From Diversity to Confusion? The Challenge of Biodiversity Footprint Quantification

Roede , Raphaela; U z, Sebas ian
A icle — Published Ve sion
F om Di e si y o Con usion? The Challenge o Biodi e si y
Foo p in Quan i ica ion
Business S a egy and he En i onmen
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Sugges ed Ci a ion: Roede , Raphaela; U z, Sebas ian (2025) : F om Di e si y o Con usion? The
Challenge o Biodi e si y Foo p in Quan i ica ion, Business S a egy and he En i onmen , ISSN
1099-0836, Wiley, Hoboken, NJ, Vol. 34, Iss. 5, pp. 5887-5900,
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Business S a egy and he En i onmen , 2025; 34:5887–5900
h ps://doi.o g/10.1002/bse.4215
5887
Business S a egy and he En i onmen
RESEARCH ARTICLE OPEN ACCESS
F om Di e si y o Con usion? The Challenge o Biodi e si y
Foo p in Quan i ica ion
RaphaelaRoede | Sebas ianU z
Facul y o Business and Economics and Cen e o Clima e Resilience, Uni e si y o Augsbu g, Augsbu g,Ge many
Co espondence: Sebas ian U z (sebas ian.u [email protected])
Recei ed: 22 Decembe 2024 | Re ised: 2 Feb ua y 2025 | Accep ed: 11 Feb ua y 2025
Funding: This esea ch was suppo ed by he Uni e si y o Augsbu g x G een Resea ch Ne wo k BRaVE.
Keywo ds: biodi e si y| biodi e si y oo p in | disag eemen
ABSTRACT
This s udy documen s a signi ican disag eemen be ween he biodi e si y oo p in s o h ee majo p o ide s. This disag eemen
mainly s ems om undamen al disag eemen on he unde lying me hods and da a (measu emen ), while p o ide s ag ee o a
la ge pa on which i m ope a ions con ibu e o a loss in biodi e si y and how hey a e agg ega ed (scope and weigh ). The dis-
ag eemen is especially high o la ge i ms wi h a high biodi e si y oo p in and i ms om he indus ies o Ene gy, Consume
S aples, and Basic Ma e ials. A anspa en and de ailed ESG disclosu e can dec ease he disag eemen . The esul s highligh he
impo ance o being ca e ul when in eg a ing biodi e si y oo p in in o inancial decision- making, egula ions, and academic
esea ch. The esul s also unde line he need o u he s anda dized and anspa en biodi e si y disclosu e on i m le el.
1 | In oduc ion
Humani y is acing an unp eceden ed loss in biodi e si y.1
Recen ly, his loss has gained awa eness among in es o s,
decision- make s, and i ms, d i en by inc easing egula ion
a ound he disclosu e and measu emen o a i m's impac
and dependencies on na u e. In Decembe 2022, he Global
Biodi e si y F amewo k (GBF) was signed by 196 coun ies,
calling on i ms o disclose hei impac on biodi e si y, and
in Sep embe 2023, he Task o ce o Na u e- ela ed Financial
Disclosu e (TNFD) published hei inal se o ecommenda-
ions o i ms and inancial ins i u ions o “iden i y, assess,
manage and (…) disclose na u e- ela ed issues” (TNFD2023b,
p.7). Al eady in 2021, he F ench go e nmen obliga ed inan-
cial ins i u ions in A icle 29 o he Ene gy and Clima e Law
o disclose hei exposu e o biodi e si y- ela ed isk as well as
hei impac on biodi e si y, e e ing o so- called biodi e si y
oo p in s (A . 29, LEC).
In esponse o hese egula o y de elopmen s, i ms and in es-
o s a e inc easingly measu ing and disclosing hei impac and
dependencies on na u e. Biodi e si y oo p in s—quan i a i e
me ics desc ibing he nega i e impac o a i m's ope a ions on
biodi e si y—ha e eme ged as in luen ial ools used by i ms,
inancial ins i u ions, esea che s, and mo e (TNFD2023a). A
a ie y o da a p o ide s now o e i m- le el biodi e si y oo -
p in s. Howe e , measu ing a i m's impac on na u e is a com-
plex and challenging p ocess as he impac on biodi e si y is
mul ilaye ed and s ems o example om esou ce use, was e
and wa e managemen , and g eenhouse gas emissions. Since
he egula o y amewo ks equi e eliable da a sou ces o be
e ec i e, unde s anding he me hods and he ag eemen o bio-
di e si y oo p in s by di e en p o ide s is key.
Va ious s udies assess he ag eemen o o he sus ainabili y a -
ings and ind subs an ial disag eemen be ween di e en p o-
ide s o ESG sco es (Be g, Kölbel, and Rigobon2022; Cha e ji
e al. 2016; Ch is ensen, Se a eim, and Sikochi2022; Do lei ne ,
Halb i e , and Nguyen 2015; Widyawa i 2020), SDG a ings
(Bauckloh e  al. 2024), physical clima e isk sco es (Hain,
Kölbel, and Leippold2022), and ITR a ings (Ka han, U z, and
Chmel2023). The low co ela ion o sus ainabili y a ings aises
This is an open access a icle unde he e ms o he C ea i e Commons A ibu ion License, which pe mi s use, dis ibu ion and ep oduc ion in any medium, p o ided he o iginal wo k is
p ope ly ci ed.
© 2025 The Au ho (s). Business S a egy and he En i onmen published by ERP En i onmen and John Wiley & Sons L d.
5888 Business S a egy and he En i onmen , 2025
ques ions abou hei use ulness. In gene al, sus ainabili y a -
ings ha e p edic i e powe o u u e ESG news, bu ha ela-
ionship weakens o i ms wi h a high disag eemen be ween
a e s (Se a eim and Yoon2023). Mo eo e , s onge ESG sco e
disag eemen is associa ed wi h highe s ock e u n ola ili y,
la ge absolu e p ice mo emen s (Ch is ensen, Se a eim, and
Sikochi2022), and highe s ock e u ns, sugges ing a isk p e-
mium o hose i ms (A amo e al. 2022; Gibson, K uege ,
and Schmid 2021). Simila ly, a low le el o ag eemen be ween
SDG a ings a ec s he isk- e u n cha ac e is ics o he a ed
i ms (Bauckloh e al. 2024).
