D'Albe o, Ricca do; Raggi, Me i; Viaggi, Da ide
A icle
Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public
Goods p o ision: Which ea u es mee he a me s' app o al? Insigh s
om Emilia-Romagna (I aly)
Bio-based and Applied Economics (BAE)
P o ided in Coope a ion wi h:
Fi enze Uni e si y P ess
Sugges ed Ci a ion: D'Albe o, Ricca do; Raggi, Me i; Viaggi, Da ide (2024) : Inno a i e con ac
solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision: Which ea u es mee he
a me s' app o al? Insigh s om Emilia-Romagna (I aly), Bio-based and Applied Economics (BAE),
ISSN 2280-6172, Fi enze Uni e si y P ess, Flo ence, Vol. 13, Iss. 1, pp. 73-101,
h ps://doi.o g/10.36253/bae-14016
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Bio-based and Applied Economics 13(1): 73-101, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14016
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Ci a ion: D’Albe o, R., Raggi, M., &
V i a g g i , D . ( 2 0 2 4 ). I n n o a i e c o n a c s o l u -
ions o he Ag i-En i onmen al-Cli-
ma e Public Goods p o ision: Which
ea u es mee he a me s’ app o al?
Insigh s om Emilia-Romagna (I aly).
Bio-based and Applied Economics 13(1):
73-101. doi: 10.36253/bae-14016
Recei ed: No embe 30, 2022
Accep ed: May 05, 2023
Published: May 20, 2024
Da a A ailabili y S a emen : All el-
e an da a a e wi hin he pape and i s
Suppo ing In o ma ion iles.
Compe ing In e es s: The Au ho (s)
decla e(s) no con lic o in e es .
Gues Edi o s: S e ano Ta ge i,
And eas Niede may , Ka i Hä ne ,
Lena Schalle
ORCID
RD: 0000-0002-7227-7485
MR: 0000-0001-6960-1099
DV: 0000-0001-9503-2977
Inno a i e con ac solu ions o he Ag i-
En i onmen al-Clima e Public Goods
p o ision: Which ea u es mee he a me s’
app o al? Insigh s om Emilia-Romagna (I aly)
Ricca do D’Albe o1,*, Me i Raggi2, Da ide Viaggi3
1 Dep . o Economics, Uni e si y o Ve ona, Via Can a ane 24, 37129 Ve ona (VR), I aly
2 Dep . o S a is ical Sciences “P. Fo una i”, Alma Ma e S udio um Uni e si y o Bolo-
gna, Via Delle Belle A i 41, 40126 Bologna (BO), I aly
3 Dep . o Ag icul u al and Food Sciences (DISTAL), Alma Ma e S udio um Uni e si y o
Bologna, Viale Fanin 50, 40127 Bologna (BO), I aly
*Co esponding au ho . E-mail: icca do.dalbe o@uni .i
Abs ac . The ag oecological ansi ion p omo ed wo ldwide is suppo ed by he
Eu opean Union Common Ag icul u al Policy owa ds di e en s a egies and pol-
icy ools. The ag i-en i onmen al schemes, o e ing a me s he possibili y o adop
en i onmen - iendly p ac ices ( hus mi iga ing nega i e ex e nali ies/p o iding posi-
i e ones) ep esen a s aigh o wa d example. Howe e , he e is dissa is ac ion abou
hei e ec i eness and e iciency, while hei imp o emen is en isaged h ough a lex-
ible mix o new ins umen s: no el con ac solu ions os e ing esul -based paymen s,
collec i e implemen a ion, in ol ing alue chains and land enu e sys ems coupled
o en i onmen al condi ionali y. This pape in es iga es how a me s om Emilia-
Romagna (I aly) pe cei e hese inno a i e con ac solu ions as “easy o unde s and”,
“applicable”, “economic bene icial”, and hei willingness o en oll. The applied o de ed
logis ic eg ession models include socio-demog aphic cha ac e is ics, s uc u al ea-
u es o he holdings, and he a me s’ p e e ence(s) o 13 indi idual con ac ea-
u es. Fa me s’ pe cep ions a e d i en by he p e ious expe ience acqui ed om simi-
la measu es, key socio-demog aphic cha ac e is ics/holding s uc u al ea u es, and
peculia con ac ual elemen s.
Keywo ds: public goods, esul -based, collec i e app oach, alue chain, land enu e.
JEL codes: Q15, Q20, Q57.
1. INTRODUCTION
An ag oecological ansi ion1 is being p omo ed wo ldwide h ough he
UN 2030 Agenda o Sus ainable De elopmen (Uni ed Na ions, 2015) and
1 Ag oecological ansi ion co esponds o a sys emic ans o ma ion gene a ed by he ecologisa ion
o ag icul u e and ood. I conce ns mul iple ac o s among a me s, supply chains, na u al esou ce
manage s, policymake s, e c. and i is cha ac e ized by he ac ha a delibe a e poli ical in en ion
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Bio-based and Applied Economics 13(1): 73-101, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14016
D’Albe o Ricca do e al.
in pa icula in he Eu opean Union (EU) h ough i s
Common Ag icul u al Policy (CAP) and he Eu ope-
an G een Deal (Baldock and Buckwell, 2021; Eu opean
Commission, 2019).
Among he CAP s a egies and policy ools, he
mos popula ins umen is he eco-condi ionali y
embedded in he indi ec subsidies (Mamine e al., 2020)
which makes he paymen condi ional on he up ake o a
se o ac ions conside ed app op ia e o educing nega-
i e ex e nali ies o imp o ing posi i e ones (Hanley e
al., 2012; Whi e and Hanley, 2016). Complemen a y o
ha , he ag i-en i onmen al schemes (AESs) unded
by he CAP a e based on paymen s o a me s o he
up ake o en i onmen - iendly p ac ices and he p o i-
sion o ecosys em se ices ha go beyond condi ional-
i y. AESs a e a compulso y elemen o he EU Membe
S a es u al de elopmen plans (RDP) design bu a e ol-
un a y o a me s. Thei ele ance lies in he manda o y
sha e o unds alloca ed o co- inancing: 30% o CAP
Pilla II (supposed o g ow in he u u e).
A la ge body o li e a u e conside s AESs, assess-
ing hei ag i-en i onmen al-clima e e ec s (see Hasle
e al., 2022 and he e e ences he ein), analyzing hei
cos -e ec i eness and e iciency (Ansell e al., 2016; Ba -
olini e al., 2021; Blazy e al., 2021; D echsle e al., 2017;
Pacini e al., 2015), es ima ing he e ec s on he ag icul-
u al holdings s uc u e and p oduc i e choices (A a a
and Sckokai, 2016; Be oni e al., 2020; Chabé-Fe e and
Sube ie, 2013; D’Albe o e al., 2018; Mennig and Sau-
e , 2020), and de ec ing he ac o s ha in luence a m-
e s’ up ake decision and beha io (B own e al., 2021;
D echsle , 2021; Gailha d e al., 2015; Raina e al., 2021;
Ve gamini e al., 2020).
Despi e his abundan li e a u e and he knowledge
on AESs, he e is dissa is ac ion abou hei e ec i e-
ness and e iciency in deli e ing ag i-en i onmen al-cli-
ma e public goods (AECPGs2) and in e ms o achie e-
men s longe i y (Bi i e al., 2021; Bullock e al., 2021).
