Modeling Supply Chain Complexity and its Impact on Financial Performance of Automotive Companies: A Case Study of Saipa Automotive Group
Subject Areas : Industrial Management Supply Chain Trendعلی اکبر ساسانی 1 , حسین عظیمی 2 , عبداله نظری 3
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Abstract :
Understanding and managing supply chain complexities is crucial for the survival of any organization in a competitive environment since they mainly affect the organization's performance in various dimensions. Therefore, the present study as a case study of the Saipa Automotive Group is an attempt to design a supply chain complexity model and measure its impact on the financial performance of automotive companies. Therefore, it is categorized as basic-applied research in terms of its purpose. The statistical population of the study encompass all managers and employees of the Saipa Automotive Group, of which 384 people were selected for the quantitative part and 17 Saipa automotive industry experts for the qualitative part using the Cochran formula. A questionnaire and semi-structured interviews were used to collect the quantitative and qualitative data, respectively. The data from the questionnaire were analyzed using SPSS and Smart PLS software, and the content analysis was used to analyze the data from the interviews. The results of the qualitative data analyis show that the supply chain complexities in automotive companies are divided into two parts: structural complexities and dynamic-behavioral complexities. These complexities in the structural section are related to the four dimensions of integration, supply, production, and distribution complexities, and in the dynamic-behavioral complexities section, they are related to the three dimensions of supply, production, and distribution, which include a total of 31 items. The results of the quantitative data analysis also reveal that supply chain complexities affect different dimensions of Saipa Group's financial performance.
Key Words
supply chain complexity model, on financial performance, structural complexity, dynamic and behavioral complexity, Saipa Automotive Group
1.Introduction
A supply chain is a complex network of business entities involved in the upstream and downstream flows of products and/or services, along with related finance and information. Supply chain management (SCM) includes the systematic and strategic coordination of these flows within and between companies in the supply chain with the aim of reducing costs, improving customer satisfaction, and gaining competitive advantage for independent companies and the entire supply chain. A supply chain that operates in a dynamic and uncertain environment is definitely a complex system with different companies, a large number and variety of relationships, processes and interactions between companies and within companies, which involve many levels of the system and a large amount of information.
2.Litrature Review
Stephen Hawking (1942-2018) argued that the 21st century would be the century of complexity. Today, VUCA factors, that is, Volatility, Uncertainty, Complexity and Ambiguity environments are becoming more and more challenging for companies to deal with. Hence, it is essential to keep these factors in mind while managing and improving organaizational performance. One of the VUCA factors is the complexity that characterizes any interconnected system and network such as a supply chain (Maka et al., 2016, Rahum et al., 2019).
3.Research methodology
In any research, the selection of data collection and analysis methods is guided by the research objectives and questions. Accordingly, to provide a model of the supply chain coomplexity within the Saipa automotive industry, in the first stage of the study, the interview method has been employed. This qualitative approach is appropriate since this research is trying to provide a complexity model and identify the most complete and relevant factor affecting the finantioal performance. In this regard, the current research is purpose-driven, with the primary audience being the scientific community and researchers. The main objective is to generate new knowledge and contribute to the understanding of supply chain complexity specifically within the Saipa automotive industry.
4.Result
Based on the results of the hypothesis test in the present research, it can be concluded that the automotive supply chain industry consists of several companies that either directly or indirectly produce both primary and secondary equipment. Every car needs different components, from the small nuts and bolts that hold the seat together with the frame, to larger parts like tires. As a result, automotive supply chains have added complexity on both the supplier and manufacturer sides. Supplier inefficiencies can be very expensive for Saipa because the industry often uses JIT production. Delayed delivery of parts or delivery of poor quality can bring the entire production line to a standstill. A high intensity of sub-dimensions of complexity is observed on the supplier side. In production, the use of continuous production lines makes it necessary that all required factors for production work well.
5.Discussion
The automotive industry has many complex suppliers. Consequently, they cannot be easily managed due to difficulties in supplier integration and ensuring traceability across levels. Supply reliability is difficult to manage, however, forecasting accuracy can be greatly improved by big data analysis. The automotive industry involves a large amount of automation, which due to machine breakdowns and changes in product design becomes an important part of the supply chain disruption. These complexities can now be easily managed through predictive maintenance and product design software.
Conflict of interest: none
