lable at ScienceDirect Journal of Cleaner Production 116 (2016) 170e176 Contents lists avai Journal of Cleaner Production journal homepage: www.elsevier .com/locate/ jc lepro Note from the field Green training and green supply chain management: evidence from Brazilian firms Adriano Alves Teixeira a, 1, Charbel Jose Chiappetta Jabbour b, *, Ana Beatriz Lopes de Sousa Jabbour b, 2, Hengky Latan c, e, 3, 5, Jorge Henrique Caldeira de Oliveira d, 4 a Environmental Management Research Group, UNESP-Univ Estadual Paulista (Sao Paulo State Univ), School of Engineering-Bauru, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, Bauru, SP 17033360, Brazil b UNESP-Univ Estadual Paulista (Sao Paulo State Univ), School of Engineering-Bauru, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, Bauru, SP 17033360, Brazil c University of Pattimura, Economic and Accounting Department, Jl. Ir. M. Putuhena Kampus-Poka, Ambon 97116, Indonesia d USP e Univ of Sao Paulo, FEARP, Av. Bandeirantes, 3900, Ribeirao Preto, SP 14033360, Brazil e Universitas Diponegoro, Faculty of Economics and Business, Department of Accounting, Jl. Erlangga Tengah 17, Semarang 50241, Indonesia a r t i c l e i n f o Article history: Received 14 November 2014 Received in revised form 3 December 2015 Accepted 17 December 2015 Available online 29 December 2015 Keywords: Brazil Green training Sustainable management Sustainable operations Green supply chain Green human resource management * Corresponding author. Tel./fax: þ55 1433036122. E-mail addresses: aatadrianobirigui@gmail.com ( gmail.com (C.J.C. Jabbour), abjabbour@feb.unesp.br hengkylatan@yahoo.com (H. Latan), jorgecaldeira@us 1 Tel./fax: þ55 1433036122. 2 Tel./fax: þ55 1433036122. 3 Tel./fax: þ62 911 322628. 4 Tel./fax: þ55 1632036122. 5 Tel./fax: þ62 248452273. http://dx.doi.org/10.1016/j.jclepro.2015.12.061 0959-6526/© 2016 Elsevier Ltd. All rights reserved. a b s t r a c t The implementation of green supply chain management practices, such as green purchasing and cooperation with customers, presents several challenges, often due to a lack of green training. In order to analyze the relationship between green training and green supply chains, a survey of Brazilian firms with ISO 14001 certification was conducted. The main characteristics of green training in the sample were also explored. The results indicated that green training is positively correlated with the adoption of green supply chain practices in green purchasing and cooperation with customers, confirming the study's main hypothesis. The research results also indicated that green training tends to help firms improve their green supply chain management to cooperate with customers and implement green purchasing. This work extends the current literature by showing that employees' green training content and requirements for greening suppliers should be further aligned. This alignment should also involve cleaner production priorities built up through customer cooperation. As a consequence, firms will reach internal environ- mental targets and achieve external environmental improvements (such as through having greener suppliers). Finally, we also discovered the main characteristics of green training that can galvanize green supply chain management, including the following: green training topics that are appropriate and cur- rent for company activities, green training contents created through a systematic analysis of training gaps and needs; and employees who receive green training and have the opportunity to apply green knowledge in everyday activities. © 2016 Elsevier Ltd. All rights reserved. A.A. Teixeira), prof.charbel@ (A.B.L. de Sousa Jabbour), p.br (J.H.C. de Oliveira). 1. Introduction and research background According to Gotschol et al. (2014), companies should give preference to GSCM (green purchasing and collaboration with customers), a more economically sustainable and environmentally friendly approach, when trying to become greener. In the context of more sustainable operations management (Walker et al., 2014; Piercy and Rich, 2015), GSCM extends the traditional concept of supply chain management (Tiwari et al., 2015; Wong et al., 2015; Govindan et al., 2014) by improving the environmental perfor- mance of products and services across their complete life cycles (Gunasekaran et al., 2015; Ahi and Searcy, 2015; Rostamzadeh et al., Delta:1_given name Delta:1_surname Delta:1_given name Delta:1_surname Delta:1_given name mailto:aatadrianobirigui@gmail.com mailto:prof.charbel@gmail.com mailto:prof.charbel@gmail.com mailto:abjabbour@feb.unesp.br mailto:hengkylatan@yahoo.com mailto:jorgecaldeira@usp.br http://crossmark.crossref.org/dialog/?doi=10.1016/j.jclepro.2015.12.061&domain=pdf www.sciencedirect.com/science/journal/09596526 http://www.elsevier.com/locate/jclepro