An empirical study of the investigation of green

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 3, Sep- Dec (2012) © IAEME
AND TECHNOLOGY (IJMET)
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 3, Issue 3, September - December (2012), pp. 654-668
IJMET
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AN EMPIRICAL STUDY OF THE INVESTIGATION OF GREEN
SUPPLY CHAIN MANAGEMENT PRACTICES IN THE
PHARMACEUTICAL INDUSTRY AND THEIR RELATION DRIVERS,
PRACTICES AND PERFORMANCES

Ajay Verma*, Dr. Anshul Gangele**
* [Research Scholar] Department of Mechanical Engineering, Suresh Gyan Vihar
University, Jaipur (Raj.) 302025
E-mail: vajay9@yahoo.co.in
**Institute of Technology & Management, Gwalior (M.P.) 474001
E-mail: anshulgangele@gmail.com

ABSTRACT

This paper aim is Green Supply Chain management (GSCM) of investigation strategy.
A study of GSCM can help of economic, social, national security, and environmental goals.
Also this study to investigation the green supply chain management practices likely to be
adopted by the pharmaceutical industry in India. Which is dominated by reduces, reuse, and
recycle, Manufacturing manufacturers, after the implementation of the Restriction of
Hazardous Substances and Waste pharmaceuticals material. The relationship between green
supply chain management practices and environmental performance and operational
performance, as well as financial performance, is studied. The approach of the present
research includes a literature review, in depth interviews and questionnaire surveys. The
companies in the pharmaceutical industry approved by the International Organization for
Standardization 14001 certification in India before January 2012 were sampled for empirical
study. Based on a literature review, twelve propositions are put forward. The survey
questionnaire was designed with 54 items using literature and industry expert input. An
exploratory factor analysis was conducted to derive results from the survey data which
included 27 responses. The data analyzed using statistical package for the social sciences, and
structural equation modeling was used as a path analysis model to verify the hypothetical
construction of the study. The results indicate that the pharmaceutical industry have adopted
green supply chain practices in response to the current wave of international green issues and
have generated favorable environmental, operational and financial performances for the
respective companies.

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KEYWORDS: Green supply chain, environmental performance, green procurement, green
manufacturing.

1. INTRODUCTION

GSCM has become an important environmental practice for companies to achieve
profit and increase market share in such a way that environmental risks are lowered and
ecological efficiency are raised. [46,51] Realizing the significance of the GSCM
implemented by the organizations, developed a strategic decision framework that aids
managerial decision making in selecting GSCM alternatives, and product life cycle,
operational life cycle (including procurement, production, distribution and reverse logistics
(RL)), organizational performance measurements and environmentally conscious business
practices serve as the foundations for the decision framework. [36, 50]
India's pharmaceutical industry is now the third largest in the world in terms of
volume. Its rank is 14th in terms of value. Between September 2009 and September 2011, the
total turnover of India's pharmaceuticals industry was US$ 21.05 billion. The domestic
market was worth US$ 12.29 billion. [28, 42] As per a report by IMS Health India, the Indian
pharmaceutical market reached US$ 10.05 billion in size in July 2011. The several
established companies which have operations in the world’s major pharmacy markets. Over
the last few years, contribution in the growth of India’s pharmaceutical industry has been
significant. The state commands 42 percent share of India’s pharmaceutical turnover and 22
percent share of exports. [28]
The Pharmaceutical Supply Chain (PSC) is a special SC in which medications are
produced, transported and consumed. Academic researchers and practitioners believe that
“pharmaceuticals are different; they cannot be treated like other commodities.” [38] The
reasons for this sentiment were the high cost and long duration for research and development
and the repercussions of the product not being available, hence again its criticality. Other
unsupported perception-based factors that appear to make this supply chain distinctive
include; the level of regulation in the product production, storage, distribution, consumption
and the complexity of the fabric of this supply chain. [21] Disposal of medication can be very
harmful to the environment and costly. Globally, in 2003 at least £0.56 billion worth of
unused drugs are flushed down the toilet. [45] From an economic point of view, efficiencies
can be made in the form of potential savings in the pulling back of stock from patients.
Medication retrieved from patients cannot be reused and must be disposed. It does however
provide vital information and can encourage more prudent prescribing. Safety is also
paramount when broaching pharmaceutical management and storage. Accidents can happen
if products fall into the hands of children or individuals who wish to abuse the product
themselves or support a “grey” market for product exchange/sales. Global and domestic
pressures on environmental, economic and safety considerations drive us to manage PSC
greening, i.e., improve the PSC economic and environmental performance by recycling the
unused/unwanted medications and reducing medications that need disposal. However, there is
very little research and practice on drug recycling or green PSC (GPSC). [3, 32] The fate of
unused consumer pharmaceuticals is an issue that has reached public consciousness more
recently. There is emerging concern about the potential impact of medicine that reaches lakes
and rivers via sewage plants and other sources. [25] Increasing pressures from a variety of
directions have caused the Indian Pharmaceutical supply chain managers to consider and
initiate implementation of green supply chain management (GSCM) practices to improve
both their economic and environmental performance. Current environmental awareness,

