DOC
CUMEN
NTATION OF L
LCWE DATA IN GAB
BI
1
INTRO
ODUCTION
N
Sustainability is an
n increasing
gly used ex pression an
nd many prroducts are marketed as
a being
sustaina
able. The definition
d
off sustainab
bility include
es ecologic
cal, econom
mic and als
so social
aspectss, as prese
ented in Fiigure 1. Cu
urrently, fo
or example carbon foootprints are highly
discussed and therrefore envirronmental a
and also eco
onomic proffiles of prodducts, but es
specially
the soccial aspectss are often
n largely n
neglected. The challe
enge for coonducting a social
e is the nee
assessm
ment along the comple
ete life cycle
ed of plenty
y – so far nnot acquired
d – data.
This situ
uation is co
omparable to
t the effortts that had to be done at the beg inning of Life Cycle
Assessm
ment itself in
i the 1980s
s.
Figure 1: Sustaiinability: Integration of ecologic, econo
omic, soccial and te
echnical
dimens
sion in a so
oftware an d database
e system
e employedd to gather socially
In order to fill thesse existing gaps, stattistical sourrces can be
e University of Stuttgarrt, Chair of Building Ph
hysics (LBP
P), Dept. Life Cycle
relevantt data. The
Enginee
ering (GaBii) develope
ed the meth
hod of Life Cycle Worrking Enviroonment (LC
CWE) to
integratte social asspects into Life Cycle Assessme
ent (LCA). In applyingg this method, high
quality p
process-spe
ecific data concerning
c
social aspe
ects for use in product LCA is obta
ained by
using sttatistical sou
urces. The following asspects are covered:
c
Page 1 / 15
•
A
Amount and
d qualification level of w
work
•
Health and safety.
phs will doc
cument the method tha
at was applied to geneerate sociall profiles
The nexxt paragrap
for all unit processe
es in the Ga
aBi databasse.
2
SELEC
CTION CR
RITERIA FO
OR INDICA
ATORS
When thinking abo
out social effects,
e
one
e of the firs
st questions
s to considder is which
h criteria
should be measured and which
w
indica
ators should be emp
ployed to ddescribe the social
implicattions of a hu
uman action
n. For the m
method desc
cribed here, the objectiive was to integrate
Engineering
social a
assessmentt into the already
a
exissting metho
odology of Life
L Cycle E
g (LCE).
That im
mposes som
me restrictio
ons upon tthe choice of indicators. Therefoore, the critteria the
employe
ed indicatorrs have to comply
c
with are describ
bed in the fo
ollowing.
2.1
Relevance
e and Con
nsensus
The soccial goals sh
hould have an actual re
elevance and a broad internationaal consensu
us. They
should iif necessaryy allow for the inclusion
n of other societal or cu
ultural valuees.
2.2
Impartialitty
The indicators and their ascerrtainment sh
hould be im
mpartial and revisable.
2.3
C
Completeness and attributab
bility
1.
A
All relevant goals shou
uld be addre
essed.
2.
T
The indicato
or should co
over the resspective social goal co
omprehensivvely.
3.
T
The indicattor should be
b clearly a
and complettely attributable to the respective product
or proce
ess.
2.4
Q
Quantitatiiveness
The ind
dicator shou
uld compris
se a quantittative meas
sure in order to be agggregated over
o
the
whole life cycle.
2.5
Pertinenc
ce of indica
ator sum
The sum
m of the indicator valu
ues of all p
processes of
o one site, company, industrial sector
s
or
country should acccurately des
scribe the ovverall situattion.
Page 2 / 15
2.6
No Overla
ap
There sshould be no
n overlap between th
he different indicators to avoid doouble counting and
thereforre overvalua
ation of sing
gle effects.
2.7
C
Comparab
bility of targets and
d indicatorrs
1.
T
The goals and
a indicato
ors should b
be compara
able in an international context.
2.
T
The goals and
a indicato
ors should b
be compara
able between different iindustries.
2.8
Product/P
Process-re
elatedness
s
The goa
als and ind
dicators sho
ould have a direct rela
ation to pro
oducts or prrocesses or should
facilitate
e to be relatted to them.
2.9
A
Average validity
v
The indicators should remain valid for ave
erage mode
elling, i.e. useful for LC
CWE databa
ases.
2.10
S
System bo
oundaries
s, cut-off c
criteria, re
eference sy
ystem
They arre chosen in
i accordan
nce with the
e ISO 1404
40 and 140
044 (CEN 22006), whereas the
“environ
nmental rele
evance” is substituted
s
by the “social relevanc
ce”.
2.11
T
Temporal stability and
a time s
series
The callculation of the social indicators sshould be repeatable
r
years, which
h means
for other ye
that time
e series sho
ow the actu
ual changess.
2.12
Data availlability/efffort
The datta collection
n should be viable unde
er justifiable
e effort.
3
LCWE
E METHOD
D DESCRIP
PTION
The nexxt paragrap
phs will exp
plain the L
LCWE meth
hod develop
ped at Univversity of Stuttgart,
S
LBP-Ga
aBi.
3.1
Indicators
s chosen for
f integra
ation into LCA
Table 1 shows th
