AppendixA.1 An Overview on Intelligent CityEvaluation Systems in the World
See Tables A.1, A.2, A.3, A.4, A.5, A.6, A.7, A.8, A.9, A.10, A.11, A.12, A.13 andA.14.
© Springer Nature Singapore Pte Ltd. and Zhejiang University Press 2018Z. Wu, Intelligent City Evaluation System, Strategic Researchon Construction and Promotion of China’s Intelligent Cities,https://doi.org/10.1007/978-981-10-5939-1
165
Tab
leA.1
Nationalintelligent
city
(district,town)
pilotindicatorsystem
Firstgrade
indicator
Second
ary
indicators
Tertiary
indicators
Indicatordescription
Security
system
andinfrastructure
Security
system
Developmentplan
outline
andim
plem
entatio
nplan
for
intelligent
city
Refersto
theintegrity
andfeasibility
ofintelligent
city
developm
entplan
outline
and
implem
entatio
nplan
Organizations
Refersto
theestablishm
entof
aspecialleadership
organizatio
nsystem
andtheexecutive
body
,respon
sibleforthecreatio
nof
smartcity
Policiesandregulatio
nsRefersto
thepoliciesandregulatio
nsto
ensure
theconstructio
nandoperationof
intelligent
city
Bud
getplanning
and
continuous
protectio
nRefersto
thebudgetplanning
andprotectio
nmeasuresof
theintelligent
city’sconstructio
n
Operatio
nmanagem
ent
Refersto
theoperationsubjectto
definite
theintelligent
city
andbuild
theoperated
supervisionsystem
Network
infrastructure
Wirelessnetwork
Refersto
thebasicconditionsof
wirelessnetworkcoverage,speed
Broadband
network
Refersto
thebasicconditionsof
fixedbroadbandaccess
coverage,accessspeed,
including
optical
fiber
Nextgeneratio
nbroadcastin
gRefersto
theconstructio
nandusageof
thenext
generatio
nbroadcastin
g
Public
platform
anddatabase
City
public
basicdatabase
Refersto
establishpu
blic
basicdatabases,such
ascity
basicspatialdatabase,p
opulation
basicdatabase,basicdatabase
oflegalperson,macroeconom
icdatabase,build
ing
foun
datio
ndatabase
andetc.
City
public
inform
ation
platform
Refersto
theconstructio
nof
inform
ationplatform
tothecity’s
allkind
sof
public
inform
ation,
which
canbe
unified
managem
entand
exchanged,
meetthe
city
allk
inds
ofbu
siness
andindu
stry
demandforpu
blic
inform
ationexchange
andservice
(con
tinued)
166 Appendix
Tab
leA.1
(con
tinued)
Firstgrade
indicator
Secondary
indicators
Tertiary
indicators
Indicatordescription
Inform
ationsecurity
Refersto
thesafeguardmeasuresandeffectivenessof
theintelligent
city’s
inform
ation
security
Smart
constructio
nand
livable
City
constructio
nadministration
Urban
andruralplanning
Refersto
thepreparationof
completeandreasonable
urbanandruralplanning,and
accordingto
theneedsof
thedevelopm
entof
thecity,makingtheroad
trafficplanning,
historical
andcultu
ralcity
protectio
nplanning,landscape
planning
andspecificplanning
,to
comprehensively
guidetheconstructio
nof
city
Digitalcity
managem
ent
Refersto
build
adigitalcity
managem
entsystem
basedon
therelevant
natio
nalstandards
with
city’s
geospatialfram
ework,
establishperfectedassessmentandincentive
mechanism
,to
realizeregional
grid
managem
ent
Constructingmarket
managem
ent
Refersto
form
ulatethelawsandregulatio
nsof
constructin
gmarketmanagem
ent,and
prom
otethego
vernment’sabilitiesof
supervisionandmanagem
entin
theconstructio
nsurvey,design,constructio
nandsupervisionby
usingtheinform
ationmeans
Estatemanagem
ent
Refersto
prom
otethego
vernment’scomprehensive
managem
entservices
abilitiesin
anumberof
areasof
housingplanning,real
estate
sales,interm
ediary
services,property
mapping
byform
ulatingandim
plem
entin
geffectivepo
lices
ofreal
estate
managem
ent,
andusetheinform
ationtechno
logy
means
tomanagethereal
estate
Smart
constructio
nand
livable
City
constructio
nmanagem
ent
Landscaping
Refersto
prom
otethelevelof
mon
itoring
andmanagem
entof
landscaping,
prom
otethe
levelo
furbangarden
greening
throughtheapplicationof
advanced
technology
ofremote
sensing
Protectio
nin
historyand
cultu
reRefersto
prom
otethelevelof
protectio
nin
urbanhistoryandcultu
rethroug
hthe
applicationof
inform
ationtechnology
means
Buildingenergy
supervision
Refersto
prom
otethecity’s
working
levelin
build
ingenergy
efficiency
supervision,
evaluatio
n,controlandmanagem
entthroughtheapplicationof
inform
ationtechnology
means
(con
tinued)
Appendix 167
Tab
leA.1
(con
tinued)
Firstgrade
indicator
Secondary
indicators
Tertiary
indicators
Indicatordescription
Green
build
ing
Refersto
prom
otecity’slevelingreenbuild
ingconstructio
n,managem
entand
evaluatio
nthroughform
ulatingeffectivepoliciesandcombining
with
theapplicationof
inform
ation
techno
logy
means
City
functio
nprom
otion
Water
supply
system
Refersto
realizereal-tim
emon
itoring
andcontroltothewho
lewater
supply
processfrom
water
source
mon
itoring
totapwater
managem
ent,form
ulatereasonable
inform
ation
publicity
system
andguaranteetheresidentialwater
security
byusinginform
ation
techno
logy
means
Drainagesystem
Refersto
theconstructio
nof
drainage
facilitiesin
dischargingof
life,
industrial
sewage,
urbanrainwater
collectionandchannel,andprom
otethedevelopm
entof
itsov
erall
functio
nby
usinginform
ationtechnology
means
Water-savingapplication
Refersto
theusageof
city
water-savingequipm
entandthecyclic
utilizatio
nof
water
resources,andprom
otetheov
eralllevelof
itsdevelopm
entby
usinginform
ation
techno
logy
means
Gas
system
Refersto
thepopularity
ofcity
usingclean,
andprom
otethedevelopm
entof
safe
operationlevelby
usinginform
ationtechnology
means
Garbage
classificatio
nand
handlin
gRefersto
thepo
pularity
ofwasteclassificatio
nforthecommunity
andthehand
lingability
ofgarbageharm
less,andprom
otetheoveralllevelof
itsdevelopm
entby
using
inform
ationtechno
logy
means
Heatin
gsupply
system
Refersto
theno
rthern
city’s
winterheatingfacilitiesconstructio
n,prom
otetheoverall
levelof
itsdevelopm
entby
usinginform
ationtechno
logy
means
Lightingsystem
Refersto
thecoverage
andenergy-savingautomationapplieddegree
ofcity’s
allk
inds
iflig
htings
Integrated
managem
entof
undergroun
dpipe
andspace
Refersto
realizeurbanundergroundpipe
networkdigitalintegrated
managem
entand
mon
itoring,andprom
otemanagem
entlevelby
usingthetechno
logy
means
of3D
visualization
(con
tinued)
168 Appendix
Tab
leA.1
(con
tinued)
Firstgrade
indicator
Second
ary
indicators
Tertiary
indicators
Indicatordescription
Smart
managem
entand
service
Gov
ernm
ent
affairsservice
Decisionsupport
Refersto
inform
ationmeans
andsystem
supportin
ggo
vernmentdecision-m
aking
Inform
ationdiscourse
Refersto
public
thegovernmentinform
ationin
thefieldof
theapprov
aland
implem
entatio
nof
budget
balance,
major
constructio
nprojects,constructio
nof
public
undertakings
activ
ely,
timelyandaccurately
throug
hthego
vernmentwebsites
Online-do
Refersto
perfectthefunctio
nof
thegovernmentportal
website,expand
thescopeof
Internet
business,im
provetheefficiency
ofon
linebu
siness
Smart
managem
entand
service
Gov
ernm
ent
affairsservice
Gov
ernm
entaffairsservice
system
Refersto
theconnectio
nandintegrationof
alltypesof
governmentaffairsservice
platform
s,build
upandlin
kage,clear
hierarchyandgovernmenta
ffairs
servicesystem
ofupperandlower
linkage,clearhierarchyandcovering
urbanandruralareas
Basic
public
service
Basic
public
education
Refersto
makeareasonableeducationdevelopm
entp
lan,
usetheinform
ationtechnology
toim
provetarget
populatio
n,which
canaccess
toconvenient
levelof
basicpublic
educationservices,andprom
otecoverage
andshareof
educationresources
Employmentservice
Refersto
throug
hthecontinuous
improv
ementof
theregulatio
nsandsystem
,com
bining
with
theapplicationof
moderninform
ationtechnology,enhance
themanagem
entlevelof
city
employmentservice,
throughthemeasuresof
theestablishm
entof
employment
inform
ationserviceplatform
toprom
otethereleaseof
employmentinform
ationability,
strengthen
theguaranteeof
free
employmenttraining,protectthelegitim
aterightsand
interestsof
workers
Social
insurance
Refersto
throughtheapplicationof
inform
ationtechnology,improvethetargetpopulatio
nto
enjoythebasicold-ageinsurance,basicmedicalinsurance,unem
ployment,workinjury
andmaternity
insuranceserviceconv
eniencedegree,im
prov
ethequ
ality
supervisionof
social
insuranceservices,im
prov
ethelevelof
residents’
lifesafegu
ardthroug
hthe
inform
ationserviceterm
inal
constructio
non
thebasisof
improvingcoverage
scale
Social
services
Refersto
throughtheapplicationof
inform
ationtechnology,improvethetargetpopulatio
nto
enjoytheconveniencedegree
ofsocial
relief,social
welfare,the
basicpensionservice
andtheentitledgroups
andotherservices,im
provethelevelo
fservice
quality
supervision
andim
prov
ethetransparency
ofservices,safeguardsocial
fairness
throug
hthe
inform
ationserviceterm
inal
constructio
non
thebasisof
improvingcoverage
scale
(con
tinued)
Appendix 169
Tab
leA.1
(con
tinued)
Firstgrade
indicator
Secondary
indicators
Tertiary
indicators
Indicatordescription
Medical
services
Refersto
improv
ethelevelof
basicpu
blic
health
services
throug
htheapplicationof
inform
ationtechno
logy
;guarantee
allk
inds
crow
dsuch
aschild
ren,
wom
en,the
oldman
getsatisfactoryservicethroughtheinform
ationmanagem
entsystem
constructio
nand
term
inalservices;g
uarantee
thesafety
supply
offood
anddrug
throughtheestablishm
ent
oftraceabilitysystem
offood
anddrugs,andprom
otepu
blic
opinionsurveillance,
improvethetransparency
ofservicequality
supervision
Public
cultu
reandsports
Refersto
enlargetheservices
ofpubliccultu
ralservice
area,improvethepopularity
rateof
access
radio,
film
andtelevision
throug
htheapplicationof
inform
ationtechno
logy
;im
provetheconvenient
degree
ofcultu
ralcontentforallkindsof
people,through
popularity
ofinform
ationterm
inal;and
increase
thesportsfacilitiesservice’scoverage
and
utilizatio
n
Services
fordisabled
Refersto
prom
otethelevelo
fsocialsecurity
andbasicservices
forthe
disabled,provide
asoundbody,h
ealth
servicefacilitiesandrich
servicecontentthrough
theInform
atization,
personalized
applicationdevelopm
enton
thebasisof
improvingthecoverage
rate
ofservice
Smart
managem
entand
service
Special
application
Basic
housingsecurity
Refersto
throug
htheapplicationof
inform
ationtechno
logy
,the
prom
otetheservicelevel
oflow-renthousing,
public
housingareas,shantytowns
transformation,
enhancethe
convenienceof
service,
improv
ethetransparency
oftheservice
Intelligent
transportatio
nRefersto
thesm
artconstructio
nandoperationof
city’s
who
letraffic,
includingpu
blic
transportatio
nconstructio
n,trafficaccident
treatm
ent,applicationof
electron
icmaps,the
urbanroad
constructio
nof
sensor
andthetrafficindu
cedinform
ationapplication
Smartenergy
Refersto
theconstructio
nof
urbanenergy
wisemanagem
entanduse,
includingsm
art
meter
installatio
n,energy
managem
entandutilizatio
n,theconstructio
nof
street
lamp
intelligent
managem
ent,etc.
Smartenvironm
ental
protectio
nRefersto
theconstructio
nof
urbanenvironm
ent,managem
entandserviceof
ecological
wisdom,includingtheconstructio
nof
airquality
monito
ring
andservice,
surfacewater
environm
entquality
monito
ring
andservice,
theenvironm
entalnoisemonito
ring
and
service,
pollu
tionsourcesmon
itoring
,urbanwater
environm
ent,etc.
(con
tinued)
170 Appendix
Tab
leA.1
(con
tinued)
Firstgrade
indicator
Secondary
indicators
Tertiary
indicators
Indicatordescription
Smartland
Refersto
thesm
artconstructio
nof
thecity
land
andresourcesmanagem
entandservice,
includingtheconstructio
nof
land
useplanning
implem
entatio
nandmonito
ring
ofland
resources,land
usechange
monito
ring,cadastralmanagem
ent,etc.
Smartem
ergency
Refersto
theconstructio
nof
urbansm
artem
ergency,
includingtheconstructio
nof
emergencyreliefmaterials,emergencyresponse
mechanism
,emergencyresponse
system
,disaster
warning
capabilities,disaster
preventio
nandmitigatio
ncapabilities,em
ergency
commandsystem
,etc.
Smartsafety
Refersto
thesm
artconstructio
nof
urbanpu
blic
safety
system
,includ
ingurbanfood
safety,drug
safety,safe
city
constructio
n
Smartlogistics
Refersto
theconstructio
nof
intelligent
logisticsmanagem
entandservice,
includingthe
constructio
nof
logisticspublicserviceplatform
,intellig
entw
arehousing
services,logistics
callcenter,logisticstraceabilitysystem
,etc.
Smartcommunity
Refersto
thedigital,convenient,intelligent
levelof
thecommunity
managem
entand
service,
includingtheconstructio
nof
community
serviceinform
ationpush,inform
ation
servicesystem
coverage,community
sensor
installatio
n,community
operationsecurity,
etc.
Smarthomefurnishing
Refersto
theconstructio
nof
homefurnishing
safety,convenience,
comfort,artistic
and
environm
entalprotectio
nandenergy
conservatio
n,includinghomefurnishing
intelligent
control,such
asintelligent
appliancecontrol,lig
htingcontrol,security
controla
ndaccess
control,homefurnishing
digitalservicecontent,homefurnishing
facilitiesinstallatio
n,etc.
Smartpaym
ent
Refersto
smartnew
paym
entway
ofonecartoon,
mobile
paym
ent,citizen
card,and
constructio
nof
convenience,
safety,andconstructio
nof
merchantspayforconvenience,
safety,etc.
Smartfinance
Refersto
theurbanfinancialsystem
smartconstructio
nandservices
includingthe
constructio
nof
honestregulatory
system
,investmentandfinancingsystem
,financial
security
system
,etc.
(con
tinued)
Appendix 171
Tab
leA.1
(con
tinued)
Firstgrade
indicator
Secondary
indicators
Tertiary
indicators
Indicatordescription
Smartindu
stry
andecon
omy
Industry
planning
Indu
stry
planning
Refersto
theurbanindu
strial
planning-m
akingandcompletion,
surrou
ndingthecity
industry
developm
ent,industry
transformationandupgrade,
thestrategicindustries
ofem
erging
industry
developm
entplanning,p
lanningof
thepublic
andthesituationof
the
implem
entatio
n
Inno
vatio
ninpu
tRefersto
thecity’s
inno
vatio
nindu
stry
inpu
t,includingcostinpu
tof
indu
stry
transformationandupgrade,
innovatio
ninputof
thedevelopm
entforem
erging
industry,
etc.
