Predicting Efficiency of Innovative Disaster Response Practices: Case Study of China’s Corporate Philanthropy

Abstract

Corporate philanthropy is significant because gifts are viewed as a means to enhance the image of a business organization in an era of intense competition. Taking into account the corporations listed on the Shenzhen stock exchanges, this research reveals that environmentally unfriendly enterprises have been exhibiting more altruistic behavior to counterbalance the negative image that has resulted from their massive emission of pollutants. In addition, a review of innovation, idle resources, and directors’ salaries indicated a substantial positive correlation. It is not required that a company be profitable for it to engage in philanthropy; rather, it should have an abundance of excess resources to donate. We also show that corporate philanthropy produces value for a company during a natural disaster and increases the company’s goodwill during times of humanitarian need.

1. Introduction

Practitioners and academics are concerned with how corporate philanthropy (CP) influences corporate image. Investors are also interested in observing value creation through CP after natural disasters and the significance of environmental aspects in CP practices. According to [1] corporate social responsibility (CSR), the contribution to reducing the danger of a stock market crash in the United States is significant. State-owned enterprise (SOE) dominance is one of the most noteworthy characteristics of the Chinese stock market. According to 2018 figures, 60 percent of all publicly traded enterprises in China are still SOEs. Extreme state ownership may improve or diminish the impact of minimizing the risk of accidents and CP. SOEs experienced a range of preferential treatment from the government compared to non-SOEs due to their close ties to the administration [2,3]. There were market responses, resulting in the dissemination of unfavorable news about investors who are less attentive and exhibit poor incentives. SOEs may be less beneficial to CP’s role in lowering collision risk. The more severe agency of SOEs in conflicts and SOEs that are subject to corporate governance mechanisms [4,5,6] in private enterprises were shown to be less successful in the management of bad news for the board. According to [7,8,9], Chinese businesses utilize charity contributions for rent seeking more often than businesses in other nations. Corporate participation in charitable organizations and activities sanctioned by the government is a highly accommodating conduit since firms obtain ethical authenticity while the government deems their conduct to be acceptable. After the 2008 Wenchuan earthquake, the government urged corporations to contribute to disaster relief, which supports this idea. The corporate philanthropic disaster response (CPDR) enabled corporations to foster a positive connection with the government, which resulted in the development of favorable policies. Similar to lobbying, the political motivations behind this type of gift result in the government favoring corporations.

A few experiments support our conclusion that CPDR is not synonymous with charity. In [10], the authors obtained data on donations from North American, European, and Asian Global Fortune 500 companies associated with the South Asian tsunami, Hurricane Katrina, and the Kashmiri earthquake. Their results revealed between-province differences in the overall probability of donations and their monetary values, providing evidence of a home-district effect on CPDR, whereby enterprises evaluated disasters that were close to home or in nearby regions. According to an analysis of the financial motivation for corporate contributions that examined Chinese enterprises’ responses to the Wenchuan earthquake [11], organizations with items specifically connected with buyers’ day-to-day lives gave, on average, 50 percent more than other firms. Considering the corporate response to Hurricane Katrina, [12] investigated the securities market responses to corporate gift announcements. Their results indicate that CPDR is unrelated to explicitly positive or negative irregular returns in general. Even though the cause (the CPDR) is perceived as positive, the association’s goals are not viewed as genuine, so they argued that the providing company does not gain any “ethical capital” in such instances. Together, the trades between firms and government and the office cost perspective suggest that CPDR, which focuses on the Chinese government, produces private benefits for directors and that this type of corporate gift is comparable to a business expense that does not necessarily benefit financial specialists. CP is not entirely driven by variations in wages or wealth [13,14]. For example, the Giving in Numbers study by [13] recently found correlations in three of its twenty-four relapses in the relationship between benefit and giving. Similarly, it has been argued that charitable emergencies have a greater impact on CP levels than the broader economic climate.