he indicators chosen to be inte
egrated into
o the Life Cycle Eng
gineering
methodology basin
ng on the crriteria descrribed above.
Page 3 / 15
Table 1: Social Ind
dicators ch
hosen
Group
Indica
ator
Unit
General Qualification
n level A (GQ
QL A)
[sec
c]
General Qualification
n level B (GQ
QL B)
[sec
c]
General Qualification
n level C (GQ
QL C)
[sec
c]
General Qualification
n level D (GQ
QL D)
[sec
c]
General Qualification
n level E (GQ
QL E)
[sec
c]
Total workiing time
[sec
c]
Lethal acc
cidents
[case
es]
Non-lethal accidents
a
[case
es]
Qualiffied working
g time
Hea
alth and Safe
ety
3.2
Data acqu
uisition me
ethod
In gene
eral, both, a bottom-up
p and a top
p-down app
proach for data
d
acquissition do ex
xist. The
bottom--up approacch would be the sepa rate acquis
sition of datta for everyy unit proce
ess. The
top-dow
wn approach
h correspon
nds to the p rorating of aggregate
a
data
d
to sing le processe
es.
3.2.1
Separate
e data acq
quisition fo
or unit pro
ocesses
Applying
g this approach, social indicato
ors have to
o be collec
cted for eaach process
s in the
producttion chain. Here
H
the prroblem occu
urs that suc
ch data is ra
arely availaable at the moment,
m
because
e a meaningful use and comprrehensive approach
a
for
f such inndicators was
w
nonexistentt so far. The initiation
n of a con
ntinuous as
scertainment of this d ata would be cost
intensivve and time consuming.
Due to this, for the beginning
g the top-d own attemp
pt is chosen for the LLCWE meth
hodology
develop
ped at the University
U
of
o Stuttgart.. Neverthele
ess, the da
ata acquisitiion for everry single
processs remains th
he middle-te
erm to long--term goal because
b
of its more preecise resultts.
3.2.2
Proration
n of aggre
egated datta to singlle process
s
Statisticcal data co
oncerning social
s
issue
es is available for most
m
of thee highly de
eveloped
countrie
es, for some
e of them de
etailed enou
ugh to use them
t
in the LCWE metthodology.
To prora
ate this data
a down to process
p
leve
el, the follow
wing assum
mptions are aapplied:
1. T
The social impacts off a processs are propo
ortional rela
ated to the amount off human
llabour of the process.
Page 4 / 15
2. T
The amoun
nt of human
n labour of a process is
i related to
o the effort made to ad
dd value
b
by processiing (which is equivalen
nt to the add
ded-value itself).
The abo
ove assump
ptions are valid within tthe same in
ndustry and in the samee country only.
In contrrast to the situation
s
forr environme
ental Input-O
Output table
es, the amoount of hum
man work
is very well correlated with the econom
mic value ad
dded of a process. Thhe precision of the
results tthat can be
e reached is
s hence hig
gh enough to
t be used as a reaso nable startiing point
for modelling on the product le
evel.
he differentt steps of tthe approac
ch developed at the U
University Stuttgart
Figure 2 shows th
at the calcu
ulation of pro
ocess speccific LCWE data.
d
aiming a
Figure 2: Generattion of proc
cess-speci fic social information
n
ollowing parragraphs, th
he steps sho
ure 2 are de
escribed in m
more detail..
In the fo
own in Figu
3.3
G
General qualificatio
q
on level off jobs
In the first step, single pro
ofessions a
are allocate
ed to different qualifiication leve
els. The
classificcation is made accord
ding to the Internation
nal Standarrd Classificcation of Ed
ducation
(UNESC
CO INSTITUT
TE FOR STATISTICS 199
97). This cla
assification was develooped in 199
97 by the
UNESC
CO in orderr to classify
y and chara
acterize diffferent school types annd school systems.
s
The ISC
CED addre
esses the required
r
qu
ualification of a job po
osition rathher than the actual
qualifica
ation of the employees
s. It classifie
es seven diffferent qualiification leveels (Level 0 – Level
6). In th
he course of the development o
of this meth
hod Level 0, Level 1 and Level 2 were
combine
ed to one le
evel. The distinctions m
made in thes
se levels for the require
red qualifica
ation of a
job are not relevant enough to
o be kept in the classification for th
he developeed method.
Page 5 / 15
3.4
Employee
e profile off the indus
stry
In the se
econd step, the profes
ssion distrib ution per industry is ca
alculated viaa a matrix based
b
on
the SIC
C code (OCCUPATIONA
C
AL HEALTH AND SAFE
ETY ADMINIS
STRATION 1 992). In th
he table
elementts of the ma
atrix, the nu
umber of po
ositions of each
e
profession in eve ry single industry is
presentted. From th
his, the emp
ployee profi le of each industry can
n be identifieed.
3.5
S
Seconds of
o labour per VA
The secconds of labour per va
alue added are derive
ed from the U.S. Econ omic Census (U.S.
CENSUS
S BUREAU 1997).
1
This
s statistic g
gives inform
mation abou
ut the num
mber of employees,
average
e number off production