Industry
upgrade
Industrialelem
entsgathered
Refersto
thecity
fortheindustry
developm
ent,industry
transformationandupgradeand
theim
plem
entatio
nof
industry
elem
entsgathered,grow
thconditions
Transform
ationof
traditional
industry
Refersto
realizethetransformationof
traditional
industries
intheprocessof
achieving
industrial
upgrading
Develop
mentof
emerging
industry
Highandnew
techno
logy
indu
stry
Refersto
theservices
anddevelopm
entof
city’s
high
andnew
technology
industries,
includ
ingthetalentsenvironm
ent,scientificresearch
environm
ent,financialenvironm
ent
andthestatus
ofthemanagem
entserviceindustries,thedevelopm
entof
high-tech
industries
andthestatus
ofthelevelof
thewhole
industry
inthecity
supportin
gthenew
andhigh
techno
logy
Mod
ernserviceindu
stry
Refersto
thecity’s
mod
ernserviceindu
stry
developm
entstatus,includingthepo
licy
environm
entfor
the,developm
ente
nvironment,developm
entlevelandinvestmento
fthe
developm
entof
mod
ernserviceindu
stry
Other
emerging
indu
stry
Reflectin
gthedevelopm
entandthestatus
oftheprom
otionof
thecity’s
otherem
erging
industries
172 Appendix
Tab
leA.2
MIIT’s
intelligent
city
evaluatio
nindicatorsystem
Overall
indicators
Firstgrade
indicator
Second
ary
indicators
Inspectio
npo
ints
Descriptio
n
City
intelligence
Intelligence
preparation
Network
environm
ent
Fixed
broadband
Average
rate
ofthenetwork
Com
prehensively
reflected
the
constructio
nof
fixedbroadband’s
appliedlevel
Userratio
ofusing4M
broadbandproductsor
above
Hou
seho
ldrate
ofop
tical
fiber
Internet
penetrationrate
Mob
ileinternet
3Gnetworkcoverage
Com
prehensively
reflected
the
constructio
nof
mobile
internet’s
developm
entallevel
WLAN
coverage
Owning
rate
ofsm
artph
one
Userratio
nof
Mobile
broadband
Techn
ical
preparation
Internet
ofThing
sapplication
demonstratio
n
Internet
ofThingsapplicationdemonstratio
nefficacy
inkey
indu
stries
ofecon
omic
operation,
includingindu
stry,
agricultu
re,circulationindustry
Com
prehensively
reflected
the
constructio
nof
Internet
ofThingsin
thecity’s
keyfield
Internetof
things
applicationdemonstratio
nefficacy
towards
thefields
ofinfrastructure
andsecurity
assurance,including
transportatio
n,electricity
,environm
entalprotectio
n
Internetof
things
applicationdemonstratio
nefficacy
towards
thefields
ofsocial
managem
entandthepeople’s
livehoo
dservices,includingpu
blic
safety,health
care,sm
artho
me
City
intelligence
Intelligence
preparation
Techn
ical
preparation
Cloud
compu
ting
technology
application
Effectiv
enessof
demonstratio
nprojectsrelatedto
cloud
compu
tingapplications
Reflectin
gtheapplicationof
clou
dcompu
tingtechno
logy
Wetherto
form
ulatepo
licydo
cumentsto
guidecloud
compu
tingapplications
Financialsupportforcloudcompu
tingapplications
Guarantee
cond
itions
Policy
planning
Wetherto
form
ulatedocumentsrelatedto
intelligent
city’s
developm
entoutline,specialplan,actio
nplan
Reflectin
gthego
vernmentattention
totheconstructio
nof
intelligent
city
(con
tinued)
Appendix 173
Tab
leA.2
(con
tinued)
Overall
indicators
Firstgrade
indicator
Second
ary
indicators
Inspectio
npoints
Descriptio
n
Wetherto
form
ulaterelevant
policydo
cumentsof
encouragingthedevelopm
entof
city
inform
atizationand
application
Capitaltalents
Governm
entinvestment,social
investmentandfinancing
supportrelatedto
theintelligent
city
constructio
nReflectin
gthegu
aranteecapability
ofintelligent
city
relatedcapital
talents
Num
berof
city
inform
ationtechnology
professionals,and
thedeveloping
training
numberof
high
school
andtraining
agencies’relatedtalents
Smart
managem
ent
City
operation
managem
ent
ability
Num
berof
unitarea
inform
ationcollection,
monito
requipm
ent
Reflectin
gcity’s
integrated
inform
ationcollectionability
Constructionandapplicationof
thebusiness
supportsystem
oroperativeoffice,
resource
sharing,
administrativeexam
inationandapproval,adm
inistrativelaw
enforcem
entsupervision
Reflectin
gthesystem
supporta
bility
ofthego
vernmentintegratedservice
Constructionandapplicationof
business
supportsystem
foreconom
icmonito
ring,creditsupervision,
investmentandfinancing,
energy
saving
and
emission
reduction
Reflectin
gthesystem
supporta
bility
ofcity
econ
omyop
eratingbu
siness
Constructionandapplicationof
business
supportsystem
fortraffic,
social
security,medical
care,education,
environm
entalprotectio
nReflectin
gthesystem
supporta
bility
ofcity
social
business
managem
ent
Constructionandapplicationof
business
supportsystem
forwater
supply,
power
supply,gassupply,land
resources
Reflectin
gthesystem
supporta
bility
ofcity
mun
icipal
resource
managem
ent
Constructionandapplicationof
business
supportsystem
forpublic
security,
emergency,
civilairdefense,
dangerou
sgo
odsmanagem
ent
Reflectin
gthesystem
supporta
bility
ofcity
public
safety
managem
ent
Abilityof
collectingcomprehensive
operationmanagem
entdata,analysisand
processing
,supporttheurbanmanagem
entdecision-m
aking
Com
prehensively
reflect
the
system
’sleadingdecision-m
aking
ability
(con
tinued)
174 Appendix
Tab
leA.2
(con
tinued)
Overall
indicators
Firstgrade
indicator
Secondary
indicators
Inspectio
npoints
Descriptio
n
Abilityto
useelectronic
means
intheprogress
ofadministrativelaw
enforcem
ent,administrativeexam
inationandapproval,public
service
provisionforsupervisionandinspectio
n
Reflectin
gtheability
ofelectronic
supervisionin
theprocessof
city
managem
ent
App
licationeffect
ofusingsm
artterm
inal
devicesto
improv
edaily
office
efficiency,andcarryou
tcity
managem
ent
Reflectin
gthemob
ileoffice
ability
intheprocessof
city
operating
managem
entdepartments
Controllin
gof constructio
nprocess
Whether
orno
tto
developdo
cuments,standardsto
guidetheconstructio
nmanagem
entof
intelligent
city
project
Reflectin
gthestandardizationand
norm
alizationof
theprocess
managem
entof
theintelligent
city
projectconstructio
n
City
intelligence
Smart
managem
ent
Process
controlof
constructio
n
Schedule
deviationrate
=(actualtim
eof
completion−plannedtim
eof
completion)/planned
timeof
completion
Reflectin
gtheprogress
deviation
degree
ofmajor
projectsandmajor
prog
rams
Budgetdeviationrate
=(actualinvestment−bu
dget
amou
nt)/bu
dget
amount
Reflectin
gthebu
dget
deviation
degree
ofmajor
projectsandmajor
prog
rams
Operatio
nmanagem
ent
mod
e
Whether
theoperationmanagem
entsubjectisclear
Reflectin
gtheperfectdegree
and
maturity
oftheintelligent
city
operatingmanagem
entmodel
toa
certainextent
Guarantee
oftheop
eratingmanagem
entcapital
Whether
form
ulatingthesystem
’sstandardsrelatedto
theoperating
managem
ent
Smart
services
Smartservice
coverage
Proportio
nof
realizingonlin
ehandlin
gin
real
timein
thecity
administrative
servicematters
Reflectin
gthecoverage
levelof
the
onlin
eadministrativeservice
Proportio
nof
realizingonlin
ereal
timeprovided
inthecity
public
service
matters
Reflectin
gthecoverage
levelof
the
onlin
epu
blic
service
Whether
disclosing
theim
portantinform
ationof
financialcapitalusage,
personnel,statisticsof
fundsto
thepublicin
realtim
ethroughthegovernment
website
Reflectin
gthecoverage
levelof
governmentwebsite’s
important
inform
ation
(con
tinued)
Appendix 175
Tab
leA.2
(con
tinued)
Overall
indicators
Firstgrade
indicator
Second
ary
indicators
Inspectio
npoints
Descriptio
n
Whether
thefields
ofmedical
treatm
ent,social
security,education,
employ
mentandtrafficprovidereal
timeonlin
econsultin
gcomplaintsin
accordance
with
theuser’s
needs
Reflectin
gthecoverage
levelof
major
field’sonlin
econsultin
gcomplaints
Convenience
ofaccessing
The
developm
entstatus
ofthegovernmentwebsite
andrelatedpublic
service
websites
Accessing
convenienceof
thecity
services
Constructionlevelof
thegovernmentmobile
applicationandpublic
service
mob
ileapplication
Whether
cananalyzeuser’s
needs,activ
elypush
therelatedinform
ationand
service
Whether
cansurround
custom
erservicerequirem
ents,associatingtherelated
serviceitemsandinform
ationresources,to
show
totheusers
Treatment
efficiency
Average
handlin
gtim
eof
theapproval
hallservicematter
Com
prehensive
reflectstheworking
efficiency
ofthecity
Average
replytim
eof
business
consultin
g
Average
processing
replytim
eof
complaints
Respo
nsespeedof
onlin
eservicesystem
176 Appendix
Table A.3 The first Guomai smart city developmental level evaluation
First gradeindicator
Secondary indicators Tertiary indicators
Smartinfrastructure
Information network facility Broadband network
Integration of three networks
Information sharing infrastructure Public cloud computing center
Information safety service
Government affairs cloud
Smartinfrastructure
City infrastructure Intelligent transformation in key areas
Smart governance Smart government affairs Decision-making ability
Government services and transparency
Business collaboration level
Smart public management Smart transportation
Smart city inspectors
Smart pipe network
Smart security and protection
Smart food and drug administration
Public and social participation
Smart people’slivehood
Smart social insurance Social security system constructionlevel
Social security information servicelevel
Smart health security Health security information servicelevel
Smart education culture Education culture information servicelevel
Smart community services Community information service level
Smart industry Per-capita output Per-capita output
Input-output ratio Input-output ratio
Resource consumption rate per tenthousand GDP
Resource consumption rate per tenthousand GDP
Integration of the two Environment of the integration of thetwo
Level of the integration of the two
Benefit of the integration of the two
Smart crowd Information utilization capacity Application of the informationproducts
Utilization of the informationresources
Innovation ability Innovation environment
Knowledge innovation ability
Quality of talents Higher education situation(continued)
Appendix 177
Table A.3 (continued)
First gradeindicator
Secondary indicators Tertiary indicators
Smart crowd Quality of talents Senior talent status
Talent introduction status
Smartenvironment
Ecological protection Environmental construction level
Environmental informatization level
Resource utilization Resource saving level
Intelligent resource application
Soft environment construction Organizational system
Planning policies
Regulatory standards
Evaluation and assessment
City brand
Table A.4 2nd smart city development level assessment of Guomai Company
First gradeindicator
Secondaryindicators
Evaluation points Evaluation description
Smartinfrastructure
Coverage ofoptical fiberand broadband
Household rate of opticalfiber
Household ratio of family opticalfiber
Wi-Fi coverage Coverage of all kinds of wirelesstransmission networks in city areas
Popularizingrate ofcomputerterminal
Netizen number Number of Internet users in theproportion of urban population
Cloud platform Construction or utilizationstatus of cloud computingcenter
Wether to plan or have beenestablished (rented) cloud computingcenter
Smartapplication
Typicalapplied project
Citizen card Issuing proportion of citizen card
Filing rate of residents’health records
Filing rate of residents’ healthrecords
Smart electric metermounting yield
Proportion of installing smart electricmeter in households
Other typical application Other typical under construction ordemonstrated application projects(such as achievement, tourism,safety, community and environment)
Smartindustry
Industrialdevelopmentlevel
Per-capita output value Gross national product per capita
Electric powerconsumption per capita
Citizen electric power consumptionper capita
Number of per capitalpatent (million)
Patent authorization quantity ofmillion citizens
Proportion of high and newtechnology industry outputvalue to GDP
Proportion of high and newtechnology industry output value toGNP
(continued)
178 Appendix
Table A.4 (continued)
First gradeindicator
Secondaryindicators
Evaluation points Evaluation description
Smartgovernance
Governmentservice ability
Public service platform Whether there’s a special platformwith public web pages, convenienceservices, service hall or enterpriseoriented
Integrity of governmentinformation disclosure
Timeliness and effectiveness ofgovernment information on theofficial website
Online service ability Universality and convenience ofgovernment online service
Information resourcesutilization
Government portal website dailyvisits per capita
Intelligentsupportability
Planningscheme
Overall plan or actionprogram
Established intelligent city detailedplanning outline or action
Upcoming intelligent city planningor outline that formulated in progress
The formed f overall intelligent citydevelopment of ideas, such aswireless city, city optical network
Organizationsystem
Special leading institutionsor actuators
Mayor/secretary of the leadershippositions
Position above city deputy, and leadas a leader or executive body
Position bellow city deputy, and leadas a leader or executive body andother cases
Investment Special fund budget Issued and clear intelligent cityspecial fund budget
Investment in the construction ofintelligent city special funds byoperators or integrators
Media andpromotion
A variety of promotionalactivities
Held an intelligent city relatedtraining, seminars, conferences orforums, such as the creation oftopics, websites and micro-blog
Appendix 179
Table A.5 4th Guomai intelligent city development level evaluation
First gradeindicator (6)
Weight Secondary indicators (15) Weight
Smartinfrastructure
25 Broadband 10
Basic database completeness 5
Application of city cloud platform 10
Smartmanagement
20 Government collaboration level 5
Implementation of industry’s total solution 10
Public management social participation 5
Smart service 20 Integrated people’s livelihood service capacity 10
Government data open service 10
Smarteconomy
15 Number of patent per capita 5
Energy consumption per ten thousand GDP 5
Proportion of information industry value added to GDP 5
Smart crowd 10 Proportion of 3G to 4G users 5
Consumption of e-commerce per capita 5
Securitysystem
10 Formulation status of development planning 5
Organization and performance evaluation 5
Plus (1) 5 Intelligent city’s pilot construction and application innovation,related honors and major events
5
Total 105 105
Table A.6 Engineering research institute intelligent city (town) development index
First grade indicator Secondary indicators
Happiness index of intelligent city Employment income
Cultural education
Medical services and health
Social insurance
Housing and consumption
City cohesion
Public service
Organization and infrastructure
Social service
Smart city management index Economic base
Science and technology innovation level
Manpower resource
Human settlement
Environmental action
Ecological environment
Intelligent city social responsibility index Level to govern
Region influence
Image transmissibility
Management and decision
Public responsibility
Equity responsibility
Integrity responsibility
180 Appendix
Tab
leA.7
Pudo
ngsm
artcity
indicatorsystem
1.0
Firstgradeindicator
Second
aryindicators
Tertiary
indicators
Reference
value
Infrastructure
Cov
eragelevelof
broadb
and
network
Accessrate
offamily
fiber
�99
%
Cov
eragerate
ofwirelessnetwork
�95
%
Wlancoverage
rate
ofmainpu
blic
�99
%
Cov
eragerate
ofnext
generatio
nbroadcast
�99
%
Broadband
networkaccess
level
Networkaccess
levelperho
usehold
�30
Average
wirelessnetworkaccess
band
width
�5M
Infrastructure
investmentlevel
Prop
ortio
nof
basicnetworkfacilitiesinvestmentinfixedassets
investment
�5%
Con
structionlevelo
fsensor
network(totalinvestmentinfixed
assets)
�1%
Public
managem
entandservice
Smartgo
vernmentservice
Adm
inistrativeexam
inationandapprov
alprojecton
line
managem
entprop
ortio
n�90
%
Electronicmon
itoring
rate
ofgo
vernmentofficial
behavior
100%
Rateof
nettransfer
ofno
n-official
documents
100%
Networkinteractionrate
betweencorporateandgo
vernment
�80
%
Networkinteractionrate
betweencitizensandgo
vernment
�60
%
Public
managem
entandservice
Smarttransportatio
nmanagem
ent
Con
cern
rate
ofcitizen
tothetrafficinform
ation
�50
%
Electronicrate
ofbu
sstop
board
�80
%
Citizentrafficgu
idance
inform
ationcompliancerate
�50
%
Cov
eragerate
ofparkinggu
idance
system
�80
%
City
road
sensingterm
inal
installatio
nrate
100%
Smartmedical
treatm
entsystem
Filin
grate
ofcitizen
electron
ichealth
record
100%
Electricmedical
historyusagerate
100%
Resou
rceandinform
ationsharingrate
betweenho
spitals
100% (con
tinued)
Appendix 181
Tab
leA.7
(con
tinued)
Firstgradeindicator
Second
aryindicators
Tertiary
indicators
Reference
value
Smartenvironm
entalprotectio
nnetwork
Mon
itoring
prop
ortio
nof
environm
entqu
ality
automation
�95
%
Mon
itoring
prop
ortio
nof
keypo
llutio
nsource
100%
Discharge
indexof
carbon
(declin
ingcomparedwith
2005
)�40
%
Smartenergy
managem
ent
Family
smartmeter
installatio
nrates
�50
%
Enterpriseintelligent
energy
managem
entprop
ortio
n�70
%
Intelligent
managem
entprop
ortio
nof
road
lamp
�90
%
New
energy
car’sprop
ortio
n�10
%
Buildingdigitalenergy
saving
ratio
�30
%
Smartcity
security
Food
anddrug
traceabilitysystem
coverage
rate
�90
%
Natural
disaster
earlywarning
releaserate
�90
%
Con
structionrate
ofmajor
emergencyrespon
sesystem
100%
Cov
eragerate
ofcity
grid
managem
ent
�99
%
Hou
seho
ldpo
pulatio
nandperm
anentpo
pulatio
ninform
ation
tracking
�99
%
Smarteducationalsystem
Urban
percapita
expend
iture
oneducation(G
DP)
�4.5%
Inform
ationinteractionrate
offamily
andscho
ol�90
%
Onlineteaching
prop
ortio
n�50
%
Smartcommun
itymanagem
ent
Cov
eragerate
ofcommun
ityinform
ationservicesystem
�99
%
Publishedrate
ofcommun
ityserviceinform
ation
�95
%
Cov
eragerate
ofinform
ationserviceforcommun
ityelderly
�90
%
Residentialarea
safety
mon
itoring
sensor
installatio
nrate
�95
%
Inform
ationserviceecon
omy
developm
ent
Indu
stry
developm
entlevel
Value
addedof
inform
ationservices
accoun
tedforGDP
�10
%
Prop
ortio
nof
e-commerce
transactions
tototalsalesof
commod
ities
�30
%
(con
tinued)
182 Appendix
Tab
leA.7
(con
tinued)
Firstgradeindicator
Second
aryindicators
Tertiary
indicators
Reference
value
Prop
ortio
nof
theinform
ationserviceindu
stry
employ
eesin
totalsocial
employ
ees
�10
%
Enterpriseinform
atization
operationlevel
Fusion
indexof
indu
strializationandinform
atization
�85
Enterprisewebsite
establishm
entrate
�90
%
Enterprisee-commerce
behavior
rate
�95
%
Utilizationrate
ofenterprise
inform
ationsystem
�90
%
Qualityof
humanistic
social
science
Citizenincomelevel
Percapita
disposable
income(RMB)
�50
,000
Yuan
Citizencultu
rescienceliteracy
Prop
ortio
nof
college
orabov
ein
totalpo
pulatio
n�30
%
Standard-reachingrate
ofcity
public
scientificliteracy
�20
%
Public
inform
ationpu
blicity
and
training
level
Prop
ortio
nof
therelevant
publicity
andtraining
ofthetotal
popu
latio
neveryyear
�8%
Citizen’slifenetworking
level
Rateof
thecitizen’s
surftheinternet
�60
%
Usage
prop
ortio
nof
mob
ileinternet
�70
%
Family
onlin
eshop
ping
prop
ortio
n�60
%
Citizen’ssubjectiv
eperceptio
nEasyfeelingof
life
Satisfactionof
networkcharge
�8po
ints
Con
venience
ofaccessingtrafficinform
ation
�8po
ints
Con
venience
ofcity’s
seekingformedical
service
�8po
ints
Con
venience
ofgo
vernmentservice
�8po
ints
Con
venience
degree
ofaccessingeducationresource
�8po
ints
Senseof
safety
forlife
Food
anddrug
safety
satisfaction
�8po
ints
Env
iron
mentsafety
satisfaction
�8po
ints
Trafficsafety
satisfaction
�8po
ints
Preventio
nandcontrolof
crim
esatisfaction
�8po
ints
Appendix 183
Tab
leA.8
Pudo
ngsm
artcity
evaluatio
nindicatorsystem
2.0
Firstgradeindicator
Second
aryindicators
Tertiary
indicators
Infrastructure
Broadband
network’sconstructio
nlevel
Accessrate
offamily
fiber
WLAN
coverage
rate
ofmainpu
blic
areas
Networkaccess
levelperho
usehold
Public
managem
entandservice
Smartgo
vernmentservice
Adm
inistrativeexam
inationandapprov
allevelon
line
Rateof
nettransfer
ofno
n-official
documents
Smarttransportatio
nmanagem
ent
Electronicrate
ofbu
sstop
board
Citizentrafficgu
idance
inform
ationcompliancerate
Smartmedical
treatm
entsystem
Filin
grate
ofcitizen
electron
ichealth
record
Electricmedical
historyusagerate
Smartenvironm
entalprotectio
nnetwork
Mon
itoring
prop
ortio
nof
environm
entqu
ality
automation
Mon
itoring
prop
ortio
nof
keypo
llutio
nsource
Smartenergy
managem
ent
Family
smartmeter
installatio
nrates
Prop
ortio
nof
new
energy
automob
ile
Buildings
digitalenergy
saving
ratio
Smartcity
safety
Con
structionrate
ofmajor
emergencyrespon
sesystem
Hazardo
uschem
icalstransportatio
nmon
itoring
level
Smarteducationsystem
City
educationspending
level
Onlineeducationprop
ortio
n
Smartcommun
itymanagem
ent
Com
mun
ityintegrated
inform
ationserviceability
Inform
ationserviceecon
omy
developm
ent
Indu
stry
developm
entlevel
Value
addedof
inform
ationservices
accoun
tedforGDP
Prop
ortio
nof
theinform
ationserviceindu
stry
employ
eesin
totalsocial
employ
ees
Enterpriseinform
atization
operationlevel
Enterprisewebsite
establishm
entrate
Enterprisee-commerce
behavior
rate
Utilizationrate
ofenterprise
inform
ationsystem
(con
tinued)
184 Appendix
Tab
leA.8
(con
tinued)
Firstgradeindicator
Second
aryindicators
Tertiary
indicators
Qualityof
humanistic
social
science
Citizenincomelevel
Percapita
disposable
income
Citizencultu
rescienceliteracy
Prop
ortio
nof
college
orabov
ein
totalpo
pulatio
n
Qualityof
humanistic
social
science
Citizen’slifenetworking
level
Rateof
thecitizen’s
surftheinternet
Family
onlin
eshop
ping
prop
ortio
n
Citizen’ssubjectiv
eperceptio
nEasyfeelingof
life
Con
venience
ofaccessingtrafficinform
ation
Con
venience
ofcity’s
seekingformedical
service
Con
venience
ofgo
vernmentservice
Senseof
safety
forlife
Food
anddrug
safety
electron
icmon
itoring
satisfaction
Env
iron
mentalsafety
inform
ationmon
itoring
satisfaction
Satisfactionof
trafficsafety
inform
ationsystem
Intelligent
city
softenvironm
ent
constructio
nSm
artcity
plan
anddesign
Intelligent
city
develops
andplan
Intelligent
city
leadership
system
Intelligent
city
atmosph
erebu
ilding
Intelligent
city
forum
meetin
gandtraining
level
Appendix 185
Tab
leA.9
SmartNanjin
gevaluatio
nindicatorsystem
Firstgradeindicator
Second
aryindicators
Fund
amentalareas
Cov
eragerate
ofwirelessnetwork
Fiberaccess
coverage
Average
networkband
width
Num
berof
natio
nalkeylabo
ratories
Smartgrid
techno
logy
andequipm
entapplications
Smartindu
stry
Smartindu
stry
fixedassetsinvestment
Smartindu
stry’s
R&D
approp
riationexpend
iture
Prop
ortio
nof
smartindu
stry
toGDP
Num
berof
smartindu
stry
practitioners
Total
applicationnu
mberof
patent
insm
artindu
stry
E-com
merce
transactions
GDPenergy
consum
ptionof
millionYuan
Smartservice
Gov
ernm
entadministrativeefficiency
index
Collabo
rativ
eapplicationsystem
Smartpu
blic
servicewidespreadapplication
Smartserviceconstructio
nfund
s
Smarthu
manity
City
labo
rprod
uctiv
ity
Prop
ortio
nof
junior
college
degree
orabov
e
Prop
ortio
nof
inform
ationserviceindu
stry
practitioners
tothewho
lesocial
practitioners
Total
inform
ationlevelindexes
City
public
servicesatisfactionsurvey
Prop
ortio
nof
cultu
ralcreativ
eindu
stry
toGDP
Evaluationon
internationalcultu
ralandsportsactiv
ities
186 Appendix
Tab
leA.10
Ningb
ointelligent
city
developm
entevaluatio
nindicatorsystem
Firstgradeindicator
Secondaryindicators
Tertiary
indicators
Smartcrow
dManpo
wer
resource
Num
berof
high
ereducationeverytenthou
sand
people
Num
berof
technicalperson
neleverytenthou
sand
peop
le
Proportio
nof
inform
ationindustry
practitioners
tothewhole
social
practitioners
Lifelon
glearning
Public
library
booksanddo
cumentscheckedou
tpercapita
Inform
ationconsum
ption
Inform
ationconsum
ptioncoefficientpercapita
E-com
merce
transactions
percapita
Smartinfrastructure
Com
municationfacilities
Mobile
phoneholdingnumbereveryonehundredpeople
Cable
TV
two-way
digitaltransformationrate
Com
puterho
ldingqu
antityeveryhu
ndredho
useholds
Cable
broadbandaccess
rate
Inform
ationsharinginfrastructure
Wirelessbroadbandnetworkcoverage
Con
structionstatus
ofgo
vernmentd
atacenter,fou
rbasicdatabases,inform
ationsecurity
disaster
Smartinfrastructure
Inform
ationsharinginfrastructure
Com
municationnetworksharingandco-building
Digitalmanagem
entlevelof
infrastructures
Smartgo
vernance
E-gov
ernm
entaffairs
Gov
ernm
entaffairsweibo
number
Status
ofone-stop
onlin
eadministrativeapproval
serviceandelectronic
monito
ring
system
constructio
n
Hits
numberof
city
governmentpo
rtal
website
Public
participationin
government
decision-m
aking
Num
berof
NPC
billregistered
Num
berof
CPP
CCproposal
registered
Num
berof
public
hearing
Inputof
public
service
General
public
serviceexpend
iture
(local
finance)
Smartpeop
le’s
livehoo
dSo
cial
security
Status
ofsocial
security
andhealth
insuranceon
e-card
constructio
n
Status
ofcitizen
card
projectconstructio
n(con
tinued)
Appendix 187
Tab
leA.10
(con
tinued)
Firstgradeindicator
Secondaryindicators
Tertiary
indicators
Medical
treatm
ent
Onlinebo
okingho
spitalproportio
n
Filin
grate
ofresident’s
electron
ichealth
record
Transportation
Transportationcard
percapita
City
trafficgu
idance
system
Electronicrate
ofbu
sstop
board
Smartecon
omy
Economypo
wer
Regionaltotalou
tput
valuepercapita
Smartindu
stry
Prop
ortio
nof
inform
