The data used in this study were obtained from manufacturing enterprises located in China's Yangtze Delta Region. There were several reasons why we chose manufacturing firms in this region as our study setting. First, firms under intense pressure to upgrade have often had strong motivations to undertake environmental innovation to survive and grow (Xie et al., 2016), and this is the situation with many companies in the Yangtze Delta Region. Second, this region has long been one of the key areas of manufacturing in China, but rapid industrial production has produced severe ecological problems, such as resource exhaustion and environmental pollution (Molina-Azorin, Claver-Cortés & Tarí, 2009; Xu, Wu & Zhang, 2020). Indeed, as shown in Fig. 2, the output and pollutant emissions from manufacturing firms in the Yangtze Delta Region increased rapidly between 2008 and 2017. Third, during the previous 20 years (i.e., since the Asian financial crisis), the Chinese government has been placing much greater importance on manufacturing industries (Yadiati, Tian, Liu, Chen, & Descamps-Large, 2016), and, because of this change, the public has become increasingly concerned about the environmental pollution caused by manufacturing industries in the Yangtze Delta Region.

Fig. 2. The.

manufacturing output and pollutant emission trend of firms in the China's Yangtze Delta Region (2008–2017).

(0.21MB).

Source: National Bureau of Statistics (2020, May 27)

Given that green innovation may help companies rid themselves of the environmental dilemma, as well as improve their financial performance (Cheng et al., 2014; Xie et al., 2016), this subject has attracted increased attention from academic, political, and, especially, commercial circles (Jung & Kwak, 2018). However, green innovation was only the necessary prerequisite for the enterprises’ sustainable development. In this vein, we believe a threshold likely exists for green innovation, especially in terms of innovations for green processes, resulting in additional R&D costs and the application of such innovations (Guo et al., 2018). Thus, it is clear that green process innovation still has a long and tough way to go in China.

We adopted the survey method in this study to collect data and provide an overview of the existing green process innovation and their effectiveness in the Yangtze Delta Region. Because the original instrument was in English, all items in our study were first translated into Chinese and then translated back into English to ensure validity. We also conducted a pretest using 30 firms, and, from the pretest results, we improved the questionnaire to make it more robust. Following the pretest, we distributed 500 questionnaires to managers and technical supervisors of manufacturing firms in this region via both field surveys and email. For key manufacturing firms in the Yangtze Delta Region, we developed a standardized method to conduct field interviews: during the initial interviews, notes were taken, and then follow-up interviews were conducted to clarify specific issues and to explore some answers more fully. After excluding incomplete questionnaires and questionnaires with outliers, we were left with 221 valid questionnaires, and thus we had a response rate of 44.2%.

The data collected via the sampling survey method raised concerns about common method bias (CMB). Thus, we adopted both procedural and statistical methods to reduce the concerns about CMB. Regarding the procedural methods, first, we used multiple items to measure the constructs, and, second, we assured the respondents that the questionnaire was anonymous. In terms of the statistical techniques, we applied Harman's single-factor test. The results from this test showed that the first factor accounted for 33.25% of the total variance, revealing that CMB was not a critical concern.

Table 1 reports the sample characteristics containing firm size, firm sales, ownership, green ratio, and International Organization for Standardization (ISO) certification. In terms of firm size, 81.9% of the firms had fewer than 1000 employees. Regarding firm sales, 81.02% of all the firms had average annual sales of less than 400 million yuan in the prior three years. In terms of ownership, 20.82% of the firms were state-owned enterprises (SOEs), 51.13% were private enterprises (PEs), and 28.05% were foreign-invested enterprises (FIEs). As for the green product ratio, 72.85% of the firms had green sales of less than 20% of total sales in the previous three years. Finally, pertaining to ISO 14,001, 61.91% of the firms had ISO certification.

