Is political connection a panacea for corporate turnaround?—An analysis based on the resource-based view during the global financial crisis

ABSTRACT

This paper constructs a three-stage model of corporate turnaround, beginning with political connections’ affects declining companies’ implementation of turnaround strategies. The model also explores political connections’ role in corporate turnaround in the context of the most recent global financial crisis. This study discovered that political connections exhibited a weaker ability to allocate resources in the financial crisis. And the government would impede the implementations of turnaround strategies as an important stakeholder. Therefore, political connections significantly and negatively impact corporate turnaround. Through group testing, this paper further demonstrates that companies more dependent on political connections experience more significant, negative impacts.

KEYWORDS:

• Political connection
• corporate turnaround
• resource acquisition
• financial crisis

1. Introduction

The sudden outbreak of COVID-19 at the end of 2019 has caused a severe setback to the global economy and could have profound long-term consequences. With rapid economic decline, sharp contraction in consumption and a surge in unemployment, it poses a huge challenge to enterprises around the world that seek business development. In face of high unpredictability and systemic risks, it becomes particularly important to investigate how declining enterprises could survive the crisis. As a typical merging market economy, China faces a range of challenges from its weak institutional environment and underdeveloped financial systems (He, Li, and Zhang 2017), which make it more difficult for Chinese enterprises to operate and develop. China’s unique historical and cultural characteristics and economic development background have led to political connections as a typical characteristic of Chinese-listed companies (Du, Guo, and Lei 2010). Entrepreneurs usually spend time and money building relationships with government officials, and anticipate that such relationships will bring substantial benefits to their businesses (Krueger 1974). Hence, political connections, which can help companies obtain inexpensive financing and allocate market resources, become pivotal in Chinese corporate governance as an important channel for acquiring corporate resources (Fisman 2001; Li, Meng, and Wang 2008). Thus, companies facing a recession will perceive political connections as life-saving due to their benefits, which many companies will want to seize. At the end of 2017, the behemoth company Hainan Airlines, which ranked among Global Fortune 500, began to crumble. While the airline had various insolvent debts in 2018, it was able to turn around in 2019 with facilitation from China’s central government, Hainan Province, and various financial institutions. Hainan Airlines’ new chairman Chen Feng noted, ‘In other countries, we may have died twice’; the meaning of his words is self-evident. Despite some fortunate companies such as Hainan Airlines, many other companies began to collapse in 2017. For example, Belle, China’s first brand of women’s shoes, was delisted in July 2017. Its board of directors is comprised of many members of the CPPCC (Chinese People’s Political Consultative Conference) – including the founder of the group, Deng Jiao – and representatives of the National People’s Congress, yet this did not redeem the dying company. Political connections are not always a panacea for corporate turnaround. Setting aside all the aura of political connections discussed in previous literature, the role of political connections in the process of corporate decline remains a mysterious ‘black box.’ Therefore, this paper aims to explore whether political connections are a ‘life-saver’ for companies in danger to help them recover from crises or only a ‘driftwood’ on which companies cannot rely.

In 2007, the U.S. subprime crisis, initially a nationwide financial crisis, eventually led to a global economic recession. The outbreak and escalation of this financial crisis have resulted in economic downturns, shrinking consumption and increased unemployment in various countries. With such a rapidly deteriorating external environment, Chinese companies also faced a large-scale decline. As mentioned above, establishing relationship with the government is one of the typical characteristics of Chinese enterprises. But it is still unknown as to whether political connections can exert significant influence in extremely harsh external environments. Therefore, the global financial crisis provides an appropriate natural experiment for our research. We use Chinese-listed companies that experienced a decline in performance in 2008 as a sample to explore whether political connections could be a panacea for corporate turnaround.

Firstly, considering the high degree of complexity of the corporate turnaround process, we propose a three-stage model based on various previous literature to facilitate a combing and understanding of this process. Secondly, we combine political connections with our proposed turnaround model to analyze whether they have a negative impact on firms’ resource acquisition and the implementation of turnaround strategies. Then, we use empirical methods to verify the hypothesis. Lastly, we consider path-dependence theory to explore whether the influence of political connections on corporate turnaround relates to the corporation’s degree of dependence. This study aims to expose the impacts of political connections on market resource allocation and corporate behavior distortion, subsequently providing some advice to the companies wishing to recover from decline.

This paper contributes to current literature in the following ways: (1) First, we propose a new turnaround model based on existing literature which more closely approximates reality. Further, the samples used in existing empirical research are too heterogeneous. Generally, corporations’ decline has substantially resulted from chance (Arogyaswamy, Barker, and Ardekani 1995). We select our sample firms from those that declined under the impact of the 2008 global financial crisis to better control the causes of a company’s decline and obtain cleaner samples. This can also provide more convincing conclusions and better empirical support for our models.

(2) Second, top corporate turnaround scholars have focused on developed countries, resulting in a lack characteristics of economies in transition China’s unique guanxi (relationship) culture generally compels Chinese companies to maintain connections with the government, and such connections have been proven to significantly impact these companies’ access to resources. However, political connections’ role in the corporate turnaround process is unknown. This paper combines political connections with the proposed turnaround model and selects Chinese-listed enterprises as a research sample to confirm political connections’ negative impact on corporate turnaround. Concurrently, this fills a gap in existing literature, and helps to define the government and market’s position and role in transitional economies.

