Ontology Based Environmental Knowledge Management

A System to Support Decisions in Manufacturing Planning

Sarfraz Ul Haque Minhas and Ulrich Berger

Chair of Automation Technology, Brandenburg University of Technology Cottbus-Senftenberg,

Siemens-Halske-Ring 14, Cottbus, Germany

Keywords: Knowledge Management, Environmental Management Tool, Ontology, Environmental Assessment,

Decision Support System.

Abstract: The environmental efficiency based decision making to decide for optimal manufacturing routes in the

decentralized production, has become very complicated. The draining of skilled workers, limited

functionalities of decision support tools, localisation of information resources, unavailability of adequate

environmental knowledge, systematic management of the same and non automated information exchange

between various information tools are among the causes that generally hamper the decision making process.

The complexities can be resolved if the mechanism for environmental data collection, structuring and

retrieval over a web environment is developed so that both collaborative and individual decision making is

possible. This paper discusses the case study from the automotive manufacturing area and the development

of environmental knowledge management tool capable of providing planners and production managers the

knowledge related to the potential environmental impact of the manufacturing choices in a distributed

manufacturing scenario.

1 INTRODUCTION

There has been tremendous increase in

environmental pollution due to frequent

manufacturing activities around the globe in

evolving distributed manufacturing systems

interlinked with product specific supply chains.

Besides, newly introduced stringent environmental

regulations and shift towards mass customized

production have given the manufacturers only option

to adopt more environmental friendly practices

inside as well as outside their factories. This is the

one of the main aspect for achieving sustainability,

which has become a very crucial factor for

competitiveness in the global market. The latter

needs efficient management of manufacturing

indispensable to target the ambitious environmental

objective envisioned by the European Commission

(EC) in its Horizon2020 program and in the

Organisation for Economic Co-operation and

Development (OECD), to embark on the journey of

sustainable manufacturing and eco-innovation.

Further, the manufacturing landscape is

distinguished by decentralization in manufacturing

systems, mass customization of products and

changing strategic goals. At the same time,

increasing production rates due to expanding

markets are resulting in huge consumption of

resources thereby influencing environment quite

sharply. In the context of manufacturing networks

and supply chains, this requires following those

procedures in planning supply chains that guide

towards sustainable manufacturing minimizing the

impact on environment and ensuring

competitiveness. However, the insufficient

knowledge support and unsystematic management of

the information related to environment hinders or

cease the decision making for eco-efficiency in

manufacturing. The following section presents a

review of approaches reported in the scientific

literature for eco-efficiency based manufacturing

planning.

2 ECO-EFFICIENCY BASED

MANUFACTURING PLANNING

The research on developing planning strategies for

eco-efficiency in manufacturing has got wide

397

Ul Haque Minhas S. and Berger U..

Ontology Based Environmental Knowledge Management - A System to Support Decisions in Manufacturing Planning.

DOI: 10.5220/0005138503970404

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2014), pages 397-404

ISBN: 978-989-758-049-9

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

importance in literature. Several initiatives have

been taken by legislative authorities European

Commission (EC), UNEP etc. These initiatives

emphasize on adopting methodologies and tools to

facilitate eco-efficient decision making in

manufacturing system. This would lead to

incorporation of environmental management

strategies in the whole factory more specifically in

the manufacturing planning ensuring better

environmental operational performance on the

factory floor. Sroufe et al. 2002 made a detailed

analysis on scientific literature that establishes

relation between environment management and the

operational performance of the manufacturing

system. Several models have therefore been

investigated linking the environmental emissions

with operations performance and listed in (Sroufe et

al. 2002) thereby highlighting its importance in

evaluating manufacturing performance based on

environmental impact (Figge et al. 2002)

(Schaltegger et al. 2000). The incorporation of this

criterion in decision making is a big challenge for

enterprises particularly the SMEs. Such system is

not yet implemented there possibly due to

development costs (Golinska and Romano, 2012).

