Green Innovation and Export Performance in Emerging Market Firms: A Legitimacy-based View

Abstract

Whereas emerging market firms (EMFs) face severe legitimacy barriers when entering global markets, whether and under what conditions green innovation can help them gain legitimacy remains under-examined. This article argues that green innovation can help EMFs obtain regulatory and social legitimacy in host countries and consequently boost their exports. Based on a panel dataset populated by 254 Chinese-listed manufacturing companies from 2011 through 2017, this article finds that green innovation is positively associated with EMF export performance. Moreover, this positive relationship is stronger when host-country political risk is lower or host-country buyer sophistication is higher but becomes weaker for state-owned EMFs. These findings enrich the legitimacy-based view and international business literature by identifying the role of green innovation in boosting EMF export performance and specifying important institutional contingencies.

摘要

新兴市场企业在进入全球市场时，常常面临严重的合法性障碍。然而，绿色创新是否能够帮助它们获得合法性，以及在何种条件下能发挥作用，却鲜有深入探讨。本文认为，绿色创新可以帮助新兴市场企业在东道国获得监管合法性和社会合法性，从而促进其出口。通过分析2011 至2017 年间254 家中国制造业上市公司的面板数据，我们发现新兴市场企业的绿色创新与其出口绩效呈正相关。而且，这种关系在东道国的政治风险较低或者顾客成熟度较高时，得到加强。相反，这种关系对于国有企业却会变弱。

Introduction

Although emerging market firms (EMFs) now account for almost half of world trade (World Trade Organization, 2021), they are often perceived skeptically by stakeholders in host countries when going abroad (Deng, Delios, & Peng, 2020; Zhang, 2022). Two factors cause EMFs to face legitimacy barriers. First, because EMFs tend to be less transparent and competent than developed market firms (Li, Li, & Wang, 2019), host-country stakeholders such as governments, business partners, not-for-profit organizations, and the public may be skeptical, concerned, and reluctant to accept EMFs. Second, because EMFs come from under-developed institutional environments and immature economic conditions (Marano, Tashman, & Kostova, 2017), their exported products and services are deemed low-end and inferior. Given that these barriers seriously undermine the potential for further global expansion by EMFs, it is critical to understand how EMFs can overcome legitimacy barriers in host countries to foster their exports.

To answer this question, prior studies have examined various approaches, such as reporting corporate social responsibility activity (Marano, Tashman, & Kostova, 2017), developing social capital (Amankwah-Amoah & Debrah, 2017), and employing host country nationals (Bertrand, Betschinger, & Moschieri, 2021). While insightful and enlightening, these approaches may not be suitable for exporters. As EMFs normally export their products via intermediaries, they cannot develop social capital in host countries or employ host-country nationals, and neither will they report corporate social responsibility activity in host countries.

Meanwhile, given rising concern for environmental protection, green innovation has become a critical means by which firms can gain legitimacy (Shu, Zhou, Xiao, & Gao, 2016; Reihlen, Schlapfner, Seeger, & Trittin-Ulbrich, 2022). Green innovation refers to the development of new products, processes, and technologies that save energy, prevent pollution, and recycle waste (Huang & Li, 2017; Kawai, Strange, & Zucchella, 2018). Green innovation is often reflected in patents which include green technologies for environmental protection, preservation, and restoration (Schiederig, Tietze, & Herstatt, 2012). The Chinese Research Data Services (CNRDS) compile patent data from Google patents and other official sources and label a patent as ‘green’ based on the International Patent Classification (IPC) Green Inventory, published by the World Intellectual Property Organization (WIPO). This international standard classification for green patents means that green patents obtained in China have to undergo strict scrutiny by patent offices (Orazi & Chan, 2020) and can attain international recognition. As such, green innovation becomes a strong and credible signal based on which stakeholders decide whether and to what extent EMFs are legitimate (Wei, Shen, Zhou, & Li, 2017). Accordingly, green innovation likely helps EMFs overcome legitimacy barriers and obtain market acceptance by host stakeholders. However, prior studies have overlooked this critical approach, which motivates us to take a legitimacy-based view to examine how green innovation affects EMF export performance.

As legitimacy is socially constructed, the legitimation process depends heavily on stakeholders’ perceptions and expectations, which are strongly influenced by regulatory, normative, and cognitive institutional pillars (Suchman, 1995; Suddaby, Bitektine, & Haack, 2017). Accordingly, we consider three moderators – host-country political risk, host-country buyer sophistication, and ownership status (whether EMFs are state-owned or not) – to represent the regulatory, normative, and cognitive pillars, respectively (Scott, 1995, 2001). Political risk reflects the degree of uncertainty triggered by host-country political changes, such as protests, boycotts, terrorism, riots, reneging on contracts, or unexpected restrictions on transfers of money, people, and goods (Cosset & Suret, 1995). Political risk leads to changes in laws, rules, and regulations and determines the extent to which these regulatory institutions have been enforced (Scott, 2001). Thus, political risk reflects the quality of the regulatory pillar in a host country. Buyer sophistication refers to buyers’ standards for product performance and their knowledge of technical specifications (Li, 1999). In a country with high buyer sophistication, specialization and professionalization are preferred and prioritized, and offering high-quality products and increasing productivity become business norms (Bruton, Ahlstrom, & Li, 2010). As such, buyer sophistication reflects the normative institutional pillar in host markets. State ownership status reflects whether a company is a state-owned enterprise (SOE) or not (Zhou, Gao, & Zhao, 2017). Compared with non-SOEs, SOEs are usually perceived by host-country stakeholders as politicized, less transparent, and less competent (Li, Xia, Shapiro, & Lin, 2018; Tang, Shu, & Zhou, 2022). As a result, host stakeholders likely view SOEs negatively (Cuervo-Cazurra & Li, 2021), making SOE status an indicator of the cognitive pillar of stakeholders in host countries.