Me hods o assess biodi e si y impac ha e been de eloped and
discussed in he Li e Cycle Assessmen (LCA) li e a u e o
some ime (e.g., Win e e al. 2017; Wil ing e al. 2017). Recen ly,
hey a e also gaining inc easing ele ance among schola s and
decision- make s in he business and inance communi ies,
whe e biodi e si y oo p in s a e o en used as a measu emen
o i m- le el biodi e si y impac . I has been shown ha in-
es o s a e including biodi e si y oo p in s in hei in es men
decisions, as a biodi e si y oo p in p emium began eme ging
a e COP15 (Ga el e al. 2024). Coque e e al.(2025) addi ion-
ally ind ha he same biodi e si y oo p in impac s bo h he
expec ed and ealized s ock e u ns. E en when only ocusing
on he i m- le el exposu e o land use, one o he main d i -
e s o biodi e si y loss, a link o s ock e u ns can be ound
(Xiong 2024). While his esea ch ocuses on biodi e si y im-
pac , ano he s eam o li e a u e has in es iga ed biodi e si y
isk, ha is, bo h he physical isk a ising om a loss in biodi-
e si y and he ansi ional isk associa ed wi h new egula ions
and ules o s op he decline in biodi e si y. Giglio e al.(2024)
de eloped an app oach o measu e he i m- le el exposu e o
biodi e si y isk om i ms' 10- K epo s. This isk al eady a -
ec s equi y p ices (Giglio e al. 2024) and hinde s i m pe o -
mance (Bach, Hoang, and Le2024). Mo eo e , i ms ha be e
manage biodi e si y isk and he closely connec ed wa e and
pollu ion isks p o i om be e long- e m e inancing condi-
ions (Hoepne e al. 2023) and su e less s ock p ice c ashes
(Bassen e al. 2024). The e is also a posi i e ela ionship be ween
i m biodi e si y disclosu e and e u n on asse s (Elsayed2023).
Fu he li e a u e in he biodi e si y inance ield ocuses on
he biodi e si y inance gap and inancing mechanisms ha
can con ibu e o conse e biodi e si y, o ins ance, blended i-
nance s uc u es (Flamme , Gi oux, and Heal2025; Ka olyi and
Tobin- de la Puen e2023).
The abo e men ioned s udies emphasize he inc easing impo -
ance o biodi e si y in i m and in es men decisions, as well as
he use o biodi e si y oo p in s by decision- make s and schol-
a s. They he eby unde line he need o a be e unde s anding
o he me ics, as well as he se e i y o po en ial consequences
om i s disag eemen . This pape aims o con ibu e o his li -
e a u e by analyzing he oo p in s o h ee majo p o ide s (i.e.,
ISS ESG, Icebe g Da a Lab, and Impac Ins i u e). A e b ie ly
desc ibing he p ocess o calcula ing a biodi e si y oo p in in
gene al, we es he le el o ag eemen be ween he biodi e si y
oo p in s o he h ee p o ide s on a global se o 941 i ms using
di e en measu es o pai - wise and mul iple p o ide  com-
pa ison. We ind subs an ial disag eemen o all p o ide s.
Subsequen ly, we in es iga e he easons o he disag eemen by
ollowing Be g, Kölbel, and Rigobon(2022) and dis inguishing
scope, measu emen , and weigh disag eemen be ween p o id-
e s. We ind ha while p o ide s gene ally ocus on simila ac-
o s when calcula ing he oo p in , he e a e s ong di e ences
in he measu emen o hose ac o s. Agg ega ing hose ac o s
in o impac d i e s ha a e esponsible o he loss in biodi e -
si y e eals ha he i ms' con ibu ion o land use & pollu ion as
well as clima e change is a la ge ac o on i s o e all con ibu ion
o biodi e si y loss. Consequen ly, he p o ide s' disag eemen
s ems in a la ge pa om he disc epancies on hese ac o s.
Using c oss- sec ional eg essions, we ind ha he disag ee-
men is pa icula ly s ong o la ge i ms and i ms om he
indus ies o Ene gy, Basic Ma e ials, and Consume S aples. In
con as , i ms om he indus ies o Telecommunica ions and
Financials exhibi a lowe disag eemen . Mo eo e , de ailed and
anspa en ESG disclosu e on i m le el as well as a high sha e
o ins i u ional in es o s end o dec ease he disag eemen by
he p o ide s.
Ou indings ha e impo an implica ions o businesses, egu-
la o s, in es o s, and o he use s o biodi e si y oo p in s. The
disag eemen be ween he biodi e si y oo p in s can ha m he
e y pu pose o hem, making i di icul o e alua e he impac
o a i m on biodi e si y. I he use s a e no awa e o he di e -
en me hodologies o do no conside hem app op ia ely when
choosing and using a biodi e si y oo p in , he oo p in s do
no con ibu e su icien ly o dec easing he in o ma ion asym-
me y be ween businesses and s akeholde s abou hei impac
on biodi e si y. This has a - eaching consequences: E o s
o ealloca e capi al in o biodi e si y- iendly i ms a e being
mi iga ed, i ms' unce ain y abou he ma e ial ac o s o bio-
di e si y pe o mance inc eases, and hei incen i e o imp o e
hei biodi e si y pe o mance dec eases. In addi ion, i educes
he eliabili y o he esul s o academic s udies based on such
me ics.
The emainde o he pape is s uc u ed as ollows. Sec ion2
desc ibes he heo e ical amewo k ha his s udy is based on.
In Sec ion3, we i s desc ibe how biodi e si y impac s a e mea-
su ed and how a biodi e si y oo p in is calcula ed in gene al.
Subsequen ly, we desc ibe ou sample. Sec ion4 s a s by show-
ing he signi ican disag eemen be ween he p o ide s, hen
decomposing he disag eemen in scope, measu emen , and
weigh , and iden i ying he con ibu ion o each o he o e all
disag eemen . Sec ion5 analyzes de e minan s o he disag ee-
men , and Sec ion6 documen s he obus ness o ou main e-
sul s. We conclude in Sec ion7.
