Political Connections and Charitable giving of Chinese Private Enterprises: Analysis Based on the Nested Structure Model

Abstract

This study examines the impact of political connections on charitable giving by private enterprises in China in the business environment context. The study constructs a nested structure model and empirically analyzes 1,426 sample enterprises from the 13th China Private Enterprise Survey (2018) data using stata15.1 software. The findings indicate that the business environment influences political connections, charitable giving, and their interaction. Political connections at the individual level of enterprise owners and core managers partly have a positive impact on the charitable giving of Chinese private enterprises. At the enterprise level, the formation of political connections, including the establishment of party organizations, cost-sharing, and receiving government subsidies, also enhances charitable giving. Additionally, certain attributes of private enterprises and entrepreneurs, such as age, year-on-year growth in net profit, and total bank loans, positively influence their charitable giving. However, a high debt-to-asset ratio may adversely affect a company’s charitable giving. These insights are invaluable for local entrepreneurs, authorities, and policymakers in understanding how to effectively conduct charitable giving within specific business and political environments. Academically, this study contributes to the corporate sociology literature by offering new perspectives and data support for future research.

Plain language summary

How Chinese private enterprises’ political connections affect their charitable giving: Insights from the nested structure model

This study looks at how political connections affect how much Chinese private enterprises give to charity. We used a special model and data from a 2018 survey of 1,426 Chinese private enterprises to do this. We found that the business climate can change how enterprises make political connections, give to charity, and how these two things work together. When business owners or their top managers have political connections, it can sometimes make the enterprise more likely to give to charity. Things like having a party organization, sharing costs with the government, or getting money from the government can also make an enterprise more likely to donate. Other important factors that make an enterprise more likely to give are things like how old the enterprises is, how fast its profits are growing, and how much money it has borrowed from the bank. But, owing a lot of money compared to what the company owns might make it less likely to give. This information can help local business people, leaders, and policymakers understand how to give to charity better in certain business and political situations. This study also gives new ideas and information to help with future research.

Keywords

political connection charitable giving Chinese private enterprises business environment nested structure model

Introduction

According to the 2020 China Philanthropy Report, total corporate donations in China in 2019 amounted to RMB 93.134 billion, of which private enterprises donated RMB 47.512 billion, accounting for 51.01% of total donations and an annual increase of 30.77% (Pi, 2020). The increase is significantly higher compared to the RMB 5.427 billion donated in 2009 (Shu, 2009). Why are China’s private enterprises increasingly keen on charitable giving? According to some scholars, private enterprises may donate to charity not only to fulfill social responsibilities, build their reputation and brand, and meet public expectations but also to gain political identities, such as becoming a deputy to the National People’s Congress (NPC) or a member of the Chinese People’s Political Consultative Conference (CPPCC). This allows them to establish political connections with the government and ruling party, and then acquire various utilitarian resources (Gustafsson et al., 2017; W. Yu, 2019). Political connection refers to the various contact mechanisms and channels established between entrepreneurs and government agencies, ruling parties, or officials (Burt & Opper, 2020; Tawiah et al., 2022).

Some research has indicated that the business environment of enterprises influences their political connections (Liu et al., 2018). Well-connected politics facilitates enterprises charitable giving (He & Ma, 2018; Q. Wang, 2023). When we collated the data from the 13th China Private Enterprise Survey released in 2018, we further found that the business environment in China is related to the desire of private enterprises to create political connections, and the business environment can also influence the charitable giving of private enterprises. So how are business environment, political connections, and charitable giving interrelated? This aroused our research interest. Previous research primarily utilized general linear regression and Tobit regression modeling methods to conduct one-line correlation studies on the relationships between the business environment and political connections, as well as between political connections and charitable giving(Peng et al., 2017; B. Zhu & Liu, 2020). These researches did not address the embedded issues between the business environment and political connections, nor have they tackled the endogeneity issues in the mutual influence between political connections and charitable giving in the interaction between the business environment, political connections, and charitable giving. Moreover, they did not explore the complex and multidimensional aspects inherent in the relationships among these variables. This paper aims to use a nested structural model to research the impact of political connections on the charitable giving of Chinese private enterprises in the context of the business environment. Refining this associative mechanism can address the gaps highlighted in previous research and also provide intellectual support on how to more effectively encourage Chinese private enterprises to engage in charitable giving.

Literature Review and Hypotheses Development

Political Connections and Corporate Charitable Giving

Political connection are established based on the interests of enterprise development or social public interests (Burt & Opper, 2020; Tawiah et al., 2022). Some scholars use whether the enterprise owners or core managers serve as deputies to the NPC at all levels, members of the CPPCC, and whether or not a party organization has been set up within the enterprise to measure the political connection of the private enterprises in China (Burt & Opper, 2020; He & Ma, 2018). Other scholars have found that many political connections are invisible and exist in private relationships that are difficult to observe and measure explicitly. For example, entrepreneurs or core managers are former government officials, leaders at all levels of the Federation of Industry and Commerce (FIC) organization, and leaders of other industry associations or chambers of commerce with government background (Fisman & Wang, 2015; Kung & Ma, 2018). However, these factors are not included in the indicator system used to measure political connections.

Corporate charitable giving refers to the behavior of enterprises that, based on fulfilling their basic social responsibilities, donate a certain amount of funds, in-kind goods, or services to those in need (P. X. Wang et al., 2023). Depending on the purpose and motivation, two highly typical scenarios exist in which enterprises engage in charitable giving. One is purely altruistic behavior with no expectation of return, while the other is instrumentally rational behavior to establish good connections with government, society, and consumers to acquire strategic resources such as social prestige and reputational capital (Fanggidae et al., 2023). Most corporate charitable giving behaviors and their motivations fall somewhere in the middle of these two scenarios (Xiong et al., 2023).

Some scholars found that politically connected private enterprises made more charitable giving than non-politically connected enterprises (L. Chen & Chen, 2014; B. Zhu & Liu, 2020). These studies suggest that political connections play a role in promoting charitable giving by Chinese private enterprises. Previous research by other scholars has identified two main situations that constitute political connections: whether the enterprise owner or core managers serve as deputies to the NPC and members of the CPPCC at various levels, and whether a party organization is established within the enterprise. How exactly do these situations impact corporate charitable giving?

