Who Drives Market Access for Genetically Modified Organisms and Products in Korea? A Political Economy Approach to Sustainable Development

Abstract

This study explores the definition of the industrial use of genetically modified organisms (GMOs), factors that affect it, and how it influences a firm’s economic performance to understand who drives market access for GMOs and GM products, considering the two premises related to sustainable development: 1) the continuing use of GMOs is one of the most prominent driving forces behind a bio-based economy’s growth, and 2) social system members seek protection from the potential risks of GMOs. The results show compelling evidence of a structural relationship between sociopolitical/economic pressures and economic performance. Additionally, these pressures vary by industry, and activities to secure both social and economic legitimacy due to these pressures have a positive impact on overall firm performance.

Introduction

the industrial use of genetically modified organisms (GMOs) is inevitably connected to sustainability or sustainable development, wherein this type of economic development should harmonise with human and environmental health protection. Furthermore, it provides firms¹ a normative message that they can access the market for GMOs and GM products derived from GMOs (GMO-derived products or GM products) if used sustainably in industry and considered in the context of socially sustainable development. It has been about forty years since Cohen, Chang, Boyer and Helling (1973) constructed a novel plasmid DNA from two separate plasmid species using modern biotechnology called recombinant DNA (the combination of genetic traits from different organisms). This breakthrough created GMOs that had not previously existed in nature. Over the last few decades, modern biotechnology has moved from the mostly laboratory-level to an important cornerstone of economic growth in the twenty-first century, with GMOs at the centre of this trend. According to KRIBB (2015), commercialised GMOs are used as inputs to produce intermediate or final goods in manufacturing industries: GM crops for oil, lecithin, sweetener, starch, dietary fibre and so on in the food/beverage sector; GM crops and microorganisms for vitamin B12 (riboflavin), amino acids (L-gltamate, L-lysin and serine) and sweeteners (xylitol, erythritol, manntitol and sorbitol), organic acids (lactic acid and saccharide), among others in the compounds/chemicals sector and GM microorganisms for insulin, somatropin, interferon, granulocyte-colony stimulating factor (G-CSF) and hirudin among others in the medical/pharmaceuticals industry. Considering commercialised or recently commercialised GMOs, for example, six nutrition-enhanced crops such as cassava, rice, canola, soybean, banana and camelina; various flowers, including nutrition-enhanced safflower; quality-enhanced apple, eucalyptuses and pine trees; silkworms to create red, green and orange silks and various microorganisms and insects (KRIBB, 2015), the scalability for industrial GMO use (Navarro, 2015) and the industrial applications of GMOs are expected to greatly extend to various manufacturing sectors.

Nonetheless, no studies have theoretically and empirically investigated issues around firms’ industrial use of GMOs in the context of socially sustainable development as of yet. This study explores how industrial GMO use is defined in the context of socially sustainable development, what factors may affect firms’ industrial use of GMOs and how firms’ industrial use of GMOs may influence their economic performance, considering the normative message that firms must use GMOs sustainably.² This study starts from the following two premises: that GMOs must be used continuously as they are one of the most prominent driving forces behind economic growth in a bio-based economy, and that members within a social system seek protection from the potential risks associated with GMOs. Therefore, GMOs and GM products can access the market only when the industrial use of GMOs meets these requirements.

Although several studies have contributed to the discussion about the connections between influential factors, firms’ intentions and economic performance in terms of industrial GMO use, some theoretical and empirical gaps still exist and require two improvements. First, studies investigating the causes and effects of firms’ industrial GMO use do not provide a theoretical background accounting for the GMO-related context, where society constantly demands that GMOs are used industrially in an environmentally sound manner, achieving sustainable development. Sustainability has numerous multi-faceted and contested notions, resulting in many conceptual frameworks holding different definitions and interpretations (Dietz & Neumayer, 2007; Gallopín, 2003). Many conceptual frameworks in the field of sustainability are generally framed by political and economic dimensions (Davidson, 2014), by necessity. This study attempts to create an analytical model and examine the causes and effects of firms’ industrial use of GMOs in the context of socially sustainable development by applying a political economy perspective of sustainability to understand who drives market access for GMOs and GM products.

Second, the empirical literature examining the factors that may influence firms’ industrial use of GMOs (Luxmore & Hull 2010; Sung & Hwang, 2013; Sung & Jang, 2008) focuses mainly on the manufacturing and agribusiness industries, leaving a requirement for more studies into the issue at each manufacturing subsector level. Agriculture and food are the main sectors for the application of genetic modification, though their use appears in the medical, pharmaceutical and chemical industries (EU, 2012; OECD, 2009). Genetic modification is not equally controversial in each subsector. Support for medical, pharmaceutical and chemical applications is relatively high and viewed positively where the benefits outweigh the risks. Criticism focuses mainly on agricultural and food applications, with relatively low support for the available agricultural applications (Arundel, 2003; EU, 2012). Given the difference in the degree of social support for genetic modification among these three subsectors, further research should consider each specific situation, testing data on the different subsectors. In this context, this study examines the issue at the manufacturing subsector level, especially for the food/beverage, compounds/chemicals and medical/pharmaceuticals industries in Korea.³

The remainder of this article is structured as follows. It provides a literature review on the causes and effects of firms’ industrial use of GMOs, the structural relationships between political–economic factors, firms’ industrial use activities and their economic performance and proposes a research model. Next, it describes the empirical methodology and data. Thereafter, the results from the empirical tests have been presented. Finally, it concludes and lists implications and limitations of this study.

Literature Review

A Political Economy Approach to the Sustainable Use of GMOs

Sustainable development indicators must ultimately link to achievable goals within a social system. Therefore, setting goals for socially sustainable development requires a multi-stakeholder process that incorporates the views of various social actors (Gallopín, 2003). In addition, sustainable GMO use and development must be agreed upon in social relationships between the members within a social system, taking into account the social, environmental and economic dimensions (COGEM, 2009; Graff, Hochman & Zilberman, 2009). Thus, the relationship between the ecological and socio-economic equilibrium of various stakeholders should be considered when using GMOs industrially. This is not an easy task because groups of stakeholders have varying values, historical and cultural backgrounds and experiences. Nonetheless, GMO-related sustainable development is structured within a social system through the convergence of various stakeholders’ many interests within society. In this regard, Hull and Luxmore (2007), who examine the factors affecting firms’ acceptance of industrial GMO use, provide a theoretical background, arguing that various stakeholders’ requirements derived from social and scientific rationality affects firms’ industrial use of GMOs. Social rationality requires that firms use GMOs in socially and environmentally desirable ways through sociopolitical pressures focused on safety issues related to the technology, processes and production methods and end product. Scientific rationality demands that firms use GMOs to promote economic performance through economic pressure that advocates scientific advancement and the introduction of new technology (Isaac & Kerr, 2003). Firms, therefore, must use GMOs in the sustainable development context by proactively responding to socio-political and economic concerns expressed by various stakeholders if they are to survive and grow.

