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A Framework for the Analysis of Sustainable Supply Chain Management: An Insight from Indian Rubber Industry


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Industrial operations could emit harmful pollutants and degrade natural environment, thereby posing a threat to human beings and wildlife (polar bears, panda, penguins, turtles, whales, walrus etc.). Globally manufacturers must ensure that the operations be done as safely and responsibly as possible keeping in line with the three dimensions of triple bottom line. We develop a framework which analyses the various complex relationships involved in a sustainable supply chain with the aid of interpretive structural modeling. The key factors influencing sustainable supply chain were identified based on a thorough literature review and in consultation with rubber industry experts. Further MICMAC analysis was applied to identify the autonomous, linkage, dependent and independent factors. Keywords: Sustainable Supply Chain Management (SSCM), Indian Rubber Industry, Interpretative Structural Modeling, MICMAC.
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Industrial operations could emit harmful pollutants and degrade natural environment, thereby posing a threat to human beings and
wildlife (polar bears, panda, penguins, turtles, whales, walrus etc.). Globally manufacturers must ensure that the operations be
done as safely and responsibly as possible keeping in line with the three dimensions of triple bottom line. We develop a framework
which analyses the various complex relationships involved in a sustainable supply chain with the aid of interpretive structural
modeling. The key factors inuencing sustainable supply chain were identied based on a thorough literature review and in
consultation with rubber industry experts. Further MICMAC analysis was applied to identify the autonomous, linkage, dependent
and independent factors.
Keywords: Sustainable Supply Chain Management (SSCM), Indian Rubber Industry, Interpretative Structural Modeling, MICMAC.
A Framework for the Analysis of Sustainable
Supply Chain Management: An Insight from
Indian Rubber Industry
Surajit Bag*, Neeraj Anand**, K.K. Pandey***
*PhD Scholar, College of Management and Economics Studies, University of Petroleum& Energy Studies,
Uttarakhand, Dehradun, India. Email:
**Professor, College of Management and Economics Studies, University of Petroleum& Energy Studies
Uttarakhand, Dehradun, India. Email:
***Associate Professor, College of Management and Economics Studies, University of Petroleum& Energy
Studies, Uttarakhand, Dehradun, India. Email:
India’s economy has grown very rapidly in recent
years. Since 1991 it has been among the top 10% of the
world’s countries in terms of economic growth. Before
the liberalization of its economy began in 1991, India
had been one of the most over-regulated and closed
economies in the world. But with the fast pace growth
of Indian economy has led to innite damages in the
environment due to industrial operations. Successful
environmental policies can contribute to efciency
by encouraging, rather than inhibiting, technological
innovation. However, little research to date has focused
on the design and implementation of sustainable supply
chains that ensure productivity improvements in the face
of increasing stringency of environmental regulations.
Reducing and mitigating carbon emissions, the culprit of
global warming and climate change, is an increasingly
important concern for both industry and government
(IPCC, 2007). The United Nations, the European Union,
and many countries have enacted legislations or designed
mechanisms, such as carbon taxes, carbon offset, clean
development, cap and trade, carbon caps, and made
joint implementation to curb the total amount of carbon
emissions. Firms worldwide, in response to such
mechanisms and legislations or to concerns raised by
their own customers, are undertaking initiatives to reduce
their carbon footprints.
However, these initiatives have largely focused on
investment in new technology, developing energy-
efcient equipment and facilities, nding less polluting
sources of energy, and implementing energy-saving
programmes. While such efforts are valuable, they tend to
ignore a potentially more signicant source of emissions
- one driven by business practices, production economics,
operational policies, interaction, and coordination, where
the ow of products to consumers engages multiple
rms in long and complex supply chains (NSF, 2010). It
is therefore necessary to address the problem of carbon
emissions reduction from a supply chain and logistics
The Indian rubber products manufacturing sector draws
its strength and stability from the rapidly growing demand
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 69
for the products in both domestic and overseas market.
The exports are well over 85 countries including US,
Russia, UK, Bangladesh, Afghanistan, Italy, Germany,
France, Saudi Arabia, UAE, Canada and the African
countries. The chemicals and the allied products export
promotion council co-ordinates activities connected with
the export of rubber products.
Indian rubber goods manufacturing sector faces major
challenge from environmental degradation resulting
from its various operations. Workers are exposed to these
hazards through inhalation and skin absorption during
rubber processing and product manufacturing. Risk of
cancer and other adverse health effects are high among
rubber products workers, DHHS (NIOSH), 93(106),
Sept 1993.CPCB has categorized this sector in the high
polluting RED category due to GHG emission and solid
waste generation and throughout the supply chain this
sector is trying hard to reduce their carbon emissions.
We have presented statistics of natural rubber and
synthetic rubber production, consumption, import and
export in Fig. 1 and 2. In Fig. 3 we have presented the
statistics of rubber goods exports.
The purpose of conducting literature review is to
understand whatsoever work has been carried out by
past researchers in the area of sustainable supply chain
management in the last decade.
Various secondary sources were considered to extract the
information and seminal papers from leading journals
such as IJPE, IJPR, Transportation Research, EJOR,
DSS, EJPSM, JOM and JPSM were referred to prepare
the groundwork for further research.
The summary of the literature on SSCM has been
tabulated in Table 1.
The review reveals various insights and gaps in the
existing GSCM literature.
1. Existing literature is not capable to explain the un-
derlying relationships among key variables in u-
encing SSCM practices in Indian Rubber Industry.
2. Lack of SSCM model for Indian Rubber Industry.
Fig. 1: Production, consumption, import and export
of natural rubber
Fig. 2: Production, consumption, import and export
of synthetic rubber
Fig. 3: Export of Rubber products
Source: Rubber Board
70 Journal of Supply Chain Management Systems Volume 3 Issue 1 January 2014
Table 1: Literature Review
Brandenburg et al.,
To understand and review
mathematical models focus-
ing on environmental/social
factors in the forward supply
Major publications and models were
found in a limited set of six journals
DSS). AHP, ANP and LCA were
commonly used tool for developing
the models.
Environmental, Social
and Economic dimen-
Mirhedayatian et al.,
To propose a novel network
DEA model for evaluating
the GSCM in the presence of
dual role factors, undesirable
outputs and fuzzy data.
