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Journal of Geographical Sciences >

2024 , Vol. 34 >Issue 5: 835 - 854

DOI: https://doi.org/10.1007/s11442-024-2229-8

Research Articles

The coupling coordination of social and economic upgrading in China: Evolution, regional disparities and influencing factors

  • HUANG Gengzhi , 1, 2 ,
  • LIU Shuyi 1 ,
  • CAI Bowei 1 ,
  • WANG Bo 1, 2
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  • 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
  • 2. Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, Guangdong, China

Huang Gengzhi, PhD and Professor, specialized in urban and social geographies. E-mail:

Received date: 2023-08-15

  Accepted date: 2024-02-07

  Online published: 2024-05-31

Supported by

National Natural Science Foundation of China(42122007)

National Natural Science Foundation of China(41930646)

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Abstract

Social upgrading does not inherently follow economic upgrading; rather, they present a complex interplay. This paper, focusing on China, utilizes the coupling coordination degree and a panel regression model to shed light on the intricate interaction between social upgrading and economic upgrading. It is found that the coupling coordination degree of social and economic upgrading in China has improved from 0.33 to 0.49 since the mid-1990s, undergoing a shift from a stage of slight imbalance to low-level coordination. However, significant regional disparities are present in terms of economic upgrading, social upgrading, and their coupling coordination degree. Developed areas exhibit a higher degree of coupling coordination compared to less developed regions, indicating a connection between the coupling coordination degree and the level of economic growth. Economic globalization, public governance, and the legal environment positively impact the coupling coordination between social and economic upgrading, while economic privatization and corporate violations of law exert negative effects. The paper concludes with policy discussions for enhancing the coupling coordination between social and economic upgrading.

Key words： coupling coordination; economic upgrading; globalization; regional disparities; social upgrading

Cite this article

HUANG Gengzhi , LIU Shuyi , CAI Bowei , WANG Bo . The coupling coordination of social and economic upgrading in China: Evolution, regional disparities and influencing factors[J]. Journal of Geographical Sciences, 2024 , 34(5) : 835 -854 . DOI: 10.1007/s11442-024-2229-8

