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Article

Improving Circular Supply Chain Performance through Green Innovations: The Moderating Role of Economic Policy Uncertainty

by
Zhaoqian Liu
and
Mengmeng Wang
*
College of Business, Gachon University, Seongnam 13120, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(24), 16888; https://doi.org/10.3390/su142416888
Submission received: 6 October 2022 / Revised: 2 December 2022 / Accepted: 10 December 2022 / Published: 16 December 2022
(This article belongs to the Special Issue Studies of Supply Chain Resilience and Manufacturing Enterprise Management from a Circular Economy Perspective)
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Abstract

:
The sudden outbreak and long-term trend of COVID-19 have brought huge attacks and uncertainty to the global economy, forcing countries to introduce various policies frequently to stimulate economic recovery. To realize sustainable development, firms established an environment-friendly economic development model by building a circular supply chain and implementing a green innovation strategy, which is expected to save resources and protect the environment by recycling resources. Based on this background, this study aims to determine the relationship between the uncertainty of economic policy, green innovation strategy, and circular supply chain performance. It divides green innovation strategies into green product innovation, green process innovation, green service innovation, and green logistics innovation to explore their different impacts on the performance of the circular supply chain. Simultaneously, the moderating effect of uncertainty of economic policy between green innovation and the performance of the circular supply chain is explored. Using survey data collected from 308 manufacturing firms in China, we empirically test the theoretical model and proposed hypotheses through the structural equation modeling approach. Our findings demonstrate that green product innovation, green process innovation, green logistics innovation, and green service innovation have a positive impact on the performance of the circular supply chain. Moreover, we also find that, contrary to our expectations, economic policy uncertainty plays a positive role in moderating the relationship between green innovation and circular supply chain performance. We believe that this paper has a clear contribution to the research on green innovation and circular supply chain management. This study provides a new perspective for the research on the integration of green innovation and circular supply chain, deepens firms’ understanding of green innovation strategy and circular supply chain, and provides important implications and guidance for manufacturing firms to better manage green innovation and circular supply chain practice as well as the risk of economic policy uncertainty.