The proposed model can be easily
computerized so as to serve as a
decision making tool in decision
Quantitative model-
Cost of quality, Sup-
plier  exibility, Car-
bon dioxide emission,
Satisfaction, Facility
technology level
Suering, S., (2013)
To review research on quan-
titative models for green or
sustainable supply chains.
Different kinds of models are
applied in this area but the social
dimension is not taken into consider-
ation. On the modeling side there are
three popular methods: Equilibrium
models, MCDM & AHP.
Environmental, Social
and Economic dimen-
Zhu and Lai. (2013) To develop and empirically
test a theoretical model.
The research contributes to the
literature on institutional theory in
corporate environmental practices.
Institution pressure:
Coercive, Normative,
Reefke and Trocchi
To develop a framework to
facilitate a balanced approach
to performance measurement
for SSCM.
A scorecard design customized for
sustainable supply chain is proposed
along with the development and
implementation process
Cost savings, Pro t,
customer satisfaction,
quality management
Liu et al. (2012) To integrate green marketing
and SSCM.
Development of a new hub and
spoke integration model. Drivers:
Improve company’s sustainable sup-
ply chain capabilities; reach green
customers before competitors; gov-
ernment regulations; green custom-
ers demand; community expectation
Products, Promotion,
Planning, Process,
People and Project
Hoejmose et al.
To understand the general
engagement with GSCM in
both B2B and B2C supply
Firms in B2B market is generally
less engaged with green practices
compared to  rms in B2C markets.
Developing Trust with supply chain
partners and top management com-
mitment is a crucial GSCM driver
among  rms in B2B markets.
Empirical Trust, Top manage-
ment commitment
Ageron et al. (2012)
To develop a Sustainable
Supply Management frame-
External pressures have positive im-
pact on the development of SSM;
Waste reduction programmes have
greater impact on greening supply
chains; MNC and SMEs’ have dif-
ferential impact on SSM; Financial
barriers have more impact on SSM;
Top management support is a critical
success factor in SSM; Key bene ts
such as customer satisfaction, sup-
plier innovation, quality and capacity
have greater positive impact on SSM.
Top Manage-
ment Commitment,
Govt. regulatory re-
quirements, Qual-
ity, Flexibility, Waste
Programs, Reducing
carbon footprint, Fi-
nancial costs, ROI,
Green Investments,
Customer Satisfaction,
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 71
Bose and Pal (2012)
To investigate the in uence
of GSCM initiatives on stock
prices of  rms.
Firms observe greater positive
change in stock price by undertak-
ing green initiatives. Firms with high
R&D expenses show strong positive
impact. Early adopters of GSCM
show greater positive impact.
Event Study R&D, Size of rm,
Stock prices
Dekker et al. (2012) To review research on green
The review highlighted the contribu-
tion of operations research to green
Mode choice, In-
termodal transport,
Equipment choice and
ef ciency, fuel choice
and carbon intensity
Chaabane et al. (2012)
To present a generic math-
ematical model to assist deci-
sion makers in designing sus-
tainable supply chains over
their entire life cycle.
The model can serve as a tool that fa-
cilitates the understanding of optimal
SC strategies under different envi-
ronmental policies.
Quantitative model-
Economic: Cost, reve-
nue, taxes, transfer En-
vironmental variables:
Carbon footprint, Raw
material use, Energy
use, Social variables:
Noise, pollution
Dubey and Bag (2013)
To explore sustainable manu-
facturing practices that im-
proves environmental and
business performance.
Green Purchasing, SRM, Green lo-
gistics and regulatory norms are
positive determinants of  rms busi-
ness performance and Environmental
Green Purchasing,
SRM, Green logistics
and Regulatory norms
and Spalanzani
To bring important issues re-
lated to sustainable business
development in both manu-
facturing and services sector.
Developed a framework for sustain-
able development along with strate-
gies, techniques and tools.
Sustainable Prod-
uct and process de-
sign, sustainability
in supply operations,
sustainability in pro-
duction operations,
sustainability in dis-
tribution operations,
sustainability through
reverse logistics
Gimenez et al. (2012)
To analyse the impact of en-
vironmental programmes on
each dimension of the triple
Internal environmental programmes
have a positive impact on the three
components of the triple bottom line.
Social initiatives have a positive im-
pact only on two components: social
and environmental performance .
and Economic perfor-
mance, Internal and
external action pro-
Hassisni et al. (2012)
To review literature on sus-
tainable supply chains from
Based on the ndings authors have
developed a framework for sustain-
able supply chain metrics.
Review and Case
Market Forces, Poli-
cyand Regulations,
Scienceand Technol-
ogy, Product Devel-
opment, Process Ca-
pability, Sourcingand
Operations, Logistics,
Marketing andPR, So-
cial issues
Barari et al. (2012)
To provide integrated and ho-
listic conceptual framework
that combines the practical
aspects of green supply chain
with the objective of pro t
With the help of evolutionary game
theory it has been possible to derive
the strategy set that not only prom-
ises maximum economic bene t and
presents a win-win situation.
Quantitative model-
Green tax, green bur-
72 Journal of Supply Chain Management Systems Volume 3 Issue 1 January 2014
Kang et al. (2012)
To establish the framework
for strategy development to
construct the sustainable sup-
ply chain.
Identi ed the factors. Theoretical
Leadership for knowl-
edge sharing, Innova-
tion of product and
Wanget al. (2011)
To provide a multi objective
mixed integerformulation for
the supply chain network de-
sign with environmental con-
The model can be effectively used in
the strategic planning for green sup-
ply chain.
Quantitative model-
Demand and Supply
of Product, Carbon
dioxide emission, ca-
pacity of facility, envi-
ronmental investment
cost, environmental
protection, Transpor-
tation cost, Handling
cost for products
Wu and Pagell (2011)
To understand how organ-
isations balance short term
pro tability and long term
environmental sustainability
when making supply chain
decisions under uncertainty.
Factors contributing to the uncertain
decision environment are as under:-
Uncertainty about environmental
outcomes and future regulation, the
saliency of each environmental issue
to multiple stakeholders, lack of vis-
ibility and in uence in one’s supply
Theoretical Operating principles,
Technical standard
Gupta and Desai
To review the current state of
academic research in sustain-
able supply chain manage-
Authors developed an integrative
framework summarizing the exist-
ing literature under four broad cat-
egories: strategic considerations,
decisions at functional interfaces,
regulation and government policies,
integrative models and decision sup-
port tools.
