measuring the effectiveness of the country’s green supply chain from a macro perspective

7/29/2019 MEASURING THE EFFECTIVENESS OF THE COUNTRYS GREEN SUPPLY CHAIN FROM A MACRO PERSPECTIVE

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Proceedings of the First Annual Kent State International Symposium on Green Supply ChainsCanton, Ohio July 29-30, 2010

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MEASURING THE EFFECTIVENESS OF THE COUNTRYS GREEN SUPPLY CHAIN

FROM A MACRO PERSPECTIVE

Hokey Min, Department of Management, BAA 3008C, College of Business Administration,Bowling Green State University, Bowling Green, Ohio 43403, Tel: 419-372-3442, Fax: 419-372-6057, E-mail:[email protected]

Ilsuk Kim, Department of Management, BAA 3019C, College of Business Administration,Bowling Green State University, Bowling Green, Ohio 43403, Tel: 419-372-3416,E-mail:[email protected]

Abstract

A Logistics Performance Index (LPI) is often used as way to measure the efficiency of thelogistics and its related activities of a particular country. Although LPI is known to be positivelyrelated to the national income level - the higher the LPI, higher the national income level andvice versa, LPI alone cannot predict the extent of the countrys commitment to green logistics orgreen supply chain management. Since there is no known measure for the countrys greenlogistics efficiency, we come up with a hybrid index combining both LPI and the EnvironmentalPerformance Index (EPI) which is periodically compiled by the World Bank. Unlike LPI, EPIhas the significantly weaker association with the national income level than does LPI. In otherwords, EPI is not paralleled with LPI. That is to say, some countries may choose to increase theirincome level at the expense of the environment degradation. Given that active logistics andsupply chain related activities can impact carbon footprints such as greenhouse gas emission, weinvestigate the inter-dynamics between logistics/supply chain management and environmentalsustainability. To combine LPI with EPI to measure the extent of the countrys commitment togreen logistics/supply chain management, we propose a data envelopment analysis (DEA) that

aims to generate the so-called green LPI by taking the LPI as an output and the EPI as an input.In this paper, we will examine to see if the green LPI is a good indicator of the countrysefficiency in managing green logistics/supply chain activities and whether the goal oflogistics/supply chain efficiency is in conflict with that of environmental quality improvement.In addition, this paper will examine whether the countrys higher level of green logistics/supplychain activities can positively influence its competitiveness in the global marketplace.

Keywords: logistics performance index (LPI), environmental performance index (EPI), dataenvelopment analysis (DEA)

1. INTRODUCTIONLogistics is one of the most important business activities that are essential for sustaining ourdaily lives. Like all other business activities, however, logistics often produce undesiredbyproducts. The extensive use of fossil burning fuels and the subsequent emissions of pollutantslike are examples of the undesired byproducts. These undesired byproducts accelerated thespeed of global warming that threatens the well-being of human species. In an effort to tackingglobal warming issues, both practitioners and academicians alike have paid increasing attention


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to Green Supply Chain Management (GSCM). In fact, the number of studies on this subject hasexploded in the published literature for the last two decades. Even with the restrictive scope ofGSCM, Srivastava (2007) reported to find at least 1,500 articles published in scholarly journalsand edited books.

While the body of knowledge on GSCM has grown dramatically, the firms environmentalperformance has yet to be on a par with its other dominating business performance indicatorssuch as cost, time or quality. In reality, many firms still focus on higher profitability, a greatermarket share, and better cash flow instead of Corporate Social Responsibility (CSR) orEnvironmentally Responsible Logistics (ERL). Many prior studies indicated that the firmtended to consider CSR or ERL when it was forced by public pressure or by governmentregulations (Holt and Ghobadian, 2009; Zhu et al, 2007; Zhu, et al, 2003; Bro and Junquera,2003; Zhuang and Synodinos, 1997). As such, to make the firm more accountable for itsenvironmental commitments, governments should play a mentoring role through theestablishment of environmental yardsticks and the introduction of appropriate legislations.

In this paper, we seek to instigate a change of mindsets and perspectives among the governmentsector by embedding a Green concept within the Logistics Performance Index (LPI). Bycombining EPI with LPI, we develop a new measure called Green LPI (GLPI). This newmeasure is calculated by DEA (Data Envelopment Analysis). Since GLPI is designed to assessthe green logistics performance of a country, we rank each countrys efforts of green logisticsbased on its GLPI. This ranking will help us identify the best-case green logistics practices thatother countries lagging green logistics performances can emulate.

