Modeling Paradigm for the Environmental Impacts of the Digital Economy

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Modeling Paradigm for the Environmental Impacts ofthe Digital EconomyRalph H. Gay , Robert A. Davis , Don T. Phillips & Daniel Z. SuiPublished online: 18 Nov 2009.

To cite this article: Ralph H. Gay , Robert A. Davis , Don T. Phillips & Daniel Z. Sui (2005) Modeling Paradigm for theEnvironmental Impacts of the Digital Economy, Journal of Organizational Computing and Electronic Commerce, 15:1, 61-82,DOI: 10.1207/s15327744joce1501_4

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Modeling Paradigmfor the Environmental Impacts

of the Digital Economy

Ralph H. GayDepartment of Systems Engineering

United States Military Academy

Robert A. DavisCIS & QM Department

Texas State University–San Marcos

Don T. PhillipsDepartment of Industrial Engineering

Texas A&M University

Daniel Z. SuiDepartment of Geography

Texas A&M University

Technological advancements of Internet communications and the recent evolution ofe-commerce have created a viable, emerging framework to conduct business electroni-cally. Undetermined at this point is the environmental impact of the new digital econ-omy and the economic profile of resulting distribution networks. This study developsand employs an integrated modeling framework to compare the environmental im-pacts of a traditional business strategy with an e-commerce strategy for the personalcomputer industry. Ecological factors are evaluated to provide an overall comparisonof the 2 business strategies over the product’s life cycle. Of particular importance arefactors relating to the distribution of products through their supply chains. Thisstudy’s integrated modeling framework includes a simulation component to addressthe stochastic modeling environment caused by business uncertainty. Also included isan environmental input–output life cycle assessment model to quantify the full directand indirect impacts of different business strategies. Outputs from this model includemeasures of electricity, natural gas, fuel and packaging expended, retail and ware-house space used, energy expenditures, vehicle emissions, and 20 different pollutantsresulting from different business strategies. Results of the study suggest 40% to 50% re-duction in life cycle energy and pollutant expenditures with e-commerce in the per-sonal computer industry.

JOURNAL OF ORGANIZATIONAL COMPUTINGAND ELECTRONIC COMMERCE 15(1), 61–82 (2005)

Correspondence and requests for reprints should be sent to Robert A. Davis, CIS & QM Department,Texas State University–San Marcos, San Marcos, TX 78666. Email: [email protected]

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digital economy, electronic commerce, environmental impact,input–output modeling, economic profile

1. INTRODUCTION

The perceived level of importance of social and environmental concerns continuesto grow worldwide. One study [1] found that 69% of the general public believedthat pollution and other environmental damage are impacting their everyday life.In response to this growing concern, individuals and businesses are looking forways to make a positive contribution. For example, Drumwright [2] and Menon andMenon [3] discussed how organizational buying decisions are changing to show agreater concern for environmental sensitivity. Increasingly, organizations are in-corporating these concerns in their marketing and management decisions to remaincompetitive. This concern for environmentalism is also impacting purchasing [4, 5]and manufacturing [6, 7].

Advances in technology are allowing new business models to evolve, but or-ganizations must continue to evaluate the environmental impact of these newmodels. Most environmental research focuses on the motivations for customersor organizations to buy green or on the impact of green efforts on specific func-tional areas. There is an important need to better understand the impact of busi-ness decisions on the environmental and economic aspects of the supply chain.As noted by Green et al. [8], the structure of a particular supply chain is critical indetermining how the environmental impacts of the various elements of the lifecycle can be reduced.

Technology is allowing the business world to change in remarkable ways, pre-senting new challenges and opportunities for companies. Technology has alsochanged the way many consumers expect to conduct their business. From basic in-formation availability to electronic auctions, the Internet has become a technologythat organizations must address. Many companies have responded to the chal-lenges and opportunities created by technology by adopting an electronic com-merce strategy. Although much research supports the value of e-commerce, verylittle research has been published that evaluates the environmental impact of thenew digital economy and the corresponding economic impact of the busi-ness-to-business (B2B), business-to-consumer (B2C), and consumer-to-consumer(C2C) revolution.

According to the U.S. Department of Commerce [9], 171 million people world-wide were connected to the Internet in 1999 and many more are connected today.As more individuals connect to the Internet, there are more online users purchas-ing retail goods through the Internet, permitting B2C e-commerce’s continuedgrowth. The U.S. Department of Commerce [10] reported that online retail salesgrew to $45.6 billion in 2002, a 26.9% increase over 2001. Jupiter Research [11] pre-dicted online spending would reach $52 billion in 2003 and will have an averageannual growth rate of 21% by 2007. Some industries such as books, travel, and com-puter hardware and software have online sales exceeding 10% of total retail reve-nue in their respective industries.

62 GAY, DAVIS, PHILLIPS, SUI

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2. PROBLEM DEFINITION

It appears that the role of e-commerce in global business will continue to increase.The effect that this change in business strategy and associated supply chains willhave on the environment is uncertain, but it is likely that the environment will be af-fected in profound ways. The benefits of e-commerce are quite obvious: speed of in-formation, shortened supply lines, and globalization of markets with new marketsand enterprises [12]. With immediate access to large amounts of information,e-commerce can encourage more energy-efficient product delivery systems, reduceexcess inventories, and affect product reuse. In addition, the need for retail outletsand storage space may be reduced by a move to centralized warehouse facilities.Even though manufacturers may need less storage space, transportation servicessuch as FedEx and UPS may need to increase their storage capacity. Packaging,which accounts for a third of all municipal solid waste, and advertising materials in-tended to attract customers may be sharply reduced through e-commerce. The ac-cessibility of information to promote product reuse benefits the consumer [13, 14]and may lead to price reductions.

