Evaluating environmentally conscious business practices

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH European Journal of Operational

Research 107 ( 1998) 159- 174

Theory and Methodology

Evaluating environmentally conscious business practices Joseph Sarkis * Graduate School of Management, Clark University, 950 Main Street, Worcester, MA 01610-1477,

USA

Received 21 March 1996; accepted 17 March 1997

Abstract Corporate environmental management is becoming more strategically oriented. With increased emphasis on the natural environmental by organizational stakeholders, including governments, stockholders, customers, employees and communities, the need for explicit consideration and incorporation of environmental strategy within corporate strategy has never been more critical to the organization. With such programs as design for the environment, total quality environmental management, life cycle analysis, green supply chain management, and IS0 14000 standards gaining notoriety, the operational and strategic decisions for environmental managers and businesses is becoming more complex. This paper integrates these elements and their attributes into a strategic assessment and decision tool using the systems with feedback or analytical network process (ANP) technique first introduced by Saaty. The ANP technique, which has been sparingly Investigated by researchers or applied by practitioners is useful for modeling dynamic strategies systemic influences on managerial decisions. 0 1998 Elsevier Science B.V. Keywords: Analytical

network

process; Environment;

Multiple criteria analysis

1. Introduction Environmentally conscious business practices (ECBP) and management has evolved with influences from reactive and proactive activities and policies set forth by organizations. The reactive pressures are typically due to governmental and legal regulations, and maintenance of a status quo among corporate competitors. Proactive pressures are associated with constructing and maintaining a sustainable competitive advantage in various markets. Both these pressures will significantly influence the strategic decisions and directions of an organization, whether they are large multinational corporations or

* Fax: + l-508-793-8822;

e-mail: [email protected].

0377-2217/98/$19.00 0 1998 Elsevier Science B.V. All rights reserved PII SO377-22 17(97)00 160-4

small family owned manufacturing enterprises. The ECBP strategies, technologies, or programs chosen or enhanced, can mean the difference between life or death of many organizations, or at least an event that will determine their marketplace competitiveness. A tool or model to structure strategic environmental decisions in a dynamic competitive and regulatory environment will lessen the competitive, environmental and legal risks faced by many organizations

DOI. This paper presents a model that considers the systemic and hierarchical relationships among a number of decision and environmental factors facing organizations. The general model links strategic and tactical decisions that are used to evaluate various strategic ECBP programs and technology alternatives. Some of the more popular strategic decision

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ofOperational

making models necessarily consider multiple attributes in their analysis. Saaty’s Analytical Hierarchy Process (AHP) [20] is one of the more widely used approaches. Yet, AHP is limited to relatively static and unidirectional interactions with little feedback among decision components and alternatives. An expanded look at the dynamic relationships among ECBP decision attributes is considered in this paper. The analysis technique to model this decision structure is the more general form of the AHP technique called the systems with feedback approach, also defined as the analytical network process (ANP). ANP allows for a systemic (non-linear) strategic analysis of decision attributes. Its application has been relatively limited when compared to the AHP approach. Some examples of its application include energy policy planning 191, product design [22], and equipment replacement decisions [ 11. The type of strategic decisions facing environmental and corporate managers can range from the type of processes introduced into an organization, to the suppliers/partners selected for a product type, to the level of training required for engineers learning design for the environment principles. To accomplish the modeling tasks for the decision environment, a review of practice and attributes involved in strategic ECBP decisions will be presented. The relationships among these attributes will be identified. Temporal, product life cycle, life cycle assessment, and organizational partnership relationships, are all examples of dynamic social, environmental, and organizational relationships that may be modeled. Included among the decision components are proactive environmental categorizations such as, total quality environmental management, design for the environment, life cycle analysis, green supply chain management, and IS0 14000 certification requirements. Reactive factors such as meeting regulatory requirements will also be integrated into the model. A number of tactical characteristics and subcomponents having relationships to the more strategic ECBP, will be defined. The purpose of the paper is to present a generic model that managerial decision makers can extend and apply to their specific organization. The paper also provides a review of the various tools and techniques for ECBP. An illustrative example provides a review of ANP while defining the capabilities of this model, as well as its

Research 107 (1998) 159-174

limitations. Managerial implications of the model are also discussed.

2. Environmental

for application

strategy and business practices

In this section we provide a review of the various and emerging ECBP components and their sub-components. This discussion will serve as the foundation for the ANP model. The review will include a discussion of five strategic ECBP components that have recently gained much attention among practitioners and researchers. The ECBP components include design for the environment (DFE), life cycle analysis (LCA), total quality environmental management (TQEM), green supply chain management (GSC), and IS0 14000 environmental management systems requirements. 2.1. Design for the environment The philosophy of DFE, evolved from the design for ‘x’ principles associated with concurrent engineering. Its goal is to consider the complete product life cycle when designing environmental aspects into a product or process. DFE incorporates the types of materials that are used in the manufacture of the product, materials’ recyclability and reusability capabilities, the materials’ long term impact on the environment, the amount of energy (and efficiency) required for the product’s manufacture and assembly, the capability for easy disassembly for remanufacturing, considerations of the product’s design to include remanufacturing characteristics, and consideration of the products durability and disposal characteristics. The DFE concept supports the philosophy that environmental factors need to be integrated into the early design of any product or process. For ANP modeling purposes, DFE has a number of functional sub-components that should be included in a successful DFE program. Another categorization could be the consideration of technological and organizational sub-components. The functionality perspective encompasses design for recyclability (RECY), remanufacturability (REMAN), reuse (REUSE), disassembly (DISASS), and disposal (DISP). The functionality grouping is used to compare attractiveness and viability of various ECBP

J. Sarkis/European

alternatives. Descriptions now presented. Designing

for

Journal

of these sub-components

reusability,

recyclability

and

of Operational

is re-

manufacturing

vary in terms of degree. The relationship between recycling, reuse and remanufacturing can be defined by the amount of treatment required, where minimal treatment of a material is more closely associated with reuse of a product, while a material that requires a large amount of treatment is more characteristic of recycling, remanufacturing typically falls in-between this spectrum. Reuse involves the on-site or off-site use, with or without treatment, of a waste product. If design for recyclability is a goal, the organization must consider the capabilities of the materials that can be recycled, or at least capabilities of the materials and sub-components of the product. Design for reuse will typically focus on the overall product and less so on the components. Design for remanufacturing refers to the design of a product with respect to repair, rework, or refurbishment of components and equipment to be held in inventory for either external sale or internal use. In a typical remanufacturing process, identical ‘cores’ (the worn-out components and equipment) are grouped into production batches, completely disassembled, and thoroughly cleaned before being reassembled t121. Design for

disassembly focuses on designing a product that may be dismantled for recycling, remanufacturing or reuse purposes. Technological and design characteristics may include various libraries and materials of alternative adhesives and connection devices that can be used to form and disassemble products. Appropriate and specialized equipment and processes will be required for implementing and managing this ECBP sub-component. Designing for disposal includes consideration of materials and transportation requirements of materials that will be used in a product. The issues of a product’s biodegradability and toxicity will play a large role in this design phase. The appropriate technological tools and equipment for incorporating design for disposal need to be determined.