ationindu
stry
addedvalueto
GDP
Prop
ortio
nof
softwareou
tsourcingservices
toGDP
R&Bability
Weightof
R&B
toGDP
Patent
authorizationquantityof
millionpersons
Outpu
tenergy
consum
ption
Energyconsum
ptionof
GDPpermillionYuan
Industrial
structureandcontributio
nAverage
addedvalueof
theagricultu
re,forestry,anim
alhusbandryandfisherycreated
bytheem
ploy
ee
Proportio
nof
high
technology
addedvalueabovethescaleto
theindustrialaddedvalue
Prop
ortio
nof
theaddedvalueof
thethirdindu
stry
toGDP
Smartenvironm
ent
Dispo
salcapability
Tow
nlifesewagetreatm
entrate
Com
prehensive
utilizatio
nrate
ofindustrial
solid
wastes
Environmentattractio
nCom
prehensive
utilizatio
nof
“three
wastes”
productou
tput
Greeningcoverage
ofbuilt
areas
Percapita
greenarea
Smartplanning
and
constructio
nIntegrationof
urbanandruralov
erall
developm
ent
Residentsincomeratio
betweencity
andcountry
Educatio
nyearsproportio
nof
urbanandruralresidents
Public
financespending
proportio
nof
urbanandrural
Urbanizationrate
Spatialarrangem
ent
Com
mutingtim
e(ortransfer
number)
Smartbuild
ings
Buildingintelligent
level
188 Appendix
Tab
leA.11
TU
Wienindicatorsystem
Dim
ension
Factor
(31items)
Weigh
t(%
)Indicator
Smartecon
omy
Inno
vativ
espirit
17Weigh
tof
R&D
toGDP
Employ
mentrate
ofkn
owledg
eintensiveindu
stry
Patent
applicationpercapita
Entrepreneurspirit
Entrepreneurship
17Weigh
tof
profession
al
New
enterprise
registratio
nnu
mber
Econo
myprospect
Econo
mic
imageandtradem
arks
17Im
portance
asthedecision
center
Prod
uctiv
ity17
City
labo
rprod
uctiv
ityof
employ
edpo
pulatio
n
Flexibility
oflabo
urmarket
17Unemploy
mentrate
Part-tim
eem
ploy
mentrate
Degreeof
internationalization
InternationalEmbedd
edness
17Total
numberof
listedcompanies
Airpassengerflo
wvo
lume
Airfreigh
ttrafficvo
lume
Smartcitizen
Smartpeop
leLevel
ofqu
alificatio
n14
Kno
wledg
ecenter
impo
rtance
(top
research
centersandun
iversities)
Popu
latio
nof
levelISCED5*
6(abo
vecollegesandun
iversities)
Level
offoreignlang
uage
Participationof
lifelong
learning
14Num
berof
borrow
ingbo
okspercapital
Participationrate
oflifelon
glearning
Participationrate
oflang
uage
course
Social
race
diversity
14Fo
reignerweigh
t
14Prop
ortio
nof
citizensbo
rnov
erseas
Flexibility
14Attitude
tojob-ho
oping
Creativity
14Creativecrow
dweigh
t
Openn
ess
14Status
ofparticipatingin
Europ
eanelectio
n
Immigrant
environm
entalfriend
lydegree
Und
erstanding
oftheEurop
e(con
tinued)
Appendix 189
Tab
leA.11
(con
tinued)
Dim
ension
Factor
(31items)
Weigh
t(%
)Indicator
Participationin
public
life
14Status
ofParticipatingin
city
electio
n
Status
ofParticipatingin
volunteerwork
Smartgo
vernance
Participationin
decision
-making
33Num
berof
citizen
representativ
epercapita
Residents’po
litical
activ
ities
Impo
rtance
ofpo
litical
forresidents
Prop
ortio
nof
wom
enrepresentativ
es
Public
andsocial
services
33Pu
blic
expend
iture
percapita
Day
care
child
renprop
ortio
n
Scho
olqu
ality
satisfaction
Transparent
governance
33Satisfactionof
governmenttransparency
Anti-corrup
tionsatisfaction
Smarttransportatio
nLocal
accessibility
25Pu
blic
transportnetworkpercapita
Accessibilitysatisfactionof
public
traffic
Public
transportqu
ality
satisfaction
(Inter-)natio
nalaccessibility
25(Inter-)natio
nalaccessibility
Availabilityof
ICT-infrastructure
25Average
compu
terforeach
household
Average
broadb
andforeach
household
Sustainable,
inno
vativ
eandsafe
transportsystem
s25
Green
trafficweigh
t
Trafficsafety
Econo
mical
caruse
Smartenvironm
ent
Attractiv
elyof
natural
environm
ent
25Su
nlight
duratio
n
Green
spaceweigh
t
Pollu
tion
25Therm
alaerosol(ozone)
PM(particulatematter)
Deadlychroniclower
respiratorydiseases
(con
tinued)
190 Appendix
Tab
leA.11
(con
tinued)
Dim
ension
Factor
(31items)
Weigh
t(%
)Indicator
Env
iron
mentalprotectio
n25
Individu
alenvironm
entalprotectio
nefforts
Env
iron
mentalprotectio
nattitud
e
Sustainableresource
managem
ent
25Water
consum
ptions
perGDP
Energyconsum
ptions
perGDP
Smartliv
ing
Culturalfacilities
14Percapita
numberto
thecinema
Percapita
numberto
visitthemuseum
Num
berto
thetheaterpercapita
Health
cond
ition
s14
Exp
ectedlifetim
e
Hospitalbeds
percapita
Doctornu
mberpercapita
Medical
system
satisfaction
Smartliv
ing
Individu
alsafety
14Crimerate
Mortalityrate
ofviolentcrim
e
Safety
satisfaction
Hou
sing
quality
14Weigh
tof
meetin
gtheloweststandard
dwellin
g
Percapita
livingspace
Person
alho
usingcond
ition
ssatisfaction
Edu
catio
nfacilities
14Percapita
numberof
stud
ents
Edu
catio
nalfacilitiesacqu
isitiveness
satisfaction
Edu
catio
nfacilitiesqu
ality
satisfaction
Tou
ristic
attractiv
ely
14Im
portance
tobe
thesigh
tseeing
Ann
ualpercapita
numberof
overnigh
tvisitors
Social
cohesion
14Po
vertyrisk
perceptio
n
Povertyrate
Appendix 191
Table A.12 IDC Indicator system
Dimension Unit Evaluation criterion
Smart dimension Smart government Open government
Government/E-services
Electronic service supply
Sustainable behaviors
Environmental protectionpolicy
Smart buildings Buildings operating efficiency
Construction quality
Smart transportation Power-driven transportation
Traffic information andmanagement
City public transportation
Smart dimension Smart energy and environment Smart power grid
Renewable energy
Environment management
Smart service Public service/emergencyservices
Tourisms/building/modernservices
Supportingcapacity
Information and communicationtechnologies
Transmissibility
Mobility
Citizen Age
Education
Population development
Economy Economic wealth
Economic development
Table A.13 IBM indicator system
System Element Internet ofThings
Interconnection Intelligent
City service Public servicemanagement/localgovernmentmanagement
Creation oflocalauthoritymanagementinformationsystem
Interconnectedservicedelivery
Immediateand jointserviceprovision
Citizen Health andeducation publicsafety governmentservices
Patientdiagnosisandscreeningequipment
Connectdoctors,hospitals andother healthserviceproviders’records
Patient drivenearlytreatment
(continued)
192 Appendix
Table A.13 (continued)
System Element Internet ofThings
Interconnection Intelligent
Commerce Businessenvironmentmanagementburden
Datacollectionabout theonlinebusinessservices
Variousstakeholdersconnecting citycommercialsystem
Providecustomizedservice forbusiness
Traffic Cars and roadpublic transportairports andseaports
Use ofmeasuringtraffic flowand tolls
Integratedtraffic, weatherand travelinginformationservices
Highwaycharges
Communication Broadband,wireless telephone,computer
Collectingdata byphone
Connectmobile phones,fixed telephoneand broadband
Provideconsumerswithpersonalizedcity serviceinformation
Water supply Health clean watersupply salt water
Collectingwater qualitymonitoringdata
Connect thewater supplyenterprise,port, energyusers
Quality, flooddroughtresponse
Energy Oil and gasrenewable energynuclear energy
Usingsensors tocollect usagedata in anenergysystem
Device andequipmentconnecting theenergyconsumer andsupplier
Optimize theuse of thesystem, andbalance theusage ofdifferent time
Appendix 193
Tab
leA.14
Ericssonindicatorsystem
Category
Field
Firstgradeindicator
Secondaryindicators
ICTdevelopm
entmaturity
Infrastructure
Broadband
quality
Average
downloadspeed
Cell-edge
networkqu
ality
Networkband
Accessibility
Family
internet
penetration
Accessrate
offiber
Highspeedwirelessnetwork
Num
berof
Wi-Fi
hotspots
Acceptability
Chargerate
Prop
ortio
nof
broadbandtariffto
city
laborprod
uctiv
ity
Prop
ortio
nof
mob
iletariffto
city
laborprod
uctiv
ity
IPsw
itching
charge
IPsw
itching
charge
permegabytedata
Application
Scienceandtechnology
application
Num
berof
mobile
phone
Num
berof
smartph
ones
percapita
Family
computerpenetrationrate
Num
berof
tablet
percapita
Personal
application
Percapita
internet
penetration
Social
networkpenetration
Public
andmarketapplication
Opendata
Electronics
andmobile
paym
ent
Three
botto
mlin
eeffect
Society
Health
Childrendead
under1year
old
Average
life
Edu
catio
nHighscho
olor
college
educationdegree
Rateof
education
Inclusive
Murderin
every100thousand
residents
Unemploymentrate
Genderequalityof
education
(con
tinued)
194 Appendix
Tab
leA.14
(con
tinued)
Category
Field
Firstgradeindicator
Second
aryindicators
Genderequalityin
city
coun
cil
Economy
Efficiency
City
labo
urproductiv
ity
Com
petitiveness
Highereducationpopularity
PCTpatent
ofeverymillionresidents
Knowledge-intensiveem
ploymentrate
New
enterprisesof
every100,000residents
Env
ironment
Resou
rce
Percapita
garbage
Recyclin
ggarbagepercapita
Percapita
fossilfuel
consum
ption
Percapita
nonfossilfuel
consum
ption
Pollu
tion
PM10
concentration
PM2.5concentration
Nitrog
endiox
idesolubility
Sulfur
diox
idesolubility
Sewagetreatin
grate
Clim
atechange
Carbonem
ission
spercapita
Appendix 195
A.2 Fuzzy Delphi Expert Consultation Questionnairefor Intelligent City Evaluation Indicator
During March 2013 to August 2013, the research group issued 56 questionnaires tothe academicians and experts within the research group about the project “StrategicResearch on Construction and Promotion of China’s Intelligent Cities” of ChinaAcademy of Engineering, to revise the indicator and determine the indicatorselected by expert scoring. Contents of the specific expert consultation question-naire are as follows.
To ________________:It is a great honor to invite you to grant instruction on this questionnaire.“Intelligent City Evaluation Indicator System Research” is a research topic that
attaches to Chinese Academy of Engineering’s key consulting project “StrategicResearch on Construction and Promotion of China’s Intelligent Cities”, the eval-uation object of this research is the city’s intelligent construction and sustainabledevelopment, starting from five dimensions: smart environment and construction,smart management and service, smart economy and industry, smart hardwarefacilities, residents’ intelligent literacy, and reflecting them by setting the corre-sponding secondary indicators and tertiary indicators according to a certain prin-ciple, respectively. Wherein, the set of the secondary indicators is mainly for thegovernment agencies’ working field, to reflect the cohesion of management ser-vices; the set of the tertiary indicators takes into account the data that can beobtained, and the development status and trend of development, to reflect the focus.
This questionnaire is an expert consultation questionnaire, which applied thefuzzy Delphi method, focusing on the importance of the secondary indicators andthe tertiary indicators under the five dimensions of the Intelligent City EvaluationIndicator System.
You can choose the familiar parts of the questionnaire to fill, after you finish thechosen parts 1–5 in this questionnaire, please send the results back to us before July25, 2013. Thank you again for your advice! If you have any further questions orsuggestions, please contact us at any time.
“Intelligent City Evaluation Indicator System Research” Research Group
• Basic information
Your major:_________________Your title: □Academician □Professor □Associate professor □Other____Your age: □<30 years old □30–39 years old □40–49 years old □50–59 years
old □� 60 years oldThis questionnaire is an open questionnaire. Its purpose is to consult on the
concern about the evaluation of intelligent city, thus to further evaluate the sec-ondary and tertiary indicators in all dimensions, and to form the evaluation indicatorcan be evaluated. The evaluation of each concern contains the following two parts.
196 Appendix
(1) Indicator concern points to fill: in addition to the secondary and tertiaryindicators that have been filled out, you have to write down the indicators thatshould be concerned in the intelligent city evaluation in the two columns foreach dimension, respectively.
(2) Importance assessment: for the existing or new indicators that you feel neededto be add, please evaluate the importance of the Indicators in the rear column,and tick the box in the degree of importance (√ ).
The above degree of importance has five grades: 1–5 points (the higher the scoreis, the more important it is), please evaluate the importance of each focus, and fill inthe important level of the indicator.
Scores 1 2 3 4 5Importance degree A lot less important Less important General Important Very important
Example: Evaluation of ecological environment quality secondary indicators andtertiary indicators.
Secondary indicators Tertiary indicators Indicator increase or decrease/amending opinionsImportance Assessment
1 2 3 4 5
Ecological environment quality
Energy efficiency air pollutant concentration environmental pollution
indicator
Per capita green area (added, importance 4) Water pollution index (added, importance 4)
√
√
√
√
• Questionnaire filling and explanation of the indicators
Consultation and evaluation object: intelligent city evaluation indicators.Consultation and evaluation purpose: From the points of five first grade indi-
cators (dimensions): smart environment and construction, smart management andservice, smart economy and industry, smart hardware facilities, residents’ intelli-gent literacy, to select and sort out the evaluation indicators of Intelligent City, andto establish a feasible, concise and sustainable evaluation indicator system.
• Filling the questionnaire
Please tick (√ ) to choose 1–5 familiar field(s) to fill out and evaluate theindicator’s dimension
Appendix 197
1. Indicators of the smart environment and construction dimension and itsimportance assessment
Secondary indicators Tertiary indicators Indicator increase or decrease/amending opinions
Importance Assessment1 2 3 4 5
Resource performanceEnergy consumptions per GDP Energy consumption per capita
Ecological environment quality
City pollutants treatment
Built environment
Per capita water consumptionRenewable energy ratio City labor productivity
Pollution monitoring coverage Air pollutant concentration Industrial pollutants of unit GDP
Reuse rate of sewage treatment Reuse rate of industrial waste treatment Reuse rate of domestic rubbish disposalProportion of green transportation
Per capita public green areas City population density
2. Indicators of smart management and service dimension and its importantassessment
Secondary indicators Tertiary indicators Indicator increase or decrease/amending opinions
Importance Assessment1 2 3 4 5
Residents demand guarantee
Medical and health service
Degree of the security of city
Coverage rate of supplying water Per capita living space
Electric medical history usage rate Expected life
Public participation proportion
Public service satisfaction
Crime rate
Percentage of voter turnout
Public participation proportion
Public satisfaction with the government
198 Appendix
3. Indicators of smart economy and industry dimension and its importantassessment
Secondary indicators Tertiary indicators Indicator increase or decrease/amending opinions
Importance Assessment1 2 3 4 5
Input and output efficiency
Industrial development trend
Ratio of capital investment
Information service industry
Industry contribution per capita
Investment in GDP ratio City output density
Proportion of GDP three industries Urban labor productivity
External investment ratio Proportion of R&D spending to GDP
Proportion of information service industry professionals
Proportion of information service GDP
City labor productivity
4. Indicators of smart hardware facility dimension and its important assessment
Secondary indicators Tertiary indicators Indicator increase or decrease/amending opinions
Importance assessment1 2 3 4 5
Information technology infrastructure
Construction of informatization of human resources
Information technology application
Information technology infrastructure investment proportion Access rate of family high speed network WLAN coverage rate in public space
Proportion of information service industry professionals
Proportion of mobile board band Proportion of Internet Per capita network information searched volume
Appendix 199
5. Indicators of residents’ intelligent literacy dimension and its importantassessment
Secondary indicators Tertiary indicators Addition or deletion of indicators / Amending Opinions
Importance Assessment1 2 3 4 5
Social spending
Residents' education degree
Development of social justice
Society diversity
Proportion of education spending to budget
Education rate of senior high school Proportion of junior college degree or above Lifelong learning engagement
Gini coefficient
City innovation
Proportion of immigration
Proportion of creative industries to GDP Number of universities and research institutes
Other indicators setting suggestions:________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________Thank you for your valuable suggestions and comments!
200 Appendix
A.3 Instruction on Intelligent City EvaluationIndicator System
A.3.1 Intelligent Environment and Construction• Indicator F11: City PM2.5/PM10 monitoring stations density
This indicator refers to the distribution density of PM2.5 and PM10 monitoringstations in the city, reflecting the level of city’s perception to the environmentalquality.
The issue of city’s air quality has appeared in the process of rapid urbanization,such as London, the world’s earliest industrialized country, suffering a serious airpollution in the 1950s, with the annual average of “fog day” (days when thevisibility is not more than 1000 m) up to 50 days or so. During December 5–10,1952, “London Smog Incident” occurred. The opera “La Traviata” was suspendedfor the audience could not see the stage, people in the theater were forced to leave,the dense smoke cut visibility to inches in the day time, and the land and watertraffic almost paralyzed.1 The United States also encountered similar problemsbetween 1940 and 1970, Los Angeles Photochemical Smog Episode caused morethan 400 deaths of people more than 65 years old, and many people developedsymptoms of eye pain, headache, and dyspnea.2
Although there are many developed countries’ warning taken from the over-turned cart in front, the city air quality crisis still broke out at the end of 2012 inChina. “Haze” has become a keyword of the year. In January 2013, 4 large-scalehaze processes shrouded 30 provinces (autonomous regions and municipalities);Beijing only has 5 non-haze days. On January 4, 2014, National disaster reductionoffice and Ministry of Civil Affairs brought the haze harmful to the health into thenatural disaster in 2013 and reported it.3
City air quality is related to people’s daily living environment and physical andmental health, which is an important aspect of city intelligent construction while thedensity of urban PM2.5/PM10 monitoring points reflects the city’s perception ofenvironmental quality. Although at the present stage, there’s no completely cor-relation between PM2.5/PM10 monitoring points density and city air quality, thecity of high PM2.5/PM10 monitoring points density city will be more convenientand accurate to sense the quality of the environment, and take it as a basis forreaction of regulation.
This is conforming to the characteristics that the intelligent cities should beperceived, judged and be reactive.
Air quality query tool “National Air Quality Index” board casts air quality indexof more than 400 major cities throughout the country in real time, with the data
1For details see http://en.wikipedia.org/wiki/Great_Smog.2For details see http://amuseum.cdstm.cn/AMuseum/atmosphere/main/k491.html.3For details see http://www.gov.cn/zhengce/2014-02/13/content_2603649.htm
Appendix 201
coming from Chinese Ministry of Environmental Protection and the U.S.Embassy4; the real time air quality index map provides the worldwide air qualityindexes.5 This book obtained the number of domestic and international city airmonitoring points with the above method, respectively. To eliminate the influenceof the different size of cities and the different definitions of size of cities at homeand abroad, the size of urban built-up area is chosen as the standard of densitymeasurement in the intelligent city evaluation indicator system. The data of theurban built-up area are obtained from the China Urban Statistical Yearbook, whilefor the foreign cities the sizes of urban area indicated on each city’s official websitewere adopted.
City PM2.5/PM10 monitoring point density is obtained by the number ofPM2.5/PM10 monitoring points within the city built-up area, and the unit is /km2.
• Indicator F12: Level of city grid management coverage
The indicator refers to the proportion of management area of the unit griddivided in by the city management area in accordance with a certain standard in thetotal city management area, reflecting the level of city digital management.
In 2004, the pilot of domestic city grid was first created in Beijing, DongchengDistrict, and in 2005, 51 cities promoted the pilot throughout the country. As ofJune 2012, among the 667 prefecture level and above (including prefecture level)cities throughout the country, there were 285 cities in the progress of city gridmanagement. As a digital city management model, the feature of city grid iscomprehensive utilization of mobile communication and network map and otherhigh-tech means, to carry out all-round and efficient city management activities onthe basis of control theory.
The main method of city grid management is to establish the grid electronic mapcorresponding to the city solid space, divide the city area fine grids on it, anddesignate them into several control areas according to a certain management range.Public components and events in the area are in accordance with their geographicallocation coded on the electronic map (Yan 2006).
Smart management of foreign cities usually combines the city grid electronicmap with the city’s open data, to carry out fine, dynamic management to the citiesbased on digital technology.
Since the grid management coverage is difficult to count, this book took thegradient evaluation method in calculation, with 100 (excellent level) indicatinghaving been implemented, with 50 (general level), indicating that there is nospecific implementation but broadcasted, part regions of part fields with imple-mentation, and with 0 indicating having not been implemented. Constructionmanagement level of the intelligent city is evaluated by obtaining the information ofcity grid management platform, city geographic information management platform,city open data platform.
4For details see: http://air.fresh-ideas.cc.5For details see: http://aqicn.org/map.
202 Appendix
• Indicator F13: Residents’ intelligent transportation tools usage level
The indicator refers to the degree of using intelligent traffic system and itsauxiliary system when traveling, such as bus query system, real-time traffic system.
With the increase of urban traffic, the environmental and social problems causedby it are becoming more and more obvious. Intelligent transportation solutions areaimed at the use of a variety of technologies, to guide a reasonable traffic order, toease urban traffic pressure, to reduce environmental pollution caused by motorvehicles. Meanwhile, it’s also a very important part of people’s lives. Good intel-ligent transportation system allows people to travel more fast, thereby improvingthe efficiency of work and life, directly makes people feel the convenience of theintelligent city.
Smart transportation system evaluated in this book shall include all aspects ofbefore travel, traveling and arrival, involving Electronic Traffic Controlling System,Parking Guidance and Information System, Intelligent Transportation CloudInformation Service Platform, Smart Car Share Service System, Smart RoadSurveillance and Maintenance System (SRSMS), Smart Bicycle/Vehicle and etc.
This book uses a gradient evaluation method in calculation, with 100 (excellentlevel) indicating having been implemented, with 50 (general level), indicating thatthere is no specific implementation but broadcasted, part regions of part fields withimplementation, and with 0 indicating having not been implemented.
• Indicator F14: Level of the publicity of the city’s online construction plan
This indicator refers to the publicity degree of intelligent city construction planon government website, reflecting the public degree of intelligent city constructionto the citizens.
With the development and popularization of Internet and mobile communicationtechnology, more and more people have access to news and information throughgovernment public website and official accounts. Government website has becomean important window for the government to promote new policies and measures,which needs to be built, maintained and updated in time.
As of the end of December 2013, the London City Council released about 50pages of “Smart London Plan”, and created “Smart London Vision” volume on thegovernment webpages, fully publicize the concept of smart construction from dataacquisition, display technology, the public impact. Compared to foreign cities’degree of openness for future plan on the Internet, there are few cities in China topublish detailed online intelligent city construction program.
