Strategic Choices for Sustainable Competitive Advantage, Marketization Degree, and the Executive-Employee Compensation Gap

Abstract

Responding to the latest demand for strategic human resource management research, the paper investigates the links between the strategic choice of sustainable competitive advantage for firms and the executive-employee compensation gap (EECG), and the moderating role of marketization degree in influencing such links between the two. A balanced panel of data consisting of 3900 annual observations of companies listed in China’s Shanghai and Shenzhen A-share manufacturing industries from 2008 to 2017 is used as the research sample, using SPSS 23.0 and STATA 16.0 software. The paper makes empirical analysis using several methods, including factor analysis, correlation analysis, multiple linear regression analysis based on OLS/2SLS, and fixed effect regression analysis, respectively. The empirical results confirmed that the differentiation strategy had a positive effect on EECG, and the marketization degree would strengthen the positive effect; and that the cost leadership strategy had an inhibitory effect on EECG, and the marketization degree would strengthen the inhibitory effect. Further exploration has found that both differentiation and cost leadership strategies can effectively improve firm performance and enhance sustainable competitive advantage when matched with a moderately higher EECG; the level of participation of female executives in corporate governance would harm the performance consequences of differentiation strategy, while improving the performance consequences of cost leadership strategy.

1. Introduction

In recent years, the polarization of compensation among Chinese companies has become increasingly serious. Hay Group, a global management consulting firm, noted in its 2015 Global Salary Report that, “the executive-employee compensation gap (EECG) is widening around the world, and it is the largest EECG within Chinese companies at about 12.7 times”. The 2015 Forbes data showed that the Lenovo CEO, Yang Yuanqing, topped the list of CEOs of Chinese listed companies with an annual salary of 119 million yuan, which was more than 700 times the salary of rank-and-file employees. The Chinese Listed Companies’ Executive Compensation Index Report (2017) announced that the average salary of the top three executives of LeTV in 2016 was nearly 450 million yuan, which was far more than a thousand times the salary of ordinary employees. According to principal-agent theory, there is asymmetrical information and inconsistent interests between principal and agent. As operators of an enterprise, senior executives have a basic grasp of the company’s information. As a result of information asymmetry, senior managers will pursue more improvement in their own salary level, social status, and reputation, and expand their own power. The EECG in Chinese enterprises is too broad and the resulting phenomenon of unfair social income distribution has been over-interpreted by the public from all circles, which has become a focal issue that needs to be addressed in Chinese society. To open the “black box” regarding the mechanism of the continuous expansion of the EECG in enterprises, scholars have been digging deeper into the evolutionary mechanism of the EECG [1]. At present, fruitful progress has been made in this area, confirming that corporate governance and organizational characteristics [2,3], top executives’ traits [4], and industrial and regional features [5] are important factors affecting the EECG. Even so, the existing literature is far from being effective in explaining the evolution of the EECG. At the same time, the issue of sustainable competitive advantage has been a central concern of both theoretical and business circles. The key to sustainable competitive advantage lies in implementing strategies to break the old equilibrium and gain new advantages. However, there is little literature examining such issues from the perspective of strategic choices for sustainable competitive advantage, and its relationship with EECG remains unclear.

Competition is an objective product of the market economy and an inevitable part of business existence. The pursuit of sustainable development is a fundamental change in the concept of human development and a major shift in an industrial civilization that has lasted for centuries. In 1980, Porter’s book “Competitive Strategy” classified firms’ competitive strategies into differentiation strategy, cost leadership strategy, and concentration strategy, in which differentiation strategy seeks to win a competitive advantage by creating products or services that are difficult to replace by competitors through research and development activities, advertising, and brand image enhancement activities, to meet the diversified and individualized needs of customers. The cost leadership strategy reduces costs by building efficient production facilities and implementing large-scale production on the premise of meeting the requirements of high product quality, while at the same time strictly controlling overhead, financial expenses, and R&D expenses, etc. There are various ways for companies to gain a sustainable competitive advantage. However, the academic community has not yet agreed on which competitive strategy is best. A significant portion of the literature supports a higher level of performance for cost leadership strategies [6,7]. In contrast, some scholars argue that firms that adopt a differentiation strategy have higher levels of short-term profitability and long-term competitiveness than those that implement a cost leadership strategy [8]. Regardless of the controversy over their views, established studies all affirm the substantial value of competitive strategies.

Compared to traditional human resource management (HRM), strategic HRM is a kind of objective management to gain a competitive advantage [9], which refers to a “full participation” HRM model. According to the theory of human capital, executives are leaders of enterprises, belonging to high-quality heterogeneous human capital in enterprises. If shareholders want executives to make full use of their highly strategic and unique human capital value and encourage them to use their human capital reasonably to create wealth for the company, they must develop more attractive compensation contracts for them from the perspective of competitive strategy. Compensation incentives are an important part of HRM, and the core of the strategic human resource incentive is to motivate employees according to the company’s strategic needs, stimulate their potential, and, ultimately, create value for the company. Therefore, some scholars have introduced strategic choice as a new perspective in the study of executive compensation formation mechanisms. In a pioneering study, Chai Cai et al. [10] took a sample of A-share listed manufacturing companies in China and empirically found that 82% of companies with differentiated strategies had excessively high internal pay gaps among top executives and 87% of companies with cost leadership strategies had excessively low internal pay gaps among top executives. According to this finding, the implementation of a differentiated strategy is more likely to lead to the “trench effect” caused by excessive pay incentives. Therefore, the implementation of differentiated strategies is more likely to lead to the “trench effect” caused by excessive compensation incentives, which is not conducive to the long-term development of the company. It can be seen that the potential effects of competitive strategy on the compensation gap among top executives have been explored by scholars to an acceptable degree, while EECG, another key dimension of executive pay, has not been studied from the perspective of strategic choices for sustainable competitive advantage.

On the whole, the existing literature still has the following gaps to be addressed: Firstly, although the internal compensation gap among top executives, who act as the main decision-makers and leaders of the competitive strategy [11], should be paid attention to, employees are the concrete executors of the strategy and are also indispensable for the success of the sustainable competitive strategy [12]. However, the studies focusing on the competitive strategy’s effects on executive compensation haven’t mentioned the link between competitive strategy and EECG [10]; therefore, the relationship between competitive strategy and EECG needs to be clarified. Secondly, the existing literature in this area is mostly discursive and normative, focusing on the qualitative matching principles of competitive strategy and compensation structure, compensation level, and compensation management system, while empirical studies based on a large amount of data are relatively scarce; therefore, empirical studies on the relationship between competitive strategy and compensation incentives need to be enriched. In addition, the marketization degree is used to reflect the relationship between the government and the market, the development of a non-state-owned economy, the development of the product market and factor market, the status quo of market intermediary organizations, and the legal environment system [13]. Due to the uneven economic development between regions in China, there are great differences in the marketization degree, which lead to varying degrees of impact on all aspects of the company’s internal and external governance. Therefore, the marketization degree should be introduced as a contextual factor to address the strategic choice of sustainable competitive advantage in relation to EECG.

Given this, this paper attempts to explore the formation mechanism of EECG from the perspective of strategic choice for sustainable competitive advantage. To be specific, using balanced panel data consisting of 3900 firm-year observations from A-share manufacturing listed companies in Shenzhen and Shanghai Stock Exchange from 2008–2017 as the research sample, we focus on the following three questions: (1) How does a company’s choice of different competitive strategies determine EECG? (2) How will the marketization degree affect the relationship between different competitive strategies and EECG? (3) How can competitive and compensation strategies be scientifically and effectively matched to achieve a sustainable competitive advantage and, thus, a leap in corporate performance?

2. Literature and Hypotheses

The impact mechanism of differentiation strategy on EECG can be interpreted in two ways.