1. Introduction

The long-term trend of COVID-19, climate deterioration, and lack of resources have caused a deep recession in the global economy, resulting in many countries’ economic recovery difficulties. The pace of global supply chain restructuring is accelerating, and the uncertainty and instability of the economic policies of various countries are increasing. To realize sustainable development, the main economies in the world regard building a circular supply chain as the basic path to breaking resource and environmental constraints, coping with climate change, and cultivating new economic growth points. Currently, the circular supply chain is viewed in two ways. One is that the circular supply chain can improve firms’ economic, social, and environmental sustainability and create greater value for firms by integrating the business ecosystem, coordinating the forward and reverse supply chains, and extending the life cycle of products, services, by-products, and wastes. It is an effective solution to achieve sustainable development [1,2,3]. On the contrary, some scholars proposed that, although constructing the circular supply chain benefits the environment and economy in the long run, firms need to make substantive changes to the current product design strategy, business model, and supply chain operation in its implementation. Whether consumers will accept the products produced by the firms is uncertain. Therefore, the economic feasibility is worth serious consideration, and great challenges are expected in the short term [4]. In other words, even though building a circular supply chain is imperative, the problem of how to improve the performance of the circular supply chain still needs to be solved.
At the same time, with increasingly serious environmental issues, firms should put forward green and innovative strategies to respond to them to meet the demand for the environmental protection of consumers. Green innovation effectively promotes sustainable economic development and can help overcome resource shortages and environmental constraints effectively [5,6]. The green innovation strategy of firms mainly includes green product innovation, green service innovation, green process innovation, and green logistics innovation. Green product innovation refers to the innovation of product design, focusing on the impact on the environment after the end of product service life [7]. Compared with traditional product innovation, green product innovation is an innovation adopted by firms to adapt to environmental changes and customer expectations, reduce excessive consumption of raw materials and energy according to environmental requirements, and avoid unnecessary uncertainties to customers’ health and safety caused by products [8]. It meets the needs of consumers for environmental protection and helps firms to open up new markets, causing difficulty for firms to replicate their products and maintain product competitiveness. Successful green product innovation can improve resource utilization efficiency and enable firms to gain competitive advantages [9]. Green process innovation refers to applying green concepts in the whole process of product production to help firms improve resource utilization [10]. Green process innovation integrates the environmental needs of stakeholders into production design, reduces the cost of producing goods, and makes products conform to environmental regulations [9]. Green process innovation can greatly reduce environmental pollution and energy and raw material consumption. Implementing green process innovation can help firms develop green products, expand their scale, and improve their reputation and image [10,11]. Green service innovation mainly includes green invention, the design of environmental services, and a combination of environmental services [12]. It focuses on social responsibility for the environment and reduces the impact on the environment by providing environmental protection services [13]. By promoting green services innovation activities, such as environmental protection services and cleaner production, firms can help achieve sustainable development goals, increase barriers to competitors’ entry, and gain competitive advantages [9]. Green logistics refers to activities such as transportation, warehousing, packaging, unloading, and processing by reducing energy consumption, focusing on the environment, and making full use of advanced logistics technologies with economic and social benefits [14]. The practical significance of green logistics is to reduce energy consumption, pay attention to environmental protection, and improve economic efficiency [15].
Regarding the close correlation between green innovation strategy and the performance of circular supply chain in solving environmental issues, clarifying the relationship between green product innovation, green process innovation, green logistics, green service innovation, and circular supply chain performance through empirical analysis and filling the gap in relevant research are necessary. This study can provide a new perspective for the research on the integration of green innovation and circular supply chain, deepen firms’ understanding of green innovation strategy and circular supply chain, and provide theoretical reference and guidance for green innovation and circular supply chain manufacturing firms in practice.
Furthermore, with the turbulence of the international situation and the protracted COVID-19 epidemic in recent years, global market volatility has also become increasingly intense. Many firms must face the uncertainty of economic policies under market turbulence in the process of green innovation to face the deterioration of resources and economic recession. The uncertainty of economic policy itself is a significant cause of the economic recession. The uncertainty of economic policy negatively impacts the macroeconomy. These impacts are reflected in the rising uncertainty of economic policies that aggravate the volatility of key macroeconomic variables and financial asset variables; they also negatively influence macroeconomic variables, such as output and employment, and hinder economic recovery [16]. Economic policy uncertainty refers to the uncertainty in terms of time, content, and potential impact of policy decisions faced by firms. In this case, firms often choose to reduce investment and hold more cash to deal with financial uncertainties caused by investment risk and cash flow uncertainty [17]. The uncertainty of economic policy makes the firms unable to predict whether, when, and how the government will change current economic policies [16]. Economic policy uncertainty also increases the volatility of commodities, which means that the potential uncertainty can permanently affect the volatility of commodities, which undoubtedly increases the financial pressure on firms [18]. Economic policy uncertainty may inhibit firms’ investment by changing the costs of business activities, with a particularly important effect on innovative activities. Facing economic policy uncertainty, firms need to weigh the uncertainties and benefits of innovative activities [16]. Thus, the second purpose of this study is to explore and analyze the moderating role of the uncertainty of economic policy between green innovation and the performance of the circular supply chain. It helps firms avoid challenges caused by the uncertainty of economic policy in implementing green innovation strategy and provides valuable suggestions for firms to maximize the performance of the circular supply chain.
In this study, we contribute to the literature on green innovation and circular supply chain management in the following ways. First, we theorize and empirically test how specific green innovation strategies may contribute to the performance of the circular supply chain among manufacturing firms in an emerging economy. Our results provide clear evidence of a positive relationship between specific green innovation dimensions (i.e., green product innovation, green process innovation, green logistics innovation, and green service innovation) and manufacturing firms’ circular supply chain performance. We believe our study provides the first empirical evidence of the role of different green innovation forces in contributing to a firm’s performance of a circular supply chain. Furthermore, we also argue and empirically explore how the contribution of specific green innovation strategies to a firm’s circular supply chain performance may be further moderated by the degree of perceived economic policy uncertainty by the firm. Our findings provide important implications for the firms by showing how differences in the perceived economic policy uncertainty may explain the variation in the relationship between specific green innovation strategies and circular supply chain performance. Therefore, we clarify theoretically the positive role of economic policy uncertainty in shaping the contribution of a firm’s specific green innovation strategies to the firm’s circular supply chain performance and thus provide novel insights into the interactive role between a firm’s green innovation strategies and economic policy uncertainty in influencing the firm’s circular supply chain performance. Finally, using structural equation modeling (SEM) with survey data collected from 308 manufacturing firms in China, one of the largest emerging economies, we empirically test the conceptual framework and proposed hypotheses. We believe China offers an ideal setting to verify our research model and our findings suggest that in China, firms indeed benefit from green innovation strategic management, and most manufacturing firms in China might rely on green innovation strategies to achieve better performance of circular supply chain. Our study thus provides a relatively complete picture of the benefits of specific green innovation strategies among manufacturing firms in China. However, we do not believe China is fundamentally different from other emerging economies, except that its markets are perhaps bigger and more heterogeneous. Therefore, we believe the idea of the roles of specific green innovation strategies and their interplay with economic policy uncertainty could be applicable to other emerging economies.

2. Literature Review and Hypothesis Development

The theory of circular economy was first proposed by British environmental economists David Pearce and Kerry Turner in a book entitled Natural Resources and Environmental Economics [19]. This concept deals with the relationship between the four economic functions of the environment, including the value of amenities, its function as a resource base and a water sink for economic activities, and its role as a life support system [20,21]. The circular economy is based on the idea of serving private firms in the transition to a more sustainable system. As a single participant with the most resources and abilities, a firm can promote such a transition by creating additional value through an expanded and more actively managed network of stakeholders [20]. A basic feature of commercial models in the circular economy is to realize a circular value chain to maximize resource efficiency [22]. Meanwhile, as one of the most important theories in strategic management, dynamic capability refers to the ability of individuals to acquire, generate, and combine knowledge-based resources to understand, explore, and adapt to environmental changes. Furthermore, solving problems based on the changing environment can bring new competitive advantages to firms [23,24]. Firms can rapidly and effectively reintegrate resources and processes to cope with the changing competitive environment by improving the dynamic capabilities of corporate management and organizational processes [25]. Using a citation search of several major electronic databases such as EBSCO’s Business Source Complete, Elsevier ScienceDirect, and ProQuest, we conducted the systematic review. Our systematic review demonstrates that, while recent circular economy research started to focus on the importance of the concept in supply chain management, such circular supply chain management (CSCM) research is largely limited to developing the concept of CSCM and integrating various terms that are seemingly related to the CSCM [26]. In addition, although this line of research also attempted to explore the relationship between circular supply chain and firm performance [27,28], the contribution of green innovation and more importantly, the role of specific green innovation strategies in shaping the performance of circular supply chain have largely remained unexplored in the literature. Given the increasing importance of developing a more green innovation-oriented strategy for firms to enhance competitive advantages and better manage their circular supply chains, much should be known about how such a green innovation-oriented strategy may shape the performance of the circular supply chain and how such a contribution of green innovation to the performance of the circular supply chain may be contingent on the degree of the perceived economic uncertainty. To address these research gaps in the literature and to deepen knowledge of green innovation and its effect on the performance of the circular supply chain among firms in emerging markets, we develop our arguments by theorizing and proposing a research model based on circular economy theory and dynamic capability theory, as shown in Figure 1. More specifically, we propose that green product innovation, green process innovation, green logistics innovation, and green service innovation may positively impact the performance of the circular supply chain. Furthermore, we expect that the contributions of these specific green innovation dimensions to the performance of the circular supply chain will be significantly moderated by the degree of economic policy uncertainty.