This book uses a gradient evaluation method in the calculation, with 100 (ex-cellent level) indicating having been published in detail, with 50 (general level),indicating that that there is no specific content but published, and with 0 indicatinghaving not been published.
Appendix 203
A3.2 Intelligent Smart Management and Services• Indicator F21: Online publicity level of the government’s non-classified
documents
The indicator refers to the proportion of the number of government non-secretdocuments published on the website in the total documents, reflecting the trans-parency of government information.
As the basis of building an intelligent city, urban information acquisition andsharing is an important support for public decision-making. For governmentmanagement, it should open up the various departments, the enterprise informationaccess and sharing channels. Communications, transportation, health care, educa-tion, real estate and other public information are important resources for the con-struction of intelligent city; the government should provide an open, free,transparent information sharing. The profound changes in information and com-munication technology have changed all the social relations, including the rela-tionship between the public and the government, and reshaped the way of publicgovernance.
In 2013, Tsinghua University released the “2013 Chinese municipal governmentfiscal transparency report”, which comprehensively evaluated the 289 cities (in-cluding 4 municipalities and 285 prefecture level cities), and established a full-sizedindicator system for the evaluation of these cities’ government fiscal transparency.6 Inthis book, the government non-confidential documents’ transparency of the domesticcities will be applied the evaluation content of this report on.
Transparency International published Corruption Perceptions Index every year.7
The degree of transparency of the government is closely related to whether or not itimplements the accountability system, to ensure the integrity of public services(Table A.15).
Continuous monitoring and review of government operations and plans, anddeliberate eliminating the fragmented situation among departments, is the basis ofopenness, transparency and information sharing. This book adopts the data in thestatement to evaluate the foreign cities, and replaces the evaluation of the cities withones of the countries in which the cities are.
• Indicator F22: Online public participation ratio
The indicator refers to the proportion of public participation in thedecision-making of city construction related events, reflecting the public partici-pation in city construction and the openness, fairness and inclusiveness ofdecision-making.
Public participation is a kind of public participation in city constructiondecision-making activities, is a two-way exchange of views, which can widely
6For details see: http://www.sppm.tsinghua.edu.cn/eWebEditor/UploadFile/20130812031437755.pdf.7For details see: http://issuu.com/silch/docs/2013_cpibrochure_en.
204 Appendix
solicit public opinions, enhance public understanding of the operation of govern-ment agencies, and communicate effectively the relations between the public andgovernment agencies.
With the arrival of the information age and the popularity of mobile Internettechnology, more and more city management departments publish related infor-mation through the Internet public account; more and more people express theiropinions and participate in the decision-making through the Internet platform.Online public participating in the questionnaire survey, program design, etc., isbecoming an indispensable part of the intelligent city construction.
This book selects Sina micro-blog and Twitter site as two online platforms fordomestic and foreign intelligent city evaluation. In 2006, Twitter website launchedthe world’s first micro blog service, which quickly became popular after the U.S.presidential campaign. In 2007, the domestic emergence of a large number offollowers of Twitter, but these early local service providers are lack of experience,
Table A.15 Top 30 scores of municipal government in 2013 China municipal government fiscaltransparency report
Ranking City Totalscores
Ranking City Totalscores
1 Shanghai 45 16 Yulin (Guangxi) 35
2 Beijing 43 17 Anqing (Anhui) 34
3 Guangzhou(Guangdong)
43 18 Jincheng (Shanxi) 34
4 Changzhi(Shanxi/0
43 19 Haikou (Hainan) 33
5 Erdos (InnerMongolia)
42 20 Jieyang(Guangdong)
33
6 Zhuhai(Guangdong)
41 21 Yueyang (Hunan) 32
7 Shenzhne(Guangdong)
41 22 Foshan(Guangdong)
32
8 Sichuan (Chengtu) 40 23 Nanning(Guangxi)
32
9 Hangzhou(Zhejiang)
38 24 Huainan (Anhui) 32
10 Wuhu (Anhui) 38 25 Guiyang(Guizhou)
32
11 Yunfo(Guangdong)
37 26 Lu’an (Anhui) 31
12 Heyuan(Guangdong)
37 27 Qingyuan(Guangdong)
31
13 Huaibei (Anhui) 37 28 Tianjin 31
14 Qingdao(Shandong)
36 29 Shantou(Guangdong)
30
15 Zunyi (Guizhou) 35 30 Zhongshan(Guangdong)
30
Appendix 205
simply imitating foreign products, but with less user usage and less attention. InAugust 2009, Sina launched Sina MicroBlog, and invited many celebrities to enter.Sina developed the nickname of “Weibo” into the well-known Internet buzzword injust half years by right of celebrity effect, successfully obtained the leading positionin the domestic MicroBlog market. In 2010, MicroBlog appeared blowout growth,the major portals, government websites, media units and life service websites havebeen launched in succession, and the first year of China MicroBlog opens. In thenext two years in 2011 and in 2012, the domestic MicroBlog user group continuedto grow. Government, schools, merchants and other institutions have launched theofficial MicroBlog, and people have become accustomed to concern, inquiry,register, participate and feedback all kind of activities through MicroBlog.
This book selected the proportion of the number of followers of intelligent cityofficial accountant (for domestic cities the data of Sina MicroBlog were adopted,while for foreign cities the data of Twitter were adopted) to the total city populationas the evaluation of Online public participation ratio.
• Indicator F23: Residents’ health electronic archives usage level
The indicator refers to the proportion of the number of residents having personalhealth electronic records in city’s total number of residents, reflecting the digiti-zation degree of citizen information.
Intelligent health care is an important part of intelligent city. Information tech-nology such as Internet of Things shall be utilized to achieve interaction betweenpatients and medical staffs, medical institutions, medical equipment, and graduallyachieve digitization, informatization through the construction of health recordsmedical information platform. The applications of intelligent health care in theintelligent city are not only for meeting the needs of seeing doctor inside thehospital, but should also include the application and promotion of public healthsystem in the city area, which is the future development direction of intelligenthealth care.
In the intelligent public health system, Electronic Health Records (EHRs) areelectronic records with preservation and reference value which are accumulated inpeople’s related health activities, stored in the computer systems, providing servicesand a life-long personal health records with security. The residents’ personal healthis the core of electronic health records, through the whole life cycle, covering allrelevant factors of health, realizing multi-channel dynamic information collection,and meeting the needs of information resources for residents’ self-health care,health management and health decision-making (Dong 2010).
This book uses a gradient evaluation method in the calculation, with 100 (ex-cellent level) indicating that there’s a detailed electronic health records application(such as related applications of public health guidance, self-searching medicaltreatment guidance, medical insurance, citizen case networking, telemedicine sys-tem on city website), with 50 (average), indicating that that the application iswithout specific content or only used in part of the region, and with 0 indicatingtotally no application.
206 Appendix
• Indicator F24: Level of intelligent coping with emergency
The indicator refers to the level of intelligent emergency system in the face ofmajor urban emergencies (such as disasters, accidents, etc.).
City safety is an typical public safety, the purpose is to protect public health, lifeand property from damage, to control all kinds of threats at a minimum degree inthe control way of socialization and legalization, and to maintain the normal orderof public life as stable as possible (Cai 2012). In the intelligent city construction, theway to use information technology to develop a set of intelligent emergency systemand working mechanism integrating prevention and emergency preparedness,monitoring and early warning, emergency response and rescue, can reflect thereal-time response and learning ability of intelligent city.
This book uses a gradient evaluation method in the calculation, with 100 (ex-cellent level) indicating that there’s a detailed electronic health records application(such as related applications of public health guidance, self-searching medicaltreatment guidance, medical insurance, citizen case networking, telemedicine sys-tem on city website), with 50 (average), indicating that that the application iswithout specific content or only used in part of the region, and with 0 indicatingtotally no application.
A3.3 Intelligent Smart Economy and Industry• Indicator F31: The proportion of R&D expenditure in GDP
This indicator refers to the proportion of city R&D expenditures accounted forGDP, reflecting the city’s scientific and technological strength, innovation and corecompetitiveness.
R&D expenditures refer to expenditures on research and development in thewhole society, including expenditures for basic research, applied research andexperimental development. There is a significant correlation between the input ofcity R&D and the number of scientific research personnel, and the number ofenterprises engaged in scientific research in the city, reflecting the city’s scientificand technological strength, innovation and core competitiveness. In the construc-tion of intelligent city, R&D expenditures have become an important indicator tojudge the ability of city’s independent innovation ability.
This book adopts the data of science and technology expenditures in item 2-24 in“China Urban Statistical Yearbook 2011” in the evaluation of domestic intelligentcity, and adopts the data of R&D expenditures of the World Bank accounted forGDP in the evaluation of international intelligent city.8
8The weight of the Word Bank’s R&D expenditures accounted for GDP is the national data. Thecity’s data can only be replaced by the country’s data in the evaluation of intelligent city’sconstruction.
Appendix 207
• Indicator F32: City labor productivity
This indicator refers to the per capita gross domestic product (GDP), reflectingthe city’s development level of intellectual economic.
• Indicator F33: City product value density
The indicator refers to the average value of GNP created by the cities per squarekilometer of land, which fully reflects the intelligence level efficiency of land use.
The city labor productivity and the density of the city output value are theeffective reflection of the city’s economic development. The urban labor produc-tivity is more objective to measure the living standard of the people of all countries,and the density of city output value more objectively reflects land efficiency.
In the evaluation of the two indicators above, this book selected the data ofGNP/population and GNP/city, respectively.
• Indicator F34: The proportion of city intelligent industry
This indicator refers to the proportion of knowledge and technology intensiveindustries in urban industries.
Intelligent industry is an advanced stage of industrial development, an importantdirection of transformation and upgrading of traditional industries. The constructionof Intelligent City takes the Internet of Things, cloud computing, mobile Internet,big data and other smart industries as the technological basis, promoting industrialdevelopment in the fields of information management services, information tech-nology related manufacturing, maintenance and design of information system,information analysis and consulting firstly, and on this basis, impacting on thewider areas of city public management and innovation service. The construction ofintelligent city will introduce the information digital technology into modernmanufacturing industry and service industry, generating the “Intelligent Industry”different from the traditional.
This book will take the proportion of e-commerce transactions and the city GDPas the judge of the proportion of intelligent industry, and for the one without citydata will alternatively adopt the data of the country or province.
A3.4 Smart Hardware Facility• Indicator F41: Public space free network coverage density
This indicator refers to proportion of the city space offering free wireless net-work in the total area of the city, reflecting the city’s information access level fromthe hardware’s.
The coverage level of city network is one of the important indicators to measurethe city’s intelligence construction. In 2004, the Philadelphia put forward theconcept of “wireless city”, and built a wireless broadband metropolitan area net-work based on WLAN standards. And then a number of cities around the worldhave begun to invest in the construction of wireless city, based on high-speed
208 Appendix
broadband wireless network, to achieve the goal of accessing the wireless networkand information services at anytime and anywhere. In 2013, China issued the“Broadband China” strategy and Implementation Plan. By the end of 2013, theWLAN to achieve the goal of accessing the city’s major public hotspots.9
This book selected China Telecom Wi-Fi Hot Query Platform10 to evaluate theproviding level of domestic intelligent city’s public space free network, andselected Free Wi-Fi Hot Query Platform11 to evaluate the providing level of abroadintelligent city’s public space free network. These two platforms provide Wi-Fihotspots, and the quotient of the number and the area of the city is used as anindicator to evaluate the coverage density of the free network. Wi-Fi free coverageareas in Shanghai and London are shown in Figs. A.1 and A.2, respectively.
Fig. A.1 Shanghai local Wi-Fi free coverage area. Picture source http://wlan.vnet.cn
9For details see http://www.gov.cn/zwgk/2013-08/17/content_2468348.htm.10For details see http://wlan.vnet.cn.11For details see http://www.wificafespots.com/wifi.
Appendix 209
• Indicator F42: Mobile network per capita usage
This indicator refers to the usage rate of per capita mobile network (phone3G/4G), reflecting the construction of city mobile network.
Similar to the free network coverage density of public space, the per capitautilization rate of mobile network is also the evaluation of the construction level ofcity Internet. The former is more from the perspective of the government to provideinfrastructure, while the latter evaluates the city’s mobile Internet’s usage level formthe perspective of popularity rate of mobile network facilities, such as mobilephone.
This book evaluates the per capita utilization of city mobile networks throughthe ratio of the number of people using the city’s mobile network.
• Indicator F43: City broadband speed
This indicator is one of the basic links in the construction of intelligent city. If a cityproposed the construction of intelligent city, while its network speed is very slow, sonaturally, there will be doubts about the construction of intelligent city. NetIndexprovides the real measurement information about the world city broadband speed.12
Fig. A.2 London local Wi-Fi free coverage area. Picture source http://www.wificafespots.com/wifi/city/GB–City_of_London
12Data source: http://www.netindex.com.
210 Appendix
• Indicator F44: intelligent grid level of coverage
The indicator refers to the intelligent power grid coverage in the city, reflectingthe city’s intelligence level of energy.
Intelligent power grid is the intelligence of power grid. Compared with the tradi-tional power grid, the advanced nature of the intelligent power grid is mainly reflectedin the link of matching point. City intelligent power combines an advanced sensortechnology, information communication technology, analysis and decision technol-ogy, automatic control technology and energy power technology, and highly inte-grates with city power grid infrastructure, to form of new modern city power grid.
The book adopts gradient evaluation method in the calculation, with 100 (ex-cellent level) indicating smart power grid application with details, with 50 (aver-age), indicating that that the application is without specific content or only used inpart of the region, and with 0 indicating totally no application.
A3.5 Residents’ Intelligent Potential• Indicator F51: Proportion of city netizens
The indicator refers to the proportion of netizens in city population, reflecting thelevel of accessing information and learning.
With the development and popularization of computer and network, the numberof people in the world is increasing, and the network has become an importantplatform to reflect public opinion and convey the voice of the people. The Internetis gradually shifting and replacing traditional media, playing a more and moreimportant role in people’s production and living.
Intelligent city should have the qualification of accessing to information, sendinginformation, and immediate feeding back information through the network plat-form. The proportion of city netizens can reflect the degree of intelligence of thecity from the perspective of the citizen.
This book adopts the data of number of Internet users in item 2-36 in “ChinaUrban Statistical Yearbook 2011” in the evaluation of domestic intelligent city, andadopts the data of the World Bank Internet usage ratio in the evaluation of intel-ligent city abroad.13
• Indicator F52: Proportion of information practitioners
The indicator refers to the proportion of information practitioners in all the cityemployees.
The proportion of information practitioners can reflect the proportion of thecity’s information services and software industry, the citizen demands for infor-mation technology services, as well as the city’s innovation capacity. This is animportant aspect in evaluating intelligent city.
13The number of Internet users in the World Bank is the national data. The city’s data can only bereplaced by the country’s data in the evaluation of intelligent city’s construction.
Appendix 211
This book adopts the data of information transmission, computer services andsoftware industry practitioners in item 2-7 in “China Urban Statistical Yearbook2011” in the evaluation of domestic intelligent city, the data reported in “TheEuropean CTC lusters” in the evaluation of European intelligent city,14 and thestatistics of the number of employees of US Department of Labor in the evaluationof American intelligent city.15
• Indicator F53: Proportion of college degree or above
The indicator refers to the proportion of the population with college degree orabove accounted for the city’s total population, reflecting city’s intelligence levelthrough educational level.
The education level of the population is an important indicator to measure thecultural quality of the population, and the proportion of city residents with highereducation can reflect the degree of city’s development.
This book adopts the data of number of students in higher education in item 2-29 in“China Urban Statistical Yearbook 2011” in the evaluation of domestic intelligentcity, and adopts education rankings published by Organization for EconomicCo-operation andDevelopment (OECD) in the evaluation of intelligent city abroad.16
• Indicator F54: number of citizens online spending per capita
The indicator refers to the proportion of the amount of per capita net con-sumption in the total consumption amount, indirectly reflecting the popularity of theInternet and the development level of the Internet of Things.
Research from Zhao (2009) shows that turnover generated by Europeane-commerce has accounted for 1/4 of total business, while in the United States it hasbeen up to 1/3 above. Well-known e-commerce companies, such as AmericanOnline, YAHOO, E-bay, began to rise around 1995, and IBM, Amazon, Wal-Martsupermarket and other e-commerce companies have made a huge profit in theirrespective areas. In China, the prosperity and development of the online shoppingmarket has greatly stimulated the city’s economic growth, and online shoppinggrows fastest in the retail sales of social consumer, which has become the newdriving force of economic growth.
This book adopts city online data in “China’s City Online ShoppingDevelopment Environmental Statement” published by Taobao in 2012 (the bookwill use 0, 25, 50, 75 and 100 to evaluate the city, respectively) in the evaluation of
14For details see: http://rucforsk.ruc.dk/site/files/32956338/the_european_ict_clusters_web_0.pdf.15For details see: http://www.bls.gov/oes.16Education rankings published by Organization for Economic Co-operation and Development(OECD) are the national data. The city’s data can only be replaced by the country’s data in theevaluation of intelligent city’s construction.
212 Appendix
domestic intelligent city, and adopts the data in “Global Perspective on Retail:Online Retailing” published by Cushman & Wakefield in 2003 in the evaluation ofinternational intelligent city.17
A4 Data processing of Intelligent City EvaluationIndicator
The dimensions of the original data are different, not only including physicalquantity, value, but also including the per capita value, percentage, so they are notable to be directly incorporated into the evaluation indicator system for comparison.To cope with the disparity of dimensions of each indicator to carry out compre-hensive summary, after the data collection work, it’s also needed to do the stan-dardization processing of the original data, making it into a dimensionless numericalvalue, to eliminate the influence of different computing units, to stabilize the data.
The influence of dimension can be eliminated by selecting simple and practicalmethod. The main principle is to determine a comparison standard for the indicatorto be evaluated firstly, as the compared standard value, and compare the actual valueand relative value of each indicator, and then it can convert a variety of indicators indifferent natures and measurements to the same measurement indicators.
There are many standardization methods for indicators, such as linear, fold lineand curve.
The linear method assumes a linear relationship between the actual value and thenormalized value of the indicators. There are two common ways to deal with:
(1) Centralized method:
A0i ¼ Ai � �A
(2) Standardization method:
A0i ¼ ðAi � �AÞ=ri; r2i ¼
XðAi � �AÞ=n2
or
A0i ¼ ðAi � AminÞ=Amax � Amin
17Data released by the Cushman & Wakefield is the national data. The city’s data can only bereplaced by the country’s data in the evaluation of intelligent city’s construction.
Appendix 213
or
A0i ¼ Ai=Amax
The fold line method is mainly used in the evaluation of the overall level ofthings affected by different interval changes, to use the extreme method to stan-dardize the treatment in segment. However, if the influence of the actual value tothe value of the evaluation is not equal, then curve type’s standardization methodshall be used. Here, we adopt A0
i ¼ Ai=Amax, so the value of each indicator is in therange of 0–100 after conversion, which is in accordance with the centennial gradingsystem.
A5 An Overview on the Basic Data of ConstructionLevel Ranking of Intelligent Cities in Chinaand in the World
See Tables A.16, A.17, A.18, A.19, A.20, A.21, A.22, A.23, A.24, A.25, A.26 andA.27.