From this perspective, some studies take an empirical approach. Sung and Jang (2008) explore the political and economic forces that may affect firms’ attitudes towards the industrial use of GMOs and show that the most important forces, in descending order, are the market, competitors, consumers and government. However, this analysis does not account for sustainable development, though they contribute the first empirical study exploring the possibility of a direct relationship between firms’ industrial use of GMOs and political and economic pressure from various stakeholders. Luxmore and Hull (2010) conduct a case analysis to consider the factors that may have an impact on successful GMO-related innovation, that is, the successful industrial use of GMOs in the agribusiness industry. Based on their results, they suggest that successfully using GMOs in industry requires that firms consider the interests of various stakeholder groups and the negative externalities from the differing interests of these stakeholder groups. This study also indirectly excludes industrial GMO use in the sustainable development context. However, negative externalities are generally recognised and interpreted as a factor that may have a negative effect on sustainability in the socio-political economy, so firms’ activities occur within the context of socially acceptable sustainable development. Sung and Hwang (2013) investigate how socio-political and economic factors affect firms’ managerial interpretations and their intentions to use GMOs industrially, and how these interpretations influence a firm’s intentions towards industrial use. Their results indicate that socio-political force directly affects intentions, and that economic forces indirectly affect intentions via managerial interpretations. Although they consider external stakeholders as a whole, firms’ interpretations of industrial use reflects the social–environmental requirements and economic aspects derived from various stakeholders in a social system, meaning that the context of socially-structured sustainable development affects firms’ activities.

The literature review indicates that the GMO debate between various groups of stakeholders requires a balanced consideration of the relationship between social, political and economic dimensions acceptable to members of society, putting political and economic pressure on firms to use GMOs in industry sustainably.

A political economy approach (COGEM, 2009; Davidson, 2014) to sustainable development focusing on the effects of various stakeholders or actors within a social system on the introduction of innovative technologies and products is therefore the most appropriate approach to analyse realistic and practical situations where these various interests create complexity. Sustainable development obligations require that firms address any political–economic actors impacted by its activities and to address these impacts. From a political economy perspective, the industrial use of GMOs in the sustainable development context can be understood as a firm’s effort to proactively respond to the perceived interests of the various groups of stakeholders which provide a basic theoretical background to grasp whether or not GMOs can access the market sustainably. According to Kissinger, William and Timmer (2011), unsustainable industrial production carried out in a region or area has a negative effect on sustainability worldwide due to international trade. Firms’ industrial use of GMOs in the sustainable development context can be understood as access to global markets.

The assumptions in a political economy perspective are captured by the stakeholder and legitimacy theories, which provide multi-faceted, interrelated, overlapping and complementary theoretical perspectives (Deegan, 2002; Harrison, Rouse & De Villiers, 2012; Van der Laan, 2009). Stakeholder theory assumes that ‘firms have several stakeholders who benefit from or are harmed by firm actions’ (Freeman, 1998, p. 174), with an interest in firms’ actions and decisions. From this perspective, a firm’s continued existence requires support and approval from stakeholders with different interests and expectations, gained by adjusting the firm’s activities. Stakeholder theory provides a theoretical perspective on how to determine the social norms that firms must conform to by identifying relevant stakeholders to whom the business might be considered accountable, and determining their requirements. Legitimacy theory posits that organisations continually seek to ensure that they operate within the norms of their respective societies (Deegan, 2000; Van der Laan, 2009). Legitimacy is regarded as ‘a generalized perception or assumption that firm actions are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs and definitions’ (Suchman, 1995, p. 574). The central problem is to legitimise its goals, structures and processes (Parsons, 1956). Legitimacy in this context is understood as a compliance with social norms, values and expectations (Oliver, 1997). Firms require two types of legitimacy: social legitimacy from non-market actors and market legitimacy from market actors (Céspedes-Lorente, De Burgos-Jiménez & Álvarez-Gil, 2003; Hawn, Chatterji & Mitchell, 2011). Legitimacy is essential for organisational survival, since it is a precondition for a continuous flow of resources and the support of core stakeholders (Pfeffer & Salancik, 1978).

Political and Economic Actors and Firms’ Intentions for Industrial Use of GMOs

Firms gain social legitimacy by complying with what stakeholders accept as appropriate company activities given existing norms and laws, stemming from socio-political forces that encourage compliance. The institutional environment normally produces the socio-political forces (Oliver, 1997; Sung & Hwang, 2013) that pressure firms to comply with environmental demands, such as human health and safety and environmental protection (Céspedes-Lorente, De Burgos-Jiménez & Álvarez-Gil, 2003; Hawn, Chatterji & Mitchell, 2011; Hull & Luxmore, 2007; Isaac & Kerr, 2003; Von Geibler, Liedtke, Wallbaum & Schaller, 2006). In this context, it is possible to establish an acceptable position on the industrial use of GMOs in the socio-political landscape (Bruce, 2002). Institutional environments exert three types of pressures: coercive, normative and mimetic, which motivate firms to align their activities with social expectations (DiMaggio & Powell, 1983). Coercive pressures can be both formal and informal, depending on the source (DiMaggio & Powell, 1983, p. 150). Formal pressures are authoritative forces imposed primarily by government mandates, such as through policies and regulations. Although regulations on GMOs have economic objectives, most policies focus on social functions through safety measures requiring that firms protect human and environmental health in the industrial use of GMOs. South Korea signed the Cartagena Protocol on Biosafety at the Convention on Biological Diversity (CPB) in 2000, and enacted the Act on Transboundary Movements of Living Modified Organisms and Other Related Matters (LMO Act) in 2001 through several public hearings and debates among multiple stakeholders, including government agencies, NGOs, civil society groups, universities, research institutions and trade and industry associations, among others, to implement the CPB. The LMO Act became effective at the beginning of 2008 when the CPB took effect in Korea, and aims to protect public health and sustainable use of biodiversity from any adverse effects posed by GMOs or GMO-derived products by taking into account its social and economic consideration in using them industrially and/or commercially. The LMO Act was revised in 2009, 2012 and 2013, which led to enactments and revisions of thirty GMO- and GM product-related laws, including enforcement ordinances, enforcement regulations and notifications in eleven government agencies responsible for the LMO Act. The GMO- and GM product-related laws, including the LMOs Act, stipulated methods and processes for risk assessments and reviewed activities related to research and development, production management, transportation, safety measures, labelling systems, facility management, post-market monitoring and training for employees at research institutions, universities, companies, records management and so on covering the industrial use of GMOs and GMO-derived products (for detailed information, refer to KRIBB, 2015, pp. 53–178, 424–434). Thus, Korean GMO- and GM product-related laws require that manufacturing firms use these products in socially sustainable ways. Hence, the study examines the following hypothesis:

H1a: Government pressure positively influences firms’ activities to secure social legitimacy.

