Journal ofApplied Input-Output Analysis, Vol. 13 & 14, 2008

The development of an enterprise input output model and its application toindustrial environmental management

By

Mitsutaka MATSUMOTO* and Jun FUJIMOTO"

Abstract

In this paper, we present an enterprise input-output (EIO) model and apply it to an indus
trial environmental management. We present two versions of the model: a "micro EIO

model" describing production within an enterprise, and a "macro EIO model" describing
production across a broader range, such as in a nation. We discuss that the C02 emissions

calculated using the models provide a metrics for companies to assess environmental man
agement within the companies. We applied the model to a group of companies in the Japa
nese electronics industrial sector. We discuss the implications of the model results on thecorporate environmental management.

1

Introduction

Climate change is a major global concern that requires a multifaceted solution. Effec
tive responses to the climate change problem need to be adopted by corporations because a substantial proportion of global C02 emissions is produced by the industrial
sector, and environmental impact assessment of product manufacturing processes are
therefore necessary for improving the energy efficiency of this sector. In addition, theincreased energy used by information and communication technology (ICT) products is
becoming a concern (Huber and Mills, 1999; Kawamoto et al., 2002; METI, 2008;
Plepys, 2000). In 2006, 230 million of personal computers (PCs) were sold worldwide.
As we review in Section 2.2, energy consumption by ICT products is estimated to be 2
-8% of the total electricity used in developed countries (Huber and Mills, 1999;
Kawamoto et al., 2002; METI, 2008). Energy consumption by the ICT sector occurs
during manufacturing process, as well when the products are used. We focus on energy
flow during the manufacturing process of ICT products using the framework of the
input-output model (IO model). The IO has been traditionally used to analyze moneCenter for Service Research, National Institute of Advanced Industrial Science and Technology(AIST), Japan.
Postal address: 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan

E-mail address: matsumoto-mi@aist.go.jp*Research Center for Advanced Science & Technology, The University of Tokyo
Postal address: 4-6-1 Komaba, Meguro, Tokyo 153-8904, Japan

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Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

tary flow in nations or regions (Leontief, 1936; Isard and Kuenne, 1953; Miller, 1957).
The model has also been applied to energy flow analyses within nations (Leontief etal., 1970; Wyckoff and Roof, 1994).
The IO model described here is intended for application to the corporate level andis therefore referred to as an enterprise input-output model (EIO model), several appli
cations of which have been described previously (Albino et al., 2003; Albino et al.,2008; Grubbstrom et al., 2000; Lin and Polenske, 1998; Marangoni et al., 2004; Polenske 1997; Polenske and McMichael, 2002). Lin and Polenske, for example, applied themodel to corporate environmental management (Lin and Polenske, 1998). They discussed that we can quantify the waste disposal costs, identify factors that influence
waste generation, and evaluate alternative options to comply with regulations, using themodel. In this paper, we focus on corporate environmental management for C02 abate
ment and discuss the application of the EIO model to provide a metrics for the man
agement. We define two versions of C02 emissions of in-company sectors: the "direct
C02 emissions" representing the emissions in the sector, and the "sales-based C02
emissions" representing the emissions in the company to produce the products that are
sold externally from the sector. We discuss the usage of the sales-based C02 emissions
for corporate environmental management.
One major obstacle to effective corporate environmental management is that theorganizational structure of a company changes frequently. WTien the organizational
structure changes, for example, a manufacturing process of an in-company sector moveto other sector, if other conditions are same, C02 emissions in the sector from which aprocess moves out will decrease, and the emissions in the sector to which the process
comes in will increase. In such cases, C02 emissions of the sectors before and after themove can not be simply compared. It makes companies difficult to set C02 abatement
goal to in-company sectors and to evaluate the effectiveness of environmental manage

ment of sectors. An effective metrics to evaluate environmental management is required. In this paper, we discuss that the sales-based C02 emissions can be a metrics.

Manufacturing processes are moved not only within a company but also to outside
the company. It is called outsourcing. We formulate the "macro EIO model" which describes productions in a broader range than in a company, such as in a nation. In themodel, an enterprise is embedded explicitly in the range. We discuss that the salesbased C02 emissions calculated using a macro EIO model provide a metrics in cases inwhich a process is outsourced outside the company. An analogy is that, in international
climate change politics, an effective metrics for national C02 emissions is required. The
emissions of a country can seemingly decrease when energy intensive industries aretransferred to abroad.

We applied the models to a group of electronics companies in Japan. The groupconsists of several tens of companies and has totally several ten thousands of employ
ees. We divided the group into 10 in-company (in-group) sectors and built the EIO ta
ble for the group. Using the EIO table, we calculated the direct and sales-based CO2
emissions of the in-company sectors. We also built the macro EIO table for the groupby integrating the (micro) EIO table with the Japanese national IO table. We calculated
the sales-based CO2 emissions using the table and analyzed the breakdowns. We present the results and discuss the implications.
The present paper is organized as follows: Section 2 outlines the previous studies

The development of an enterprise input output model and its application to industrial environmental management 125

on EIO models and introduces the studies on the impact of ICT on energy consump
tion. In Section 3, formulation of the EIO model is presented. We formulate two versions ofthe model, with the former used as the IO model for individual companies andthe latter for companies that are explicitly linked to a national IO model. In Section 4,
we apply the models to the analysis of energy flow within companies. We present themathematical formulation of the sales-based C02 emissions. In Section 5, we present
the findings obtained using actual data. We applied the model and methods to a groupof Japanese electronics companies and discuss the implication of the model results on
corporate environmental management. Finally, our conclusions are presented in Section
6 and recommends future research.