214 Appendix
Tab
leA.16
Intelligent
constructio
ncomprehensive
evaluatio
nanddividedevaluatio
nof
33citiesin
China
City
Overall
Intelligent
environm
entand
constructio
n
Intelligent
managem
entand
services
Intelligent
econom
yandindustry
Intelligent
hardware
facilities
Residents’
intelligent
potential
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Jinhua
162.92
386.08
2836.50
356.17
177.91
157.93
Ningbo
257.09
682.65
370.50
2332.29
658.79
841.20
Zhuhai
356.13
1471.31
761.47
2727.70
269.84
450.33
Wenzhou
455.80
881.14
2639.98
2033.60
368.58
255.67
Wuhan
555.44
979.84
469.29
2431.18
954.55
742.33
Nanjin
g6
54.78
1866.35
274.94
1635.16
559.02
938.45
Wuxi
754.67
781.60
1160.22
257.65
1446.50
2227.41
Pudong,Sh
anghai
854.48
1175.45
175.65
1140.45
1350.61
1830.24
Taizhou
953.98
1966.19
1358.66
166.51
1842.83
1135.72
Changzhou
1053.25
1670.37
2146.38
452.27
464.39
1532.84
Weihai
1153.22
287.11
1455.57
943.67
1644.75
1334.99
Zhenjiang
1253.09
584.55
2246.16
551.68
1251.60
1631.46
Dongying
1351.97
187.50
1060.28
748.44
2728.44
1235.19
Langfang
1451.85
484.98
3223.16
1340.11
856.16
354.81
Dezhou
1548.41
1373.02
960.55
844.31
1941.25
2422.90
Xianyang
1647.65
1078.78
1650.41
1834.43
2336.95
1037.66
Ya’an
1745.77
2350.00
2442.49
1535.16
1053.11
648.09
Nanping
1845.47
3325.00
1848.96
651.64
1152.45
549.29
Zhuzhou
1943.61
2163.57
1259.59
2529.91
2237.01
2127.95
Tongling
2042.75
2450.00
2540.34
1437.28
756.22
1929.91
Wuhu
2142.69
2257.49
1946.55
1240.26
2040.73
2028.42
Lasa
2240.82
1767.33
1749.49
337.90
1744.58
1434.78
(con
tinued)
Appendix 215
Tab
leA.16
(con
tinued)
City
Overall
Intelligent
environm
entand
constructio
n
Intelligent
managem
entand
services
Intelligent
econom
yandindustry
Intelligent
hardware
facilities
Residents’
intelligent
potential
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Changzhi
2340.75
2063.78
663.67
2825.13
2630.92
2620.25
Bengbu
2440.43
2550.00
861.23
1734.72
2138.58
2717.63
Huainan
2540.36
1275.00
2344.05
2232.41
2435.65
2914.67
Pingxiang
2638.67
2650.00
2934.62
1043.18
1544.78
2520.76
Hebi
2737.57
2750.00
567.73
2628.72
2827.88
3013.55
Qinhuangdao
2836.60
3049.33
1555.02
3020.53
2927.47
1730.67
Handan
2935.19
1570.97
3320.79
1934.25
3023.88
2326.06
Liupanshui
3033.03
2850.00
2046.48
2922.92
2534.81
3310.92
Luohe
3130.22
2950.00
3131.14
2133.35
3119.83
2816.77
Wuhai
3222.48
3137.50
2738.93
3216.32
336.91
3112.72
Liaoyuan
3321.55
3237.50
3032.50
3117.56
329.23
3210.95
216 Appendix
Tab
leA.17
Intelligent
environm
entandconstructio
noriginal
data
andscoreof
33citiesin
China
Ranking
City
City
PM2.5/PM
10mon
itoring
stations
density
City
grid
managem
ent
levelof
coverage
Residents’intelligent
transportatio
ntools
usagelevel
Onlinepu
blishing
levelof
city
future
constructio
nplan
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
bScore
Original
data
bScore
1Don
gying
0.09
1810
0.00
100.00
100.00
100.00
100.00
50.00
50.00
87.50
2Weihai
0.04
4448
.44
100.00
100.00
100.00
100.00
100.00
100.00
87.11
3Jinh
ua0.04
0744
.34
100.00
100.00
100.00
100.00
100.00
100.00
86.08
4Langfang
0.08
2589
.92
100.00
100.00
100.00
100.00
50.00
50.00
84.98
5Zhenjiang
0.03
5138
.21
100.00
100.00
100.00
100.00
100.00
100.00
84.55
6Ningb
o0.02
8130
.60
100.00
100.00
100.00
100.00
100.00
100.00
82.65
7Wux
i0.02
4226
.39
100.00
100.00
100.00
100.00
100.00
100.00
81.60
8Wenzhou
0.06
8474
.57
50.00
50.00
100.00
100.00
100.00
100.00
81.14
9Wuh
an0.01
7819
.37
100.00
100.00
100.00
100.00
100.00
100.00
79.84
10Xiany
ang
0.05
9765
.11
50.00
50.00
100.00
100.00
100.00
100.00
78.78
11Pu
dong
,Sh
angh
ai0.00
171.80
100.00
100.00
100.00
100.00
100.00
100.00
75.45
12Huainan
0.00
000.00
100.00
100.00
100.00
100.00
100.00
100.00
75.00
13Dezho
u0.08
4592
.10
50.00
50.00
100.00
100.00
50.00
50.00
73.02
14Zhu
hai
0.03
2435
.26
50.00
50.00
100.00
100.00
100.00
100.00
71.31
15Handan
0.07
7083
.88
50.00
50.00
100.00
100.00
50.00
50.00
70.97
16Chang
zhou
0.02
8931
.47
50.00
50.00
100.00
100.00
100.00
100.00
70.37
17Lasa
0.06
3669
.33
100.00
100.00
50.00
50.00
50.00
50.00
67.33
18Nanjin
g0.01
4115
.38
50.00
50.00
100.00
100.00
100.00
100.00
66.35
19Taizhou
0.05
9464
.77
50.00
50.00
50.00
50.00
100.00
100.00
66.19
20Chang
zhi
0.05
0655
.13
100.00
100.00
50.00
50.00
50.00
50.00
63.78 (con
tinued)
Appendix 217
Tab
leA.17
(con
tinued)
Ranking
City
City
PM2.5/PM
10mon
itoring
stations
density
City
grid
managem
ent
levelof
coverage
Residents’intelligent
transportatio
ntools
usagelevel
Onlinepu
blishing
levelof
city
future
constructio
nplan
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
bScore
Original
data
bScore
21Zhu
zhou
0.04
9854
.30
50.00
50.00
100.00
100.00
50.00
50.00
63.57
22Wuh
u0.02
7529
.96
100.00
100.00
50.00
50.00
50.00
50.00
57.49
23Luo
he0.00
000.00
50.00
50.00
100.00
100.00
50.00
50.00
50.00
24Bengb
u0.00
000.00
50.00
50.00
100.00
100.00
50.00
50.00
50.00
25Ton
gling
0.00
000.00
50.00
50.00
50.00
50.00
100.00
100.00
50.00
26Ya’an
0.00
000.00
50.00
50.00
50.00
50.00
100.00
100.00
50.00
27Ping
xiang
0.00
000.00
100.00
100.00
0.00
0.00
100.00
100.00
50.00
28Hebi
0.00
000.00
50.00
50.00
50.00
50.00
100.00
100.00
50.00
29Liupanshu
i0.00
000.00
50.00
50.00
100.00
100.00
50.00
50.00
50.00
30Qinhu
angd
ao0.04
3447
.32
50.00
50.00
50.00
50.00
50.00
50.00
49.33
31Wuh
ai0.00
000.00
50.00
50.00
50.00
50.00
50.00
50.00
37.50
32Liaoy
uan
0.00
000.00
50.00
50.00
0.00
0.00
100.00
100.00
37.50
33Nanping
0.00
000.00
50.00
50.00
0.00
0.00
50.00
50.00
25.00
Unitof
a:pcs/km
2
Unitof
b:no
ne
218 Appendix
Tab
leA.18
Intelligent
managem
entandserviceoriginal
data
andscoreof
33citiesin
China
Ranking
City
Onlinepu
blicity
level
ofthego
vernment’s
non-classified
documents
Onlinepu
blic
participationratio
Residents’health
electron
icarchives
usagelevel
Emergencyintelligent
levelof
emergency
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
aScore
Original
data
aScore
1Pu
dong
,Sh
angh
ai45
100.00
2.84
2.59
100.00
100.00
100.00
100.00
75.65
2Nanjin
g21
46.99
0.57
7952
.78
100.00
100.00
100.00
100.00
74.94
3Ningb
o23
50.35
0.34
6531
.64
100.00
100.00
100.00
100.00
70.50
4Wuh
an23
51.39
0.28
2225
.77
100.00
100.00
100.00
100.00
69.29
5Hebi
1840
.96
0.32
7829
.94
100.00
100.00
100.00
100.00
67.73
6Chang
zhi
4395
.45
0.10
129.24
50.00
50.00
100.00
100.00
63.67
7Zhu
hai
4191
.07
0.05
284.83
50.00
50.00
100.00
100.00
61.47
8Bengb
u19
42.23
0.02
962.70
100.00
100.00
100.00
100.00
61.23
9Dezho
u19
42.20
1.09
4910
0.00
50.00
50.00
50.00
50.00
60.55
10Don
gying
1430
.76
0.11
3310
.35
100.00
100.00
100.00
100.00
60.28
11Wux
i22
48.42
0.46
4842
.45
50.00
50.00
100.00
100.00
60.22
12Zhu
zhou
1329
.34
0.09
889.02
100.00
100.00
100.00
100.00
59.59
13Taizhou
1839
.80
1.03
8394
.83
50.00
50.00
50.00
50.00
58.66
14Weihai
1635
.22
0.40
6037
.08
50.00
50.00
100.00
100.00
55.57
15Qinhu
angd
ao18
40.07
0.32
8530
.00
100.00
100.00
50.00
50.00
55.02
16Xiany
ang
2250
.26
0.01
491.36
100.00
100.00
50.00
50.00
50.41
17Lasa
48.39
0.43
3539
.59
100.00
100.00
50.00
50.00
49.49
18Nanping
1941
.67
0.04
584.18
100.00
100.00
50.00
50.00
48.96
19Wuh
u38
84.62
0.01
721.57
100.00
100.00
0.00
0.00
46.55 (con
tinued)
Appendix 219
Tab
leA.18
(con
tinued)
Ranking
City
Onlinepu
blicity
level
ofthego
vernment’s
non-classified
documents
Onlinepu
blic
participationratio
Residents’health
electron
icarchives
usagelevel
Emergencyintelligent
levelof
emergency
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
aScore
Original
data
aScore
20Liupanshu
i16
35.94
0.00
000.00
100.00
100.00
50.00
50.00
46.48
21Chang
zhou
1635
.40
0.00
140.13
100.00
100.00
50.00
50.00
46.38
22Zhenjiang
2147
.54
0.40
6037
.08
100.00
100.00
0.00
0.00
46.16
23Huainan
3270
.80
0.05
925.41
100.00
100.00
0.00
0.00
44.05
24Ya’an
48.39
0.12
6711
.57
100.00
100.00
50.00
50.00
42.49
25Ton
gling
2248
.46
0.14
1012
.88
50.00
50.00
50.00
50.00
40.34
26Wenzhou
2044
.52
0.16
8815
.41
50.00
50.00
50.00
50.00
39.98
27Wuh
ai3
5.59
0.00
130.12
100.00
100.00
50.00
50.00
38.93
28Jinh
ua18
39.29
0.07
326.69
100.00
100.00
0.00
0.00
36.50
29Ping
xiang
2352
.12
0.39
8036
.35
0.00
0.00
50.00
50.00
34.62
30Liaoy
uan
1022
.37
0.08
357.63
50.00
50.00
50.00
50.00
32.50
31Luo
he10
22.37
0.02
402.19
100.00
100.00
0.00
0.00
31.14
32Langfang
1431
.32
0.12
4111
.33
50.00
50.00
0.00
0.00
23.16
33Handan
1327
.97
0.05
675.18
50.00
50.00
0.00
0.00
20.79
Unitof
a:no
neUnitof
b:%
220 Appendix
Tab
leA.19
Intelligent
econ
omyandindu
stry
original
data
andscoreof
33citiesin
China
Ranking
City
The
prop
ortio
nof
R&D
expend
iture
inGDP
City
labo
rprod
uctiv
ityCity
prod
uctvalue
density
The
prop
ortio
nof
city
intelligent
indu
stry
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
aScore
1Taizhou
0.10
3.35
3239
4871
.79
2974
7410
0.00
3.75
90.89
66.51
2Wux
i0.20
6.86
2973
4165
.89
1991
7066
.95
3.75
90.89
57.65
3Jinh
ua0.07
2.42
4512
4910
0.00
2840
6695
.49
1.11
26.77
56.17
4Chang
zhou
0.16
5.63
2471
7654
.78
1718
7457
.78
3.75
90.89
52.27
5Zhenjiang
0.10
3.29
2478
7754
.93
1714
2957
.63
3.75
90.89
51.68
6Nanping
0.05
1.58
3755
1783
.22
2579
8486
.73
1.45
35.02
51.64
7Don
gying
0.05
1.61
3832
3284
.93
2165
4872
.80
1.42
34.41
48.44
8Dezho
u0.01
0.20
2802
9762
.12
2394
3780
.49
1.42
34.41
44.31
9Weihai
0.10
3.54
3985
0488
.31
1440
5248
.43
1.42
34.41
43.67
10Ping
xiang
0.05
1.70
1382
6130
.64
1200
9240
.37
4.13
100.00
43.18
11Pu
dong
,Sh
angh
ai2.90
100.00
1059
7123
.48
4530
715
.23
0.95
23.10
40.45
12Wuh
u0.64
22.20
9948
422
.05
7422
724
.95
3.79
91.84
40.26
13Langfang
0.05
1.60
2888
8964
.02
2145
2172
.11
0.94
22.72
40.11
14Ton
gling
0.16
5.35
1198
6726
.56
7544
425
.36
3.79
91.84
37.28
15Ya’an
0.02
0.52
1517
3133
.62
1523
8151
.22
2.28
55.28
35.16
16Nanjin
g0.30
10.46
7669
317
.00
6633
122
.30
3.75
90.89
35.16
17Bengb
u0.33
11.42
7691
317
.04
5530
018
.59
3.79
91.84
34.72
18Xiany
ang
0.03
0.91
1330
9329
.49
1641
0555
.17
2.16
52.16
34.43
19Handan
0.03
1.06
1546
7434
.28
1966
9966
.12
1.47
35.53
34.25 (con
tinued)
Appendix 221
Tab
leA.19
(con
tinued)
Ranking
City
The
prop
ortio
nof
R&D
expend
iture
inGDP
City
labo
rprod
uctiv
ityCity
prod
uctvalue
density
The
prop
ortio
nof
city
intelligent
indu
stry
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
aScore
20Wenzhou
0.11
3.74
2353
1852
.15
1539
4751
.75
1.11
26.77
33.60
21Luo
he0.04
1.25
1233
9427
.35
1136
6738
.21
2.75
66.61
33.35
22Huainan
0.12
4.21
5725
912
.69
6216
120
.90
3.79
91.84
32.41
23Ningb
o0.25
8.64
1926
3142
.69
1519
4351
.08
0.01
1126
.77
32.29
24Wuh
an0.17
5.95
9941
822
.03
1089
0236
.61
0.02
4860
.14
31.18
25Zhu
zhou
0.15
5.28
1367
3930
.30
1057
9635
.56
0.02
0048
.48
29.91
26Hebi
0.05
1.68
1012
0522
.43
7185
624
.16
0.02
7566
.61
28.72
27Zhu
hai
0.33
11.42
1607
1735
.62
9721
832
.68
0.01
2831
.09
27.70
28Chang
zhi
0.06
1.97
1375
9430
.49
1551
8252
.17
0.00
6615
.88
25.13
29Liupanshu
i0.04
1.52
1734
7238
.44
1300
3643
.71
0.00
338.01
22.92
30Qinhu
angd
ao0.05
1.82
1066
5123
.63
1009
5533
.94
0.00
9422
.72
20.53
31Liaoy
uan
0.05
1.73
8266
118
.32
8847
629
.74
0.00
8520
.45
17.56
32Wuh
ai0.15
5.26
8840
919
.59
6182
520
.78
0.00
8119
.66
16.32
33Lasa
0.00
0.00
8321
418
.44
2845
39.56
0.00
153.60
7.90
Unitof
a:%
Unitof
b:Yuan/person
Unitof
c:tenthou
sand
Yuan/km
2
222 Appendix
Tab
leA.20
Intelligent
hardwarefacilitiesoriginal
data
andscoreof
33citiesin
China
Ranking
City
Public
spacefree
networkcoverage
density
Mob
ilenetworkper
capita
usage
City
broadb
andspeed
Intelligent
grid
levelo
fcoverage
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
dScore
1Jinh
ua16
.07
100.00
103.40
100.00
29.67
61.66
50.00
50.00
77.91
2Zhu
hai
3.81
23.71
96.27
93.10
30.10
62.55
100.00
100.00
69.84
3Wenzhou
4.38
27.28
77.23
74.69
34.81
72.34
100.00
100.00
68.58
4Chang
zhou
8.42
52.40
39.87
38.55
32.05
66.60
100.00
100.00
64.39
5Nanjin
g3.51
21.84
32.64
31.56
39.78
82.67
100.00
100.00
59.02
6Ningb
o4.32
26.91
37.18
35.96
35.19
73.13
100.00
100.00
58.79
7Ton
gling
6.62
41.19
37.38
36.15
27.83
57.83
100.00
100.00
56.22
8Langfang
3.13
19.50
30.80
29.79
36.38
75.60
100.00
100.00
56.16
9Wuh
an0.76
4.72
53.33
51.58
32.89
68.35
100.00
100.00
54.55
10Ya’an
3.23
20.09
45.43
43.93
26.07
54.18
50.00
50.00
53.11
11Nanping
1.19
7.41
56.90
55.03
48.12
100.00
50.00
50.00
52.45
12Zhenjiang
5.04
31.36
77.48
74.93
25.76
53.53
100.00
100.00
51.60
13Pu
dong
,Sh
angh
ai5.00
31.14
30.41
29.41
22.07
45.86
100.00
100.00
50.61
14Wux
i0.83
5.14
20.87
20.18
37.10
77.10
50.00
50.00
46.50
15Ping
xiang
4.36
27.16
31.91
30.86
34.22
71.11
50.00
50.00
44.78
16Weihai
0.56
3.50
49.18
47.56
37.50
77.93
50.00
50.00
44.75
17Lasa
4.76
29.59
27.91
26.99
10.47
21.76
100.00
100.00
44.58
18Taizhou
6.40
39.85
19.42
18.78
30.16
62.68
50.00
50.00
42.83
19Dezho
u0.24
1.49
19.79
19.13
21.36
44.39
100.00
100.00
41.25 (con
tinued)
Appendix 223
Tab
leA.20
(con
tinued)
Ranking
City
Public
spacefree
networkcoverage
density
Mob
ilenetworkper
capita
usage
City
broadb
andspeed
Intelligent
grid
levelo
fcoverage
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
dScore
20Wuh
u4.32
26.90
33.16
32.07
25.96
53.95
50.00
50.00
40.73
21Bengb
u2.06
12.79
15.38
14.88
36.89
76.66
50.00
50.00
38.58
22Zhu
zhou
1.79
11.16
25.76
24.91
29.82
61.97
50.00
50.00
37.01
23Xiany
ang
2.54
15.80
29.07
28.12
25.92
53.87
50.00
50.00
36.95
24Huainan
7.74
48.18
11.32
10.95
40.16
83.46
0.00
0.00
35.65
25Liupanshu
i0.94
5.82
41.58
40.21
20.80
43.23
50.00
50.00
34.81
26Chang
zhi
0.42
2.62
35.89
34.70
17.49
36.35
50.00
50.00
30.92
27Don
gying
0.08
0.51
19.49
18.85
21.36
44.39
50.00
50.00
28.44
28Hebi
0.26
1.60
2.41
2.33
27.72
57.61
50.00
50.00
27.88
29Qinhu
angd
ao0.60
3.72
13.76
13.31
20.63
42.87
50.00
50.00
27.47
30Handan
0.05
0.32
16.14
15.61
14.24
29.59
50.00
50.00
23.88
31Luo
he0.12
0.73
21.71
21.00
27.72
57.61
0.00
0.00
19.83
32Liaoy
uan
0.22
1.34
2.02
1.95
16.19
33.65
0.00
0.00
9.23
33Wuh
ai0.24
1.48
4.55
4.40
10.47
21.76
0.00
0.00
6.91
Unitof
a:pcs/km
2
Unitof
b:%
Unitof
c:Mbp
sUnitof
d:no
ne
224 Appendix
Tab
leA.21
Residents’intelligent
potentialoriginal
data
andscoreof
33citiesin
China
Ranking
City
The
prop
ortio
nof
Internet
usersin
city
The
prop
ortio
nof
inform
ation
profession
als
The
prop
ortio
nof
junior
college
orabov
eeducationallevel
popu
latio
n
Residents’percapita
onlin
eshop
ping
expend
iture
amou
nt
Synthetical
value
Original
data
aScore
Original
data
aScore
Original
data
aScore
Original
data
bScore
1Jinh
ua16
3.33
46.18
1.27
66.50
16.25
69.04
50.00
50.00
57.93
2Wenzhou
353.66
100.00
0.43
22.31
5.97
25.38
75.00
75.00
55.67
3Langfang
89.09
25.19
0.84
44.18
23.50
99.86
50.00
50.00
54.81
4Zhu
hai
39.84
11.27
1.10
57.37
13.58
57.70
75.00
75.00
50.33
5Nanping
96.52
27.29
1.91
100.00
10.56
44.87
25.00
25.00
49.29
6Ya’an
36.44
10.30
1.09
57.06
23.53
100.00
25.00
25.00
48.09
7Wuh
an29
.92
8.46
0.40
21.03
15.26
64.82
75.00
75.00
42.33
8Ningb
o65
.55
18.53
0.40
20.72
6.01
25.54
100.00
100.00
41.20
9Nanjin
g25
.76
7.28
0.23
11.95
14.02
59.58
75.00
75.00
38.45
10Xiany
ang
26.20
7.41
0.41
21.55
10.99
46.70
75.00
75.00
37.66
11Taizhou
63.30
17.90
0.86
44.87
7.09
30.13
50.00
50.00
35.72
12Don
gying
44.92
12.70
0.81
42.48
8.37
35.58
50.00
50.00
35.19
13Weihai
65.76
18.59
0.35
18.23
12.51
53.14
50.00
50.00
34.99
14Lasa
0.00
00.00
1.72
90.05
5.66
24.07
25.00
25.00
34.78
15Chang
zhou
68.13
19.27
0.34
17.82
10.42
44.28
50.00
50.00
32.84
16Zhenjiang
46.99
13.29
0.30
15.91
10.98
46.65
50.00
50.00
31.46
17Qinhu
angd
ao45
.51
12.87
0.32
16.80
10.12
42.99
50.00
50.00
30.67
18Pu
dong
,Sh
angh
ai78
.25
22.13
0.28
14.53
2.18
9.28
75.00
75.00
30.24
19Ton
gling
24.65
6.97
0.21
10.74
6.33
26.92
75.00
75.00
29.91 (con
tinued)
Appendix 225
Tab
leA.21
(con
tinued)
Ranking
City
The
prop
ortio
nof
Internet
usersin
city
The
prop
ortio
nof
inform
ation
profession
als
The
prop
ortio
nof
junior
college
orabov
eeducationallevel
popu
latio
n
Residents’percapita
onlin
eshop
ping
expend
iture
amou
nt
Synthetical
value
Original
data
aScore
Original
data
aScore
Original
data
aScore
Original
data
bScore
20Wuh
u22
.64
6.40
0.17
8.68
11.44
48.61
50.00
50.00
28.42
21Zhu
zhou
19.88
5.62
0.43
22.46
7.93
33.71
50.00
50.00
27.95
22Wux
i60
.43
17.09
0.34
17.83
5.82
24.73
50.00
50.00
27.41
23Handan
67.19
19.00
0.35
18.30
3.98
16.93
50.00
50.00
26.06
24Dezho
u41
.38
11.70
0.51
26.74
6.63
28.17
25.00
25.00
22.90
25Ping
xiang
39.76
11.24
0.69
36.17
2.50
10.61
25.00
25.00
20.76
26Chang
zhi
35.83
10.13
0.51
26.60
4.54
19.29
25.00
25.00
20.25
27Bengb
u20
.46
5.78
0.22
11.40
6.67
28.35
25.00
25.00
17.63
28Luo
he30
.41
8.60
0.29
15.15
4.32
18.34
25.00
25.00
16.77
29Huainan
11.79
3.33
0.12
6.42
5.63
23.94
25.00
25.00
14.67
30Hebi
31.41
8.88
0.22
11.35
2.11
8.96
25.00
25.00
13.55
31Wuh
ai15
.84
4.48
0.34
17.84
0.84
3.56
25.00
25.00
12.72
32Liaoy
uan
12.79
3.62
0.16
8.44
1.59
6.75
25.00
25.00
10.95
33Liupanshu
i26
.34
7.45
0.49
25.38
2.55
10.85
0.00
0.00
10.92
Unitof
a:%
Unitof
b:no
ne
226 Appendix
Tab
leA.22
Intelligent
constructio
ncomprehensive
evaluatio
nanddividedevaluatio
nof
41citiesin
theworld
City
Overall
Intelligent
environm
entand
constructio
n
Intelligent
managem
entand
services
Intelligent
econ
omyand
indu
stry
Intelligent
hardwarefacilities
Residents’
intelligent
potential
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Lon
don
165
.67
1377
.66
472
.05
653
.33
463
.47
561
.85
Amsterdam
265.51
197.84
372.86
554.14
1056.56
2746.13
Helsink
i3
64.01
1084
.84
174
.98
847
.55
2347
.53
365
.15
Boston
463
.87
688
.42
274
.36
359
.63
3141
.29
1455
.65
Cop
enhagen
562
.92
885
.90
2750
.60
459
.60
562
.72
1355
.78
Vienn
a6
61.22
492
.03
1568
.98
2235
.83
760
.97
2548
.30
WashingtonDC
760
.92
2467
.79
1961
.54
175
.58
2445
.85
2353
.84
Seattle
860
.02
292
.43
3345
.91
947
.07
959
.53
1855
.16
Chicago
959
.04
1875
.70
1370
.09
1742
.38
1751
.82
1755
.19
SanJose
1058
.77
1476
.86
1170
.16
2434
.57
1453
.58
858
.67
Portland
1157
.92
2368
.55
1070
.22
2038
.82
1254
.80
1057
.21
SanDiego
1257
.09
1776
.00
571
.60
2833
.11
2149
.69
1955
.06
Dub
uque
1356
.62
2662
.50
870
.95
3427
.43
1850
.19
172
.04
Manchester
1456
.21
1282
.27
2848
.04
752
.08
3635
.09
463
.59
New
York
1555
.51
2272
.10
3245
.95
1444
.12
860
.83
2254
.56
Barcelona
1655.22
2075.00
2653.71
1046.70
268.73
2831.98
Detroit
1752
.51
3444
.52
1270
.15
1841
.42
1949
.97
1156
.49
MinneapolisandSaoPaulo
1852
.16
2762
.50
2059
.85
1543
.67
3539
.16
1555
.61
Philadelphia
1952.12
1576.21
3146.31
1643.12
3340.34
2154.63
Ningb
o20
51.86
786
.81
671
.52
3722
.54
365
.00
3713
.44
Issy-les-M
oulin
eaux,Paris
2151.39
3825.00
2358.19
3030.95
171.27
271.55
(con
tinued)
Appendix 227
Tab
leA.22
(con
tinued)
City
Overall
Intelligent
environm
entand
constructio
n
Intelligent
managem
entand
services
Intelligent
econ
omyand
indu
stry
Intelligent
hardwarefacilities
Residents’
intelligent