n workers, p
production workers' ho
ours, cost of contract work
w
and
the valu
ue added. The
T value ad
dded given in the statis
stic is calcu
ulated from tthe income through
the sale
e of the pro
oduced goo
ods less the
e expenditu
ures for aux
xiliary mateerials, interm
mediates
and/or resources and the expenditure
es for sub
bcontracting
g. The val ue added for the
calculattion of the seconds
s
of labour per VA – relation is thereffore correctted by this number.
The wo
orking time is only qu
uoted for w
workers, no
ot for appo
ointees. It iis assumed
d in the
methodology, that an appointe
ee works th e same hou
urs per yearr as a workeer.
3.6
Q
Qualificattional labo
our profile
e of the ind
dustry
In the next step, th
he total work
king time pe
er value add
ded can be broken dow
wn with the
e support
of the ta
ables and matrixes
m
ge
enerated in the steps before.
b
The result is a qualificatio
on profile
of each industry per value ad
dded generrated. This qualification
n profile shhows the am
mount of
working
g time in eacch of the fiv
ve qualificattion levels to
t generate one Euro vvalue added
d. These
values, same as th
he total worrking to gen
nerate one Euro
E
value added, varry between different
industrie
es.
3.7
Rate of no
on-fatal injuries perr VA
For the
e calculation
n of non-fa
atal injuriess, two kinds
s of data are
a availabble (UNITED STATES
DEPARTTMENT OF LABOR
A
1999): The injurie
es listed as injury rates
s, as well ass absolute numbers
n
of injuries per ind
dustry. The injury rate
es present the numbe
ers of injurries per pe
erformed
working
g time. Thesse rates are
e correspon
nding with the risk of th
he employeees to get in
njured in
the spe
ecific industrry. The abs
solute ratess give the to
otal number of injuriess without ta
aking the
total number of em
mployees in the specificc industry in
nto accountt. In the conntext of the
e method
describe
ed here, th
he non – fa
atal injuriess have to be
b related to
t the totall working time and
respectively to the value ad
dded in orrder to cla
assify them
m to the ddifferent pro
ocesses.
Therefo
ore, the rate
e of non-fata
al injuries iss used.
3.8
Rate of fatal injuries per VA
The fata
al injuries are
a also collected and p
published by
b the U. S. Departmennt of Labor (UNITED
STATES DEPARTME
ENT OF LAB
BOR 1999). For the fa
atal injuries
s only absoolute numb
bers are
Page 6 / 15
available. A statem
ment concerrning the rissk of fatal in
njuries in the different industries therefore
is not po
ossible.
In orderr to relate th
he fatal injuries to the ttotal workin
ng time and hence to thhe value added, the
working
g time for every
e
industry has to be available. For the reasons exxplained in the last
n from diffferent sourc
paragra
aph, values should no
ot be drawn
ces. So vaalues from different
tables, generated based on th
he source m
mentioned above on non-fatal
n
annd fatal injuries, are
used: T
The total wo
orking time for each ind
dustry is de
erived from the non-fattal injuries rate and
from the
e absolute number
n
of non-fatal
n
inj uries.
3.9
S
Social Pro
ofile of the
e industry
y
The soccial profile for
f each ind
dustry includ
des the wo
orking time in different qualification levels,
the non-fatal and the fatal inju
uries, each related to one
o Euro off value addeed generate
ed in the
respective industryy.
3.10
Prices forr GaBi-Flows
For rela
ating the social data to
o LCA proce
ess data, th
he value added of eachh LCA proc
cess has
to be id
dentified. Th
his is done by calcula ting the delta of prices between the output and the
input flo
ows of each
h process. Therefore, for all mate
erials, intermediate prooducts or products,
p
as well as variouss energy flluxes, whicch go in an
nd out of processes,
p
prices hav
ve to be
determined and asssigned. Sin
nce the pro
oduct prices
s depend on
n a dynamicc market, th
he same
referencce period for
f both the
e prices an
nd for the identificatio
on of the vvalue added
d of the
industrie
es should be selected
d. In this ccase the calculation is made wiith annual average
values o
of the same reference
e period. A foreign trade statistic is used to provide co
onsistent
price da
ata (U.S. CENSUS
E
BURE
EAU 2002A, U.S. CENSU
US BUREAU 2002
2
B).
For mo
ost of the flows,
f
price
es can be calculated regarding quantities and total value
v
of
exported commodiities. In cas
ses where tthis is not possible,
p
prrices are esstimated pe
er expert
judgeme
ent using the
t
assump
ptions that tthere are no
n negative
e value adddeds and th
hat price
ranges can be esttimated on the basis o
of the lowe
er price of a preliminaary product and the
higher p
price of a su
ubsequent product.
p
Th is kind of es
stimation ha
as an impacct on the res
sult if
1. tthe according flow pas