http://dx.doi.org/10.1016/j.jclepro.2015.12.061 http://dx.doi.org/10.1016/j.jclepro.2015.12.061 http://dx.doi.org/10.1016/j.jclepro.2015.12.061 A.A. Teixeira et al. / Journal of Cleaner Production 116 (2016) 170e176 171 2015). In the context of searching for greater sustainability in supply chains (Brandenburg et al., 2014), the implementation of GSCM faces several barriers, such as the lack of financial resources to support remanufacturing (Zhu et al., 2014; Rauer and Kaufmann, 2014). Other potential barriers include the lack of trust among members in supply chains (Wood and Gray,1991) and the lack of an appropriate commitment from top management (Luthra et al., 2015). Although this topic has been discussed for the last decade (Srivastava, 2007), its implementation is still a challenge because of the aforementioned barriersdespecially in emerging economies (Tiwari et al., 2015; Fahimnia et al., 2015; Gunasekaran et al., 2014; Muduli et al., 2013; Jabbour et al., 2013; Zhu et al., 2005), where research on the topic needs to advance for companies to make real contributions to environmental management (Pagell and Shevchenko, 2014; Tachizawa and Wong, 2015). This situation is no different in Brazil, which was until 2013 one of the world's fastest-growing economies (along with India, Russia, and China) and the most important economy of South America. According to a recent report, Brazil will keep its position as one of the world's top 10 economies through 2050 (PWC, 2015)). It is necessary to know more about GSCM in South America, which is, according to Fahimnia et al. (2015), one of the world's least-studied areas regarding the current state of the art on GSCM, accounting for just 2.1% of the available literature on the subject. Although recent studies have shown that there is a positive scenario in which to adopt GSCM in Brazil (Alves and Nascimento, 2014), the current adoption level of GSCM practices can be further improved (Kannan et al., 2014). Of the wide range of possible GSCM practices (Zhu et al., 2005), we highlight green purchasing (GP) in this research, as this is related to the inclusion of envi- ronmental criteria in supplier selection and purchasing and to collaboration with consumers (CC), which refers to customer engagement, green feedback and guidelines on the greening of firms (Zhu et al., 2008). GP and CC practices are used in an attempt to overcome the challenges of stakeholder inclusion in environ- mental actions (Abreu et al., 2015) by involving customers and suppliers in the decision-making processes related to green issues across the supply chain. According to the resource-based view of sustainable supply chains (Touboulic and Walker, 2015), the alignment between hu- man resource management and environmental management (including GSCM)dalso known as green human resource man- agement (GHRM) (Jackson et al., 2014)dcan help firms to over- come barriers to adopting CC and GP. This is because GHRM, which is defined as the alignment between traditional human resources practices (such as training and performance appraisals) and envi- ronmental policies and objectives (Jackson et al., 2014; Renwick et al., 2013), can contribute to greater employee engagement in sustainability management (Renwick et al., 2013). This is particu- larly true in a context in which increasingly proactive environ- mental behaviors are necessary (Graves et al., 2013; Ehnert, 2009). Among the GHRM practices that can contribute to GSCM, we highlighted green or environmental training (GT). GT can be defined as a process of on-the-job training and continued edu- cation intended to achieve corporate environmental manage- ment targets and purposes (Daily and Huang, 2001). According to Paill�e et al. (2014) and Muduli et al. (2013), GT is a type of training related to relevant environmental topics; it enables all staff (top, senior, and middle managers and the workforce) to integrate the firm's performance with environmental issues. Recent research suggests that GT is positively related to the greening of companies around the world. For example, Sarkis et al. (2010) claimed that GT was relevant to the adoption of advanced environmental practices among companies in Spain. Daily et al. (2012) stated that GT is relevant to green teams. Jabbour (2015) indicated that GT is positively related to the evolution of environmental management in firms. Other studies have reinforced the importance of GT for a green economy (Jackson et al., 2014; Renwick et al., 2013). However, based on the available knowledge, the following gaps still remain in the current literature. First, works have suggested that organizational learning (van Hoof, 2014) and training are relevant to cleaner production programs (Stone, 2000). More spe- cifically, Gosling