Insufficient reference data, information asymmetry, and inability to scientifically determine the growth rate are the main obstacles restricting the proposal of a reasonable and effective collective negotiation plan. In the context of the country accelerating the national cyber development strategy, the construction of digital China, and labor unions vigorously promoting the construction of intelligent labor unions, this paper follows the whole process of collective negotiation, utilizing human decision making (intervention) and computer information processing (AI, etc.), and tries to establish six modules, including big data screening, policy and regulation correction, cloud computing processing, rights and interests compensation, psychological expectation revision, and supervision, to intelligentize the main process of collective negotiation. The scientific operation of the modules is ensured by establishing a dynamic prediction platform based on improving data accuracy and a dual-layer linkage data sharing platform based on improving the breadth of data from All-China Federation of labor unions (ACFTU) to grass-roots labor unions vertically and from industry to enterprise labor unions horizontally. At the same time, reasonable wage increase range and quantitative correction scheme under special circumstances are given through the use of "negative feedback" principle of automatic control theory, the large cycle of closed-loop control system, and the analysis of the absolute and relative value range of wage increase in two-dimensional coordinates. Using qualitative and quantitative analysis methods, the exploration of intelligent collective negotiation can be creatively carried out, and they provide innovative ideas for breaking through the barriers of collective negotiation between labor and management, formulating scientific and feasible collective negotiation plans, and promoting win-win and stability for both labor and management.

A Xiang. A Preliminary Study on the Programmatic Module Construction of Collective Negotiation. International Journal of Frontiers in Sociology (2023), Vol. 5, Issue 8: 91-101. https://doi.org/10.25236/IJFS.2023.050816.

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