This research aims to introduce a systematic mechanism for developing an organization specific supply chain performance measurement (SCPM) model and for generating a single regression relationship between the overall supply chain performance (SCP) and each of the SCPM areas using an organization's numerical data. The research uses a case study conducted in a small-scale asphalt manufacturing plant located in West Texas, USA with a sample of 218 data records collected over a period of one year. In this article, the systematic mechanism is demonstrated using the data from the case study organization. It provides guidance for developing a hierarchical SCPM model for the organization using the Supply Chain Operations Reference (SCOR) model, and then to obtain the final regression equation for the overall SCP using the Structural Equations Modeling (SEM) technique. The results obtained from the SCPM mechanism are then compared with the managerial input on the SCP that was analyzed using the Analytical Hierarchical Process (AHP). The results of the comparison are used to validate the SCPM results. A major finding of this research is that the regression coefficients provide a clue for the level of sensitivity those measures have on the overall SCP under given organizational SC capacity and operating levels. The SCPM areas with higher regression coefficients reflect higher sensitivity, thus even a slight variation in the measures contributing to those areas will be contributing to a considerable impact on the overall SCP measures. The findings lead to the implication that managers should pay close attention to controlling the stability of the SC operational processes which are responsible for generating those SCP measures. The goal should be to maintain the desired output levels with the least amount of fluctuations. The regression results therefore provide insight to the managers for identifying the individual SCP measures to be managed more intensely than others based on their relative impacts on the overall SCP. The results are applicable as long as the organization does not change its organizational SC capacity and operating levels, thus can be used for better managing the SC in future. This research fulfills multiple research gaps highlighted in literature, mainly: the absence of a systematic approach to generate an organization specific SCPM model; and the absence of a SCPM system capable of generating a single cause–and-effect relationship between the overall SCP and the numerous hierarchical performance measures reflecting their relative impact. Therefore, this study can be viewed as an attempt to increase the level of awareness in the SC field. The article also proposes several future research directions to test the repeatability and validity of the proposed SCPM mechanism.
All Science Journal Classification (ASJC) codes
- Business, Management and Accounting(all)
- Economics and Econometrics
- Management Science and Operations Research
- Industrial and Manufacturing Engineering