Firstly, a differentiation strategy improves a company’s sustainable competitive advantage through technological innovation [14], which requires continuous investment and exploration of new areas to capture consumers’ minds and meet market opportunities. Therefore, the implementation of a differentiation strategy is usually accompanied by higher investment in R&D. Executives are key decision-makers in companies’ innovation activities and play a pivotal role in this strategic decision. Because R&D activities are highly uncertain and risky, executives tend to reduce their investment in risky technology innovation to avoid the corresponding operational and decision-making risks [15]. In this case, according to principal-agent theory, executive compensation, as an incentive mechanism, can effectively solve the problem of moral hazard and adverse selection [16]. Compensation incentives can compensate executives for the potential loss of short-term earnings from R&D investments [17] and paying a higher level of compensation in return can weaken their negative risk-resilience attitude and motivate executives to actively invest in R&D. In addition, executives are more knowledgeable than shareholders about the company’s operating conditions and the internal and external environment it faces, and shareholders rely on executives to make accurate analyses and judgments of the complex operating situation. Especially for companies implementing differentiation strategies, achieving a differentiated sustainable competitive advantage depends on the rich experience of executives and keen insight into cutting-edge technologies. According to human capital theory, executives can provide a commercialized decision-making perspective and their own high-quality heterogeneous human capital in the company [18]. Therefore, from the perspective of shareholders and the board of directors, there is a tendency to give executives higher levels of compensation in return, which can motivate them to continuously develop technological innovation to create value for the company on the one hand and retain the company’s core human capital on the other. Therefore, shareholders and the board of directors would pay more attention to the contribution of executives to the company, while relatively ignoring the value of ordinary employees. As a result, increasing the level of executive compensation will mean widening the EECG.

Secondly, from the CEOs’ perspective, managerial power theory suggests that CEOs usually manipulate their own compensation by misusing their discretion, as evidenced by increasing their compensation levels inappropriately to achieve both material and moral satisfaction [19]. On the one hand, for companies pursuing a sustainable differentiation strategy, relatively low upfront fixed capital investment [20] and higher R&D expenditures [21] are generally accompanied in order to win the competitive advantage of differentiation. Since CEOs have less discretion to manipulate upfront fixed capital investment and more flexibility to manipulate accounting operations for R&D expenses, the capital expenditure structure of low fixed capital investment and high R&D expense investment resulting from the differentiation strategy helps CEOs use their discretion to maximize their own interests; on the other hand, the CEO of a company pursuing the differentiation strategy needs to have excellent foresight of industry development prospects and insight into consumer preferences, which would require higher decision-making power and better risk-control capability from the CEO. In this case, whether trying to motivate the CEO and his executive team who have scarce and valuable human capital in the management market, or trying to make full use of his heterogeneous human capital and business talents to enhance the competitiveness of the company, the CEO needs to be given more discretion [22]. The greater the CEO’s discretion, the stronger his or her manipulation of compensation gains. Powerful CEOs control the allocation of corporate resources, while rank-and-file employees are in a weak position in the development of compensation programs, and, more often than not, they are only passive recipients of corporate compensation programs [1]. As a result, the EECG is bound to increase. In view of this, the following hypothesis is proposed.

H1: 

Differentiation strategy has a significant positive impact on EECG.

The links between cost leadership strategy and EECG can be interpreted in two ways.

On the one hand, the essential nature of the cost leadership strategy is characterized by mass production with low marginal profit under specific quality standards, pursuing a commitment to lower product prices as a way to attract price-sensitive customers. In this case, the company is less engaged in R&D and promotional activities and, instead, gains profit by amortizing unit costs through increased sales [23]. The relative stability of a company’s production technology determines that the investment activities under the cost leadership strategy are more robust than those under the differentiation strategy. As a result, senior managers need to take significantly fewer operational and decision-making risks, and their bargaining power over compensation is weakened. Therefore, the additional risk compensation premium paid to executives is bound to be reduced, while the less intensive executive compensation incentives are precisely in line with the firm’s goal of reasonably controlling labor costs [10].

Ordinary employees, from the point of view of risk compensation, only need to efficiently complete the standardized and mechanical tasks required to improve efficiency and work specialization. During their daily work, the requirements for their technical diversity and individual innovative behavior are low, and the demand for risk compensation in employees’ pay structure is limited. From this perspective, the employees’ compensation would also be lower than that in enterprises adopting a differentiation strategy. However, such a decrease in the employees’ compensation would be rather limited. According to behavioral theory, a small wage gap can generate sustained cohesion, improve employee satisfaction, and thus improve business performance. Too large a pay gap can easily breed employee dissatisfaction, which can have a negative impact on business performance. The reason relies on the fact that employees’ compensation has downward rigidity, since reducing employee compensation will trigger extreme dissatisfaction, and negative idle behavior, or even anti-production behavior due to compensation dissatisfaction, will reduce production efficiency [24]. According to social comparison theory, employees in enterprises compare their own compensation with that of others to gain a perception of the company’s compensation policies. Competitors with cost leadership strategies should therefore be used as a benchmark for determining employee pay to ensure that it is not significantly higher or lower than the average wage level in the same industry or region. At this time, the company will determine the salary paid to employees by using competitors adopting a cost leadership strategy as a benchmark to ensure that it is not significantly higher or lower than the average compensation level in the same industry or region. Hence, while both executive compensation and employee compensation would be constrained by the cost leadership strategy, the reduced size of the former outweighs that of the latter. As a result, adopting cost leadership would potentially reduce the pay gap between executives and employees.

On the other hand, most companies that implement cost leadership strategies adopt job-based pay systems, and moderate pay gaps at different job levels can motivate employees to work harder for promotion opportunities and higher positions, thus increasing productivity. However, too high a pay gap can cause a psychological sense of unfairness among ordinary employees, and employees with lower pay levels are more psychologically sensitive to pay increases. In this case, each unit of pay increase in cost leadership strategy companies can provide a higher marginal incentive effect for such employees compared to employees with higher pay levels in differentiated companies. According to the effective wage theory, higher wages lead to higher productivity and can maintain a lower turnover rate of personnel. Consequently, a slight increase in the pay level of average employees in low-cost companies has a distinct incentive effect. At the same time, a cost leadership strategy that seeks to reduce product costs inherently requires lower compensation incentives for executives [25], as well as paying employees at levels that do not significantly exceed industry averages. If the pay gap between adjacent job levels is widened, mid- and senior-level salaries are set to be excessively high, contrary to the original principle of the cost leadership strategy. Therefore, companies need to maintain a delicate balance between setting appropriate pay gaps between job levels that are not only high enough to motivate average employees to increase productivity and effort, but also low enough to ensure that they do not hinder their strategic cost-control goals. The existing literature suggests that, compared to the differentiated firms, top executives of low-cost firms are best at maximizing the motivation of their human resources with limited compensation resources to achieve the optimal allocation of assets, equipment, and other resources [26]. All in all, it can be inferred that firms implementing cost leadership strategies tend to reduce the EECG to some extent.

H2: 

Cost leadership strategy has a significant negative impact on the EECG.

The level of marketization is used to reflect the quality of the relationship between the government and the market, the development of the non-state economy, the development of product and factor markets, market intermediary organizations, and the legal environment system [27].

First of all, the higher the marketization process, the more intense the market competition and talent competition become, which would lead to greater labor mobility. There are significant differences in average wages between regions in China. For example, the average pay gap in the eastern regions was generally higher from 2004 to 2013 than in the other regions. A favorable market environment significantly reduces the noise of the relationship between the corporate strategy and the effort level of the strategic decision-makers, and further helps strengthen the link between the sustainable competitive strategy and the executives’ contributions [28]. At this time, in order to enhance the professional competence of executives and improve their work engagement, especially proactively providing forward-looking decision-making advice on corporate competitive strategy from a long-term competitiveness perspective, companies would like to pay more attention to executives’ efforts in developing corporate strategic solutions and actively pursuing a sustainable competitive strategy, and tend to provide them with more attractive compensation contracts. Tournament theory believes that increasing EECG will provide strong incentives for executives and, ultimately, improve company performance. A well-designed pay gap can effectively motivate executives [29] and, at the same time, reduce the pressure to lose good talent.