2.1 Enterprise input-output model

Input-output analysis (IO analysis) is an analytical framework for economics originallydeveloped by Leontief (Leontief, 1936). The model provides a consistent method forascertaining the flows from suppliers to users within a nation. In addition to the na
tional level, considerable IO activities occur at a variety of levels; whether it is for agroup of nations, a county, or a metropolitan area. Regional IO models deal with a sin
gle region or with two or more regions and their interconnections. Examples of the ear
liest attempts of quantifying single-region IO tables can be found in (Isard and Kuenne,
1953; Miller, 1957).

Researchers in countries, such as Belgium, Italy and China, have developed enter
prise input-output (EIO) models (Albino et al., 2003; Albino et al., 2008; Grubbstrom
et al., 2000; Lin and Polenske, 1998; Marangoni et al., 2004; Polenske 1997; Polenske
and McMichael, 2002). The basic units of the EIO model are typically products andbranches within a company, which are in many cases treated in the same way as thesectors in national IO tables. EIO models were proposed to support corporate manage

ment accounting system and were used for a variety of analytical tasks in the firm.
Their applications to corporate environmental management were also proposed. In par
ticular, Lin and Polenske built a specific IO model for a steel plant, and presented themethods to investigate the energy intensity of the plant (Lin and Polenske, 1998).
Polenske and McMichael built an IO model for a cokemaking plant and assessed theeconomic and energy requirements of using alternative cokemaking technologies(Polenske and McMichael, 2002). Using a similar approach, Albino et al. have formu
lated models that analyze logistics flows in industrial clusters (Albino et al, 2008). In
this paper, we apply the EIO model to support corporate environmental management toabate the C02 emissions in companies. C02 emission abatement is a pressing issue forcompanies today. Also, we apply the methods to a group of Japanese electronics com
panies. EIO models have not been applied to recent ICT product manufacturing compa
nies nor were they used in Japanese companies.

2.2 Environmental impacts of ICT

Increased energy use by ICT products is a concern (Huber and Mills, 1999;
Kawamoto et al., 2002; METI, 2008; Plepys, 2000). In 2006, 230 millions of PCs, and1 billion of cellular phones were sold in the world. In addition, the number of servers

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Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

and wireless base-stations that support both internet and telecommunication systems

also increased. According to previous studies, ICT products consume 3 to 8% of all theelectricity in U.S. (Huber and Mills, 1999; Kawamoto et al., 2002; METI, 2008). In Ja
pan also, IT-related energy consumption has been rapidly increasing. According to theJapan Ministry of Economy, Trade and Industry (METI), 50 TWh of electricity wasused in 2006 to run all the servers and PCs in the country (METI, 2008). That repre

sents about 5 percent of all electricity use nationwide. METI estimated that ICT prod
ucts consume over 20% of electricity in 2025 (METI, 2008).

It is important to remember that energy consumption occurs during the manufac
turing process of the product, as well as when the product is used. WTiile the findingsof life cycle assessment (LCA) studies are different1, the energy use in manufacturing
processes of products is not negligible. The approaches for assessing energy use during
the manufacturing phase are categorized as two types: process-analysis assessments andnational-IO-based assessments. For the former type, energy use in the manufacturing
processes is assessed in detail, while for the latter type, national IO tables are used toestimate the total energy multipliers that describe energy per unit of consumption for
producing commodities. WTiile process-analysis-based assessments are generally moreaccurate, it is difficult to obtain all the necessary data for the analysis. Conversely, IObased-assessments use data that can be accessed with relative ease; however, the accuracy is lower. To optimize the potential associated with both approaches, a hybrid
method is frequently used (Bullard et al., 1978; Joshi, 2001). In this method, theprocess-analysis- based assessment methodology is used for the data is available, andthe IO-based assessment methodology is applied for the remaining instances when thedata is not available.

The EIO model could further complement such an assessment as the EIO model

uses data that is more readily available (company accounting data) compared to thedata that is required for process-analysis-based assessments. In addition, the EIO model

uses data that is more specific to the targeted manufacturing process than the data used
for national-IO-based assessment.

3 Enterprise input-output table
The IO tables have been formulated for a variety of levels, ranging from nations, togroups of nations, regions within nations, cities, etc. Enterprise input-output (EIO) ta
bles are IO tables that apply to a company or a group companies2, and which describe

Energy use in manufacturing phase has been analyzed in LCA studies. However, the assessed results

are divisive. Tekawa et al., for example, reported that the ratio of energy use in manufacturing phaseand usage phase is 2:8 in the case of desktop PC (Tekawa et al., 1997). Williams reported the ratio is8:2. The difference largely comes from the estimate for energy consumption in semi-conductor material manufacturing process (Williams, 2003). The process is placed in chemical industry sector in na
tional IO table and not in electronics industry sector.

Although the focus of EIO model is "a company", it could be "a group of companies".

The development of an enterprise input output model and its application to industrial environmental management

127

the flow of commodities within a company. We represent this flow using monetary
units because the national IO tables usually use monetary units and we incorporate EIO
tables with the national IO tables.

We formulate two versions of EIO tables: one is what we refer to as a "micro EIO

table", and the other is a "macro EIO table". A micro EIO table is analogous to a na
tional IO table. It contains the IO data for a specific company. A macro EIO table isanalogous to a multi-regional IO table. It represents IO data for a nation and is com
prised of both company and national data from which the company data is excluded.
Such a table is formulated by integrating a micro EIO table and a national IO table.

3.1 Micro EIO table

Micro EIO tables are analogous to national or single-region IO tables. We divide acompany into sectors and products manufactured by each intra-company (in-company
hereinafter) sector are regarded as distinct products. It is a general assumption in IO ta
bles.