Informal pressures may arise from the cultural expectations within which the firm functions, affecting firms’ activities as much as formal coercive pressures do. For example, more extensive debate about GMOs allows the general public and interest groups, such as consumer and non-governmental organisations (NGOs), to voice their opinions, informally forcing company compliance through socio-political pressures. The public is the most important social force in these innovative products and technologies, such as GM technologies, GMOs and GM products, which are successful only when they become socially acceptable. The public’s main concerns regarding the uncertainties and potential side effects of GMOs and GM products are about human health and the environment (Twardowski, 2012; Vergragt & Brown, 2008). However, these attitudes differ across cultures and geographical regions (Connor & Siegrist, 2010), as well as by sectors and types of application (Arundel, 2003; EU, 2012). Although some influential variables, such as the level of scientific knowledge and education, can affect public attitudes towards new technologies (Priest, Bonfadelli & Rusanen, 2003), people are often influenced by concerns or fears rather than by objectively quantifiable probabilities or expectations (Lee, Scheuffle & Lewenstein, 2005). Therefore, public concern over the safety of GMOs can no longer be taken as an acceptable value affecting firms’ activities in the industrial use of GMOs. Therefore:

H1b: General public⁴ pressure positively influences firms’ activities to secure social legitimacy.

NGOs are formal, private, not-for-profit, voluntary and publicly beneficial organisations (Salamon & Anheier, 1994), one of the most influential external political actors, are generally against GMOs, taking a watchdog role and acting as private enforcers or collecting and disseminating information about GMOs (Aerni & Bernauer, 2006; Legge & Durant, 2010; Soule, 2003). Such activities receive widespread social support, which helps NGOs increase their social legitimacy (Doh & Teegen, 2002). Innovations such as GMOs that antagonise NGOs will face significantly greater challenges than those that do not (Luxmore & Hull, 2011). There is a variety of strategic approaches to partnering with NGOs, but full partnerships are not easy (Nijhof, De Bruijn & Honders, 2008) because NGOs have been replicating and improving the anti-GMO movement. NGOs in Korea, including civil society groups, have conducted more frequent and systematic anti-GMO and GMO-derived product campaigns and demanded more information about GMO and GMO-derived products since 2005. Hwang Woo-suk’s episode occurred before this. In fact, the Korean government’s enhancements of existing institutional labelling systems for GMOs and GMO-derived products in 2014 were related to general concerns about the adverse effect of industrial and commercial GMO and GMO-derived product use on society, and aimed to address the general public’s desire for more strict regulations of industrial or commercial use of GMOs and GMO-derived products. The regulatory changes were influenced substantially by various GMO and GM product-free campaigns from NGOs (KRIBB, 2015, p. 388). Therefore:

H1c: NGOs pressure positively influences firms’ activities to secure social legitimacy.

Normative pressures originate from the professionalisation of industry or sector members who attempt to define the conditions and methods of their work to legitimise their professional autonomy (Covaleski & Dirsmith, 1988). Normative isomorphism arises when organisational members are subject to pressures to conform to a set of norms, values and rules of occupational and professional bodies (Van der Laan, 2009), or from an organisational imitation or modelling of norms or practices in the organisation’s institutional field as an organisational response to mimetic pressures. According to DiMaggio and Powell (1983), members of professions interact through networks and trade associations, leading to the professionalisation which is the source of isomorphism. Today, trade associations exert normative or mimetic forces by supporting safety standards, industrial charters and/or guidelines to secure human and environmental safety and diffusing ideas and models for safety management practices. This study therefore proposes:

H1d: Pressure from trade association positively influences firms’ activities to secure social legitimacy.

Economic legitimacy stems from organisational activities that align with the norms and values of markets (Hawn, Chatterji & Mitchell, 2011). Firms gain economic legitimacy by actively responding to economic pressures and seeking benefits. The market and its actors, consumers and competitors generate the main economic forces by exerting competitive pressure on firms within the same industry (Oliver, 1997). In competitive environments, firms quickly respond to the market to maintain their competitive advantage through more active and competitive activities. When firms perceive that activities related to the industrial use of GMOs are profitable, the competition among firms in the same industry to capture the market opportunity and competitive advantage will be fierce. Competitors’ activities to secure economic legitimacy threaten a firm’s growth and survival, providing mimetic pressure through competition (Sharfman, Ellington & Meo, 1997).

Consumers tend to purchase satisfactory products and services for their own benefit. European consumers’ strong rejection of GMOs and GM products indicates that they neither experience any immediate benefits from this technology nor perceive it as useful and inevitable (Heyder & Theuvsen, 2010). Genetic modifications that focus on improving nutritional features and processing characteristics, rather than on the dominant inputs for GM products, provide significant benefits to end-users, affecting pricing and marketing. It is clear that biotechnology can be of tremendous benefit to consumers (Evans & Ballen, 2013), which influences consumers’ positive attitudes towards GMOs and GM products and affects their purchase intentions and behaviours, directly influencing firms’ industrial use of GMOs. Market attractiveness may be the most important characteristic of GMOs and GM products affecting economic performance for profit-seeking firms impacted by factors such as market size, rate of market growth, profitability and competitive intensity, which directly affect firms’ decisions on investment and market entry. A firm will therefore devise strategies and tactics when it perceives high market attractiveness from higher probabilities of creating business opportunities and profits. This logic also applies to the industrial use of GMOs. Therefore:

H2a: Consumer pressure positively influences firms’ activities to secure economic legitimacy.

H2b: Competitor pressure positively influences firms’ activities to secure economic legitimacy.

H2c: Market pressure positively influences firms’ activities to secure economic legitimacy.

Firms’ Intentions to Use GMOs and Expected Performance

Companies using GMOs industrially must persuade external stakeholders that this will provide everyone with long-term benefits, mainly by securing social and economic legitimacy. Responding to political and social pressure stimulates interest in social actors or partners through marketing efforts communicating a positive impact on welfare and the environment, accounting for stakeholders’ requirements (Wood, 1991), which may in turn enhance the firm’s economic performance. This demonstrates that markets essentially require social legitimacy given that a firm’s political sustainability ultimately depends on it, as do global markets if they are to persist (Abdelal & Ruggie, 2009). In this context, a firm’s actions to secure social legitimacy for the industrial use of GMOs are likely to have a positive effect on its economic performance. Economic pressure created by market attractiveness based on the market and its actors, consumers and competitors, encourages companies to apply GMOs industrially for economic performance. Such market-oriented activities require resource expenditures on organisational learning, leading to an accumulation of competence that can help firms enhance their competitive advantage. Therefore, this study proposes:

H3a: Firms’ intended activities to secure social legitimacy positively contribute to their expected performance.

H3b: Firms’ intended activities to secure economic legitimacy positively contribute to their expected performances.

Figure 1 illustrates the theoretical model used to test the hypotheses.

Figure 1

Source: Authors’ own.

Methodology and Data

Methodology

This study analyses the structural relationship between the causes and effects of a firm’s intentions to use GMOs industrially using structural equation modelling (SEM) to understand who drives market access for GMOs and GM products. The relationships are tested in two steps. First, the estimation may include a common method bias that can inflate relationships between variables measured through self-reports, affecting the validity of the conclusions drawn about relationships between the measures (Podsakoff, MacKenzie, Lee & Podsakoff, 2003). The likelihood of a common method bias is trivially small in this study, as its items measuring the different constructs have no conceptual overlap and these are based on perceptions rather than objective evaluations (Conway & Lance, 2010). The constructs are first tested with a single-factor test using exploratory factor analysis, principal axis factoring and the non-rotated factor solution to confirm that there is no problem with common method bias (Harman, 1967). Second, the study uses partial least squares (PLS) to test the structural relationships between the variables. The study follows Hair, Anderson and Tatham’s (1998) recommendations along with Hoyle’s (1995) two-stage model-building process, in which a confirmatory factor analysis (CFA) examines the reliability and validity of the measurement. The structural model is then analysed to test the hypotheses in the theoretical model.