2. THE LPI, THE EPI AND GREEN LPI (GLPI)2.1. The LPI

The LPI was first introduced in 2007 through the cooperation between the World Bank and itsacademic partners. It is an international benchmarking tool focused specifically on measuring thetrade and transport facilitation friendliness of a particular country, inducing them to realizelogistics challenges and opportunities it encounters. In fact, it is closely monitored by policymakers and professionals in both developing and developed economies as is the cases of otherimportant international indicators like Global Competitiveness Index (GCI) published by theWorld Economic Forum. The compilation of the index is performed primarily through the onlinesurvey of approximately 1,000 professionals from multinational firms in 130 countries, engagedprimarily in international freight forwarding operations. The LPI is comprised of twocomponents: International and Domestic.

The International LPI evaluates each country in six areas:

Efficiency of the customer clearance process (Customs): speed, simplicity andpredictability of border control agencies including customs

Quality of trade and transport-related infrastructure (Infrastructure): ports, railroads,and information technology

Ease of arranging competitively priced shipments (International shipments)


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Competence and quality of logistics services (Logistics quality and competence):transport operators and customs brokers

Ability to track and trace consignment (Tracking and tracing) Frequency with which shipments reach the consignee within the schedule or expected

time (Timeliness)

The phrases in the parenthesis correspond to the exact title of data categories used in the 2010LPI report. The respondents evaluate eight countries randomly selected based on theirinvolvement in international trade. Five evaluation scales, from very low to very high areused. To generate a single, summary indicator combining the scores of the six different areas, aprincipal component analysis (PCA) was used. The final country scores were produced afterconverting the responses into logarithms and then averaged them across all the respondents for agiven country.

The domestic part of LPI is not included in the overall country score, i.e., the national ranking,but is used as a way to assess the following areas:

Logistics environment Core logistics process Institutions Performance/cost

The assessment is made by the respondents residing in the countries under evaluation. The samefive evaluation scales are used. It is also complemented with quantitative information providedby the respondents on particular aspects of international supply chains in their countries of workincluding import/export, lead time, supply chain costs, customs clearance, and the percentage ofshipments subjected to physical inspection.

For government policy makers and business leaders, being competitive is the overriding concern

in interpreting their position in LPI just like in the case of the Global Competitiveness Index. Theonly difference is that LPI represents more micro perspective by covering trade logisticsoperations, whereas GCI being more macro by covering the overall domestic competitiveness.The global supply chain supports an international production network where speed and reliabilityof delivery have precedence over others such as environment, health or safety. An one-pointdifference in the LPI score implies two to four additional days for moving imports and exportsbetween the port and a companys warehouse (Arvis, et. al., 2010). At times, therefore, higherlogistics efficiency is achieved at the expense of environmentally less friendly mode oftransportation such as air which emits substantially higher (twenty times or so) amount of(NTM, 2005-2006).

Given the different ways of achieving competitiveness, that is being either efficient in usingresources or allocating more inputs, that is, more man-hours or equipment-hours, without beingefficient, it is important for us to note that the LPI is not free of distortion, particularly from theperspective of environment. This is reflected in the fact that there are noticeable over achieversor under achievers relative to their income levels although the LPI is known to be positivelyrelated to national income level higher the LPI, higher the income level and vice versa. Figure1 shows clearly the positive relationship between LPI and the national income level, with R-square of 70.7%. The typical developed economies like the United States, Germany and


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Singapore situate at the northeastern corner combining very high income and with equally highLPI scores. It is worthy to note, however, the relatively high performances shown by some of thetypical low cost countries (LCCs) like China, India or Vietnam. Their LPI scores are even abovethose of developed economies like Portugal, Greece and Iceland. They may have achieved it atthe expense of transportation efficiency simply by employing more resources, thereby increasing

the pollutants footprints. The World Bank report of 2010 LPI in fact cites that majority of thesurvey respondents showed high level of dissatisfaction on the rail services. This will obviouslyundermine the logistics performance of a country employing rail more than its peers. Therefore,it is a highly plausible that countries and businesses shun rail transport although it is anenvironmentally friendly mode of transportation

Figure 1: Regression between the LPI and national income

2.2 The EPI

The EPI is the product of collaboration between the World Economic Forum and the academiaincluding Yale and Columbia Universities. It was first published in 1999 as the Environmental


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Sustainability Index (ESI). In 2006 the Pilot EPI was published, thereafter the EPI is publishedbiannually, in 2008 and 2010. The EPI measures two core objectives of environmental policy,namely Ecosystem Vitality and Environmental Health.

