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The impact of green supply chain management practices on firm performance:

the role of collaborative capability

Article  in  Operations Management Research · June 2015

DOI: 10.1007/s12063-015-0100-x

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The Impact of Green Supply Chain Management Practices on Firm
Performance: The Role of Collaborative Capability

Donghyun Choi
School of Air Transport, Transportation, Logistics, and Air & Space Law
Korea Aerospace University, South Korea
Email: dchoi@kau.ac.kr
Telephone: 82-2-300-0374

Taewon Hwang*
Harley Langdale Jr. College of Business Administration
Valdosta State University, USA
Email: thwang@valdosta.edu
Telephone: 1-229-245-2238

* Corresponding author

To appear in Operations Management Research

1
Abstract

This study attempts to contribute to the growing research on green supply chain management

(GSCM) strategies by relying on the Natural Resource Based View (NRBV) and relational view.

Specifically, this study investigates the role of collaborative capability in moderating the effects of

GSCM practices on firm performance. Using hierarchical regression, this study analyzes data

from a survey of 230 South Korean manufacturers. The results show that the implementation of

GSCM practices can improve both environmental and financial performance of the firm. Also, the

findings indicate that firms can expect improved financial performance when they seek a

synergistic effect by involving their partners in the GSCM implementation process.

Key words: Green supply chain management; Collaborative capability; Natural resource based

view; Eco-design; Investment recovery; South Korea.

1 Introduction

Green supply chain management (GSCM) can be generally defined as the practice of improving

environmental performance along the supply chain, including product design, operations

management, and customer relationships (Srivastava 2007). A significant number of GSCM

studies have investigated whether the implementation of environmetal supply chain strategies

leads to enhanced firm performance (Sarkis 2012). However, the results of these studies were

mostly mixed, ranging from little or no improvement (Zhu et al. 2005). To explain these contrasting

results, several researchers have explored factors that influence this relationship (Lopez-Gamero

et al. 2009; Sarkis et al. 2010; Zhu and Sarkis 2007). Following this stream of thought, the present

2
study intends to examine another possible moderating effect – collaborative capability, which can

be defined as a firm's ability to leverage other actors’ resources and knowledge (Kotabe et al. 2003;

Koufteros et al. 2007; Patnayakuni et al. 2006). Collaboration relationships have helped firms to

reduce transaction costs and create a sustainable competitive position in highly uncertain business

environments (Cao and Zhang 2011).

Recently, a number of major firms have begun to capitalize on the potential of supply chain

collaboration in the implementation of green strategies. For instance, Coca-Cola has launched a

wide range of collaborative green practices such as the Community Water Partnership (Reuters

2011). Working jointly with bottling partners and environmental charities, it has developed

PlantBottle, the first recyclable plastic beverage bottle made partially from plants. Coca-Cola has

also formed a strategic partnership with H. J. Heinz Company, which uses PlantBottle for its

ketchup.

Despite the popularity of collaborative green strategies, there has been little systematic

research on the role of collaborative capability in the adoption of these strategies. The purpose of

this study is to investigate the relationship between GSCM practices and firm performance by

answering the following research questions: (1) Is GSCM implementation positively related to

firm performance? (2) Does the firm’s level of collaboration moderate the relationship between

GSCM practices and firm performance? To answer these research questions, this study conducts a

field survey of South Korean manufacturers. South Korea has been credited with adopting low

carbon and green growth as a national goal (Lee et al. 2012). Most importantly, the Korean

government has placed a greater emphasis on collaboration across the supply chain by encouraging

large manufacturers to share their environmental management know-how with supply chain

3
partners (Lee 2008; Lee and Klassen 2008). Thus, South Korea could provide a unique setting to

examine the role of collaboration between GSCM practices and firm performance.

This study is organized as follows. The second section introduces GSCM practices and

collaborative capability by focusing on the perspective of the natural resource based view (NRBV)

and relational view. The third section presents the conceptual framework of this study and

development of hypotheses. The fourth section provides the research methodology. The fifth

section presents the results and the sixth section discusses the findings of the study. The final

section concludes the study and also discusses the limitations of the study.

2 Theoretical backgrounds

2.1 The natural-resource based view (NRBV) and GSCM practices

The resource-based view (RBV) has been widely used to explain the impact of GSCM practices

on firm performance (Sharma and Vredenburg 1998). The resource-based view (RBV) suggests

that firms need to increase their strategic resources and leverage them to create sustainable

competitive advantage (Barney 2001). These resources can include both tangible and intangible

assets such as human, information technology, capital, equipment, and knowledge. RBV defines a

strategic asset as a resource that is rare, valuable, imperfectly imitable and non-substitutable. Firms

that establish distinctive competencies through unique combinations of strategic assets can achieve

advantage over competitors and earn above-normal rates of return (Acedo et al. 2006).

Recently, Hart (1995) has attempted to expand the scope of RBV by including the

constraints and opportunities given by the natural environment. Hart’s typology, referred to as the

natural resource-based view (NRBV), suggests that firms can gain competitive advantage from the

4
implementation of green strategies such as pollution prevention, product stewardship, and

sustainable development. Pollution prevention seeks to prevent waste and emissions at the source

instead of at the end-of-the-pipe. Product stewardship ensures that all those involved in the life

cycle of a product share responsibility for reducing its environmental impacts. Sustainable

development, which goes beyond simply reducing environmental damage, encompasses economic

and social concerns. A significant body of GSCM research has examined the competitiveness

effects of these strategies, pollution prevention in particular (Hart and Dowell 2011). For example,

Klassen and Whybark (1999) found that pollution prevention technologies, instead of pollution

control technologies, were associated with improved firm performance. The NRBV has been

further elaborated through the work of many researchers, showing the importance of

environmental practices as a strategic asset that contributes directly to better firm performance

(Shi et al. 2012).

2.2 The relation view and collaborative capability as a moderator

The RBV is considered to be essentially static in its nature. Adopting an inward-looking view, the

RBV assumes that firms should own or fully control strategic resources in order to create

sustainable competitive advantage. This assumption of ownership or control implies that firms

should establish barriers to protect their core resources from being imitated by competitors.

However, a growing number of studies have begun to question this proprietary assumption,

arguing that resources of supply chain partners have a considerable impact on firm performance

(Lee et al. 2001). They criticized the RBV for remaining trapped in an internal perspective (Priem

and Butler 2001). To address this theoretical challenge, some researchers have attempted to

5
reformulate the RBV by arguing that a firm’s competitiveness not only arises from internal

resources but also depends on inter-firm collaborations (Dyer 1996; Dyer and Singh 1998). This

line of thought, called the relational view, has been applied to the environmental sustainability

context (Christmann 2000). Vachon and Klassen (2008) found that collaborative environmental

activities with suppliers are related to process-based performance while collaborative green

practices with customers are linked with product-based performance. Zhu et al. (2008) showed

that knowledge created by collaboration plays a crucial role in eliminating environmentally

harmful materials or processes. Sharfman et al. (2009) found that inter-firm trust is one of the main

factors that affect the extent to which firms engage in cooperative GSCM. Albino et al. (2012)

simultaneously considered the effects of environmental collaborations with different types of

actors on environmental performance. They found that collaborations with a wide range of actors,

including suppliers, customers, governments and non-governmental organizations, can be

beneficial for a firm’s environmental performance.

