quality management and environmental management_direct and indirect effects

8/12/2019 Quality Management and Environmental Management_direct and Indirect Effects

1/13

Quality management, environmental management maturity,

green supply chain practices and green performance of Brazilian

companies with ISO 14001 certification: Direct and indirect

effects

Ana Beatriz Lopes de Sousa Jabbour a,1, Charbel Jose Chiappetta Jabbour a,, Hengky Latan b,Adriano Alves Teixeira c, Jorge Henrique Caldeira de Oliveira c

a UNESP Univ Estadual Paulista (Sao Paulo State Univ), Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, Bauru, SP CEP 17033360, Brazilb University of Pattimura, Economic and Accounting Department, Indonesiac USP Faculdade de Economia, Administrao e Contabilidade de Ribeiro Preto, Av. Bandeirantes, 3900, Monte Alegre, Ribeiro Preto CEP 14033390, Brazil

a r t i c l e i n f o

Article history:

Received 26 September 2013

Received in revised form 22 February 2014

Accepted 9 March 2014

Keywords:

Green supply chain practices

Environmental management

Quality management

Green performance

Sustainable operations

Brazil

a b s t r a c t

This study aims to test a new conceptual model based on the relationship between quality

management (QM), environmental management maturity (EMM), adoption of external

practices of green supply chain management (GSCM) (green purchasing and collaboration

with customers) and green performance (GP) with data from 95 Brazilian firms with ISO

14001. To our knowledge, such links and relationships are not simultaneously identified

and tested in the literature. The results indicate the validation of all of the research hypoth-

eses. This paper highlights that an improvement in green performance will require atten-

tion to quality management, environmental management maturity, and green supplychain.

2014 Elsevier Ltd. All rights reserved.

1. Introduction

In a recent survey, approximately 70% of business leaders said that sustainability has a permanent place in their

management agendas, but the success of this process depends on collaborations established between supply chain firms

(Kiron et al., 2012). In this context, the concept of green supply chain management (GSCM) has grown in importance because

it contributes in the transition towards eco-efficiency (Govindan et al., 2014) and sustainability (Yusuf et al., 2013; Zhu et al.,

2013b) and also to the future of operations management (Gunasekaran and Ngai, 2012; Diabat and Govindan, 2011).

As a consequence of the concept of extended producer responsibility (EPR) (Sheu and Talley, 2011), GSCM can be defined

as the coordination of the supply chain in a form that integrates environmental concerns and considers inter-organizational

activities (Green et al., 2012). GSCM manages the acquisition, production and distribution of materials to meet the

http://dx.doi.org/10.1016/j.tre.2014.03.005

1366-5545/ 2014 Elsevier Ltd. All rights reserved.

Corresponding author. Tel./fax: +55 14 31036122.

E-mail addresses: [email protected] (A.B.L.S. Jabbour), [email protected] (C.J.C. Jabbour),[email protected] (H. Latan),aatadrianobirigui@

gmail.com(A.A. Teixeira), [email protected](J.H.C. de Oliveira).1 Tel./fax: +55 14 31036122.

Transportation Research Part E 67 (2014) 3951

Contents lists available at ScienceDirect

Transportation Research Part E

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a te / t r e
http://dx.doi.org/10.1016/j.tre.2014.03.005mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]://dx.doi.org/10.1016/j.tre.2014.03.005http://www.sciencedirect.com/science/journal/13665545http://www.elsevier.com/locate/trehttp://www.elsevier.com/locate/trehttp://www.sciencedirect.com/science/journal/13665545http://dx.doi.org/10.1016/j.tre.2014.03.005mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]://dx.doi.org/10.1016/j.tre.2014.03.005http://-/?-http://-/?-http://-/?-http://crossmark.crossref.org/dialog/?doi=10.1016/j.tre.2014.03.005&domain=pdf


2/13

requirements of stakeholders to improve profitability, competitiveness and the resilience of organization in the short and

medium terms through improved green performance (Ahi and Searcy, 2013). GSCM practices that involve every tier in

the greening of a supply chain are often called external GSCM practices (Zhu et al., 2007a).

The literature argues that in general, the adoption of GSCM practices tends to affect not only the companys green per-

formance (Zhu et al., 2007b, 2013b) but also supply chain performance too (Azevedo et al., 2011). However, with regard

to external GSCM practices, such findings may not appear conclusive because both supporting (Zhu et al., 2007a; Green

et al., 2012) and contradictory results (Zailani et al., 2012) can be found. Another relevant finding, according toZhu et al.

(2012a), is that it is desirable for companies improve their EMM before they improve green management performance

through external GSCM practices. Hence the maturity level of environmental management may have implications for the

adoption of GSCM practices. Certainly, one way to improve the EMM in companies is through the early adoption of quality

management (QM) principles (Pereira-Moliner et al., 2012; Llanch et al., 2013; Zhu et al., 2013a).

However, the literature lacks an adequate analysis of the relationship between QM, the environmental management

maturity (EMM), external GSCM practices and the environmental performance of firms (GP).

Additionally, two relevant variables may influence this relationship: the national context and firm size. Seuring and

Gold (2013)note that there are few studies on developing countries within the theme of sustainability in supply chains.

Thus, analyzing Brazilian companies may be important, particularly because Brazil is part of the BRIC group (Brazil, Russia,

India and China) and corresponds to approximately 30% of GDP in Latin America. In addition, Brazil is among the 10 larg-

est world economies (Jabbour and Jabbour, 2014). The importance of firm size has also been highlighted by several

authors as a variable that can influence the green performance of organizations ( Gonzlez-Benito and Gonzlez-Benito,

2006).

From the above, the questions that we seek to answer in this study are as follows: Does quality management (QM) influ-

ence environmental management maturity (EMM)? Does EMM influence the adoption of external green supply chain man-

agement (GSCM) practices? Do external GSCM practices influence the green performance of these firms (GP)? Does EMM

mediate the relationship between QM and GSCM? Does GSCM mediate the influences of EMM and GP? Are these relation-

ships valid for the companies in Brazil with ISO 14001 certification?

Thus, the aim of this research is to answer the questions above. To this end, we present the results of a survey of 95 Bra-

zilian companies with ISO 14001 certification and test these data using a conceptual model that incorporates 9 research

hypotheses. The value of this analysis derives from the following: (a) the literature on organizational sustainability, as far

as the authors of this article know, still presents no simultaneous testing of the identified relationships, (b) the reality of

developing countries, with the exception of China, is still poorly analyzed. Thus, to our knowledge, these are the first research

findings that combine the concepts of QM, EMM, GSCM and GP based on the Brazilian context.

This paper is structured as follows: Section2presents the literature review and the research hypotheses; Section3pre-

sents the research methodology; Section4presents the results; Section5presents the discussion and, finally, Section6pre-

sents the conclusions of this paper.

2. Theory and hypothesis development

2.1. Quality management (QM) and environmental management

In the 1980s, Western companies began to import a series of concepts, tools and Asian techniques to improve processes

and, subsequently, competitiveness through QM (Lo et al., 2013). Just as QM had its greatest development in companies dur-

ing the 1980s and 1990s, environmental management, a set of initiatives to mitigate the impact of organizations operations

on the environment (Bansal and Roth, 2000), intensified in the 1990s. According toLubin and Esty (2010), the concept of

environmental sustainability has changed the way in which companies conduct their business, and it appears to have fol-

lowed a trajectory similar to that of QM.

Furthermore, the specialized literature (Narasimhan and Schoenherr, 2012; Pereira-Moliner et al., 2012) notes that there

are numerous similarities between QM and environmental practices, such as zero defects, life cycle assessment, waste reduc-

tion, and the involvement and training of employees and senior management ( Sroufe and Curkovic, 2008).

In this sense, some studies suggest that QM practices such as ISO 9001 and other certification programs and supplier total

quality management (TQM) can facilitate or accelerate the implementation of environmental practices as well as increasing

their effectiveness (Wiengarten and Pagell, 2012;Pereira-Moliner et al., 2012; Llanch et al., 2013). Indeed,Wiengarten and

Pagell (2012)found empirical evidence that companies improve their performance in terms of cost, flexibility and delivery

performance when environmental management practices exist due to high investments in QM practices.

Further, Pereira-Moliner et al. (2012) examined hotels in Spain, Llanch et al. (2013) investigated 374 restaurant managers,

and Zhu et al. (2013a)studied manufacturing companies in China. All these studies observed that QM practices facilitate the

development of environmental management practices, which in turn have a positive impact on quality management prac-

tices, producing knowledge that is acquired that then facilitates the adoption of environmental practices in a synergistic way.

In other words, it is possible to favor the implementation of environmental practices by taking advantage of the resourcesand capabilities developed for QM.