Product design
and product life
cycle,Regulation and
government policies
Azevedo et al. (2011)
To investigate the relation-
ships between green prac-
tices and supply chain perfor-
A conceptual model of the relation-
ships between green practices and
SC performance was developed.
Case Study
Environmental friend-
ly practices in pur-
chasing, Environmen-
tal collaboration with
suppliers, Minimizing
waste, Environmen-
tal collaboration with
customers, Reverse
Pereira (2009)
To understand how IT can
foster information manage-
ment and help sort out supply
chain problems.
IT must be used to develop SC strate-
gies to make supply chains more ro-
bust and resilient.
Conceptual Information Technol-
Longo and Mirabelli
To present an advance mod-
eling approach and a simula-
tion model and provide a de-
cision making tool for supply
An advance model is proposed based
on programming code, tables and
event generators and provides the
user with a simulator capable of high
ef ciency for executing simulation
Quantitative model-
Inventory Control,
Lead Time, Demand
Intensity, Demand
Linton et al. (2007)
To prepare a background to
better understand current
trends in the area of sustain-
able supply chains.
Research on Sustainable supply
chain is still at a infant stage.It is
strong links with government policy.
Product life extension,
Product design, Re-
covery process at end
of life.
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 73
1. What are the key variables in uencing SSCM
practices and the nature of relationship existing
between the variables in context to Indian Rubber
2. Can a SSCM model be developed for Indian
Rubber Industry?
Literature review has given a direction to identify the
research gaps and to develop the below two speci c
research objectives for the present study are as follows:-
1. To identify the key factors in uencing SSCM prac-
tices and understand the relationships in context to
Indian rubber goods manufacturing sector.
2. To develop a SSCM model for Indian rubber goods
manufacturing sector.
Phase I:
Based on the synthesis of literature review and ex-
perts opinion from rubber industry; the key variables
in uencing SSCM practices have been identi ed.
Phase II:
GSCM model has been developed by using ISM
technique which was further re ned using MICMAC
The research variables have been derived from the above
literature review. To reduce the redundancy and check
their relevancy in present Indian context the pretesting
has been carried out among ten selected experts who are
having more than 20 years of work experience. The  nal
shortlisted variables are as under:-
1. Supplier Relationship Management (SRM)
2. Customer Relationship (CR)
3. Top Management Commitment (TMC)
4. Regulatory Pressures (RP)
5. Market Pressures (MP)
6. Green Technology Adoption (GTA)
7. Total Quality Management (TQM)
8. Flexible operations (FO)
9. Technology Innovativeness (TI)
10. Cleaner Production (CP)
11. Environmental and Social Responsibility (ESR)
12. Carbon Emissions Reduction (CER)
13. Export Sales (ES)
14. Market Share (MS)
15. Pro t (PR)
ISM is a proven and popular methodology for
understanding relationships among speci c items that
de ne a problem. ISM is useful to achieve the objective
in presence of large number of directly and indirectly
related elements and complex interactions among them
Zhu and Sarkis (2004)
To determine the economic
and environmental relation-
ships of GSCM practices
among Chinese  rms.
Signi cant win-win opportunities
exist for Chinese rms practicing
GSCM. Strong relationship exists
between GSCM practice and positive
economic performance.
Commitment of
GSCM from senior
managers, Total qual-
ity environmental
management, Envi-
ronmental compliance
and auditing pro-
grams, Supplier rela-
tionship, green design
Croom et al. (2000) To conduct literature review.
Lack of theoretical work in the  eld
as compared to empirical based stud-
Sourcing strategy, at-
titude and commit-
ment to collaborative
improvement pro-
74 Journal of Supply Chain Management Systems Volume 3 Issue 1 January 2014
which may or may not be expressed in a proper manner.
ISM plays a vital role in this kind of situation and helps
in understanding a structure within a system. The ISM
model depicts the structure of a complex problem in a
carefully designed pattern.
ISM has been used in the past by several researchers due
to multiple bene ts. It guides and records the results of
group response on complex issues in an ef cient and
systematic manner, (Source: Attri et al., 2013; War eld
1994, 1974).ISM has been applied in different areas of the
supply chain starting from purchasing to production and
logistics management. Dubey et al., (2013) have applied
ISM to understand the contextual relationship among
antecedents of truck freight.Sushil (2012) hascontributed
in the ISM literature by providing directions to interpret
the links in ISM using the tool of interpretive matrix.
ISM steps are as follows:
1. Developing the structural self interaction matrix
For developing SSIM, the below symbols have been used
to denote the direction of relationships between variables
(i and j):
V: i leads to j but j does not lead to i
A: i does not lead to j but j leads to i
X: i leads to j and j leads to i
O: i and j are unrelated to each other
2. Develop Reachability Matrix
The SSIM has been converted into a binary matrix i.e.,
the reachability matrix (Table 4) by substituting V, A, X
and O by 1 and 0. The substitutions of ‘1’ and ‘0’ have
been done as below:
i. If the (i, j) entry in the SSIM is V, then the (i.j) en-
try in the reachability matrix becomes ‘1’ and (j,i)
entry becomes ‘0’
ii. If the (i, j) entry in the SSIM is A, then the (i.j) en-
try in the reachability matrix becomes ‘0’ and (j,i)
entry becomes ‘1’
iii. If the (i, j) entry in the SSIM is X, then the (i.j) en-
try in the reachability matrix becomes ‘1’ and (j,i)
entry also becomes ‘1’
iv. If the (i, j) entry in the SSIM is O, then the (i.j) en-
try in the reachability matrix becomes ‘0’ and (j,i)
entry also becomes ‘0’
Matrice d’ Impacts croises multiplication appliqué an
classment (cross-impact matrix multiplication applied to
classi cation) is abbreviated as MICMAC. The objective
of MICMAC analysis is to analyze the drive power and
dependence power of factors. Based on the drive power
and dependence power the factors have been classi ed
into four factors: autonomous factors, linkage factors,
dependent and independent factors.
