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Resources, Conservation and Recycling 55 (2011) 567–579

Contents lists available at ScienceDirect

Resources, Conservation and Recycling

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / r e s c o n r e c

evelopment of key performance measures for the automobile green upply chain

zutah Udoncy Olugu, Kuan Yew Wong ∗, Awaludin Mohamed Shaharoun epartment of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Malaysia

r t i c l e i n f o

rticle history: eceived 30 October 2009 eceived in revised form 12 April 2010 ccepted 4 June 2010

eywords: reen supply chain erformance measurement everse logistics erformance measures

a b s t r a c t

The main purpose of this study was to develop a set of measures for evaluating the performance of the automobile green supply chain. This study reviewed various literatures on green supply chain perfor- mance measurement, environmental management, traditional supply chain performance measurement, and automobile supply chain management. In order to comprehensively and effectively establish the relevant measures, a suitable framework which considered the automobile green supply chain as a two-in-one chain was adopted. This two-in-one chain comprised a forward and backward chain for the automobile industry. Consequently, 10 measures with 49 metrics and 6 measures with 23 metrics were identified and developed for the forward and backward chains, respectively. Sequel to the development of these measures, a survey was conducted using a four-page questionnaire distributed to experts (includ- ing academics and practitioners) to establish their importance and applicability. The findings of this study suggested that the importance and applicability of all the developed measures have been substantiated.

For the forward chain, the most crucial measure was customer perspective while the most applicable one was traditional supply chain cost. The reverse chain measures were topped by management com- mitment in terms of both importance and applicability. This study contributed to the advancement of knowledge by pioneering the development of a set of holistic measures for evaluating the performance of the automobile green supply chain. The study was wrapped up with the proposition of directions for further studies.

. Introduction

Within today’s manufacturing circle, there is a rapid revolution ue to so many reasons, ranging from customer oriented prod- cts, shortening product life cycles, stakeholder requirements, local nd international regulatory compliances, to competitions amongst layers within the industry. For any manufacturing organization o survive these challenges there is a need to devise innovative trategies which can generate a sustainable competitive edge while atisfying all the requirements from stakeholders and regulatory gencies. It is an established observation, that the global ecosys- em is witnessing a rigorous challenge in its economic sub-system s energy capacity and waste disposal capability are approaching heir limits (Solvang et al., 2006). The major source of this imbalance n the ecosystem has been attributed to manufacturing operations,

hus numerous laws and regulations have been put in place to mon- tor these manufacturing operations and their ensuing products.

anufacturing operations have a major contribution to environ-

∗ Corresponding author. Tel.: +60 7 5534691; fax: +60 7 5566159. E-mail addresses: [email protected], [email protected]

K.Y. Wong).

921-3449/$ – see front matter © 2010 Elsevier B.V. All rights reserved. oi:10.1016/j.resconrec.2010.06.003

© 2010 Elsevier B.V. All rights reserved.

mental degradation at various stages in the product life cycle, from resource extraction to manufacturing, use, reuse, recycling and disposal. It is therefore eminent for manufacturers to imbibe the philosophy of environmental responsible manufacturing. This can be adopted as a strategy to achieve competitive edge and increase market share through the process of improving the overall environ- mental impacts of products (van Hoek, 1999; Zhu and Sarkis, 2006). Recently, the focus on environmental management has shifted from operations internal to the manufacturing companies or facilities to the entire supply chain. Extending this practice along the entire echelons within the supply chain involved in the production of a product, will unarguably yield the greatest value in terms of effi- ciency and effectiveness. Chung and Wee (2008) supported this by stating that product design and manufacture significantly influ- ences the cost of disassembly, inspection, repair, remanufacturing and recycling. Handfield and Nichols (1999) have made a similar observation regarding the cost associated with the supply chain. They believed that optimization involving all parties within the chain can yield the lowest cost minimization.

With the advent of environmental concerns, supply chain man- agement has been redefined making it more complicated. Different legislations and regulations in most developed countries such as the European community (EC, 2000; US-AEP, 1999) have made

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he manufacturers accountable for their products, throughout their ntire useful life and beyond. This has resulted in the extension f the traditional supply chain to include the after-use phase of he products. This after-use phase cannot achieve its objectives in solation, thus there is a need to develop an integrated approach or planning and controlling the features and manners in which

aterials flow within the supply chain. This integrated approach is mbedded into green supply chain management. Beamon (1999b) nd Linton et al. (2007) craved for a redefinition in supply chain anagement to incorporate the new environmental challenges hich are faced in manufacturing and production operations. It as further pointed out that a major stride towards achieving this t would be to define a new structure for the entire supply chain by

ncorporating environmental concerns. Supply chain performance easurement has been identified as a major stride towards an

ffective and efficient supply chain management (Liang et al., 2006). ond (1999) stated that performance measurement will indicate hether a company should continue with its current strategy or ake adjustments. Many automobile organizations have failed in

upply chain management due to their inability to develop the per- ormance measures and metrics required for complete supply chain ntegration and performance measurement (Mentzer et al., 2007). hus, there is a need to establish suitable measures for effective reen supply chain performance measurement in the automotive ndustry.

This paper begins with a description on green supply chain anagement and its performance measurement in general. It goes

head to describe a suitable framework to measure the green sup- ly chain performance in the automotive industry. On that note, a et of measures for performance measurement in this industry is stablished. These measures are justified through a survey using uestionnaires and the results are discussed. The paper ends with onclusions and recommendations on the directions for further tudies.

. Conceptual background

In this section, previous literature upon which the concept of erformance measurement for a green supply chain is anchored pon is reviewed. This involves the use of existing literature in the eld of supply chain performance measurement to justify the need

or green supply chain performance measurement. Many researchers have defined a green supply chain in various

anners using different terms. Some studies defined it as a closed oop supply chain (van Hoek, 1999; Beamon, 1999b; Steven, 2004; nderfurth, 2004; Spengler et al., 2004; Zhu and Sarkis, 2006). It as been described as a sustainable supply chain by Linton et al. 2007) and Beamon (2005). Some have called it as an environ-

ental supply chain (Hall, 2000; Beamon, 2005), ethical supply hain (Roberts, 2003; Beamon, 2005), and integrated supply chain Preuss, 2001; Mezher and Ajam, 2006; Vachon and Klassen, 2006; hu and Sarkis, 2006). It was also termed as a socially responsible upply chain (Salam, 2009) and the list can continue. Irrespec- ive of the nomenclature adopted, the bottom line remains the ame, i.e. “environment”. Green supply chain management is thus efined as the totality of green purchasing, green manufacturing nd material management, green distribution and marketing, and nally reverse logistics (Hervani et al., 2005; Linton et al., 2007; hu and Sarkis, 2006). This is in line with the explanation given y Vachon and Klassen (2008) that suppliers, manufacturers and ustomers should work together towards the reduction of envi-

onmental impact from production processes and products. The chematic of the material flow and the echelons involved in a green upply chain is presented in Fig. 1. Reverse logistics is highlighted s making the forward supply chain becomes a closed loop which

Fig. 1. Green supply chain.