However, the cost factor changes when a

manufacturing planning is viewed from the

hierarchical perspective. In (Sroufe et al. 2001), the

researchers have grouped environmental

management related practices at operational, tactical

and strategic levels in a performed case study. This

study shows that the manufacturers are now

emphasizing on adopting environment related

decisions at the operational level. These practices

include scheduling, sequencing and capacity

planning. Apart from introduced methodologies to

evaluate environmental impact in distinct areas of

the manufacturing, numerous tools have been

reported in the literature which uses eco-efficiency

related performance indicators in the manufacturing

planning particularly in the efficiency evaluation of

supply chains. For example, the efficiency of the

supply chain is based on how well the material

requirements planning is made, which is primarily

dependent upon effective tools addressing all the

necessary strategic and the derived operational

objectives and performance indicators of the

company. Melynk et al. 2001 introduced a Green

material requirement tools to incorporate

environmental issues in material requirement

planning. It is one among many preliminary

concepts that targeted minimization of

environmental impacts of waste stream generated in

manufacturing processes. A model based on fuzzy

set theory for the assessment of environmental

hazards in manufacturing is introduced in (Hui et al.

2002). The big issue in such assessment is the

uncertainty of the information used. A case study

was performed (Hui et al. 2002) manifesting the

fuzzy set based approach as a lever to minimize

uncertainty in the information being used for

environment assessment of manufacturing processes.

Manufacturing processes generally consume huge

amount of energy which directly affects the

environment. Therefore, research literature

principally addresses issue of evaluation of energy

performance in manufacturing systems, defining

strategies to reduce energy consumption and the

environmental impact of manufacturing processes.

The environmental impact reduction through energy

performance improvement has been targeted and

several solutions have been proposed. A common

measurement framework for guiding the company

managers and external stakeholders to adopt eco-

efficiency as means for environmental sustainability

has been introduced in (Verfaillie et al. 2000). This

framework provides assessment of environmental

impact during product creation and during service

based on five prominent indicators i.e. energy

consumption, water consumption, material

consumption, Green house gas emissions (GHG) and

Ozone depleting substance emissions (ODS). Hence

this way, the framework provides a flexible

framework that is widely used, broadly accepted and

easily interpreted in the environmental measurement

framework. Therefore, more environmental

sustainability can be ensured once the guidelines

mentioned in this framework are followed. However

the quantification of sustainability needs assessment

methodology that can be practically used widely in

the industry. One of the methodologies for such

quantifications is the Life Cycle Assessment

approach. It is termed as the grouping and

assessment of potential environmental impact of

products and services along the life cycle, enabling

determination of the environmentally aggressive

stages in the product life cycle. Preuss (2005)

emphasized the need for environmental management

system for greening the supply chain. Several

methods were outlined e.g. allowing manufacturers

laying focus on eco-efficiency of the material

acquired from the suppliers, including the criteria of

eco-efficiency in the selection of suppliers,

incorporating better environmental monitoring

procedures based on environmental standards like

ISO 14001 and by establishing environmental

management system in a manufacturing company.

Bojarski et al. 2009 introduced optimization based

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on environmental impact using IMPACT 2002+

methodology. Decisions are made on determining

the most eco- friendly manufacturing location and

processing technology. In (Guillén-Gosálbez and

Grossmann, 2009), the supply chain design problem

take into account the presence of uncertainties in the

life cycle inventory connected to the operation of

supply chain network. A bi-criterion stochastic

mixed-integer nonlinear program was developed to

achieve maximization of the net present value and

the minimization of the environmental impact for

any given probability level. An LCA based Eco-

indictor99 method was used to compute the

environmental performance of the supply chain

network. The stochastic model is transformed into

deterministic model by re-defining the probabilistic

constraints needed for computing the environmental

impact. The capabilities of this model and the

solution procedure using two case studies for

determining the solution by trading off between the

environmental impact and the profit has been

elaborated. The solutions provide guidance to the

decision makers for selecting the more eco-friendly

supply chain in uncertain situations. A mixed integer

model is developed that minimizes emissions

throughout the supply chain by considering

environmental sourcing (Abdallah et al. 2012). Life

cycle assessment was made considering a case

study. This case study covers three different

scenarios based on different carbon emissions costs.

The model helps manufacturers in choosing

suppliers with better environmental performance.

The above approaches provide models and methods

how environmental performance can be included in

the decision making. They however, do not focus on

information systems needed for supporting

environmental based decision making. The

information system for supporting decision making

based on environmental impact are known from the

chemical industry in which energy and material

flows are considered (Funk et al. 2009).

In various projects like OPUS (Bullinger et al.

2000), CARE, INTUS the environmental accounting

instruments in the ERP systems were created as

described in (Funk et al. 2009). However, these

projects could not deliver a comprehensive tool or

reference architecture of the information system

model for the incorporation of environmental

impact/eco-efficiency as a criterion in decision

making. Further, they did not address issues related

to information representation complexities in

environmental based decision making. Möller et al.

