PROJECT REPORT ON “A STRATEGIC FRAMEWORK FOR

GREEN SUPPLY CHAIN MANAGEMENT”

BY GAURAV DUTTA

1212026 M-6

INTRODUCTION •Environment conscious business practices have been receiving great scrutiny from both researchers and practitioners.

•Interdisciplinary research has integrated the efforts of management, engineering, physical and social science to move forward toward green supply chain.

•Moreover, when organization thinks for environmental decision to be made, they are mostly strategic with complex mechanism which includes internal & external implications for management of organization.

• One of the methods to approach is to model the dynamic natural environment into a decision framework that is capable of considering the multidimensional qualitative and strategic characteristics.

• Alternative may include such factors of who to partner with, what type of technology to introduce, or what type of organizational practice to adopt.

• The decision to adopt one of alternatives are evaluated on “network hierarchy” is necessary for an effective green supply chain which is dependent on a no. of factors and elements.

• The technique for analyzing the decision is based on the analytical network process (ANP) or the systems-with-feedback approach first introduced by “Saaty”.

• Issues & possible extensions to the ANP approach identify some of its application limitations and its flexibility.

Green Supply Chain Management Lowe defines industrial ecology as “ a systematic organizing

framework for the many facets of environmental management. It views the industrial world as a natural system- a part of the local ecosystems and the global biosphere. It offers a fundamental understanding of the value of modeling the industrial system on ecosystems to achieve sustainable environmental performance ”.

• It has been defined to exist on 3 levels which are characterized by the amount of recycling or reuse of the material that is within the system (or the system’s “openness”).

1st level is a completely closed system with no material or energy leaving the system.

2nd level is identified by some factor of energy and material is reused within the system.

3rd level is completely open system with little material or energy, once consumed, remaining within a system.

• 2nd level is most applicable model for actual systems. It is within these industrial ecosystems models that green supply chains will play a critical and practical one.

• Companies like Hewlett-Packard, IBM, Xerox & Digital Equipment Corporation have introduced some form of initiative for green their supply chains including the integration of suppliers, distributors, & reclamation facilities with increased acceptance of ISO 14001 environmental standards.

• Multidimensional decision environment making includes the elements like influences & relationships of the product life cycle, operational life cycle, organizational performance measurements, & environmentally conscious business practices. These serve as the foundation for a decision framework for prioritizing or selecting systems by the organization that will aid in managing green supply chain.

Product Life Cycle Influence An organization strategic factor that will influence the management

of a supply chain is the product life cycle positioning of the product(s) of an organization.

The typical product life cycle is composed of 4 phases;

1. A product introduction phase is identified by investment in product research & development.

2. A growth phase identified by increasing production capacity and logistics channels.

3. A maturity phase identified where process & cost efficiencies are typically implemented.

4. A decline phase identified where the focus is on product divestment.

The product life cycle phase will necessarily impact the greening of the supply chain.

In the mature and decline stages of the product life cycle the improvement of processes and having an efficient reverse logistics system in place will impact the environmental practices of the organization.

For a multiproduct analysis, environmental decisions become increasingly complex. But, within the product portfolio of the company there should be differential environmental strategies and development product life cycle foci which will depend upon the product’s life cycle maturity.

The Operational Life cycle A more tactical set of organization elements that will influence how

the supply chain is to be managed (either internally or externally) can be described by the operational life cycle (or value chain) of an organization.

The major elements of the operational life cycle will typically include procurement, production, distribution & reverse logistics.

The procurement or purchasing decisions will impact the green supply chain through the purchase of materials that are either recyclable or reusable, or already been recycled. The selection of vendors will also be an important decision at this stage.

Production processes can influence the greening of the supply chain in numerous ways. Some of these impacts include : a process capacity to use certain materials, capabilities to integrate reusable or remanufactured components to system (which would require disassembly capacities), and how well the processes are designed for the prevention of waste.