40 A.B.L.S. Jabbour et al. / Transportation Research Part E 67 (2014) 3951
http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


3/13

Pereira-Moliner et al. (2012)emphasize that companies can use QM approaches to develop a comprehensive system for

reducing and eliminating all waste streams associated with the design, manufacture, use and/or disposal of products and

materials, thus improving the EMM of firms. From the above, we derive the first hypothesis:

H1. QM positively influences the environmental management maturity in firms.

2.2. The environmental management maturity (EMM) and external GSCM practices

Environmental management is a set of initiatives that seek to mitigate the impact of an organizations activities on the

environment (Haden et al., 2009). Organizations can reduce their environmental impact through products, processes and

policies that reduce energy consumption and waste generation, and which promote the use of resources that are both

environmentally friendly and sustainable and which employ Environmental Management Systems too ( Bansal and Roth,

2000). According toKolk and Mauser (2002), due to the complexity and diversity of environmental management practices

and because of the different attitudes with which companies face the challenges of environmental problems (Tomomi, 2010),

an increasing number of business leaders and scholars have been characterizing companies in terms of their environmental

actions (Aragn-Correa and Rubio-Lpez, 2007).

The different environmental conscience of industrial businesses can be positioned along their environmental maturity

level (Murillo-Luna et al., 2011), which varies according to the viewpoint of authors. According to Jabbour and Jabbour

(2009), Jabbour (2010)andTeixeira et al. (2012), companies can be positioned in one of the three following environmental

management maturity levels:

Reactive Stage of Environmental Management companies at this stage are concerned about the cost of failure to comply

with environmental legislation, so the focus is on the end of the process, for example, the use of filters in chimneys and

the correct disposal of waste. Therefore, environmental management does not take place within the production process

with the intent of performing some type of structural change.

Preventive Stage of Environmental Management companies at this stage avoid/minimize the generation of waste or the

overuse of inputs. Therefore, the focus is on the pursuit of eco-efficiency. Environmental management begins to have a

role in the companys organizational structure.

Proactive Stage of Environmental Management companies at this stage consider aspects of environmental management

as a strategy for the companys competitive advantage. The objective of environmental management is to make consid-

erable changes in the processes and/or products. At this stage, companies have actions with the support of suppliers and

customers.

The discussion of environmental management cannot be restricted to the organization, as the entire organization influ-

ences and is influenced by the supply chain (Seuring and Gold, 2013). Thus, organizations have interdependencies because

they engage in material and information flows, from the supplier of raw materials to the final customer ( Mentzer et al.,

2001), adding value to the product at each tier in the supply chain ( Tan, 2001). This broader supply chain perspective is rel-

evant for the transition towards sustainability, and it is termed green supply chain management (GSCM). According to

Srivastava (2007), GSCM is defined as the integration of environmental thinking into the management of the supply chain,

including product design, procurement and material selection and product delivery to the end customer as well as managing

the life cycle of the products after-life.Sarkis et al. (2011)define GSCM as the integration of environmental management

into the inter-organizational practices of the supply chain, including reverse logistics.

Zhu et al. (2008)suggest several GSCM practices and highlight two in particular: green purchasing and cooperation with

customers. Green purchases are related to aspects of cooperation with suppliers to achieve environmental objectives and the

valuation of suppliers based on audits and ISO 14001 certification. Cooperation with customers considers customer

collaboration for eco design, cleaner production and green packaging.

The literature suggests that external GSCM practices have been less frequently adopted than internal environmental

practices (Zhu and Sarkis, 2004, 2006; Zhu et al., 2007a,b, 2008, 2012b; Holt and Ghobadian, 2009; Liu et al., 2012), and

also indicates that these external GSCM practices are fundamental to the pursuit of more sustainable organizations. For

example,Yang et al. (2013)confirm that internal green practices and external green collaboration have positive impacts

on green performance. Advanced environmental management tends to coincide with the adoption of external GSCM

practices.

De Giovanni and Vinzi (2012)claim that being a green company internally is a prerequisite for collaboration in GSCM.

According toGreen et al. (2012), achieving a certain level of environmental management is a prerequisite for external GSCM

actions. Here, Zhu et al. (2012a) argue that to improve environmental performance by making use of external GSCM

practices, it is desirable for the company to first implement internal environmental management practices, and Zhu et al.

(2013b) indicate that, due to institutional pressures, Chinese companies adopt internal environmental management

practices followed by external GSCM. According to Darnall et al. (2008), previous experience with an internal

environmental management system can favor the adoption of GSCM practices. Consequently, according to Testa and

Iraldo (2010), GSCM is a result of the maturing of environmental management. From the above, we derive the followingtwo hypotheses:

A.B.L.S. Jabbour et al. / Transportation Research Part E 67 (2014) 3951 41
http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


4/13

H2a. The environmental management maturity (EMM) influences the adoption of external GSCM practices such as

cooperation with customers.

H2b. The environmental management maturity (EMM) influences the adoption of external GSCM practices such as green

purchasing.

2.3. External GSCM practices and the green performance (GP) of firms

According toHervani et al. (2005), green performance (GP) indicators are essential requirements for GSCM. Zhu et al.

(2008)conducted an empirical study of Chinese companies and proposed a method for evaluating green performance in

organizations using: pollution emission/waste; environmental legislation adequacy; environmental reputation, overall envi-

ronmental performance.

Zhu and Sarkis (2004)emphasize that external GSCM practices have a direct and positive impact on green performance,

whilePerotti et al. (2012), De Giovanni (2012) andZhu et al. (2012a)argue that to improve green performance through the

adoption of external GSCM practices, it is desirable for the company to first establish a high level of EMM. According to De

Giovanni and Vinzi (2012), the relationship between external GSCM practices and green performance needs to be strength-

ened. In general, the literature appears to highlight the findings by Zhu et al. (2007b) and Zhu et al. (2013b) that the adoption

of GSCM practices improves green performance.

Green et al. (2012) indicate that among external GSCM practices, green purchasing does not have as significant impact on

green performance as the practice of cooperation with customers, a finding which was confirmed by Zhu et al. (2007a), in theirresearch on Chinese automotive companies. However, Zailani et al. (2012), in their study of Malaysian companies, found that

green purchasing has a positive effect on environmental performance, and Yang et al. (2013) suggest that GSCM have positive

impacts on green performance too. Additional evidence fromJabbour et al. (2014) based on mixed methodology (survey and

case studies) suggests that GSCM is linked with EMM. From the above we develop the following two hypotheses:

H3a. The adoption of external GSCM practices such as cooperation with customers influences the green performance (GP)

of firms.

H3b. The adoption of external GSCM practices such as green purchasing influences the green performance (GP) of firms.

Additionally, as the literature asks if QM influences EMM (Simon et al., 2013; Zhu et al., 2013a), and proposes that EMM in

turn can influence the adoption of external GSCM practices (Jabbour et al., 2014), we derive two further hypothses:

H4a. EMM mediates the relationship between QM and the adoption of external GSCM such as cooperation with

customers.

H4b. EMM mediates the relationship between QM and the adoption of external GSCM practices such as green purchasing.

Nonetheless, as the literature also asks if external GSCM practices can improve the green performance of firms (Yang

et al., 2013) but see GSCM as also influenced by EMM, then we derive the following two hypotheses also, that:

H5a. External GSCM practices such as cooperation with customers mediate the relationship between EMM and the green

performance of firms.

H5b. External GSCM practices such as green purchases mediate the relationship between EMM and the green performance

of firms.

2.4. Firm size as a control variable of green performance (GP)

In general, the size of the firm is a control variable in statistical models. One measure of firm size is the number of com-

pany employees (Zhu et al., 2007a; Lpez-Gamero et al., 2010; Murillo-Luna et al., 2011 ). In Brazil, according toSebrae

(2013), firms can be classified according to the number of employees into four groups: micro (119 employees), small

(2099 employees), medium (100499 employees) and large (500 or more employees).

Lpez-Gamero et al. (2010)found that company size is a relevant condition for achieving a proactive EMM, and Murillo-

Luna et al. (2011)also reached the conclusion that small firms face greater difficulties than large enterprises when adopting

more advanced practices for environmental protection. Ribeiro et al. (2012) found that the degree of development ofenvironmental management practices is higher in large companies, whileGonzlez et al. (2008)note that the requirements

http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


5/13

from companies for their suppliers related to environmental issues increase with organization size, and Gonzlez-Benito and

Gonzlez-Benito (2006)highlight the role of firm size in greater environmental maturity.

Concerning the adoption of GSCM practices, size also appears relevant. Here,Zhu and Sarkis (2004) found that large firms

are more likely to have robust GSCM practices than small businesses. Indeed,Zhu et al. (2008)emphasize that medium and

large firms are more advanced than most small companies with regards to GSCM practices and, in particular, with regards to

external GSCM practices. Moreover, Zhu et al. (2007a) note that firm size has a positive impact on a companys green

performance (GP) in the context of GSCM. Therefore, in our study, we consider firm size as a control variable of GP.