Recent logistics trends have increased emphasis on air transport to meetjust-in-time requirements, which result in more logistic vans on the road to meetthese increasing demands. Just-in-time often results in partial truckloads and an in-creased number of deliveries. These logistic transporters consume nonrenewableenergy and generate emissions of carbon dioxide, nitrogen, and sulfur dioxides,plus other forms of pollutants. It has been suggested that 50% of America’s total en-ergy consumption is the result of the operation of motor systems [15].

Researchers and managers are grappling with the future impact of e-commerceon the structure of the economy and the environment [16, 17]. How will this radicalchange in business strategy affect the world economy and the net balance of fragileecological factors? Is e-commerce completely environmentally benign, or are theresignificant structural changes in the consumption of resources that are influencedby the digital economy and the rapid exchange of information? This article exam-ines the flow of products within manufacturing and delivery systems. Because theimpact of e-commerce may be different for different industrial segments, this studyconducts a life cycle assessment for a specific industry, the personal computer in-dustry. Both traditional and e-commerce business strategies are investigated andthe environmental impacts of each strategy are determined.

The personal computer industry was chosen for analysis in this study becausethere are companies that use e-commerce very effectively and others that continue touse a more traditional business strategy. This sector produces an estimated $100 bil-lion in annual revenues and is a major manufacturer in the United States with a sig-nificant delivery chain from the manufacturer to the consumer. Personal computermaker Dell has captured a dominant share of the market using a strictly online busi-ness model. This performance surge by Dell has forced other personal computermanufacturers to reexamine their strategies, evaluate the benefits of the e-commercemodel, and compare it to the traditional methods of personal computer delivery tothe consumer. The study focuses on the portions of a personal computer’s life cyclewhere differences may exist when comparing the two business strategies.

MODELING ENVIRONMENTAL IMPACTS OF DIGITAL ECONOMY 63

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For purposes of analysis, we assume that the personal computer life cycle con-sists of up to nine phases: purchase of raw materials, computer manufacturing,warehouse and central distribution, transportation, storage in retail stores, salesand marketing, usage by the consumer, customer support service, and final dis-posal. When comparing e-commerce to a traditional approach in manufacturingand distributing personal computers, it is assumed that the primary life cyclephases in which significant differences might exist are in the computer manufac-turing, warehouse and central distribution, transportation, and storage in retailstores. An integrated model analyzes these relevant phases of a personal com-puter’s life cycle so that environmental and economic comparisons can be made be-tween the two business strategies.

3. INTERINDUSTRY PARADIGM DEVELOPMENT

Hurst [18] explored 13 possible impacts that e-commerce could have on the envi-ronment, such as a decrease in energy consumption and a decrease in paper de-mand due to an increase in the use of digital information. Hurst suggested that thegrowth of e-commerce will necessitate more in-depth life cycle analyses of supplychains and the accessibility of reuse and recycle operations. Cairns [19] stated thatthere are six key factors that can impact the environmental burdens or benefits ofe-commerce: product returns, cost structures, delivery locations, vehicle use, rout-ing and scheduling optimization, and load consolidation. Romm [20] illustrated theinterdependence of industrial segments. He described how a change in one indus-trial sector can create a change in a different sector, resulting in a rippling effectthroughout the economy. This cause-and-effect relationship is the basis ofinterindustry economics.

Wassily Leontief developed the first empirical interindustry mathematicalmodel, input–output analysis. This model is developed through a series of linearequations and the economy is organized by industry. Government and house-holds are included as final demand. An industry sells its output, which in turn, isanother industry’s input, which it needs to sell its output. The Leontief modelcan be used to predict the net flow of industrial goods and services among indus-trial sectors.

A general input–output model is depicted in Figure 1, which when completedfor an economy, will cover all the goods and services produced in that economy.Let xij represent the flows from sector i to sector j for a specific time period. Xj is thetotal output of a sector for this specified time frame. The economy is divided into npurchasing sectors (input) and n producing sectors (output). These sectors are di-vided into Standard Industrial Classification (SIC; now known as NAICS) levels.

The final output of a sector will equal the row sum of the intermediate demandsof the other sectors and the final or direct demand, which includes investment,government, household, and export demands. Often, the sum of all intermediatedemands is greater than the final demand.