Nowadays, AESs a e la gely domina ed by ac ion-based
app oaches add essing indi idual a me s, while hei
imp o emen is en isaged h ough a lexible mix o new
ins umen s (He zon e al., 2018; Oli ie i e al., 2021),
such as con ac solu ions os e ing esul -based pay-
men schemes o collec i e implemen a ion, and solu-
ions in ol ing alue chains and/o implemen ing new
o ms o land enu e sys ems coupled o en i onmen al
is willing o b ing such a ans o ma ion o mo e owa ds a mo e
sus ainable ag icul u al and ood sys em (Mag ini e al., 2019).
2 These a e non- i al, non-excludable goods p o ided by ag icul u e
and o es y wi h di ec implica ions in e ms o (po en ial) posi i e
ex e nali ies o bo h clima e and en i onmen (e.g., ca bon
seques a ion, ai and wa e quali y and quan i y, soil es o a ion/
main enance, e c.) (Coope e al., 2009).
condi ionali y. These no el app oaches a e expec ed o
p o ide AECPGs in a mo e e icien and e ec i e way,
being complian wi h wha is en isaged by he Fa m o
Fo k s a egy and he EU Biodi e si y S a egy o 2030.
The o me is a he hea o he Eu opean G een Deal
ha aims a making Eu ope he i s clima e-neu al
con inen by 2050. I plans o educe he en i onmen al
and clima e oo p in o he EU ood sys em by add ess-
ing comp ehensi e challenges in e ms o sus ainabili y
owa ds a ansi ion ha ensu es ha he whole ood
chain has a neu al o posi i e en i onmen al impac
(Eu opean Commission, 2020a). The la e s ongly sup-
po s such a ansi ion by acknowledging ha i canno
be success ully achie ed wi hou es o ing he endan-
ge ed ecosys ems, “b inging na u e back o ag icul u al
land” (Eu opean Commission, 2020b). Bo h ini ia i es
s ongly suppo and incen i ize he ansi ion o ully
sus ainable p ac ices.
To he bes o ou knowledge, some o hese new
incen i e app oaches ha e been mainly in es iga ed
indi idually, like he esul -based paymen s – he mos
s udied ins umen so a – (Bi ge e al., 2017; Russi e
al., 2016; Sidemo-Holm e al., 2018; Šum ada e al., 2022,
2021; Zabel, 2019) and he collec i e app oaches (El
Mokaddem e al., 2016; Na loch e al., 2017; Wes e ink e
al., 2017), while land enu e con ac s wi h en i onmen-
al clauses and he ini ia i es along he alue chain we e
seldom add essed by he li e a u e.
This pape in es iga es ou no el con ac solu ions
o he AECPGs p o ision: esul -based (RB), collec i e
(Co), alue chain (VC), and land enu e (LT) con ac s.
These con ac ypes a e analyzed in e ms o a me s’
accep abili y and willingness o up ake, by assessing:
1) The a me s’ pe cep ion o he easiness o unde -
s anding ela ed o he inno a i e con ac solu ion.
2) The a me s’ pe cep ion o he con ac ’s applicabil-
i y in he a m.
3) The a me s’ pe cep ion o he economic bene i
de i ing om he con ac .
4) The a me s’ willingness o en oll.
The p e e ences conce ning hese poin s a e
explained using he socio-demog aphic cha ac e is ics o
he a me s/land manage s and he s uc u al ea u es o
he ag icul u al holdings. The pape also ocuses on he
assessmen o he in luence ha 13 indi idual ea u es
ha de ine he con ac solu ions can play in de e min-
ing he a me s’ p e e ences. Da a a e collec ed by means
o an online su ey ca ied ou wi hin he EU CONSOLE
P ojec 3 among he a me s o Emilia-Romagna (I aly).
3 The CONSOLE P ojec has ecei ed unding om he Eu opean
Union’s Ho izon 2020 Resea ch and Inno a ion P og amme unde G an
Ag eemen No. 817949. Fo u he de ails: h ps://console-p ojec .eu.
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Bio-based and Applied Economics 13(1): 73-101, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14016
Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
The no el y o he pape lies in 1) he in es iga ion
o a me s’ pe cep ions o ou new, incen i e con ac
ypes ha combine a lexible mix o new ins umen s;
2) he inclusion in he modeling exe cise (in addi ion o
he socio-demog aphic cha ac e is ics o he a me as
well as he s uc u al ea u es o he ag icul u al hold-
ing) o he in o ma ion abou he a me s’ p e e enc-
es o se e al indi idual ea u es cha ac e izing hese
ins umen s; 3) he applica ion o o de ed logis ic eg es-
sion ha , o he bes o ou knowledge, has ne e been
applied o analyze a me s’ p e e ences o AECPGs
con ac s.4 O de ed logis ic eg ession models a e a he
solid (Ag es i, 2019, 2010), bu he so-called pa ial p o-
po ional odds/non-pa allel lines modelling app oach
has only ecen ly a ained a cohesi e o maliza ion (Wil-
liams, 2006; Yee, 2010). The main, ecen inno a ion
consis ed in hei expansion o allowing he elaxa-
ion o i s key assump ion, he “p opo ionali y o he
odds” (Williams, 2016). The la e s a es ha a espond-
en ope a es a p opo ional shi when e alua ing his/
he p e e ences o he le els depic ed by he ca ego ical
ou come a iable. In o he wo ds, he assump ion s a es
ha he “dis ance” in e ms o indi idual’s p e e ences
be ween a lowe le el o he ca ego ical ou come a i-
able and a highe one, is p opo ional o all he le els
o such a a iable. I has been demons a ed ha iola-
ions o his assump ion equen ly occu in p ac ice
and hey ha e been nimbly dis ega ded (B an , 1990;
Long and F eese, 2014; Xu e al., 2022), hence leading o
biased and mis-in e p e able esul s (Ag es i, 2010). This
is no he case o he p esen wo k. Indeed, we es he
p opo ionali y o he odds and elax he assump ion
when needed. This elaxa ion allows o a oiding biased
es ima es by p ope ly depic ing he shi o indi idual’s
p e e ences among he di e en le els o he ca ego i-
cal ou come a iable, applying he pa ial p opo ional
odds model when he e is no p opo ionali y o he odds
abou he le els o p e e ence.
The esul s hin a he in luence ha p e ious expe-
ience (acqui ed om e y simila measu es), key socio-
demog aphic cha ac e is ics, and s uc u al ea u es o
he holding play in d i ing he a me s’ pe cep ions o
he easiness o unde s anding, applicabili y, and eco-
nomic bene i o he con ac solu ions, as well as hei
willingness o en oll. In addi ion, he abo e-men ioned
pe cep ions can be in luenced by peculia con ac ual
elemen s, no only hose s aigh o wa dly linked o he
iden i ica ion o he con ac ype.
The pape is s uc u ed as ollows: sec ion 2 p esen s
he esea ch amewo k, he case s udy, he da a a hand,
4 A simila applica ion (logi modelling), bu a ge ing AESs is o e ed
by Gailha d and Bojnec (2015).
and he s a is ical me hod. Sec ion 3 p esen s he esul s,
while in sec ion 4 we discuss hem. Finally, sec ion 5
hos s he conclusions.
