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Assignment 1

Looking for someone is very specific with information and gives great detail within their writing. Need good quality work. No plagiarism, honesty, and A++ work. Someone who will take their time to understand and follow given instructions carefully. Deliver work ahead of time and not have me asking and looking for expected assignment. If you have any questions about the assignment or unsure about something please ask. Instructions attached.

I have provided the two sources that need to be used in the attached PDF files. Please use those two sources. If you have any questions, please ask. I’ve also included a sample of how the work is to be done.

Student Name

COLL 300

Evaluating Sources: CMS (Chicago)

Bjelopera, Jerome P. “Combating Homegrown Terrorism: Enforcement Activities,”
Congressional Research Service, Report (November 15, 2011): 36-53. International
Security & Counter Terrorism Reference Center, EBSCOhost .

Credible Author: Jerome P. Bjelopera is recognized as a specialist in organized crime and terrorism by his peers. A Google search revealed numerous hits for him. The hits on the first page were for reputable sites ending with .edu and .org. Also, a search of his name on the Amazon website revealed he has authored a couple of books in addition to some other articles.

Reliable Publisher: The Congressional Research Service (CRS) is a reliable organization. The CRS falls under the Library of Congress, and they provide policy and legal analysis to Capitol Hill members. This service is provided to all parties and is unbiased in nature. The CRS has existed for almost 100 years.

Accuracy: The article appears to be accurate in its facts. I could not find any errors or conclusions that did not add up. The author had a section on the Newburgh Four case as well as the Liberty City Seven case. These cases are well known and the facts can be easily verified through other websites if a reader was not already familiar with the cases. Bjelopera’s article is reasonable and balanced, and he backs up his assertions with credible sources. He also presented the reader with some of the existing policies in this post 9/11 world. An example of this is a quote he used from Deputy Attorney General, Paul McNulty letting the reader know what the Justice Department’s policy is regarding preventive policing. . The information he has presented in this article is pretty consistent with other information I have read on the topic.

Currency: This article was published in 2011 and is therefore, very current. The author addresses topics that are very relevant in this post 9/11 world. Two examples are the section titled “The Role of State and Local Law Enforcement” and the section called “Detecting the Shift from Radical to Violent Jihadist.”

Objectivity: Jerome P. Bjelopera’s article appears to be unbiased. It is obvious he believes that we need to do everything in our power to prevent future terrorist attacks, and he writes from this perspective. However, he does bring up opposing views. An example of this is in the section called “The Capone Approach.” He acknowledges that this method has come under attack by the media.

Byman, Daniel. “Strategic Surprise and the September 11 Attacks.” Annual Review Of Political Science 8, no. 1 (June 2005): 145-170. Academic Search Premier,
EBSCOhost

Credible Author: Dr. Daniel L. Byman is a professor at Georgetown University in the School of Foreign Service. He was a member of the 9/11 Commission and the Joint 9/11 Inquiry Staff of the House and Senate Intelligence Committees. He is highly respected in topics related to terrorism, international security, and the Middle East. In addition, he had numerous hits come up after conducting a google search on him.

Reliable Publisher: Annual Reviews is a nonprofit scientific publisher. Annual Reviews has been in existence since 1932. It was created by scientists and its mission is to publish scientific reviews in 40 different scientific fields. It is managed by scientists and is considered a reliable organization.

Accuracy: The information is very accurate and backed up with numerous, credible sources. It is filled with a lot of useful, factual information that can be easily verified. The report appears to be well balanced and complete. Byman offered six examples of missed opportunities for intelligence in regards to the 9/11 terrorist attacks. These aren’t just his assumptions, these are facts that were uncovered by the 9/11 Commission. They are all well documented.

Currency: This report was published in 2005 and the information is still accurate and current today in this post 9/11 world.

Objectivity: The author was unbiased in his report. He presented ideas that were backed up by facts. Although this report discusses the failure to anticipate the 9/11 terrorist attacks, the points he brought up are widely agreed upon by various government officials and organizations.

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Assignment Instructions

This assignment will give you an opportunity to analyze the strength of your sources and to practice citing two of your sources in the documentation style you have chosen for your paper. Remember, your final paper must include a minimum of 7 sources with at least 4 sources coming from peer-reviewed journals taken from the APUS library database.
Source Evaluations: After completing this week’s required readings, select 2 of the sources you will use in your paper and compose a minimum one page evaluation of each source. Ensure that 1 of those sources is from a peer-reviewed journal at the APUS Library.

Be sure to include your documentation style in your heading. After formatting the source information according to your documentation style, use the headings below to create your evaluation.

First Source (including proper citation and URL)

From Peer-reviewed Journal at APUS Library?

Credible Author: Explain how/why the author should be considered an expert on your chosen topic.
Reliable Publisher: Who is the publisher? What is the publisher’s reputation? Has this source been published by a scholarly or peer-reviewed press? Is this source available in trusted archives, such as subscription databases? If this is from a website, how stable is that website?
Accuracy: Does the information seem to be accurate? Does the information correspond with or contradict information found in sources known to be reliable? Has the information been peer-reviewed? Is there a reference list available so you can verify the information? Are there any factual errors, statistical flaws, or faulty conclusions?
Current Information: Is the material up to date? If it is from a website, when was it last updated?
Objectivity (Bias): Are all sides of the issue/topic treated fairly? Do you detect any bias? (For instance, is the author connected to any institution or foundation that might be paying him, which could suggest bias?)

Second Source (including proper citation and URL)

From Peer-reviewed Journal at APUS Library?

Strategic orientations,
sustainable supply chain

initiatives

, and reverse logistic

Empirical evidence from an emerging market

Chin-Chun Hsu and Keah-Choon Tan
Lee Business School, University of Nevada, Las Vegas, Nevada, USA, and

Suhaiza Hanim Mohamad Zailani
University of Malaya, Kuala Lumpur, Malays

Abstract
Purpose – Global outsourcing shifts manufacturing jobs to emerging countries, which provides new
opportunities for improving their economic development. The authors develop and test a theoretical
model to predict first, how sustainable supply chain initiatives might influence reverse logistics
outcomes and second, the impact of eco-reputation and eco-innovation orientation strategies on the
deployment of sustainable supply chain initiatives. The paper aims to discuss these issues.
Design/methodology/approach – The proposed new model of antecedents and outcomes of
sustainable supply chain initiatives underwent a rigorous empirical test through structural equation
modeling with samples from an emerging market.
Findings – The results show that firms that implement sustainable supply chain initiatives can realize
positive reverse logistics outcomes; the study also provides new insights into eco-innovation and
eco-reputation strategic orientations as theoretically important antecedents of sustainable supply
chain

initiatives.

Research limitations/implications – Though the authors identify three components of sustainable
supply chain initiatives, other components could exist, and ongoing research should investigate them.
Practical implications – The findings have important implications for managers in emerging
markets seeking to initiate ecologically friendly business practices. The authors offer strong evidence of
the benefits obtained from reverse logistics in sustainable supply chain initiatives. Policy makers and
firms attempting to nurture sustainable supply chain initiatives should not overlook the important role of
eco-reputation and eco-innovation strategic orientations, which the results identify as important enablers.
Originality/value – This study offers evidence of the critical role of eco-reputation and
eco-innovation strategic orientations in deploying sustainable supply chain initiative programs, as well
as of their mutual effects. This study also offers empirical evidence that implementing sustainable
supply chain initiatives leads to reverse logistics, creating value, and a new source of competitive
advantages.
Keywords Eco-innovation, Emerging market, Strategic orientation, Eco-reputation,
Reverse logistics, Sustainable supply chain initiatives

Paper type Research paper

1. Introduction
Outsourcing trends since the early 1990s have transformed emerging countries into
significant players in the global economy. Global outsourcing thus has reshaped global
supply chain systems in significant ways, such that the globalized manufacturing
network has shifted manufacturing jobs to emerging countries, which providing
new opportunities for improving the economic development of emerging markets. But a
globalized manufacturing network also poses significant risks to individual health
and safety, national economies, and local, regional, and global environments

International Journal of Operatio

& Production Management
Vol. 36 No. 1, 2016
pp. 86-

110

©EmeraldGroup Publishing Limited
0144-3577
DOI 10.1108/IJOPM-06-2014-0252

Received 20 July 2014
Revised 10 December 2014
29 January 2015
24 February 2015
Accepted 26 February 2015

The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0144-3577.htm

IJOPM
36,1

(O’Rourke, 2005). Thus the question of whether manufacturing firms in emerging
countries can manage their profit growth and environmental sustainability goals
effectively has important implications at both national and global levels.

Sustainable business practices can help create wealth for firms and raise the standard
of living in emerging markets; unsustainable economic activities lead to environmental
degradation that can threaten an emerging country’s long-term prosperity and economic
competiveness (Schmidheiny, 1992). Firms in emerging countries might adapt ecologically
friendly strategies and guidelines from their business clients or competitors in more
advanced economies, though rapid business development and continuous environmental
deterioration also have increased the emphasis on environmental sustainability.
In particular, environmental concerns have prompted the governments of some
emerging economies to regulate business practices and set broad environmental
improvement objectives (Child and Tsai, 2005). On the flip side, profit pressures and weak
ecological traditions can decrease firms’ incentives to address the broader range of
stakeholder interests associated with sustainable practices.

In this context, we note three pertinent knowledge gaps. First, many studies have
focussed on green business approaches in advanced economies, but much less research
has addressed the antecedents or outcomes of ecologically friendly business practices in
emerging markets (Blome et al., 2014; Fabbe-Costes et al., 2014). Second, despite the
ongoing debate about the potential outcomes of ecologically friendly supply chain
activities (Prajogo et al., 2014), the benefits or outcomes of sustainable supply
chain initiatives are poorly understood (Roehrich et al., 2014), though outcome measures
are essential for managing and navigating competitive global markets. In a related sense,
surprisingly few empirical studies examine the impacts on reverse logistics (Aitken and
Harrison, 2013), despite their promise for creating new value and providing competitive
advantages ( Jayaraman and Luo, 2007). Third, even when ecologically friendly supply
chain commitments make sense, managers lack guidelines for how to start greening their
firms’ supply chain efforts. A few prior studies identify external “enablers,” derived from
institutional or stakeholder theory (Zailani et al., 2012), but relatively few cite strategically
relevant factors. That is, research into sustainable supply chain initiatives tends to
pertain to organizational capabilities, not the strategic orientation antecedents that
precede the adoption of sustainable supply chain initiatives. By focussing on
sustainability practices, definitions, and decision frameworks, these studies ignore the
need for insights into how to develop sustainability strategies from an organizational
perspective (Zhu and Sarkis, 2007). The fragmented, incomplete knowledge in this area
thus fails to address adequately which key strategic orientation forces will drive
sustainable supply chain initiatives.

In attempting to fill these knowledge gaps, this study makes three primary
contributions. First, we study emerging economies. Some manufacturing firms identify
and target segments of ecologically conscious buyers, in an effort to position themselves
as favorable green suppliers, but most companies refuse to abandon their existing
operations and production processes, regardless of the growing interest in sustainability
(Größler et al., 2013). Thus, manufacturing firms in emerging countries must find ways to
execute existing supply chain strategies through sustainable initiatives that implement
more ecologically friendly programs than appeared in their past supply chain efforts.
In particular, we study Malaysia, which is a member of Association of Southeastern
Asian Nations and an integral part of the global economy; Malaysian suppliers have
critical roles in global supply chains. The country represents an important
manufacturing hub for global firms that seek to outsource the manufacture of

Sustainable
supply chain

initiatives

component parts. The United Nations Conference on Trade and Development (UNCTAD

)

reports that foreign direct investment (FDI) inflows to Malaysia increased from
US$9.1 billion in 2010 to US$11.9 billion in 2011, an increase of 30.8 percent
(World Investment Report, 2013), which also raised Malaysia’s rank to 13 from 16 in the
list of Top Prospective Host Economies for 2013-2015 (World Investment Report, 2013).
Thus, the UNCTAD report affirms Malaysia’s attractiveness as a FDI destination. In this
emerging economy, sustainable development remains at an early stage, whereas profit
maximization is the priority for most manufacturing firms.

Second, we examine the reverse logistic effects of ecologically friendly purchasing,
manufacturing, and packaging programs (De Leeuw et al., 2013; Hsu et al., 2013).
Sustainable supply chain initiatives can deliver reverse logistic benefits; our empirical
evidence even shows that firms can create competitive advantages for new value
creation (Chavez et al., 2013). Reverse logistics refers to returns of products or
packaging, after their use, for reuse, recycling, or reclamation of materials
(Kapetanopoulou and Tagaras, 2011). By engaging in reverse logistics, firms can
recycle remanufactured parts or components, as well as dispose properly of those
components that cannot undergo remanufacturing or recycling (Lo, 2014). In turn, they
constitute a substantial cost-driving area and may result in greater profitability and
customer satisfaction, as well as benefitting the environment (Hsu et al., 2013).

Third, this study considers specific strategic orientation drivers that engender
success in sustainable supply chain initiatives. Specifically, we identify and empirically
examine two new strategic orientation factors that have been overlooked:
eco-reputation and eco-innovation, both of which integrate environmental concerns
into the firm’s business strategies. This study thus offers evidence of the critical role of
eco-reputation and eco-innovation strategic orientations in deploying sustainable
supply chain initiative programs, as well as of their mutual effects. Both antecedents
may be important for understanding how firms respond to ecological challenges and
derive sustainable supply chain initiatives, but neither has been the subject of prior
research. We show that firms wishing to sustain their firm’s supply chain initiatives
should develop their eco-reputation and eco-innovation strategic orientations first.

In the next section, we present a theoretical framework for the strategic orientation
antecedents and reverse logistics outcomes of sustainable supply chain initiatives.
Our research hypotheses reflect input from a wide array of literature. We discuss the
research methodology and the results of the data analyses. Finally, this paper
concludes by delineating the findings, their managerial implications, and limitations.

2. Literature review
2.1 Strategic orientations
Strategic orientation originally stemmed from the market orientation notion, which
was a popular means to measure firm performance. According to Manu and Sriram
(1996, p. 79), strategic orientation refers to “how an organization uses strategy to adapt
and/or change aspects of its environment for a more favorable alignment.” Extended
versions focus on customer or technology orientations, and Narver and Slater (1990)
argue that strategic orientation is an critical component of profitability for both
manufacturing and service businesses, such that an orientation influences business
decisions through its effects on business profitability (Schniederjans and Cao, 2009).