We test our hypotheses with a sample of listed manufacturing companies that operate in China, the largest exporter in the world (World Trade Organization, 2021). China has also become a powerhouse in developing green innovation and has been a leading investor in renewable energy since 2012 (REN21, 2021). China thus offers a suitable context in which to examine green innovation and exports. With strong empirical support, our study offers three contributions. First, this study enriches prior EMF research by proposing green innovation as an important mechanism enabling EMFs to overcome legitimacy barriers in host countries. Previous research on EMFs has predominantly focused on their capabilities, liabilities, and location choices (Deng et al., 2020; Wright, Filatotchev, Hoskisson, & Peng, 2005; Xia, Ma, Lu, & Yiu, 2014; Zhou, Hui, Zhou, & Gong, 2022). However, we contend that EMFs have to overcome legitimacy challenges in order to survive and thrive in host countries. Although prior studies shed some light on how to overcome legitimacy challenges (Bertrand et al., 2021; Hunter & Bansal, 2007; Marano et al., 2017), the role of green innovation as a legitimacy-building mechanism has been ignored. Therefore, our research offers a complete framework of whether and how green innovation can help EMFs overcome legitimacy barriers.

Second, our study shows that green innovation can enhance EMF export performance, which adds to the international business literature on EMF exports by identifying a novel antecedent. Existing literature on the relationship between innovation and internationalization has primarily focused on how internationalization regarded as a learning process influences innovation (Chiarvesio, Marchi, & Maria, 2015; Kim, Pantzalis, & Zhang, 2021), but relatively little attention has been given to how EMFs’ domestic innovation affects their internationalization. As China has increasingly become an innovation powerhouse, especially in the realm of green innovation, and has transformed itself into an ‘innovative internationalizer’ (Zhou et al., 2017), our study enriches the internationalization literature by embracing a novel perspective to examine an important driver, green innovation, for EMFs’ successful internationalization.

Third, this research identifies critical institutional pillars that moderate the effects of green innovation on export performance, offering more nuanced evidence of when EMFs can export successfully. We particularly consider three moderators – host-country political risk, host-country buyer sophistication, and EMFs’ ownership status (whether a firm operates under state or non-state ownership) – to map onto the regulatory, normative, and cognitive pillars of host countries, respectively. We thus enrich and expand the EMFs’ internationalization literature by more comprehensively examining the three institutional pillars as contingencies.

Theoretical Framework

A Legitimacy-based View of EMFs’ Export

Legitimacy is ‘a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions’ (Suchman, 1995: 574). The legitimacy-based view suggests that, to increase their chances of survival, firms have to seek legitimacy by adjusting to a set of external institutional pressures (Scott, 1995, 2001; Suchman, 1995). It is the degree of fit between firms’ attributes and external stakeholders’ expectations that decides whether and to what extent firms are legitimate (Ruef & Scott, 1998). As such, legitimacy determines organizational survival and development (Zimmerman & Zeitz, 2002).

Legitimacy is typically classified into two types – regulatory legitimacy and social legitimacy – because regulatory bodies and social audiences are the two primary sources of legitimacy (Bitektine, 2011; Zhang, 2022). Host governments are particularly interested in observing and evaluating whether EMFs’ activities and characteristics are consistent with the governments’ long-term economic, political, and social goals (Stevens, Xie, & Peng, 2016). EMFs can meet regulatory requirements in host countries only when they can obtain regulatory approval and market entry permits.

Moreover, EMF practices and products can also be evaluated in host countries by a broad set of social groups such as suppliers, customers, competitors, media, and the public (Luo & Tung, 2007; Stevens et al., 2016). These social constituencies can provide or withhold their acceptance of EMFs, depending on whether the firms’ activities and practices are perceived as consistent with their social norms, cultural values, and societal taken-for-grantedness (Palazzo & Scherer, 2006). Social legitimacy is thus essential for EMFs because it determines the extent to which their market offerings are accepted by host customers.

The legitimacy-based view indicates that organizations should conform to their environments to build legitimacy (Suchman, 1995). A conforming organization adapts its practices to the requirements and expectations of a variety of constituencies (Baumann-Pauly, Scherer, & Palazzo, 2016). Green innovation reflected by green patents is an important channel and signal through which innovators can comply with regulations, rules, social expectations, and business norms regarding environmental issues (Shu et al., 2016; Wei et al., 2017). We therefore suggest that green innovation provides a viable strategy that EMFs can deploy to build legitimacy and subsequently foster their exports. In particular, green innovation can help EMFs gain regulatory legitimacy by abiding by environmental regulations and in that way overcome entry barriers and obtain green certificates (Bansal & Clelland, 2004), possibly increasing EMFs’ social legitimacy by building environmentally friendly images and advocating norms and values that warrant stakeholders’ endorsements and support (Ambec & Lanoie, 2008; Shu, Zhao, Liu, & Lindsay, 2020).

Institutional Contingencies

When exporting their products, EMFs may be confronted with higher entry barriers set up by host countries rather than export constraints imposed by their home countries. As such, we focus on institutional pillars in host countries as important contingencies, because the legitimization process is strongly influenced by the surrounding regulatory, normative, and cognitive institutional pillars (Scott, 1995, 2001; Zhang, 2022). The regulatory pillar rests on the setting, monitoring, and enforcing of rules, laws, and regulations (Xu & Shenkar, 2002). These regulatory institutions generate pressure on EMFs to comply with laws and rules when they enter and operate in host countries (Zhou et al., 2022). If regulatory institutions are not stable and fairly enforced in host countries, EMFs have to deal with ambiguous and opaque rules and regulations, increasing the difficulties they face in overcoming legitimacy barriers in those countries (Kolk & Curran, 2017; Ramachandran & Pant, 2010). In particular, host-country political risk may change the rules of the game, trigger high operational uncertainties, increase political friction, and muddle the standards applied when evaluating EMFs (Cosset & Suret, 1995; Lee, Jiménez, Yang, & Song, 2020; Witte, Burger, & Pennings, 2020). In this regard, we consider host-country political risk an essential regulatory pillar for the efficacy of green innovation.

The normative pillar represents widely accepted norms and patterns of organizational and individual behaviors and practices based on obligatory dimensions of social, professional, and organizational interactions (Scott, 1995, 2001). Buyer sophistication reflects the extent to which customers are hard to please when making purchase decisions as well as the depth of customers’ knowledge of market offerings (Hasija, Liou, & Ellstrand, 2020; Wheelwright & Clark, 1992). When buyer sophistication in a host country is highly developed, EMFs have to endeavor to enhance their products’ advantages through customization and excellent customer relationship management (Li, 1999). As such, specialization and professionalization would become norms and widely accepted values and beliefs rather than special cases in host countries (Bruton et al., 2010). Therefore, we regard host-country buyer sophistication as a normative pillar that can affect how green innovation can drive EMFs’ exports.

