - Article
AN - SCOPUS:85091454373
SN - 0254-5330
VL - 295
SP - 923
EP - 950
JO - Annals of Operations Research
JF - Annals of Operations Research
IS - 2
ER -