(3) Finally, we strengthen the contextual reinforcement of political connections. Previously, scholars had not reached a unified conclusion regarding political connections’ impacts on company performance and value. The main reason for such a disagreement in existing research is that the advantages and disadvantages of political associations are generalized and lack specific situational research. Therefore, we study political connections’ influence under companies’ specific internal and external environments.

2. Theoretical analysis and hypothesis development

2.1. Summary of corporate turnaround research

Corporate turnaround is a highly complex process. Thus, we propose a three-stage model (Figure 1) based on many previous works in literature to facilitate a combing and understanding of this process. The first turnaround phase noted in this paper is the cognitive stage, in which enterprises should first judge the basic turnaround situation, then choose an appropriate turnaround strategy accordingly. After choosing a strategy, the key to realizing a turnaround involves recognizing whether it can be effectively implemented. Thus, we consider the turnaround strategy’s effective implementation and its influencing factors in the second stage: the behavioral stage, which will also be the focus of this paper. Finally, we refer to the models proposed by other scholars by defining the third stage of turnaround as the turnaround result.

Scholars have generally agreed that there should be a clear cause of the decline, and thus give rise to the typologies of a recession (Pauchant and Mitroff 1992). On the one hand, corporate performance may decline for internal reasons at both the strategic and operational levels. The strategic level primarily refers to the inappropriate choice of enterprise strategy, while the operational level refers to the inefficiency caused by poor management. On the other hand, a recession may also be the outcome of a particular environment (Roux-Dufort 2007) in which companies may have failed to adapt to external environmental changes.

Clearly, the origin of the crisis has significantly impacted studies of corporate turnaround, and the reasons for decline have become an important consideration in choosing turnaround strategies (Pearce and Robbins 1993). Firms must reposition their strategies in response to the decline caused by an internal strategic dimension, although firms facing an operational-level decline must improve efficiency to focus on retrenchment. Alternatively, firms experiencing a decline caused by environmental changes do not need retrenchment to turn around if the market environment is relatively optimistic (Trahms, Ndofor, and Sirmon 2013). However, retrenchment is much more significant in turnaround processes for companies facing pessimistic economic situations (Xu et al. 2018).

After classifying and analyzing the causes of decline, the severity of the decline in corporate performance is another important consideration in choosing turnaround strategies (Hofer 1980). Firms with a relatively modest decline in performance must only cut costs, while firms facing a decline so severe that it threatens the firm’s survival must divest their assets.

Thus far, our analysis of the turnaround situation and the choice of turnaround strategy have centered on the first stage: the cognitive stage of turnaround. However, a correct, sober cognition of the situation is necessary but insufficient to realize turnaround. Correct cognition in strategy implementation is key to achieving turnaround, and various factors can be influential in this process; the most important aspects include firms’ ability to acquire resources and such subjective factors as executive cognition and stakeholders’ support.

In 1984, Wernerfelt proposed the resource-based view, in which the heterogeneity of firm resources is an important assumption. Firms’ resource endowment determines their ability to manage, develop, and even deal with crises. Superior resource endowment not only helps companies improve their ability to adapt to their environments (Bonanno et al. 2010; Hobfoll 1989) but also more significantly impacts enterprises’ ability to implement turnaround strategies (Pretorius 2008). When corporations face decline, internal resources become strained, but only sufficient available resources can prepare firms in decline to implement subsequent turnaround strategies (Pearce and Robbins 1993). Firm size is also an important manifestation of the firm’s resource heterogeneity. Ramanujam (1984) found that large firms have more resources that can be deployed, and thus, are more likely to turn around. Therefore, the firm’s ability to acquire resources affects how they can respond to crises and determines whether they can effectively implement turnaround strategies; consequently, this determines whether the firm can successfully survive a crisis (Bonanno et al. 2004).

The richness of firm resources is an objective factor that affects the implementation of turnaround strategies, but many other subjective factors can influence such impacts. First, leaders’ perceptions of decline are an important factor that influences organizations’ response to the crisis (Furrer, Pandian, and Thomas 2007). Second, the realization of decline is ambiguous, as financial indicators may interfere with managers’ judgment (Winn 1997). Finally, different leadership styles also impact the implementation of turnaround strategies, as some leadership styles are considered more effective than others (Bundy and Pfarrer 2015).

The degree of stakeholder cooperation is another subjective factor that can affect the implementation of turnaround strategies, as weakening stakeholder support is often perceived as an inevitable consequence of declining performance. Thus, regaining stakeholders’ support is a necessary condition for implementing a follow-up recovery strategy (Arogyaswamy, Barker, and Ardekani 1995). In summary, our paper notes the behavioral stage as the second phase in implementing the turnaround strategy and defines its influencing factors.

We reference Lohrke, Bedeian, and Palmer (2004) and Trahms, Ndofor, and Sirmon (2013) turnaround models to note third stage, which involves the changes in firm performance after the turnaround strategy’s implementation: the turnaround result. Firms may smoothly improve their performance after their initial efforts, although some companies will continue to face declining performance until they exit the market. We believe that a return to pre-decline levels proves a successful turnaround, while the latter two cases are considered failures.

Figure 1. Three-stage turnaround model.