et al. (2014) suggested that organizational learning is relevant to creating more sustainable supply chains. However, these works do not directly discuss the link between GT and GSCM. On the other hand, many works on green training are qualitative (Perron et al., 2006; Teixeira et al., 2012) or conceptual, such as literature reviews (Jabbour, 2013). More quantitative studies are still needed (Jabbour and Jabbour, 2016). As a consequence, this is a useful avenue for future research. A research gap also exists regarding whether green training is positively related to green supply chain practices (such as green purchasing and cooperation with customers). Additionally, this study presented the main green training characteristics that sup- port the above-mentioned GSCM practices. Furthermore, considering that firm size (FS) plays amajor role in the adoption of more sustainable management practices (Bai et al., 2015), this measure is expected to exert significant control over the adoption of GSCM. Assuming that green training is positively related to green supply chain management, we surveyed Brazilian companies that used the ISO 14001 certification for environmental management systems to test the validity of the proposed frame- work and research hypothesis. Additionally, we tested the role of firm size (FS). So far, we have found no similar works in the Scopus or ISI Web of Science databases dedicated to analyzing GT for GSCM (CC/GP) in this kind of sample. 2. Research method This research was quantitative and based on an electronic sur- vey. We proposed the research framework shown in Fig. 1. Survey studies are generally relational because they tend to be designed to empirically examine relationships among two or more constructs or variables (Rungtusanatham et al., 2003). Surveys are also rele- vant for describing important variables or characteristics of con- structs (Rungtusanatham et al., 2003). The survey approach was selected in this work mainly because we tested the relationship between GT and GSCM to provide a description of GT's main characteristics. This quantitative approach was adequate for the research questions presented herein. As a consequence, we tested the following relationship (H1): GT is positively related to the adop- tion of GSCM practices. We also explored GT's main characteristics. The survey questionnaire included the measurement of eight GSCM practices/items (five for GP and three for CC). The selected GSCM practices were validated by Zhu et al. (2008) in the Chinese context. As discussed by Zhu et al. (2008), the scale was inspired by assumptions from the ecological modernization theory applied to GSCM andwere further discussed by Sarkis et al. (2011). In addition, the questionnaire measured 10 GT practices. The GT practices were based on the validated scale from Daily et al. (2012) and were inspired by works discussing GT, such as Teixeira et al. (2012) and the ISO 10015 (2001). Table 1 shows the references for all the selected items in the research questionnaire. As explained above, all the selected items were validated by the literature. In addition, we measured the FS variable using four types of patterns in Brazil based on the number of employees: micro-sized firms (up to 19 employees), small firms (20e99 employees), medium-sized firms (100e499 employees), and large firms (500 or Fig. 1. Research framework. Table 1 Constructs/Items used in the research's questionnaire. Concept Items Adapted from GT (Green Training) GT1dContents of GT are raised through a systematic analysis of training gaps and needs Daily et al. (2012); Teixeira et al. (2012); ISO 10015 (2001); ISO 14001 (2004) GT2dThe responsibilities and duties of official green trainers are precisely defined Daily et al. (2012); Teixeira et al. (2012); ISO 14001 (2004) GT3dGT is offered to all employees (including outsourced) Daily et al. (2012); Teixeira et al. (2012); ISO 14001 (2004) GT4dThere is an adequate infrastructure (physical space, material, people) for the delivery of GT Daily et al. (2012); Teixeira et al. (2012); ISO 10015 (2001) GT5dGT sessions occur within the company Daily et al. (2012); Teixeira et al. (2012); ISO 10015 (2001) GT6dGT sessions occur outside of the company Daily et al. (2012); Teixeira et al. (2012); ISO 10015 (2001) GT7dThere are adequate assessments of employees' performance after attending GT sessions Daily et al. (2012); Teixeira et al. (2012); ISO 10015 (2001) GT8dGenerally, employees are satisfied with the GT offered; Daily et al. (2012); Teixeira et al. (2012); ISO 10015 (2001) GT9dThe topics approached during GT are appropriate and current for company activities Daily et al. (2012); Teixeira et al. (2012) GT10dEmployees who receive GT have the opportunity to apply green knowledge in everyday activities