These previous studies made significant contributions to understanding the importance of

collaborations in the context of GSCM. However, they did not differentiate between GSCM

practices and a firm’s collaborative capability. There is growing evidence that a firm's collaborative

capability should be conceptualized as a distinct factor (Hofmann et al. 2012). For instance, many

original equipment manufacturers (OEMs) have implemented asset recovery programs for their

end-of-life (EOL) products (Toffel 2004). According to the NRBV, such GSCM practices can be

considered a strategic resource that directly improves firm performance. However, when it comes

to the question of whether these OEMs work with their supply chain partners to obtain the

maximum benefits from asset recovery programs, it is another issue. In fact, after initiating asset

6
recovery programs, quite a few OEMs are still unwilling to collaborate with other actors such as

independent product recovery companies (Toffel 2004). Although these OEMs can reduce

potential losses of both market share and brand image, this practice is self-defeating over the long

run because it could be difficult for a single firm to possess all the resources required to implement

GSCM programs successfully (Wiens 2014). After all, GSCM programs involve a wide range of

activities, requiring expertise from almost all members of the entire supply chain (Nakano and

Hirao 2011). Based on this rationale, this study draws a distinction between a firm’s collaborative

capability and GSCM programs, suggesting that firms with high levels of collaborative capability

are likely to achieve better performance from the implementation of GSCM programs. In addition,

this study focuses on a firm's collaborations and partnerships with actors such as suppliers,

customers, governments, and non-governmental organizations because working with these actors

does not have a different impact on firm performance (Albino et al. 2012).

3 Hypotheses development

Figure 1 shows our conceptual model. Building on the NRBV, we posit that GSCM practices are

positively associated with firm performance. We also posit that a firm’s collaborative capability

moderates the relationship between GSCM practices and firm performance. Previously, GSCM

practices largely operated under a firm-centered paradigm, focusing on environmental activities

within the boundaries of a firm (Bansal and Roth 2000; Handfield et al. 2005). Although internally

focused GSCM practices contribute to improving firm performance, achieving full value from

GSCM programs requires a significant commitment to developing strong collaborations with

various actors (Albino et al. 2014). Following this line of thought, we focus on two GSCM

7
practices that are most likely to be influenced by a firm’s collaborative capability: eco-design and

investment recovery (Zhu and Sarkis 2004, 2007; Zhu et al. 2008). The purpose of eco-design is

to reduce the negative environmental impacts of a product over its full life cycle (Aoe 2007). The

objective of investment recovery is to recover the highest value from obsolete, EOL, and surplus

items (Ayres et al. 1997).

We exclude internally oriented GSCM practices such as commitment of GSCM from senior

managers, total quality environmental management, and ISO 14001 certification because they are

likely to receive limited benefits from collaborations. In addition, as mentioned earlier, we intend

to distinguish a firm’s collaborative capability from GSCM practices. Thus, some external GSCM

practices such as cooperation with external partners for environmental objectives are excluded for

this study.

We use two important indicators of firm performance. The first is environmental

performance, defined as the ecological results of a firm-wide commitment to preserve and improve

the natural environment (Nawrocka and Parker 2009). With the growing number of firms that are

committed to creating social and environmental value, the measurement and evaluation of

environmental performance are becoming more important than ever before (Kainuma and Tawara

2006; Testa and Irald 2010). The second is financial performance, which is one of the most

common drivers for the implementation of GSCM practices. A number of studies showed that

firms that perform better environmentally are also the most successful financially (Berry and

Rondinelli 1998; Tsoulfas and Pappis 2008).

< Figure 1>

8
3.1 GSCM practices and firm performance

The concept of eco-design has been described under various terms such as green design, design

for environment, sustainable design, etc. (Luttropp and Lagerstedt 2006). As shown in Figure 2,

eco-design seeks to create a sustainable product by incorporating environmental considerations

throughout its life cycle, from raw material acquisition to final disposal (Aoe 2007). Some eco-

design strategies include:

- Using renewable and recyclable materials at the procurement stage

- Using less energy and water at the manufacturing stage

- Using less packaging at the distribution stage

- Reducing greenhouse gas emissions at the use stage

Eco-design seeks to systematically integrate environmental aspects into product design

while maintaining all functional and safety requirements for consumers. It also emphasizes the

importance of early product design decisions because approximately 80% of all product-related

environmental impacts can be identified during the design phrases of product development

(Karlsson and Luttropp 2006). Researchers have proposed a number of eco-design tools to enhance

the design of the product from an environmental perspective (Bovea and Pérez-Belis 2012). One

of the most popular tools is life cycle assessment (LCA), which evaluates all relevant resources

and emissions consumed at each stage of the product’s life cycle (Arena et al. 2013).

Eco-design has been widely recognized as a useful tool for improving environmental

9
performance, as evidenced by a number of empirical studies conducted in various fields such as

electronics (Aoe 2007) and disposable diapers (Mirabella et al. 2013). However, despite explicit

advantages from lower production costs, eco-design was often found to be related to poor financial

performance (King and Lenox 2001). Recently, with growing consumer awareness about the

environment, this conventional view has been challenged (Griskevicius et al. 2010). A number of

environmentally conscious consumers are willing to pay more for eco-design products (Akehurst

et al. 2012). Moreover, continuous eco-design innovations not only improve a firm’s image as a

green champion but also serve as the principal source of competition, leading to higher sales

growth (Chen 2008). For example, Toyota Motor Corporation has introduced an LCA system

called Eco-VAS (Eco-Vehicle Assessment System) to heighten the environmental performance of

its vehicles (Nakano et al. 2007). The Toyota Prius has earned a reputation as the first hybrid car,

achieving significant sales growth since its introduction in 1997. Therefore, it is reasonable to

expect that eco-design contributes to financial performance as well as environmental performance.

H1a: Eco-design is positively related to environmental performance.

H1b: Eco-design is positively related to financial performance.

< Figure 2>

While eco-design is concerned with sustainable product/process development, investment

recovery focuses on obsolete, EOL, and surplus asset recovery (Ayres et al. 1997). In addition,

investment recovery differs from eco-design in that the former seeks to achieve a higher form of

10
recycling/reuse by pursuing value-added recovery involving remanufacturing (Guide 2000). As

shown in Figure 2, investment recovery attempts to integrate obsolete, EOL, and surplus assets

back into reverse logistics processes so that these assets can be properly recovered or disposed of

(Chan et al. 2010). In this way, investment recovery can help firms to maximize cost savings and

value recovery. Investment recovery has been successfully applied to a wide range of industries

such as computers (White et al. 2003) and automobiles (Gerrard and Kandlikar 2007). Some

investment recovery strategies include:

- Consolidating product returns from multiple locations at the collection stage

- Recovering valuable components from used materials at the recycling stage

- Making refurbished products for sales at the remanufacturing stage

Investment recovery has received increased attention in recent years as a growing number

of environmental regulations impose greater responsibilities on OEMs for managing their EOL

products (e.g., the European Union’s Extended Producer Responsibility) (Spicer and Johnson

2004). Instead of simply banning EOL products from landfills or incinerators, these “product take-

back” regulations offer financial incentives to encourage manufacturers to develop effective asset

recovery strategies (Toffel 2004). Another significant driver towards investment recovery is the

increasing volume of product returns (Petersen and Kumar 2009). According to a recent survey

from the Reverse Logistics Association, the annual volume of products returned by consumers in

the U.S. is estimated at between $150 and $200 billion at cost. This trend is expected to continue

with more liberal return policies (Jayaraman and Luo 2007). Previously, product returns were

11
considered troublesome; product returns were usually shipped in bulk to minimize costs, often

resulting in significant delays in the recovery process (Guide et al. 2005). However, firms are now

recognizing the potential value of product returns; product returns have recoverable value and can

bring additional revenue into firm, if properly managed (Blackburn et al. 2004; Ilgin and Gupta

2010). For instances, Xerox has established an asset recovery program called the Xerox Green

World Alliance, which aims to improve the environmental performance of its EOL products

through a closed-loop supply chain (Xerox 2014). The program has helped Xerox to save millions

of dollars in raw material costs over the past 20 years. Therefore, it is reasonable to argue that

investment recovery contributes to financial performance as well as environment performance.