For companies implementing differentiated strategies with a higher marketization degree, executives’ difficulties in making and implementing differentiated strategic decisions are greatly strengthened, and, at the same time, spending on retaining valuable executives increases more sharply. Therefore, marketization degree improves the positive relationship between the differentiation strategy and the EECG. For firms implementing cost leadership strategies with higher degrees of marketization, executives’ difficulties in making and implementing low-cost strategic decisions are greatly reduced, and their bargaining power over pay is significantly reduced, due to the relative wealth of professional managers with cost leadership strategy capabilities in the Manager Market. Therefore, the marketization process reinforces the negative impact of the cost leadership strategy on the EECG.

Secondly, the regions with a lower marketization degree in China are mostly located in the central and western regions, which are relatively backward in terms of social and cultural development, compared with the eastern regions. People in such regions are relatively conservative in their mindsets and severely imprisoned by the traditional concept of the income distribution of “fairness over everything”, and relatively narrow salary structures between different ranks are more likely to be accepted by employees. In addition, the degree of government intervention in the company’s operations is higher in regions with a lower marketization degree [30]. According to the theory of management power, if the compensation system arrangement of an enterprise is sufficiently transparent, and if senior executives receive compensation from the enterprise far exceeding the amount they deserve under the fair trade model, it will cause complaints from external personnel of the enterprise, and this negative reaction will bring external angry costs to senior executives. Under the influence of both government and public opinion, the “cost of external anger” directly limits the EECG within the company. At this point, to alleviate public discontent with the unequal distribution of income [31,32], firms must control the “excessive” growth of the EECG. By contrast, when the marketization process gets higher and the economy develops well, individuals will become more open-minded and inclusive, and their “psychological threshold” for the EECG to change from a reasonable level to an unfair one becomes higher, which means they are more receptive to the EECG. With the increasing marketization process, the government’s intervention in enterprises is becoming less and less.

For enterprises implementing the differentiated strategy, from the perspective of the tournament incentive effects of the pay gap, since the competitive strategies implemented by enterprises need to be related to the compensation design of positions at each level within the enterprises, the EECG tends to increase in accordance with the requirements of the market [33]. For enterprises implementing the cost leadership strategy, when the marketization process increases, it will be more conducive for such enterprises to play their strategic characteristics. Business leaders committed to cost reduction are best placed to use limited compensation resources to maximize internal motivation, achieve optimal allocation of assets, equipment, and other resources, and place greater emphasis on reducing EECG within businesses. Therefore, the marketing process significantly enhances the promotional effects of the differentiation strategy on the EECG, while, at the same time, the degree of marketing reinforces the marketization degree of the negative effects of the cost leadership strategy on the EECG.

Finally, in regions with poor marketization processes, the degree of standardization of social governance and the legal environment are relatively lagging behind, and enterprises are subject to great resistance to creating differentiated or low-cost competitive advantages; whereas, regions with high marketization processes enjoy a relatively higher degree of standardization of social governance, more abundant social and human capital, a higher degree of foreign capital introduction, and greater economic volume, which form external supportive conditions for the development of enterprises and lay a better material foundation for the implementation of both competitive strategies [34]. According to the theory of resource dependence, the survival and development of enterprises depend on obtaining resources from the external environment. Therefore, the higher the marketization degree, the higher the government’s support for the implementation of competitive strategies. In addition, the higher the marketization degree, the more the government deregulates compensation within enterprises, leading to a relatively free mechanism for determining compensation. In this case, the pricing of human capital is dominated by the market.

In view of this, in regions with a higher marketization degree, enterprises will actively adjust executive compensation contracts in order to pursue profit maximization [35]. Therefore, in firms implementing differentiated strategies, market-based compensation mechanisms play a key role in compensation incentives by increasing compensation levels for executives and widening the pay gap across different job levels within firms. In companies with a cost leadership strategy, the increased marketization degree also provides a strong guarantee that the company will be able to produce large quantities of goods with specified quality standards, which is more conducive to the formation of economies of scale, leading to a higher link between cost leadership and the EECG. Therefore, the marketization degree can strengthen the relationship between competitive strategies and the EECG.

H3: 

The marketization degree reinforces the positive relationship between the differentiation strategy and the EECG.

H4: 

The marketization degree reinforces the negative relationship between the cost leadership strategy and the EECG.

3. Methodology

3.1. Sample and Data

Taking all A-share listed manufacturing companies in the Shanghai and Shenzhen Stock Exchanges from 2008 to 2017 as the initial sample framework, the research sample was selected according to the following requirements:

(1)

The firm should not ever be punished publicly by the government authorities for any reasons over the sample years;

(2)

The firm should not be ever marked with ST, *ST, SST, or PT (ST (Special treatment) is a company that has been operating at a loss for 2 consecutive years and is subject to special treatment; *ST is a company that has been operating at a loss for 3 consecutive years and is subject to a delisting warning; SST is a company that has been operating at a loss for 2 consecutive years, requires special treatment, and has not yet completed the share reform. The first S represents that the share reform has not been completed; PT (Particular Transfer) is a company that has been operating at a loss for 3 consecutive years, and its shares will be suspended from listing. The Shanghai and Shenzhen Stock Exchange implements special transfer services for such suspended stocks, and such companies will be marked as PT companies) over the sample years;

(3)

The firm should have disclosed all the data needed according to the measures’ design mentioned in Section 3.2;

(4)

The firm should run relatively normally and smoothly, in which the following facts should not be allowed, i.e., abnormal asset-liability ratio higher than 100%, unreasonable EECG lower than zero, unexplainable performance collapse, or too high a turnover rate of top executives being more than one-third, etc. In order to eliminate the distortion effect of data outliers on the regression results, the main continuous-type variables were subjected to Winsorize’s tail reduction treatment in percentages of 1%, both top and bottom. According to these rules, the final balanced panel data consisting of a total of 3900 firm-year observations from 390 valid listed companies over the years 2008–2017 were designed.

Data on R&D expenditures were collected from the annual reports of listed companies published on CNINFO or published on the companies’ official websites. Data on the marketization degree of each region in China were collected from the “China Provincial Marketization Index Report” [27]. All the other research data were selected from the Financial Research Database of CSMAR and RESSET, the two most popular research databases in China. In order to ensure the accuracy of the data to a greater extent, the data of about 1% of the sample firms from the databases were randomly selected to compare with the corresponding data from the annual reports by hand. The comparison results confirmed the correctness of the final sample data.

3.2. Measures

a.

Measurement of explanatory variables

Following the mainstream view of the empirical studies on competitive strategies’ antecedents and consequences, competitive strategies are classified into differentiation strategy and cost leadership. There are mainly three types of competitive strategy identification methods, including cluster analysis method, factor analysis method, and DEA-based method. In measuring competitive strategies, although some literature has chosen questionnaires [36], more scholars believe that the objective financial indicators of listed companies can more accurately reflect the type of competitive strategies implemented by current companies [37,38]. Therefore, in this study, we try to adopt public financial indicators to measure competitive strategies and apply the factor analysis method to identify the type of competitive strategies.

Drawing on established literature [37,38], the three indicators of Gross Operating Margin, Overhead Rate, and R&D Intensity are used to identify and measure differentiation strategy (DIFF). The differentiation strategy reflects a firm’s comprehensive competence in integrating innovative technical capability, management capability, and marketing strength. Both technological innovation and management innovation are the keys to enhancing a firm’s differentiated competitiveness, thus requiring a firm to promote R&D innovation and put more effort into product design or advertising, which would inevitably generate high overhead and R&D costs. When an enterprise’s products or services can truly meet the specialized needs of consumers, it will reduce the price sensitivity of customers and promote their purchasing behavior. In this case, the products’ price premium exceeds the increased cost of creating uniqueness, and the enterprise thus obtains a higher Gross Profit Margin. Therefore, the three financial indicators of Gross Operating Margin, Overhead Rate, and R&D Intensity can effectively measure the degree of differentiation strategy. The higher the value of these three indicators, the higher the degree of differentiation strategy implemented by the enterprise.