According to [10], their study revealed that corporate charitable contributions to natural disasters vary greatly by area (both in the likelihood of a firm to donate and the values of the donations from firms). In determining CPDR, the existence of companies in the affected area has an impact in addition to the home effect. The researchers investigated the geographical effect of CPDR using three disasters from various locations, namely the South Asian Tsunami, Hurricane Katrina, and the Kashmir earthquake. The term “disaster weariness” refers to the fact that the initial tragedy received more attention than subsequent disasters, which received less. In [5], the authors studying CP and disaster primarily focused on the ownership type effect on corporate charitable giving as a response to disasters. Using the Sichuan earthquake as a natural disaster for the study of Chinese firms, two main hypotheses were developed to be tested, the first of which posited that non-state-owned firms are more generous than state-owned firms in response to natural disasters. The other hypothesis centered on firm factors pertinent to corporate philanthropic catastrophe donations in China, such as firm size, financial performance, leverage, industry, and geography. The sample of 703 companies used by [5], which represented 47 percent of Chinese-listed firms, used the period of May–June 2008 to analyze press releases, using a logistic regression model to analyze the likelihood of a firm to donate and a multiple regression analysis to support hypotheses regarding the relationship between ownership type and corporate philanthropic disaster donations in China. The research findings of [5] indicated that the ownership structure of a company has a crucial influence in shaping the corporate philanthropy reaction to a natural disaster. Profitability is a crucial determinant of the level of corporate giving after natural catastrophes, and cash on hand is related to larger donations, according to the study’s findings. In addition, their data validated that geographical location is positively associated with the size of corporate philanthropic catastrophe gifts and that leverage is negatively connected with the decision to respond with corporate philanthropy to a crisis.

Using Hurricane Katrina as a natural disaster, a study [12] utilized a sample of US Fortune 500 companies to assess CP and the disaster impact. First, their research revealed that natural disasters are negative events that have negative impacts on the stock prices of companies. The other factor under review that greatly influences the responses of corporations to natural catastrophes is generosity. Their study also revealed that firms with a lower level of philanthropy are more susceptible to the negative influence on their profitability, whereas socially responsible firms are less susceptible. The results of [12] demonstrated that corporations are more inclined to be charitable in a time of humanitarian need. Thus, they donate in catastrophes to show social responsibility for goodwill. In management sciences and behavioral finance, there have long been debates on corporate philanthropy (CP) and corporate social responsibility (CSR), which have various studies addressing subject matter by humanitarian groups and surfaced in the recent period. There are many studies focused on CP from diverse points of view, yet at the same time this topic is seen as intriguing and rich for further research. Managers of corporations often focused on charitable contributions to boost the image of the corporation in the eyes of employees as well as consumers and other stakeholders. CP also contributes to the long-term growth of a company’s goodwill and competitive advantage. Customers and staff have typically demonstrated more loyalty to companies as a result of CP’s initiatives. The CP phenomenon is beyond the firm’s financial activities or legal needs, as [15] identified four forms of CSR, which included economic, ethical, legal, and charitable actions and requirements. CP can be characterized as “gifts by corporations to charitable purposes such as, to promote education; or for aid to natural disasters’ impacted; or support to enrich culture; or donate for health care and wellness program services” [16,17,18]. Other scholars [19,20,21] described corporate philanthropy as the discretionary allocation of a corporation’s surplus resources to unrelated economic operations that promote the welfare and well-being of society, such as philanthropic social services. As CP for this study, we used the amounts of donations reported by companies in their financial statements. Typically, corporations report their donation amounts in comments to the financial statements, and firms registered on China’s stock exchanges (Shenzhen and Shanghai) are required by law to reveal their financial situations.

The management utility maximization theory [22,23,24,25,26,27] and the profit maximization theory [22,23,24,25,26,27] are the two most common competing theoretical frameworks used to study the reasons underlying CP. Since the emergence of these two theories, however, stakeholder theoretical thought has been the dominant paradigm in the field. A few academics argue that corporate charitable contributions enhance an organization’s image in the eyes of its stakeholders [26,28,29,30,31,32,33]. A positive social image encourages stakeholder support and provides protection or security-like assurance for the organization’s social resources [16,22,34,35,36], enabling organizations to safeguard stakeholder-controlled fundamental resources [34,37,38]. Despite the fact that the majority of the CP literature [27,39,40] argues from a stakeholder theory perspective, a number of studies [41,42,43] claim that CP expenditure is related to agency cost difficulties. According to [44], when a principal–agent connection exists, there is the possibility of incurring agency costs, which vary from manager to manager. There are various literary explanations for this. Advocates of agency theory view CP as an agency cost due to genuine managerial intent and the personal benefits derived from CP by upper management [43,45,46,47,48]. It is difficult to identify a genuine managerial purpose for CP, as managers’ motivations for engaging in CP are opaque, making them difficult to differentiate, and CP may aid corporations in gaining societal respect [49]. Several earlier studies investigating the relationship between financial performance (FP) and corporate performance (CP) have yielded varied results. Using different proxies for both FP and CP, some studies [50,51,52,53] identified a strong positive correlation between the two. In [54], the authors claimed that CP and profitability have a negative relationship due to an agency issue. Due to the intricate relationship between CP and profitability, we postulate that the relationship is curvilinear.