Policy categories Indicators Weights (%)Environmental burdenof disease

Environmental burden of disease 25

Air pollution (effectson humans)

Indoor air pollution 6.3

Access to water 6.3

EnvironmentalHealth

Water (effects onhumans)

Access to sanitation 6.3

50

Sulfur dioxide emissions per populatedland area

2.1

Nitrogen oxides emissions perpopulated land area

0.7

Non-methane volatile organiccompound emissions per populated

0.7

Air pollution (effectson ecosystem)

Ecosystem ozone 0.7

4.2

Water quality index 2.1

Water stress index 1

Water (effects onecosystem)

Water scarcity index 1

4.2

Biome protection 2.1

Marine protection 1Biodiversity & habitat

Critical habitat protection 1

4.2

Growing stock change 2.1Forestry

Forest cover change 2.14.2

Marine trophic index 2.1Fisheries

Trawling intensity 2.14.2

Agricultural water intensity 0.8

Agricultural subsidies 1.3

EcosystemVitality

Agriculture

Pesticide regulation 2.1

4.2

50


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Greenhouse gas emissions per capita 12.5

CO2 emissions per electricitygeneration

6.3Climate Change

Industrial greenhouse gas emissionsintensity

6.3

25

Table 1: The EPI Indicators and assigned weights

Ecosystem Vitality covers the policy categories for air pollution, water, biodiversity andhabitat, forestry, fisheries, agriculture and climate change. Environmental Health covers thepolicy categories for environmental burden of diseases, air pollution and water. The EPI capturesfor each country the impact of the environmental changes on their people (human) andecosystem. The indicators for measuring the environmental impact per each policy categoriesand the weights assigned to them in calculating overall country index is shown in Table 1. Intotal the EPI has 10 core policy categories and 25 indicators capturing the performance of

countries for each category. Absent a clear consensus on how best to construct composite indicesthat combine disparate issues, the 2010 EPI reports says that equal division of the EPI into sub-scores into humans and nature is not a matter of science but rather a policy judgment. Furtherassigning of the weights for each indicators level was the outcome of similar policy judgment.

Although national income correlates highly with the EPI scores, the degree of correlations issubstantially weakened compared with the case between the LPI and national income. The resultof simple regression generates the R-squared value of 21.7 % whereas in the case of LPI thevalue is 70.7 %. Typical wealthy nations of northern Europe like Sweden, Switzerland andNorway show very high EPI scores. On the other hand, poor nations of Africa and Asia arelocated in the southwestern corner of the Figure, combining very low income levels with very

low EPI scores. Since the nations are in low development level, it seems unlikely that thesenations will undertake meaningful environmental measures that might interfere with economicdevelopment. Their situation supports common perception that only the wealthy nations canafford a clean environment. But this perception is refuted by the high EPI scores registered bysome of the low cost countries (LCCs) like Colombia or Panama; the World Bank define the PerCapita PPP (Purchasing Power Parity) of $11,906 to the dividing line between LCCs and highcost countries. Theirs in fact are higher than those of developed countries like Netherlands,Belgium as well as the US. Overall countries with renewable power sources like hydropower andgeothermal energy fare better than others. Very low LPI scores of the oil producing, wealthynations of the Middle East such as Kuwait, Bahrain and United Arab Emirates also reflect this.


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Figure 1: Regression between the EPI and national income

2.3 The Meaning of GLPI

A large part of the research efforts in green management and GSCM is about reverse logistics. Inthis sense, being green in the management context is about recyclability. Other than that, theterminology is loosely defined or not defined at all.