takes into consideration the reuse, remanufacturing, and recycling of materials into new materials or other products (Tsoulfas and Pappis, 2008). Beamon (1999b) went ahead to state that a green supply chain has a bi-objective structure which is the economi- cal double-objective involving cost reduction and manufacturing waste reduction. It is an established fact that many manufacturing organizations have resorted to supply chain management for the enhancement of their core competitiveness (Gunasekaran et al., 2004). With the advent of green supply chain management, oth- ers have seen it as an avenue to boost their competitiveness and comply with environmental requirements of various regulatory bodies (Hervani et al., 2005; Rao, 2002). There are a lot of reasons to measure the performance of a supply chain since it involves pro- cesses beyond organizational boundaries (Lai et al., 2002). Sabri and Beamon (2000) stated that following the nature of the chain, any factor which affects any particular element in the chain will be extended to the rest of the chain. Thus, in green supply chain man- agement, the internal (midstream) processes have to be assessed, coupled with the external (upstream and downstream) processes. The midstream involves operations which are internal to the man- ufacturing companies, while the upstream involves the suppliers and the downstream involves the distributors and customers. Bond (1999) posited that performance measurement has the benefits of stabilizing the green supply chain management process and identi- fying areas for further improvement within the system. Olugu and Wong (2009) expatiated that measuring the performance of a green supply chain will also reveal whether there is a need for an organi- zation to continue with its current strategy (maintaining the status quo) or to adopt a re-engineering of its strategy.

Liang et al. (2006) highlighted that for an effective green sup- ply chain management, evaluating the overall performance of the entire chain is crucial. Neely et al. (2005) defined performance measures as metrics used in quantifying the efficiency and/or effec- tiveness of a particular action. Wong and Wong (2008) stated that performance indicators or measures must be defined to monitor the effort of organizations in achieving sustainable development at all levels. Since greening cannot be achieved overnight, performance measures will reveal at any point the extent to which an organiza- tion has invested in its environmental supply chain initiative.

3. A framework for green supply chain performance measurement (GSCPM) in the automotive industry

Greening the automotive supply chain has become a major source of concern in many parts of the globe, thus measuring its performance is an important issue as the available landfills are fast running out. When compared to other supply chains, the automo- tive supply chain is also a very unusual and complex one. The first reason is because vehicles are complex with numerous components and parts outsourced from various suppliers from different geo- graphical locations, at varying costs and complexities, thus using the regular supply chain does not fit in well for these products (Vonderembse et al., 2006; Olugu and Wong, 2009). The varying

parts have made the automotive supply chain a bit more cumber- some than the ordinary one, thus measuring the performance of such a chain is quite demanding. Secondly, as green supply chain involves a from-birth-to-death approach, most products can easily

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e consumed once they get to the end user. This makes the consid- ration on their entire life including the reverse logistics an easy rocess. In the case of the automotive industry, this is quite differ- nt since vehicles have a useful life of at least 5 years under normal ircumstances.

The primary objective of the automotive supply chain involves aking sure that vehicles get to the end user at the right quan-

ity, under good conditions at the right time (Wong and Wong, 007). On the other hand, closing the loop involves making sure hat the end-of-life vehicles (ELVs) are recycled efficiently and ffectively, and reabsorbed back into the manufacturing process. eamon (1999b) supported this by stating that greening the supply hain involves consideration of the total immediate and even- ual environmental effects of all products and processes. In the ight of this two varying objectives for the automotive closed loop upply chain, a framework for measuring its performance as a two- n-one chain is necessary. This is supported further by Beamon 1999b)’s assertions that extending the supply chain to include ecovery operations, such as remanufacturing, recycling, and re- se adds an additional level of complexity to its design, and a new et of potential operational and strategic considerations. This also as an effect on how the performance of a green supply chain hould be addressed. The proposed framework is presented in ig. 2.

Thus, the first chain will be concerned with the forward flow of ehicles which should terminate at the customer while the sec- nd one (backward chain) will begin after the useful life of the ehicle and ends when the product has been efficiently absorbed ack into the chain. Beamon (1999b) further highlighted that the omplexity in green supply chain management stems from two ajor sources which are uncertainties associated with the replace- ent/recovery process (on-time requirements, and quality and

uantity of returned products), and the reverse distribution process tself which involves collection and transportation of used prod- cts. By adopting the proposed framework, the complexities will e considerably minimized. This is in line with the assertion by lugu et al. (2009a), that a framework for supply chain performance easurement should be designed in a way that would reduce its

omplexity. In this way, the forward chain will be aimed at making ure that vehicles get to the customers at the right time while satis- ying the stakeholders’ and regulatory bodies’ needs. The backward hain will be responsible for making sure that the end-of-life vehi- les are reprocessed to reduce waste to the minimum possible level. he explanation is supported by the definition given by Handfield nd Nichols (1999), that green supply chain management should ddress three interrelated task areas, i.e. upstream, internal-stream nd downstream of the organization. The upstream of the organiza- ion’s supply chain involves the inclusion of environmental criteria n the evaluation and selection of suppliers and in the specifications f components. The internal-stream will be concerned with oper- tions within the manufacturing company itself. The downstream f the organization’s supply chain is charged with the responsibil- ty for disposal and sale of excess stock, including opportunities for ecovery and recycling of materials (Handfield and Nichols, 1999).

.1. The forward chain

This chain will involve all the processes aimed at making sure hat the product is green enough and satisfies the customers’ needs. hus, the performance measurement of this chain involves quanti- ying how green the processes of making the vehicles and delivering hem to the end users while satisfying the customers’ needs for on-

ime delivery of the right product at the right quantity. Therefore, he performance measurement shall involve assessing all the ech- lons and their contribution towards making sure that the product s green while satisfying key customer value.

and Recycling 55 (2011) 567–579 569

3.2. The backward chain

This chain begins with the customers, and flows to the collec- tion centers, then to the recycling centers where shredders, dryers, sorters and the actual recycling plants are located. From there, the materials which are the recycled materials go back to the supplier, who then makes them available to the manufacturer. The other sce- nario will involve the manufacturer collecting the material directly from the recycling center and integrating it into the manufacturing operation. The essence of the reverse chain performance measure- ment is to assess the effectiveness of returning end-of-life vehicles and the efficiency of ensuing recycling processes and finally, the smoothness with which the recycled materials are integrated back into the main manufacturing stream.

4. Key performance measures and metrics for GSCPM in the automotive industry

Based on the proposed framework and the information consol- idated from the literature, key performance measures and metrics for green supply chain performance measurement in the automo- tive industry are then developed. The measures and metrics are grouped under the context of the forward and backward chain.

4.1. Forward chain measures

These are the measures used in the evaluation of the forward chain operations. This consists of the evaluation of upstream supply chain operations involving the suppliers, the midstream operations which are processes within the manufacturing company itself, and the downstream operations involving the customers.

4.1.1. Upstream measures These are measures which are aimed at assessing the suppliers’

performance. Since the automotive industry involves mostly out- sourced components or parts, the effectiveness of this aspect of the chain will be looked at by the following measures and metrics.

4.1.1.1. Supplier commitment. This is the extent to which suppli- ers are devoted to the greening exercise. This is considered to be a very vital measure as most of the automobile components are outsourced. Zhu et al. (2007), van Hoek (1999), Rao (2002) and Rao and Holt (2005) all pointed out that this measure is a very crucial one. Under this measure, there are some developed metrics that will enable its assessment. These metrics are discussed hereunder.

