竞争网络与公司财务绩效

doi:10.16381/j.cnki.issn1003-207x.2022.2294

Abstract

Abstract:

The significance of the competitive network position as a key factor in firms' strategic decision-making and its impact on financial performance is the focus of this study. First， using China's property insurance industry from 2008 to 2019 as the research subject， a Random Forest model is constructed to investigate the predictability of competitive network characteristics and market structure characteristics. Next， the importance of competitive network and market structure is analyzed using the feature importance evaluation method of the Random Forest model. Finally， the nonlinear functional relationship between these important features and financial performance is revealed using SHAP values and further the causal relationship between key competitive network features and financial performance is verified using traditional econometric models （Propensity Score Matching）. It also explores the differences between nonlinear and linear model results.The research findings show that　（1） Overall， the absence of either competitive network or market structure features can reduce the fitting performance of the enterprise financial performance model， with the impact of missing competitive network features being more pronounced. （2） In terms of the ranking of feature importance， competitive network features account for approximately 30% of the importance to enterprise financial performance， significantly higher than the importance of market structure features. Key features within competitive network include： individual network size， intermediary frequency， and closeness centrality. （3） These three key features follow a power-law distribution with respect to enterprise financial performance， and the existence of a strong causal relationship between important competitive network features and financial performance was verified through propensity score matching. The conclusions of this paper enrich the research outcomes in the field of competitive networks and financial performance， providing support for them， and offer a new solution for causal analysis and verification between high-dimensional， nonlinear factors.

Key words: competitive network, financial performance, random forest, SHAP model

CLC Number:

F832.5

Jianxin Zhu, Kexin Liu, Nengmin Zeng, Xiong Wu. Competitive Network and Financial Performance: Empirical Evidence Based on Explainable Random Forest[J]. Chinese Journal of Management Science, 2025, 33(8): 75-89.

Figures/Tables 8

变量类型	变量名称	变量符号	变量测度方法
财务绩效
-	收入	PI	保费收入
-	成本	Cost	赔付支出
-	利润	Profit	净利润
竞争网络特征
个体网指标	个体网规模	Size	与焦点企业直接相连的其他企业的数量
	个体网密度	Densit	$D = 2 L n (n - 1)$
	中间人次数	Broker	若企业A需要通过企业B才能与企业C联络，则B记为中间人
	可达效率	ReachE	企业节点在两步内可达的点数占各个节点的个体网规模总和的比重
	中介中心性	Betweenness	$B i = ∑ s ≠ i ≠ t n i s t g s t$
	接近中心性	inCloseness	$C i = 1 n - 1 ∑ j = 1 n d i j$
	特征向量中心性	Eigenvec	$E C i = c ∑ j = 1 n a i j x j$
	网络约束系数	Constra	$C T i = ∑ j (P i j + ∑ q P i q P q j) 2$
	等效度指数	Hierarc	$H I i = ∑ j (C i j / C n) l n (C i j / C n) n l n (n)$
	网络有效规模	EffSize	$E S i = ∑ j (1 - ∑ q P i q P j q) = n - 1 n ∑ j ∑ q P j q$
	效率	Efficie	$E F i = E S i n$
	介数中心性	EgoBet	$C B = ∑ i ∑ j g i j (q) g i j$
	聚类系数	Clus Coef	$C C i = 2 E (i) n (n - 1)$
市场结构特征
竞争地位	勒纳指数	Lerner	详见式（12）~式（15）
基准特征
资金实力	企业规模	Asset	企业期末总资产
经营效能	产品集中度	HHI	$H H I i = ∑ i = 1 N (P i P) 2$
	再保险比例	Rein	分出保费/总保费收入
	赔付率	Payout	综合赔款支出/已赚保费
偿债能力	资本比例	Cap	所有者权益/总资产
	业务杠杆	OL	保费收入/所有者权益
	财务杠杆	Lev	负债总额/所有者权益
	资产负债率	DebtR	负债总额/总资产
成长能力	投资收益率	ROI	投资收益/平均可投资资产
	资产收益率	ROA	净利润/总资产
	保费收入增长率	RINF	（当年保费收入-上年保费收入）/当年保费收入
公司治理	股权制衡度	S2s1	第二大股东持股占比/第一大股东持股占比
	董事会规模	Board	董事会总人数
	股权集中度	Sum3	前三个股东持股比例的平方和
	两职合一	Duality	董事长与总经理为同一人时记为1，否则为0
公司性质	是否上市	Listed	上市公司记为1，否则为0
	成立年限	Age	企业年龄
	是否外资	Foreign	含有外资资本记为1，否则为0