2. DATA AND METHODS
2.1 Case s udy
The Emilia-Romagna egion is loca ed in No h-
eas e n I aly. The sou he n pa is hilly and includes he
moun ainous a eas o he Apennines, while he sou h-
e n pa o he Po Ri e plain domina es he no he n
po ion o he e i o y. The plains a e cha ac e ized by
in ensi e ag icul u e and a able c ops, he hills by ine-
ya ds and o cha ds, and he moun ains mainly by g ass-
lands, a able c ops, and woods. The plain a ea is highly
u banized, while he moun ainous a eas a e ma ginal-
ized and cha ac e ized by land abandonmen .
Da a on Emilia-Romagna ci izens we e collec ed
online, using Qual ics, om May o July 2021 wi h a
ques ionnai e p omo ed on he ins i u ional websi e
o he Emilia-Romagna egion dedica ed o Ag icul-
u e (Regione Emilia-Romagna, 2022a) and on he co -
esponding o icial Facebook page (Regione Emilia-
Romagna, 2022b), allowing esponden s o eely access
he Qual ics link. 559 ques ionnai es we e ini ia ed, o
which 305 comple ely answe ed ques ionnai es (55%) a e
used o he p esen analysis. Table 1 depic s he main
desc ip i e s a is ics o he sample.
2.2 Ques ionnai e o e iew
The su ey ques ionnai e (D’Albe o e al., 2022) is
based on wo pa s: he i s collec s he socio-demo-
g aphic cha ac e is ics o he esponden and he main
cha ac e is ics o he ag icul u al holding he/she man-
ages/owns; he second ocuses on he con ac solu ions.
Fi s , we in es iga ed he esponden ’s p e e ence(s) o
13 indi idual ea u es ha po en ially de ine a gene ic
en i onmen al p og amme/con ac . Secondly, in o ma-
ion on he esponden ’s p e e ence abou he ou con-
ac solu ions (RB, Co, VC, LT) was collec ed, speci ied
in e ms o “unde s andabili y”, “applicabili y” in he
a m, and “economic bene i ”. Finally, he esponden
was asked abou his/he willingness o en oll.
Table 2 depic s he 13 indi idual con ac ea u es
wi h hei de ini ions, buil on he indings om he sci-
en i ic li e a u e e iew on he subjec (Eichho n e al.,
2020) in combina ion wi h he insigh s ga he ed om
he discussion o such indings among (and wi h) he
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D’Albe o Ricca do e al.
Table 1. Desc ip i e s a is ics o he sample.
Explana o y a iable N . o obse a ions Pe cen Q1, Median, Mean, Q3
(S anda d De ia ion)
Gende
male 264 86.56 %
emale 41 13.44 %
Age
18-30 29 9.51 %
31-40 42 13.77 %
41-50 67 21.97 %
51-60 104 34.10 %
61-70 41 13.44 %
>71 22 7.21 %
Educa ional le el
p ima y 74 24.26 %
seconda y 156 51.15 %
uni e si y o highe – BA’s, MA’s, Ph.D. o equi alen 75 24.59 %
Membe ship
none 149 48.85 %
a me s union 108 35.41 %
na u e conse a ion/ en i onmen al o ganiza ion 48 15.74 %
P opo ion o holding sales – o p ocesso
0 % 213 69.84 %
1-30 % 38 12.46 %
31-60 % 14 4.59 %
61-100 % 40 13.11 %
P opo ion o holding sales – o p i a e wholesale / e aile
0 % 139 45.57 %
1-30 % 58 19.02 %
31-60 % 25 8.20 %
61-100 % 83 27.21 %
P opo ion o holding sales – o coope a i es
0 % 193 63.28 %
1-30 % 21 6.89 %
31-60 % 21 6.89 %
61-100 % 70 22.95 %
P opo ion o holding sales – di ec o inal consume
0 % 228 74.75 %
1-30 % 37 12.13 %
31-60 % 15 4.92 %
61-100 % 25 8.20 %
Specializa ion
a able 136 44.59 %
ho icul u e 15 4.92 %
pe manen 84 27.54 %
li es ock 32 10.49 %
mixed 38 12.46 %
(Con inued)
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Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
Eu opean s akeholde s (Viaggi e al., 2020b).5 These ea-
u es we e selec ed since hey po en ially cha ac e ize,
in gene al, an ag i-en i onmen al p og amme/con ac
and, a he same ime, o being speci ically dis inc i e
o one (o mo e) incen i e con ac solu ion. Fo exam-
ple, “ he paymen ge s highe , he be e you en i on-
men al esul s a e” speci ically i s o esul -based con-
ac solu ion. Howe e , his con ac ual elemen can
be pa o a collec i e-based incen i e o a solu ion
in ol ing he alue chain. The e o e, he ea u es a e no
explici ly linked o a con ac ype, while each o hem
can ega d a speci ic aspec o he con ac . Finally, as
pe he s akeholde s’ sugges ions and insigh s, he 13
ea u es help in aming he gene al idea o he inno a-
i e con ac solu ions in he mos unde s andable way
o he EU a me s/land manage s, dis ega ding hei
expe ience(s) wi h he CAP ag i-en i onmen al-clima e
measu es (AECMs).
The ea u es in Table 2 we e p esen ed o he
esponden as gene al a ibu es o a hypo he ical ag i-
en i onmen al con ac /p og amme. Be o e desc ib-
ing RB, Co, VC, and LT con ac solu ions in de ail, he
esponden was asked: “How much would he ollowing
5 The li e a u e e iew ound and analyzed 58 exis ing case s udies
wi hin and ou side he EU. A su ey among p ojec pa ne s and
s akeholde s and a wo kshop add essing 105 s akeholde s om 11
EU Membe S a es and he Uni ed Kingdom we e held o discussing,
selec ing, and deba ing he mos p omising examples.
cha ac e is ics o ag i-en i onmen al con ac s inc ease
o dec ease you willingness o en oll o an en i onmen al
con ac o p og amme?”. The possible answe s (Like
scale) we e: 1 = “Dec eases my willingness conside ably”,
2 = “Somewha dec eases my willingness”, 3 = “No e ec
on my willingness”, 4 = “Somewha inc eases my will-
ingness”, 5 = “Inc eases my willingness conside ably”.
Table 3 depic s he desc ip ions o he ou con ac
solu ions o e ed o he esponden (Viaggi e al., 2020a,
2020b).
A e each sho desc ip ion o he con ac , he
esponden was asked: “How do you see his con ac ype?
Do you ag ee o disag ee wi h he ollowing s a emen s?”.
The h ee s a emen s we e: “Easy o unde s and”, “Appli-
cable o my a m”, and “Po en ially economically bene i-
cial o my a m”. The esponden was asked o exp ess an
opinion whe e 1 = “S ongly Disag ee”, 2 = “Disag ee”, 3
= “Neu al”, 4 = “Ag ee”, 5 = “S ongly Ag ee”.
Finally, o each speci ic con ac solu ion (RB, Co,
VC, LT) he esponden was asked: “How likely is ha
you would en oll in a –name– con ac ype in he u u e?”