2.1. Green Product Innovation and Circular Supply Chain Performance

The implementation of green innovation by firms can help firms improve product quality and firm popularity, expand market share, and increase the sales volume of their products. It also helps firms reduce the pressure on inventory and manage their supply chain [10,29]. With consumers’ increasing awareness and demand for environmental protection, firms providing more environmentally friendly products than their competitors will help them develop new markets and gain competitive advantages [30]. By promoting green product innovation, firms improve the possibility of implementing a differentiation strategy, which helps increase consumers’ perceived value of products. The development of green product innovation can promote cross-functional integration, coordination, and knowledge flow and help firms to establish and manage close communication and knowledge flow with external actors [31]. Green products bring more choices for firms to choose raw materials. Multi-line production reduces the pressure on inventory and meets the needs of firms for cleaner production [29]. The circular supply chain built by firms is mainly to improve technical materials’ reuse, remanufacturing, and recycling ratio through innovative product design [32]. As green product innovation focuses on reducing the impact on the environment during product design, if the firm carries out green product innovation, it will improve the performance of the firm’s circular supply chain. Thus, this study proposes the following hypothesis:
Hypothesis 1.
Green product innovation has a positive effect on the performance of the circular supply chain.

2.2. Green Process Innovation and Circular Supply Chain Performance

Firms can obtain double dividends by reducing environmental burden and promoting technological modernization by implementing green process innovation [10]. Green process innovation can help firms and supply chain members establish knowledge sharing and reduce loopholes to lessen the possibility of risk [33]. From the perspective of innovation economics, green process innovation can enhance the economy’s performance by optimizing the element configuration of firms, including benefits such as reducing production and operation costs, expanding production, increasing market share, and obtaining a green technology patent license [34]. Green process innovation positively improves resource utilization, reducing investment and waste disposal costs [35]. Green process innovation can improve the existing production process to reduce the adverse impact on the environment, improve firms’ environmental adaptability and bring differentiation advantages to firms [10]. Green process innovation upgrades information channels improve the breadth and speed of information sharing, and positively improves firm risk management capabilities [33]. Firms have brought many benefits to the environment and resource reuse in implementing green process innovation. Thus, this study predicts that firms’ implementation of green process innovation in market competition can improve the performance of the circular supply chain. This study proposes the following hypothesis:
Hypothesis 2.
Green process innovation has a positive influence on the performance of the circular supply chain.

2.3. Green Logistics Innovation and Circular Supply Chain Performance

Green logistics innovation can control costs and improve value through reusing or reselling materials, which can help firms recover lost profits and reduce operating costs [36]. Green logistics innovation can eliminate potential safety hazards and reduce product-related costs and uncertainties [36]. Green logistics innovation enables employees and stakeholders to strive to achieve the production goals of improving efficiency, reducing energy use, and preventing environmental pollution, and helps firms achieve sustainable development [15]. Furthermore, green logistics innovation can make firms have flexible transportation systems and respond quickly to the rapidly changing business environment. Firms promote green logistics innovation, use the Internet of Things data to guide warehousing operations, and improve work efficiency; logistics transport vehicles use new energy vehicles to reduce carbon emissions; the outer packaging of the protected goods has been changed into degradable materials. While protecting the environment, these measures can also help firms respond to regulatory pressure from the government, industry associations, and the media [14,37]. Given that green logistics innovation contributes to reducing resource waste and sustainable development, implementing green logistics innovation by firms will improve the performance of the circular supply chain. Thus, this study proposes the following hypothesis:
Hypothesis 3.
Green logistics innovation has a positive effect on the performance of the circular supply chain.

2.4. Green Service Innovation and Circular Supply Chain Performance

Green service innovation means that firms repackage new products and services, expand new production lines, and provide customers with new environment-friendly products based on environmental concerns [12]. Green service innovation focuses on environmental issues and can create unique competitive advantages that could not be replicated by competitors easily [38]. By providing green service innovation, the firms alleviate the negative impact on the environment and contribute to the connection between firms and the international market, enabling firms to meet the environmental service requirements of the international community [39]. Green service innovation can add value to products and services, improve the competitiveness and creativity of firms, and help firms to gain competitive advantages [13]. Furthermore, green service innovation can improve the quality of employees and provide customers with better service [33]. Green service innovation shows customers that the firms realize innovation by providing green services, which can meet customers’ demand for green services, increase their perceived value, and provides them with a good green experience. Green service innovation is conducive to identifying, creating, collecting, organizing, storing, disseminating, and applying green knowledge [13]. Given the various benefits of green service innovation for environmental protection, implementing green service innovation by firms may improve the performance of the circular supply chain. Thus, this study proposes the following hypothesis:
Hypothesis 4.
Green service innovation has a positive influence on the performance of the circular supply chain.