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ment, (LCA) focuses on the analysis of the design and is closely linked to DFE outputs. LCA appraises various characteristics of a product’s life cycle from the preparation of its input materials to the end of its use. An LCA of the product design “evaluates the types and quantities of product inputs such as energy, raw materials, and water, and of product outputs, such as atmospheric emissions, solid and waterborne wastes, and end-product” [5]. The LCA methodology can be used as an objective tool to identify and evaluate opportunities to reduce the environmental impacts associated with a specific product, process, or activity. The four basic interrelated components of an LCA include: Inventory Analysis (INVAN) is the identification and quantification of energy and resource use and the environmental effects to natural resources throughout a product’s life [6]. The processes of acquiring inventory data and component analysis, which are required for inventory analysis, are further discussed in [7] and [28]. Impact Analysis (IMPAN) is the assessment of the consequences and risks that wastes have on the environment [4]. It evaluates an array of alternatives and identifies the activities with greater and lesser environmental consequences. Life-Cycle Costing (LCC) is a methodology in which all costs are identified for a product throughout its lifetime, from raw materials acquisition to disposal [2]. This method of cradle-to-grave product accounting attaches a monetary figure to every effect of a product [ 111. LCC should be performed before the product is manufactured so that changes in design can be made easily but can be performed at the end of an existing product’s life-cycle [ 13,151. Improvement Analysis (IMPVAN) (often referred to as environmental auditing) is the evaluation and implementation of opportunities that effect environmental improvements [4]. Improvement analysis systematically documents periodic reviews of a facility’s operations, ensuring waste minimization and pollution prevention. 2.3. Total quality environmental

management

2.2. Life cycle analysis Where DFE is primarily focused on design of a product or process, life-cycle analysis, or assess-

TQEM sub-components are closely related to the sub-components of standard TQM. The elements of TQEM have been characterized by the Malcolm

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Baldrige Award criteria for a number of organizations and the Environmental Protection Agency (EPA) [3,14,25,27]. These criteria are redefined for TQEM and introduced as the following sub-components, leadership, human resources development, environmental quality management systems, strategic environmental quality planning, environmental quality assurance, environmental measurements, and stakeholder emphasis. Each of the Baldrige based TQEM sub-components is briefly defined. Leadership (LEADER) in an organization requires support for environmental strategies and programs by upper management. Typically most strategic programs fail due to lack of management support. Management leadership in TQEM environments are discussed in [ 14,271: Human resources development (HRD) and utilization requires that employees at all levels be empowered and trained to observe, control, and implement ECBP. Environmental quality management systems (EQMS) requirements include having the right documents and information on the environmental quality systems and processes. The EQMS should be able to incorporate life cycle data, environmental design information, regulatory data, materials and process data. EQMS needs to appropriately distribute environmental quality information. Strategic environmental quality planning (SEQP) supports inclusion of the natural environment in organizational strategic planning. Environmental quality assurance (EQA) is the operational sub-component of TQEM. Execution and implementation of tools, techniques, and processes that can manage the continuous improvement of environmental quality is one of its goals. Integrating new and traditional quality control tools is an important dimension of this sub-component. Environmental measurements (EMEAS) need to encompass a number of levels of analysis. Some of the criteria for measurement are regulatory, others may be competitively (customer-stakeholder) oriented. For example both pollution prevention, in-process, and end-of-pipe environmental impact metrics should be developed. A stakeholder emphasis (STAKE) is the last (and first) criteria for TQEM. The term stakeholder is accentuated here since it goes beyond the typical

Research 107 (1998) 159-174

‘customer’ focus. Stakeholders include community, government, stockholder, employee, supplier, as well as customer representatives. For a more complete discussion on stakeholder theory, see Freeman [6a]. 2.4. Green supply chain management Our focus of the ECBP components has been on internal organizational practices. To help link the ECBP to external relationships, GSC issues become relevant. Specifically, the GSC assessment can be completed by considering the various elements of logistics planning and packaging. The major subcomponents for GSC are inbound logistics (which includes procurement), materials management, outbound logistics, packaging, and reverse logistics issues. The relevant literature related to this ECBP component can be found in [16-l&23,29]. Inbound logistics and procurement (INBD) focuses on the delivery and purchase of materials. This sub-component will be influenced by supplier and vendor management issues as well. The acquisition of materials includes the ability to locate and determine the existence of environmentally friendly materials and vendors. Materials Management (MTMAN) includes the internal organizational transformation and movement of materials. Minimization of inventory and inventory management play a significant role within this sub-component. Outbound logistics (OUTBD) may be the subcomponent with the highest potential environmental impact. This sub-component includes transportation, warehouse, and distribution planning. Whereas, inbound logistics considered suppliers and material for transformation purposes, outbound logistics is concerned with customer requirements and finished goods. Packaging (PACK) may include three definitions: primary packaging, secondary packaging, and shipping packaging [29]. Better packaging, along with rearranged loading patterns, can reduce materials usage, increase space utilization in the warehouse and in the trailer, and reduce the amount of handling required. Reverse Logistics (REVLOG) includes the following major phases: collection, separation, denxijication, transitional processing, delivery and inte-

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qf Operational Research 107 f 1998) 159-I 74

grution. A system for reintegration of disposed materials and products into the manufacturing system is a focus of reverse logistics.