Previous research on corporate slack [17,55,56] indicated that poor financial execution is typically a precursor to slack assets rather than a measure of slack itself. The assumption that firm donations depend on the availability of authoritative slack is widely accepted in the business and society literature, but few quantitative experimental tests of this link exist, and only one study [57] has analyzed financial slack as an indication of donations. It is claimed that a company’s cash flow is a more accurate indicator of spare resources than its accounting earnings because cash flow represents monies that are available for charitable and unconstrained purposes. The majority of companies have reasonable profits but inadequate cash flows. The optional method of corporate donations and philanthropic beneficiaries suggests that a company’s obligations are contingent not only on the CEO’s voting power but also on the availability of optional resources. Optional assets constitute authoritative slack, which is characterized as extra or uncommitted assets, a pad of assets over the base required to maintain the hierarchical coalition [58] or excess assets beyond those anticipated to produce a particular level of yield [59]. Researchers have identified numerous sorts of slack resources (such as additional material, labor, or work-in-progress or machine power), but the most significant slack resource is available cash [17,55]. They concluded that there is a positive correlation between a firm’s perceived slack and charity activities based on the [57] evidence that corporate slack has an impact on the financing of a company’s charitable activities. This study was based on middle-aged businesses from two industries.

In the context of Chinese ownership concentration, [60] discovered a negative link. We also anticipate a negative association if a company’s ownership is highly concentrated; the largest shareholders apply pressure on management to reduce CP. In addition, large shareholders have a greater voice on the board, and they will only permit strategic philanthropy that increases the firm’s value. When it comes to the percentage of shares held by the state, however, the research has contradictory findings. Studies by a variety of authors, including [2,9,60], indicate that state-owned companies donate less. In general, the ownership structure is measured by the concentration of ownership as the proportion of shares held by the top 10 shareholders. State ownership is measured by the percentage of state-held shares. In their study, [46] showed that research and development had a positive effect on CP. Other researchers, such as [50,60,61], have employed innovation as a CP determinant. These studies suggest that innovative companies are more charitable by nature. Innovation proxies based on intangible assets divided by total assets as research and development expenses are unavailable for years prior to 2006. Several investigations found a favorable and statistically significant correlation between size and CP [22,62,63,64]. The conclusion of [65] was that small and large enterprises are more charitable than medium firms.

Managers, executives, and board members use shareholder funds to support their personal preferences and causes through cash gifts. Contributions are utilized by directors to help their own ideologically chosen causes acquire higher social status by providing corporate resources, as mentioned in [66]. Most CP is viewed as a business expense by managers, and its likelihood of being incurred under inadequate financial and monitoring controls is considerable. We expect that a favorable correlation between board size and CP may happen for two reasons. Firstly, the problem of free riders and the communication dilemma may be higher on a huge board, which leads to insufficient monitoring. Secondly if it is regarded as a work-related perquisite, directors will use gifts in the form of cash to support their own agendas in the case of a larger board, at the expense of shareholders. In addition to a monitoring role, boards are accountable for many functions, and huge boards complete their objectives at the cost of shareholder value maximization. In China, the Wenchuan earthquake is among the deadliest natural disasters. This incident occurred on 12 May 2008, when about 69,000 people were killed, nearly 370,000 were injured, and many others were reported missing. According to the Richter scale, the intensity was a magnitude of 8. We chose the 2008 earthquake since it was China’s deadliest natural calamity in recent decades. To determine the effect of the disaster on China’s CP practices, we incorporated a dummy variable for 2008, which was a disaster-affected year. In [60], the authors centered on competition in CPDR and why first movers donate more than late movers to enhance their visibility and business performance. In [21], the authors observed that large organizations are the first to respond to disasters by engaging in CP activities and actions compared to small and medium-sized private firms due public scrutiny. An attention-based perspective of CP was discussed in [67], and it was discovered that corporations target CP actions in the same manner they target other resources for allocation and that attention seeking is the primary motivation for CP actions and their control. In 2008, [8] examined 217 Chinese enterprises that engaged in CPDR and concluded that industry pressure and public interest influenced CP activities. In [68], research on the corporate social responsibility (CP) practices and outcomes of Chinese enterprises indicated that corporations prioritized CP with a long-term rather than a short-term viewpoint. On the basis of 206 disasters from 2005 to 2014, [69] examined the relationship between physical geography, disaster type, and more anticipatory company responses, which can improve how firms and communities adapt to the risks posed by various types of natural disasters.