4.1.1.1.1. Level of supplier environmental certification. This is the extent to which the selected suppliers of automobile compo- nents have been formally recognized as a committed practitioner of green sourcing and supplying. This can be judged by the number of environmental certifications acquired over the years.

4.1.1.1.2. Level of supplier performance on sustainability. The overall efforts of the suppliers have to be assessed from time to time to evaluate their commitment in greening. The sustainabil- ity of their greening initiatives is assessed here. This can be done periodically to reassure their devotion on the greening exercise.

4.1.1.1.3. Number of supplier initiatives on environmental man- agement. This involves all the initiatives the suppliers have put in place to enhance their green status. They can be in the form of motivation programs for their workers, agents, etc.

4.1.1.1.4. Level of disclosure of environmental initiative to the pub- lic. This involves the extent to which the suppliers declare their

green intentions openly. When they declare their commitment openly, it is easy for people to be assured of their responsibility.

4.1.1.1.5. Level of supplier preprocessing of raw materials. This is a measure of the extent to which the suppliers process their

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upplied components in order to minimize or eliminate anti- nvironmental components.

.1.2. Midstream measures These are measures which are used in assessing the internal

perations of the company towards achieving and maintaining n environmentally sound supply chain. Under this category are he greening cost, level of process management, product charac- eristics, management commitment, traditional supply chain cost, esponsiveness, quality, and flexibility.

.1.2.1. Greening cost. This is the overall cost incurred by the ompany in making sure that its operations are environmen- ally sustainable. It has been considered as important by Beamon 1999b), Hervani et al. (2005), Tsoulfas and Pappis (2008) and Zhu t al. (2007). Klassen and Whybark (1999) have demonstrated that he investment pattern of an organization has a huge impact on nvironmental performance. Based on its level of consideration nd significance, greening cost is one of the major measures for n efficient green supply chain management. The metrics under his measure are as discussed in the ensuing paragraphs.

4.1.2.1.1. Cost associated with environmental compliance. This s very vital in assessing the greening cost. This involves all capital nvested by a company in trying to meet up with all the environ-

ental requirements. It is believed that environmental compliance nvolves a series of expenditures. Thus, the more a company spends n trying to achieve compliance, the more likely it will yield an ffective green supply chain.

bined framework.

4.1.2.1.2. Cost associated with energy consumption. Under this cost, the energy which the company consumes in its manufactur- ing operation is considered. Specifically, it includes the energy cost of the plant and machineries, and that spent on other functional aspects of the organization. For a green company, the level of con- sumption should be comparatively low.

4.1.2.1.3. Cost associated with environmentally friendly materi- als. This involves the totality of capital invested by an organization towards the acquisition of environmentally compliant raw mate- rials. It is a known fact that in order to acquire environmentally friendly raw materials, a company will have to spend additional capital on the suppliers. Higher capital invested in this regard will yield greater motivation to the suppliers and thus will boost the greening effort.

4.1.2.1.4. Green cost per revenue. This item means the capital which the organization sets apart from all its revenue solely for the implementation of green supply chain management.

4.1.2.2. Level of process management. This means the extent an organization has gone in optimizing and modifying its processes to enhance the reduction of environmental impact. This is very impor- tant as it reduces significantly the immediate and eventual effects of the products. To buttress the importance of this measure, many researchers have recognized its essentiality, thus its consideration (Mclntyre et al., 1998; Beamon, 1999b; van Hoek, 1999; Rao, 2002;

Rao and Holt, 2005; Hervani et al., 2005; Tsoulfas and Pappis, 2008). The metrics under this measure are as follows.

4.1.2.2.1. Availability of process optimization for waste reduction. This item considers whether the company has any structure in place

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o enhance the reduction of waste generated during manufacturing. he definition of waste here involves both solid and liquid waste.

4.1.2.2.2. Level of spillage, leakage and pollution control. When- ver environmental effects associated with manufacturing are alked about, the first thing that comes to mind is emission. Under his metric, the level of emission, spillage and leakage control is onsidered.

4.1.2.2.3. Level of waste generated during production. This is the uantity of waste generated through manufacturing operations ithin an organization. It is believed that if the process is green

nough, the level of waste generated should be considerably mini- al. 4.1.2.2.4. Quantity of utility used. This takes into account the

uantity of water, electricity, and gas that is employed in the com- any over a given period of time. This is a very important metric as

t shows that the ecosystem should be tapped with caution. 4.1.2.2.5. Number of violations of environmental regulations.

his is the bottom line of the metrics for process management. It imply shows whether an organization is really living up to expec- ation in its bid to maintaining an environmentally sound process. ince many regulatory bodies are in place to monitor this, it is very asy to notice when an organization violates any given area.

.1.2.3. Product characteristics. This is the most glaring measure s it involves the features and components of the automobile. any studies have acknowledged its importance by relating to it

n one form or another. This is evident in studies done by Mclntyre t al. (1998), Beamon (1999b), van Hoek (1999) and Rao (2002). ther researchers that took product features into consideration re Hervani et al. (2005), Rao and Holt (2005), Zhu et al. (2007), nd Tsoulfas and Pappis (2008). Under this measure, the metrics onsidered are as follows.

4.1.2.3.1. Level of recycled material in products. This measures he extent to which the company integrates recycled materials back nto its main stream manufacturing process. This is a major step in ncouraging reverse logistics by becoming a major customer of its wn recycled materials.

4.1.2.3.2. Level of product to be disposed to landfill or incinerated. his looks at the percentage of the vehicle that is not recyclable, hus destined to the landfills or incinerators. If a company is fol- owing the standard practice enshrined by the European Union for he automotive industry (EC, 2000), the expected quantity should e less than 15% of the entire car and it is expected to be less than % by 2015 (Cruz-Rivera and Ertel, 2009).

4.1.2.3.3. Availability of eco-labelling. Eco-label is a labelling ystem for consumer products that are made in a fashion that avoids etrimental effects on the environment. This has been identified s a way of showcasing the environmental compliance of a given roduct, making it an obvious sight for a green conscious customer.

4.1.2.3.4. Level of biodegradable content in products. This mea- ures the quantity of materials in the vehicle which is capable of eing decomposed by biological agents such as bacteria and other iodegradable detergents. Biodegradable materials will eventually eturn to the mother earth after they have been disposed. They o not pose much threat to the environment. Inclusion of such aterials in the vehicle components contributes to the greening

rive. 4.1.2.3.5. Level of usage of design-for-assembly in products.

esign-for-assembly involves designing with ease of assembly in ind. This has been expanded to include design-for-disassembly.

f products contain fewer parts or are provided with features which ake it easier to grasp, move, orient and insert them, it will take less

ime to assemble and disassemble, thereby reducing assembly or isassembly costs. These will in-turn enhance recycling processes.

4.1.2.3.6. Level of market share controlled by green products. his is a measure of the proportion of industry sales of a green

and Recycling 55 (2011) 567–579 571

vehicle. It is believed that this will have a great impact on assessing the success of a green product.

4.1.2.4. Management commitment. This measures the overall effort and initiatives employed by the management of an organization in combating anti-environmental practices within its supply chain. This is considered to be the most important, because unless the top management has decided to implement green supply chain man- agement as a strategy, it cannot succeed. Managers are the ones responsible for making decisions related to supplier selection and manufacturing operations (Rao and Holt, 2005; Zhu et al., 2007). To establish the level of importance of management commitment, almost all the reviewed studies in the area of green supply chain performance measurement have emphasized it (Beamon, 1999b; Hervani et al., 2005; Tsoulfas and Pappis, 2008; Rao, 2002; van Hoek, 1999). Under this measure are the following metrics.