2006 investigated the role of Information

Technology (IT) systems to support environmental

management accounting in ERP supported decision

making processes. They also emphasized on well-

defined data exchange between the ERP systems and

the environmental information systems to help better

storage of best practices of business processes in the

ERP systems. Rautenstrauch 2007 described

environmental management information solutions

already made in the integration of the ERP with

other management tools such as material flow

management. The feasibility of integration of

environmental management system with the ERP

systems was investigated, which has got a very

limited implementation scope. Funk et al. 2009

proposed calculation of environmental impact in

ERP systems using environmental related

information from external databases. Wohlgemuth et

al. 2008 provided the basic architecture of software

platform for environmental management information

system. This platform supports the customized

development of software tools as a plug-in

application for material flow management but it does

not provide any information system that could

support in decision making in manufacturing

planning based on the necessary key environmental

criteria. Knowledge-based approaches have been

tested in several distinct manufacturing planning

areas for solving a number of individualized

problems e.g. in (Cakir and Cavdar, 2006), a

knowledge-base system is proposed to get

recommendations on optimal cutting parameters in

machining operations like milling, drilling and

turning etc. However, knowledge management

system has been limited to the development of

information portals where environmental knowledge

has been kept in inoperable fashion.

3 CASE STUDY AND PROBLEM

DEFINITION

The presented literature review summarizes that the

environmental based assessment of manufacturing

processes is a necessary key performance

assessment criterion in the manufacturing planning.

This implies that the environmental impact of

potential solutions has to be determined before

deciding on the optimal choices for manufacturing

processes, resources, manufacturing locations and

transportation means in the whole decentralized

manufacturing setups. The commercially available

Product Life Cycle Management (PLM) and

Enterprise Resource Planning (ERP) solutions do

not cover holistic consideration of potential

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environmental impact in the evaluation of potential

production schemes and eventually in the decision

making process. The decision making process is a

time consuming and non-trivial as the selected

options have to be simulated using the conventional

simulation tools and then the results are shared

through non-standardized interfaces with the other

simulation tools or even through manual means.

Additionally, the planners have to rely on the LCA

experts to conduct simulations and deliver results

back to ERP/PLM planners. The exchange of

information takes place in manual ways, which

make decision making even more difficult when the

resources are placed in a distributed fashion and

intensive reliance of software on company’s IT

infrastructure. The distributed resources, however,

furnish more intensive inter and intra departmental

collaboration along the whole product development

cycle. However, one of the challenging problems

related to distributed systems in the manufacturing

environment is to connect them semantically and

infer required knowledge that facilitates planners

with the comprehensive decision making. The

question arises as to how it can be practiced actually

in the manufacturing industry.

Figure 1: Environmental based decision making work flow

(As-Is Versus To-Be).

In Figure 1, the nodes are numbered to represent the

following

1. Order preparation/request for assessment

2. Correspondence & approval

3. Data collection (from inventory)

4. Hiring of LCA expert

5. Signing confidentiality/contractual

agreement

6A. Environmental knowledge retrieval

6. Conduction of LCA study/environmental

assessment

7. Reporting to planning department & final

decision

represents time to reach decision.

Considering the case of automotive industry, the

work flow for environmental based decision (As-Is)

is shown in Figure 1. The product for which the

environmental impact has to be assessed is done in

the following order (Referring to Figure 1).

1. The planning department requests for the

assessment of potential environmental impact of the

particular product.

2. Next the correspondence is made with the

inventory department for the acquisition of product

related information and negotiations are made to

determine who will be selected for the LCA

assessment.

3. Environmental related data as well as the

product information is collected from the respective

departments.

4. Afterwards, the LCA expert is hired to conduct

such assessments. The assessments are made by

internally or externally hired LCA expert.

5. In case of an externally hired LCA expert, a

confidential agreement is generally made.

6. The assessment of environmental impact is

made with the aid of commercially available life

cycle assessment tools.