Bearing this in mind, we judge that it is necessary to establish a clear meaning of Green in thecontext of this study. Green supply chain strategies refer to efforts to minimize the negativeimpact of firms and their supply chains on the natural environment (Mollenkopf, et. al., 2010).Another important concept frequently appearing in the logistics literature is sustainability. TheWorld Commission on Environmental and Development (the Brundtland Commission) definedsustainable development that meets the needs of the present without compromising the ability offuture generations to meet their own needs (Kleindorfer, et. al., 2005). The meaning of Greenbecomes clearer when compared with that of lean, a byword in logistics. Lean supply chainstrategies focus on waste reduction, helping firms eliminate non-value adding activities related toexcess time, labor, equipment, space, and inventories across the supply chain (Corbett and


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Klassen, 2006). Better route planning, education in ECO-driving, better coordination of transfersof shipments are some examples of actions that will not only lower costs but also will stem thenegative impacts caused by logistics activities on environment (Kohn and Brodin, 2008). Whenwaste is minimized as part of environmental management, it results in better utilization of naturalresources, improved efficiency and higher productivity and reduces operating costs. Improved

environmental performance of the firm is translated into tremendous marketing advantage, andthis will lead to improved revenue, increased market share, and new market opportunities.

In sum, Green is a macro concept encompassing lean manufacturing, GSCM and recyclability,all of which independently or in conjunction with others will mitigate the negative impacts ofbusiness operations on the environment, make both the business and the environment moresustainable and ultimately result in higher performance for the firms and a country as whole.This concept of green as being a all encompassing, proactive strategy is made clearer when wecombine the LPI with EPI to gain an insight in developing a new measure to assess the logisticsproficiency of a country from the perspective the environment along with the traditionalemphasis on productivity and competitiveness.

Figure 2: Regression between the LPI and EPI


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Figure 2 shows the relationship between the LPI and EPI, one being competitiveness oriented theother being environment oriented. Being competitive without considering for the environment isnot sustainable. The countries located at the northeast corner combine the high LPI scores withequally high EPI. These countries provide a benchmark for being Green as well as beingcompetitive. This is the meaning of green this paper intends to present by introducing newmeasure assessing the logistics performance of the countries from the perspective of theenvironment or sustainability.

3. LITERATURE REVIEWLiteratures dealing with international comparison of the country level environmentalperformance or the related issues such as sustainable development are scarce. Those dealing withinternational comparison of national level logistics comparison are equally scarce. Although the

LPI had been first published in 2007 logistics research utilizing or related with this invaluableundertaking seems almost not existing. Key word search using the LPI on the research database such as Business Source Complete or Ohio Link EJC (Electronic Journal Center) fails togenerate any hits. Keyword search on the same data base using the EPI and ESI (EnvironmentalSustainability Index), the forerunner of EPI, generate several hits. None of them have directbearings on logistics, supply chain management or the LPI, however. For example, Morse andFraser (2004) provides a critical evaluation of the 1999 ESI, arguing that the ESI creates amisleading impression that Western countries are more sustainable than the developing worlddue to its methodological bias including indicator selection. Similarly, Atici (2009) and Siche etal (2008) critically appraise the ESI to make it capture more relevant, accurate information on theenvironmental sustainability of the countries. Despite not being an international comparison,

Hens et al (2004) applies the ESI methodology to calculating the ESI score of ShandongProvince, China and finds that the province is far from a position of sustainable development ascompared to other countries of the world.

The work of Vachon and Mao (2008) is unique for dealing with the ESI from the logisticsperspective. Using the data from The Global Competitiveness Report (2004-2005) and the 2005Environmental Sustainability Index (ESI), they examine the linkage between supply chainstrength and sustainable development encompassing environmental performance, corporateenvironmental practices and social sustainability.

Nearly complete absence of the researches in the logistics and supply chain management

academia on the LPI/ESI/EPI and other issues emanating from them can be explained in twoways. Firstly, a country level research is predominantly considered as the proper domain ofeconomics research since the management academia in general is usually interested in firm levelanalysis. The second reason lie in the source of research data required for country levelcomparative researches and hence is related with the first reason. For this particular kindresearch the use of secondary data is naturally adequate and practical because those data areusually available from public sources like the publications of national government, international


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organizations or non-profit organizations. The usual issue areas of the management research ingeneral are not covered by these sources, however.