3. Research method

3.1. Methodological approach

Our study follows deductive logic, and is developed by means of gathering quantitative data via a survey instrument. A

survey is a research strategy in which experts in a particular subject are asked about their perception of relevant organiza-

tional aspects (Rungtusanatham et al., 2003). Surveys are found to allow for a connection between academia and reality

because they facilitate the testing of conceptual models using organizational data (Flynn et al., 1990).

3.2. Conceptual model and measurements

3.2.1. Conceptual model

Based on our literature review and the direct hypotheses we detailed above H1, H2A, H2B, H3A, a n d H3B, and our hypothesesregarding indirect and mediated relationships in H4A, H4B, and H5AH5B, (as state in Section2),Fig. 1outlines the conceptual

model that we empirically test in this study.

In our model, QM is an important green antecedent (Simon et al., 2013) in firms EMM (Zhu et al., 2013a), that in turn

influences: the adoption of the external practices of GSCM (green purchasing; cooperation with customers); company GP

(Yang et al., 2013), which is controlled by the size of the firm as suggested by Zhu and Sarkis (2004).

Furthermore, it is expected that EMM has a mediating effect on the relationship between QM practices and external

GSCM, and likewise, external GSCM practices are expected to present a mediating effect on the relationship between

EMM and the green performance (GP) of firms. We now detail how each latent variable in the conceptual model was

measured as follows.

3.2.2. The measurement of quality management (QM)

Several studies have tested the effect of QM practices on business performance (e.g., Kaynak, 2003). In our study, QM is

measured using three items: ISO 9001; the certification of suppliers based on quality criteria; and TQM. Each of thesepractices was measured using a 5-point Likert scale with a range of between 1 (minimum degree of implementation) and

5 (maximum degree of implementation).

3.2.3. Measuring the environmental management maturity (EMM)

Regarding the maturity level of the environmental management (EMM) construct, procedures similar to those adopted by

Murillo-Luna et al. (2011)where used, i.e. the relationship between the maturity level of environmental management and

Quality

management

Environmental

management

Level

Green

Purchasing

(External Green

Supply Chain

Managementpractice)

Green

Performance

Firm Size

Collaboration

with Costumers

(External

Green Supply

Chain

Management

practice)

H1

H2A

H2B

H3A

H3B

H4A

H4B

H5A

H5B

Direct effect

Indirect effect

Fig. 1. Conceptual model used in the research, with direct and indirect relationships.

http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


6/13

barriers to environmental adjustment. Thus, the maturity levels of environmental management considered in this study

were: (1) reactive; (2) preventive; and (3) pro-active. The levels that comprise the maturity level of environmental manage-

ment were entered in the questionnaire as per the definition presented for each stage in Section 2.2 above. Questionnaire

respondents were able to choose only one of the three levels to position their company in the environmental management

scale, meaning a 3-point scale was used to convert the maturity levels of environmental management in this study.

3.2.4. The Measurement of external GSCM practices collaboration with customers (CC_GSCM) and green purchasing (GP_GSCM)

In this study, we consider two types of external GSCM practices based onZhu et al. (2007a). The first relates to the prac-tice of green purchasing (GP_GSCM), measured by the following items: cooperation with the suppliers to achieve the goals of

environmental management; the delivery of environmental guidelines to suppliers for each product to be purchased; the

selection of suppliers based on ISO 14001; the evaluation of environmental management of the second-tier suppliers; and

environmental audits of supplier firms.

Cooperation with customers (CC_GSCM) was also measured according to the following items of Zhu et al. (2007a),

namely: cooperation with customers for cleaner production; cooperation with the customers to develop ecologically sound

packaging; and cooperation with the customers for eco-design. Each of these practices was measured using a 5-point Likert

scale ranging between 1 (minimum degree of implementation) and 5 (maximum degree of implementation).

3.2.5. Measurement of green performance (GP)

Green performance was measured according to the work ofZhu et al. (2008), and based on their four items: the emission

of pollution/waste; compliance with environmental legislation; company environmental reputation; and company overall

environmental performance. Each of these items was measured using a 5-point Likert scale ranging between 1 (maximumdeterioration) and 5 (maximum improvement).

3.2.6. Firm size as a control variable

The size of the firm was measured using four categories: micro, small, medium-sized or large companies. We used the

Brazilian classification of firm size, which is based on the number of company employees (Sebrae, 2013), as detailed earlier.

3.3. Population, sample and data collection

Based on the work ofSynodinos (2003), an instrument was developed to collect data using an online questionnaire,

located in a virtual environment, which housed the items used to measure each of the key concepts in this research, which

are documented in Appendix A. The web link for our questionnaire was sent by email to the Environmental Managers of Bra-

zilian companies with ISO 14001 certification.

The contact information for these environmental managers was collected using the database on ISO 14001 environmental

certification hosted by Inmetro and using additional contacts possessed by the research team. Altogether, about 330 envi-

ronmental managers were contacted by e-mail. Additionally, after sending the original invitation requesting that the partic-

ipants complete the survey, the research team also sent three additional email reminders. Finally, the research team initiated

a more personalized approach by telephoning the target respondents. At the end of this process, which lasted between 2012

and 2013, we obtained 95 valid and correctly completed questionnaires, corresponding to a 28.78% rate of return. This rate of

return is superior to those usually obtained in studies of the survey type (Synodinos, 2003) and also higher than the rate of

return observed in recent studies in the area of environmental management (Murillo-Luna et al., 2011; Pereira-Moliner et al.,

2012). In absolute terms, the number of questionnaires obtained is adequate compared to other research in the environmen-

tal field (Wolf, 2013; Delmas, 2001).

To verify the adequacy of the sample obtained, that is, whether 95 questionnaires would be sufficient, the research team

utilized the software G*Power 3 (Faul et al., 2007), which, based on the search parameters to be performed, calculates the

minimum sample required so that the sample size does not affect the statistical significance of the tests. After processing

the data using G*Power 3, it was concluded that the minimum sample required for the validity of the research would be

about 90 questionnaires. Thus, our 95 fully completed questionnaires not only complies with, but also slightly improves

upon, the minimum required number of questionnaires detailed by G*Power 3.

3.4. Data analysis

The hypotheses of this conceptual model were tested based on empirical data by means of structural equation modeling

using partial least squares (PLS) with the support of the software Smart PLS 2.0 M3 (Ringle et al., 2005). Structural equation

modeling is a second-generation multivariate statistical analysis that has been gaining attention in the areas of both envi-

ronmental management (Murillo-Luna et al., 2011; Pereira-Moliner et al., 2012) and operations management (Peng and Lai,

2012). The test of our conceptual model involves obtaining a measurement model (outer model) and a structural model

(inner model).

We chose to adopt the perspective of reflective indicators, which is the dominant perspective in the field of operationsmanagement studies (Large and Thomsen, 2011). As such, nine hypotheses were tested in this study, including direct and

http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


7/13

mediated relationships. In our conceptual model, there are constructs/variables (QM, EMM, CC_GSCM, GP_GSCM, GP), each

consisting of measuring items (assertive). We applied the following cut-off values during the data analysis:

AVE higher than 0.5 (Hair et al., 2011; Latan and Ghozali, 2012).

Composite reliability higher than 0.7 (Hair et al., 2011; Latan and Ghozali, 2012).

Square root of AVE higher than correlation among construct (Latan and Ghozali, 2012).

Cronbachs alpha higher than 0.6 (Hair et al., 2011; Latan and Ghozali, 2012).

Communality higher than 0.6 (Latan and Ghozali, 2012).

Redundancy higher than zero (Latan and Ghozali, 2012).

R2 small = 0.02;R2 medium = 0.13;R2 large = 0.26 (Cohen, 1992).

The ttest values near 1.65, 1.96 and 2.58 will be considered with significance levels of 10%, 5% and 1%, respectively (Latan

and Ghozali, 2012; Hair et al., 2011).

GoF calculation was obtained multiplying the Square root of AVE by average ofR2 (where AVE = 0.5;R2 small = 0.02;R2

medium = 0.13; R2 large = 0.26), thus, GoF small, medium and large = 0.10, 0.25 and 0.36 (Latan and Ghozali, 2012;

Wetzels et al., 2009).

AVE, communality, and square root AVE were used to measure validity. Next, Cronbach alpha and composite reliability

were used to measure reliability. Redundancy and R-square were used to measure the explained variance (dependent/

endogenous constructs). The t-statistic was adopted for test hypotheses, and GoF was used as goodness of fit model

indicator.

4. Results

All items for the latent variables that were considered in the conceptual model of this research showed good levels of

statistical quality, and therefore no item had to be discarded in the analyses. With help from the SmartPLS 2.0 M3 software

(Ringle et al., 2005), the measures for the model were obtained. The main statistical indicators showed satisfactory values

that were above the minimum levels of reference. For all latent variables, the AVE obtained values above 0.619; the compos-

ite reliability showed values above 0.836; the Cronbachs alpha obtained a minimum value of 0.768; the minimum common-

ality was 0.619; and the redundancy was also adequate (Table 1).

