Research on the Coupling of Big Data-Enabled Precision Decision-Making in Marketing and Human Resource Incentive Mechanisms in Business Administration
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Abstract
In the digital economy era, big data technology has reshaped enterprise operation and management by enabling datadriven precision decision-making. This study focuses on the coupling relationship between big data-enabled precision marketing decision-making and human-resource incentive mechanisms in business administration. Through theoretical analysis, model construction, and case verification, the internal logic, implementation path, and optimization strategy of the coupling mechanism are systematically explored. The study first defines the core dimensions of precision marketing decision-making enabled by big data and the key elements of human-resource incentive mechanisms. A coupling model covering data-driven decision-making, demand matching, incentive response, and performance feedback is then constructed. Empirical analysis is conducted using survey data from 60 representative enterprises. The results show that user profiling, precision marketing channel selection, and marketing-effect prediction have significant positive coupling effects with different types of human-resource incentives. Enterprises with higher coupling degrees show significantly higher market-share growth rates and employee performance compliance rates than those with lower coupling degrees. The study provides technical and managerial support for coordinated development between marketing decision-making and human-resource management.
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