( he answe s we e 1 = “Ve y Unlikely”, 2 = “Unlikely”, 3
= “Neu al”, 4 = “Likely”, 5 = “Ve y Likely”).
Conside ing he con ac ea u es p esen ed in Table
2, Figu e 1 depic s he dis ibu ion o he sco es ha
ha e been gi en by he esponden s o he 13 indi idual
con ac ea u es.
As pe Figu e 1, he e a e indi idual con ac ea-
u es ha ele an ly in luence, in a posi i e way, he
Explana o y a iable N . o obse a ions Pe cen Q1, Median, Mean, Q3
(S anda d De ia ion)
O ganic p oduc ion
no 232 76.07 %
yes 73 23.93 %
U ilized Ag icul u al A ea owned – in hec a es 5.5, 18, 62.41, 40
(191.57)
U ilized Ag icul u al A ea en ed in – in hec a es 0, 9, 49.67, 45
(188.81)
Di ec CAP paymen s
no 60 19.67 %
yes 245 80.33 %
RDP paymen s – Eu o
no 115 62.30 %
yes 190 37.70 %
P e ious expe ience
no 205 67.21 %
yes 100 32.79 %
No e: Q1 = 1s qua ile; Q3 = 3 d qua ile.
Table 1. (Con inued).
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D’Albe o Ricca do e al.
willingness o en oll in a hypo he ical ag i-en i onmen-
al con ac /p og amme, e.g., “sel -chosen measu es”,
“be e esul s, highe paymen ”, and “annual compensa-
ion”. Namely, esponden s s a ed ha each one o hese
cha ac e is ics con ibu e in inc easing conside ably
hei willingness o en oll in an en i onmen al con ac /
Table 2. Indi idual con ac ea u es.
Con ac ea u e De ini ion
Sel -chosen measu es In he con ac , you a e ee o decide abou he managemen p ac ices o achie e he speci ied
en i onmen al esul (s).
Be e esul s, highe paymen The paymen ge s highe , he be e you en i onmen al esul s a e.
Collec i e ag eemen You can collec i ely ag ee on en i onmen al a ge s and measu es a landscape-le el oge he wi h o he
land manage s/ o es s owne s.
Common paymen You and o he land manage s ( a me s/ o es s owne s) ecei e a common paymen . You join ly ag ee on
he dis ibu ion o he paymen .
Labelled p oduc You sell you holding’s p oduc s labelled as en i onmen ally iendly (e.g., animal wel a e p oduc s, clima e
iendly p oduc s) when ollowing managemen measu es as p esc ibed in a p ocesso o e aile con ac .
Paid by cus ome s The con ac is no paid by public money, ins ead he compensa ion ha you ge o en i onmen ally
iendly p oduc ion is paid by buye s o you p oduc s.
Reduced land en You can lease land wi h a educed en , i you ag ee o ollow en i onmen al managemen clauses as
speci ied in he lease con ac .
Sel -moni o ing You can do he moni o ing o he en i onmen al esul s you sel (e.g., coun speci ic plan s).
Con ol by au ho i y The esul s ha you achie e a e egula ly con olled by he compe en au ho i y coming on o you a m,
e.g., once pe yea .
F ee aining o ad ice You a e o e ed ee aining and ad ice ha enables you o each he en i onmen al a ge s.
Sales gua an ee You ge a sales gua an ee om a p ocesso o e aile in e u n o implemen ing en i onmen al measu es.
Annual compensa ion You ge en i onmen al compensa ion paymen on an annual basis.
Pe iodical paymen You ge hal o he en i onmen al paymen a he beginning o , e.g., he i e-yea con ac , and hal a he
end o i .
Table 3. Con ac solu ions desc ip ions.
Con ac solu ion Desc ip ion
Resul -based
In a esul -based con ac you ecei e a paymen only o he deli e y o en i onmen al o clima e esul s. You
a e ee in you decision abou he managemen p ac ices, e.g., how o con ibu e o wa e p o ec ion, landscape
imp o emen , biodi e si y o o seques e ca bon. Selec ed indica o s and sco ing sys ems o moni o en i onmen al o
clima e esul s a e o en used, and hey will be exac ly de ined in he con ac . You ha e access o ee ad ice o aining
when you pa icipa e in his con ac , and you can olun a ily engage in he moni o ing ac i i y.
Collec i e
You become a membe o a g oup o land manage s ( a me s o o es e s) who applies join ly o compensa ion in
o de o implemen en i onmen al o clima e ac i i ies, e.g., wa e p o ec ion, ca bon seques a ion, biodi e si y o
landscape imp o emen . A minimum numbe o g oup membe s (e.g., 5) om you egion is equi ed o collabo a e
in o de o ge a paymen . The g oup membe s decide abou he implemen a ion and loca ing he measu es, and he
dis ibu ion o he paymen . Wi hin he g oup, pee land manage s and ad iso s sha e knowledge and suppo he
achie emen o he en i onmen al objec i es.
Value chain
As a p oduce , you a e pa o he alue chain (p oduce , p ocesso , e aile , dis ibu o ). You engage in a con ac
whe e you commi o deli e en i onmen al o clima e bene i s connec ed o he p oduc ion o selec ed p oduc s,
e.g., by ca ying ou managemen measu es which con ibu e o wa e p o ec ion, landscape imp o emen , biodi e si y,
o ca bon seques a ion. O en hese p oduc s ge a special label. You a e paid o i by he ma ke , mainly h ough a
p emium p ice paid by he p ocesso o e aile .
Land enu e
You en e in o a land- enu e con ac whe e you commi o gi e pa icula a en ion o en i onmen al aspec s
beyond legal equi emen s when p oducing on he leased land. The landowne accep s a lowe lease paymen
han o compa able land unde usual land enu e ag eemen s o compensa e you addi ional e o s. In he con ac
en i onmen ally iendly managemen p ac ices on he leased land a e p esc ibed in o de o main ain o imp o e
en i onmen al a ge s, e.g., wa e p o ec ion, landscape and biodi e si y imp o emen o ca bon seques a ion o
al e na i ely.
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Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
p og amme. In con as , a ea u e like, e.g., “common
paymen ” has a nega i e in luence on he willingness o
en oll (i.e., i is expec ed o somewha dec ease such a
willingness).
2.3 Me hodological app oach: p opo ional odds and pa -
ial p opo ional logi models
The socio-demog aphic cha ac e is ics o he
esponden s, he cha ac e is ics o ag icul u al hold-
ings, and he sco es ela ed o he 13 indi idual con ac
ea u es a e used as explana o y a iables in he mod-
els (one o each incen i e con ac solu ion) whe e he
o de ed esponse a iables a e 1) he easiness o unde -
s anding, 2) he applicabili y in he a m, 3) he economic
bene i , 4) he willingness o en oll.