This study addressed catastrophic disasters by distinguishing givers from non-givers in order to examine the impacts of strategic gifts on financial investment and mean stock prices (AR). We refer to the findings in [12] and extended their methodology to show that CPDR-engaged enterprises enjoyed positive AR. Thus, the negative impact of a calamity on the stock values of giving corporations was diminished. This study’s overarching objective was to analyze natural disasters as negative occurrences and determine whether givers and non-givers behaved differently in response to natural disasters as well as to examine environmental unfriendly industry firms and their philanthropic responses to massive emissions of pollution.

2. Data and Methodology

This study utilized data collected from the CSMAR and RESSET databases, both of which contain the financial statement data given by companies. We utilized companies listed on the Shanghai and Shenzhen stock markets that remained listed until 31 December 2018. For enterprises to be included in the sample, we employed an additional criterion requiring that they were founded prior to 2010, resulting in unbalanced panels of firms. We used data on an annual basis from 2004 to 2018 for 2177 enterprises including all industries. According to their giving habits, these businesses were subdivided into three groups for analysis purposes. We separated firms with respect to their giving characteristics and made three additional subsamples, first including firms that never provided charity in 15 complete years; they comprised 420 firms called non-givers. There were 842 companies categorized as givers for donating more than fifty percent or for seven years. The third and final group were seldom givers which provided less than 50 percent of years and included 915 firms in the sample. We eliminated companies with negative revenue incomes and obtained a total of 20,079 observations. Each province’s China Statistical Yearbook was combed for information pertaining to macrovariables such as GRP and environmental pollution.

The primary objective of this study was to determine how shareholders value CP from their perspective. We have empirically explored whether the CARs of givers and non-givers differ after natural disasters. Using CP, we have closed the gap in how enterprises are valued by investors. This section focuses on the examination of events. First, we determined if natural disasters such as earthquakes are negative events. Then, using a simple T test, we determined whether the CARs of givers and non-givers differed after natural disasters. We determined whether investors truly value companies with superior CP practices. The model incorporated all factors encompassing the micro- and macrolevels of our framework. Different regressions were conducted for givers, seldom givers, and all businesses for both models. In addition, a quadratic component was provided to support the profitability of a curvilinear relationship. In [46,61], the authors employed OLS regressions for CP’s determinants. Stata 12 was used for quantitative analyses.

The general model was as follows:

$$C{P}_{it}=\alpha +{\beta }_{1}C{P}_{i\left(t-1\right)}+{\beta }_{2}PB{T}_{it}+{\beta }_{3}GR{P}_{it}+{\beta }_{4}EPL{I}_{it}+{\beta }_{5}O{S}_{it}+{\beta }_{6}INO{V}_{it}+{\beta }_{7}C{G}_{it}+{\beta }_{8}S{R}_{it}+{\beta }_{j}CO{N}_{it}+D2008+{\epsilon }_{it}$$

where

CP = corporate philanthropy;

PBT = profitability;

GRP = gross regional product;

$EPLI$ = environment pollution level;

OS = ownership structure;

INOV = innovation;

CG = corporate governance;

SR = slack resources;

CON = control variables;

D2008= dummy 2008 year.

Corporate philanthropy (CP) was measured by the natural logarithm of the donation amounts listed on a company’s yearly report. Numerous researchers have employed donor amounts as surrogates for CP, such as in [2,5,10,20,21,46]. We also utilized the lag of CP, as donations are also based on donations from the prior year. Profitability in this study was determined using ROA (return on assets). Numerous researchers [42,43,50,52,53] have employed ROA as a credible indicator of profitability. We also utilized a quadratic term for profitability to support the relationship’s curved nature. To quantify idle resources, we utilized year-to-date free cash flow. This proxy was utilized by [17,26,62,70] as well. The natural logarithm of free cash flows in CNY was utilized. This study employed leverage as a factor in the CP determination. Leverage has been evaluated by the debt-to-equity ratio [2,43,46,71]. The debt-to-equity ratio was acquired by taking the percentage of total liabilities with relation to equity. This study’s primary proxy for ownership structure was the ownership concentration of the top ten shareholders. State ownership was measured by the percentage of state-held shares. Different scholars have utilized these factors in their investigations, including [2,9,60]. In addition, we used the proportion of tradeable shares to better assess the ownership structure of the company.