Table 1 shows the outline of a typical micro EIO table. The table consists of fol
lowing components.

\Si, ..., Sn\ set, in-company sectors;\P,, ..., Pn\ set, products of in-company sectors;\Ei, ..., Em\ set, externally procured products;\VAi, ..., VAq\ set, primary inputs;
X matrix, intermediate inputs of in-company produced products;
Xy, input of product P, in sector Sj
Y matrix, inputs of externally procured products;
Yy, input of product Et in sector 5,
V matrix, primary inputs;

Vy , input of primary input VAi in sector Sj
T vector, total outputs;

T , total output (production) of sector S,
IV vector, investment;

IV! , investment of product P, in the company
IV- , investment of product £, in the company
EX vector, external sales of products;
EXi, external sales of product P, from the company
IM vector, external procurement;

IMi, external procurement of product £, of the company

To illustrate the model, consider a hypothetical computer equipment company thatsells 50 million dollars of hard disk drive (HDD) and 100 million dollars of computera year, as shown in Table 2.

Each column of Table 2 provides information on the inputs used and outputs gen
erated in each in-company sector. The inputs include those produced by the company,

those purchased externally, and primary inputs (such as labor, capital, and land). We
use the computer sector (column 2) as an example. To produce 100 million dollars of128

Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

computers, the sector used 50 million dollars of HDD, 10 million dollars of parts and
20 million dollars of energy, and required 10 million dollars of capital and 10 million
dollars of labor wages. Consumption of 20 million dollars of energy produced 40 thousand tons of C02.

When each element in a column of Table 2 is divided by the total output of thesector, we obtain the input or technical coefficients matrix. Each coefficient shows theamount of input required for each unit of output.
Mathematically, the input coefficients are obtained asay = XylTi

ay=Yy/Ti.

(1)

Each row in the table describes the use of a commodity or input. For example, thefirst row (Hard Disk row) of Table 2 shows that 100 million dollars of HDD were pro

duced by the corporation, of which 50 million dollars were used in the production ofcomputers and the remaining 50 million dollars were sold to external customers. The
forth row (Energy row) indicates the energy-use pattern in the company: 30 million
dollars used for HDD producing and 20 million dollars in the computer producing op
erations. The total energy input was 50 million dollars a year.
The row of the input-output table, therefore, provides a statistical account of input-output flows in the corporation. These flows must be balanced, as follows:
Xi, + Xi2 +...+ Xin + IV? + EXi = Ti

Yu + Yi2 +...+ Yin + IVt - IMi = 0(2)Table 1: Structure of micro enterprise input-output tables
In-Company Sectors
Invest-ment

Products ofIn-

Company

External

External

Total

sales

procurement

Output

Si

S2

Pi

Xu

X12

Xijn

IV!

EXi

0

Ti

P2

X21

X22

X2M

m

EX2

0

T2

Pj

X31

X.u

X3.„

m

EXj

0

T3

m

EXn

0

Sectors

Pn
External

Ei

Yu

Yn

Yu

-IMi

Procure

E2

Y21

Y22

Yu

-IM2

ment

Em

Primary
Inputs

Total

Output

Ym,2

/K

VA,

Vu

Vt2

Vu

VAq

Vq,i

Vq.2

Vq,n

Ti

T2

-IMm

The development of an enterprise input output model and itsapplication to industrial environmental management

129

Table 2: Micro enterprise input-output table: hypothetical hard disk drive(HDD) and computer company(unit: million dollars)
HDD

ComputerInvest-External

ProcureSector

Sector

ment

Sales

ment

Output

HDD

0

50

0

50

0

100

Computer

0

0

0

100

0

100

Parts

50

10

0

0

-60

0

0

0

-50

0

Energy

30

20

(C02)

(60K ton)(40K ton)

Capital

10

10

Labor

10

10

Output100

100

In matrix notation, it is expressed as follows:
AT + F -M = T(3)

T = (I -AY\F - M)

(4)

Or,

where,

Ti

T =

T„

,A =

All

•• al 0 • • 0/Vf + EX^0an

- al 0 ; • 0

m

+ ex.

0

m

+ ex„

al\ ' •• al 0 • • 0

F =

,M =

0

0

a\\ ' •• a\n 0

• ••

0

/Vf

/M,

0

aem\ ' •* amn 0

*•• 0

iv:

Mm

(5)

The formula (4) clarifies the relationship between total outputs (T,, T2, ...) and final demands (/Vf + EX,, /Vf + EXi, ...)•
3.2 Macro EIO table

Macro EIO tables are analogous to multi-regional IO tables which deal with two or

more regions and their interconnections' and are formulated by integrating a micro EIO

table and a national IO table. The boundary associated with a macro EIO table is sameas that of national IO table in that it covers an entire nation. In an EIO table, the com

pany and the rest of the nation are explicitly distinguished. Table 3 outlines the structure ofa macro EIO table. In Table 3, the column "Company" under "Intermediate De
mand" is identical to the data in the micro EIO table compiled for the company. The
3 Multi-regional IO tables were proposed by Isard in 1951.

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Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

Table 3: Structure of macro enterprise input-output tables
Intermediate Demand
NationExportNation(besides thecompany)

Consumption

In-company

Domestic

Domestic

Foreignproduct flow

sales (1)sales (2)sales(National IO)(National IO)(National IO)

Company

Company

Final Demand

NationProcurement(besides the company)

for production

Investment +ImportTotal

OutputPrimary
Inputs
Total

Outputrow "Company" in Table 3 contains more information than the data shown in the mi
cro EIO table. The cells "Domestic sales (1)", "Domestic sales (2)" and "Foreign
sales" in Table 3 specify which sectors the company sells its products to, but these are
not specified in the micro EIO. The cells in the "National IO" column in Table 3 are
populated with values derived from the data of the national IO table.
The mathematical expressions for the macro EIO tables are the same as those em
ployed for micro EIO tables. The matrix A has more columns and rows because it also

contains the columns and rows that correspond to the sectors and products of "Nation".
Similarly, vectors T, M and F have more elements. The elements of F are the sum of

the values for the columns of "Company", "Nation" and "Export" under "Final De
mand" in Table 3.