Table 2: Review on ISM application
Author and Year ISM Application
Hawthrone and Sage(1975) Higher education program planning
Sage (1977) Modeling complex situations
Jedlica and Meyer (1980) Exploring factors involved in a cross cultural context
Saxena et al. (1992) Determining the hierarchy and class of elements in cement industry
Mandal and Desmukh (1993) Vendor selection
Kanungo et al. (1999) Developing an IS effectiveness framework
Ravi and Shankar (2004) Explore reverse logistics barriers
Jharkaria and Shankar (2005) Enablers of IT implementation in SC
Ravi et al. (2005) Indentify key reverse logistics variables
Faisal et al. (2006) Modeling the enablers for supply chain risk mitigation
Thakkar et al. (2006) Integrated approach with ISM and ANP to develop a balanced scorecard
Source: Diabat et al. 2013
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 75
Table 3: Structural self -interaction matrix (SSIM)
15 14 13 12 11 10 9 8 7 6 5 4 3 2 1
1 V O V V A V V V V V A A A O
2 V V V A A A A X V A O O A
3 V V V V V V V V V V A A
4O O O V V V V O O V X
5O O O V V V V V V V
6V V V V X V A A A
7 V V V V X V V V
8V O O O O A A
9V O O V A V
10 V O V V A
11 O V V V
12 V V V
13 V V
14 V
Table 4: Reachability Matrix
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DRIVING POWER (Y)
1 1 0 0 0 0 1 1 1 1 1 0 1 1 0 1 9
2 0 1 0 0 0 0 1 1 0 0 0 0 1 1 1 6
3 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 13
4 1 0 1 1 1 1 0 0 1 1 1 1 0 0 0 9
5 1 0 1 1 1 1 1 1 1 1 1 1 0 0 011
60 1 0 0 0 1 0 0 0 1 1 1 1 1 1 8
70 0 0 0 0 1 1 1 1 1 1 1 1 1 1 10
8 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 4
9 0 1 0 0 0 1 0 1 1 1 0 1 0 0 1 7
10 0 1 0 0 0 0 0 1 0 1 0 1 1 0 1 6
11 1 1 0 0 0 1 1 0 1 1 1 1 1 1 0 10
12 0 1 0 0 0 0 0 0 0 0 0 1 1 1 1 5
13 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 3
14 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2
15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
DEPENDENCE POWER (X) 5 8 3 2 2 9 6 8 7 9 6 10 8 8 12
Cluster 1: Autonomous variables
These factors have a weak drive power and weak
dependence power. In this cluster we do not have any
Cluster 2: Dependence variables
These factors have a weak drive power but strong
dependence power. In this cluster we have seven variables,
i.e, 2 (Customer Relationship),8 (Flexible operations),10
(Cleaner Production),12 (Carbon Emissions Reduction),13
(Export Sales), 14 (Market Share) and 15(Pro t)
Cluster 3: Linkage variables
76 Journal of Supply Chain Management Systems Volume 3 Issue 1 January 2014
Table 5: Transivity
TRANSIVITY 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1 1 1* 0 0 0 1 1 1 1 1 1* 1 1 1* 1
2 0 1 0 0 0 1* 1 1 1* 1* 1* 1* 1 1 1
3 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1
4 1 1* 1 1 1 1 1* 1* 1 1 1 1 1* 1* 1*
5 1 1* 1 1 1 1 1 1 1 1 1 1 1* 1* 1*
6 1* 1 0 0 0 1 1* 1* 1* 1 1 1 1 1 1
7 1* 1* 0 0 0 1 1 1 1 1 1 1 1 1 1
8 0 1 0 0 0 1 1* 1 0 1* 1* 1* 1* 1* 1
9 0 1 0 0 0 1 1* 1 1 1 1* 1 1* 1* 1
10 0 1 0 0 0 1* 1* 1 0 1 0 1 1 1* 1
11 1 1 0 0 0 1 1 1* 1 1 1 1 1 1 1*
12 0 1 0 0 0 0 1* 1* 0 0 0 1 1 1 1
13 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1
14 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
Table 6: Level Partitioning (Iteration 1)
1 1,2,6,7,8,9,10,11,12,13,14,15 1,3,4,5,6,7,11 1,6,7,11
2 2,6,7,8,9,10,11,12,13,14,15 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,9,10,11,12
3 1,2,3,6,7,8,9,10,11,12,13,14,15 3,4,5 3
4 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 4,5 4,5
5 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 4,5 4,5
6 1,2,6,7,8,9,10,11,12,13,14,15 1,2,3,4,5,6,7,8,9,10,11 1,2,6,7,8,9,10,11
7 1,2,6,7,8,9,10,11,12,13,14,15 1,2,3,4,5,6,7,8,9,10,11,12 1,2,6,7,8,9,10,11,12
8 2,6,7,8,10,11,12,13,14,15 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,10,11,12
9 2,6,7,8,9,10,11,12,13,14,15 1,2,3,4,5,6,7,9,11 2,6,7,9,11
10 2,6,7,8,10,12,13,14,15 1,2,3,4,5,6,7,8,9,10,11 2,6,7,8,10
11 1,2,6,7,8,9,10,11,12,13,14,15 1,2,3,4,5,6,7,8,9,11 1,2,6,7,8,9,11
12 2,7,8,12,13,14,15 1,2,3,4,5,6,7,8,9,10,11,12 2,7,8,12
13 13,14,15 1,2,3,4,5,6,7,8,9,10,11,12,13 13
14 14,15 1,2,3,4,5,6,7,8,9,10,11,12,13,14 14
15 15 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 15 1
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 77
Table 7: Level Partitioning (Iteration 2)
1 1,2,6,7,8,9,10,11,12,13,14 1,3,4,5,6,7,11 1,6,7,11
2 2,6,7,8,9,10,11,12,13,14 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,9,10,11,12