These ou come a iables a e o de ed ca ego ical
a iables, based on a Like scale. They can be ea ed
by he o de ed logi model, also called he p opo ional
odds (PO) o pa allel lines (PL) model (Mccullagh, 1980;
Winship and Ma e, 1984). Following he no a ion o
Ag es i (2010), le Y be he ou come o in e es : an o di-
nal dependen a iable o M ca ego ies obse ed o he
i- h indi idual (i=1,…,N). The gene alized o de ed logi
model can be w i en as:
(1)
whe e j=1,…,M-1. The p obabili ies ha he ou come
a iable akes on each o he alues 1,…,M a e equal o:
P(Yi=1)=1-g(Xiβ1),
P(Yi=j)=g(Xiβj-1)-g(Xiβj), wi h j=2,…,M-1 (2)
P(Yi=M)=g(X_iβM-1).
F om his gene alized amewo k, special cases can
be de i ed. Fo example, when M=2, he model in Equa-
ion 1) equals he logis ic eg ession, while, o M>2, i
Figu e 1. Dis ibu ion o he sco es o he 13 indi idual con ac ea u es.
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D’Albe o Ricca do e al.
becomes equal o a se ies o bina y logis ic eg essions,
one o each pai o ca ego ies o he dependen a iable.
The PO/PL model is a u he special case ha can
be w i en as ollows:
(3)
whe e j=1,…,M-1. Such a model p esen s β coe icien s
ha do no a y ac oss he alues o j, as i is ins ead
in Equa ion 1). The e o e, his modelling app oach
equi es ha only he α’s do a y ac oss he j alues
and, hence, i implies ha he M-1 eg ession lines a e
pa allel. This is he key unde lying assump ion o he
PO/PL model, usually called “p opo ionali y o he
odds”. I s a es ha he ela ionship be ween each pai
o ou come le els is he same. Namely, he shi in indi-
idual’s p e e ences om one le el o he ca ego ical
a iable o he highe /lowe one is p opo ional o all
he le els o such a a iable. I is well-acknowledged
ha his canno always occu in p ac ice. The me hod
has been la gely applied by se e al disciplines in di -
e en ields (Ag es i, 2019), bu iola ions o his un-
damen al assump ion which can equen ly occu in
p ac ice ha e been nimbly dis ega ded (B an , 1990;
Long and F eese, 2014; Xu e al., 2022) leading o biased
and mis-in e p e able esul s (Ag es i, 2010). Fu he -
mo e, his assump ion has been disco e ed o be o e ly
es ic i e (Williams, 2016).
In ac , he PO/PL model o e s wo main p os: 1) i
can lead o highly in e p e able esul s (Williams, 2016);
2) i bene i s om compu a ional e iciency (Ag es i,
2010). Al hough being e y sensi i e o iola ions o he
p opo ionali y o he odds, by elaxing he assump ion,
he a o emen ioned p os can s ill be o in e es in choos-
ing o apply such a modelling s a egy. A success ul solu-
ion o elaxing he assump ion is o e ed by he pa ial
p opo ional logi model (PPO) o non-pa allel lines
model (NPL) (Mccullagh and Nelde , 1989; Pe e son and
Ha ell, 1990). This al e na i e modelling s a egy has
ecen ly gained a en ion due o he de elopmen s p o-
posed by Williams (2006) and Yee (2010), being a g ea
al e na i e o he gene alized o de ed logi model (Wil-
liams, 2016).
Relaxing he p opo ionali y o he odds can lead
o one o mo e β’s di e ing ac oss he alues o j, while
some o he coe icien s can s ill be equal. Fo he sake o
cla i y, le X1,X2,X3 be h ee explana o y a iables. The
model in Equa ion 3) can be e-w i en as:
(4)
whe e j=1,…,M-1. In he model o Equa ion 4) he β’s o
X1,X2 a e he same o all he alues o j, while he coe -
icien o X3 can di e .
Fo he sake o simplici y, he uncons ained PPO
model p oposed by Pe e son and Ha ell (1990) and
u he ex ended by Lall e al. (2002) is adop ed he e.
This model o e s a e-pa ame iza ion o he model in
Equa ion 4) such ha , o each explana o y a iable, we
ha e a coe icien β and M-2 γ coe icien s ha indica e a
de ia ion om p opo ionali y.
The e o e, he e we conside PO/PL models as he
s a ing poin o he analysis, es he p opo ionali y o
he odds, and (when needed) e en ually elax such an
assump ion by adop ing a p ope ly speci ied PPO/NPL
model.
The choice o which explana o y a iables should be
included in he model o he ou come a iable o in e -
es is based on he ollowing s epwise app oach. Fi s ,
we included in he PO-de ined model all he po en ial
explana o y a iables. Second, we checked o con e -
gence o he model, disca ding he explana o y a iables
ha o ced con e gence o ail. Thi d, we ha e unde gone
he assessmen o he pa allel lines assump ion as sug-
ges ed by Long and F eese (2014) and Williams (2016):
i he whole model ails he assump ion acco ding o he
B an es , a PPO-de ined model is un, by elaxing he
assump ion o p opo ionali y o he odds o he explan-
a o y a iables o which he B an es is s a is ically sig-
ni ican . Fou h, we a emp ed o disca d he explana o y
a iables showing non-s a is ically signi ican coe icien s
bu keeping hem i hei disca ding lowe ed he log-like-
lihood and he pseudo-R2 o he model, in compa ison
o he o he , newly de ined model(s) (i.e., we kep hem i
he model’s goodness o i dec eased).
3. RESULTS
In he ollowing, he es ima ed odds a ios a e p e-
sen ed.6
The esul s a e depic ed acco ding o he p esc ip-
ions o C aeme (2009) and Williams (2016): when he
explana o y a iables included in he model mee he
pa allel lines assump ion, he β coe icien s a e depic ed
(wi h he ela ed p- alues). In o he wo ds, i he coe -
icien s a e depic ed only o he i s ca ego y o he
6 Fo he sake o b e i y, only he s a is ically signi ican explana o y
a iables a e depic ed. Please, e e o he supplemen a y ma e ial o
he in eg al e sion o he esul s on he models’ coe icien s. Please,
no e ha we p esen he e only he odds a ios o he s a is ically
signi ican p edic o s, al hough he p edic o s included in he models
we e all hose depic ed in he in eg al e sion o he ables in he
supplemen a y ma e ial.
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Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
– Ac oss he ou con ac solu ions, age has a peculia
(bu well-acknowledged in he li e a u e on he sub-
jec ) ole: he olde he a me , he lowe he willing-
ness o conside he new con ac solu ion as appli-
cable.
The accep ance o con ac ypes is also a ec ed
by he pe cep ion o indi idual con ac ea u es. As
expec ed, he pe cep ions o he con ac ual elemen s
ha mo e e iden ly cha ac e ize each con ac solu-
ion in luence mo e ele an ly he accep ance o a m-
e s abou he incen i e con ac ype (e.g., he collec i e
ag eemen o Co con ac s o he educed land en o
LT con ac s). Howe e , he e a e addi ional con ac
ea u es ha can play a ole in impac ing he le el o
accep ance. Fo example, wi h espec o RB con ac s,
a posi i e pe cep ion o he possibili y o eely deciding
abou he managemen p ac ices o achie e he speci-
ied en i onmen al esul (s) can inc ease he pe cei ed
unde s andabili y o he con ac .
O e all, ou indings hin a he ac ha imp o ed
con ac solu ions can be based on a mix o ins umen s
and ha hese can be mo e p o i ably implemen ed when
ailo ed o he need o a me s/land manage s h ough a
lexible combina ion o a la ge se o di e en con ac-
ual elemen s con ibu ing o he con ac design.
