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Digi alized bioeconomy : Planned obsolescence-d i en ci cula economy enabled by Co-
E olu iona y coupling
© 2018 Else ie L d.
Accep ed e sion (Final d a )
Wa anabe, Chihi o; Na eed, Kashi ; Nei aanmäki, Pekka
Wa anabe, C., Na eed, K., & Nei aanmäki, P. (2019). Digi alized bioeconomy : Planned
obsolescence-d i en ci cula economy enabled by Co-E olu iona y coupling. Technology in
Socie y, 56, 8-30. h ps://doi.o g/10.1016/j. echsoc.2018.09.002
2019
Accep ed Manusc ip
Digi alized bioeconomy: Planned obsolescence-d i en ci cula economy enabled by
Co-E olu iona y coupling
Chihi o Wa anabe, Nasi Na eed, Pekka Nei aanmäki
PII: S0160-791X(18)30120-9
DOI: 10.1016/j. echsoc.2018.09.002
Re e ence: TIS 1081
To appea in: Technology in Socie y
Recei ed Da e: 8 May 2018
Re ised Da e: 6 Augus 2018
Accep ed Da e: 10 Sep embe 2018
Please ci e his a icle as: Wa anabe C, Na eed N, Nei aanmäki P, Digi alized bioeconomy: Planned
obsolescence-d i en ci cula economy enabled by Co-E olu iona y coupling, Technology in Socie y
(2018), doi: h ps://doi.o g/10.1016/j. echsoc.2018.09.002.
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Digi alized Bioeconomy: Planned Obsolescence-D i en
Ci cula Economy Enabled by Co-E olu iona y Coupling
Chihi o Wa anabe
a,b
, Nasi Na eed
a
and Pekka Nei aanmäki
a
a
Facul y o In o ma ion Technology, Uni e si y o Jy äskylä, Finland
b
In e na ional Ins i u e o Applied Sys ems Analysis (IIASA), Aus ia
Abs ac
D i en by digi al solu ions, he bioeconomy is aking majo s eps o wa d in ecen yea s
owa d achie emen o he long-las ing goal o ansi ion om a adi ional ossil
economy o a bioeconomy-based ci cula economy.
The coupling o digi aliza ion and bioeconomy is leading owa ds a digi alized
bioeconomy ha can sa is y he shi in consume s’ p e e ences o eco-consciousness,
which in u n induces coupling o up-down s eam ope a ion in he alue chain.
Thus, he co-e olu ion o he coupling o digi aliza ion and bioeconomy and o ups eam
and downs eam ope a ions is ans o ming he o es -based bioeconomy in o a digi al
pla o m indus y.
Aiming a add essing his ans o ma ion, a model was de eloped ha explains abo e
men ioned dynamism and demons a ed i s eliabili y h ough an empi ical analysis
ocusing on he de elopmen ajec o y o UPM ( o es -based ecosys em leade in
Eu ope and a wo ld pionee in he ci cula economy) o e he las qua e cen u y,
highligh ing i s e o s owa ds planned obsolescence-d i en ci cula economy.
I was comp ehended ha wi h he ad ancemen o digi al inno a ions, UPM has
inco po a ed a sel -p opaga ing unc ion ha accele a es digi al solu ion. Fu he mo e,
his sel -p opaga ing unc ion was igge ed by coupling wi h a downs eam leade ,
Amazon, in he Uni ed S a es.
The dynamism in ans o ming a o es -based bioeconomy in o a digi al pla o m
indus y is hus cla i ied, and new insigh s common o all indus ies in he digi al
economy a e p o ided.
Keywo ds: Digi alized bioeconomy; Digi al-bio coupling; Ups eam-downs eam
coupling; Ci cula economy; Planned obsolescence.
Co esponding au ho
Chihi o Wa anabe (wa anabe.c.pq @gmail.com)
TIS_2018_105_Re ised_Manusc ip
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1. In oduc ion
The ma ked ad ancemen o he In e ne has gene a ed he digi al economy, changing he
way we conduc business and ou daily li es (Tapsco , 1994). This ad ancemen has
hence c ea ed a digi al economy and also ans o med he adi ional bio-based economy
1
,
pa icula ly, in he p esen con ex , he o es -based bioeconomy, in o a consolida ed
pla o m. This ans o ma ion is no associa ed o na u al esou ces and echnologies only
bu also complex u u e ajec o ies o socie ies, i ms and indi iduals. These ajec o ies
a e in o med by socio-cul u al and e hical pe spec i es as well as echno-economic
pe spec i es (VTT, 2017). Wide socio-economic ans o ma ions, no me ely
echnological and ma e ial p ocesses can be expanded by he se ice s a egies o such an
economy (Pelli e al., 2017).
Thus, d i en by digi al solu ions, he bioeconomy is aking majo s eps o wa d in ecen
yea s, enabling he po en ial achie emen o he long-las ing goal o ansi ioning om a
adi ional ossil-based economy owa ds a bio-based ci cula economy (MISTRA,
2017).
Consume p e e ences ha e ended o shi owa ds sup a- unc ionali y and now go
beyond basic economic alue, encompassing social, cul u al and emo ional alues
(McDonagh, 2008; Wa anabe e al., 2015). In his con ex , a ci cula economy ul ima ely
seeks o decouple global economic de elopmen om in ini e esou ce consump ion
(Ellen Maca hu Founda ion, 2015). Acco dingly, he coupling o digi aliza ion and
bioeconomy ha eme ges digi alized bioeconomy sa is ies a downs eam shi in
consume p e e ences (Wa anabe e al., 2018b).
Fu he mo e, hese p e e ences induce u he ups eam coupling o he alue chain.
Thus, he co-e olu iona y coupling o bioeconomy and digi aliza ion and o ups eam
and downs eam ope a ions is ans o ming he o es -based bioeconomy in o a digi al
pla o m indus y.
Mega ends: popula ion g ow h, u baniza ion, demog aphic change, esou ce sca ci y,
ole o enewables, digi aliza ion, e-comme ce, clima e change, esponsibili y and
compliance highligh he impo ance o bioeconomy-based ci cula economy. New
eme ging echnologies such as indus ial bio echnologies, 3D p in ing and ene gy
echnologies gi e new ways o c ea e inno a i e solu ions wi hou comp omising he
sus ainabili y. All hese b ing economic, social and en i onmen al alue o he
s akeholde s and he socie y.
1
Based on EC de ini ion (Bioeconomy o Eu ope, 2012), he e he bio-based economy (bioeconomy) has
been de ined and ecognized as ollows (Wa anabe e al., 208b):
The economy encompassing he p oduc ion o enewable biological esou ces and hei con e sion in o
ood, eed, bio-based p oduc s and bioene gy. The o es -based bioeconomy is an impo an sub-sec o o
he bioeconomy. Ad ancemen o digi aliza ion has ans o med his economy and his ans o ma ion is
no abou na u al esou ces and echnologies bu abou he complex u u e po en ial ajec o ies o socie ies,
i ms, and indi iduals.
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To da e, many s udies ha e analyzed he sys ems na u e o he o es -based bioeconomy.
Se e al s udies ha e poin ed ou he possibili y o c ea i e dis up ion by s emming om
he abo emen ioned mega ends con on ing he pulp and pape indus y (PPI) as
oppo uni ies a he han h ea s (e.g., He emaki e al., 2014; He emaki, 2016). The
possibili y o achie ing digi al solu ions has accele a ed hese s udies.
The e o e, we a emp o demons a e he abo e hypo he ical iew by conduc ing an
empi ical analysis o he co e business ac i i ies a he o e on o bo h he ups eam and
downs eam ope a ions o he o es -based bioeconomy chain. In pa icula , we showed a
ans o ma i e s eam esul ing in he cons uc ion o a c ea i e dis up ion pla o m and
he emb acemen o digi al solu ions (Wa anabe e al., 2017). While his analysis
p o ides new insigh in o a o es -based bioeconomy wi hin a digi al economy,
digi aliza ion does no s op he ans o ma ion s eam as he PPI p oduces mo e
di e si ied p oduc s (Toppinen e al., 2017) such as bio uels, biocomposi es, biochemical
and enewable ma e ials o plas ic indus y. In addi ion, ac o s om di e en sec o s
in e ac and play di e en oles (Giu ca e al., 2017), and all s akeholde s in ol ed in he
o es -based bioeconomy should be conside ed (Mus alah i, 2018).
Consequen ly, new insigh is p o ided in o he o es -based bioeconomy as well as
nume ous indus ies in he digi al economy ha a e cons uc ing a c ea i e dis up ion
pla o m by emb acing digi al solu ions.
Based on hese expec a ions, we a emp ed o ace his ans o ma ion by de eloping a
model ha explains abo emen ioned dynamism and demons a ed i s eliabili y h ough
an empi ical analysis ocusing on he de elopmen ajec o y o UPM ( o es -based
ecosys em leade in Eu ope and a wo ld pionee in he ci cula economy) o e he las
qua e cen u y since a e he eme gence o he digi al economy, highligh ing i s e o s
owa ds planned obsolescence-d i en ci cula economy.
The p ocess o consolida ing a pla o m simila o a supe compu e called ‘supe digi al
bio o e compu e ’ by consolida ing ups eam and downs eam ope a ions as well as
p oduce s and consume s (p osume ) was en isioned, whe ein ‘bio o e’ implies a
sus ainably g owing bio- o es (Wa anabe e al., 2018b).
Since an enabling mechanism o his ‘supe compu e ’ has been s ongly equi ed, he
ope a ionaliza ion o he a o emen ioned concep o he co-e olu iona y coupling o
bioeconomy and digi aliza ion and o ups eam and downs eam ope a ions is also
necessa y.
The e o e, his pape a emp s o ope a ionalize he dynamism o his co-e olu ion by
acing he abo e men ioned ans o ma ion dynamism. In o de o demons a e he
eliabili y o he model used o he analysis, an empi ical analysis ocusing on he
de elopmen ajec o y o UPM o e he las qua e cen u y was conduc ed, wi h special
a en ion placed on he esu gence o he planned, obsolescence-d i en ci cula economy.
In long-las ing deba e on planned obsolescence (e.g., Swan, 1972; Bulow, 1986;