3 1,2,3,6,7,8,9,10,11,12,13,14 3,4,5 3
4 1,2,3,4,5,6,7,8,9,10,11,12,13,14 4,5 4,5
5 1,2,3,4,5,6,7,8,9,10,11,12,13,14 4,5 4,5
6 1,2,6,7,8,9,10,11,12,13,14 1,2,3,4,5,6,7,8,9,10,11 1,2,6,7,8,9,10,11
7 1,2,6,7,8,9,10,11,12,13,14 1,2,3,4,5,6,7,8,9,10,11,12 1,2,6,7,8,9,10,11,12
8 2,6,7,8,10,11,12,13,14 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,10,11,12
9 2,6,7,8,9,10,11,12,13,14 1,2,3,4,5,6,7,9,11 2,6,7,9,11
10 2,6,7,8,10,12,13,14 1,2,3,4,5,6,7,8,9,10,11 2,6,7,8,10
11 1,2,6,7,8,9,10,11,12,13,14 1,2,3,4,5,6,7,8,9,11 1,2,6,7,8,9,11
12 2,7,8,12,13,14 1,2,3,4,5,6,7,8,9,10,11,12 2,7,8,12
13 13,14 1,2,3,4,5,6,7,8,9,10,11,12,13 13
14 14 1,2,3,4,5,6,7,8,9,10,11,12,13,14 14 2
Table 8: Level Partitioning (Iteration 3)
1 1,2,6,7,8,9,10,11,12,13 1,3,4,5,6,7,11 1,6,7,11
2 2,6,7,8,9,10,11,12,13 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,9,10,11,12
3 1,2,3,6,7,8,9,10,11,12,13 3,4,5 3
4 1,2,3,4,5,6,7,8,9,10,11,12,13 4,5 4,5
5 1,2,3,4,5,6,7,8,9,10,11,12,13 4,5 4,5
6 1,2,6,7,8,9,10,11,12,13 1,2,3,4,5,6,7,8,9,10,11 1,2,6,7,8,9,10,11
7 1,2,6,7,8,9,10,11,12,13 1,2,3,4,5,6,7,8,9,10,11,12 1,2,6,7,8,9,10,11,12
8 2,6,7,8,10,11,12,13 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,10,11,12
9 2,6,7,8,9,10,11,12,13 1,2,3,4,5,6,7,9,11 2,6,7,9,11
10 2,6,7,8,10,12,13 1,2,3,4,5,6,7,8,9,10,11 2,6,7,8,10
11 1,2,6,7,8,9,10,11,12,13 1,2,3,4,5,6,7,8,9,11 1,2,6,7,8,9,11
12 2,7,8,12,13 1,2,3,4,5,6,7,8,9,10,11,12 2,7,8,12
13 13 1,2,3,4,5,6,7,8,9,10,11,12,13 13 3
Table 9: Level Partitioning (Iteration 4)
1 1,2,6,7,8,9,10,11,12 1,3,4,5,6,7,11 1,6,7,11
2 2,6,7,8,9,10,11,12 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,9,10,11,12
3 1,2,3,6,7,8,9,10,11,12 3,4,5 3
4 1,2,3,4,5,6,7,8,9,10,11,12 4,5 4,5
5 1,2,3,4,5,6,7,8,9,10,11,12 4,5 4,5
6 1,2,6,7,8,9,10,11,12 1,2,3,4,5,6,7,8,9,10,11 1,2,6,7,8,9,10,11 4
7 1,2,6,7,8,9,10,11,12 1,2,3,4,5,6,7,8,9,10,11,12 1,2,6,7,8,9,10,11,12 4
78 Journal of Supply Chain Management Systems Volume 3 Issue 1 January 2014
8 2,6,7,8,10,11,12 1,2,3,4,5,6,7,8,9,10,11,12 2,6,7,8,10,11,12 4
9 2,6,7,8,9,10,11,12 1,2,3,4,5,6,7,9,11 2,6,7,9,11
10 2,6,7,8,10,12 1,2,3,4,5,6,7,8,9,10,11 2,6,7,8,10
11 1,2,6,7,8,9,10,11,12 1,2,3,4,5,6,7,8,9,11 1,2,6,7,8,9,11
12 2,7,8,12 1,2,3,4,5,6,7,8,9,10,11,12 2,7,8,12 4
Table 10: Level Partitioning (Iteration 5)
1 1,2,9,10,11 1,3,4,5,11 1,11
2 2,9,10,11 1,2,3,4,5,9,10,11 2,9,10,11 5
3 1,2,3,9,10,11 3,4,5 3
4 1,2,3,4,5,9,10,11 4,5 4,5
5 1,2,3,4,5,9,10,11 4,5 4,5
9 2,9,10,11 1,2,3,4,5,9,11 2,9,11
10 2,10 1,2,3,4,5,9,10,11 2,10 5
11 1,2,9,10,11 1,2,3,4,5,9,11 1,2,9,11
Table 11: Level Partitioning (Iteration 6)
1 1,9,11 1,3,4,5,11 1,11
3 1,3,9,11 3,4,5 3
4 1,3,4,5,9,11 4,5 4,5
5 1,3,4,5,9,11 4,5 4,5
9 9,11 1,2,3,4,5,9,11 9,11 6
11 1,9,11 1,2,3,4,5,9,11 1,9,11 6
Table 12: Level Partitioning (Iteration 7)
1 1 1,3,4,5 1 7
3 1,3 3,4,5 3
4 1,3,4,5 4,5 4,5
5 1,3,4,5 4,5 4,5
Table 13: Level Partitioning (Iteration 8)
3 3 3,4,5 3 8
4 3,4,5 4,5 4,5
5 3,4,5 4,5 4,5
Table 14: Level Partitioning (Iteration 9)
4 4,5 4,5 4,5 9
5 4,5 4,5 4,5 9
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 79
Table 15: Position coordinates of identifi ed variables
Variables Dependence Power (X) Driving Power(Y)
1 5 9
2 8 6
3 3 13
4 2 9
5 2 11
6 9 8
7 6 10
8 8 4
9 7 7
10 9 6
11 6 10
12 10 5
13 8 3
14 8 2
15 12 1
Fig. 4: ISM Model
80 Journal of Supply Chain Management Systems Volume 3 Issue 1 January 2014
These factors have a strong drive power as well as strong
dependence power. In this cluster we have three variables, i.e., 6
(Green Technology Adoption), 7 (Total Quality Management),
9 (Technology Innovativeness)and 11(Environmental and
Social Responsibility).
Cluster 4: Driving variables
These factors have a strong drive power but weak
dependence power. In this cluster we have four variables,
i.e., 1 (Supplier Relationship Management), 3 (Top
Management Commitment), 4 (Regulatory Pressures)
and 5 (Market Pressures)
Earlier works and reviews have a limited focus and
narrow perspective. They do not cover adequately
all the aspects and facets of SSCM. Although rub-
ber industry is of national important for the growth
of Indian economy but lack of previous SSCM em-
pirical studies related to this sector is the main rea-
son for lack of SSCM knowledge. Rubber board of
India is putting emphasis in enhancing export sales
and showing interest in GSCM practices. Literature
show that without SSCM practices it is impossible
to develop competitiveness in the global market.