Distribution and transportation operations networks are important operational characteristics that will affect the green supply chain. A no. of decisions including distribution outlet location, just-in-time policies, will not only influence the forward logistics network, but also the reverse logistics network.

The reverse logistics operation is probably the least developed & studied of the operational functions. The definition of it from environmental perspective focuses primarily on the return of recyclable or reusable products and materials into the forward supply chain.

Porlen & Farris in a study of the plastics reverse logistics process have identified a no. of stages within a reverse logistics channels. Included are : Collection, Separation, Densification, transitional processing delivery, and integration.

Packing has a strong relationship with other components of the operational life cycle. It characteristics such as size, shape & materials have an impact on distribution due to their affect on the transport character tics of the goods. Better packing, 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.

• Environmentally Influential Organizational Practices

o 5 major practices that will impact the waste generated by a supply chain : reduction (reduce), reuse, remanufacture, recycle & disposal alternatives.

o Reduction may be to design the product and process to take into consideration environmental factors (as defined as design for the environment) .Introduction of alternative processes and materials may be used to reduce more hazardous material.

o Reuse, remanufacture & recycle practices are similar, but only vary in degree of reuse of the material.

o Reuse typically keeps the original physically structure of the material with little substitution.

o Remanufacturing requires some disassembly and replacement of parts or components around a core.

o Recycling can take on new physical and chemical characteristics of the product.

o The choice of which practice is best for an organization will depend on the organization and product characteristics.

o A summary of the possible relationships between operational life cycle and environmentally conscious organization practices are shown in figure 1.

Fig 1: Functional model of an organizational supply chain with environmental influential practices.

• KEYWORDS

@ Raw Material @ Process Design @Waste Distribution

@ Virgin Material @ Product Design @ Reuse

@ Fabrication @ Procurement @ Remanufacture

@ Assembly @ Production @Recycle

@ Customer @ Waste @Disposal @Energy

• Process Design : It is the process of creating a new product to be

sold by a business to its customers.

• Process Design : It is the design of new facilities or it can be the modification or expansion of existing facilities.

• Raw Material : It is basic material used in the production of goods, finished products or intermediate materials.

• Energy : It is a source of power, such as fuel, used for driving machines.

• Procurement :It is the acquisition of goods, services or works from an outside external source.

• Virgin Material : It is processed material after raw material used in production of goods , finished product or intermediate material.

• Fabrication : It is the building of small components by different manufacturing processes.

• Assembly : It is a manufacturing in which parts are added as the semi-finished assembly moves from work station to work station where the parts are added in sequence until the final product is produced.

• Production : It is the act of manufacturing goods

• Customer : It is the recipient of a good, service, product, or idea, obtained from a seller, vendor, or supplier for a monetary or other valuable consideration.

• Waste : It is useless materials generated during a manufacturing supply.

• Waste Distribution : It is the process of collective waste collection from raw material till customer ends.

• Reuse : It is process to use an item again after it has been used.

• Remanufacture : It is the process of disassembly and recovery at the module level and, eventually, at the component level.

• Recycle : It is a process to change (waste) materials into new products to prevent waste of potentially useful materials, reduce the consumption of fresh raw materials.

• Disposal : It is the action or process of getting rid of waste or the product.

• Diagram of the cycles is typical for a single organization. A chain of these figures can be developed that show the relationship among a number of organization. Moreover, feedback arrows shown in the figure may represent a no. of organizations that are involved in reverse logistics process.

Organizational Performance Requirements

• To complete the decision framework specific organizational performance requirements are included.

• The alternative that is selected should not only best support the green supply chain, but also make business sense.

• The categorization of elements for organizational performance requires : cost, quality, time & flexibility.

• Characteristics of organizational performance is that they are not static. They tends to change over time and will be greatly influenced by the product life cycle.