On the one hand, in China’s social and political environment, being a deputy to the NPC or a member of the CPPCC not only implies power and honor but also requires taking on more responsibility. Exercising responsibility is essential for retaining authority and gaining respect. Studies have shown that entrepreneurs who are NPC deputies or CPPCC members tend to be more involved in charitable activities, poverty alleviation, environmental protection, and assisting disadvantaged groups (Huang & Zhao, 2016; Zhang et al., 2022). On the other hand, government work and policy development constitute the business environment that affects the survival and development of private enterprises in China. Entrepreneurs who are elected as NPC deputies or CPPCC members can influence government policies that affect their enterprises, leading to a better business environment and improved corporate performance. These enterprises are also inclined to contribute to social and public affairs, engage in charitable giving, and establish stronger political connections with the government (C. Chen, 2019).

The formation of party organizations within Chinese private enterprises constitutes a significant form of political connection. These party organizations promote charitable giving by coordinating relationships among society, government, and employees, and they also contribute to supervision, rights protection, coordination, and guidance (W. Yu, 2019; Zheng & Xie, 2019). Party organizations maintain strong connections with the government and can use their organizational strengths to efficiently convey relevant information about the external environment to private enterprise owners promptly and accurately. This not only aids enterprises in acquiring a variety of valuable information regarding supportive policies and enhancing corporate performance but also assists in mitigating misjudgment of the institutional environment and reducing the expenses associated with adapting to environmental changes. In return, enterprises will also make more charitable giving in response to government and social advocacy (He & Ma, 2016). For example, in situations where difficulties arise during operation and management (such as excessive interference in production by specific government officials), enterprises can convey their needs and address issues via the grassroots party organization. This channel serves as a means of political participation and expression of interests, facilitating direct dialog with higher party committees and the government. In return, enterprises will complete various charitable giving tasks assigned by the grassroots party organization (Cao, 2006).

The above scholars measure the political connections of private enterprises only by whether individuals serve as deputies to the NPC, members of the CPPCC, or by the establishment of a party organization within the enterprise. This does not fully correspond to the reality of political relationships within private enterprises in China (Wei et al., 2023). This study, considering the reality of China, incorporates additional factors into the measurement system for political connections. These include former government officials as the owners or core managers, leading positions in FIC at all levels, serving in industry associations with government affiliations, and government-apportioned expenses and government subsidies. Building on this foundation, the study divides political connections into two types based on the subject of the connection: individual and enterprise levels. The former refers to the political connections established by private enterprise owners or core managers through systems or personal friendships that can serve the interests of the enterprise. The latter refers to various political connections constructed through the formal system of enterprise organization. This not only makes the measurement more comprehensive and in-depth, but also compensates for the shortcomings of previous scholars in this research field. Through this approach, this study can provide a more accurate and comprehensive framework for understanding and analyzing the connection between Chinese private enterprises and the government, thereby further promoting research progress in the field of corporate sociology.

Drawing from the preceding analysis, this study proposes the following research hypotheses:

Hypothesis 1: The individual-level political connections of enterprise owners or core managers can increase the charitable giving of enterprises.

Hypothesis 2: The enterprise-level political connections can improve the level of charitable giving of the enterprise.

The Business Environment and Its Impact on Political Connections and Corporate Charitable Giving

The business environment of enterprises pertains to the diverse factors from outside the enterprises that can offer market opportunities or pose environmental threats to them (Ahmad et al., 2024). Measurements can be conducted using the subjective judgments of entrepreneurs (Li, 2023). Additionally, objective calculations based on the World Bank’s indicator system can be utilized (B. Wang et al., 2023).

Some studies have found that a good business environment can reduce the dependence of private enterprises on political connections. When the business environment is optimized and formal systems are improved, private enterprises will encounter fewer obstacles and uncertainties in their business processes, which reduces their motivation to seek privileges or avoid risks through political connections (G. Yu, 2024; B. Zhu & Liu, 2020). Other studies have found that a good business environment can stimulate private enterprises to participate more in social welfare activities such as charitable giving. Enterprises are more likely to gain social recognition and support in a fair and transparent market environment, thereby becoming more motivated to fulfill their social responsibilities (Affiah et al., 2024; Dienhart, 1988; Peterson et al., 2021). Some studies have also found through political connections, enterprises, and entrepreneurs can gain access to influential decision-makers (Tawiah et al., 2022), assist enterprises in accessing low-cost credit financing, entering high-barrier industries, and gaining protection from imperfect conditions, thus promoting enterprise development (Liu et al., 2018; Peng et al., 2017). Thus they have more ability to carry out charitable giving (He & Ma, 2018; Q. Wang, 2023). Enterprise charitable giving behaviors can also foster new political connections (Bao et al., 2018; J. Zhu et al., 2013).

The findings discussed above address how the business environment of private enterprises influences their political connections and charitable giving behaviors. In practice, political connections and charitable activities mutually reinforce and influence each other, with the business environment playing an important role in shaping the interactions between these two factors (L. Chen & Chen, 2014). The interactions between private enterprise political connections and charitable giving can exhibit endogeneity. These two aspects are areas that previous scholars have not fully explored. To address these issues, this study proposes the following research hypothesis:

Hypothesis 3: The business environment of private enterprises can have an impact on the interaction between political connections and charitable giving.

Characteristics of Private Enterprises and Entrepreneurs and Charitable Giving

Several scholars have found that individual characteristics of private enterprises and entrepreneurs have a positive impact on corporate charitable giving. For example, there is a correlation between the entrepreneur’s age and charitable giving in terms of their accumulated wealth, altruistic personal values, experience, and success (Dhesi, 2010; Yang, 2022). The economic condition of enterprise owners has a significant positive impact on the amount of charitable giving. Enterprise age is also significantly positively correlated with the amount of charitable giving, while the asset-liability ratio is significantly negatively correlated with the amount of charitable giving (H. Chen & Zhang, 2022). Enterprise size and return on assets have a significant positive effect on the amount of corporate charitable giving (Yang, 2022).

