Dynamic Partner Retention, Network Dominance, and SME Productivity: A Statistical Modeling Approach

Static concentration measures cannot show whether economically important trading relationships persist over time. This study constructs transaction-value-weighted measures of supplier and customer retention and incorporates them into a network-augmented model of firm productivity. Chinese value-added tax invoices and matched firm records from 2019 to 2025 yield an unbalanced panel of 443,506 firm–year observations. Supplier stability is the share of current purchases from suppliers retained from the preceding year, while customer stability is defined analogously using sales. Annual directed, weighted transaction networks are reconstructed from invoice flows, and DomiRank measures firms’ structural dominance. Total factor productivity is estimated using the Levinsohn–Petrin method. Firm and year fixed-effects estimates show negative relationships between both stability dimensions and productivity. Two-stage least-squares estimates using leave-one-out same-industry peer stability as instruments remain negative. Positive interactions with DomiRank indicate that stronger network positions attenuate these relationships. Potential operating-channel analyses associate stable ties with higher gross margins and asset turnover, but also with greater expenses, weaker operating profitability, slower inventory turnover, and longer operating cycles. Results are robust to alternative measures, matching, high-dimensional fixed effects, outlier treatment, lagged specifications, and industry–year stratified permutation tests. The findings show how longitudinal transaction statistics and network position jointly explain productivity heterogeneity among SMEs.