According to strategic choice theory (Child, 1972), strategic decisions also have a
determining role in a firm’s business survival, and the fundamental issue is the strategic
orientation, with a foundational assumption that firms can enact and actively shape their

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36,1

environments. Strategic choice theory centers on decision making in organizations
designed to achieve well-defined goals. Thus, managerial discretion, interpretation,
and perspective have great influence in strategic decision making, over the span of
shared organizational actions. To achieve organizational effectiveness, firms must
make appropriate strategic choices that “represent the competitive strategy implemented
by a firm to create continuing performance improvements” (Morgan and Strong, 1998,
p. 1055). Ultimately a strategic orientation is a firm’s overall direction and objectives,
oriented toward an external business environment and driven by top management
(Voss and Voss, 2000). Strategic choice theory focusses on managers’ strategic choices
when their firms face external challenges (Child, 1972). If they have a strategic orientation,
firms choose to leverage their strategy to adapt or change aspects of their external
environment to ensure more favorable alignment. It also helps explain why firms take
proactive and committed actions to address urgent issues such as sustainability.

Firms do not interact with their operating environments in identical ways. For
example, in the same industry, some firms focus on a narrow, limited, product-market
domains, in an effort to protect their market share. Others search continuously for new
market opportunities through innovation and new product development. Responses to
the operating environment reflect firms’ strategic orientations; strategic orientations
largely their choices, establish their strategic positioning, affect their performance,
involve multiple functions, are highly complex and ambiguous, and demand
substantial resource commitments. In addition, a strategic orientation choice refers
to the process of choosing one course of action rather than another. Thus a strategic
orientation offers a means to comprehend the actions that firms take to enhance their
profitability and competitive advantage. This pattern of past, or intended, decisions
guides a firm’s ongoing alignment with its external environment and shapes strategic
policies and procedures (Hill and Cuthbertson, 2011; Minarro-Viseras et al., 2005).

From a sustainable supply chain perspective, firms’ strategic orientations are
critical, because sustainable business practices demand substantial firm resources and
are technically complex, such that they require diverse skills contributed by technical
experts, organizational experts, and top management (Saeed et al., 2014). From a
strategic choice theory perspective, Sharma (2000) examines how firms use freedom of
choice (discretion, interpretation, and perspective) to create strategies that influence
firms’ orientation toward adopting sustainability initiatives. Ketchen and Hult (2011)
cite strategic choice theory as appropriate for studying strategic supply chain
management. With its focus on the best value, strategic choice theory seeks to identify
supply chain models that can affect organizational outcomes and enact the
environment. Strategic choice theory centers on the intra-organizational level and the
provision of certain strategic capabilities (Ketchen and Hult, 2011). It also seeks to
answers questions and challenges in extant supply chain management research.
Finally, a strategic orientation toward sustainable business practices is influenced by
various external agents, including suppliers, governments, regulatory organizations,
green social groups, and rapidly changing technology (Shrivastava and Grant, 1985).

We examine two particular ecological strategic orientations: eco-reputation and
eco-innovation. An eco-reputation is a stakeholder’s overall perception of a company’s
efforts on environmental protection over time. This evaluation reflects each
stakeholder’s experience of the ecological commitment of the company, as well as
images based on the company’s actions, beyond simple compliance with government
regulations (e.g. Chen, 2010). This definition is consistent with Banerjee (2001),
Banerjee et al. (2003) and Esty and Winston (2009). Eco-innovation instead refers to the

Sustainable
supply chain
initiatives

development of products and processes that explicitly account for concerns about
the natural environment in pursuit of the goal of sustainable development and
ecological improvements (e.g. Menon et al., 1999). Thus eco-innovation constitutes a
firm’s strategic resources, from ecologically friendly technological advances to socially
acceptable innovative paths, consistent with the view that product development and
process improvement can be designed and executed in ways that are less harmful to the
natural environment (Fussler and James, 1996; Segarra-Oña et al., 2014).

Hong et al. (2009) define an ecological strategic orientation as a firm’s long-term
commitment to producing environmentally sound products and services by
implementing environmental improvement goals. Environmentally sound products
can promote a firm’s overall economic performance, through internal integration and
external coordination with both major stakeholders, such as customers and suppliers.
Moreover, to ensure a sustainable orientation for the supply chain, the firm must
maintain its successful past practices while promoting and encouraging the
implementation of consistent environmental innovative initiatives that reinforce its
long-term sustainability (Hong et al., 2009; Awaysheh and Klassen, 2010). The adoption
of sustainable supply chain initiatives depends on the firm’s strategic orientation
(Baines et al., 2005). An ecological strategic orientation, such as eco-reputation or
eco-innovation, influences strategic choices, such that each ecological strategic
orientation can influence the impact of the firm’s decision makers on the adoption of
sustainable business practices throughout the firm (Chiang et al., 2012).

2.2 Sustainable supply chain management
Supply chain management encompasses “a set of three or more entities directly
involved in the upstream or downstream flows of products, services, finances, and/or
information from a source to a customer” (Mentzer et al., 2001, p. 4). This definition sets
the boundaries of the supply chain with the final customer. Traditional supply chains
also are based on the production paradigm (Doran et al., 2007). In contrast, sustainable
supply chains is an inter-disciplinary, cross-cutting issue. The 2005 world summit on
social development (www.un.org/ga/59/hl60_plenarymeeting.html) identified three
pillars of sustainability: economic development (profit), social development (people),
and environmental protection (plant). These pillars are not mutually exclusive but can
be mutually reinforcing. In the contemporary accounting framework, the triple bottom
line provides the measure of business sustainability, in terms of financial, social, and
environmental performance. In addition, Peter Senge, in an interview by Harvard
Business Review, identifies sustainable supply chains as the core enablers of the next
industrial revolution (Prokesch, 2010). The United Nations Global Compact recently
launched a guide for advancing sustainability in global supply chains in four key areas:
human rights, labor, environment, and anti-corruption (www.unglobalcompact.org).

With this study, we focus on the environmental perspective of sustainable supply
chain practices. Specifically, firms must to partner with members throughout their
supply chains to improve energy efficiency while reducing natural resource usage,
waste, and adverse environmental impacts, which together lead to a stronger bottom
line. Sustainable supply chains account for the environmental impacts of products and
services as they flow throughout the supply chain. These environmentally friendly
extensions of traditional supply chains include activities to minimize the negative
environmental impacts of a product or service throughout its entire life cycle.

Sustainable supply chains deal with environmental issues in both forward and reverse
versions (Rao and Holt, 2005). A sustainable forward supply chain would address

IJOPM
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www.un.org/ga/59/hl60_plenarymeeting.html

www.unglobalcompact.org

environmental issues both upstream and downstream (Geyer and Jackson, 2004).
Upstream, sustainable supply chains can have significant effects in terms of improving
suppliers’ environmental performance (Sarkis, 2006). Downstream, these sustainable
supply chains focus on reducing the environmental impacts of the products produced
during their use and disposal. Such reductions often offer significant environmental
benefits, because products generate most of their environmental emissions and waste
during their use, such that these detrimental impacts may exceed those generated during
the manufacturing stage. Through these outcomes, sustainable supply chains provide
both economic and environmental benefits (Carter et al., 2000; Rao and Holt, 2005).

2.3 Sustainable supply chain initiatives
Supply chains encompass all activities associated with the process flow for
transforming raw materials into goods for end users. The process cycle begins with
purchasing, including raw material purchasing activities by suppliers. Manufacturing
activities follow, after which the product must be distributed to customers or retailers
(Hill et al., 2012). According to sustainability literature, the potential green elements in
this cycle include vendor assessments, environmental purchasing policies, green
production policies, waste management, training, cross-functional integration, effective
coordination between companies and suppliers, performance evaluation processes,
the selection of suppliers, and leveraging relationships between suppliers and
customers (Giovanni, 2012). We therefore conceptualize sustainable supply chain
initiatives as those designed to accomplish the firm’s strategic supply chain functions –
purchasing, manufacturing, and packaging – in ways that minimize their negative
impacts on the natural environment. This conceptualization is line with prior
definitions of sustainable supply chains (e.g. Hsu et al., 2013).

Green purchasing refers to an ecologically conscious purchasing initiative that aims
to ensure procured materials or components meet the firm’s eco-friendly goals. The
purchasing process can manifest the firm’s environmental preferences if it includes
green purchasing criteria (Saghiri and Hill, 2014). Carter and Ellram (1998) argue
that green purchasing also should reflect efforts to reduce, reuse, and recycle materials.
Thus, purchasing decisions have significant influences on the sustainable supply chain
(Yang et al., 2013) through the procurement of raw materials and components.

Green manufacturing entails the environmentally conscious production of a
product, with the goal of minimizing its negative environmental impacts throughout its
entire life cycle, as well as promoting positive ecological business operation practices,
such as recycling and reusing products (Dam and Petkova, 2014). That is, green
manufacturing considers environmental impacts in every stage of the product lifecycle
(Giovanni, 2012), in an effort to minimize the environmental impacts of manufacturing
processes, generate minimum waste, and reduce environmental pollution. Pursuing
green manufacturing also helps firms lower their raw material costs, gain production
efficiency, reduce environmental and occupational safety expenses, and improve their
corporate image (Zhu and Sarkis, 2007). Thus, green manufacturing helps firms
achieve profit growth and increase their market share.

Finally, green packaging is environmentally conscious packaging of a product, to
minimize the associated negative environmental impacts. Packaging contributes directly
to product success in supply chains, because it can enable the efficient distribution of
products, as well as lower environmental impacts due to spoilage or waste. Increased
attention to global climate change has made green packaging a primary focus area, to
reduce waste and improve air quality, because different packaging characteristics

Sustainable
supply chain
initiatives

(e.g. size, shape, materials) have different impacts. Hsu et al. (2013) indicate that green
packaging includes considerations of cost (materials and shipping), performance
(adequate protection of the product), convenience (easy to use), compliance (with legal
requirements), and environmental impact (Liu et al., 2013; Lin et al., 2013).

2.4 Reverse logistics and competitive advantage
Dowlatshahi (2000) define reverse logistics as activities by which a producer retrieves
products and components to recycle, rebuild, or dispose of them properly. Reverse
logistics also might refer to the actual process of return or take-back, after the
consumer has used the product or packaging, to reuse, recycle, or reclaim materials,
or else provide safe refills (Carter and Ellram, 1998). Using reverse logistics as a supply
chain performance measure suggests how companies can obtain competitive
advantages by quantifying the efficiency and effectiveness of their actions (Lehtinen
and Ahola, 2010). Thus reverse logistics differentiate a firm, leading to a market
advantage and opportunities to build competitive advantages.

Specifically, reverse logistics create tangible and intangible value by helping firms
first, extract value from used/returned goods instead of wasting manpower, time, and
to procure more raw materials, second, create additional value through increasing
product life cycles, third, improve customer satisfaction and loyalty by paying more
attention to faulty goods and merchandise repairs, and fourth, obtain feedback to
suggest improvements and enhance understanding of the real reasons for product
returns, which should lead to future product improvements or new product designs
(Aitken and Harrison, 2013). Through reverse logistics, manufacturing firms not only
receive products back from the consumer but also collect unsold merchandise for the
manufacturer to take apart, sort, reassemble, or recycle (Yu et al., 2012). Alternatively,
the returned product might be re-sold in secondary channels and thus generate
revenue (Aitken and Harrison, 2013). Reverse logistics also might enhance customer
loyalty, because customers respond positively to environmentally responsible
actions by the firm, so goodwill generated by reverse logistics could be a source of
firm competitiveness.

3. Hypotheses development
We depict the key study constructs in Figure 1. The two strategic orientation
antecedents, eco-innovation, and eco-reputation, precede sustainable supply chain
initiatives. Sustainable supply chain initiatives then relate to the firm’s reverse logistics.

3.1 Relationship of eco-reputation and eco-innovation strategic orientations
According to strategic orientation literature and strategic choice theory, a firm’s
strategic orientations are critical, because they involve the commitment of a large
amount of firm resources (De Toni and Tonchia, 2003). They also tend to be
technically complex, demanding diverse skills gathered from technical experts,
organizational experts, and top management. Furthermore, strategic orientations
depend on external agents, such as suppliers, organized labor unions, and rapidly
changing technology (Shrivastava and Grant, 1985). Strategic orientation choice
involves a process of choosing a particular course of action, which helps explicate the
actions that firms take to achieve enhanced profitability and competitive advantage.
Because a strategic orientation is a pattern of past or intended decisions, guiding
the firm’s ongoing alignment with its external environment and shaping internal

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36,1

procedures and policies, a firm may apply multiple orientation decisions at the same
time to fulfill its strategic goals.

Testa and Iraldo (2010) introduce two strategic orientations that favor the adoption
of green supply chain management practices by firms. We consider an eco-reputation
strategic orientation, a strategy designed to make all stakeholders (customers,
suppliers, society) aware of the firm’s efforts to implement eco-friendly systems
and thus enhance its corporate image. We also note an eco-innovation strategic
orientation, a strategy that guides companies to develop innovative products and
operational processes that can improve their environmental performance. Companies
that are frontrunners in developing eco-friendly product and process innovations have
an opportunity to strengthen their leadership and differentiate themselves more from
their competitors.

An organization’s ecologically friendly strategic orientation thus comprises all
positioning strategies associated with a particular issue, such that greater integration

Strategic Orientations
(SO)

Eco-reputation SO

Eco-innovation SO

Sustainable Supply Chain
(SC)

Upstream SC

Green Purchasing

Downstream SC

Green Manufacturing
Green Packaging

Outcome

Reverse SC

Reverse Logistics

Strategic Choice Theory
• Firms have freedom of choice when formulating and implementing strategies.
• Strategic orientation focusses on firms’ strategic choices when facing external challenges.
• Strategic choice theory centers on the intra-organizational level and the provision of certain strategic capabilities.
• Firms use freedom of choice to influence firms’ orientation toward adopting sustainability initiatives.
• Ecological strategic orientation can influence the adoption of sustainable business practices.

Sustainable SCM Literature
• Sustainable SCs account for the environmental impacts
of products /services as they flow throughout the SC.
• Using reverse logistics as a SC business/environment
performance measure.
• Reverse logistics create tangible and intangible value.
• Firms obtain competitive advantages by quantifying
the efficiency/effectiveness of their SC actions.

Strategic Orientations
Sustainable Supply

Chain Initiatives
Outcome

Eco-Reputation
Strategic Orientation

(ERSO)

Eco-Innovation
Strategic Orientation

(EISO)

Green
Manufacturing (GM)

Green
Packaging (GK)

Green
Purchasing (GP)

Reverse Logistics
(RL)

H2a

H2b

H2c

H3a

H3b

H3c

H4a

H4b

H4c
Figure 1.