The total requirements matrix in Figure 1 permits the tracing of raw materialsthrough the many phases of manufacturing to the final product. By examining therows of Figure 1, the resulting system of linear equations can be expressed by:


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X1 = x11 + x12 + … + x1j + … + x1n + Y1

X2 = x21 + x22 + … + x2j + … + x2n + Y2…

Xi = xi1 + xi2 + … + xij + … + xin + Yi…

Xn = an1X1 + an2X2 + … + annXn + Yn (1)

From this format, one can see the interdependency of the interindustry flows on thetotal output, Xn, for each sector n. Furthermore, if one knows the final demand, Ynfor a specific time period, possible inputs from industries to meet the final demandfor a sector n can be determined. In linear programming format, the Yi for each re-spective sector i would be known, along with the intersector technical unitless coef-ficients, ann, and the outputs, Xi, for each sector i would be the unknowns for whichone would solve. An element aij represents the dollar purchases from sector i associ-ated with the dollar output of sector j. The relation among the interindustry flow,the sector output, and the technical coefficient is depicted by:

xi1 = ai1X1 (2)

3.1 Environmental Burden Input–Output Formulation

Ayres and Kneese [21] first observed environmental pollution as a material bal-ance problem and examined the interrelation among energy consumption, mate-rials processing, and final consumption in terms of the Leontief inputcoefficients. Leontief and Ford [22] examined aggregated 90-sector input–outputtables for the years 1958, 1963, and an estimated 1980 to determine the air pollu-tion coefficients for particles of sulfur oxides (SOx), hydrocarbons (HC), carbonmonoxide (CO), and nitrogen oxides (NOx). The Leontief and Ford study was


Figure 1. General input–output model.

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one of the first to state that an expanded input–output table could illustrate theeconomic activities and environmental burdens such as generation and elimina-tion of pollutants commensurate with industrial production operations. Millerand Blair [23] presented additional environmental and energy input–outputmodels that have been developed to provide a useful framework for tracing re-source expenditures throughout interindustry activities. Arrous [24] demon-strated how production processes with energy sources as inputs can be used ininput–output analysis with no major modification to the input–output formula-tion. The Green Design Initiative at Carnegie Mellon University developed amethodology to identify the environmental burdens from the input–outputmodel [25]. Its methodology is to first estimate the changes in final demand Y,then assess the direct and indirect changes with the input–output matrix a. Itthen determines the environmental burdens for each sector output. The total out-put is represented in Equation 3.

X = Y + aX, (3)

where:

which can be modified to be:

Y = X – aX. (4)

According to Leontief and Ford [22], [I – a]–1 represents the sum of the indirectand direct effects of a large increase in the final demand of any particular industryon the total output of this and all other industries. Multiply both sides of Equation 4by [I – a]–1 to obtain the total sector output vector to meet an exogenous demand, Y.Here, I is the identity matrix.

[I – a]–1Y = [I – a]–1(X – aX). (5)

[I – a]–1Y = X. (6)

[I – a]–1 can be expanded to an infinite series by binomial series expansion to repre-sent the direct and indirect requirements by:

[I – a]–1 = [I + a + a2 + a3 + a4 + … + an]. (7)

Combining Equations 6 and 7, one can determine the final demand vector Y, fromthe direct requirements, a, and the indirect requirements: a2, a3, a4, … an by:

[I + a + a2 + a3 + a4 + …] Y = X. (8)


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–1,1 –1, –1 –1,

,1 , –1 ,

n n

i j

n n n n n

n n n n n n n

X Y a a a

X Y aX Y a

a a a

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This technique is explained by Leontief [26] and Joshi [27]. Let r be the environmen-tal burden k × n matrix, where rkj is the proportion of the pollutant k per dollar out-put generated by sector j. Vector Y remains the total exogenous final demand vectorand E is the vector of total environmental burden. Equations 4 and 6 are updated toinclude the environmental burdens by:

r[I – a]–1 Y = rX = E, (9)

where r = [r1, r2, …, rn]. E multiplies a vector of per dollar emissions, ri, by the totaloutputs of each vector.

3.2 Environmental Input–Output Life Cycle Assessment

Duchin [28] was one of the first authors to initiate the idea of employing input–out-put economic techniques in an environmental life cycle setting. This environmentalinput–output life cycle assessment (EIO–LCA) determines the complex interactionsinvolved in the production of an item by evaluating all the resources and raw mate-rials required to produce the item, plus all the resources necessary to produce thebill of materials for the product. Recently, researchers have employed economic in-put–output models for environmental life cycle assessment [27, 29]. EIO–LCA usessimultaneous linear equations to examine the interindustry interactions and inter-dependencies. King and Lennox [30] were the first to use EIO–LCA to explore theeconomic profits attributed to waste prevention in an environmental context.

4. MODELING METHODOLOGY

At the foundation of this integrated modeling framework is SmartCost®, a softwaretool developed by two of the coauthors to assess the economic impact of new tech-nological innovation. SmartCost is an object-oriented cost modeling system thatcategorizes and computes both indirect and direct costs using a hierarchical,bill-of-material type representation. SmartCost was adapted to compute the eco-nomic and environmental impact of different business strategies. In this study, ma-jor resources (approximately 200 items) expended throughout the relevant phasesof the life cycle of a personal computer are prototyped in a detailed spreadsheet.SmartCost, coupled with Excel, computes the energy and material resource expen-ditures throughout the product’s life cycle. Integration of simulation methodolo-gies permits an examination of the impact of a parameter’s stochastic variations andthe cause-and-effect relations.