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practices, and performance of GSCM in general and in pharmaceutical enterprises sets the
foundation for various issues (propositions) that will be evaluated using the empirical data.
Expanding on some earlier work investigating general GSCM practices in India, this paper
explores the GSCM drivers, initiatives and performance of the pharmaceutical supply chain
using an empirical analysis of selected pharmaceutical enterprises. In particular, the
relationships between green supply chain management dimensions and firm performance are
examined in this study.

2. LITERATURE REVIEW

“Green Supply Chain practices (SCM components) adopted is functions of external
(open system view of organization) and internal environment (management component). In
another word the totality of inputs to the system (including agent, mechanism, and functions)
results in outputs (practices). These outputs are measured by considering GSCM practices
from within the whole system.” [13]

2.1 External pressures
The importance of external factors is borrowed to illustrate the complementary nature
of the factors for Chinese companies to adopt GSCM practices at the early stage of
environmental policy transformation. Besides the requirements of governmental regulations,
the domestic and foreign clients, competitors and neighboring communities may exert
pressures on the companies. [15] These external pressures have jointly prompted the
companies to become more aware of their environmental problems and to practice certain
GSCM activities. External pressures are believed to be the important factors affecting a
firm’s GSCM practices. [15, 35, 55]

2.2 Internal factors
As is well known, the institutional theory neglects certain fundamental issues of
business strategy. It is argued that the firms adopt heterogeneous sets of environmental
practices also due to their individual interpretations of the objective pressures from the
outside. The difference between the ‘objective’ and ‘perceived’ pressures may lead to diverse
responses from the firms. Therefore, the analytical model adds two internal organizational
factors, namely support of top managers and a firm’s learning capacity, to jointly explain a
firm’s GSCM practices. Top management support can affect new initiatives success by
facilitating employee involvement or by promoting a cultural shift of the company, etc. As
GSCM is a broad-based organizational endeavor, it has the potential to benefit from top
management support. Meanwhile, a firm’s learning capacity is viewed as especially
important in a resource-based framework. GSCM practices are amenable to the benefits
derived from learning since they are human resource intensive and greatly rely on tacit skill
development by employee involvement, team work and shared expertise. [16] The capacity
for implementing innovative environmental approaches is normally enhanced by employee
self-learning, professional education and job training. The education level of employees and
the frequency of internally environmental training are often used as proxies of a firm’s
learning capacity. [48] To implement GSCM, organizations should follow GSCM practices
which consist of environmental supply chain management guidelines. Numerous studies have
tried to identify GSCM practices in organization which are referred to such internal systems
as environmental and quality management systems. Internal environmental management is
critical to improving the organization’s environmental performance. [56] Performance is a

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measure for assessing the degree of a corporation’s objective attainment. [10] Corporations
adopting GSCM practices may generate environmental and business performances. [47, 54]
A green supply chain, for example, can improve environmental performance (reducing waste
and emissions as well as increasing environmental commitment) and
competitiveness(improving product quality, increasing efficiency, enhancing productivity and
cutting cost), thereby further affecting economic performance, a new marketing opportunities
and increasing product price, profit margin, market share and sale. [30] Expert’s opinion are
organizational performance is considered to include environmental, operational and economic
performance. [30, 47, 54]

3. RESEARCH METHODOLOGY

After surveying the environmental performance assessment in the ISO environmental
management system, as well as comments from experts and academics in the chemical and
machine engineering, a questionnaire was created as the tool of the present study. [30, 35, 36,
51, 53,] The items in the questionnaire were then taken as research variables according to the
conceptual model of the study. [28] The data used in this study consist of questionnaire
responses from employees in Indian manufacturing and processing industries that have
profound impact on the environment. Structural equation modeling was used as a path
analysis model to verify the hypothetical construction of the study. The questionnaire
contains three sections:

• General Information: This contains gender, and job title of the respondents from the
organization as well as annual sales of the company and number of persons employed.
This information is gathered only for a glance of an industry and its size.
• Basic Green Supply Chain Management Information: This includes questions
regarding company’s step towards GSCM. It also contains reasons for adoption and
no implementation of GSCM. If company has not yet implemented the GSC practices
then in this section respondents can provide maturity period for GSCM as per their
company policies.
• Impact of drivers on implementation of GSCM practices and relation to
organizational performance part includes items affecting implementation
(pressures/drivers), current practices and corresponding performance.
In this section twelve different variables (Environment Regulation, Market, Suppliers,
Internal drivers, Internal Management, Green Supply, Cooperation with Customers,
Investment recovery, Eco-design and reverse logistics, Environment Performance,
Operational Performance and Economical Performance) were tested with fifty four sub
variable. All twelve items in this part were based on a number of sources from the literature
and divided in three different parts. Questions were answered using a seven-point Likert-type
scale (e.g.1 = Very Strongly Disagree; 2 = Strongly Disagree; 3 = Disagree; 4 = Neutral; 5 =
Agree; 6 = Strongly Agree; 7 = Very Strongly Agree). To avoid confusing respondents on
three different seven-point Likert scales, we provided a brief explanation of the three groups
of items at the beginning of each survey section. 27 companies in the pharmaceutical industry
approved by the International Organization for Standardization 14001 certification in India
before January 2012 were sampled for empirical study. The data were then analyzed using
statistical package for the social sciences (Predictive Analytics Soft-Ware-PASW) and
LISREL (SIS Inc.)

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3.1 Variables
From the literature analysis, twelve different variables introduced according to the
methodology of structural equation modeling are described as follows: Environmental
regulations, market pressure, suppliers and internal drivers are four exogenous latent
variables used in this study. Environmental regulation reflects factors like regional laws,
exporting country’s regulations etc. The exogenous latent variables of market are reflected in
exports, sales, domestic consumers’ awareness towards environmental issues etc. Items like
cost of hazardous materials, environment friendly goods and green packages are revealed in
internal drivers. The endogenous latent variables are divided into interpretative and outcome
variables. Internal management, Green supply, cooperation with customers, investment
recovery, eco-deign and reverse logistics are variables which are defined as interpretative
endogenous latent variables. Outcome endogenous latent variables include economic
performance, environmental performance and operational performance.
3.2 Hypothesis
H1: Environmental regulations have a positive relationship with Green Supply Chain
Practices.
H2: External stakeholders have a positive relationship with GSCM practices.
H3: GSCM practices have a positive relationship with environmental performance.
H4: GSCM practices have a positive relationship with financial performance.
Table1: Elementary data analysis
Elementary Measure No. of companies %
Factor
Gender Male 27 100
Female 0 0
Job Title General Manager 11 40.75
Site Head 1 3.7
Environment Department 14 51.85
Head
Assistant Manager 1 3.7
Other 0 0
No. of Less than 100 3 11.1
Employees 100-200 10 37
200-500 9 33.3
500-1000 5 18.6
Greater than 1 0 0
Annual Sales Less than 10 crore 2 7.4
10-50 Crores 3 11.1
50-100 Crores 11 40.8
100- 500 Crores 8 29.6
Greater than 500 crores 3 11.1
Environment Yes 26 96.3
Department No 1 3.7
Age of GSCM < 1 Year 1 3.7
1-3 Year 7 25.9
3-5 Year 6 22.2
>5 years 13 48.1

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4. ANALYSIS

Table1 presents a detailed analysis of the demographic characteristics of respondents’
firms. There was no female representative throughout the survey. More than 50% respondents
were head of the environment department. 40.75 % respondents were general manager from
departments like supply chain, purchase, marketing etc.
As regards employees, 18.6 percent of respondents’ firms had over 500-1000 employees,
while one third companies have employed persons in range of 200-500. About 37%
companies have employed between 100 and 200 full-time workers.
Firms’ sales varied considerably. Just over a quarter (29.6percent)of firms’ sales was between
Rs. 100 500 Crores and 40.8 percent reported sales of Rs. 50-100 Crores. Almost half of the
industries surveyed have replied that their organizations are active players in GSCM field
since last 5 or more years. Almost every organization have environmental department in their
organizations.

4.1 Offending estimate
In the evaluation of model variables, there is unlikely to be a negative error variance
or a very large standard error, and the standardized coefficient cannot be larger than 0.95. [1]
As can be seen from Table 3, all error variances are positive; standard errors are small,
ranging from 0.01 to 0.24, and standardized coefficients range from 0.50 to 0.95, which is
less than 0.95 and lies below the significance level, suggesting that the effect of offending
estimate was absent.

4.2 Reliability test
As can be seen from Table 4, the 13 observable variables’ R2 are between 0.57 and
0.90, conforming to the recommendation that the confidence R2 of an individual observable
variable should be larger than 0.50. Also, the construct reliability of the five latent variables
is between 0.75 and 0.94, complying with the requirement that the value should be larger than
0.6. [2]

4.3 Validity test
4.3.1 Convergent validity: The factor loadings (λ1“0λ13) of the observable variables shown
in Table 3 range from 0.76 to 0.95, which achieve significance and are higher than the
threshold, 0.45, indicating that all observable variables can reflect the latent variables
constructed. The extracted average variances of the latent variables are 0.78, 0.85, 0.81, 0.60
and 0.79, all of which are larger than 0.5, indicating that the amount contributed to the latent
variables is larger for the observed variables than for the error in measurements. [2]

4.3.2 Discriminate validity: The latent variables shown in Table 5 have all reached the
significance level, indicating that there is a discrepancy between the model in which the
correlation between any two latent variables is set to be 1.00 and the model in which the
correlations for all latent variables are arbitrarily estimated. This discrepancy suggests that
the correlation between latent variables can be distinguished, i.e., the discriminate validity is
supported.