4.1.2.4.1. Level of management effort to motivate employees. It is a popular adage that ‘charity begins at home’. So this metric measures the top management’s effort in motivating its employ- ees towards green supply chain management. Since the employees are directly in-charge of implementing the strategy, it is necessary to motivate them towards its success.

4.1.2.4.2. Availability of environmental evaluation schemes. If an organization is to succeed in greening its internal operation, there is a need to put an appraisal system in place that will be charged with the responsibility of measuring how well the different departments within the organization are implementing the practice.

4.1.2.4.3. Availability of environmental auditing systems. This metric evaluates the availability of such internal environmental regulating systems. This ensures that the right attitudes and actions are being implemented towards greening the internal processes within the organization.

4.1.2.4.4. Availability of mission statement on sustainability. A mission statement is a document which is intended to serve as a summary of the business goals and values of an organization. If companies include greening in their mission statement, it implies they are really serious about it. Availability of such a document is a measure of greening commitment.

4.1.2.4.5. Number of environmental management initiatives. This is a measure of the level to which the companies have devised several programs aimed at encouraging green supply chain man- agement within and outside their immediate organization.

4.1.2.4.6. Level of management effort to enlighten consumers on sustainability. This metric measures the level to which the man- agement is enlightening the customer with information about greening effect. Since information is power, its dissemination by the management will result in more confidence and conviction gained by the customer.

4.1.2.4.7. Availability of environmental reward systems. This measures the availability of an incentive package or any form of compensation created to encourage individuals, departments or suppliers to practice green supply chain management.

4.1.2.4.8. Level of management effort to motivate suppliers. Under this metric, the level of encouragement given to the sup- pliers by the management of an organization aimed at boosting their greening strives is assessed. It can be in the form of training, financial assistance, etc.

4.1.2.5. Traditional supply chain cost. This is the regular cost incurred by the supply chain as a result of the normal opera- tions in the chain. This cost has been identified as an important measure of the supply chain performance for a long time

(Gunasekaran et al., 2001; Beamon, 1999a; Schonsleben, 2004; Stephens, 2001; Morgan, 2004; Bhagwat and Sharma, 2007). It is believed that by greening the supply chain, the traditional supply chain cost will be influenced in one way or another.

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he aspects of cost identified are listed in the ensuing para- raphs.

4.1.2.5.1. Percentage decrease in total supply chain cost (tangi- le and intangible cost). This is the total cost incurred in running he entire supply chain by an organization. It takes into account ll costs accruable in making sure that goods get to the end users. unasekaran et al. (2001) included cost of operation per hour. Chan

2003) included total overhead cost, tangible cost and incentive ost. Beamon (1999a) included total cost of resources and manufac- uring. It was described to cover returns processing cost and total upply chain cost (Stephens, 2001). Bhagwat and Sharma (2007) alled it supply chain finance, logistic cost and cost associated with ssets.

4.1.2.5.2. Percentage decrease in delivery cost. It is believed that he cost of delivery will be reduced under a sound green sup- ly chain management. Chan (2003) highlighted this to be a very

mportant metric. Schonsleben (2004) expressed it as cost of fin- shed goods in transit. The change in delivery cost should be a metric o assess the overall traditional supply chain cost.

4.1.2.5.3. Percentage decrease in inventory cost. This is the cost ssociated with inventory storage within the company over a eriod of time. Morgan (2004) called it inventory carrying cost. tephens (2001) expressed this as cost of inventory for supplies, hile it was called inventory utilization and warehousing cost

y Chan and Qi (2003). Beamon (1999a) considered it as inven- ory obsolesce and inventory investment cost. Schonsleben (2004) alled it inventory turnover cost and Bhagwat and Sharma (2007) alled it total inventory cost. It is believed that inventory cost will educe as a result of green supply chain management.

4.1.2.5.4. Percentage decrease in information sharing cost. Infor- ation sharing cost includes all the costs associated with

nformation processing for a smooth operation of the supply hain. Gunasekaran et al. (2001) and Bhagwat and Sharma (2007) eferred to it as information carrying cost, while Stewart (1995) nd Gunasekaran et al. (2004) expressed it as information process- ng cost. A decrease in information sharing cost is expected within he supply chain as a result of the greening initiatives. This is due o the fact that all parties share common goals.

4.1.2.5.5. Percentage decrease in ordering cost. This is the cost ssociated with orders placed on raw materials. Gunasekaran et l. (2001) included economic order quantity and effectiveness of roduction schedule as elements in ordering cost. Beamon (1999a)

ooked at it as the number of back orders and stock out proba- ilities. Morgan (2004) looked at it as order processing cost. It is elieved that a good supply chain practice such as green supply hain management should reduce the ordering cost.

.1.2.6. Responsiveness. This is a measure of the rate at which he supply chain responds to certain elements such as order ead time, product development cycle time, manufacturing lead ime, total supply chain cycle time and on-time delivery. Some esearchers who recognized this as a key performance measure nclude Gunasekaran et al. (2001) and Beamon (1999a). It is elieved that responsiveness will be affected by the greening ini- iative and thus, a measure of the effect is necessary. The metrics o be considered are as follows.

4.1.2.6.1. Percentage decrease in order lead time. This is the time lapsed between the ordering of raw materials and components, nd when they are received. Gunasekaran et al. (2001) included upplier lead time and purchase order cycle time. Beamon (1999a) xpressed this as the average lateness and average earliness of rders. Stephens (2001) discussed this as order fulfillment lead

ime. Another researcher who considered this is Chan (2003).

4.1.2.6.2. Percentage decrease in product development cycle time. his is the time taken from the conception of ideas till the com- letion of the design. Researchers such as Chan (2003) considered

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it as the duration to produce a new product mix and the percent- age decrease in the time to produce a new product. Gunasekaran et al. (2001), and Bhagwat and Sharma (2007) considered it under product development cycle time.

4.1.2.6.3. Percentage decrease in manufacturing lead time. This measures the delay from the moment the order is ready for man- ufacturing until its completion. Some studies have identified it as very crucial as is evident in Beamon (1999a) and Stephens (2001).

4.1.2.6.4. Percentage decrease in total supply chain cycle time. This is the total time elapsed between the ordering of raw materials and components from the suppliers until when the finished prod- ucts reach the end users. Researchers such as Schonsleben (2004), Gunasekaran et al. (2001) and Beamon (1999a) identified it as a very crucial metric. Schonsleben (2004) and Morgan (2004) dis- cussed this as total supply chain response time. These show the level of importance attached to this metric.

4.1.2.6.5. Percentage increase in on-time delivery. This mea- sures the tardiness in the delivery of finished products. Tra- ditionally, some researchers looked at it as delivery lead time (Gunasekaran et al., 2001; Chan, 2003; Beamon, 1999a; Stephens, 2001). The emphasis on this has been established based on the level of attention it has received.