This study focused not only on the structure of ownership but also on the impact of the board structure and its characteristics. We analyzed the agency problem using the number of the board of directors and the percentage of independent directors. Different researchers have utilized these factors in their investigations, such as [21,43,46,71]. We used the remuneration of directors and its effect on CP as well as the natural logarithm of the amount in CNY received by directors as remuneration, which has been used as a proxy by other researchers [7,43,57,72]. Numerous researchers determined CP using innovation [50,60,61]. We selected the ratio of net intangible assets to total assets as a proxy for innovation rather than R&D because, in China, research and development expenses became publicly disclosed after 2006. This study employed market beta as a surrogate for the firm’s risk, and the RESSET database contains market beta as the market return obtained using the tradable market value weighted approach. Numerous researchers have utilized beta risk in CP-related studies, such as [40].

The gross regional product of each province where a business was registered was utilized. Previous research, such as [38], investigated the link between GDP and CP using GDP. The GRP proxy is the GRP indices (prior year = 100) extracted from the China Statistical Yearbook. We employed two proxies to analyze the environmental situation of the firm’s surroundings. According to the China Statistical Yearbook, the levels of SO₂ and PM10 in 10,000 tons relate to air quality [17,42,43,46,61]. Previous researchers distinguished industries mostly using two-digit SIC codes [17,42,43,46,61]. Our industry categories were initially retrieved using the industrial sector name categories from the RESSET database. Various industry categories used in earlier literature were explored, and CSRC industry codes from the RESSET database were utilized. From these CSRC industry codes, we distinguished firms into environmental impact industry firms and financial regulated firms, and we built dummy industries for these industries together with interaction terms for the pollution level in the province where the firm was registered. EUI companies include coal mining and washing, papermaking and paper product manufacturing, chemical manufacturing, and petroleum and natural gas extraction, among others. The complete details are provided in the Abbreviations. Other firm characteristics, such as firm size and age, were also considered. In general, researchers utilize total assets to indicate the size of a company; however, in this study, we used the natural logarithm of total assets as a proxy, in accordance with previous research, e.g., [7,21,43,46]. Some studies have utilized employee count as a proxy for firm size. Various researchers [2,43] have also used the total number of employees working in each firm on an annual basis, as did this study. Various scholars, including [42,46,60,71,73], have utilized the number of years that have transpired since a company’s founding date to determine its age.

3. Results

Table 1. Cumulative abnormal return (CAR) comparison among givers and non-givers.

CARs	Full Sample	Subsample Givers (A)	Subsample Non-Givers (B)	Test of Difference
	N = 1262	N = 842	N = 420	(A-B)
	Mean	Mean	Mean	Mean
CAR (−1, 1)	−0.573 **	−0.519 **	−0.682 **	0.163 **
CAR (−2, 2)	−0.991 **	−0.915 **	−1.143 **	0.281 **
CAR (−5, 5)	−2.317 **	−2.154 **	−2.642 **	0.488 **

Note: ** p < 0.05.

presents the CARs (−1, 1), CARs (−2, 2), and CARs (−5, 5) for all firms, givers, and non-givers as well as the univariate test for mean differences. The sample included 842 donating firms and 420 non-giving firms for a total of 1262 firms. The CARs (−1, 1) for the entire sample were −0.573 and were significant at the 5 percent level, whereas they were −0.519 and −0.682, respectively, for giving and non-giving firms. The univariate test for differences in the means indicated that the means of the two groups were substantially different from one another, and the positive value indicated that investors gave more weight to giving firms and that the decline in stock prices was less than for non-giving firms. Similarly, comparable outcomes were obvious for CARs (−2, 2) and CARs (−5, 5).

Table 2. Correlation coefficients of all firms.

	1	2	3	4	5	6	7	8	9	10	11	12
1. CP	1
2. PBT	0.3588 ***	1
3. LTA	0.1329 ***	0.8739 ***	1
4. Age	0.0108	−0.0192 ***	−0.0154	1
5. No. of Employees	0.4176 ***	0.7940 ***	0.6513 ***	−0.0368 ***	1
6. Number of Directors	0.0596 ***	0.1099 ***	0.1109 ***	0.2435 ***	0.1126 ***	1
7. Free Cash Flow	−0.0101	0.2438 ***	0.2863 ***	−0.00790	0.2088 ***	0.0418 ***	1
8. Innovation	−0.00410	−0.0315 ***	−0.0354 ***	0.0167	−0.0176	−0.00200	−0.0157	1
9. GRP	−0.0209 ***	−0.0538 ***	−0.0503 ***	−0.1383 ***	−0.0624 ***	0.0928 ***	−0.0133	−0.0232 ***	1
10. Pollution	−0.0262 ***	−0.0345 ***	−0.0325 ***	−0.1330 ***	−0.0269 ***	0.0920 ***	−0.00700	−0.0100	0.3099 ***	1
11. Environment Impact Industry Dummy	0.00420	−0.0487 ***	−0.0735 ***	−0.1162 ***	−0.00400	−0.0866 ***	−0.0284 ***	−0.00950	0.0527 ***	0.0676 ***	1
12. Financial Regulated Industry Dummy	0.0584 ***	0.2791 ***	0.3508 ***	0.0550 ***	0.2208 ***	0.1454 ***	0.1330 ***	−0.0816 ***	−0.0153	−0.0104	−0.2150 ***	1