Research model
and hypotheses

Sustainable
supply chain
initiatives

and formulation of positioning strategies should enable them to influence the firm’s
sustainable business practices. That is, eco-reputation and eco-innovation strategic
orientations should be mutually interdependent:

H1. An eco-reputation strategic orientation correlates positively with an eco-innovation
strategic orientation.

3.2 Eco-reputation antecedents of supply chain initiatives
Organizations may adopt sustainable business practices in response to the
expectations of stakeholders. For example, such efforts appeal to consumers as they
become increasingly aware of the need to protect the environment, such that they might
expand the product’s unique selling points and boost corporate reputation.
An eco-reputation strategic orientation also provides a buffer against short-term
performance demands, such that managers can take a longer-term view and
experiment with new strategies to enhance the firm’s reputation (Zhu and Sarkis, 2007).
Ecologically friendly investments are significant expenditures with long return terms,
so firms with an eco-reputation strategic orientation should be better able to make such
investments (Fabbe-Costes et al., 2014; Hoejmose et al., 2013).

Toyota enjoys a strong eco-reputation, considering its top position on the Global 50
Green Brands List (Interbrand, 2013). As an auto manufacturer, Toyota regards its
eco-reputation as its most important strategic resource; it has made large strides in
reducing energy consumption, water use, waste, and toxic emissions (Chan et al., 2012).
Toyota also successfully shares its eco-reputation strategic orientation with its
suppliers; by working with them, Toyota exploits eco-reputation to not only create a
positive image among consumers but also make profit from them, as evidenced by the
economic success of its hybrid-electric Prius and its collaboration to produce the
all-electric Tesla. Half of all Americans consider the ecological impacts of the products
and services they buy (Leiserowitz et al., 2013), and a firm’s eco-reputation represents
an important criterion for purchasing decisions. Many global firms therefore strategize
to develop and maintain environmental reputations. For example, 3M launched an
ecologically friendly version of its post-it notes made from recycled paper and started
packaging large post-it packs in recyclable cartons instead of plastic wrap.

An eco-reputation strategic orientation grants managers the ability to invest capital
to sustain their supply chain programs and wait to reap longer-term reputation benefits
from their deployment (Huq et al., 2014). Eco-reputation is not an optional or low
priority strategic orientation; it becomes the key to a company’s image. Therefore, this
strategic orientation not some nice-to-have “add-on” but rather a core business
philosophy that weaves throughout the company and radiates outward throughout the
entire supply chain and its activities ( Jerónimo et al., 2013). We posit:

H2. An eco-reputation strategic orientation has a positive effect on a firm’s
deployment of (a) green purchasing; (b) green manufacturing; and (c) green
packaging.

3.3 Eco-innovation antecedent of supply chain initiatives
According to Teece (2007), eco-innovation is the firm’s ability to integrate, establish,
and reconfigure external and internal, environmentally friendly capabilities.
Specifically, eco-innovation requires the development of new value through more
efficient and effective environmentally friendly products, services, and processes.
Product eco-innovation focusses on the creation of new products or improvement of
existing products to meet environmental concerns; process eco-innovation focusses on

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the creation and implementation of innovative or substantially improved production or
delivery methods (Blome et al., 2014).

Many global enterprises and governments use the term eco-innovation to emphasize
the contributions of business to sustainable development while also improving
competitiveness. For example, the European Commission launched the eco-innovation
action plan (EcoAP) in 2011 to promote eco-innovation development across Europe.
The EcoAP is a significant milestone, moving the European Union beyond ecologically
friendly technologies and further fostering a comprehensive range of eco-innovative
business activities. The long-term objective will focus on initiating and maintaining
stronger, broader eco-innovation awareness across, and beyond European Union.

In a supply chain context, an eco-innovation strategic orientation guides firms to
develop products and improve processes using product life-cycle viewpoints, as well as
apply stricter environmental requirements for suppliers. Such a strategy requires
environmental competencies and integrates relevant ecological activities, such as
purchasing, manufacturing, and packaging, to improve current product and process
developments (Chen and Hung, 2014). Therefore an eco-innovation strategy motivates
firms to commit extra resources and cultivate innovative capabilities to build supply
chain sustainability. To reach this goal, firms must develop innovative technologies
that reflect the industry-specific characteristics and nature of the business, which
likely differ from current practices, to improve their environmental performance
(Saeed et al., 2014; Hoejmose, et al., 2013). Therefore, we posit:

H3. An eco-innovation strategic orientation has a positive effect on a firm’s deployment
of (a) green purchasing; (b) green manufacturing; and (c) green packaging.

3.4 Reverse logistics outcomes
Manufacturing companies have become increasingly responsible for collecting,
dismantling, and upgrading used products and packaging materials (Zhu et al., 2012).
Reverse logistics is inherently green and ecologically friendly, because repairing,
refurbishing, or recycling a product instead of throwing it in a landfill protects the
environment. Through reverse logistics, returned goods can be put back into inventory
again, re-sold at liquidation centers, or broken down to component parts for sale
(Aitken and Harrison, 2013) – all steps that can cut costs, increase profits, reduce
negative impacts on the environment, minimize liabilities, and improve customer
relationship (Chavez et al., 2013). Resource commitments to reverse logistics thus
should be a priority (Zailani et al., 2012), because of their potential for enhancing
performance through new value creation and offering strategic means to develop
lasting linkages with customers and positive firm images. These reverse flows differ
from standard, outbound operations and need special handling, likely requiring
additional resource allocations throughout the product lifecycle. Allocating sufficient
resources to support sustainable supply chain initiatives constitutes one of the
principle antecedents of strong reverse logistics programs. Reverse logistics also
depend heavily on reversing the sustainable supply chain, to enable firms to identify
and categorize returned products, components, and packaging materials correctly for
disposition, whether used or unused.

Reverse logistics is a continuous, embedded process, not just a one-time occurrence,
such that it entails a built-in process (De Brito and Dekker, 2004). By affecting many
components of the manufacturing process, reverse logistics expands the
responsibilities of the supply chain. Therefore, reverse logistics demands a thorough
reexamination of product life cycles to determine the amount of energy or waste

Sustainable
supply chain
initiatives

consumed and generated by each product in every stage. The successful
implementation of reverse logistics requires a comprehensive review of operational
processes at every level of the company – from raw material procurement to packaging
(Meade and Sarkis, 2002; Murphy and Poist, 2003).

Accordingly, firms need to implement at least the following strategies into each
supply chain activity to make their reverse logistics work:

(1) Green purchasing: the procurement of environmentally friendly materials alters
purchasing requirements and expands the related criteria (Min and Galle, 2001).
green purchasing promotes recycling and the reclamation of purchased materials,
which creates value if used or unwanted products can be recollected. However,
non-returnable products often are less expensive to produce, and virgin materials
tend to be priced equal to or lower than recycled materials (Walton et al., 1998).

(2) Green manufacturing: research and development can design specifications for
environmentally friendly products, and firms can reengineer their
manufacturing and production processes to rely on the addition of recyclable
materials as part of the process. Green manufacturing considers environmental
impacts throughout the product lifecycle, including the sale of used, unsold, or
returned products in secondary markets (Van Hoek, 1999).

(3) Green packaging: examining current packaging can reveal possible changes
and the potential of gathering leftover packaging or using less packaging
(González-Torre et al., 2004). Green packaging addresses all packaging issues,
including size, shape, and materials. Because reverse logistics entails a process
of continuously taking back products or packaging materials to avoid
environmental damages, it entails not just the use of recycled or recyclable
materials but also the impacts of packaging on distribution arrangements,
such as loading and handling efficiency and space utilization. The packaging
used must be less costly, easy to handle, and environmentally friendly
(Wu and Dunn, 1995). Because greener packaging can reduce reverse logistics
costs, a positive relationship likely exists between the deployment of
sustainable supply chain initiatives and reverse logistics.

Adding sustainability concepts for reverse logistics leads to a comprehensive framework
for integrating green purchasing, green manufacturing, and green packaging
(De Brito and Dekker, 2004). This model also acknowledges that modern customers
prioritize sustainability factors in their strategic agendas in both production and service
sectors (Murphy and Poist, 2000). Firms developing ecologically friendly reverse logistics
networks can minimize the cost of returns, focus on designing recyclable packaging and
pallets, reduce unnecessary deliveries, and exploit green materials for product design
(Rogers and Tibben‐Lembke, 2001). Therefore, we hypothesize:

H4. A firm’s reverse logistic outcomes are positively associated with the deployment
of (a) green purchasing; (b) green manufacturing; and (c) green packaging.

4. Methods
4.1 Sample
We conducted survey in Malaysia among all EMS ISO 14001 – certified firms. By
selecting firms with this certification, we ensure that the respondents have embarked,
at least to some extent, on the adoption of sustainable supply chain initiatives. Of the

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36,1

2,255 manufacturing firms in Malaysia, 342 companies had obtained ISO 14001
certification. To obtain reliable data from this limited sample, we applied census
sampling methods and requested that all 342 companies participate by providing input
about their practices.

4.2 Respondents
We received 125 completed questionnaires, for a response rate of approximately
36.5 percent. We describe the responding firms in Table I.

4.3 Measures
We used multiple indicators to measure each research construct based on relevant
literature. The Appendix details the survey instrument. Eco-reputation strategic
orientation is the extent to which the firm maintains its environmental reputation
throughout the product lifecycle. The five measurement items came from Testa and
Iraldo (2010). Eco-innovation strategic orientation is company awareness, as reflected by
its adoption of new ideals and strategies in its supply chain practices. These six
measurement items came from Testa and Iraldo (2010). For both eco-reputation and
eco-innovation strategic orientations, respondents used five-point Likert scales
(1¼ “strongly disagree,” 5¼ “strongly agree”). Green purchasing practices include raw
materials and components content requirements and restrictions, content labeling or
disclosure, supplier questionnaires, supplier EMS certification, and supplier compliance
audits. Six measurement items were adapted from Hammer (2006). Green manufacturing
entails production activities applied to the process, such that inputs have relatively low
negative environmental impact, are highly efficient, and generate little pollution. Seven
relevant items were adopted from Ninlawan et al. (2010) and Zhu et al. (2007). Green

Description Categories Frequency %

Ownership of firm Malaysian fully owned 26 20.8
Joint venture 99 79.2

Number of employees Less than 100 12 9.6
100-250 2 1.6
251-500 17 13.6
501-1000 20 16.0
More than 1,000 74 59.2

Age of the firm Less than 6 years 26 20.8
6-10 years 14 11.2
11-15 years 7 5.6
More than 15 years 78 62.4

Type of products Consumer products 66 52.8
Industrial products 48 38.4
Combination/others 11 8.8

Major source for key materials and components Domestic 11 8.8
Regional/Asian 20 16.0
Global 94 75.2

Number of suppliers for key materials and components Single supplier 6 4.8
2-5 suppliers 31 24.8
6-10 supplier 9 7.2
More than 10 suppliers 79 63.2

Note: n¼ 125

Table I.
Respondent profile

information

Sustainable
supply chain
initiatives

packaging includes characteristics such as size, shape, weight, and materials being used.
We adapted four measurement items from Ninlawan et al. (2010). A five-point Likert scale
measured the three sustainable supply chain initiatives (1¼ “not at all,” 5¼ “very high
extent”). Reverse logistics is the process of retrieving products from end consumers, to
capture value or ensure proper disposal. We took seven items from Ninlawan et al. (2010)
and used a five-point Likert scale (1¼ “not at all,” 5¼ “very high extent”) to assess the
implementation of reverse logistics in each firm.

5. Results
Figure 2 depicts the measurement models and Table II provides the descriptive statistics
and zero-order correlation matrix for the six latent variables. The Cronbach’s α statistics
for the constructs range from 0.904 (eco-reputation) to 0.975 (green manufacturing,
reverse logistics), so the scales appear sufficiently reliable. The composite reliability
statistics range from 0.890 (eco-reputation) to 0.972 (green manufacturing); the minimum
AVE of 0.619 (eco-reputation) also exceeds the threshold value of 0.50.

In Figure 2, the CFA results show that the large and significant standardized
loadings of each measured item on its construct offer evidence of convergent validity.
The AVE statistics indicate excellent convergent validity. All the correlation
coefficients are significant and less than 0.5, in support of discriminant validity.
A more rigorous structural equation model approach is the χ2 difference test between
a constrained and unconstrained model for each pair of constructs. Table III summarizes
the results of these χ2 difference tests, which confirm the discriminant validity of the six
constructs. Nomological validity also is supported, according to the various model fit
indices in Figure 3.

Figure 3 also shows that eco-reputation strategic orientation has a positive effect on
sustainable supply chain initiative components, in support of H2. Specifically, an
eco-reputation strategic orientation related strongly to the deployment of green
purchasing ( β¼ 0.33, po0.05), green manufacturing ( β¼ 0.22, po0.05), and
green packaging ( β¼ 0.28, po0.05). Our results also offer broad support for H3;
eco-innovation strategic orientation related positively to the deployment of green
purchasing ( β¼ 0.26, po0.05), green manufacturing ( β¼ 0.35, po0.05), and
green packaging ( β¼ 0.42, po0.05).

The results provide strong evidence of the positive impact of reverse logistics in terms of
sustaining firms’ supply chain initiatives, though these effects differ according to the
individual sustainable supply chain initiative components. Specifically, in line withH4b and
H4c, green manufacturing (β¼ 0.26, po0.05) and green packaging (β¼ 0.19, po0.05)
initiatives positively affect firms’ reverse logistics outcomes. However, green purchasing
(β¼ 0.08, pW0.05) initiatives exhibited no significant relationship with reverse logistics
outcomes, so we cannot confirm H4a. These findings suggest that green manufacturing
and packaging initiatives are more effective in differentiating firms’ reverse logistic
outcomes than are green purchasing initiatives. Perhaps green purchased materials simply
are less visible in reverse logistics than are green manufacturing and green packaging.