1 Introduction

Economic upgrading is generally identified as a movement of firms to higher value-added activities in global production networks (Gereffi, 2005). Specifically, economic upgrading is a process in which firms boost their competitiveness and innovation to increase their added value, reap more profits, and capture a larger market share, ultimately leading to elevated economic efficiency (Gereffi and Lee, 2016). When examined from a national or regional angle, economic upgrading is considered a strategy to achieve higher benefits within the global production network (Gereffi, 1999). Given China’s transition to a “new normal” economy and its focus on high-quality development, the pursuit of high-value upgrading has emerged as a strategic priority, becoming a key area of interest in the study of economic geography.
For a long time, due to the assumption that economic upgrading will naturally lead to social upgrading, a large body of studies in the field of global value chains (GVCs) and global production networks (GPNs) have been focused on economic upgrading while neglecting social upgrading (Barrientos et al., 2011; Barrientos et al., 2016). Recently, attention to workers’ welfare and employment quality has surged (Coe, 2013; Huang and Zhou, 2021a), and the notion of social upgrading has come to the fore. In contrast to the economic upgrading pertaining to the capital dimension, the concept of social upgrading sheds light on the labor dimension of globalized economic development and is concerned about the rights and entitlements of workers as social actors (Barrientos et al., 2011). Framed by the ILO’s Decent Work Agenda, social upgrading is characterized by workers elevating their social standing and worth in terms of enhanced job quality, higher income, robust social security, and increased social rights (Milberg and Winkler, 2011). Differing from the concepts like social integration and class mobility in sociology, social upgrading places an emphasis on the process of the improvement in the well-being of workers from their participation in global production networks/global value chains (Huang and Zhou, 2021b). In other words, social upgrading connotes the impacts of economic globalization on the quality of labor’s work and life. It can be understood as a conceptual extension of economic upgrading to the labor dimension. Traditional narratives often view economic upgrading as a necessary precondition for social upgrading, suggesting that the latter only becomes feasible once the former has reached a certain threshold and is typically seen as a natural corollary. However, this perspective tends to oversimplify the complex interplay between economic upgrading and social upgrading (Lee and Gereffi, 2015). In reality, their relationship is not merely a straightforward cause-and-effect sequence (Bernhardt and Milberg, 2011; Mohammad and Mark, 2019).
The influence of economic upgrading on social upgrading is shaped by local contextual factors and individual characteristics of the labor force. On a national level, it is observed that developing countries, unlike their developed peers, are more susceptible to a negative reciprocal relationship between economic and social upgrading, thus making social and economic coordinated development a considerable challenge (Bernhardt and Pollak, 2016; Mohammad and Mark, 2019). On a more localized level, scholars suggest that social upgrading cannot be entirely predicated upon economic elements. The local social systems and public governance play a critical role in shaping the transformation process in which economic upgrading leads to social upgrading (Milberg and Winkler, 2011; Rossi, 2013; Gereffi and Lee, 2016). Empirical evidence from Mexico illustrates that the impact of economic upgrading on social upgrading is intimately intertwined with the local social fabric (Salido and Bellhouse, 2016). Studies focusing on textile workers also underscore that the transformation from economic to social upgrading is influenced by a complex interplay of market forces, public governance, and labor unions (Lohmeyer et al., 2022).
From the perspective of worker-specific traits, numerous factors such as gender (Sproll, 2022), worker status (Butollo, 2013), a worker’s position in the value chain (Lee and Gereffi, 2015), and the characteristics of the industry where workers work (Bernhardt and Pollak, 2016) can shape the influence of economic upgrading on social upgrading. Further, notably, within a single region, the outcomes of social upgrading resulting from different types of economic upgrading can vary. For example, research suggests that the social upgrading effects ushered in by the service sector boom in Shenzhen are more far-reaching than the reindustrialization of Foshan (Wang et al., 2020). Beyond these structural elements, sporadic factors such as the COVID-19 pandemic (Anner, 2022) can also sway the relationship between the two. Consequently, while economic upgrading is a necessary condition for social upgrading, it is not a guarantee. The dynamic relationship between the two is subject to multiple influences and characterized by variability.
Viewed from the lens of worker agency, social upgrading can have a reverse impact on economic upgrading. Workers have the power to use tools such as strikes and protests to strengthen their bargaining rights. Thus, they can enhance their work environment and push for additional benefits, driving the process of social upgrading (Ahmed and Nathan, 2014). However, this does not come without potential compromises. Firms may need to make concessions to their workers or unions, which could impact their competitive edge in the global market, possibly leading to economic downgrading (Mulubiran and Karlsen, 2023). This pattern of simultaneous social upgrading and economic downgrading has been seen in studies of the textile industry in Mexico (Salido and Bellhouse, 2016). Nonetheless, social upgrading can yield positive outcomes. It can enhance human capital and work efficiency, which, in turn, can enhance a company’s competitiveness and ability to innovate (Gambardella et al., 2015), thereby leading to economic upgrading. Therefore, social upgrading can catalyze and inhibit economic upgrading. Although economic and social upgrading inherently comes from economic growth, the relationship between them is complex, showing a unique coupling coordination (Milberg and Winkler, 2013).
An intriguing question that has captured the attention of academics is the investigation of the factors that shape how economic upgrading fosters social upgrading (Huang and Zhou, 2021b). Current literature sheds light on two pivotal elements in this dynamic—the role of economic globalization and the influence of local public governance. Notably, foreign direct investment can act as a catalyst, encouraging both economic and social upgrading in tandem (Reinecke and Posthuma, 2019; Danish and Khattak, 2020). There is also evidence to suggest that state intervention and regulatory practices can play a productive role in harmonizing the progression of both types of upgrading (Wang et al., 2022b). More recently, studies have considered both economic globalization and public governance, revealing the bridging role governance plays in stimulating the process economic upgrading brings about social upgrading in a globalized context (Zhou and Huang, 2021).
To sum up, much of the research to date has been predicated on a one-way cause-and-effect model, with a bias toward the impact of economic upgrading on social upgrading while overlooking the potential for a two-way street. This approach tends to embrace a static perspective, analyzing the influence of economic upgrading on social upgrading, but often lacks a dynamic viewpoint to explore their interplay fully. The relationship between economic and social upgrading is densely interconnected. They can demonstrate either a harmonious relationship or a discordant or imbalanced relationship with opposing trajectories. The challenge lies in fostering coupling coordination between these two systems, ensuring that as the economic system heightens its innovative prowess and competitiveness, the quality of employment and protection of workers’ rights are simultaneously enhanced. This improvement can, in turn, spur labor productivity and augment business competitiveness, further propelling economic upgrading. To unravel this complex relationship, this study introduces an approach of coupling coordination degree. It delves into an analysis of the spatiotemporal patterns in the interplay between social and economic upgrading in China from 1996 to 2020. Leveraging a panel regression model, the study aims to shed light on the factors influencing this interactive relationship. By providing empirically grounded insights from China, this study broadens the comprehension of the intricate dance between economic and social upgrading, laying a theoretical groundwork for fostering the synergistic development of the economy and society.