The model developed by us clearly explains the
complex relationships among key variables and also
show the direct and indirect relationships in a better
fashion so that managers can easily understand the
links and devise GSCM strategies successfully.
SSCM practices in Indian rubber industry are main-
ly in uenced by Market Pressures, Carbon Emission
Reduction, Market Share and Pro t. Rubber indus-
try feel motivated in SSCM practices due to increase
in market share and pro t. Also there would be re-
duction in carbon emission and hence less market
pressure on the sector. This will increase the brand
image of the  rm.
Secondly Supplier relationship management and
Green technology adoption are the linkage variables
with respect to SSCM practices in Indian rubber
Thirdly Supplier Relationship Management, Top
Management Commitment, Regulatory Pressures
and Market Pressures are the key drivers of SSCM
practices in Indian rubber industry.
Reducing emissions in the rubber industry requires
a sustained and focused effort.
Maximize energy ef ciency potential by replacing
obsolete, inef cient equipments and adopting best
available technologies and best practices.
Switching to low carbon energy sources.
Fig. 5: MICMAC analysis
Driving Power(Y),
5, 9
Driving Power(Y),
8, 6
Driving Power(Y),
3, 13
Driving Power(Y),
2, 9
Driving Power(Y),
2, 11
Driving Power(Y),
9, 8
Driving Power(Y),
Driving Power(Y),
8, 4
Driving Power(Y),
7, 7
Driving Power(Y),
9, 6
Driving Power(Y),
6, 10
Driving Power(Y),
10, 5
Driving Power(Y),
8, 3
Driving Power(Y),
8, 2 Driving Power(Y),
12, 1
Driving Power
Dependence Power
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
9, 8
9, 8
9, 8
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
Driving Power(Y),
variables Dependence
Driving variables
A Framework for the Analysis of Sustainable Supply Chain Management: an Insight from Indian Rubber Industry 81
Alter product design and waste disposal protocol to
facilitate reuse and recycle in order to close the sup-
ply chain loop.
Improve benchmarking through standardized mea-
surement and data capturing protocols.
Formation of a cross functional team and prepare
the action plan for implementing GSCM in a holistic
Preparation of the GSCM/environmental policy and
create awareness among all employees.
Approving the budget from top management for in-
vestment in clean technologies/best practices.
Emphasis on supplier relationship management.
Train and educate suppliers so as to implement ISO
Emphasis on TQM practices.
Monitor progress on a periodic basis is important.
We understand that every management research has its
own limitations; the present study also suffers from certain
limitations. Present study is con ned to a single sector
and need to be validated in other sector and industry.
There are three important components of ‘Unique
Contributions’ i.e., What, How and Why (Whetten,
1989). In the present study we have put effort to answer
the three vital questions in terms of variables which we
have identi ed from the synthesis of literature and experts
opinion. We have developed a contextual relationships
using ISM approach and further re ned using MICMAC
Given the nature of this study, researcher makes three
First researcher provides one of the most compre-
hensive analyses of SSCM in Indian context.
Second the study furthers existing research in the
eld of SSCM, which suggests that SRM is an im-
portant factor for its successful implementation.
Researcher therefore contributes to an emergent lit-
erature, which suggests that the implementation of
SSCM is sensitive to the characteristics of buyer-
supplier relationships.
Third SSCM has been explored on a more in-depth
and theoretical level, by integrating NRBV and in-
stitutional theories, and addressing both internal and
external perspectives of the  rm.
To eradicate the limitations of present research we propose
to validate the model empirically in other sectors by using
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... A second key area includes logistics processes that enable the reduction of negative effects on the environment, e.g., carbon footprint. This result may be due to the fact that, in the research related to sustainability in enterprises conducted so far, the greatest attention has been focused on practices in distribution channels [84][85][86][87]. This area is one of the first undertaken by enterprises, and thus, the implementation of sustainability in this area is advanced and has well-established practices. ...
Full-text available
The implementation of the concept of sustainable marketing in corporate strategies plays a significant role in the realities of the modern market. The failure to include actions for sustainable development in traditional marketing mix tools makes it necessary to redefine them. The main goal of this article is to provide a comprehensive understanding of the scope of implementing sustainable marketing tools (5P) in SMEs of the food and drink industry in socioeconomically diverse markets of Poland (as an example of a developed country) and Sri Lanka (as an example of a developing country). This empirical study was based on responses obtained from 262 questionnaires conducted among SMEs operating in two different countries, i.e., 150 companies operating in Poland (example of a developed country), and 112 in Sri Lanka (example of a developing country). The aim of this study is to provide a complete understanding of the scope of implementing a sustainable marketing mix in SMEs operating in the food industry within Poland and Sri Lanka—in particular, the ways of defining individual marketing tools, as well as the differences between enterprises operating in the two surveyed countries.
... The latest study of Agrawal et al. (2017) and Schulz and Flanigan (2016) posits that the integration of sustainability can help market-oriented firms achieve such an advantage. Despite the research focussing on the relationship between sustainability implementation and company profitability and performance, most research in the field of sustainability focus on supply chain practices (Khan et al., 2017;Knight et al., 2015;Foerstl et al., 2015;Pagell and Shavchenko, 2014;Hoejmose et al., 2014;Bag et al., 2014;Chakraborty and Mandal, 2014). Research proves that responsible supply chain practices can enhance reputations and thereby create competitive benefits in the long run. ...
Full-text available
Purpose The paper aims to make a contribution by providing a comprehensive understanding of the scope of the implementation of sustainable marketing tools in SMEs operating in the food and drink industry in Europe. The focus will be put on the identification of differences between companies operating in business-to-business (B2B) and business-to-customer (B2C) context. Design/methodology/approach The empirical basis is a survey of 770 European SMEs, of which 369 operate in Western European countries (including UK, Germany and Spain) and 401 in Central and Eastern Europe (including Poland, Croatia and Russia). The respondents in the particular countries were stratified according to company size, measured by the number of employees. The research covered 316 micro companies, 5 small companies and 209 medium ones. The questionnaire was completed by the managing directors of the enterprises (CEOs) or heads of the marketing departments (CMOs). The research was conducted between April 2016 and January 2017. An in-depth analysis of the findings helped to identify differences between the two groups of SMEs, i.e. operating in the B2B and B2C context, in terms of the extent of sustainable marketing implementation. The non-parametric U Mann–Whitney test was used to examine the significance of the differences between the two groups of companies. Findings The research results suggest that both groups of B2B and B2C companies implement sustainable marketing tools to some extent. However, in most cases, B2B organizations do it to a significantly greater extent. Nevertheless, these activities relate mainly to those tools, which are directly visible to customers, both institutional and individual, such as packaging, product ingredients or certificates. To a lesser extent, they involve marketing activities of an internal nature, such as production process and the level of energy, water or resources used. Originality/value To the best knowledge of the author, this is the first empirical research study on the implementation of the sustainable marketing concept in SMEs operating in European countries. The study is a comparative analysis of the phenomenon between B2B and B2C companies, which has not been previously researched.