6. Discussion
Most emerging countries have undergone rapid economic development quickly.
The downside to this rapid growth is the host of environmental pollution problems that
have arisen and are of serious global concern. In response, this study makes three
important contributions. First, by collecting empirical data from Malaysia, a major
emerging country, we demonstrate for the first time the specific effects of each

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36,1

sustainable supply chain initiative on reverse logistics in a developing economy.
Second, we extend prior research on the role of performance measures in green supply
chain management and uncover how reverse logistics create competitive advantages.
Third, we examine two unique, previously untested drivers of green supply chain

0.01

0.36

0.51

0.25

0.27

0.80

0.70

0.87

0.86

0.02 C6

0.99
0.01

0.23

0.00

0.09

0.27

0.16

0.35

1.00

0.95

0.85

0.92

0.81

0.19 D6

0.90

0.11 D7

0.94

0.27

0.07

0.06

Eco-Reputation Strategic Orientation (ERSO) Eco-Innovation Strategic Orientation (EISO)

Green Purchasing Initiative (GP) Green Manufacturing Initiative (GM)

ERSO

0.55

0.45

0.23
0.35

0.32

0.17

0.67

0.74

0.88

0.80

0.82

0.23

EISO

0.16
0.16

0.49

0.11

0.00

0.13

0.92

0.91

0.72

0.94
1.00

0.16 B6

0.92
0.07

0.08

0.15

0.12

0.06

0.28

0.04

0.94

0.97

0.85

0.98
RL

0.27

0.24

0.01
0.00
0.15

0.85
0.87
0.99
1.00
0.92

0.23 F6

0.88

0.03

0.24

Green Packaging Initiative (GK) Reverse Logistics (RL)

�2/df=0.74 /3=0.25, p-value=0.86, RMSEA = 0.000
NFI=1.00, CFI=1.00, RFI=1.00, AGFI=0.99
Cronbach’s �=0.904, CR=0.890, AVE=0.619

�2/df=0.75 /5=0.15, p-value=0.98, RMSEA=0.000
NFI=1.00, CFI=1.00, RFI=1.00, AGFI=0.99
Cronbach’s �=0.969, CR=0.964, AVE=0.820

�2/df=7.60 /7=1.09, p-value=0.37, RMSEA=0.026
NFI=0.99, CFI=1.00, RFI=0.99, AGFI=0.94
Cronbach’s �=0.953, CR=0.950, AVE=0.764

�2/df=2.18 /11=0.20, p-value=0.998, RMSEA=0.000
NFI=1.00, CFI=1.00, RFI=1.00, AGFI=0.99
Cronbach’s �=0.975, CR=0.972, AVE=0.833

�2/df=3.71/2=1.86, p-value=0.16, RMSEA=0.083
NFI=0.99, CFI=1.00, RFI=0.98, AGFI=0.93
Cronbach’s �=0.964, CR=0.966, AVE=0.875

�2/df=3.79/7=0.54, p-value=0.80, RMSEA=0.000
NFI=1.00, CFI=1.00, RFI=0.99, AGFI=0.97
Cronbach’s �=0.975, CR=0.971, AVE=0.850

Notes: �, Cronbach’s �. CR, composite reliability = (�c) = (Σ�)2/ [(Σ�)2+Σ(�)].
AVE, average variance extracted = (�v) = (Σ�2) / [Σ�2+Σ(�)]. where � is the
indicator loadings, and � is the indicator error variances

Figure 2.
Measurement models

99
Sustainable
supply chain
initiatives

initiatives, eco-reputation strategic orientation and eco-innovation strategic orientation.
The results offer useful theoretical and managerial implications.

Advancing sustainable business practices has the potential to help manufacturing
firms in Malaysia manage their competing goals of profit growth and environmental
protection. Although this model was developed in Malaysia, the findings should apply
to firms in other emerging countries too. Most emerging countries remain in an early
stage of economic development and face trade-offs between wealth creation and potential
negative effects on social and environmental conditions. Manufacturing firms’ apparent
efforts to pursue profit growth at all costs is the leading cause for a country’s dismal
pollution record; unsustainable business practices lead to an array of environmental
problems. The information in this paper can help business leaders in emerging markets
develop sustainable supply chain activities that ensure their business success, through
reverse logistics. Business leaders in emerging countries also should strengthen their
eco-strategic orientation and develop sustainable business practices to enhance
their implementation of reverse logistics, which can help them fulfill their
environmental responsibilities. Building a sustainable business culture is a long
process, but manufacturing firms’ ability to advance sustainable business practices

Mean
( µ)

SD
(σ) ERSO EISO GP GM GK RL

ERSO correlation coefficient
significant (2-tailed) 3.122 0.889 1.000
EISO correlation coefficient
significant (2-tailed) 2.665 0.908 0.351 (0.000) 1.000
GP correlation coefficient
significant (2-tailed) 3.031 1.033 0.396 (0.000) 0.372 (0.000) 1.000
GM correlation coefficient
significant (2-tailed) 2.898 1.027 0.291 (0.000) 0.386 (0.000) 0.281 (0.000) 1.000
GK correlation coefficient
significant (2-tailed) 2.822 0.983 0.387 (0.000) 0.439 (0.000) 0.418 (0.000) 0.362 (0.000) 1.000
RL correlation coefficient
significant (2-tailed) 3.008 1.043 0.322 (0.000) 0.330 (0.000) 0.251 (0.000) 0.284 (0.000) 0.305 (0.000) 1.000

Table II.
Descriptive statistics
and correlations of
the constructs

Constrained model Unconstrained model χ2 Difference test, df¼ 1
Paired analysis χ2 df χ2 df χ2 diff. p-value

ERSO-EISO 50.42 38 39.16 37 11.26 0.0008
ERSO-GP 108.65 40 100.82 39 7.83 0.0051
ERSO-GM 50.51 49 39.40 48 11.11 0.0009
ERSO-GK 49.43 25 39.60 24 9.83 0.0017
ERSO-RL 60.11 40 51.52 39 8.59 0.0034
EISO-GP 128.24 48 118.84 47 9.40 0.0022
EISO-GM 53.46 58 43.58 57 9.88 0.0017
EISO-GK 40.22 31 32.04 30 8.18 0.0042
EISO-RL 59.17 48 49.00 47 10.17 0.0014
GP-GM 73.49 60 63.56 59 9.93 0.0016
GP-GK 61.41 33 55.61 32 5.80 0.0160
GP-RL 149.83 50 140.58 49 9.25 0.0024
GM-GK 36.17 41 26.00 40 10.17 0.0014
GM-RL 46.19 60 36.71 59 9.48 0.0021
GK-RL 55.58 33 44.82 32 10.76 0.0010

Table III.
Discriminant
validity test

100

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36,1

ultimately could contribute to their competitiveness by enhancing their firms’ reputation
and increasing consumer confidence at both international and national levels.

Eco-reputation strategic orientation and eco-innovation strategic orientation can
enable sustainable supply chain initiatives. Our results show that eco-reputation
strategic orientation is positively associated with sustainable supply chain initiatives;
an eco-innovation strategic orientation suggests that sustainable supply chain
initiatives are less risky than failing to adopt such practices. In addition, when the
firm has both an eco-reputation and an eco-innovation strategic orientation, the two
strategic orientations positively affect each other. Most studies of the drivers of
organizational sustainability efforts empirically examine only the independent effects
of the antecedent variables; our results suggest the antecedents also can interact in
their effects, so they enhance understanding of when and why firms engage
in sustainable activities. Incorporating bi-directional relationships thus can enhance
knowledge of the drivers of organizational sustainable involvement. Furthermore,
most sustainable supply chain studies draw their conceptual framework from the
notion of institutional theory, with the assumption that external institutional forces
motivate a company’s implementation of sustainable initiatives (Kauppi, 2013).
Our findings suggest that the enablers of sustainable business practices may not be
as divergent as has commonly been assumed. Instead, engaging in sustainable
supply chain initiatives might combine the organization’s overall strategic
orientations with respect to the natural environment and deliver environmental
benefits (Stonebraker and Liao, 2004).

The results highlight the potential value of simultaneously examining different
components of sustainable supply chain initiatives. The limited research in
developing economy domains tends to focussed on a single aspect of sustainable
supply chain initiatives. Our analyses reveal relatively strong positive correlations
among the three different sustainable supply chain initiatives (Table II) but also
indicate that each initiative can have different impacts on outcomes in different
conditions. Empirical research on sustainable supply chain management should
allow for this possibility.

Sustainable Supply
Chain Initiatives

OutcomeStrategic Orientations

Eco-Reputation
Strategic Orientation
(ERSO)
Eco-Innovation
Strategic Orientation
(EISO)
Green
Manufacturing (GM)
Green
Packaging (GK)
Green
Purchasing (GP)
Reverse Logistics
(RL)

0.33

0.22

0.28

0.50

0.26

0.35

0.42

0.08
0.26

0.19

Insignificant path
Significant at �=2.5%

�2/df = 780.14/504 = 1.548, RMSEA = 0.066, NFI = 0.94, NNFI = 0.97, CFI = 0.97, IFI = 0.97, RFI = 0.93, PGFI = 0.62
ECVI: Model = 7.76, Saturated Model = 9.60, Independence Model = 123.10

CAIC: Model =1,310.51, Saturated Model = 3,467.85, Independence Model =15,395.17

Figure 3.
Results of structural

equation model

101

Sustainable
supply chain
initiatives

7. Management implications
This study also offers important new insights for managers. Figure 4 synthesizes the
results with their related managerial implications. Our findings offer needed empirical
support for investing in sustainable supply chain initiatives, and we offer strong
evidence of the benefits obtained from reverse logistics in sustainable supply chain
initiatives (Alblas et al., 2014). Managers can be confident that sustainable supply
chain initiatives will benefit their firms’ reverse logistics. Ecological requirements are
key criteria for products and production, particularly for companies that seek ways to
ensure economic sustainability by staying competitive and profitable. This study offers
empirical evidence that implementing sustainable supply chain initiatives leads to
reverse logistics, creating value, and a new source of competitive advantages
( Jayaraman and Luo, 2007).

For managers interested in developing sustainable supply chain initiatives, our
results also offer some alternatives. Decision makers in the firms attempting to nurture
sustainable supply chain initiatives should not overlook the importance of
eco-reputation and eco-innovation strategic orientations, which our results identify
as important enablers (Awaysheh and Klassen, 2010). In general, making sustainable
supply chain investments is easier if an ecological strategic orientation is a top priority
within the firm or top managers emphasize eco-friendly business practices as sources
of the company’s image (Roehrich et al., 2014). However, managers also need to attend
carefully to the bi-directional relationship between eco-innovation and eco-reputation
strategic orientation. In the presence of both, managers may find it easier and more
effective to emphasize green supply chain activities.

The significant reverse logistics benefits stemming from sustainable supply chain
initiatives suggest that manufacturing companies cannot only receive products back
from consumers but also collect unsold merchandise, to take apart, sort, reassemble, or
recycle. The returned product also can be re-sold in secondary channels and generate
revenue. Managers thus should emphasize the strategic benefits of sustainable supply
chain initiatives, rather than regarding reverse logistics as a cost center. They
also should place more emphasis on the benefits of environmental sustainability,
to encourage their firms to become environmentally sensitive.

8. Limitations and future studies
This research has some limitations, and our findings also suggest several avenues for
research. First, we collected most of the data from a single key informant in each
Malaysian company. The potential thus exists for key informant common method bias,
though we followed the recommendations by Phillips (1981) and used credible
respondents (i.e. EMRs) to minimize this threat. Further research employing
multi-informant designs or direct investigator observations might be useful though,
to confirm our results. Second, our sample included manufacturing companies in
Malaysia; we cannot guarantee that our results generalize to different industries.
This research was developed primarily among manufacturing firms, with little
consideration of the green supply chain behavior of service sectors. Thus, we
encourage further research to examine the applicability of our findings to service
sectors (Hill and Brown, 2007). Third, though we identify three components of
sustainable supply chain initiatives, other components could exist, and ongoing
research should investigate them. Forth, internal stakeholders, such as employers, are
critical to drive sustainable purchasing. However, the research design of our study
focusses on the firm’s strategic orientations in general; we do not aim to understand

102

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Managerial
implications

103

Sustainable
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each stakeholder’s behavior. Noting the importance of internal stakeholders, we now
address this concern as a potential future study. Fifth, we collected our sample from
certified manufacturing firms, which tend to be larger and relatively resource
abundant. Excluding small and medium-sized enterprises (SMEs) from our study might
bias our findings. The incentives for SMEs to develop sustainable supply chains thus
may differ from those that drive well-established firms. Moreover, with their limited
resources, their ability to implement reverse logistics is questionable. Further research
should test our results and validate our model using non-certified SMEs.

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Appendix. Survey instrument
I. Strategic orientations
This section assesses the strategic green orientations that firms use to implement green supply
chain initiatives. We ask respondents to indicate on a five-point Likert scale (1¼ strongly
disagree, 5¼ strongly agree) how the following focusses, concepts, and practices guide their
firm’s green supply chain initiatives in terms of green purchasing, green manufacturing, and
green packaging.

(A) Eco-reputation strategic orientation (ERSO)

A1. Our company is well-known for environmentally responsible and contributes in green
initiatives.

A2. Consumers recognize our company and products due to our involvement in various green
activities.

A3. Our company policy promotes green initiatives/activities and we have made good
progress.

A4. Our company respects environmental welfare and is committed to develop green products.
A5. We enhance our firm’s image and reputation through development of green initiatives.

(B) Eco-innovation strategic orientation (EISO)

B1. Our company allocates adequate resources for new green innovation initiatives/activities.
B2. Our top management emphasizes process and product innovation that promotes

green initiatives.
B3. Green life-cycle assessment is an important criterion while developing new products.
B4. Our company competes on innovative driven goals and green initiatives.
B5. Innovation culture is well-established in my company.
B6. Our company aggressively conducts training and education in innovation-based green

initiatives.

II. Sustainable supply chain initiatives

This section assesses the extent of existence of sustainable supply chain initiatives
(green purchasing, green manufacturing. and green packaging), We ask respondents to
indicate on a five point Likert scale (1¼ not at all, 5¼ very high extent) the existence of the
following initiatives in their firm.

Cl. Provides suppliers with design specifications that include green or environmental
requirements.

109

Sustainable
supply chain
initiatives

C2. Purchases materials from suppliers who are qualified in green partner environmental
standards.

C3. Audit suppliers regularly to ensure that they are in compliance with environmental
regulations.

C4. Requires key suppliers to be certified in EMS, such as ISO 14001.
C5. Ensure purchased components are free of undesirable items such as lead or hazardous

materials.
C6. Evaluates suppliers based on specific environmental criteria.

