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Investigates resource reconstruction efficiency in small- and medium-sized manufacturing enterprises, suggesting dynamic model shifts for collaboration.
With the continuous embedding of small- and medium-sized manufacturing enterprises (SMMEs) into manufacturing platform ecosystems, selecting the optimal resource reconstruction model has become a critical decision for both platforms and SMMEs. However, the existing literature provides limited insight into how different resource types compare in terms of their efficiency in enabling capability reconstruction. Addressing this gap, this paper constructs asymmetric Stackelberg game-theoretic models for the platform–SMME collaborative system and systematically investigates efficiency differentiation and strategy selection under three resource models: the fund resource model, the knowledge resource model, and the fund and knowledge hybrid model. Drawing on dynamic capability theory, the models formalize the transmission paths through which heterogeneous resources affect SMMEs’ capability reconstruction, and derive the equilibrium conditions governing resource input, pricing, revenue-sharing, and payoff outcomes. The findings reveal three key insights. (1) As dynamic capability matures and price sensitivity rises, the platform’s optimal strategy shifts systematically from fund resource model through hybrid model to knowledge resource model, requiring dynamic model switching aligned with the SMME’s capability path and market conditions. (2) Fund-driven improvement operates through two paths, while knowledge-driven improvement operates through four paths and the upstream paths, creating a win-win zone and downstream paths generating diverging interests. (3) Dynamic capability, particularly conversion efficiency of “information-management,” reduces resource input while increasing both parties’ payoffs, shifting the strategy from a fund resource model to a knowledge resource model. The findings point to a shift from resource provision to capability-driven collaboration, requiring dynamic model switching by platforms, precision matching by SMMEs, and shared investment in dynamic capabilities for sustainable mutual benefit.
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Wang et al. (2026) studied this question.
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