• In the introduction phases, flexibility & time may be more important than cost. Whereas cost efficiencies tend to gain important in more mature environments. These dynamical characteristics are incorporated into decision framework

Green Supply Chain Alternatives

• The alternative may include technological, process, or organizational characteristics. Ex- Organizational goal to improve the TQEM (Total Quality Environmental Management), Acceptance of ISO 14000 over ISO 9000 by suppliers and customers, Introduction of information systems such as electronic data interchange which may justified for other reasons, but can evaluated from a greening perceptive.

• A good discussion of various systems, requirement and alternatives than can aid the development of green supply chain can be found.

The Decision Making Framework

• It is represented by an “organization network hierarchy”, which is varies from a standard decision structure as defined by standard analytical hierarchy process.

• The variation occurs primarily because 2 way & ‘looped’ relationships are allowed among the various levels. These levels may also be defined as clusters. These relationships represent multiple dependencies & independencies among the elements within the clusters.

Figure 2 : High level graphical representation of clusters s and influence relationships for decision framework for managing and improving the green supply chain

Organization Performance

Criteria

System Alternatives for Green Supply Chain

Product Life Cycle Stages

Operational Life Cycle / Logistics

Focus

Environment Influential Organization Practices

Improved Green Supply Chain Operations

• Figure 2 shows a “high level” description of the analytical hierarchy network, which does not detail the components within each clusters.

• The objective or goal of the organization, which appears on the right side of figure 2, is to develop improved green chain.

• The relationships may vary due to assumptions made by the decision-makers, and level of complexity they wish to model.

• The arrows represent the relationships among the clusters.

• Another set of relationships exists between the organization performance measures and the operational life cycle elements. The relative importance of different performance measures may be allowed to vary among the operational life cycle elements.

• Within the network, the relative impact (importance) of each alternative will be evaluated for both the performance measures and the environmental practices.

• There is a two-way dependency between the operational and product life cycles.

• The relative importance of each operational life cycle element will be dependent on what stage of the product life cycle is being considered. Moreover, the importance of each product life cycle with respect to a given operational element will also be determined (e.g. the early stages of the product life cycle will have more of an influence on the procurement operations than the decline stages).

• The various environmental practices may also play distinct roles within the operational life cycle.

• The effect would be give a relatively larger importance valuation on reduction than reuse for the production element.

• For the packing portion, the reuse capability may be more important than disposal.

Evaluating the Analytical Network hierarchy

Figure 3 : graphical representation f relationships for the green supply chain evaluation

framework.

• The evaluation methodology will composed of two phases.

1. The first phase will focus on the development of pairwise comparisons for each of the dependency relationships to determine their relative importance weights which will be used as an input to the systems-with-feedback supermatrix to help determine the network influences from among the various relationship represented in figure 2 & 3.

2. The supermatrix evaluation, the second phase, will encompass 3 steps, the formation of the supermatrix, the normalization of the supermatrix (making it “column stochastic”) and convergence to a solution.

• The converged supermatrix will provide us with the relative priorities for each of the alternatives considered within the decision framework

Pairwise Comparison Evaluations

• The fundamental decision makers inputs required for the ANP technique are the pairwise comparisons of each elements within each cluster, from which pairwise comparison matrices are formed.

• A pairwise comparison matrix is required when the relative importance of lower level elements are to be determined for their ‘controlling’ element.

• To determine the relative importance of the operational life cycle elements (the lower level elements) to the introduction phase of the product life cycle elements (the controlling element) a no. of pairwise comparison questions will be asked of the decision-maker.

• A pairwise comparison matrix can show the relative importances of the operational life cycle elements within the introductory phase of a product life cycle.

• The valuation scales used are those recommended by Saaty, where 1 is equal importance, 5 is strong importance, 7 is very strong or demonstrated importance, & 9 is extreme important. Even numbered values will fall in between importance level. Reciprocal values means less importance , strongly less importance, etc.

• Once all pairwise comparisons are complete, the relative importance weight for each component is determined.

• A is pairwise comparison matrix, weights can be determined by expression (1).