(D) Green manufacturing (GM)

D1. Produces products with reused or recycled contents such as recycled plastics and glass.
D2. Uses life-cycle assessment to evaluate the environmental load of products.
D3. Produces products that are free of hazardous substances, such as lead, mercury, and

chromium.
D4. Designs products to ensure they have recyclable or reusable contents.
D5. Produces products that reduce the consumption of materials and energy during use.
D6. Reduces power consumption in products during manufacturing and transportation.
D7. Increases product life-span resulting in higher efficiency and productivity.

(E) Green packaging (GK)

El. Makes sure that packaging uses renewable or recyclable contents.
E2. Makes sure that packaging is reusable.
E3. Minimizes the use of materials in packaging.
E4. Avoids or reduces the use of hazardous materials in packaging.

III. Reverse logistics
This section assesses the extent of reverse logistics implementation in the firm for the purpose of
reuse, recycle, or reclamation of materials from the product or packaging. We ask respondents to
indicate on a five-point Likert scale (1¼ not at all, 5¼ very high extent) the existence of reverse
logistics implementation in their firm.

(F) Reverse logistics (RL)

Fl. Collects used or unwanted products from customers for recycling, reclamation of materials,
or reuse.

F2. Collects used packaging from customers for reuse or recycling.
F3. Requires customers to collect packaging materials for us.
F4. Collects used or unwanted products from customers for remanufacturing.
F5. Collects shipping materials from customers for reuse or recycling.
F6. Returns products to customers after refill or repair.

Corresponding author
Dr Chin-Chun Hsu can be contacted at: vincent.hsu@unlv.edu

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Outline placeholder

Appendix.Survey instrument

lable at ScienceDirect

Journal of Cleaner Production 129 (2016) 608e621

Contents lists avai

Journal of Cleaner Production

journal homepage: www.elsevier .com/locate/ jc lepro

Critical success factors for reverse logistics in Indian industries: a
structural model

Sachin Kumar Mangla a, Kannan Govindan b, *, Sunil Luthra c

a Department of Mechanical Engineering, Graphic Era University, Dehradun, India
b Center for Sustainable Engineering Operations Management, Department of Technology and Innovation, University of Southern Denmark, Denmark
c Department of Mechanical Engineering, Government Polytechnic, Jhajjar, Haryana, India

a r t i c l e i n f o

Article history:
Received 22 February 20

Received in revised form
22 February 2016
Accepted 16 March 2016
Available online 12 April 2016

Keywords:
Reverse logistics (RL)
Critical success factors (CSFs)
Sustainability
AHP
DEMATEL
Indian manufacturing industries

* Corresponding author.
E-mail address: kgov@iti.sdu.dk (K. Govindan).

http://dx.doi.org/10.1016/j.jclepro.2016.03.124
0959-6526/

a b s t r a c t

Industries face significant pressures to enact eco-friendly practices in their supply chain due to the
constraints of natural resources and growing ecological awareness among customers. Reverse logistics
(RL) has been considered as a systematic approach for industries to improve their environmental impacts
and to ensure sustainability in business. Industries are enthusiastic to adopt RL activities in their busi-
nesses, but they also face challenges such as insufficient knowledge and resources regarding RL imple-
mentation. Therefore, we seek to evaluate the critical success factors (CSFs) linked to the implementation
of RL in manufacturing industries in India. In this work, a structural model is proposed by using
Analytical Hierarchy Process (AHP) and Decision Making Trial and Evaluation Laboratory (DEMATEL)
methods to evaluate the CSFs in RL adoption. The AHP methodology assists in establishing the priorities
of the CSFs, while the DEMATEL approach categorizes the causal relationships among them. The findings
of this work shows that the Global competitiveness main factor is highly prioritized, and thus, needs to
be focused greatly in order to increase the effectiveness of RL adoption in business. The relative priority
of the remaining main factors through AHP analysis is given as Regulatory factors – HR and organizational
factors -Economic factors – Strategic factors. The findings also indicate that Global competitiveness;
Regulatory; HR and organizational main factors are classified under cause group, while Economic and
Strategic main factors belong to effect group. This model will help business analysts and supply chain
managers formulate both short-term and long-term, flexible decision strategies for successfully man-
aging and implementing RL adoption in the supply chain scenarios.

1. Introduction

Conservation of the environment has taken a prime position
among areas of concern for managers and practitioners all across
the globe. Likewise, customers are more environmentally
conscious, which creates a demand for industries to adopt clean,
green, eco-friendly processes for their businesses (Millet, 2011;
Sarkis et al., 2011; Almeida et al., 2013; Seuring and Gold, 2013;
Luthra et al., 2014a, 2015a; Gandhi et al., 2015). Growing
competitive and financial pressures, diminishing product life cy-
cles, and stringent environmental rules have increased the
attention paid to green and Reverse Logistics (RL) activities that
industries embrace to improve their environmental impacts

(Subramoniam et al., 2009; Chan et al., 2012; Mangla et al., 2013;
Zhu and Geng, 2013). RL comprises all operations related to the
recovery and reuse of products and materials, and proves to be a
rational instrument for industries to improve their firms’ sus-
tainability in terms of ecological, economic, and social gains
(Schwartz, 2000; Sarkis, 2003, 2010; Zhang et al., 2011; Nikolaou
et al., 2013; Abdulrahman et al., 2014). In addition, RL opera-
tions and its related practices are also proven to be crucial in
reducing operational expenses (PricewaterhouseCoopers’ report,
2008). RL has gained attention among business organizations as
an effective, strategic approach to improving profitability, product
lifecycles, supply chain complexity, consumer preferences, and
reducing environmental impact (Thierry et al., 1995; Fleischmann
et al., 1997; Carter and Ellram, 1998; Van Hoek, 1999; Stock, 1998,
2001; Toffel, 2003; Neto et al., 2008; Tsai et al., 2009; Hu and
Bidanda, 2009; Gunasekaran and Spalanzani, 2012; Govindan
et al., 2015).

Delta:1_given name

Delta:1_surname

Delta:1_given name

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S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621 609

However, the adoption and implementation of RL practices is
relatively difficult from industrial viewpoints. Many industries are
comparatively less familiar with how to initiate RL and what ben-
efits could be realized through implementing RL practices (Chan
and Kai Chan, 2008). To deal with this uncertainty, scholars and
practitioners have tried to isolate the important determinants of
initiation and implementation of RL among industries (Vijayan
et al., 2014).

Several factors are vital to the successful implementation of RL
in business, such as management commitment, globalization, reg-
ulations, consumer requirements, financial resources, competi-
tiveness, and benchmarking (Jindal and Sangwan, 2011; Chio et al.,
2012; Mangla et al., 2013). Given that these factors are critical for
industries in order to adopt RL efficiently (Chio et al., 2012), we
need to identify and evaluate the various Critical Success Factors
(CSFs) required for the implementation of RL practices in the in-
dustrial supply chain.

The goal of this work is to evaluate the CSFs related to initiation
and implementation of RL on tactical (or operational) and strategic
levels in business. It is no surprise that different industries may
exhibit different perceptions in adopting RL practices in their
respective businesses (Srivastava and Srivastava, 2006). To
acknowledge these considerations and to achieve the above
formulated objectives, a two phase-methodology is introduced and
used in this work. In the first phase, various CSFs that assist in the
implementation of RL from the industrial viewpoint are deter-
mined. For this phase, several different industries operational in the
western region of India were examined. A literature survey and
discussions from industrial experts resulted in a collection of the
most commonly accepted RL implementation CSFs. In the second
phase, the finalized common RL implementation CSFs were sub-
jected to evaluation, using Analytical Hierarchy Process (AHP) and
Decision Making Trial and Evaluation Laboratory (DEMATEL)
methods, through the input of industry and field experts. The AHP
method (Saaty, 1980) helps to prioritize or to identify the essential
RL implementation CSFs. On the other hand, the DEMATEL method
(Gabus and Fontela, 1972) is used to study the interrelationships
between the RL implementation CSFs with the help of a causal map.
It assists practicing managers and policy makers to prepare both
short-term and long-term flexible decision strategies that will
prove beneficial for performance improvements of RL imple-
mentation from an industrial perspective.

The remainder of the paper is arranged as follows. Literature
relevant to this work is discussed in Section 2. Section 3 provides
detail on the proposed research methods. The proposed research
framework is given in Section 4, and its application to Indian
manufacturing industries is presented in Section 5. Next, Section 6
identifies results obtained from the research and their implications.
Finally, research conclusions are presented in Section 7, along with
limitations and scope for future work.

2. Relevant literature

The present section includes the literature on RL implementa-
tion in industries in Indian context, RL implementation factors, and
draws the research gaps for this study.

2.1. Industrial RL implementation in India

RL can be expressed as the process of planning, implementing,
and regulating the efficient and cost effective flow of rawmaterials,
in-process inventory, finished goods, and related information from
the point of consumption to the point of origin for the purpose of
recapturing value or proper disposal (Rogers and Tibben-Lembke,
2001; De Brito and Dekker, 2004; Blumberg, 2005; Meade et al.,

2007; Wadhwa et al., 2009). With regard to the adoption and
implementation of RL initiatives, Abdulrahman et al. (2014) argued
that RL literature in developing countries context is still in its in-
fancy state. India accounts for approximately 17.5% of the world’s
population. Due to industrialization, manufacturing industries are
growing at a rapid pace, leading to the generation of a huge amount
of hazardous and non-hazardous waste. According to Comptroller
and Auditor- General’s (CAG) report, over 7.2 MT of industrial or
hazardous waste was generated in India in 2000, out of which 1.4
million tonswas recyclable, 0.1 million tons was incinerateable, and
5.2 million tons was destined for disposal on land (MoEF, 2000). In
addition, India Central Pollution Control Board (CPCB, 2000)
documented that some 41,523 industries in the country generate
about 7.90 million tons of hazardous/industrial waste every year, of
which recyclable hazardous waste is 3.98 million tons (50.38%),
landfill waste is 3.32 million tons (42.02%), and incinerateable
waste is 0.60 million tons (7.60%). The waste sector in India has
evolved greatly in last 15 years (from 2000 onwards) and waste is
generated in several forms such as industrial waste, e-waste, and
bio medical waste, municipal waste. According to the report of
Novonous waste management market in India is expected to be
worth US$ 13.62 billion by 2025. It is expected that. E-waste
management market is likely to grow at a compound annual
growth rate (CAGR) of 10.03% by 2025. Bio medical waste man-
agement market may grow at a CAGR of 8.41% (Novonous, 2014). In
addition, the generation andmanagement of Municipal SolidWaste
(MSW) is also becoming a serious problem for India. Indian MSW
management market is likely to grow at a CAGR of 7.14% by 2025.
Based on the latest report of CPCB (CPCB, 2014) 1, 27,486 Tons per
day (TPD) of MSW was generated in India in 2011e12. Of which,
only 15,881 TPD (12.50%) was processed for eco-friendly disposal
(MoEF, 2012e13). Recently, Kannan et al. (2016) suggested that
formal recycling of e-waste could contribute to sustainable society.

From these numbers, we can conclude that there is a substantial
scope of RL implementation within Indian industries that, if
implemented, would be crucial not only in reducing the amount of
waste but also in improving organizational, ecological, financial,
and competitive performance levels (MoEF, 2012e13).

RL is distinguished as a crucial means to lower the waste gen-
eration and to prevent pollution by managing the environmental
burden of products after their end-of-life (Ravi, 2012). However, the
concept of RL is not as popular among Indian business organiza-
tions (Ravi et al., 2005; Hung Lau and Wang, 2009; Sharma et al.,
2011). In India, this hesitance may be due to lack of support from
top management and other business partners; these decision
makers are often not ready to spend more money to implement RL
solutions after investing large amounts of capital to set up the fa-
cility and infrastructure (Ravi et al., 2005). Also, governmental
support has an influence on the strategic decision of RL imple-
mentation for any organization. Analyzing some RL studies relevant
to Indian contexts, Jindal and Sangwan (2011) listed and analyzed
sixteen barriers to the implementation of RL through their litera-
ture studies. They find that RL practices can play an important role
in achieving sustainability in Indian business contexts. In their
study, Sharma et al. (2011) analyzed barriers in context to Indian
industries for RL implementation and segregated factors into
driving factors and driven factors. Srivastava and Srivastava (2006)
examined several categories of products in order to make a sys-
tematic understanding of the possibility of implementing RL in
Indian context. Ravi et al. (2005) described the management of RL
operations by investigating a paper industry. Pati et al. (2008)
presented a mixed integer goal programming model to help in
the appropriate management of the RL system through paper
recycling in India. Govindan et al. (2012) analyzed third party RL
providers with the help of interpretive structural modeling by

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621610

taking a case study from a tire company. Diabat et al. (2013)
examined the interaction among major barriers hindering the
implementation of third-party logistics in Indian manufacturing
industries. Lack of qualification for employees in third-party lo-
gistics provider and fear of employees of the firm have been found
as the most hindering barriers in implementation of third-party
logistics. Mangla et al. (2013) recognized and analyzed fourteen
variables related to the handling and returning of products by
closing the loop of a green focused supply chain in paper mill in-
dustries in an Indian perspective. Researchers have determined
that the different variables associated with the initiation and or
implementation of product recovery activities (i.e., RL initiatives)
are important to distinguish, and their subsequent analysis may
help the decision makers to achieve higher ecological-economic
benefits (Mangla et al., 2012).

In addition, in the 12th Five Years Plan (2012e2017), it appears
that RL is being practiced in India, but it is still in unorganized
sectors and not much consideration is given to improving envi-
ronmental performances. Under these considerations, Critical
Success Factors (CSFs) of RL implementation need to be identified
and analyzed more rigorously. This step would help industries in
India to implement RL in their respective businesses, and to
approach RL in a more organized chain. It will further assist Indian
industries to improve their economical, social, and environmental
performances, and it should strengthen sustainability in business
(Jindal and Sangwan, 2011).

2.2. RL implementation factors

Gonz�alez-Benito and Gonz�alez-Benito (2006) confirmed that
pressure from stakeholders and the values and beliefs endorsed by
the manager’s environmental awareness leads more quickly to the
implementation of eco-friendly practices in logistics operations. It
also reveals the fact that the organizations with environmentally
aware managers tend not to follow a reactive approach; instead,
they are more proactive towards eco-friendly requirements. How-
ever, in accordance with the study conducted by Chio et al. (2012),
the successful implementation of RL leads to improvisation in the
organization’s performance, financial position, and competitive
advantage. In the same work, these authors also insist that a suc-
cessful implementation of RL is only possiblewith topmanagement
support and commitments. The foremost requirement of all is the
integration of every function for a smooth flow of material in both
(forward and reverse) directions.