Note: *** p < 0.01.

explains the Pearson correlation matrix of the factors used in the study for all companies, whereas

Table 3. Correlation coefficients of giving firms.

	1	2	3	4	5	6	7	8	9	10	11	12
1. CP	1
2. PBT	0.5635 ***	1
3. LTA	0.2490 ***	0.7593 *	1
4. Age	−0.0093	−0.0303 *	−0.0248	1
5. No. of Employees	0.6749 *	0.8387 *	0.5188 *	−0.0288 *	1
6. Number of Directors	0.0481 *	0.0754 *	0.0726 *	0.1075 *	0.0909 *	1
7. Free Cash Flow	0.0219	0.0594 *	0.0587 *	−0.0021	0.0551 *	0.0154	1
8. Innovation	0.0009	−0.0304 *	−0.0312 *	0.0654 *	−0.0114	0.0241	−0.0117	1
9. GRP	−0.0302 *	−0.0577 *	−0.0490 *	−0.2523 *	−0.0763 *	−0.0164	−0.0057	−0.0138	1
10. Pollution	−0.0452 *	−0.0396 *	−0.0361 *	−0.2392 *	−0.0350 *	−0.0026	−0.0066	−0.0118	0.2309 *	1
11. Environment Impact Industry Dummy	0.0184	−0.0154	−0.0525 *	−0.1391 *	0.0322 *	−0.0846 *	−0.0144	0.0133	0.0600 *	0.0787 *	1
12. Financial Regulated Industry Dummy	0.0429 ***	0.1668 *	0.2721 *	0.0265 *	0.0842 *	0.1070 *	0.0552 *	−0.0630 *	−0.019	−0.0238	−0.1979 *	1

Note: *** p < 0.01, * p < 0.1.

and

Table 4. Correlation coefficients of seldom-giver firms.

	1	2	3	4	5	6	7	8	9	10	11	12
1. CP	1
2. PBT	0.3900 *	1
3. LTA	0.2455 *	0.8365 *	1
4. Age	0.0004	0.0360 *	0.0822 *	1
5. No. of Employees	0.1608 *	0.4789 *	0.3902 *	−0.0215	1
6. Number of Directors	0.0454 *	0.1628 *	0.2008 *	0.2855 *	0.0826 *	1
7. Free Cash Flow	−0.0724 *	0.2166 *	0.2603 *	0.0176	0.1451 *	0.0635 *	1
8. Innovation	−0.0043	−0.0271 *	−0.0463 *	0.0149	−0.0105	0.003	−0.023	1
9. GRP	−0.0418 *	−0.0753 *	−0.0690 *	−0.1519 *	−0.0798 *	0.0513 *	−0.0095	−0.0294 *	1
10. Pollution	−0.0275 *	−0.0497 *	−0.0442 *	−0.1165 *	−0.0387 *	0.0992 *	−0.0067	−0.0066	0.3145 *	1
11. Environment Impact Industry Dummy	−0.0132	−0.0626 *	−0.1005 *	−0.1354 *	0.025	−0.1298 *	−0.0368 *	0.0052	−0.0038	0.0330 *	1
12. Financial Regulated Industry Dummy	0.1024 *	0.3981 *	0.4987 *	0.0935 *	0.1658 *	0.1799 *	0.1880 *	−0.0848 *	−0.0044	0.001	−0.2170 *	1

Note: * p < 0.1.