2.5. IS0 14000 requirements The IS0 14000 environmental management family of standards are in the process of being finalized and should be complete by late 1996 or in 1997. The sub-components presented here are representative of the most recent IS0 14001 standards. IS0 14001 focuses on the specification of systems and guidance for use, which form the core of the IS0 14000 standards. Much of the information presented here is detailed in [26]. The major elements within this category include setting of environmental policy, planning, implementation and operation, checking and corrective action, and management review. The pattern in these standards is to set the policy, then carry out the plan, do, check, act (PDCA) cycle for continuous improvement, with a management review completion. IS0 14000 has grown out of the IS0 9000 and British environmental standard BS 7750 (see [ 191, for a good review of the BS 7750 standards and their history). A summary of the pertinent sections and sub-sections for IS0 14001 is shown in Table 1. These factors alone may serve as a separate analysis hierarchy, but will be used as sub-components for the model developed in this paper. Environmental policy (EP) is a “statement by the organization of its intentions and principles in relation to its overall environmental performance.” Requirements of an EP include a commitment to compliance, prevention of pollution, continual improvement, that is to be documented and communicated to stakeholders. Planning (PLAN) has been defined by the IS0 standards to incorporate five steps/elements. These steps include defining controllable environmental aspects, determine which aspects have significant environmental impacts, determine the legal dimensions of these impacts, establish objectives and targets, and establish the environmental management system. Implementation and operation (IO) requires getting human, physical, and financial resources in place to achieve the company’s objectives and targets. It is within this sub-component that actual documentation

of the processes and environmental programs needs to be completed. Checking and corrective action (CCA) includes the measurement and evaluation of environmental performance, applying any necessary corrective actions, maintenance of records, and auditing the environmental systems. Management review (MREV) looks at the overall environmental management system, beyond operational auditing and control. Policy, objectives and procedures need to be reviewed. Feedback systems that include all levels of personnel and management will support the successful completion of this subcomponent. All together these ECBP components and subcomponents form the foundation of any organization’s efforts to become environmentally benign. For clarity, the various components, sub-components, and their abbreviations, are summarized in Table 2. Many necessary organizational programs, technologies, projects, and processes that may serve as alternatives to support these components and sub-components still need to be implemented in organizations. These alternatives, which may require significant planning and resources for implementation, will typically re-

Table I IS0 14001 certification systems 4.1 4.2 4.2.1 4.2.2 4.2.3 4.2.4 4.3 4.3. I 4.3.2 4.3.3 4.3.4 4.3.5 4.3.6 4.3.1 4.4 4.4.1 4.4.2 4.4.3 4.4.4 4.5

sections

for environmental

management

Environmental policy Planning (PLAN) Environmental aspects Legal and other requirements Objectives and targets Environmental management program(s) Implementation and operation (IO) Structure and responsibility Training, awareness and competence Communication Environmental management system documentation Document control Operational control Emergency preparedness and response Checking and corrective action (CCA) Monitoring and measurement Non conformance and corrective and preventive action Records Environmental management system audit Management review (MREV)

164 Table 2 Summary

J. Sarkis/European

of components

Environmentally

and sub-components

conscious

Design for the Environment

Journal of Operational

of major environmentally

business practices components (DPE)

Total Quality Environmental

conscious

Environmental Design Design Design Design Design

Life Cycle Analysis (LCA)

Research 107 (1998) 159-174

for for for for for

business practices conscious

business practices

sub-components

Recyclability (RECY) Reuse (REUSE) Remanufacturability (REMAN) Disassembly (DISASS) Disposal (DISP)

Inventory Analysis (INVAN) Life Cycle Costing (LCC) Impact Analysis (IMPAN) Improvement Analysis (IMPVAN) Management

Green Supply Chain Management

(TQEM)

(GSCI

IS0 14000 EMS Requirements

quire some form of justification. This need for justification is due to most organizations lack necessary resources to effectively implement these all supporting ECBP alternatives. Thus, a decision tool to aid in an initial evaluation will enhance the effectiveness of those ECBP alternatives that are selected to aid an organization in meeting its environmental strategic goals.

3. The decision environment Thus far, various ECBP components and subcomponents and their relationships have been defined. The concern at this time is to evaluate projects, systems, alternatives, etc., that will have an influence on the environmental performance of an organization, The primary factors for analysis will be

Leadership (LEADER) Strategic Environmental Quality Planning (SEQP) Environmental Quality Management Systems (EQMS) Human Resources Development (HRD) Stakeholder Emphasis (STAKE) Environmental Measurements (EMEAS) Environmental Quality Assurance (EQA) Inbound Logistics/Procurement (INBD) Materials Management (MTMANI Outbound Logistics/Transportation (OUTBD) Packaging (PACK) Reverse Logistics (REVLOG) Environmental Policy (EP) Planning (PLAN) Implementation and Operation (IO) Checking and Corrective Action (CCA) Management Review (MREV)

the ECBP components and sub-components. Additional considerations include the external environmental pressures that could influence the priority scheme of each of the components. The network relationships among the various levels of components are summarized in Fig. 1. Fig. 1 shows that the planning time period has a two-way dependency with the regulatory environment. Similar relationships exist between ECBP components and the regulatory environment components. An additional interdependency within the ECBP components exists. The interdependency is modeled by a looped arrow. At the lower levels of the network hierarchy, we have only included one way dependencies, as in a traditional analytical hierarchy, between the ECBP components, sub-components and alternatives. This network hierarchy’s goal is to influence a strategic organizational decision on the various alternatives. A

J. Sarkis / European Journal of Operational

Fig. 1. General representation of the analytical network hierarchy for ECBP strategic evaluation.

more detailed graphic of this network architecture is shown in Fig. 2. We shall now describe some of the major relationships that may exist among the components and levels.

74

2

-.*

N

Reaulatorv Environment

ECBP Sub -Componcn

Alternative Systems, Projects erc.

CurrentSystem

165

The major external influences on ECBP decisions involve the type of regulatory environment that the organization faces. For example, three types of potential environments may exist, remediation, compliance and cooperative (see [8] for a similar categorization). Remediation concerns include the previous history of environmental performance of the organization and the efforts by communities and government agencies to implement more remediation oriented policies (e.g. superfund). In this situation, those ECBP that would aid in remediation processes are expected to have a more central role. Green supply chains, will help guarantee that remediation problems are limited, and if remediation issues occur, having a supply chain (or reverse supply chain) that can support the wastes from a remediation situation, would greatly enhance an organization’s response to this area. Some of the TQEM approaches of managing stakeholder expectations and some of the information/documentation requirements of IS0 14000 may be important characteristics for the remediation environment. A compliance oriented environment would influence current practices through adherence to legal and

ECBP Strategic Chic+

Time Period 1

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System A

System B

Fig. 2. Detailed graphical representation of analytical network hierarchy for ECBP strategic evaluation.