Data

The research instrument is a fixed-response questionnaire using a five-point Likert scale. The data are collected from a survey conducted in South Korea from 3 March to 28 April 2014 from a random sample of 1346 firms listed in the Annual Corporation Report 2013 issued by Maeil Business Newspaper (2013), which contains some 3,941 firms operating in the sectors of interest within Korea: food/beverage (411, 32.3 per cent), compounds/chemicals (650, 40.6 per cent) and medical material/pharmaceutical (285, 26.9 per cent). To boost questionnaire response rates, the study targeted well-qualified people to answer the questionnaire and determined the subject’s intention to answer the questionnaire by telephone prior to starting the field survey. The questionnaire was sent to 1,346 firms and collected 300 responses, 18 of which were not suitable for analysis. The final data set includes responses from 71, 120 and 91 firms in the food/beverage, compounds/chemicals and medical material/pharmaceutical sectors, respectively, for 282 total responses.

Government pressure (GP) is the intensity of the regulatory environment related to safety and environmental issues in the industrial use of GMOs, assessed with five items (Brookes, 2012; Graff, Hochman & Zilberman, 2009; Mutambara, 2013; Sung & Jang, 2008; Tan, Shen, Reed, Saghaian & Chen, 2013; Vergragt & Brown, 2008): (GP1) overall stringency, (GP2) cost burden, (GP3) threat to operations, (GP4) restrictions on growth and (GP5) the number of regulatory inspections. Public pressure (PP) is the tendency of the general public to evaluate the industrial use of GMOs, including GMOs and GM products, with a certain degree of favourability, measured with five items (Durant & Legge, 2005; Frewer, Lassen, Scholderer, Beekman & Berdal, 2004; Goyal & Gurtoo, 2011; Hoban, 2000; Legge & Durant, 2010; Twardowski, 2012; Vergragt & Brown, 2008): (PP1) belief in safety, (PP2) perception of need, (PP3) perception of benefit, (PP4) support and (PP5) overall acceptance. The study defined NGOs pressure (NP) as NGOs objections (Aerni & Bernauer, 2006; Legge & Durant, 2010; Luxmore & Hull, 2011; Nijhof, De Brujin & Honders, 2008; Sung & Jang, 2008), measured with five items: (NP1) intensity, (NP2) frequency of NGOs’ demonstrations, (NP3) organisation of NGOs’ activities, (NP4) social support and (NP5) anti-sentiment caused by opposition activity. Trade association pressure (TP) is the degree of recommendations to firms to implement and adopt standards or guidelines for activities related to securing safety in socially responsible ways, assessed with five items (Richardson, 2010; Snell, 2009; Sung & Jang, 2008; Van der Laan, 2009): (TP1) the association’s active recommendations, (TP2) strength of the association’s support, (TP3) adoption by major competitors, (TP4) compliance and implementation by major competitors and (TP5) overall intensity. Consumer pressure (CP) is consumer tendency to evaluate industrial GMO use, including GMOs and GM products, with a certain degree of favourability, and is measured with five items (Evans & Ballen, 2013; Heyder & Theuvsen, 2010; Lockie, Lawrence, Lyons & Grice, 2005; Sung & Jang, 2008): (CP1) overall acceptance, (CP2) trust in safety, (CP3) perceptions of benefits, (CP4) preference and (CP5) support. Competitive pressure or industry pressure (IP) is the competitive intensity, the extent of competition and the activities of competing firms in the industrial use of GMOs, assessed with five items: (IP1) major competitors’ interest, (IP2) major competitors’ aggressiveness, (IP3) competition intensity among firms, (IP4) competition for investment among firms and (IP5) competition for differentiation among firms in the industrial use of GMOs, in line with Cui, Griffith and Cavusgil (2005) and Sung and Jang (2008). The study defines market pressure (MP) as market attractiveness based on Sung and Hwang’s study (2013) and measures this with five items: (MP1) current market size, (MP2) potential market size, (MP3) market demand for GMOs and GM products, (MP4) number of consumers who want GMOs and GM products and (MP5) profitability of GMOs and GM products.

Intentions to engage in activities to secure social legitimacy (IASL) is the degree of behavioural intentions to perform the activities that enhance social reputation and acceptance (Céspedes-Lorente, De Burgos-Jiménez & Álvarez-Gil, 2003; Hawn, Chatterji & Mitchell, 2011; Hull & Luxmore, 2007; Schuman, 1995) by harmonising the social values associated with or implied by firms’ activities and the norms of acceptable behaviour in the larger social system (Dowling & Pfeffer, 1975, p. 122). The study measures IASL with eight items: (IASL1) improvements to the consumer’s right to know and choose, (IASL2) conformity with industrial guidelines for safety, (IASL3) preparation and implementation of a public participation process, (IASL4) implementing precautionary prevention activities, (IASL5) establishing and implementing a system to prevent damage to society, (IASL6) establishing and implementing a system to recover damage done to society, (IASL7) communication with society and (IASL8) a management system to safely use GMOs industrially. Intention to engage in activities to secure economic legitimacy (IAEL) is the degree of behavioural intentions to seek profits by actively responding to business or market opportunities (Céspedes-Lorente, De Burgos-Jiménez & Álvarez-Gil, 2003; Hawn, Chatterji & Mitchell., 2011; Hull & Luxmore, 2007), measured with six items: (IAEL1) investment, (IAEL2) research and development activity, (IAEL3) exploring ways to enhance financial performance, (IAEL4) improving competitiveness, (IAEL5) enhancing value and (IAEL6) creation of partnerships.

Expected performance (EXP) is measured in terms of (EXP1) increases in sales, (EXP2) reductions in costs, (EXP3) enhancements to company image, (EXP4) expansion of market share and (EXP5) market pre-emption accrued from conducting activities to use GMOs industrially, based on the study of Cavusgil and Zou (1994) and Oliver (1997).

Empirical Analysis

Common Method Variance

The study collected data via a single source (self-reported scales) cross-sectional survey method, which could conflate relationships among the variables, referred to as common method variance (CMV). Harman’s (1976) single-factor test was applied to address this problem for ten latent variables in the research model that was straightforward and incurred no additional resources (Craighead, Ketchen, Dunn & Hult, 2011), and found no significant biases in the dataset, showing the absence of a common factor loading on all measures: the single factor accounted for 25.8 per cent, 27.5 per cent and 21.5 per cent of the variance in the food/beverage, compounds/ chemicals and medical material/pharmaceutical sector samples, respectively (results available upon request). Therefore, CMV is not a major concern.