4.3.3 Test for overall model fit: The overall model fit is required to adopt at least the
following three fit tests [1]:

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4.3.4 Absolute fit test:
1. GFI (Goodness of fit index)
A good fit requires the GFI to be larger than 0.90. The theoretical model fit of the present
study is 0.91, indicating a good fit.
Table 2: Averages, standard deviations, skewness coefficients and kurtosis coefficients of
observed variables
Dimension Average SD Skewness Kurtosis
coefficient Coefficient
Environmental regulations
Domestic environmental regulations 5.69 0.90 -0.55 -0.57
Government environmental policy 5.33 0.73 -0.09 -0.36
International environmental agreements 5.30 0.80 -0.14 -0.15
External stakeholders
Supplier 5.90 0.64 -0.68 -0.13
Customer 5.84 0.73 -1.51 2.69
Community stakeholders 5.88 0.68 -1.12 1.32
GSCM practices
Green procurement practices 5.69 0.84 0.01 -0.85
Green manufacturing practices 5.08 0.67 -0.03 -1.12
Environmental performance
Management performance 6.19 0.57 -1.19 0.78
Operational performance 6.16 0.67 -0.21 -1.20
Financial performance
Cost reduction 5.41 0.61 -0.34 -0.30
Market share growth 5.41 0.69 -0.21 -0.42
Profit increase 5.72 0.68 -0.96 0.01

2. RMR (Root mean square residual)
Good fit demands the RMR to be smaller than or equal to 0.05. The theoretical model fit is
0.046, and thus it qualifies as a good fit.
3. RMSEA (Root mean square error of approximation) RMSEA smaller than or equal to 0.05
is considered a good fit and the theoretical model fit here is 0.06, indicating that it is a good
fit.

4.3.5 Relative fit test:
1. NNFI (Non nor-med fit index)
NNFI, larger than 0.9 is generally considered acceptable. The value is 0.97 for the present
theoretical model, indicating that the present model is acceptable.
2. CFI (Comparative fit index)
CFI, larger than 0.9 is generally considered acceptable. The CFI is 0.97 for the present
theoretical model, indicating that the present model is acceptable.
Parsimonious fit test:
1. PNFI (Parsimony nor-med Fit Index)
A PNFI larger than 0.5 is generally considered as a good model. The value is 0.72 for the
present theoretical model, indicating that the present model is acceptable.

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2. PGFI (Parsimony Goodness of Fit Index)
A PGFI larger than 0.5 is generally considered as a good model. The value is 0.60 for the
present theoretical model, indicating that the present model is acceptable.
3. nor-med Chi-Square
An index of less than 3 is considered as a good fit. The value of the present model is 1.51,
indicating a good overall fit. Tests for overall model fit were performed in order to
understand the fit between the observed data and the hypothesized model. [19]

Table 3: Estimation of model parameters
Parameter Un-standardized Standard error t-value Standardized
Parameter estimate Parameter estimate
λ1 1.00 - - 0.89
λ2 0.88 0.048 18.39 0.95
λ3 0.93 0.053 17.54 0.93
λ4 1.00 - - 0.86
λ5 1.21 0.084 14.35 0.90
λ6 1.12 0.078 14.37 0.90
λ7 1.00 - - 0.92
λ8 0.76 0.067 11.42 0.88
λ9 1.00 - - 0.76
λ10 1.23 024 5.14 0.80
λ11 1.00 - - 0.85
λ12 1.27 0.083 15.32 0.95
λ13 1.13 0.083 13.61 0.86
γ1 0.28 0.08 3.39 0.28
γ2 0.39 0.12 3.22 0.27
β1 0.29 0.06 4.68 0.51
β2 0.30 0.06 5.12 0.45
δ1 0.11 0.02 6.44 0.27
δ2 0.10 0.02 4.95 0.19
δ3 0.09 0.02 4.92 0.18
δ4 0.17 0.03 6.67 0.21
δ5 0.05 0.01 3.94 0.10
δ6 0.09 0.02 5.33 0.14
ε1 0.11 0.04 2.47 0.15
ε2 0.10 0.03 3.59 0.22
ε3 0.14 0.04 3.78 0.43
ε4 0.17 0.06 3.03 0.37
ε5 0.10 0.02 6.58 0.27
ε6 0.05 0.02 2.87 0.10
ε7 0.12 0.02 6.47 0.26