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Aladeojebi, 2013), many indus ies ocused on a p o i maximiza ion s a egy and
p oduced goods and se ices wi h in en ionally sho e economic li es o s imula e
consume s o make epea ed pu chases in a sho e pe iod o ime. While some ecen
analyses (e.g., Fabian, 2016; Sa y o e al., 2018) discussed a signi icance o planned
obsolescence owa d a ci cula economy, no analysis has unde aken planned
obsolescence s a egy in he con ex o he de elopmen s age o he indus y owa d a
ci cula economy.
In ligh o he ans o ma ion o a ossil economy owa ds a bioeconomy-based ci cula
economy amids an abundance o digi al solu ions, his pape a emp s o explo e new
insigh s in o c ea i e dis up i e pla o m ha is expec ed o be ini ia ed by a planned
obsolescence-d i en ci cula economy enabled by he co-e olu ion o he coupling o
bioeconomy and digi aliza ion and o ups eam and downs eam ope a ions.
In line wi h an o ien a ion owa ds a planned obsolescence-d i en ci cula economy,
UPM has inco po a ed a sel -p opaga ing unc ion ha accele a es digi al solu ions.
Fu he mo e, his sel -p opaga ing unc ion was p omo ed h ough coupling wi h a
downs eam leade , Amazon, in he Uni ed S a es.
The dynamism in ans o ming a o es -based bioeconomy in o a digi al pla o m
indus y is hus cla i ied, and new insigh s common o all indus ies in he digi al
economy a e p o ided.
The s uc u e o his pape is as ollows: Sec ion 2 explo es he dynamism in cons uc ing
a consolida ed pla o m ecosys em. Sec ion 3 e iews he co-e olu ion o he dual
couplings o he bioeconomy and digi aliza ion, and o ups eam and downs eam
ope a ions. Sec ion 4 analyzes sus ainable de elopmen wi h an o ien a ion owa ds
planned, obsolescence-d i en ci cula economy. Sec ion 5 b ie ly summa izes no ewo hy
indings, implica ions and sugges ions o u u e wo ks.
2. Dynamism in Cons uc ing a Consolida ed Pla o m Ecosys em
2.1 Digi al Solu ion o T ans o ma ion in o a C ea i e Dis up ion Pla o m
We p e iously demons a ed ha he ad ancemen o digi al inno a ion ans o ms he
alue chain o he o es indus y in o a c ea i e dis up ion pla o m in a s epwise manne
c ea ing a consolida ed pla o m ecosys em (Wa anabe e al., 2018b).
The con en ional linea supply chain om o es y o consump ion (s ep 1) ans o ms
in o c ea i e dis up ion pla o ms wi hin he ups eam and downs eam indus ies (s ep 2).
Dis up ion in ups eam is induced (s ep 3) by he espousal o digi al solu ions and c ea ion
o new business sys ems in he downs eam (s ep 4). This is how we can expec he
eme gence o c ea i e dis up ion in he alue chain o o es -based bioeconomy. Mo eo e ,
di e si ied p oduc ion o add ess he people’s shi ing p e e ences o eco-consciousness,
di e en ac o s’ a ying oles and in e ac ion in he alue chain as well as s akeholde s
in ol emen accele a e he consolida ion o up-downs eam ope a ions and hus leads
o es -based bioeconomy in o a digi al pla o m indus y (s ep 5).
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The o es -based ecosys em leade in Eu ope, UPM in Finland, has unde aken a s ong
ini ia i e o es uc u e i s business model and has mo ed owa ds digi al-d i en solu ions
and an eco-design app oach since he beginning o he second decade o his cen u y,
whe eas Amazon has agg essi ely emb aced digi al solu ions o di e si y i s p oduc s and
o imp o e use s’ expe ience on he downs eam side. Thus, simila o he conspicuous
business accomplishmen s o Amazon on he downs eam side, UPM has demons a ed
no able accomplishmen s on he ups eam side as e idenced in Figs. 1 and 2.
Fig. 1. Top 20 Global Fo es , Pape and Packaging Indus y Fi ms in he Wo ld
by Ne Income (2015).
Sou ce: PWC (2016).
Fig. 1 demons a es UPM’s no able accomplishmen o gaining he wo ld’s highes ne
income wi hin he pape and packaging indus y in 2015. Fig. 2 demons a es i s
esu gence om he beginning o he second decade o his cen u y, as he company has
main ained sus ainable ma ke capi aliza ion g ow h since 2012.
Fig. 2. T end in UPM’s Ma ke Capi aliza ion (1990 – 2017) – 2010 ixed p ice.
Sou ce: UPM annual epo s (annual issues).
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2.2
Planned Obsolescence-D i en Ci cula Economy
1) UPM’s Endea o Towa ds De eloping a Ci cula Economy
UPM’s esu gence can be a ibu ed o i s s a egic shi owa ds a planned
obsolescence-d i en ci cula economy ha is enabled by digi al solu ions in eg a ing
bo h ups eam and downs eam ope a ions. I has aken s ong ini ia i e o shi om he
ossil economy owa ds a ci cula economy.
UPM was es ablished in 1995 by he me ging o he Kymmene Co po a ion and Repola
L d wi h i s subsidia y Uni ed Pape Mills L d, as illus a ed in Fig. 3. The new company
s a ed ope a ions on May 1, 1996.
Fig. 3. De elopmen T ajec o y o UPM.
Sou ce: Elabo a ed by he au ho s based on UPM (2016).
UPM has a long adi ion in he Finnish o es p oduc s indus y. The g oup’s i s
mechanical pulp mill, pape mills and sawmills s a ed ope a ions a he beginning o he
1870s. Pulp p oduc ion began in he 1880s and pulp was con e ed o pape by he 1920s,
wi h plywood p oduc ion beginning he ollowing decade. The p esen g oup comp ises
app oxima ely 100 p oduc ion acili ies ha o iginally unc ioned as independen
companies. Among o he s, he ollowing companies and o es indus y ope a ions we e
me ged in o he g oup: Kymi, Uni ed Pape Mills, Kaukas, Kajaani Schauman, Rosenlew,
Ra . Haa la and Rauma-Repola.
In 2008, UPM adop ed a new, ma ke d i en business s uc u e comp ising h ee
business g oups: Ene gy and Pulp, Pape , and Enginee ed Ma e ials (UPM, 2008). La e
in 2013, UPM once again implemen ed a new business s uc u e o d i e a clea change
in p o i abili y. Thus, UPM u he de eloped i s business po olio and changed om a
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e ically in eg a ed o es indus y o a company wi h six sepa a e business a eas: UPM
Bio e ining, UPM Ene gy, UPM Ra la ac, UPM Pape Asia, UPM Pape Eu ope and
UPM Plywood (UPM, 2013).
While UPM s a ed as a esou ce in ensi e i m, i ecognized he po en ially a al shi
om a ossil economy o a non- ossil economy wi hin he eme ging con ex o
sus ainable de elopmen , as illus a ed in Fig. 4.
Fig. 4. T ans o ming Di ec ion o Business Model Towa d Bioeconomy-based
Ci cula Economy.
Sou ce: UPM Annual Repo (2017).
Ci cula economy hinking add esses wo c ucial global issues i.e. clima e change and
sca ci y o na u al esou ces. In ci cula economy, ma e ials, p oduc ion was e and
p oduc s a e ecycled se e al imes o c ea e added- alue h ough sma solu ions.
Mo eo e , was e gene a ion is a oided by maximizing he use o enewable ene gy and
ma e ials. UPM aims o achie e he a ge o no p ocess was e o land ills by 2030. Fig.
5 demons a es he UPM’s ci cula economy app oach.
Fig. 5. Scheme o a UPM’s Ci cula Economy.
Sou ce: UPM Ci cula Economy (2018).
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By means o a co ela ion analysis be ween ma ke alue o UPM and he go e ning
ac o s o bo h ups eam and downs eam lows o e he 1998-2016 pe iod, we
p e iously demons a ed he signi icance o he o going dynamism enabled by he
coupling o ups eam and downs eam ope a ions (Wa anabe e al., 2018).
Fig. 11. Coupling o Ups eam and Downs eam Ope a ions
– A Case o UPM’s Ma ke
Capi aliza ion E ec
(1998-2016).
In Fig. 11 and abo emen ioned co ela ion analysis, we no ed ha UPM has been
sus aining an inc ease in ma ke capi aliza ion since 2012, as e iewed ea lie (Fig. 2).
The e ec s o R&D and economic en i onmen on ans o ming ma ke capi aliza ion
in o sus ainable inc eases we e no en i ely ema kable, ye his ans o ma ion can
la gely be a ibu ed o he imp o emen in ope a ing income and also he s ockp ice
inc ease o Amazon in he downs eam. The o me con ibu ion can be p ima ily
a ibu ed o he coupling o bioeconomy and digi aliza ion, as ou lined in sec ion 3.1,
and he la e con ibu ion can de ini ely be a ibu ed o he coupling o ups eam and
downs eam ope a ions ini ia ed by he i ual link e-comme ce link, as shown in Fig. 10.
Fu he mo e, spi al inc eases in bo h couplings he ea e con ince us ha he
co-e olu ion be ween hese wo couplings is well unc ioning.
Own
p o i
Inno a ion
e o s
Ex e nal
ma ke
condi ion
s
Coupling e ec
o he business
pe o mance in
downs eam side