These studies basically cover the individual characteristics of entrepreneurs and enterprises, but they ignore the individual signs that are directly related to this study, such as the ratio of enterprises’ net profits to operating revenues, the year-on-year growth rate of net profits, the total amount of bank loans and the ratio of employees participating in social insurance.

Methodology

Data Collection

This study employs a quantitative research method and uses data from the 13th China Private Enterprise Survey released in 2018. The survey was organized by the All-China Federation of Industry and Commerce (ACFIC), the State Administration for Industry and Commerce (SAIC), and the China Society for Private Economic Research (CSPER). It was specifically aimed at private enterprises and encompassed all 31 provincial administrative units in China, excluding Hong Kong, Macao, and Taiwan.

The sampling method employed in the 13th China Private Enterprise Survey is a multistage sampling approach. Firstly, the total number of samples and the number of individuals to be sampled in each province, municipality, and autonomous region are determined. Secondly, within each province, municipality, and autonomous region, one planned separately administered city or provincial capital, one prefecture-level city, and one county-level city, as well as one county with high, medium, and low levels of economic development, are selected, totaling six cities and counties. Thirdly, the number of urban and rural individuals to be surveyed is determined according to the urban-rural ratio. For each selected sample enterprise, researchers conduct structured interviews with business owners or managers based on questionnaires to collect information about the enterprises and their owners.

The questionnaire used in the 13th China Private Enterprise Survey provides a detailed investigation of the current situation of Chinese private enterprises and specifically examines the common issues faced by them. The questionnaire consists of five sections. The first section (questions 1–9) focuses on “Main investor and contributors of the enterprise,” the second section (questions 10–24) focuses on “Enterprise situation,” the third section (questions 25–29) focuses on “Governance structure and social relations,” the fourth section (questions 30–38) focuses on “Transformation and upgrading, and social responsibility,” and the fifth section (questions 39–45) focuses on “Business environment.” There are a total of 45 questions. The first section, “Main contributors of the enterprise,” focuses on the political connections and self-assessed social status of the enterprise owner. The second section, “Enterprise situation,” examines aspects such as family shareholding in the enterprise, employment, financing, various costs, and outstanding accounts receivable. The third section, “Governance structure and social relations,” focuses on the establishment of party organizations within enterprises and the experiences of enterprise owners before starting their businesses. The fourth section, “Transformation and upgrading, and social responsibility,” focuses on aspects such as research and development within the enterprise, penalties imposed, and charitable donations. The fifth section, “Business environment,” inquiries the enterprise’s assessment of current intellectual property protection, administrative approval, administrative law enforcement, economic disputes, judicial litigation, and future social risks.

A total of 3,973 private enterprises were included in the survey. Some enterprises may find it difficult to answer certain questions due to unclear accounting records, or they may refuse to answer certain questions due to concerns about disclosing proprietary information. Structured interviews based on the questionnaire have inherent limitations and cannot compensate for missing or refused responses, leading to significant sample missingness in the database. After testing that all kinds of missing value filling methods will cause more serious bias, this paper chooses to delete the missing values, and the final valid samples total 1,426.

Variables

Dependent Variable

The study’s dependent variable is the amount of charitable giving from private enterprises. Choose option fill-in-the-blank item F in question 19 of the questionnaire titled “How much did your enterprise donate to charity and society in 2017?” Take the logarithm of the continuous variable “amount of charitable giving” + 1.

Independent Variable

The independent variable in this study is corporate political connections. Referring to the existing studies (Burt & Opper, 2020; Tawiah et al., 2022; Wei et al., 2023), Political connections are assessed using two interconnected variables, both at the individual and corporate levels.

Political connections at the individual level of enterprise owners or core managers primarily encompass four main scenarios. First, we created a dichotomous dummy variable named “NPC or CPPCC” by summing up item A of question 7 in the questionnaire, a fill-in-the-blank question “Are you a current NPC deputy?” and item B, another fill-in-the-blank question “Are you a current CPPCC member?.” A value of 0 indicates that the individual is not an NPC deputy or CPPCC member, while a value of 1 means current membership in either the NPC or CPPCC. The reason for using the summation method to construct the dichotomous dummy variable is that both are the most direct and typical political connections. According to system regulations, NPC deputies or CPPCC members are generally prohibited from holding concurrent positions.

Second, drawing from question 8, item B, a single-choice question “At which level of the FIC do you hold a position?,” another dichotomous dummy variable, referred to as “Federation of Industry and Commerce,” was formulated. The options for question 8 range from 1 to 4, representing county/district, prefecture-level city, province, and national levels respectively, while option 5 indicates “not holding a position.” If the respondent selects option 5, it is assigned a value of 0, indicating not holding a position in the Federation of Industry and Commerce. If the respondent selects options 1 to 4, it is assigned a value of 1, indicating holding a position in the FIC. Given that holding a position within the FIC often involves a higher degree of government association, this study also treats it as a political connection.

Third, the dichotomous dummy variable “government association” is generated from item D in question 8, a multiple-choice question “Have you joined other trade associations or chambers of commerce with a government background?” Option 4 “Have you joined other industry associations or chambers of commerce with a government background.” If the respondent does not select option 4, it is assigned a value of 0, indicating not joining any industry associations or chambers of commerce with a government background. If the respondent selects option 4, it is assigned a value of 1, indicating joining industry associations or chambers of commerce with a government background.

Fourth, the dichotomous variable “government work experience” is created based on item A of question 28, Question 28 “Have you worked in a party or government organization or institution before initiating your business?” is a multiple-choice question, with option A “Worked in government agencies or public institutions,” option B “Worked in state-owned enterprises or collective enterprises,” option C “Worked in foreign-funded, Hong Kong, Macao, or Taiwan-funded enterprises,” option D “Worked in private enterprises,” and option E “Worked in rural areas.” If the respondent selects option A, it is assigned a value of 1, indicating no prior experience in a party or government organization or institution. If the respondent does not select option A, it is assigned a value of 0, indicating prior experience in such an entity.