In addition to the indicators of statistical quality, the discriminant and convergent validity of the latent variables were

also checked. The discriminant validity was obtained by comparing the square roots of the average variance extracted

and the paths between the latent variables. The values for the square roots of average variance extracted on the diagonal

shown in bold demonstrate that they are acceptable (Table 2).The convergent validity was analyzed to verify whether the measuring items for the latent variables have, in fact, their

highest loads in their original concepts; in other words, do the items have higher loads for the concepts that they belong to.

This test showed adequate results (Table 3).

To ensure that these positive relationships are, in fact, statistically significant, we applied a bootstrapping technique

(2000 sub-samples). Here we find that all such values are positive, and statistically significant, as shown in Fig. 2.

R-squares for all dependent variables went from small to large. The tested models have predictive relevance because

theQ2 result is larger than 0. There is no collinearity problem among predictor variables with VIF values for all


8/13

Table 2

Discriminant validity.

Latent Variables CC_GSCM EMM GP_GSCM GP QM

CC_GSCM 0.867871 0.0000 0.0000 0.0000 0.0000

EMM 0.2934 1.000 0.0000 0.0000 0.0000

GP_GSCM 0.5524 0.4043 0.786893 0.0000 0.0000

GP 0.3999 0.3200 0.4058 0.851645 0.0000

QM 0.1838 0.1490 0.2283 0.0318 0.796178

Note:Square roots of average variance extracted shown on diagonal (bold).

Table 3

Convergent validity (cross loadings).

Indicators CC_GSCM EMM GP_GSCM GP QM

CC_GSCM1 0.8808 0.3031 0.5929 0.4077 0.1354

CC_GSCM2 0.8574 0.2115 0.4328 0.3587 0.1952

CC_GSCM3 0.8652 0.2354 0.3671 0.2421 0.1526

EMM 0.2934 1.0000 0.4043 0.3200 0.1490

GP1 0.3758 0.2649 0.3416 0.8291 0.0138

GP2 0.2713 0.2104 0.3104 0.8172 0.0127

GP3 0.3929 0.3226 0.4034 0.8756 0.0411

GP4 0.2967 0.2755 0.3085 0.8827 0.0378

GP_GSCM1 0.3937 0.3228 0.8013 0.3659 0.2270

GP_GSCM2 0.5063 0.3726 0.8776 0.3471 0.1209

GP_GSCM3 0.5027 0.3455 0.8288 0.3142 0.2412

GP_GSCM4 0.4439 0.1916 0.7074 0.2606 0.1633

GP_GSCM5 0.3320 0.3235 0.7046 0.2941 0.1476

QM1 0.0668 0.0170 0.0169 0.0771 0.6813

QM2 0.2247 0.1563 0.2484 0.0312 0.9111

QM3 0.0619 0.0978 0.1375 0.1112 0.7794

Note: Bold applied to values higher than 0.6.

Quality

Management

Environmental

Management

Level

Green

Purchasing

(External GreenSupply Chain

Management

Practice)

Green

Performance

Firm Size

Collaboration

with Customers

(External

Green Supply

Chain

Management

Practice)

*

**

**

*

**

Fig. 2. Structural model direct influences. Note: forp 6 0.05; forp 6 0.01.

Table 4

Inner model/structural model result.

Latent variables R-square Effect size Q2 predictive relevance GoF absolute VIF

CC_GSCM 0.0861 0.072894 0.874 0.927106

EMM 0.0222 0.1634/0.0861 0.045 0.8366

Firm size 0.0679 0.9321

GP_GSCM 0.1634 0.06304 0.171 0.93696

GP 0.2592 0.262 0.323523

QM 0.0222 0.9778



9/13

GoF (Goodness of Fit Statistics), which measures the overall statistical fitness of the model tested, has an effect near to

large (0.3235) for our study, meaning our proposed and tested model can be considered valid.

5. Discussion

Based on the fact that GSCM is a important subject (Sheu and Talley, 2011; Yang et al., 2013; Govindan et al., 2014 ), our

study explores a new model to determine whether quality management (QM), environmental management maturity (EMM),

and the adoption of external GSCM practices influence the green performance (GP) of 95 Brazilian companies with ISO 14001

certification. All of the direct relationships proposed in our conceptual model of this research were validated statistically.

Thus the results we obtained are supported by the literature and highlight that QM appears to be an important antecedentfor the EMM in firms (Zhu et al., 2013a;Llanch et al., 2013;Pereira-Moliner et al., 2012). The EMM in firms also seems

Table 5

Path coefficients.

Relationship Sample mean (M) Standard error (STERR) Tstatistics (|O/STERR|) Sig. direct effect Sig. indirect effect

CC_GSCM? GP 0.2776 0.1051 2.6503 Yes

EMM? CC_GSCM 0.2959 0.0972 3.0175 Yes

EMM?GP_GSCM 0.4102 0.0824 4.9059 Yes

GP_GSCM?GP 0.2743 0.1157 2.2709 Yes

QM? EMM 0.2072 0.0757 1.989 Yes

EMM?GP_GSCM? GP 38.70153 YesEMM? CC_GSCM? GP 45.71777 Yes

QM? EMM? GP_GSCM 53.50966 Yes

QM? EMM? CC_GSCM 57.75888 Yes

Quality

Management

Environmental

Management

Level

Green

Purchasing

(External Green

Supply Chain

Management

Practice)

GreenPerformance

Collaboration

with Customers

(External

Green Supply

Chain

Management

Practice)

**

**

**

**

Fig. 3. Structural model indirect/mediating effects. Note: forp 6 0:05; forp 6 0:01.

Table 6Overview of the hypotheses test.

Hypotheses Result

H1 QM influences the environmental management maturity of firms Accept

H2a The environmental management maturity influences the adoption of external GSCM practices such as cooperation with customers. Accept

H2b The environmental management maturity influences the adoption of external GSCM practices such as green purchasing. Accept

H3a The adoption of external GSCM practices such as cooperation with customers influences the environmental performance of firms Accept

H3b The adoption of external GSCM practices such as green purchasing influences the environmental performance of firms Accept

H4a EMM mediates the relationship between QM and the adoption of external GSCM such as cooperation with customers. Accept

H4b EMM mediates the relationship between QM and the adoption of external GSCM practices such as green purchasing Accept

H5a External GSCM practices such as cooperation with customers mediate the relationship between EMM and the environmental

performance of firms

Accept

H5a External GSCM practices such as green purchases mediate the relationship between EMM and the environmental performance of

firms

Accept

http://-/?-http://-/?-


10/13

relevant in the adoption of external GSCM practices, especially for green purchasing ( De Giovanni and Vinzi, 2012; Green

et al., 2012). In turn, GSCM practices may also influence the green performance of firms (Zhu and Sarkis, 2004; Zhu et al.,

2007b, 2013b), which is also controlled by the size of the firm (Gonzlez-Benito and Gonzlez-Benito, 2006; Murillo-Luna

et al., 2011).

To our knowledge, a conceptual model of this nature has not been tested before considering the workings of Brazilian

companies with ISO 14001-certification. Furthermore, it was found that QM influences GSCM practices when mediated by

EMM, and additionally, the level of EMM indirectly influences green performance when mediated by the adoption of GSCM

practices.

In general, our model showed an acceptable level of statistical adjustment (GoF), demonstrating that the conceptually

formulated interrelationships are also relevant to organizational context. Our results extend the existing literature ( Sheu

and Talley, 2011) using 9 hypotheses to test the relationships in it via a single model and in a developing country context,

Brazil, using a sample of ISO 14001-certified companies. These results reveal that environmental certification and firm size

can provide a favorable context for positive green scenarios in organizations.

This paper contributes to the relevant literature as it highlights that an improvement in Green Performance may require

attention to quality management, evolution of environmental management, and green supply chain management too. In the

context of GSCM, our study reveals that green purchasing perhaps deserves more attention than cooperation with customers,

findings which may also be useful to managers pursuing sustainability initiatives.

6. Conclusions

The objective of our study was to determine whether quality management (QM), environmental management maturity

(EMM), and the adoption of external GSCM practices influence the green performance (GP) of identified Brazilian companies

with ISO 14001 certification. Our testing of these relationships present an extension of the literature on this subject in that,

to date, they have not been tested simultaneously using, testing and confirming a conceptual model which uses both direct

and mediated relationships in the Brazilian context.