The SmartCost outputs describe the electricity, natural gas, liquid fuels, paper,packaging, and solid and liquid waste consumed or expended, plus retail or ware-house space used. To determine all the resources needed to produce a good, onemust identify all the energy expenditures and resultant environmental burdens re-quired to produce the resources needed for this good. The EIO–LCA software de-veloped by Carnegie Mellon University in the late 1990s serves as the tool to assessthese direct and indirect impacts of two disparate business strategies: e-commerce


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and traditional brick-and-mortar business. The 485 commodity sectors in the 1992input–output tables produced by the U.S. Department of Commerce [31] are usedwith the U.S. Environmental Protection Agency’s (EPA) Toxic Release Inventoryand greenhouse gas emissions factors along with other data sources. SmartCost re-sults (electricity, liquid fuel, etc.) are computed in terms of the latest 2001 prices(the U.S. Department of Energy’s Department of Information Administration hascurrent prices for energy sources) and then converted to 1992 prices (as required bythe EIO–LCA model) for comparison based on the Consumer Price Index InflationCalculator from the U.S. Bureau of Labor Statistics. These SmartCost results are thevalues that are depicted by X, the output vector in Equation 9, and multiplied bythe vector r = [r1, r2, ..., rn] in Equation 9. The vector of per-dollar emissions, ri, iscomputed by the EIO-LCA software. The EIO-LCA output portrays the environ-mental impact of each business strategy alternative depicting the results in terms ofenergy, sulfur dioxide, carbon monoxide, lead, natural gas, coal, fuel oil, motor gas,nitrogen dioxide, and up to 20 other pollutants and residue. This result is repre-sented by the theoretical value E in Equation 9.

Figure 2 depicts the key steps that were accomplished in this study. They pro-vide an overview of the types and sources of inputs that were used in the model.The key steps include:

• Simulation modeling framework was developed that involved linking dispa-rate industrial engineering, environmental engineering, and operations re-search software.

• Material resource requirements, energy requirements, and other input pa-rameters were determined through personal interviews, government sources,and published research.

• The stochastic and deterministic values were input into SmartCost to deter-mine the amount of resources consumed for a particular business strategy.Stochastic values were evaluated through Microsoft Excel and @Risk.


Figure 2. Model methodology.

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• Resource values were then converted to 1992 dollars as required by theEIO-LCA model.

• Environmental burdens for 20 different factors were determined by theEIO-LCA model.

• Output data were imported into a Microsoft Access database to facilitate com-parative analysis.

Using this integrated modeling framework in Figure 2, the research analyst cantake the energy and raw materials needed throughout the full life cycle of a productand input them into the SmartCost software itemized by life cycle phase and subse-quently aggregated so that the whole life cycle is considered. The outputs ofSmartCost are converted into 1992 dollar units by the Department of Energy datasources in Excel, which are then hyperlinked and input into the EIO-LCA software.The EIO-LCA software incorporates 10 environmental databases to evaluate thesebusiness practices throughout the entire supply chain of the product. The output ofthe EIO-LCA software is hyperlinked to an Access database that shows the com-plete environmental burden or E in Equation 9 of the specific phases of the life cycleunder analysis. Thus, this entire simulation model permits one to determine wherethe benefits and costs are for several modes of business: traditional, e-commerce, oreven a hybrid mix of the two.

5. E-COMMERCE IN THE PERSONAL COMPUTER INDUSTRY

In the late 1990s, personal computer manufacturers began to turn to online selling oftheir products to gain market share and enjoy some of the success Dell Computershad with its online sales business strategy. Dell realized early that it could sharplyreduce inventory by refraining from building computers until orders were submit-ted online. Each personal computer could be personally tailored to the specificneeds of the consumer. The massive reduction in inventory led to strong gains inprofits and Dell surpassed Compaq and Gateway in the production of personalcomputers. Customizing computers in a build-on-demand manner is enablingcompanies to become more fully cognizant of demands and permitting more accu-rate forecasting along their supply chains. In addition, the reduction of inventorypermits the reduction in the size of warehouses and increases the possibility of elim-inating regional warehouses completely. Because these customized computers arebuilt to meet the desired specifications of the consumer, the percentage of returns issharply reduced. Other companies such as GE and Cisco have reduced mistaken or-ders and subsequent returns from 25% to 2% by moving to ordering online [20].

5.1 Modeling E-Commerce and Traditional Business Strategiesin the Personal Computer Industry

The major differences between e-commerce and the traditional means of con-ducting business in the personal computer industry are the warehousing andtransportation and distribution processes. This study focuses on the areas wherethere may be significant differences between the two order and receipt methods inthe life cycle. Figures 3 and 4 depict the two business strategies being evaluated.


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The traditional approach to distributing personal computers usually involves acentral warehouse, a regional distribution center, a series of retail stores, and multi-ple trips between consumers’ homes and retail outlets (Figure 3). In contrast, per-sonal computers in the e-commerce-oriented supply chain usually move directly tothe consumer and bypass the central warehouse, retail stores, and consumer tripsto the retail outlet (Figure 4). The central warehouse, popular in the traditionalmodel, usually holds a large amount of inventory that requires a great deal of spaceand resources to maintain. The e-commerce strategy can reduce the size and eventhe need for regional distribution centers as well as retail stores because the per-sonal computer goes straight to the consumer, at home or at work. Reduction in fa-cility requirements can save a large amount of energy and construction materials,in addition to the energy required to manufacture and transport these materials.