2 | Theo e ical Backg ound
Ins i u ional heo y p o ides he heo e ical ounda ion o why
businesses and o he s akeholde s (such as in es o s) demand
consis en biodi e si y oo p in s. A key elemen o he ins i u-
ional heo y is he concep o ins i u ional p essu es, which,
o example, desc ibe a socie y's e hical expec a ions on an o -
ganiza ion's beha io (Meye and Rowan1977; DiMaggio and
Powell 1983; Sco and Meye  1994). The esponses o a i m
o ins i u ional p essu es a e mainly d i en by he mo i a ion
o ensu e i s legi imacy (Meye and Rowan1977). Legi imacy
is c i ical o a i m's su i al as i ensu es access o impo -
an esou ces such as capi al and alen . I also dec eases he
5889
p obabili y o being a ge ed wi h e ibu ions like ines o loss
o sales (Deegan2002a). In ha sense, sus ainabili y epo s can
be seen as means o ob ain app o al om socie y, comply wi h
he “communi y license o ope a e” and suppo i s con inued
exis ence (Deegan 2002b). While epo ing on clima e- ela ed
issues such as ca bon emissions is inc easingly being s anda d-
ized, biodi e si y- ocused disclosu e is ound o be e y lim-
i ed, inconsis en , and highly a iable be ween i ms (Hassan,
Robe s, and A kins2020; Adle e al. 2017; Adle , Mansi, and
Pandey 2018). Ala mingly, i ms wi h a signi ican nega i e
impac on biodi e si y e en adop epo ing s a egies aimed a
neu alizing s akeholde conce ns a he han p o iding ans-
pa ency (Boi al2016). This inconsis en epo ing en i onmen
o biodi e si y impac leads o a high le el o unce ain y and
in o ma ion asymme y ega ding biodi e si y impac s o
s akeholde s.
Biodi e si y oo p in s, like o he hi d- pa y sus ainabili y
a ings, ha e he po en ial o educe in o ma ion asymme y
by ac ing as in e media ies be ween i ms and s akeholde s
(Bauckloh e al. 2024; Cha e ji and Toggel2010). S ill, his po-
en ial can only be ealized i he a ailable oo p in measu es
p o ide an accu a e and consis en signal o a i m's biodi e -
si y impac . To he bes o ou knowledge, he e is no esea ch
a ound he eliabili y and consis ency o biodi e si y oo p in s
ye . Since he e a e nume ous models ha can be used o cal-
cula ing biodi e si y impac (e.g., Damiani e al. 2023, wi h a e-
iew o 64 me hods), and he usage o di e en models has been
ound o lead o di e en esul s (Sany- Mengual e al. 2023), he
oo p in s by di e en p o ide s migh also exhibi signi ican
di e ences. This obse a ion would add o he inding o s ud-
ies ha aise conce ns ega ding he accu acy and consis ency
o o he sus ainabili y a ings. I has been ound ha i ms im-
plemen supe icial ac ions p ima ily o imp o e hei a ings
a he han o achie e subs an i e en i onmen al imp o emen s
(Co naggia and Co naggia2023; Clemen ino and Pe kins2020;
Chelli and Gend on2013). Mo eo e , sus ainabili y a ings ex-
hibi signi ican disag eemen among p o ide s (Cha e ji e al.
2016; Be g, Kölbel, and Rigobon 2022; Bauckloh e  al. 2024;
Hain, Kölbel, and Leippold2022; Ka han, U z, and Chmel2023).
This lack o cla i y can hinde app op ia e decision- making by
in es o s and o he s akeholde s, which has se e e asse p ic-
ing implica ions (A amo e  al. 2022; Gibson, K uege , and
Schmid 2021; Se a eim and Yoon2023; Ch is ensen, Se a eim,
and Sikochi2022). Disc epancies among biodi e si y oo p in s
could lead o simila ly ad e se consequences, especially consid-
e ing ha inancial ins i u ions o en apply hem oo simplis ic
(TNFD2023a). Biodi e si y disclosu e and biodi e si y isk a e
al eady a ec ing s ock e u ns (Elsayed2023; Giglio e al. 2024).
Biodi e si y oo p in s o hi d- pa y p o ide s ha e also been
ound o ha e implica ions o asse p icing (Ga el e al. 2024;
Coque e e al. 2025).
While he disag eemen be ween ESG sco es can be ela ed o
di e en pe cep ions o wha sus ainabili y is, he biodi e si y
oo p in ocuses clea ly on he i m's impac on he di e si y o
species. The e o e, on he one hand, biodi e si y oo p in s could
p o ide a clea e signal and ag ee mo e s ongly han o he sus-
ainabili y a ings, such as ESG sco es. On he o he hand, di -
e ences in ESG sco es ha e been ound o be s ongly d i en by
di e ences in measu emen (Be g, Kölbel, and Rigobon2022).
Di e ences in measu emen can also lead o disag eemen
be ween biodi e si y oo p in s, in pa icula aking in o ac-
coun he mul i ude o possibly unde lying me hods and models
(Damiani e al. 2023; Sany- Mengual e al. 2023). This a iabil-
i y migh e en be mo e p onounced, as he impac on biodi-
e si y is mul ilaye ed, i m disclosu es a e unclea (Hassan,
Robe s, and A kins2020; Adle e al. 2017; Adle , Mansi, and
Pandey2018), and he oo p in is explici ly ying o cap u e he
impac h ough he whole alue chain o he i m and he en i e
li e cycle o i s p oduc s.
Ou s udy empi ically es s whe he biodi e si y oo p in s a e a
sui able means o i ms (s akeholde s) o ensu e (assess) legi i-
macy. Fo his pu pose, we analyze whe he he p o ide s c ea e
a clea signal o i ms' biodi e si y impac .
3 | Sample and Da a
3.1 | Measu ing Biodi e si y Impac s
Resea ch ins i u ions (e.g., Ox o d Biodi e si y Ne wo k2023;
Uni e si y o Camb idge Ins i u e o Sus ainabili y
Leade ship 2020), i ms (e.g., ASN Bank and PRé
Sus ainabili y2022; Ke ing2021), go e nmen s (e.g., B oe e al.