2.2. Summary of political connections research

Scholars have recognized the ‘supporting hand’ and ‘predatory hand’ as two competing conclusions in terms of political connections’ influence on corporate performance. Some scholars believe that the government extends a ‘supporting hand’ to corporate operations, or specifically, firms with political connections can improve their performance by seeking political rents (Wang and Wu 2008; Luo and Luo 2008). Previous studies have generally agreed that political connections can help companies easily obtain long-term loans from state-controlled banks (Yu and Pan 2008) and enjoy significantly lower loan rates than non-connected companies (Guiso, Sapienza, and Zingales 2001). This can help connected companies ease their financing constraints while creating higher growth rates and superior performance (Fisman 2001; Johnson and Mitton 2003). In addition to their financial advantages, political connections can help companies reduce their tax burdens (Wu, Wu, and Rui 2009), enter government-controlled industries (Hu and Shi 2008), and even increase their confidence in the judicial system (Li, Meng, and Wang 2008).

Another group of scholars believes that the government extends a ‘predatory hand’ in corporations’ development, which provides the latter with various conveniences while also exhibiting rent-seeking behaviors to achieve certain policy objectives (Rajan and Zingales 1998). The government’s rent-seeking behavior will cause corporations to deviate from their best decisions, decreasing performance (Deng and Zheng 2009; Li, Qiu, and Gu 2010). Moreover, Chen et al. (2011) discovered that a company’s political connections reduce its investment efficiency, while Yu (2016) suggested that political connections can expand a company’s size but impair its efficiency. Additionally, political connections have been proven to significantly relate to overemployment (Guo 2011) and over-management expenses (Du, Guo, and Lei 2010).

As a typical emerging market economy, China has made remarkable achievements in reforming its product market since the nation’s reform and opening-up periods, although its factor market considerably lags in comparable development (Chen, Chen, and Chen 2014). The nation’s imperfect factor markets have led to the government maintaining a relatively important position in allocating resources. Further, the connection between businesses and government has significantly impacted the former’s ability to obtain resources. Simultaneously, the existence of political connections has resulted in the government’s role as an important stakeholder in these firms, which has influenced the latter’s decision-making and operations. Combined with the previously mentioned three-stage turnaround model, we infer that political connections significantly affect the turnaround strategy’s effects, which subsequently impacts declining firms’ turnaround results. However, in the previous study, political connections have never been regarded as a major factor influencing firms’ recovery. Further, political connections always lack contextual reinforcement, and thus, scholars have not reached a unified conclusion regarding their impact on corporate performance and value. Our paper aims to explore political connections’ role in the global financial crisis, which is an inevitable systemic risk.

2.3. Political connections and corporate turnaround

Guanxi has become an important aspect of social activities and interpersonal communication during China’s 5,000-year history, and is vital to Chinese companies’ business activities (Park and Luo 2001). The most direct embodiment of Chinese guanxi culture in corporate management involves establishing government connections, as these affect firms’ acquisition of resources. Such connections also compel the government to become an important firm stakeholder, which impacts all the firm’s managerial aspects. According to our three-stage turnaround model, these important aspects can all affect a turnaround strategy’s implementation. Consequently, the next part of our paper will primarily discuss whether political connections can affect the implementation of corporate turnaround strategies, which will ultimately affect the turnaround outcomes from a firm’s decline as caused by the global financial crisis.

First, we can analyze this process from the firm perspective in general, and the firms’ resource acquisition capability in particular. In 2007, the U.S. subprime mortgage crisis continued to evolve and led to the global financial crisis, which substantially impacted firms’ operations and development in various countries; this impact was greater than any previous crisis in history. Prior work indicates that the financial crisis’ impact on firms is primarily reflected in two ways: the product market’s sales and the capital market’s cash flows (Ma and Meng 2009). The capital market experienced a serious credit crisis as a result; financial institutions had to increase loan audits and reduce their loaning of lines of credit to prevent risk, shrinking the capital market. Domestic banks have become more risk-conscious, with more stringent credit policies (He, Li, and Zhou 2013), while companies can only compete more fiercely for their industry’s few remaining basic resources (Arogyaswamy, Barker, and Ardekani 1995). This significantly decreased these firms’ ability to independently access resources.

Politically connected firms can obtain additional resources through government allocations; however, as the financial crisis continuously evolved, this created a crisis involving resources’ liquidity (Chen, Wei, and Xu 2010). This decreased the liquidity of various rare resources in the factor market, which accordingly decreased the government’s capacity to allocate them. Companies that had wanted to rely on political connections for additional resources would experience difficulty in doing so. Similarly, Johnson and Mitton (2003) studied the Asian financial crisis between 1997 and 1998 and found that macroeconomic shocks weakened the government’s fiscal strength and left it powerless to help politically connected companies.

Second, political connections cause the government to become an important stakeholder in their connected firms. In the global financial crisis, the government experienced greater pressure to bear political achievements while maintaining people’s livelihood, and thus, was more likely to transfer this pressure to their connected firms to obstruct their turnaround strategies, and force them to deviate from their optimum decisions. The financial crisis gradually impacted product sales, which substantially decreased demand, such that the number of firms decreased that industries could support. As previously mentioned, the market size decreases when the macro-economy is poor; consequently, retrenchment and improving operational efficiency should be a necessary turnaround strategy.

Xu et al. (2018) also considered the 2008 financial crisis to confirm the necessity for retrenchment among declining companies. Contrary to the much-needed strategic adjustment, the size-expansion effect is a common consequence of political connections (Yu 2016), and involves political connections used to encourage companies to expand their investments and scale upward. However, these companies will experience difficulty in decreasing costs and divesting assets. Simultaneously, universal overemployment (Guo 2011) and excess management costs (Du, Guo, and Lei 2010) in politically connected firms have forced these companies to pay additional resources after the financial crisis’ impact, as these companies must ‘economize food and clothing.’ This will inevitably lead to the crowding of other internal resources and will affect the implementation of turnaround strategies.