... Organisations operating beyond their national boundaries can no longer depend on previously proven domestic quality practices (Mehra & Agrawal, 2003). For an example as per Bag, Anand, and Pandey (2014), Indian rubber manufacturing firms introduced SCM in order to increase their firm performance. Similarly, Sri Lanka Rubber Secretariat, Ministry of Plantation Industries, Sri Lanka (2016) highlights the importance of introducing whole-of-the-supply-chain approach to the rubber industry of Sri Lanka in order to gain a competitive advantage. ...
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Rubber industry, one of the growing industries in the world creates a vacuum to exploit foreign markets especially for countries like Sri Lanka. However, lack of strategic relationships and low quality products with higher cost keep Sri Lanka's rubber industry performance away from the global market. Since supply chain management (SCM) is implicated in the issue of external relationships and quality management (QM) is implicated in low product quality, the key aim of this study was to test the relationships between SCM, QM and organisational performance, in the context of the rubber industry in Sri Lanka. In particular, it empirically tested the mediating role played by SCM in the relationship between QM and operational performance (OP) of rubber manufacturing organisations though this relationship has already been established in theoretical literature. Data was gathered through a questionnaire from managers of 44 firms in the rubber products manufacturing sector in Sri Lanka. Data was analysed with the descriptive and inferential statistical analyses. The results indicated that QM practices and SCM practices improve OP while SCM practices are partially mediating the effect of QM practices on OP. The results of this study help the rubber products manufacturing Colombo Business Journal 8(2), 2017 20 organisations in Sri Lanka to formulate successful strategies by enhancing the OP via QM and SCM practices.
Conference Paper
براساس مطالعات صورت گرفته توسط بانک جهانی، بهبود و ارتقاي عملكرد لجستيک به عنوان يكی از اهداف مهم توسعه کشورها، طی ساليان اخير مطرح شده است؛ چرا که لجستيک تأثير بسزايی بر فعاليت‌هاي اقتصادي کشورها دارد. داشتن عملكرد لجستيكی بهتر، به نحو قابل ملاحظه‌اي با شكوفايی تجارت، تنوع صادرات، جذابيت براي سرمايه‌گذاري مستقيم خارجی و رشد اقتصادي مرتبط است. هدف از انجام پژوهش حاضر بررسی تأثیر ابعاد استراتژی لجستیک (فرآیند، بازار و اطلاعات) و اثربخشی خدمات مشتری با نقش میانجی اثربخشی هماهنگی لجستیک بر رقابت‌پذیری شرکت‌ها بوده است. این پژوهش از نظر هدف، کاربردی و از نظر روش، توصیفی ـ پیمایشی است. مورد مطالعه پژوهش، تعداد 150 شرکت تولیدکننده مواد غذایی شهر مشهد به عنوان بخشی از شرکت‌های تولیدکننده مواد غذایی می‌باشد. ابزار پژوهش حاضر پرسشنامه است که روایی و پایایی آن مورد تأیید است و برای تحلیل داده‌های آماری و آزمون فرضیه‌ها از روش مدل‌یابی معادلات ساختاری و نرم‌افزار Smart-PLS استفاده شده است. نتایج پژوهش نشان می‌دهد که نقش استراتژی لجستیک و اثربخشی خدمات مشتری با نقش میانجی اثربخشی هماهنگی لجستیک بر رقابت‌پذیری شرکت‌ها مثبت است.
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This paper provides a systematic literature review (SLR) of 59 sustainable supply chain management (SSCM) SLRs. The key findings are that 1) we have reached a point of saturation, where we likely do not need additional SSCM SLRs that simply provide a broad overview of the content, themes and structure of the SSCM literature (although periodic updates of existing SLRs may be warranted); however, 2) there is "white space" and opportunity to examine relationships among specific constructs and use SLRs for theory development; and 3) there is a need to improve the methodological rigor of future SSCM SLRs, as found through our introduction of a modified set of AMSTAR criteria to assess SLR quality. Finally, there is an opportunity for studies that move beyond metrics and investigation of performance from the perspective of a single organization to the broader supply chain.
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India is rapidly urbanizing and the class I cities contribute more than 72 percent of the total solid waste generated in urban areas. However managing solid waste scientifically has become one of the biggest challenges in front of state and local authorities. Limited space for dumping and skilled manpower is a constraint for managing the solid wastes. Illegal dumping outside cities and unscientific processing often leads to foul odor generation, leachate contaminating the water streams and spreading of germs detrimental to public health and society. Globally environmental scientists are looking for innovative and sustainable methods for recovering the useful components from waste consisting of value and can be reused. Presently several waste to energy projects have gained popularity across the world. Unfortunately none of these practices have gained popularity in India and further motivated in pursuing the present study. The objective of the study is twofold. First authors assessed the current status of solid waste management practices in India. Secondly the leading barriers are identified and Interpretive structural modeling technique is performed to identify the contextual interrelationships between leading barriers influencing the solid waste to energy programs in the country. The dependence and driving power of the barriers are further analyzed. Finally the conclusions are drawn which may assist policy makers in designing sustainable waste management programs.
