Developing a suitability assessment model for Public Private Partnerships: a case in urban China

The study addresses whether and where PPPs are suitable as a model for urban infrastructure and public service delivery. While PPPs can improve efficiency, risk allocation, and service outcomes, they are not universally appropriate across all places or sectors. The spatial distribution of PPPs is uneven globally and within countries due to differences in economic, social, institutional, and governance conditions. This paper focuses on the city-level environmental suitability for PPP adoption (distinct from project-level suitability). Using China—characterized by rapid PPP expansion and diverse regional contexts—the study develops and applies a quantitative suitability assessment model to evaluate PPP adoption potential across prefecture-level cities. The purpose is to provide evidence-based, place-specific guidance for sustainable PPP governance. The study contributes by filling a gap in place-based PPP suitability analysis, supporting sustainable PPP development aligned with SDGs, and offering insights relevant to other developing countries.

PPPs encompass diverse models (e.g., BOT, PFI, DBFO) and are generally defined as long-term public–private collaborations for infrastructure and services grounded in risk/benefit sharing and contractual governance. Prior research highlights two suitability dimensions: (1) project-level appropriateness (widely studied) and (2) the suitability of a city’s overall environment for PPP adoption (limited research). The geography of PPPs shows that urbanization, economic development, governance capacity, regulation, and local culture shape PPP uptake and performance, leading to pronounced spatial differences even within a single country. Most existing assessments emphasize national-level enabling environments—legal frameworks, PPP units, and financial markets—rather than city-specific suitability. China, with its extensive PPP experience, rapid urbanization, data availability, and marked regional variation, is an ideal context to develop and demonstrate a city-level PPP suitability model. The paper addresses the gap in evaluating PPP suitability through a localized lens, especially critical given China’s post-2014 PPP surge and subsequent governance challenges (e.g., debt risks, project irregularities).

Research design: The study constructs a multi-criteria suitability assessment model for PPP adoption at the city level and demonstrates it using data from 287 Chinese prefecture-level cities (cross-sectional up to 2021). The workflow: indicator selection and system design; objective weighting via entropy method; comprehensive evaluation and ranking via TOPSIS; classification of cities using the natural breakpoint method. Model framework (target–rule–indicator): Target: assess a city’s suitability to adopt PPPs and guide localized PPP strategies. Rules and indicators: (1) Development needs: GDP; urbanization rate; infrastructure investment (fixed asset investment to GDP). (2) Local government efficiency: government–business relationship indicator. (3) Fiscal capacity: financial revenue (general public budget revenue/GDP); financial self-sufficiency (revenue/expenditure). (4) Government credit: government credit regulatory ranking. (5) Government regulatory capacity: number of local PPP projects; number of local PPP demonstration projects (selected by Ministry of Finance). (6) Urban development characteristics: environmental sustainability (air quality); social sustainability (urban livelihood development). Data sources: China Urban Statistical Yearbook (GDP, urbanization, infrastructure investment, fiscal indicators); Ministry of Finance PPP project database (PPP projects, PPP demonstration projects); CreditChina (government credit index); Renmin University of China report on government–business relationship (health index); Ministry of Ecology and Environment (Air Quality Index); Beijing Normal University People’s Livelihood Development Report (livelihood index). Data are cross-sectional up to 2021. Data processing and evaluation: Indicators are normalized (beneficial indicators scaled so larger is better; cost indicators reversed). Objective weights are determined via the entropy method, where higher dispersion yields higher weight. The weighted normalized matrix is evaluated using TOPSIS: distances to positive and negative ideal solutions are computed, and a closeness coefficient T is obtained for each city; higher T indicates greater suitability. Cities are then categorized by natural breaks into four suitability classes. Weights: The entropy method produced the following weights (selected): GDP 0.23214; infrastructure investment 0.15049; society sustainability 0.10721; local PPP demonstration projects 0.18776; local PPP projects 0.08760; financial self-sufficiency 0.06933; financial revenue 0.04605; government–business relationship 0.05063; urbanization rate 0.02863; environment sustainability 0.03013; government credit 0.01002.

- The model evaluated 287 prefecture-level cities. The TOPSIS closeness coefficient T was used to rank suitability. - Classification thresholds (natural breaks) by T: high suitability (>0.3459); medium (0.2229–0.3458); low (0.1446–0.2228); unsuitable (<0.1445). - Distribution: 18 high-suitability cities (T range 0.3459–0.6623; e.g., Beijing 0.6623, Shanghai 0.5271, Shenzhen 0.4518, Guangzhou 0.4328, Jining 0.4282); 50 medium; 81 low; 138 unsuitable. - Overall, 219 cities (≈76%) fall into low or unsuitable categories (T ≤ 0.2228), indicating PPPs are not broadly applicable across most Chinese cities under current conditions. - Spatial pattern: provincial capitals and economically developed cities score higher; eastern coastal cities are generally more suitable than central and western regions. - Determinants: economic development is critical. Indicator weights emphasize GDP (0.23214) and infrastructure investment (0.15049). Government regulatory capacity—particularly the number of PPP demonstration projects—also has high importance (0.18776), indicating experience and standardization strongly correlate with suitability. - Case illustrations: Cities like Yibin and Chifeng, though not top in economic size, rank high in PPP demonstration projects, reflecting strong regulatory capacity and PPP experience that enhance suitability. - Many low/unsuitable cities exhibit weaker economies, lower fiscal capacity, limited regulatory capacity and government credit, and sometimes shrinking populations—factors undermining PPP feasibility and increasing risks.

The research question concerns where PPPs are suitable at the city level and which factors drive that suitability. Findings show PPP suitability is highly uneven spatially and is strongly associated with economic and fiscal strength, governance capacity, and accumulated PPP experience. This supports the premise that PPPs are not a one-size-fits-all solution and must be tailored to local conditions. The high weights on GDP, infrastructure investment, and PPP demonstration experience indicate that market depth, development needs, and institutional/regulatory maturity enable PPP success. Less-developed cities may be motivated to use PPPs to spur growth, but without strong governance, creditworthiness, and regulatory capacity, risks of failure, inefficiency, and fiscal stress increase. Policy implications: adopt differentiated strategies—encourage standardization and scaling in high-suitability cities; proceed cautiously and methodically in medium-suitability cities; in low/unsuitable cities, prioritize capacity building, governance improvements, and limited pilot PPPs before wider adoption. These measures align PPP deployment with local readiness, reducing risks and improving outcomes.

The study develops and demonstrates a city-level PPP suitability assessment model combining entropy-based objective weighting and TOPSIS ranking, applied to 287 Chinese cities. It reveals pronounced spatial heterogeneity: only a minority of cities are highly suitable, while most are low or unsuitable under current conditions. The model offers a scientific basis for more sustainable, place-based PPP governance in China and provides a reference framework for other developing countries. Future research should refine and expand indicators (e.g., through expert input), test the model in other national contexts, analyze dynamic interactions among determinants, and conduct longitudinal assessments to evaluate long-term PPP sustainability and outcomes. Policy recommendations include using PPPs as a complementary, not dominant, delivery model; ensuring standardization and legal compliance; and enhancing transparency, accountability, and stakeholder engagement.

- Indicator coverage: The selected indicators may not capture all relevant dimensions of PPP suitability, affecting comprehensiveness. - Data constraints: Availability and quality limitations (cross-sectional up to 2021) may influence accuracy and timeliness. - Generalizability: The model’s applicability to other countries is uncertain and may require extensive local data and adaptation.