Finally, from a management perspective, political connections can create unproductive, excess income for firms (Bain 1956; Fraumeni and Jorgenson 1997), and consequently create false prosperity. Companies can often relax their internal management if they rely on non-market forces to easily generate excess profits – or specifically, their rent-seeking gains outweigh the gains from production (Leibenstein 1966) – and ignore the problem of improving efficiency in enterprise management. The implementation of a turnaround strategy emphasizes timeliness; generally, if the declining company implements a turnaround strategy after entering an inactive phase, the effects will be substantially decreased (Tangpong, Abebe, and Li 2015). Political connections also decrease companies’ production and operation efficiency (Deng and Zheng 2009). It is then difficult for companies in this inefficient operating environment to adjust their strategies in a timely, efficient manner. Thus, political connections again become a stumbling block for corporations in implementing turnaround strategies. Additionally, our paper’s turnaround model presents the leader as another important factor influencing the implementation of a turnaround strategy. Hiring executives with government or military experience is primarily how companies build political connections, but these politically connected executives’ relatively limited management experience (Piotroski and Zhang 2014) may adversely affect the corporate turnaround process.

Therefore, we posit that the political connection itself distorted firm behavior in the context of the international financial crisis to be more ‘predatory’ than ‘supportive,’ and we hypothesize:

Hypothesis 1: Political connections significantly and negatively affect corporate turnaround.

3. Research design

3.1. Data sources and sample

Our sample consists of A-share listed companies in China from 2005 to 2011. Sample screening: (1) excluding companies in the financial sector; (2) companies that retain information that spans 2005 to 2013 and is fully disclosed; (3) 166 declining companies were screened by the definition of decline and turnaround, of which 52 turnaround successfully (see variable definition for specific screening criteria). Part of the data comes from the CSMAR database, and some of the data from the annual reports of listed companies, obtained by hand. In order to eliminate the extreme value effect, the main continuous variables exclude those in the upper and lower 1% level of the tail processing.

The main reasons for selecting the data from 2005 to 2011 are (1) In general, the research period for corporate decline is mostly concentrated within 3–5 years. In addition, the period of 2005 to 2011 contains a seven-year observation period, which is sufficient to fully study the decline of corporates; (2) Events of the 2008 global financial crisis fall within the selected observation period of our study. In the face of such unavoidable systemic risks, it can better reflect the impact of various factors on the corporate decline and turnaround.

3.2. Variable definition

3.2.1. Dependent variable: turnaround

Based on the definition and measurement corporate decline in previously research (Trahms, Ndofor, and Sirmon 2013; Mei and Zhang 2015; Xu et al. 2018), this paper selects the return on assets (ROA) as the index of enterprise performance. We define corporate decline and turnaround as follows: (1) ROA in 2005, 2006 was positive and (2) ROA in 2007–2009 was decreased by 16.67% relative to 2006 (i.e. profit growth decreased by 20% relative to asset growth); (3) in 2010 or 2011, ROA returned to 2006 levels. First, we filter out the companies that meet criteria (1) and (2) as the declining enterprise. On this basis, A corporate meeting condition (3) is the turnaround corporate, recorded as 1; a corporate that does not meet condition (3) is recorded as the not turnaround corporate, recorded as 0.

3.2.2. Independent variable: political connections

Methods to determine the measurement of political connections are very diverse. Some scholars use dummy variable to measure corporates’ political connections, while other scholars use more specific measurement to give different scores to different levels of political connections. As the establishment of connections with the government is a relatively common phenomenon in China (Du, Guo, and Lei 2010), the assignment method can better illustrate the intensity of political connections compared to dummy variable, while the dummy variable is not sufficient to reflect the differences in the degree of political connections between corporates. Thus, we use the method of assigned points to measure the degree of political connections. Based on the political background of the board of directors (except independent directors), supervisory boards and executive teams, we assign points according to the administrative level of their positions. Specifically, those below township level are assigned 1 point, township level (chief or vice) are assigned 2 points, county level (chief or vice) are assigned 3 points, bureau level (chief or vice) are assigned 4 points, provincial and ministerial level (chief or vice) are assigned 5 points, the national level (chief or vice) assigned 6 points. Every corporate’s total points are summed up to become variable (Political).

3.2.3. Control variables

With reference to research by Mei and Zhang (2015), Xu et al. (2018), Chen et al. (2011) and Chen and Hambrick (2012), Schmitt and Raisch (2013), Tangpong, Abebe, and Li (2015), we set the marketization degree, property rights, firm size, etc. as the control variables (As Table 1 shown).