The cognitive pillar involves taken-for-grantedness and preconscious behaviors that people practice but barely think about (Suddaby, Elsbach, Greenwood, Meyer, & Zilber, 2010). The cognitive frame in host countries determines whether and to what extent EMFs are accepted by host-country stakeholders (He & Zhang, 2018). SOEs comprise a large share of exporters from emerging markets (UNCTAD, 2021). Inasmuch as SOEs likely have political agendas (Tang et al., 2022), host-country stakeholders may be skeptical of their internationalization aims, concerned over their political ideology, and suspicious of their product quality and operational capability. As such, by affecting the cognition of host-country stakeholders, SOE status may determine how EMFs are perceived and evaluated by these stakeholders. Figure 1 shows our conceptual model and hypotheses.

Figure 1. Conceptual model and hypotheses

Hypotheses

Green Innovation and Export Performance

We argue that because green innovation as reflected by green patents can send strong and credible signals to host country stakeholders such as the government, suppliers, customers, and the public, it can help EMFs obtain both regulatory and social legitimacy in host countries and can thus boost their export performance.

First, green innovation enables EMFs to gain acceptance and approval by a host country's government, lowering regulatory barriers. Only when products exported by EMFs can meet related regulatory requirements can EMFs be allowed to enter host countries. As developing countries typically lag behind developed countries in environmental protection and preservation (Shu et al., 2016), EMFs face negative perceptions and unfavorable stereotypes that often portray them as environmentally unfriendly and seekers of pollution havens (Du, 2015). Powered by green technologies and patents, EMFs can develop green products, use green packaging, embrace green production, and employ end-of-pipe pollution-processing methods (Wang et al., 2022). By using these green practices, EMFs should be able to mitigate unfavorable perceptions, reverse unfriendly stereotypes, and satisfy environmental laws and regulations in host countries. Therefore, green innovation can send favorable signals to regulatory stakeholders in host countries and thus should help EMFs acquire regulatory legitimacy and overcome entry barriers in these countries (Huang & Li, 2017; Li, Huang, Ren, Chen, & Ning, 2018).

Second, green innovation helps EMFs gain social legitimacy because green patents are favored worldwide and going green has become a widely accepted business practice (Junior, Best, & Cotter, 2014). Green technologies and products can help firms cut carbon emissions, reduce pollution, and protect human health, so green innovation can help EMFs gain social recognition and acceptance from business partners, customers, and the public (Suchman, 1995). Moreover, EMFs can gain strong support in host countries if their green practices and activities are consistent with business guidelines and industry standards (Berrone, Fosfuri, Gelabert, & Gomez-Mejia, 2013) and are aligned with the public's awareness of and interest in environmental protection and preservation (Shu et al., 2016; Shu, Liu, Zhao, & Davidson, 2020). In this circumstance, based on a significant and credible signaling effect of green patents, EMFs can establish intimate business partnerships, secure more favorable financial support, and win customer patronage and loyalty (Richey, Musgrove, Gillison, & Gabler, 2014). As such, EMFs’ export performance could be enhanced by green innovation.

Hypothesis 1 (H1): Green innovation in an emerging market firm is positively associated with its export performance.

The Moderating Role of Host-Country Political Risk

Political risk reflects uncertainty and discontinuity in laws, regulations, and their enforcement, creating ‘explicit barriers to capital flows, taxes, expropriation, [and] exchange controls’ (Cosset & Suret, 1995: 302). We thus suggest that political risk may weaken the positive effect of green innovation on export performance.

First, host-country political risk may reduce the potential for green innovation to help EMFs gain regulatory legitimacy in host countries. Green innovation could signal to host country stakeholders that an EMF is willing to conform to the expectations, has a long-term commitment to reduce emission, and offers a more substantive response to local institutional demands (Berrone et al., 2013; Galbreath, 2019; Ren, Huang, Liu, & Yan, 2023). However, when host-country political risk is high, the host government is unable or unwilling to offer fair and credible policies and impose effective regulations and often unexpectedly changes rules and regulations (Lee et al., 2020; Li & Filer, 2007). Under this circumstance, EMFs’ green practices and efforts may not be fully recognized or quickly recognized and approved by host regulators, as the instability and discontinuity of host governments may prevent them from enforcing their environmental regulations fully or in a timely way. The regulatory legitimacy-building effect of green innovation may encounter obstacles due to bureaucratic red tape, unclear and arbitrarily enforced rules, and corruption under high political instability (Chan & Makino, 2007). As such, the signaling benefit of green innovation may be challenged and weakened by political risk (Rodriguez, Uhlenbruck, & Eden, 2005). Moreover, political risk also leads to a hostile and unstable business environment, high transaction costs, and operational risks (Kolk & Curran, 2017; Witte et al., 2020), which may create additional difficulties and costs for EMFs signaling to host-governments and seeking their approval for entry and operations.

Second, host-country political risk also undermines the efficacy with which green innovation can help EMFs gain social legitimacy. Political risk triggers societal instability and business uncertainty, forcing suppliers, customers, and the public to adopt a short-term orientation and focus on quick returns (Lee et al., 2020). Therefore, the signaling effect of green innovation could be eroded when host-country political risk leads to changes and insufficient enforcement of green business norms and practices. In this case, host markets may be suspicious of the quality and green features of EMFs’ products because of their lack of legitimacy. In addition, as protecting and restoring the environment takes a long time and requires input over generations, the value of EMFs’ green practices and activities may be under-estimated and ignored by a host society in a politically risky environment. If an EMF's activities are not recognized or favored by a host market, customers there may not purchase its products and services (London & Hart, 2004). As a result, host-country political risk may undermine the role that green innovation plays in building social legitimacy, thus weakening the effect of green innovation on export performance. Therefore, we propose:

Hypothesis 2 (H2): The positive relationship between green innovation and export performance becomes weaker when host-country political risk is higher.