7. Finally the results are communicated to the

planning department about the potential

environmental impact of product under the LCA

study

The total duration of this process is generally six

to eight months depending upon the complexity of

the product and the associated process chains under

study. Moreover, the duration can be prolonged upto

18 months if the LCA study is made externally

through sub-contracting. This situation reflects that

the environmental based decision making cannot be

incorporated in the company’s operational

performance due to time consuming workflow in

mass customization scenario. As the mass

customization has engulfed our manufacturing

landscape, the environmental assessment of

customized products and of manufacturing networks

will become a part of operational planning. The

environmental management system based on

knowledge-based must therefore be devised to

reduce this workflow substantially as shown in

Figure 1 (To-Be). The objectives of environmental

knowledge management system are the following:

i) Development of product independent taxonomies

for manufacturing and environment related domain

knowledge, which is required for environmental

simulations in LCA tools and for decision making.

ii) Development of Ontology based knowledge-base

to enable storage of knowledge generation from or

through interaction with the LCA simulation tools.

iii) Enriching ontologies with the semantic rules for

product and process classifications and mapping to

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the environmental concepts, to infer simulation

models for the LCA tools.

iv) Navigation through ontologies using

standardized query formats and searching

algorithms.

v) Seamless exchange of information from the

legacy tools and automatic generation of queries for

synthesizing simulation models for the LCA

simulation. The architecture for this web based

environmental knowledge management tool must

support the development using state of the art web

technologies, knowledge representation formats,

data exchange formats to deliver easy to use, easy to

access, domain independent and location

independent solution.

4 CONCEPT AND

IMPLEMENTATION

Considering the case study, the problem formulation

and the required objectives, the concept for

environmental management system for

environmental based decision making is presented in

Figure 2.

Figure 2: Overall concept of the knowledge management

system.

The architecture concept for environmental

management system comprises of the main modules

namely the knowledge extraction sub-module,

knowledge structuring module, navigation module,

model synthesizer module and model visualization

module. The knowledge is generated by both ways

i.e. through interaction with simulation tool as well

as the results generated from LCA simulation tools.

The knowledge is extracted either through manual

means formalized in the form of documented

statements and by linking the tags. The knowledge is

structured through formal representation using

ontologies. These ontologies are used for knowledge

extraction as well as for knowledge retrieval. The

topics from the manufacturing and environment

need to be conceptualized and articulated as several

ontologies. The domain ontologies are constructed

using standard ontology editor namely Protegé

available as an open source aims at development of

ontologies. The knowledge generated as a result of

interaction between the simulation tool and the LCA

planners is used to create new taxonomies or to

populate the existing ontologies. The implicit

knowledge of domains experts are translated into

additional rules that would infer practical solutions

for decision making. The ontologies are described in

a formalized way complying with the W3C

standards. The production scheme, which describes

the details of decentralized manufacturing network

for producing the customized product in an xml

format, is imported in the knowledge retrieval portal.

These specifications are related to products,

processes and resources of all the selected

manufacturing and supply locations against the

customized order. This multi-level and cross

connected information file needs to be parsed which

afterwards is used for generating queries in

compliance with the W3C standards. The query

generator takes each node one by one and generates

respective queries against each node mentioned in

the production scheme.

5 VALIDATION

The implemented tool was tested based on the pilot

case: the example of customized/individualized

manufacturing of car hood assembly is selected to

validate the concept. While it consists of simple

multi-level bill of materials i.e. four parts and two

customized additional parts, it is sufficient to

demonstrate the concept, which facilitates users in

understanding the product and process structure with

or without customization easily. It also supports free

manipulation of explicit knowledge (e.g. technical

information) and tacit knowledge without violating

the confidentiality of manufacturer related

information/knowledge. The environment

knowledge management system takes production

scheme as an input (see Figure 4) and parses each

manufacturing node in a sequential manner. This

information is later on used to generate relevant

queries. Thus knowledge is retrieved in a seamless

and automatic manner. On the contrary, users can

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also search manually through a restricted search

approach. The input given by the user through this

web-based graphical user interface is processed by

the query generator, which synthesizes queries

complying with the knowledgebase structure.

For validation, the retrieval of environment

related knowledge through the knowledge portal

(web-based graphical user interface), the production

of customized hood assembly in decentralized

manufacturing is taken as an example. It includes a

knowledge management system based on ontologies

and inference system seamlessly connected with

legacy tools. A wrapper is developed that connects

the knowledge base system with the LCA simulation

tool.

Figure 4: The XML representation of production scheme

(Node A in Figure 2).

Suppose a user wants to search for knowledge

concerning the possible environmental impact of the

hood assembly of any customized order.