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5. DISCUSSION AND CONCLUSION

GSCM is a relatively new green issue for the majority of India corporations. From the
perspective of management, GSCM is a management strategy, taking into account the effects of the
entire supply chain on environmental protection and economic development. However, the feasibility
of reaching the right balance between the environmental performance and financial performance is a
serious concern for corporations implementing GSCM. The present empirical study investigated the
GSCM practices adopted by the OEM and ODM-dominated pharmaceutical and electronic industry in
India in response to the EU ROHS and WEEE directives. The pressures or drives to implement
GSCM practices and the relationship between GSCM practices and environmental performance as
well as financial performance were also studied. The approach adopted in the present study included a
questionnaire and in-depth interviews with the pharmaceutical and electronic corporations approved
by the ISO14001 certification in India before December 2004. The findings obtained from the 151
valid samples are described as follows:

Table 4: Reliability of observed variables, as well as construct reliability and average variance
extracted of latent variables
Dimension R2 Construct Average variance
reliability extracted
Environmental regulations 0.91 0.78
Domestic environmental regulations 0.73
Government environmental policy 0.81
International environmental 0.82
agreements
External stakeholders 0.94 0.85
Supplier 0.79
Customers 0.90
Community stakeholders 0.86
GSCM practices 0.89 0.81
Green procurement practices 0.85
Green manufacturing practices 0.78
Environmental performance 0.75 0.60
Management performance 0.57
Operational performance 0.63
Financial performance 0.91 0.79
Cost reduction 0.73
Market share growth 0.90
Profit increase 0.74

Table 5: Convergent validity and discriminate validity
Latent variables Environmental External GSCM Environmental
regulations stakeholders practices performance
Environmental regulations 1.000
External stakeholders 0.295* 1.000
GSCM practices 0.798* 0.225* 1.000
Environmental performance 0.271* 0.431* 0.251* 1.000
Financial performance 0.396* 0.399* 0.267* 0.265*

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Hypothesis 1
The environmental regulations factors consist of three observed variables: domestic
environmental regulations, government environmental policy and international environmental
agreements. Their factor loadings, λ1, λ2 and λ3, of the environmental regulations factors of
latent variables are 0.89, 0.95 and 0.93, respectively. Their t values are all larger than the
significance level of 1.96, indicating that the preliminary fit index is favorable. On the other
hand, the path coefficient, γ1, of the normative factors to the latent variables of GSCM
practices is 0.28 and t is 3.39, suggesting that the normative factor has a positive relationship
with the investigation of GSCM practices.
Also, λ2 (government environmental policy) is 0.95, higher than λ1 (0.89) and λ3 (0.93) of
domestic environmental regulations and international environmental agreements,
respectively, indicating that the pressure on enterprises to adopt green supply chain
management practices comes from the government environmental policy of environmental
regulations factors.

Hypothesis 2
The factor loadings, λ4, λ5 and λ6, of the external stakeholders of latent variables are 0.86,
0.90 and 0.90, respectively, and their t values are all larger than the significance level of 1.96.
On the other hand, the path coefficient, γ2, of the external stakeholders factors to the latent
variables of GSCM practices is 0.27 and t is 3.22, suggesting that the external stakeholders
factors have a positive relationship with the investigation of GSCM practices. The values of
λ5 (customers) and λ6 (community stakeholders) are both equal to 0.90, indicating that
customers and community stakeholders of external stakeholders have a larger effect on
enterprises’ adoption of green supply chain management practices than suppliers. A possible
cause, as revealed in the in-depth interviews conducted in this study, can be identified from
the fact that some interviewees regard suppliers as enterprises’ internal stakeholders.

Hypothesis 3
GSCM practices consist of two observed variables: green manufacturing practices, including
green design, manufacturing green products, recovery and reuse of used products, and setting
standards for green products, and green procurement practices, including establishing a
control list of environmentally hazardous substances, the profile for raw materials containing
no prohibited substances, the assessment table of environmental management for suppliers,
the green product approval data, and the auditing mechanism for green management. The
factor loadings, λ7 and λ8, of the environmental performance of latent variables are 0.92 and
0.88, respectively, and their t values are both larger than the significance level of 1.96. On the
other hand, the path coefficient, β1, of GSCM practices to the latent variable environmental
performance is 0.51 and t is 4.68, indicating that the investigation of GSCM practices has a
positive relationship with the environmental performance of corporations.