Measurement Model Results

We used the SmartPLS 2.0 statistics package for the empirical analysis and conducted CFA to assess the reliability, convergent validity and discriminant validity of the scales. Reliability was examined using the composite reliability (CR) values. Table 1 reports the CFA results.

Table 1 demonstrates that the proposed models have good construct reliability, showing CR values for each construct above 0.7, a commonly acceptable level (Nunnally & Bernstein, 1994). We assessed convergent validity using the criteria that the average variance extracted (AVE) of each construct should exceed the variance due to measurement error for that construct, 0.50 (Fornell & Larcker, 1981). Table 1 also demonstrates the model’s convergent validity, with AVE values for all constructs greater than 0.5 (Hair, Anderson & Tatham, 1998).

Table 2 shows that no pair of measures has correlations exceeding 0.9. In addition, no multicollinearity exists between the constructs. In terms of a more robust method of measuring discriminant validity (Fornell & Larcker, 1981), the correlation between two constructs is lower than the squared root of the AVE value for any of the two constructs. All constructs, therefore, have discriminant validity.

Structural Model Assessment

Unlike covariance-based SEM, PLS does not call for goodness-of-fit measures (Hulland, 1999). Figure 2 presents the results of the structural model tested with PLS. To assess the structural model, we use the variance value from the model (R²), and consider the size of the standardised path coefficients after observing both the t-statistics and the significance levels obtained from the bootstrap test with 500 subsamples. The structural model results, along with the path coefficients and their significance values in Figure 2 show that all hypothesised paths were significant at the 1 per cent, 5 per cent or 10 per cent levels.

Table 1

Evaluation of the Measurement Model

Constructs	Items	Food/Beverage Sector (n = 71)			Compounds/Chemicals Sector (n = 120)			Medical/Pharmaceutical Sector (n = 91)
Constructs	Items	Loadings	CR	AVE	Loadings	CR	AVE	Loadings	CR	AVE
Government pressure	GP1 GP2 GP3 GP4 GP5	0.945 0.867 0.886 0.903 0.955	0.961	0.831	0.922 0.914 0.869 0.925 0.927	0.960	0.828	0.946 0.807 0.823 0.845 0.936	0.941	0.763
Public pressure	PPC1 PPC2 PPC3 PPC4 PPC5	0.800 0.794 0.865 0.857 0.739	0.906	0.660	0.851 0.838 0.878 0.853 0.834	0.929	0.725	0.826 0.781 0.816 0.874 0.808	0.912	0.675
NGOs pressure	NP1 NP2 NP3 NP4 NP5	0.965 0.925 0.913 0.871 0.947	0.967	0.857	0.928 0.901 0.890 0.876 0.928	0.957	0.819	0.927 0.815 0.819 0.817 0.918	0.934	0.741
Trade association pressure	TP1 TP2 TP3 TP4 TP5	0.968 0.925 0.913 0.871 0.947	0.976	0.891	0.939 0.933 0.931 0.899 0.927	0.968	0.858	0.910 0.910 0.940 0.928 0.958	0.969	0.864
Consumer pressure	CP1 CP2 CP3 CP4 CP5	0.662 0.574 0.871 0.906 0.771	0.874	0.589	0.736 0.910 0.925 0.891 0.939	0.946	0.781	0.828 0.874 0.914 0.900 0.933	0.950	0.794
Industry pressure	IP1 IP2 IP3 IP4 IP5	0.821 0.863 0.926 0.877 0.913	0.945	0.776	0.845 0.834 0.912 0.817 0.912	0.937	0.749	0.776 0.876 0.918 0.805 0.913	0.933	0.739
Market pressure	MP1 MP2 MP3 MP4 MP5	0.723 0.840 0.853 0.760 0.812	0.898	0.639	0.817 0.766 0.852 0.808 0.826	0.907	0.663	0.802 0.805 0.823 0.807 0.751	0.897	0.637
Intention for activity to secure social legitimacy	IASL1 IASL2 IASL3 IASL4 IASL5 IASL6 IASL7 IASL8	0.924 0.924 0.859 0.753 0.889 0.864 0.828 0.816	0.957	0.738	0.954 0.958 0.955 0.878 0.942 0.891 0.921 0.936	0.980	0.865	0.935 0.933 0.957 0.768 0.912 0.758 0.883 0.913	0.966	0.784
Intention for activity to secure economic legitimacy	IAEL1 IAEL2 IAEL3 IAEL4 IAEL5 IAEL6	0.803 0.785 0.855 0.833 0.798 0.834	0.924	0.670	0.858 0.847 0.880 0.871 0.808 0.787	0.936	0.710	0.708 0.817 0.793 0.846 0.701 0.611	0.884	0.563
Expected performance	EXP1 EXP2 EXP3 EXP4 EXP4	0.906 0.529 0.907 0.775 0.879	0.903	0.660	0.793 0.686 0.801 0.812 0.888	0.897	0.638	0.793 0.679 0.850 0.690 0.881	0.887	0.613

Source: Authors’ own.

Note: CR = composite reliability; AVE = average variance extracted.

Table 2

Correlations between the Constructs

	1	2	3	4	5	6	7	8	9	10
Food/beverage sector
1. Government pressure	0.912
2. Public pressure	0.415	0.813
3. NGOs pressure	0.539	0.278	0.926
4. Trade association pressure	0.388	0.324	0.275	0.944
5. Consumer pressure	0.109	0.264	0.061	0.430	0.768
6. Industry pressure	0.493	0.437	0.282	0.273	0.140	0.881
7. Market pressure	0.307	0.658	0.180	0.420	0.211	0.622	0.800
8. Intentions to engage in activities to secure social legitimacy	0.491	0.412	0.528	0.545	0.061	0.349	0.438	0.859
9. Intentions to engage in activities to secure economic legitimacy	0.483	0.624	0.211	0.365	0.380	0.684	0.670	0.290	0.819
10. Expected performance	0.415	0.606	0.313	0.586	0.349	0.481	0.679	0.587	0.673	0.813
Compounds/chemicals sector
1. Government pressure	0.910
2. Public pressure	0.416	0.852
3. NGOs pressure	0.330	0.309	0.905
4. Trade association pressure	0.387	0.171	0.234	0.926
5. Consumer pressure	0.222	0.161	0.203	0.193	0.884
6. Industry pressure	0.346	0.200	0.215	–0.025	0.307	0.865
7. Market pressure	0.389	0.358	0.253	–0.027	0.286	0.601	0.815
8. Intentions to engage in activities to secure social legitimacy	0.533	0.367	0.437	0.470	0.161	0.150	0.263	0.930
9. Intentions to engage in activities to secure economic legitimacy	0.436	0.385	0.332	0.205	0.468	0.535	0.665	0.352	0.843
10. Expected performance	0.464	0.327	0.384	0.230	0.309	0.384	0.560	0.575	0.629	0.799
Medical/pharmaceutical sector
1. Government pressure	0.874
2. Public pressure	0.207	0.822
3. NGOs pressure	0.381	0.294	0.861
4. Trade association pressure	0.259	0.279	0.217	0.930
5. Consumer pressure	0.153	0.170	0.179	0.327	0.891
6. Industry pressure	0.290	0.238	0.091	0.214	0.139	0.860
7. Market pressure	0.283	0.426	0.061	0.242	0.193	0.483	0.799
8. Intentions to engage in activities to secure social legitimacy	0.433	0.357	0.379	0.381	0.209	0.247	0.206	0.886
9. Intentions to engage in activities to secure economic legitimacy	0.246	0.490	0.129	0.217	0.237	0.493	0.667	0.252	0.751
10. Expected performance	0.327	0.312	0.255	0.224	0.029	0.471	0.598	0.441	0.582	0.783

Source: Authors’ own.