4 Enterprise input-output analyses
4.1 Micro EIO analysis
4.1.1 Direct C02 emissions and sales-based C02 emissions

We define two types of C02 emissions in in-company sectors: direct C02 emissions andsales-based C02 emissions. Both emissions can be calculated using an EIO table. We
discuss the application of the analysis to corporate environmental management.
One of the difficulties in corporate environmental management is that the organ
izational structure of a company changes frequently. When the organizational structurechanges, the C02 emissions of the in-company sectors before and after the change can
not be simply compared. This makes it difficult for companies to set C02 abatement
goals for in-company sectors and to evaluate the effectiveness of environmental man
agement of the sectors by comparing the emission amounts at different times. In otherwords, an effective metrics for comparison or evaluation is needed. We define the sales-based C02 emissions and insist that they can be used as a metrics.

The sales-based C02 emissions of an in-company sector are defined as: theThe development of an enterprise input output model and its application to industrial environmental management

131

amount of C02 emissions induced by energy use in the company to produce productsthat are sold externally from the sector. Figure 1 illustrates the company of Table 2.
Suppose that the company emits 100 thousand ton of C02 a year and that the direct
C02 emission of hard disk drive (HDD) sector and computer sector are 60 thousand
tons and 40 thousand tons, respectively. Table 2 and Figure 1 show that a half of HDD
produced in HDD sector is for external sales and that another half is used by the com
puter sector as intermediate input. We regard that a half of the direct C02 emissions in
HDD sector are the sales-based C02 emissions of computer sector. Consequently, thesales-based C02 emissions of HDD sector are 30 thousand tons and those for computer
sector are 70 (= 40+60/2) thousand tons.

Figure 2 shows an example of organizational restructuring from Figure 1. For sim
plicity, suppose that the company has two HDD manufacturing factories, and that one

Figure 1: Illustration of the direct and sales-based C02 emissions
External sales

External sales

HDD
SectorComputer

OutputDirect CO:emissions

Input

SectorSales-based

OBEXES'

C02 emissions

Figure 2: An example oforganizational restructuring (from Figure 1)
External sales

External sales

Comforter
As%kszi-S'

1#-'••-,• •'-• • •'•OutputDirect CO,emissions

Input
HDD
SectorSales-based
CO, emissions'^ZZZZ
5M^t>Computer
Sector*7ftKt^F~

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Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

factory (factory A) manufactures HDD for external sales and the other factory (factoryB) manufactures HDD for computer sector. While in Figure 1, both factories belong to
HDD sector, as the result of organizational restructuring, in Figure 2, factory B belongs

to computer sector. As the result of the restructuring, while the direct C02 emissions of
the sectors change (in Figure 1, 60 thousand ton and 40 thousand ton for HDD andcomputer sectors, respectively; in Figure 2, 30 thousand ton and 70 thousand ton for
HDD and computer sectors, respectively), the sales-based C02 emissions do not change(both in Figure 1 and 2, 30 thousand ton for HDD sector and 70 thousand ton forcomputer sector).
It indicates that the sales-based C02 emissions can be used as a metrics to com

pare the C02 impacts of the in-company sectors at different times and, accordingly, toevaluate the environmental management of the sectors. The mathematical formulationof the sales-based C02 emissions and a numerical example are presented in next sec
tions.

4.1.2 Mathematical formulation of sales-based C02 emissions

Sales-based C02 emissions can be calculated using micro EIO tables. In addition to thedefinitions in (3) in 3.1, we define T, F' and e as follows:

r

=

r,

o

••

0

0

... 0

F, 0

0

0

• • 0

0

r2 ••

0

0

... 0

0

F2

0

0

• • 0

0

o

T„ 0

... 0
... 0

••

0

o

••

0

0

0

o

••

0

0

,Fl =

0

0

Fo 0

• • 0

0

0

0

0

• • 0

0

0

0

0

• • 0

e = (ex e2 ••• en +m)(6)where et is the C02 coefficient of the / th commodity (goods), which is nonzero for energy goods such as oil, and represents the C02 emissions associated with the unit inputof the energy goods (ton-C02 per dollar).

The direct C02 emissions of in-company sectors can be calculated using the expressioneAT(7)

while the sales-based C02 emissions of in-company sectors are calculated using

eiJ-AVF1(8)The sales-based C02 emissions of a sector are comprised of the direct emissions

in the sector and indirect emissions in other sectors. In Figure 1, for example, the sales-based C02 emissions of the computer sector (70 thousand ton) are comprised of thedirect emissions in the sector (40 thousand ton) and indirect emissions (30 thousand
ton) which were directly made in HDD sector. The direct C02 emissions in sales-based

C02 emissions (intersection of the direct C02 and the sales-based C02) can be calcu-

The development of an enterprise input output model and its application to industrial environmental management 133
lated using
eAF1

(9)

4.1.3 Numerical example

We present the numerical examples of EIO analysis for the example company of Fig
ure 1 (Table 2) and Figure 2. The EIO matrix and vectors for the company of Figure 1(Table 2) are as follows.

0 0.5 0 0"
A =

0

0

0 0

,F =

0.3 0.2 0 0' 50 "

' 0"

100

0

0

0.5 0.1 0 0.