Our primary results determine that our hypotheses were valid. Thus, QM is an important antecedent for a firms EMM,

which in turn influences the adoption of external GSCM practices that influence green performance, the latter being also con-

trolled by the size of firms. Moreover, it was found that indirectly, the level of EMM mediates the relationship between QM

and the adoption of GSCM practices. In turn, GSCM practices mediate the relationship between the level of EMM and the

green performance of firms. These results not only confirm several arguments made by the literature in this field but also

present empirical evidence from Brazilian companies and draw attention to the importance of the mediating effects in

the research on organizational sustainability. Thus, the contributions of the paper to the literature are: (a) QM has been

an important antecedent for the EMM in firms (Zhu et al., 2013a;Llanch et al., 2013;Pereira-Moliner et al., 2012); (b) theEMM in firms is also relevant in the adoption of external GSCM practices, especially for green purchasing ( De Giovanni

and Vinzi, 2012; Green et al., 2012); (c) GSCM practices influence the green performance of firms (Zhu and Sarkis, 2004;

Zhu et al., 2007b, 2013b).

This study like any other has limitations. The first limitation relates to the sample size, which, although statistically

appropriate, does not represent all Brazilian business contexts. Additionally, there may be a bias in the results because all

of the included companies have ISO 14001 certification. Another limitation is that only one respondent per company com-

pleted the entire questionnaire. Finally, the study is limited because we analyzed the green performance of businesses, a lim-

itation which cannot fully meet the expectations of all practitioners, who may also be interested in other types of

organizational performance too, such as financial, marketing and operational performance. The assessment of the EMM var-

iable also need a future improvement. We recommended that future research replicate the model tested herein and extend it

by changing the type of organizational performance under analysis too.

6.1. Implications for practitioners

For practitioners e.g. business leaders interested in improving the green performance of firms, our study raises some

implications that they might wish to consider. First, it may be important to begin the search for better green performance

by investing in QM and by improving the level of EMM. Only after these phases have been consolidated should there be

investment in external GSCM practices. Special attention should be given to the GSCM practices that involve collaboration

with customers, which has been shown to be less sensitive to EMM. Finally, leaders of smaller companies should be prepared

to face more challenges than larger companies.

For industrial development policymakers, it is suggested that technical/conceptual support should be provided so that

companies can adopt QM as a first step towards organizational sustainability. However, this support should also continue

for companies so that they can advance with the step-by-step implementation of other environmental management prac-

tices and then GSCM to finally improve their green performance. The public sector should pay special attention to smaller

companies, given that the firm size variable tends to control green performance; meaning smaller companies may needspecific training and differentiated environmental investments.

http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


11/13

Appendix A. Sample - Concepts, measures and codes research questionnaire

Concept Assertive Items

Quality management (QM) ISO 9001 QM1

Certification of suppliers based on quality criteria QM2

Total quality management QM3

Environmental management maturity (EMM) Environmental management maturity level EMM1

Green supply chain management green

purchasing (GP_GSCM)

Selection of suppliers with ISO 14001 certification GP_GSCM1

Collaboration with suppliers to achieve the goals of

environmental management

GP_GSCM2

Delivery of environmental guidelines for each

purchased product to providers

GP_GSCM3

Assessment of the environmental management of

second-tier suppliers

GP_GSCM4

Performance of environmental audits of suppliers GP_GSCM5

Green supply chain management customers

collaboration (CC_GSCM)

Collaboration with customers for cleaner production CC_GSCM1

Collaboration with customers for the development of

ecological packaging

CC_GSCM2

Collaboration with customers for ecodesign CC_GSCM3

Green performance (GP) Pollution emission/waste GP1

Environmental management compliance GP2

Environmental reputation of the company GP3

Environmental performance of the company GP4

References

Ahi, P., Searcy, C., 2013. A comparative literature analysis of definitions for green and sustainable supply chain management. J. Cleaner Prod. 52 (August),329341.

Aragn-Correa, J.A., Rubio-Lpez, E.A., 2007. Proactive corporate environmental strategies: myths and misunderstandings. LongRange Plan. 40 (3), 357381.

Azevedo, S.G., Carvalho, H., Cruz Machado, V., 2011. The influence of green practices on supply chain performance: a case study approach. Transp. Res. PartE: Logist. Transp. Rev. 47 (6), 850871.

Bansal, P., Roth, K., 2000. Why companies go green. A model of ecological responsiveness. Acad. Manage. J. 43 (4), 717736 .Cohen, J., 1992. A power primer. Psychol. Bull. 122 (1), 155159.Darnall, N., Jolley, G.J., Handfield, R., 2008. Environmental management systems and green supply chain management: complements for sustainability?

Business Strategy Environ. 18 (1), 3045.De Giovanni, P., 2012. Do internal and external environmental management contribute to the triple bottomline? Int. J. Oper. Prod. Manage. 32 (3), 265290.De Giovanni, P., Vinzi, V.E., 2012. Covariance versus component-based estimations of performance in green supply chain management. Int. J. Prod. Econ. 135

(2), 907916.Delmas, M., 2001. Stakeholders and competitive advantage: the case of ISO 14001. Prod. Oper. Manage. 10 (3), 343358.Diabat, A., Govindan, K., 2011. An analysis of the drivers affecting the implementation of green supply chain management. Resour. Conserv. Recycl. 55 (6),

659667.Faul, F., Erdfelder, E., Lang, A.-G., Buchner, A., 2007. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical

sciences. Behav. Res. Methods 39, 175191.Flynn, B.B., Sakakibara, S., Schroeder, R.G., Bates, K.A., Flynn, E.J., 1990. Empirical research methods in operations management. J. Oper. Manage. 9 (2), 250

284.Gonzlez, P., Sarkis, J., Adenso-Daz, 2008. Environmental management system certification and its influence on corporate practices: evidence from the

automotive industry. Int. J. Oper. Prod. Manage. 28 (11), 10211041.Gonzlez-Benito, J., Gonzlez-Benito, O., 2006. A review of determinant factors of environmental proactivity. Business Strategy Environ. 15 (2), 87102 .Govindan, K., Sarkis, J., Jabbour, C.J.C., Zhu, Q., Geng, Y., 2014. Eco-efficiency based green supply chain management: current status and opportunities. Eur. J.

Oper. Res. 233 (2), 293298.Green Jr, K.W., Zelbst, P.J., Meacham, J., Bhadauria, V.S., 2012. Green supply chain management practices: impact on performance. Supply Chain Manage.:

Int. J. 17 (3), 290305.Gunasekaran, A., Ngai, E.W., 2012. The future of operations management: an outlook and analysis. Int. J. Prod. Econ. 135 (2), 687701 .Haden, S.S.P., Oyler, J.D., Humphreys, J.H., 2009. Historical, practical, and theoretical perspectives on green management: an exploratory analysis. Manag.

Decis. 47 (7), 10411055.Hair Jr., J.F., Ringle, C.M., Sarstedt, M., 2011. PLS-SEM: indeed a silver bullet. J. Market. Theory Pract. 19 (2), 139151.Hervani, A.A., Helms, M.M., Sarkis, J., 2005. Performance measurement for green supply chain management. Benchmarking: Int. J. 12 (4), 330353 .Holt, D., Ghobadian, A., 2009. An empirical study of green supply chain management practices amongst UK manufacturers. J. Manuf. Technol. Manage. 20

(7), 933956.Jabbour, C.J.C., 2010. Non-linear pathways of corporate environmental management: a survey of ISO 14001 certified companies in Brazil. J. Cleaner Prod. 18

(12), 12221225.Jabbour, A.B.L., Jabbour, C.J.C., 2009. Are supplier selection criteria going green? Case studies of companies in Brazil. Ind. Manage. Data Syst. 109 (4), 477

495.

Jabbour, C.J.C., Jabbour, A.B.L.S., 2014. Latin America: research opportunities on management for sustainable development. Latin Am. J. Manage. Sustain.Dev. (in press).