Drawing on established literature [37,38], the three indicators of Fixed Asset Turnover, Total Asset Turnover, and Employee Efficiency are adopted to identify the cost leadership strategy (COST). Companies adopting the cost leadership strategy are focused on price-sensitive customers and are committed to achieving a sustainable competitive advantage by reducing raw material and labor costs, creating economies of scale, and improving learning outcomes linked to improved labor productivity. In this case, the cost per unit of production decreases with the increase in the number of products produced. Therefore, the higher the value of the above three indicators, the more likely the company is to implement a cost leadership strategy.

Using SPSS 23.0 software to test the sample adequacy of the six financial indicators of competitive strategies using the panel data selected in this study, the results indicated that the KMO statistics were 0.724, with a significant significance value of 1%, confirming its suitability for factor analysis. According to the criterion of Eigenvalue greater than 1, the cumulative variance of the original variables explained by the extraction of two public factors reaches 60.1%, indicating that the analysis result of the extraction of two factors is acceptable.

Table 1. Rotated competitive strategy component matrix ^a.

	Factors
	Diff	Cost
Gross Operating Margin	0.634
Overhead Rate	0.742
R&D Intensity	0.763
Fixed Asset Turnover		0.797
Total Assets Turnover		0.855
Employee Efficiency		0.593

^a Extraction method: Principal Component. Rotation method: An orthogonal rotation method with Kaiser Standardization.

is the rotated component matrix of the competitive strategies’ factors, which shows that the loadings of the factors after rotation can be accepted statistically. Referring to Lei and Wang [29], DIFF measures the differentiation factor, and COST measures the cost leadership factor.

b.

Measurement of explained variables

Two methods were used to measure the EECG. One is the absolute EECG (A_EECG), which is the logarithm of the difference between “the average of the executives’ compensation” and “the average of the rank-and-file employees’ compensation”; the other is the relative EECG (R_EECG), which is the ratio of the two above-mentioned variables. Here, “the average of the executives’ compensation” is the average of the compensation of the top three executives, and “the average of the rank-and-file employees’ compensation” is calculated by the equation: “(the cash compensation paid to and for employees, minus the total annual compensation of the directors, supervisors, and executives)/the number of the rank-and-file employees”. Additionally, “the number of rank-and-file employees” is equal to the difference between the total number of employees and the number of directors, supervisors, and executives in the company [4,39].

c.

Measurement of moderating variable

MARK is used to measure the marketization degree of a region, which is collected from the marketization index in “China’s Provincial Marketization Index Report”, compiled by Wang Xiaolu et al. [27]. In order to capture the potential research opportunities for the next few years, this paper adopts the time series analysis method [40] and reasonably estimates the marketization index data from 2015–2017 by index smoothing based on the existing regional marketization index during 2008–2014, reported in “China’s Provincial Marketization Index Report”.

d.

Control variables

Referring to the literature on competitive strategy, this study selects firm size (SIZE), a growth rate of operating income (GRS), leverage ratio (LEV), equity concentration (FIRS), supervisory board size (SUP), and state-owned nature of property rights (SOE) as control variables. The specific definitions of each variable are shown in

Table 2. Variables definitions.

Variables Types	Variables Names	Variables Codes	Definitions	Sources
Explanatory variables	(1) Differentiation factor	DIFF	Differentiation factor score, indicating the degree of differentiation	[37,38]; [5]
	Cost leadership factor	COST	Cost leadership factor score, indicating the degree of cost leadership
Explained variables	EECG	A_EECG	LN (average of the executives’ compensation—average of the rank-and-file employees’ compensation)	[4,39]
		R_EECG	The ratio of average of the executives’ compensation to average of the rank-and-file employees’ compensation
Moderating variable	(4) Marketization degree	MARK	China Marketization Index by Province	[27]
Control variables	Firm size	SIZE	Ln (Total assets)	[41]
	Growth rate of operating income	GRS	(Operating income of the current year—Operating income of the previous year)/Operating income of the previous year	[42]
	Leverage ratio	LEV	Total liabilities/Total assets	[42]
	Concentration of equity	FIRS	Shareholding percentage of the first largest shareholder	[4]
	Size of the supervisory board	SUP	Number of all the supervisors	[43]
	(10) Nature of property rights	SOE	Being recorded as 1 for the case of the state-owned enterprises, 0 otherwise	[4]

.

3.3. Descriptive Statistics and Correlation Analysis of Variables

The results of descriptive statistics and correlation coefficients for the main research variables are shown in

Table 3. Descriptive statistics and correlations of the main research variables.

Variables	Mean Value	Standard Deviation	1	2	3	4	5	6	7	8	9	10
1. DIFF	0.65	1.406	1
2. COST	6.22	4.037	−0.237 **	1
3. A_EECG	12.72	0.930	0.190 **	.000	1
4. MARK	7.56	1.895	0.144 **	−0.093 **	0.337 **	1
5. SIZE	21.86	1.070	−0.167 **	0.187 **	0.380 **	0.112 **	1
6. GRS	0.14	0.357	0.026	0.172 **	0.075 **	0.006	0.060 **	1
7. LEV	0.46	0.209	−0.158 **	0.092 **	−0.1780**	−0.165 **	0.279 **	032 *	1
8. FIRS	0.33	0.139	0.031	0.204 **	0.016	−0.070 **	0.1580**	0.008	0.021	1
9. SUP	3.81	1.197	−0.077 **	0.031	0.010	−0.184 **	0.229 **	−0.036 *	0.146 **	0.068**	1
10. SOE	0.47	0.499	0.038 *	0.010	−0.092 **	−0.185 **	0.154 **	−0.047 **	0.132 **	0.214 **	0.276 **	1

Note: N = 3900; ** and *, respectively, indicates the significance level of 0.01 and 0.05 (two-tailed).

. The average value of the EECG is RMB 489,000, and the average executives’ compensation is about eight times the average compensation of rank-and-file employees. The mean value of the marketization degree is 7.56. A_EECG was significantly correlated with most control variables, indicating the reasonableness of the choice of control variables. None of the correlation coefficients between the explanatory variables and the control variables exceeded 0.5, indicating that the potential multicollinearity problem among the variables is acceptable, which is conducive to regression analysis in the next sections.

3.4. Empirical Model Design

To test H1 and H2, two multiple regression models have been constructed based on OLS as follows:

$$\begin{array}{ll}A\_EEC{G}_{it}=& \alpha +{\sigma }_{1}DIF{F}_{it}+{\sigma }_{2}SIZ{E}_{it}+{\sigma }_{3}GR{S}_{it}+{\sigma }_{4}LE{V}_{it}\\ & + {\sigma }_{5}FIR{S}_{it}+{\sigma }_{6}SU{P}_{it}+{\sigma }_{7}SO{E}_{it}+\mathrm{\Sigma }Year+{\epsilon }_{it}\end{array}$$

Model (1)

$$\begin{array}{ll}A\_EEC{G}_{it}=& \alpha +{\sigma }_{1}COS{T}_{it}+{\sigma }_{2}SIZ{E}_{it}+{\sigma }_{3}GR{S}_{it}+{\sigma }_{4}LE{V}_{it}\\ & + {\sigma }_{5}FIR{S}_{it}+{\sigma }_{6}SU{P}_{it}+{\sigma }_{7}SO{E}_{it}+\mathrm{\Sigma }Year+{\epsilon }_{it}\end{array}$$

Model (2)