Nevertheless, there are several external and internal factors
governing the effective and efficient implementation of RL prac-
tices in the supply chain. Some of the external and internal factors
suggested by researchers are government regulations, customer
demand, policy entrepreneurs, support of top management,
stakeholder commitment, incentive systems, quality of inputs, and
vertical integration (Srivastava, 2008; Hung Lau and Wang, 2009;
Tsai et al., 2009; Rahman and Subramanian, 2012; Dowlatshahi,
2012). Ho et al. (2012) concluded that internal and external fac-
tors significantly influence RL. They suggest that financial and hu-
man resources play an important role in companies’
implementation of RL, whereas tangible resources do not have
much influence on the practice. They also declare that companies
with excellent collaboration and relationship with other business
partners can make use of RL more effectively and efficiently (Ho
et al., 2012). Rogers and Tibben-Lembke (1999) identified several
key RL management elements, including asset recovery, compact-
ing disposition cycle time, centralized return centers, gate keeping,
zero returns, negotiation, RL information systems, remanufacture
and refurbishment, financial management, and outsourcing. Carter

and Ellram (1998) listed some critical RL implementation factors
given as regulations, customer demand, policy entrepreneurs, and
so forth.

It has been stated that the critical (key) success factor theory
enables managers to know the importance of process improvement
for their company (Grimm et al., 2014). The theory of critical suc-
cess factors is primarily based on strategy research, which recog-
nizes the functions, activities, and measures to improve a
company’s competitive advantage from an organizational supply
chain context (Dinter, 2013; Vasconcellos and S�a, 1988). Hence, it is
important to align Critical Success Factors (CSFs) with the firm’s
desired outcome. However, constant supervision is required to
recognize CSF and its relevant activities to support decision making
and to develop high performance management systems, especially
in supply chains (Bai and Sarkis, 2012). Therefore, the identification
of CSF in terms of both how and why is important steps in adopting
and implementing RL initiatives from a supply chain context.

2.3. Research gaps

The benefits of RL implementation are not yet fully realized in
some of the world’s emerging economies. The adoption and
implementation of RL practices is also relatively difficult frommany
industrial viewpoints (Prakash and Brua, 2015). While a lot of
attention has been paid to the implementation of RL practices in
developed countries, there is still a lot to do in a developing country
like India (Jindal and Sangwan, 2011; Sharma et al., 2011;
Subramanian et al., 2014). Govindan et al. (2015) suggested in
their research that multi objective decision making is still a gap in
different studies as compared to single objective analyses in the
area of RL/CLSC. As real world problems are rarely single objective
only, it is necessary for researchers to pay more attention to multi
objective functions instead of single objective ones (Govindan et al.,
2015).

From the extensive literature, we observed that several enablers
and barriers exist to implement RL activities in the business (Jindal
and Sangwan, 2011; Chio et al., 2012; Bouzon et al., 2016). To the
best of our knowledge, the specific consideration of CSFs in the
implementation of reverse logistics to maximize sustainable ad-
vantages is not covered in the literature. Business organizations face
many complexities and challenges in implementing RL activities.

Thus, this work aims to identify the RL implementation CSFs to
provide a theoretical ground for the managers by showing the role
of identified CSFs in RL implementation initiatives. The identified
CSFs can help in understanding the realistic issues to adopting RL
practices from an organizational supply chain perspective. Hence,
within the framework and understanding of the theory of CSFs, the
present research seeks to identify and analyze CSFs to contribute to
successful implementation of reverse logistics from the Indian
manufacturing industry perspective. Tomeet the above highlighted
research gap, the AHP and DEMATEL methods have been used;
other details about the application of AHP and DEMATEL are given
in next section.

3. Research methods

This section presents the description of the proposed and uti-
lized research methods. The AHP method has been used to rank
factors according to their significance on the basis of industry ex-
perts’ opinion. However, there is a need to determine the causal
interactions between factors useful for managers in framing short-
term decision making strategies (Najmi and Makui, 2010). DEMA-
TEL is recognized as a powerful tool in dealing with the issue; it
portrays a basic concept of contextual relation among the elements

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621 611

of the system. The DEMATEL method can evaluate decision ele-
ments by signifying the interdependence between them, which
may help policy makers to frame long-term decision strategies
(Chio et al., 2012). Thus, the AHP and the DEMATEL methods when
applied together will give a clearer illustration of use for industries
to plan both the tactical or operational and the strategic decision
strategies. However, the details of the research methods are given
in the following sub-sections.

3.1. AHP method

AHP, first introduced by Thomas L. Saaty (1980), is a flexible
multi criteria decision analysis technique, designed to solve un-
structured decision problems. The AHP technique is based on the
fundamentals of the decomposition of the problem, of the pair-
wise assessments, and finally of the generation and synthesis of
priority vector (Ho, 2008; Sarmiento and Thomas, 2010; Luthra
et al., 2015b). In contrast to the analytic network process (ANP),
AHP is a linear evaluation technique. On the other hand, it needs to
develop several pair-wise assessment matrices in ANP, and in
addition, it involves a complex survey process for non-expert’s
viewpoint (Harputlugil et al., 2011). The methodology of AHP en-
ables the managers to analyze the complicated system more easily
(Vaidya and Kumar 2006; Talib et al., 2011; Govindan et al., 2014;
Mani et al., 2014; Kumar et al., 2015; Mangla et al., 2015c). How-
ever, AHP has several limitations as well, given as (Ishizaka and
Labib, 2009):

� Rank reversal (i.e. changes in the importance ratings whenever
criteria or alternatives are added-to or deleted-from the initial
set of criteria or alternatives compared).

� The assumption of criteria independence.
� The use of judgment scales whilemaking pair-wise comparisons
may involve ambiguity and human bias.

The steps involved in employing the AHP methodology (Chang
et al., 2007; Madaan and Mangla, 2015) for this research are
described as below:

Step 1: To define the goal: The goal of this research, i.e. to
evaluate the success factors in implementation of RL, is defined.
Based on this, the factors and sub-factors are established that
help in structuring a decision hierarchy. The sources of literature
and expert judgments will be crucial for this.
Step 2: To collect data and form the pair-wise evaluations: In
this step, data is collected to frame the pair-wise evaluations
among factors. A judgment matrix (designated as ‘A’) is formed
which is used for calculating factor priorities. Let A1, A2 … An, be
the set of stimuli. The computed judgments on a pair of stimuli
Ai, Aj, are denoted as,

A ¼ �aij
�

where; i; j ¼ 1;2;&;n: (1)
The survey instrument in terms of questioners’ evaluation can

be used to collect data. Based on the data collected, the rating or
pair-wise evaluations among the factors are acquired by means of a
nine rating Saaty’s scale, which assists to achieve numerical
quantities representing the values of aij (elements of the pair-wise
comparison matrix) transformed from verbal judgments.

Step 3: To attain the Eigen values and Eigen vectors: In this step,
the framed pair-wise evaluation matrices were operated in or-
der to obtain the importance weights of the factors. Based on
obtained importance weights, the priority for the respective
factor is attained.

3.2. DEMATEL method

DEMATEL approach was developed by Science and Human Af-
fairs Program of the Battelle Memorial Institute of Geneva some-
where in 1972 and 1976 (Gandhi et al., 2015). This method relies on
graph theory, and enables an analysis of complicated problems by
means of visualization techniques (Lin, 2013). Compared to inter-
pretive structural modeling (ISM), the methodology of DEMATEL, on
the other hand, assists in capturing the contextual relations be-
tween elements in the system and defining the strength of their
interrelationships, as well (Wu, 2008). The procedural steps of
DEMATEL methodology (Tzeng and Huang, 2011; Jia et al., 2015)
with regard to this work is given as follows:

Step 1: To define the goal and factors to be evaluated: In this
step, a critical review of literature is required to explore and
gather relevant data. The expert’s judgment is also crucial in this
step for discussion on the issue to achieve the goal. The probable
factors associated with the effective implementation of RL are
selected and finalized as factors to be evaluated from the in-
formation gathered and expert judgments.
Step 2: To form the initial direct relation matrix and average
matrix (M): An initial relation matrix is formulated based on the
direct influence between any two factors and is obtained
through the expert’s judgment by asking them to score the
factor on the basis of scale given as, 0e ‘No influence’; 1e ‘Little
influence’; 2 e ‘High influence’; 3 e ‘Very high influence’.

If ‘n’ be the number of factors and ‘k’ be the number of re-
spondents with 1 � k � H, then for each respondent (n � n) non-
negative matrices can be established as Xk ¼ [xkij]. The notation
‘xij’ indicates the degree to which the expert conceives that factor i
affects factor j. Based on this, it can be possible to construct X1, X2,
X3 …, XH matrices given by H respondents respectively (H repre-
sents the number of experts). To incorporate all opinions from H
respondents, the average matrix or the average direct relation
matrix A ¼ [aij] is constructed by means of Eq. as follows:

mij ¼
1
H

K¼1
xkij: (2)

Step 3: To compute the normalized direct-relation matrix (D):
The average matrix (M) is transformed into a normalized direct-
relation matrix by using the Eq. given below,

D ¼ M � S (3)

where, S ¼ min

2
6664

1
max

Pn
j¼1jmijj

; 1
max

Pn
i¼1jmijj

3
7775 .

Step 4: To attain the total relation matrix (T): The total relation
matrix (T) is computed by using the Eq. given below:

T ¼ DðI � DÞ�1 (4)

where ‘I’ is the identity matrix, after attaining the Matrix
T ¼ [tij]n�n, the summation of all the rows and columns are
calculated.

Let [ri]n�1 and [cj]1�n be the vectors representing the sum of
rows and sum of columns of the total relationmatrix respectively. ri

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621612

summarizes both direct and indirect effects imparted by factor ‘i’ to
the other factors, whereas, cj depicts both direct and indirect effects
received by factor ‘j’ from the other factors. Sum (ri þ cj) known as
‘Prominence’ demonstrates the total effects given and received by
factor ‘i’, whereas the difference (ri – cj) known as ‘Relation’ dem-
onstrates the net effect through which factor ‘i’ impacts the system.
Specifically, if the value (ri – cj) is positive, factor ‘i’ is in the net
cause group, while factor ‘i’ will be in the net receiver group if the
value (ri – cj) is negative (Tzeng et al., 2007).

4. Proposed research framework

The research framework for evaluating the CSFs in effective
adoption and implementation of RL practices, based on the AHP
and DEMATEL methods, consists of three phases. Phase 1: identi-
fication of the most common RL implementation CSFs from litera-
ture resources and from industrial and field expert inputs. Phase 2:
prioritizing the CSFs to develop the short-term, flexible decision
plans in order to adopt RL practices using the AHPmethod. Phase 3:
analyzing the causal interactions among CSFs to formulate the
long-term, flexible decision strategies in order to adopt RL practices
using the DEMATEL method. The research framework for evalu-
ating the CSFs in implementation of RL in Indian manufacturing
industries is shown in Fig. 1.

5. An application example of the proposed model to
manufacturing industries in India

5.1. Data collection

The main source of the data collection is manufacturing com-
panies operational in the western region of India. A total of 50
manufacturing companies were targeted for the data collection.
These companies were covered under convenience sampling, not

Fig. 1. Proposed Rese

random sampling. Companies were selected on the basis of prior
experience and using personal contacts. There is no formula for
taking sample size in convenience sampling. It all depends upon
the on cost and resources needed for data analysis and time limits
to complete the project. Due to cost and resources and time con-
straints, it is assumed that the considered sample size would be
sufficient and representative of the population under analysis.

Further, after frequent phone calls, e-mails and meetings, 42
companies agreed to take part in the process in the end. A ques-
tionnaire was formed and circulated among various middle and
senior level managers and field experts of the manufacturing
companies in question to collect data needed for this research
work. The selected managerial and field experts are highly profi-
cient in their respective domains and have an industrial experience
of more than 10 years. The middle and lower level managers were
primarily selected for data collection, because they are primarily
involved in strategic decision making of adoption and imple-
mentation of RL initiatives from the industrial context (Mangla
et al., 2015a). After having several discussion sessions and group
meetings with experts, a total of 42 replies were collected. Out of
these 42 replies, 30 replies were found suitable in all respects (i.e.
completely filled). These 30 replies were examined for further
analysis. The response rate was nearly around 60%, which is
acceptable. Further, according to Malhotra and Grover (1998), a
response rate of above 20% is considered as a reasonable one. The
basic profile of the respondent industries is shown in Table 1.

The data collected is used in three phases as described in the
following sub-sections.

5.1.1. Phase 1: identification and selection of the common RL
implementation critical success factors

Initially twenty-two CSFs for the implementation of RL were
identified on the basis of literature review. Later, a questionnaire
was formed and mailed to different manufacturing industries in

arch framework.

Table 1
Basic profile of the respondent industries.

S. No. Basic data of respondents Criteria Number of
respondent

1 Type of industry Paper industry 14
Sugar industry 05
Heavy engineering 05
Automobile industry 14
Iron and steel industry 04
Total 42

2 Annual turnover
(in Indian rupees)

Less than or Equal to
1000 Millions

1001 to 5000 Millions 20
More than 5000 Millions 07
Total 42

3 Nature of business Original Equipment
Manufacturer

Supplier 36
Total 42

4 Average numbers
of suppliers

Less than or Equal to 50 04
50 to 200 20
More than 200 18
Total 42

5 Environmental
management system

Yes 30
No 0
In Progress 12
Total 42

Source: Industry log book, data records, and expert inputs.

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621 613

India for their inputs to rank the significance of each factor on the
scale of 1e5 (where, 1-least significant, 2- less significant, 3- sig-
nificant, 4- high significant, and 5-most significant). The purpose of
this scalewas to rate the importance of initially identified 22 factors
with regard to the discussion sessions arranged with the experts
according to the effective adoption and implementation of RL ini-
tiatives in Indian context. The factors with a rating of 1 or 2 were
decided to be deleted, but we retained ratings of 3 and above for
each factor. Therefore, there was no elimination from the initial list.
In addition, a column was added to the questionnaire where the
respondents (industry and field experts) can add any other critical
factor important to the RL implementation point of view as per
their perception. By virtue of this, 3 more factors were added to the
initial literature identified 22 RL implementation CSFs. The three
added factors are given as e Extended producer responsibilities,
Benchmarking, and Globalization. Hence, a total of 25 CSFs linked
to implementation of RL for Indian manufacturing industries are
selected. These finalized 25 CSFs were then classified into five main
factors depending on their intended meaning and functional sim-
ilarities (see Table 2). These are given ase Regulatory factors (RF),
Global competitiveness factors (GCF), Economic factors (EF), HR
and organizational factors (HROF), and Strategic factors (SF).