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4. Sus ainable De elopmen Based on a Planned Obsolescence D i en
Ci cula Economy O ien a ion
4.1 Analy ical F amewo k
UPM’s esu gen de elopmen by means o a planned obsolescence d i en ci cula
economy enabled by co-e olu iona y coupling is demons a ed as ollowing.
Gi en he In e ne comme cializa ion in 1991 which igge ed he digi al economy, his
has p o ided signi ican impac on UPM’s de elopmen s a egy in shi ing om na u al
esou ces dependen s uc u e o digi al solu ion seeking s uc u e.
This shi can be examined by digi al solu ion subs i u ion o na u al esou ces as
depic ed as ollows:
ln
=+

ln



whe e I: In e ne dependence as a p oxy o digi al solu ion
3
; E: ene gy consump ion as a p oxy o
na u al esou ces dependence; p
i
: In e ne p ice; p
e
: ene gy p ices; 

: elas ici y o In e ne
subs i u ion o ene gy; and a: coe icien .
In his equa ion, in case when 

> 1, I subs i u ion o E can be demons a ed
4
.
Table 1 summa izes he esul o he abo e co ela ion analysis in UPM o e he pe iod
o 1991-2017 which demons a es s a is ically signi ican .
Table 1 Co ela ion o UPM’s Digi al Sollu ion – Resou ces Dependence Ra io and
hei P ices Ra io
(1991-2017)
ln


=−1.697+1.264ln
!"
!#
+ 0.498D
1
- 0.577D
2
D: Dummy a iables
D
1
: 1998, 2016, 2017 =1, o he s = 0; D
2
: 1991, 1992 = 1, o he s = 0.
The igu es in pa en heses indica e -s a is ics: All a e signi ican a he 1% le el.
Table 1 demons a es digi al solu ion (I) subs i u ion o na u al esou ces (E) which
endo ses ha UPM has been endea ou ing o shi ing om na u al esou ces dependen
s uc u e o digi al solu ion seeking s uc u e o i s su i al in he digi al economy.
Wi h his p e-analysis, UPM’s esu gen de elopmen ajec o y analysis was conduc ed
ocusing on i s digi al solu ion seeking ajec o y.
3
Since he In e ne has been pe mea ing in o b oad ICT in he digi al economy, In e ne dependency
can be conside ed a p oxy o digi al solu ion (Wa anabe e al., 2018c).
3
$≡&'()*')()+,)'-.(/*)
0')*12)+,)'-.(/*) = &∙,
.
0⋅,
)
ln5=ln
−ln!
"
!
#
= a +