We adapted the main items in this study from previous research, including studies on green process innovation (Mendes, 2012), financial performance (Chan, Yee, Dai & Lim, 2016), green social capital (Delgado-Verde et al., 2014), and customers’ tacit green needs (Cui & Wu, 2016); however, where appropriate, we modified items from the previous research to enhance our understanding of the specific Chinese context. The respondents were requested to assess the degree to which they agreed with various statements regarding their companies’ green innovation strategies and practices in the past three years (see Table 2). We assessed the items for the constructs by each respondent using a 5-point Likert scale, ranging from 1 = ‘strongly disagree’ to 5 = ‘strongly agree’.

Green process innovation. Adapted from Mendes (2012) and Chen et al. (2006)), we evaluated green process innovation in this study using five items (see Table 2): (a) investing in new technologies to prevent or reduce air, water, and soil pollution; (b) using new technologies for alternative energy sources; (c) introducing new technologies to reduce the emission of hazardous substances or waste generated during processing; (d) introducing new technologies to recycle waste and emissions, allowing them to be treated or reused; and (e) employing silencer equipment to reduce noise pollution. The Cronbach's alpha value of this scale was 0.920.

Financial performance. We measured financial performance using a four-item scale originally developed by Chan et al. (2016)). It included an evaluation of (a) profit/loss, (b) return on equity, (c) profit margin, and (d) return on assets.

Green social capital. As mentioned earlier, green social capital mainly relates to informal intra-organizational exchanges and experience sharing among employees and concerns environmental commitment and collaboration (Delgado-Verde et al., 2014). Adapting the work of Delgado-Verde et al. (2014)), we measured green social capital using five items: (a) appreciating the existence of informal contacts among employees to exchange information about the environmental aspects of the activity, (b) appreciating the existence of constructive discussions among employees to solve the environmental problems of the firm, (c) showing willingness on the part of employees to share their environmental knowledge and experiences, (d) embracing the idea of employees assisting each other to generate new ideas, and (e) supporting employees who assist one another to improve performance.

Customers’ tacit green needs. Adapted from Cui and Wu (2016) and Maletic et al. (2010)), we measured customers’ tacit green needs via four items: (a) it was difficult to put customers’ green needs in written form, (b) it was difficult to comprehensively document customers’ green needs in written form, (c) it was difficult to fully understand customers’ green needs from written documents, and (d) it was hard to precisely communicate customers’ green needs via written documents.

Controls. Given that prior research has indicated that particular characteristics of enterprises have highly influenced firms’ financial performance (Sheng & Chien, 2016; Subramaniam & Youndt, 2005), we used ownership type, firm size, firm sales, green product ratio, and ISO certification as our control variables. We assessed ownership via three types: (a) SOEs, (b) PEs, and (c) FIEs, and we measured firm size by the number of employees using a 4-item scale, from 1 = 〈 20 to 4 = 〉 1000. We also measured annual sales with a 4-item scale: 1 = 〈 3 million yuan to 4 = 〉 400 million yuan. We measured the green product ratio on a 5-item scale, from 1 = 〈 5% to 5 = 〉 31%. Lastly, we used the ISO14001 as a dummy control variable, whereby 1 meant that the respondent answered ‘yes’, but 0 otherwise.

Table 2 displays the results of the reliability and validity analysis for each variable. First, we can see that each latent variable factor loading was significant at the 0.001 level, and that the average standardized loading was mostly greater than 0.7, revealing that the factor structure was consistent with the theoretical expectations—and that the internal structural validity was acceptable. Second, we found that both the Cronbach's alpha value and the construct reliability (CR) were greater than 0.7, indicating that the scale reliability was acceptable. Third, the average variance extracted (AVE) values of all the variables were greater than the threshold value of 0.50, indicating that the convergence validity of each latent variable was within an acceptable range. Additionally, Table 2 also shows the full model fit index constructed by the confirmatory factor analysis (CFA). This indicated that the model fit the data well (χ2 = 294.00, p = 0.000, χ2/df = 2.070, GFI = 0.920, CFI = 0.957, IFI = 0.957, RMSEA = 0.070).