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regulatory requirements. The command and control situation presented by a compliance oriented regulatory environment focuses on strict controls for endof-the-pipe wastes. The characteristics of this environment are relatively reactive, but organizations will have more direct control than trying to manage historical occurrences, as in the remediation environment. The IS0 14000 component may prove a little more valuable in this regulatory environment since a major focus of the EMS requirements are regulations oriented. DFE tools which can help manage what comes out at the end-of-the-pipe may prove beneficial here. The final external regulatory environment that may exist is a cooperative situation. Cooperation between industry and its stakeholders is a typical goal. But, it may not always be the final situation. The use of most of the tools, especially green supply chains, TQEM and LCA are relatively proactive and helpful for this environment. The other directional relationship shown in Fig. 2 in the regulatory environment-ECBP level of relationships is not as clear. This set of relationships can be interpreted by the importance of an ECBP being greater for the organization in a regulatory environment where the ECBP is weaker or lagging. That is, the DFE tools available in the organization may be lagging for a cooperation environment and thus need more developmental emphasis for that environment. This variance would put a higher relative importance weight on cooperation over remediation where DFE is a controlling component. The time factor-regulatory environment relationship defines what the expected relative importance or emphasis of each regulatory environment will be in a given time period. The regulatory environment-time factor relationship defines the relative impact of the regulatory environment factor across time periods. These interdependent relationships among levels will provide a long-term set of weights for various potential environments for the ECBP. The other ‘non-linear’ linkage is the interdependence of the ECBP components and sub-components among each other. For example, for a given LCA level, there will be some impact on DFE practices. In addition, to the standard pairwise comparisons of the sub-component to component relationships, the relative importance weights of the alternate projects or

Research IO7 (I 998) 159-I

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programs will need to be determined for each of the ECBP sub-components. This relationship will require a pairwise comparison matrix of alternatives for each sub-component. Additional examples of some of the various interdependencies among ECBP components and sub-components include: A number of TQEM and LCA requirements and sub-components are linked to environmental management system and documentation requirements of IS0 14000. The environmental planning sub-component of IS0 14000 relates closely to TQEM’s leadership and strategic planning sub-components. Improvement analysis, a sub-component of LCA, which identilies problems, measures progress over time, and offers a means for continuous improvement is related to the goals of TQEM’s continuous improvement philosophies. Packaging, a Green Supply Chain ECBP subcomponent, has a relationship to DFE. Reverse Logistics, another Green Supply Chain ECBP sub-component, has linkages to DFE and TQEM components through their product design and stakeholder relationships sub-components, respectively. IS0 14000 certification may aid in the process of locating vendors for a Green Supply Chain. Materials Management, a Green Supply Chain sub-component, from a process management perspective relates to quality control and internal organizational TQEM efforts. The last major set of components in the model are the alternatives that the decision makers wish to evaluate. The alternatives in this model may represent technologies, programs, or projects that can impact any or all of these programs. It is not necessary that the alternatives be mutually exclusive (e.g. only one project can be selected). Portfolios of alternatives may be evaluated, where the ranks can be used in capital rationing models. Examples of technology alternatives could be development or purchase of systems or databases that have life cycle information for particular products manufactured by the organization. The type of information or the data would need to be gathered from various functions and locations of the organization or suppliers and customers. This information will impact every ECBP

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we have mentioned at some level. An example program would be training programs geared toward understanding and implementing environmentally conscious processes in organizations. Who is to be trained and type of training programs would be alternatives that could be evaluated on each of the ECBPs. As more and more consultants and vendors develop wares and technology for corporate environmental management, the number and types of alternatives will increase. The discussion of the ANP process supported by an illustrative example will provide additional explanation of the linkages and insights into how this framework could be used to support managerial decisions.

167

example, a number of interdependencies are identified, and will form the supermatrix. The two-way level to level interdependencies include the time and regulatory environment components, and the regulatory environment and ECBP components. Withinlevel interdependencies exist at the ECBP components level. The values used for the illustrative example are assumed. In an actual application of this model a complex iterative approach is recommended, one designed to elicit the data from the ‘minds’ of one or more strategic planners who have a stake in the final decision. This may include input from sources outside the immediate enterprise such as customers and suppliers. 4.1. ANP analysis and solution methodology

4. The analytical network process ANP is a more general form of AHP. Whereas AHP models a decision making framework using a uni-directional hierarchical relationship among decision levels, ANP allows for more complex interrelationships among the decision levels and components. Typically, in AHP the top element of the hierarchy is the overall goal for the decision model. The hierarchy decomposes from a general to a more specific attribute until a level of manageable decision criteria is met. ANP does not require this strictly hierarchical structure. Interdependencies may be graphically represented by two way arrows (or arcs> among levels, or if within the same level of analysis, a looped arc. The directions of the arcs, in this case, signify dependence, arcs emanate from an attribute to other attributes that may influence it. The relative importance or strength of the impacts on a given element is measured on a ratio scale similar to AHP. A priority (relative importance weighting) vector may be determined by asking the decision maker for their numerical weight directly, but there may be less consistency, since part of the process of decomposing the hierarchy is to provide better definitions of higher level attributes. The ANP approach is capable of handling interdependence among elements by obtaining the composite weights through the development of a ‘supermau-ix’. Saaty [20,21] explains the supermatrix concept as a parallel to the Markov chain process. The supermatrix development is detailed below. In this

The ANP analysis will be reviewed through a series of six steps that includes the analysis of the ECBP model. Step I. Model Construction and Problem Structuring: The first step is to construct a model to be evaluated. The illustrative example will use the ECBP model that was developed earlier in the paper and a detailed summary presented in Fig. 2. The relevant criteria and alternatives are structured in the form of a hierarchy where the higher the level, the more encompassing or ‘strategic’ the attribute. The model development will require the delineation of attributes at each level and a definition of their relationships. In this example, a number of levels of interdependence or feedback are observed. Step 2. Pairwise Comparisons Matrices of lnterdependent Component Levels: Eliciting preferences of various components and attributes will require a series of pairwise comparisons where the decision maker will compare two components at a time with respect to an upper level ‘control’ criterion. These comparisons are collected in a pairwise comparison matrix. In ANP, like AHP, pairwise comparisons of the elements in each level are conducted with respect to their relative importance towards their control criterion. Within this illustrative example the relative importance of the ECBP with respect to a specific regulatory environment (e.g. TQEM in a compliance environment) is first determined. A pairwise comparison matrix will be required for each of the three