We need to notice that the newly emerged management research agenda such as CSR and greenGSCM owe their advent largely to the awareness by the general public on the global or nationalenvironmental issues and the governmental regulatory policies and legislations responding tothem. This linkage of issues covering both the business and the public sectors mandates thelogistics academia pay research efforts to country level issues like the LPI or green LPI,however scant its research base is at the current stage.

4. THE RESEARCH FRAMEWORK4.1 The relationship between environment and logistics activity

The logistics activity encompasses many areas including procurement, manufacturing,

packaging, distribution, transportation and warehousing. All of these are prone to have someimpact on the environment in varying degrees. Within the scope of logistics activities,environmentally friendly logistics structure are characterized by fewer movements, less handling,shorter transportation distances, more direct shipping routes and better utilization (Wu and Dunn,1995). But there seems to be no easy, clear cut answer to how this can be achieved withoutharming the effectiveness of logistics systems to support international or domestic trade. Oneobvious way of curbing the emissions from logistics sector is to arbitrarily controlling thetransportation demand by using fewer and larger vehicles despite the risk of the widening gapwith the actual demand generated from the market. Given the fact that the timeliness and cost arethe paramount quality standards in the trade economy, it would not be a farfetched speculationthat most of firms and countries tacitly place higher priority on business performance in lieu of

the environmental concerns.

Absent the proactive measures on the part of the business firms to curve these negative impactson the environment, governments around the world usually resort to regulatory measures tomitigate the impacts. Besides, international regimes like the Kyoto Protocol, designed curve theglobal green house gas emissions, also plays vital role in these endeavor. Recognizing thetradeoff between the environmental initiatives and the economic growth, however, individualgovernments usually take a great care in order not to create detrimental effects retardingeconomic progress. The defaulting stance upheld by the US as to the domestic ratification of theKyoto Protocol exemplifies the precarious situation national governments face when pursuingambitious environmental protection initiatives.

As a right reflection of this reality, the academia conceives it as a contentious issue whether thereis a trade-off relationship between environmental protection initiatives and economic growth orfirms performance. In fact, a great portion of researches including empirical ones on GreenManagement are concentrated on the nature of relationship between the environmental practicesand the firms performances, predominantly financial ones. Based on the case of 3M, Shrivastava(1995) argues that the adoption of environmental goals such as zero pollution and the


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environmental technologies enhances competitiveness of firms. Goldsby and Stank (2000) findthat implementation of ERL is positively associated with world class logistics performance.According to many research, ERL primarily focuses on reverse logistics including not onlyrecycling but also source reduction/conservation and disposal. Rao and Holt (2005) finds thecause and effect relationship between greening the different phases of the supply chain and

firms competitiveness and economic performance based on the survey of the executive levelmanagers ISO 14001 certified organizations in the Philippines, Indonesia, Malaysia, Thailandand Singapore. Some researchers find that the adoption of green practices results in theimprovement of the quality. The existence of a positive relationship between proactiveenvironmental practices and the firms performance were supported by the works of Klassen andWhybark (1999), Zhu and Sarkis (2004), Lpez-Gamero et al. (2010). According to Ganzlez-Benito and Ganzlez-Benito (2005), however, although operational performances such as qualityand reliability can be improved with the adoption of the environmental practices, no evidencewas found to prove likewise in the case of the financial performance. Their work is based on thesample of 186 Spanish industrial companies. Sarkis and Cordeiro (2001) also show a similarconclusion on the sample of the US companies. Montabon et. al. (2007) also find a positive

relationship between some of environmental management practices and firm performance basedon the survey of the US and international corporations but concede that so many other factors inaddition to environmental management practices affect the firm performance such as ROI(Return on Investment) the result is not without limitation. Overall the results are mixed, ratherthan conclusive.

4.2 Linking the LPI with EPI

Among the variety of activities engaged in logistics, the transport sector is one of the mainsources of pressure on the environment, particularly regarding air pollution and noise (Aronssonand Brodin, 2006). With regards to emissions in the case of EU, the transport sector isresponsible for a volume of 910 million tons, representing 44 percent of the total emissionsfrom fossil fuels in 2001. Compared to 1991, this represents an increase over 22 percent,although the overall emissions from fossil fuels increased only by 4 percent (Eurostat,2003). In this sense, therefore, the LPI is a key driver of EPI. Since the LPI is a comprehensivemeasure of a nations logistics performance, encompassing the diverse areas like government,regulations, law enforcement and industry, some of the LPI elements are irrelevant orinsignificant in determining a countrys EPI score.