H2a: Investment recovery is positively related to environmental performance.

H2b: Investment recovery is positively related to financial performance.

3.2 Collaborative capability, GSCM practices and firm performance

As mentioned earlier, conventional eco-design approaches were internally oriented. As eco-design

includes a broad range of environmental activities among supply chain members, it has become

more difficult for a single firm to have all the information on a product and its production processes

(Nakano and Hirao 2011). To truly maximize the value of eco-design, a firm should leverage

potential synergistic effects of supply chain collaboration (Thabrew et al. 2009). This notion is

clearly supported by the International Electrotechnical Commission (IEC), which suggests that

eco-design requires collaborations and contributions of all supply chain participants (IEC 2010).

A number of studies also indicate that firms can expect more substantial environmental and

12
financial improvements when they take into account design factors outside of their immediate

control, including suppliers, customers, recyclers, etc. (González-Benito and González-Benito

2005). Previously, it was difficult to collect all the data required to analyze eco-design activities

from globally dispersed business partners (Nakano and Hirao 2011). With the recent rapid

advances in information and communication technologies, it is now possible for firms to easily

share their valuable experiences on eco-design. For instance, LCA software packages such as

SimaPro can help firms to quantify their eco-design activities and goals, enabling them to

accurately measure the potential environmental and financial consequences of their new product

(Vallet et al. 2013).

Indeed, collaboration is not optional anymore, but a basic requirement for eco-design. For

example, collaborative environmental assessment is one of the keys to L’Oréal’s eco-design

initiative (Fayolle et al. 2008). Specifically, L’Oréal works closely with its suppliers to evaluate

the environmental impact of raw materials throughout their life-cycle. This is an important part of

L’Oréal’s long-term environmental plan, which aims to source 100 percent renewable raw

materials from sustainable sources by the year 2020. Collaborations are also crucial to Levi Strauss

& Co.’s efforts to use less water in the life cycle of its new “Water<Less” jeans collection (Joule

2011). Because it was found that the majority of water use is for the cotton production process,

Levi’s joined the Better Cotton Initiative, a program that helps cotton suppliers to make cotton

more sustainable. Since the launch of the collection in 2011, Levi's has saved over 770 million

liters of water, selling over 13 million "Water<Less" pairs of jeans. These examples clearly show

that collaborative improvement activities are essential to reap the full benefits of eco-design. Based

on the above discussion, the following hypotheses are suggested.

13
H3a: Collaborative capability moderates the relationship between eco-design and environmental

performance.

H3b: Collaborative capability moderates the relationship between eco-design and financial

performance.

Previously, investment recovery tended to focus on how to handle surplus items within the

boundaries of a firm (e.g., idle equipment within a firm) (Sinding 2000). Managers viewed reverse

logistics as a series of fragmented non-value-added activities; this lack of supply chain visibility

led them to address each reverse logistics activity in isolation from a silo perspective (Guide et al.

2005). Consequently, the focus of most investment recovery strategies was to achieve maximum

local efficiencies and economies of scale.

However, as mentioned earlier, the responsibility to handle the EOL management

increasingly shifts back to the manufacturers. As a result, the traditional supply chain has been

expanded to include both forward and reverse logistics (Olorunniwo and Li 2010). Such a supply

chain framework, the combination of forward and reverse logistics, is called a closed-loop supply

chain (Savaskan et al. 2004). In this integrated environment, firms can benefit from collaborative

investment recovery strategies; for example, a manufacturer facing time-sensitive product returns

such as laptop computers can establish partnerships with its retailers to minimize the loss in

product value due to time delays; retailers evaluate product condition as early as possible at the

point of customer returns to identify product returns with high recoverable value (Blackburn et al.

2004).

14
 Many firms have attempted to maximize the value of investment recovery through

collaborative efforts of closed-loop supply chain members (Toffel 2004). For instance, Nissan

Motor Corporation in Japan works with a number of supply chain partners to improve the recovery

rate for its EOL vehicles (Nissan 2014). Nissan relies on its dealerships, which collect discarded

bumpers. Nissan pulverizes these discarded bumpers so that bumper materials can be used to make

new bumpers. In addition, Nissan has teamed with the Sumitomo Corporation to evaluate the reuse

of the Nissan LEAF battery for commercial purposes. Nissan recovered over 100 thousand tons of

automobile shredder residue collected from vehicles in Japan, earning a profit of over 800 million

Japanese yen (8 million US dollars). These examples clearly indicate that collaborative

improvement efforts are important to maximize the value of investment recovery. Based on the

above discussion, the following hypotheses are suggested.

H4a: Collaborative capability moderates the relationship between investment recovery and

environmental performance.

H4b: Collaborative capability moderates the relationship between investment recovery and

financial performance.

3.3 Control variables

Following the literature, this study included firm size as a control variable (Zhu and Sarkis 2004,

2007). Large firms are more likely to adopt GSCM practices because they have a greater amount

of resources and typically face higher environmental pressure than small or medium sized firms.

Industry type was also included as a control variable.

15
4. Research methodology

4.1 Sample

The data for this study were collected from South Korean manufacturers. Our empirical setting is

particularly appropriate for several reasons: First, South Korea has taken many green initiatives as

a national development strategy (Lee et al. 2012). For example, it has become the first Asian nation

to pass legislation introducing the nation-wide greenhouse gas emission trading scheme, which is

set to come into force in 2015 (Chae 2010). Recent studies have focused on South Korea to

understand a variety of GSCM related issues (Kim and Rhee 2012; Kim et al. 2011). Second, the

increasing global competition over the past decade has enabled South Korean firms to improve the

ability to react to global standards for green business (Kwon et al. 2002; Lee and Kim 2011). The

majority of South Korean firms rely on international trade for a large portion of their annual

revenue. According to OECD statistics in 2010, 45% of Korean GDP is from international trade.

To create opportunities for new markets in the global market, South Korea’s large firms such as

Samsung, Hyundai, and LG have sought to develop green strategies that effectively address global

environmental issues (Green Growth Korea 2010). Third, the Korean government’s Green

Partnership project is actively encouraging large manufacturers to contribute their green

philosophy to small and medium-sized suppliers (Lee 2008; Lee and Klassen 2008). This has led

manufacturers to shift the focus of their green strategies from single plant improvements to the

entire supply chain. For instance, Samsung SDI has started the Global Green Partnership project,

which aims to help its suppliers to enhance the ability to respond to environmental regulations

(Samsung SDI 2012). Samsung SDI has recently created a green management collaboration system

16
for its suppliers in China and plans to expand the systems to its suppliers in other countries such

as Vietnam and Malaysia. For all of the reasons above, South Korea provides a quite suitable

empirical setting for our research purposes.