Table 1. Definition of variables

Type	Variable	Symbol	Definition
Dependent variable	Whether turnaround	Turnaround	A dummy variable equals 1 if a firm successfully turnaround and 0 otherwise
Independent variable	Political connection	Political	Corporates’ political connection indicator.
Control variables	Marketization degree	Market	Degree of marketization in the province where the company is located, according to the marketization degree of China's provinces in 《China Marketing Index》(2011 edition) (Fan Gang, 2011).
	Property right	State	A dummy variable equals 1 if the corporate is state-owned and 0 otherwise.
	Financial leverage	Leverage	Financial leverage= (net profit + income tax + financial cost) / (net profit + income tax).
	Firm size	Size	ln (the total number of corporate employees).
	Equity concentration	Cocen	The first largest shareholder’s shares / the second largest shareholder’s shares
	Resource slack	Slack	Resource slack=net cash flow generated by operating activities / total assets to measure the redundant resources of firms.
	Corporate age	Age	A dummy variable equals 1 if corporate age is greater than industry average and 0 otherwise.
	Current ratio	Liquidity	Current ratio= current assets / current liability
	Corporate lifecycle	Life_market	A dummy variable equals 0 if the corporate is in a growth industry(the average market growth rate is beyond 10%, equals 1 if the corporate is in a mature industry(the average market growth is between 0 and 10%, and 2 otherwise.
	Regulatory Industries	Industry_control	A dummy variable equals 1 if the industry codes are B, C4, C6, D, F, G which are taken as regulated industry and 0 otherwise.

3.3. Model definition

In this section, we develop a model arguing that political connections have a significant negative impact on corporate turnaround. Considering that the dependent variable is a dummy variable, we apply probit-model to test Hypothesis 1.

In Model (1), the dependent variable is Turnaround and the independent variable is Political. The coefficient of the Political is expected to be significantly negative, which means that corporates with stronger political connections are less likely to turn around from decline.

(1) $Turnaround={\alpha }_0+{\alpha }_{1}Political+\sum {\beta }_{j}Controlvariables+\epsilon$(1)

4. Results

4.1. Descriptive results

Table 2 shows the summary statistics. The average of the dependent variable Turnaround is 0.31 and the median is 0, indicating that only 31% of corporates can successfully turn around from decline. From this point of view, the possibility turnaround is quite rare for declining firms. The mean of the independent variable Political is 7.8, which indicates that it is a common for corporates in China to establish connections with the government, in order to attain some kind of benefit.

Table 2. Descriptive statistics

	N	Mean	min	p25	Median	p75	max	St.Dev
Turnaround	166	0.31	0.00	0.00	0.00	1.00	1.00	0.47
Political	166	7.72	0.00	3.00	6.00	12.00	34.00	7.59
Market	166	6.58	3.59	5.67	6.67	7.80	8.01	1.24
State	166	0.77	0.00	1.00	1.00	1.00	1.00	0.43
Leverage	166	2.34	−1.77	1.10	1.43	2.21	17.08	2.81
Cocen	166	18.86	1.03	2.14	6.97	23.37	167.81	28.72
Size	166	7.12	3.09	6.25	7.26	8.06	10.24	1.46
Slack	166	0.02	−0.25	−0.01	0.04	0.08	0.25	0.09
Age	166	0.55	0.00	0.00	1.00	1.00	1.00	0.50
Liquidity	166	0.90	0.08	0.44	0.66	0.99	5.42	0.85
Life_market	166	0.14	0	0	0	0	2	0.47

Table 3 shows the results of the Pearson and the Spearman correlation coefficients. The correlation matrix preliminary shows that there is a significant negative correlation between the political connections and corporate turnaround, but the specific relationship needs to be further examined by adding the control variables. Variable Market, State, Cocen, and Size are significantly negatively correlated with turnaround. The maximum absolute value of the correlation coefficient between the independent variable and the control variables is 0.27. The correlation coefficient between the main variables is no more than 0.5, so the regression result is not seriously disturbed by multiple collinearity.

Table 3. Pearson/Spearman correlation matrix

	Turnaround	Political	Market	State	Leverage	Concen	Size	Slack	Age	Liquidity	Life_market
Turnaround	1.00	−0.16**	−0.20***	−0.18**	0.06	0.09	−0.16**	−0.02	−0.13	0.03	0.06
Political	−0.22***	1.00	0.02	0.06	−0.04	−0.01	−0.01	0.02	−0.08	−0.02	0.002
Market	−0.26***	0.05	1.00	0.05	−0.15*	0.11	−0.02	−0.10	0.07	−0.14*	−0.01
State	−0.18**	0.09	0.09	1.00	0.15*	0.18**	0.22***	0.11	−0.01	−0.18**	−0.12
Leverage	−0.002	0.04	−0.12	0.13*	1.00	0.02	0.07	0.06	0.11	−0.27***	−0.06
Cocen	0.14*	0.02	0.04	0.18**	0.10	1.00	0.06	0.07	−0.05	−0.09	−0.13
Size	−0.14*	0.005	0.001	0.26***	−0.03	0.03	1.00	0.19***	−0.06	−0.10	−0.08
Slack	0.02	0.06	−0.09	0.07	0.06	0.09	0.19**	1.00	0.06	−0.03	−0.06
Age	−0.13	−0.06	0.04	−0.01	0.02	−0.13	−0.06	0.04	1.00	−0.11	−0.01
Liquidity	−0.007	−0.01	−0.10	−0.13*	−0.12	0.02	−0.09	−0.02	−0.09	1.00	0.10
Life_market	0.05	0.02	−0.05	−0.08	0.04	−0.11	−0.08	−0.02	−0.02	0.004	1.00

*p < 0.10; **p < 0.05; ***p < 0.01.

4.2. Regression results

Table 4 provides the t-test results for the two subsamples of main variables: successfully and unsuccessfully turnaround. The difference between the two subsamples’ means reveals that the political connections of corporations that did not successfully turn around iare significantly higher than those who did. Just like the turnaround model we propose before indicates that the more employees in a firm – as important internal stakeholders – the more employees in a firm – as important internal stakeholders – the more difficult is to reach a consensus. As we use the number of employees to measure firm size, the t-test result shows that the firms that did not turn around are typically larger. Additionally, the companies that did not turn around also have a lower concentration of equity operating in provinces with higher degrees of marketization, operate longer and more likely to be state-owned.