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D’Albe o Ricca do e al.
SUPPLEMENTARY MATERIAL
Tables 4, 5, 6, and 7 o he manusc ip depic he
odds a io o he s a is ically signi ican explana o y a -
iables included in he models conside ed.
He e, we p esen he same ables which, ins ead, do
depic he coe icien s o he explana o y a iables (same
e e ing models). Howe e , he ollowing ables a e p e-
sen ed in hei in eg al e sion (i.e., he ollowing ables
depic he es ima ed models’ coe icien s conce ning all
he explana o y a iables ha we e included in he mod-
els, no only he s a is ically signi ican ones).
Each able is ollowed by a b ie commen abou he
s a is ically signi ican coe icien s.
The ou models in Table 4 a e PO/PL models, as pe
he one depic ed in Equa ion 3) o he manusc ip .
All he s a is ically signi ican a iables depic ed in
Table 4 mee he p opo ionali y o he odds assump-
ion. Highe alues o age make i mo e likely ha he
esponden will be in he cu en (o lowe ) ca ego y
o easiness o unde s anding. Being a membe o na u e
conse a ion/en i onmen al o ganiza ions makes i
mo e likely ha he esponden will unde s and he con-
ac mo e easily. An inc ease in sco ing o sel -chosen
measu es makes i mo e likely ha he esponden will
be in a highe ca ego y o easiness o unde s anding.
The coe icien s o he p opo ion o holding sales ( o
coope a i es), o ganic p oduc ion, sel -chosen measu es,
and collec i e ag eemen posi i ely in luence he pe -
cei ed applicabili y o RB con ac s.
Be e esul s, highe paymen is he only s a is ically
signi ican p edic o o economic bene i in ela ion o
RB con ac s. An inc ease in he sco ing o his con ac
cha ac e is ic makes i mo e likely ha he esponden
will be in a highe ca ego y o economic bene i .
Being olde makes i mo e likely ha he esponden
will be a he cu en le el (o lowe ) o he willingness
o en oll in he con ac . Inc eases in sco ing o sel -mon-
i o ing and pe iodical paymen make i mo e likely ha
he esponden will be in a highe ca ego y o willingness
o en oll. An inc ease in he sco ing o he con ac ea-
u e ee aining makes i mo e likely ha he espond-
en will be in he cu en (o lowe ) le el o willingness.
The models in Table 5 ela ed o he ou come a i-
ables easiness o unde s anding and economic bene i a e
PPO/NPL models, as pe he one depic ed in Equa ion 4)
o he manusc ip . In con as , he models o he ou -
come a iables applicabili y in he a m and willingness
o en oll a e PO/PL models, as pe he one depic ed in
Equa ion 3) o he manusc ip .
Di ec CAP paymen s and collec i e ag eemen p e-
dic o s do ail he es on he p opo ionali y o he
odds. Recei ing di ec CAP paymen s boos s he unde -
s andabili y o he collec i e con ac solu ion, abo e all
wi h espec o he ex eme uppe le els o he o dinal
ou come a iable. Collec i e ag eemen p oduces di e -
gen e ec s on he ex eme lowe and uppe ca ego ies.
P e ious expe ience sugges s ha ha ing expe ienced
collec i e-alike measu es makes he collec i e con ac
mo e “easily unde s andable”.
Being olde nega i ely in luences he pe cei ed
applicabili y o Co con ac s. Being bigge in e ms o
holding size makes i mo e likely ha he esponden
will pe cei e “applicable” he Co con ac . An inc ease
in he sco ing o he a iables collec i e ag eemen and
common paymen makes i mo e likely ha he espond-
en will pe cei e “applicable” he Co con ac .
Pe iodical paymen is he only s a is ically signi i-
can p edic o in luencing (nega i ely) he economic ben-
e i o Co con ac s.
The willingness o en oll is in luenced by age, collec-
i e ag eemen , common paymen , and sel -moni o ing.
Being olde makes i mo e likely ha he esponden
will be in he cu en (o lowe ) ca ego y o willingness
o en oll, while he inc ease in he sco ing o he h ee
con ac ea u es has a posi i e e ec .
The models in Table 6 a e, all, PO/PL models, as pe
he one depic ed in Equa ion 3) o he manusc ip .
Being a holding wi h a sha e o sales o 1-30% o
p i a e wholesale s/ e aile s makes i less likely ha
a esponden will be in a highe ca ego y o easiness o
unde s anding. Highe alues o p opo ion o holding
sales (di ec o inal consume ) make i mo e likely ha
he esponden will be in a highe ca ego y ( han he
cu en one) o he pe cei ed unde s andabili y. Being
li es ock-specialized holding makes i mo e likely ha
he VC con ac s a e mo e “easily unde s andable”. The
inc ease in he amoun o en ed-in land (in e ms o
hec a es o UAA) makes i mo e likely ha he espond-
en will easily unde s and he VC con ac , as well as
ha ing expe ienced alue chain-alike measu es.
Being a holding wi h a sha e o sales o 1-30% o
p i a e wholesale s/ e aile s (compa ed o holdings
no exposed o such ades) makes i less likely ha he
esponden will be in a highe le el o applicabili y in
he a m. Being a holding exposed o he same sha e o
sales o di ec consume s makes i mo e likely ha he
esponden will be in a highe ca ego y o he applica-
bili y o VC con ac s. Ha ing expe ienced alue chain-
alike measu es makes i mo e likely ha he esponden
will pe cei e “applicable” he VC con ac . Highe sco -
ing o labelled p oduc and con ol by au ho i y make i
mo e likely ha he esponden will be in a highe ca -
ego y o applicabili y in he a m.
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Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
Table 4. Model o esul -based con ac solu ion.
Explana o y a iable VU s U, N, L, VL*VU, U s N, L, VL*VU, U, N s L, VL*VU, U, N, L s VL*
Easiness o unde s anding
Age (18-30)
31-40 -0.081 (0.859)
41-50 ‡ -0.929 (0.030)
51-60 -0.616 (0.141)
61-70 -0.478 (0.312)
>71 -0.358 (0.529)
Educa ional le el (p ima y)
seconda y 0.072 (0.798)
uni e si y o highe 0.507 (0.118)
Membe ship (none)
a me s union 0.308 (0.191)
na u e conse a ion/ en i onmen al o g. ‡ 0.691 (0.046)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % -0.305 (0.326)
31-60 % -0.276 (0.531)
61-100 % -0.158 (0.573)
Sel -chosen measu es ‡ 0.562 (0.016)
Be e esul s, highe paymen 0.232 (0.346)
Collec i e ag eemen 0.280 (0.079)
Labelled p oduc 0.097 (0.651)
Applicabili y in he a m
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % -0.329 (0.299)
31-60 % 0.363 (0.457)
61-100 % -0.136 (0.661)
P opo ion o holding sales – o coope a i es (0%)
1-30 % 0.685 (0.116)
31-60 % 0.480 (0.340)
61-100 % ‡ 0.818 (0.006)
O ganic p oduc ion (no)
yes ‡ 0.833 (0.002)
Sel -chosen measu es ‡ 0.530 (0.038)
Be e esul s, highe paymen 0.404 (0.133)
Collec i e ag eemen ‡ 0.487 (0.004)
Labelled p oduc 0.236 (0.299)
Reduced land en ‡ 0.651 (0.006)
Sel -moni o ing 0.184 (0.368)
Con ol by au ho i y 0.195 (0.299)
F ee aining -0.267 (0.355)
Sales gua an ee -0.335 (0.257)
Annual compensa ion 0.441 (0.172)
Pe iodical paymen 0.271 (0.147)
Economic bene i
Sel -chosen measu es 0.440 (0.082)
Be e esul s, highe paymen ‡ 0.549 (0.036)
(Con inued)
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D’Albe o Ricca do e al.