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regulatory environments for calculation of impacts by each of the ECBPs. In addition, five pairwise comparison matrices are used for calculation of the relative impacts of the regulatory environment on a specific ECBP. To fully describe these two-way relationships, 8 pairwise comparison matrices will be required. To elicit the values for the pairwise comparisons for interdependent levels, the questions need to be carefully worded. For example, one question may be, “How much more important is it for your organization to have a TQEM program rather than a DFE program in a compliance focused regulatory environment?” The controlling attribute in this circumstance is the compliance regulatory environment and the comparison is between a TQEM and DFE program. An example of the pairwise comparison matrices within the compliance regulatory environment is presented in Table 3. A review of the pairwise comparison matrices formation and calculation approach is summarized in Appendix A. In the compliance environment, the DFE ECBP is viewed as being less important (a,, = 0.200) then the TQEM ECBP. The weighted priorities for this pairwise comparison matrix are shown as the last column in Table 3 (the eVector column). The weighted priorities columns for each of the regulatory environment matrices (three in all) are combined to create a matrix A with five rows and three columns (see Table 4). The results in Table 4 show that green supply chains (which include reverse logistics) is the most important ECBP in a remediation environment for this organization. In a compliance environment, with TQEM’s emphasis on pollution prevention and IS0 14000’s emphasis on documentation of systems, make these two ECBPs most environment, a DFE important. In a cooperative program may be viewed most highly by this organi-

Table 3 Pairwise comparison matrix for ECBP with compliance environment as ‘controlling’ component

regulatory

Compliance

DPE

LCA

TQEM

GSC

IS0

eVector

DPE LCA TQEM GSC IS0

1.000 2.000 5.000 1.000 3.000

0.500 1.000 2.000 0.500 2.000

0.200 0.500 1.000 0.333 0.500

1.000 2.000 3.000 1.000 7.000

0.333 0.500 2.000 0.143 1.000

0.080 0.160 0.373 0.081 0.306

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Table 4 Matrix A, aggregation of relative importance in each of the regulatory environments

weights for ECBPs

Matrix A

Remediation

Compliance

Cooperation

DPE LCA TQEM GSC IS0

0.045 0.255 0.154 0.491 0.055

0.080 0.160 0.373 0.08 1 0.306

0.469 0.187 0.181 0.107 0.056

zation due to the development of processes and products that may be environmentally benign, with support for design and development of these items from governmental agencies. Similarly, there is a matrix B (three rows and five columns) that is formed from the accumulated weighted priorities of the ECBP within each period. Calculation of the relationships between the time factors and the type of regulatory environment may then be determined (the order of calculations for interdependencies among levels is not particularly significant). Questions as to the likelihood of particular regulatory environments existing in certain periods and relative focus of each regulatory environment for a given period will need to be asked for completing these pairwise comparison matrices. Assuming there are four time periods to be considered in this model, seven pairwise comparison matrices will be required for this level of interdependency. The pairwise comparison matrix will be similar to the one presented in Table 3 for the other interdependent levels. The relative importance weights for each of the pairwise comparison matrices will be aggregated as matrix C and D respectively for each directional relationship. The final interdependencies, in this example, exist among the ECBP components themselves. Each ECBP will have itself as a controlling attribute with the comparisons made among each of the components. A sample question may be: “When practicing ECBP, given a TQEM program, which other ECBP component contributes to TQEM, more; and how much more?” A zero indicates that there is no effect nor dependence among the components. Thus, the pairwise comparison matrices would identify the controlling variable and ECBP components with significant dependence for that controlling variable. An

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Table 5 Example pairwise comparison matrix for ECBP interdependencies with TQEM as ‘controlling’ component TQEM

DFE

LCA

TQEM

IS0

eVector

DFE LCA TQEM IS0

1.000 0.333 7.oOil 3.000

3.000 1.000 9.OQO 8.000

0.143 0.111 1.000 0.200

0.333 0.125 5.000 1.000

0.095 0.043 0.627 0.235

sub-matrices (all the elements in a zero sub-matrix are zero>. In Fig. 3 we show the generalized submatrices in letter notation as they would appear in the ‘unweighted’ super’matrix. Table 6 presents the values associated with the ‘unweighted’ supermatrix. In the unweighted supermatrix the columns may not be column-stochastic, (i.e. do not sum to one). A transformation is required for the columns to become column-stochastic (this transformation forms a ‘weighted’ supermatrix) and thus minimize the possibility for divergence to infinity or convergence to zero. One transformation process proposed by Saaty [20,21] to make the supermatrix column-stochastic is to weight the components according to their impact on the column of blocks. The row components of the non-zero column blocks within the supermatrix are compared according to that column block. In this case only two component block pairwise comparison matrices will be required (since the time period column is already column-stochastic). Each block is weighted to the relative importance weight corresponding to the component in that row. We shall

Step 3. Supermatrix Formation: The supermatrix allows for a resolution of the effects of interdependence that exists between the elements of the ANP network. The supermatrix is a partitioned matrix, where each sub-matrix is composed of the pairwise comparison matrices formed in Step 2 or are zero

super-matrix for interdependencies

among component

T

1

Fig. 3. Generalized supermatrix for time (T), regulatory environconscious business practices (EC), ment (R), and environmentally relationships and submatrix locations.

example matrix where TQEM is a controlling variable is shown in Table 5, note that Green Supply Chains are not included in this pairwise comparison matrix because it is assumed that no significant relationship exists. The results in Table 5 clearly show that a enhancing elements of the TQEM program will most impact the TQEM program. The second most important factor that may influence the TQEM program is the addition or enhancement of the IS0 14000 ECBP. This importance ranking is due to the many interlinkages between IS0 14000 and the TQEM ECBP sub-components, as described earlier. The relative importance weights for each of the ECBP interdependency pairwise comparison matrices will be aggregated into a matrix E.