To test hypotheses H3 and H4, two multiple regression models, including cross terms containing the marketization degree, were constructed based on OLS as follows:

$$\begin{array}{cc}A\_EEC{G}_{it}=& \alpha +{\sigma }_{1}DIF{F}_{it}+{\sigma }_{2}MAR{K}_{it}+{\sigma }_{3}DIFF\ast MAR{K}_{it}+{\sigma }_{4}SIZ{E}_{it}+{\sigma }_{5}GR{S}_{it}\\ & + {\sigma }_{6}LE{V}_{it}+{\sigma }_{7}FIR{S}_{it}+{\sigma }_{8}SU{P}_{it}+{\sigma }_{9}SO{E}_{it}+\mathrm{\Sigma }Year+{\epsilon }_{it}\end{array}$$

Model (3)

$$\begin{array}{cc}A\_EEC{G}_{it}=& \alpha +{\sigma }_{1}COS{T}_{it}+{\sigma }_{2}MAR{K}_{it}+{\sigma }_{3}COST\ast MAR{K}_{it}+{\sigma }_{4}SIZ{E}_{it}+{\sigma }_{5}GR{S}_{it}\\ & + {\sigma }_{6}LE{V}_{it}+{\sigma }_{7}FIR{S}_{it}+{\sigma }_{8}SU{P}_{it}+{\sigma }_{9}SO{E}_{it}+\mathrm{\Sigma }Year+{\epsilon }_{it}\end{array}$$

Model (4)

4. Results

4.1. Hypotheses Tests

Sample data are used to fit Model (1) to Model (4), respectively. The results are reported in

Table 4. Test results of H1 to H4.

	Model 1	Model 2	Model 3	Model 4	Model 1 *	Model 2 *	Model 3 *	Model 4 *
(Constant)	5.272 *** (17.639)	6.088 *** (20.063)	4.625 *** (15.453)	5.108 *** (16.228)	−2.958 *** (−12.295)	−2.705 *** (−11.316)	−3.239 *** (−13.263)	−0.391 *** (−12.300)
SIZE	0.383 *** (27.245)	0.374 *** (24.142)	0.368 *** (26.555)	0.339 *** (23.951)	0.237 *** (20.953)	0.226 *** (19.988)	0.232 *** (20.507)	0.223 *** (19.732)
GRS	0.111 ** (3.130)	0.125 ** (3.390)	0.114 ** (3.261)	0.129 *** (3.570)	0.123 *** (4.292)	0.132 *** (4.535)	0.125 *** (4.383)	0.134 *** (4.617)
LEV	−1.083 *** (−17.316)	−1.158 *** (−18.105)	−1.010 *** (−16.286)	−1.059 *** (−16.710)	−0.585 *** (−11.631)	−0.610 *** (−12.108)	−0.550 *** (−10.871)	−0.568 *** (−11.228)
FIRS	0.050 (.536)	0.125 (1.288)	0.004 (0.048)	0.088 (0.927)	−0.160 ** (−2.137)	0.122 (−1.600)	−0.173 ** (−2.307)	−0.137 ** (−1.802)
SUP	−0.014 (−1.276)	−0.019 * (−1.650)	0.005 (0.471)	0.000 (0.006)	−0.007 (−0.788)	009 (−0.984)	0.000 (0.049)	−0.001 (−0.106)
SOE	−0.242 *** (−9.193)	−0.214 *** (−7.906)	−0.210 *** (−7.646)	−0.158 *** (−5.857)	−0.304 *** (−14.328)	−0.295 *** (−13.869)	−0.284 *** (−13.260)	−0.272 *** (−12.655)
DIFF	0.134 *** (14.643)		0.034 (−0.937)		0.048 *** (6.446)		0.018 (0.626)
COST		−0.009 ** (−2.657)		0.028 ** (2.379)		−0.006 ** (−2.153)		0.006 (0.599)
MARK			0.096 *** (11.966)	0.120 *** (9.551)			0.038 *** (5.794)	0.047 *** (4.704)
DIFF × MARK			0.021 *** (4.594)				0.003 ** (2.098)
COST × MARK				−0.005 ** (−3.095)				−0.001 * (−1.962)
YEAR	Control
F	118.272	100.004	116.909	100.424	48.125	45.389	45.132	43.003
R2	0.328	0.292	0.352	0.318	0.165	0.158	0.173	0.166
Adjusted R2	0.325	0.289	0.349	0.315	0.162	0.154	0.169	0.162
Sig.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Note: N = 3900; ***, ** and *, respectively, indicates the significance level of 0.01, 0.05 and 0.10.

.

Column II shows that the DIFF regression coefficient is 0.134 (p < 0.01), indicating that the differentiation strategy does have a positive impact on the EECG, i.e., the firms implementing differentiation strategies tend to widen the compensation gap between executives and rank-and file-employees. H1 holds.

Column III reports that the COST regression coefficient on A_EECG is −0.009 (p < 0.05), indicating that the cost leadership strategy has a significant negative effect on the EECG, i.e., the firms implementing the cost leadership strategy tend to reduce the pay gap between executives and rank-and file-employees. H2 holds.

Column IV reports a significantly positive regression coefficient (B = 0.021, p < 0.01) of DIFF × MARK in Model (3) on A_EECG, indicating that the marketization degree reinforces the positive link between the differentiation strategy and the EECG. H3 holds.

Column V reports a significantly negative regression coefficient (B = −0.005, p < 0.05) of COST × MARK in Model (4) on A_EECG, indicating that the marketization degree reinforces the negative link between the cost leadership strategy and the EECG. H4 holds.

4.2. Robustness Tests

To test the reliability of the empirical results, the study performs robustness tests in three aspects.

First, R_EECG is adopted to replace A_EECG as the proxy for the EECG in the four empirical models, whereby the revised models, i.e., Model (1*), Model (2*), Model (3*), and Model (4*) were constructed. Regression results reported in Column VI to Column IX of Table 4 confirm H1 to H4 again.

Second, considering the possibility that the links between the competitive strategies and the EECG may be affected by the time lag effect, the A_EECG in Model (1) to Model (4) adopts the value of year “t + 1”, while all the other variables’ values remain unchanged, i.e., they still adopt the value of “year t”. In this case, H1 to H4 still hold. Results are reported in Column II to Column V of

Table 5. Robustness tests results.

	Model 1	Model 2	Model 3	Model 4	Model 1	Model 2	Model 3	Model 4
(Constant)	4.634 *** (13.117)	5.422 *** (13.986)	4.626 *** (19.384)	4.892 *** (13.458)	4.224 *** (13.679)	4.743 *** (11.765)	4.269 *** (13.256)	4.351 *** (12.330)
SIZE	0.309 *** (22.410)	0.342 *** (24.142)	0.384 *** (23.223)	0.328 *** (23.981)	0.345 *** (19.634)	0.326 *** (19.958)	0.332 *** (20.567)	0.323*** (19.892)
GRS	0.129 ** (3.782)	0.189 *** (3.923)	0.129 ** (3.290)	0.169 *** (3.210)	0.163 *** (4.432)	0.167 *** (4.545)	0.156 *** (4.653)	0.154 *** (4.642)
LEV	−1.059 *** (−17.316)	−1.123 *** (−12.652)	−1.229 *** (−13.475)	−1.159 *** (−15.342)	−1.555 *** (−15.672)	−1.650 *** (−18.538)	−1.550 *** (−13.551)	−1.558 *** (−14.678)
FIRS	0.010 * (0.338)	0.129 (0.782)	0.009 (0.052)	0.092 (0.967)	−0.024 ** (0.568)	0.024 (0.589)	−0.129 ** (0.244)	−0.134 ** (0.232)
SUP	−0.025 * (−1.276)	−0.017 ** (−1.526)	0.017 * (0.451)	0.001 (0.016)	−0.022 * (−0.925)	019 ** (−0.984)	0.003 * (.032)	−0.005 (−0.135)
SOE	−0.261 *** (−9.193)	−0.239 *** (−8.792)	−0.229 *** (−8.273)	−0.206 *** (−7.379)	−0.245 *** (−10.234)	−0.255 *** (−9.321)	−0.264 *** (−10.445)	−0.272 *** (−12.425)
DIFF	0.117 *** (8.234)		0.097 (−1.210)		0.132 *** (7.232)		0.012 (0.626)
COST		−0.010 ** (−2.135)		0.022 ** (2.293)		−0.012 ** (−2.321)		0.003 * (0.521)
MARK			0.078 *** (12.239)	0.123 *** (9.241)			0.092 *** (5.234)	0.143 *** (4.234)
DIFF × MARK			0.028 *** (5.081)				0.005 ** (2.134)
COST × MARK				−0.023 ** (−3.269)				−0.003 ** (−2.345)
YEAR	Control
F	42.325	39.341	39.932	41.245	103.442	100.214	110.339	103.454
R2	0.146	0.133	0.156	0.143	0.235	0.238	0.273	0.266
Adjusted R2	0.143	0.130	0.152	0.139	0.231	0.234	0.269	0.262
Sig.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

***, ** and *, respectively, indicates the significance level of 0.01, 0.05 and 0.10.

.