http://refhub.elsevier.com/S1366-5545(14)00038-6/h0010http://refhub.elsevier.com/S1366-5545(14)00038-6/h0010http://refhub.elsevier.com/S1366-5545(14)00038-6/h0015http://refhub.elsevier.com/S1366-5545(14)00038-6/h0005http://refhub.elsevier.com/S1366-5545(14)00038-6/h0005http://refhub.elsevier.com/S1366-5545(14)00038-6/h0005http://refhub.elsevier.com/S1366-5545(14)00038-6/h0020http://refhub.elsevier.com/S1366-5545(14)00038-6/h0025http://refhub.elsevier.com/S1366-5545(14)00038-6/h0030http://refhub.elsevier.com/S1366-5545(14)00038-6/h0030http://refhub.elsevier.com/S1366-5545(14)00038-6/h0035http://refhub.elsevier.com/S1366-5545(14)00038-6/h0040http://refhub.elsevier.com/S1366-5545(14)00038-6/h0040http://refhub.elsevier.com/S1366-5545(14)00038-6/h0045http://refhub.elsevier.com/S1366-5545(14)00038-6/h0045http://refhub.elsevier.com/S1366-5545(14)00038-6/h0050http://refhub.elsevier.com/S1366-5545(14)00038-6/h0050http://refhub.elsevier.com/S1366-5545(14)00038-6/h0055http://refhub.elsevier.com/S1366-5545(14)00038-6/h0055http://refhub.elsevier.com/S1366-5545(14)00038-6/h0060http://refhub.elsevier.com/S1366-5545(14)00038-6/h0060http://refhub.elsevier.com/S1366-5545(14)00038-6/h0065http://refhub.elsevier.com/S1366-5545(14)00038-6/h0065http://refhub.elsevier.com/S1366-5545(14)00038-6/h0065http://refhub.elsevier.com/S1366-5545(14)00038-6/h0070http://refhub.elsevier.com/S1366-5545(14)00038-6/h0075http://refhub.elsevier.com/S1366-5545(14)00038-6/h0075http://refhub.elsevier.com/S1366-5545(14)00038-6/h0080http://refhub.elsevier.com/S1366-5545(14)00038-6/h0080http://refhub.elsevier.com/S1366-5545(14)00038-6/h0085http://refhub.elsevier.com/S1366-5545(14)00038-6/h0085http://refhub.elsevier.com/S1366-5545(14)00038-6/h0090http://refhub.elsevier.com/S1366-5545(14)00038-6/h0090http://refhub.elsevier.com/S1366-5545(14)00038-6/h0095http://refhub.elsevier.com/S1366-5545(14)00038-6/h0100http://refhub.elsevier.com/S1366-5545(14)00038-6/h0105http://refhub.elsevier.com/S1366-5545(14)00038-6/h0105http://refhub.elsevier.com/S1366-5545(14)00038-6/h0120http://refhub.elsevier.com/S1366-5545(14)00038-6/h0120http://refhub.elsevier.com/S1366-5545(14)00038-6/h0115http://refhub.elsevier.com/S1366-5545(14)00038-6/h0115http://refhub.elsevier.com/S1366-5545(14)00038-6/h0115http://refhub.elsevier.com/S1366-5545(14)00038-6/h0115http://refhub.elsevier.com/S1366-5545(14)00038-6/h0120http://refhub.elsevier.com/S1366-5545(14)00038-6/h0120http://refhub.elsevier.com/S1366-5545(14)00038-6/h0105http://refhub.elsevier.com/S1366-5545(14)00038-6/h0105http://refhub.elsevier.com/S1366-5545(14)00038-6/h0100http://refhub.elsevier.com/S1366-5545(14)00038-6/h0095http://refhub.elsevier.com/S1366-5545(14)00038-6/h0090http://refhub.elsevier.com/S1366-5545(14)00038-6/h0090http://refhub.elsevier.com/S1366-5545(14)00038-6/h0085http://refhub.elsevier.com/S1366-5545(14)00038-6/h0080http://refhub.elsevier.com/S1366-5545(14)00038-6/h0080http://refhub.elsevier.com/S1366-5545(14)00038-6/h0075http://refhub.elsevier.com/S1366-5545(14)00038-6/h0075http://refhub.elsevier.com/S1366-5545(14)00038-6/h0070http://refhub.elsevier.com/S1366-5545(14)00038-6/h0065http://refhub.elsevier.com/S1366-5545(14)00038-6/h0065http://refhub.elsevier.com/S1366-5545(14)00038-6/h0060http://refhub.elsevier.com/S1366-5545(14)00038-6/h0060http://refhub.elsevier.com/S1366-5545(14)00038-6/h0055http://refhub.elsevier.com/S1366-5545(14)00038-6/h0055http://refhub.elsevier.com/S1366-5545(14)00038-6/h0050http://refhub.elsevier.com/S1366-5545(14)00038-6/h0050http://refhub.elsevier.com/S1366-5545(14)00038-6/h0045http://refhub.elsevier.com/S1366-5545(14)00038-6/h0040http://refhub.elsevier.com/S1366-5545(14)00038-6/h0040http://refhub.elsevier.com/S1366-5545(14)00038-6/h0035http://refhub.elsevier.com/S1366-5545(14)00038-6/h0030http://refhub.elsevier.com/S1366-5545(14)00038-6/h0030http://refhub.elsevier.com/S1366-5545(14)00038-6/h0025http://refhub.elsevier.com/S1366-5545(14)00038-6/h0020http://refhub.elsevier.com/S1366-5545(14)00038-6/h0005http://refhub.elsevier.com/S1366-5545(14)00038-6/h0005http://refhub.elsevier.com/S1366-5545(14)00038-6/h0015http://refhub.elsevier.com/S1366-5545(14)00038-6/h0010http://refhub.elsevier.com/S1366-5545(14)00038-6/h0010http://-/?-


12/13

Jabbour, A.B.L.S., Jabbour, C.J.C., Arantes, A.F., Kannan, D., Govindan, K., 2014. Mixed methodology to analyze the relationship between maturity ofenvironmental management and the adoption of Green Supply Chain Management in Brazil. Resour., Conserv. Recycl. (in press).

Kaynak, H., 2003. The relationship between total quality management practices and their effects on firm performance. J. Oper. Manage. 21 (4), 405435 .Kiron, D., Kruschwitz, N., Haanaes, K., Velken, I.V.S., 2012. Sustainability nears a tipping point. MIT Sloan Manage. Rev. 53 (2), 6974 .Kolk, A., Mauser, A., 2002. The evolution of environmental management: from stage models to performance evaluation. Business Strategy Environ. 11 (1),

1431.Large, R.O., Thomsen, C.G., 2011. Drivers of green supply management performance: evidence from Germany. J. Purchasing Supply Manage. 17 (3), 176184.Latan, H., Ghozali, I., 2012. Partial Least Squares: Concepts, Techniques and Applications using SmartPLS 2.0 M3. Diponegoro University Press .Liu, X., Yang, J., Qu, S., Wang, L., 2012. Sustainable production: practices and determinant factors of green supply chain management of Chinese companies.

Business Strategy Environ. 21 (1), 116.

Llanch, J., Perramon, J., Alonso-Almeida, M.D.M., Bagur-Femenas, L., 2013. Joint impact of quality and environmental practices of firm performance in smallservice businesses: an empirical study of restaurants. J. Cleaner Prod. 44 (April), 96104.

Lo, C.K., Wiengarten, F., Humphreys, P., Yeung, A.C., Cheng, T.C.E., 2013. The impact of contextual factors on the efficacy of ISO 9000 adoption. J. Oper.Manage. 31 (5), 229235.

Lpez-Gamero, M.D., Molina-Azorn, J.F., Claver-Corts, E., 2010. The potential of environmental regulation to change managerial perception, environmentalmanagement, competitiveness and financial performance. J. Cleaner Prod. 18 (1011), 963974 .

Lubin, D.A., Esty, D.C., 2010. The sustainability imperative. Harvard Business Rev. 88 (5), 4250.Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D., Zacharia, Z.G., 2001. Defining supply chain management. J. Business Logist. 22 (2),

125.Murillo-Luna, J.L., Garcs-Ayerbe, C., Rivera-Torres, P., 2011. Barriers to the adoption of proactive environmental strategies. J. Cleaner Prod. 19 (13),

14171425.Narasimhan, R., Schoenherr, T., 2012. The effects of integrated supply management practices and environmental management practices on relative

competitive quality advantage. Int. J. Prod. Res. 40 (4), 11851201.Peng, D.X., Lai, F., 2012. Usingpartial least squares in operations management research: a practical guideline and summaryof past research. J. Oper.Manage.

30 (6), 467480.Pereira-Moliner, J., Claver-Corts, E., Molina-Azorn, J.F., Tar, J.J., 2012. Quality management, environmental management and firm performance: direct and

mediating effects in the hotel industry. J. Cleaner Prod. 37 (December), 8292.

Perotti, S., Zorzini, M., Cagno, E., Micheli, G.J.L., 2012. Green supply chain practices and company performance: the case of 3PLs in Italy. Int. J. Phys. Distrib.Logist. Manage. 42 (7), 640672.

Ribeiro, V.P.L., Guzmn, C.A., Monteiro, S.M.S., Guzmn, B., 2012. Determining factors of environmental management practices in Portuguese local entities.Manage. Environ. Qual.: Int. J. 23 (5), 486502.

Ringle, C.M., Wende, S., Will, A., 2005. Smart PLS 2.0 M3. University of Hamburg .Rungtusanatham, M.J., Choi, T.Y., Hollingworth, D.G., Wu, Z., Forza, C., 2003. Survey researchin operations management: historical analyses. J. Oper. Manage.