The Moderating Role of Host-Country Buyer Sophistication

Buyer sophistication is characterized by demanding and knowledgeable customers (Hasija et al., 2020). We thus suggest that host-country buyer sophistication may enhance the positive impact of green innovation on EMFs’ export performance. First, host-country buyer sophistication can augment the role of green innovation in building regulatory legitimacy and subsequently enhance its effect on promoting exports. When host-country buyers become more sophisticated, demanding, and knowledgeable, they are more easily capable of accurately evaluating the quality of EMFs’ market offerings (Green, Zimmerer, & Steadman, 1994). Green innovation can help protect the national environment, improve working conditions, and enhance the efficiency of resource consumption (Chang, 2011). As a result, sophisticated buyers in host countries may be more likely to recognize these benefits of green innovation and thus more likely to support the government's efforts to implement strict environmental regulations on imports. In this case, the positive role of EMFs’ green innovation in gaining regulatory legitimacy in host countries could be augmented when host-country buyer sophistication rises.

Second, host-country buyer sophistication can also enhance the role that green innovation plays in building social legitimacy for EMFs in host countries and therefore strengthen the effect of green innovation on export performance. When buyers in a host country are highly sophisticated, they are better able to detect nuances and differences among market offerings and more willing to purchase environmentally friendly products (York & Venkataraman, 2010). In this case, marketing offerings supported by green innovation are more likely to stand out and the benefits of green innovation could be better recognized and accepted by stakeholders in host countries. In addition, green products can instill customer pride and trust (Khachatryan, Rihn, & Wei, 2021), which can increase social acceptance of these products. For example, a recent study shows that products with eco-labels can enhance customer pride, which in turn forms customers’ beliefs regarding product quality and safety (Donato & D'Aniello, 2022). The above discussion leads us to propose that:

Hypothesis 3 (H3): The positive relationship between green innovation and export performance becomes stronger when host-country buyer sophistication is higher.

The Moderating Role of SOE Status

State ownership is an important mechanism that has been used extensively by governments in emerging countries to intervene in their economies (Luo, Xue, & Han, 2010; Zhou et al., 2017). SOE status thus becomes a robust and reliable signal to host-country governments, partners, media, and publics that informs their perceptions and judgments of EMFs (Li, Li et al., 2019). Because SOE status can influence the cognition and judgment of stakeholders in host countries, we therefore suggest that SOE status could also moderate the effect of EMFs’ green innovation on export performance.

First, SOE status may reduce the role that green innovation plays in gaining regulatory legitimacy in host countries and thus weaken the effect of green innovation on EMF export performance. An SOE is usually perceived as an entity that speaks for a home-country government, acting on behalf of the government to exercise and fulfill certain political objectives and ideological agendas (Cui & Jiang, 2012). As such, the host-country government may perceive the entry of an SOE as a political threat, worry about its political independence, and therefore disapprove SOEs’ market-entry applications, withhold business certificates, and hesitate to recognize their business practices (Cannizzaro & Weiner, 2018; Cuervo-Cazurra, Inkpen, Musacchio, & Ramaswamy, 2014). Therefore, SOEs face greater challenges than non-SOEs in obtaining and building regulatory legitimacy in host countries. Although green innovation could help EMFs obtain regulatory legitimacy in host countries, political concerns may overrun environmental gains. As such, when the benefits of green innovation with respect to regulatory legitimacy in host countries are attenuated, the impact of green innovation on EMF export performance is weakened.

Second, SOE status may also reduce the efficacy of green innovation in building social legitimacy in host countries and, in turn, weaken the positive effect of green innovation on export performance. Although SOEs are legally independent entities, they are owned by home-country governments, leaving them in a condition of incomplete dependence (Du & Luo, 2016; Zhou et al., 2017). Such a dependent status may lead host-country stakeholders to form unfavorable and even negative perceptions of SOEs as inefficient, non-transparent, incompetent, and wasteful of resources (Cuervo-Cazurra et al., 2014; Li, Li et al., 2019; Tang et al., 2022). These unfavorable perceptions and impressions of SOEs from emerging markets may cancel out the social legitimacy brought by green innovation (Kalasin, Cuervo-Cazurra, & Ramamurti, 2020), consequently reducing business partners’ support and acceptance of SOEs and harming EMFs’ export performance. Thus, we predict:

Hypothesis 4 (H4): The positive relationship between green innovation and export performance becomes weaker for SOEs than for non-SOEs.

Methods

Sample and Data Collection

Our sample consists of Chinese manufacturing firms listed on the Shenzhen or Shanghai stock exchanges for the period spanning 2011 through 2017. We choose this time frame for two reasons. First, policy changes require Chinese exporters to commit to developing and commercializing green innovation. China's Twelfth Five-Year Plan for National Economic and Social Development began in 2011, and an environmental tax was also implemented in this period, requiring firms to invest in environmental protection and preservation. Second, environmental pollution has attracted significant public attention and, in 2011, Chinese firms began to disclose information in their annual reports regarding green innovation (Li, Huang et al., 2018). We focus on the manufacturing sector for two reasons: (1) this sector is a main source of pollution, producing a large amount of gas, water, and materials pollution (Li, Qiao, & Shi, 2019); (2) this sector holds a large number of green patents (Chang, 2011) and accounts for a large portion of exports (Efrat, Hughes, Nemkova, Souchon, & Sy-Changco, 2018).

We construct a sample of A-share listed manufacturing firms. We exclude firms that are suspended from listing, firms that receive ‘special treatment’, firms with no export data, and firms with missing information for key variables such as green innovation. In the end, we obtained 254 manufacturing firms for the period running from 2011 through 2017 with 1,524 firm-year observations. To avoid finding reverse causality, we lag explanatory variables by one year and thus the observation window for our explanatory variables runs from 2011 through 2016 while that for our dependent variable runs from 2012 through 2017.

We compile our dataset from multiple sources. We collect data on listed companies’ export sales from WIND. We obtain patent data from the Chinese Research Data Services Platform (CNRDS) to construct the measure of green innovation (Li, Xu, & Ramanathan, 2022). Information on export destinations is gathered from the General Administration of Customs of P. R. China (GAC), information on political risk is gathered from the International Country Risk Guide (ICRG) (Datta, Musteen, & Basuil, 2015), buyer sophistication is based on the Global Competitiveness Report published by the World Economic Forum¹ (Hasija et al., 2020), and China Stock Market & Accounting Research (CSMAR) is the information source for measuring state ownership. These data sources have been widely used in recent business studies (Xu, Zhou, & Du, 2019; Zhou et al., 2017). Table 1 presents the measures and data sources for the studied variables.