2 Methods and data

2.1 Measurement of economic and social upgrading

Economic upgrading, often referred to as “industrial upgrading” or “upgrading”, is defined as the process of improving the innovation and competitiveness of enterprises and achieving higher value-added gains. It is understood as four types of upgrading, namely, process upgrading aimed at improving the efficiency of production processes, product upgrading with the invention of advanced products, functional upgrading towards higher value-added production activities, and chain upgrading towards more complex production chains with new industrial technologies (Milberg and Winkler, 2011). These micro-level (firm-level) activities of economic upgrading will bring about the results of economic growth, structural changes and quality improvement at the macro level (the provincial or national level). Economic upgrading is therefore also measured in various ways and through proxy variables at both national and regional levels (Milberg and Winkler, 2011). Based on the availability of economic data from the National Bureau of Statistics, this paper measures economic upgrading at the regional/provincial level by focusing on four dimensions: economic structure, economic efficiency, economic innovation, and economic growth (Table 1). Hence, economic upgrading at the provincial level is defined in the paper as a move of the regional economy to a higher value-added economic structure, to enhance labor productivity and capability of industrial innovation, and to improve the per-capita output of economic growth.
Table 1 Measurement of economic upgrading
Primary
indicators		 Secondary
indicators		 Proxy variables Influence direction Weight
Economic structure Change rate Lilien coefficient + 0.1006
Industrial upgrading Industrial structure sophistication index + 0.0809
(Value added of tertiary industry/value added of secondary industry)
Economic efficiency Outcome conversion Profits from industrial enterprises above designated size/main business income + 0.0501
Quality benefit Social labor productivity + 0.1123
Economic innovation R&D investment R&D expenditure/GDP + 0.1088
R&D outputs Granted invention patent applications/R&D expenditure + 0.1003
Innovation
environment		 Per capita technology market transaction value + 0.2847
Innovation
efficiency		 New product sales income from industrial enterprises above
designated size/main business income		 + 0.1154
Economic growth Output growth Per capita GDP growth + 0.0470
The economic structure indicator attempts to capture the pace of change and the depth of transition in a region’s economic industry structure. For this purpose, the study employed the Lilien coefficient (Ma and Hao, 2017) and an index that represents the sophistication of the industrial structure. The economic efficiency indicator reflects the extent to which economic upgrading translates into tangible outcomes. It is quantified by using two proxy variables: the ratio of profits from industrial enterprises above designated size to their main business income, the social labor productivity rate. The economic innovation indicator gauges the level of technological advances in economic production and how they bolster production efficiency or enhance product value. This is quantified using four proxy variables: the proportion of R&D expenditure relative to GDP, the ratio of granted invention patent applications to R&D expenditure, the per capita technology market transaction value, and the proportion of new product sales income from industrial enterprises above designated size to their main business income. The economic growth indicator reflects a region’s overall economic development, using per capita GDP growth as the proxy variable.
Social upgrading is defined as the process in which the basic rights of workers are guaranteed and the quality of their employment is improved. It is a concept that extends the economic upgrading of enterprises to the scope of labor force and describes the degree and process of improvement in workers' benefits in participating in global economic production. The measurement of social upgrading encompasses aspects of employment, standards and rights at work, social protection, and social dialogue (Barrientos et al., 2011). For the purpose of quantified research, social upgrading can be decomposed into four dimensions (Milberg and Winkler, 2011): 1) labor employment, indicating adequate employment opportunities and adequate remuneration, as well as a safe and healthy working environment; 2) social security, referring to job security and the guarantee to meet the urgent needs of workers’ lives; 3) basic rights, meaning no child labor, no forced labor, no poor working conditions, no discrimination and freedom of association; and 4) social dialogue, referring to a system for social and economic organizations to cooperate with the government to jointly resolve the conflict of interests in an industrial relationship, including collective bargain economic democracy and participation in the formulation and implementation of labor policies. Hence, social upgrading at the regional level is defined in this paper as the improvement in workers’ employment quality, social security, basic rights at work, and their rights to collective bargaining. Based on these above four dimensions, a comprehensive measurement system consisting of 4 first-level indicators and 10 second-level indicators is established to measure the social upgrading of 31 provinces/municipalities/autonomous regions (hereinafter referred to as provincial-level regions, excluding Hong Kong and Macao special administrative regions, and Taiwan) in China (Table 2).
Table 2 Measurement of social upgrading
Primary
indicators		 Secondary indicators Proxy variables Influence
direction		 Weight
Labor
employment		 Job opportunities Current job openings registered by businesses + 0.1419
Unemployment rate Unemployment rate - 0.0449
Remunerated employment Average salary of urban employees + 0.1253
Social security Social security Medical insurance coverage rate + 0.1367
Basic rights Access to education Proportion of employed individuals with a college degree or above + 0.0954
Gender equality Proportion of female workers + 0.0787
Union participation Ratio of union membership to total employment + 0.0568
Social dialogue Negotiation and consultation Success rate of labor dispute arbitrations + 0.0580
Union role Success rate of dispute mediations involving unions + 0.1287
Economic democracy Number of implemented rational suggestions + 0.1335
As shown in Table 2, labor employment measures the enhancement of job opportunities and wage growth. Job opportunities were measured in this study with two proxy variables: the count of job openings registered by business units during the current term and the unemployment rate. The average salary of urban employees serves as the proxy for remunerated employment. Social security signifies the degree of protection laborers receive in society, which is measured by the medical insurance coverage rate. Basic rights underline the assurance of essential rights that laborers should have, both as part of the labor force and as social participants. This includes three metrics: access to education, gender equality, and union participation. Social dialogue refers to the structures and channels through which laborers can equitably and democratically communicate and negotiate with employers, governments, or other stakeholders. It is measured with three indicators: negotiation and consultation, union roles, and economic democracy.
To determine the weight of these indicators, this study used a combination of the entropy-weight and CRITIC weighting methods. The entropy-weight method calculates the entropy value of each indicator, assessing its diversity and significance and determining its weight accordingly. The CRITIC weighting method measures an indicator based on its comparative strength and its conflict with other indicators (Chen et al., 2022). This method’s advantage lies in considering the correlation between indicators, compensating for the limitations of the entropy-weight method. However, it does not account for the discreteness between indicators, which is a weakness balanced by the entropy-weight method. This study determined the weight of the indicators by referencing existing research (Wu et al., 2019). After nondimensionalizing the original data using the range method, this study calculated the CRITIC weight (wj1) and the entropy weight (wj2) for the indicator j. Assuming equal importance of the two weighting methods, the combined weight (wj) can be computed as follows:
$\begin{matrix} {{w}_{j}}=0.5{{w}_{j1}}+0.5{{w}_{j2}} \\\end{matrix}$
Finally, the aggregate of the weights provides the comprehensive index for each system:
$U_{1}=\sum_{j=0}^{n} w_{j} X_{\mathrm{i} j}^{\prime}, U_{2}=\sum_{j=0}^{n} w_{j} X_{\mathrm{i} j}^{\prime}$
where $X_{\mathrm{ij}}^{\prime}$ is the nondimensionalized variable, i represents a specific year and region, j represents a specific indicator, U1 stands for economic upgrading, U2 stands for social upgrading, and n signifies the number of indicators.