67
−1ln
6
7
When


> 1, p
e
inc ease (o p
i
dec ease) eac s o In e ne expendi u e inc ease (I subs i u es o E).
(
-
19.68) (34.57)
(4.08) (
-
3.32)
adj. R
2
0.986
DW 1.19
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The amewo k o he analysis is ou lined in Figs. 12 and 13
(see he de ails o he
nume ical model in Appendices 1 and 2).
Fig. 12. F amewo k o a Planned Obsolescence-D i en Ci cula Economy Enabled
by Co-E olu iona y Couplings.
Simple Logis ic G ow h
(
SLG
)
Logis ic G ow h wi hin a Dynamic
Ca ying Capaci y (LGDCC)
Planned obsolescence s a egy
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Fig. 13. F amewo k o Planned Obsolescence Managemen .
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4.2 Da a Cons uc ion
Da a u ilized o he analysis a e abula ed in Table 2 (see he de ails o he da a in
Appendices 3 and 4).
Table 2 Da a o he Analysis
Ca ego y o Da a Re e ences
P ima y da a
UPM sales (nominal, eal)
UPM annual epo s (1997-2017)
UPM R&D expendi u e (nominal, eal)
UPM annual epo s (1997-2017)
UPM R&D in ensi y
UPM annual epo s (1997-2017)
UPM ene gy cos (nominal, eal)
UPM annual epo s (1997-2017)
GDP de la o
Wo ld
B
ank na ional accoun s and
OECD na ional accoun s da a iles
Long- e m in e es a e
OECD, long- e m in e es a es (2018)
Finland in e ne dependence
In e na ional Telecommunica ion Union
(ITU), s a is ics (2018)
Cons uc ed da a
Ra e o obsolescence o echnology
UPM annual epo s and ITU da a
L
ead ime be ween R&D and
comme cializa ion
UPM echnology s ock and ITU da a
R
a e o dep ecia ion o sold goods and
se ices
UPM echnology s ock and ITU da a
UPM echnology knowledge s ock
Compu ed
-
based UPM annual epo s
da a (1997-2017)
UPM ma ke alue
Compu ed
-
based UPM annual epo s
da a (1997-2017)
Fig. 14 illus a es ends in UPM’s sales, R&D expendi u e and R&D in ensi y.
Fig. 14. T ends in UPM Sales, R&D expendi u e and R&D In ensi y
(
1990-2017; 2010 eal p ice).
Sou ce: UPM Annual Repo s.
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Upon examining Fig. 14 we no ed ha sales gene ally inc eased a he beginning o his
cen u y (excep du ing Asian inancial c isis in 1998),
as he indus y enjoyed he
bene i s o his eme ging economy. The ea e , sales gene ally dec eased as he indus y
shi ed o a ma u ed economy. This con inued dec ease was once again modi ied o an
inc easing end du ing he ea ly pa o he second decade o his cen u y, allowing UPM
o gene a e he wo ld’s op ne income in 2015, as shown in Fig. 1. This eco e y can be
a ibu ed o he shi owa ds a ci cula economy, as desc ibed in Sec ion 2. R&D
in es men was demons a ed o be gene ally subjec o ends in sales. Figs. 15 and 16
illus a e ends in In e ne dependence in Finland, Japan, Singapo e and he USA and in
he long- e m in e es a e in Eu opean coun ies o e he 1990-2017 pe iod, espec i ely.
Fig. 15. T ends in In e ne Dependence
(%; 1990-2017).
Sou ce: In e na ional Telecommunica ion Union.
Fig. 15 shows he high dependence o Finland on he In e ne , pa icula ly in his cen u y,
and demons a es he ma ked ole o he In e ne in he planned obsolescence s a egy.
Fig. 16. T ends in he Long-Te m In e es Ra e in Eu opean-Coun ies
(1990-2017)
.
Sou ce: OECD.
Fig. 16 demons a es ends in he long- e m in e es a e in Eu opean coun ies o e he
1990-2017 pe iod. This declining end has induced an ex ension o echnology li e
co esponding o a ci cula economy wi hin a ma u ed economy (see he de ails o his
mechanism in Appendices 2 and 4).