Table 1. Measurements and data sources

Measurements

Export performance

Consistent with prior studies (Jean, Kim, Zhou, & Cavusgil, 2021; Li, Liu, & Qian, 2019), we use a firm's export sales to measure its export performance. We specify a firm's export sales as the natural logarithm of total export sales (in thousands of US dollars) to all countries (Katsikeas, Leonidou, & Morgan, 2000). We use the volume of export sales rather than export intensity (measured by the ratio of export sales to total sales) because the latter reflects the extent of a firm's internationalization but not the actual income and revenue from internationalization (Verwaal & Donkers, 2002). Moreover, the value of export intensity is determined by both export sales and domestic sales, which cannot accurately reflect changes in export sales.

Green innovation

Consistent with prior studies (Li, Huang et al., 2018; Yuan, Ye, & Sun, 2021), we use the number of granted green patents (including both green invention patents and green utility patents) as a measure of green innovation. Granted green patents are more appropriate for representing a firm's actual situation regarding green innovation than green patent applications (Berrone et al., 2013). The green patent data are obtained from the CNRDS platform which extracts patent data from official sources such as Google patents. By relying on the IPC's Green Inventory presented by WIPO, CNRDS determines whether a patent is a green patent or not. This inventory is developed by the IPC committee of experts to facilitate patent information search related to Environmentally Sound Technologies, as defined by the United Nations Framework Convention on Climate Change. It covers six specific fields: the alternative energy production, transportation, energy conservation, waste management, agriculture/forestry, administrative, regulatory or design aspects, and nuclear power generation. Specifically, if a patent's IPC classification falls within the categories of C10L3/00, F02C3/28, H01M4/86, H01M8/00, H01M12/00, F03D, F24J1/00, F24J3/00, F24J3/06, B61, H02J, E04B1/62, E04B1/74, E04B1/88, E04BA/90, or F03G7/08, it is classified as a green patent. Green patents based on IPCs include only two types of patents: invention and utility model patents, both of which represent significant technological improvements.

Host-country political risk

We first obtain information indicating export destinations and each destination's export sales from the GAC, and we calculate a weighted political risk score for each exporter with $\sum i$ = the exporter's sales to market i / the exporter's global sales, whereas i = the exporter's ith international market (Kobrin, 1991; Salomon & Shaver, 2005). Following well-accepted practices (Li, Xia et al., 2018), we exclude Hong Kong, Macau, the Cayman Islands, and other tax havens as export destinations. The political-risk index scores are collected from the ICRG by year and firm. The ICRG consists of 12 indicators and totals 100 points: government stability (12 points), socioeconomic conditions (12 points), investment profile (12 points), internal conflicts (12 points), external conflicts (12 points), corruption (6 points), military in politics (6 points), religious tensions (6 points), law and order (6 points), ethnic tensions (6 points), democratic accountability (6 points), and bureaucracy quality (4 points). A higher index score indicates lower political risk in a given country. To facilitate interpretation, we reverse-code this variable as (100 –index value) such that a higher value indicates higher political risk.

Host-country buyer sophistication

We define this variable by reference to the weighted measure of the buyer sophistication index. Buyer sophistication is characterized by the quality strictness of buyer's requirements for product performance and their knowledge of technical specifications (Li, 1999). The item, labeled ‘buyer sophistication’, asked executives, ‘In your country, on what basis do buyers make purchasing decisions? [1 = based solely on the lowest price; 7 = based on sophisticated performance attributes]’ (Fainshmidt, Smith, & Judge, 2016). The index range from 1 to 7, with 1 indicating the least and 7 indicating the greatest buyer sophistication.

SOE status

We capture SOE status with a dummy variable because, in the eyes of host stakeholders, an EMF is either an SOE or it is not. As such, we measure SOE status depending on whether the ultimate control lies with the government and its agencies or not (1 = yes; 0 = not) (Zhou et al., 2017). In robustness checks, we treat state ownership as a continuous variable by using the state share percentage of the top ten shareholders (information taken from the Wind database) (Xia et al., 2014).

Control variables

As firm age and firm size can affect the capacity to intensify foreign activities given the scale, resource, and legitimacy challenges they present (Bertrand et al., 2021), we control for firm age (measured by the natural logarithm of the number of years since a firm's establishment) and firm size (as the natural logarithm of total employees). Because organizational slack consists of having resources that can be diverted or redeployed for other purposes and critically affect a firm's ability to grow in foreign markets, we use the natural logarithm of ‘(current ratio + asset-liability ratio + cost-to-income ratio) / 3’ to control for organizational slack (Xu et al., 2019). We consider ROA (return on assets) in the preceding year to capture the impact of past performance because ROA captures a firm's efficiency and reflects internal decision-making related to capabilities and performance (Li, Huang et al., 2018). We use R&D expenses divided by operating income to control for R&D intensity, as R&D intensity is associated with increased penetration of export markets (Zhou et al., 2017).

Industry competition forces firms to respond quickly to market demand and develop innovative products to meet customers’ preferences, so we further control for industry competition with ‘1 minus the Herfindahl-Hirschman index (HHI)’ (Zhou et al., 2017). HHI is a widely accepted measure of industry competition and is calculated by squaring the market share of each firm that competes in a given industry and then summing the resulting numbers. The identification of an Industry is based on the classification provided by the China Securities Regulatory Commission. ${\rm HHI} = \mathop \sum \limits_{i = 1}^n ( {X_i/X} ) ^2$, where X _i is the sales revenue of firm i in an industry, X is total sales revenue for all firms in the industry, and n is the number of firms. A high HHI score represents weak competition. Export history is included because previous export experience may lead firms to increase their export commitments and structure their export activities more effectively (Jean et al., 2021). Marketing intensity can help boost export performance, so we control for marketing intensity, calculated as the ratio of sales expenses to operating income (Kotabe, Srinivasan, & Aulakh, 2002). Considering that export market diversity signals firms’ capabilities and prospects and helps them achieve more significant economies of scale by trading in multiple countries, we control for export market diversity, which is calculated by the entropy measure (Jean et al., 2021). The entropy-type formula for export market diversity (EMD) is $EMD = \mathop \sum \limits_i [ {P_I \times ln( {1/P_I} ) } ]$, where P _I is the share of export market region I for each firm, and ln (1/P _I) is the weight given to each export market region, as defined by the natural logarithm of the inverse of its sales (Zahra, Ireland, & Hitt, 2000). We also include five year dummy variables to control for time effects and five sub-industry dummies to control for industry effects (1 = computer, communications, and other electronic equipment manufacturing, 2 = automotive manufacturing, 3 = electrical machinery and equipment manufacturing, 4 = general equipment manufacturing, 5 = paper products manufacturing, 0 = others). Table 2 summarizes the descriptive statistics for and correlations between all variables.