2.2 Research methods

2.2.1 Model of coupling coordination degree

This study utilized the model of coupling coordination degree to examine the interplay between economic and social upgrading. The model is prevalent in quantifying the coupling and coordinated development between disparate systems, with extensive applications in areas such as urbanization and ecological environment studies (Fan et al., 2023). The coupling degree is a measure of the synchronicity between two systems. However, the coupling coordination degree goes a step further, incorporating the individual development levels of the systems and providing an amalgamated reflection of the synchronicity and the self-evolution of the systems. In essence, the coupling coordination degree sketches the synchronized relationship between social upgrading and economic upgrading while keeping track of their respective inherent progress. A high coupling coordination degree signifies parallel growth and a harmonious progression in the same direction, capturing the synergistic elevation of social and economic upgrading.
This study utilized the enhanced formula for the coupling coordination degree model (Wang et al., 2021a):
$\begin{matrix} C=\sqrt{\left[ 1-\sqrt{{{\left( {{U}_{2}}-{{U}_{1}} \right)}^{2}}} \right]\times \frac{{{U}_{1}}}{{{U}_{2}}}}=\sqrt{\left[ 1-\left( {{U}_{2}}-{{U}_{1}} \right) \right]\times \frac{{{U}_{1}}}{{{U}_{2}}}} \\\end{matrix}$
$\begin{matrix} T=\alpha {{U}_{1}}+\beta {{U}_{2}} \\\end{matrix}$
$\begin{matrix} D=\sqrt{C\times T} \\\end{matrix}$
where C represents the coupling degree, T stands for the degree of development, and D is the coupling coordination degree; α and β are specific weights. Given the equal significance of economic upgrading (U1) and social upgrading (U2), this study assigned both α and β a value of 0.5 (Wang et al., 2023). The equidistant partitioning method is commonly used to classify the degree of coupling coordination (Tian and Lin, 2022). And the number of classifications is generally determined according to the results of specific research (Huang et al., 2020). Following such approach, this study adopted a five-tier classification standard for the coupling coordination degree (Table 3). A value below 0.4 indicates an imbalanced coupling coordination in which economic upgrading and social upgrading fail to interact in a way of mutual promotion, while a value exceeding 0.4 denotes a coordinated state of mutual promotion between social and economic upgrading in the region.
Table 3 Degree of coupling coordination between economic upgrading and social upgrading
Coupling coordination degree Division of developmental stages
(0, 0.2] Severe imbalance
(0.2, 0.4] Moderate imbalance
(0.4, 0.6] Low coordination
(0.6, 0.8] Moderate coordination
(0.8, 1] Advanced coordination

2.2.2 Inequality index

The inequality index serves as a tool for gauging the extent of disparities across various regions, enabling a comparative analysis of the evolving trend of regional differences over numerous years. This study harnessed the Theil index as a comprehensive representation for quantifying variations in economic and social upgrading among different regions. The formula is as follows (Hartvigsen, 2014):
$\begin{matrix} Theil=\frac{1}{n}\underset{i=1}{\overset{n}{\mathop \sum }}\,~\frac{{{y}_{i}}}{{\bar{y}}}\ln \left( \frac{{{y}_{i}}}{{\bar{y}}} \right) \\\end{matrix}$
where n signifies the number of regions (31 provincial-level regions), i corresponds to the region, yi represents the relevant numerical series intended for measurement in region i (such as social and economic upgrading), and $\bar{y}$ denotes the average of yi.

2.2.3 Panel regression model

The panel regression model was used to uncover the key determinants influencing the coupling coordination relationship between economic and social upgrading. The ordinary least squares (OLS) approach provides a direct measurement of the relationship of influence, while the fixed effects (FE) model considers the impacts of individual factors. However, these models inadvertently sidestep issues related to heteroscedasticity and serial autocorrelation. To address these biases, this study used the feasible generalized least squares (FGLS) estimation method (Liu et al., 2017). The regression model is formulated as follows:
$\begin{matrix} {{D}_{it}}=C+{{\beta }_{i}}{{X}_{it}}+{{a}_{i}}+{{\varepsilon }_{it}} \\\end{matrix}$
where i stands for the region, t represents the year, Dit denotes the coupling coordination degree of different regions, and Xit represents a set of explanatory variables. Further, βi is the regression coefficient, ai indicates the FE associated with the region, C is the constant, and εit is the random error term.

2.3 Data sources

This study adopted a temporal frame stretching from 1996 to 2020 and targeted 31 provincial-level regions in China, resulting in a total of 775 research samples. The study extracted data from respective editions of the China Statistical Yearbook, China Labor Statistical Yearbook, China Social Statistical Yearbook, China City Statistical Yearbook, provincial statistical yearbooks, and the marketization index report (Wang et al., 2021b). For a few missing data points, this study used linear interpolation to fill in the gaps.