Political connections at the corporate level mainly include three situations. First, we constructed a dichotomous dummy variable for “party organization” based on question 25. Question 25 “Which of the following organizations exist in your company?” is a multiple-choice question, with options 1 to 11 respectively as Shareholders’ Meeting, Board of Directors, Board of Supervisors, Communist Party of Chinese Communist Party (CCP) organization, Labor Union, Workers’ Congress, Family Office or similar institution, Communist Youth League organization, Legal Department, Department or personnel dedicated to handling government relations, Human Resources Department, or personnel. If the respondent does not select option 4 “Communist Party of China (CPC) organization,” it is assigned a value of 0, indicating the absence of a party organization. If the respondent selects option 4, it is assigned a value of 1, indicating the presence of such an organization.

Second, referring to question 19, item D of the questionnaire, a fill-in-blank question “What was the total amount of apportion expenses by your enterprise in 2017?” Take the logarithm of the continuous variable “apportion expenses” + 1.

Third, using item G in question 19, a fill-in bank question “What was the total amount of various government subsidies received by your enterprise in 2017?” Take the logarithm of the continuous variable “government subsidies” + 1. This is a government-initiated political connection.

Stratified Variables and Control Variables

Based on item L of question 41, question 41 is a scale question, “In the past year, how do you perceive the improvement of the following situations?” where option L is “In the past year, how do you perceive the overall business environment?” Options 1 to 6 are “Significant improvement,”“More improvement,”“General,”“Little improvement,”“No improvement at all,” and “No experience, don’t know,” respectively. Option 6 is removed, and options 1 to 5 are used for stratification.

Referring to the existing literature (H. Chen & Zhang, 2022; Dhesi, 2010; Yang, 2022), the control variables in this study include the following variables. Entrepreneur age, derived from question 3, a fill-in-blank question “What year were you born?” Enterprise age, derived from question 20, item B, a fill-in-blank question “In which year was your current enterprise registered?” The ratio of net profit to operating revenues, derived from question 20, item A, a fill-in-blank question “What was the net profit of your company in 2017?” and question 19, item A, a fill-in-blank question “What was the main operating revenue of your company in 2017?,” calculated by dividing net profit by main operating revenue. Year-on-year net profit growth, derived from question 20, item B, a single-choice question “How did the net profit of your company change year-on-year in 2017?,” options 1 to 3 are “Increased,”“ Flat,” and “ Decline.” Asset-liability ratio, derived from question 21, item A, a fill-in-blank question “What was the Asset-liability ratio of your enterprise at the end of 2017?” Total bank loans, derived from question 18, item C, a fill-in-blank question “What was the total bank loans of your enterprise from state-owned and joint-stock commercial banks at the end of 2017?,” with a natural log transformation applied after adding one to the variable. Employee participation rate in social insurance, derived from question 17, item B, a fill-in-blank question “How many employees were covered by social insurance in your enterprise in 2017?” and question 15, item A, a fill-in-blank question “How many employees were hired by your enterprise in the whole year of 2017?,” calculated by dividing the number of employees covered by social insurance by the total number of hired employees. This variable is used to measure the company’s compliance with legal obligations. The measurement of control variables and stratification variables are detailed in Table 1.

Table 1.

Measurement of Variables and Descriptive Statistics (n = 1,426).

Categorical variables	Definition	Frequency		Percentage (%)
NPC and CPPCC	0 = Not in office	756		53.02
NPC and CPPCC	1 = Be in office	670		46.98
FIC	0 = Not in office	270		18.93
FIC	1 = Be in office	1,156		81.07
Government background associations	0 = Not joined	697		48.88
Government background associations	1 = Joined	729		51.12
Government work experience	0 = No	1,162		81.49
Government work experience	1 = Yes	264		18.51
CCP organization	0 = non-established	624		43.76
CCP organization	1 = Established	802		56.24
Year-on-year growth in net profit	1 = Decline	410		28.75
	2 = Flat	355		24.89
	3 = Increase	661		46.35
Business environment	1 = Significant improvement	212		14.87
	2 = More improvement	717		50.28
	3 = General	361		25.32
	4 = Little improvement	105		7.36
	5 = No improvement at all	31		2.17
Continuous variables	Definition	Mean value	Standard deviation	Minimum value	Maximum value
Charitable giving	Ln (Amount of charitable giving + 1)	1.565	1.536	0	9.904
Government-apportioned	Ln (Amount of government-apportioned + 1)	0.545	1.221	0	8.215
Government subsidy	Ln (Amount of government subsidies + 1)	1.628	2.200	0	10.050
Entrepreneur age	Age of entrepreneur or manager	47.748	8.725	23.000	76.000
Enterprise age	Enterprise age	13.994	7.402	0	63.000
The ratio of net profit to operating revenues	net profit/Main operating income	0.050	0.455	−5.000	1.000
Asset-liability ratio	Enterprise’s 2017 asset-liability ratio	0.347	0.291	0	2.9
Total bank loans	Ln(Total loans of state-owned and joint-stock commercial banks+)	3.796	3.911	0	13.424
Employee participation rate in social insurance	The number of employees whose social insurance is paid by the enterprise /Total employees	0.652	0.348	0	1.000

Research Model

As mentioned above, the business environment and political connections of private enterprises in this study interact with each other and jointly affect the charitable giving of enterprises. Nested structure models, also known as hierarchical models, assume that data exhibit a hierarchical structure, where individual observations are grouped into different levels, with each level corresponding to a specific grouping of the data, and the model is used to describe the relationships between these different levels. The term “levels” essentially represents aggregated information about the background or characteristics of the studied population. By using nested structure models, it’s possible to reduce estimation bias caused by within-group correlations, examine whether the relationship between independent and dependent variables holds across all levels, and assess the impact of the delineated levels on the relationship between independent and dependent variables. In order to study the relationship and mechanism, this paper regards the data of corporate political connections and charitable giving as nested structural data and analyzes them using a nested structure model. The specific approach is as follows:

The nested data was initially organized based on the categorization of the business environment. The dependent variable, charitable giving, underwent a one-way analysis of variance (ANOVA) with random effects. The analysis yielded an Intra-group Correlation Coefficient (ICC) exceeding 0 and passed the likelihood ratio test at the .05 significance level. The ICC quantifies the proportion of total variation attributed to differences between high-level measurement units, encompassing both between-group disparities and within-group correlations among individuals. The outcomes from the one-way ANOVA with random effects suggest that the data satisfy the fundamental prerequisites for a nested structure model. Given that the data doesn’t support creating covariates to characterize distinct layers of the business environment, this study employs a one-way covariance analysis with random effects as detailed below:

Layer 1 model:

Y_{ij} = β_{0 j} + β_{1} X_{ij} + r_{ij}

(1)

Subscript j represents the upper group unit, implying different levels of the business environment. The subscript i stands for individuals, implying enterprises. X_ij stands for independent variables and control variables. r_ij stands for random errors for a particular enterprise.

Layer 2 model:

β_{0 j} = r_{00} + u_{0 j}

(2)

β_{1 j} = r_{10}

(3)

r₀₀ represents total average charitable giving. u_0j represents the random error term under different business environment strata. r₁₀ represents the general effect of enterprise characteristics. (2) is calculated as the intercept of (1), and (3) is calculated as the slope of (1).

In practice, the above steps are carried out using Maximum Likelihood Estimation (MLE) and the combined model is:

Y_{ij} = r_{00} + r_{10} X_{ij} + u_{0 j} + r_{ij}

(4)

Since a one-way ANOVA with random effects may not be able to calculate the difference between the variables. Table 2 is plotted to show the characteristics of the dependent and independent variables in the different strata.

Table 2.

Characteristics of Dependent and Independent Variables in Different Business Environments.

Business environment stratification	Significant improvement	More improvement	General	Little improvement	No improvement at all
Mean value of charitable giving	1.588	1.686	1.342	1.545	1.266
Percentage serving in NPC/CPPCC (%)	51.4	47.6	43.5	46.7	45.2
Percentage of positions in the FIC (%)	83.5	79.1	82.8	83.8	80.6
Percentage of membership in associations with a governmental background (%)	52.8	50.6	49.6	60.0	38.7
Percentage with government experience (%)	19.3	17.9	18.6	21.9	16.1
Mean apportioned expenses	0.422	0.540	0.460	1.047	0.812
Mean value of government subsidies	1.716	1.705	1.451	1.629	1.304

As indicated in Table 2, it is evident that a more pronounced enhancement in the business environment corresponds to greater charitable giving. The mean value fluctuates between 1.266 and 1.588. Additionally, a higher proportion of individuals serving in the NPC or the CPPCC is observed, with the proportion ranging from 45.2% to 51.4%. Conversely, a decrease in allocated expenses is evident, with the mean value fluctuating between 0.812 and 0.422. Furthermore, a higher mean value of government subsidies is noted, ranging from 1.304 to 1.716. Holding a position in the FIC, joining government background associations, and having government work experience do not show relatively consistent change characteristics. In addition, this study builds a Tobit model based on all variables for control.

Traditionally, studies on the political connections and charitable donations of Chinese private enterprises have primarily utilized Tobit models or examined mediating and moderating effects, either by directly incorporating the business environment or similar variables into Tobit models or by setting them as mediators or moderators. The mediating effect refers to the pathway through which the independent variable of political connections affects the dependent variable of charitable donations via the mediating variable of the business environment. The moderating effect involves how the moderating variable of the business environment changes the degree or direction of the relationship between the independent variable of political connections and the dependent variable of charitable giving. Traditional methods encounter challenges in understanding the interaction between political connections and the business environment and the exact nature of their relationship. This study employs nested structure models, treating enterprises as existing within specific business environments. The business environment serves as the backdrop for enterprise existence, imparting corresponding characteristics to the enterprise. Within this specific business environment, the study explores how political connections influence charitable donations. In simpler terms, the business environment is the soil in which enterprises thrive, shaping the relationship between the independent variable of political connections and the dependent variable of charitable donations.

As can be seen from the above, this research method creatively addresses the shortcomings of previous scholars’ studies (Huang & Zhao, 2016; Wei et al., 2023; Zhang et al., 2022). It mitigates the issue of interaction between the business environment and political connections. It also better reflects the reality of political connections in Chinese private enterprises, namely that private enterprises exist within specific business environments and operate within those environments. This approach encompasses not only the diverse array of political connections in practice but also solves the problem of interplaying between the political connections and the business environment in influencing the process of charitable giving. This promotes the development of the discipline of corporate sociology and contributes to the accumulation of new knowledge.

Results

Political Connections and Corporate Charitable Giving in the Context of the Business Environment

The results of the regression of political connections and corporate charitable giving are shown in Table 3. Model 1 shows the regression results of the Tobit model and Model 2 shows the regression results of the nested structure model. In Model 2, the ICC is greater than 0, which passes the likelihood ratio test at the 0.1 level and satisfies the basic conditions for the use of the nested structure model.

Table 3.

Political Connections and Charitable Giving by Private Enterprises (n = 1,426).

	Model 1Tobit	Model 2Nested structure
Served in NPC/CPPCC (non-represented for reference)	0.582*** (0.102)	0.413*** (0.076)
Served in FIC (non-represented as reference)	0.439*** (0.134)	0.273*** (0.097)
Membership in governmental background associations (non-membership as reference)	0.199** (0.099)	0.132* (0.074)
Have government work experience (no work experience as reference)	0.036 (0.125)	0.027 (0.094)
Establishment of party organizations (no party organization established as reference)	0.422*** (0.107)	0.294*** (0.079)
Government-apportioned expenses	0.365*** (0.039)	0.289*** (0.030)
Government subsidies	0.126*** (0.025)	0.108*** (0.018)
Entrepreneur age	0.011* (0.006)	0.009** (0.004)
Enterprise age	0.017** (0.007)	0.015*** (0.005)
The ratio of net profit to operating revenues	0.124 (1.110)	0.040 (0.080)
Year-on-year increase in net profit (decrease as reference)
Flat	0.408*** (0.134)	0.348*** (0.010)
Increases	0.410*** (0.118)	0.382*** (0.087)
Asset-liability ratio	−0.883*** (0.185)	−0.653*** (0.135)
Total bank loans	0.067*** (0.014)	0.051*** (0.011)
Employee participation rate in social insurance	−0.337** (0.141)	−0.162 (0.105)
Business environment (significant improvement as a reference)		Lamination
More improvement	0.159 (0.143)
General	−0.098 (0.159)
Little improvement	−0.078 (0.220)
No improvement at all	−0.324 (0.355)
Constant	−0.998*** (0.336)	−0.233 (0.235)
R²	0.068
X²	344.71***	352.12***

Note. Layer 2 in Model 2 has no characteristic variables to calculate R².