sses from on
ne industry into anothe
er industry aand
2. tthe social profile
p
of botth industriess varies.
3.11
V
Value Add
ded of GaB
Bi-Proces
sses
In orderr to calculatte the value added of a single proc
cess, the to
otal value off the incoming flows
is subtrracted from
m the total value of th
he outgoing
g flows of a process. The total value is
calculatted by multiplying the amount of the flow wiith its price and then bby summing
g up the
values o
of all flows.
Page 7 / 15
This ste
ep requires an access
s to a life cyycle model on a unit process levvel of the particular
p
productt. Furthermore, as consistent ass possible data
d
are necessary foor all econ
nomically
relevantt material and energy flows,
f
which
h flow in and out the un
nit processees.
3.12
Process Data
D
Sets
To gene
erate a LCW
WE process
s data set, each individ
dual proces
ss must be classified to one of
the variious industrries. Subse
equently, the
e social pro
ofile of the industry is multiplied with the
value ad
dded of the individual process.
p
In doing this, the reference to one E
Euro of valu
ue added
is lost a
and the indu
ustry profile is scaled o n a unit pro
ocess.
3.13
Evaluation
n
In the ccourse of the balance calculation,
c
the values of unit processes aree summarize
ed along
the valu
ue chain according to
o the summ
marization of
o LCA inventory dataa and can thus be
evaluate
ed equally.
3.14
Processin
ng of Data(-sets) in the Softw
ware
In the cclassic LCA
A the particu
ular processses are sc
caled accord
ding to theiir connectio
ons over
input an
nd output flo
ows. Beside
es, the elem
mentary flow
ws, which exceed
e
the system bou
undaries
and thus cause an impact, are
e scaled witth the factor of their orriginal proceess. In this way,
w
the
contribu
ution of ea
ach individu
ual processs to the fu
unction of the
t
total sy
system is weighted
w
correctlyy. By includ
ding social data into L
LCA datase
ets, the sam
me weightinng principle
es apply,
thus lea
ading to correct results that can be
e evaluated in accordance to LCA
A results.
3.15
G
Generatio
on of Indic
cators and
d Evaluatio
on
In classsic LCA methodolo
ogy, the summation
n is follo
owed by classificatio
on and
characte
erization. In
n contrast, the indicattors for the social aspects are chhosen the way
w that
they ea
ach build its
i own cla
ass. The sstep of the
e classification as re lation of particular
p
contribu
utors to a potential
p
kin
nd of impacct therefore is superflu
uous. Withinn each clas
ss, there
are no contributorrs that hav
ve to be vvalued differently. Com
mpared to a considerration of
ecologiccal values, a characte
erization th
herefore is not necess
sary. This can be seen as a
fundamental differrence between ecolog
gical LCA and social aspects cconsideratio
on within
LCA; in case of the ecologica
al LCA the interim bala
ance of mass and eneergy flows is
s drown.
These flows are then misca
alculated in
n respect to
t their va
arious envirronmental impacts.
Howeve
er, when examining
e
social asp
pects, the indicators are seleccted so th
hat they
correspond directlyy with a soc
cial aspect. The evalua
ation of indic
cators howeever can be
e done in
analogyy to the cla
assic LCA-m
method: Ea
ach indicato
or receives
s its own im
mpact category (or
rather for each impact ca
ategory a described indicator is to be found) an
nd each
characte
erization factor gets the value one
e.
Page 8 / 15
3.16
V
Validity
As explained abovve, a respec
ctive validitty of a resu
ult depends on the seleection of th
he social
indicato
ors, on their ability to
o be summ
med up, on an ability to be weiighted that can be
comparred with ma
aterial and energy
e
flow
ws and, of course,
c
on the availabbility of data
a for the
unit pro
ocesses. All
A these co
onditions a
are given fo
or the worrking time values in different
qualifica
ation levels, the non-fa
atal and fata
al injuries presented ab
bove. If the re is a poss
sibility to
relate th
hem to the basic value
e working tim
me, also forr other socia
al factors too be develo
oped, the
criteriass of summin
ng up and weighting
w
ca
an be accomplished. The
T availabbility of data
a is to be
proved separatelyy, and a ge
eneral valid
dity or rath
her reasona
ableness sshould be used
u
as
primary selection criterion.
c
4
EXAM
MPLE
To show
w the poten
ntials and va
alidate the feasibility of
o the asses
ssment metthod, it was
s applied
in severral projects so far. There are princcipally two possibilities
p
to use the LCWE method:
1. Use of the
e comprehe
ensive and
d consistent backgrou
und databaase. The da
ata was
ccalculated as
a explained above.
2. G
Gathering of
o own, project and pro
ocess specific data. The data can be inserted
d directly
in the LCWE tab, when
n creating a new proce