Figure 3 graphically captures this relationship between the major sectors of a country and theinfluence flow from them to the LPI, then to EPI. For example, a countrys score of the customselement of LPI is influence by the regulatory policy and the caliber of law enforcement agencies

like the immigration or customs duties. Those activities associated with Customs, however,have no direct bearings on EPI simply because they do not generate any pollutants. The same canbe said of International Shipment, Logistics Quality and Competence, and Tracking andtracing. They are influenced by the market characteristics such as the levels of sophisticationand competition, and the quality of workforce but do not generate pollutants to the environment.


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Figure 3: Influence relationship between a countrys LPI and EPI

Infrastructure and Timeliness are the important determinants of the EPI. For a betterInfrastructure a country has to expand the network of roads, rails and port facilities, all ofwhich involves construction and it in turn generates even more demand for transportation. In thisintermodal choice is important; whether to have more rails than roads and vice versa. Rail isenvironmentally friendly mode of transportation, but it is costlier to build than roads and lessflexible. Therefore, a government is likely to adopt rail for the sake of efficiency not only in therespect of transportation itself but also of the finance. Timeliness is equally important driver.To be on time, many will pay premium. Premium results in the increase in the employment ofshipments of less than truck load and priority shipments employing truck vs. rail, air vs. truck, allof which means more trucks on the road, burns more fuel on the ground and air. This in turnmeans more pollutants emitted to the environment.

Since we are interested in the pollutants footprint of logistics activities, not all of the elements of

the LPI are considered in linking with the EPI. Some of the categories need to be left out. Amongthe total of 11 data categories of the LPI we judged that those listed below are removed from thelinkage. The results are summarized in Table 2 below.


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Data Categories Inclusion Reasons

Customs X Pertains to bureaucratic red tapes, over regulation and

transparency: no direct impact on the environment

Infrastructure (L1) O Subjected to availability/expanse of road/rail

networks, and construction, maintenance and usage:direct impact on the environment

International shipment X Refers to market condition (openness/competition): no

direct relations with the environment

Logistics quality and competence X Refers to human development (labor quality) and

market sophistication: no direct relations with the

environment

Tracking and tracing X (same as above)

LPI

Timeliness (L2) O Subject to intermodal decisions and the

availability/expanse of transportation network, fuel

consumptions: direct impact on the environment

Outdoor air pollution (E1) O

Sulfur dioxide emissions (E2) O

Nitrogen oxides emissions (E3) O

Non-methane volatile organic

compound emission (E4)

O

Ecosystem ozone (E5) O

Greenhouse gas emissions (E6) O

EPI

Industrial greenhouse gas emissions

(E7)

O

Key indicators of the environmental conditions and

performance

Table 2: The Relevant Factors of LPI and EPI for DEA Run

4.3. Data Envelopment Analysis (DEA)

DEA was developed by Charnes et al(1978) as an auditing tool for evaluating public programs,particularly those of education and health care areas. The pool of literature employing as aresearch tool began to appear from the early 1980s and has expanded into wide areas ofacademic disciplines including engineering as well as management.

The DEA model defines the efficiency of DMU (Decision Making Unit) as the maximum ratioof weighted outputs to weighted inputs subject to the condition that the ratios for every DMUare less than or equal to unity. The model is mathematically presented as:


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Max =

Subject to:

; j = 1,, n

, 0; r = 1,,s ; i=1,, m

Where:

, are the unknown outputs and inputs of jth DMU and

, are the variable weights, assigned to output r and input i, respectively.

The solution of the model will determine the values of , . The optimization process, basedon linear programming methodology, gives the DMU represented by the subscript 0 among theset of j = 1,,n DMUs the most favorable weights possible to maximize its efficiency score.

The solutions are based on four different DEA models;

Input minimizing constant returns to scale model Input minimizing variable returns to scale model Output maximizing constant returns to scale model Output maximizing variable returns to scale model

The results (efficiency score) of the different DEA models are identical between the inputminimization and output maximization models. The constant returns to scale and the variablereturns to scale models produce different results, however. Constant returns to scale assume thatif an input factor is increased, then the output of a DMU will increase the same proportion.Variable returns to scale have two different properties: increasing returns to scale and decreasingreturns to scale. In the increasing returns to scale, output increases more than the proportion bywhich an input increases, and vice versa. Therefore, the kind of model to use must be carefullydecided in consideration of the context of the problems to solve.