Third, considering the special requirements of panel data characteristics on the functions of statistical analysis software, STATA 16.0 was used instead of SPSS 23.0 for hypothesis testing. Keeping all variables in Model (1) to Model (4) unchanged, regression results based on fixed effects are consistent with H1 to H4 expectations. Results are reported in Column VI to Column IX of Table 5.

4.3. Endogeneity Treatments

a.

Hausman’s endogeneity test

Considering the correlations of random error terms among equations under endogeneity conditions and the subjectivity of instrumental variable selection, using Yi Meiqun et al. [44] to test for endogeneity, a joint system of equations is built to be used for the empirical test, and the regression estimation uses the 2SLS method to improve estimation validity. For specific purposes, Model (1′), Model (2′), Model (3′), and Model (4′) are constructed.

$$DIF{F}_{i,t}={\sigma }_0+{\sigma }_{1}A\_EEC{G}_{i,t}+{\sigma }_{2}A\_EEC{G}_{i,t-1}+{\sigma }_{3}A\_EEC{G}_{i,t-2}+{\sigma }_{4}Controls+{\epsilon }_{i,t}$$

Model (1′)

$$A\_EEC{G}_{i,t}={\alpha }_0+{\alpha }_{1}DIF{F}_{i,t}+{\alpha }_{2}DIF{F}_{i,t-1}+{\alpha }_{3}DIF{F}_{i,t-2}+{\alpha }_{4}Controls+{\epsilon }_{i,t}$$

Model (2′)

$$COS{T}_{i,t}={\beta }_0+{\beta }_{1}A\_EEC{G}_{i,t}+{\beta }_{2}A\_EEC{G}_{i,t-1}+{\beta }_{3}A\_EEC{G}_{i,t-2}+{\beta }_{4}Controls+{\mu }_{i,t}$$

Model (3′)

$$A\_EEC{G}_{i,t}={\gamma }_0+{\gamma }_{1}COS{T}_{i,t}+{\gamma }_{2}COS{T}_{i,t-1}+{\gamma }_{3}COS{T}_{i,t-2}+{\gamma }_{4}Controls+{\epsilon }_{i,t}$$

Model (4′)

According to the previous theoretical analysis, different competitive strategies adopted by firms may lead to different levels of EECG, and, conversely, different levels of EECG of the firms may also affect the choice of different competitive strategies. In this case, there may be an endogenous relationship between the competitive strategies and the EECG that affects each of them, which, in turn, would lead to the endogeneity bias of OLS regression results adopting the ordinary single equation. Therefore, in this paper, we first test the endogeneity of the two variables, that is, we test the simultaneity of the set of equations. The results are shown in

Table 6. Hausman test results.

Variables	Coefficient	Standard Deviation	t-Value	p-Value
e1	−31.981	0.230	−38.95	0.000
e2	15.323	0.142	107.93	0.000

. Symbol e₁ is the residuals obtained from DIFF’s OLS regression on all exogenous variables in Model (1′). Regression was performed by introducing e₁ into Model (2′), reaching a regression coefficient of −31.9811. Symbol e₂ is the residuals obtained from COST OLS regression on all exogenous variables in Model (3′). Regression was performed by introducing e₂ into Model (4′), reaching a regression coefficient of 15.3232. Both coefficients are significantly different from zero at the 1% level, indicating that there is an endogenous relationship between the competitive strategy and the EECG.

b.

The 2SLS estimation results of the simultaneous equations

First, in order to solve the H1 endogeneity problem, the 2SLS estimation is performed for the full sample by applying the simultaneous equations of Model (1′) and Model (2′), and the results are presented in Column III of

Table 7. 2SLS estimation results of the simultaneous equations.

Column I	Column II	Column III	Column IV	Column V	Column VI	Column VII	Column VIII	Column IX
Model	Model (1)	Model (1′) Model (2′)	Model (1′) Model (2′)	Model (1′) Model (2′)	Model (2)	Model (3′) Model (4′)	Model (3′) Model (4′)	Model (3′) Model (4′)
Method	OLS	2SLS	2SLS	2SLS	OLS	2SLS	2SLS	2SLS
Sample	Full sample	Full sample	H_MARK sub-sample	L_MARK sub-sample	Full sample	Full sample	H_MARK sub-sample	L_MARK sub-sample
(Constant)	5.272 *** (17.639)	4.225 *** (14.561)	5.005 *** (13.165)	4.145 *** (9.439)	6.088 *** (20.063)	4.810 *** (16.168)	5.399 *** (13.683)	4.953 *** (11.357)
DIFF	0.134 *** (14.543)	0.165 *** (15.491)	0.166 *** (12.369)	0.124 *** (7.143)
LOW					−0.009 ** (−2.657)	−0.014 *** (−3.606)	−0.016 *** (−3.145)	0.004 (−0.685)
MARK	0.096 *** (11.966)				0.120 *** (9.551)
DIFF × MARK	0.021 *** (4.594)
LOW × MARK					−0.005 ** (−3.095)
CONTROLS	YES	YES	YES	YES	YES	YES	YES	YES
YEAR F R ² Adjusted R ² Sig. N	YES 118.272 0.211 0.325 0.000 3900	YES 177.189 0.285 0.283 0.000 3900	YES 85.425 0.251 0.248 0.000 2042	YES 73.020 0.279 0.275 0.000 1858	YES 100.004 0.292 0.289 0.000 3900	YES 134.761 0.233 0.231 0.000 3900	YES 60.461 0.192 0.189 0.000 2042	YES 62.864 0.250 0.246 0.000 1858

*** and **, respectively, indicates the significance level of 0.01 and 0.10.

. Column III shows that the normalized DIFF coefficient relative to A_EECG when considering the endogeneity problem is significantly positive at the 1% significance level, i.e., the differentiation strategy still has a significantly positive impact on the EECG. H1 still holds. To address the H2 endogeneity problem, a 2SLS estimation is performed with the full sample by applying the simultaneous equations of Model (3′) and Model (4′), and the results are shown in Column VII of Table 7, where the standard COST coefficient relative to A_EECG is significantly negative at 1% when considering the endogeneity problem, i.e., the cost leadership strategy still has a significant negative impact on the EECG. H2 holds.

Secondly, in order to solve the problem of H3 endogeneity, the sample is divided into a sub-sample with a high marketization degree (H_MARK) and a sub-sample with a low marketization degree (L_MARK) at the mean value of MARK in the whole sample. The 2SLS estimation for both sub-samples is performed by applying the simultaneous equations of Model (1′) and Model (2′), and the results are presented in Columns IV and V of Table 7, respectively. Columns IV and V show that, when endogeneity is considered, the positive effect of differentiation strategy on EECG is significantly higher in the H_MARK sub-sample than in the L_MARK sub-sample. By comparing the results in Columns IV and V, the existence of a moderating effect of marketization degree on the relationship between the differentiation strategy and the EECG can be confirmed. H3 holds when endogeneity is considered.