Age p oduces a nega i e e ec on economic bene i .
Being specialized in li es ock makes i mo e likely
ha he esponden will be in a highe le el o he will-
ingness o en oll in VC con ac s. Ha ing expe ienced
alue chain-alike measu es makes i mo e likely ha he
esponden will be in he cu en (o lowe ) ca ego y o
willingness o en oll. An inc ease in he sco ing o paid
by cus ome s and con ol by au ho i y has a posi i e
impac on willingness o en oll.
The models in Table 7 a e, all bu he one o he
Explana o y a iable VU s U, N, L, VL*VU, U s N, L, VL*VU, U, N s L, VL*VU, U, N, L s VL*
Collec i e ag eemen 0.163 (0.304)
Labelled p oduc -0.132 (0.557)
Reduced land en 0.027 (0.901)
Sel -moni o ing 0.332 (0.103)
Con ol by au ho i y -0.177 (0.069)
F ee aining -0.068 (0.540)
Sales gua an ee -0.309 (0.805)
Annual compensa ion 0.320 (0.335)
Pe iodical paymen 0.091 (0.623)
Willingness o en oll
Age (18-30)
31-40 0.297 (0.598)
41-50 -0.096 (0.850)
51-60 -0.410 (0.408)
61-70 -0.437 (0.428)
>71 ‡ -1.612 (0.016)
Educa ional le el (p ima y)
seconda y -0.217 (0.521)
uni e si y o highe 0.236 (0.547)
Membe ship (none)
a me s union -0.290 (0.280)
na u e conse a ion/en i onmen al o g. 0.546 (0.242)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % 0.418 (0.252)
31-60 % -0.077 (0.874)
61-100 % 0.193 (0.610)
P e ious expe ience (no)
yes 0.041 (0.924)
Sel -chosen measu es 0.246 (0.370)
Be e esul s, highe paymen 0.322 (0.277)
Collec i e ag eemen 0.271 (0.180)
Labelled p oduc 0.310 (0.213)
Reduced land en 0.142 (0.563)
Sel -moni o ing ‡ 0.506 (0.035)
Con ol by au ho i y -0.055 (0.802)
F ee aining ‡ -0.705 (0.029)
Sales gua an ee 0.371 (0.228)
Annual compensa ion 0.063 (0.862)
Pe iodical paymen ‡ 0.525 (0.012)
No e: The e e ence modali y o he explana o y a iable is in pa en heses. * VU = Ve y Unlikely, U = Unlikely, N = Neu al, L = Likely, VL
= Ve y Likely; p- alues in pa en heses; ‡ in bold indica es he 0.05 le el o s a is ical signi icance.
Table 4. (Con inued).
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Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
Table 5. Model o collec i e con ac solu ion.
Explana o y a iable VU s U, N, L, VL*VU, U s N, L, VL*VU, U, N s L, VL*VU, U, N, L s VL*
Easiness o unde s anding
Membe ship (none)
a me s union -0.085 (0.841)
na u e conse a ion/ en i onmen al o g. 0.735 (0.496)
Specializa ion (a able)
ho icul u e 0.107 (0.835)
pe manen -0.228 (0.440)
li es ock 0.184 (0.638)
mixed -0.014 (0.971)
O ganic p oduc ion (no)
yes -0.176 (0.505)
Di ec CAP paymen s (no)
yes -1.022 (0.051) 0.559 (0.236) ‡ 1.693 (0.005) ‡ 2.316 (0.046)
P e ious expe ience (no)
yes ‡ 1.823 (0.000)
Sel -chosen measu es -0.100 (0.693)
Be e esul s, highe paymen 0.088 (0.744)
Collec i e ag eemen ‡ 0.744 (0.022) -0.323 (0.236) -0.350 (0.288) ‡ -0.818 (0.023)
Labelled p oduc 0.072 (0.751)
Paid by cus ome s 0.088 (0.646)
Reduced land en 0.321 (0.140)
Sel -moni o ing 0.255 (0.223)
Con ol by au ho i y -0.069 (0.715)
F ee aining -0.035 (0.900)
Sales gua an ee -0.038 (0.891)
Annual compensa ion 0.257 (0.432)
Pe iodical paymen 0.254 (0.174)
Applicabili y in he a m
Age (18-30)
31-40 ‡ -0.946 (0.040)
41-50 ‡ -1.029 (0.014)
51-60 -0.711 (0.075)
61-70 -0.291 (0.521)
>71 ‡ -1.116 (0.037)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % -0.190 (0.533)
31-60 % 0.658 (0.125)
61-100 % -0.134 (0.629)
U ilized Ag icul u al A ea owned – in hec a es ‡ -0.001 (0.024)
Sel -chosen measu es 0.220 (0.375)
Be e esul s, highe paymen -0.004 (0.989)
Collec i e ag eemen ‡ 0.641 (0.001)
Common paymen ‡ 0.472 (0.006)
Reduced land en 0.352 (0.105)
Sel -moni o ing 0.281 (0.153)
Con ol by au ho i y -0.107 (0.556)
(Con inued)
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D’Albe o Ricca do e al.
Explana o y a iable VU s U, N, L, VL*VU, U s N, L, VL*VU, U, N s L, VL*VU, U, N, L s VL*
F ee aining 0.087 (0.754)
Sales gua an ee -0.191 (0.461)
Annual compensa ion 0.109 (0.718)
Pe iodical paymen 0.274 (0.130)
Economic bene i
Age (18-30)
31-40 -0.588 (0.208)
41-50 -0.368 (0.394)
51-60 -0.386 (0.353)
61-70 -0.077 (0.871)
>71 -0.758 (0.168)
Membe ship (none)
a me s union -0.323 (0.186)
na u e conse a ion/ en i onmen al o g. 0.209 (0.575)
P opo ion o holding sales – o p ocesso (0%)
1-30 % 0.389 (0.253)
31-60 % -0.240 (0.657)
61-100 % -0.456 (0.244)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % -0.160 (0.633)
31-60 % 0.474 (0.324)
61-100 % -0.268 (0.507)
P opo ion o holding sales – o coope a i es (0%)
1-30 % -0.227 (0.618)
31-60 % -0.885 (0.071)
61-100 % -0.592 (0.075)
P e ious expe ience (no)
yes 0.373 (0.335)
Sel -chosen measu es 0.127 (0.617)
Be e esul s, highe paymen 0.151 (0.561)
Collec i e ag eemen 0.140 (0.587) 0.301 (0.108) 0.229 (0.395) 0.453 (0.232)
Common paymen 0.305 (0.085)
Labelled p oduc -0.239 (0.314)
Paid by cus ome s 0.039 (0.847)
Reduced land en 0.391 (0.077)
Sel -moni o ing 0.361 (0.094)
Con ol by au ho i y 0.192 (0.321)
F ee aining -0.088 (0.760)
Sales gua an ee 0.003 (0.990)
Annual compensa ion -0.060 (0.843)
Pe iodical paymen ‡ 0.389 (0.038)
Willingness o en oll
Age (18-30)
31-40 -0.802 (0.117)
41-50 ‡ -1.146 (0.016)
51-60 -0.813 (0.075)
61-70 -0.595 (0.251)
>71 ‡ -1.711 (0.006)
Table 5. (Con inued).
