6. ~250
years
of
infrastructure
transforma3ons
Installation
Crash
Deployment
Irruption
Frenzy
Synergy
Maturity
• Formation of Mfg. industry
1
The Industrial 1771
Panic
• Repeal of Corn Laws 1829
Revolution 1797
opening trade
• Standards on gauge, time
Age of Steam Panic
2
and Railways
1829
1847
• Catalog sales companies
1873
• Economies of scale
Age of Steel, Electricity Depression
• Urban development
3
and Heavy Engineering 1875
1893
• Support for interventionism
1920
• Build-out of Interstate
Age of Oil, Automobiles Crash
4
and Mass Production
1908
1929
highways
1974
• IMF, World Bank, BIS
Coming period of
Age of Information and Credit Crisis
5
Telecommunications
1971 2008
Institutional Adjustment
and Production Capital
Source: Carlota Perez, Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages; (Edward Elar Publishers, 2003).
6
7. 知識集約型サービス経済の発展
Estimated world (pre-1800) and then U.S. Labor Percentages by Sector
2M years as hunting clans/
bands
10K years as farm families
200 years as factory workers
60 years (so far) as
knowledge workers in
organizations and now digital 1771 Industrial revolution
networks 1875 Heavy engineering
1908 Mass production
1971 IT
Cyber physical and People based
Service system transformation
Estimations based on Porat, M. (1977) Info Economy: Definitions and Measurement
14. サービス・マーケティング研究に
よるサービスの定義
• 1970−2000
– 単純な商品（goods)に対するサービスの課題の認識
– サービスは“行為”であるという共通認識の芽生え
– サービスにおける共通課題の定義
• IHIP: 無形性 (Intangibility)、異質性 (Heterogeneity)、同時性
(Inseparability)、消滅製 (Perish ability)
• 2000-
– IHIPに対する懐疑
• “Whither Services Marketing? In Search of a New Paradigm and Fresh
Perspectives”
• (Lovelock Gummesson)
• “Service portraits in service research: a critical review” (Ebvardssonら)
– 新しい視点の提示
• サービス提供者と“顧客との価値の共創”からサービスを見直すService-
Dominant Logicの提案 (Vargo Lusch） 14
15. Applicability of “Unique Characteristics of Services”
to Different Types of Services
Service Category Involving
Physical Acts Physical Acts Nonphysical Processing
to Customers’ to Owned Acts to of Information
Bodies Objects Customers’
Minds
Intangibility Misleading Misleading Yes Yes
Heterogeneity Numerous Numerous Numerous
Yes exceptions exceptions
exceptions
Inseparability of
Only when
production and Many
Yes No performance is
consumption delivered “live” exceptions
Perishability –
cannot be Yes Yes Numerous Many
inventoried after exceptions exceptions
production
15
Ref 1: Principles of Service Marketing and Management by Christopher H. Lovelock
18. サービスシステムの構成要素
Based
on
Jim
Spohrer’s
ecology
model
Service System
Entities Interactions Outcomes
People Value proposition (win, lose)
based Interactions x
(win, lose)
Technology
Governance based
Information Interactions
Organization
18
19. サービスシステムの階層
Level AKA ~No.
People ~No.
En00es Example
0.
Individual Person 1 10,000,000,000 Jim
1.
Family Household 10 1,000,000,000 Spohrer’s
2.Neighborhood Street 100 100,000,000 Kensington
3.
Community Block 1000 10,000,000 Bird
Land
4.
Urban-‐Zone District 10,000 1,000,000 SC
Unified
5.
Urban-‐Center City 100,0000 100,000 Santa
Clara
6.Metro-‐Region County 1,000,000 10,000 SC
County
7.
State Province 10,000,000 1,000 CA
8.
Na3on Country 100,000,000 100 USA
9.
Con3nent Union 1,000,000,000 10 NAFTA
10.