2.5. The Moderating Effect of Economic Policy Uncertainty

As an external risk, the uncertainty of economic policy leads to difficulty for firms to form a stable and consistent pre-judgment of their financial situation and external environment. Firms have to choose to hold more cash flows, which makes them afraid to try innovative strategies easily [40]. The increased uncertainty of economic policy will lead to a reduction in investment, bond issuance and expenditure, and stagnation of R&D and innovation strategies of new products. After the outbreak of COVID-19, countries and governments need more time to make decisions. Without clear policies, firms tend to choose conservative behavior and do not dare to carry out innovative strategic development under uncertain policies [41]. Under high uncertainty of economic policy, firms can hardly predict the future behaviors of the government and tend to adopt conservative and prudent strategies, which are not conducive to innovation [18]. Furthermore, a firm’s supply chain is fragile, and it is easily interrupted by the uncertainty of economic policy. To prevent the risk of supply chain interruption caused by uncertain economic policy, many firms choose to carry out green innovation to cope with environmental changes [42,43,44]. Green product innovation can help firms increase their choice of raw materials, improve their bargaining power, and gain competitive advantages [29]. Green process innovation can reduce production costs, broaden the market, and improve the environment through process innovation, which can also maintain the green image of firms [34]. Green logistics innovation can help firms reduce product-related uncertainties, better supervise the government and society, and establish a good corporate image [37]. Green service innovation can add value to the products of firms and improve their competitiveness. Meanwhile, it can enhance employees’ quality and thinking ability and improve their emergency response capability in the face of emergencies [33,39]. Considering that any strategy pursued by firms is a combination of opportunities and challenges, supply chain risk plays a negative role in regulating the relationship between a firm green innovation strategy and firm performance when firms carry out green product innovation, green process innovation, and green service innovation [9]. As a part of the supply chain risk, when the uncertainty of economic policy increases, firms are more likely to suffer losses if they rush to green innovation strategies. If the firms choose conservative strategies and give up green innovation temporarily, they will not establish a circular system at the supply chain level. To sum up, the uncertainty of economic policy may play a negative role in regulating the performance of the circular supply chain when firms promote green product innovation, green process innovation, green logistics innovation, and green service innovation to improve the performance of the circular supply chain. Thus, this study proposes the following hypothesis:
Hypothesis 5a.
Economic policy uncertainty plays a negative role in moderating the relationship between green product innovation and circular supply chain performance.
Hypothesis 5b.
Economic policy uncertainty plays a negative role in moderating the relationship between green process innovation and circular supply chain performance.
Hypothesis 5c.
Economic policy uncertainty plays a negative role in moderating the relationship between green logistics innovation and circular supply chain performance.
Hypothesis 5d.
Economic policy uncertainty plays a negative role in moderating the relationship between green service innovation and circular supply chain performance.

3. Methodology

3.1. Sampling and Data Collection

To empirically examine our hypotheses, we collected data by conducting a survey targeting firms in China. China represents an ideal research setting to explore how the forms of green innovation may contribute to circular supply chain performance and the role of economic policy uncertainty in shaping such green innovation effects on circular supply chain performance. As one of the fastest-growing economies in the world and its largest emerging economy, China has been making substantial efforts to transform its economy into one that is more environmentally friendly, low-carbon, and green [45]. For example, it was estimated that China invested more than 2 trillion yuan (roughly $375 billion) during 2011–2015 to facilitate the development of major energy-saving projects that had been expected to help China save an equivalent of 300 million tons of coal in that period [46]. In addition, to better contribute to the global response to climate change and achieve the goals of carbon peak and neutrality before 2030 and 2060, respectively, the Chinese government is exerting considerable efforts to foster green and high-quality development. In doing so, China is actively implementing effective policies to not only ensure the clean and efficient use of coal but also reduce the use of the fuel and replace it with alternative renewable and clean energy sources. China has successfully reduced its carbon emissions intensity by 34.4% over the last decade due to its green commitment [47]. More importantly, with the implementation of such environmental-friendly and green supporting policies, more new business opportunities are quickly emerging in China and many firms are actively adopting green-oriented innovative strategies to ride the wave of the green transformation in the country by developing new businesses or upgrading their existing production facilities. As a result, to achieve sustainable development and ride the wave of China’s carbon peak and neutrality goals, Chinese firms have been increasingly practicing green transformation over the past years by developing a large number of green, low-carbon, and environmentally friendly consumer products or services. According to a survey conducted by the market consultancy Ernst & Young, 38% of Chinese consumers considered sustainability the priority in shaping their consumption decisions, compared with the fact only 10% of these surveyed consumers emphasized the importance of cost-effectiveness [48]. In particular, many Chinese consumers, especially the new generation of consumers, are increasingly interested in pursuing environmentally and eco-friendly products. For instance, according to the estimates of cosmetics by a marketing director of the global e-commerce giant, Alibaba Tmall Global, more than 70% of Chinese consumers are willing to purchase nature-based beauty products and more than 81% are willing to buy eco-friendly skincare products. The marketing director also suggested that Chinese young consumers online are willing to pay an extra 10%–20% to seek environmentally friendly brands.
We followed a careful procedure to develop the survey instrument. In doing so, we first developed an English-language version of the questionnaire and then translated it into Chinese with the assistance of two independent professional bilingual translators. To ensure conceptual accuracy, we further back-translated the Chinese version of the questionnaire into English by employing two additional independent professional bilingual translators [49,50]. We also checked for the measures’ content and validity by conducting in-depth interviews online with top-level strategic managers (e.g., CEO, vice president, senior managers) of Chinese firms who are believed to be uniquely qualified to respond to our strategic issues and the questions regarding green innovation and circular supply chain management under investigation. We also pretested the Chinese version of the questionnaire before formally administering the survey to 16 senior managers from Chinese firms and modified some items of the questionnaire based on the feedback from these managers. Most importantly, because prior research has argued for the importance of developing close relationships and trust with respondents to enhance their participation and ensure high-quality responses when surveying in China [51,52], we hired a renowned Chinese local research company that has successfully collected high-quality data in the Chinese market to help us administer the survey. We selected a random sample of 600 firms from a list of manufacturing firms provided by a marketing research company, which covers diverse industries, such as electronics, machinery, and communications. Through the development of such a careful research procedure and the collaboration with the highly reputable national research company as well as well-trained research assistants to help us collect data, we received a total of 345 responses. We excluded 37 questionnaires that have a small amount of missing data for our key variables and thus utilized a total of 308 effective questionnaires for the final data analysis. Our sample is mainly small and medium-sized, and relatively young firms. Of the 308 firms, roughly 81% had less than 500 employees and 71.6% had been established less than 20 years.