4.1.2.7. Quality. This is a distinguishing attribute as it measures the standard of the product. It has been considered by so many researchers as having a very big impact on supply chain perfor- mance. The majority of researchers have included it in their studies such as Artz (1999), Gunasekaran et al. (2001), Beamon (1999a), Stephens (2001), Hieber (2002), Chan and Qi (2003), Chan (2003), Graham et al. (1994), Bhagwat and Sharma (2007), Morgan (2004), and Windischer and Grote (2003). Metrics under this measure are discussed here under.

4.1.2.7.1. Percentage decrease in customer dissatisfaction. This involves dissatisfaction of the customer from product use, etc. Beamon (1999a) and Morgan (2004) identified this as customer complaint level, while Gunasekaran et al. (2001) and Chan (2003) considered it as customer satisfaction. It was also discussed as ser- vice level against competitors’ and customer perception of service (Bhagwat and Sharma, 2007). This is considered as a very vital metric since customer satisfaction is the most valuable asset an organization can have.

4.1.2.7.2. Percentage decrease in delivery unreliability. This refers to the level of dissatisfaction arising from unsatisfactory delivery of products. It is believed that a high quality should be reflected in the reduced number of complaints with regard to unre- liable delivery.

4.1.2.7.3. Percentage decrease in scrap and rework. This is the number of products that is reworked due to certain reasons as well as those which cannot be reworked which are classified as scraps. Chan (2003) termed this as the proportion of wrong products man- ufactured. Morgan (2004) called it damaged product. It is believed that a reduced level of scrap and rework depicts a high level of quality in manufacturing processes.

4.1.2.7.4. Availability of green product warranty. This is the level to which green products are guaranteed against any form of fail- ure. Morgan (2004) called this damage claim level. A warranty will instill confidence in the customers on the purchase and use of green products.

4.1.2.8. Flexibility. This implies that the chain has the ability for adjustment to suit the various scenarios that might arise due

to changes in the normal supply chain processes. The impor- tance of flexibility is evident in the studies which considered it as a measure, such as Chan (2003), Beamon (1999a), Gunasekaran et al. (2004), Gunasekaran et al. (2001), Stephens (2001) and

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chonsleben (2004). Particularly, the changes that are inflicted on he various metrics due to the greening process are considered.

4.1.2.8.1. Percentage increase in demand flexibility. This is the evel to which the orders can be changed due to customers’ emands (Morgan, 2004). The supply chain should be able to ccommodate changes in customers’ orders without much effect on he system. Bhagwat and Sharma (2007) termed it as effectiveness f scheduling.

4.1.2.8.2. Percentage increase in delivery flexibility. This is the bility of the system to accommodate changes in delivery time nd method, etc. Gunasekaran et al. (2001), Bhagwat and Sharma 2007), and Chan and Qi (2003) called it as ability to respond to rgent deliveries, while Beamon (1999a) termed it as delivery flex-

bility. 4.1.2.8.3. Percentage increase in production flexibility. This is

he flexibility of production systems to meet particular customer eeds (Bhagwat and Sharma, 2007; Stephens, 2001). Schonsleben 2004) and Beamon (1999a) called it as volume capacity, while hagwat and Sharma (2007) used the term ‘range of products’.

4.1.2.8.4. Percentage increase in fill rate. This is a measure of ow fast the supply chain is reacting to replenish the delivered tock. It was described as the stock velocity and transportation apacity utility (Morgan, 2004). This is considered very important or the supply chain to cope with demands.

.1.3. Downstream measures These are measures which are used in the downstream of a sup-

ly chain, taking into account the customer point of view. Under he downstream measures, the customer perspective will be con- idered.

.1.3.1. Customer perspective. This involves consideration on the ustomers’ view with respect to the green supply chain and the roduct thereof. Since the aim of every manufacturer is to sell their roducts to the consumers, it is thus considered as the most impor- ant measure in greening a supply chain (Gunasekaran et al., 2004). upply chain performance measurement must be built around the ustomers’ satisfaction (Beamon, 1999a; van Hoek et al., 2001; Zhu t al., 2007). Under customer perspective, some metrics have been dentified as follows.

4.1.3.1.1. Level of customer interest in green products. This nvolves considering the extent to which the customers really care bout the environmental effects of the products they consume. It is elieved that some customers who have been victims of environ- ental degradation would really care about the extent to which it

s considered in the design of a product. Hence, customers’ interest s very vital in the design and production of green products.

4.1.3.1.2. Level of customer satisfaction from green products. nder this metric, the satisfaction derived by the customer from

he green product is measured. Since green products must entail ertain modifications, it is believed that it is worthy to measure the xtent to which the customers are satisfied with these products espite the modifications.

4.1.3.1.3. Level of customer dissemination of green information. ne of the major means of creating awareness about any product

s by word-of-mouth. It is easier for a customer to convince another ustomer based on his/her experience on a given product. On that ote, it is believed that the level of customers’ dissemination of nvironmental information will reflect their overall interest.

.2. Backward (reverse) chain measures

These are the measures that will be used in assessing the perfor- ance of the reverse chain. From the earlier analysis, it was stated

hat these measures should be employed to evaluate the efficiency nd effectiveness of returning the end-of-life vehicles (ELVs) and

Fig. 3. Reverse chain activities.

their subsequent recycling and reintegration into the main man- ufacturing stream. The operations upon which the measures are established for the reverse chain are presented in Fig. 3. It shows that the ELV moves from the customer to the collection center, from which it is sent to a draining center, where the fluid (petrol, engine oil, etc.) in the vehicle is removed. After this draining, the car is sent to the disassembly process where it is reduced to bits and pieces. This process is followed by sorting in which the various parts are classified accordingly. The next operation involves shredding and finally reprocessing. Thus, the measures for this reverse chain are based on these processes.

From the available literature reviewed (Beamon, 1999b; Rao, 2002; van Hoek, 1999; Zhu et al., 2007; Hervani et al., 2005; Tsoulfas and Pappis, 2008; Rao and Holt, 2005; Mclntyre et al., 1998), it was found that every one of them included recycling, but none really went on to explain the elements, even for a general supply chain. In addition, none of the studies had constructed a detailed list of measures for evaluating the backward chain. In this research, the relevant measures and metrics have been developed based on the activities discussed in the previous paragraph.

4.2.1. Upstream measures 4.2.1.1. Customer involvement. This is a measure which is intended to evaluate the overall cooperation and willingness of the cus- tomers in returning the ELVs. It is believed that the customers have to support this exercise for it to succeed. Dyckhoff et al. (2004) stated that in order to bridge the gap in the collection of ELVs, the customers must be considered. Theyel (2006) also supported this fact. Under this measure, the following metrics are considered.

4.2.1.1.1. Level of customer cooperation in returning of ELVs. This measures the willingness of the customers to return their ELVs to a designated collection center. Dyckhoff et al. (2004) considered this as very important. It is believed that a high level of returned vehicles by customers is an indication of their support and cooperation in the greening effort.

4.2.1.1.2. Level of customer-to-customer dissemination of infor- mation. This is the level to which customers are applying the

word-of-mouth concept to encourage their peers and friends in realizing the importance of participating in the reverse chain (Dyckhoff et al., 2004).

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4.2.1.1.3. Level of understanding of green process by customers. his measures the understanding of customers in the greening rocess. Dyckhoff et al. (2004) believed that without this under- tanding the customers will not participate fully in the process. It s only when they understand the rationale behind a process that hey can really support it whole heartedly.