ess.
For the example, data
d
from the backgrou
und databas
se is used in
n order to sshow the application
of the m
method. Two
o different kinds
k
of plasstic are com
mpared.
4.1
Descriptio
on of the assessed
a
system
Concern
ning the soccial implicattions, the w
whole production phase
e of the diffeerent alternatives is
assesse
ed including all upstrream value
e chains (p
production and supplly of all precursor
p
substan
nces, operatting supplie
es, auxiliary materials, energies etc.).
In the ffollowing, th
he results for the asssessment of
o two route
es will be sshown exemplarily:
Polyethylene fibress production
n and the prroduction off Polyethyle
ene terephthhalate (PET
T) fibres.
4.2
Results
Table 2 shows the
e working time
t
distrib
bution into the
t
general qualificatioon levels (GQL) in
secondss, that is re
elated to jobs with the
e respective
e qualificatio
on level ass requireme
ent. Jobs
with a G
GQL A do have
h
the hig
ghest qualiffication as prerequisite
p
e, Jobs withh a GQL E relate to
work w
with low qualification requirement
r
ts. The tottal working time, beinng the sum
m of the
numberrs listed under the diffferent GQL
Ls, is the su
um of all human labouur employe
ed in the
producttion of 1 kg plastic.
F
3 pre
esent, the plastic PET
T production requires considerab
bly more
As Table 2 and Figure
an PE prod
duction. Th is is cause
ed by the more compplex manuffacturing
human labour tha
processs for PET than for PE.
Page 9 / 15
Table 2
2: Working time and accidents
a
fo
for the prod
duction of 1 kg PE an
nd 1 kg PET
T
Qu
ualification Level
PE
PET
GQL A [s]
1.4
9.9
GQL B [s]
11.0
61.1
GQL C [ss]
14.4
72.5
GQL D [ss]
15.1
59.4
GQL E [s]
7.6
27.2
Tottal working tiime [s]
49.5
230.1
Leth
hal accidents [cases]
3,23E-07
11,06E-06
Non-le
ethal acciden
nts [cases]
5,45E-10
11,03E-09
aphics also show that in
i industriall process ch
hains rather few jobs w
without qua
alification
The gra
and witth a very high qualifiication can
n be found. Industry requires a minimum level of
qualifica
ation and only few peo
ople with a very high qualification
q
n on the maanagement level. A
higher sshare of workers
w
with
hout qualificcation is ra
ather found in the serrvice sector (sales,
direct se
ervices etc.).
Qu
ualified
d Workking Tim
me
Qualified working time in [s]
250,0
200,0
GQL E [s]
150,0
GQL D [s]
GQL C [s]
100,0
GQL B [s]
50,0
GQL A [s]
0,0
PE
PET
Figure 3: Qualified
d working time for th
he production of 1 kg PE and PE
ET
Figure 4 and Figurre 5 show the amount of non-leth
hal and letha
al accidentss for the pro
oduction
of 1 kg PE or PET.. The numb
bers are verry small as they are related to thee functional unit of 1
kilogram
m.
Page 10 / 15
N
Non‐leth
hal accidents
Non‐lethal accidents [cases]
1,20E‐09
1,00E‐09
8,00E‐10
6,00E‐10
4,00E‐10
2,00E‐10
0,00E+00
PE
P
PET
Figure 4: Non-leth
hal acciden
nts caused by the pro
oduction off 1 kg PE aand PET
eneral results are sim
milar to qua
alified work
king time: There are significanttly more
The ge
acciden
nts when producing a kg of PET
T than PE. Again thiis is due to the more
e labour
intensivve and more
e complex manufacturi
m
ng process of PET.
Lethal accide
ents
Lethal accidents [cases]
1,20E‐06
6
1,00E‐06
6
8,00E‐07
7
6,00E‐07
7
4,00E‐07
7
2,00E‐07
7
0,00E+00
0
PE
PET
Figure 5: Lethal accidents
a
caused
c
by tthe produc
ction of 1 kg
g PE and P
PET
Page 11 / 15
6
Discussio
on and outtlook
Holistic and forwa
ard-looking decisions must be based
b
on a broad baasis of all relevant
information. The so
ocial dimens
sion of hum
man actions clearly mus
st be considdered.
ethod develo
oped and th
he respectivve backgrou
und database is a firstt, promising attempt
The me
to addre
ess the social pillar of sustainabilit
s
ty in the sco
ope of the well
w establisshed metho
od of Life
Cycle A
Assessmen
nt and Life
e Cycle En
ngineering. Social efffects that would hav
ve been
neglecte
ed by an LCA
L
can be
e included a
and show remarkable results. Prooblem shifting from
the environmental realm to the
e social field
d can be av
voided.
ample show
ws, that the results of th
he LCWE method
m
can be used sim
milarly to the
e results
The exa
of an L
LCA: Inform
mation is prresented on
n a unit pro
ocess level and also project or process
specific informatio
on can be inserted. IInformation about soc
cial issues is summa
able and
scalable
e as the LC
CA user is fa
amiliar with from the environment
e
tal LCA. In the compre
ehensive
backgro
ound databa
ase, informa
ation for alll unit processes regard
ding the quaalified work
king time
and leth
hal and no
on-lethal ac
ccidents is available. Additionally
y, informatiion concern
ning the
following indicatorss can be ins
serted in the
e GaBi softw
ware in the LCWE tab by the userr:

A
Actual wom
men employment

C
Child labour

ccess
Discrimination in job ac

our
Forced labo

Hazardous child labour

ng
No collectivve bargainin

No right to organise
o

Unequal remuneration
All inforrmation has to be in relation to wo rking time in seconds.
Howeve
er, it has to be stated that due to
o the above mentioned restrictionss for indicators, not
all relevvant social information can be acccounted forr by this me
ethod, so faar. Additional social
effects h
have to be considered in future de
evelopmentt of the meth
hodology.
As all LCWE data currently prresent in the
e GaBi data
abase is de
erived from US statistic
cs, it can
be rega
arded valid for all coun
ntries holdin
ng similar economic
e
and
a socio-ecconomic co
onditions
than the
e US.
Using th
he LCWE data
d
for decision makin
ng, it has to be conside
ered that ass the data is
s derived
from sta
atistics, it do
oes not rep
present exacct site spec
cific situations and shoould only be
e used to
comparre for exam
mple genera
al product options. For the com
mparison off social aspects of
different suppliers, company-s
specific data
a has to be used.
To conclude with,, the social database can be used as a hotspot daatabase in order to
e the main contributorrs to social profiles along the pro
ocess chainns of produ
ucts. For
examine
these m
main contributors, site specific
s
soccial data can
n be gathere
ed in a secoond step in order to
get a more precise
e picture of the
t social im
mplications of a produc
ct.
Page 12 / 15
6
LITER
RATURE
NATION
NAL
NATIONA
AL CROSSWA
ALK SERVIC
CE CENTER (1997): NO
OICC Maste
er Crosswallk,
CROSS
SWALK
Version 4.3. Nation al Crosswa
alk Service Center.
C
SERVIC
CE CENTER
R
h
xwalkcenter.org/index.php.
Online: http://www.x
(1997))
OCCUP
PATIONAL
HEALTH
D
H
AND
SAFETY
Y
ADMINISTRATIION (1992)
ATIONAL HEA
ALTH AND SAFETY
A
ADMIN
NISTRATION (1992): Sta
andard
OCCUPA
Industria
al Classifica
ation (SIC) system.
s
United States Department of Labor;
Occupattional Healt h and Safetty Administrration.
Online: http://www.o
h
osha.gov/plls/imis/sic_m
manual.htm
ml;
http://ww
ww.census.g
gov/epcd/w
www/sic.html.
O INSTITUTE
E FOR STATISTICS (1997
7): Internatio
ional Standa
ard
UNESCO
UNESC
CO
Classific
cation
of
Ed
ducation
ISC
CED
1997.
UNESCO
U
In
nstitute
for
Statistics.
S
INSTITU
UTE
FOR
R
Online:
STATIS
STICS (1997))
http://ww
ww.unesco.o
org/education/informattion/nfsunessco/doc/isced_1997.httm
; http://w
www.uis.une
esco.org/ev_
_en.php?ID
D=7433_2011&ID2=DO_
_TOPIC.
PARTMENT OF
O LABOR (1999): US Fa
Fatal and No
on-Fatal
UNITED
D
STATES
S UNITED STATES DEP
Injuries and
a illnesse
es. United States
S
Depa
artment of LLabor and Bureau
B
of
DEPAR
RTMENT OF
F
Labor Sttatistics.
LABOR
R (1999)
Online:
http://ww
ww.bls.gov/iiif/oshwc/os
sh/os/ostb06
641.pdf; htttp://www.bls
s.gov/iif/osh
hw
c/osh/os
s/ostb0642.p
pdf.
CENSUS
U.S.