Table 2. Descriptive statistics and correlations

Notes: N = 1,524; *** p < 0.001, ** p < 0.01, * p < 0.05, ⁺p < 0.1 (two-tailed); year dummies and sub-industry type dummies are not shown.

Estimation

To address the threat of endogeneity, we use a two-stage least squares (2SLS) regression method and employ the industry average of green innovation (excluding focal firms) as an instrumental variable. The industry average of green innovation creates an industrial norm that can motivate a focal firm to develop green innovation. As such, the industry average of green innovation is positively related to a focal firm's green innovation, but it will not directly affect the focal firm's export performance, making it a suitable instrumental variable in our study. We mean-center the explanatory variables before creating their interaction terms (Aiken & West, 1991). To reduce endogeneity bias we also lag all independent and control variables in the following models:

Stage 1:

$$\eqalign{{\rm G}{\rm I}_{{\rm it}} & = \alpha _0 + \alpha _1{\rm IG}{\rm I}_{{\rm i}( {t-1} ) } + \alpha _2{\rm Ag}{\rm e}_{i( {t-1} ) } + \alpha _3{\rm Siz}{\rm e}_{i( {t-1} ) } + \alpha _4{\rm Slac}{\rm k}_{i( {t-1} ) } + \alpha _5{\rm RO}{\rm A}_{i( {t-1} ) } + \alpha _6{\rm RD}{\rm I}_{i( {t-1} ) } \cr & \hskip10pt+ \alpha _7{\rm I}{\rm C}_{i( {t-1} ) } + \alpha _8{\rm E}{\rm H}_{i( {t-1} ) } + \alpha _9{\rm M}{\rm I}_{i( t-1) } + \alpha _{10}{\rm EM}{\rm D}_{i( {t-1} ) } + \alpha _{11}{\rm I}{\rm T}_{i( t-1) } + \alpha _{12}{\rm Year} + \varepsilon _{i( t-1) }, \;} $$

Stage 2:

$$\eqalign{{\rm Expor}{\rm t}_{it} & = \beta _0 + \beta _1\widehat{{GI}}_{i( {t-1} ) } + \beta _2{\rm P}{\rm R}_{i( t-1) } + \beta _3{\rm P}{\rm R}_{i( {t-1} ) \ast }\widehat{{GI}}_{i( {t-1} ) } + \beta _4{\rm B}{\rm S}_{i( t-1) } + \beta _5{\rm B}{\rm S}_{i( {t-1} ) \ast }\widehat{{GI}}_{i( {t-1} ) } \cr & \quad+ \beta _6{\rm S}{\rm O}_{i( t-1) } + \beta _7{\rm S}{\rm O}_{i( {t-1} ) \ast }\widehat{{GI}}_{i( {t-1} ) } + \beta _8{\rm Ag}{\rm e}_{i( t-1) } + \beta _9{\rm Siz}{\rm e}_{i( t-1) } + \beta _{10}{\rm Slac}{\rm k}_{i( t-1) } + \beta _{11}{\rm RO}{\rm A}_{i( t-1) } \cr & \quad+ \beta _{12}{\rm RD}{\rm I}_{i( t-1) } + \beta _{13}{\rm I}{\rm C}_{i( t-1) } + \beta _{14}{\rm E}{\rm H}_{i( t-1) } + \beta _{15}{\rm M}{\rm I}_{i( t-1) } + \beta _{16}{\rm EM\ }{\rm D}_{i( t-1) } + \beta _{17}{\rm I}{\rm T}_{i( t-1) } \cr & \quad+ \beta _{18}{\rm Year} + \varepsilon _{i( t-1) }, \;} $$

where: i and t index firm and year. Export means export sales, GI means green innovation, $\widehat{{GI}}$ means the predicted value of GI, IGI means industry average of green innovation (excluding the focal firm), PR means political risk, BS means buyer sophistication, and SO means state ownership. Age, Size, Slack, ROA, RDI, IC, EH, MI, EMD, IT, and Year are the control variables in the model, representing firm age, firm size, organizational slack, return on assets, R&D intensity, industry competition, export history, marketing intensity, export market diversity, sub-industry dummies, and year dummies, respectively.

Results

Hypothesis Testing

The results of the 2SLS regression analysis are reported in Table 3. Model 1 produces the predicted value of green innovation, model 2 includes the independent and control variables, models 3–5 add the interaction effects of each moderator, and model 6 is the full model. The results obtained with model 1 reveal that the industry average of green innovation is significantly related to focal firms’ green innovation (b = 0.15, p = 0.00). Thus, the instrumental variable – the industry average of green innovation – meets the exclusion restriction.

Table 3. Results of 2SLS regressions

Notes: N = 1,524; t-statistics in parentheses; *** p < 0.001, ** p < 0.01, * p < 0.05, ⁺p < 0.1 (two-tailed); year dummies and sub-industry type dummies are not shown.

We use models 2 through 6 as reported in Table 3 to calculate and report the results of the second-stage estimations. The results obtained with models 2 and 6 and reported in Table 3 also show that green innovation is positively associated with export performance (b = 0.51, p < 0.01; b = 1.54, p < 0.01), supporting H1.

The results obtained with models 3 and 6 reveal support for H2, as the interaction terms between green innovation and host-country political risk in these two models are negative and significant (b = −0.52, p < 0.05; b = −0.49, p < 0.05, respectively). To facilitate interpretation, we plot the interaction effects in Figure 2 based on the results for model 7 shown in Table 3. As the results plotted in panel A indicate, the positive relationship between green innovation and export performance becomes weaker when the level of political risk is high (b = 0.37, p < 0.01) than when it is low (b = 0.43, p < 0.05).