potential
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
Ranking
Score
SanFrancisco
2250.96
2566.71
3047.12
1345.27
3240.89
2054.83
Lisbo
n23
49.51
2862
.50
1667
.05
2931
.90
662
.43
3423
.69
Cleveland
2448
.46
3537
.50
2159
.08
1940
.52
2049
.84
1655
.37
Birmingham
2547.48
3728.14
771.20
1245.73
4032.51
659.79
Aarhu
s26
47.40
2962
.50
3825
.07
1145
.79
2645
.25
958
.40
Liverpo
ol27
46.65
4020
.02
2258
.41
261
.21
3734
.10
759
.53
Wuh
an28
46.23
1182
.48
1469
.19
3527
.06
3041
.86
4110
.58
Wux
i29
45.85
985
.18
1762
.89
2335
.31
3833
.31
3812
.58
Turin
3045
.33
3150
.00
1861
.84
2733
.97
1353
.60
3227
.26
Zhenjiang
3145
.21
589
.75
2947
.34
2534
.51
2942
.51
3911
.95
Pudo
ng,Sh
anghai
3245
.06
1975
.70
970
.56
4019
.45
2545
.34
3514
.26
Jinh
ua33
44.69
392
.11
3533
.47
3626
.45
3439
.74
2931
.67
Taizhou
3443
.26
2175
.00
2457
.82
2137
.18
3932
.72
3613
.61
Kolner
3543
.16
3250
.00
4021
.93
2634
.18
1553
.39
1256
.32
Zhu
hai
3642
.05
1676
.11
2557
.13
3822
.11
2842
.93
4011
.94
Lyo
n37
41.70
3053
.09
3632
.01
3329
.22
2248
.01
2646
.19
Frederikshavn
3836.38
3925.00
3434.04
3229.28
2743.26
2450.30
Malaga
3934
.89
3637
.50
4118
.25
3130
.74
1156
.35
3031
.62
Santander
4032
.41
3350
.00
3728
.87
3921
.71
4131
.02
3130
.47
Veron
a41
25.81
4112
.50
3924
.40
4112
.27
1652
.63
3327
.26
228 Appendix
Tab
leA.23
Intelligent
environm
entandconstructio
noriginal
data
andscoreof
41citiesin
theworld
Ranking
City
City
PM2.5/PM
10mon
itoring
stations
density
City
grid
managem
entlevelof
coverage
Residents’intelligent
transportatio
ntools
usagelevel
Onlinepu
blishing
levelof
city
future
constructio
nplan
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
bScore
Original
data
bScore
1Amsterdam
0.05
4391
.35
100.00
100.00
100.00
100.00
100.00
100.00
97.84
2Seattle
0.04
1469
.72
100.00
100.00
100.00
100.00
100.00
100.00
92.43
3Jinh
ua0.04
0768
.45
100.00
100.00
100.00
100.00
100.00
100.00
92.11
4Vienn
a0.04
0568
.11
100.00
100.00
100.00
100.00
100.00
100.00
92.03
5Zhenjiang
0.03
5158
.98
100.00
100.00
100.00
100.00
100.00
100.00
89.75
6Boston
0.03
1953
.67
100.00
100.00
100.00
100.00
100.00
100.00
88.42
7Ningb
o0.02
8147
.24
100.00
100.00
100.00
100.00
100.00
100.00
86.81
8Cop
enhagen
0.02
5943
.59
100.00
100.00
100.00
100.00
100.00
100.00
85.90
9Wux
i0.02
4240
.74
100.00
100.00
100.00
100.00
100.00
100.00
85.18
10Helsink
i0.02
3439
.36
100.00
100.00
100.00
100.00
100.00
100.00
84.84
11Wuh
an0.01
7829
.90
100.00
100.00
100.00
100.00
100.00
100.00
82.48
12Manchester
0.01
7329
.10
100.00
100.00
100.00
100.00
100.00
100.00
82.27
13Lon
don
0.00
6310
.65
100.00
100.00
100.00
100.00
100.00
100.00
77.66
14SanJose
0.00
447.43
100.00
100.00
100.00
100.00
100.00
100.00
76.86
15Ph
iladelphia
0.00
294.84
100.00
100.00
100.00
100.00
100.00
100.00
76.21
16Zhu
hai
0.03
2454
.43
50.00
50.00
100.00
100.00
100.00
100.00
76.11
17SanDiego
0.00
244.01
100.00
100.00
100.00
100.00
100.00
100.00
76.00
18Chicago
0.00
172.80
100.00
100.00
100.00
100.00
100.00
100.00
75.70
19Pu
dong
,Sh
angh
ai0.00
172.78
100.00
100.00
100.00
100.00
100.00
100.00
75.70
20Barcelona
0.00
000.00
100.00
100.00
100.00
100.00
100.00
100.00
75.00
(con
tinued)
Appendix 229
Tab
leA.23
(con
tinued)
Ranking
City
City
PM2.5/PM
10mon
itoring
stations
density
City
grid
managem
entlevelof
coverage
Residents’intelligent
transportatio
ntools
usagelevel
Onlinepu
blishing
levelof
city
future
constructio
nplan
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
bScore
Original
data
bScore
21Taizhou
0.05
9410
0.00
50.00
50.00
50.00
50.00
100.00
100.00
75.00
22New
York
0.02
2838
.38
100.00
100.00
100.00
100.00
50.00
50.00
72.10
23Po
rtland
0.01
4424
.18
100.00
100.00
100.00
100.00
50.00
50.00
68.55
24Washing
tonDC
0.01
2621
.16
100.00
100.00
100.00
100.00
50.00
50.00
67.79
25SanFrancisco
0.01
0016
.83
100.00
100.00
100.00
100.00
50.00
50.00
66.71
26Lisbo
n0.00
000.00
50.00
50.00
100.00
100.00
100.00
100.00
62.50
27MinneapolisandSao
Paulo
0.00
000.00
100.00
100.00
100.00
100.00
50.00
50.00
62.50
28Dub
uque
0.00
000.00
50.00
50.00
100.00
100.00
100.00
100.00
62.50
29Aarhu
s0.00
000.00
100.00
100.00
100.00
100.00
50.00
50.00
62.50
30Lyo
n0.00
7312
.34
100.00
100.00
0.00
0.00
100.00
100.00
53.09
31Turin
0.00
000.00
0.00
0.00
100.00
100.00
100.00
100.00
50.00
32Kolner
0.00
000.00
0.00
0.00
100.00
100.00
100.00
100.00
50.00
33Santander
0.00
000.00
0.00
0.00
100.00
100.00
100.00
100.00
50.00
34Detroit
0.01
6728
.09
100.00
100.00
0.00
0.00
50.00
50.00
44.52
35Cleveland
0.00
000.00
0.00
0.00
100.00
100.00
50.00
50.00
37.50
36Malaga
0.00
000.00
0.00
0.00
100.00
100.00
50.00
50.00
37.50
37Birmingh
am0.00
7512
.57
0.00
0.00
0.00
0.00
100.00
100.00
28.14
38Issy-les-M
oulin
eaux
,Paris
0.00
000.00
0.00
0.00
0.00
0.00
100.00
100.00
25.00
39Frederikshavn
0.00
000.00
0.00
0.00
0.00
0.00
100.00
100.00
25.00
(con
tinued)
230 Appendix
Tab
leA.23
(con
tinued)
Ranking
City
City
PM2.5/PM
10mon
itoring
stations
density
City
grid
managem
entlevelof
coverage
Residents’intelligent
transportatio
ntools
usagelevel
Onlinepu
blishing
levelof
city
future
constructio
nplan
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
bScore
Original
data
bScore
40Liverpo
ol0.01
7930
.09
0.00
0.00
0.00
0.00
50.00
50.00
20.02
41Veron
a0.00
000.00
0.00
0.00
0.00
0.00
50.00
50.00
12.50
Unitof
a:pcs/km
2
Unitof
b:no
ne
Appendix 231
Tab
leA.24
Intelligent
managem
entandserviceoriginal
data
andscoreof
41citiesin
theworld
Ranking
City
Onlinepu
blicity
levelof
the
government’s
non-classified
documents
Onlinepu
blic
participationratio
Residents’health
electron
icarchives
usagelevel
Emergency
intelligent
levelof
emergency
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
aScore
Original
data
aScore
1Helsink
i89
.00
97.80
1.49
2.13
100.00
100.00
100.00
100.00
74.98
2Boston
73.00
80.22
12.07
17.23
100.00
100.00
100.00
100.00
74.36
3Amsterdam
83.00
91.21
0.17
0.24
100.00
100.00
100.00
100.00
72.86
4Lon
don
76.00
83.52
3.28
4.68
100.00
100.00
100.00
100.00
72.05
5SanDiego
73.00
80.22
4.33
6.18
100.00
100.00
100.00
100.00
71.60
6Ningb
o36
.01
39.57
32.59
46.51
100.00
100.00
100.00
100.00
71.52
7Birmingh
am76
.00
83.52
0.90
1.28
100.00
100.00
100.00
100.00
71.20
8Dub
uque
73.00
80.22
2.52
3.59
100.00
100.00
100.00
100.00
70.95
9Pu
dong
,Sh
angh
ai71
.51
78.58
2.57
3.67
100.00
100.00
100.00
100.00
70.56
10Po
rtland
73.00
80.22
0.47
0.67
100.00
100.00
100.00
100.00
70.22
11SanJose
73.00
80.22
0.30
0.43
100.00
100.00
100.00
100.00
70.16
12Detroit
73.00
80.22
0.26
0.37
100.00
100.00
100.00
100.00
70.15
13Chicago
73.00
80.22
0.11
0.15
100.00
100.00
100.00
100.00
70.09
14Wuh
an36
.75
40.38
25.48
36.36
100.00
100.00
100.00
100.00
69.19
15Vienn
a69
.00
75.82
0.06
0.09
100.00
100.00
100.00
100.00
68.98
16Lisbo
n62
.00
68.13
0.05
0.06
100.00
100.00
100.00
100.00
67.05
17Wux
i34
.62
38.04
44.49
63.50
50.00
50.00
100.00
100.00
62.89
18Turin
43.00
47.25
0.08
0.11
100.00
100.00
100.00
100.00
61.84
19Washing
tonDC
73.00
80.22
11.17
15.95
100.00
100.00
50.00
50.00
61.54
(con
tinued)
232 Appendix
Tab
leA.24
(con
tinued)
Ranking
City
Onlinepu
blicity
levelof
the
government’s
non-classified
documents
Onlinepu
blic
participationratio
Residents’health
electron
icarchives
usagelevel
Emergency
intelligent
levelof
emergency
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
aScore
Original
data
aScore
20MinneapolisandSao
Paulo
73.00
80.22
6.44
9.20
100.00
100.00
50.00
50.00
59.85
21Cleveland
73.00
80.22
4.27
6.09
100.00
100.00
50.00
50.00
59.08
22Liverpo
ol76
.00
83.52
0.09
0.13
50.00
50.00
100.00
100.00
58.41
23Issy-les-M
oulin
eaux
,Paris
71.00
78.02
3.31
4.73
100.00
100.00
50.00
50.00
58.19
24Taizhou
28.46
31.27
70.06
100.00
50.00
50.00
50.00
50.00
57.82
25Zhu
hai
65.13
71.57
4.88
6.97
50.00
50.00
100.00
100.00
57.13
26Barcelona
59.00
64.84
0.01
0.02
100.00
100.00
50.00
50.00
53.71
27Cop
enhagen
91.00
100.00
1.68
2.40
100.00
100.00
0.00
0.00
50.60
28Manchester
76.00
83.52
6.04
8.62
0.00
0.00
100.00
100.00
48.04
29Zhenjiang
34.00
37.36
36.43
52.00
100.00
100.00
0.00
0.00
47.34
30SanFrancisco
73.00
80.22
5.79
8.27
0.00
0.00
100.00
100.00
47.12
31Ph
iladelphia
73.00
80.22
3.53
5.03
100.00
100.00
0.00
0.00
46.31
32New
York
73.00
80.22
2.51
3.59
50.00
50.00
50.00
50.00
45.95
33Seattle
73.00
80.22
2.39
3.41
0.00
0.00
100.00
100.00
45.91
34Frederikshavn
78.00
85.71
0.30
0.43
50.00
50.00
0.00
0.00
34.04
35Jinh
ua28
.10
30.88
2.12
3.02
100.00
100.00
0.00
0.00
33.47
36Lyo
n71
.00
78.02
0.03
0.04
50.00
50.00
0.00
0.00
32.01
(con
tinued)
Appendix 233
Tab
leA.24
(con
tinued)
Ranking
City
Onlinepu
blicity
levelof
the
government’s
non-classified
documents
Onlinepu
blic
participationratio
Residents’health
electron
icarchives
usagelevel
Emergency
intelligent
levelof
emergency
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
aScore
Original
data
aScore
37Santander
59.00
64.84
0.44
0.63
50.00
50.00
0.00
0.00
28.87
38Aarhu
s91
.00
100.00
0.19
0.27
0.00
0.00
0.00
0.00
25.07
39Veron
a43
.00
47.25
0.24
0.34
50.00
50.00
0.00
0.00
24.40
40Kolner
78.00
85.71
1.41
2.01
0.00
0.00
0.00
0.00
21.93
41Malaga
59.00
64.84
5.72
8.16
0.00
0.00
0.00
0.00
18.25
Unitof
a:no
neUnitof
b:%
234 Appendix
Tab
leA.25
Intelligent
econ
omyandindu
stry
original
data
andscoreof
41citiesin
theworld
Ranking
City
The
prop
ortio
nof
R&D
expend
iture
inGDP
City
labo
rprod
uctiv
ityCity
prod
uctvalue
density
The
prop
ortio
nof
city
intelligent
indu
stry
Synthetical
value
Original
data
aScore
Original
data
bScore
cOriginal
data
Score
Original
data
aScore
1Washing
tonDC
2.79
78.59
6422
7810
0.00
2345
7627
1210
0.00
1.39
23.72
75.58
2Liverpo
ol1.72
48.45
2890
5845
.01
1205
4810
4451
.39
5.86
100.00
61.21
3Boston
2.79
78.59
4964
6677
.30
1381
7320
1258
.90
1.39
23.72
59.63
4Cop
enhagen
3.10
87.32
2045
4531
.85
1351
5081
2157
.61
3.61
61.60
59.60
5Amsterdam
2.16
60.85
3961
5961
.68
1469
5422
2162
.65
1.84
31.40
54.14
6Lon
don
1.72
48.45
8687
713
.53
1204
7120
8551
.36
5.86
100.00
53.33
7Manchester
1.72
48.45
1755
8227
.34
7635
1059
232
.55
5.86
100.00
52.08
8Helsink
i3.55
100.00
1229
4919
.14
1055
2209
04.50
3.90
66.55
47.55
9Seattle
2.79
78.59
3805
0859
.24
6273
0227
526
.74
1.39
23.72
47.07
10Barcelona
3.00
84.51
1054
9416
.42
1678
1158
0071
.54
0.84
14.33
46.70
11Aarhu
s3.10
87.32
1234
5519
.22
3523
9560
415
.02
3.61
61.60
45.79
12Birmingh
am1.72
48.45
1046
3916
.29
4268
5887
118
.20
5.86
100.00
45.73
13SanFrancisco
2.79
78.59
3661
1557
.00
5104
8951
021
.76
1.39
23.72
45.27
14New
York
2.79
78.59
1451
4122
.60
1210
0000
0051
.58
1.39
23.72
44.12
15MinneapolisandSao
Paulo
2.79
78.59
2875
7844
.77
6468
7847
427
.58
1.39
23.72
43.67
16Ph
iladelphia
2.79
78.59
2087
3532
.50
8833
7874
737
.66
1.39
23.72
43.12
17Chicago
2.79
78.59
1946
1430
.30
8656
7656
836
.90
1.39
23.72
42.38
18Detroit
2.79
78.59
2705
9642
.13
4980
6772
421
.23
1.39
23.72
41.42
19Cleveland
2.79
78.59
2545
2739
.63
4728
4644
220
.16
1.39
23.72
40.52
(con
tinued)
Appendix 235
Tab
leA.25
(con
tinued)
Ranking
City
The
prop
ortio
nof
R&D
expend
iture
inGDP
City
labo
rprod
uctiv
ityCity
prod
uctvalue
density
The
prop
ortio
nof
city
intelligent
indu
stry
Synthetical
value
Original
data
aScore
Original
data
bScore
cOriginal
data
Score
Original
data
aScore
20Po
rtland
2.79
78.59
2386
1937
.15
3706
9562
015
.80
1.39
23.72
38.82
21Taizhou
1.98
55.77
5276
08.21
4844
8533
720
.65
3.75
64.08
37.18
22Vienn
a2.39
67.32
1018
3215
.85
4336
1871
518
.49
2.44
41.64
35.83
23Wux
i1.98
55.77
4842
77.54
3243
8084
313
.83
3.75
64.08
35.31
24SanJose
2.79
78.59
1454
2222
.64
3121
5874
413
.31
1.39
23.72
34.57
25Zhenjiang
1.98
55.77
4037
16.29
2791
9962
811
.90
3.75
64.08
34.51
26Kolner
2.92
82.25
1056
8916
.46
2672
2201
711
.39
1.56
26.62
34.18
27Turin
3.00
84.51
8411
713
.10
5892
2946
925
.12
0.77
13.14
33.97
28SanDiego
2.79
78.59
1399
8121
.79
1953
3234
58.33
1.39
23.72
33.11
29Lisbo
n1.50
42.25
1738
4027
.07
1122
6415
0947
.86
0.61
10.41
31.90
30Issy-les-M
oulin
eaux
,Paris
2.26
63.66
6426
310
.01
2352
3622
010
.03
2.35
40.10
30.95
31Malaga
1.30
36.62
3317
3651
.65
4774
5316
520
.35
0.84
14.33
30.74
32Frederikshavn
2.92
82.25
4297
86.69
3644
6860
1.55
1.56
26.62
29.28
33Lyo
n2.26
63.66
5827
69.07
9474
0041
4.04
2.35
40.10
29.22
34Dub
uque
2.79
78.59
3990
56.21
2844
4225
1.21
1.39
23.72
27.43
35Wuh
an1.98
55.77
1619
22.52
1773
6433
67.56
2.48
42.40
27.06
36Jinh
ua1.98
55.77
7349
311
.44
4626
4761
619
.72
1.11
18.87
26.45
37Ningb
o1.98
55.77
3137
34.88
2474
6371
110
.55
1.11
18.94
22.54
38Zhu
hai
1.98
55.77
2617
54.08
1583
3506
36.75
1.28
21.84
22.11
(con
tinued)
236 Appendix
Tab
leA.25
(con
tinued)
Ranking
City
The
prop
ortio
nof
R&D
expend
iture
inGDP
City
labo
rprod
uctiv
ityCity
prod
uctvalue
density
The
prop
ortio
nof
city
intelligent
indu
stry
Synthetical
value
Original
data
aScore
Original
data
bScore
cOriginal
data
Score
Original
data
aScore
39Santander
1.30
36.62
9620
414
.98
4905
4285
720
.91
0.84
14.33
21.71
40Pu
dong
,Sh
angh
ai1.98
55.77
1725
92.69
7378
9841
3.15
0.95
16.21
19.45
41Veron
a1.27
35.77
754
0.12
9679
140.04
0.77
13.14
12.27
Unitof
a:%
Unitof
b:do
llars/person
Unitof
c:do
llars/km
2
Appendix 237
Tab
leA.26
Intelligent
hardwarefacilitiesoriginal
data
andscoreof
41citiesin
theworld
Ranking
City
Public
spacefree
networkcoverage
density
Mob
ilenetworkper
capita
usage
City
broadb
and
speed
Intelligent
grid
level
ofcoverage
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
dScore
1Issy-les-M
oulin
eaux
,Paris
1.17
6517
.78
82.77
67.31
104.81
100.00
100.00
100.00
71.27
2Barcelona
2.61
0439
.45
113.98
92.69
44.83
42.77
100.00
100.00
68.73
3Ningb
o6.61
7510
0.00
41.15
33.46
27.83
26.55
100.00
100.00
65.00
4Lon
don
2.22
0933
.56
114.3
92.95
28.70
27.38
100.00
100.00
63.47
5Cop
enhagen
1.13
6917
.18
106.5
86.61
49.37
47.10
100.00
100.00
62.72
6Lisbo
n1.14
3917
.29
114.51
93.12
41.20
39.31
100.00
100.00
62.43
7Vienn
a0.67
5310
.20
112.97
91.87
43.82
41.81
100.00
100.00
60.97
8New
York
1.45
6022
.00
83.93
68.25
55.61
53.06
100.00
100.00
60.83
9Seattle
0.14
262.15
108.11
87.92
52.44
50.03
100.00
100.00
60.03
10Amsterdam
1.44
1021
.77
83.93
68.25
50.40
48.09
100.00
100.00
59.53
11Malaga
0.40
586.13
95.13
77.36
44.80
42.74
100.00
100.00
56.56
12Po
rtland
0.01
270.19
113.98
92.69
34.09
32.53
100.00
100.00
56.35
13Turin
1.06
7116
.13
83.93
68.25
36.48
34.81
100.00
100.00
54.80
14SanJose
0.14
602.21
122.97
100.00
12.78
12.19
100.00
100.00
53.60
15Kolner
0.45
276.84
83.93
68.25
41.10
39.21
100.00
100.00
53.58
16Veron
a0.15
062.28
102.34
83.22
29.40
28.05
100.00
100.00
53.39
17Chicago
0.01
940.29
122.97
100.00
10.70
10.21
100.00
100.00
52.63
18Dub
uque
0.67
6610
.22
83.93
68.25
30.20
28.81
100.00
100.00
51.82
19Detroit
0.08
661.31
83.93
68.25
32.70
31.20
100.00
100.00
50.19
(con
tinued)
238 Appendix
Tab
leA.26
(con
tinued)
Ranking
City
Public
spacefree
networkcoverage
density
Mob
ilenetworkper
capita
usage
City
broadb
and
speed
Intelligent
grid
level
ofcoverage
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
dScore
20Cleveland
0.45
676.90
83.93
68.25
25.90
24.71
100.00
100.00
49.97
21SanDiego
0.63
679.62
83.93
68.25
22.50
21.47
100.00
100.00
49.84
22Lyo
n0.22
603.42
83.93
68.25
28.40
27.10
100.00
100.00
49.69
23Helsink
i0.11
001.66
82.77
67.31
76.57
73.06
50.00
50.00
48.01
24Washing
tonDC
2.00
0030
.22
83.93
68.25
36.60
34.92
50.00
50.00
45.85
25Pu
dong
,Sh
angh
ai1.07
3316
.22
41.15
33.46
35.19
33.58
100.00
100.00
45.81
26Aarhu
s0.82
6412
.49
41.15
33.46
37.10
35.40
100.00
100.00
45.34
27Frederikshavn
0.16
482.49
106.5
86.61
43.93
41.91
50.00
50.00
45.25
28Zhu
hai
0.21
463.24
102.34
83.22
38.35
36.59
50.00
50.00
43.26
29Zhenjiang
0.63
199.55
41.15
33.46
30.10
28.72
100.00
100.00
42.93
30Wuh
an1.02
8015
.53
41.15
33.46
22.07
21.06
100.00
100.00
42.51
31Boston
0.60
159.09
41.15
33.46
26.07
24.87
100.00
100.00
41.86
32SanFrancisco
0.91
3413
.80
83.93
68.25
34.70
33.11
50.00
50.00
41.29
33Ph
iladelphia
0.61
279.26
83.93
68.25
37.80
36.07
50.00
50.00
40.89
34Jinh
ua0.48
507.33
83.93
68.25
37.50
35.78
50.00
50.00
40.34
35MinneapolisandSao
Paulo
3.12
1447
.17
41.15
33.46
29.67
28.31
50.00
50.00
39.74
36Manchester
0.98
7214
.92
83.93
68.25
24.60
23.47
50.00
50.00
39.16
37Liverpo
ol1.40
0821
.17
114.3
92.95
27.50
26.24
0.00
0.00
35.09
38Wux
i0.88
5213
.38
114.3
92.95
31.50
30.05
0.00
0.00
34.10
(con
tinued)
Appendix 239
Tab
leA.26
(con
tinued)
Ranking
City
Public
spacefree
networkcoverage
density
Mob
ilenetworkper
capita
usage
City
broadb
and
speed
Intelligent
grid
level
ofcoverage
Synthetical
value
Original
data
aScore
Original
data
bScore
Original
data
cScore
Original
data
dScore
39Taizhou
1.23
2318
.62
41.15
33.46
30.16
28.78
50.00
50.00
32.72
40Birmingh
am0.36
975.59
114.3
92.95
33.00
31.49
0.00
0.00
32.51
41Santander
0.42
866.48
113.98
92.69
26.13
24.93
0.00
0.00
31.02
Unitof
a:pcs/km
2
Unitof
b:%
Unitof
c:Mbp
sUnitof
d:no
ne
240 Appendix
Tab
leA.27
Residents’intelligent
potentialoriginal
data
andscoreof
41citiesin
theworld
Ranking
City
The
prop
ortio
nof
Internet
usersin
city
The
prop
ortio
nof
inform
ation
profession
als
The
prop
ortio
nof
junior
college
orabov
eeducational
levelpo
pulatio
n
Residents’percapita
onlin
eshop
ping
expend
iture
amou
nt
Synthetical
value
Original
data
aScore
Original
data
aScore
Original
data
aScore
Original
data
bScore
1Dub
uque
77.50
47.45
41.60
75.23
89.30
100.00
586.12
65.47
72.04
2Issy-les-M
oulin
eaux
,Paris
90.00
55.10
55.29
100.00
71.60
80.18
455.91
50.92
71.55
3Helsink
i91
.50
56.02
6.00
10.85
83.70
93.73
895.29
100.00
65.15
4Manchester
89.80
54.98
9.94
17.98
76.80
86.00
853.93
95.38
63.59
5Lon
don
89.80
54.98
6.10
11.03
76.80
86.00
853.93
95.38
61.85
6Birmingh
am89
.80
54.98
1.56
2.81
76.80
86.00
853.93
95.38
59.79
7Liverpo
ol89
.80
54.98
0.96
1.74
76.80
86.00
853.93
95.38
59.53
8SanJose
79.70
48.80
11.30
20.44
89.30
100.00
586.12
65.47
58.67
9Aarhu
s94
.60
57.92
7.70
13.92
76.90
86.11
677.33
75.65
58.40
10Po
rtland
86.10
52.72
5.90
10.67
89.30
100.00
586.12
65.47
57.21
11Detroit
78.40
48.00
6.90
12.48
89.30
100.00
586.12
65.47
56.49
12Kolner
84.00
51.43
18.20
32.91
86.30
96.64
396.71
44.31
56.32
13Cop
enhagen
95.00
58.16
1.76
3.18
76.90
86.11
677.33
75.65
55.78
14Boston
86.20
52.78
2.40
4.34
89.30
100.00
586.12
65.47
55.65
15MinneapolisandSao
Paulo
82.10
50.27
3.70
6.69
89.30
100.00
586.12
65.47
55.61
16Cleveland
76.70
46.96
5.00
9.04
89.30
100.00
586.12
65.47
55.37
17Chicago
78.50
48.06
4.00
7.23
89.30
100.00
586.12
65.47
55.19
18Seattle
85.70
52.47
1.50
2.71
89.30
100.00
586.12
65.47
55.16
(con
tinued)
Appendix 241
Tab
leA.27
(con
tinued)
Ranking
City
The
prop
ortio
nof
Internet
usersin
city
The
prop
ortio
nof
inform
ation
profession
als
The
prop
ortio
nof
junior
college
orabov
eeducational
levelpo
pulatio
n
Residents’percapita