***

p < .01, **p < .05, *p < .1.

According to Table 3, the Tobit model has higher regression coefficients than any of the nested models. This indicates that the effect of different components of political connections on charitable giving is overestimated in the Tobit model, and this effect decreases after nesting the variable of the business environment. Considering the relationship between political connections and the business environment as shown in Table 2, This validates research hypothesis 3.

Based on Model 2 in Table 3, within different business environments, enterprise owners serving as a deputy to the NPC or a member of the CPPCC (β = .413, p < .01), serving in the FIC (β = .273, p < .01), and joining associations with governmental backgrounds (β = .132, p < .05) positively affect enterprise charitable giving. These validate hypothesis 1. In various business environments, the experience of enterprise owners who have served in the government department before the establishment of a private enterprise does not significantly affect charitable giving, thereby refuting hypothesis 1. This implies that the personal-level political connections of enterprise owners or core managers partially influence their charitable giving outcomes. Moreover, enterprise owners who serve as deputies to the NPC or members of the CPPCC, hold positions within the FIC and participate in associations with governmental backgrounds can all contribute to enhancing the charitable giving behavior of their enterprises.

According to Model 2 as presented in Table 3, concerning enterprise-level political connections, the presence of a party organization within an enterprise (β = .294, p < .01), the extent of apportioned expenses (β = .289, p < .01), and the magnitude of governmental subsidies (β = .108, p < .01) all exert a significant and positive influence on charitable giving in different business environments. These validate hypothesis 2.2.

In summary, all variables related to political connections within private enterprises, except for the owner’s prior experience in a government department before establishing a private enterprise, have a significant impact on increasing their charitable giving behavior or amount. The relationship between political connections and charitable giving remains significant even when accounting for various business environments, but the amount of charitable giving increased by political connections is lower than before.

Control Variables and Charitable Giving

According to Model 1 (Tobit) in Table 3, the age of an entrepreneur has a positive impact on their charitable giving. When entrepreneurs get older, their corporate charitable giving tends to increase. After nesting the business environment, we found that the level of significance increased from 0.1 to 0.05. However, the regression coefficient decreased from 0.011 to 0.009. This means that the likelihood of entrepreneur age affecting charitable giving increased, but the degree of influence decreased. This suggests that the business environment also plays a role in this process. This also occurs for all the other control variables in the later section.

The longer the enterprise has been in existence, the greater its charitable giving. After nesting the business environment, the significant level rises from 0.05 to 0.01. However, the regression coefficient drops from 0.017 to 0.015. This means that the likelihood of the enterprise’s impact on charitable giving increases, but to a lesser degree.

The ratio of enterprise net profit to operating revenues has no significant effect on charitable giving. However, the year-on-year increase in enterprise net profit (p < .01) significantly and positively affects charitable giving. The data show that a flat or higher net profit compared to previous years can increase charitable giving. After nesting the business environment, the year-on-year change in net profit affects charitable giving to a lesser extent.

According to Model 1 (Tobit) in Table 3, the enterprise asset-liability ratio (β = −.883, p < .01) significantly and negatively affects charitable giving. As the enterprise asset-liability ratio increases, charitable giving tends to decrease. After nesting the business environment, the regression coefficient increases from −0.883 to −0.653, and the degree of the negative impact of the asset-liability ratio on charitable giving decreases.

Based on Model 1 (Tobit) as presented in Table 3, charitable giving by enterprises tends to increase with higher total bank loans. After nesting the business environment, the regression coefficient decreases from 0.067 to 0.051, resulting in a diminished impact of total bank loans on charitable giving.

Within the Tobit model, an elevated rate of employee participation in social insurance corresponds to a reduction in charitable giving by the enterprise. The nested structure model dismisses this unfounded correlation, which shows that the influence factors and the degree of influence of the enterprise’s charitable giving are more realistically presented after fully considering the business environment.

Based on the above analysis, it can be seen that all control variables, except for the ratio of net profit to operating income, have an impact on the amount of charitable giving by enterprises. This suggests that private enterprise and entrepreneurial characteristics affect the level of charitable giving.

According to Table 3, the regression coefficients of the Tobit model are higher than those of the nested model for all control variables, which suggests that the effect of the control variables on the charitable giving of enterprises decreases after nesting the variable of the business environment. This further validates the hypothesis 3.

Robustness Test

In order to test the robustness of our analysis, we transformed the dependent variable, “charitable giving,” into a categorical variable. This transformation assigned a value of 0 to indicate “no giving” and a value of 1 to indicate “giving.” We then performed a regression analysis using the Logit model.

Furthermore, to evaluate the relationship between enterprise size and political connections with charitable giving, The net assets variable contains many missing values. After eliminating observations with missing values, a total of 903 samples for the enterprise-size dataset were obtained. All 903 new samples were included in the master sample of 1,426. Based on the mean value of enterprise size, 516 samples were categorized as “relatively small enterprises” (for observations with a size less than or equal to the mean) and 387 samples as “relatively large enterprises” (for observations with a size greater than the mean). The Tobit model was employed to examine the influence of political connections on charitable giving in both small and large enterprises.