2021), and da a p o ide s ha e de eloped me hodologies and
me ics o measu e he impac and dependencies o a i m on
na u e. O e ime, he so- called biodi e si y oo p in has be-
come he mos commonly used me hod o measu e and exp ess
a i m's impac on na u e.
While he e is no clea ag eemen on a de ini ion o a biodi e -
si y oo p in , he Ins i u e o Eu opean En i onmen al Policy
(IEEP) men ions ha i has o be “measu ed in e ms o biodi e -
si y change as a esul o p oduc ion and consump ion o pa ic-
ula goods and se ices” (IEEP2021, p. 12), and he Pa ne ship
o Biodi e si y Accoun ing Financials (PBAF) emphasizes ha
he impac mus be quan i ied (PBAF2022).
The calcula ion o he biodi e si y oo p in is based on a LCA
app oach. LCA is used o quan i y a p oduc 's o o ganiza ion's
impac on he en i onmen o e i s ull li e cycle and in ha
con ex he impac on biodi e si y has been explo ed al eady
o o e 20 yea s (Win e e al. 2017), long be o e biodi e si y
became a ele an opic in he inance indus y. Today, he e is
a wide a ie y o me hodologies o calcula e a biodi e si y oo -
p in (Damiani e al. 2023). While he oo p in s o some p o-
ide s a e de eloped o analyze he impac o a i m on na u e,
o he s ocus only on in es men s, p oduc s, and p ojec s, as well
as indus ies and coun ies. Mo eo e , he me hodologies di -
e in he da a used, he calcula ions, he ou come me ic, and
mo e. In his pape , we employ i m- le el oo p in s gene a ed
by hi d- pa y da a p o ide s.
The i s s ep o calcula e he oo p in o a i m is o iden i y
en i onmen al inpu s and ou pu s ha a e linked o he i m's
business ac i i ies. These aspec s include he amoun o wa e
used, he emi ed g eenhouse gas emission, and he amoun
o land ha a i m uses. Fac o s like he di e si y o species
and he amoun o endange ed species in a i m's ope a ing
a eas also a ec he biodi e si y oo p in . Tha in o ma ion is
5890 Business S a egy and he En i onmen , 2025
usually based on geospa ial da a and o en s ems om u he
hi d pa y p o ide s, o example, he In eg a ed Biodi e si y
Assessmen Tool (IBAT). I a i m is no p o iding speci ic
in o ma ion bu hei pee s do, some p o ide s use a bench-
ma king app oach, o he s de eloped sophis ica ed machine
lea ning me hods. In he second s ep, i m- speci ic inpu
and ou pu a iables a e ansla ed in o impac d i e s which
exe p essu e on biodi e si y by con ibu ing o (1) habi a
loss, (2) o e exploi a ion, (3) clima e change, (4) pollu ion, and
(5) he in oduc ion o in asi e species (IPBES2019). Las ly,
he impac o hese p essu es is measu ed and usually ex-
p essed in “Mean Species Abundance” (MSA) o “Po en ially
Disappea ed F ac ion o Species” (PDF) (PBAF 2022; B oe
e al. 2021). Bo h MSA and PDF a e measu es o biodi e si y
in ac ness. The MSA compa es he abundance o an o iginal
species in an a ea o he es ima ed abundance i he ecosys em
would be undis u bed and is exp essed as a pe cen age a e
(He og, Bo , and de Ho de2022; Schippe e al. 2020). The
PDF shows he ac ion o species los in a speci ic a ea due
o en i onmen al p essu es, wi hou aking a decline in spe-
cies popula ion in o accoun (He og, Bo , and de Ho de2022).
Howe e , i is also possible o exp ess he oo p in in o he
measu es, such as a loss o p is ine biodi e si y pe hec a e o
in a mone ized way.
Besides calcula ing a biodi e si y oo p in , he impac and de-
pendencies o a i m on na u e can be exp essed in o he ag-
g ega ed sco es. Fo ins ance, he Wo ld Benchma k Alliance
publishes i s assessmen o he impac on biodi e si y o o e 800
i ms on a scale om 0 o 100.2 I is impo an o no e ha mos
biodi e si y sco es ha a e no biodi e si y oo p in s ocus only
on pa ial aspec s o biodi e si y o use simpli ied app oaches
o cap u e biodi e si y impac s and isks. Examples comp ise
he a ing o he commi men o o e 700 inancial ins i u ions
o de o es a ion gene a ed by he nonp o i o ganiza ion Global
Canopy,3 he pe cen age alue s a ing o wha le el a i m com-
plies wi h he “Do No Signi ican Ha m” goal ega ding he bio-
di e si y objec i e o he EU Taxonomy o Bloombe g, and he
sco ing o he exposu e o US i ms o biodi e si y isks based
on a ex ual analysis o hei 10- K s a emen s (Giglio e al. 2024;
Bach, Hoang, and Le2024). Pe de ini ion, hese sco es a e no
cons uc ed o cap u e he impac o a i m on biodi e si y as
a whole, while he ma ked goal o biodi e si y oo p in s is o
include he en i e ange o biodi e si y aspec s h oughou he
whole li e cycle o a p oduc o a i m. The e o e, we a e limi ing
he analysis o oo p in measu es.
3.2 | Sample Desc ip ion
We ob ain he mos ecen ly a ailable biodi e si y oo p in s in
Janua y 2024 om he h ee p o ide s Icebe g Da a Lab (IDL),
Impac Ins i u e (II), and ISS ESG (ISS). All h ee sco es a e
ecommended by he Finance o Biodi e si y Founda ion and
he EU Business and Biodi e si y Pla o m (Bailon, Bo , and
Redn 2024); he sco es by IDL and II a e also ecommended
by he TNFD (TNFD 2023a). Mo eo e , he biodi e si y oo -
p in s by IDL ha e al eady been used in di e en esea ch
(Coque e e al. 2025; Ga el e al. 2024). IDL discloses he oo -
p in and he unde lying impac d i e s in MSA.km2, ISS bo h
in PDF.km2 and MSA.km2, and II in MSA.ha and PDF.ha. To
ensu e compa abili y, we z- s anda dize hese alues o he em-
pi ical analysis. A highe numbe indica es a la ge biodi e -
si y oo p in , meaning a s onge nega i e impac o a i m on
biodi e si y.