Daily et al. (2012); ISO 10015 (2001) GSCM (Green Supply Chain Management) GP1dSelection of suppliers with ISO 14001 certification Zhu et al. (2008) GP2dCooperation with suppliers to achieve green goals GP3dAvailable green guidelines to suppliers GP4dAssessment of green issues of second-tier suppliers GP5dConducting green audits within the suppliers CC1dCooperation with customers for cleaner production CC2dCooperation with the customers to develop greener packaging CC3dCooperation with customer for eco-design Note: GT was measured with a Likert scale from 1 to 5, where 1 means “strongly disagree,” and 5 means “strongly agree”; GSCMwas measured with a Likert scale from 1 to 5, where 1 means “not implemented” and 5 is “fully implemented.” A.A. Teixeira et al. / Journal of Cleaner Production 116 (2016) 170e176172 more employees). Based on data from 2013, there are about 3700 ISO 14001-certified firms in Brazil (ISO, 2013). An online link to this research questionnaire was sent by email to Brazilian environ- mental/sustainability/operations managers and to owners of manufacturing firms with ISO 14001 certification (as listed in the INMETRO [Instituto Nacional de Metrologia, Qualidade e Tecnolo- gia] database). About 330 potential participants were contacted by email and by phone in 2012 and 2013, and 95 questionnaires were collected; thus, a return rate of 28.78%was obtained. Of the participants in the final research sample, 66.32% were from the manufacturing sector (among all participants: 20% from automotive companies, 13.68% from the chemical sector, 10.53% from the electronics sector and 22.11% from other manufacturing areas); 9.47% were from the coal, oil, and gas equipment sector; and 24.21% were frommixed sectors. This sample's representation comprised 2.1% micro-sized firms, 18.9% small firms, 42.1% medium-sized firms, and 36.9% large companies, all of which had ISO 14001 certification. The data were analyzed with structural equation modeling (SEM) using partial least squares (PLS) with the support of the SmartPLS 2.0 M3 software. 3. Research results The research results analyzed the following two main questions posed by this work. First, is there a positive link between GT and GSCM? Second, what are the main characteristics of GT that can drive GSCM? Because we analyzed the data through SEM, given the collin- earity issues that arise from running the model using the tradi- tional, repeated indicators approach, we chose to use a two-stage approach (Kock and Lynn, 2012), which was the only one for which we could manage the problems of the collinear data that we faced (see Table 2). In order to process the collected data, a path diagram was built to show the relationship between the dependent and independent Table 2 Convergent validity and internal consistency reliability (factor weighting scheme; mean 0, Var 1; Max. Iteration 300). Latent variables Items/ Indicators Indicator reliability AVE Composite reliability Green Training GT1 0.807 GT2 0.734 GT3 0.669 GT7 0.740 0.5821 0.9066 GT8 0.745 GT9 0.837 GT10 0.794 CC CC1 0.882 CC2 0.850 0.7535 0.9017 CC3 0.871 GP GP1 0.812 GP2 0.895 GP3 0.849 0.6161 0.8878 GP4 0.695 GP5 0.644 Note: Some items were removed because they have indicators of reliability <0.6. All items have indicators of reliability >0.6, AVE >0.5, and CR >0.7. A.A. Teixeira et al. / Journal of Cleaner Production 116 (2016) 170e176 173 variables, including their related variables (Esposito Vinzi et al., 2010; Kristensen and Eskildsen, 2010). After processing the path diagram, a measurement model was built to determine if the ob- tained coefficients were significant (Hair Jr. et al., 1998). Initially, as shown in Fig. 2, we found that the GT construct needed to be refined with a reduced number of variables; we excluded the GT4eGT6 items mainly because those variables had Fig. 2. Path diagram outer model with Smar reliability lower than 0.6 and AVE lower than 0.5, both of which were lower than recommended (Latan and Ghozali, 2012). Fig. 2 above shows the first step of the two-stage approach. In this stage, all the first-order constructs were linked to assess the validity and reliability of the outer model PLS. Fig. 2 shows that the loading factors for all the indicators were greater than 0.6 and that the values of AVE and CR generated by each construct were compliant (see Tables 2 and 3). After all the criteria were met, the score of each latent variable was used for the second step to test the hypothesis of the inner model PLS. After excluding items GT4eGT6 and adopting a two-stage approach, the convergent validity, internal consistency reliability, and discriminant validity showed improved statistical fit, as sug- gested by the literature (Latan and Ghozali, 2012; see Table 3). Going ahead with the statistical