,M =

"100"
100

50

,7- =

.60

0

(10)

0
0

We assume that the third row in the table represents energy goods such as oil andthat its C02 coefficient is 2 (thousand ton-C02 per million dollar). The other products
do not emit C02 directly and their C02 coefficients are 0. Accordingly, vector e is:
e = (0 0 2 0)

(id

From the description in (7), we can obtain the following

AT' =

0

50

1

0.5

0

0

0

0

0

1

0

0

30

20

0.3 0.35

1

0

50

10

0.5 0.35

01(7-A)-'F' =(I-AT' =

50

50

0

0

0

100 0

0

15

35

0

0

25

35

0

0

(12)
From these, we obtain

eAF = (60 40 0 0), e(I - A)-]F' = (30 70 0 0),(13)

and eAF' = (30 40 0 0)

Direct C02 emissions of the sectors are 60 and 40 thousand tons, respectively, andthe sales-based C02 emissions are 30 and 70 thousand tons, respectively. The direct
C02 in the sales-based CO2 emissions are 30 and 40 thousand tons, respectively.
Next, we calculate the CO2 emissions for the company of Figure 2 — an organ
izational restructuring was made from Figure 1. The EIO matrix and vectors are

A =

0

000"

0

0

0

0

0.3 0.35 0 0,F =0.5 0.35 0 0.
The calculation results are:' 50 "

"0 "

100

0

,M =

0

50

0

60.

' 50 "
,T =

100
0

0J

(14)

134 Journal ofApplied Input-Output Analysis, Vol. 13 & 14, 2008

Mr = (30 70 0 0),e(/-A)-'F' = (30 70 0 0),

and eAF1 = (30 70 0 0)

(15)

While the direct C02 emissions changed as the result of the restructuring, the sales-based C02 emissions did not change. Production of HDD for external sales induced
30 thousand ton of C02 emissions to the company (sales-based C02) and production ofcomputers induced 70 thousand ton of the C02 emissions to the company.
4.2 Macro Enterprise Input-Output Analysis
4.2.1 Macro EIO analysis

The macro EIO table describes the productions in wider range such as in a nation, andin the model, a company (micro EIO table) is embedded explicitly in the range. Using
the macro EIO, not only the C02 emissions within the company but also the emissions
in their upstream industries outside the company are analyzed. For example, if a com
puter manufacturing company procures parts from other company (upstream company),
the C02 emissions to produce the parts are counted. We call the sales-based C02 emis
sions including the emissions in upstream industries as "the macro sales-based C02
emissions". In analysis, we use formula (6) using the macro EIO values instead of mi
cro EIO values.

We propose two applications of the macro sales-based C02 emissions to corporate
environmental management. One application is, again, to use as a metrics. Suppose thata company outsources a process to other company. By outsourcing a process, the C02
emissions in the company also decrease. However, as the macro sales-based C02 emis

sions include both the emissions within a company and those in upstream companies,
the C02 impacts before and after the outsourcing can be compared by using the macrosales-based C02 emissions. If the C02 efficiency for the process in the company is bet
ter than that in outside the company, the macro sales-based C02 emissions will increase(the metrics gets worse).

Another application is analysis of the ratio of C02 emissions for product manufac
turing. By calculating the macro sales-based C02 emissions, and the direct and sales-

based C02 emissions using the micro EIO model, we can compare: 1) the direct C02
emissions in in-company sector which sells the products, 2) C02 emissions in other incompany sectors to produce the products, and 3) C02 emissions outside the company(in upstream company). From the analysis, implications for an effective corporate envi
ronmental management are available. For example, if the direct C02 emissions in the in-company sectors are relatively large, energy efficiency improvement in the sector issubstantial. Or, if the C02 emissions in upstream company are relatively large, green
procurement is effective to abate C02 impacts.
4.2.2 Mathematical formulation

The macro sales-based C02 emissions of in-company sectors are calculated using fol
lowing expression.

ed-BYF1(16)

where B is the input coefficient matrix for the macro EIO table, and e, F and F1 are

The development of an enterprise input output model and its application to industrial environmental management 135

the same as in the micro EIO analysis (e is the C02 coefficient vector, F is the external sales vector).

The C02 emission ratio is analyzed by comparing, 1) the macro sales-base C02
emissions which are calculated by the above formula, 2) the C02 emissions within thecompany total which are calculated by formula (8), and 3) the C02 emissions within
the in-company sectors which are calculated by formula (9).
4.2.3 Numerical Example

Table 4 presents an example macro EIO table for the company ofFigure 1.
We apply the formula (6) using the following matrix and vectors:

B =

0

0.5

0

0.01

0.005 "

0

0

0

0.01

0.005

0

0

0

0

0

r 50
100

,F =

0.25

0

0.5 0.1

0.45

0

0.5 0.14,e = (00200)

0

0.3 0.2 0.3 0.05

(17)

We obtain the macro sales-based C02 emissions of the in-company sectors as follows.

e(I - BT'F1 = (60.8 117.2 0 0 0)

(18)

In the macro EIO table (Table 4), we assumed that the C02 efficiencies in the in-company HDD sector and the external HDD sector are identical. Suppose that the com
pany outsources the production of HDD which are used in computer sector to an external HDD company, the coefficient matrix becomes as follows.

