From silos to systems: Network-based evaluation of industrial land use efficiency—A case study of the biopharmaceutical industry in Chinese Suzhou industrial park

In the era of stock development, the redevelopment of industrial parks, as a critical component of urban renewal, offers a pathway for smart growth and sustainable development in Chinese cities. A scientifically sound performance evaluation model serves as an essential analytical tool and decision-making basis for such redevelopment. While the efficiency evaluation model of industrial parks has gone through a stage of characteristic evolution from rough to fine and then to comprehensive, current practices often treat individual enterprises or land parcels as isolated entities, neglecting the systemic value of industrial cluster linkages. This study critically examines the “Isolated Island Dilemma”—a systemic flaw in current models where enterprises are evaluated as disconnected entities, ignoring their industrial linkages. To address this, we propose an “Archipelago-style” evaluation framework. Unlike the isolationist approach, this framework treats the park as a connected ecosystem, where the value of each entity is determined by its network contribution. Using the biopharmaceutical industry in Suzhou Industrial Park (SIP) as a case study, we introduce the Network Topology Efficiency Index ( Q )—a composite metric quantifying the connectivity, efficiency, and bridging role of enterprises—to operationalize this systemic perspective. By constructing network topology efficiency metrics, this approach transcends isolated perspectives to quantify the relational contributions of individual enterprises to the park's ecosystem, while comparing discrepancies with results from conventional evaluation models. The findings reveal theoretical and practical shortcomings in current evaluation paradigms, such as causing the restriction of development and even the withdrawal of enterprises that play pivotal roles in regional industrial development. So, this study proposes integrating holistic systems thinking through collaborative network analysis, offering a foundation and optimization strategies for developing an archipelago-style performance evaluation framework.