21 (4), 475488.Sarkis, J., Zhu, Q., Lai, K., 2011. An organizational theoretic review of green supply chain management literature. Int. J. Prod. Econ. 130 (1), 115 .Sebrae, 2013. Critrios de classificao de empresas: EI ME EPP. Disponvel em:

Acessado em e julho de 2013.Seuring, S., Gold, S., 2013. Sustainability management beyond corporate boundaries: from stakeholders to performance. J. Cleaner Prod. 56 (October),

16.Sheu, J.B., Talley, W.K., 2011. Green supply chain management: trends, challenges, and solutions. Transp. Res. Part E: Logist. Transp. Rev. 47 (6), 791792.Simon, A., Bernardo, M., Karapetrovic, S., Casadesus, M., 2013. Implementing integrated management systems in chemical firms. Total Qual. Manage.

Business Excellence 24 (34), 294309.Srivastava, S.K., 2007. Green supply-chain management: a state-of-the-art literature review. Int. J. Manage. Rev. 9 (1), 5380 .Sroufe, R., Curkovic, S., 2008. An examination of ISO 9000:2000 and supply chain quality assurance. J. Oper. Manage. 26 (4), 503520 .

Synodinos, N.E., 2003. The art of questionnaire construction: some important considerations for manufacturing studies. Integr. Manuf. Syst. 14 (3), 221237.

Tan, K.C., 2001. A framework of supply chain management literature. Eur. J. Purchasing Supply Manage. 7 (1), 3948.Teixeira, A.A., Jabbour, C.J.C., Jabbour, A.B.L.S., 2012. Relationship between green management and environmental training in companies located in Brazil: a

theoretical framework and case studies. Int. J. Prod. Econ. 140 (1), 318329.Testa, F., Iraldo, F., 2010. Shadows and light of GSCM (Green Supply Chain Management): determinants and effects of these practices based on multi-

national study. J. Cleaner Prod. 18 (1011), 953962.Tomomi, T., 2010. Environmental management strategy for small and medium-sized enterprises: whydo SMBs practice environmental management? Asian

Business Manage. 9 (June), 265280.Wetzels, M., Odekerken-Schroder, G., Van Oppen, C., 2009. Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical

illustration. MIS Q. 33 (1), 177195.Wiengarten, F., Pagell, M., 2012. The importance of quality management for the success of environmental management initiatives. Int. J. Prod. Econ. 140 (1),

407415.Wolf, J., 2013. Improving the sustainable development of firms: the role of employees. Business Strategy Environ. 22 (2), 92108.Yang, C.S., Lu, C.S., Haider, J.J., Marlow, P.B., 2013. The effect of green supply chain management on green performance and firm competitiveness in the

context of container shipping in Taiwan. Transp. Res. Part E: Logist. Transp. Rev. 55 (August), 5573.Yusuf, Y.Y., Gunasekaran, A., Musa, A., El-Berishy, N.M., Abubakar, T., Ambursa, H.M., 2013. The UK oil and gas supply chains: an empirical analysis of

adoption of sustainable measures and performance outcomes. Int. J. Prod. Econ. 146 (2), 501514 .Zailani, S., Jeyaraman, K., Vengadasan, G., Premkumar, R., 2012. Sustainable supply chain management (SSCM) in Malaysia: a survey. Int. J. Prod. Econ. 140

(1), 330340.Zhu, Q., Sarkis, J., 2004. Relationship between operational practices and performance among early adopters of green supply chain management practices in

Chinese manufacturing enterprises. J. Oper. Manage. 22 (3), 265289.Zhu, Q., Sarkis, J., 2006. An inter-sectoral comparison of green supply chain management in China: drivers and practices. J. Cleaner Prod. 14 (5), 472486 .Zhu, Q., Sarkis, J., Lai, K., 2007a. Green supply chain management: pressures, practices and performance within the Chinese automobile industry. J. Cleaner

Prod. 15 (1112), 10411052.Zhu, Q., Sarkis, J., Lai, K., 2007b. Initiatives and outcomes of green supply chain management implementation by Chinese manufactures. J. Environ. Manage.

85 (1), 179189.Zhu, Q., Sarkis, J., Lai, K., 2008.Confirmation of measurement model for green supply chainmanagement practices implementation. Int. J. Prod. Econ.111 (2),

261273.Zhu, Q., Sarkis, J., Lai, K., Geng, Y., 2008. The role of organizational size in the adoption of green supply chain management practices in China. Corp. Soc.

Responsib. Environ. Manag. 15 (6), 322337.Zhu, Q., Sarkis, J., Lai, K., 2012a. Examiningthe effects of green supply chain management practices and their mediations on performance improvements. Int.

J. Prod. Res. 50 (5), 13771394.Zhu, Q., Sarkis, J., Lai, K., 2012b. Green supply chain management innovation diffusion and its relationship to organizational improvement: an ecological

modernization perspective. J. Eng. Tech. Manage. 29 (1), 168185.