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4.3 Empi ical Analysis
4.3.1 C ea ion o Technology Knowledge S ock and Ma ke Value
Measu emen o echnology knowledge s ock and ma ke alue is essen ial o he
analysis o UPM’s echnology-d i en de elopmen ajec o y owa ds a ci cula
economy.
G iliches (1980) pos ula ed ha echnology knowledge s ock can be measu ed as a
cumula i e s ock o R&D in es men by conside ing he obsolescence a e ( o
comme cializa ion (m), as illus a ed in Fig. 12 (see he de ails o he equa ion in
Appendix 1). I was p e iously iden i ied ha i ms a emp o manage his lead ime
depending on he a e o obsolescence o echnology (Wa anabe, 1999).
Simila ly, ma ke alue can be measu ed as he cumula i e s ock o sales aking in o
accoun hei dep ecia ion a e (:). In his case, con a y o echnology knowledge s ock,
lead ime can be conside ed negligibly small (see also Fig. 12 and Appendix 1).
Gene ally, ‘dep ecia ion’ in a b oad sense (some imes also called ‘obsolescence’) can be
de ined as he loss in se ice alue incu ed in connec ion wi h he consump ion o
p ospec i e e i emen o a p ope y (NARUC, 1996). I gene ally esul s om wo
p inciple classes o losses: (i) adi ional mo ali y o ces, such as wea and ea om
usage, de e io a ion wi h age and acciden al o chance des uc ion, and (ii) echnological
obsolescence (Ba eca, 2000). These losses can be de i ed om ei he physical
obsolescence o echnical obsolescence mechanisms (Aladeojebi, 2013). Be o e he
1970s, he o e whelming d i e s o mo ali y o u ili y p ope y we e adi ional
mo ali y o ces be o e he 1970s (Ba eca, 2000); howe e , echnological obsolescence
has a p ima y ole as echnology ad ances. When echnological obsolescence is p esen ,
mo ali y a es inc ease wi h he passage o ime (Ba eca, 2000), leading o a much
highe obsolescence/dep ecia ion a e han ha o s emming om adi ional mo ali y
o ces.
In his pape , in line wi h G iliches (1980), he dep ecia ion a e o echnology is amed
as he a e o obsolescence o echnology, while he dep ecia ion a e o sales is amed
as he a e o dep ecia ion o sold goods and se ices.
4.3.2 Planned Obsolescence S a egy
The abo e pos ula es sugges ha he a es o obsolescence o echnology and
dep ecia ion o sold goods and se ices play decisi e oles in measu ing echnology
knowledge s ock and ma ke alue. Pa icula ly, ca e ul a en ion should be paid o hese
a es o obsolescence and dep ecia ion in he con ex o he esu gence o UPM and i s
planned obsolescence-d i en ci cula economy.
1) Ra e o Obsolescence o Technology
Con on ing he s agna ing end in he o es -based bioeconomy o Eu ope as a
consequence o he ad ancemen o he digi al economy and g owing ine ia in eme ging
economies, he planned obsolescence managemen s a egy has become impo an in
leading Eu opean pulp and pape i ms (MISTRA, 2017).
Leading pulp and pape i ms in Eu ope ha e aken since e conside a ion o planned
obsolescence as a echnology s a egy (Muba eka e al., 2016) and ha e implemen ed
digi al solu ions as an addi ional s a egy s emming om he d ama ic ad ancemen o
digi al inno a ions (Mus alah i, 2018).
T adi ionally, he pu pose o his s a egy was o o ce consume s o pu chase newe
p oduc s by sho ening he na u al end o li e o he cu en p oduc s owned by
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consume s (Packa d, 1960; Swan, 1972; Bulow, 1986; Slade, 2006; Aladeojebi, 2013).
Howe e , in line wi h inc easing conce ns o e he en i onmen and consume
p e e ences, some conce ns wi h espec o ‘planned longe i y’ ha e a isen (e.g. Swan,
1972; Bulow, 1986; Keeble, 2013; EMF, 2015; Fabian, 2016; Sa y o e al., 2018).
In ligh o he me abolic change in he o es -based bioeconomy, pa icula ly in UPM’s
ans o ma i e de elopmen ajec o y owa ds a ci cula economy, an op imal
obsolescence managemen s a egy encompassing bo h possibili ies o sho ening and
ex ending echnology li e (UPM, 2017a) was sough in his pape based on he p inciple
o p o i able R&D wi h minimum R&D in es men and maximum u iliza ion o digi al
solu ions, as demons a ed in Fig. 7. In addi ion, he s a e o he de elopmen ajec o y
was aken in o accoun (see he de ails o ma hema ical analyses in Appendix 2).
The e a e wo o ms o obsolescence: ex e nal obsolescence and unc ional obsolescence
(Ba ecca, 2000). The o me can be a ibu ed o ex e nal ci cums ances including he
de elopmen , di usion and u iliza ion o echnology, whe eas, he la e esul s om a
law in s uc u es, ma e ials o design ha diminishes he unc ion, u ili y and alue o an
asse (Ba ecca, 2000). He e, law e e s o any de iciency in an asse ha nega i ely
impac i s abili y o pe o m he desi ed unc ion pe cus ome expec a ion.
Wi h he apid ad ancemen o echnology, echnological obsolescence is he p inciple
cause o unc ionali y obsolescence oday, o e shadowing ex e nal obsolescence, which
is ele an o he analysis o he a e o obsolescence o echnology o measu ing
echnology knowledge s ock.
Hence, echnology-d i en unc ionali y obsolescence was ocused on in his pape in he
analysis o he a e o obsolescence o echnology.
I was p e iously demons a ed ha i ms’ a e o obsolescence o echnology can be
depic ed as a unc ion o hei echnology knowledge s ock le el (Wa anabe, 1999).
UPM’s endea ou o shi owa ds a planned obsolescence s a egy wi hin a ci cula
economy co esponds wi h a digi al solu ion s a egy p ima ily ini ia ed by he e ec i e
u iliza ion and ad ancemen o digi al inno a ion led by he ad ancemen o he in e ne
(I) (Tie o, 2017). This p eceding app oach was u ilized h ough de eloping In e ne
dependence a he han inducing gene al echnology knowledge s ock. This dependence
ep esen s a gene al end in co-e olu iona y coupling.
As e iewed ea lie , p o i maximiza ion can be a ained by inc easing he a e o
obsolescence o echnology (( apid subs i u ion wi h new echnology) in an eme ging
economy, while he e e se occu s in a ma u ed economy. In a ma u ed economy, an
ex ension o he echnology li e cycle (dec ease) is equi ed, co esponding wi h he
p inciples o a ci cula economy (EMF, 2015; UPM, 2017a).
In addi ion, as e iewed in Fig. 12, gi en i ms’ planned obsolescence managemen
s a egy, hei a e o obsolescence o echnology is subjec o he long- e m in e es a e,
as demons a ed in Fig. 16 (see he de ailed mechanism in Appendices 1 and 2).
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Based on he o egoing e iew and he his o ical e iew wi h in e na ional compa isons
(Scho , 1978; Boswo h, 1978; Japan Science and Technology Agency, 1985; Mi subishi
Resea ch Ins i u e, 1991; Wa anabe, 1992; Wa anabe, 1999; OECD, annual issues), he
a e o obsolescence o echnology in UPM o e he 1990-2017 pe iod was es ima ed, as
illus a ed in Fig. 17 (see he de ails o he es ima ion app oach and es ima ed alues in
Appendices 3 and 4).
Fig. 17. T end in he Ra e o Obsolescence o Technology in UPM
(1990-2017).
Dynamic change in a e o obsolescence o echnology, as e iewed in Fig. 12, e idence
he capaci y o i ms o change lead ime be ween R&D and comme cializa ion (m), as
illus a ed in Fig. 18 (see he de ails o es ima ed alues in Appendix 4). This dynamic
change in lead ime was e lec ed in he measu emen o he echnology knowledge
s ock.
Fig. 18. T end in Lead Time be ween R&D and Comme cializa ion
(1990-2017)
.
dT
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2) Ra e o Dep ecia ion o Sold Goods and Se ices
In p inciple, he s a egy o i ms o he planned dep ecia ion o ma ke alue is based
on he simila s a egy o planned obsolescence o echnology (Keeble, 2013). Howe e ,
i la gely depends on ex e nal obsolescence and is mo e sensi i e o ac o s o he han
digi al solu ions (Disney e al., 2003; Obeng e al., 2014). I is subjec o he
ad ancemen o he In e ne , simila o , ye i is also subjec o he sales end (S) o ,
speci ically, he popula i y o sold goods and se ices in he ma ke . Ye no ably, i is
decisi e ac o o i ms’ planned dep ecia ion s a egy (Rod iguez e al., 2015). In
addi ion, echnology knowledge s ock (T) canno be o e looked as i may p oduce new
goods and se ices ha subs i u e exis ing ones. Fu he mo e, ad ancemen o he
in e ne accele a es dissemina ion o goods and se ices in new eme ging ma ke s and
ex ends hei li e cycle leading, o dec easing :.
Hence, he a e o dep ecia ion o sold goods and se ices : can be depic ed by a
unc ion desc ibing dependence on he In e ne , he sales end and echnology
knowledge s ock.
Con a y o a e o obsolescence o echnology, he dep ecia ion o sold goods and
se ices is p ima ily go e ned by adi ional mo ali y o ces, such as wea and ea and
de e io a ion. These o ces a e ypically a cons an unc ion o he age o he asse s and
do no change wi h he passage o ime (Ba eca, 2000)
5
.
In addi ion, compa ed o echnological obsolescence, which inc eases he mo ali y a e
o e ime, leading o a highe a e o obsolescence, he a e o dep ecia ion o sold goods
and se ices is conside ed o be much lowe as i s ems om adi ional mo ali y o ces.
Based on he o egoing e iew in addi ion o he li ecycles o UPM’s leading p oduc s,
he a e o dep ecia ion o goods and se ices sold by UPM o e he 1990-2017 pe iod
was es ima ed, as illus a ed in Fig. 19 (see he de ails o he es ima ion app oach and
es ima ed alues in Appendices 3 and 4).
Fig. 19. T end in he Ra e o Dep ecia ion o Sold Goods and Se ices
(1990-2017).
5
Ba eca (2000) demons a ed as ollows:
5 yea s ago, 10 yea pld asse s may ha e had a 3% e i emen a e (dep ecia ion a e); oday, 10 yea old
asse s would s ill ha e a 3% e i emen a e; and 30 yea s om now, 10 yea old asse s would s ill ha e a
3% e i emen a e.
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Appendix 1. Model Cons uc ed o he Analysis
Ma ke alue c ea ed by i ms in a compe i i e en i onmen can be desc ibed as ollows:
B =CD,E (1)
whe e V: ma ke alue; X: adi ional p oduc ion ac o s; and T: echnology
knowledge s ock.
Gi en he emphasis on in e ne -d i en digi al solu ions, he in e ne pe mea es T as
ollows:
B =CD,E (2)
whe e I: in e ne dependence.
Fu he mo e, I embodies X in an in e ne o hings (IoT) socie y as ollows:
B =CD,E
(3)
Thus, he ma ke alue o i ms seeking digi al solu ions in an IoT socie y is go e ned by
he ollowing unc ion:
B ≈CE (4)
Technology knowledge s ock a ime , T
can be depic ed as ollows:
E
G
=H
GIJ
+1−E
GIK
, E
L
=H
KIJ
+M
⁄
(5)
whe e R
: R&D expendi u e a ime ; m: ime lag be ween R&D o
comme cializa ion; : a e o obsolescence o echnology; and g: inc easing a e o
R&D expendi u e a he ini ial pe iod.
Gi en he c ea i e dis up ion caused by emb acing digi al solu ions, hese solu ions can
be ep esen ed by he dec easing a e o obsolescence o echnology (i.e. p olongmen o
he li e ime o echnology) ini ia ed by he ad ancemen o he in e ne as ollows:

G
=
L

GO
(6)
whe e P: lea ning coe icien o digi al R&D.
Co esponding o change in ,m also changes as ollows (Wa anabe, 1999):
Q
G
=
RSTU=U
⁄IRS<VWX
RSKWX
+1 (7)
Simila ly, ma ke alue a ime V
can be depic ed as ollows:
B
G
=Y
G
+ (1 -:B
GIK
, B
L
=Y
K
:+Z
⁄
(8)
whe e S
: sales a ime ; :: a e o dep ecia ion o sold goods and se ices; and k:
g ow h a e o sales a he ini ial pe iod.
Gi en he logis ic na u e o he g ow h o in e ne , equa ion (4) can be de eloped by he
ollowing T-d i en logis ic g ow h unc ion:
B
G
≈C[E ,
;]
;=
=
^]
^=
∙
;=
;=
=
^]
^=
=B1−
]
_

(9)
whe e N: ca ying capaci y and a: eloci y o di usion.
Equa ion (9) de elops he ollowing simple logis ic g ow h unc ion (SLG):
B
G
E
G
=
_
KW`abcV
(10)
whe e b: coe icien indica ing he ini ial le el o di usion.

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The c i ical le el in o ming i ms’ decision o unde ake R&D should sa is y he
ollowing balance (see No e):
^]
^=
=1+Qdd+ (11)
whe e : in e es a e.
Simila o  as a unc ion o in e ne -d i en lea ning o digi al solu ions, : can be
depic ed as a unc ion o he in e ne -d i en lea ning in an IoT socie y as ollows:
:
G
=:
L

Ge
(12)
whe e : lea ning coe icien o sales p omo ion.
This a e is also subjec o he ends in sales (S) and echnology s ock (T). In addi ion,
ad ancemen o he in e ne expands he ma ke leading o he ex ension o he li e ime
o goods and se ices. Thus, δis go e ned by hY,E, as depic ed in equa ion (13).
:
G
=:
L

Ge
∙hY,E, (13)
No e:
In e nal a e o e u n o R&D in es men
The c i ical le el ha in o ms i ms’ decision o unde ake R&D is de ined by he
ollowing discoun a e ( : in e nal a e o e u n [IRR] o R&D in es men ), which
should no be lowe han he in e es a e (Wa anabe e al., 1997).
iB
iE
＝

1
+
Qd


d
+

）
Thus, he
c i ical le el
in o ming
i ms’ decision o unde ake R&D should
sa is y he ollowing balance gi en ma ginal echnology p oduc i i y:
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Appendix 2. Planned Obsolescence in a Ma u ed Indus y Shi ing
Towa d Digi al Solu ions
F om equa ion (1) i ms’ echnology p oduc i i y can be de eloped as ollows:
;]
;=
=
^]
^j
∙
;j
;=
+
^]
^=
∙
;=
;=
=
^]
^j
∙
;j
;=
+
^]
^=
(14)
Φ≡
ð]
^j
∙
;j
;=
=
;]
;=
−
^]
^=
(15)
F om equa ions (9) and (11), he componen s o equa ion (15) can be p o ided as
ollows:
m≡
;]
;=
=B1−
]
_

(9)
n≡
^]
^=
=1+Qdd+
(11)
P o ided ha i ms seek p o i able R&D wi h minimum R&D in es men and maximum
u iliza ion o digi al solu ions, he planned obsolescence s a egy can be depic ed as
ollows
6
:
;o
;<
= 0
(16)
pΦ
p =pm
p−pn
p =qpB
p 1−B
s −B
s∙pB
pu−pn
p
=⋅
;]
;<
1−
w]
_
x−
;y
;<
=⋅
;]
;=
⋅
;=
;<
 1−
w]
_
x−
;y
;<
=∙B 1−
]
_
x 1−
w]
_
x
;=
;<
−
;y
;<
=0
;<
;=
=
z
{
]KI
|
}~a{|
}
•€
••

(17)
P o ided ha in e es a e is gi en by an ex e nal ma ke independen om 
managemen , he ollowing holds ue:
pn
p = p
p1+Qdd+=d⋅pQ
pd++1+Qd
=
IK
RSKWX
∙
‚<W‚
<WX
+1+Qd≈−
‚<W‚
X<WX
+1+Qd
In he case ha H ≡
X<WX
‚<W‚
1+Qd>1,
;y
;<
>0 , hen
;<
;=
<0 The nume a o o
equa ion (17) is nega i e in a ma u ed economy (N > V > N/2) whe eas he opposi e
occu s in an eme ging economy (V < N/2).
In he case ha g > ,
X<WX
‚<W‚
1+Qd>
‚<W‚
‚<W‚
1+Qd=1+Qd>1,
;<
;=
<0.
6
The in e nal a e o e u n o R&D in es men in equa ion (11) should be no lowe han he
in e es a e, and maximum digi al subs i u ion o adi ional p oduc ion ac o X should be sough .
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Appendix 3. Ra es o Obsolescence o Technology and Dep ecia ion o
Sold Goods and Se ices
A3.1 Ra e o Obsolescence o Technology
On he basis o a his o ical e iew compa ing di e en coun ies which is abula ed in
Table 4, he a e o obsolescence o echnology in he Finnish PPI
7
in 1995 can be
es ima ed as 7%.
Table A1 Ra e o Obsolescence o Technology in he Manu ac u ing Indus y
in he 1980s and 1990s
1980s a e age
(1985)
1995 A e age
g ow h a e Re e ences
Japan
9.8
*1
12.3
*2
2.5 % p.a
*1 Japan Science & Technology Agency (1985)
Wa anabe (1992)
*2 Wa anabe (1999)
USA
6.7
*3
9.0
*4
3.0 % p.a
*4
*3 Mi subishi Resea ch Ins i u e (1991)
*4 Highe pace han Japan du ing a pe iod o
new economy
Eu ope
5-10
*5
6.5
*6
8.0
*7
2.0% p.a
*7
*5 Scho and Boswo h (1978).
*6 Pace o echnological change is simila o
he USA (OECD).
*7 Pace o echnological change is simila o
Japan (OECD)
Elec onics/machine y 9%, Chemicals 8%
Pulp & pape / ood 7%
As e iewed in Sec ion 2, UPM’s de elopmen ajec o y o e he las qua e cen u y
has been shi ing om an eme ging economy o a ma u ed economy in o med by a
ci cula economic s a egy wi hin a esu gen economy. This ajec o y shi co esponds
o he ad ancemen o he digi al economy, and he coun e measu es o his shi la gely
depend on digi al solu ions led by he ad ancemen o he in e ne (Tie o, 2017).
Wi h his unde s anding, UPM’s a e o obsolescence o echnology as pa o i s planned
obsolescence s a egy can be conside ed a unc ion o he ad ancemen o digi al
inno a ion ep esen ed by in e ne dependence (I) as ollows:

G
=
L∙

O
(18)
whe e 
L
: he a e o obsolescence o echnology o he base yea and P: coe icien .
As e iewed in Sec ion 2,

;<
;
> 0
in an eme ging economy, while
;<
;
<0 in a ma u ed
economy. Finally,

;<
;ƒ
< 0→
;<
;
> 0
in ci cula economy based on a esu gen economy
8
.
In addi ion, as e iewed in Fig. 13, gi en i ms’ planned obsolescence managemen
7
Since pulp and pape indus y is non-R&D in ensi e indus y as demons a ed below, i s pace o
echnological change is among he lowes g oup in he manu ac u ing indus y.
R&D in ensi y in 2014 (Japan’s case): Pha maceu ical 7.8%, elec onics 6.5%, chemicals 3.9%, machine y
3.7%, ex iles 2.4%, pulp & pape 0.7%, ood 0.6%.
8
;<
;=
=
;<
;
∙
;
;=
and
;
;=
>0 in a digi al economy.
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s a egy, he a e o obsolescence o echnology is also subjec o he long- e m in e es
a e ( ).
Taking all hese ac o s in o accoun , UPM’s a e o obsolescence o echnology o e he
1990-2017 pe iod was es ima ed by he ollowing equa ion. The coe icien was
iden i ied by a heu is ic app oach, sa is ying all condi ions necessa y o he planned
obsolescence s a egy, as illus a ed in Fig. 13.

