Research on the Adoption of Artificial Intelligence and Procurement Decision-Making Behavior in B2B Scenarios Based on Quantitative Analysis

Bojun Liu

doi:10.54097/ed4weq35

Authors

Bojun Liu

DOI:

https://doi.org/10.54097/ed4weq35

Keywords:

B2B scenarios, Artificial intelligence adoption, Procurement decision-making, Quantitative analysis, Organizational resources

Abstract

This article focuses on 326 small and medium-sized B2B enterprise procurement managers and supply chain managers in the Yangtze River Delta and Pearl River Delta regions, covering areas such as machinery manufacturing and industrial product wholesale. The research focuses on the pain points of digital transformation in small and medium-sized enterprise procurement. Through questionnaire surveys and multiple linear regression methods, it explores the influencing factors of artificial intelligence (AI) adoption in the procurement process (such as supplier screening and demand forecasting) and its role in procurement decision-making efficiency and cost control. The results show that perceived usefulness and supplier AI capability positively drive adoption (β=0.32, 0.28, p<0.01), Insufficient organizational resources significantly inhibits adoption (β=-0.19, p<0.05); The adoption of AI can shorten the procurement decision-making cycle by 21.3% and reduce procurement costs by 15.7%. The data is sourced from field research conducted in 2024 and public reports from the Ministry of Industry and Information Technology and the National Bureau of Statistics, providing empirical reference for B2B enterprises to optimize AI procurement strategies, solve transformation difficulties, and improve supply chain management levels.

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