According to Table 4, in Model 3, although the significance of control variables is different from the previous, independent variables show a consistent effect on charitable giving. Entrepreneurs serving as NPC/CPPCC members, serving in the FIC, membership in governmental background associations, party organizations established in the enterprise, government apportionment and government subsidies significantly increase charitable giving, and government work experience does not have a significant effect on charitable giving.

Table 4.

Robustness Test.

	Model 3Logit	Model 4Relatively small size enterprises	Model 5Relatively large size enterprises
Served in NPC/CPPCC (non-represented for reference)	0.117*** (0.024)	0.563*** (0.154)	0.553*** (0.211)
Served in FIC (non-represented as reference)	0.080** (0.031)	0.102 (0.189)	0.741** (0.293)
Membership in governmental background associations (non-membership as reference)	0.043* (0.023)	0.350** (0.146)	−0.038 (0.214)
Have government work experience (no work experience as reference)	−0.003 (0.030)	0.027 (0.203)	0.259 (0.244)
Establishment of party organizations (no party organization established as reference)	0.084*** (0.025)	0.280* (0.153)	0.420* (0.245)
Government-apportioned expenses	0.092*** (0.018)	0.407*** (0.069)	0.276*** (0.071)
Government subsidies	0.010* (0.006)	0.075 (0.037)	0.119*** (0.043)
Entrepreneur age	0.001 (0.001)	0.001 (0.009)	0.012 (0.013)
Enterprise age	0.001 (0.002)	0.017 (0.011)	0.012 (0.015)
The ratio of net profit to operating revenues	0.056** (0.024)	0.299 (0.220)	0.037 (0.244)
Year-on-year increase in net profit (decrease as reference)
Flat	0.042 (0.031)	0.438** (0.191)	0.998*** (0.328)
Increases	0.013 (0.028)	0.215 (0.178)	0.677*** (0.244)
Asset-liability ratio	−0.130*** (0.045)	−0.197 (0.280)	−0.648 (0.541)
Total bank loans	0.011*** (0.003)	0.024 (0.021)	0.108*** (0.030)
Employee participation rate in social insurance	−0.101*** (0.033)	−0.260 (0.207)	−0.105 (0.321)
Business environment (significant improvement as a reference)
More improvement	0.038 (0.034)	0.143 (0.211)	0.334 (0.309)
General	0.034 (0.037)	−0.121 (0.231)	−0.273 (0.355)
Little improvement	0.008 (0.056)	−0.161 (0.314)	0.063 (0.466)
No improvement at all	−0.007 (0.088)	0.556 (0.535)	−0.588 (0.697)
Constant	−0.321 (0.418)	−0.427 (0.528)	−1.763** (0.745)
R²	0.107	0.060	0.065
X²	125.60	99.63	94.92
N	1,426	516	387

Note. The coefficients in Model 2 represent marginal effects, with robust standard errors in parentheses.

***

p < .01, **p < .05, *p < .1.

According to Table 4, in Models 4 and 5, relatively small size and relatively large size enterprises show some differences in independent variables. Small enterprise owners serving in the FIC has no significant effect on charitable giving, while membership in governmental background associations significantly increases charitable giving. The opposite is true for large enterprise owners, where serving in the FIC significantly increases charitable giving, and membership in governmental background associations has no significant effect. This may be due to the fact that small enterprise owners have limited opportunities to serve in the FIC, while large enterprise owners have more opportunities to participate in higher arenas.

Overall, the model presents robustness.

Discussion

The authors proposed three hypotheses for this study, namely:

Hypothesis 1: The individual-level political connections of enterprise owners or core managers can increase the charitable giving of enterprises.

Hypothesis 2: The enterprise-level political connections can improve the level of charitable giving of the enterprise.

Hypothesis 3: The business environment of private enterprises can have an impact on the interaction between political connections and charitable giving.

Hypothesis 1 has been partially validated. The political connections established at the individual level by enterprise owners or core managers have partially increased the enterprise’s charitable giving. The political connections variables, such as enterprise owners serving as delegates to the NPC or members of the CPPCC, holding positions in FIC, and joining associations with governmental backgrounds, all have a positive impact on enterprise charitable giving. These connections actively contribute to increasing the amount of charitable giving made by enterprises. The experience of private enterprise owners who held positions in government departments before founding their businesses does not have a significant impact on charitable giving. The positive effects of serving as a delegate to the NPC or a member of the CPPCC on charitable giving confirm previous perspectives. Holding positions in the FIC and joining associations with a governmental background has a positive impact on charitable giving, which expanded the previous research field. Hypothesis 2 has been validated. Political connections at the enterprise level, such as the establishment of party organizations within the enterprise, government-apportioned expenses, and government subsidies, all contribute to an increase in the volume of Chinese private enterprise charitable giving.

Theoretically, the above research findings offer a more comprehensive and in-depth measurement of political connections, addressing the previously noted inadequacies in the measurement system of political connections within this field of study (L. Chen & Chen, 2014; Huang & Zhao, 2016; Zhang et al., 2022; B. Zhu & Liu, 2020). From a practical application perspective, these two research findings demonstrate that Chinese private enterprises can establish various political connections through different means at both the individual and enterprise levels, thereby influencing charitable giving, which expands the research scope established by previous scholars. Additionally, they provide a more realistic theoretical framework and standard system for Chinese private enterprises to engage in charitable giving.

Hypothesis 3 has been validated. The business environment of private enterprises can impact the interaction between political connections and charitable giving. This study embedded political connections and charitable giving within the business environment and established a nested model. This approach addresses the limitations found in the unidimensional impact analysis between the business environment, political connections, and charitable giving behaviors in studies by (C. Chen, 2019; W. Yu, 2019; Zheng & Xie, 2019). It resolves the issues of interrelation and endogeneity caused by the mutual influence of political connections and charitable giving under the business environment context, making the research outcomes more aligned with reality. This approach represents an innovative and exploratory step in research methodology, driving the advancement of corporate sociology theory within the discipline.