Note: Bold diagonal figures are the square roots of AVE.

Figure 2

Source: Authors’ own.

H1a, H1b, H1c and H1d dealing with the influence of external socio-political actors on firms state that activities to secure social legitimacy for the industrial use of GMOs will be interpreted as the norm, and the intentions for such activities will be stronger when firms perceive high socio-political pressure. The hypotheses were established for each sector, demonstrating that external socio-political actors have a significant positive effect on firms’ intentions towards activities to secure social legitimacy in the industrial use of GMOs. H2a, H2b and H2c dealing with the influence of external economic actors on firms indicate that activities to secure economic legitimacy for the industrial use of GMOs will be interpreted as a basis for survival, and the intentions towards such activities will be stronger when firms perceive high economic pressure. The hypotheses were established for each sector, showing that external economic actors have a significant positive effect on firms’ intentions to conduct activities to secure economic legitimacy for industrial GMO use. The impacts of intentions to engage in activities to secure social legitimacy (H3a) and economic legitimacy (H3b) on expected performance were fully verified in each sector.

Discussion and Conclusion

Summary and Policy Implications

This study tested the links between the causes and effects of a firm’s industrial use of GMOs in the socially sustainable development context using survey data from South Korean firms, thereby examining who drives market access for GMOs and GM products. The study used an SEM approach with PLS to analyse the data and assess the relationships between the constructs. The study’s results provide several important implications.

First, this study shows that the effects of socio-political and economic pressures on firms to engage in activities to secure social and economic legitimacy for the industrial use of GMOs vary by sector. The SEM results show the importance of external pressures that may affect the implementation of effective policies and strategies for GMO and GM products’ market access to ensure that these are used sustainably in each sector. Based on the coefficients for the relationships between socio-political actors’ pressure and IASL, the most important variables in descending order are TP, NP and PP in the food/beverage sector; GP, TP and NP in the compounds/chemicals sector and GP, TP, PP and NP in the medical/ pharmaceutical sector. The most important variables, in descending order, based on the coefficients for to the relationship between economic actors’ pressure and IAEL are IP, MP and CP in the food/beverage sector; MP, CP and IP in the compounds/chemicals sector and MP and IP in the medical/pharmaceutical sector. However, these pressures may vary across countries (Hull & Luxmore, 2007; Luxmore & Hull, 2010; Sung & Hwang, 2013; Sung & Jang, 2008). In addition, these pressures are complex and dynamic (Inghelbrecht, Dessein & Van Huylenbroeck, 2015). Thus, government should not consider external stakeholders as a whole, but rather pressure from multiple actors (Aerni & Bernauer, 2006; Vergragt & Brown, 2008) from both the institutional and task environment by focusing on their importance, requirements and the means through which they influence a firm’s activity (Sung & Hwang, 2013). In this context, the results suggest that policy-makers and managers must recognise and prioritise these factors for each industrial sector through various learning activities to gain market access for GMOs and GM products. They must simultaneously fully account for key stakeholders’ needs and expectations arising from the socio-political and economic environment, and develop and implement industrial policy and strategic measures. In the social context, from the perspective of policy effectiveness, NP and TP commonly appeared to have important influence on the three industries examined in this study. This suggests that trade associations and NGOs generally play key roles in achieving social sustainability in the industrial use of GMOs and GMO-derived products. Trade associations mainly monitor, collect and distribute information about safety issues and measures to their member companies, while also requiring them to adopt certain safety measures, standards or guidelines, to promote sustainable GMO use. NGOs distribute information about safety issues to the public, conduct GMO-free campaigns and monitor GMO-related policies and firms’ activities, among other functions, which increase public awareness. This in turn leads to further revisions, improvements or enactments of new policies and encourages firms to use GMOs industrially in socially sustainable ways. The results imply that governments should make use of trade associations and NGOs in forcing firms to use GMOs in socially sustainable ways through various policy measures.

Second, this study indicates that in all sectors analysed, firms’ intentions to engage in activities to secure both social and economic legitimacy have positive effects on its expected performance related to the industrial use of GMOs. This shows that firms perceive the importance of activities to deal with the coexistence of business opportunities and risk in the socio-political and economic environments and implies that firms should use GMOs in a socio-economically friendly manner. This can contribute to environmentally sound and sustainable development, including enhancements to company performance. In this context, the results suggest that developing and implementing policy measures to support managers in correctly and objectively evaluating the socio-political economic aspects of GMOs (Sung & Hwang, 2013) should get the highest priority for promoting long-term sustainability.

Third, this study shows that firms’ activities to secure social legitimacy are more important for performance in the food/beverage sector than in the other two, as shown by the differing coefficients in the food/beverage (0.43), compounds/chemicals (0.40) and medical/pharmaceutical (0.32) sectors. This implies, as Arundel (2003) and the EU (2012) state, that there is relatively little support for the current food/beverage applications compared with other sectors indicating that this sector requires more social acceptance than the others. Furthermore, the results imply that there is no socio-political consensus on industrial GMO use in these sectors. Despite the potential benefits and evidence that there are positive relationships between intentions to secure economic legitimacy in these sectors, any industry that remains hostile to socio-political pressure will not survive, so firms in all sectors should consider this aspect of the environment. Firms can give strategic preference to powerful stakeholders and respond to their pressures, though this may not be the most desirable way to meet sustainability obligations (Clifton & Amran, 2011). Nonetheless, firms should bear in mind that the potential industrial use of GMOs relies heavily on the establishment of an acceptable vision shared by all members in a social system (Bruce, 2002).

Limitations and Further Research

Although this study contributes towards understanding the relationship between influential factors, firms’ intentions and economic performance regarding the industrial use of GMOs, and thereby grasping who drives market access for GMOs and GM products, this study is subject to several limitations. First, this study assumes that the instrument measures the same construct in the three industrial sectors, though there is a potential for measurement invariance, which could not be verified due to the sample size from each sector. Further research should obtain a larger sample and examine the measurement invariance for more meaningful comparisons across industrial sectors. Second, this cross-sectional study does not explain changes in socio-political and economic actors’ influence on activity to secure social and economic legitimacy. Creating and implementing policies and strategic measures to gain market access for GMOs and GM products by encouraging firms to use GMOs industrially in sustainable ways should be based on yearly follow-up surveys over a longer period. Further research with a longitudinal design will provide policy-makers and managers with reliable evidence from a political-economy perspective of sustainability in the long run. Finally, this study does not control for omitted variables that may significantly affect a firm’s performance, an issue requiring future research.