Aw = λmax w (1)

where λmax is the largest eigenvalue of A and w is the relative importance weights or priority vector (actually the eigenvectors for the principal eigenvalue λmax).

Table 1 Pairwise comparison matrix for operational life cycle elements relative importances during introduction phase of the product life cycle

Introduction Phase

Procurement Production Distribution Reverse Logistics

Packing Importance weights

Procurement 1.000 6.000 3.000 8.000 2.000 0.448

Production 0.167 1.000 0.500 2.000 0.200 0.073

Distribution 0.333 2.000 1.000 4.000 0.500 0.151

Reverse Logistics

0.125 0.500 0.250 1.000 0.167 0.043

Packing 0.500 5.000 2.000 6.000 1.000 0.285

• The consistency index for a pairwise comparison matrix is determined by:

C.I. = λmax –n / (n-1) (2)

where n is the number of components that are evaluated in the pairwise comparison matrix.

• The C.R. is calculated by taking the C.I. and dividing by a random inconsistency (R.I.) value.

• A consistency index (C.I.) and consistency ratio (C.R.) also need to be calculated.

• For a pairwise comparison matrix to be consistent, C.R < 0.10. In Table 1 we show the values for λmax, C.I., and C.R. We see that this is a relatively consistent set of weights. The priority vector shows that for organization and industry, procurement , followed by packaging , seem to be the functions that are deemed most important for the early stages of a product’s life cycle.

Supermatrix formation

• The supermatrix (M) is formed from a number of sub matrices that are used to model Figs. 2 and 3 in matrix notation.

• The supermatrix and its general sub matrices are shown in Fig. 4. There will be 9 sub-matrices (A, B, C,D, E, F, G, H and J) that will be formed using the priority vectors. An additional identity sub-matrix (I) is added for the alternatives cluster for computational requirements.

Figure 4 : General sub matrix notation for supermatrix

X GSC PLC OLC PRF ENV ALT

GSC 0 0 0 0 0 0

PLC 0 0 A 0 0 0

OLC B C D 0 0 0

PRF 0 E F 0 0 0

ENV 0 0 G 0 0 0

ALT 0 0 0 H J I

• The formation of sub-matrix C will require the determination of the relative impact of each operational life cycle phase on each of the four product life cycle stages. Four priority vectors will be required to complete C. Already shown one set of priority weights for C this vector begins in the second column and sixth row of the initial supermatrix, which appears in bold lettering in Table 2.

The Solution Procedure

• The supermatrix M is a reducible matrix with a multiple root, as defined by Saaty.

• To solve for the values of the alternatives, Saaty recommends that the values of M be column stochastic. That is, the sums of the columns should be normalized to equal a value of 1.

• One method of making M column stochastic is by determining the relative importances of clusters and multiplying their relevant matrix elements by their relative importance score.

• We just assumed that all clusters were of equal importance. Two adjustments will need to be completed for the supermatrix to be translated into a column stochastic matrix.

• The first adjustment influences the operational life cycle and performance measure clusters and their impact on the product life cycle elements. Since there are two clusters, each representative sub matrix, in this case sub matrices C and E, are multiplied by 0.5.

• The second adjustment will be for the four clusters that influence the operational life cycle represented by sub matrices A, D, F and G. Assuming, once again, that each cluster equally impacts the operational life cycle, we multiply sub matrices A, D, F and G, by 0.25.

• The adjusted column stochastic supermatrix (Ms) is shown in Table 3.

• The final step in the process is to obtain a priority ranking for each of the alternatives.

• To determine this ranking by calculating the influence of each of the alternatives on the objective of improving the green supply chain.

• Saaty states that a simple hierarchy and the additive solution approach is appropriate if strong dependencies among the criteria do not exist.

• Schenkerman has shown that the supermatrix approach is capable of reducing the occurrence of rank reversal, thus providing more accurate portrayals of decision-maker preferences.

• Saaty recommends a simple solution technique to solve this problem by raising the supermatrix Ms to a large power until convergence occurs.