Table 4. T-test result

Variable	Turnaround = 0	Mean	Turnaround = 1	Mean	MeanDiff
Political	114	8.83	52	5.31	3.52***
Market	114	6.80	52	6.10	0.70***
State	114	0.82	52	0.65	0.16**
Leverage	114	2.35	52	2.34	0.01
Cocen	114	16.21	52	24.67	−8.46*
Size	114	7.26	52	6.82	0.44*
Slack	114	0.02	52	0.03	−0.01
Age	114	0.60	52	0.46	−0.14*
Liquidity	114	0.91	52	0.89	0.02
Life_market	114	0.12	52	0.17	−0.05

*p < 0.10; **p < 0.05; ***p < 0.01.

Table 5 reports the results from testing Hypothesis 1. Column (1) shows the coefficients between Turnaround and Political without control variables; Column (2) shows the results that contain control variables except Life_market. Enterprises in different stages of the life cycle have different organizational structure, scale of production and operation, and strategic choices (Miller and Friesen 1984). Therefore, Column (4) introduces and adds the concept of corporate life cycle (Schmitt and Raisch 2013) to the model.

Table 5. Regression result

Variable	Turnaround
	Main effect test			Robustness test
	(1)	(2)	(3)	(1)	(2)
Political	−0.043***	−0.046***	−0.045***
	(0.016)	(0.017)	(0.018)
Political_agency				−0.007**	−0.007**
				(0.003)	(0.003)
Market		−0.282***	−0.282***	−0.274***	−0.274***
		(0.090)	(0.901)	(0.090)	(0.090)
State		−0.319	−0.318	−0.256	−0.256
		(0.278)	(0.279)	(0.280)	(0.280)
Leverage		−0.004	−0.005	−0.002	−0.002
		(0.042)	(0.042)	(0.043)	(0.043)
Cocen		0.008**	0.009**	0.008**	0.008**
		(0.004)	(0.004)	(0.004)	(0.004)
Size		−0.122	−0.122	−0.128	−0.128
		(0.081)	(0.081)	(0.081)	(0.081)
slack		1.127	1.124	1.317	1.320
		(1.281)	(1.282)	(1.283)	(1.283)
Age		−0.383*	−0.383*	−0.329	−0.330
		(0.230)	(0.230)	(0.226)	(0.226)
Liquidity		−0.198	−0.198	−0.190	−0.190
		(0.157)	(0.157)	(0.154)	(0.154)
Life_market			0.038		−0.027
			(0.244)		(0.243)
_cons	0.063	3.244***	3.232***	3.109***	3.120***
	(0.171)	(0.895)	(0.900)	(0.886)	(0.891)
Industry_control	Yes	Yes	Yes	Yes	Yes
Obs.	166	166	166	166	166
Pseudo R2	0.079	0.196	0.196	0.181	0.181

*p < 0.10; **p < 0.05; ***p < 0.01.

The Political coefficient in Column (1) is positive and highly significant at the 1% level. With the control variables added in Columns (2) and (3), the negative correlation between political connections and corporate turnaround is still significant at 1%. This fully illustrates political connections’ adverse effect on firms that desire to recovery from decline during the crisis period, thus verifying Hypothesis 1.

Additionally, the results of Columns (2) and (3) reveal that the degree of marketization also significantly impacts corporate turnaround. Marketization has been the goal of China’s economic reform, and from the empirical results, we can make initial observations about how macro-business environment critically impacts corporate turnaround. Specifically, firms located in the province with higher degree of marketization are less likely to recover from decline; and the negative coefficient between them is significant at 1% level.

Equity concentration is another important factor affecting corporate turnaround, reflecting the level of management’s freedom. The empirical results suggest that equity concentration has a positive impact on corporate turnaround and significant at 5% level. It demonstrates that a higher concentration of equity, which means higher degree of stakeholders’ cooperation, is more likely to result in turnaround. Besides this, the empirical results also indicate that the corporate age has a negative impact on corporate turnaround and it is significant at 10% level, meaning the older the company, the more unlikely for it to achieve a turnaround.

We use alternative measures of political connections as a robust test for empirical results. In main effect test, we use administrative level of positions to measure political connections. While in the robust test, we use the level of the board, independent directors, supervisory boards and executive teams’ serving agency to measure the variable instead. And the negative correlation between turnaround and political connections is still significant at 5% level, suggesting that the results in Table 5 are robust.

5. Further analysis: political connections and corporate turnaround in different situations

Based on the above research, we now explore whether political connections’ role in corporate turnaround differs under the circumstances in which firms depend on political connections, to varying degrees.

Economic systems’ development and evolution are typically influenced by people’s past choices. However, research indicates that strategic adjustments and various strategies’ implementation during business operations also exhibit similar path dependence characteristics (Chen 2002). Managers choose their companies’ business strategies based on their subjective judgment of the external environment and internal resources, but they also often rely on previous profit models. Specific to the situation in this paper, if firms have relied on political connections to obtain excess income, they will expect this profit model to be effective again, which will develop into a type of long-term dependence. This is reflected in firms’ inertia in strategic adjustment decisions. First, managers will find it difficult to perceive political connections’ disadvantages in a particular context. Second, and as the above analysis indicates, governments’ ability to allocate resources weakened during the global financial crisis, and will hinder the implementation of a turnaround strategy. However, it will be difficult for connected firms to completely cast off political connections’ effects. We have previously confirmed political connections’ negative impact on corporate turnaround during the global financial crisis; therefore, the next section will further explore whether this negative impact is stronger and more significant for companies with a greater dependence on political connections.