Footnotes

Acknowledgements

This article is supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A5A2A01019030).

Notes

References

Abdelal

, & Ruggie

J. G.

(2009). Principles of embedded liberalism: Social legitimacy and global capitalism. In Moss

& Cisternino

(Eds), New perspectives on regulation (pp. 151–162). Cambridge: The Tobin Project.

Aerni

, & Bernauer

(2006). Stakeholder attitudes toward GMOs in the Philippines, Mexico, and South Africa: The issues of public trust. World Development, 34(3), 557–575.

Arundel

(2003). Biotechnology indicators and public policy (OECD Science, Technology and Industry Working Papers 2003/5). Paris: OECD.

Benson

(2015, January 26). GMO found growing in South Korea despite national ban. Natural News. Retrieved from http://www.naturalnews.com/048631_GMOs_genetic_pollution_South_Korea.html

Brookes

(2012). Economic impacts of the biosafety law and implementing regulations in Turkey on the Turkish importing and user sectors. Briefing document. Dorset, UK: PG Economics Ltd.

Bruce

D. M.

(2002). A social contract for biotechnology: Shared visions for risky technologies? Journal of Agricultural and Environmental Ethics, 15(3), 279–289.

Cavusgil

S. T.

, & Zou

(1994). Marketing strategy-performance relationship: An investigation of the empirical link in export market ventures. Journal of Marketing, 58(1), 1–21.

Céspedes-Lorente

, De Burgos-Jiménez

, & Álvarez-Gil

M. J.

(2003). Stakeholders’ environmental influence. An empirical analysis in the Spanish hotel industry. Scandinavian Journal of Management, 19(3), 333–358.

Choi

S. J.

(2015, July 23). South Korea’s imports of GMO food at an all time high. The Hankyoreh. Retrieved from http://www.hani.co.kr/arti/english_edition/e_national/674976.html

10.

Clifton

, & Amran

(2011). The stakeholder approach: A sustainability perspective. Journal of Business Ethics, 98(1), 121–136.

11.

COGEM. (2009). Socio-economic aspects of GMOs: Building blocks for an EU sustainability assessment of genetically modified crops (090929-01). Report CGM/090929-01.

12.

Cohen

S. C.

, Chang

A. C. Y.

, Boyer

H. W.

, & Helling

R. B.

(1973). Construction of biologically functional bacterial plasmids in vitro. Proceedings National Academy of Science USA, 70(11), 3240–3244.

13.

Connor

, & Siegrist

(2010). Factors influencing people’s acceptance of gene technologies: The role of knowledge, health expectations, naturalness and social trust. Science Communication, 32(4), 514–538.

14.

Conway

J. M.

, & Lance

C. E.

(2010). What reviewers should expect from authors regarding common method bias in organization research. Journal of Business and Psychology, 25(3), 325–334.

15.

Covaleski

M. A.

, & Dirsmith

M. W.

(1988). An institutional perspective on the rise, social transformation, and fall of a university budget category. Administrative Science Quarterly, 33(4), 562–587.

16.

Craighead

C. W.

, Ketchen

D. J.

, Dunn

K. S.

, & Hult

G. G.

(2011). Addressing common method variance: Guidelines for survey research on information technology, operations, and supply chain management. IEEE Transactions on Engineering Management, 58(3), 578–588.

17.

Cui

A. S.

, Griffith

, & Cavusgil

S. T.

(2005). The influence of competitive intensity and market dynamism on knowledge management capabilities of multinational corporation subsidiaries. Journal of International Marketing, 13(3), 32–53.

18.

Davidson

(2014). A typology to categorize the ideologies for actors in the sustainable development debate. Sustainable Development, 22(1), 1–14.

19.

Deegan

(2000). Financial accounting theory. Sydney: McGraw-Hill.

20.

Deegan

(2002). Introduction: The legitimizing effect of social and environmental disclosures—A theoretical foundation. Accounting, Auditing & Accountability Journal, 15(3), 281–311.

21.

Dietz

, & Neumayer

(2007). Weak and strong sustainability in the SEEA: Concepts and measurement. Ecological Economics, 62(4), 617–626.

22.

DiMaggio

P. J.

, & Powell

W. W.

(1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational field. American Sociological Review, 48(2), 147–160.

23.

Doh

J. P.

, & Teegen

(2002). Nongovernmental organizations as institutional actors in international business: Theory and implications. International Business Review, 11(6), 665–684.

24.

Dowling

, & Pfeffer

(1975). Organizational legitimacy: Social values and organizational behavior. Pacific Sociological Review, 18(1), 122–136.

25.

Durant

R. F.

, & Legge

J. S.

(2005). Public opinion, risk perception, and genetically modified food regulatory policy reassessing the calculus of dissent among European citizens. European Union Politics, 6(2), 181–200.

26.

EU. (2012). Opinion of the European Economic Social Committee on ‘GMOs in the EU’ (additional opinion) (C 68/11). Report Official Journal of the European Union (OJEC) 2012/C 68/11.

27.

Evans

E. A.

, & Ballen

F. H.

(2013). A synopsis of US consumer perception of genetically modified (biotech) crops (EDIS document FE934). University of Florida, Gainesville: Food and Agricultural Sciences (IFAS).

28.

Fornell

, & Larcker

D. F.

(1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

29.

Freeman

R. E.

(1998). A stakeholder theory of the modern corporation. In Pincus

L. B.

(Ed.), Perspectives in business ethics (pp. 171–181). Singapore: McGraw-Hill.

30.

Frewer

, Lassen

, Scholderer

, Beekman

, & Berdal

K. G.

(2004). Societal aspects of genetically modified foods. Food Chem. Food and Chemical Toxicology, 42(7), 1181–1193.

31.

Gallopín

(2003). A systems approach to sustainability and sustainable development. Santiago, Chile: United Nations.

32.

Goyal

, & Gurtoo

(2011). Factors influencing public perception: Genetically modified organisms. GMO Biosafety Research, 2(1), 1–11.

33.

Graff

G. D.

, Hochman

, & Zilberman

(2009). The political economy of agricultural biotechnology policies. AgBioForum, 12(1), 34–46.

34.

Hair

J. F.

, Anderson

R. L.

, & Tatham

W. C.

(1998). Multivariate data analysis with reading. Upper Saddle River, NJ: Prentice-Hall.

35.

Harman

H. H.

(1967). Modern factor analysis. Chicago: University of Chicago Press.

36.

Harman

H. H.

(1976). Modern factor analysis (3rd ed.). Chicago, IL: University of Chicago Press.

37.

Harrison

J. A.

, Rouse

, & De Villiers

C. J.

(2012). Accountability and performance measurement: A stakeholder perspective. JCC: The Business and Economics Research Journal, 5(2), 243–258.

38.

Hawn

, Chatterji

, & Mitchell

(2011). Two coins in one purse? How market legitimacy affects the financial impact of changes in social legitimacy: Addition and deletion by the Dow Jones Sustainability Index (Working Paper No. 2418300). Durham, NC: Duke University.

39.

Heyder

, & Theuvsen

(2010). Corporate Social Responsibility in the agri-food sector: The case of GMOs. Problems of World Agriculture, 10(3), 15–32.