Ou sample pe p o ide consis s o 3388 i ms (IDL), 1516 i ms
(II), and 17,931 i ms (ISS). The inal da a se consis s o all
i ms ha ha e been a ed by all h ee p o ide s and a e publicly
aded, lea ing a se o 941 i ms. Hence o h, he p o ide s will
be anonymized and labeled only as “P o ide 1”, “P o ide 2”,
and “P o ide  3” o ensu e disc e ion ega ding hei exac
me hodologies.
Table 1 shows he a e age s anda dized oo p in by indus y
and egion pe p o ide . Mos o he analyzed i ms' headqua-
e s a e loca ed in No h Ame ica (405 i ms) and Eu ope (258
i ms), ope a ing in he Financials, Indus ials, Consume
Disc e iona y, and Technology indus y.Fu he , Table1 indi-
ca es a s ong disag eemen be ween p o ide s on egion- and
indus y- le el. Ac oss egions, La in Ame ica has he highes
mean oo p in o P o ide s 2 and 3 bu he smalles mean
oo p in o P o ide 1. Simila s ong disag eemen s can be
ound when compa ing he a e age oo p in s by indus y pe
p o ide . The e is no ag eemen on which indus y has he mos
o he leas a e age impac on biodi e si y. S ill, he Ene gy and
Consume S aples indus ies display a high a e age biodi e si y
oo p in o all p o ide s, wi h a s anda dized mean oo p in
anging be ween 0.132 and 1.572, and 0.028 and 0.887, espec-
i ely. In con as o ha , he indus ies Real Es a e, Technology,
and Telecommunica ions end o ha e a small impac on biodi-
e si y, wi h a oo p in below he mean o ze o o all p o ide s.
Table2 p esen s he dis ibu ion o he s anda dized oo p in s
pe p o ide . I demons a es ha o all p o ide s, e y ew
i ms ha e an ex emely la ge oo p in , wi h he maximum
anging be ween 19.369 o P o ide 1 and 29.483 o P o ide
4.4 A la ge sha e o he emaining i ms has e y simila - sized
oo p in s well below he mean. The median anges be ween
−0.248 o P o ide 2 and −0.050 o P o ide 3.
4 | The Disag eemen o Biodi e si y Foo p in s
This sec ion discusses he le el o ag eemen be ween he biodi-
e si y oo p in s o di e en p o ide s.
4.1 | Associa ion Measu es
Table1 indica es s ong disag eemen be ween all p o ide s on
egion- and indus y- le el. Mo eo e , anecdo al e idence also
sugges s disag eemen on i m- le el. Walma , o example, has
a s anda dized oo p in o 11.58 o P o ide 1 bu −0.029 o
P o ide 3. To u he unde s and he ag eemen on i m- le el,
we calcula e me ics o pai - wise (Pea son and Spea man co -
ela ion) and mul iple (K ippendo 's alpha) p o ide compa i-
son. While he Pea son co ela ion measu es he linea and he
Spea man co ela ion he ank- based ela ionship be ween wo
con inuous a iables, K ippendo 's alpha is commonly used
o analyze in e - a e eliabili y. A alue o 1 indica es pe ec
ag eemen , a alue o 0 he comple e absence o ag eemen , and

5891
a nega i e alue indica es sys ema ic disag eemen . A alue
g ea e han 0.8 can be in e p e ed as su icien ag eemen ,
while 0.667 is he lowes accep able limi o conclude any ag ee-
men (K ippendo 2004).
Table3 shows he co ela ion ma ices o he s anda dized bio-
di e si y oo p in o ou sample i ms. The Pea son co ela-
ion anges be ween 0.024 and 0.493 wi h an a e age o 0.206,
and he Spea man co ela ion anges be ween 0.619and 0.745
wi h an a e age o 0.670. The o e all K ippendo 's alpha o
all a e s is 0.206. We also calcula e K ippendo 's alphas o
all combina ions o wo p o ide s and ind alues in he ange
o 0.025 and 0.493 (un epo ed esul s). No pai o p o ide s
displays a K ippendo 's alpha highe han he h eshold o
0.667, sugges ing no sys ema ic ag eemen be ween he di e -
en oo p in s. O e all, he disag eemen on i ms' biodi e si y
oo p in measu ed by K ippendo 's alpha is subs an ially
highe han he disag eemen on ESG sco es, which al eady has
se e e consequences (Se a eim and Yoon2023; A amo e al.
2022; Ch is ensen, Se a eim, and Sikochi 2022). ESG sco es
om di e en p o ide s ha e a K ippendo 's alpha o 0.55
(Be g, Kölbel, and Rigobon2022). The a e age pai wise Pea son
co ela ions be ween 0.45 (Gibson, K uege , and Schmid 2021)
and 0.54 (Be g, Kölbel, and Rigobon2022) a e o simila size as
he co ela ions we obse e o he biodi e si y oo p in . Thus,
we documen indica ions ha he biodi e si y oo p in s o he
TABLE 1 | This able epo s he mean and s anda d de ia ion o he s anda dized biodi e si y oo p in by he di e en p o ide s, dis ibu ed by
egion (Panel A) and ICB indus y classi ica ion (Panel B).
P o ide 1 P o ide 2 P o ide 3
N
Mean S d. de . Mean S d. de . Mean S d. de .