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变量	Obs	Mean	Std. Dev.	Min	Max
财务绩效
PI	410	15052.961	38859.17	34.85	281010
Cost	410	7625.967	19971.136	4.25	154267
Profit	410	668.307	2286.783	-98.18	21294.801
竞争网络特征
Size	410	27.654	18.146	0	79
Densit	410	52.577	13.112	0	66.67
ReachE	410	7.695	12.994	0	100
Broker	410	241.199	272.486	0	1574
Betweenness	410	46.871	91.679	0	686.852
inCloseness	410	6.527	5.16	1.124	48.438
Eigenvec	410	0.114	0.062	0.033	0.707
EffSize	410	7.195	2.945	0	15.502
Efficie	410	0.112	0.032	0	0.315
Constra	410	0.068	0.043	0	0.752
Hierarc	410	0.006	0.005	0	0.028
EgoBet	410	10.974	19.659	0	126.81
Clus Coef	410	0.512	0.053	0	0.595
市场结构特征
Lerner	410	0.531	0.186	0	0.915
基准特征
DebtR	410	0.648	0.177	0.105	1.202
Cap	410	0.349	0.175	-0.202	0.895
Lev	410	3.291	16.771	-112.566	311.713
OL	410	2.886	18.097	-80.319	350.821
RINF	410	0.303	0.871	-0.365	15.528
ROI	410	0.129	0.109	-0.108	0.705
HHI	410	0.532	0.196	0.156	1
Rein	410	0.344	0.723	-1	6.753
Payout	410	0.698	0.479	0.04	6.529
Asset	410	24572.252	59908.115	190.34	420379
Sum3	410	0.771	0.247	0.3	1
S2s1	410	0.439	0.398	0	1
Board	410	8.641	3.345	2	18
Duality	410	0.149	0.356	0	1
Foreign	410	0.351	0.478	0	1
Listed	410	0.044	0.205	0	1
Age	410	8.222	5.731	0	36
ROA	410	-0.157	5.249	-39.782	11.722

变量	Group1	Group2	Group3	Group4	Group5
模型1：PI
MAE	3186.5083	2648.646	2672.1404	2899.5221	3232.8047
RMSE	13647.8888	8966.45932	9200.4416	12271.0331	14761.0894
R²_Score	0.8459	0.9927	0.9555	0.8971	0.8145
模型2：Cost
MAE	1930.2821	1842.2862	1850.6995	1990.1941	2098.6977
RMSE	7199.5338	6557.3977	6842.8924	7400.7595	8326.7164
R²_Score	0.8712	0.9097	0.8941	0.8535	0.8053
模型3：Profit
MAE	301.7199	264.1507	271.8229	309.2835	325.3374
RMSE	1117.5600	809.2412	903.9652	954.2894	1001.7300
R²_Score	0.7861	0.8732	0.8199	0.7731	0.7687

类别	模型1：PI		模型2：Cost		模型3：Profit
类别	特征变量	重要性%	特征变量	重要性%	特征变量	重要性%
资金实力	Asset	50.4933	Asset	50.5651	Asset	59.3051
个体网	Size	11.3570	inCloseness	9.8442	inCloseness	11.0168
	Broker	8.5704	Size	7.4878	Size	3.8096
	inCloseness	7.4085	Broker	6.1018	Broker	3.4051
	Constra	2.5553	ReachE	2.986	EffSize	1.1798
	ReachE	1.8088	EffSize	2.7482	Densit	1.1320
	EffSize	1.0448	Densit	2.0000	ReachE	1.1283
	Eigenvec	0.8835	Constra	1.7326	Eigenvec	0.4803
	Densit	0.7868	Eigenvec	0.6730	Constra	0.2853
	Efficie	0.1778	Efficie	0.2740	Hierarc	0.2439
	Hierarc	0.1495	Hierarc	0.2427	Clus Coef	0.1228
	Clus Coef	0.0617	Clus Coef	0.1688	Efficie	0.1081
	Betweenness	0.0031	EgoBet	0.0516	EgoBet	0.0183
	EgoBet	0.0023	Betweenness	0.0268	Betweenness	0.0111
	小计	34.8095	小计	34.3375	小计	22.9414
竞争地位	Lerner	0.5647	Lerner	0.5152	Lerner	0.5089
经营效能	HHI	4.5855	HHI	5.9666	HHI	3.5907
	Rein	0.6978	Rein	0.5224	Rein	1.2342
	Payout	0.2013	Payout	0.0981	Payout	0.3689
偿债能力	Cap	1.4275	OL	0.8836	Cap	0.8355
	OL	1.2999	Cap	0.5825	OL	0.6692
	Lev	0.6522	DebtR	0.4373	DebtR	0.5129
	DebtR	0.5125	Lev	0.3833	Lev	0.5008
成长能力	ROI	1.5261	ROA	2.6443	ROA	4.3204
	ROA	1.2071	ROI	0.4926	ROI	1.7035
	RINF	0.5298	RINF	0.1828	RINF	0.2966
公司治理	S2s1	0.6917	S2s1	0.9171	S2s1	0.8715
	Board	0.2654	Sum3	0.6681	Sum3	0.4863
	Sum3	0.1144	Board	0.1651	Board	0.3645
	Duality	0.0059	Duality	0.0035	Duality	0.1573
公司性质	Listed	0.2106	Age	0.3250	Listed	1.0545
	Age	0.2047	Listed	0.3097	Age	0.2756
	Foreign	0.0001	Foreign	0.0002	Foreign	0.0022

Competitive Network and Financial Performance: Empirical Evidence Based on Explainable Random Forest

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