From the view of assessing a green LPI by way of linking LPI with EPI, the input minimizingconstant returns to scale DEA model seems more realistic than others. This is because countrieswould like to run their trade logistics network efficiently while minimizing their externalities asmuch as possible. As to the matter of returns to scale, presuming constant returns to scale is anatural choice unless there is a substantive rationale to use variable returns to scale.

The 2010 LPI covers 155 countries and the 2010 EPI covering 163 countries, thereby producing146 countries for which both the LPI and EPI scores are available for DEA model run. For the

sake of linking the LPI and EPI and facilitating the DEA run, the combinedLogistics/Environmental Performance Index (Green LPI: GLPI) is defined as:

GLPI =


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As summarized in Table 2, therefore, two of the LPI data (L1 and L2) are to be included asoutput factors and six of EPI data (E1~E7) as input factors. Then, a DEA run determines theoptimized weight for each of these data elements and also the maximum GLPI for each country.

5. RESEARCH QUESTIONS

From an analytical point of view what is expected from the results of DEA solution is the GLPIrankings of 163 countries are significantly altered as the result of factoring in the EPI elements,mostly pollutants emitted from the economic activities to which logistics is a significant part.

Based upon the earlier finding that LPI shows a stronger degree of association with the nationalincome level than that the EPI has with it and even lesser degree of association between the LPIand EPI themselves, we posit the following propositions to test with the outcome of DEA run.

Proposition 1: Sparsely populated northern European countries like Norway, Swedenand Denmark will sustain equally high GLPI scores as in the LPI.

Proposition 2: Some of developing and developed countries, notably Vietnam, China,South Korea, Belgium, Netherlands or Germany, with high export/import orientedeconomies will make significantly lower GLPI scores than the LPI scores.

Proposition 3: Those middle income countries such as Columbia, Costa Rica andAlgeria, combining the mediocre LPI scores with relatively high EPI scores will see theirGLPI scores significantly improved.

Proposition 4: Typical poor nations in Africa or Middle East will see their performancein GLPI suffer even more than in the LPI or the EPI.

Proposition 5: Overall, the degree of association between the GLPI and the nationalincome will become even less discernable than in the cases of the LPI and EPI.

If the above propositions are proved to hold according to the outcome of DEA runs, we expectthat it will provide new impetus and inspiration for the policy makers of the nationalgovernments, international logistics professionals and multinational firms to renew their effortsto greening their supply chains, their transport logistics section in particular. Pursuing such apolicy initiatives is becoming increasingly important in light of the fact that the transportationsector keeps on increasing its share in the world economy as a result of the globalization ofmanufacturing and business operations. In this we need to pay attention to the EU Commission

findings that from the mid 1980s to the early 2000s the transportation volumes have increasedmore than GNP in Europe.


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Hokey Min is James R. Good Chair in Global Supply Chain Strategy in the Department ofManagement at the Bowling Green State University. He was Distinguished University Scholarand Founding Director of the UPS Center for World-wide Supply Chain Management and the

Center for Supply Chain Workforce Development at the University of Louisville. He earned hisPh.D. degree in Management Sciences and Logistics from the Ohio State University. Hisresearch interests include global logistics strategy, e-synchronized supply chain, benchmarking,and supply chain modeling. He has published more than 130 articles in various refereed journalsincluding European Journal of Operational Research, Journal of Business Logistics, Journal ofthe Operational Research Society, Transportation Journal, and Transportation Research.

Ilsuk Kim is a Visiting Scholar in the Department of Management at Bowling Green StateUniversity. He holds Ph.D., M.S. and B.S. degrees from Lancaster University, US NavalPostgraduate School and South Korea Air Force Academy respectively. His papers have beenpublished or due to be published in International Journal of Services and OperationsManagement, Journal of Operational Research Society and Defense Analysis. Dr. Kimsresearch interest includes supply chain management, green logistics and humanitarian logistics.

measuring the effectiveness of the country’s green supply chain from a macro perspective

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