Table 4: Example of macro EIO table(unit: million dollars)Intermediate Input

Company
HDD

CompNation
En

HDD

any

HDD

Comp

NationOther

Invest

ergy

uter

Comp

Final Demand
Im

Consu

Exp

mption

ort

port

Total

Ext

Out

ernal

put

Sales

0

50

0

10

10

0

30

0

0

100

50

0

0

0

10

10

0

80

0

0

100

100

0

0

0

0

0

0

200

0

0

200

30

20

60

50

500

0

400

0

0

1000

0

900

0

0

2000

uter

HDD
En

Nation

ergy

Other

50

10

100

140

900

Primary Inputs

20

20

40

790

580

Total Output

100

100

200

1000

2000

136

Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

Table 5: Energy flow analysis using macro EIO(unit: thousand ton)

Before outsourcing

Macro sales-based C02 emissions(thousand ton)

After outsourcing

HDD

Computer

HDD

Computer

60.8

117.2

60.8

117.2

40

30

40

C02 in the sector

30

C02 in other in-company sector

0

30

0

0

C02 in outside the company

30.8

47.2

30.8

77.2

Direct C02 emissions

60

40

30

40

B'=

0

0

0

0.01

0.005

0

0

0

0.01

0.005

0

0.5

0

0

0

0.3 0.2 0.3 0.05

0.25

0.5 0.1

0.45

0.5 0.14(19)

The macro sales-based C02 emissions obtained are same as those before the out
sourcing.

We calculated the C02 emissions in in-company sectors and in company total in Sec
tion 4.1.3. The ratio of the C02 emissions of the company of Table 5 is summarized inTable 6.

4.2.4 Application to Life Cycle Assessment (LCA)

The idea ofmacro sales-based C02 emissions has a common with life cycle assessment(LCA) and with carbon footprints. They differ in the boundaries for assessments. LCA

counts the environmental (C02) impacts in production, distribution, usage, and end-oflife phases of products. Carbon footprint generally counts the C02 impacts until the
point ofconsumer's receiving products (production and distribution phases). The macrosales-based C02 emissions count the C02 impacts until the point of products' going out
the company. Accordingly, the macro sales-based CO, emissions consists a part ofLCA

and carbon footprints. In LCA studies, C02 impacts are investigated by process analy
sis, and when process analysis data is not available, data is supplemented by national
IO-based IO analysis (Bullard et al., 1978; Joshi, 2001). As an EIO model contains

company-specific energy flow data, the EIO analysis provides an easy and more precise C02 impact assessment method.

5 EIO model applied to group of Japanese electronics companies
5.1 EIO Table

5.1.1 EIO Table Construction

We applied the model to a group of Japanese electronics companies. The group in-

The development of an enterprise input output model and its application to industrial environmental management 137

eluded thirty companies with a total of fifty thousands of employees. The companies
produce electronic devices, information and communication technology (ICT) hardwareand ICT services. Using corporate accounting data for fiscal year (FY) 2001, we gener
ated an EIO table for the group. The total sales of the group in the year were 25.5 billion U.S. dollars (2.55 trillion Japanese Yen).

The accounting data records documented the data on: 1) the products and ex
penses that each division procured from inside and outside the group (the products
were categorized into approximately two thousand categories), 2) the products andrevenues that each division sold to inside and outside the group, and 3) each division's
expenses on wages, facility depreciation, and land rents.

We defined the table components that we specified in section 3.1 as follows.

0 In-company sectors {Si}: The group includes 20 business divisions operating during
FY 2001. The divisions correspond to 10 sectors represented in the Japanese na
tional IO table (categorization of the divisions was more refined than that of thenational IO table). We reclassified the business divisions to be consistent with the

10 sectors. The 10 in-company sectors represent three electronic device production
sectors: 1) semiconductor devices, 2) electronic devices, and 3) display devices;four ICT hardware sectors: 4) computers, 5) radio communication equipment, 6)
wired communication equipment, and 7) computer accessory equipment; and three
ICT service sectors: 8) information service, 9) telecommunication service, and 10)
software service. In addition, the companies all have headquarters-divisions andthe monetary flows within these divisions are considerable. In the table, instead ofdefining each of the divisions as an independent in-company sector, the divisions'monetary flows were allocated to the 10 in-company sectors in proportional to division sales.

e Products {Pi}: We defined the products that are produced in sector S, as Pi. Using thisdefinition for P„ by-products do not appear in the table. Different divisions within
the group rarely sell identical products. Consequently, a one-to-one correspon
dence between sector and product does not cause problems.

° Externally procured products {£,}: Using the accounting data, products procured
from outside the group were categorized into approximately two thousand catego
ries. We aggregated the categories and aligned them with those in the Japanese na
tional IO table (the national table has approximately 500 products in total). The

products procured by the group from external sources FY 2001 were categorized
into 63 product types.

• Intermediate inputs of in-company produced products {X}: Accounting records docu
ment trades within the group. Based on the records, we can determine the internal
inputs {Xy}.

• Inputs of externally procured products {Yy} and external procurements {Mi}: Ac
counting data records document external procurements. The inputs of externallyprocured products {Yy} and {/M,} were set based on the accounting records.
• Investment {TVi}: The accounting data records did not contain data for large invest-

4 In real world scenarios, energy use for such construction of new plants should also be considered incorporate energy analyses.

138 Journal of Applied Input-Output Analysis, Vol. 13 & 14, 2008

ments such as expenses for new plant construction. Therefore, in the table, we set
the values for IV? and IV? as zero4• External sales {EXy} and total outputs {Ti}: The accounting data records document
external sales of products for each sectors (EXy). By adding the amount of trade
within the group (Xy) to the external sales amount, we determine the total sector
output (Ti).