(Con inued)
95
Bio-based and Applied Economics 13(1): 73-101, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14016
Inno a i e con ac solu ions o he Ag i-En i onmen al-Clima e Public Goods p o ision
ou come a iable economic bene i ha is a PPO/NPL
model (as he one in Equa ion 4) o he manusc ip ), PO/
PL models, as pe he one depic ed in Equa ion 3) o he
manusc ip .
In Table 7, he p edic o sel -chosen measu es ails
o mee he assump ion o p opo ionali y o he odds.
Being olde makes i mo e likely ha he esponden will
be in he cu en (o lowe ) ca ego y o easiness o unde -
s anding. Ha ing p e iously expe ienced land enu e-
alike measu es makes i mo e likely ha he esponden
will be in a highe ca ego y o easiness o unde s anding.
An inc ease in sco ing o sel -chosen measu es makes i
mo e likely ha he esponden will be in a highe le el
o easiness o unde s anding, while an inc ease in sco ing
o sales gua an ee makes i mo e likely ha he espond-
en will be in he cu en (o lowe ) ca ego y.
Being olde makes i mo e likely ha he esponden
will be in he cu en (o lowe ) ca ego y o applicabili y
in he a m. Highe alues o con ol by au ho i y makes
i mo e likely ha he esponden will conside “applica-
ble” he LT con ac s.
Being a holding wi h a sha e o 31-60% o sales
di ec ly o inal consume s makes i mo e likely ha he
esponden will be in a highe ca ego y o he pe cei ed
applicabili y o LT con ac s. An inc ease in sco ing o
educed land en makes i mo e likely ha he espond-
en will be in a highe ca ego y o he o dinal ou come
a iable. An inc ease in sco ing o con ol by au ho -
i y makes i mo e likely ha he esponden will pe cei e
“applicable” he LT con ac solu ion. A nega i e impac
on he pe cei ed economic bene i o LT con ac s is gen-
e a ed by he inc ease in he sco ing o sales gua an ee.
Being olde makes i mo e likely ha he espond-
en will be in he cu en (o lowe ) ca ego y o willing-
ness o en oll. Being a holding wi h a sha e o sales o
1-30% o p ocesso s (compa ed o holdings no exposed
o such ades) makes i mo e likely ha he esponden
will be in a highe ca ego y o willingness o en oll. Being
exposed o he sales o p i a e wholesale s/ e aile s o a
sha e o 31-60% makes i mo e likely ha he espond-
en will be in he cu en (o lowe ) le el o willingness,
while i is posi i ely impac ed by educed land en .
Explana o y a iable VU s U, N, L, VL*VU, U s N, L, VL*VU, U, N s L, VL*VU, U, N, L s VL*
Membe ship (none)
a me s union -0.406 (0.123)
na u e conse a ion/ en i onmen al o g. 0.033 (0.937)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % 0.095 (0.785)
31-60 % -0.137 (0.771)
61-100 % -0.132 (0.709)
Di ec CAP paymen s (no)
yes -0.264 (0.398)
P e ious expe ience (no)
yes 0.286 (0.492)
Sel -chosen measu es 0.426 (0.117)
Be e esul s, highe paymen -0.257 (0.366)
Collec i e ag eemen ‡ 0.423 (0.039)
Common paymen ‡ 0.510 (0.007)
Labelled p oduc -0.385 (0.126)
Paid by cus ome s 0.261 (0.212)
Reduced land en 0.428 (0.070)
Sel -moni o ing ‡ 0.691 (0.003)
Con ol by au ho i y 0.139 (0.488)
F ee aining 0.267 (0.374)
Sales gua an ee -0.477 (0.107)
Annual compensa ion 0.192 (0.583)
Pe iodical paymen 0.325 (0.092)
No e: The e e ence modali y o he explana o y a iable is in pa en heses. * VU = Ve y Unlikely, U = Unlikely, N = Neu al, L = Likely, VL
= Ve y Likely; p- alues in pa en heses; ‡ in bold indica es he 0.05 le el o s a is ical signi icance.
Table 5. (Con inued).
96
Bio-based and Applied Economics 13(1): 73-101, 2024 | e-ISSN 2280-6172 | DOI: 10.36253/bae-14016
D’Albe o Ricca do e al.
Table 6. Model o alue chain con ac solu ion.
Explana o y a iable VU s U, N, L, VL*VU, U s N, L, VL*VU, U, N s L, VL*VU, U, N, L s VL*
Easiness o unde s anding
Membe ship (none)
a me s union 0.276 (0.270)
na u e conse a ion/ en i onmen al o g. 0.230 (0.551)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % ‡ -1.255 (0.000)
31-60 % -0.683 (0.150)
61-100 % 0.162 (0.659)
P opo ion o holding sales – di ec o inal consume (0%)
1-30 % ‡ 0.881 (0.019)
31-60 % ‡ 1.281 (0.025)
61-100 % -0.640 (0.126)
Specializa ion (a able)
ho icul u e 0.096 (0.867)
pe manen 0.115 (0.711)
li es ock ‡ 1.020 (0.016)
mixed 0.102 (0.781)
U ilized Ag icul u al A ea en ed in – in hec a es ‡ 0.003 (0.046)
Di ec CAP paymen s (no)
yes -0.171 (0.556)
P e ious expe ience (no)
yes ‡ 2.075 (0.000)
Sel -chosen measu es 0.022 (0.931)
Be e esul s, highe paymen -0.171 (0.526)
Labelled p oduc -0.126 (0.606)
Paid by cus ome s 0.164 (0.422)
Reduced land en 0.289 (0.208)
Sel -moni o ing 0.343 (0.112)
Con ol by au ho i y 0.146 (0.471)
F ee aining -0.036 (0.898)
Sales gua an ee -0.005 (0.984)
Annual compensa ion 0.328 (0.304)
Pe iodical paymen 0.121 (0.526)
Applicabili y in he a m
Age (18-30)
31-40 -0.048 (0.926)
41-50 -0.553 (0.247)
51-60 -0.580 (0.201)
61-70 -0.348 (0.508)
>71 -0.628 (0.294)
Membe ship (none)
a me s union -0.023 (0.930)
na u e conse a ion/ en i onmen al o g. 0.108 (0.792)
P opo ion o holding sales – o p i a e wholesale / e aile (0%)
1-30 % ‡ -0.773 (0.034)
31-60 % 0.337 (0.948)
61-100 % 0.023 (0.951)
(Con inued)