4.2 Survey questionnaire and data collection

The survey questionnaire was developed to collect research data. The initial pool of items was

selected from existing scales, with wording changed to reflect the context of manufacturing

processes. The design process for the questionnaire consisted of two stages. In the first stage, an

extensive literature review on environmental practices was conducted to ensure the questionnaire’s

content validity. Five academic colleagues were asked to review the initial questionnaire for

ambiguity and appropriateness of the items. We modified the instrument based on their feedback.

In the second stage, the survey questionnaire was pilot-tested in a sample of ten supply chain

practitioners. They were also asked to evaluate whether the items reflect adequately the domain

of interest. Their feedback resulted in minor changes. The double translation protocol was used

for the questionnaire development because data were collected from South Korean firms (Brislin

1976). The authors of this study translated the final English version of the questionnaire into

Korean and then translated the Korean version back into English. Two bilingual researchers who

teach operation management in the US also examined the English versions and found no

significant differences. As shown in Table 1, the questionnaire included seven items for GSCM

practices (Zhu and Sarkis 2004, 2007; Zhu et al. 2008), eight items for firm performance (Zhu and

Sarkis 2004, 2007), and eight items for collaborative capability (Kotabe et al. 2003; Koufteros et

al. 2007; Patnayakuni et al. 2006). They were measured using a seven-point Likert scale with

17
anchors ranging from strongly disagree (1) to strongly agree (7) in order to ensure high statistical

variability among survey responses.

<Table 1>

The Web-based questionnaire was sent out to supply chain managers of 910 South Korean

manufacturing firms with ISO 14001, ISO 9001, or ROHS certification. The Web-based survey is

a more convenient method with substantially fewer missing responses than mail-based surveys

(Boyer et al. 2002). About two weeks later, we sent follow-up emails to remind managers who had

not responded to take part in the survey. The non-response bias was assessed to compare early

respondents who answered within the first two weeks, later respondents who answered after the

third week, and non-respondents (a sub-sample of 25 non-respondents were randomly selected

from the sample of 910) (Armstrong and Overton 1977). A simple paired t test was conducted for

three pairs (early-late; early-non respondent; late-non respondent). T test comparison showed no

significant difference (p<0.05) between the firm size, industry sector, eco-design, investment

recovery, two performance factors or levels of collaborative capability.

The survey yielded 230 useable responses (a response rate of 25.3%), achieving an

acceptable response rate for a supply chain management survey (Rosenzweig et al. 2003). The data

shows the firms’ annual sales ranged from 2.5 million to 325 million US dollars with a median of

184.1 million US dollars. Also, most respondents were from operations, purchasing, and supply

chain management team. Relatively few respondents were (10 out of 230) from other departments

such as marketing and R&D. Table 2 shows the sample characteristics in terms of industry type

18
and the number of employees. Descriptive data, including means, standard deviations, and samples

size are shown in Table 3.

<Table 2>

< Table 3>

4.3 Factor analysis

The influence of common methods variance might be problematic when data on the independent

and dependent variables are collected from the same respondents in the same survey. A principal

component factor analysis (with a direct oblimin rotation, delta = 0) was conducted through SPSS

18.0 to further confirm grouping GSCM practices, collaborative capability and firm performance.

The Kaiser criterion (eigenvalues > 1) was employed in conjunction with parallel analysis and

Cattell’s (1966) scree test. As expected, the results showed the presence of two, one, and two

components for GSCM practices, collaborative capability and firm performance, respectively. It

means that common methods bias is not a serious problem in the data. Tables 4 and 5 present the

pattern matrix for GSCM practices and firm performance, respectively. The two GSCM practice

components explained 84.16% of the total variance and two firm performance components

accounted for 82.07% of the total variance. As shown in Table 6, collaborative capability, extracted

as one component with no cross-loadings, explained 69.55% of total variance. For all the scales,

Cronbach's alpha exceeded the recommended level of 0.70 (Gefen et al. 2000).

< Table 4>

19
 < Table 5>

< Table 6>

Table 7 shows the means, standard deviations, and correlations of all the factors. Because

investment recovery is correlated at 0.61 with eco-design and at 0.60 with environment

performance, Fornell and Larcker’s (1981) test was conducted for discriminant validity. This test

requires that the average variance extracted (AVE) for each factor should be greater than the

squared correlation between the factor and other factors in the model. Table 7 shows the square

root of AVE on the diagonal axis. All diagonal elements are larger than their corresponding

correlation coefficients, indicating appropriate discriminant validity.

<Table 7>

5 Results

Hierarchical regression was used to test hypotheses. The analysis was conducted in four steps.

First, the control variable, firm size was entered into the regression. Then one GSCM practice

variable was entered into the regression. Third, the moderator variable, collaborative capability,

and the interaction term of one GSCM practice variable and collaborative capability was entered.

The data were mean-centered in order to mitigate the effects of multicollinearity in regression

models with interaction terms (Cronbach 1987).

Hypotheses 1a and 1b posit a direct, positive relationship between eco-design and two

performance factors. Table 8 indicates that both relationships were statistically significant,

20
supporting both Hypotheses 1a and 1b. Hypotheses 2a and 2b posit a direct, positive relationship

between investment recovery and two performance factors. Table 9 shows that investment

recovery had a direct, positive association with two performance factors, supporting Hypotheses

2a and 2b.

Hypotheses 3a and 3b suggest that collaborative capability moderates the relationship

between eco-design and two performance factors. Table 7 shows that the interaction terms between

eco-design and collaborative capability had significant positive coefficients for financial

performance, supporting Hypothesis 3b. Hypotheses 4a and 4b suggest that collaborative

capability moderates the relationship between investment recovery and two performance factors.

The same pattern was observed as shown in Table 9. The interaction terms between investment

recovery and collaborative capability had significant positive coefficients for financial

performance only, supporting Hypothesis 4b.

Figure 3 and Table 10 summarize the results of the hypotheses testing. Overall, the

implementation of GSCM practices was positively related to both firm performance factors.

Collaborative capability positively moderated the relationship between GSCM practices and

financial performance.

< Table 8>

< Table 9>

< Table 10>

< Figure 3>

21
6 Discussion

6.1 The impacts of GSCM practices on firm performance

We found that GSCM practices can be beneficial for a firm’s performance, thereby providing

support to the NRBV. Thus, it can be argued that the implementation of GSCM practices helps a

firm to develop unique environmental management capabilities that lead to higher performance.

This finding is consistent with the results of recent studies drawing on the NRBV (Lee and Klassen

2006; Shi et al. 2012). Previously, most firms have relied on the “win-win” argument to justify

investments in GSCM programs. This assumption has often been criticized on the ground that such

investments will raise the cost burden and in turn influence financial performance negatively. For

example, Green et al. (2102) have shown that both eco-design and investment recovery are

positively linked to environmental performance but not financial performance.

However, we found that GSCM strategies can be integrated into business with improved

environmental and financial performance. The discrepancy between these two studies could be

due to differences in the samples. Green et al. (2012) used a diverse group of US manufacturers

while this study employed a focused group of South Korean manufacturers. In fact, the results of

this study are consistent with those of Zhu and Sarkis (2004), who used a homogeneous group of

Chinese manufacturers.

Another explanation for improved financial performance is the Korean government’s

supply chain environmental management (SCEM) program, which includes special funds and tax-

cut incentives for firms that actively implement environmental initiatives (Lee 2008). With such

assistance programs, it is possible that South Korean manufacturers reduce costs related to the

implementation of GSCM programs, leading to significant financial improvement.