Figure 2. Moderating effects

The results obtained with models 4 and 6 reveal support for H3 because significant and positive interaction terms between host-country buyer sophistication and green innovation on export performance are observed with these two models (b = 0.25, p < 0.05; b = 0.28, p < 0.05, respectively). The results plotted in panel B of Figure 2 indicate that the positive relationship between green innovation and export performance becomes stronger when the value of buyer sophistication is high (i.e., 1 SD above the mean) (b = 0.64, p < 0.05) than when it is low (i.e., 1 SD below the mean) (b = 0.33, p < 0.01).

The results obtained with models 5 and 6 support H4 as the interaction terms between green innovation and SOE status are negative and significant (b = −0.64, p < 0.05; b = −0.76, p < 0.01, respectively). The results plotted in panel C of Figure 2 indicate that the positive relationship between green innovation and export performance becomes stronger for non-SOEs (b = 0.54, p < 0.01) than for SOEs (b = 0.22, p < 0.05).

Robustness Tests

We conduct several robustness tests and report the results in Tables 4 and 5. First, we apply the fixed-effect model associated with Table 4. According to econometric theory, using either a fixed- or random-effects specification reduces the threat of unobserved heterogeneity (Greene, 2000). We applied a Hausman (1978) specification test and the p value is 0.00, which strongly rejects the null hypothesis and confirms that we should use fixed-effect estimations. Results obtained from the fixed-effect estimations are consistent with those reported in Table 3. Results obtained with models 1 and 5 and reported in Table 4 also show that the relationship between green innovation and export performance is positive and significant (b = 0.18, p = 0.00; b = 0.19, p = 0.00), supporting H1. Results obtained with models 2 and 5 reveal support for H2, as the interaction terms between green innovation and host-country political risk in these two models are negative and significant (b = −0.07, p < 0.01; b = −0.06, p < 0.01). Results obtained with models 3 and 5 reveal support for H3 because the interaction terms between host-country buyer sophistication and green innovation on export performance are significant and positive (b = 0.06, p < 0.05; b = 0.14, p = 0.00, respectively). The results obtained with models 4 and 5 support H4 as the interaction terms between green innovation and SOE status are negative and significant (b = −0.50, p = 0.00; b = −0.59, p = 0.00, respectively).

Table 4. Results of fixed-effect regressions

Notes: N = 1,524; t-statistics in parentheses; *** p < 0.001, **p < 0.01, *p < 0.05, ⁺p < 0.1 (two-tailed).

Table 5 Results of robustness tests

Notes: N = 1,524; t-statistics in parentheses; *** p < 0.001, ** p < 0.01, * p < 0.05, ⁺p < 0.1 (two-tailed); year dummies and sub-industry type dummies are not shown. Baseline models are omitted for parsimonious consideration. Model 1 reports the results of green invention patents as an alternative measure for green innovation. Model 2 reports the results that state ownership is measured alternatively by using state share percentage of top ten shareholders. Model 3 reports the results of environmental policy stringency as an alternative measure for host-country regulatory institution within the context of OECD countries (N = 1227).

Second, we consider a specific class of green patents (invention patents) to measure green innovation and examine the impact of such patents on export performance because invention patents are relatively more innovative than utility patents. Our findings show that a green invention patent is positively associated with export performance (Table 5, model 1: b = 0.28, p < 0.01).

Third, we explore an alternative measure of state ownership using the state's percentage share in the top ten shareholders. Our findings show that state ownership has a negative moderating effect on the green innovation–export link (Table 5, model 2: b = −0.02, p < 0.05), corroborating prior findings.

Fourth, we explore an alternative variable related to the host country regulatory institution by utilizing the Environmental Policy Stringency (EPS) Index provided by the OECD Environmental Statistics. EPS refers to the degree to which environmental policies put an explicit or implicit price on polluting or environmentally harmful behavior (Barbaglia, Bianchini, Butticè, Elia, & Mariani, 2023). Due to the fact that our sample of companies export to 136 different countries and regions, while OECD's EPS index covers only 33 countries, we thus limit our analysis to sampled companies who exported to OECD nations and conduct an additional analysis. The findings show that EPS has a positive moderating effect on the green innovation–export link (Table 5, model 3: b = 0.17, p < 0.05), suggesting that green innovation plays a pivotal role in establishing corporate legitimacy within host countries.

Discussion

Theoretical Contributions

This study offers several contributions to the legitimacy and international business literatures. First, this article proposes that green innovation can function as an important mechanism enabling EMFs to overcome legitimacy barriers in host countries. The legitimacy-based view posits that EMFs face legitimacy hurdles when they are going global because of their emerging and late-comer status (Deng et al., 2020). The current literature has recommended several mechanisms for building and gaining legitimacy, such as hiring local managers and lobbying local governments (Bertrand et al., 2021; Hunter & Bansal, 2007; Marano et al., 2017). However, the role that EMFs’ green innovation might play has been overlooked. As green innovation can help EMFs gain regulatory and social legitimacy, this form of innovation represents an important mechanism through which EMFs can overcome legitimacy barriers. In addition, recognizing this extended role of green innovation in overcoming legitimacy barriers enriches our understanding of how green innovation can function as a strategic asset for building competitive advantage (Atkinson & Rosenthal, 2014). As such, granted green patents in a home country can serve as a strategic tool that helps EMFs attain legitimacy in the global market.

Second, we add to the international business literature by substantiating the important role that green innovation plays in enhancing EMFs’ export performance. Although environmental issues have become a global concern, the role of green innovation in EMF exports has not been examined in the current literature (Bıçakcıoğlu, Theoharakis, & Tanyeri, 2019). More broadly speaking, when it comes to the relationship between green innovation and internationalization, prior studies focus on how the latter impacts the former (Chiarvesio et al., 2015; Kim et al., 2021), leaving it still unclear how green innovation impacts internationalization. Our research finds that EMFs’ green innovation is positively associated with export performance, supporting our argument that green innovation can boost EMF exports through the proposed mechanism for overcoming legitimacy barriers in host countries. In this case, this study identifies a novel antecedent to EMFs’ exports and proposes a legitimacy-based explanation of how green innovation influences EMFs’ export performance.