S U.S. CEN
NSUS BUREA
AU (1997): 1997
1
Econo
omic Censuus. General Summary
BUREA
AU (1997)
Mining and
a Manufa
acturing, Ind
dustry Summ
mary Constr
truction. U.S
S. Census
Bureau. Online: http
p://www.cen
nsus.gov/prrod/ec97/977m31s-gs.pdf;
http://ww
ww.census.g
gov/prod/ec
c97/97c23-is.pdf;
http://ww
ww.census.g
gov/prod/ec
c97/97n21-g
gs.pdf.
PORTS OF ME
ERCHANDISE
E (2002A): History
H
DVD
D-ROM. U.S
S. Census
U.S. IMPORTS OF
F U.S. IMP
Bureau.
MERCH
HANDISE
h
census.gov
v/foreignOnline: http://www.c
(2002A)
trade/refference/pro
oducts/catalo
og/imphisto
ory.html.
PORTS OF M ERCHANDIS
SE 2002B: History
H
DVD--ROM. U.S. Census
U.S. EXPORTS OF
F U.S. EXP
Bureau.
MERCH
HANDISE
h
census.gov
v/foreignOnline: http://www.c
(2002B)
trade/refference/pro
oducts/catalo
og/exphisto
ory.html.
Page 13 / 15
APPEN
NDIX
In this chapter the
e data sources are a
addressed, which serv
ve as a bassis for the method
develop
ped at the University
U
Stuttgart.
S
Th
he particular statistics should
s
meeet various criteria
c
to
be used
d in this metthod. These
e criteria are
e as well sp
pecified in th
he followingg paragraph
hs.
U.S. Ec
conomic Census
C
The “U..S. Econom
mic Census”” (http://ww
ww.census.g
gov/) is a comprehenssive data co
ollection,
that give
es a detaile
ed review of
o the Amer ican economy. It is fulfilled by thee “Census Bureau”,
B
the Ame
erican dem
mographic ag
gency. The
e results are
e gathered every five yyears, whereas the
collecte
ed basic datta include to
o a large exxtent the sta
atistics of all
a US comppanies. At th
he same
time, th
he data collection for the
t
agricult ure and the
e authoritie
es takes plaace in para
allel. The
data co
ollection is based on a clear stru
uctured cla
assification of the whoole econom
my into a
strictly hierarchica
al system of
o industria
al sectors and subse
ectors – th e so calle
ed North
America
an Industry Classification Standarrd (NAICS).. It is importtant that noot the companies as
a whole
e, but the single locatio
on of these ccompanies as minimum
m unit are l isted. It allo
ows both
a betterr spatial ressolution and
d a better re
esolution ac
ccording to activity, as a company
y can be
active in
n different sectors.
s
The NAICS cclassifies 1179 various industries, 1070 of which
w
are
covered
d in the U.S. Economic
c Census.
The datta is provide
ed for free and
a is supp
posed to serrve several purposes. The following fields
of appliccation exem
mplify this:

C
Companiess can comp
pare their ssales figure
es with thos
se for theirr whole ind
dustry. It
a
allows them
m to calcula
ate their ma
arket share in order to check theirr performan
nce or to
d
define new targets.

C
Companiess can also compare th
heir business ratio witth average numbers from
f
the
to assess
U.S. Census as a benchmark
b
s their perrformance with those
e of the
cconcurrent organizatio
ons.