3.2. Bias Testing

When conducting survey-based research, a major concern is nonresponse bias. We checked for such a potential issue by comparing the responding firms and nonresponding firms, as well as early-responding firms and late-responding firms, on key firm-specific characteristics (e.g., firm size and age) [53]. The results of the nonresponse bias test suggest no significant differences in the answers between either responding and nonresponding firms or the early and late responding firms, suggesting that nonresponse bias should not be a significant concern in our data. In addition, common method variance (CMV) may arise in self-report survey data [54,55]. However, we are confident that our data are less likely to suffer from such potential CMV concerns due to the following reasons. To minimize CMV in our survey data, we assured the respondents in a cover letter accompanying the questionnaire that the questions included in the survey have no ‘right’ or ‘wrong’ answers and that their responses will be simply used for academic research purposes. We also assured the respondents of the anonymity and confidentiality of their responses. To further minimize potential CMV issues, we carefully designed the survey instrument by arranging the questions randomly using a unique survey software and locating the questions in several separate subsections in the questionnaire. Nevertheless, following recommendations in [56], we checked for CMV by performing the Harman-one-factor test. In doing so, we perform an exploratory factor analysis by entering all self-reported variables into the unrotated factor structure. Our results demonstrate that no single factor emerges from the unrotated factor analysis and no one general factor accounts for the majority of the variance. Therefore, CMV is not a serious issue in our data.

3.3. Variables and Measurement

In this work, we used multiple-item, seven-point Likert scales (“strongly disagree” = 1, “strongly agree” = 7) to measure all independent and dependent variables. Following prior work (e.g., [9,10,30,57]), we measured green product innovation using eight items. To measure green process innovation, we adopted seven items from prior studies (e.g., [9,10,30]). Following prior work (e.g., [37,58]), we measured green logistics innovation using eight items. To measure green service innovation, we used five items derived from prior studies (e.g., [9,12,30]). To capture the degree of economic policy uncertainty, we adopted four items that were derived from prior studies (e.g., [59,60,61]). To measure circular supply chain performance, we adopted nine items from prior studies by integrating environmental, operational, and marketing performance indicators of the supply chain (e.g., [62]).
To account for any alternative explanations of circular performance differences, we also included several control variables in the analyses: firm size, firm age, and industry category. We measured firm size and firm age using the natural logarithm of the number of employees and the natural logarithm of the number of years since the firm was established, respectively. To measure industry category, we created a dummy variable which was 1 for industrial firms.

4. Analyses and Results

We employed moderated regression analyses to empirically examine our hypotheses. Before examining the hypotheses, we first checked for the reliability and validity of the constructs.

4.1. Measurement Reliability and Validity

To assess the reliability and validity of the constructs used in the study, we conducted an overall six-factor confirmatory factor analysis (CFA). We report the results of CFA in Table 1. The CFA model demonstrates an excellent fit to the data (χ2 (764) = 894.977, p < 0.01 comparative fit index [CFI] = 0.985, Tucker–Lewis index [TLI] = 0.984, incremental fit index [IFI] = 0.985, and root mean square error of approximation [RMSEA] = 0.024) [63]. Furthermore, all the factor loadings are statistically significant (p < 0.001), and the Cronbach’s alpha values (ranging from 0.885 to 0.941) and the composite reliabilities (ranging from 0.887 to 0.941) of all the constructs are greater than 0.80, thus well exceeding the threshold of 0.70. To assess the convergent validity of the constructs, we calculated the average variances extracted (AVE) of all constructs. The results indicate that the AVE values of all variables exceed the 0.50 benchmark. Therefore, the results indicate that our constructs achieved adequate convergent validity and reliability [64]. To assess discriminant validity, we compared the square root of AVE of each construct with all the possible pairs of correlations between the construct and other constructs in the models) [64]. As shown in Table 2, the results suggest that all possible correction values are lower than the square root of the AVE of each construct, thereby offering evidence of adequate discriminant validity of the measures [64].

