Decision Support System in Strategic Supply Chain Management: A Thai SMEs’ Perspective

Abstract

Modern businesses have been relentlessly competing with a new product, new technology, and efficient supply chain management. With an increase in demand variety and product features, a modern supply chain tends to grow in complexity as a result of product variety and complexity. Large, resourceful companies always have advantages in wielding the power of the supply chain, resources, and information to compete in modern business with more competitive products. However, SMEs, as the backbone of the country's economy, does not have that kind of power. Generally, they lack critical resources such as human resources, financial resources, and proper knowledge of business and supply chain management to handle their business operations properly. Moreover, the inability to exploit information technology makes SMEs even more vulnerable in the era of a data-driven economy. As a result of the pain points of SMEs, this research aims to design and develop the DSS for SMEs by combining the concept of strategic supply management and the aspect of the product characteristics. The DSS assists SMEs by supporting a strategic implication of supply chain management toward the product characteristics. The scope of strategic decisions was designed to cover the critical functions of supply chain management activities in SMEs, from sourcing and inventory, manufacturing, and distribution. The utilization of the machine learning technique made the DSS more generalized and can be utilized in numerous manufacturing industries, especially manufacturing SMEs, due to its adaptability and learning capability. Besides the reliable results, implementing the DSS also help the SMEs to realize more about the importance of data, and encourage them to take more advantages in utilizing the data in long term business operations.