display the Pearson correlation matrices of the variables used in the study for givers and infrequent givers, respectively. The correlation coefficient between CP and the log of total assets is positive and statistically significant at the 1 percent level in Table 2, Table 3 and Table 4. However, the coefficient is stronger in Table 2, which compares giving firms to others, with a value of 0.2490. In addition, the correlation coefficient between CP and environmental pollution in the area where the firm is located is negative and statistically significant at the 1 percent level in Table 2, Table 3 and Table 4, whereas the coefficient is stronger in Table 2, which compares giving firms to others, with a value of −0.0452. However, the correlation coefficient between CP and GRP growth is negative and statistically significant at the 1 percent level in Table 2, Table 3 and Table 4, while the coefficient strength is greater in Table 4, which represents enterprises that give less frequently than others, with a value of −0.0418. The coefficient for the environment-unfriendly industry dummy variable is positive. This indicates that these characteristics have a substantial correlation with enterprises that give compared to firms that give infrequently or do not give at all. The results from Table 2, Table 3 and Table 4 are also useful for determining the multicollinearity of predictors. According to the correlation coefficient matrix, there is no multicollinearity among predictors. The largest connection is between the employee count and profitability, which is significant at the 1 percent level and exceeds 0.60. Consequently, we also computed the variance inflationary factors (VIFs) for all variables, which were less than 10. Hence, it can be concluded that the predictors are free of multicollinearity.

Table 5. CP comparisons among firms due to giving behavior.

	Givers		Seldom Givers		All Firms
Variables	1	2	1	2	1	2
PBT	1.105 ***	1.105 ***	1.388 ***	1.390 ***	1.115 ***	1.116 ***
PBT2	−0.00389 ***	−0.00389 ***	0.00350 *	0.00348 *	−0.00368 ***	−0.00368 ***
LTA	−0.475 ***	−0.425 ***	−0.0688	−0.0596	−0.221 ***	−0.200 ***
Innovation	3.216 **	3.145 **	1.011	0.958	3.210 ***	3.099 ***
Age	0.00100	0.00909	−0.0512 **	−0.0498 **	−0.00848	−0.00409
Number of Directors	−0.0530 **	−0.0559 **	−0.0518	−0.0541 *	−0.0366 *	−0.0413 **
Free Cash Flows	0.105 ***	0.104 ***	0.363 ***	0.364 ***	0.171 ***	0.171 ***
Ownership Concentration (Top 10)	0.140	0.124	−0.299	−0.231	−0.670	−0.519
State Share %	0.190	−0.217	−0.232	−0.353	−0.0635	−0.394
Debt-to-Equity Ratio	−0.000213	−0.000168	−0.00197	−0.00220	−0.00234	−0.00237
Director Salary	0.300 ***	0.302 ***	0.189 ***	0.189 ***	0.262 ***	0.263 ***
No. of Employees	0.187 ***	0.186 ***	−0.00149	−0.00174	−0.00423	−0.00475
Tradable Share %	0.0650	−0.552	0.101	−0.0222	−0.155	−0.544
Risk Beta	0.254	0.207	−0.0823	−0.0796	0.340	0.322
Revenue	0.0334 ***	0.0335 ***	−0.0179 **	−0.0180 **	0.0657 ***	0.0657 ***
Dividend Paid Ratio	−0.00834	−0.00863	−0.101	−0.0992	0.00325	0.00286
GRP	0.256 ***	0.287 ***	−0.0186	−0.0152	0.181 ***	0.195 ***
Pollution	0.0170 *	0.0131	0.00843	0.00737	0.0134 *	0.0102
Environment Impact Industry Dummy	1.707 ***	1.676 ***	0.440	0.437	1.130 ***	1.116 ***
Environment Impact Industry Dummy × Pollution	−0.0322 ***	−0.0311 ***	−0.0101	−0.00983	−0.0198 **	−0.0190 **
Dummy 2008		1.993 ***		0.603		1.553 ***
Constant	−20.04 ***	−24.05 ***	4.354	3.870	−15.95 ***	−17.65 ***
Observations	10,619	10,619	9460	9460	20,079	20,079
R-squared	0.846	0.898	0.723	0.823	0.856	0.887

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

presents the data of a basic OLS regression encompassing both micro- and macrolevel variables as well as a dummy for the disaster-affected year. Separate regressions were conducted for givers, infrequent givers, and all companies. Corporate philanthropy was the dependent variable for these various types of firms. CP displays the donation amounts in thousands made by each company. The overall model fit was significant for all models. The results of the determinants corresponded with those of the previous section. When incorporating the 2008 dummy variable, we found a substantial positive relationship between giving firms and the dummy variable. On the other hand, non-givers had pleasant associations, but their relationships were minimal. In addition, there was no curvilinear link between profitability and CP in the absence of givers.