5.1.2. Phase 2: determining the relative importance of the RL
implementation common success factors using AHP

The finalized common RL implementation CSFs is evaluated by
using the AHPmethod. It helps to recognize the relative importance
of each factor based on the ranks obtained from their numerical
priorities. For this, a hierarchal structure is constructed to analyze
the problem. It comprises of three levels: goal statement (Level-1),
main factors (Level-2), and sub factors (Level-3) as shown in Fig. 2.

Next, the pair-wise evaluation matrix for the main factors and
each sub factor is constructed by taking into consideration the
expert’s judgments. The importance rating of each expert is
collected based on scale as mentioned in Section 3.1. Notably, the
geometric meanmethod is among themost common usedmethods
in AHP to aggregate the individual ratings of the experts (Saaty,
2008). Thus, in this work, geometric mean of individual opinions

is computed for determining the ranks of the factors. The pair-wise
evaluation matrix for the main group factors is represented in
Table 3 below.

After following the steps mentioned in Section 3.1, Eigen values
and Eigen vectors are calculated, and is given as maximum Eigen
value ¼ 5.245; Consistency index (C.I.) ¼ 0.0612. The relative
weights attained and corresponding ranks for the main factor are
shown in Table 4.

The consistency ratio (C.R.) is calculated which comes out to be
0.055 (C.R. ¼ 0.0612/1.11). As evident, the consistency ratio (C.R.) is
well below the permissible limits (i.e. C.R.� 0.10); thus, the results
are considered to be acceptable. Likewise, the relative weights of all
the sub factors are calculated. Further, for obtaining the global
weights of all the sub factors, the relative weight of each main
factor is multiplied with its corresponding sub factor weights (see
Table 5).

5.1.3. Phase 3: determining interdependence among the RL
implementation common success factors using DEMATEL

In this phase, DEMATEL approach is used in order to determine
the interdependence between listed common CSFs relevant to RL
implementation from industries in Indian perspective. It assists to
evaluate the interrelationship between the CSFs in terms of a causal
effect map. For this, the same selected industry and field experts
were contacted and asked to rate the CSFs on the scale of 0e3
depending upon the influence of one factor over other factors. This
step is done to construct the pair-wise matrix of the main success
factors needed to construct the average matrix (A) and which is
formed by taking the average of the responses of the experts
(shown in Table 6).

In the next step, the normalized initial direct relation matrix (D)
is formed using Eq. (3) (see Table 7).

Following this, the total relation matrix (T) is constructed by
using Eq. (4), and is shown in Table 8.

According to Table 8, values in (r þ c) column (i.e. prominence),
demonstrates the total effect of each main factor over the entire
system; thus, Global competition factors (GCF) havemore influence
in comparison to other success factors. Likewise, values in (r e c)
column (i.e. relation), helps to divide the success factors into cause
and effect groups depending on their positive and negative values
attained respectively. Next to this, the threshold value has been
calculated, which facilitates to making this structure distinct. It is
obtained by taking the average of all the factors in total relation
matrix (T). It may help to reflect how one success factor influences
other factors, and assists to filter out some negligible effects in the
causal effect map. The causal-effect map of the main factors is
shown in Fig. 3.

Based upon the prominence values, the importance of main
factors in the implementation of RL practices in Indian
manufacturing industries is given as GCF-SF-HROF-RF and EF (see
Fig. 3). Further identified six main factors have been categorized
into cause-effect groups. The cause-effect diagram provides valu-
able insight to analyze the main factors in the implementation of
reverse logistics in Indian manufacturing industries. The main
factors – namely GCF, RF, and HROF – have been categorized into
the cause group, and the other two main factors (namely SF and EF)
are categorized into the effect group.

With respect to the differentmain factors, their position, and the
relative importance in the system, experts distinguish the main
factor which affects the decisions of the implementation of RL in
Indian manufacturing industries greatly, and thus, improvements
are made accordingly. Similarly, the DEMATEL calculations have
been performed for sub factors within their respective main factors
(Appendix A). The causal-effect map for the sub factors has also
been formed as shown in

Appendix B

Table 2
Common success factors related to RL implementation.

S. No. Success factor Description Source

Regulatory factors (RF)
1 Government norms and support (RF1) Government directives and support act as very important factors for

industries to put RL in practice
Kumar and Putnam, 2008; Hung Lau
and Wang, 2009; Subramoniam et al.,
2009; Ho et al., 2012; Rahman and
Subramanian, 2012

2 Preferential tax policies (RF2) Favorable taxation policies can motivate industries to implement RL
practices

Shaik and Abdul-Kader, 2012;
Abdulrahman et al., 2014

3 Environmental management
certifications (RF3)

Certification helps organizations to start and encourage environmentally
friendly activities in their business activities, and generates consciousness
among the employees

Knemeyer et al., 2002; Kumar and
Putnam, 2008; Hung Lau and Wang,
2009; Chio et al., 2012

4 Extended producer responsibility (RF4) Manufacturers should be responsible enough to manage products at their
end-of-life within India

Opinion received from the experts

5 Waste management practices (RF5) Wastemanagement practices is a big concern for industries to contribute for
society and environment

Knemeyer et al., 2002

Global competitiveness factors (GCF)
6 Competition (GCF1) Adopting RL practices can tremendously improve an organizational

competitive image in the market
Knemeyer et al., 2002; Subramoniam
et al., 2009; Chio et al., 2012; Giannetti
et al., 2013

7 Benchmarking (GCF2) Benchmarking the operations may significantly improve the RL adoption at
industrial context

Opinion received from the experts

8 Globalization (GCF3) Globalization proves to be a thrust for industries in RL adoption Opinion received from the experts
9 Green image building (GCF4) RL has been recognized as an important step for industries to enhance their

green image
Hsu and Hu, 2009; Hung Lau andWang,
2009; Subramoniam et al., 2009;
Mangla et al., 2014a

10 Sustainability (GCF5) Implementation of RL practices helps to bring sustainability in the business Kumar and Putnam, 2008; Lee et al.,
2010; Luthra et al., 2014b; Mangla et al.,
2015b; Nikolaou et al., 2013;
Subramanian et al., 2014

Economic factors (EF)
11 Reduced consumption of raw/virgin

material (EF1)
RL offers a huge scope of value recovery from used products, so helps in
reducing the raw/virgin material consumption

Seuring and Müller, 2008; Akdo�gan and
Coşkun, 2012

12 Decreased waste generation (EF2) Adopting RL operations like recycling, reuse, remanufacturing results in the
reduction of waste generation

Hung Lau and Wang, 2009; Pigosso
et al., 2010; Akdo�gan and Coşkun, 2012

13 Financial opportunities (EF3) Financial opportunities in terms of the second hand market can be obtained
through RL adoption

Rahman and Subramanian, 2012; Shaik
and Abdul-Kader, 2012

HR and organizational factors (HROF)
14 Stakeholders’ role and support (HROF1) Stakeholders such as investors, employees, management, etc. are

considered to be significant in making the decision to bring in the RL
perspective within the business culture

Gonz�alez-Benito and Gonz�alez-Benito,
2006; Rahman and Subramanian, 2012;
Shaik and Abdul-Kader, 2012

15 Experts involvement (HROF2) Experts involvement and knowledge can be valuable for the successful
implementation of RL

Ho et al., 2012; Abdulrahman et al.,
2014

16 Organization’s policy and mission
(HROF3)

Organization’s policy, mission and vision are very crucial for the acceptance
of the implementation of RL model

Dowlatshahi, 2005; Gonz�alez-Benito
and Gonz�alez-Benito, 2006

17 Top management commitment and
support (HROF4)

Top management commitment and support is very important for initiation
and implementation of RL

Dowlatshahi, 2005; Abdulrahman et al.,
2014

18 Employee expertise and involvement
(HROF5)

RL implementation needs employee involvement; otherwise, its effective
implementation could be very difficult

Ho et al., 2012; Abdulrahman et al.,
2014

19 Customer environmental awareness
(HROF6)

Customer environmental perception and knowledge is key to insist
industries to adopt RL practices

Tsoulfas and Pappis, 2008; Rahman and
Subramanian, 2012; Shaik and
Abdul-Kader, 2012; Abdulrahman
et al., 2014

Strategic factors (SF)
20 Integration and coordination (SF1) Integration and coordination among SC members may result in successful

implementation of RL
Rahman and Subramanian, 2012;

Lambert et al., 2011

21 Technology advancements (SF2) Adopting new processes and technology in RL initiatives will result in
increased efficiency

Lambert et al., 2011; Shaik and
Abdul-Kader, 2012

22 Management information system (SF3) It helps in bringing visibility within the system, thus, assisting on all levels of
RL implementation

Lambert et al., 2011

23 Infrastructure (SF4) Infrastructure plays a major role in RL adoption Lambert et al., 2011
24 Understanding best practices (SF5) Understanding RL implementation best practices will be crucial at industrial

perspective
Abdulrahman et al., 2014

25 Flexibility (SF6) Flexibility in operations, process and methods can help in adopting
successful RL practices in business

Knemeyer et al., 2002; Bai and Sarkis,
2013; Nagarajan et al., 2013

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621614

6. Results and discussions

From Table 4, the main factors to implement RL practices can be
arranged in relation to their relative importance or ranking as e
Global competitiveness factors (GCF), Regulatory factors (RF), HR
and organizational factors (HROF), Economic factors (EF), and
Strategic factors (SF). The relative importance or ranking of the sub

factors has also been determined. Next, considering the DEMATEL
results, the main factors GCF, RF, and HROF belong to the cause
group, and the main factors EF and SF belong to the effect group. It
clearly indicates that AHP based highly prioritized factors are the
causal factors in accordance with the DEMATEL results. In addition,
the importance order and causality mechanisms of the main factors
and sub factors in efficient implementation of RL have also been

Fig. 2. AHP based hierarchical structure for the research.

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621 615

recognized. Based on this, the present research offers several
management science implications as follows.

The finding of this research work reveals that the Global
competitiveness main factor (GCF) acquires the first rank, and
consequently, it obtains the highest priority among other main
factors (see Table 4). Regarding GCF, it is fitted to cause group factor
(see Fig. 3), due to the positive value of (r e c) score (i.e. 0.875). It

Table 3
Pair wise evaluation matrix for main factors.

Factors RF GCF EF HROF SF

RF 1 1 3 2 3
GCF 1 1 5 3 5
EF 1/3 1/5 1 1/3 3
HROF ½ 1/3 3 1 3
SF 1/3 1/5 1/3 1/3 1

has a considerable significant influence on the other main factors.
Therefore, it can be inferred that the GCF grouping is a crucial factor
for industries in order to reduce the waste generation and emis-
sions and to increase their environmental performances (Chio et al.,
2012). Hence, it needs a great managerial commitment. Within this
main factor, there are five sub factors, namely GCF1, GCF2, GCF3,
GCF4, GCF5. These can be arranged in accordance with their

Table 4
Ranking of main factors in RL implementation.

Main factors Relative weights Ranks

GCF 0.3794 1
RF 0.285 2
HROF 0.1761 3
EF 0.0977 4
SF 0.0618 5

Table 5
Ranking of sub-factors in RL implementation.

Main factors Relative weights Sub factors Relative weights Relative ranking Global weights Global ranking

Regulatory factors (RF) 0.285 RF1 0.497 1 0.142 2
RF2 0.071 5 0.020 17
RF3 0.182 2 0.052 6
RF4 0.158 3 0.045 8
RF5 0.093 4 0.027 14

Global competitiveness factors (GCF) 0.379 GCF1 0.150 3 0.057 5
GCF2 0.124 4 0.047 7
GCF3 0.448 1 0.170 1
GCF4 0.208 2 0.079 3
GCF5 0.071 5 0.027 13

Economic factors (EF) 0.098 EF1 0.637 1 0.062 4
EF2 0.258 2 0.025 15
EF3 0.105 3 0.010 22

HR and organizational factors (HROF) 0.176 HROF1 0.200 2 0.035 10
HROF2 0.073 6 0.013 21
HROF3 0.162 4 0.029 12
HROF4 0.243 1 0.043 9
HROF5 0.135 5 0.024 16
HROF6 0.186 3 0.033 11

Strategic factors (SF) 0.062 SF1 0.217 3 0.013 20
SF2 0.278 1 0.017 18
SF3 0.224 2 0.014 19
SF4 0.119 4 0.007 23
SF5 0.113 5 0.007 24
SF6 0.048 6 0.003 25

Table 6
Average direct relation matrix (A) (Main factors).

0.00 2.67 2.33 2.00 2.33
2.33 0.00 2.33 2.00 2.33
0.67 1.33 0.00 1.67

2.00

1.33 2.00 2.33 0.00 2.33
1.67 1.67 1.67 2.00

0.00

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621616

priority, given as: – Globalization (GCF3), > Green image building
(GCF4), > Competition (GCF1), >Benchmarking (GCF2), > Sustain-
ability (GCF5). Globalization (GCF3), is highly ranked in global
ranking column aswell (see Table 5), and demonstrated as themost
important success factor for Indian industries to put into practice
the RL initiative decisions. To have more insights into the results,
the success factors GCF1, GCF2, GCF3 are categorized as cause group
factors and GCF4, GCF5, are classified under effect group factors
based on the (re c) values (see Appendix A). This grouping suggests
that there is a critical need to regulate cause group factors, and
consequently, the effect group factors can surely acknowledge the
objectives of successful accomplishment of RL adoption across In-
dian industries.

Regulatory main factors (RF) obtain the second highest priority
in the list. The establishment of well-defined and environmental
supportive regulating directives and guidelines is very significant
for industries in adopting the RL initiatives at industrial standpoints
(Jindal and Sangwan, 2011; Sharma et al., 2011). Further, in relation
to this main factor, it finds its place among the cause group factor
(Fig. 3), indicating that it may act as a major contributing factor to
increase the success rate of RL adoption and implementation

Table 7
Normalized direct relation matrix (D) (Main factors).