The user insert material, the process parameters

particularly the whole or section of the process chain

indicating the start process node to the end process

node and can also select for the possible

environmental impact indictors. For example, the

user can explore the knowledgebase for environment

impact of Hood Frame during a section of its whole

process chain (i.e. from sealing hood process to the

adhesive curing of hood). The query engine takes

this input and generates SPARQL based queries to

search the relevant information in ontologies.

The knowledgebase comprises of material,

process, resource and environment related

ontologies. The material ontology describes

materials as final products, products in processing

phase and raw materials. The Figure 5 shows the

taxonomies of ontologies of materials, processes,

resource and environmental related ontologies.

Figure 5: Excerpt of manufacturing related ontology

(Node B in Figure 2).

The process ontology covers two main associated

and closely related sub-concepts i.e. operations and

resources. The operations related to the

manufacturing of customized hood as well as the

machines used are stored as instances in the

knowledgebase. The tacit knowledge from the LCA

experts as well as from the manufacturing planners

involved in hood manufacturing was added to the

knowledgebase as additional production rules.

This enables concrete search helpful for

providing recommendations to the planners as well

as suggested LCA (Life Cycle Assessment)

simulation model and hence determine the eco-

friendly manufacturing processes and routes.

The simplest example of such rules is the supply

of optimal quantity of hood frames from suppliers at

a certain location to any of the manufacturing

location using the available transportation routes and

resources without exceeding the allowable limit of

emissions. In this example, both the experience

of LCA experts as well as the other planners is

involved.

The tacit knowledge concerning this case is

programmed as additional rules to enrich the

knowledgebase.

Figure 6 is an example of the graphical input

output model (Car Hood Assembly). This model

shows the environmental impact of the requested

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Figure 6: Generated knowledge related to part of the

manufacturing operation in customized hood assembly

(Node C in Figure 2).

operation in customized hood assembly, generated

against a respective operation node mentioned in the

production scheme (see Figure 4). The tool infers

environmental knowledge related to the

manufacturing of customized products through

seamless generation of SPARQL based queries. It

allows easy navigation inside the knowledge base

for possible emissions and their values (if available

in the knowledgebase). The tool facilitates inclusion

of tacit knowledge from both planners and the LCA

experts.

4 CONCLUSIONS

The environmental knowledge management is

needed to work seamlessly with the company

planning software tools to support reliable, precise

and much quicker decision making than those

practices already in place. A concept for

environmental knowledge management system is

implemented and validated through the pilot case

from the automotive industry. With the help of this

pilot case, the knowledge from manufacturing and

environmental domains is implemented using

ontologies in compliance with the W3C standards. A

Web-based software solution is developed for

customized user query interface, ontology based

knowledge-base is implemented and validated.

The environmental knowledge management tool

allows input by two means: directly from users in

the form of customized user queries or by simply

uploading the production scheme data generated by

legacy tools. This query is generated after the user

has customized his input information through text

input or through keyword using free search

functionality. The query engine allows searching of

information from ontologies, which is delivered to

the model synthesizer inferring LCA based

simulation models. The generated results are used to

enrich the knowledge base for better inference

capabilities. As an outlook, new functionalities like

processing of natural language queries with smart

context will be added. Additionally, the extraction of

environmental related information and automatic

population of ontologies will be made, seamlessly

linking both the company legacy tools information

and as well as the LCA tool outputs linked with the

environmental knowledge management tool.

ACKNOWLEDGEMENTS

The authors kindly acknowledge that this research

work is partially supported by the European

Commission Project e-Custom FP7-2010-NMP-ICT-

FoF 260067 “A Web-based Collaboration System

for Mass Customization”.

REFERENCES

Abdallah, T., Farhat, A., Diabat, A., Kennedy, S., 2012.

Green supply chains with carbon trading and

environmental sourcing: Formulation and life cycle

assessment. In Applied Mathematical Modelling, vol.

36, no. 9, pp. 4271–4285.

Bojarski, A. D., Laínez, J. M., Espuña, A., Puigjaner, L.,

2009. Incorporating environmental impacts and

regulations in a holistic supply chains modeling: An

LCA approach. Computers & Chemical Engineering,

vol. 33, no. 10, pp. 1747–1759.

Bullinger, H.-J., Eversheim, W., Haasis, H.-D., 2000.