Planet World 10,000,000,000 1 UN
19
22. サービスシステム知識体系
systems Systems that focus on flows of things Systems that support people’s activities Systems that govern
transportation ICT retail healthcare city
food education state nation
disciplines supply chain water
waste
energy
products electricity
cloud building hospitality banking family
construction finance
work secure scale laws
behavioral sciences
Customer
stakeholders
e.g., marketing
Provider management sciences
e.g., operations
political sciences
Observe Stakeholders (As-Is)
Authority
e.g., public policy
learning sciences
Competitors e.g., game theory
and strategy
cognitive sciences
People
e.g., psychology
resources
system sciences
Technology
e.g., industrial eng.
information sciences Observe Resource Access (As-Is)
Information
e.g., computer sci
organization sciences
Organizations
e.g., knowledge mgmt
History social sciences
change
e.g., econ law
(Data Analytics)
Future
decision sciences Imagine Possibilities (Has-Been Might-Become)
e.g., stats design
(Roadmap)
run professions
Run
e.g., knowledge worker
Transform
Realize Value (To-Be)
value
transform professions
(Copy)
e.g., consultant
Innovate innovate professions
(Invent)
e.g., entrepreneur
22
23. T型サービスシステム人財
depth
breadth
Many cultures
Many disciplines
Many systems
(understanding communications)
BREADTH
Deep in one discipline
Deep in one culture
Deep in one system
DEPTH
(analytic thinking problem solving)
23
23
32. Service
Science
related
disciplines
Business
Organiza3on
International Trade
Informa3on
Engineering economics and management, Supply
chain
management
Cogni3ve
science
and
psychology
Mathema3cs
and
non-‐linear
Complex
adap3ve
systems
theory
dynamics
Computer
Computer supported cooperative Opera3ons
management
(OM)
science and
work
Opera3onal
research
(OR)
Human AI/web
resource Financial and value engineering
Organiza3on
theory
and
learning
services
Software
Project
management
manage Economics Industrial
engineering
(IE)
and
Queuing
theory
metrics
ment
and law
systems
Statistical and
Industrial
and
process
automa3on
Simula3on,
modeling
control developm
Knowledge
management
visualiza3on
Political theory
ent
Management
of
informa3on
Sociology
and
anthropology
Science
Strategy
and
finance
systems
System
design
Management
of
technology
Systems
dynamics
theory
and
and
sokware
innova3on
design
architecture
Marke3ng
and
customer
knowledge
Total
quality
management,
lean,
six
sigma
Behavioral sciences and education, Game theory and mechanism design
Technology
Experience design, theatre and arts
People
32
Ref:
“Succeeding
through
service
innova3on”
hpp://www.ifm.eng.cam.ac.uk/ssme/
33. 問題解決型サービス科学研究開発プロジェクト（平成22-23年度）
ディシプリンへのマッピング
Business
Organiza0on
Informa
0on
クリエイティ サービス・マネジメント
ブ・サービス
農業
水利
サービス価値
価値共創の サービス指
共創モデル
可視化と支援
向集合知
基礎理論
便益遅延サービス
サービス・デザイン サービス工学
サービス構成支援法
利他性
音声つぶやき
People
A研究
Technolo
B研究
gy
33 Ref:
“Succeeding
through
service
innova3on”
hpp://www.ifm.eng.cam.ac.uk/ssme/
39. 問題解決型サービス科学の構築に向けて
2010
2011
2012
2013
2014
3Q
4Q
1Q
2Q
3Q
4Q
1Q
2Q
3Q
4Q
1Q
2Q
3Q
4Q
1Q
2Q
ベストなプロジェクトを採択し、研究の柱とする
サービス科学コミュニティの形成(学会、科研費)
研究開発成果の国内外への発進
プロジェクト採択
公開フォーラム
サービス・サイエンス・セミナー
サービス科学研究ブック
サービス学会検討
合宿
国際会議
Human
side
of
Service
Engineering
AMA
S-‐SIG?
情報処理学会／情報システム／横幹連合／OR学会／AI学会／SRII等サービス関
連イベント
プログラム主催外部イベント
プログラム内イベント
39
Japan
Science
and
Technology/RISTEX
プログラム外関連イベント
40. 参加者募集中
7月21−25 Global Perspectives on Service
Science: Japan
サンフランシスコ 日本の研究開発版
Call for Chapter
40
41. Overseas
Projects
no. of
Nation
Source
Features
projects
National Science Foundation Public services, finance, logistics, etc… based on OR
(NSF): Service Enterprise 18(new)/ Shift from service modeling to measurement of service system,
US
Systems Program year human behavior
(Report by CRDS/JST G-Tec $5M/year
Collaboration with Decision, Risk and Management Sciences
group)
(DRMS)
focus is on shifting from a manufacturing focus to a balanced
The Finish Funding Agency for
service focus
Technology and Innovation
60/year Trading, Logistics, land, Finance, Knowledge intensive services,
Finland
(Tekes)
E50M/5year
etc.