• There is need to raise the supermatrix to a power of 16 (M16s ) before convergence occurred within the fourth decimal place (i.e. 104). The converged supermatrix is shown in Table 4. The relative influences of the alternatives on the objective of improving the environmental performance of the supply chain are shown in the “Goal” column.

Discussion

• The ANP approach, in practical application, requires significant decision maker input. Its application needs to be targeted to those

areas where strategic decision making is required.

• Its use should be limited, especially if its use in the decision making process costs more than the outcome of the decision.

• For the case of greening the supply chain, the decision is strategic and will broadly effect the operations of not just one, but many organizations.

• The investment in making a decision that would profoundly effect the operation of the supply chain clearly requires intensive and robust managerial analysis.

• One important consideration in the effectiveness and efficiency of the decision framework begins at the modeling stages. The model and the various dependencies will determine the amount of effort required to arrive at a solution. This effort includes input from decision-makers as well as the mathematical approach to solve the problem.

• There are some managerial aides that the supermatrix does provide through its summarized structure. One of these aides is a summary of the various linkages and relationships. This summary allows managers to determine what patterns might exist among the various relationships.

• A management team is able to look at submatrices C and E to see how the priorities of the organization are shifting over a product’s life cycle. The shifting of priorities can be monitored and evaluated by observing this supermatrix. This observation of the managerial significance of the supermatrix has implications for sensitivity analysis.

• An interorganizational application of this decision framework will have to incorporate the perceptions of a number of stakeholders. Not only will there be diverse preferences and perceptions within an organization, but also those of other organizations.

• Alterations to the supermatrix and an addition to the decision framework incorporating a “firm” control hierarchy, where relative organization influences or impact determinations are made can incorporate some of the diversity of opinion or preferences among the organizations.

• The decision framework has only modeled internal influences and relationships. A number of external factors could be introduced into the model.

• The type of environmental forces such as remediation, command and control, or cooperative regulatory policies may also be modeled.

• The models may be formed as control hierarchies or as part of network hierarchies for decision modeling purposes. A control hierarchy has the characteristic of being separate from a network interdependency model, where the results can be aggregated using an additive model.

• A number of other decision factors and criteria can be included in the model, yet the complexity of the decision environment will tend to increase. Increasing complexity, even though more realistic, usually requires additional effort for preference elicitation from decision makers and more complex computations.

• The tradeoffs between amount of decision maker time and ‘realism 'of the model need to be considered.

• The application of the ANP approach should not only be concerned with a ‘final’ solution to the problem, but it also should be applied as a learning tool for decision makers and managers to help understand the various linkages among the various components, clusters, and elements.

Summary

• The issue of organizations incorporating the natural environment into strategic and operational decisions is a reality that they will or have already encountered. The influences of the natural environment organizational decisions will not only effect the organization that makes the decision, but its customers and suppliers, as well.

• Incorporating various elements, functions and activities of supply chain management is one method to incorporate some of the systemic organizational and inter-organizational implications of environmentally influential policies.

• A number of business and environmental factors need to be integrated into this decision. One such decision framework that considers these factors, whose goal is to improve the green supply chain.

• These elements include product life cycle, operational life cycle, performance measures, and environmentally influential organizational policy elements. The goal of the framework is to help evaluate a number of alternatives(projects, partnerships, systems or technologies, etc.)that impact these various factors,

• The decision framework is modeled and solved as an analytical network process (ANP).

• The ANP methodology is a robust multiattribute decision making technique for analyzing the major issues facing green supply chains and environmentally conscious business practices, both of which are strategic in scope.

• The major disadvantage of the ANP approach is the large amount of decision-maker input required, even for rather simple networks.

• The advantage of allowing managers and decision-makers the flexibility to identify and incorporate major interdependencies among many factors and clusters in a “dynamic” fashion, makes this technique a viable alternative to AHP and other multiattribute approaches.

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