• Primary inputs {VAy}: The accounting data records document labor wages, facility
depreciation, and land rents for the companies. We set the amounts as VAy.
• C02 coefficient vector e : For fossil fuel (oil and gas) use and electricity, we apply a
non-zero C02 coefficient vector e. Although electricity is technically not a C02

emitting commodity (because C02 is directly emitted by the electricity generationindustry and not by the companies that use the electricity), as most companies determine their C02 emissions based on their fossil fuel consumption and electricity

use, we treated electricity as a direct C02 emitting commodity. We set the C02 co
efficient for oil, gas, and electricity in FY 2001 as 10.4, 2.9 and 3.5 kg-C02 perdollar, respectively, based on the C02 intensities of the energies and the prices inthe year.
5.1.2 EIO Table Overview

Table 6 shows the micro EIO table for the group.

The total external sales of the group were 25.5 billion U.S. dollars. The threelarge sectors in terms of external sales were: 1) radio communication equipment sector(23% of the group total), 2) computer sector (23% of the group total), and 3) semicon
ductor device sector (18% of the group total).
The total output of the group was amounted to 42.7 billion dollars. The total out
put is equivalent to the sum of external sales and intra-group sales. The ratio of external sales to intra-group sales was 3:2 (25.5 and 17.2 billion dollars, respectively),
which indicates 40% of the group output was used within group (40% was intermedi
ate commodities in the group).
The total output is also equivalent to the sum of intra-group procurement (= intragroup sales), external procurement, and the value added. The share of the three items
was 40:32:28. The external procurement and the value added were 13.5 and 12.0 bil
lion dollars, respectively.
The C02 emissions of the group were calculated as 502 thousand ton-C02. The direct C02 emissions of the sectors calculated with formula (7) are shown in the table. In
the group, the semiconductor device sector was the most energy consuming sector. The
sector emitted over 60% of the group total C02 emissions.

5.2 Micro EIO analysis
Based on the micro EIO analysis framework described in Section 4.1, we calculated
the sales-based C02 emissions for the 10 in-company sectors. We calculated the direct
and sales-based C02 emissions for the 10 in-company sectors. As shown in Figure 1,
the sectors whose sales-based C02 emissions are greater than direct C02 emissions aredownstream sectors in terms of C02 flows (the "computer" sector in the example), andvice versa. If the differences between the two emissions total is large, the interdepend-Table 6: Micro EIO table(Unit: million U.S. dollars (1 dollar = 100 Japanese Yen))
In-•company sectors

Sub

InvestExternal

External

Total

A10

total

ment

sales

procure.

output

0

4

3204

4511

7715

2

0

0

54

175

230

1

0

0

0

137

587

734

125

257

964

238

4

5009

5773

10782

Al

A2

A3

A4

A5

A6

A7

A8

A9

1 Semiconductor

2450

98

300

131

128

84

7

2

2 Electronic device

12

19

7

6

6

2

1

3 Display device

74

51

0

4

5

1

4 Computers

54

4

5

3169

189

5 Wired comm. eq.

73

4

6

218

2924

767

22

78

15

2

4110

in-company 6 Radio comm. eq.

23

1

1

93

310

708

9

21

3

2

1171

5802

6973

7 Computer acces.

3

0

0

351

13

7

17

84

13

0

488

760

1248

8 Information serv.

61

4

6

1068

96

78

118

839

182

9

2461

2791

5253

9 Telecomm. serv.

36

2

4

125

75

61

14

73

73

1

464

594

1058

10 Software

20

3

2

9

10

10

3

5

1

2

66

24

Products ofsectors

Total Internal Proc

External

procurement

4475

8585

0

Total:

0

25502

90
Total:

Material (*i)

482

8

8

274

161

99

64

58

13

5

1172

Parts (*2)

1198

44

254

1226

892

2429

194

151

15

6

6409

-6409

Services (*3)

138

8

8

449

1109

622

58

853

43

14

3302

-3302

5.0

0.02

0.05

1.9

1.2

0.5

0.2

1.0

0.1

0.01

10

Others (*4)
Oil

0

0

-2516

Gas

7.5

0.3

0.2

0.9

1.5

0.8

0.1

0.4

0.08

0.4

12

-12

70.1

1.5

1.3

10.0

9.6

5.7

1.4

6.9

2.3

2.1

111

-111

(C02 (K-ton-C02))

(316)

(6)

(5)

(57)

(50)

(27)

(7)

(36)

(10)

(8)

(502)

Total External Proc.

2052

67

292

3204

2583

3390

461

1308

138

35

13531

2858

-26

111

2399

2247

1741

339

1876

395

29

11971

:

0

-10

Electricity

Value added

42668

-1172

Total:-13531

Total Output

Al: Semiconductor device, A2: Electronic device, A3: Display device, A4: Computers, A5: Wired communication equipment,
A6: Radio communication equipment, A7: Computer accessory equipment, A8: Information service, A9: Telecommunication service, A10: Software*1: Material products (total of 32 type products); *2: Parts products (12 type products); *3: Services (7 types); *4: Other products (9 type products)u>VO140 Journal ofApplied Input-Output Analysis, Vol. 13 & 14, 2008

Figure 3: Sales-based C02 emissions, direct C02 emissions, and external sales often sectors (% in group total);

The numbers are the ratio of the sales-based C02 to the direct C02 emissions(sales-based C02 emissions / direct C02 emissions)'h****** **<*M''

Semiconductor

Device.; Electronic device

sectors1

JE3 3.7

Display device m

1

0.9

><>

2.0
1.6

Computers
iifSr*~+x?*~> •^^rrsjs-y'^i

Wired comm. eq.

^P 1.2

H

Hardware -N'

f**V-&K«*'«3 . >• -tRadio comm. eq.
Computer acces.

1.0

111
H Sales-based C02

pJS^SsfesdL.

0.9

Information srv.