.2.2. Midstream measures

.2.2.1. Recycling cost. This is the cost associated with all the pro- esses involved in recycling the ELVs, ranging from the cost of eturning, draining, disassembling, sorting, shredding, to repro- essing. Inderfurth (2004) considered it as remanufacturing cost. ince cost has already been identified as very vital to supply chain erformance measurement, the cost associated with the reverse hain will no doubt be a very important measure. Under recycling ost, the following metrics are discussed.

4.2.2.1.1. Cost associated with returning of ELVs. This is the otality of money spent in making sure that the ELVs get to the col- ection centers and eventually to the final reprocessing plant. This s believed to be very vital to the efficient collection of the vehicles. yckhoff et al. (2004) pointed out that returning of ELVs is vital for ffective recycling. Thus, the cost incurred is a good metric to assess ts success.

4.2.2.1.2. Cost associated with processing of recyclables. This ncludes the cost of draining, disassembling, shredding and final eprocessing of the ELVs. Schultmann et al. (2004) called this as cost f treatment of ELVs, while Schultmann et al. (2001) considered it s cost of reprocessing activities. All these costs are necessary for ffective reprocessing of the vehicles.

4.2.2.1.3. Cost of sorting and segregation of recyclables. Under his metric, the capital invested for separating different recyclables nto different categories is considered. Spengler et al. (2004) con- idered this as recovery cost. It is believed that effective and fficient sorting will enhance the effectiveness of the recycling pro- ess.

4.2.2.1.4. Cost of disposal for hazardous and unprocessed waste. t the end of the recycling process, there is always a residue. ccording to Dyckhoff et al. (2004) and Cruz-Rivera and Ertel

2009), this waste should constitute about 15% of the ELV and it is xpected to be less than 5% by 2015. Thus, this and other hazardous aste generated should be properly disposed. The cost involved in

his disposal (Dyckhoff et al., 2004) is considered here.

.2.2.2. Material features. This measures the composition and ffect of the materials in the ELVs on the reverse supply chain. ifferent automobiles have different compositions and thus will ffect the entire reverse logistics process. Hesselbach et al. (2007) onsidered this as the recyclability of the materials. This is a major easure of the effectiveness of the reverse chain and the following etrics are developed. 4.2.2.2.1. Level of waste generated. This is the quantity of waste

solid and liquid) that is generated per ELV at the end of the recy- ling process. It is expected that this waste should have a direct elationship with the material composition of the ELV. Dyckhoff t al. (2004) and Cruz-Rivera and Ertel (2009) highlighted that his waste is a very important metric. Therefore, the higher the on-recyclable portion of the automobile, the higher the expected uantity of waste to be generated.

4.2.2.2.2. Ratio of materials recycled to recyclable materials. This s the proportion of the actual recycled materials to the supposed ecyclable materials in the ELV. In other words, this is the ratio of the ctual volume achieved in the recycling process to the theoretical

olume of recyclables. Hesselbach et al. (2007) considered this as he recycling potential of the product.

4.2.2.2.3. Material recovery time. This metric is the total time pent on a given ELV from draining, disassembling, shredding, to

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reprocessing. The lower the time, the more efficient and effective the recycling processes. Fleischer et al. (2007) and Hesselbach et al. (2007) supported this fact. A good material composition of an ELV should enhance the recovery time positively.

4.2.2.3. Management commitment. This is a measure of the totality of the top management’s initiatives aimed at making sure that the recycling is efficiently and effectively carried out. Under this mea- sure, there are several metrics which could be employed. Mezher and Ajam (2006) and Olugu et al. (2009b) considered this as a key success factor for environmental stewardship of a product.

4.2.2.3.1. Level of motivation to customers on ELVs. In most cases the management has introduced a lot of initiatives aimed at moti- vating the customers to return their ELVs. Some of these include a trade-in of the ELV for a new car, while some give a certain level of rebate. Dyckhoff et al. (2004) considered these efforts as customer incentives and they are geared towards motivating the customers.

4.2.2.3.2. Availability of standard operating procedure for the col- lection of ELVs. This is aimed at assessing the management effort in having a defined procedure in place for returning the ELVs and their subsequent reprocessing. Schultmann et al. (2004) and Dyckhoff et al. (2004) described this to be very important. If a structure is in place, obviously it will boost the effectiveness of the entire process.

4.2.2.3.3. Availability of collection centers. It is expected that the management will be responsible for providing a collection center. Dyckhoff et al. (2004) and Helms and Hervani (2006) believed that this will be very necessary for an effective returning of ELVs. The availability and ease of accessibility of collection centers for ELVs will boost the returning process.

4.2.2.3.4. Availability of waste management schemes. This is aimed at evaluating the availability and effectiveness of the waste management scheme for waste generated at the end of the recy- cling process. Since there is always a certain level of waste generated at the end of the recycling process, there should be a proper management and disposal program in place. Dyckhoff et al. (2004), Schultmann et al. (2004) and Hesselbach et al. (2007) supported this as an important metric.

4.2.2.4. Recycling efficiency. This is a measure of the overall effec- tiveness of the recycling processes. A higher recycling efficiency signifies that the processes are supporting green supply chain man- agement. Below are some metrics used in the measurement of the recycling efficiency.

4.2.2.4.1. Percentage decrease in the recycling time. This is the overall reduction in the time taken to completely recycle ELVs (from the time they arrive at collection centers until they have been finally reprocessed). Fleischer et al. (2007) considered it as recycling rate and Schultmann et al. (2004) supported this as an important metric. It is believed that when the workers become more familiar with the system, the process will become faster. This reduction in time shows that there is an improvement in the process.

4.2.2.4.2. Availability of recycling standards. This is aimed at measuring the existence of a standard established for all the recy- cling processes. Without a standard, it will be difficult to know whether the recycling is effective or not. Thus, this is a vital metric. Hesselbach et al. (2007) and Spengler et al. (2004) identified this as very important in assessing the recyclability of any product.

4.2.2.4.3. Availability of standard operating procedures. This metric measures whether there is any standard procedure or methodology to guide the recycling process. Spengler et al. (2004) called this procedure as the product recycling passport or recycling

database. This will save cost arising from waste due to errors or omissions in the recycling processes.

4.2.2.4.4. Percentage decrease in utility usage during recycling. This is a measure of the amount of power consumed, water used,

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as used, etc., during the recycling of a given quantity of ELVs. It s believed that a higher efficiency of the process will lead to a ower usage of utilities. Tsoulfas and Pappis (2008) and Hervani t al. (2005) considered this metric as important.

4.2.2.4.5. Efficiency of shredders and dismantlers. The shredders nd dismantlers are two vital players within the recycling process Schultmann et al., 2004). If they do not carry out their job very effi- iently, the overall time for the recycling process will be increased. n addition, there will be more waste generated during the process.

4.2.2.4.6. Percentage reduction in emission and waste generated. lmer (2007) considered this metric as the amount of pollutant per ommodity. Basically, it looks at the level to which the emission and aste generated has been reduced during each recycling operation.

ince recycling is aimed at waste reduction, the lower the waste and mission generated, the more efficient the recycling process.

.2.3. Downstream measures

.2.3.1. Supplier commitment. This is to assess the initiatives put in lace by the suppliers in making sure that the entire reverse supply hain process is successful. Hamner (2006) supported this to be a ery crucial measure. The metrics employed here are as follows.