analysis, to obtain better sta- tistical fit and check the statistical significance of the obtained coefficients, a structural model was estimated based on boot- strapping with 2000 subsamples (Tables 4 and 5). This test ob- tained the following results (Fig. 3). The R-squared (R2) values were, according to Cohen (1992), large and satisfactory. The variance inflation factor (VIF) was less than 1.412, which is considered adequate (Latan and Ghozali, 2012). GT's effect size (f2) on GSCM was 0.292, which is significant (Latan and Ghozali, 2012). The R2 set was considered small when it was less than 0.25, medium when it was less than 0.50, and large when it was less than 0.70. Therefore, it was considered small and appropriate (Latan and Ghozali, 2012). Enough Q2 predictive validity was obtained, as the dependent variable’s validity was 0.310 (Latan and Ghozali, 2012). Finally, the goodness of fit (GoF absolute), which is a general measure of a tPLS 2.0 M3 using Two-Stage Approach. Table 3 Discriminant validity. Variables CC GP GT CC (0.8680) GP 0.5565 (0.7849) GT 0.4417 0.4979 (0.7630) Note: Square roots of average variances extracted (AVEs) shown diagonally must be higher than the others correlations. A.A. Teixeira et al. / Journal of Cleaner Production 116 (2016) 170e176174 model's statistical adequacy, was equal to 0.458, which is consid- ered large; therefore, the model was considered valid, based on Latan and Ghozali (2012). According to Latan and Ghozali (2012) and Hair Jr. et al. (2011), t values of 1.65, 1.96, and 2.58 are considered equivalent to signifi- cance levels of 10%, 5%, and 1%, respectively. As a consequence, it is possible to conclude that the relationship between GT and GSCM was significant at the 1% level and that the FS-GSCM relationship (t ¼ 2.0571) was not significant at the 1% level (following Fig. 3 and Table 5). Table 4 Inner model analysis (bootstrapping / sign changes ¼ individual changes; cases 95; sa Latent Variables R-Squared (R2) Adjusted R2 Effect si GT e e 0.292 CC 0.218 0.201 e GP 0.264 0.248 e GSCM 0.308 0.293 e Note: For computing the adjusted R2, we used the formula below, as SmartPLS cannot co R2Y ¼ R-squared; n ¼ sample size; and k ¼ number of predictor variables. For computin compute it automatically: Q2 ¼ 1�P DED= P DOD , where D¼ omission distance; E¼ num used the formula below because SmartPLS cannot compute it automatically: GoF ¼ ffiffiffiffiffi AA p Table 5 Hypothesis testing for relationship among variables (Sig. 5% two-tails with DF ¼ 96 / S Relations Original sample (O) Sample mean (M) Standard de Green Training / GSCM 0.5497 0.5538 0.0618 Fig. 3. Path diagram inner model with Smar Thus, responding to the first research question, the research results (Table 5) show that H1 should be considered valid, as GT was positively related with GSCM. Fig. 2 shows that GT was more heavily related to GP than to CC. Regarding the second research question the GT practices from the sample that were most intensely related to GSCM practices were items GT9 (“The topics approached during GT are appropriate and current for company activities.”), GT1 (“The contents of GT are raised through a systematic analysis of training gaps and needs.”), and GT10 (“Employees who receive GT have the opportunity to apply green knowledge in everyday activities.”), in that order. The most relevant GP practices were GP2 (“cooperation with suppliers to achieve green goals”) and GP3 (“green guidelines available for suppliers”). On the other hand, the most relevant CC items were CC1 (“cooperation with customers for cleaner produc- tion”) and CC2 (“cooperation with customers to develop greener packaging”). These results suggest that firms adopting GSCM practices should empower their employees with green awareness and skills through GT (such as GT9). If employees have more environmental mple 2000). ze (f2) Q2 predictive Validity VIF GoF absolute e 1.412 e e 1.251 e e 1.330 e 0.310 e 0.458 mpute it automatically: eR2Y ¼ 1� ð1� R2Y Þn� 1=n� k� 1, where eR2Y ¼ adjusted R2; g the Q2 predictive validity, we used the formula below because SmartPLS cannot ber of squares; and O¼ number of square errors. For computing the absolute GoF, weffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi VE� AARS, where AAVE ¼ Average AVE and AARS ¼ Average Adjusted R2. tudent's t ¼ 1.980). viation (STDEV) Standard error (STERR) T Statistics (jO/STERRj) Decision 0.0618 8.9006 Accept tPLS 2.0 M3 using Two-Stage Approach. A.A. Teixeira et al. / Journal of Cleaner Production 116 (2016) 170e176 175 awareness, they may be able to support the greening of suppliers across the supply chain (GP2). On the other hand, this process may also make customers consider cleaner production improvements (CC1). Consequently, GTmay bridge firms, suppliers, and customers in the greening process. 