4.2. Hypothesis Testing

Following the assessment of the construct’s reliability and validity, we empirically examined our proposed hypotheses. Table 2 reports the descriptive statistics and correlations of the variables used in the regression analysis. The correlation coefficients between independent variables reported in Table 2 indicate that multicollinearity is less likely to be a serious concern in the data analysis. Nevertheless, to further minimize the potential multicollinearity of interaction terms between independent and moderating variables, we mean-centered the independent and moderating variables before creating the interaction terms [65]. We also checked for the variance inflation factors (VIFs) in all the post-regression tests and the results demonstrate that all VIFs are fairly below the value of 2, which is below the recommended cut-off value of 10, thus further providing no evidence of multicollinearity concern. Table 3 presents the results of the moderated regressions examining our hypotheses. We conducted a moderated hierarchical approach by first inserting the control variables in Model 1, then adding the focal variables in Model 2, and finally including the respective interaction terms in the subsequent Models 3–6. In Model 1, the baseline mode, we include only the control variables and add the main and moderating effects in the subsequent models. Specifically, we tested the main effects of various forms of green innovations on circular supply chain performance in Model 2 of Table 3. The results from Model 2 suggest that all four forms of green innovations, namely, green product innovation (β = 0.400, p < 0.001), green process innovation (β = 0.204, p < 0.001), green logistics innovation (β = 0.192, p < 0.001), and green service innovation (β = 0.194, p < 0.001), are statistically significant and positively associated with circular supply chain performance. These results provide strong support for Hypotheses 1–4. In addition, although examining the direct effect of economic policy uncertainty goes beyond our scope, we find that, as expected, economic policy uncertainty is statistically significant and negatively associated with circular supply chain performance.
To empirically test our hypotheses proposing the moderating effect of economic policy uncertainty on the contribution of various forms of green innovations to circular supply chain performance, we added the respective interaction terms between green product innovation, green process innovation, green logistics innovation, green service innovation, and economic policy uncertainty in Models 3–6, respectively. As shown in Model 3 of Table 3, the interactions between green product innovation (β = 0.112, p < 0.01), green process innovation (β = 0.114, p < 0.01), green logistics innovation (β = 0.0.090, p < 0.05), green service innovation (β = 0.094, p < 0.01), and economic policy uncertainty are all statistically significant, but positively associated with circular supply chain performance. These results suggest rejecting Hypotheses 5a–5d. Figure 2 summarizes the main findings from Table 3.

4.3. Robustness Checks

To examine the robustness of the results, we adopted a partial least squares SEM approach. In doing so, we conducted the two-step modeling procedure by first estimating a measurement model and then examining the structural model relationships. The findings of our SEM analyses provide additional confidence in the robustness of the main effects of various forms of green innovations on circular supply chain performance and the role of economic policy uncertainty in moderating such effects of specific green innovations on circular supply chain performance. Owing to space constraints, we only reported the results of moderated hierarchical regression analyses in the study, but the findings of our robustness check using the SEM approach are available upon request from the authors.