K„„…
=0.07, 
G
=
K„„…
∙
L.K
(1990-2001),

G†<{UU~

IL.K
(2002-2017)
A3.2 Ra e o Dep ecia ion o Sold Goods and Se ices
While i ms’ s a egy o planned dep ecia ion o ma ke alue is based on he simila
s a egy o planned obsolescence o echnology in p inciple (Keeble, 2013), i is mo e
sensi i e o ac o s o he han digi al solu ions (Disney e al., 2003; Obeng e al., 2014).
As e iewed in Sec ion 4, i is subjec o he ad ancemen o he in e ne , simila o
,ye i is also subjec o he ends in sales (S) and echnology s ock (T). Bo h gene ally
eac o sa u a e and/o subs i u e goods and se ices, leading o an inc ease in he a e o
dep ecia ion o ma ke alue : (Boswo h, 1978). In addi ion, ad ancemen o he
in e ne eac s by ex ending he li e cycle, leading o dec easing :. The e o e :
G
can be
depic ed by he ollowing equa ion:
:
G
=:
L

Ge
∙hY,E, (13)
‡
G
=ˆ⋅Y
‰
E
Š

‹

(19)
whe e A: scale ac o and Œ,•and•: coe icien s.
Following he es ima ed a e o obsolescence o echnology, he p ima y go e ning ac o
:
L

Ge
 can be es ima ed as ollows
9
:
:
K„„…
=0.04, :
G
=:
K„„…
∙
L.K
(1990-2001),
:
G
=:
wLLK
∙
IL.K
(2002-2017)
By means o a heu is ic app oach sa is ying all condi ions necessa y o he planned
obsolescence s a egy, as illus a ed in Fig. 12, he coe icien s o equa ion (19) we e
iden i ied as ollows:
h
G
=0.25∙Y
L.’“
E
L.”w

IL.K“
(1990-2001), h
G
=0.29∙Y
L.’“
E
L.”w

IL.K„
(2002-2017)
Consequen ly, :
G
was es ima ed as ollows:
:
G
=0.01⋅
IL.L“
Y
L.’“
E
L.”w
(1990-2001), 0.013∙
IL.w„
Y
L.’“
E
L.”w
(2002-2017):
G
9
The esu gence o he o es indus y has been expec ed o dissemina e goods and se ices in exis ing
indus ies h ough inno a ion (Technology S a egy Boa d, 2014): Fo mable plywood (de eloped by
UPM) and wood-based cas ing plas e (de eloped by Onbone) a e ypical examples in he 2010s, wi h
li e imes o 30 yea s (Finnish Fo es Indus ies Fede a ion, 2012). Acco dingly, hei :
wLKL•
was es ima ed
as 0.033. Gi en he dec easing end in:
G
since he ea ly 1990s, :
K„„…
was es ima ed o be 0.04.
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Appendix 4. Key Da a o Analyses (1): P ima y Da a
GDP de la o alue o 2017 was es ima ed based on he g ow h a e o he las 20 yea s.
R&D alues o 1992-1994 we e es ima ed based on he g ow h a e o he ollowing 5 yea s.
The in e ne dependence alue o 2017 was adjus ed based on 2013-2015 g ow h a e.
In e ne p ice p
i
was es ima ed by he ollowing lea ning
equa ion: 
G
=55.3
G
-0.6
(Tou e al., 2018).
UPM ene gy cos : UPM’s annual epo s. Values o 1990-1994 we e based on backwa d es ima ion.
Ene gy P ice: A e age annual OPEC c ude oil p ice (S a is a, 2018); ene gy cos and p ices we e de la ed by GDP de la o
.
Yea UPM
Sales
(Mil.
Eu o)
(nominal)
UPM
Sales
(Mil.
Eu o)
( eal)
UPM
R&D
(Mil.
Eu o)
(nominal)
UPM
R&D
(Mil.
Eu o)
( eal)
UPM
R&D
in ensi y
(R&D/
Sales)(%)
UPM ma ke
capi aliza ion
(Mil. Eu o)
(nominal)
UPM ma ke
capi aliza ion
(Mil. Eu o)
(Real)
GDP
de la o
(base yea
2010)
In e ne
dependence
Finland
(%)
In e ne
p ice
Finland
(Real)
UPM
ene gy
cos
(Mil.
Eu o)
(Real)
Ene gy
p ice
US$/ba el
(Real)
1990
6224.0 8629.5 21.5 29.8 0.35 2002 2776 72.13 0.4 95.83 747.51 30.86
1991
6007.0 8200.7 23.6 32.2 0.39 1894 2586 73.25 1.4 45.19 743.84 25.42
1992
6283.0 8498.6 25.7 34.8 0.41 1968 2662 73.93 1.9 37.62 744.72 24.94
1993
7394.0 9824.1 27.8 37.0 0.38 3852 5118 75.26 2.6 31.17 739.11 21.70
1994
8067.0 10524.3 29.9 39.1 0.37 3948 5151 76.65 4.9 21.31 733.20 20.26
1995
9206.0 11526.7 33.0 41.3 0.36 3690 4620 79.87 13.9 11.40 741.23 21.11
1996
8705.0 10910.3 35.0 43.9 0.40 4340 5439 79.79 16.8 10.18 736.96 25.43
1997
8478.0 10405.3 35.0 43.0 0.41 4957 6084 81.48 19.5 9.30 704.49 23.15
1998
8365.0 9956.8 36.0 42.9 0.43 6630 7892 84.01 25.5 7.92 651.09 14.62
1999
8261.0 9740.7 41.0 48.3 0.50 10663 12573 84.81 32.3 6.87 633.19 20.56
2000
9583.0 11118.3 44.0 51.0 0.46 9502 11024 86.19 37.3 6.31 718.17 32.02
2001
9918.0 11135.7 45.0 50.5 0.45 9681 10870 89.06 43.1 5.78 715.21 25.96
2002
10475.0 11648.1 46.0 51.2 0.44 7960 8851 89.93 62.4 4.63 765.05 27.09
2003
9948.0 11038.5 48.0 53.3 0.48 7917 8785 90.12 69.2 4.35 745.66 31.18
2004
9820.0 10830.6 47.0 51.8 0.48 8578 9461 90.67 72.4 4.24 843.73 39.76
2005
9348.0 10215.7 50.0 54.6 0.53 8665 9469 91.51 74.5 4.16 885.19 55.29
2006
10022.0 10853.2 44.0 47.6 0.44 10005 10835 92.34 79.7 4.00 1012.55 66.06
2007
10035.0 10574.9 50.0 52.7 0.50 7084 7465 94.89 80.8 3.97 916.81 72.75
2008
9461.0 9672.4 49.0 50.1 0.52 4680 4785 97.81 82.5 3.92 858.77 96.20
2009
7719.0 7746.1 48.0 48.2 0.62 4326 4341 99.65 83.7 3.88 818.86 69.10
2010
8924.0 8924.0 45.0 45.0 0.50 6874 6874 100.00 86.9 3.80 836.00 77.38
2011
10068.0 9814.4 50.0 48.7 0.50 4466 4354 102.58 88.7 3.75 965.06 104.75
2012
10492.0 9934.3 45.0 42.6 0.43 4633 4387 105.61 89.9 3.72 885.30 103.63
2013
10054.0 9282.7 38.0 35.1 0.38 6497 5999 108.31 91.5 3.68 839.27 97.75
2014
9868.0 8959.3 35.0 31.8 0.35 7266 6597 110.14 92.4 3.67 892.48 87.42
2015
10138.0 9023.3 37.0 33.0 0.37 9192 8181 112.35 92.7 3.65 704.92 44.05
2016
9812.0 8652.3 40.0 35.4 0.41 12452 10980 113.40 93.4 3.63 589.93 35.87
2017
10010.0 8818.4 51.0 44.9 0.48 13818 12173 113.51 94.0 3.62 523.29 46.26