Hypothesis 4
The path coefficient, β2, of GSCM practices to the latent variable financial performance is
0.45 and t is 5.12, indicating that the investigation of GSCM practices has a positive
relationship with financial performance. On the other hand, the investigation of GSCM
practices can provide benefits to organizations, including cost reduction, market share growth
and profit increase, whose effects on financial performance are reflected by the values λ11
(0.85), λ12 (0.95) and λ13 (0.86), respectively; the most significant effect of enterprises’
investigation of GSCM practices is, therefore, in enhancing market share growth. The above

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findings suggest that the pressure or drive from environmental regulations, suppliers,
consumers and community stakeholders have prompted the pharmaceutical and electronic
manufacturers in India to implement GSCM practices. From the present study, it is found that
regulations and external stakeholders exert pressure on corporations to implement GSCM
practices. [14, 37] Furthermore, it was found that the investigation of GSCM practices can
enhance the environmental and financial performance of corporations, consistent with the
findings of who emphasized the beneficial effects of the investigation of GSCM practices in
improving environmental and financial performance. [30, 36] A corporation should not
overlook long-term sustainability while pursuing short-term profit. It is important to pursue
economic development and at the same time consider environmental burden, thereby
preserving the natural resources and environment on which the entire human race is
dependent, instead of relentlessly exploiting available resources. In pursuing economic
development, social justice has to be taken into account in order to strike the right balance
between economy, environment and benefit to society. It is therefore suggested that future
research may focus on the relationship between GSCM practices and sustainable
performance. Enterprises used to be concerned only with their own profit, ignoring the most
important links in their production chain: upstream suppliers and downstream customers. The
present study found that, in the face of the current global green issue, corporations can benefit
from an entirely green supply chain by cooperating with upstream suppliers on green
production technology and exchanging green information with them, as well as taking the
voices of downstream customers and green consumers into account in their production
processes. The conventional end-of-pipe treatment approach taken by corporations in face of
environmental problems can no longer meet the demands of international environmental
protection. To meet the expectations of society, pollution preventive measures should be
adopted as an environmental management strategy. However, corporations in general are
concerned that stressing environmental performance would add to their operational cost,
accompanied by a decreasing market share and competitiveness. Nevertheless, the present
study found that the investigation of GSCM practices has a positive effect on environmental
and financial performance; that is, an increase in environmental performance will be
accompanied by increased corporation profit and market share. These conclusions effectively
dispel the doubts of those corporations in India that have not yet implemented GSCM
practices.
Environmental protection activities can have a positive effect on a corporation’s financial
performance. GSCM can cut the cost of materials purchasing and energy consumption,
reduce the cost of waste treatment and discharge, and avoid a fine in the case of
environmental accidents. [51] A sustainable approach can lead to internal cost saving, open
new markets and find beneficial uses for waste. [44] Environmental munificence has a
positive effect on financial performance for example, growth in profits, sales and market
share. [12] Financial performance is defined here as cost reduction, market share growth and
profit increase. To analyze the research issues a hypothesis:

Tools and parameters
“The relationship between green supply chain management practices and organizational
performances,” was created as the tool of the present study. The items in the questionnaire
were then taken as research variables according to the conceptual model of the study. The
operational definitions of the research variables are shown in Table 1. According to the
methodology of structural equation modeling, the variables of the present research are
described as follows:

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Exogenous variables
There are two exogenous latent variables in the present study: environmental regulations and
external stakeholders. The exogenous latent variables of environmental regulations are
reflected in domestic environmental regulations, government policies on environmental
protection and international environmental agreements. On the other hand, the exogenous
latent variables of external stakeholders are reflected in suppliers, customers and community
stakeholders.

Endogenous variables
The endogenous latent variables in the present study are divided into interpretative variables
and outcome variables for the final outcome according to the cause–effect relation.
Interpretative variables adopted in green supply chain management practices are reflected in
two observed variables, green procurement practices and green manufacturing practices.
Outcome variables include environmental and financial performance. Environmental
performance is reflected in two observable variables, environmental management
performance and environmental operation performance, whereas financial performance is
reflected in three observable variables, namely cost reduction, market share growth and profit
increase.

6. REFERENCES

1. Bagozzi R.P.; Yi Y. (1988) On the evaluation of structural equation models, Jr. Acad.
Mark. Sci., 16, 74-94.
2. Bentler P.M.; Wu E J.C. (1993) EQS/Windows user’s guide. Los Angeles: BMDP
Statistical software.
3. Breen L. and Xie Y. (2009), Examining the role of the customer in facilitating reverse
logistics system in NHS community pharmacy in the UK, proceeding of the Logistics
Research Network annual conference, 9-11 September, 2009, Cardiff, UK, 588-591.
4. Brent, A.C.; Visser, J.K., (2005). An environmental performance resource impact
indicator for life cycle management in the manufacturing industry, J. Clean. Prod. 13,
557-565.
5. Brown, G.(2006), Speech by the RtHon Gordon Brown MP, Chancellorof the
Exchequer, to United Nations Ambassadors, New York,NY,April2006.
6. Cetindamar, D. (2001), “The role of regulations in the diffusion of Environment
technologies: Micro and macro issues”, European Journal of Innovation Management,
Vol.4No.4, pp.186-93.
7. Cheng, J., Yeh, C. and Tu, C.(2008),“Trust and knowledge sharing in green supply
chains”, Supply Chain Management: An International Journal, Vol.13 No.4, pp.283-
95.
8. Chien, M. K., Shith, L. H., (2007), An empirical study of the implementation of green
supply chain management practices in the electrical and electronics industry and their
relation to organizational performances. 4(3), 383-394
9. Conover, William Jay (1999). Practical Nonparametric Statistics (Third Edition ed.).
Wiley, New York, NY USA. pp. 388–395. ISBN0471160687 9780471160687
10. Daft, R.L., (1995). Organization Theory and Design. (5th. Ed.). New York: West
Publishing Company.
11. Food_ and_ Drug_ Control_ Administration_(FDCA)