5.1. Political connections and corporate turnaround in different marketization processes

The degree of marketization and the institutional environment have been shown to directly impact political connections (Fan, Wong, and Zhang 2007). As a merging market economy, China’s marketization primarily differs from that of western countries in two respects: macroeconomic regulation and market-standardized management (Jiang and Song 1995). Therefore, the government can excessively intervene in microeconomic activities and the allocation of resources. In the case of this relatively imperfect market mechanism, political connections may become an effective alternative mechanism (Rajan and Zingales 1998). This essentially reflects the government’s intervention in corporate activities (Du, Lei, and Guo 2009), accompanied by the government’s rent-seeking behavior (Du, Guo, and Lei 2010). China has persistently advanced its market-oriented reforms to improve institutional guarantees and build a fair market environment. Specifically, marketization is merely a process to eliminate all privileges and discrimination, and establish market rules for equal contracts, participation, and competition (Fan, Wang, and Zhu 2011). However, many of these initiatives – from establishing special economic zones to unevenly developing regional economies – have led to the asynchronous progress of marketization reforms among China’s various regions. For example, the market itself has a relatively weak ability to allocate resources in low-marketization regions, and thus, political connections are a stronger substitute for the market. Consequently, the government plays a greater role in allocating resources, and the government in such regions will be more likely to provide companies with the development resources they need; these companies will be more likely to gain excess returns through their political connections (Yu and Pan 2008). This increases companies’ dependence on these political connections.

To test whether the negative impact of political connections is stronger and more significant for companies with a greater dependence, we divide our sample into two sub-samples by the degree of marketization. Firms scoring greater than the entire sample’s median are designated as having high degrees of marketization, and the other firms form the low-marketization group.

According to the empirical results in Table 6, we can observe that the negative coefficient between political connections and corporate turnaround is not significant in the high-marketization sub-sample. While in the low-marketization sub-sample, the negative correlation between political connections and corporate turnaround is stronger than the other sub-sample and significant at the 1% level, which proves that companies located in provinces with lower degree of marketization are more negatively affected by these connections during the turnaround process. This shows that companies that depend more on political connections are more negatively affected by such connections.

Table 6. Regression result

Variable	Turnaround
	High degree of marketization			Low degree of marketization
	Main effect		Robustness	Main effect		Robustness
	(1)	(2)	(1)	(1)	(2)	(1)
Political	−0.030	−0.039		−0.057**	−0.070***
	(0.025)	(0.028)		(0.023)	(0.026)
Political_agency			−0.001			−0.015**
			(0.005)			(0.006)
Market
State		−0.559	−0.517		−0.227	−0.129
		(0.408)	(0.408)		(0.414)	(0.421)
Leverage		0.227	0.235		−0.032	−0.021
		(0.199)	(0.202)		(0.049)	(0.052)
Cocen		0.008	0.006		0.010*	0.010*
		(0.007)	(0.006)		(0.006)	(0.006)
Size		−0.176	−0.182		−0.113	−0.119
		(0.136)	(0.134)		(0.109)	(0.111)
Slack		0.172	0.427		2.664	3.165
		(1.940)	(1.882)		(2.000)	(2.114)
Age		−0.404	−0.292		−0.353	−0.297
		(0.374)	(0.369)		(0.332)	(0.334)
Liquidity		−0.025	−0.002		−0.417	−0.416
		(0.194)	(0.193)		(0.262)	(0.266)
Life_market		−0.105	−0.139		0.193	0.098
		(0.414)	(0.410)		(0.342)	(0.350)
_cons	−0.433*	0.970	0.741	0.653**	2.206**	2.223**
	(0.241)	(1.035)	(1.038)	(0.264)	(0.947)	(0.957)
Industry_control	Yes	Yes	Yes	Yes	Yes	Yes
Obs.	81	81	81	85	85	85
Pseudo R2	0.052	0.135	0.110	0.148	0.247	0.251

*p < 0.10; **p < 0.05; ***p < 0.01.

In the robust test, the empirical results are consistent with those in previous regression, suggesting that our results in Table 6 are robust.

5.2. Political connections and corporate turnaround under different property rights

The institution is the basis for regulating corporate behavior and ensuring economic operations. All companies must conduct their activities within the scope prescribed by this system (Norh 1990). However, due to the special nature of China’s economic development and the relative lack of inertia among its policies, companies must face corresponding policy risks. Political connections are one important way to prevent such risks, as the formation and functioning mechanism of corporate political connections differ among firms with different property rights (Tang and Sun 2014). For state-owned firms, the ownership itself is more direct and stronger than executives’ political identities (Wu, Wu, and Rui 2010). Further, private firms face greater policy risks than state-owned firms, which have ‘natural’ political connections (Tan and Litschert 1994). To avoid risks, private firms typically focus more on establishing political connection than state-owned enterprises (Ji and Song 2014).