4.2.3.1.1. Extent of delivery from suppliers back to manufacturers. nder this metric, the effectiveness of inclusion and integration of

he recycled materials into the main manufacturing stream is eval- ated. If suppliers give their full support to this integration, it will oost the entire process. It is believed that without a commitment rom the suppliers to smoothly integrate the recycled materials into heir supplies, the relevance of the backward chain will be defeated. roufe (2006) and Baumgarten et al. (2007) considered this metric s a key success factor for the selection of suppliers and reverse ogistics.

4.2.3.1.2. Certification system for suppliers in the recycling process. he availability of a system that will certify the effectiveness of the uppliers in reverse logistics is assessed here. It can serve as an udit system to know whether the integration is really taking place. amner (2006) and Sroufe (2006) believed this to be a very crucial etric. 4.2.3.1.3. Number of supplier initiatives in the recycling process.

his is a measure of the number of initiatives put in place by the sup- liers to encourage and promote the effective recycling of the ELVs. his should be evaluated based on the key programs employed by he raw material suppliers aimed at boosting the recycling process. roufe (2006) highlighted this to be an important metric.

. Research methodology

In order to validate the proposed measures, a survey was car- ied out. It should be noted that this was an expert evaluation xercise rather than a full-fledged industrial survey. Based on the ramework which has been discussed earlier in Section 3, a four- age questionnaire was developed for assessing the importance nd applicability level of the measures and metrics. The question- aire comprised three sections. The first part of the questionnaire as aimed to obtain background information about the respon- ents. The second section comprised the measures for the forward hain and their corresponding metrics. The respondents were asked o assign a score to each of the metrics to evaluate their importance nd applicability level in measuring the performance of an auto- otive green supply chain. Importance level implies the degree

f perceived importance placed on the metrics, while applicability eans the extent to which they can be applied or used in practice. A

coring scale from 0 to 5 was applied where 0 = no idea, 1 = very low, = low, 3 = moderate, 4 = high, and 5 = very high. The third section omprised the measures and metrics for the reverse chain. Sim- larly, the respondents were asked to rate each of the metrics to

Fig. 4. The mean importance scores for the forward chain measures.

assess their importance and applicability level using a scale from 0 to 5.

After the development of the questionnaire, it was sent to five experts from the academia and the industry to conduct content validation. This was aimed at making sure that the contents are measuring what they are intended to measure (Malhotra and Birks, 2006; Loewenthal, 2001). The comments and feedbacks from the experts were used to revise the questionnaire. After the revision, the questionnaires were sent back to the same experts and they all showed their satisfaction.

A total of 200 experts from the academia and the industry were then selected as potential respondents to assess the measures and metrics. The selected academics were based on their expertise and contributions in the field of supply chain management and green supply chain management, while experts from the automo- tive industry were included based on their position and number of years of experience in the automobile supply chain. This list com- prises experts from Asia, Oceania, North America, South America, Europe and Africa. The questionnaires were mailed by post where applicable, while some were sent by emails.

6. Results and discussion

All the responses were received within 21 days from the dis- patch date. Of the 200 questionnaires mailed, 33 were completed and returned. Of these, 24 were from academics while 9 came from practitioners in the industry. The completed and returned question- naires represent 16.5% of the overall sample. This is an acceptable level as can be seen from Gunasekaran et al. (2004) where 14% was considered adequate. 11 respondents returned the questionnaires uncompleted, stating that they were too busy. These represent 5.5% of the respondents. 8 out of the 200 declined out-rightly to com- plete the questionnaires, representing 4% of the sample.

As mentioned earlier, each of the measures was assessed based on their corresponding metrics. Hence, an average mean score was calculated for each of the measures to establish their level of impor- tance and applicability. The results are summarized in Figs. 4–7.

It can be seen from Fig. 4 that customer perspective (CP) had the highest score of 4.67, which implied a 93.4% importance. This was followed by quality (QUALI) – 4.02, supplier commitment (SC) – 4.01, management commitment (MC) – 4, and greening cost (GC) – 3.92, with an importance percentage of 80.4%, 80.2%, 80% and 78.4%, respectively. The list continued with product characteristics (PC) – 3.77, level of process management (LPM) – 3.72, responsive- ness (RESP) – 3.56, traditional supply chain cost (TSCC) – 3.52, and flexibility (FLEX) – 3.2. These represent an importance percentage

of 75.4%, 74.4%, 71.2%, 70.4% and 64%, respectively.

For the backward chain measures presented in Fig. 5, man- agement commitment (MC) was ranked the highest with an importance score of 4.13 and importance percentage of 82.6%. This

576 E.U. Olugu et al. / Resources, Conservation

Fig. 5. The mean importance scores for the backward chain measures.

Fig. 6. The mean applicability scores for the forward chain measures.

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Fig. 7. The mean applicability scores for the backward chain measures.

as followed by material features (MF) – 4.05, recycling efficiency RE) – 3.96, supplier commitment (SC) – 3.92, recycling cost (RC) – .91 and finally, customer involvement (CI) – 3.66. These are rep- esented by an importance percentage of 81%, 79.2%, 78.4%, 78.2% nd 73.2%, respectively.

In terms of applicability, the results are presented in Figs. 6 and 7

or the forward and backward chain, respectively. As can be een in Fig. 6, the traditional supply chain cost ranked the high- st in applicability with a score of 4.44. This was followed by uality – 4.28, management commitment – 4.19, customer per-

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spective – 4.07, greening cost – 3.95, supplier commitment – 3.92, product characteristics – 3.91, level of process manage- ment – 3.85, responsiveness – 3.77 and finally, flexibility – 3.51.

It can be seen from Fig. 7 that for the reverse chain measures, management commitment was ranked the highest in applicability with a score of 4.28, followed by supplier commitment with a score of 4.05. Customer involvement was ranked third with 4.04. Others were recycling efficiency – 4.01, recycling cost – 3.96 and material features – 3.88.

Another statistical analysis, Mann–Whitney U-test was con- ducted to evaluate whether the mean scores of the two sets of data (importance and applicability) differ significantly (Ho = the importance and applicability of the measures should be statisti- cally the same). This is a non-parametric test conducted using the SPSS software. Since the Mann–Whitney U-test is conducted on ranked scores, the distributions of the data for the two groups do not have to be normally distributed. Both the forward and back- ward chain measures were evaluated using this test and the results are presented in Tables 1 and 2.

For the forward chain measures, their mean importance and mean applicability scores were comparatively similar (refer to Table 1). None of the P values was less than 0.05, thus implying that there was no significant difference between the two groups. These results help to buttress that there is a strong correlation between the importance and applicability of the measures.

With respect to the backward chain measures as presented in Table 2, it was found that no significant difference existed between the mean scores of the 2 data sets. The only measure that showed a significant difference in terms of its importance and applicability was customer involvement. This is probably because theoretically, the respondents might think that customers are not so important as they do not play a visible role in the backward chain, but in practice, they must be involved for the chain to suc- ceed.

