In the volatility, uncertainty, complexity, and ambiguity (VUCA) era, platform enterprises face the critical challenge of balancing flexibility and controllability to sustain competitive advantage. Existing studies have examined these two dimensions separately but offer limited insight into their synergistic mechanisms within complex adaptive ecosystems. Drawing on the structural, cognitive, and relational dimensions of social capital theory, with a particular emphasis on institutional-level collaborative social capital among platform enterprises and their supply-chain partners, this study employs dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify the configurational pathways through which Chinese platform enterprises achieve high sustainable development performance. Using panel data from Chinese A-share listed platform enterprises (2014–2024), we identify three equifinal configurational pathways sufficient for high sustainable development performance: (1) a cognitive-relational alliance-driven path, (2) a structural-relational hybrid synergy path, (3) a structural-cognitive flexible innovation path. Innovation value consensus emerges as a core condition across all pathways. These configurations are sufficient for platforms to exhibit flexible market responsiveness and strategic controllability under varying environmental conditions. The study advances social capital theory by demonstrating the multidimensional, synergistic, and context-sensitive nature of flexibility-controllability coupling in platform governance. It also provides managers with actionable insights for tailoring social capital investments to specific regional and strategic contexts.

E-commerce systems often collect data that clearly express user preferences without considering the remaining negative cases, which gives rise to the hidden semantic problem. In this paper, we improve the original hidden semantic model and propose an intergroup effect model that incorporates users historical browsing behavior, user type, and browsing content; by adopting the weighting and add weighting factors, we can predict users preferences for different products more accurately and match the candidate products with users current behaviors, so as to give more reasonable and effective product recommendation results; by adding the group effect model of user group and product group, we can achieve more accurate prediction of user preferences and make the recommendation more reasonable and effective. The research shows that the hidden semantic method based on intergroup effects information is better than other basic methods at a certain identified evaluation stage. In practice, users purchasing preferences change with time, and using a hidden semantic method based on intergroup effects recommendation can effectively improve the recommendation quality of e-commerce recommendation systems.

Currently, intelligent agent applications generally face the bottleneck of “strong single-agent intelligence but weak group collaboration,” making it difficult to form systemic ecological advantages through network effects. Addressing this practical dilemma, this paper adopts the platform ecosystem perspective, defines three dimensions of intelligent agent network ecological advantage—resource complementarity, governance coordination, and dynamic adaptability—and systematically reveals its nonlinear formation mechanism based on the coupling of self-organization, emergence, and governance. Taking 2024 Chinese listed platform enterprises as the sample and employing fuzzy-set qualitative comparative analysis (fsQCA), this study identifies three multi-factor equivalent configurational paths that drive high ecological advantage: the resource-open collaborative type achieves synergistic amplification and leap through deep fusion of resource openness; the algorithm-incentive-regulation type drives asymmetric leadership through technological depth and governance response; and the resource-governance-adaptive type constructs resilience barriers in highly uncertain environments through comprehensive and balanced configurations. This paper constructs an active symbiosis theory of intelligent agent ecosystems, advancing ecosystem theory from the traditional “passive complementarity” paradigm to a new “active symbiosis” paradigm, revealing multiple concurrent causality and asymmetric causality, clarifying the dual role of regulatory sensitivity as both a “bridge” and an “amplifier,” and providing a novel theoretical framework and analytical paradigm for platform ecosystem governance in the GenAI and multi-agent era.