Table 6 The unweighted

R.EC

levels

R

EC

Per. 1

Per. 2

Per. 3

Per. 4

Remed

Comp

Coop

DFE

LCA

TQEM

GSC

IS0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0.105 0.225 0.123 0.547

0.331 0.418 0.172 0.079

0.117 0.197 0.223 0.463

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

Remed Comp coop

0.455 0.3 12 0.233

0.345 0.399 0.256

0.234 0.415 0.351

0.133 0.222 0.645

0 0 0

0 0 0

0 0 0

0.125 0.221 0.654

0.413 0.222 0.365

0.455 0.297 0.248

0.337 0.215 0.448

0.313 0.445 0.242

DFE LCA TQEM GSC IS0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0.045 0.255 0.154 0.49 1 0.055

0.080 0.160 0.373 0.08 1 0.306

0.469 0.187 0.181 0.107 0.056

0.672 0.221 0.054 0.032 0.02 1

0.203 0.554 0.061 0.012 0.170

0.095 0.043 0.627 0.000 0.235

0.098 0.113 0.187 0.602 0

0.109 0.02 1 0.209 0.028 0.633

T

Per. Per. Per. Per.

R

EC

1 2 3 4

170

J. Sarkis/European

Journal of Operational Research 107 (1998) 159-174

Table 7 The weighted supermatrix (MI for interdependencies among component levels T Per.

EC

R

1

Per. 2

Per. 3

Per. 4

Remed

Comp

Coop

DPE

LCA

TQEM

GSC

IS0

T

Per. 1 Per. 2 Per. 3 Per. 4

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0.079 0.169 0.092 0.410

0.248 0.314 0.129 0.059

0.088 0.148 0.167 0.347

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

R

Remed Comp Coop

0.455 0.312 0.233

0.345 0.399 0.256

0.234 0.415 0.351

0.133 0.222 0.645

0 0 0

0 0 0

0 0 0

0.050 0.088 0.262

0.165 0.089 0.146

0.182 0.119 0.099

0.135 0.086 0.189

0.125 0.178 0.097

EC

DFE LCA TQEM GSC IS0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0.011 0.064 0.038 0.123 0.014

0.020 0.040 0.093 0.020 0.077

0.117 0.047 0.045 0.027 0.014

0.403 0.133 0.032 0.019 0.013

0.122 0.332 0.037 0.007 0.102

0.057 0.026 0.376 0.000 0.141

0.059 0.068 0.112 0.36 I 0.000

0.065 0.013 0.125 0.017 0.380

Table 8 The converged supermatrix (M”‘) T

EC

R

Per. 1

Per. 2

Per. 3

Per. 4

Remed

Comp

Coop

DPE

LCA

TQEM

GSC

IS0

Per. I Per. 2 Per. 3 Per. 4

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.1 !6

0.057 0.086 0.056 0.116

0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

0.057 0.086 0.056 0.116

R

Remed Comp coop

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

0.118 0.130 0.172

EC

DFE LCA TQEM GSC IS0

0.065 0.05 1 0.062 0.038 0.046

0.065 0.05 1 0.062 0.038 0.046

0.065 0.051 0.062 0.038 0.046

0.065 0.05 1 0.062 0.038 0.046

0.065 0.05 I 0.062 0.038 0.046

0.065 0.051 0.062 0.038 0.046

0.065 0.05 1 0.062 0.038 0.046

0.065 0.051 0.062 0.038 0.046

0.065 0.05 1 0.062 0.038 0.046

0.065 0.051 0.062 0.038 0.046

0.065 0.05 1 0.062 0.038 0.046

0.065 0.05 1 0.062 0.038 0.046

T

assume the two column block weightings for the regulation environment (R) column to be a 0.75 weighting for the time period (T) column block and 0.25 for the ECBP (EC) column block. The two column block weights R and EC for the EC column are assumed to be 0.40 and 0.60, respectively. The component block weights are then multiplied to each of the respective column elements. Table 7 shows the weighted supermatrix M. Raising the supermatrix to the power 2k + 1, where k is an arbitrarily large number, allows convergence of the interdependent relationships and pro-

vides the long-term impacts of the components on each other. In this example, convergence (to 10M4 precision) was reached at M129. The converged supermatrix is shown in Table 8. The priority weights Table 9 Pairwise comparison matrix for alternatives with respect to design for recyclability (RECY) sub-component

RECY

Current

A

B

eVector

Current A B

1.000 4.000 7.000

0.250 l.OtXl 0.500

0.143 2.000 1.000

0.091 0.514 0.396

INVAN LCC IMPAN IMPVAN

LEADER SEQP EQMS HRD STAKE EMEAS

LCA

TQEM

INBD MTMAN OUTBD PACK REVLOG

EP PLAN IO CCA MREV Desirability indices

IS0

GSC

RECY REUSE REMAN D&ASS DISP

DFE

EQA

Sub-component

ECBP

0.175 0.175 0.175 0.175 0.175

0.145 0.145 0.145 0.145 0.145

0.237 0.237 0.237 0.237 0.237 0.237 0.237

0.195 0.195 0.195 0.195

0.248 0.248 0.248 0.248 0.248

0.127 0.176 0.29 I 0.312 0.094

0.310 0.228 0.176 0.084 0.202

0.190 0.127 0.058 0.149 0.22 I 0.095 0.160

0.098 0.249 0.44 1 0.212

0.125 0.234 0.287 0.024 0.330

Sub-camp.