In the integrated model framework, each relevant phase of the personal com-puter life cycle is broken down into specific functions. For example, in theSmartCost warehouse object shown in Figure 5, the key outputs are computerproducts shipped directly to the customer and others packaged in bulk for distri-bution to a retail outlet. Many different resources are consumed by the warehousefunction for the outputs to be realized. SmartCost totals the energy and material re-source expenditures through the relevant portions of a computer’s life cycle andoutput electricity, natural gas, liquid fuels, paper and packaging consumed as wellas retail or warehouse space used.

Based on a survey of retail facilities such as Best Buy and Circuit City, the areadesignated for the display, service, and inventory storage of personal computersfor this study is approximately 2,000 square feet. Such facilities are suppliedweekly by a large 18-wheeled cargo truck that delivers about 50 computers perweek, which takes up 25% of cargo capacity within the truck. The truck originatesat a regional distribution center and makes weekly deliveries to four retail facilities,approximately 100 miles apart in a rural area or approximately 15 to 20 miles apartin a more metropolitan area. The fully loaded truck will deliver approximately 200computers per week to the four retail facilities.

The packaging for a computer is typically 30” × 30” × 24” or 12.5 cubic feet. Thecontainer for a large 18-wheeler cargo truck is 40’ × 8’ × 8’ or 2,560 cubic feet. Thismeans that the truck can contain a maximum of 205 personal computers. The ware-


Figure 3. Traditional delivery process for personal computers.

Figure 4. E-commerce delivery process for personal computers.

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house space required to house the 200 computers transported weekly in a fullyloaded truck is approximately 800 square feet stacked four levels high. In thisstudy, based on the 200 computers per week model where the required warehousefloor space to store each computer is 0.083 square feet per unit-year, the warehousespace consumed is 863 square feet per year.

Total cost of electricity E is:

E = (Ew + Er)(I) (10)

Ew = Sw (Cw) I and Er = Sr (Cr)I, (11)

where Ew is the electricity for the warehouse and Sw is the square footage of thewarehouse. Correspondingly Er and Sr are the electricity and square footage of theretail space for the four stores. I is the inflation factor to convert all values to 1992dollars as required for input into the EIO-LCA model.

Figure 6 depicts the traditional logistical distribution network for deliveringpersonal computers to retail facilities. The model was developed based on industryinterviews with retail and transportation service executives. Computers are boxedand loaded from the manufacturing facility straight into a large cargo truck con-tainer. When full, the container is picked up by the third-party transportation ser-vice and travels to a computer distribution center, which is located in a centralfacility with easy access to interstate highways. Ingram Micro is an example of thistype of distribution center, with facilities in Dallas, Memphis, Chicago, and centralCalifornia.

From the computer distribution centers, 18-wheeler trucks ship computers to re-gional distribution centers in large metropolitan areas and are cross-docked, whereother 18-wheeler trucks pick up the computers and deliver them to retail outlets.Eighty percent of retail outlets are within 80 miles of regional distribution centers,


Figure 5. SmartCost warehouse ob-ject: Inputs and outputs.

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whereas 20 percent are located in rural areas where a 400-mile round trip deliverscomputers to retail facilities. Consumers travel on average 11.28 miles round trip topick up and receive computers [32]. Returns and inventory for the traditionalmethod are 10% percent and 1.64% for e-commerce. Inventory is computed by:

I = R/365. (12)

Here, I is the percent inventory and R is the inventory turn rate in days. The inven-tory turn rate for Dell, an e-commerce company, is 6 days. The turn rate for Compaq,a more traditional commerce company, is 33.6 days [33]. Applied cost factors anddata sources are contained in Table 1.

Figure 7 depicts the e-commerce distribution model used in this study modeledafter Dell Computer Corporation. Dell employs two delivery methods initiated byonline orders: air (1–2-day delivery) and ground. It is expected that 10% of Dell’sorders are by air, but increases in this factor are considered in the study to evaluateenvironmental impact. Dell computers originate at one of its two manufacturingplants: Campbellsville, Kentucky, and Round Rock, Texas. Computers are trans-ported daily via third-party transportation service trucks to the local major airportand then by air to the air hub of the third-party transportation service, maximizingutilization of the aircraft capacity load. From the airports, shipments arecross-docked at third-party warehouses near airports and shipped by vans that areless than full truckloads (LTL) directly to local consumer houses 80% of the time.The other 20% of shipments require trucking by large cargo vehicles to rural spokesor subhubs, and from there to local residents within an average of 70-mile roundtrip of this facility.

If computers can be delivered on time, shipments are trucked and not sent byair. Trucks fully loaded at the plants (Campbellsville, Kentucky, or Round Rock,Texas) travel directly to third-party major distribution centers such as Memphisand Dallas. Computers are then shipped in fully loaded trucks to regional metro-politan distribution centers or to outlying subhub spokes, where they are deliveredto the consumers.


Figure 6. Transportation distribution model for traditional delivery of personal computers.