3 Evolution and regional disparities in the coupling coordination between social and economic upgrading

3.1 Evolution of social and economic upgrading

Figure 1 maps out the transformation in the mean values of the composite indices for social upgrading and economic upgrading in China. Over the period 1996-2020, the social upgrading index in China ascended from 0.22 to 0.36, depicting an overall trajectory that first descended before taking an upward turn. In the period 1996-2002, the social upgrading level was on a persistent decline. The main reason for the decline is the reform of state-owned enterprises in the mid-1990s, which gave rise to millions of workers being either dismissed or forced into competitive labor markets (Huang et al., 2022). This market-oriented reform broke the state sector’s ‘iron rice bowl’ arrangement established in the early socialist period that provided workers with a guaranteed job and income (Lee, 2007). It led to the loss of stable jobs and the erosion of social welfare benefits covering housing, pensions, children’s education, and medical care (Kuruvilla et al., 2011). Hence, the declining trend of social upgrading in the period reveals the temporary sharp shock of state-owned enterprises reform on labor in the 1990s. The trend was reversed after 2002 and embarked on a sustained ascension. This can be explained by the rapid industrialization, which has brought about a vast number of job opportunities and improved workers’ income. The new Labor Contract Law enacted in 2008 also contributed to the improvement in protection of workers’ rights and interests. By comparison, economic upgrading has shown a consistent and progressive upward trend, surging from 0.11 in 1996 to 0.27 by 2020. Importantly, during the phase of the “13th Five-Year Plan” subsequent to 2015, the escalation rate of the economic upgrading index experienced a marked amplification.
Figure 1 The flux in the indices for social and economic upgrading

3.2 Disparities in social and economic upgrading across regions

As Figure 2 illustrates, the regional discrepancies in economic upgrading are sizable and widening progressively. This suggests that while developed regions possess a strong propensity for economic upgrading, their less developed counterparts struggle, revealing the emergence of a “Matthew Effect” in the course of development. Conversely, the regional disparities in social upgrading are considerably lesser and more stable, demonstrating an initial surge followed by a decline around the pivotal point of the 2008 economic crisis. Nevertheless, overall, the variations across regions remain relatively modest. Insights drawn from Figures 1 and 2 reveal that post 2002, despite continuous development in China’s social upgrading, there has been no exacerbation of regional discrepancies. Hence, the issue of geographical imbalances is less acute in the realm of social upgrading than in economic upgrading.
Figure 2 Disparities in social and economic upgrading across regions
Economic upgrading is primarily a market-driven process, which, under the sway of agglomeration effects, can easily give rise to unbalanced regional development (Cheong and Wu, 2014). Conversely, social upgrading is not solely market-driven but is also shaped by government interventions and institutional factors. For instance, the Chinese government has bolstered labor rights by refining labor contract laws, putting a check on excessive capitalist exploitation. Moreover, through the formulation of employment support policies, the government has fostered additional job opportunities (Qian et al., 2022), ensuring stability in the employment market. All these governmental interventions effectively facilitate a more balanced regional spread in the realm of social upgrading.

3.3 Degree of coupling coordination between social and economic upgrading

In the period 1996-2020, the mean degree of coupling coordination between social and economic upgrading in China rose from 0.33 to 0.49 (Figure 3). This reveals an escalating degree of coupling between these two processes, moving from a stage of mild imbalance toward a phase of low coordination. However, it also underscores that the overall coordination is in a relatively low state at the national level.
Figure 3 Evolution of the degree of coupling coordination between social and economic upgrading
Before 2002, the coupling coordination degree lingered at a low level, with its rise marked by a slow and steady pace. This can be traced back to the influence of the mid-1990s reforms in state-owned enterprises on the labor market. The wave of marketization, while propelling economic upgrading, simultaneously triggered a large-scale wave of layoffs in state-owned economic sectors. This led to a decrease in employment opportunities and wage compensation, amplified labor-capital tensions, and consequently resulted in social downgrading (see Figure 1).
In the period following 2002, the enactment and implementation of new union laws and labor contract laws, coupled with the strategic aim of creating harmonious labor relations, significantly improved workers’ rights and the quality of employment. This lent momentum to the rise in social upgrading. Further, China’s ongoing market reforms and its accession to the WTO at the end of 2001 continually fueled economic upgrading. In particular, during the “13th Five-Year Plan” phase from 2016 to 2020, there was a marked elevation in the coupling coordination degree. This aligns closely with the national ideology of coordinated economic and social development post the 18th National Congress of the Communist Party of China, which emphasized a balanced focus on industrial transformation and innovation, as well as the enhancement of people’s well-being.
The evolution of the coupling coordination between social and economic upgrading mirrors China’s ideological shift over the last two decades from an economy-centric approach to a more balanced focus on both economic and social development.