onlin
eshop
ping
expend
iture
amou
nt
Synthetical
value
Original
data
aScore
Original
data
aScore
Original
data
aScore
Original
data
bScore
19SanDiego
79.70
48.80
3.30
5.97
89.30
100.00
586.12
65.47
55.06
20SanFrancisco
79.70
48.80
2.80
5.06
89.30
100.00
586.12
65.47
54.83
21Ph
iladelphia
77.80
47.63
3.00
5.43
89.30
100.00
586.12
65.47
54.63
22New
York
81.50
49.90
1.60
2.89
89.30
100.00
586.12
65.47
54.56
23Washing
tonDC
76.50
46.84
170
3.07
89.30
100.00
586.12
65.47
53.84
24Frederikshavn
98.40
60.25
0.00
0.00
86.30
96.64
396.71
44.31
50.30
25Vienn
a80
.60
49.35
3.96
7.17
82.50
92.39
396.71
44.31
48.30
26Lyo
n81
.90
50.14
1.93
3.50
71.60
80.18
455.91
50.92
46.19
27Amsterdam
94.00
57.55
4.36
7.89
72.30
80.96
341.23
38.11
46.13
28Barcelona
75.00
45.92
2.19
3.96
54.00
60.47
157.25
17.56
31.98
29Jinh
ua16
3.33
100.00
1.27
2.30
16.25
18.20
55.35
6.18
31.67
30Malaga
71.60
43.84
2.55
4.61
54.00
60.47
157.25
17.56
31.62
31Santander
71.60
43.84
0.00
0.00
54.00
60.47
157.25
17.56
30.47
32Turin
58.50
35.82
0.00
0.00
56.00
62.71
94.19
10.52
27.26
33Veron
a58
.50
35.82
0.00
0.00
56.00
62.71
94.19
10.52
27.26
34Lisbo
n62
.10
38.02
0.00
0.00
35.00
39.19
157.25
17.56
23.69
35Pu
dong
,Sh
angh
ai78
.25
47.91
0.28
0.51
2.18
2.44
55.35
6.18
14.26
36Taizhou
63.30
38.76
0.86
1.56
7.09
7.94
55.35
6.18
13.61
37Ningb
o65
.55
40.13
0.40
0.72
6.01
6.73
55.35
6.18
13.44
(con
tinued)
242 Appendix
Tab
leA.27
(con
tinued)
Ranking
City
The
prop
ortio
nof
Internet
usersin
city
The
prop
ortio
nof
inform
ation
profession
als
The
prop
ortio
nof
junior
college
orabov
eeducational
levelpo
pulatio
n
Residents’percapita
onlin
eshop
ping
expend
iture
amou
nt
Synthetical
value
Original
data
aScore
Original
data
aScore
Original
data
aScore
Original
data
bScore
38Wux
i60
.43
37.00
0.34
0.61
5.82
6.52
55.35
6.18
12.58
39Zhenjiang
46.99
28.77
0.30
0.54
10.98
12.30
55.35
6.18
11.95
40Zhu
hai
39.84
24.39
1.10
1.99
13.58
15.21
55.35
6.18
11.94
41Wuh
an29
.92
18.32
0.40
0.72
15.26
17.09
55.35
6.18
10.58
Unitof
a:%
Unitof
b:do
llars/person
Appendix 243
A6 An Overview and Ranking of Intelligent CityConstruction in China and in the World
Please visit http://www.Intelligent City Evaluation.org to see the details of a reviewand evaluation score of intelligent construction in this book (see Fig. A.3 for QRcode). The website will annually release world’s intelligent city ranking list.
Fig. A.3 QR code of intelligent city website
244 Appendix
A7 R&D Case of Intelligent City Evaluation IndicatorSystem—Pudong, Shanghai18
As a new mode and a new path of city development, intelligent city constructionhas been attracting the attention of domestic cities and being sought after in recentyears. More and more cities take intelligent city construction as a strategic choice oflocal development of social economic transition. With the rapid development andapplication of information technology and under the trend of national policy,Pudong New Area has put forward a preliminary conception of constructing“Intelligent City” in 2009. In 2011, Pudong New Area took the lead putting forwardIntelligent Pudong Construction Outline (iPudong2015), Carry Forward IntelligentPudong Construction 2011–2013 Action Plan, which is focusing on the top-leveldesign of appropriately advanced intelligent city construction.
To organize the contents of intelligent city construction better and measure thedevelopment level of intelligent city, China has released some indicator systems forintelligent city successively since 2011. The setting of standard is just one of thepractices and results of putting emphasis on intelligent government affairs. Thebasic and final purpose of exploring a more scientific intelligent government affairsdevelopment pattern, which is more suitable for national conditions, is promotingthe scientific development of intelligent city. This built the basis for setting up ofthe standards and paved the way for standardization during the practices of pro-moting intelligent city construction.
In 2011, Shanghai Pudong Intelligent City Development Research Institute tookthe lead to release Intelligent City Evaluation Indicator System, which wasimproved in 2012. Dozens of indicator data from Intelligent City EvaluationIndicator System 1.0 released in 2011 and Intelligent City Evaluation IndicatorSystem 2.0 released in 2012 provided references for intelligent city construction.
From Intelligent City Evaluation Indicator System 1.0 to Intelligent CityEvaluation Indicator System 2.0, the research continued for about one year. Version2.0 added further improvements and testing evaluations on the basis of version 1.0,and put forward six dimensions for intelligent city evaluation: intelligent cityinfrastructures, intelligent city public administration and services, intelligent cityinformation service economy development, intelligent city humane studiesaccomplishment, intelligent city residents’ subjective perception, intelligent citysoft environment construction. The modifications of the six dimensions and relevantsegmented indicators helped version 2.0 “feel the pulse” of intelligent city con-struction process in China deeper and more precisely.
18The materials in this section are based on modification and improvement of Six Dimensionsof Pudong, “Feel the Pulse” of Intelligent City (Authors: Sheng Xuefeng, Yang Xinmin). Theoriginal is available on China Informatization, 2012 No. 14.
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A7.1 Trinity—Government, Society and Residents
Intelligent city evaluation indicator system is the standard to comprehensivelyreflect and measure intelligent city construction development stage and level, whichhas measuring and guiding function for intelligent city construction. Therefore,when designing indicator system frame and selecting specific indicators, not onlytheir guidance for the government promoting intelligent city construction should beconsidered, they should also be fully suitable for various aspects of operation andexperience for intelligent city construction, so the typical representative indicatorsshould be selected form three aspects: government promotion, social participation,public perception, which should not only focusing on collectability and compara-bility of indicators, but also the history and current data should be collected reliably,conveniently and scientifically and be comparable within different cities anddistricts.
Hence, three aspects (government, society and citizens) were centered on duringthe further improvement of intelligent city evaluation indicator system, which putforward a three-level indicator system with six dimensions as the core.
The frame system covers the subjects of each level such as construction, oper-ation, management and perception of intelligent city, and limits the total number ofindicators strictly trying to reflect most current situations with least indicators.When designing indicators, compare quantitative indicators with qualitative indi-cators, and focus on complementation and reflection between specific indicators, tryto reduce systematic errors caused by individual indicators.
A7.2 Cling to Construction Status, Lead the FutureDevelopment
The six dimensions of intelligent city evaluation indicator system has fully con-sidered intelligent city infrastructures, demonstration application, industrial devel-opment and public perception in aspect of coverage, and reflected considering theconstruction status and leading the future development when selecting indicatorsand setting reference values.
1. Intelligent City Infrastructures
In the aspect of broad sense, intelligent city infrastructures refer to relatedinfrastructures that ensure each function of intelligent city working togethersmoothly and safely. So to speak, all the infrastructures playing a role in intelligentcity are included. While looking at the current status of intelligent city constructionin China, the intelligent city infrastructures that we are now focusing on mainlyinclude construction and application level of various wired and wireless broadbandnetwork.
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Optical fiber broadband and wireless broadband are the core and basis ofintelligent city (or digital city, smart city) construction in China. Many cities,including Shanghai, have regarded “optical network city” and “wireless city” as thebasic function and safeguard of intelligent city construction. To scientifically reflectthe city’s basic network construction and application level, it put forward “familyoptical fiber access rate”, “WLAN coverage rate of major public places” and“network access level of per family” from two aspects—the level of broadbandnetwork coverage and access level, and abandoned “average wireless networkaccess broadband”, “the proportion of network infrastructures investment in totalinvestment of social fixed assets” and other indicators that were relatively repetitiveand hard to collected. At same time, it should also refer to the city network con-struction and application situations domestic and overseas to put forward referencevalues for intelligent city construction. For example, both “family optical fiberaccess rate” and “WLAN coverage rate of major public places” should be higherthan 99%, i.e. basically realizing full coverage, “network access level of per family”should be 30 M or above, which are also development goals in several future yearsof many cities in China.
2. Intelligent City Public Administration and Services
Intelligent city public administration and services are the core areas of theintelligent city construction. They involves many aspects, such as intelligent gov-ernment administration, road traffic, health care, education, environmental moni-toring, safety monitoring and controlling, energy management, social insurance andetc., which directly influence city residents’ happiness and city managementoperation efficiency. At present, the mode of intelligent city construction planningin China is segmenting intelligent city public administration and services intoseveral professional fields. For example, “intelligent Pudong” is planning to pro-mote the construction of nine demonstration application engineering such as“Governmental Service Collaboration Engineering”, while Ningbo has put forwardten application systems construction including “build intelligent logistics system” inintelligent city decisions. Under this frame system, we also fully combined with theintelligent city construction mode in China, and considered eight aspects individ-ually—intelligent governmental services, traffic management, medical system,environmental protection, energy management, city safety, education system andcommunity management, according to the basic frame of city intelligent applica-tion, and selected several specific indicators that were representative and that couldfully reflect the construction application situation.
On the one hand, the designing of indicators mainly reflects the combinationwith current intelligent city construction concepts and planning in China, andmanaged to target at construction contents that are being built by intelligent cities inChina or that are considered as important matters would be promoted in the future.For example, for intelligent governmental services, “online transaction proportionof administrative examination and approval matters” and “online flow rate of thegovernment’s non-classified documents” are selected, with the reference values setto 90 and 100% or above respectively, for intelligent traffic management,
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“electronic rate of bus stop board” and “citizens’ compliance rate for traffic routinginformation” are selected, with the reference values set to 80 and 50% or aboverespectively, to provide references for intelligent city construction and applicationlevel. On the other hand, some perspective and leading indicators are designed inview of the intelligent city construction and development trend. For example, forintelligent energy management, “new energy automobile proportion” and “buildingdigital energy saving proportion” were included in the indicator system, and theywere set to the reference values of 10 and 30% or above. For intelligent educationsystem, “network teaching proportion” was put forward and the reference value of itwas set to 50% or above. We will guide the domestic intelligent city construction topay more attention to these aspects through these perspective and leadingindicators.
3. Intelligent City Information Service Economy Development
Intelligent city information service economy development presents a relationshipof mutual promotion and interdependence to some extent. On the one hand,intelligent city construction depends on research and application of new tech-nologies and new products; on the other hand, intelligent city construction opera-tion will greatly promote the development of these industries, especially thedevelopment of information industry.
Therefore, we think the development of related industrial economies in intelli-gent city is an important factor to measure intelligent city construction level. Giventhat the scope of industrial economies related to intelligent city is wide, which isinvolved in electronic and information manufacturing, software information serviceand various aspects, and that there are huge differences among industrial structuresof cities, if all the industries are included, there will be less comparability betweencities. Therefore, when designing the indicator system, we should mainly considerthe development situation of information service industry that derived from intel-ligent city construction and development or that supports intelligent city con-struction operation, which mainly includes the following two aspects.
(1) The overall level of industrial development, which refers to overall strength ofthe development of the city information services. Specific considerationsindicators include “the proportion of added value of information servicesindustry in gross regional production” and “the proportion of informationservice industry employees in total social employees”, and the referencevalues of both are 10% or above. The overall level of information servicedevelopment can be reflected by these two indicators.
(2) Enterprise informatization operating level, which refers to the developmentlevel that supports enterprise’s production and operation through informati-zation system. It mainly includes three specific indicators—“the building rateof enterprise website”, “enterprise electronic commerce behavior rate” and“enterprise informatization system usage rate”, and the reference values ofthem are set to 90, 95 and 90% or above respectively. At the current stage of
248 Appendix
intelligent city construction in China, the above three indicators can reflect theenterprise informatization operation level better.
4. Intelligent City Humane Studies Accomplishment
Intelligent city humane studies accomplishment is mainly used to measure cit-izens’ cognition of intelligent city development concepts, the mastery of basicscience and technology (including information technology) as well as intelligent lifeconcepts. As the main body of intelligent city operation and service, citizens’ ownsituation is decisive for the successful construction of intelligent city. At the sametime, the intelligence of their behavior is most important factors that directly reflectintelligent city construction results. To this end, we will talk about intelligent cityhumane studies accomplishment level.
(1) Residents income level. Although resident’s income level is the indicator ofcity economic development, we think residents’ income will have enormousinfluence on city management and life. It’s hard to think intelligent citymanagement mode and resident’s life style can be built up in a city where theresident’s income level is very low. According to resident’s disposable incomelevel in Shanghai and other regions, the reference value of intelligent cityresidents income is about 50 thousand Yuan or above.
(2) Residents culture science literacy. Resident’s culture science literacy includesknowledge of natural sciences, social sciences and other aspects. It is anindicator that can comprehensively reflect resident’s culture science literacy,which plays an important role in intelligent city construction. “The proportionof specific colleague course or above in gross population” is selected as theindicator to reflect residents culture science literacy. Combined with the sit-uations of Shanghai and other major cities, the reference value of this indicatoris set to 30% or above.
(3) Residents life networked level. Networked life is an important feature ofintelligent city. Therefore, When investigating the intelligent city citizenculture science literacy, resident’s life networked level is an important refer-ence system; especially “resident’s network access rate” and “familyonline-shopping proportion”, they should become characteristic indicators ofresident’s life networked level. So, the reference values of both are set to 60%or above.
5. Intelligent City Residents’ Subjective Perception
Intelligent city residents’ subjective perception gives priority to the indicator ofresident’s subjective perception. Evaluating and measuring important aspectsrelated to intelligent city construction are critical reflections of residents’ happiness.Indicators related to intelligent city residents’ subjective perception are importantcomplements to other indicators that are not related to subjective perception. They
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can reflect intelligent city construction results more precisely and more intuitively,and they are important ways to reflect the spirit of “people oriented intelligent city”.Indicators shall be designed from both sense of convenience and security, using themode of “sample investigation + subjective rating” to acquire the results of intel-ligent city construction in the mind of residents.
(1) The sense of convenience of life mainly refers to convenience degree invarious aspects such as traveling, seeking medical treatment and handlingaffairs. Indicators shall be designed according to current main focusing pointsof city development—transportation, medical and government services, andlet residents rate the convenience degree of obtaining traffic information,medical treatment and governmental services, and the reference value is set to8 points or above (the total points are 10).