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Table 1Data Sources for Personal Computers Commodity Models

Parameters Units SIC Sector Code Unit Price Reference

Electricity kWh Electric Services(Utilities) #4911

$0.02 [34]

Natural gas BTU Natural GasTransmission &Distribution #4923

$0.0000055 ($5.48 per millionBTU)

[35]

Transportation(ground)

Per mile Trucking & CourierServices (ExceptAir) #42

$0.43 (loaded truck)$0.38 (not fully loaded truck)$0.10 (LTL)$0.04 (car)

[36][37][38]

Transportation(air)

Miles Air Transportation#45

$10.48 [36]

Paperpackaging

PC box Paperboard,Containers andBoxes #265

$10.33 [39]

Warehouse andretail space

Public Warehousing& Storage #422

$19.00/sq. ft. [40]

PC productioncost

ElectronicComputers #3571

$677.65 [41][42]

Note. SIC = Standard Industrial Classification; BTU = British thermal unit; LTL = less than truckload.

Figure 7. Transportation distribution model for e-commerce delivery of personal computers.

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For both models, transportation environmental impacts are based on the dis-tance traveled. Environmental impact factors for various modes of transportationare shown in Table 2. Five hundred simulation runs were conducted to determine a95% confidence interval for total ground transportation costs in the traditionalmethod to have a coefficient of variation (CV) of 8.28%. The CV for total groundtransportation costs for the e-commerce method was 0.16% and the CV for the totalair transportation costs was 0.22%. These CV values reflect the robustness of thesignificant simulation results.

5.2 Results

The simulated time period of the study is 48 months, which corresponds to the ex-pected life span of a personal computer. The computer industry was simulated forthis time under both the traditional and e-commerce business strategies. The objec-tive was to assess the environmental and corresponding economic impacts of thetwo business strategies over the relevant phases (computer manufacturing, ware-house and central distribution, transportation, and storage in retail stores) of theproduct life cycle. Life-cycle comparisons, including all relevant phases of the twostrategies, are illustrated in Table 3.

The base e-commerce model developed here is under Dell’s anticipated 10% ofshipments by air. The sensitivity of the model to changes in the percentage ship-ments by air was addressed by considering three additional scenarios: 25%, 50%,and 75% of air shipments. The environmental impact under each scenario wasevaluated. Included in the analysis are electricity consumption; energy consump-tion; and amount of release of many of the critical EPA pollutants, including carbonmonoxide, nitrogen dioxide, hydrocarbons, and carbon dioxide. It can be seenfrom Table 3 that the e-commerce strategy exhibits a lower environmental burdenthan the traditional strategy at air freight levels from 10% to 50%. At 75% airfreight, nitrogen dioxide and carbon dioxide emissions are higher than the tradi-tional method. Table 3 also shows consistently more than 60% savings in electricityconsumption by the use of e-commerce over the traditional approach. This reduc-tion in electricity consumption is primarily due to the reduction in inventory of


Table 2Transportation Mode Emissions Based on Distance Traveled

EnvironmentalImpact

LargeTruck

LightTruck

PassengerCar Air Freight Boeing 747 Units

Energy use 24.37 7.614 6.134 634 MJ/mileHydrocarbons 5.32 3.51 2.8 488 + 1.2 × miles gm/mileCarbon monoxide 48.67 27.7 20.9 29 300 + 14.26 × miles gm/mileNitrogen oxides 4.72 1.81 1.395 72 200 + 252.34 × miles gm/mileCarbon dioxide 3.74 1.2 0.916 –5 456.49 + 59.33 × miles lbs/mileMotor gasoline

consumed0.164 0.0585 0.0465 — Gallons/mile

Aviation fuelconsumed

— — — 5 Gallons/mile

Note. MJ = megajoules.

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personal computers held under the traditional strategy. The reduction in inventoryalso consistently represents 70% or more reduction in the life cycle production anddelivery costs.

It is useful to further investigate the environmental impact of the traditional busi-nessstrategyfromTable3bylookingat the influencingfactors.Table4showsthat in-ventory is responsible for almost 70% of the total life cycle electricity consumption inthe traditional strategy. Higher levels of inventory must be held in traditionalbrick-and-mortar organizations to meet customer needs. These higher levels are ne-cessitated by the uncertainty of demand due to the stochastic nature of customers’desires.Because thee-commercecompany(in thiscase,Dell)doesnotmanufactureacomputer until the demand is certain, it will be able to keep a lower amount of inven-tory. Thus, this factor will remain high until traditional organizations minimizeon-hand inventory. Dell boasts consistently that its main competitive advantage is“no”inventory. Inventoryaccounts foralmost40%ofallenergyuse inthetraditionalmethod, as shown in Table 4. The table also isolates individual contributors to envi-ronmentalburden.Thedistributionmethodsof traditionalcommerceaccount foral-most 30% of the energy consumption along with over 50% of the carbon monoxideemissions. When coupled with passenger vehicle auto emissions, distribution ac-counts for over 80% of the carbon monoxide. Carbon dioxide and hydrocarbon emis-sions are exclusively the result of the transportation service systems. Distribution bytrucks from the manufacturing facility to retail establishments accounts for 60% to77% of hydrocarbons and carbon dioxides. Even though automobiles travel a shortdistance to and from the retail facility, they account for 38% of total hydrocarbonemissions and 22% of the carbon dioxide emissions.