Panel A: Regions
Asia Ex Japan 48 0.271 2.859 −0.069 1.066 −0.038 0.061
Eu ope 258 0.028 0.827 0.030 1.422 −0.043 0.026
Japan 184 −0.125 0.290 −0.165 0.423 −0.045 0.011
La in Ame ica 6−0.220 0.093 0.157 0.904 4.872 12.057
No h Ame ica 405 0.028 0.936 0.071 0.879 −0.015 0.414
Oceania 40 −0.177 0.235 −0.095 0.496 −0.048 0.005
Panel B: Indus ies
Basic ma e ials 45 0.271 1.246 −0.052 0.378 −0.041 0.011
Consume Disc e iona y 148 0.025 1.148 −0.017 0.902 −0.046 0.008
Consume S aples 82 0.887 2.415 0.468 1.213 0.028 0.324
Ene gy 37 0.132 0.447 1.572 3.552 0.986 4.982
Financials 146 −0.073 0.425 −0.173 0.304 −0.050 0.002
Heal h Ca e 91 0.011 0.926 −0.047 0.587 −0.044 0.013
Indus ials 175 −0.173 0.192 −0.123 0.447 −0.047 0.009
Real Es a e 54 −0.271 0.017 −0.347 0.045 −0.050 0.001
Technology 114 −0.240 0.071 −0.204 0.450 −0.048 0.009
Telecommunica ions 20 −0.271 0.016 −0.081 0.414 −0.049 0.001
U ili ies 29 −0.218 0.060 0.105 0.488 −0.049 0.002
TABLE 2 | This able epo s he dis ibu ion o he s anda dized oo p in s pe p o ide by p esen ing he minimum, maximum, and he 1%, 10%,
50%, 90%, and 99% pe cen iles.
Minimum 1% pe c. 10% pe c. 50% pe c. 90% pe c. 99% pe c. Maximum
P o ide 1 −0.281 −0.281 −0.281 −0.241 0.324 3.606 19.369
P o ide 2 −0.379 −0.377 −0.361 −0.248 0.496 3.374 20.923
P o ide 3 −0.051 −0.051 −0.051 −0.050 −0.035 0.073 29.483
No e:The mean s anda dized oo p in o all p o ide s is ze o, due o he z- s anda diza ion.
5892 Business S a egy and he En i onmen , 2025
conside ed p o ide s di e subs an ially. In he ollowing sec-
ions, we analyze whe e he disag eemen comes om and o
which i ms i is pa icula ly p onounced.
4.2 | Reasons o Disag eemen
In he ollowing sec ion, we explo e he easons o he
p o ide s' disag eemen . Following Be g, Kölbel, and
Rigobon(2022)'s analysis o he disag eemen be ween ESG
a e s, he causes o in e - a e disag eemen can s em om
di e gence in scope, measu emen , and weigh . Like ESG
sco es, biodi e si y oo p in s a e based on di e en indica-
o s. Consequen ly, also he disag eemen in he biodi e si y
oo p in s can be decomposed in o hese ac o s. In ou case,
scope e e s o he di e en impac d i e s ha he p o ide s
conside when calcula ing he oo p in , measu emen o di -
e ences in he calcula ions on impac d i e le el, and weigh
o he weigh wi h which each impac d i e con ibu es o he
inal sco e.
Scope. Di e gence in scope occu s i he p o ide s a e measu -
ing di e en ac o s o cap u e a i m's biodi e si y impac . As
desc ibed abo e, he biodi e si y oo p in s a e calcula ed by
iden i ying how a i m's ac i i ies con ibu e o di e en impac
d i e s. Benea h hese impac d i e s lie di e en indica o s, o
example, speci ic gas emissions con ibu ing o ai pollu ion o
di e en ia ion be ween eshwa e and ma ine acidi ica ion,
bo h con ibu ing o wa e pollu ion. The agg ega ed numbe
o conside ed indica o s a ies om 4 o 13 ac oss he h ee
p o ide s. Compa ing he numbe and dep h o hese indica o s
only gi es insigh in o he g anula i y o he da a ha he p o-
ide s sha e wi h hei clien s, bu i would be alse o assume
ha i can be ansla ed in o di e gences in scope. The e o e,
we summa ize he indica o s in o impac d i e s ha hey con-
ibu e o and compa e hem. P o ide s 1 and 2 conside he ou
impac d i e s Clima e Change, Ai Pollu ion, Wa e Pollu ion,
and Land Use & Pollu ion. P o ide 3 indi idually sha es indica-
o s o Clima e Change, Land Use & Pollu ion, Wa e Pollu ion,
and Wa e Ex ac ion.
The p o ide s exp ess he con ibu ion o each indica o o he
decline in biodi e si y in he same me ic ha hey use o he
oo p in (PDF o MSA). Agg ega ed, he alues o all indica-
o s add up o he en i e oo p in . This allows us o measu e
he con ibu ion o each impac d i e o he en i e oo p in by
calcula ing he a e age sha e o he agg ega ed indica o alues
ha a e unde lying he espec i e impac d i e o he en i e
oo p in :
In Equa ion(1),
deno es one o he 941 in es iga ed i ms,
di
he impac d i e by P o ide 
i,ind i
he alue o he unde -
lying indica o o i m
by P o ide 
i
and
F i
he comple e
oo p in o i m
by P o ide 
i
. Na u ally, he con ibu ions
o all impac d i e s pe p o ide sum up o 1. Table4 shows
he con ibu ion o each impac d i e pe p o ide in %. On
a e age, he impac d i e Land Use & Pollu ion con ibu es
67.17% o he o e all oo p in and is he e o e he mos in-
luen ial impac d i e , ollowed by Clima e Change, which
con ibu es on a e age 17.06%.
Measu emen . Di e gences in measu emen desc ibe how
p o ide s use di e en app oaches and da a o measu e he
same ac o . This can s em om di e en ideas abou which
i m ac i i ies con ibu e in which way o an impac d i e ,
and om di e en app oaches o sol ing he issue o missing
da a. As egula ions on biodi e si y disclosu e a e globally
s ill in a e y ea ly s adium, many i ms only p o ide e y
limi ed in o ma ion abou hei impac on biodi e si y (Adle
e al. 2017; Adle , Mansi, and Pandey2018; Hassan, Robe s,
and A kins2020). While some p o ide s use a benchma k ap-
p oach o ill hese da a gaps, o he s ha e de eloped machine-
lea ning models.
(1)
Con ibu ion(
di)=1
941 �
∈{1, …,941}
∑
ind∈di
ind i
F i
TABLE 3 | This able epo s he pai - wise Pea son and Spea man
co ela ion o each p o ide pai .