Third, we identify important boundary conditions for the positive effect of green innovation on EMF export performance, offering a more nuanced understanding of how green innovation influences exports. In particular, we study the moderating roles of host-country political risk, host-country buyer sophistication, and SOE status. The first two factors reflect the regulatory and normative institutional pillars, while the third factor influences stakeholder cognition in host countries (Peng, Wang, & Jiang, 2008; Scott, 1995). In international business research, political risk represents a critical consideration for EMFs, as it is often associated with policy shifts in taxation or regulations, changes in policies, or the imposition of capital and foreign exchange controls (Benischke, Guldiken, Doh, Martin, & Zhang, 2022). Regarding host-country political risk, prior studies agree that high political risk can discourage foreign investment (Cosset & Suret, 1995; Witte et al., 2020), change entry modes for multinational companies (Benischke et al., 2022), and influence subsidiaries’ operational integration (Lee et al., 2020). Prior research linking political risk to EMF establishment-mode strategy is broadly based on logic implying that political risk may make it difficult for EMFs to exploit their firm-specific advantages when expanding abroad (Witte, Burger, Ianchovichina, & Pennings, 2017). Our research adds to this line of inquiry by finding that host-country political risk can weaken the effects of green innovation on EMF export performance.

Moreover, recent years have seen growing scholarly attention to the effects of buyer sophistication on internationalization, but research findings are not conclusive. On the one hand, buyer sophistication reduces entry and transaction costs and provides firms with stronger incentives to experiment with innovative new resource combinations and/or product offerings (Fainshmidt et al., 2016; Barnes & McTavish, 1983). On the other hand, buyer sophistication intensifies competition and market dynamics (Li, 1999; Ellis, 2006), resulting in loss of market share and eventual exit by less efficient firms that fail to capitalize on market opportunities triggered by that freedom (Bennett, 2021). Our study suggests that, in countries with more sophisticated buyers, stakeholders are more likely to uphold green norms and expectations and therefore the value of green innovation in overcoming legitimacy barriers becomes more substantial. As such, our findings suggest that buyer sophistication may create competitive pressure, but because green innovation can help EMFs build competitive advantage they may benefit from buyer sophistication. Our study thus implies that whether buyer sophistication is harmful or beneficial may also depend on EMFs’ market advantages.

Furthermore, prior research on internationalization by SOEs focuses on the foreign expansion motive, the level of internationalization, country selection, and choice of entry mode (Cuervo-Cazurra & Li, 2021; Tang et al., 2022), and there exists a diversity of views of the impact of state ownership on internationalization. Some studies support an advantage view of stateness (i.e., in reference to the additional benefits that SOEs enjoy in their international expansion in comparison with private firms) (Luo et al., 2010; Wang, Hong, Kafouros, & Wright, 2012), while others go along with the disadvantages of stateness (i.e., additional hurdles that SOEs have to conquer as compared with private firms) (Deng, Yan, & Van Essen, 2018; Li, Xia et al., 2018). Our findings suggest that unfavorable stereotypes and perceptions associated with SOE status may attenuate the effects of green innovation on EMFs’ export performance. These findings support our argument that SOE status sends a strong signal which can influence cognition among host-country stakeholders. This view of SOE status enriches the traditional view that state ownership is a firm-level attribute in that SOE attributes determine how host-country stakeholders perceive, evaluate, and judge EMFs.

Managerial Implications

Our research offers several implications for EMF managers seeking to expand into overseas markets. First, this study suggests that EMFs can rely on green innovation to improve export performance. Given their countries of origin, EMFs may be confronted with adverse treatment, negative impressions, and unfavorable stereotypes in host countries. Our findings suggest that green innovation can help EMFs lower entry barriers through complying with environmental regulations and thereby enhance social acceptance. More specifically, EMFs’ market offerings that are supported by green technologies are consistent with customers’ expectations and preferences, making the EMFs more acceptable to host-country stakeholders. As such, to overcome legitimacy barriers in the global market, EMFs should emphasize the commitment of investments to developing green technologies and environmentally friendly innovation.

Second, EMFs need to understand the boundary conditions of green innovation when making their market-entry decisions. EMF managers need to pay close attention to host-country political risk, as it reduces the positive impact of green innovation on export performance. Thus, when making market-entry decisions, EMFs that pursue green innovation should focus on countries where political risk is low. Moreover, EMF managers also need to consider host-country buyer sophistication, as it enhances the impact of green innovation on export. As such, EMFs that pursue green innovation should enter countries with sophisticated buyers; in these countries, governments, business partners, and publics put more emphasis on environmental protection and preservation and strongly favor green products and eco-services.

Finally, managers should understand that the impact of green innovation on exports is stronger for non-SOEs than for SOEs. Accordingly, SOE managers should consider allying with renowned partners in host countries to weather perceived inferiority in the eyes of host-country stakeholders. In contrast, non-SOEs can rely on their green innovation to obtain regulatory and social legitimacy more easily. As a result, private EMFs should focus more attention on green innovation to boost their exports in global markets.

Limitations and Future Research

This study is subject to several limitations. First, we choose manufacturing as our industrial focus because it generates significant innovations and greatly contributes to exports. Although the single-industry context has the merit of ruling out confounding industry impacts, caution should be taken when generalizing our findings to other industries. We also focus on Chinese firms, as China has been the largest global exporter of goods since 2009 (McKinsey Global Institute, 2019). While China is an important emerging market, it also possesses unique characteristics. Other emerging countries, such as Brazil, India, and Mexico, are also important exporters. Thus, future research is encouraged to extend our research in other industries or emerging markets to corroborate our findings.

Second, we examine the moderating roles of three institutional pillars. Future studies could examine other important factors, such as host-country institutional complexity/ambiguity and top-management-team overseas experience. Given rising concern with geopolitical risk, future research could explore host–home political distance and its influence on establishing EMFs’ legitimacy in host country. In addition, future research could also explore the role of environmental regulations in host countries as more relevant moderators.

Third, our research examines the impact on the export performance of green patents granted in a home country. Future investigations could examine how green patents obtained by EMFs’ foreign subsidiaries or granted in a host country influence EMFs’ export performance or subsidiary performance. Future studies could thereby extend our findings by considering differences in intellectual property protection regimes across countries.