22
6.2 The moderating effects of collaborative capability on firm performance

We found that firms with high levels of collaborative capability tend to gain better financial

performance from the implementation of GSCM programs. Figures 4a and 4b show that the

stronger collaborative capability, the greater the positive relationship between GSCM practices

and financial performance. In other words, firms that implement GSCM programs with close

collaboration with their supply chain partners are more likely to experience high financial

performance than those who do not have such strong relationships. Recent studies that focused on

South Korean firms also reported similar results (Kim et al. 2011; Kim and Rhee 2012; Lee and

Kim 2011).

<Figure 4>

However, the results of this study indicate that there is no significant moderating effect of

collaboration for environmental performance. The results have an important implication for our

understanding of how firms use their resources for supply chain collaboration. In South Korea, it

is possible that some manufacturers implement environmental programs reactively because they

are required to meet the government’s environmental requirements. Those manufacturers that are

less environmentally motivated are likely to put more resources into collaborative activities for

financial improvement rather than environmental improvement. Presumably, after simply meeting

the minimum requirements set by the government, less environmentally motivated manufacturers

may focus on maintaining the status quo without further attempting to improve environmental

23
performance.

Another explanation for this insignificant moderating effect may be simply that our sample

firms did not collaborate on environmental activities. In this study, the scale of collaborative

capability did not differentiate the context of collaboration. Therefore, it could be possible that

these firms collaborated more on traditional issues such as quality improvements and cost savings

rather than on environmental issues.

6.3 Contributions of this study

Overall, this study contributes to the growing research on GSCM strategies by highlighting the

role of another important complementary asset – collaborative capability. As discussed earlier,

previous studies that examined the effects of GSCM practices underscored the necessity to identify

possible moderators. Researchers should continue to explore potential moderators to better explain

the effects of GSCM practices on firm performance.

Another contribution of this study is to add to a growing body of GSCM research conducted

in a variety of countries. GSCM studies have traditionally tended to focus on developed countries

such as Germany (Thun and Müller 2010), the UK (Holt and Ghobadian 2009), the US (Green et

al. 2010), etc. As more and more firms are moving a significant portion of their manufacturing

operations to Asia, recent GSCM research efforts have shifted toward countries such as China (Zhu

et al. 2008), India (Mitra and Datta 2014), Malaysia (Eltayeb et al. 2011), Taiwan (Shang et al.

2010), Thailand (Setthasakko 2009), etc. These studies showed that those countries have

developed unique green initiatives, suggesting that country-specific characteristics in this region

deserve more research attention in the study of GSCM (Rao and Holt 2005). The results of this

24
study also indicate that future GSCM studies should continue to place a greater emphasis on

country-specific aspects.

7 Conclusion

As an important new strategy, GSCM allows firms to achieve financial and market share goals by

lowering their environmental costs while ensuring environment friendly operations. Recently, the

importance of GSCM has received considerable attention. Implementing GSCM can benefit the

firm as it can be a revenue driver. However, most GSCM related studies have yet to investigate

which capability of the firm is needed for successful GSCM. This study proposed collaborative

capability as an important moderator for the relationship between GSCM implementation and firm

performance. The results of this study show that the positive relationship between GSCM practices

and financial performance is stronger when a firm actively collaborates with various partners. In

an increasingly competitive and dynamic global business environment, multinational

manufacturers can seek benefits from investing in GSCM through collaboration with suppliers that

implement operations that satisfy green standards. Firms that implement GSCM practices by

building close relationships with their partners can obtain higher financial outcome. The literature

on collaboration between inter-firm involvements also indicates that collaboration plays a critical

role when the complexity increases in the business environment. Through communication,

coordination, and conflict resolution processes with various partners, firms can obtain shared

interpretation of the information, which enables swift and decisive actions to solve environmental

problems.

25
 There are some limitations to this study. Since our data were collected from a single source,

the risk of common methods bias might be problematic. Also, financial performance is measured

by perception of respondents, not by real financial data. This perception has potential to exaggerate

the performance. The self-reported survey data used in this study might not fully reflect the actual

situation. However, the self-reported survey data are commonly used to measure performance and

we believe that our approach is sufficient to provide a snapshot of current practices of green

practices among South Korean manufacturers. Last but not least, some supply chain partners

might achieve some type of environmental certification, biasing our findings. These limitations

should be addressed in the future research, including a longitudinal analysis of GSCM practices

over time.

Acknowledgement

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning) Korea

under the C-ITRC (Convergence Information Technology Research Center) support program

(NIPA-2014-H0401-14-1021) supervised by the NIPA (National IT Industry Promotion Agency).

26
References

Acedo FJ, Barroso C, Galan JL (2006) The resource-based theory: dissemination and main trends.

Strategic Management Journal 27:621-636

Albino V, Dangelico RM, Pontrandolfo P (2012) Do inter-organizational collaborations enhance a

firm’s environmental performance? a study of the largest US companies. Journal of Cleaner

Production 37: 304-315

Akehurst G, Afonso C, Gonçalves H (2012) Re-examining green purchase behaviour and the green

consumer profile: new evidences. Management Decision 50: 972-988

Aoe T (2007) Eco-efficiency and eco-design in electrical and electronic products. Journal of

Cleaner Production 15: 1406-1414

Arena M, Azzone G, Conte A (2013) A streamlined LCA framework to support early decision

making in vehicle development. Journal of Cleaner Production 41: 105-113

Armstrong JS, Overton TS (1977) Estimating nonresponse bias in mail surveys. Journal of

Marketing Research 14: 396-402

Ayres R, Ferrer G, Van Leynseele T (1997) Eco-efficiency, asset recovery and remanufacturing.

European Management Journal 15: 557-574

Bansal P, Roth K (2000) Why companies go green: a model of ecological responsiveness.

Academy of Management Journal 43: 717-736

Barney JB (2001) Is the resource-based view a useful perspective for strategic management

research? Yes. Academy of Management Review 26:41-56

Berry MA, Rondinelli DA (1998) Proactive corporate environmental management: a new

industrial revolution. Academy of Management Executive 12:38-50

27
Blackburn J, Guide V, Souza G, Van Wassenhove L (2004) Reverse supply chains for commercial

returns. California Management Review 46:6-22

Boyer K, Olson J, Calantone R, Jackson E (2002) Print versus electronic surveys: a comparison of

two data collection methodologies. Journal of Operations Management 20:357-373

Bovea M, Pérez-Belis V (2012) A taxonomy of ecodesign tools for integrating environmental

requirements into the product design process. Journal of Cleaner Production 20: 61-71

Brislin RW (1976) Comparative research methodology: cross-cultural studies. International

Journal of Psychology 11:215-229

Cao M, Zhang Q (2011) Supply chain collaboration: impact on collaborative advantage and firm

performance. Journal of Operations Management 29:163-180

Cattell RB (1966) The scree test for the number of factors. Multivariate Behavioral Research

1:245-276

Chae Y (2010) Co-benefit analysis of an air quality management plan and greenhouse gas

reduction strategies in the Seoul metropolitan area. Environmental Science & Policy 13:205-216

Chan HK, Yin S, Chan FT (2010) Implementing just-in-time philosophy to reverse logistics

systems: a review. International Journal of Production Research 48: 6293-6313

Chen YS (2008) The driver of green innovation and green image – green core competence. Journal

of Business Ethics 81: 531-543

Christmann P (2000) Effects of “best practices” of environmental management on cost advantage:

the role of complementary assets. Academy of Management Journal 43:663-680

Cronbach L (1987) Statistical tests for moderator variables: flaws in analyses recently proposed.