P o ide 1 P o ide 2 P o ide 3
Panel A: Pea son co ela ion
P o ide 1 — 0.493 0.024
P o ide 2 0.493 —0.100
P o ide 3 0.024 0.100 —
Panel B: Spea man co ela ion
P o ide 1 — 0.619 0.646
P o ide 2 0.619 —0.745
P o ide 3 0.646 0.745 —
TABLE 4 | This able shows he a e age con ibu ion o each impac d i e o he en i e oo p in (in %).
Impac d i e P o ide 1 P o ide 2 P o ide 3
Clima e Change 22.13 28.18 0.87
Land Use & Pollu ion 51.53 51.56 98.41
Ai Pollu ion 6.82 19.34 0
Wa e Pollu ion 19.52 0.92 0.71
Wa e Ex ac ion 0 0 0.00
5893
The di e gence in measu emen is assessed by calcula ing he
same ag eemen measu es as o he o e all oo p in o he
alue o he di e en impac d i e s. A low ag eemen on im-
pac d i e le el would poin ou ha he o e all disag eemen
canno only s em om disc epancies in he p o ide 's pe cep-
ion abou wha con ibu es o biodi e si y loss (scope) and o
which deg ee (weigh ) bu ha hey also in ac ha e di e en
ways o measu ing he same aspec s. The esul s in Table5 show
ha he highes ag eemen be ween he p o ide s is on he Land
Use & Pollu ion o he i ms, eaching a K ippendo 's alpha o
0.458. The ag eemen o he impac d i e s Ai Pollu ion and
Clima e Change is highe han o he o e all oo p in as well,
wi h a K ippendo 's alpha o 0.442 and 0.211, espec i ely. On
he o he hand, he e seems o be a lo o unce ain y a ound
Wa e Pollu ion. S ill, K ippendo 's alpha does no exceed he
limi o 0.667 o any o he impac d i e s, indica ing no sys em-
a ic ag eemen also on impac d i e le el.
Weigh . Be g, Kölbel, and Rigobon(2022) also s udy he weigh o
he indica o s in hei s udy on ESG sco es. In ou cases, he con-
side ed biodi e si y oo p in s o IDL, II, and ISS ollow an equally
weigh ed agg ega ion scheme, ha is, he weigh s a e known.
As all oo p in s ollow an equal- weigh ing in gene al, we expec
weigh no o be a subs an ial d i e o he obse ed disag eemen .
A heo e ical a gumen ha weigh should no d i e he disag ee-
men is based on he uni a which he biodi e si y oo p in s a e
measu ed. The oo p in s a e ypically exp essed in MSA o PDF
uni s, which essen ially quan i y he numbe o species o indi id-
uals o a species ha a i m displaces o elimina es wi hin a pa ic-
ula egion. Impac d i e s p o ide mo e g anula da a, indica ing
ha a i m's land use esul s in he ex inc ion o x species/indi id-
uals, while wa e pollu ion causes he loss o y species/indi iduals,
o ins ance. Na u ally, impac d i e s a e simply summa ized,
and while di e en weigh ing makes sense o ESG sco es, i does
no o oo p in s in MSA and PDF uni s.
4.3 | Decomposi ion
The p e ious sec ion showed ha he p o ide s disag ee bo h in
scope and measu emen . In his sec ion, we ollow Be g, Kölbel,
and Rigobon(2022) and decompose he oo p in s o de e mine
how much each ac o con ibu es o he o e all disag eemen
be ween he oo p in s.
Le
F i
be he no - s anda dized oo p in o a i m
, gi en by a
P o ide
i∈{1;2;3}
. Fo each wo P o ide s
i,j
(
i,j∈{1;2;3},i≠j
),
i hen holds:
whe e
D i,com
is he sum o he impac d i e s by p o ide 
i
ha
i
has in common wi h p o ide 
j
o i m
, measu ed in PDF o
MSA depending on he p o ide , and
D i,ex
is he sum o he mu-
ually exclusi e impac d i e s o p o ide 
i
and
j
, by p o ide 
i
o i m
.
As he o iginal oo p in s a e gi en in di e en me ics depend-
ing on he p o ide (PDF o MSA), we ha e o s anda dize he
oo p in s o he same uni when we analyze he di e ences in
he oo p in s o wo p o ide s. I ollows om he o mula o he
z- s anda diza ion ha o he s anda dized oo p in
Fz
i
o i m
by P o ide 
i
, i holds he ollowing:
whe e
d i
is he alue o a single impac d i e by P o ide 
i
o
i m
om ei he he se o common impac d i e s
D i,com
o
he se o exclusi e impac d i e s
D i,ex,𝜇i
is he c oss- sec ional
mean o all agg ega ed oo p in s by P o ide 
i,𝜎i
he s anda d
de ia ion o he agg ega ed oo p in s by P o ide 
i
, and
Ni
he
numbe o impac d i e s (bo h exclusi e and common) ha
P o ide 
i
is including. In ou case,
Ni
is 4 o all p o ide s.Fo
easie eadabili y, we de ine he i s summand o Equa ion(3)
as
Dz
i,com
and he second summand as
Dz
i,ex
.
Consequen ly, we can decompose he di e ence
Δz
i,j
in he s an-
da dized oo p in s by P o ide s
i
and
j
o i m
in he ollow-
ing way:
(2)
F i =D i,com +D i,ex
(3)
F
z
i =∑
d i∈D i,com
d i −
1
Ni𝜇i
𝜎i
⏟⏞⏞⏞⏞⏞⏞⏞⏞⏞⏟⏞⏞⏞⏞⏞⏞⏞⏞⏞⏟
:=Dz
i
,
com
+∑
d i∈D i,ex
d i −
1
Ni𝜇i
𝜎i
⏟⏞⏞⏞⏞⏞⏞⏞⏞⏟⏞⏞⏞⏞⏞⏞⏞⏞⏟
:=Dz
i
,
ex
TABLE 5 | This able shows he pai - wise Pea son (Spea man in pa en heses) co ela ions be ween he p o ide s o each impac d i e as well
as K ippendo 's alpha measu ing he ag eemen o e all a e s.