Inventory reductions through e-commerce permit energy savings in all thee-commerce scenarios (10%, 25%, 50%, and 75% air freight), as shown in Figure 8.Through this sensitivity analysis we found in the e-commerce scenarios that car-


Table 3Life Cycle Comparisons Between E-Commerce and Traditional Commerce of Personal Computers

Over 48-Month Period

ElectricityM-kWh

Energy(TJ)

CO(Mt)

NO2(Mt)

HC(Mt)

CO2(Mt)

$(Millions)

Traditional commerce 1.317 48.07 41.007 10.51 3.455 873.8 8.43E-commerce (10% air) 0.44757 26.938 21.684 6.27 1.729 616.3 2.16Reduction of

environmental burden 66.02% 43.96% 47.1% 40.3% 50% 29% 74.4%E-commerce (25% air) 0.4549 29.569 20.067 7.567 1.535 707.6 2.24Reduction of

environmental burden 65.46% 38.49% 51.1% 28.0% 56% 19% 73.3%E-commerce (50% air) 0.467 37.25 17.31 9.711 1.206 858.1 2.4Reduction of

environmental burden 64.54% 22.51% 57.8% 7.6% 65% 1.8% 71.7%E-commerce (75% air) 0.47917 44.933 14.55 11.86 0.878 1008.0 2.53Reduction of

environmental burden 63.62% 6.53% 64.5% –12.8% 75% –15% 69.99%

Note. Underlining is for emphasis. M-k Wh = million kilowatt-hours; TJ = terajoules; CO = carbonmonoxide; Mt = metric tons; NO2 = nitrogen oxides; HC = hydrocarbons; CO2 = carbon dioxide.

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bon monoxide emissions are far lower (up to 60%) than the traditional strategy. Ni-trogen oxides in the traditional business approach originate mostly fromtransportation by large cargo trucks and the production of excess personal com-puters held in inventory. These emissions exceed those resulting from all thee-commerce scenarios except for the scenario involving 75% air freight. Thus, ouranalysis of the full life cycle environmental burdens is sensitive to changes in theamount of air cargo employed. The traditional strategy produces far more hydro-carbons than the e-commerce strategy under all scenarios.

More detailed sensitivity analysis was conducted by isolating on the transporta-tion and delivery aspect of the personal computer industry. When looking specifi-cally at the transportation element of a personal computer’s life cycle, ane-commerce business strategy does not clearly dominate the traditional strategy in


Table 4Influencers of the Environmental Impacts Using the Traditional Method of Delivery of Personal

Computers Over of a 48-Month Period

InfluencersElectricity(M-kWh)

Energy(TJ)

CO(Mt)

NO2(Mt)

HC(Mt)

CO2(Mt)

$(Millions)

% Impact of cars 0.26 6.9 25.3 0.70 38.7 22.7 0.37% Impact of distribution

without cars2.70 28.8 57.0 42.01 61.0 77.3 3.85

% Impact of retail andwarehouse

5.67 8.6 0.88 5.72 0.0 0.00 3.13

% Impact of inventory 69.15 39.1 10.7 32.56 0.0 0.00 82.7% Impact of packaging 22.21 16.6 6.12 19.03 0.0 0.00 9.97

Note. M-k Wh = million kilowatt-hours; TJ = terajoules; CO = carbon monoxide; Mt = metric tons;NO2 = nitrogen oxides; HC = hydrocarbons; CO2 = carbon dioxide.

Figure 8. Life cycle energy and emissions comparisons between traditional and e-commercefor shipment of personal computers over a 48-month period.

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energy consumption and NO2 emissions and is sensitive to the amount of airfreight employed (see Figure 9). At about 15% air freight, e-commerce will con-sume more energy and produce more NO2. At all levels of air freight, e-commerceis more favorable than the traditional approach in the production of CO. For airfreight values greater than 50%, e-commerce produces higher levels of CO2.

Figure 10 considers the 48-month expected life of a personal computer under anassumed 25% rate of air freight. It demonstrates how various functions contribute toelectricity and energy consumption and the production of carbon monoxide, nitro-gen dioxide, and hydrocarbons. It also shows how the functions contribute to theoverall production and delivery cost of the personal computer. Packaging is respon-sible for over 50% of electricity use and inventory accounts for another third of its us-age. Airplanes and trucks (distribution) were primarily responsible for energyconsumption and polluting emissions such as hydrocarbons, carbon monoxide, andnitrogen dioxide. Inventory accounted for almost half of the cost of e-commerce,whereas packaging accounted for another third and distribution accounted for al-most a fifth of the overall cost. Although these figures shown are for 25% air freight,they are consistent with results for the other three air freight scenarios.

6. CONCLUSIONS

Technology in general and the Internet in particular are allowing individuals andorganizations to modify the way they order and receive goods and services. Thereare definite environmental consequences of these changes. The environmental im-pact of more people working at home, less business travel, online purchasing, andincreasing applications of the Web to better coordinate supply chains can be dra-matic. One such dramatic improvement is a general reduction in inventories that re-sults in reduced need for warehouse space that requires many types of resources tomaintain. The need for retail space can also be reduced through e-commerce, and


Figure 9. Life cycle energy and emissions comparisons of only the transportation systems be-tween traditional and e-commerce for personal computers.

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increasing numbers of online transactions are greatly reducing paper use world-wide. The ultimate level of contribution of e-commerce to society and the environ-ment will greatly depend on individual consumer decisions. If everyone orders on-line and demands overnight delivery, the environmental burden from moreairplanes and trucks will increase. It takes approximately six times the fuel to re-ceive products overnight than through normal delivery methods. On the otherhand, e-commerce sharply reduces the use of passenger cars, which are a very largesource of air pollution.

