With the Internet’s popularity and the economy’s rapid development, e-commerce has entered a whole new era in China. This study aims to investigate the factors affecting intelligent engineering B2B platforms and develop an indicator system based on the theory of resource complementarity. In addition, this study used a combination of qualitative and quantitative research to calculate the weights. We used the Fuzzy Decision-Making Trial and Evaluation Laboratory and Analytic Network Process (fuzzy DANP) method to determine the weights of the dimensions and indicators. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method ranks the well-known intelligent engineering B2B platforms in China. The results show that platform transaction volume, relationship stability and durability, and degree of dependence are key elements affecting the platforms. Finally, it is proposed that media and companies can prioritize two aspects of cooperation performance and relationship quality to improve the operational efficiency of both parties. Platforms should pay more attention to three indicators: relationship stability and durability, closeness, and platform traffic increase, to reasonably allocate resources, grasp the development opportunities, attract users to reside, and improve the economic benefits of the companies.
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