0.00 0.29 0.26 0.22 0.26
0.26 0.00 0.26 0.22 0.26
0.07 0.15 0.00 0.18 0.22
0.15 0.22 0.26 0.00 0.26
0.18 0.18 0.18 0.22 0.00

among industries in Indian context. The five sub factors related to
this main factor are from RF1 to RF5. The preference or relative
importance order for these sub factors is given as Government
norms and support (RF1), > Environmental management certifi-
cations (RF3), > Extended producer responsibility (RF4), > Waste
management practices (RF5), > Preferential tax policies (RF2). In
addition to this, Government norms and support (RF1), is ranked
secondly as per global ranking and proves to be a key factor in
taking on RL aspects in business (Table 5). The success factors RF1,
RF3, and RF4 found their places in the cause group (see Appendix
A), which implies that they have significant influential impacts
over the other factors found in the effect group (namely RF2, RF5).
Moreover, all these factors play a significant role to the point of
Indian industries where RL initiatives are still in infancy. Clearly, a
systematic implementation of strategies and plans linked to these
factors’ completion may foster sustainable business developments
among Indian industries.

HR and organizational factors (HROF) occupies third rank in the
list. It finds its place among the cause group factor (Fig. 3), which
implies that it is relatively important among all other main factors.
Having proficient human resources, their expertise, and knowledge
along with organizational capabilities in terms of employee
involvement and their skills may resolve the difficulties relevant to
RL adoption and provide an opportunity to undertake the accep-
tance of RL’s contemporary activities like reuse, recycling, or
remanufacturing from business viewpoints (Sharma et al., 2011;
Abdulrahman et al., 2014). Stakeholders such as investors and
partners are pushing industries to accept RL related activities in

Table 8
Total relation and direct-indirect influence matrix (Main factors).

Factors RF GCF EF HROF SF R r þ c r e c
RF 0.91 1.33 1.44 1.30 1.48 6.45 10.88 2.030
GCF 1.08 1.06 1.40 1.26 1.44 6.24 11.61 0.875
EF 0.66 0.83 0.79 0.88 1.00 4.15 10.16 �1.860
HROF 0.91 1.12 1.27 0.97 1.31 5.57 11.04 0.100
SF 0.87 1.02 1.13 1.06 1.01 5.08 11.31 �1.145
C 4.42 5.37 6.01 5.47 6.24 Threshold value ¼ 1.10

GCF

HROF

–

2.50

-2.00

–

1.50

–

1.00

–

0.50

0.00
0.50
1.00
1.50
2.00
2.50

10.00 10.20 10.40 10.60 10.80 11.00 11.20 11.40 11.60 11.80

Fig. 3. Causal effect map (Main factors).

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621 617

supply chains (Chio et al., 2012). The relative ranking of six sub
factors related to this main factor are – Top management commit-
ment and support (HROF4), > Stakeholders’ role and support
(HROF1), > Customer environmental awareness (HROF6), > Orga-
nization’s policy and mission (HROF3), > expertise and involve-
ment (HROF5), > Experts involvement (HROF2). Moreover, success
factors HROF1- HROF4- HROF6 occurs in the cause group, which
has a significant influence over the factors HROF2- HROF3- HROF5,
which are in the effect group (see Appendix A).

Economic factors (EF) acquired the fourth importance level and
play a crucial role in adopting effective green concepts in an in-
dustrial context. Further, considering the causal effect map, it be-
longs to effect group. It suggests that the various associated
activities in implementation of RL practices have a tendency to in-
fluence finance flow and resources (Chio et al., 2012). Under this
consideration, it may be difficult for Indian industries to initiate and
adopt RL practices in the initial stage of business, but at the later
stage, it will offer a huge financial opportunity in terms of the
reduction of raw material consumption, of significant cuts in waste
generation, and of financial opportunities for used products in the
new or secondary market, etc. Thus, the Indian industries may be
financially benefitted and contribute more to their country’s econ-
omy. This main factor contains three sub factors and the priority
order for them is listed as – Reduced consumption of raw/virgin
material (EF1), > Decreased waste generation (EF2), > Financial
opportunities (EF3). With regard to these three sub factors, EF1 and
EF2 fall under the cause group, whereas EF3 comes under the effect
group (see Appendix B). Thus, managers are suggested to consid-
erably resolve the causal matters helpful in performance improve-
ments in aspects of RL adoption and implementation.

Strategic factors (SF) hold the last place in priority list. It would
be valuable for industries if they have strategic plans and visions
associated with adoption and implementation of RL practices in
their businesses. Understanding and analyzing Strategic factors is
important to develop strengths into competitive advantages and to
improve certain weaknesses related to technology, infrastructure,
supply chain coordination and integration, and flexibility; such
improvements will result in increased environmental, economical,
and social performances of the Indian industries. There are six sub
factors in strategic factors, and the preference order for them is
highlighted as Technology advancements (SF2), > Management
information system (SF3), > Integration and coordination (SF1), >
Infrastructure (SF4), > Understanding best practices (SF5), >
Operational flexibility (SF6). The success factors SF1, SF2, SF3 and
SF4 found their places in the cause group (see Appendix B), which
implies that they have significant influential impacts over the other
factors occurring in the effect group, namely SF5 and SF6.

AHP results of main factors to implement RL practices in relation
to their priority are given, in order, as GCF-RF-HROF-EF and SF. The
DEMATTEL results of main factors to implement RL practices ac-
cording to the prominence values are given as GCF-SF-HROF-RF and
EF. From this, we can say that AHP and the prominence results are
almost consistent. The combined results will help managers not
only to prioritize the RL implementation success factors, but also to
obtain their causal interactive relationships. This understanding
may result in performance improvements in their industries, and it
may help to ensure sustainable business developments.

6.1. Implications of research

The AHP and DEMATEL based model proposed in this work will
enable Indian manufacturing company managers to understand
different CSFs to implement RL practices in India. It would be
crucial to know the relative importance and causal interactions of
the various CSFs and the techniques for implementing RL adoption
from industrial standpoints. This research work will certainly pre-
pare them for the more efficient and effective implementation of RL
practices in India. The findings obtained in this work will help
managers and practitioners to improve the sustainability of the
organizations in implementing RL practices of the industries. CSFs
with higher priority demonstrate more of a tactical or operational
orientation; on the other hand, those categorized as cause and ef-
fect groups are more geared towards performance and result
orientation. However, strategic results/desired effects can be ach-
ieved by continuously improving cause group factors. This work
may help RL practitioners/managers to manage these identified
CSFs according to their AHP ranking priority and DEMATEL based
prominence to achieve sustainability in the business.

From the results, Global competitiveness and Regulatory factors
are highly prioritized factors and belong to cause group factors as
well. In that way, the companies should contact and lobby the
government and regulating authorities to express their concerns of
the issue of RL implementation and its benefits in business. Gov-
ernment and various regulating agencies support is much needed
to adopt green and product recovery activities (Madaan and
Mangla, 2015). To help companies, a well-designed and system-
atic reverse logistics network is recommended to overcome the
complexities in returning and recycling collected products for their
reuse (Mangla et al., 2015a). In this sense, some motivational pro-
grams and seminars/campaigns may be conducted to educate
customers regarding products’ reuse, recyclability, etc. In addition,
some easily accessible collection stations may be opened to
enhance the return and recovery of used products. Strict penalty
and rewards systems may improve the recovery mechanism.

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621618

To end with, the proposed network model may provide some
valuable guidelines to the supply chain analysts and management
science professionals to develop their plan of action in terms of
design of the short-term and the long-term, flexible decision stra-
tegies for implementing RL on various business levels.

Factors RF1 RF2 RF3 RF4 RF5 r r þ c r e c
RF1 0.53 1.03 0.82 0.95 0.83 4.17 6.76 1.58
RF2 0.45 0.54 0.55 0.65 0.54 2.73 6.77 �1.31
RF3 0.57 0.85 0.50 0.69 0.65 3.25 6.38 0.11
RF4 0.61 0.91 0.75 0.61 0.66 3.54 7.05 0.02
RF5 0.44 0.71 0.51 0.62 0.40 2.69 5.77 �0.39
c 2.59 4.04 3.14 3.52 3.08 Threshold value ¼ 0.65

Factors GCF1 GCF2 GCF3 GCF4 GCF5 R r þ c r e c
GCF1 2.60 2.57 2.71 2.74 2.74 13.36 26.40 0.33
GCF2 2.76 2.34 2.69 2.66 2.67 13.13 25.07 1.18
GCF3 2.85 2.59 2.54 2.77 2.72 13.46 26.13 0.80
GCF4 2.41 2.22 2.34 2.18 2.37 11.53 24.24 �1.19
GCF5 2.42 2.23 2.38 2.36 2.19 11.58 24.27 �1.12
c 13.03 11.95 12.67 12.71 12.70 Threshold value ¼ 2.52

Factors EF1 EF2 EF3 r r þ c r e c
EF1 1.03 1.25 1.66 3.93 7.02 0.84
EF2 1.15 0.80 1.45 3.40 6.19 0.60
EF3 0.92 0.76 0.84 2.52 6.47 �1.44
c 3.09 2.80 3.95 Threshold value ¼ 1.09

7. Conclusions, limitations, and scope for future work

Industries are constantly seeking ways to curb their negative
impacts on the environment to ensure business sustainability. The
implementation of reverse logistics (RL) practices has received
major attention among developed countries; however, it needs a
more in-depth examination in order to most effectively benefit a
developing country such as India. Nevertheless, there are several
critical factors linked to the implementation of RL practices. Hence,
it is necessary to analyze these factors to increase the RL imple-
mentation success rate. Therefore, from industrial viewpoints, the
various CSFs related to the implementation of RL practices are
evaluated in this study.

In this research work, an attempt has been made to evaluate the
CSFs in RL implementation, by framing both short-term and long-
term flexible decision strategies with AHP and DEMATEL
methods. The AHP method helps to rank the factors (i.e. deter-
mining of the priority) according to their relative importance. On
the other hand, DEMATEL helps to establish interactive and or
causal relationships between the factors, and classifies them into
cause and effect groups.

The proposed AHP and DEMATEL based model is extended to
the manufacturing industries in the Indian context. RL has been
either already initiated or is in an early stage of adoption in the
industries surveyed. A total of 25 common RL implementation CSFs
have been selected, based on literature resources and the industry
and field expert judgments.

The findings of this work shows that the Global competitiveness
main factor (GCF) is highly prioritized, and thus, needs to be
focused greatly in order to increase the effectiveness and efficiency
of RL adoption in business. The relative priority or importance order
of the remaining main factors through AHP analysis is given as
Regulatory factors (RF) – HR and organizational factors (HROF),
-Economic factors (EF) – Strategic factors (SF). The findings also
indicate that Global competitiveness; Regulatory; HR and organi-
zational main factors are classified under cause group, while Eco-
nomic and Strategic main factors belong to effect group. The cause
group factors are vital due to their direct impact on the overall
system; therefore, it would be significant to focus on these group
factors to expedite the overall performance. On the contrary, effect
group factors tend to be easily affected by other factors (i.e. from
the factors of cause group), and thus, make a significant contribu-
tion towards achieving the desired goals (Mangla et al., 2015b. The
results in terms of relative priorities and of interactive relationships
for the sub factors are also derived.

This work has its own limitations, which can be taken as op-
portunities for future research. The work carried out in this
research is based on the methods of AHP and DEMATEL, and

Factors HROF1 HROF2 HROF3 HROF4

HROF1 0.70 1.07 1.19 1.09
HROF2 0.53 0.60 0.79 0.73
HROF3 0.75 0.97 0.89 0.98
HROF4 0.76 0.98 1.09 0.82
HROF5 0.64 0.90 0.96 0.86
HROF6 0.64 0.77 0.85 0.79
c 4.02 5.29 5.77 5.26

identifies 25 CSFs in the context of implementation of RL in Indian
context. Some other CSFs have not been revealed and classified. For
future studies, the hierarchical intertwined interactions and feed-
back paths among recognized RL implementation CSFs can be
analyzed by using other multi-criteria analysis methods like the
Technique for Order of Preference by Similarity to Ideal Solution
(TOPSIS), Analytic Network Process (ANP)methods, and other fuzzy
or grey related MCDM approaches (Govindan et al., 2015a, 2016;
Govindan and Chaudhuri, 2016; Xia et al., 2015). The proposed
model may be applied to other sectors of industry, for example,
service or construction that seeks to analyze the RL implementation
performance at various business levels. It should be noted that the
expert’s opinion may vary with industry type and its priorities.

Appendix A

DEMATEL Calculations for Sub-factors within their respective
Main factors.

Total relation and direct-indirect influence matrix (Regulatory
factors).

Total relation and direct-indirect influence matrix (Global
competitiveness factors).

Total relation and direct-indirect influence matrix (Economic
factors).

Total relation and direct-indirect influence matrix (HR and
organizational factors).

HROF5 HROF6 r r þ c r-c
0.97 0.90 5.92 9.94 1.89
0.67 0.55 3.87 9.16 �1.41
0.90 0.76 5.25 11.02 �0.51
0.95 0.71 5.30 10.56 0.03
0.66 0.65 4.68 9.49 �0.14
0.67 0.51 4.22 8.30 0.14
4.81 4.08 Threshold value ¼ 0.81

S.K. Mangla et al. / Journal of Cleaner Production 129 (2016) 608e621 619

Total relation and direct-indirect influence matrix (Strategic
factors).

Factors SF1 SF2 SF3 SF4 SF5 SF6 r r þ c r-c
SF1 0.84 1.01 1.09 0.98 1.12 1.07 6.11 11.84 0.37
SF2 1.09 0.98 1.23 1.09 1.27 1.26 6.91 12.85 0.97
SF3 1.03 1.04 0.95 1.02 1.20 1.14 6.38 12.62 0.15
SF4 0.98 0.99 1.00 0.83 1.16 1.06 6.03 11.79 0.26
SF5 0.82 0.89 0.90 0.87 0.85 0.95 5.27 12.00 �1.46
SF6 0.98 1.03 1.07 0.98 1.12 0.94 6.12 12.53 �0.29
c 5.74 5.94 6.24 5.77 6.73 6.41 Threshold value ¼ 1.02

Appendix B

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Critical success factors for reverse logistics in Indian industries: a structural model

1. Introduction
2. Relevant literature
2.1. Industrial RL implementation in India
2.2. RL implementation factors
2.3. Research gaps
3. Research methods
3.1. AHP method
3.2. DEMATEL method
4. Proposed research framework
5. An application example of the proposed model to manufacturing industries in India
5.1. Data collection
5.1.1. Phase 1: identification and selection of the common RL implementation critical success factors
5.1.2. Phase 2: determining the relative importance of the RL implementation common success factors using AHP
5.1.3. Phase 3: determining interdependence among the RL implementation common success factors using DEMATEL

6. Results and discussions
6.1. Implications of research
7. Conclusions, limitations, and scope for future work
Appendix A
Appendix B
References

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