To test the main effect and the moderating effects, we constructed the models shown in Eq. (1) and Eq. (2), respectively. The first model examined the impact of green process innovation and green process innovation squared on a firm's financial performance. The second model examined how green social capital and customers’ tacit green needs moderated the curvilinear relationship between green process innovation and a firm's financial performance.

In these equations, FPEi, is the financial performance of firm i;  GPIi denotes the green process innovation of firm i; GPIi2 represents the squared term of green process innovation of firm i; GSCi  is the green social capital of firm i; CNTi signifies customers’ tacit green needs; and both GPIi * GSCi and GPIi2 * CNTi  are interaction terms. Further, Controls, stands for the control variables, including ownership type, firm size, annual sales, green product ratio, and ISO certification, whereas εi is a normal error term.

Our research contributes to the body of knowledge on green process innovation literature in three areas: First, this study contributes to green process innovation research by examining the U-shaped relationship between green process innovation and firms’ financial performance. More specifically, our findings revealed that firms pursuing green process innovations do not always experience higher financial performance than non-green innovative firms; rather, only a high level of green process innovation can enhance firms’ financial performance. This finding differs from the results of Miroshnychenko et al. (2017)) and Przychodzen et al. (2020)), who found that green process innovation has a positive linear effect on financial performance. At the same time, by conducting an in-depth analysis of the impact of different levels of green process innovation on firms’ financial performance, our study complements the work of previous researchers (e.g., Aguilera-Caracuel & Ortiz-de-Mandojana, 2013; Rezende et al., 2019). Overall, our study helps us better understand how firms’ financial performance differs, depending on the different levels of green process innovation.

Second, in this study, we theoretically and empirically examined the boundary conditions regarding how green social capital moderates the relationship between green process innovation and firms’ financial performance from the angle of internal factors. Although various studies have focused on the internal factors affecting green process innovation, such as in terms of management commitment and HR practices (e.g., El-Kassar & Singh, 2019), firm image (e.g., Ma et al., 2017; X. Xie et al., 2019b), or knowledge sharing (e.g., Wong, 2013), little research has examined the internal factors from the perspective of green social capital. To address this gap, we investigated the role of green social capital in the U-shaped relationship between green process innovation and firms’ financial performance, finding that the negative impact of green process innovation on financial performance is weakened when firms demonstrate a higher level of green social capital. This result suggests green social capital, defined as informal exchanges and experience sharing among employees, can reduce the potential for failure as firms pursue their green process innovations, as well as optimize the social relationships within the organization, both of which play a crucial role in enhancing green innovation performance (Chen et al., 2019). Therefore, green social capital can be seen as an internal information condition that helps firms pursuing green process innovation overcome challenges as they move in innovative green directions, thus positively affecting their financial performance. Overall, our work extends previous research by Chen et al. (2019), Delgado-Verde et al. (2014)), and Yadiati et al. (2019)) by providing a more nuanced understanding of how green social capital affects the performance of firms’ green process innovations. Furthermore, our findings also expand our current understanding of why some firms may succeed when they invest in green process innovation, whereas others do not.

Third, this study theoretically and empirically examined the contextual boundary of how customers’ tacit green needs moderate the relationship between green process innovation and firms’ financial performance from the angle of external factors. Prior research has examined the external factors that influence green process innovation, such as environmental regulations (e.g., Guo et al., 2018) and green subsidies (e.g., Xie et al., 2016), but little research has focused on external factors from the perspective of customers’ tacit green needs. To address this gap, we explored the effect of this tacitness on the relationship between green process innovation and firms’ financial performance, finding that the negative effect of green process innovation on firms’ financial performance is stronger when firms demonstrate a higher level of  green needs’ tacitness. This result reveals that firms with high green needs’ tacitness face a greater risk of losing their direction or relevance during the production process, which may lead to a significant decline in financial performance because they are unable to satisfy their customers’ green needs. Therefore, customers’ tacit green needs can be seen as an external factor that negatively affects the financial performance of innovative green process firms. This work complements previous studies (e.g., Zhang et al., 2015; (Zhang and Xiao, 2020)Zhang & Xiao, 2019), which asserted that innovation outcomes differ, depending on the level of customers’ tacit green needs. Overall, our work further enlarges our understanding of the relationship between green process innovation and firms’ financial performance in the context of customers’ tacit green needs, which expands the boundary conditions of green process innovation research.