Software <Tl(Sales-based CO 2/Direct CO2

f^ki'si^i >--U

sectors'1

Telecom, srv.

&0.9

Software

P °'3

D Direct C02• External sales

sectors

10

p

b

J

&

1?J

\7

20

30

40

50

60

70

(% in group total)

encies among in-company sectors is greater.
Figure 3 shows the sales-based C02 emissions, the direct C02 emissions, and theexternal sales, for each of the 10 sectors. The amounts are presented as the shares (%)
in the group. The numbers in Figure 3 show the ratio of the sales-based COs emissions
to direct C02 emissions of the sectors.

In the group, the sectors — electronic device, display device, and the four hardware sectors were in the downstream. The interdependencies of the electronic device,display device and software service sectors to other sectors were high. In the case ofelectronic device and display device sectors, they used devices produced in the semi
conductor device sector. In such cases, the two sectors might be better to support abat
ing C02 emissions at the semiconductor sector (the upstream sector) rather than tomake efforts to abate direct C02 emissions in the own sector, in order to abate the total
C02 emissions in the group.
As we discussed in Section 4.1, the sales-based C02 emissions can be used as a

metrics to set up intra-company environmental management goals or to evaluate the incompany sectors' environmental management performance. Even if organizational restructuring is undertaken within the group, the C02 impacts of in-company sectors, or
those of their externally sold products, can be compared using the metrics for before
and after the reorganization.

5.3 Macro EIO analysis
We generated a macro EIO table for the group by integrating the micro EIO table with

http://www.stat.go.jp/english/data/io/index.htm

The development of an enterprise input output model and its application to industrial environmental management 141
Figure 4: Breakdown of the macro sales-based C02 emissions
H C02 in the sector

11 C02 in other in-company sectors
D CQ2 outside the group
Semiconductor

DeviceElectronic device

sectors

Display device

Computers

Wired comm. eq.
Hardwaresectors

Radio comm. eq.
Computer acces.
Information srv.

SoftwareTelecom, srv.

sectors

Software00%

the Japanese national IO table5. The group represented approximately 0.3% of the na
tional economy based on total output.
We calculated the macro sales-based C02 emissions of the in-company sectors.
The macro sales-based C02 emissions of an in-company sector are the amount of C02
emissions caused by production of products or services that are sold externally fromthe sector (see Section 4.2 and Table 4). We analyzed the ratio of emissions within the
sector itself, for other in-company sectors, and for companies outside the group.
Figure 4 shows the ratio results for the sectors. In the device sectors, the C02
emissions generated within the sectors made up a relatively large share (more than
30% in semiconductor device sector). In contrast, for hardware sectors, around 90% of

the sales-based C02 were attributed to outside the group. Similarly, around 80% of thesales-based C02 emissions from the software sectors were attributed to the productionof the externally procured products.
The results have implications for corporate environmental management. To abate
C02 impacts from sector products in semiconductor device sector, for example, efforts
to further improve the energy efficiency within the sector are important ("C02 in the
sector" was large). For electronic device sector, energy efficiency improvement in up
stream sector (semiconductor device sector) is important ("C02 in other in-company
sectors" was large). In hardware and software sectors, C02 abatement in upstream com
panies outside the group or procurement of less-C02 intensive products (green procurements) would be more effective in reducing C02 impacts ("C02 outside the group" waslarge).

6

Conclusions and future work

In the present study, we formulated micro EIO and macro EIO models. We proposed

142

Journal ofApplied Input-Output Analysis, Vol. 13 & 14, 2008

the calculation of sales-based C02 emissions for in-company sectors (products) using
the models. The emissions contributions can be used as metrics for evaluating in-company sectors' environmental management even if organizational restructuring oc
curs within the company. In addition, the breakdown of the C02 impacts of the incompany sectors —the ratios of C02 caused by production within the sector, by pro
duction in other upstream in-company sectors, and by production outside the company— are analyzed using the methods. EIO models could improve the accuracies of prod
uct life cycle assessments (LCAs). In previous LCAs, national IO tables have beenused when process C02 analysis data for a company is not available. Using EIO tables
instead of national IO tables enables analyses that are more accurate because EIO ta
bles contain company-specific data.
In the current study, we applied the EIO models to a group of electronics compa

nies in Japan. EIO models have not previously been applied to electronics companies,
not to Japanese companies. We described the outline of the EIO table and presented
the results of the sales-based C02 emissions calculation. The analysis revealed C02

flows within the group and interdependencies among the in-company sectors in termsof C02 emissions. However, the EIO table could only be generated for one fiscal year

in the current study. In the future, we will apply our model to generate tables for dif
ferent years. Changes in the prices of electronics products could affect the input coeffi
cient values. A comparison of years would insure the stability of input coefficients.
We also analyzed the (macro) sales-based C02 emissions of the in-company sec
tors (Figure 4) by source. The group procured materials and parts from other compa
nies, while the main processes of the group were device processing and product assem
bly. Therefore, a large amount of C02 emissions was generated by upstream production. To abate the group's C02 impacts, cooperation with such companies is necessary.
Environmentally sustainable manufacturing industries require various levels of pol
lution control measures, associated with product design, manufacturing, corporate man
agement, governmental policy, and international policy. To plan for and evaluate control measures, a framework for consistently modeling the various levels is needed; theEIO model provides a framework for modeling monetary/material/C02 flow at both thein-company sector and national levels. In the current study, we applied the model toC02 flow analyses. However, the model could also be applied to material flow analy
ses. In electronics industries, for example, material flow analyses are gaining more at
tentions as legislative efforts restrict chemical and hazardous substances. Our goal is toextend the applicability of the EIO model and to develop a more integrated frameworkfor supporting corporate environmental management.

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