Psychological Bulletin 102:414-417

28
Dyer JH (1996) Specialized supplier networks as a source of competitive advantage: evidence

from the auto industry. Strategic Management Journal 17:271-291

Dyer JH, Singh H (1998) The relational view: cooperative strategy and sources of

interorganizational competitive advantage. Academy of Management Review 23:660-679

Eltayeb TK, Zailani S, Ramayah T (2011) Green supply chain initiatives among certified

companies in Malaysia and environmental sustainability: investigating the outcomes. Resources,

Conservation and Recycling 55:495-506

Fayolle A, Basso O, Legrain T (2008) Corporate culture and values: genesis and sources of

L’Oreal's entrepreneurial orientation. Journal of Small Business and Entrepreneurship 21:215-230

Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables

and measurement error. Journal of Marketing Research 18: 39-50

Gefen D, Straub DW, Boudreau MC (2000) Structural equation modelling and regerssion:

guidelines for research practice. Communications of the AIS 4: 1-79

Gerrard J, Kandlikar M (2007) Is European end-of-life vehicle legislation living up to expectations?

assessing the impact of the ELV Directive on ‘green’ innovation and vehicle recovery. Journal of

Cleaner Production 15: 17-27

González-Benito J, González-Benito O (2005) Environmental proactivity and business

performance: an empirical analysis. OMEGA: The International Journal of Management Science

33: 1–15

Green KW, Zelbst PJ, Meacham J, Bhadauria MV (2012) Green supply chain management

practices: impact on performance. Supply Chain Management: An International Journal 17:290-

305

29
Green Growth Korea (2010) Korea's green growth footprint.

http://www.greengrowth.go.kr/?page_id=42454. Accessed 24 April 2015

Griskevicius V, Tybur JM, Van den Bergh B (2010) Going green to be seen: status, reputation, and

conspicuous conservation. Journal of personality and social psychology 98: 392-404

Guide, VDR (2000) Production planning and control for remanufacturing: industry practice and

research needs. Journal of Operations Management, 18: 467-483

Guide VDR, Muyldermans L, Van Wassenhove LN (2005) Hewlett-Packard company unlocks the

value potential from time-sensitive returns. Interfaces 35: 281-293

Handfield RB, Sroufe R, Walton SV (2005) Integrating environmental management and supply

chain strategies. Business Strategy and the Environment 14: 1-19

Hart SL (1995) A natural-resource-based view of the firm. Academy of Management Review 20:

986-1014

Hart SL, Dowell G (2011) A natural-resource-based view of the firm: fifteen years after. Journal

of Management 37:1464-1479

Hofmann KH, Theyel G, Wood CH (2012) Identifying firm capabilities as drivers of environmental

management and sustainability practices – evidence from small and medium‐sized manufacturers.

Business Strategy and the Environment 21: 530-545

Holt D, Ghobadian A (2009) An empirical study of green supply chain management practices

amongst UK manufacturers. Journal of Manufacturing Technology Management 20:933-956

IEC (2010) Environmentally conscious design for electrical and electronic products.

http://www.nema.org/Standards/ComplimentaryDocuments/62430-Contents-and-Scope.pdf.

Accessed 24 April 2015

30
Ilgin MA, Gupta SM (2010) Environmentally conscious manufacturing and product recovery

(ECMPRO): a review of the state of the art. Journal of environmental management 91: 563-591

Jayaraman V, Luo Y (2007) Creating competitive advantages through new value creation: a reverse

logistics perspective. Academy of Management Perspectives 21: 56-73

Joule E (2011) Fashion-forward thinking: sustainability as a business model at Levi Strauss. Global

Business and Organizational Excellence 30: 16-22

Kainuma Y, Tawara N (2006) A multiple attribute utility theory approach to lean and green supply

chain management. International Journal of Production Economics 10:99-108

Karlsson R, Luttropp C (2006) Eco-design: what's happening? an overview of the subject area of

eco-design and of the papers in this special issue. Journal of Cleaner Production 14: 1291-1298

Kim J, Rhee J (2012) An empirical study on the impact of critical success factors on the balanced

scorecard performance in Korean green supply chain management enterprises. International

Journal of Production Research 50:2465-2483

Kim J, Youn S, Roh J (2011) Green supply chain management orientation and firm performance:

evidence from South Korea. International Journal of Services and Operations Management 8:283-

304

King AA, Lenox MJ (2001) Lean and green? an empirical examination of the relationship between

lean production and environmental performance. Production and Operations Management 10: 244-

256

Klassen RD, Whybark DC (1999) The impact of environmental technologies on manufacturing

performance. Academy of Management Journal 42:599-615

Kotabe M, Martin X, Domoto H (2003) Gaining from vertical partnerships: knowledge transfer,

31
relationship duration, and supplier performance improvement in the US and Japanese automotive

industries. Strategic Management Journal 24:293-316

Koufteros XA, Cheng TCE, Lai KH (2007) Black-box and gray-box supplier integration in product

development: antecedents, consequences and the moderating role of firm size. Journal of

Operations Management 25:847-870

Kwon DM, Seo MS, Seo YC (2002) A study of compliance with environmental regulations of

ISO 14001 certified companies in Korea. Journal of Environmental Management 65:347-353

Lee S (2008) Drivers for the participation of small and medium-sized suppliers in green supply

chain initiatives. Supply Chain Management: An International Journal 13:185-198

Lee C, Lee K, Pennings JM (2001) Internal capabilities, external networks, and performance: a

study on technology-based ventures. Strategic Management Journal 22:615-640

Lee K, Kim J (2011) Integrating suppliers into green product innovation development: an empirical

case study in the semiconductor industry. Business Strategy and the Environment 20:527-538

Lee SM, Kim ST, Choi D (2012) Green supply chain management and organizational performance.

Industrial Management & Data Systems 112:1148-1180

Lee S, Klassen R (2008) Drivers and enablers that foster environmental management capabilities

in small and medium-sized suppliers in supply chains. Productions and Operations Management

17:573-586

Lopez-Gamero MD, Molina-Azorin JF, Claver-Cortes E (2009) The whole relationship between

environmental variables and firm performance: competitive advantage and firm resources as

mediator variables. Journal of Environmental Management 90:3110-3121

Luttropp C, Lagerstedt J (2006) Eco-design and the ten golden rules: generic advice for merging

32
environmental aspects into product development. Journal of Cleaner Production 14: 1396-1408

Mirabella N, Castellani V, Sala S (2013) Life cycle assessment of bio-based products: a disposable

diaper case study. International Journal of Life Cycle Assessment 18: 1036-1047

Mitra S, Datta PP (2014) Adoption of green supply chain management practices and their impact

on performance: an exploratory study of Indian manufacturing firms. International Journal of

Production Research 52:2085-2107

Nakano K, Hirao M (2011) Collaborative activity with business partners for improvement of

product environmental performance using LCA. Journal of Cleaner Production 19: 1189-1197

Nakano K, Nakaniwa C, Kabeya T, Iguchi T, Aoki R (2007) Current activities of the life cycle

assessment society of Japan. International Journal of Life Cycle Assessment 12: 546-546

Nawrocka D, Parker T (2009) Finding the connection: environmental management systems and

environmental performance. Journal of Cleaner Production 17:601-607

Nissan (2014) Nissan Motor Corporation sustainability report 2014. http://www.nissan-

global.com/EN/DOCUMENT/PDF/SR/2014/SR14_E_P014.pdf. Accessed 24 April 2015

Olorunniwo FO, Li X (2010) Information sharing and collaboration practices in reverse logistics.