665


12. Fuentes-Fuentes, M.M.; Albacete-Saez, C.A.; Llorens-Montes, F.J., (2004). The
impact of environmental characteristics on TQM principles and organizational
performance, Int. J. Manage. Sci., 32, 425-442.
13. Ghobadian, A., Viney, H. and Holt, D. (2001), “Seeking congruence in implementing
corporate environmental strategy”, International Journal of Environmental
Technology and Management, Vol.1 No.4 , pp.384-401.
14. Gottberg, A.; Morris, J.; Pollard, S.; Mark-Herbert C.; Cook, M., (2006). Producer
responsibility, waste minimization and the WEEE Directive: Case studies in eco-
design from the Europen lighting sector, Sci. Total Environ., 359, 38-56.
15. Hall, J., (2000). Environmental supply chain dynamics, J. Clean. Product., 8, 455-471.
16. Hart, S., 1995. A natural resource-based view of the firm. Academy of Management
Review, 20(4), 30-37.
17. Hervani, A.A.; Helms, M.M.; Sarkis, J., (2005). Performance measurement for green
supply chain management, Benchmarking: An Int. J., 12, 4,330-353.
18. Hong, P., Known, H-B., Roh, J. J.,(2009), Implementation of strategic green
orientation in supply chain An empirical study of manufacturing firms”, European
Journal of Innovation Management, Vol.12 No.4, pp.512-532
19. Hu, L.T.; Bentler, P.M., (1999). Cutoff criteria for fit indexes in covariance structure
analysis: conventional criteria versus new alternatives. Struct. Equ. Model., 6(1), 1-
55.
20. Kline, Rex B., (1998). Principles and practice of structural equation modeling. New
York: The Guilford press.
21. Knight, L.K. (2005) Roles, Relationships and Dynamics of the Pharma Network. A
discussion document on opportunities for supply research, Draft internal report to the
NHS Purchasing and Supply Agency 2005.
22. Kotler, P. & Keller, K. L., 2009, Marketing Management, 13th edn., Pearson-Prentice
Hall.
23. Lambert, D.M., Cooper, M.C. and Pagh, J.D.(1998),“Supply chain management:
implementation Issues and research opportunities”, International Journal of Logistic
Management,Vol.9No.2,pp.1-16.
24. Lewis, H. and Gretsakis, J. (2001), Design + Environment: A Global Guide to
Designing Greener Goods. Greenleaf Publishing, Sheffield.
25. New Hampshire Department of Environmental Services (2009) “How to address
unwanted medicine disposal in New Hampshire”, available at: http://des.nh.gov
/organization/commissioner/pip/publications/wmd/documents/unused_medicine.pdf
(accessed 28 May 2009)
26. New, S., Green, K., Morton, B., 2002. An analysis of private versus public sector
responses to the environmental challenges of the supply chain. Journal of Public
Procurement 2 (1), 93–105.
27. Oliver, R. K. and Webber, M.D. (1982), “Supply chain management: logistics catches
up with strategy”, in Christopher, M. (Ed.), Logistics: The Strategic Issues, Chapman
& Hall, London, reprinted 1992.
28. Pandya Amit R. & Mavani Pratik M. An Empirical Study of Green Supply Chain
Management Drivers, Practices and Performances: With Reference to the
Pharmaceutical Industry of Ankleshwar I.J.E.M.S., ISSN 2229-600X VOL.3 (3) 2012
pp. 339-355