with final calculated

ECBP weights

Table 10 Scores and weights for alternatives, weights

desirability

0.223 0.237 0.035 0.112 0.1 12

0.112 0.554 0.192 0.354 0.333

0.333 0.333 0.241 0.034 0.123 0.651 0.358

0.233 0.122 0.336 0.458

0.091 0.322 0.441 0.243 0.098

Incumbent

indices weight Alt. A weight

0.128 0.389 0.455 0.713 0.112

0.423 0.212 0.56 I 0.122 0.561

0.333 0.334 0.125 0.483 0.532 0.148 0.302

0.214 0.322 0.552 0.1 I5

0.514 0.425 0.441 0.379 0.155

Alt. B weight

0.649 0.374 0.510 0.175 0.776

0.465 0.234 0.247 0.524 0.106

0.334 0.333 0.634 0.483 0.345 0.201 0.340

0.553 0.556 0.112 0.427

0.395 0.253 0.118 0.378 0.747

Incumbent

0.005 0.007 0.002 0.006 0.002 0.249

0.005 0.018 0.005 0.004 0.010

0.015 0.010 0.003 0.001 0.006 0.015 0.014

0.004 0.006 0.029 0.019

0.003 0.019 0.03 1 0.001 0.008

score

0.003 0.012 0.023 0.039 0.002 0.382

0.019 0.007 0.014 0.001 0.016

0.015 0.010 0.002 0.017 0.028 0.003 0.01 I

0.004 0.016 0.047 0.005

0.016 0.025 0.03 1 0.002 0.013

Alt. A score

0.014 0.012 0.026 0.010 0.013 0.369

0.02 I 0.008 0.006 0.006 0.003

0.015 0.010 0.009 0.017 0.018 0.005 0.013

0.011 0.027 0.010 0.018

0.012 0.015 0.008 0.002 0.06 I

Alt. B score

172

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Journal of Operational

that will be important for the selection analysis appear in the ECBP rows. These weights may be normalized to one by dividing each of the five components by the sum of the components. This normalization provides the following weights: DFE (0.248), LCA (0.195), TQEM (0.237), GSC (0.145), IS0 (0.175). These weights take into consideration the major interdependencies in the analysis network hierarchy. DFE seems to have the largest weights due to its consistent influence on other ECBPs and its strong relationship to the cooperative regulatory environment (which also seemed to have the highest ratings among the regulatory environment components). Step 4. Analyze ECBP sub-components: In this illustration it is assumed that no interdependence between the ECBP components level and their subcomponents exist. A similar pairwise comparison that was made in Step 2 is made for the attributes level for relative importance weight calculation (or eigenvector determination). There are five pairwise comparison matrices that are developed for this step in the analysis. A typical question that may be asked to help complete these pairwise comparison matrices is: “What is the relative importance to your organization for the introduction of sub-component i when compared to sub-component j for controlling component k?”

Step 5. Alternative Program, Project, or Technology Evaluations: Each alternative will need to be evaluated on each of the ECBP sub-components. This evaluation is completed by making a pairwise comparison of the performance or impact of each alternative on each sub-component. Since there are 26 sub-components, an additional 26 n X n pairwise comparison matrices (where n is the number of alternatives) will be needed for evaluation. This illustration includes three alternatives, a current (incumbent) system that is to be evaluated against two new alternatives, which may be hard technology alternatives (e.g. a new process technology) or soft technology (e.g. environmental training program). For a more extensive list of possible environmental alternatives in a manufacturing/design environment see [24]. The pairwise comparisons are completed by asking the relative impact of one system on a ECBP sub-component. For example in Table 9, the first ECBP sub-component ‘designing for recyclability’

Research 107 (1998) 159-l

74

(RECY), is compared for the current system and alternatives ‘A’ and ‘B’. The current system is assumed to perform worse on the RECY than system ‘A’ and ‘B’, since the other systems include an extensive materials database linkage for alternative materials and may be linked to procurement’s systems. Step 6. Selection of Best Alternative: The selection of the best alternative depends on the calculation of the ‘desirability index’ for an alternative i (Oil. The equation for Di is defined by: K, Di=

i j=l

C

PjAkjSiklt

(1)

k=l

where Pj is the relative importance weight of ECBP component j (from the converged supermatrix), A,, is the relative importance weight for sub-component k of ECBP component j, and S. j is the relative impact of alternative i on sub-corn onent k of ECBP component j. Kj is the index J t of attributes for ECBP component j. J is the index set of components. The alternative with the largest desirability index (calculations shown in Table 10) should be the one selected. In this example the desirability indices are 0.249, 0.382, 0.369, respectively for the incumbent, alternative A and alternative B respectively. This result implies that the most preferable alternative to support our environmentally conscious business practices over the long run, considering the implications of the regulatory environment is alternative A.

5. Summary

and conclusion

in The importance of the natural environment every day and long-term organizational practice and processes is at a level that is unparalleled since the start of the industrial revolution. Regulations, legislation, and competitive pressures have made organizations more aware of the natural environment. The strategic evaluation of environmental practices and programs helps in analyzing various project, technological or business decision alternatives. A systemic evaluation model to aid in accomplishing this task was introduced in this paper. The analytical network process (ANP) was the modeling approach utilized.

J. Sarkis / European Journal

of Operational

It is an effective tool to model complex internal decisions to powerful external forces. The central focus of the model was on the impact of various organizational alternatives on major environmentally conscious business practices, including design for the environment, life cycle analysis, total quality environmental management, green supply chain management, and IS0 14000 requirements. These initiatives were major components of the model. Logical subcomponents for each of these initiatives were also defined within this paper. Many additional initiatives will occur over the next decade, and these should be taken into consideration as the systemic model evolves. An illustrative example showed how the model could be applied. The model does provide a comprehensive strategic analysis framework that has not be delineated elsewhere. Yet, the limitations of the model, and possible extensions, are many. For example, other decision factors need to be incorporated, strategic elements such as cost, flexibility, quality issues need to be integrated to help determine the full impact of the alternatives. Expanding the lower level attributes by defining operational requirements could also provide opportunity for application of this model. As was the case here, the evaluation using ANP can prove relatively cumbersome, especially the elicitation of information for the pairwise comparison matrices (in this case over 50 pairwise comparison matrices were required). The determination of the relationships *vi11require a number of levels of analysts and experts. Yet, as organizations use this tool more frequently, learning takes place, data may be more easily acquired, and model tweaking will become easier for more efficiencies. This initial effort can prove useful for helping organizations make more effective decisions, especially where the long-term well being of the organization and its stakeholders is concerned.

Acknowledgements

This work was partially supported by NSF Grants 9320949 and 9505967, and Texas Higher Education Coordinating Board ATP Grant Number 003656-036.