3.4 Regional characteristics of coupling coordination between social and economic upgrading

Using the average per capita GDP from 1996 to 2020 as a benchmark for assessing the level of regional economic development and subsequently ranking these from highest to lowest, this study observed the annual distribution of coupling coordination degrees across different regions (Figure 4). The following key patterns emerge. First, a pronounced regional variation exists in the degree of coupling coordination. The economically advanced regions of East China demonstrate a significantly higher degree of coupling coordination compared to the less developed areas in the central and western parts of the country. This spatial pattern is consistent with the general regional unevenness of economic development in China.
Figure 4 Regional disparities in the coupling coordination between social upgrading and economic upgrading
Second, these more affluent regions transitioned into the phase of coordinated development ahead of their less developed counterparts. Beijing and Shanghai embarked on this coordinated phase as early as 1996, with Tianjin following suit in 2002. By 2020, only these three municipalities directly under the central government (namely, Beijing, Shanghai and Tianjin) had graduated to the intermediate phase of coordination. Other economically advanced regions, such as Zhejiang, Jiangsu, and Guangdong, successively transitioned into the initial coordination phase post-2007, while most less developed regions languished in a period of imbalance for an extended duration.
Third, compared to their wealthier counterparts, the less developed regions display greater volatility in the progress of their coupling coordination. Instances of shifts from coordination back to imbalance have been observed in regions such as Hainan, Ningxia, Jilin, Shanxi, Heilongjiang, Yunnan, Tibet, and Guangxi. These areas are characterized by a relatively homogeneous industrial structure and a lack of economic diversity. In the face of adverse external economic conditions, their economic upgrading processes are more prone to stagnation. Compared with the economically developed areas, the infrastructure and investment level in the underdeveloped areas are relatively weak, and it is difficult for them to promote the generation of economic upgrading. Therefore, compared with the stable development of social upgrading, the amplitude of economic upgrading in less developed areas is larger, and the situation of upgrading failure often occurs, leading to the recurrence of upgrading and downgrading. Consequently, relative to the steadiness of social upgrading, the economic upgrading in these less developed regions exhibits larger fluctuations. This results in a cyclical pattern of economic upgrading and downgrading, leading to a low and oscillating state of coupling coordination between social and economic upgrading.
Fourth, there are some special regions with weak coupling coordination in the relatively developed regions in terms of per capita GDP. They are resource-dependent regions, such as Xinjiang and Inner Mongolia. Poor performance of economic upgrading was the main reason for the weak coordinated development. Although the per capita GDP level of Xinjiang and Inner Mongolia is high, their coordinated development level is significantly lower than that of the developed region echelon. As resource-based regions, the economies of Xinjiang and Inner Mongolia mainly rely on energy and resource industries. This resulted in their industrial structures lacking diversity and being mostly export-oriented. Economic resilience of them is thus weak and easy to be affected by external interference. Moreover, the willingness of these regions to upgrade economic structure is not strong. With rich natural resources such as fuel and minerals and high-output export processing industries, such areas have relatively little desire to update the industrial structure. At the same time, the industrial upgrading direction of such areas is different from other regions. The industrial upgrading of resource-based areas is more inclined to low-carbon environmental protection rather than increasing added value. However, compared with economic upgrading, social upgrading in these resource-based areas is favorable due to the dominance of the state-owned economy. Workers are protected by a more labor-friendly system, in which workers’ jobs are more stable, the labor-capital relationship is more harmonious, and the quality of employment is higher. It is this imbalance that resulted in the low level of coupling coordination between social and economic upgrading in these resource-based regions. Such imbalance indicates a non-linear and complex relationship between social and economic upgrading.

4 Factors influencing coupling coordination between social and economic upgrading

4.1 Theoretical analysis and selection of indicators

The interplay between social and economic upgrading is influenced by a combination of market, governmental, and institutional factors, including economic privatization, globalization, public governance, the legal environment, and the law compliance of corporate behavior (Huang and Zhou, 2021b; Wang et al., 2022b).
First, economic privatization often hampers the coupling coordination between social and economic upgrading. In regions with a high degree of economic privatization, state-owned capital typically takes a backseat, while private enterprises take the lead. These private entities, in their pursuit of maximizing profits, tend to place a greater emphasis on economic upgrading. This often results in a reduction of labor costs and a disregard for labor rights, causing social upgrading to trail behind economic upgrading. This imbalance disrupts the desired coupling coordination between the two. Conversely, state-owned capital tends to strike a balance. It focuses on the transformation and upgrading abilities of enterprises (Li and Guan, 2022) and places importance on maintaining the quality of employment and upholding workers’ rights (Shang et al., 2022). This balanced approach fosters the coupling coordination between social and economic upgrading. To quantify the degree of economic privatization (NSTAT), this study used an index that represents the proportion of the non-state economy in industrial sales (Wang et al., 2021a). This index signifies the percentage of total industrial sales that non-state industrial enterprises contribute.
Second, economic globalization plays a pivotal role in fostering the coupling coordination between economic and social upgrading (Lund-Thomsen et al., 2012; Ruwanpura, 2016; Jindra et al., 2019). On the one hand, the inflow of global capital into local markets brings investment and technologies. This bolsters regional economic growth and stimulates transformation, creating a ripple effect that enhances the availability of job opportunities. On the other hand, engaging in the international division of labor and becoming a part of the global production network can accelerate local social upgrading. This effect is primarily facilitated by multinational corporations that adhere to their corporate social responsibility (CSR) commitments. These corporations typically set standards for their local suppliers, enforcing an 8-hour workday and minimum wage system and insisting on improved working conditions, including the provision of social insurance. The level of economic globalization (ln(pIFDI)) is measured using per capita foreign direct investment.
Third, public governance significantly contributes to the coupling coordination between economic and social upgrading. Motivated by the prospect of political progression, local government officials often endeavor to stimulate local economic development and industry transformation (Wang et al., 2022a), fostering economic upgrading. Simultaneously, the government bears the duty of improving public welfare and safeguarding labor rights. This is typically achieved through the implementation of relevant labor regulations, the execution of employment policies, and enhancements to the welfare system, contributing to social upgrading (Pyke and Lund-Thomsen, 2016). The effectiveness of government governance (ln(pFE)) is measured using per capita fiscal expenditure.
Fourth, the soundness of the legal environment facilitates the coupling coordination between economic and social upgrading. A solid legal infrastructure can attract businesses (Demirguc-Kunt et al., 2006), fostering vibrant market competition and providing fertile soil for economic upgrading. In regions with a well-protected legal framework, societal transparency is typically high (Montes and Luna, 2021), effectively addressing labor concerns, safeguarding worker rights, and ensuring that workers reap benefits from economic upgrading. This transparency can also invigorate workers to innovate and venture into entrepreneurship, further driving economic upgrading. The legal environment (LAW) is gauged using the index of development of market intermediaries and the legal system environment provided by Wang et al. (2021b). This index signifies the extent to which the external environment supports and protects local market development.
Finally, corporate violations of law are detrimental to the coupling coordination between economic and social upgrading. Some enterprises, during the implementation of restructuring and upgrading strategies (such as automation, relocation, mergers, and acquisitions), disregard labor rights and breach labor contract laws. Other enterprises consistently circumvent labor laws and regulations, relying on the excessive exploitation of labor to sustain their competitive edge (Davies, 2020). Clearly, economic upgrading rooted in legal violations does not lead to a corresponding social upgrading. Corporate violations of law are gauged by the ratio of fines and forfeitures in fiscal revenue to GDP (FP_GDP).
The descriptive statistics for the aforementioned explanatory variables are showed in Table 4.
Table 4 Descriptive statistics for variables in regression model
Regression variables Measurement indicators Mean Median Maximum Minimum Variance Sample size
Level of coupling coordination (D) Degree of coupling coordination 0.390 0.374 0.735 0.270 0.071 775
Economic privatization (NSTAT) Index of non-state economy’s
share in industrial sales		 5.951 5.731 12.796 -0.270 3.427 775
Economic globalization (ln(pIFDI)) Logarithm of per capita foreign direct investment 8.739 8.614 14.442 4.019 1.456 775
Government governance (ln(pFE)) Logarithm of per capita fiscal
expenditure		 8.082 8.372 11.013 3.000 1.501 775
Legal environment
(LAW)		 Index of development of market intermediaries and the legal
system environment		 4.934 3.790 14.297 -0.736 3.315 775
Corporate violations
(FP_GDP)		 Ratio of fines and forfeitures in fiscal revenue to GDP 0.003 0.003 0.007 0.001 0.001 775