4. Discussion

Natural disasters are viewed as an incentive for managers to donate in times of humanitarian need and demonstrate the company’s social responsibility to the public and government. According to the findings, CP influences the behavior of investors and potential investors. The results of CARs demonstrated that financial investors prefer to purchase the stocks of companies that engage in charitable giving over those who do not. Both professionals and academics are worried about how CP practices affect investment performance. We view the Wenchuan earthquake that occurred in China on 12 May 2008 as a negative event. We determined abnormal returns by estimating the market model using the 200 trading days of return data that concluded 11 days prior to the natural disaster. The results of a univariate test indicated that the mean CARs of givers and non-givers differed. While negative CARs indicated that the Wenchuan earthquake was a negative occurrence overall, this was not the case. The outcome demonstrated rising profitability when donations increased, but at a certain point this relationship reversed and donations were no longer proportional to profitability growth. Managers donated up to a particular amount when profitability was rising when they believed they had reached maturity and could not generate additional profitability by further donations. Another justification for the curvilinear relationship is that each firm had its own strategy for donating and its own motivations to increase profitability. Managers donated up to the point where the firm’s profitability increased as a result of donations but stopped donating at a certain level of profitability due to stakeholder pressure. More profitability does not necessarily indicate the availability of cash flows; nonetheless, high-performing or successful businesses are also adept at cash management. Profitable businesses make better use of capital and have fewer idle assets. Therefore, we justify a linear relationship between profitability and CP. The strength of the coefficient for PBT rose in the case of infrequent givers, indicating that infrequent givers are more sensitive to profitability, whereas givers provide in accordance with their strategic policy.

There is another restriction on corporations, as they only donate in the case of slack resource availability. The positive sign suggested that corporations tend to donate more when there is an availability of free cash flows. The strength of the coefficient for free cash flows increased in seldom givers, which implies that seldom-giver firm are more sensitive to the availability of slack resources, whereas giver firms donate with their strategic policy. Hence, we can state that in the case of giver firms CP is strategic in nature, and giver firms tend to donate higher amounts in contrast with seldom givers. The results indicate that companies with a greater number of tradable shares are likely to donate more money. The explanation behind this may be that corporations with a larger number of marketable shares are more transparent and visible and hence have a pressure for CP. The innovation results indicate a significant favorable association. This validates our theory that innovative organizations tend to donate more compared to others. Good economic conditions have a favorable impact on CP. Environmentally unfriendly industry (EUI) companies give to offset their unfavorable reputations. The significant results of the environment pollution level, EUI, and their interaction term in giving firms revealed that EUI firms are sensitive to the pollution level and giving firms used CP to counterbalance their unfavorable images in society. Moreover, giving corporations employed CP as a strategy to lessen or address the harm they have done to the environment. It is noted that macrovariables also play major role in determining CP, along with microvariables.

5. Conclusions

The CARs of givers had less impact than those of non-givers, and investors favored CP-oriented companies over non-givers. The seldom-giver firms were more sensitive to profitability, whereas donor firms donated with their strategic policy, together with the availability of slack resources. Innovative firms tended to donate more compared to others. As a result, NGO fundraisers should concentrate on creative companies. Environmentally unfriendly industries (EUIs) or companies gave to offset their unfavorable reputations. Business philanthropy had a favorable impact on corporate financial performance from the perspective of stakeholders but a negative impact due to agency costs, resulting in an overall curvilinear connection. Corporate philanthropy increased the value of a company until stakeholder theory was proven valid and agency costs did not emerge. This work can be utilized by managers of charitable organizations for goal formulation and fundraising campaigns. This study will help them determine which characteristics are most influential on the giving behaviors of businesses and thereby prioritize the most generous organizations. This study is also important for the government in formulating trade policy by educating businesses on CP practices, as trade policies effect CP practices as well. As CP is indirectly associated with government goals for the well-being of their own societies, provincial governments can better structure their tax policies to encourage more CP by understanding the phenomena. In addition, provincial governments are able to compare themselves to other provinces and design better regulations, environmental preservation, and CP practice awareness campaigns. The results of this study provide support for the theory that enterprises can create value in the eyes of shareholders through effective CP practices. Managers in China and emerging nations will consider CP as a strategic initiative in the future. This study will aid new entrants’ enterprises in China to better grasp the existing CP practices and help them to create and position their CP strategies when entering the Chinese market. In the future, non-monetary or in-kind donations can be incorporated into this study approach. Future scholars can also utilize this approach to analyze non-monetary or in-kind donations. Our paradigm does not incorporate portfolio theory. Future research may focus on analyzing the role of CP in the construction of stock portfolios in China.