This study looks specifically at the personal computer industry and the environ-mental impact of e-commerce. When evaluating over the life cycle of personal com-puters, e-commerce is more environmentally beneficial to the world than thetraditional method of purchasing and delivery. This is a result of efficiente-commerce logistical systems that minimize travel and space in the transport ofgoods, and the reduction of waste from excess inventory common to traditionalcommerce. Given the increased environmental burden of air freight, the percent-age of air freight used impacts the environmental benefits of e-commerce. Resultsof this study suggest that at near 75% air freight, the amount of nitrogen dioxideand carbon dioxide released into the environment is greater than through tradi-tional commerce. The increased use of vans and small trucks on the road for B2Chome delivery are far better for the environment because they help reduce the


Figure 10. E-commerce 25% air freight impacts by environmental output for a 48-monthperiod.

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heavy pollutants caused by a large number of consumer vehicles traveling to andfrom retail stores. Over a quarter of the air pollutants in traditional commerce re-sult from these passenger cars. The remaining air pollutants are a result of othertransportation methods.

The digital revolution has provided the Internet as a useful tool to benefit the en-vironment. Dramatic shifts in raw material consumption and distribution patternsshow marked potential to stem the tide of society’s increasing desire for resourceconsumption and willingness to pollute the environment. Information technologyhas created a window of opportunity for a sustainable, resource-smart, and envi-ronmentally friendly economy.

7. AREAS FOR FUTURE STUDY

This is a novel topic in the study of e-commerce and we have identified one of theunexpected benefits from this new business strategy. There are many aspects ofe-commerce and traditional business to examine and compare throughout the lifecycle of a product.

This article modeled specific industries based on the proprietary informationthat could be gleaned from the current manufacturing, warehousing, and distribu-tion practices by firms in multifarious trades. We found the results to be sensitive tothe amount of air freight employed in shipping operations. In future studies onecould examine the impact of producing personal computers at one single locationrather than two distinct locations in the United States. Probably the factor thatcould have the most significant empirical impact on future studies in this area is theissue of chain shopping, making trips to traditional personal computer outlets,such as Best Buy and Circuit City, in conjunction with other passenger vehicle trav-els. Other areas that may impact the benefits of e-commerce are the employment ofhydrogen or electric cars, which would replace passenger cars, the highest singlecontributor to pollutants. These new fuel-efficient cars, the development of whichwas strongly encouraged in George W. Bush’s State of the Union address in 2003,may reduce the beneficial effects of e-commerce as observed here. The issue wouldbe the identification of the most environmentally friendly option: fuel-efficient pas-senger cars or polluting vans or trucks. Even though there are far fewer deliveryvans and trucks than passenger cars on the road, if we use hydrogen or electricityto power these major transportation vehicles, what would be the environmentalbenefits?

Our findings may also be sensitive to the type and size of item being shipped.High-volume items like books may not provide such environmentally favorableresults. In addition, we can further examine the sensitivity of our results to reducedinventory levels in specific industries enhanced by information age technologies.One can use this modeling methodology to examine many other industries inwhich e-commerce is currently being utilized or may be utilized in the future.Moreover, the scope of this project can be expanded to examine the global environ-mental impact of e-commerce for many trades, such as broadband video streamingor online banking and governmental services, and incorporate worldwide in-put–output databases that are under development. In addition, this analysis tech-


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nique can be used to examine the environmental impact of e-commerce on a regionor town, rather than specifically the United States, as was done here.

In this study, the National Science Foundation-sponsored Environmental LifeCycle software from Carnegie Mellon was employed. There is other environmentallife cycle software on the market that can be used to compare the digital economywith traditional means of doing business. One could compare the two means ofcommerce through each type of environmental life cycle software and compareand contrast the results. Furthermore, this study examined strictly B2C issues,whereas e-commerce may have even more influence in today’s B2B environment.The many environmental and energy benefits obtained from reduced supply chaininventories and efficient networking of distribution system may also be realizedwhen one examines the environmental impacts on B2B e-commerce.

If e-commerce is consistently environmentally more beneficial in other indus-tries and areas of commerce, governmental agencies may want to encouragee-commerce. Reduced sales tax or the elimination of sales taxes on e-commerceitems would further promote this type of commercial exchange by providing eco-nomic incentives. In fact, U.S. Representative Cliff Sterns and House Energy andCommerce Committee Chairman Billy Tauzin want information-based productssuch as the digital delivery of software and music to be exempt from taxes. Suchprogressive legislation will advance the future of this type of commerce and facili-tate concomitant environmental benefits.

As suggested by this study, e-commerce has proven to be very beneficial andclearly demonstrates reduction in energy consumption and the generation of po-tentially harmful pollutants. Although the increased industrialization of our worldmay foster greater consumption of power and resources, it is clearly possible thatthe digital economy has proved to be a means for our world to reduce expendituresof pollutants and energy. We are only just beginning to learn the salutary benefitsfrom intelligent and effective use of this new technology, and its beneficial applica-tions are only limited to man’s creativity and inventiveness.

ACKNOWLEDGMENT

This project was partially funded by National Science Foundation ProjectBES–9985653.

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Documents

Modeling Paradigm for the Environmental Impacts of the Digital Economy