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Appendix 4. Key Da a o Analyses (2): Cons uc ed Da a
EG =HGIJ +1−EGIK, EL =HKIJ +M
⁄
, whe e g = 0.05
(a e age o g ow h a e o 1996-2000). Fo

G
,
see
Appendix 3, and o m
,
see Appendix 1.
BG=YG+ (1 -:BGIK, BL=YK:+Z
⁄
,
whe e
k = 0.01 (a e age g ow h a e o 1995-2000), Fo :?, see Appendix 3.
Yea
Ra e o
obsolescence
o echnology
ρ
Ra e o
dep ecia ion
o sold goods
and se ices
:
::
:
UPM
echnology
knowledge
s ock
(Mil. Eu .)
T
UPM
ma ke alue
(Mil. Eu .)
V
Lead ime
be ween
R&D and
comme ciali
za ion
m
In e ne
dependence
Finland
(s anda dized
1995 = 1)
I
UPM
ene gy
consump ion
(Ba el)
E
1990
6.9 0.037 244.4 211857.9 3.5 0.03 24.2
1991
6.9 0.034 259.6 212865.8 3.4 0.10 29.3
1992
6.9 0.035 274.8 213935.1 3.4 0.14 29.9
1993
7.0 0.041 290.0 215065.9 3.4 0.19 34.1
1994
7.0 0.043 305.2 216257.7 3.3 0.35 36.2
1995
7.0 0.040 308.0 216484.6 3.3 1.00 35.1
1996
7.0 0.045 323.4 217759.0 3.2 1.21 29.0
1997
7.0 0.041 339.6 219176.5 3.2 1.40 30.4
1998
7.1 0.038 356.9 220747.7 3.1 1.83 44.5
1999
7.1 0.036 375.3 222496.1 3.1 2.32 30.8
2000
7.2 0.043 391.4 224076.2 3.0 2.68 22.4
2001
7.2 0.043 406.0 225556.6 2.9 3.10 27.6
2002
7.2 0.043 425.3 227549.9 3.0 4.49 28.2
2003
7.1 0.039 446.0 229751.5 3.1 4.98 23.9
2004
7.0 0.038 465.1 231815.9 3.2 5.21 21.2
2005
7.0 0.035 483.9 233867.3 3.4 5.36 16.0
2006
6.9 0.037 503.9 236048.8 3.5 5.73 15.3
2007
6.8 0.037 521.3 237948.0 3.6 5.81 12.6
2008
6.8 0.032 540.6 240038.8 3.7 5.94 8.9
2009
6.7 0.027 551.9 241250.8 3.8 6.02 11.9
2010
6.7 0.030 567.6 242914.3 3.8 6.25 10.8
2011
6.7 0.035 579.8 244180.2 3.8 6.38 9.2
2012
6.7 0.037 589.2 245152.5 3.8 6.47 8.5
2013
6.7 0.035 594.9 245734.2 3.9 6.58 8.6
2014
6.7 0.033 604.0 246650.6 3.9 6.61 10.2
2015
6.7 0.036 606.4 246888.2 3.9 6.67 16.0
2016
6.7 0.032 613.8 247622.4 3.9 6.72 16.4
2017
6.7 0.033 619.8 248217.5 3.9 6.76 11.3
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Appendix 5.
T end in Ma ginal P oduc i i y o Technology Co esponding
wi h In e nal Ra e o Re u n o R&D In es men
(1990-2017)
Fig. A1. T end in UPM’s Ma ginal P oduc i i y o Technology (1990-2017).
Table A2 T end in Ma ginal P oduc i i y o Technology Co esponding wi h
In e nal Ra e o Re u n o R&D In es men
(1990-2017)
Yea ρ m
Q = (1 + m )( + ρ) H = g(ρ + g)(1 + m )/ ( + ρ)
1990 0.109 0.069 2.789 0.232 0.401
1991 0.102 0.069 2.835 0.220 0.442
1992 0.098 0.069 2.880 0.215 0.465
1993 0.084 0.070 2.926 0.192 0.576
1994 0.082 0.070 3.284 0.192 0.613
1995 0.087 0.070 3.249 0.202 0.561
1996 0.072 0.071 3.217 0.177 0.720
1997 0.060 0.072 3.145 0.157 0.924
1998 0.047 0.074 3.063 0.139 1.247
1999 0.047 0.076 3.003 0.140 1.257
2000 0.054 0.077 2.933 0.153 1.030
2001 0.050 0.078 2.991 0.148 1.141
2002 0.049 0.060 3.066 0.126 1.178
2003 0.042 0.060 3.214 0.115 1.476
2004 0.041 0.059 3.369 0.115 1.494
2005 0.034 0.059 3.485 0.105 1.899
2006 0.039 0.059 3.573 0.111 1.647
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2007 0.043 0.059 3.670 0.118 1.426
2008 0.044 0.059 3.765 0.119 1.419
2009 0.040 0.058 3.803 0.114 1.571
2010 0.038 0.058 3.824 0.110 1.706
2011 0.043 0.058 3.838 0.118 1.444
2012 0.031 0.058 3.857 0.099 2.236
2013 0.030 0.058 3.861 0.098 2.273
2014 0.023 0.058 3.871 0.088 3.190
2015 0.013 0.058 3.879 0.074 6.313
2016 0.009 0.058 3.886 0.070 8.947
2017 0.005 0.058 5.4713 0.064 19.185
pB
pE =iB
iE =B
G
E
G
 1−B
G
E
G

s = 1+Q
G
d
G
d
G
+
G

: Long e m in e es a e
10
o eu o a ea exp essed as pe cen pe annum (Sou ce: OECD).
ρ: Ra e o obsolescence o echnology.
m: Lead ime be ween R&D and comme cializa ion.
g: Inc ease in a e o R&D a ini ial s age.
In he case ha H > 1, p/pE < 0 (see Appendix 2). Table 2 demons a es he s abili y
o H, in which H > 1a e 2003.
10
‘
Long- e m in e es a es e e o go e nmen bonds ma u ing in en yea s. Ra es a e mainly de e mined by he
p ice cha ged by he lende , he isk om he bo owe and he all in he capi al alue. Long- e m in e es a es a e
gene ally a e ages o daily a es, measu ed as a pe cen age. These in e es a es a e implied by he p ices a which he
go e nmen bonds a e aded on inancial ma ke s, no he in e es a es a which he loans we e issued. In all cases,
hey e e o bonds whose capi al epaymen is gua an eed by go e nmen s. Long- e m in e es a es a e one o he
de e minan s o business in es men . Low long- e m in e es a es encou age in es men in new equipmen and high
in e es a es discou age i . In es men is, in u n, a majo sou ce o economic g ow h’ (OECD).
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Re e ences
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[3] Boswo h, D.L., 1978. The Ra e o Obsolescence o Technical Knowledge: A
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