Auftragsabwicklung optimieren nach Umwelt- und

Kostenzielen: OPUS - Organisationsmodelle und

Informationssysteme für einen produktionsintegrierten

Umweltschutz. Springer Berlin.

Cakir M. C., Cavdar, K., 2006. Development of a

knowledge-based expert system for solving metal

cutting problems. In Materials & Design, vol. 27, no.

10, pp. 1027–1034.

Figge, F., Hahn, T., Schaltegger, S., Wagner, M., 2002.

The Sustainability Balanced Scorecard - linking

sustainability management to business strategy.

Business Strategy and the Environment, vol. 11, no. 5,

pp. 269–284.

Funk, B., Möller, A., Niemeyer, P., 2009. Integration of

environmental management information systems and

ERP systems using integration platforms. In

Environmental Science and Engineering, Information

Technologies in Environmental Engineering, I. N.

Athanasiadis, A. E. Rizzoli, P. A. Mitkas, and J. M.

Gómez, Eds, Springer Berlin Heidelberg, pp. 53–63.

Golinska, P., Romano, C.A., Eds, 2012. Environmental

Issues in Supply Chain Management. Berlin,

Heidelberg: Springer Berlin Heidelberg.

Guillén-Gosálbez, G., Grossmann, I. E., 2009. Optimal

design and planning of sustainable chemical supply

OntologyBasedEnvironmentalKnowledgeManagement-ASystemtoSupportDecisionsinManufacturingPlanning

403

chains under uncertainty. In AIChE Journal , vol. 55,

no. 1, pp. 99–121.

Hesselbach, J., Herrmann C.,Thiede, S., Kara, S.,

Hesselbach, J., 2011. Energy oriented simulation of

manufacturing systems – Concept and application. In

CIRP Annals - Manufacturing Technology, vol. 60, no.

1, pp. 45–48.

Hui, I. K., He, L., Dang, C., 2002. Environmental impact

assessment in an uncertain environment. International

Journal of Production Research, vol. 40, no. 2, pp.

375–388.

Melnyk, S. A., Sroufe, R. P., Montabon, F. L., Hinds, T.

J., 2001. Green MRP: Identifying the material and

environmental impacts of production schedules. In

International Journal of Production Research, vol. 39,

no. 8, pp. 1559–1573.

Möller, A., Prox, M., Viere, T., 2006. Computer Support

for Environmental Management Accounting. In

Sustainability Accounting and Reporting, S.

Schaltegger, M. Bennett, and R. Burritt, Eds. Springer

Netherlands, pp. 605–624.

Preuss L., 2005. The green multiplier: A study of

environmental protection and the supply chain.

Palgrave Macmillan, Houndmills, Basingstoke,

Hampshire, New York.

Rautenstrauch, C., 2007. Integration of MRP II and

Material Flow Management Systems. In

Environmental Science and Engineering, Information

Technologies in Environmental Engineering, J. M.

Gómez, M. Sonnenschein, M. Müller, H. Welsch, and

C. Rautenstrauch, Eds, Springer Berlin Heidelberg,

pp. 261–269.

Schaltegger, S., Hahn, T., and Burritt, R., 2000.

Environmental management accounting: Overview

and main approaches. Center for Sustainability

Management, Lueneburg.

Sroufe, R., Montabon, F. L., Narasimhan, R., and Xinyan,

W., 2002. An examination of the relationship between

environmental practices and firm performance. In

Proceedings of 33rd Annual Meeting of the Decision

Sciences Institute, San Diego, CA.

Sroufe, R., Montabon, F. L., Narasimhan, R.,Xinyan, W.,

2001. A Framework for corporate environmental

practices and its applications for enhancing

environmental mangaement. In Proceedings of the

Supply Chain and Information Management

Conference.

Verfaillie, H. A., Bidwell, R., Cowe, R., 2000. Measuring

eco-efficiency: A guide to reporting company

performance. World Business Council for Sustainable

Development, Geneva, Switzerland.

Wohlgemuth, V., Schackenbeck, T., Panic, D., Barling,

R.-L., 2008. Development of an open source software

framework as a basis for implementing plugin-based

Environmental Management Information Systems

(EMIS). In Environmental informatics and industrial

ecology: EnviroInfo 2008 : 22nd International

Conference on Informatics for Environmental

Protection,, A. Möller, B. Page, and M. Schreiber,

Eds, Aachen: Shaker, 2008.

KEOD2014-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment

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