4. Discussion Some managerial implications emerged from the above- mentioned results. Employees' GT content must be aligned with the requirements for greening suppliers. This alignment should also consider cleaner production priorities built up through cos- tumers' cooperation. As a consequence of these actions, firms will reach internal environmental targets and make external environ- mental improvements through their greener suppliers. Secondly, GT offered may have to be extended from internal employees to the supply chain as a wholedincluding to suppliers and customersdto achieve a better fit in green management. These results confirmed the relevance of GHRM and GSCM integration (Jabbour and Jabbour, 2016) in a context of more sus- tainable human resource management (Ehnert, 2009). They also supported Stone (2000), whose findings suggested that GT is a key aspect of cleaner production initiatives. In this context, GT can also be considered a key aspect of better green management coopera- tion with customers. GT may also be a source of green organiza- tional learning and knowledge because it is related to the adoption of GP and CC across the supply chain. This confirms not only the relevance of GHRM (Jackson et al., 2014; Renwick et al., 2013) but also the specific role that GT plays in making organizations greener (Sarkis et al., 2010). In this context, GT is a source of competitive advantage for firms (Touboulic and Walker, 2015). When focusing on GT, companies should invest in the content of training sections, the systematic analysis of training gaps and needs, and opportu- nities for employees to apply green knowledge. 5. Conclusions Based on the stated research questions, this work determined whether green training (GT) was positively related to the adoption of GSCM practices such as GP and CC (the main variables of GT that influence GSCM). Themain characteristics of GTwere also explored. This work added empirical evidence on GSCM in South America, an under-studied region (Fahimnia et al., 2015). It contributed to a better understanding of the integration between GSCM and GHRM (Jabbour and Jabbour, 2016). After researching the relationship between GT and GSCM in 95 firms with ISO 14001 certification in Brazil, we concluded that the tested framework as a whole pre- sented good validity (GoF), and that GTdmainly items GT9, GT1 and GT10dwas positively and significantly related to GSCM in the analyzed firms, which confirmed the main research hypothesis. The results showed the relevance of green training, confirming that organizational learning (Gosling et al., 2014) and the alignment of human resources practices (Jackson et al., 2014) are crucial to the greening of firms, as they reduce barriers to GSCM adoption. Spe- cifically, we confirmed that the adoption of more advanced envi- ronmental management practicesdsuch as GSCMdrequires more attention from green training programs, as suggested by Sarkis et al. (2010). GT should consider how to involve stakeholders, mainly customers, in the search for GSCM. Some important characteristics of GT can bolster the green supply chain, such as GT9 (“The topics approached during GT are appropriate and current for company activities.”), GT1 (“The con- tents of GT are raised through a systematic analysis of training gaps and needs.”), and GT10 (“Employees who receive GT have the op- portunity to apply green knowledge in everyday activities.”). Finally, the role of firm size in the interaction between GSCM and GT may be a relevant research avenue, as it did not seem to be significant in this research. This work has some limitations. First, social desirability bias has become a concern in sustainability studies, as the respondents try to perform as they believe interviewers expect. Under this circumstance, less accurate responses can be obtained (Roxas and Lindsay, 2012). Furthermore, this work was only related to the Brazilian context, and only focused on ISO 14001-certified firms. Finally, this study's research sample did not represent the distri- bution of ISO 14001 sectors and firms across Brazil. Future research should consider the effect of the industrial sector (as a control variable) and other complex characteristics of GSCM implementa- tion, such as GSCM governance. Acknowledgments Research reported in this work was partially supported by FAPESP e Sao Paulo State Research Foundation (Grant # 2013/ 22380-0) and by CNPq e Brazilian Council for Scientific and Tech- nological Development (Grant # 304225/2013-4; Grant # 303484/ 2013-6; Grant # 232060/2013-4). 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Introduction and research background 2. Research method 3. Research results 4. Discussion 5. Conclusions Acknowledgments References