Supply Chain Management: An International Journal 15: 454-462

Patnayakuni R, Rai A, Seth N (2006) Relational antecedents of information flow integration for

supply chain coordination. Journal of Management Information System 23:13-49

Petersen JA, Kumar V (2009) Are product returns a necessary evil? antecedents and consequences.

Journal of Marketing 73: 35-51

Priem RL, Butler JE (2001) Is the resource-based theory a useful perspective for strategic

management research? Academy of Management Review 26:22–40

33
Rao P, Holt D (2005) Do green supply chains lead to competitiveness and economic performance?

International Journal of Operations & Production Management 25:898- 916

Reuters (2011) Heinz to use Coke's “plant bottle” for its ketchup.

http://www.reuters.com/article/2011/02/23/coke-heinz-idUSN2315974620110223. Accessed 24

April 2015

Rosenzweig E, Roth A, Dean J (2003) The influence of an integration strategy on competitive

capabilities and business performance: an exploratory study of consumer products manufacturers.

Journal of Operations Management 21:437-456

Samsung SDI (2012) Supply chain environmental management.

http://www.samsungsdi.com/sustainability/approach/eco-value-creation. Accessed 24 April 2015

Sarkis J (2012) A boundaries and flows perspective of green supply chain management. Supply

Chain Management: An International Journal 17:202-216

Sarkis J, Gonzalez-Torre P, Adenso-Diaz B (2010) Stakeholder pressure and the adoption of

environmental practices: the mediating effect of training. Journal of Operations Management

28:163-176

Savaskan RC, Bhattacharya S, Van Wassenhove LN (2004) Closed-loop supply chain models with

product remanufacturing. Management Science 50: 239-252

Setthasakko W (2009) Barriers to implementing corporate environmental responsibility in

Thailand: a qualitative approach. International Journal of Organizational Analysis 17:169-183

Shang K, Lu C, Li S (2010) A taxonomy of green supply chain management capability among

electronics-related manufacturing firms in Taiwan. Journal of Environmental Management

91:1218-1226

34
Sharfman MP, Shaft TM, Anex RP (2009) The road to cooperative supply chain environmental

management: trust and uncertainty among pro-active firms. Business Strategy and the

Environment 19:1-13

Sharma S, Vredenburg H (1998) Proactive corporate environmental strategy and the development

of competitively valuable organizational capabilities. Strategic Management Journal 19:729-753

Shi VG, Koh SCL, Baldwin J, Cucchiella F (2012) Natural resource based green supply chain

management. Supply Chain Management: An International Journal 17:54-67

Sinding K (2000) Environmental management beyond the boundaries of the firm: definitions and

constraints. Business Strategy and the Environment 9:79-91

Spicer AJ, Johnson MR (2004) Third-party demanufacturing as a solution for extended producer

responsibility. Journal of Cleaner Production 12: 37-45

Srivastava SK (2007) Green supply-chain management: a state-of-the-art literature review.

International Journal of Management Reviews 9:53-80

Testa F, Iraldo F (2010) Shadows and lights of green supply chain management: determinants and

effects of these practices based on a multi-national study. Journal of Cleaner Production 18:953-

962

Thabrew L, Wiek A, Ries R (2009) Environmental decision making in multi-stakeholder contexts:

applicability of life cycle thinking in development planning and implementation. Journal of

Cleaner Production 17: 67-76

Thun J, Müller A (2010) An empirical analysis of green supply chain management in the German

automotive industry. Business Strategy and the Environment 19:119–132

Toffel MW (2004) Strategic management of product recovery. California Management Review 46:

35
120-141

Tsoulfas GT, Pappis CP (2008) A model for supply chains environmental performance analysis

and decision making. Journal of Cleaner Production 16:1647-1657

Vachon S, Klassen RD (2008) Environmental management and manufacturing performance: the

role of collaboration in the supply chain. International Journal of Production Economics 111:299

-315

Vallet F, Eynard B, Millet D, Mahut SG, Tyl B, Bertoluci G (2013) Using eco-design tools: an

overview of experts’ practices. Design Studies 34: 345-377

White CD, Masanet E, Rosen CM, Beckman SL (2003) Product recovery with some byte: an

overview of management challenges and environmental consequences in reverse manufacturing

for the computer industry. Journal of Cleaner Production 11: 445-458

Wiens K (2014) Intellectual property is putting circular economy in jeopardy. The Guardian.

http://www.theguardian.com/sustainable-business/intellectual-property-circular-economy-bmw-

apple. Accessed 24 April 2015

Xerox (2014) Sustainable services and products. http://www.xerox.com/corporate-

citizenship/2014/sustainability/sustainable-products/enus.html. Accessed 24 April 2015

Zhu Q, Sarkis J (2004) Relationships between operational practices and performance among early

adopters of green supply chain management practices in Chinese manufacturing enterprises.

Journal of Operations Management 22:265-289

Zhu Q, Sarkis J (2007) The moderating effects of institutional pressures on emergent green supply

chain practices and performance. International Journal of Production Research, 45:4333-4355

Zhu Q, Sarkis J, Geng Y (2005) Green supply chain management in China: pressures, practices

36
and performance. International Journal of Operations & Production Management 25:449-468

Zhu Q, Sarkis J, Cordeiro JJ, Lai KH (2008) Firm-level correlates of emergent green supply chain

management practices in the Chinese context. Omega 36:577-591

37
Figure 1 Conceptual framework

Figure 2 Eco design and investment recovery in a closed loop supply chain

38
Figure 3 Results of the hypotheses testing

Figure 4 Moderating effects of collaboration on financial performance

39
Table 1 List of questionnaire items

GSCM practice factors

Eco-design
We design our products to avoid or reduce the use of hazardous products and their manufacturing process.
We provide design specifications to our partners that include environmental requirements for purchased items.
We design products considering life cycle assessment (LCA).
We design our products for reuse, recycle, and recovery of material and component parts.
Investment recovery
We have implemented collecting policies.
We have implemented recycle policies.
We have implemented remanufacturing policies.
Collaborative capability factor
We rely on our partners’ engineering capability.
Our partners’ tools and machinery are customized to our needs.
Our partners spend a significant amount of time and effort to our relationship.
Our partners’ knowledge of our procedures, culture, and technological know-how are difficult to replace.
The frequent contacts between our partners and our engineers are important.
The direction of our communication is bilateral rather than unilateral.
Our engineers and sales staff work closely with our partners’ staff.
We share our high level of engineering capability with our partners.
Firm performance factors
Environmental performance
Our CO2 emission has been reduced after the introduction of green management.
Our waste water has been reduced after the introduction of green management.
Our solid waste has been reduced after the introduction of green management.
Our energy consumption has been reduced after the introduction of green management.
Financial performance
Our profitability has increased after the introduction of green management.
Our market share has increased after the introduction of green management.
Our sale growth rate has increased after the introduction of green management.
Our earnings per share rate has increased after the introduction of green management.