5. Discussion and Conclusions

Under the background of the long-term trend of COVID-19 and the global economic recession, many countries frequently introduce various policies to stimulate economic recovery, and economic policy uncertainty is increasing. Many firms regard improving the performance of the circular supply chain as an important way to break the economic dilemma, break through the constraints of environmental resources, and achieve sustainable economic development. To construct a circular supply chain, firms put forward many green innovation strategies, which are the most direct and effective means to improve the performance of the circular supply chain and have gradually entered people’s vision. By referring to circular economy theory and dynamic capability theory, this study divides green innovation strategies of firms into green product innovation, green process innovation, green service innovation, and green logistics innovation to explore their different effects on the performance of the circular supply chain. The empirical analysis has clarified the relationships among the uncertainty of economic policy, green innovation strategies, and the performance of a circular supply chain, providing a theoretical basis for firms developing green innovation strategies and building circular supply chains in the post-epidemic era. It also provides a valuable reference for firms to manage the challenges brought by the uncertainty of economic policy and improve the performance of the circular supply chain. It offers effective solutions for firms to implement green innovation strategies and enhance the performance of the circular supply chain. By investigating 308 Chinese manufacturing firms, this study contributes to the literature in the following ways.
First, green product innovation has a positive effect on the performance of the circular supply chain. Previous studies emphasize that green product innovation can help firms gain competitive advantages [9]. The present study extends the results of previous studies and proves that green product innovation of firms can significantly improve the performance of the circular supply chain. The firms are highly consistent in goals and actions, with a certain causal relationship. Green product innovation can be used as an important tool for improving the circular supply chain. The firms are recommended to innovate in product design, use environment-friendly materials, end the use of toxic compounds, consider the product life cycle fully, make waste easy to recycle, and mark the product packaging with green marks. In the case of limited resources and high demand for environmental protection, only by strengthening the self-restraint mechanism of environmental protection in the process of product innovation firms can provide necessary industrial support for implementing energy conservation and emission reduction indicators and building a circular supply chain.
Second, through empirical analysis, this study found that green process innovation has a positive effect on improving the performance of the circular supply chain. Previous studies emphasize that implementing green process innovation by firms can help them expand their scale and improve their reputation and image [10,11]. This study further proves that implementing green process innovation has a positive effect on improving the performance of the circular supply chain. Firms are suggested to enlarge the investment in research and development of environmental protection technologies; reduce energy consumption; reduce pollution to soil, water quality, and air; maximize resource utilization; and achieve balanced development of economic, social, and environmental benefits in the improvement of equipment and production processes.
Third, through empirical analysis, this study found that green service innovation has a positive effect on improving the performance of the circular supply chain. Previous studies have emphasized that firms can increase their competitors’ barriers and gain competitive advantages by implementing green service innovation [13]. It helps firms achieve sustainable development and improve firm performance [9]. This study has refined and extended the previous literature results, proving that green service innovation of firms is conducive to improving the performance of the circular supply chain. The global trend of climate deterioration, resource shortage, and serious environmental pollution has increasingly challenged humankind to balance economic development and protect the environment. The firms should attach importance to social responsibility for the environment and promote a series of green service innovation strategies, such as environmental protection services and cleaner production. Only by implementing the green innovation strategy can the firms promote the recycling of energy conservation and emission reduction of resources and guarantee a circular supply chain. In addition, this study also found that the green logistics innovation of firms can enhance the performance of the circular supply chain significantly. Previous studies have verified that green logistics innovation can reduce energy consumption and improve economic performance [15]. The results of this study are consistent with those of previous research and prove that green logistics innovation can promote circular supply chain performance. The firms should strengthen the environmental information sharing of the whole logistics network and use sustainable transportation methods to reduce energy consumption and waste emissions. Simultaneously, logistics-related employees and stakeholders should participate in green training to implement green programs more professionally. To protect the current and future resources, firms shall incorporate the green innovation concept into the whole circular supply chain, focus on the environment and the performance of the circular supply chain, and promote the transformation of the entire supply chain to the circular economy through green innovation.
Finally, we offer another important contribution to the literature by theorizing and empirically exploring the moderating effect of economic policy uncertainty on the relationship between green innovation and the performance of the circular supply chain. Through empirical analysis, this study found that economic policy uncertainty plays a positive role in moderating the relationship between green product innovation and circular supply chain performance. In other words, the contribution of green innovation to the performance of the circular supply chain is higher with a more uncertain economic policy. When the government adopts tight financial supervision policies, the firms would have more difficulty obtaining loans from banks, bringing huge financial stress to the strategic investment of firms [60]. As an external risk, the uncertainty of economic policy causes difficulty for firms to predict the future behaviors of the government without clear policies by the state and government, and firms often choose conservative behaviors and hold more cash flow and will not try innovative strategies easily [40,41]. According to the results of this study, the government should make clear the policy of green innovation and circular supply chain, so that firms can clarify the policy direction of the government, stand on the firm level, pay attention to changes in economic policies, and make plans to deal with all changes when improving the circular supply chain through green innovation. When the uncertainty of economic policy increases, firms are willing to increase their investment and gradually expand the scale of innovation. Notably, considering that environment-friendly production machinery and equipment need to be introduced and the production processes shall be improved during the green process innovation of firms, if the replaced machinery and equipment come from abroad, bearing transportation and political uncertainties may be necessary, and the uncertainty of economic policy will bring great pressure on the investment cost of firms [60,66]. Therefore, firms should fully take the cost pressure brought by the uncertainty of economic policy into account when replacing equipment and production processes in carrying out green process innovation and should clearly understand the important role played by green innovation in helping them avoid the potential challenges brought by the uncertainty of economic policy. Furthermore, the uncertainty of economic policy will lead to sharp fluctuations in customer demand, and the green service innovation of firms may become particularly important to meet customers’ changing needs [60]. To this end, firms should continue to pay attention to the changes in customers’ needs when carrying out green service innovation and update their own service models according to the changes in customers’ demands. At the same time, firms need to use sustainable energy to reduce waste emissions for green logistics innovation, increasing investment costs for firms in a short time. The uncertainty of economic policy will lead to higher investment costs for firms, which will put firms under higher financial pressure and adversely affect the performance of the circular supply chain [60]. To sum up, firms must consider the indeterminacy caused by the uncertainty of economic policies when carrying out green logistics innovation to avoid causing huge pressure on the financial cost of firms.

6. Limitations and Future Study

Limited by time, energy, and resources, this study has the following three limitations. First, this study only includes Chinese firms in representative developing countries. Given that different countries adopt different economic policies in the face of global economic turbulence, the impact of uncertainty of economic policy on firms will be different.
In the future, the research objectives should be extended to European and American developed countries for analysis. Second, compared with individual users, firm users are hard to investigate, and many firms are reluctant to disclose their financial performance and other sensitive information. In future research, other relevant information about firms can be obtained through other ways to understand better how the pressure of uncertainty of economic policy on firm performance and to improve the persuasiveness of the research. Third, this study has explored the different impacts of four green innovation strategies on the performance of the circular supply chain. As an emerging topic, green innovation and circular supply chains involve the environment, society, and economic interests. In the future, more research variables such as green business model innovation should be incorporated into the theoretical model to explore their influencing factors and mechanisms specifically, which we believe may help deepen firms’ understanding of green innovation and circular supply chain, and thus provide more valuable implications for the firms to improve their performance of circular supply chain.