(Report by CRDS/JST G-Tec
By 2007, 121 projects are selected, 30 from university, 91 from
group)
companies
E3.5M for Co funded by the Economic and Social Research Council
The Advanced Institute of innovation (ESRC) and Engineering and Physical Sciences Research
UK
Management Research (AIM) productivity Council (EPSRC)
http://www.aimresearch.org/ gland Productivity and performance, Sustaining innovation, Promising
challenge
practices, Excellence in the public sector
Service engineering, IT, automation for management innovation,
German BMBF Innovation with Services
E70M/5yesr industry growth, and new job creation
y
http://www.bmbf.de/en/
Include socio-science research
Science and Technology Policy focus is on shifting from a manufacturing focus to a balanced
Korea
Institute (STEPI)
service focus (increase service funding)
Japan Science and Technology
7(new)/year Aiming the fusion of arts and sciences supported the
Agency (JST): Solutions and
Japan
Foundation research program for
$7.5M/year management team.
41
(in 3 years) The program is facilitated by social technology funding agency
SSME
42. Share
of
Total
Business
RD
Held
by
Services
and
Manufacturing
RD
among
OECD
Countries
(2004)
42
Japan
Science
and
Technology/RISTEX
12.5.31
43. Academic Landscape of SSMERef: Bibliometric Analysis of Service Social Change
Research, Technological Forecasting
Innovation
(Service Science, Management and Engineering )
#8, IT Web, 459papers, 2003.4
#2, medical care, 1,681papers, 2002.7
#4, ecosystem,
914papers, 2004.1
#6, public service,
#3, mental health care, 866papers, 2002.2
1,314papers, 2000.8
#7, public medical care,
632papers, 2001.8
#5, QOS, 906papers, 2002.7
#1, management, 1,818papers, 2003.0
12.5.31 Only clusters
Copyright 2002-2009 Naoki Shibata All Rights Reserved. whose #papers ≧ 400 were named.
43
44. SSME
paper
sub-‐cluster
label
analysis
Industry
ecosystem:
Healthcare
services
Financial
services
Ecosystem
service
Public
services,
SCM
Environment
Ecosystem
Walter,
mountain
valua3on
Web
service
Emergence
of
Ecosystem
Process
management
Service
Science
resilience
Ecosystem
Human
resource
management
management
Opera3on
management
Service
innova3on
Knowledge
management
Service
quality,
TQM
BPR
45. IBM:
Service
Science
Research
Themes
hpp://www.trl.ibm.com/projects/index.htm
Site knowledge
Business strategy
SCM
Business
modeling
Research management
Business evaluation methods
CRM
Service value evaluation methods
Quality analysis
Service system modeling
Environment/traffic simulation
Service provider support
Risk analysis
Service
quality
Social
modeling
Problem determination
Optimization
Brand analysis
Behavior analysis
CSAT analysis
Psychology
Voice Network analysis
Text mining
Software enquiring
Simulation
Natural language processing System software
RD
outputs
New
research
Data science
Information technology Math Science
theme
46. Na3ons
compete
and
cooperate:
Universi3es
important
%
WW
GDP
and
%
WW
Top-‐500-‐Universi3es
(2009
Data)
46
47. Up-Skill = New Venture = Graduates with = High-Growth
Cycle Smarter Planet skills
= Acquisition = IBMer moving from Acquisition/
New IBM BU
mature BU to acquisition
(Growing)
= IBMer moving into
IBMer on Campus role = High-Productivity/
University-Region1 (help create graduates
with Smarter-Planet skills, Mature IBM BU
help create Smarter Planet
oriented new ventures; (Shrinking)
Refresh skills
IBM
University-Region2
47
48. Regional Competitiveness and U-BEEs:
Where imagined possible worlds become observable real worlds
http://www.service-science.info/archives/1056
Innovations Nation
“The future is already
Universities/ State/Province
here (at universities),
City/Region
Regions For-profits U-BEE it is just not evenly
Calculus (Cambridge/UK)
Physics (Cambridge/UK) Job Creator/Sustainer distributed.”