40
Table 2 Sample charateristics

Industry type Frequency Percent

Miscellaneous manufacturing 56 24.3
Automobile hardware, metal, and manufacturing 42 18.3
Industrial, commercial machinery and computer equipment 39 17.0
Transportation services 29 12.6
Rubber and miscellaneous plastics products 26 11.3
Primary metal industries 25 10.9
Electronic/other electrical equipment and components, except computer 7 3.0
Equipment 6 2.6
Total 230 100.0
Number of employees Frequency Percent
Up to 100 34 14.8
101-300 23 10.0
301-500 19 8.3
501-700 30 13.0
701-900 39 17.0
Over 900 85 37.0
Total 230 100.0

41
Table 3 Descriptive statistics

GSCM practice factors Mean SD

Eco-design
We design our products to avoid or reduce the use of hazardous products and their manufacturing process. 4.713 1.368
We provide design specifications to our partners that include environmental requirements for purchased 4.548 1.343
items.
We design products considering life cycle assessment (LCA). 4.574 1.345
We design our products for reuse, recycle, and recovery of material and component parts. 4.696 1.309
Investment recovery
We have implemented collecting policies. 4.683 1.193
We have implemented recycle policies. 4.735 1.191
We have implemented remanufacturing policies. 4.726 1.185
Collaborative capability factor
We rely on our partners’ engineering capability. 2.969 1.302
Our partners’ tools and machinery are customized to our needs. 3.017 1.233
Our partners spend a significant amount of time and effort to our relationship. 3.057 1.223
Our partners’ knowledge of our procedures, culture, and technological know-how are difficult to replace. 3.026 1.274
The frequent contacts between our partners and our engineers are important. 3.017 1.226
The direction of our communication is bilateral rather than unilateral. 3.044 1.125
Our engineers and sales staff work closely with our partners’ staff. 2.913 1.160
We share our high level of engineering capability with our partners. 2.935 1.215
Firm performance factors
Environmental performance
Our CO2 emission has been reduced after the introduction of green management. 4.752 1.176
Our waste water has been reduced after the introduction of green management. 4.835 1.163
Our solid waste has been reduced after the introduction of green management. 4.883 1.129
Our energy consumption has been reduced after the introduction of green management. 4.752 1.198
Financial performance
Our profitability has increased after the introduction of green management. 4.817 1.208
Our market share has increased after the introduction of green management. 4.578 1.268
Our sale growth rate has increased after the introduction of green management. 4.630 1.225
Our earnings per share rate has increased after the introduction of green management. 4.574 1.275

42
Table 4 Factor matrix-GSCM practices

Component
Survey items
1 2
We design products considering life cycle assessment (LCA). .955 -.065
We provide design specifications to our partners that include environmental requirements for purchased items. .888 .012
We design our products to avoid or reduce the use of hazardous products and their manufacturing process. .858 .063
We design our products for reuse, recycle, and recovery of material and component parts. .734 .160
We have implemented recycle policies. .244 .880
We have implemented remanufacturing policies. .247 .858
We have implemented collecting policies. .376 .791
Extraction Method: Principal Component Analysis
Rotation Method: Oblimin with Kaiser Normalization
Rotation converged in 5 iterations

Table 5 Factor matrix-firm performance

Component
Survey items
1 2
Our waste water has been reduced after the introduction of green policies. .924 -.007
Our solid waste has been reduced after the introduction of green policies. .921 -.031
Our energy consumption has been reduced after the introduction of green policies. .909 .006
CO2 emission has been reduced after the introduction of green policies. .844 .042
Our earnings per share rate has increased after the introduction of green management. -.061 .941
Our sale growth rate has increased after the introduction of green management. .013 .916
Our market share has increased after the introduction of green management. -.032 .914
Our profitability has increased after the introduction of green management. .099 .775
Extraction Method: Principal Component Analysis
Rotation Method: Oblimin with Kaiser Normalization
Rotation converged in 6 iterations

43
Table 6 Factor matrix-collaborative capability

Component
Survey items
1
Our partners’ tools and machinery are customized to our needs. .856
We rely on our partners’ engineering capability. .855
Our partners spend a significant amount of time and effort to our relationship. .852
Our engineers and sales staff work closely with our partners’ staff. .845
Our partners’ knowledge of our procedures, culture, and technological know-how are difficult to replace. .823
The frequent contacts between our partners and our engineers are important. .816
We share our high level engineering capability with our partners. .815
The direction of our communication is bilateral rather than unilateral. .790
Extraction Method: Principal Component Analysis
1 component extracted

Table 7 Mean, standard deviations, correlations, and the square root of AVE

Mean SD ED IR CC EP FP
Eco-design (ED) 4.63 1.19 .838
Investment
4.71 1.06 .610** .903
recovery (IR)
Collaborative
2.99 1.01 -.467** -.434** .883
capability (CC)
Environmental
4.80 1.05 .545** .600** -.436** .889
performance (EP)
Financial
4.65 1.10 .429** .426** -.504** .401** .922
performance (FP)
Firm size 4.18 1.85 607** .550** -.448** .631** .312**
** p < 0.01

44
Table 8 Hierarchical regression with eco-design and collaborative capability interaction

Dependent variable
Variable
Environmental performance Financial performance
entered
Step 1 Step 2 Step 3 Step 1 Step 2 Step 3
Firm size 0.349** 0.265** 0.241** 0.186** 0.035 -0.043
(control) (0.030) (0.036) (0.037) (0.038) (0.045) (0.042)
Industry -.023 -0.016 -0.015 -0.053 -0.042 -0.037
(control) (0.022) (0.021) (0.021) (0.028) (0.027) (0.024)
0.221** 0.183** 0.342** 0.227**
Eco-design
(0.055) (0.057) (0.069) (0.064)
Collaborative -0.116 -0.271
capability (0.066) (0.075)
Collaborative
0.039 0.219**
capability ×
(0.041) (0.046)
Eco-design
F 76.193** 59.574** 37.873** 14.190** 18.514** 26.931**
R2 0.402 0.442 0.446 0.103 0.187 0.362
2
R Change 0.402** 0.039** 0.004 0.103** 0.083** 0.175**
** p < 0.01

45
 Table 9 Hierarchical regression with investment recovery and collaborative capability interaction

Dependent variable
Variable
Environmental performance Financial performance
entered
Step 1 Step 2 Step 3 Step 1 Step 2 Step 3
Firm size 0.349** 0.241** 0.223** 0.166** 0.054 -0.010
(control) (0.030) (0.033) (0.034) (0.039) (0.043) (0.040)
Industry -0.023 -0.011 -0.009 -0.053 -.040 -0.029
(control) (0.022) (0.020) (0.020) (0.028) (0.027) (0.024)
Investment 0.356** 0.316** 0.370** 0.204**
recovery (0.057) (0.059) (0.075) (0.070)
Collaborative -0.100 -0.339
capability (0.060) (0.071)
Collaborative
capability × 0.035 0.186**
Investment (0.039) (0.046)
recovery
F 76.193** 72.684** 45.235** 14.190** 18.649** 25.358**
R2 0.402 0.491 0.502 0.111 0.198 0.361
2
R Change 0.402** 0.089 0.011* 0.111** 0.087** 0.163**
* p < 0.05
** p < 0.01

Table 10 Hypotheses and results summary

Hypothesis Statistics Support

(beta)
H1a Eco-design is positively related to environmental performance. 0.252** Supported
H1b Eco-design is positively related to financial performance. 0.342** Supported
H2a Investment recovery is positively related to environmental performance. 0.360** Supported
H2b Investment recovery is positively related to financial performance. 0.355** Supported
Collaborative capability moderates the relationship between eco-design and
H3a 0.056 Not supported
environmental performance.
Collaborative capability moderates the relationship between eco-design and
H3b 0.301** Supported
financial performance.
Collaborative capability moderates the relationship between investment recovery
H4a 0.048 Not supported
and environmental performance.
Collaborative capability moderates the relationship between investment recovery
H4b 0.245** Supported
and financial performance.
** p < 0.01

46

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