http://refhub.elsevier.com/S1366-5545(14)00038-6/h0130http://refhub.elsevier.com/S1366-5545(14)00038-6/h0130http://refhub.elsevier.com/S1366-5545(14)00038-6/h0135http://refhub.elsevier.com/S1366-5545(14)00038-6/h0140http://refhub.elsevier.com/S1366-5545(14)00038-6/h0140http://refhub.elsevier.com/S1366-5545(14)00038-6/h0140http://refhub.elsevier.com/S1366-5545(14)00038-6/h0145http://refhub.elsevier.com/S1366-5545(14)00038-6/h0150http://refhub.elsevier.com/S1366-5545(14)00038-6/h0150http://refhub.elsevier.com/S1366-5545(14)00038-6/h0155http://refhub.elsevier.com/S1366-5545(14)00038-6/h0155http://refhub.elsevier.com/S1366-5545(14)00038-6/h0160http://refhub.elsevier.com/S1366-5545(14)00038-6/h0160http://refhub.elsevier.com/S1366-5545(14)00038-6/h0160http://refhub.elsevier.com/S1366-5545(14)00038-6/h0165http://refhub.elsevier.com/S1366-5545(14)00038-6/h0165http://refhub.elsevier.com/S1366-5545(14)00038-6/h0170http://refhub.elsevier.com/S1366-5545(14)00038-6/h0170http://refhub.elsevier.com/S1366-5545(14)00038-6/h0175http://refhub.elsevier.com/S1366-5545(14)00038-6/h0180http://refhub.elsevier.com/S1366-5545(14)00038-6/h0180http://refhub.elsevier.com/S1366-5545(14)00038-6/h0185http://refhub.elsevier.com/S1366-5545(14)00038-6/h0185http://refhub.elsevier.com/S1366-5545(14)00038-6/h0190http://refhub.elsevier.com/S1366-5545(14)00038-6/h0190http://refhub.elsevier.com/S1366-5545(14)00038-6/h0190http://refhub.elsevier.com/S1366-5545(14)00038-6/h0195http://refhub.elsevier.com/S1366-5545(14)00038-6/h0195http://refhub.elsevier.com/S1366-5545(14)00038-6/h0200http://refhub.elsevier.com/S1366-5545(14)00038-6/h0200http://refhub.elsevier.com/S1366-5545(14)00038-6/h0205http://refhub.elsevier.com/S1366-5545(14)00038-6/h0205http://refhub.elsevier.com/S1366-5545(14)00038-6/h0210http://refhub.elsevier.com/S1366-5545(14)00038-6/h0210http://refhub.elsevier.com/S1366-5545(14)00038-6/h0215http://refhub.elsevier.com/S1366-5545(14)00038-6/h0215http://refhub.elsevier.com/S1366-5545(14)00038-6/h0220http://refhub.elsevier.com/S1366-5545(14)00038-6/h0220http://refhub.elsevier.com/S1366-5545(14)00038-6/h0225http://refhub.elsevier.com/S1366-5545(14)00038-6/h0225http://www.sebrae-sc.com.br/leis/default.asp?vcdtexto=4154http://refhub.elsevier.com/S1366-5545(14)00038-6/h0235http://refhub.elsevier.com/S1366-5545(14)00038-6/h0235http://refhub.elsevier.com/S1366-5545(14)00038-6/h0240http://refhub.elsevier.com/S1366-5545(14)00038-6/h0245http://refhub.elsevier.com/S1366-5545(14)00038-6/h0245http://refhub.elsevier.com/S1366-5545(14)00038-6/h0250http://refhub.elsevier.com/S1366-5545(14)00038-6/h0255http://refhub.elsevier.com/S1366-5545(14)00038-6/h0260http://refhub.elsevier.com/S1366-5545(14)00038-6/h0260http://refhub.elsevier.com/S1366-5545(14)00038-6/h0265http://refhub.elsevier.com/S1366-5545(14)00038-6/h0265http://refhub.elsevier.com/S1366-5545(14)00038-6/h0270http://refhub.elsevier.com/S1366-5545(14)00038-6/h0270http://refhub.elsevier.com/S1366-5545(14)00038-6/h0275http://refhub.elsevier.com/S1366-5545(14)00038-6/h0275http://refhub.elsevier.com/S1366-5545(14)00038-6/h0280http://refhub.elsevier.com/S1366-5545(14)00038-6/h0280http://refhub.elsevier.com/S1366-5545(14)00038-6/h0295http://refhub.elsevier.com/S1366-5545(14)00038-6/h0295http://refhub.elsevier.com/S1366-5545(14)00038-6/h0295http://refhub.elsevier.com/S1366-5545(14)00038-6/h0300http://refhub.elsevier.com/S1366-5545(14)00038-6/h0300http://refhub.elsevier.com/S1366-5545(14)00038-6/h0305http://refhub.elsevier.com/S1366-5545(14)00038-6/h0285http://refhub.elsevier.com/S1366-5545(14)00038-6/h0285http://refhub.elsevier.com/S1366-5545(14)00038-6/h0290http://refhub.elsevier.com/S1366-5545(14)00038-6/h0290http://refhub.elsevier.com/S1366-5545(14)00038-6/h0310http://refhub.elsevier.com/S1366-5545(14)00038-6/h0310http://refhub.elsevier.com/S1366-5545(14)00038-6/h0320http://refhub.elsevier.com/S1366-5545(14)00038-6/h0320http://refhub.elsevier.com/S1366-5545(14)00038-6/h0325http://refhub.elsevier.com/S1366-5545(14)00038-6/h0330http://refhub.elsevier.com/S1366-5545(14)00038-6/h0330http://refhub.elsevier.com/S1366-5545(14)00038-6/h0335http://refhub.elsevier.com/S1366-5545(14)00038-6/h0335http://refhub.elsevier.com/S1366-5545(14)00038-6/h0340http://refhub.elsevier.com/S1366-5545(14)00038-6/h0340http://refhub.elsevier.com/S1366-5545(14)00038-6/h0355http://refhub.elsevier.com/S1366-5545(14)00038-6/h0355http://refhub.elsevier.com/S1366-5545(14)00038-6/h0345http://refhub.elsevier.com/S1366-5545(14)00038-6/h0345http://refhub.elsevier.com/S1366-5545(14)00038-6/h0350http://refhub.elsevier.com/S1366-5545(14)00038-6/h0350http://refhub.elsevier.com/S1366-5545(14)00038-6/h0350http://refhub.elsevier.com/S1366-5545(14)00038-6/h0350http://refhub.elsevier.com/S1366-5545(14)00038-6/h0345http://refhub.elsevier.com/S1366-5545(14)00038-6/h0345http://refhub.elsevier.com/S1366-5545(14)00038-6/h0355http://refhub.elsevier.com/S1366-5545(14)00038-6/h0355http://refhub.elsevier.com/S1366-5545(14)00038-6/h0340http://refhub.elsevier.com/S1366-5545(14)00038-6/h0340http://refhub.elsevier.com/S1366-5545(14)00038-6/h0335http://refhub.elsevier.com/S1366-5545(14)00038-6/h0335http://refhub.elsevier.com/S1366-5545(14)00038-6/h0330http://refhub.elsevier.com/S1366-5545(14)00038-6/h0330http://refhub.elsevier.com/S1366-5545(14)00038-6/h0325http://refhub.elsevier.com/S1366-5545(14)00038-6/h0320http://refhub.elsevier.com/S1366-5545(14)00038-6/h0320http://refhub.elsevier.com/S1366-5545(14)00038-6/h0310http://refhub.elsevier.com/S1366-5545(14)00038-6/h0310http://refhub.elsevier.com/S1366-5545(14)00038-6/h0290http://refhub.elsevier.com/S1366-5545(14)00038-6/h0290http://refhub.elsevier.com/S1366-5545(14)00038-6/h0285http://refhub.elsevier.com/S1366-5545(14)00038-6/h0285http://refhub.elsevier.com/S1366-5545(14)00038-6/h0305http://refhub.elsevier.com/S1366-5545(14)00038-6/h0300http://refhub.elsevier.com/S1366-5545(14)00038-6/h0300http://refhub.elsevier.com/S1366-5545(14)00038-6/h0295http://refhub.elsevier.com/S1366-5545(14)00038-6/h0295http://refhub.elsevier.com/S1366-5545(14)00038-6/h0280http://refhub.elsevier.com/S1366-5545(14)00038-6/h0280http://refhub.elsevier.com/S1366-5545(14)00038-6/h0275http://refhub.elsevier.com/S1366-5545(14)00038-6/h0275http://refhub.elsevier.com/S1366-5545(14)00038-6/h0270http://refhub.elsevier.com/S1366-5545(14)00038-6/h0270http://refhub.elsevier.com/S1366-5545(14)00038-6/h0265http://refhub.elsevier.com/S1366-5545(14)00038-6/h0260http://refhub.elsevier.com/S1366-5545(14)00038-6/h0260http://refhub.elsevier.com/S1366-5545(14)00038-6/h0255http://refhub.elsevier.com/S1366-5545(14)00038-6/h0250http://refhub.elsevier.com/S1366-5545(14)00038-6/h0245http://refhub.elsevier.com/S1366-5545(14)00038-6/h0245http://refhub.elsevier.com/S1366-5545(14)00038-6/h0240http://refhub.elsevier.com/S1366-5545(14)00038-6/h0235http://refhub.elsevier.com/S1366-5545(14)00038-6/h0235http://www.sebrae-sc.com.br/leis/default.asp?vcdtexto=4154http://refhub.elsevier.com/S1366-5545(14)00038-6/h0225http://refhub.elsevier.com/S1366-5545(14)00038-6/h0220http://refhub.elsevier.com/S1366-5545(14)00038-6/h0220http://refhub.elsevier.com/S1366-5545(14)00038-6/h0215http://refhub.elsevier.com/S1366-5545(14)00038-6/h0210http://refhub.elsevier.com/S1366-5545(14)00038-6/h0210http://refhub.elsevier.com/S1366-5545(14)00038-6/h0205http://refhub.elsevier.com/S1366-5545(14)00038-6/h0205http://refhub.elsevier.com/S1366-5545(14)00038-6/h0200http://refhub.elsevier.com/S1366-5545(14)00038-6/h0200http://refhub.elsevier.com/S1366-5545(14)00038-6/h0195http://refhub.elsevier.com/S1366-5545(14)00038-6/h0195http://refhub.elsevier.com/S1366-5545(14)00038-6/h0190http://refhub.elsevier.com/S1366-5545(14)00038-6/h0190http://refhub.elsevier.com/S1366-5545(14)00038-6/h0185http://refhub.elsevier.com/S1366-5545(14)00038-6/h0185http://refhub.elsevier.com/S1366-5545(14)00038-6/h0180http://refhub.elsevier.com/S1366-5545(14)00038-6/h0180http://refhub.elsevier.com/S1366-5545(14)00038-6/h0175http://refhub.elsevier.com/S1366-5545(14)00038-6/h0170http://refhub.elsevier.com/S1366-5545(14)00038-6/h0170http://refhub.elsevier.com/S1366-5545(14)00038-6/h0165http://refhub.elsevier.com/S1366-5545(14)00038-6/h0165http://refhub.elsevier.com/S1366-5545(14)00038-6/h0160http://refhub.elsevier.com/S1366-5545(14)00038-6/h0160http://refhub.elsevier.com/S1366-5545(14)00038-6/h0155http://refhub.elsevier.com/S1366-5545(14)00038-6/h0155http://refhub.elsevier.com/S1366-5545(14)00038-6/h0150http://refhub.elsevier.com/S1366-5545(14)00038-6/h0145http://refhub.elsevier.com/S1366-5545(14)00038-6/h0140http://refhub.elsevier.com/S1366-5545(14)00038-6/h0140http://refhub.elsevier.com/S1366-5545(14)00038-6/h0135http://refhub.elsevier.com/S1366-5545(14)00038-6/h0130


13/13

Zhu, Q., Cordeiro, J., Sarkis, J., 2013a. Institutional pressures, dynamic capabilities and environmental management systems: investigating ISO 9000 environmental management system implementation linkage. J. Environ. Manage. 114 (January), 232242 .

Zhu, Q., Sarkis, L., Lai, K., 2013b. Institutional-based antecedents and performance outcomes of internal and external green supply chain managementpractices. J. Purchasing Supply Manage. 19 (2), 106117.

http://refhub.elsevier.com/S1366-5545(14)00038-6/h0315http://refhub.elsevier.com/S1366-5545(14)00038-6/h0315http://refhub.elsevier.com/S1366-5545(14)00038-6/h0360http://refhub.elsevier.com/S1366-5545(14)00038-6/h0360http://refhub.elsevier.com/S1366-5545(14)00038-6/h0360http://refhub.elsevier.com/S1366-5545(14)00038-6/h0360http://refhub.elsevier.com/S1366-5545(14)00038-6/h0315http://refhub.elsevier.com/S1366-5545(14)00038-6/h0315

quality management and environmental management_direct and indirect effects

Documents