Clima e Change Land Use & Pollu ion Ai Pollu ion Wa e Pollu ion
Pea son (Spea man) co ela ion be ween P o ide 1 and
P o ide 2 0.546 0.660 0.442 0.158
(0.667) (0.507) (0.651) (0.344)
P o ide 3 0.002 0.311 − 0.006
(0.672) (0.553) (0.495)
Pea son (Spea man) co ela ion be ween P o ide 2 and
P o ide 3 0.083 0.403 0.039
(0.850) (0.718) (0.669)
K ippendo 's alpha 0.211 0.458 0.442 0.064
5894 Business S a egy and he En i onmen , 2025
We de ine
Δz
i,j,meas
as he di e ence be ween
Dz
i,com
and
Dz
j,com
,
s emming om di e gence in he measu emen o he common
impac d i e s, and
Δz
i,scope
as he di e ence be ween
Dz
i,ex
and
Dz
j,ex
, s emming om di e ences in he scope o each p o ide .
As all a ings a e no malized o ha e a mean o ze o, he o al
di e ence be ween wo a ings sums o ze o as well. Howe e ,
he i m- speci ic di e ences a y om ze o. By using he a i-
ance as a measu e o disag eemen , we ob ain summa y s a is-
ics o hese di e ences. The e o e, we ake he a iance o e he
sample o i ms in Equa ion(4) and ob ain he ollowing:
Now we can calcula e he con ibu ion o scope and measu e-
men o he disag eemen as
Table6 p esen s he esul s o Equa ion(6) o each pai o p o id-
e s, and he a e age o each p o ide . O e all, he con ibu ion o
measu emen o he o e all disag eemen is 96.29% and hus con-
side ably highe han ha o scope (3.71%). As P o ide s 1 and 2
conside he same impac d i e s, hei disag eemen s ems only
om di e gence in measu emen . Despi e conside ing a unique
se o impac d i e s compa ed o he o he p o ide s, he a e age
con ibu ion o scope di e gence o he o e all disag eemen is
only 5.56% o P o ide 3. This can be explained by he con ibu-
ion o each impac d i e o he en i e oo p in ha is p esen ed
in Table4. The impac d i e Wa e Ex ac ion, which is no con-
side ed by P o ide s 1 and 2, only has a e y small impac on he
o e all oo p in by P o ide 3, while he impac d i e Land Use
& Pollu ion, which is sha ed wi h bo ho he p o ide s, con ibu es
by a he mos o he en i e oo p in .
5 | De e minan s o he Disag eemen
In his sec ion, we analyze how he disag eemen be ween he
impac d i e and di e en i m cha ac e is ics is d i ing he
o e all disag eemen . Fo ha pu pose, we ollow Bauckloh
e al.(2024) and calcula e he wo i m- le el disag eemen mea-
su es sd and max−min. sd is he s anda d de ia ion o he h ee
s anda dized oo p in s pe i m, while max−min is he di e -
ence be ween he maximum and he minimum s anda dized
oo p in o each i m. The same disag eemen measu es a e
calcula ed a he impac d i e le el.
Fi s , we explain he a ia ion in he o e all sd and max−min
wi h he espec i e disag eemen measu es a he impac d i e
le el by unning he ollowing wo eg ession models, using o-
bus s anda d e o s:
whe e
sd(impac d i e )
and
max
−
min(impac d i e )
ep esen
he s anda d de ia ion and ange o he s anda dized assess-
men s o he h ee p o ide s o he espec i e impac d i e o
each i m
.
𝛼
is he cons an e m and
𝛽j(j=1, …, 4)
a e he
coe icien s es ima ed in he eg ession analysis. As he impac
d i e Wa e Ex ac ionis exclusi ely conside ed by P o ide 3,
i is no included in his pa o he analysis.
Table7 shows he esul s. The high
R2
o 0.876 and 0.874 indica e
ha he o e all disag eemen can be explained o a la ge ex en
h ough he disag eemen a he impac d i e le el, which unde -
lines he esul s ound in he decomposi ion (Sec ion4.3). The dis-
ag eemen measu es o bo h impac d i e s Clima e Change and
Wa e Pollu ion ha e coe icien s signi ican a 1%- le el. Clima e
Change (Wa e Pollu ion) displays a coe icien o 0.387 (0.352) o
he sd- eg ession and 0.382 (0.349) o he max− min- eg ession.
(4)
Δz
i,j=
Fz
i −
Fz
j
=Dz
i,com −Dz
j,com
⏟⏞⏞⏞⏞⏞⏞⏟⏞⏞⏞⏞⏞⏞⏟
:=Δz
i,j,meas
+Dz
i,ex −Dz
j,
ex
⏟⏞⏞⏞⏞⏟⏞⏞⏞⏞⏟
:=Δz
i,j,scope
(5)
Va (
Δ
z
i,j
)
=
Co (
Δ
z
i,j
,
Δ
z
i,j
)
=Co (Δz
i,j
,Δz
i,j,meas
)+Co (Δz
i,j
,Δz
i,j,scope)
(6)
Con ibu ion Measu emen
=
Co (
Δ
z
i,j
,
Δ
z
i,j,meas
)
Va (Δz
i,j)
Con ibu ion Scope =
Co (Δz
i,j,Δz
i,j,scope
)
Va (Δz
i,j
)
(7)
sd
=
𝛼
+
𝛽1
×sd(Land Use &Pollu ion)
+𝛽2×sd(Wa e Pollu ion)
+𝛽3×sd(Clima e Change)
+𝛽4×sd(Ai Pollu ion)
+𝜖
(8)
max
−
min
=𝛼+𝛽1×
max
−
min(Land Use &Pollu ion)
+𝛽2×max−min(Wa e Pollu ion)
+𝛽3×max−min(Clima e Change)
+𝛽4×max−min(Ai Pollu ion)
+𝜖
,
TABLE 6 | This able p esen s he con ibu ion o measu emen and
scope o he disag eemen .
Measu emen Scope
Panel A: Ra e pai s
P o ide 1 P o ide 2 100.00% 0.00%
P o ide 1 P o ide 3 99.45% 0.55%
P o ide 2 P o ide 3 89.43% 10.57%
A e age 96.29% 3.71%
Panel B: Ra e a e ages
P o ide 1 99.73% 0.27%
P o ide 2 94.72% 5.28%
P o ide 3 94.44% 5.56%