State-owned firms’ ‘natural’ political connections are the other reason. Private firms must spend more resources to establish ties with the government, resulting in greater potential costs for them to develop these political connections. The significant and inherent economic benefits will compel them to continue to maintain this political status (Pan 2009). With this stronger motivation to establish political connections and the higher cost of abandoning them, we conclude that private firms will also depend more on political connections than state-owned enterprises.

To test whether political connections’ negative impact is stronger and more significant for companies with a greater dependence, we divide our sample into two sub-samples by property rights. According to the empirical results in Table 7, we can observe that the negative coefficient between political connections and corporate turnaround is significant both in the state-owned sub-sample and the non-state-owned sub-sample. While in the non-state-owned sub-sample, the negative correlation between political connections and corporate turnaround is stronger and more significant than the other sub-sample, which proves that non-state-owned companies are more negatively impacted by these connections during the turnaround process. That is, companies that depend more on political connections are more negatively affected by these connections.

Table 7. Regression result

Variable	Turnaround
	State			Non-state
	Main effect		Robustness	Main effect		Robustness
	(1)	(2)	(1)	(1)	(2)	(1)
Political	−0.032*	−0.033*		−0.115**	−0.143**
	(0.018)	(0.019)		(0.050)	(0.063)
Political_agency			−0.004			−0.025**
			(0.004)			(0.012)
Market		−0.311***	−0.306***		−0.511*	−0.426*
		(0.115)	(0.117)		(0.276)	(0.223)
State
Leverage		−0.008	−0.006		0.116	0.140
		(0.046)	(0.047)		(0.160)	(0.164)
Cocen		0.008*	0.008**		0.013	0.019
		(0.004)	(0.004)		(0.026)	(0.025)
Size		−0.142	−0.142		0.043	−0.026
		(0.102)	(0.102)		(0.198)	(0.182)
Slack		−1.309	−1.189		12.859**	14.979***
		(1.567)	(1.572)		(5.244)	(5.688)
Age		−0.421	−0.386		−0.047	0.286
		(0.272)	(0.269)		(0.607)	(0.605)
Liquidity		−0.183	−0.196		−0.322	−0.024
		(0.193)	(0.194)		(0.378)	(0.337)
Life_market		−0.153	−0.220		−0.276	−0.164
		(0.318)	(0.316)		(0.638)	(0.609)
_cons	−0.160	3.194***	3.133***	0.815**	4.311*	3.329*
	(0.204)	(1.145)	(1.148)	(0.394)	(2.448)	(1.997)
Industry_control	Yes	Yes	Yes	Yes	Yes	Yes
Obs.	127	127	127	39	39	39
Pseudo R2	0.052	0.182	0.171	0.166	0.486	0.475

*p < 0.10; **p < 0.05; ***p < 0.01.

In the robust test, the empirical results are consistent with those in previous regression, suggesting that our results in Table 7 are robust.

6. Conclusions

With China’s rapid economic development and increasingly fierce corporate competition, scholars have increasingly focused on how firms in decline can successfully recover. With the introduction of sociology and other disciplines, corporate turnaround research has gradually broadened, and more factors have been proven to significantly influence the corporate turnaround process. Since Bibeault established the original two-stage model in 1982, more scholars have examined the corporate turnaround process by establishing turnaround models. From simple linear models to those adding contingencies and feedback, these models have evolved from the simple to the complex to more closely approximate reality. After reading and organizing prior literature, we proposed a new turnaround model from another perspective and divide the turnaround process into three stages: cognition, behavior, and outcome. Further, we posit that the behavioral phase – or the phase involving the implementation of a turnaround strategy – is the focus of the entire process, with implementation results affected by corporate resources and other subjective factors. The subjective factors here primarily refer to corporate executives’ levels of awareness and decision-making and the degrees of cooperation among corporate stakeholders.

We establish this new model to discover that political connections are an important influencing factor. We consider dual perspectives, or firms’ ability to acquire resources and the government’s role as a corporate stakeholder, to analyze political connections’ impact on the corporate turnaround process. Political connections are a relatively common phenomenon in emerging market economies, and China is a typical country among them. The outbreak of the 2008 global financial crisis provided a suitable natural experiment setting for our research. Our research sample included selected Chinese companies with declining performance during this global financial crisis to observe how companies can recover after decreased performance under this unavoidable systemic risk. We revealed that resource liquidity decreased during the financial crisis, and political connections could not help companies obtain additional resources. Simultaneously, the government as a stakeholder created certain obstacles to the smooth implementation of turnaround strategies. Our further analysis subdivided our sample, based on the path dependence theory, which demonstrated that political connections have more negative impacts on more dependent companies. It is noteworthy that prior literature generally believed that political connections have a greater negative impact on the operation of state-owned firms. However, this article contrasts other works by beginning with the path-dependent characteristics of corporate strategy adjustments during the crisis, confirming that private firms are more negatively affected by political connections during the turnaround process. The following primary implications can be derived from this article in practice:

(1) The financial crisis has broken the aura of political connections, and these are not always a panacea for companies. As the economic situation deteriorates, this gradually reveals the disadvantages of political connections. Therefore, corporations should not regard political connections as a life-saver, but should actively implement turnaround strategies to independently survive crises, and even facilitate higher-level development.

(2) Firms’ core competitiveness is the key to achieving sustainable development. With the continuous advancement of marketization, Chinese firms’ operating environment has continuously improved, and fairness and justice have become keywords in this reform period. Further, guanxi should not be a substitute for market allocations, nor should companies and their managers focus on the political connections.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

National Social Science Foundation of China, ID: 19ZDA084