4.2 Selection of regression model

The existence of unit roots can lead to a lack of stability in series, which results in unsteady and biased regression outcomes. Therefore, the initial step entails conducting a unit root test on the panel data. Employing the Levin-Lin-Chu (LLC) and Augmented Dickey-Fuller (ADF) tests, the results show that with first-order differencing, the unit root was rejected at a 1% level of significance for all original data. This led to the same order of first-order differencing across all variable data (Table 5).
Table 5 Results of unit root test
Variable LLC ADF Stationarity state
Statistic P-value Statistic P-value
D -4.04 0.00 101.59 0.00 Stationary
ΔD -25.55 0.00 568.60 0.00 Stationary
NSTAT -3.69 0.00 56.06 0.69 Non-stationary
ΔNSTAT -18.55 0.00 380.90 0.00 Stationary
ln(pIFDI) 0.67 0.75 104.92 0.00 Non-stationary
Δln(pIFDI) -14.60 0.00 382.42 0.00 Stationary
ln(pFE) -14.45 0.00 333.73 0.00 Stationary
Δln(pFE) -8.25 0.00 186.25 0.00 Stationary
LAW -5.80 0.00 120.25 0.00 Stationary
ΔLAW -16.36 0.00 373.77 0.00 Stationary
FP_GDP -2.90 0.00 113.82 0.00 Stationary
ΔFP_GDP -15.25 0.00 375.33 0.00 Stationary
Subsequently, a panel cointegration test was performed on all variables. Both the KAO and Pedroni tests rejected the null hypothesis at a significance level of 1% for all variables (Table 6). This suggests a cointegration relationship among the variables, permitting the study to proceed with panel regression analysis.
Table 6 Results of panel cointegration test
Methodology KAO
ADF-
Statistic		 Pedroni
Panel PP-Statistic Panel ADF-Statistic Group PP-Statistic Group ADF-Statistic
Statistic -6.88 -8.20 -8.06 -12.50 -9.14
P-value 0.00 0.00 0.00 0.00 0.00
Result Reject the null hypothesis
In determining the type of panel regression model, an F-test was employed to test the mixed-effects model. Afterward, a Hausman test was conducted, with the results rejecting the null hypothesis at a confidence level of 5%, leading the study to select the FE model. Given the substantial regional differences and the data’s short-panel type in this study, an individual FE model was selected.

4.3 Regression results

Model regression was performed using OLS, individual FE model, and FGLS methods, with the outcomes outlined in Table 7. The coefficient of the variable representing economic privatization consistently shows a negative value at a 1% significance level across all models. This suggests that an increase in the extent of non-state economic activity in a region corresponds with a decrease in the level of coupling coordination between social and economic upgrading. Workers in non-state enterprises, when compared with their counterparts in state-owned entities, tend to have less job stability and weaker collective bargaining power, presenting challenges in sharing the enterprises’ benefits of economic upgrading (Lin, 2021).
Table 7 Results of panel regression
Dependent variable Model 1 OLS Model 2 FE Model 3 FGLS
NSTAT -0.004*** -0.005*** -0.004***
ln(pIFDI) 0.018*** 0.020*** 0.019***
ln(pFE) 0.008*** 0.010*** 0.007***
LAW 0.012*** 0.010*** 0.010***
FP_GDP -4.641*** -4.350*** -1.402
Constant 0.140*** 0.132*** 0.144***
N 775 775 775
R2 0.797 0.876 0.875
Adjusted-R2 0.796 0.870 0.869
F-test 603.20*** 149.28*** 147.27***

Note: *, **, and *** represent significance levels of 10%, 5%, and 1%, respectively.