From the results obtained, it can be seen that all the forward chain measures obtained a mean importance score of more than 3. The most important measure identified by the respondents is cus- tomer perspective (Fig. 4). This implies that the customer must be considered first in an effort to green the supply chain. This is in line with the assertions given by van Hoek et al. (2001) and Gunasekaran et al. (2004) that customer satisfaction should be the crux of sup- ply chain performance evaluation. Quality, supplier commitment, and management commitment were also highly ranked with rela- tively the same score (Fig. 4). This shows that total quality practices of a company as well as support from suppliers and management have a great influence on greening the chain. Green quality function deployment has been highlighted in the literature (Pun, 2006), thus supporting its necessity in green supply chain performance mea- surement. In addition, all the reviewed studies considered supplier and management commitment as key factors. Another measure that was highly ranked is greening cost. This shows that cost is a major issue towards achieving a closed loop supply chain. Other measures which showed a considerably high rank are level of pro- cess management and product characteristics.

In terms of applicability, all the measures showed a relatively high score of at least 3.5 which implies that they are all appli- cable for the measurement of green supply chain performance in the automotive industry. The most applicable measure is tra- ditional supply chain cost, followed by quality and management commitment. A closer look on the results reveals that measures such as greening cost, supplier commitment, product character-

istics, and level of process management have relatively similar scores.

For the reverse chain, it can also be observed that all the measures scored an average above 3.5 in terms of importance

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Table 1 Mann–Whitney U-test results for the forward chain measures.

No. Measures P Importance Applicability

Mean ranks Mean scores Mean ranks Mean scores

FM1 Greening cost 0.682 32.55 3.92 34.45 3.95 FM2 Customer perspective 0.131 29.97 4.67 37.03 4.07 FM3 Level of process management 0.126 29.92 3.72 37.08 3.85 FM4 Product characteristics 0.234 30.73 3.77 36.27 3.91 FM5 Management commitment 0.061 29.09 4.00 37.91 4.19 FM6 Supplier commitment 0.476 35.17 4.01 31.83 3.92 FM7 Traditional SC cost 0.195 30.45 3.52 36.55 4.44 FM8 Responsiveness 0.120 29.85 3.56 37.15 3.77 FM9 Quality 0.115 36.83 4.02 40.17 4.28 FM10 Flexibility 0.444 31.71 3.20 35.29 3.51

Table 2 Mann–Whitney U-test results for the backward chain measures.

No. Measures P Importance Applicability

Mean ranks Mean scores Mean ranks Mean scores

BM1 Recycling cost 0.594 32.26 3.91 34.74 3.96 BM2 Customer involvement 0.038 28.67 3.66 38.33 4.04 BM3 Material features 0.206 36.41 4.05 30.59 3.88

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BM4 Management commitment 0.364 31 BM5 Supplier commitment 0.210 30 BM6 Recycling efficiency 0.701 32

nd applicability. This shows that all the measures established re essential and can be applied in green supply chain perfor- ance measurement for the reverse chain in the automotive

ndustry. It is clearly shown in Fig. 5 that management commit- ent is the most influential measure. This implies that the top anagement has a very enormous impact on the effectiveness

f the reverse chain. High importance scores for recycling effi- iency and supplier commitment signify the importance of the uppliers’ effort as well as the effectiveness of the recycling pro- edure on the reverse chain. Other measures that are crucial are

aterial features and recycling cost. This is not unexpected as

he material composition and the amount of capital invested on ecycling influence the reverse chain effectiveness. On the other and, customer involvement did not show a considerable high

Fig. 8. Overall mean scores for upstream, m

4.13 35.59 4.28 3.92 36.40 4.05 3.96 34.39 4.01

level of importance in the reverse chain compared to the for- ward chain. This might imply that customers do not have a very high influence on the reverse chain as they do on the forward chain.

On applicability grounds, all the measures showed a consid- erable high score. Specifically, management commitment is the most applicable one. Other measures which showed a considerably high level of applicability are recycling efficiency, supplier commit- ment, and customer involvement. Customer involvement showed a higher score in applicability compared to its importance. This might

be because in practice, customers play an imperative role in the success of the actual returning of ELVs, even though they could be perceived as less important. Material features showed a relatively low score. Probably, the respondents believed that it is difficult to

idstream and downstream measures.

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78 E.U. Olugu et al. / Resources, Conser

ssess material features in the performance measurement of the everse chain.

The results obtained from the Mann–Whitney U-test suggest hat all the measures (except for customer involvement) are as mportant as they are applicable in the performance evaluation f a closed loop supply chain. Finally, all the measures have een grouped into upstream, midstream and downstream, and the verall average mean scores for each of the streams in terms of mportance and applicability are presented in Fig. 8. In all, it can be aid that the midstream measures scored the highest in terms of mportance for both the forward and backward chains. This shows hat operations and decisions internal to an organization are the

ost significant in greening an automotive supply chain. To further buttress the importance of the midstream measures,

he downstream measure (customer perspective) of the forward hain is a responsibility shouldered within the organization. In ddition, the upstream measure (supplier commitment) of the orward chain is considered by the organization in its supplier election. This is also true for the backward chain, where the pstream measure (customer involvement) and downstream mea- ure (supplier commitment) depend on the midstream measures uch as management commitment. Thus, effort within an organi- ation has a tremendous effect on green supply chain management. ence, greening should start with internal decisions and operations ithin the company. In essence, it can be observed that the effec-

ive greening of an automotive supply chain is a combined effort of ll the echelons within the chain.

In terms of applicability, it can be seen that the downstream easure of the forward chain showed a considerably high score.

his can be attributed to the fact that it only has a single mea- ure (customer perspective) which is comparatively easier to be pplied. The midstream measures of the backward chain showed a ower score. This might be because of the difficulties envisaged by he respondents in the evaluation of the reprocessing operations nvolved. The downstream measure of the backward chain scored he highest, which might also be as a result of its ease of assessment s a single measure (supplier commitment). It is believed that the ase of assessment can be further enhanced if the same suppliers n the forward chain are engaged in the backward chain.

. Conclusions and recommendations

This study started with a proposition of key performance mea- ures for an automobile green supply chain. Based on a performance easurement framework proposed in the study, 10 key perfor- ance measures with 49 metrics were developed for the forward

hain. On the other hand, 6 key performance measures with 23 etrics were developed for the reverse chain. An evaluation was

onducted using questionnaires distributed to experts from the ndustry and the academia. The results obtained suggest that the mportance and applicability of all the developed measures have een substantiated. The findings from the Mann–Whitney U-test how that in general, the importance and applicability of the mea- ures do not differ statistically. This means that the measures are ot only crucial from the theoretical perspective, but they are also pplicable from the practical standpoint. The only factor that shows difference in this respect is customer involvement. As mentioned arlier, the respondents perceived that the theoretical importance f customer involvement in the reverse chain is lower as compared o the practical implication of this measure for the process to be uccessful.

One of the limitations of this study is that the survey conducted as only an expert evaluation exercise rather than a full-fledged

ndustrial survey. This is because to date, green supply chain man- gement is still a relatively new concept which has not been widely

and Recycling 55 (2011) 567–579

implemented in the industry. Hence, launching an industrial sur- vey is not a viable approach to assess the performance measures. In terms of future work, it is recommended that the measures should be applied together with the proposed framework to evaluate the performance of a green supply chain in the automotive industry. Finally, these measures could be extended to other products with a long useful life in order to measure the performance of their green supply chain.

Acknowledgment

The authors would like to thank the Ministry of Higher Educa- tion in Malaysia for supporting this research.

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