C
Companiess which sell their goodss or service
es to other companies
c
can find in the U.S.
C
Census ne
ew target industriess. Besides, producerrs learn ffrom the material
cconsumptio
on statistics more abou
ut the industtries that co
onsume theiir products.

C
Companiess can use the data tto determin
ne their sa
ales areas, to place a target
ments.
a
advertiseme
ent and to find
f
the besst locations for
f their new
w establishm

Important key
k figures about
a
the e
economic de
evelopmentt as monthlyy retail sale
es or the
g
gross dome
estic produc
ct are base
ed on the da
ata of the U.S.
U
Censuss. Associatiions and
tthe press analyze th
he data to identify ec
conomic circumstancees and to forecast
d
developments.

T
The legislattive body uses the datta for the preparation
p
and assesssment of ne
ew laws.
T
The state and local authorities
a
monitor the
e Census data
d
to undderstand economic
basics and to decide whether
b
w
the
ey should se
ettle new businesses oor keep the
e already
e
existing one
es.
Page 14 / 15

C
Consultantss and researchers ma
ake use of the data to
o analyze tthe change
es in the
industries’ structure
s
orr in the spattial resolutio
on. These data
d
are nott explicitly collected
c
ffor the use
e in the me
ethod. Neve
ertheless th
hey work well
w for the developed method
b
because off the level of
o detail and
d their basis
s on the clear hierarch ical structure of the
industries’ classificatio
c
on.
In the 2
2002 U.S. Economic
E
Census
C
the data for th
he year 200
02 are colleected. In De
ecember
2002 data collecttion questio
onnaires w
were sent to more than 5 millioon compan
nies, the
deadline
e was set on
o the 12th
h of Februa ry 2003. Du
ue to adapttion of the ddata entry forms to
the individual industries, there
e exist now
w more than
n 600 differrent versionns. Only some very
small co
ompanies do
d not rece
eive questio
onnaires. Fo
or them the
e data alreaady available at the
federal authorities’’ are used. These autthorities pro
ovide basic
c data as loocation and
d kind of
businesss, sales figures, wage
es and salarries, numbe
er of employ
yees and foorm of organization.
The U.S
S. Econom
mic Census is enshrine
ed in title 13 of the United
U
Stattes Code. The law
commitss organizatiions to send
d back the ffilled forms and awards penalties in case companies
Census Bu
omit this. Besides,, the law sw
wears the C
ureau to sec
crecy. No ddata are pu
ublished,
which disclose the identity or activity
a
of a n individuall or a company.
Standa
ard Industtry Classiffication (S
SIC)
The Sta
andard Indu
ustry Classiification (SI C)-Code is
s a four-digit numerica l code assigned by
the U.S
S. governme
ent to the business esttablishmentts to identify
y the primaary business
s activity
of the e
establishme
ent (http://w
www.osha.g ov/pls/imis//sic_manual.html). Thee classificattion was
develop
ped to facilitate the collection, p
presentation
n and analy
ysis of datta; and to promote
uniformity and comparability in the pre
esentation of statistic
cal data coollected by various
agencie
es of the federal go
overnment, state age
encies and
d private oorganization
ns. The
classificcation cove
ers all eco
onomic acttivities: agrriculture, fo
orestry, fisshing, hunting and
trapping
g; mining; construction
c
n; manufactturing; trans
sportation; communicaations, elec
ctric, gas
and sanitary services; whole
esale trade
e; retail trade; finance
e; insurance
ce and real estate;
servicess; and publiic administrration.
The Burreau of Lab
bour Statistics is a unit of U.S. Department off Labour. Thhis unit is in
n charge
for the ffact-finding for the fede
eral govern
nment in the
e wide field of occupattional econo
omy and
occupattional statistics.
US Imp
port/Export History
The data about “U
U.S. Exporrts of Mercchandise” (U
U.S. CENSU
US BUREAU 2002B) an
nd “U.S.
Imports of Mercha
andise” (U.S
S. CENSUS BUREAU 20
002A) are gathered
g
annd provided
d by the
U.S. Ce
ensus Bureau. The export statistiics contain data aboutt the value and the qu
uantity of
9.000 vvarious goods, which were
w
exporrted from th
he USA; the
e import staatistics prov
vide this
information for 17
7.000 differrent importe
ed goods. Depending
g on the uunit the quantity is
specifie
ds can be calculated
ed in, an ave
erage price of the good
c
based
b
on thhese data. The
T data
are also
o available for
f the pastt years. Forr the method
d described
d here, dataa from the re
eference
year 2002 was use
ed.
Page 15 / 15