(2) The sense of security of life mainly refers to the degree of satisfaction ofresidents to intelligence level of food and drug safety, environmental safety,transportation safety and etc. In recently years, food and drug safety, envi-ronmental safety and transportation safety are three major fields in citymanagement operation and public life. One of the important goals of intelli-gent city is to protect these three safeties through intelligent applicationsystem.
Therefore, modified indicators include “food and drug safety electronic moni-toring satisfaction degree”, “environmental safety information monitoring satis-faction degree” and “traffic safety information system satisfaction degree”, whichreflect intelligent city management application system construction and operationlevel from the perspective of subjective perception of residents.
6. Intelligent City Soft Environment Construction
Intelligent city soft environment construction mainly consists of planning,design and environmental building of intelligent city development. Now, China isin an early stage of intelligent city construction, the status of overall planning anddesign and soft environment construction such as environmental building will haveimportant influence on intelligent city construction. Therefore, modified indicatorsystem has contained three specific indicators—“intelligent city developmentplanning”, “intelligent city organizational leadership mechanism” and “intelligentcity forum conference and training level”, in the view of intelligent city planningand design and intelligent city atmosphere building. These three specific indicatorscould reflect the soft environment power of the city.
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A7.3 The Indicator System Needs to Be Modifiedand Improved Continuously Through Empirical Research
Intelligent city construction is not achieved overnight. It needs long-time invest-ment and construction as well as focusing promotion. Therefore, when performingintelligent city evaluation, considering some characteristics such as collectabilityand comparability, indicators are classified. Some indicators of greater importanceare characterized as “core indicators”, and others were characterized as “generalindicators”, and they will be given different weights during evaluation. For eval-uation results, we pay more attention to the current stage of development, anddivide the evaluation results into three kinds—incubation period, hatching periodand embryonic period.
Through collecting and test-evaluating the indicators from Shanghai PudongNew Area, Hangzhou and other regions, the indicator system more truly reflects theintelligent city construction stage and level, and finds out weaknesses in currentintelligent city construction to some extent. For example, the subjective perceptionof residents in current intelligent city construction is still relatively weak. Thismeans intelligent city construction is still staying in the government level to a largeextent, both promotion and effectiveness have not yet deeply rooted in the hearts ofpeople. The scores related to intelligent energy management are generally low,which shows that efficiency of energy conservation and emissions reduction orsmart grid construction needs to be accelerated. Empirical test evaluation is theinspection of the indicator system, which means some measuring and guidingsignificance to intelligent city construction. Meanwhile, empirical research alsomeans a lot to the further improvement of the indicator system.
Intelligent city construction is a long and complicated process. As an importanttool for measuring and guiding intelligent city construction, the indicator systemalso needs to be updated and changed continuously. Not only the system frameshould be more completed and scientific, but also the indicator selection should bemore typical and efficient.
Only when we improve the intelligent city evaluation indicators system duringthe development and perfect it constantly during practices, it could truly keep pacewith the times and measure the intelligent city construction stage and level forplaying a leading role in city innovation and development in China.
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A8 R&D Case of Intelligent City Evaluation IndicatorSystem—TU Wien19
The intelligent city evaluation indicators system—Smart City Indicators, is led anddeveloped by Regional Research Center in Vienna University of Technology (TUWien) through cooperation with multiple scientific research departments and localcities. Since the first version of the indicator system and evaluation report waspublished in 2007, two subsequent updated versions have been released in 2013 and2014 respectively. This evaluation indicator system is research result of the uni-versity scientific research team, which is funded by public and private funds. Mostof the research results and part of the processes were published to the public. At thesame time, their research results were also promoted and applied in the researchesand practices of other intelligent cities.
Since 2007, the team led by Prof. Rudolf Giffinger, the director of RegionalResearch Center in Vienna University of Technology, has started to carry outrelated researches and built up an intelligent city model under the background ofEuropean city development based on their understanding of intelligent city.Considering the large proportion of medium-sized cities in European city residents,as well as the feasibility of the research and data availability, the research focusedon sustainable evaluation and ranking of medium-sized European cities. The mainevaluation and ranking results were published and updated on the official website ofEuropean intelligent cities established by the team.20 As a scholar who has geog-raphy and city planning background, Prof. Giffinger understood and built theintelligent city model from the perspective of city planning. When the first versionof this evaluation system was published in 2007, it was based on model design anddivided into three hierarchies. Based on the premise of keeping the basic frame, thesecond version published in 2013 has been improved a lot. The understanding ofthree hierarchies was updated, and these changes were kept in the third versionpublished in 2014. Prof. Giffinger thought the model and evaluation system was agood way to measure and research the innovative performance in all respects ofobjective cities.
A8.1 Research Process
At first, evaluating and ranking an intelligent city should be based on the under-standing of the concept of intelligent city. Economy and technology developmentunder the background of globalization have profoundly influenced the Europeancities, presenting double challenges to European cities—city competitiveness
19The materials in this section are based on the interview with Prof. RudolfGiffinger from ViennaUniversity of Technology (Author: Lü Hui). Thanks.20Please go to http://www.smart-cities.eu for details.
252 Appendix
improvement and sustainable development. While these challenges are closelybound up with all respects of cities, especially problems related with life quality ofresidents, such as housing, economy, culture, society, environment and etc. Theconcept of intelligent city is originated from the development of information andcommunication technologies. Cities are looking forward to dealing with multiplechallenges they are facing through technologies. Prof. Giffinger thinks technologyis just one dimension of intelligent city, while social innovation dominated byself-organizing and learning process is an indispensable part of intelligent city. Weneed to understand intelligent city through a more comprehensive perspective. Thereason for choosing to rank cities—a seemingly non-academic method, is that in thecombination of city research and planning practice, ranking is possible to become acatalyst. Meanwhile, Prof. Giffinger hopes to make it an effective tool through cityevaluation and ranking, promoting horizontal comparison between cities in theintelligent city model combing with development status of each city to finddevelopment direction and covert the evaluation ranking into a reference system forspecific development strategies of cities.
1. The First Version of Evaluation Indicator System
Vienna University of Technology has published a research report—Smart Cities:Ranking of European Medium-Sized Cities in cooperation with its research partnersin October, 2007. The research participants included University of Ljubljana inSlovenia and Delft University of Technology in Netherlands.
The aspects and indicators of intelligent city evaluation used in the research areclosely related to the target cities. Because there were no evaluation and ranking forintelligent city in the beginning of the research, the evaluation and ranking systemof 7 cities that have more influences than considered first, and they selected eval-uation ranking results of years near the research year to investigate, see Table A.28.
In Table A.28, some (such as 1, 3, 4, 6) mainly focus on life quality of individualresidents in the city, while others (such as 5 and 7) include a wider range of factors,such as geographic elements and tourist attraction and etc., and the 2nd evaluationranking focuses on a particular aspect of the city—the sustainability of the cityenvironment.
The evaluation ranking limits the evaluation scope to a certain spatial scale, suchas global scale or a country scale. Because it’s difficult to evaluate and compare allthe cities through one method, generally, cities would be classified according totheir population size (such as 2, 5, 7), or they will select target cities to be evaluatedaccording to their importance (such as 1, 3, 4). The selection method of 6th rankingis more comprehensive, perform preliminary evaluation for 643 cities in Europefirst, then select 58 cities to perform actual evaluation and ranking according to theresults of preliminary evaluation. Data availability is another factor that will impactevaluation method. Some evaluations (such as 1 and 3) get data through fieldsurvey and the interview, while most of them (such as 2, 4, 5, 6, 7) use data analysisresearch. For evaluations, to determine the weight of each factor is an importantaspect. The weights in most evaluations are determined by the research team, while
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the weights in some evaluations (such as 1) is based on the results of interviews oftarget cities.
The team of Prof. Giffinger built intelligent city evaluation indicator systemframe model first based on preliminary theories and empirical researches. The firstversion of intelligent city evaluation indicator system model uses hierarchicalindicators, including 6 characteristics, 31 factors and 74 quantifiable indicators, tosort and research medium-sized cities in Europe through this model (see Fig. A.4).
6 intelligent city characteristics are intelligent economy, intelligent residents,intelligent governance, intelligent transportation, intelligent environment andintelligent life. Each characteristic has a number of factors respectively. Viewingfrom the characteristics and factors, some of them are hardware constructions thatare more technical, such as equipment and facilities, and others are economicfactors such as productivity levels, while more of them are evaluations for software,i.e. measurement on development level of social capital. Social capital is not only ahot point of academic discussion, but also an important soft power for citydevelopment. In order to evaluate such factors, it should further decompose intel-ligent city factors into quantifiable indicators.
For selection of research objects, it shall screen in 1595 cities determined byEuropean Union related researches according to three constraint conditions. First,only medium-sized cities can be selected, where the population size is limited to0.1–0.5 million. Second, there must be at least one university in the city as the basisof knowledge production. The last condition is excluding satellite cities of big cities(there is no large city with a population of more than 1.5 million nearby). Inaddition, the city must be within the scope of Urban Audit city database of EU.With the further constraints in the availability of data, 70 cities were screened out asresearch objects gradually.
The research established a research database for 70 cities and 74 indicatorsmainly using secondary data from research projects at EU level, and preformed
Table A.28 Evaluation ranking results referenced in the research
No. Title Author Yearpublished
Scope
1 Quality of living survey Mercer Human Resource Consulting 2007 200 cities in theworld
2 Canada’s mostsustainable cities
Corporate Knights: The CanadianMagazine for Responsible Business
2007 Large citycenters inCanada
3 How the world views itscities
Anholt City Brands 2006 60 cities in theworld
4 Worldwide cost of living Economist Intelligence Unit 2006 130 cities in theworld
5 DritterGroßstadtvergleich
IW Consult GmbH/Institute of theGerman Industry
2006 50 Germancities
6 Europas AttaktivstesMetropolen für Manger
University of Mannheim/ManagerMagazin
2005 58 Europeancities
7 Les Villes Européennes:analyse comparative
UMR Espace (Rozenbiat, Cicille) 2003 180 westernEuropean cities
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standardized process for the data in order to realize indicator integration and hor-izontal comparison. The research acquired 6 characteristics and overall performancescores of 70 cities, then got corresponding ranking (see Fig. A.5) and distributedthem on the map for investigation.
At same time, with the analysis the evaluation results combined with the actualsituation of the city, we could set up the general situation of each intelligent city,and put forward intelligent city development strategic direction for each city on thebasis of their own conditions and comparison.
Fig. A.4 The first version of intelligent city evaluation indicator system model developed by TUWien
Fig. A.5 Score and ranking of the whole and characteristics of cities
Appendix 255
The overall ranking is only to position. A city with higher ranking are notnecessarily doing well in every aspect, while a city with lower ranking might havesome prominent indicators. Although the balance may be poor, it also has dis-tinctive development characteristics. So, in this evaluation system, strengths andweaknesses of each factor will be analyzed in detail. For example, when concludingfactors of aspects of Luxembourg, which took the first spot, you can see that,flexibility and creativity under the characteristic of intelligent residents as well aseducation facilities and other indicators under intelligent life of Luxembourg arestill very weak, which are short boards of its city development (see Fig. A.6).
Fig. A.6 TU Wien city evaluation situation of Luxembourg, which ranked first in the first version
256 Appendix
This evaluation system could not only evaluate and rank cities in a whole, butalso perform specific analysis on a certain city, and even realize city evaluation andcomparison through breaking it into indicators level in order to help identifyspecific problems of city. For example, only for the medical conditions factor underthe characteristic of intelligent life, city distribution is analyzed based on secondaryindicators to determine the development status of the cities and developmentcharacteristics of regional spaces.
2. The Second Version of the Evaluation Indicator System: Improvement onMethods and Visualization
Prof. Giffinger’s team has performed the research of the second version ofintelligent city evaluation indicator system from the end of 2012 to the beginning of2013, the result of which was published in 2013. The second version updated thedatabase and ranking based on the original intelligent city model. It enlarged thenumber of cities to 71 on the basis of intelligent development and data availability.
Under the frame of original evaluation model method, the second version haschanged the original factors to domains, adjusted the number of domains to 28,replaced indicators with components and adjusted its number to 82 according tochanges of city development and evaluation requirements while keeping the mainframe stable (see Fig. A.7).
In 2013, the model also introduced new intelligent city evaluation overviewfunction. It could directly select several cities from database to perform horizontalcomparison on the basis of the discussion on city’s specific characteristics andfactors. Intuitive comparison of six characteristics of the cities ranked 1st(Luxembourg), 2nd (Aarhus) and 13th (Graz) in 2013 is shown as Fig. A.8.
Meanwhile, the indicator data of each city were described by city overview,including specific evaluation values of 6 characteristics and evaluation values of
Fig. A.7 The second versionof intelligent city evaluationindicator system modeldeveloped by TU Wien
Appendix 257
domains of sub-hierarchy. Additional visualization functions and an openself-service data platform have made evaluation methods and research processesmore open and transparent. The evaluation overview of Aarhus, Denmark, whichranked 2nd in the second version, is shown as Fig. A.9.
3. The Third Version of the Evaluation Indicator System: Wider Application
The third version of intelligent city evaluation indicator system published in2014 basically continued to use the methods in the second version, fine-tuned thecomponents of the third hierarchy, reduced its number to 81, and changed char-acteristics to key fields (see Fig. A.10). This new version is supported by 7 EU
Fig. A.8 TU Wien city’s horizontal comparison tool of the second version of the evaluationindicator system
Fig. A.9 TU Wien city evaluation in the second version of the evaluation indicator system(Aarhus, Denmark)
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Seventh Framework Programme and Planning for Energy Efficient Cities, PLEEC,at the same time (Giffinger et al. 2014a, b). Due to the requirements of PLEECproject research, all of 6 case cities cooperating with the project were included asevaluation objects on the basis of the original, so the number of evaluation objectivecity is added to 77. Because 2 of the added cities are not covered by Urban Auditdatabase, the immediate data will be collected to perform research.
The third version continued to use the visualization and display technologies inthe second version, and updated the data. At the same time, due to the researchrequirements of PLEEC project, it performed energy intelligent city research on 6case cities in respect of energy efficiency. It performed evaluation in a similarhierarchical method on the basis of data of two investigations and about 100interviews, which formed Energy Smart City Profiles. The third version selected asubsystem section of intelligent city, designated domains and components anddetermined the weights according to immediate investigation data. Then, it per-formed more detailed description and comparative research through secondinvestigation and put forward targeted development direction and recommendationsin terms of intelligent city construction path for promoting sustainable energy forcities.
The third version of intelligent city evaluation indicator system paid moreattention to specific objects to describe and understand intelligent city overviewthrough the integration with PLEEC project requirements. Intelligent city is ageneral concept, so when actually evaluating cities, we should combine it withspecific environment.
Fig. A.10 The third versionof intelligent city evaluationindicator system modeldeveloped by TU Wien
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A8.2 Research Review and Outlook
Prof. Giffinger thinks the way to understand intelligent city and city development isthe core that determines indicator operation and direction. Therefore, beforeanswering the question “How to evaluate, measure and rank intelligent cities?”, weshould answer “How should we understand intelligent city?”
Intelligent city is put forward to deal with challenges that cities are facing on thebasis of sustainable development requirements such as economy reconstruction,social change and environmental and climatic changes. In the normative research ofintelligent city model construction, Prof. Giffinger determined the structure ofhierarchical indicator system to ensure the feasibility and put forward 6 intelligentcity characteristics, each of which has numbers of factors and consists of severalindicators. This creates the frame of the first version of intelligent city evaluationindicator system model.
In this model, characteristics and factors are understanding of intelligent city.And on this basis, we should further find out indicators or indicator combinations inorder to describe these factors reasonably. For each basic indicator evaluating theintelligent city, Prof. Giffinger thinks due to the close relationship in city networks,indicator selection should not be limited to indicators of the city itself. For theselection of some indicators, we need to consider indicators of a lager spatialdimension. For example, some regional even national indicators could also be usedto measure city performance.
The evaluation rankings of three versions are based on a same intelligent citymodel and same understanding of intelligent city. The latter two versions replacedfactors with domains in order to describe the information contents covered by themmore precisely. In addition, during the research in cooperation with PLEEC project,when empirical research on 6 case cities was performe, it’s found that it’s difficultto describe the status of each case city precisely or carry out horizontal comparisonon these cities only according to the statistical data. The first version indicators areset according to EU Urban Audit city database, and the data of indicators arerequired to be precise and specific. Therefore, the case city not covered by thedatabase could not provide all the corresponding data.
In 2014, Prof. Giffinger put forward an idea that under the original model frame,the specific indicators of level three should not only rely on quantifiable statisticsindicators, but also need to be addressed to various stakeholders in the city (such asgovernment, enterprises and citizens). Qualitative research methods were partlyadopted. Therefore, during the research in cooperation with PLEEC project, for 6case cities, a set of survey questionnaire was designed to make sure the degree ofimportance of all domains under different key characteristics, and further discussedabout which domains have higher recognition degree, as well as what aspects therelevant parties want to promote. Prof. Giffinger noted that, although interviews andresearches for 6 case cities have taken so much time and energy, domains and evencomponents and their weights in the evaluation system are still sensitive, and maybe different depending on relevant parties, time and population discussed for a
260 Appendix
certain case city but have relative stability in general. Cities have been in a dynamicprocess, and intelligent cities should have local economy, culture, and environmentand time characteristics of their own. Prof. Giffinger thinks that such evaluationsystem and information data acquisition methods more suitable for the requirementsof this target characteristics of cities.
Although the intelligent city ranking is just one of the popularized researchresults, the indicators and methods behind it are based on the understanding of citiesand their intelligence. Prof. Giffinger thinks intelligent city needs social innovationmethods to guide and support the development of technologies. This is aself-learning process of cities and should not only be guided by technologies. Forevaluation indicators and especially research methods which determines weights,the three versions of intelligent city evaluation model have changed from relying onunified statistical data to expressing ideas of parties of cities. So to speak, its ownintelligence has been promoted through self-learning and improving. City evalua-tion and ranking should be regarded as a toolkit for experience learning, problemdiagnosis and policy adjustment of cities, which plays a practical role in the for-mulation of city’s development strategies.
A8.3 Application and Popularization
Since the first version of intelligent city evaluation report was published in 2007,the research has been carrying out in Regional Research Center in ViennaUniversity of Technology. In addition to the discussion and research improvementin the field of academic (such as PLEEC research project), contents related to theresearch are popularized and applied in intelligent city practices in Europe and eventhe whole world to some extent. In Austria, some cities such as Vienna, Graz andLinz, the results of the evaluation method were used to formulate intelligent citydevelopment strategies. In the scope of Europe, Ljubljana of Slovenia, Bilbao ofSpain, Krakow of Poland and some other cities also use the research method toguide the development of intelligent cities. At the same time, Prof. Giffinger alsoprovides advices for cities in Germany, Israel, Japan and other countries based onintelligent city evaluation and development as a consultant.
Bilbao continues to use above intelligent city model to perform its intelligent cityresearch, and on the basis of this, they also put forward corresponding indicators asthe development guide for intelligent cities based on case research and its owndevelopment characteristics.
Then intelligent city project of Krakow—SMART_KOM was started in 2013.The team led by Prof. Giffinger was responsible for the formulation of intelligentcity strategies as an international participant of the project. Krakow Science andTechnology Park was the organizer of the project, but in the strategic level, theycooperated with Krakow and Krakow Metropolitan Area in a higher space level.
The project was conducted in two phases (see Fig. A.11). The project contentwas divided into three pieces: problem diagnosis, case researches integration, and
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strategy development and promotion. The first two were conducted at the same timeas the basis. At first, under above intelligent city frame model, they discussed on 6basic characteristics—intelligent residents, intelligent life, intelligent environment,intelligent economy, intelligent transportation and intelligent governance respec-tively. From November, 2013 to March, 2014, they organized work seminars—Smart City Work shop, which attracted 161 participants in total. Before each workseminar, they prepared basic reports. Each working group would prepare prelimi-nary reports, collect status and data of each space level under the topic of theseminar, and perform basic analysis as primary diagnosis. On the seminar, theywould perform SWOT (strengths, weaknesses, opportunities and threat) analysis fora certain intelligent domain, and put forward city problems that require intelligentsolutions most. Then, each party put forward relevant actors of particular intelligentcity sub-systems.
At last, they would determine preferential actions in each domain through dis-cussion and consider key development points as behavior and implementing goals.
On the basis of 6 topic seminars, an intelligent city comprehensive seminarintegrating results of the 6 discussions and a joint seminar of regional government’sfunctional departments were held in April, 2014. The 6 seminar has collected manyideas and future visions for Krakow and regional intelligent city developmentpotential, and set some of preferential development items.
Of course, these preferential development items were obtained through specificgroup discussion, which were coordinated according to the overall developmentneeds. In next phase, they collected and researched further data to put forwardregional, city and park’s development strategies based on the model setting. ViennaUniversity of Technology also continued to play an important role in this as thescientific research team of city planning background. Prof. Giffinger think, in the
Fig. A.11 Krakow intelligent city project—SMART_KOM promotion frame
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Krakow intelligent city project, because we need to consider the developmentrequirements of three space levels, quantitative indicators has lost its most signif-icance. In the level of city, they could be compared under the whole Europeanbackground, but in the level of region and considering the coordination of citydevelopment, this project used qualitative analysis and research methods, i.e.determining preferential development items (not indicators) of domains undercharacteristics, as well as relevant actors specific to items, and set correspondingdevelopment goals of some items. In the next phase, we’re looking forward toformulate further intelligent city development strategies on the basis of these pre-liminary works to realize a smooth evolution from theory to practice.
References
Cai DF (2012) About public security of cities. Democracy (2):8–9Dong Ji C (2010) Introductory medical informatics. People’s Medical Publishing House, BeijingGiffinger R, Haindlmaier G, Kramar H et al (2014a) PLEEC report: energy smart city profiles [R/OL].
http://www.pleecproject.eu/downloads/Reports/Work%20Package%202/wp2_d23_energy_smart_city_profiles.pdf. Accessed 11 June 2016
Giffinger R, Haindlmaier G, Hemis H et al (2014b) PLEEC report: methodology for monitoring.http://www.pleecproject.eu/downloads/Reports/Work%20Package%202/wp2_d24_methodolgy_for_monitoring.pdf. Accessed 10 June 2015
Sheng XF, Yang XM (2012) Six dimensions of Pudong, “feel the pulse” of intelligent city. ChinaInformatization (14):20–23
Yan YJ (2006) The characteristics and enlightenment of city grid management. City Probl(2):76–79
Zhao JY (2009) E-commerce industry highlights the logistics requirements. Logistics MaterHandling 14(10):43–46
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