Certain characteristics of private enterprises and entrepreneurs, such as the age of the entrepreneur, the duration of the enterprise’s existence, the year-on-year net profit growth, and the total amount of bank loans, have a positive impact on enterprise charitable giving. Conversely, the asset-liability ratio has a negative impact on charitable giving. Regarding the characteristics of private enterprises and entrepreneurs, which serve as control variables in this study. The ratio of net profit to operating revenues, the year-on-year growth rate of net profit, the total bank loans, and the ratio of employee participation in social insurance have been incorporated. These additions to the measurement index system are built upon prior research by scholars, aiming to address the limitations observed in the works of (H. Chen & Zhang, 2022; Dhesi, 2010; Yang, 2022), and other researchers. These research findings address shortcomings in previous studies.

Conclusion

Enterprises always operate within specific business environments, and the impact of the political connections of Chinese private enterprises on charitable giving is no exception. Researching the mechanisms that link the business environment, political connections, and charitable giving is a challenging task. Nested structural modeling is an effective approach to tackle this complexity. It addresses the issue of the interplay between political connections and the business environment in influencing charitable giving, as well as the endogeneity problems that arise during these interactions. This approach enables researchers to draw conclusions that more accurately reflect the actual dynamics of the situation.

The business environment affects both political connections and charitable giving, as well as their interaction. Moreover, strong political connections can improve the business environment for private enterprises by providing access to various social and governmental resources, thereby enhancing the enterprise’s performance and enabling enterprises to engage in more charitable giving. Conversely, an increase in charitable giving can also improve the business environment for private enterprises, leading to enhanced enterprise performance. This partly answers the two questions raised at the beginning of this study: why are Chinese private enterprises becoming more and more enthusiastic about charitable giving? What is the relationship between the business environment of private enterprises, their political connections, and charitable giving?

In the context of the business environment, the establishment of certain political connections at the individual level by owners or core managers has a positive impact on the charitable giving of Chinese private enterprises. These connections include serving as deputies to the NPC or members of the CPPCC, holding positions in the FIC, and joining associations with a government background. In practice, these political ties are highly valuable relational resources for Chinese private enterprises, enabling them to secure various beneficial protections and resources for development. Consequently, private enterprises that establish these political connections are more capable and inclined to engage in charitable giving.

In the context of the business environment, the establishment of political connections at the enterprise level, including the formation of party organizations, government-apportioned expenses, and government subsidies, also positively impacts the charitable giving of private enterprises. The establishment of internal party organizations within enterprises aids in accessing various advantageous information and policy support. Enterprises need to respond to government advocacy by increasing charitable giving. When national or local disasters occur, governments at various levels may actively advocate or require enterprises to share costs. Governments may promise support for future development in formal or informal ways, thereby establishing political connections between enterprises and the government. When advocacy or demands are issued, charitable giving inevitably increases. When private enterprises receive government subsidies, they may initiate charitable giving, either actively or passively, to respond to the corresponding support.

Certain characteristics of private enterprises and entrepreneurs, such as the age of the enterprise and entrepreneur, year-on-year net profit growth, and the total amount of bank loans, have a positive impact on charitable giving, especially when the enterprise is performing well and profitability is increasing. However, a high asset-liability ratio may have a negative impact on the charitable giving of an enterprise. Older enterprises and entrepreneurs, with greater economic strength and a sense of social responsibility, tend to have a greater capacity and willingness to engage in charitable giving. An increase in net profit suggests that an enterprise may have surplus resources available for charitable giving. Private enterprises may also be motivated to enhance their reputation and creditworthiness to secure larger bank loans, which could indirectly encourage them to participate in charitable giving. When the asset-liability ratio is high, enterprises may need to prioritize debt repayment, which could limit their ability to contribute to charitable giving.

Thus, the nested structural model plays a crucial role in exploring the relationship between political connections and charitable giving of Chinese private enterprises within the context of the business environment. By examining how variables such as the business environment, political connections, and charitable giving intertwine, this model provides an effective analytical tool and methodological framework. It helps us gain a deeper understanding of this complex social phenomenon, illustrating how political connections influence charitable giving.

Limitations and Further Research

While this study has achieved certain advancements, it also bears certain limitations. First, due to inherent data constraints, this study fails to measure the full breadth and depth of political connections. In China’s societal context, the strength and effect of political connections at different levels of government on the impact of private enterprises’ charitable giving will be different. Second, the study omits an analysis of the distinctive instrumental rationality behind private enterprises establishing political connections. For instance, some private enterprises’ charitable giving is affected by financing constraints and agency costs. Enterprises with pronounced financial limitations may rely on charitable giving to secure external resources, while enterprises with higher agency costs may experience excessive donations by senior executives for their private interests (T. Wang & Chen, 2016). These are aspects outside the scope of this study. In addition, political connections can also raise concerns about corruption, favoritism, and unequal access to political influence that can undermine the overall business environment. Scholars have argued that political connections can allow privileged access and undue influence over policy decisions, undermining transparency, accountability, and democratic processes (Boland, 2020). Data reflecting these aspects of the problem were unable to be found, nor were corresponding hypotheses about their resolution able to be formulated. Finally, the findings of this study are only appropriate for the Chinese context and cannot be generalized to other countries.

Future research must transcend the present limitations, broadening the scope and depth of exploration into political connections. Additionally, careful consideration should be given to the instrumental rationality guiding enterprises’ pursuit of political connections. These endeavors are crucial for advancing the investigation into the mechanisms and fundamental principles governing the impact of political connections on charitable giving made by private enterprises in China.

Footnotes

Acknowledgements

We thank the editor, three anonymous reviewers of the journal for helpful comments and suggestions on earlier drafts of this paper. We are grateful to our colleagues and peers for their thoughtful discussions, feedback, and collaboration, which have enhanced the depth and breadth of our research. Furthermore, we acknowledge the financial support provided by the Planning Fund of the Ministry of Education of the People’s Republic of China (19YJA840016).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Planning Fund of the Ministry of Education of the People’s Republic of China (19YJA840016).

An Ethics Statement (including the committee approval number) for animal and human studies. If this is not applicable,please state this instead.

This study does not involve animal or human research. The researchers are committed to maintaining the highest ethical standards throughout the research process and ensuring the confidentiality, safety, and well-being of all participants.

ORCID iD

Jichao Wang

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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