Nevertheless, the variable representing economic globalization maintains a positive coefficient at the 1% significance level in all models. This supports the viewpoint that foreign investment positively impacts the coupling coordination between social and economic upgrading in local contexts. Ever since the economic reforms, foreign investment has been a catalyst for China’s industrialization, promoting initial capital accumulation and spurring local enterprise development. This has amplified employment opportunities and facilitated the introduction of advanced managerial and production techniques. Consequently, this has bolstered local enterprise growth and the improvement of labor rights (Biglaiser and Lee, 2019), propelling synchronous advancements in regional social and economic upgrading.
In all models, the coefficient for the public governance variable was positive at a 1% significance level. This indicates that local governance plays an instrumental role in fostering the coupling coordination between social and economic upgrading, aligning well with existing studies (Zhou and Huang, 2021) and mirroring the government’s role as a key facilitator of balanced socioeconomic development. The Chinese government stimulates enterprise transformation and upgrading via industrial policies, tax incentives, and fiscal subsidies. However, it enhances the quality of employment and safeguards labor rights through labor law enforcement, collective bargaining systems, and the refinement of the social security system.
Similarly, in all models, the coefficient for the legal environment variable was positive at a 1% significance level, implying that a robust legal environment is beneficial to the coupling coordination between social and economic upgrading. An effective legal environment helps maintain market order, ensures fair business competition, fosters healthy market growth, enforces property rights protection, cultivates a favorable environment for entrepreneurship and innovation, and reduces transaction costs, accelerating economic upgrading. Additionally, the improvement of legal frameworks encourages enterprises to meet their labor law obligations and implement workers’ protections, facilitating the process economic upgrading leading to social upgrading.
The coefficient for the variable of corporate violations was negative at a 1% significance level in Models 1 and 2, suggesting that corporate violations negatively impact the coupling coordination between social and economic upgrading. A high prevalence of illegal activities points to a disordered local market economy and a challenging business environment, both of which hinder economic transformation and upgrading. Enterprises that disregard labor laws, delay wage payments, or neglect social security responsibilities impede the social upgrading of local workers. In regions where industrial and labor regulations are not respected, achieving coupling coordination between social and economic upgrading becomes difficult.

5 Discussion and conclusion

This study delves into the intricate interaction between social and economic upgrading in China and its influencing factors through the lens of coupling coordination. This approach provides a valuable counterbalance to the existing research (e.g., Rossi, 2013; Barrientos et al., 2016; Zhou and Huang, 2021), which predominantly explores the unidirectional influence of economic upgrading on social upgrading. It provides the Chinese case study to illustrate the complex interaction between economic upgrading and social upgrading in developing countries (Milberg and Winkler, 2011). Hence, this study lays the empirical groundwork for further probing the theory on the interplay between these two processes. The findings highlight that since the mid-1990s, there has been a perceptible improvement in the coupling coordination between social and economic upgrading in China, transitioning from a state of mild imbalance to a stage of low coordination. However, this transition signifies that the nation is grappling with a low level of coordinated development overall. Assessing the geographical distribution reveals stark regional disparities in economic upgrading, social upgrading, and their coupling coordination. This geographical unevenness is encapsulated by two key observations. First, as social upgrading is largely influenced by national-level governance and institutional factors, its regional disparity is less pronounced compared to that of the market-driven economic upgrading. This unconformity is in line with the existing argument that economic upgrading does not necessarily lead to social upgrading, or to put it another way, that social upgrading will not necessarily go hand in hand with economic upgrading (Pyke and Lund-Thomsen, 2016; Lohmeyer et al., 2022). Second, the degree of coupling coordination between social and economic upgrading is intrinsically linked with the phase of economic development. Developed regions tend to have a higher degree of coupling coordination compared to their less developed counterparts, indicating that the level of coupling coordination enhances as the economy matures. This suggests that the capability of mutual promotion between social and economic upgrading tends to improve with the advancement in the level of economic development. Current literature has shown that global actors such as lead firms in GPNs and the local public governance play productive roles in coordinating the progression of social and economic upgrading (Gereffi and Lee, 2016; Reinecke and Posthuma, 2019; Wang et al., 2022b). Consistent with this, our study shows that factors including economic globalization, effective public governance, and a strong legal structure bolster the coupling coordination between social and economic upgrading. However, the shift toward economic privatization (or de-nationalization) and corporate violations of law tend to undermine the coupling coordination.
This study has policy implications for enhancing the coupling coordination between social and economic upgrading. First, we should persist in encouraging external openness, actively involving the national and local economy in the global economic labor division, and welcoming advanced technologies and industry standards. Second, we should harness the potential of local governments in regulating economic and social development, continuously focusing on the betterment of the legal environment and fostering a thriving market economy. Special care must be taken to strengthen labor rights protections and refine the tripartite dialogue mechanism that involves labor, capital, and the government. Third, it is crucial to address the regional unevenness that exists in economic upgrading, social upgrading, and their coupling coordination. It is essential to facilitate the conversion of economic upgrading benefits to laborers, reinforce assistance from economically developed regions to underdeveloped areas, and guide the nationwide social and economic upgrading into a stage of healthy coupling coordination.
In essence, the relationship between social and economic upgrading revolves around the question of how laborers can partake in the success of enterprise development. As such, it illuminates a useful perspective for studying common prosperity and lessening the wealth disparity. Future research should probe the interplay of these two aspects from the micro perspective of individual enterprises and the meso perspective of industrial clusters. The research should focus on identifying the conditions and methods that stimulate reciprocal advancement in social and economic upgrading, uncovering the institutional factors that enhance their coupling coordination, and discovering the institutional arrangements and policy measures that promote their coupling coordination across different scales, such as national, local, industrial clusters, and enterprises.

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