As green process innovation become increasingly important for firms, our study presents managers with several important implications: First, our findings reveal there is an appropriate “inflection point” among the levels of green process innovation beyond which green process innovation can play a positive role in promoting firms’ financial performance. Accordingly, the level of green process innovation needs to be strengthened enough to make it across this inflection point to promote firms’ financial performance. From the managerial point of view, we thus suggest that greater investment should be made in green process innovations by taking the long view regarding the environmental and economic benefits of green process innovation.

Second, firms should leverage their internal green social capital to strengthen the benefits that come from their green process innovations. Given that green social capital is a critical factor for speeding up knowledge flow among employees within organizations, firms should take advantage of green social capital by enhancing their ability to communicate and share knowledge among employees to raise awareness of green process innovations. Furthermore, firm managers should employ appropriate human resource management strategies to foster these connections and exchanges, as well as increase trust and social cohesion among employees. Accordingly, if members feel more connected and supported, and they are willing to share information, this can reduce some of the isolation and fragmentation issues that can occur in the pursuit of green process innovation.

Third, firms should consider the level of customers’ tacit green needs to achieve better innovation outcomes. Our findings suggest successfully comprehending, translating, and absorbing customers’ tacit green needs play a key role in promoting green innovation practices. Therefore, managers should strive to overcome the challenges of identifying customers’ green needs. For example, firms might wish to consider allowing customers to participate in customer needs’ data analysis or to participate in the product design process ((Zhang and Xiao, 2020); Kobarg, Stumpf-Wollersheim, Schlägel & Welpe, 2020). According to Bretschneider and Zogaj (2016), the Ideas Competitions (or Ideas Communities), the Story Telling-Strategy, and the Observing Customer Activities-Strategy may encourage customers to verbalize and showcase their ideas. Particularly, in the Ideas Competitions, customers’ ideas expressed by short videos should be encouraged rather than written forms because managers can easily observe their actions and “translate” their tacit needs. Or, standardized questionnaire, interviews, or product trial session may allow managers to conduct more personalized interactions with the customers and exploit their tacit knowledge more efficiently. In this way, firms could utilize their customers’ creativity and knowledge (Cui & Wu, 2016) to successfully discover and translate their customers’ green needs and, in so doing, boost financial performance.

This study had several limitations: First, our findings came from survey data collected from companies in the Yangtze Delta Region, which, when considering all of China, is still a relatively small number of Chinese firms. Future analysis could expand the research scope to include more firms—and from other areas—as well. Second, the survey data provides a birds-eye analysis of how green process innovation can influence firms’ financial performance in multiple industry sectors. Therefore, upcoming research could go further to capture in-depth data in a particular industry, such as the inert sector (Ilg, 2019). Third, we only considered the moderating roles of green social capital and customers’ tacit green needs in the link between green process innovation and firms’ financial performance. However, there could be other factors, such as management commitment and HR practices (El-Kassar & Singh, 2019) or sociocultural and economic factors (Méndez-Picazo, Galindo-Martín & Castaño-Martínez, 2021), which could also have effects on firms’ green process innovation efforts. Thus, it is important to develop multiple moderators for green process innovation and use a larger firm-level data source to further examine this subject. Ultimately, we hope this study inspires more research on how green process innovation can promote firms’ financial performance in the modern economy, where there is an ever-increasing demand for firms to be more environmentally friendly.