Comparative Study on Supply Chain Complexity Management Efficiency of Global Automobile Companies

Abstract

Complexity Management has recently attained considerable attention from both academia and practice. Especially, multinational companies with global supply chains are suffering from this complexity crisis as the business environment gets more complicated. Although it seems evident that complexity will harm the performance of the supply chain, there has been little scientific research conducted on this topic.

In this study, I focused on the managerial efficiency of supply chain complexity in global automotive industry. Then a model based on Data Envelopment Analysis (DEA) was adopted in order to evaluate the relative efficiency of supply chain complexity management.

First of all, input variables and output variables were selected from an extensive literature review of preceding research. Factors such as numbers of product types, business divisions, and production facilities of each company were collected as input measures, and net profit was selected as an output measure. Then the initial model was designed with these variables. Secondly, a total of 20 global car manufacturers were selected as decision making units of the model. After the initial analysis, an alternative model with 15 decision making units was designed to achieve a better result reflecting the actual automobile market conditions.

The results of the study are summarized as follows: Toyota and B.M.W. both showed the highest efficiency value (1.0000), following Hyundai Motors (0.8398), Daimler AG (0.7990), and GM (0.7679). In contrast, Fiat-Crysler (FCA) showed the lowest efficiency score (0.061) following Peugeot-Citroen PSA Group (0.1737), Mitsubishi Motors (0.1746), and Suzuki Motors (0.2656).

The study contributes to further understanding of the supply chain complexity by measuring relative efficiency score of each unit. Also, practitioners in the industry could find a room for improvement by benchmarking the results of the study.