To address H4 endogeneity, the 2SLS estimation for both sub-samples is performed by applying the simultaneous equations of Model (3′) and Model (4′), and the results are presented in Columns VIII and IX of Table 7, respectively. Column VIII shows that the COST normalized coefficient relative to A_EECG is significantly positive at the 1% significance level in the H_MARK sub-sample when considering endogeneity. The negative effect of the cost leadership strategy on the EECG was higher in the H_MARK sub-sample compared to the full sample. Column IX shows that the standard cost estimate coefficient on the EECG is insignificant at the 10% significance level in the L_MARK sub-sample when endogeneity issues are considered. By comparing the results in columns VIII and IX, the moderating effect of marketization degree on the relationship between the cost leadership strategy and the EECG was confirmed. H4 holds when endogeneity is considered.

5. Further Exploration

a.

Impact of the fit between the competitive strategy and the EECG on firm performance

Since the 1980s, Gmoez Mejia, an expert in human resource management in the United States, has introduced the concept of “matching” into the field of compensation for the first time, arguing that the compensation strategy of a company should change along with changes in the strategic environment and corporate strategy. Matching the competitive strategy with the compensation strategy is conducive to improving the company’s innovation capacity, thus enabling the company to capture profits in competition and achieve a sustainable competitive advantage. Based on the above empirical results of this paper, the competitive strategy may affect the EECG.

Therefore, it is more relevant for enterprise development to consider in-depth the performance consequences of matching strategic choices for sustainable competition with EECG. Tournament theory and behavioral theory illustrate the business performance consequences of EECG from two opposing perspectives. Tournament theory believes that broadening the EECG can lead to healthy competition, motivate employees to work hard, and thus improve corporate performance [45]; in contrast, the behavioral theory believes that a too large EECG can trigger a sense of unfairness among employees [43], bring vicious jealousy, and be detrimental to team cohesion and firm performance [46].

To explore the impact of matching the competitive strategy and the EECG on firm performance, we divide the whole sample into a strong differentiation sub-sample (S_DIFF) and a weak differentiation sub-sample (W_DIFF), by taking the mean value of DIFF as the dividing point, and then dividing the whole sample into a strong cost leadership sub-sample (S_COST) and a weak cost leadership sub-sample (W_COST) by taking the mean value of COST as the dividing point. The return on total assets (ROA_t+1) in period t + 1 is used as the dependent variable, and the primary term of the EECG, the squared term of the EECG, and the selected control variables are included in the same regression model (Model (5), Model (6)). To test the effect of EECG on firm performance under different competitive strategy strengths, the grouped regression results are shown in

Table 8. Results of further exploration (ROA_t+1 as the explained variable).

	Sub-Samples of Competitive Strategy				Sub-Samples of EECG			Moderating Role of Female Executives
	S_DIFF Sub-Sample	W_DIFF Sub-Sample	S_COST Sub-Sample	W_COST Sub-Sample	>81% Quantile Sub-Sample	>83% Quantile Sub-Sample	>91% Quantile Sub-Sample	Full Sample
	Model (5)		Model (6)		Model (7)			Model (5)	Model (6)
(Constant)	0.718 *** (4.528)	0.921 *** (4.584)	0.406 * (1.899)	0.799 *** (5.549)	0.107 (−1.268)	0.040 (−0.430)	0.149 (1.011)	0.893 *** (5.218)	0.623 *** (5.232)
DIFF			0.003 *** (3.503)	0.004 ** (2.011)					0.003 *** (4.322)
COST	0.004 *** (9.775)	0.002 *** (4.185)						0.003 *** (7.392)
DIFF × RFEMALE									−0.004 *** (−2.345)
COST × RFEMALE								−0.003 *** (−3.291)
A_EECG	−0.100 *** (−4.086)	−0.137 *** (−4.418)	−0.071 ** (−2.197)	−0.107 *** (−4.781)	0.011 ** (2.018)	0.007 (1.188)	−0.007 (−0.717)	−0.134 *** (−4.220)	−0.132 *** (−4.409)
A_EECG2	0.005 *** (4.665)	0.006 *** (4.886)	0.003 ** (2.554)	0.005 *** (5.507)				0.005 *** (4.635)	0.004 *** (2.345)
CONTROLS	YES	YES	YES	YES	YES	YES	YES	YES	YES
YEAR	YES	YES	YES	YES	YES	YES	YES	YES	YES
N	2018	1492	1229	2281	668	600	321	3900	3900
F	46.512	21.951	63.172	29.926	36.533	31.479	20.289	106.512	102.512
R2	0.156	0.106	0.293	0.095	0.249	0.242	0.279	0.339	0.319
Adjusted R2	0.153	0.101	0.288	0.092	0.242	0.234	0.266	0.334	0.316
Sig.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Note: ***, ** and * indicate that the responding regression coefficient is significant at the 0.01, 0.05, and 0.10 levels, respectively.

.

$$RO{A}_{i,t+1}={\beta }_0+{\beta }_{1}COS{T}_{i,t}+{\beta }_{2}A\_EEC{G}_{i,t}+{\beta }_{3}A\_EEC{G}_{i,t}{}^2+{\beta }_{4}Controls+\mathrm{\sum }Year+{\epsilon }_{i,t}$$

Model (5)

$$RO{A}_{i,t+1}={\beta }_0+{\beta }_{1}DIF{F}_{i,t}+{\beta }_{2}A\_EEC{G}_{i,t}+{\beta }_{3}A\_EEC{G}_{i,t}{}^2+{\beta }_{4}Controls+\mathrm{\sum }Year+{\epsilon }_{i,t}$$

Model (6)

Analyzing Columns II-V of Table 8, the A_EECG coefficient was significantly negative at 1% and the A_EECG² coefficient was significantly positive at 1% in the S_DIFF sub-sample. It can be argued that when firms implement a highly differentiated strategy, the U-shaped relationship between the EECG and corporate performance is evident. Similarly, in the W_DIFF sub-sample, the S_COST sub-sample, and the W_COST sub-sample, the positive U-shaped relationships between the EECG and firm performance remain significant. It can be seen that when the EECG is very small, behavioral theory dominates. At this time, employees who are accustomed to “extreme equality” will be psychologically uncomfortable or even show “vicious jealousy” when the EECG increases, which will have a negative impact on corporate performance, while, when the EECG is larger, tournament theory dominates [47]. At this time, employees who have adapted to the principle of “pay for performance or merit” will have more “benign envy” and positive motivation when they face an appropriate increase in the EECG, which will ultimately promote the improvement of corporate performance.

Based on the above regression results, a comparative analysis of the positive U-shaped effect of the EECG on future firm performance under different competitive strategy intensities is proposed, as shown in Figure 1 and Figure 2. The figures show that the symmetry of the U-shaped curve symmetry axis under the weak cost leadership strategy is to the left of the U-shaped curve symmetry axis under the weaker differentiation strategy, while the symmetry axis of the U-shaped curve under the weak cost leadership strategy lies to the left of the symmetry axis of the U-shaped curve under the strong cost leadership strategy. In other words, firms with a strong differentiation strategy are able to exploit the tournament incentive effect of the EECG more fully than firms with a weak differentiation strategy, while firms with a strong cost leadership strategy are relatively less able to exploit the tournament incentive effect of the EECG than firms with a weak cost leadership strategy. However, overall results show that both differentiation and cost leadership strategies can effectively improve firm performance when matched with a higher EECG within a reasonable range.