Author Contributions

Writing—review & editing and investigation, Z.L.; Conceptualization, Writing, investigation and methodology, M.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data will be available upon request. The data are not publicly available due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 16888 g001 550
Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Figure 2. Estimated results of the hypothesis tests using moderated hierarchical regression analyses.
Figure 2. Estimated results of the hypothesis tests using moderated hierarchical regression analyses.
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Table
Table 1. Assessments of the construct reliability and validity.
Table 1. Assessments of the construct reliability and validity.
Construct and IndicatorsSFLCronbach’s
Alpha		CRAVE
Green product innovation (GTI) 0.9350.9350.642
GTI10.846
GTI20.805
GTI30.801
GTI40.797
GTI50.786
GTI60.794
GTI70.790
GTI80.792
Green process innovation (GSI) 0.9180.9180.616
GSI10.755
GSI20.777
GSI30.794
GSI40.781
GSI50.821
GSI60.778
GSI70.785
Green logistics innovation (GLI) 0.9260.9270.612
GLI10.761
GLI20.802
GLI30.798
GLI40.771
GLI50.790
GLI60.785
GLI70.760
GLI80.792
Green service innovation (GEI) 0.8870.8880.613
GEI10.778
GEI20.761
GEI30.822
GEI40.777
GEI50.774
Economic policy uncertainty (EPU) 0.8850.8870.663
EPU10.723
EPU20.796
EPU30.862
EPU40.869
Circular supply chain performance (CSCP) 0.9410.9410.639
CSCP10.809
CSCP20.827
CSCP30.801
CSCP40.777
CSCP50.799
CSCP60.756
CSCP70.832
CSCP80.774
CSCP90.817
Note: SFL = standardized factor loading, AVE = average variance extracted, CR = composite reliability. Owing to space limitations, we do not report detailed measurement items, but they are available upon request.
Table
Table 2. Descriptive statistics and correlations among the variables.
Table 2. Descriptive statistics and correlations among the variables.
VariableMeanSTD123456789
  • Firm size
5.1621.598
2.
Firm age
2.6190.7260.399
3.
Industry category
0.2690.4440.3450.079
4.
Green product innovation
5.5731.1300.2660.0700.2900.801
5.
Green process innovation
5.4921.1120.186−0.0360.2840.5660.785
6.
Green logistics innovation
5.4231.1260.2020.0400.2310.5650.5690.782
7.
Green service innovation
5.5011.0820.190−0.0470.2500.5330.5290.4990.783
8.
Economic policy uncertainty
3.8761.5060.1590.173−0.005−0.051−0.0750.010−0.0520.814
9.
Circular SCP
5.4291.1690.190−0.0080.2110.7150.6330.6180.602−0.1130.799
Note: All correlations with absolute values greater than 0.110 are statistically significant at p < 0.05. Values in italicized bold denote the square root of the AVE of each construct. SCP = supply chain performance.
Table
Table 3. Results of moderated hierarchical regression analyses.
Table 3. Results of moderated hierarchical regression analyses.
VariablesModel 1Model 2Model 3Model 4Model 5Model 6
Firm size0.170 **0.005−0.0100.0010.0020.003
(2.641)(0.121)(−0.247)(0.035)(0.052)(0.072)
Firm age−0.089−0.013−0.024−0.026−0.025−0.012
(−1.463)(−0.333)(−0.632)(−0.687)(−0.668)(−0.327)
Industry0.160 **−0.056−0.050−0.054−0.054−0.056
(2.701)(−1.486)(−1.342)(−1.437)(−1.436)(−1.480)
Green product innovation (GTI) 0.400 ***0.409 ***0.414 ***0.413 ***0.396 ***
(8.505)(8.816)(8.919)(8.818)(8.505)
Green process innovation (GSI) 0.204 ***0.207 ***0.191 ***0.196 ***0.211 ***
(4.374)(4.495)(4.127)(4.217)(4.562)
Green logistics innovation (GLI) 0.192 ***0.204 ***0.190 ***0.192***0.201 ***
(4.209)(4.514)(4.237)(4.243)(4.442)
Green service innovation (GEI) 0.194 ***0.190 ***0.207 ***0.202 ***0.197 ***
(4.397)(4.385)(4.750)(4.608)(4.528)
Economic policy uncertainty (EPU) −0.069 †−0.056−0.067 †−0.063 †−0.064 †
(−1.944)(−1.600)(−1.936)(−1.811)(−1.832)
GTI × EPU 0.112
(3.219) **
GSI × EPU 0.114 **
(3.308)
GLI × EPU 0.090 *
(2.577)
GEI × EPU 0.094 **
(2.748)
R20.0670.6480.6600.6600.6550.656
ΔR2 0.581 ***0.012 **0.012 **0.008 *0.009 **
F statistics7.245 ***68.725 ***64.152 ***64.336 ***62.980 ***63.267 ***
Note: The values reported in the table are standardized values with t-statistics in parentheses. † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001.
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Liu, Z.; Wang, M. Improving Circular Supply Chain Performance through Green Innovations: The Moderating Role of Economic Policy Uncertainty. Sustainability 2022, 14, 16888. https://doi.org/10.3390/su142416888

AMA Style

Liu Z, Wang M. Improving Circular Supply Chain Performance through Green Innovations: The Moderating Role of Economic Policy Uncertainty. Sustainability. 2022; 14(24):16888. https://doi.org/10.3390/su142416888

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Liu, Zhaoqian, and Mengmeng Wang. 2022. "Improving Circular Supply Chain Performance through Green Innovations: The Moderating Role of Economic Policy Uncertainty" Sustainability 14, no. 24: 16888. https://doi.org/10.3390/su142416888

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