666


29. Pilkington, A. and Dyerson, R. (2006),“Innovation in disruptive regulatory
environments: a patent study of electric vehicle technology development”, European
Journal of Innovation Management,Vol.9No.1,pp.79-91.
30. Purba, R., (2002). Greening the supply chain: A new initiative in South East Asia, Int.
J. Oper. Prod. Manage., 22(6), 632-655.
31. Rao P. 2002. Greening the supply chain: a new initiative in South East Asia.
International Journal of Operations and ProductionManagement 22: 632–655.
32. Ritchie, L., Burnes, B., Whittle, P. and Hey, R. (2000), “The benefits of reverse
logistics: the case of the Manchester Royal Infirmary Pharmacy”, Supply Chain
Management: An International Journal, Vol. 5 No. 5, pp. 226-233.
33. Robinson,R. and Wilcox,S. (2008), “The greening of supply chains”, Supply Chain
Management Review, Vol.12No.7, pp.61-6.
34. Sarkis, J. (2003), “A strategic decision making framework for green supply chain
management”, Journal of Cleaner Production, Vol. 11 No. 4, pp. 397-409.
35. Sarkis, J., (1998). Theory and Methodology Evaluating environmentally conscious
business practices, Eur. J. Oper. Res. 107, 159-174.
36. Sarkis, J., (2001). Greening supply chain management, GMI 35 Autumn, Greenleaf
publishing.
37. Seuring , S., (2004). Integrated chain management and supply chain management
comparative analysis and illustrative cases. J. Clean. Prod., 12, 1059-1071.
38. Savage, C.J., Roberts, K.J., and Wang, X.Z. (2006), “A holistic analysis of
pharmaceutical manufacturing and distribution: are conventional supply chain
techniques appropriate?” Pharmaceutical Engineering, July/August, pp. 10-18.
39. Schiffman, L. G. & Kanuk, L. L., 2007, Consumer Behavior, 9th edn., Pearson
Prentice Hall, Upper Saddle River, New Jersey, 561 pages.
40. Seuring , S., (2004). Integrated chain management and supply chain management
comparative analysis and illustrative cases. J. Clean. Prod., 12, 1059-1071.
41. Sheth, J.N.; Sharma, A., (1997). Supplier relationships, Ind. Market. Manage., 26, 91-
100.
42. The Department of Pharmaceuticals, Ministry of Chemicals and Fertilizers, 2011, “A
brief report on pharmaceutical industry of India.” US Environmental Protection
Agency (USEPA). 2001. 1999
43. Toxic Release Inventory: Public Data Release, EPA 260-R- 01-001.USEPA, Office of
Environmental Information: Washington, DC.
44. Tsoulfas, G.T.; Pappis, C.P., (2006). Environmental principles applicable to supply
chains design and operation , J. Clean. Prod., 14, 1593-1602.
45. Van Eijken M., Tsang S., Wensing M., De Smet P.A.G.M., and Grol R.P.T.M.
(2003), “Interventions to improve medication compliance in older patients living in
the community: A systematic review of the literature”. Drugs & Aging., Vol. 20 No.3,
pp. 229-240.
46. Van Hock, R.I. and Erasmus (2000), “From reversed logistics to green supply
chains”, Logistics Solutions, No. 2, pp. 28-33.
47. Walton V S, Hadfield R B, Melnyk S A. (1998). The green supply chain: integrating
suppliers into environmental management process[J]. International Journal of
Purchasing and Materials Management, 4:2-10

667


48. Xianbing, L., Leina W., Jie Y., Tomohiro S., Cunkuan B., Kazunori O., (2010),
“Practices and Opportunities of Green Supply Chain Management in China”, the 1st
Congress of East Asian Association of Environmental and Natural Resource
Economics, Hokkaido University, Japan
49. Xie Y. (2009), “Greening pharmaceutical supply chain in China”, In proceedings of
the 20th International Conference on Production Research, 2nd-6th August, Shanghai,
P.R.China, pp137
50. Xie, Y., Breen, L., (2010),“Green Community Pharmaceutical Supply Chain in UK:
Reducing and Recycling Pharmaceutical Waste”, POMS, 21st Annual Conference
Vancouver, Canada.
51. Zhu, Q., and Sarkis, J. (2004). Relationships between operational practices and
performance among early adopters of green supply chain management practices in
Chinese manufacturing enterprises. Journal of Operations Management, 22(3), 265-
289.
52. Zhu, Q., Sarkis J., Geng Y., (2004). Green supply chain management in China:
pressures, practices and performances. IJO & Production Management. 25, 449-468.
53. Zhu, Q.; Cote, R.P., (2003). Green supply chain management in China: why and
how?, Internet Conference on Ecocity Development
54. Zhu, Q.; Cote, R.P., (2004). Integrating green supply chain management into an
embryonic eco-industrial development: a case study of the Guitang Group, J. Clean.
Prod., 12,1025- 1035.
55. Zhu, Q.; Sarkis, J., (2004). Relationships between operational practices and
performance among early adopters of green supply chain management practices in
Chinese manufacturing enterprises, J. Oper. Manage. 22, 265-289.
56. Zhu, Q.H., Sarkis, J., Cordeiro, J.J., Lai, K.H., 2008. Firmlevel correlates of emergent
green supply chain management practices in the Chinese context. Omega, 36(4), 577-
591.

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