40.

Hoban

T. J.

(2000). Biotechnology: Addressing today’s core issues for better food and industry growth. Forum, Fourth Quarter, 95–105. Retrieved from http://www.agbioworld.org/pdf/Forum-BT.pdf

41.

Hoyle

R. H.

(1995). Structuring equation modeling: Concepts, issues and applications. London: SAGE Publications.

42.

Hull

C. E.

, & Luxmore

S. R.

(2007). Influence the acceptance on innovation: A tale of two perspectives on genetically-modified organisms. International Journal of Business strategy, 7(2), 12–17.

43.

Hulland

(1999). Use of partial least squares (PLS) in strategic management research: A review off our recent studies. Strategic Management Journal, 20(2), 195–204.

44.

Inghelbrecht

, Dessein

, & Van Huylenbroeck

(2015). Explaining the present GM business strategy on the EU food market: The gatekeepers’ perspective. New Biotechnology, 32(1), 65–77.

45.

Isaac

G. E.

, & Kerr

W. A.

(2003). Genetically modified organisms at the world trade organization: A harvest of trouble. Journal of World Trade, 37(6), 1083–1095.

46.

Kissinger

, William

E. R.

, & Timmer

(2011). Interregional sustainability: Governance and policy in an ecologically interdependent world. Environmental Science & Policy, 14(8), 965–976.

47.

Korea Research Institute of Bioscience and Biotechnology (KRIBB). (2015). Biosafety white paper 2015. Seoul: Moohan Publishing.

48.

Lee

C. J.

, Scheuffle

D. A.

, & Lewenstein

B. V.

(2005). Public attitudes toward emerging technologies. Science Communication, 27(2), 240–267.

49.

Legge

J. S.

, & Durant

R. F.

(2010). Public opinion, risk assessment, and biotechnology: Lessons from attitudes toward genetically modified foods in the European Union. Review of Policy Research, 27(1), 59–76.

50.

Lockie

, Lawrence

, Lyons

, & Grice

(2005). Factors underlying support or opposition to biotechnology among Australian food consumers and implications for retailer-led food regulation. Food Policy, 30(4), 399–418.

51.

Luxmore

S. R.

, & Hull

C. E.

(2010). Externalities and the six facets model of technology management: Genetically modified organisms in agribusiness. International Journal of Innovation and Technology Management, 7(1), 19–36.

52.

Luxmore

S. R.

, & Hull

C. E.

(2011). Innovation and NGOs. International Journal of Entrepreneurship and Innovation, 12(1), 17–27.

53.

Maeil Business Newspaper. (2013). Annual Corporation Reports 2014. Seoul: Maeil Business Publishing Co.

54.

Mutambara

(2013). A preliminary review of regulatory constraints affecting pig industry in Zimbabwe. Livestock Research for Rural Development, 25(3), 205–208.

55.

Navarro

M. J.

(2015). Voices and view: Why biotech? (ISAAA Briefs No. 50). Ithaca, NY: The International Service for the Acquisition of Agri-biotech Application (ISAAA).

56.

Nijhof

, De Bruijn

, & Honders

(2008). Partnerships for corporate social responsibility: A review of concepts and strategic options. Management Decision, 46(1), 152–167.

57.

Nunnally

I. C.

, & Bernstein

I. H.

(1994). Psychometric theory (3rd ed.). NY: McGraw-Hill.

58.

OECD. (2009). The bioeconomy to 2030: Designing a policy agenda–main findings and policy conclusions. Paris: OECD.

59.

Oliver

(1997). The influence of institutional and task environment relationships on organizational performance: The Canadian construction industry. Journal of Management Studies, 34(1), 99–124.

60.

Parsons

(1956). Suggestions for a sociological approach to the theory of organizations I. Administrative Science Quarterly, 1(1), 63–85.

61.

Pfeffer

, & Salancik

R. R.

(1978). The external control of organizations: A resource dependence perspective. New York: Harper & Row Publishers.

62.

Podsakoff

P. M.

, MacKenzie

S. B.

, Lee

J. Y.

, & Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.

63.

Priest

S. H.

, Bonfadelli

, & Rusanen

(2003). The ‘trust gap’ hypothesis: Predicting support for biotechnology across national cultures as functions of trust in actors. Risk Analysis, 23, 751–766.

64.

Richardson

(2010). From a fossil fuel to a bio-based economy? Reframing the third wave of biotechnology. IPEG Papers in Global Political Economy No. 45. International Political Economy Group (IPEG).

65.

Salamon

L. M.

, & Anheier

H. K.

(1994). The emerging sector: The non-profit sector in comparative perspective—An overview. Baltimore: Institute for Policy Studies, The Johns Hopkins University.

66.

Sharfman

, Ellington

R. T.

, & Meo

(1997). The next step in becoming ‘Green’: Life-cycle oriented environmental management. Business Horizons, 40(3), 12–22.

67.

Snell

(2009). Social responsibility in developing new biotechnology: Interpretations of responsibility in the governance of Finnish biotechnology (PhD Thesis). Retrieved from Department of Sociology, Research Reports 258. University of Helsinki.

68.

Soule

(2003). Corporate strategy, government regulatory policy and NGO activism: The case of genetically modified crops. In Doh

& Teegen

(Eds.), Globalization and NGOs: Transforming business, government and society (pp. 130–156). Westport, CT: Praeger.

69.

Suchman

(1995). Managing legitimacy: Strategic approaches and institutional approaches. Academy of Management Review, 20(3), 571–610.

70.

Sung

, & Hwang

(2013). Firms’ intentions to use genetically modified organisms industrially: The influence of sociopolitical-economic forces and managerial interpretations in the Korean context. Technol. Technological Forecasting and Social Change, 80(7), 1387–1394.

71.

Sung

, & Jang

(2008). How external political-economic forces affect firms’ attitudes towards the industrial use of genetically modified organisms: An analysis in the South Korean context. AgBioForum, 11(2), 114–122.

72.

Tan

, Shen

, Reed

, Saghaian

, & Chen

(2013). The impact of GMO safety regulation on Chinese soybean exports. Journal of Basic and Applied Scientific Research, 3(3), 162–171.

73.

Twardowski

(2012). Social and legal determinants for the marketing of GM products in Poland. New Biotechnology, 29(3), 249–253.

74.

Van der Laan

(2009). The role of theory in explaining motivation for corporate social disclosures: Voluntary disclosures vs ‘solicited’ disclosures. Australasian Accounting Business and Finance Journal, 3(4), 13–25.

75.

Vergragt

P. J.

, & Brown

H. S.

(2008). Genetic engineering in agriculture: New approaches for risk management through sustainability reporting. Technological Forecasting and Social Chang, 75(6), 783–798.

76.

Von Geibler

, Liedtke

, Wallbaum

, & Schaller

(2006). Accounting for the social dimension of sustainability: Experiences form the biotechnology industry. Business Strategy and the Environment, 15(5), 334–346.

77.

Wood

D. J.

(1991). Corporate social performance revisited. Academy of Management Review, 16(4), 691–718.