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The purpose of this paper is to explore manufacturing practices that helps firm to achieve better environmental and business performance. In simple words it can be termed as antecedents "green manufacturing" practices that enhances firm performance. In this paper we have adopted secondary literature survey approach to identify variables and identify research gaps. Based on the constructs and items identified through literature survey researchers have developed a structured questionnaire which was pretested before using for final survey. We have collected data from 54 manufacturing firms.In this study we have performed PLSR (Partial Least Square Regression) analysis, using EFA (Exploratory Factor Analysis) output as an input of PLSR analysis. The Exploratory Factor Analysis (EFA) output has been used as an input for PLSR modeling. The PLSR modeling has been conducted on two measures i.e. (1) Impact of green purchasing, supplier relationship management, green logistics and regulatory norms on "Business Performance". The PLSR modeling output suggest that model explain over 22.6% of the total business performance outcome variable. The PLSR coefficient output suggest that green purchasing, supplier relationship management, green logistics and regulatory norms are positive determinants of company business performance, secondly impact of green purchasing, supplier relationship management, green logistics and regulatory norms on "Environmental Performance "outcome. The PLSR modeling output suggest that model explain over 33.2% of the total environmental performance outcome variable. The PLSR coefficient output suggests that supplier relationship management is the positive determinant of environmental performance outcome.
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The purpose of the paper is to develop Truck Freight Model (TFM) using interpretive structural modelling (ISM) and MICMAC analysis. In the present study, we have employed exhaustive literature survey published in reputed refereed and indexed journals and reports published by reputed agencies to identify the variables which are used for developing TFM. In order to further resolve the conflicts among variables identified through literature review we have further adopted expert opinion using ISM model to establish contextual relationship which we further refined the model using MICMAC analysis. The present study provides a unique insight into TFM. The study identifies road condition as an independent variable which results into axle failure or frequent road accidents resulting into shortage of truck drivers, has major impact on different TFM model.
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The objective of this study is to determine antecedents of the innovation process in Indian conditions. In this research, researchers have used interpretive structural modelling (ISM) to develop inter-relationship among antecedents of innovation, which will provide direction to researchers for further research. It will further help managers in formulating innovation strategies. The research was conducted based on expert's opinion about antecedents of innovation. It is observed, 'scarce resources' and 'innovation culture' are two important antecedents which have affected all the antecedents of innovation in India. In order to increase innovation performance in India, 'innovation culture' and 'scarce resources' should be resolved. There have been a number of researches about innovation barriers in general. This paper must be taken as a theoretical model development and can be empirically tested in Indian conditions.
The article focuses on the development of a theory. A discussion is presented about steps involved in developing a theory, such as seeing which factors logically should be considered as part of the explanation of the social or individual phenomena of interest. The authors assert that authors developing theories are considering these factors, they should err in favor of including too many factors, recognizing that over time their ideas will be refined. The article presents information about the importance of sensitivity to the competing virtues of parsimony and comprehensiveness.
Green supply chain management (GSCM) has become a method to improve environmental performance. Under stakeholder pressures, forces and regulations, companies need to improve the GSCM practice, which are effected by practices such as green purchasing, green design, product recovery, and collaboration with patrons and suppliers. As companies promote the GSCM, their economic performance and environmental performance will be enhanced. Hence, GSCM evaluation is very important for any company. One of the techniques that can be used for evaluating GSCM is data envelopment analysis (DEA). Traditional models of data envelopment analysis (DEA) are based upon thinking about production as a “black box”. One of the drawbacks of these models is to omit linking activities. The objective of this paper is to propose a novel network DEA model for evaluating the GSCM in the presence of dual-role factors, undesirable outputs, and fuzzy data. A case study demonstrates the application of the proposed model. A case study demonstrates the applicability of the proposed model.
The ‘LTI Set’, consisting of 20 Laws of Complexity, a Taxonomy of the Laws of Complexity, and five Indexes of Complexity, is proposed as the core of a developing science of complexity that is applicable to resolving complexity in organizations. The LTI Set links to these included topics: Alternative Science-Free Organizational Practices; Educational Practices Appropriate to Complexity; Quality Control of Science; Applications of the Science of Complexity in Organizations; Enabling Conditions for Effective Organizational Practice. A critical condition for significant advances in resolving complexity is that the organization recognize the strong, even dominant, behavioral aspects of complexity, as reflected in the Laws; and take account of these in redefining the main role of top management. That role is to set up and administer a responsive corporate infrastructure to meet the demands of complexity, along the lines set forth here. Further advances in behavior can be made through new educational programs that reflect older scientific values applied to the challenges of today, in contrast to reliance on unwarranted assumptions that undermine organizations. Appropriately remodeled to reflect the relentless demands of complexity, the university can become a model for other institutions in society. Copyright © 1999 John Wiley & Sons, Ltd.
Purpose ‐ Supply chains (SCs) are integral to the globalized economy and offer many business opportunities but can also lead to unintended social and environmental impacts. Accurate performance assessments are crucial for SC control and are also a cornerstone for sustainable development. Hence, procedural, technological, and operational support is needed to facilitate a balanced approach to performance measurement for sustainable SCs. Design/methodology/approach ‐ The paper combines concepts derived from literature on performance measurement in SCs and sustainability with the balanced scorecard (BSC). Synthesis of these related approaches leads to the proposal of a customized scorecard design and development processes which are further elaborated through illustrations and practical examples. Findings ‐ A scorecard design customized for sustainable SCs is proposed along with development and implementation processes. Research limitations/implications ‐ The organization and synthesis of related performance measurement approaches advances the theoretical understanding of how a BSC can be operationalized in sustainable SCs. Research opportunities are derived based on the presented findings. The results are limited due to their mainly conceptual development. Practical implications ‐ The BSC is illustrated by practical examples in an attempt to demonstrate the feasibility and practical value of the conceptual approach. Originality/value ‐ The field of sustainable supply chain management continues to be beset by little guidance in terms of principles and applicable tools for performance assessment. The paper provides structure in this regard, integrates concepts central to the performance of sustainable SCs, and supports the practical application of a BSC approach.
With the differences of customization attributes, the changes of the implementing stages of rules and different selling countries, the contents of the check value of RoHS (Restriction of the use of certain Hazardous Substance in electrical and electronic equipment) which each enterprise has to comply with and which is more complicated than component selection operation for general products are different. Under such complicated productive production, it is a major test for business decision makers to maintain the most effective operational efficiency and the lowest cost. This study puts forward a set of solutions which integrate group technology and neural network against component selection of green supply chain management (GSCM). First, neural networks are used for grouping products with the similar customized need against the value of the check item of each part of orders. Next, according to the information of existing inventory within the enterprise, available parts are selected and the total production costs are calculated to effectively reduce the complexity of the planning of the production lines for production manager. The above operation mode is established to be an information system of a component selection for green supply chain. Finally, data is analyzed to account for the using situation to ensure the availability of practical operation of the system based on the case of a company.