For firms on the right side of the symmetry axis of the U-shaped curve in Figure 1 and Figure 2, the larger the EECG, the better the future firm performance will be. Following this logic, the EECG appears to be infinitely expandable, which is obviously questionable. In view of this, the sample is sorted according to the EECG from the lowest to the highest, starting from the 75% quantile of the EECG, and using two percentage points as incremental units to construct the “>75% quantile sub-sample”, “>77% quantile sub-sample”, “>79% quantile sub-sample”, …, and “>99% quantile sub-sample”, etc. A series of regression results are shown in Figure 3. Columns VI to VIII of Table 5 report the typical regression results of Model (7), i.e., “>81% quantile sub-sample”, “>83% quantile sub-sample”, and “>91% quantile sub-sample”. The results show that the overall effect of the EECG on firm performance has shifted from positive to negative if the excessive range of the EECG is too high.

$$RO{A}_{i,t+1}={\beta }_0+{\beta }_{1}A\_EEC{G}_{i,t}+{\beta }_{2}Controls+\sum Y\mathrm{ear}+{\epsilon }_{i,t}$$

Model (7)

To be specific, the EECG had a significant positive effect on firm performance (p < 0.05) at and before the 81% quantification of the EECG; the positive effect of the EECG on firm performance at the 83% to 89% quantification began to be insignificant at the 10% level; and the effect of the EECG on firm performance after the 91% quantification began to show a trend of negative effect. This indicates that the marginal contribution of the EECG decreases on the right side of the U-shaped curve. The positive effect of higher EECG (83–89%) on business performance has gradually diminished, and extreme EECG (≥91%) shows a tendency to reduce business performance. Therefore, it is reasonable to infer that it is not wise to enhance business performance by infinitely widening the pay gap, which will only lead to more losses than gains.

b.

The moderating role of female executives in influencing the link between competitive strategy and firm performance

Introducing the ratio of the number of female executives to the number of all executives (RFEMALE) and its cross-item with DIFF (RFEMALE*DIFF) into Model (5), Model (5′) was built. Similarly, with the introduction of RFEMALE and its COST cross-item (RFEMALE*COST) into Model (6), Model (6′) was constructed. The regression results of Model (5′) show that the RFEMALE*DIFF coefficient on ROA_t+1 is significantly negative, indicating that the degree of participation of female executives in corporate governance would harm the performance consequences of the differentiation strategy. The regression results of Model (6′) show that the RFEMALE*COST coefficient on ROA_t+1 is significantly negative, indicating that the degree of participation of female executives in corporate governance would improve the performance consequences of the cost leadership strategy. Results are reported in Column VI to Column X of Table 8.

6. Discussion and Conclusions

6.1. Conclusions

In response to the latest call for research on strategic human resource management, the impact of strategic choice of sustainable competition on EECG is explored. This paper examines the relationship between the competitive strategy and the EECG using balanced panel data of A-share listed manufacturing companies in Shanghai and Shenzhen Stock Exchange over 2008–2017 as the research sample, and further investigates the moderating role of the marketization degree in the relationship between the two by applying Factor Analysis, Fixed Effects Regression, and Multiple Linear Regression Analysis based on OLS. The empirical results confirmed that the differentiation strategy has a facilitating effect on the EECG, and the marketization degree strengthens the facilitating effect; the cost leadership strategy has a restraining effect on the EECG, and the marketization degree also strengthens the restraining effect.

Further findings suggest that both differentiation and cost leadership strategies need to be matched with a larger EECG to facilitate performance improvement. Therefore, for the implementation of the differentiation strategy, companies should systematically expand the EECG, continuously giving full play to their competitive advantage of differentiation and increasing the degree of differentiation strategy to improve corporate performance. For enterprises aiming to be cost leaders, since the cost leadership strategy itself tends to inhibit the EECG, they should pay particular attention to how they can overcome the inhibitory effect of the cost leadership strategy on the EECG.

6.2. Theoretical Contributions

The potential theoretical contributions of this study include at least two aspects: firstly, it expands the research on the formation mechanism of the EECG, enriches the research on the consequences of the sustainable competitive strategy, and clarifies the influence mechanisms of the differentiation strategy and the cost leadership strategy on the EECG; secondly, it confirms the contingent nature of the relationship between the competitive strategy and the EECG, i.e., the moderating effect of the marketization degree. It provides a theoretical direction for the government to continuously promote economic system reform and improve economic efficiency.

6.3. Managerial Implications

On the one hand, from the government’s perspective, it should continue to deepen the reform of the economic system, make efforts to promote the marketization process in China, use market forces to guide compensation incentives for executives, and promote the EECG of listed companies to maintain a relatively high, but reasonable, level. The government needs to reduce its intervention in the market and businesses need to improve the marketization process in each region as a whole and play the role of effective market regulation. From the company’s perspective, a clear competitive strategy and the matching of the EECG will bring the company rich profits. In contemporary society, to achieve sustainable development, enterprises face complex and all-round competition, which is not only constrained by hardware such as resources, environment, facilities, and equipment, but also by software such as policies, regulations, and management, etc. It is crucial to establish the right development goals and choose the right competitive strategy. Therefore, enterprises should clarify their strategic direction, spare no effort to build a platform to create a competitive strategy suitable for their development, and give full play to their strategic advantages so that they can take their place in fierce market competition, which can enable them to gain stable monopoly power in competition and thus maintain a high level of profitability.

On the other hand, extreme events concerning the excessive incentive of executive compensation in recent years, such as the frequent reports about “sky-high salaries” of Lenovo, LeTV, Shuanghui, and other listed companies, should be treated differently. The above significant pay gaps are abnormal and belong to corporate governance events that are not in line with the law of economic development and the orderly development of society. The “sky-high salaries” have been excessively interpreted and even maliciously speculated by the public from all walks of life, and have been subject to controversy and continuous fermentation, forming a “psychological pay gap” in the public. The public condemnation of “overpriced compensation” has a demonstration effect that far exceeds the harm caused by the incident itself. A series of abnormal wage events have triggered and amplified people’s interpretation of the unfair distribution of labor income. Through the social communication mechanism of “generalization of individual extreme events”, the very few events of “sky-high wages” in practice have distorted the public’s psychological perception of the objective wage gap and seriously damaged harmonious social–labor relations. As a result, the micro-corporate behavior of the ever-increasingly widening EECG has gradually accumulated into an insurmountable pay gap in the public psyche, an unreasonable macro-social phenomenon. Therefore, for companies with the highest EECG, it is no longer effective to improve business performance by broadening the EECG, and it may even produce the opposite result. For companies where the EECG is in the normal range, an increase in the EECG can still contribute to performance improvement.

6.4. Limitations and Prospects

There are several limitations to this paper. Firstly, limited by time and effort, only the data of listed A-share manufacturing companies in China from 2008 to 2017 are selected as the sample. Therefore, the scope of the study is relatively narrow, while future research should include data from listed companies over a longer period of time, and also attempt to collect data from non-listed companies in a wider range to improve the empirical basis of this study. Secondly, limited by the availability of objective data, the lack of investigation and analysis of the subjective data, such as the psychological processes and psychological variables, creates speculation on the influence mechanism of the competitive strategy of the EECG’s lack of direct data verification. Therefore, future research should attempt to directly collect psychological perceptual data from relevant subjects such as CEOs, executives, and shareholders in compensation decision-making processes to accurately analyze the roles and motivations of each party in such processes. Thirdly, due to environmental differences, the marketization degree varies significantly from region to region in China. Regional controls should therefore be increased in future studies. Fourthly, the pay gap within an enterprise is a multidimensional concept, and the EECG cannot reflect its full picture. Future research can also include other dimensions such as the executives’ pay gap, executives’ gender pay gap, and the inter-employee pay gap, and conduct comparative studies on them. Finally, while the EECG can trigger a range of agency issues, it can also guide and retain core talent and stimulate enthusiasm at all levels of work. Therefore, future research could attempt to pay particular attention to companies with large executive pay gaps (the top 10%), assess in real-time whether excessive compensation incentives are detrimental to shareholders and other stakeholders, and prevent executives from turning corporate strategies into personal profit-seeking tools.