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Appendix A. Eigenvector, relative weights, calculation methodology

173

importance

Saaty [20] has recommended a scale of 1 to 9 when comparing two components, with a score of 1 representing indifference between the two components and 9 being overwhelming dominance of the component under consideration (row component) over the comparison component (column component). If a component has some level of weaker impact the range of scores will be from 1 to l/9, where 1 represents indifference and l/9 being an overwhelming dominance by a column element over the row element. When scoring is conducted for a pair, a reciprocal value is automatically assigned to the reverse comparison within the matrix. That is, if a,, is a matrix value assigned to the relationship of component i to component j, then a,, is equal to 1). Since many of these values are l/a,, (or strategic, additional strategic group decision making tools such as scenario planning or the Delphi approach can be utilized to assign meaningful values to these pairwise comparisons. Once the pairwise comparisons are completed, the local priority vector w (defined as the eVector in the example figures) is computed as the unique solution to: a;ju,,

Aw = A,,,w,

=

(A.‘)

where A,,, is the largest eigenvalue of A. Saaty [20] provides several algorithms for approximating w. In this paper a two-stage algorithm that involved forming a new n X n matrix by dividing each element in a column by the sum of the column elements and then summing the elements in each row of the resultant matrix and dividing by the II elements in the row. This is referred to as the process of averaging over normalized columns. This method is represented as:

(A.2) where w, is the weighted priority for component i; J is the index number of columns (components); and I is the index number of rows (components).

174

_I. Sarkis/European

Journal

ofOperational

It is still a relatively crude approach, but one of the better methods for estimation of eigenvalues, as proposed by Saaty. This method is recommended because it can be easily used by practitioners who may only have access to simple spreadsheets. In the assessment process there may occur a problem in the transitivity or consistency of the pairwise comparisons. For an explanation on inconsistencies in relationships and their calculations see Saaty [20]. The pairwise comparison matrices are consistent in these examples. References [l] T.M. Azhar, L.C. Leung, A multi-attribute life cycle approach to replacement decisions: An application of Saaty’s system with feedback method, The Engineering Economist 38 (4) (1993) 321-342. [2] E.P. Barnes-Smith, ECM 93 Workshop: Cost benefit analysis, Workshop proceedings, Albuquerque, NM, 1993. [3] B.F. Dambach, B.R. Allenby, Implementing design for environment at AT&T, Total Quality Environmental Management 4 (3)(1995) 51-62. [4] Environmental Protection Agency (EPA), Office of Pollution Prevention and Toxics, The environmental challenges of the 1990’s, in: Proceedings of the International Conference on Pollution Prevention: Clean Technologies and Clean Products, Washington, D.C., 1990. [5] Environmental Protection Agency (EPA), Office of Research and Development, Facility pollution prevention guide, Washington, 1992. [6] F. Field, J.A. Isaacs, J.P. Clark, Life cycle analysis and its role in product and process development, lntemational Journal of Environmentally Conscious Design and Manufacturing 2 (2) (1993) 13-20. [6a] R.E. Freeman, Strategic Management: A Stakeholder Appreach, Pitman, Boston, MA, 1984. t71 B. Gockel, R. Watkins, Application of life cycle analysis in a flexible manufacturing environment, International Journal of Environmentally Conscious Design and Manufacturing 2 (41 (1993) 43-48. 181T.E. Graedel, B.R. Allenby, Industrial Ecology, Prentice Hall, Englewood Cliffs, New Jersey, 1995. [91 R.P. Hamalainen, T.O. Seppalainen, The analytic network process in energy policy planning, Socio-Economic Planning Sciences 20 (6) (1986) 399-405. HOI I. Henrique, P. Sadorsky, The determinants of an environmentally responsive firm: An empirical approach, Journal of Environmental Economics and Management 20 (1996) 38 l395. 1111A. Kleiner, What does it mean to be green?, Harvard Business Review (1991) 39-47. [I21 Lund, R.T., Guidelines for an original equipment manufacturer starting a remanufacturing operation, Technical paper,

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Massachusetts Institute of Technology, Cambridge, MA, 1983. [ 131 L. Matysiak, Cost-benefit analysis for design of environmentally conscious manufacturing, International Journal of Environmentally Conscious Design and Manufacturing 2 (3) (1993) 11-13. [14] E.C. McGee, A.K. Bhushan, Applying the Baldrige quality criteria to environmental performance: Lessons from leading organizations, Total Quality Environmental Management 3 (1) (1993) l-18. and Computer Technology Corporation [I51 Microelectronics (MCC), Electronics and the Environment Roadmap Workshop Proceedings, Washington, D.C., 1993. Role and iI61 P.R. Murphy, R.F. Poist, CD. Braunschweig, relevance of logistics to corporate environmentalism - An empirical assessment, International Journal of Physical Distribution and Logistics Management 25 (2) (1995) 5-19. 171 P.R. Murphy, R.F. Poist, C.D. Braunschweig, Management of environmental issues in logistics: Current status and future potential, Transportation Journal 34 (1) (1994) 48-56. 181T.L. Pohlen, M.T. Fart%., Reverse logistics in plastics recycling, International Journal of Physical Distribution and Logistics Management 22 (7) (1992) 35-47. 191 B. Rothery, BS 7750: Implementing the Environment Management Standard and the EC Eco-management Scheme, Aldershot, Hampshire, UK, 1993. DO1T.L. Saaty, The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill International Book Co., New York, 1980. 1211T.L. Saaty, Decision Making with Dependence and Feedback: The Analytic Network Process, RWS Publications, Pittsburgh, PA, 1996. [221 T.L. Saaty, M. Takizawa, Dependence and independence: From linear hierarchies to nonlinear networks, European Journal of Operational Research 26 (1986) 229-237. [231 J. Sarkis, Supply chain management and environmentally conscious design and manufacturing, International Journal of Environmentally Conscious Design and Manufacturing 4 (2) (1995143-52. 1241J. Sarkis, Manufacturing strategy and environmental consciousness, Technovation 15 (2) (1995) 79-97. 1251M. Shon, Chemical strategies ‘94: Responsible care - A handful of changes, Chemical Marketing Reporter 245 (11 (1994) 8-9. 1261T. Tibor, 1.. Feldman, IS0 14000: A Guide to the New Environmental Management Standards, Irwin Professional Publishing, Chicago, Illinois, 1996. 1271G.H. Wever, G.F. Vorhauer, Kodak’s framework and assessment tool for implementing TQEM, Total Quality Environmental Management 3 (1) (1993) 19-30. [281 H. Wenzel, M.Z. Hauschild, J. Jorgensen, L. Alting, Environmental tools in product development, IEEE International Symposium on Electronics and the Environment, San Francisco, 1994. [291 H.-J. Wu, S.C. Dunn, Environmentally responsible logistics systems, International Journal of Physical Distribution and Logistics Management 25 (2) (1995) 20-38.