Computer Science (Columbia/NY)
Cultural Hospital
Microsoft (Harvard/WA) University
Conference Medical
Yahoo (Stanford/CA) College
Hotels Research
Google (Stanford/CA) K-12
Facebook (Harvard/CA)
“The best way to
Non-profits Worker
(professional)
Family
(household) predict the future
is to (inspire the next
generation of students
to) build it better.”
U-BEEs = University-Based Entrepreneurial Ecosystems, City Within City
48
49. Sustainability/Resilience
Innova3on:
Local-‐p
global-‐i
supply
chains
World as System of Systems
World (light blue - largest)
Nations (green - large)
States (dark blue - medium)
Cities (yellow - small)
Universities (red - smallest)
Developed Market Cities as System of Systems
- Transportation Supply Chain
Nations - Water Waste Recycling
( $20K GDP/Capita) - Food Products ((Nano)
- Energy Electricity
- Information/ICT Cloud (Info)
Emerging Market - Buildings Construction
- Retail Hospitality/Media Entertainment
Nations - Banking Finance
( $20K GDP/Capita) - Healthcare Family (Bio)
- Education Professions (Cogno)
- Government (City, State, Nation)
Nations: Innovation Opportunities
- GDP/Capita (level and growth rate)
- Energy/Capita (fossil and renewable)
49
50. Service
systems
en33es
learn
to
apply
knowledge
Learning
To Apply Knowledge
Do It Invent It
Exploitation Exploration
Run Transform Innovate
Operations L Internal Incremental
Maintenance
Copy It External Radical
Insurance Interaction Super-Radical
A Service Scientist becomes an entrepreneur!
March, J.G. (1991) Exploration and exploitation in organizational learning. Organizational Science. 2(1).71-87.
Sanford, L.S. (2006) Let go to grow: Escaping the commodity trap. Prentice Hall. New York, NY.
50
52. Innova3on
research
Service
marke0ng
RD
management
management
(1980-‐)
Focused
Product
based
industry
Service
industry
industry
New
Product
New
Service
Development
Research
Development
(NPD)
(NSD)
Innova3on
Service
professional
Technology
trajectory
source
trajectory
Product
and
process
Process
and
knowledge/
Outcomes
innova3on
organiza3onal
innova3on
53. Science
Technology
Social
Studies
Service
Science
1970 1980 1990 2000 2010
Public Public
acceptance Understanding of 1995 limitation of Deficit Model, Wynne
(PA) Science (PUS)
Technology Consensus conference
assessment Consensus conference with public participation
1972 trans-science, Weinberg 1994 Mode2, Gibbons
1999 World conference on science
1974 Framing, Goffman
1983 Local knowledge, Geertz 2003 Parameters in operationalization, Fujigaki
2004 Service Science, Innovate America
2004 Service Dominant Logic, Vargo, Lusch
2003 On Demand Innovation Services (IBM)
2005 Service Research (IBM)
2007-8 University curriculum, MEXT
2010- Service Research, JST/
RISTEX
53
54. Service
Science:
Conceptual
Framework
Ecology
(Populations Diversity)
Entities Interactions Outcomes
(Service Systems, both (Service Networks, (Value Changes, both
Individuals Institutions) link, nest, merge, divide) beneficial and non-beneficial)
Identity Value Proposition Governance Mechanism Reputation
(Aspirations Lifecycle/ (Offers Reconfigurations/ (Rules Constraints/ (Opportunities Variety/
History) Incentives, Penalties Risks) Incentives, Penalties Risks) History)
Access Rights Measures
(Relationships of Entities) (Rankings of Entities)
lose-win win-win prefer sustainable
lose-lose win-lose non-zero-sum
Resources Stakeholders outcomes,
(Competences, Roles in Processes, (Processes of Valuing, i.e., win-win
Specialized, Integrated/Holistic) Perspectives, Engagement)
• Resources:
People,
Organiza3ons,
Technology,
Shared
Informa3on
• Resources:
Individuals,
Ins3tu3ons,
Infrastructure,
Informa3on
• Stakeholders:
Customers,
Providers,
Authori3es,
Compe3tors
• Measures:
Quality,
Produc3vity,
Compliance,
Sustainable
Innova3on
• Access
Rights:
Own,
Lease,
Shared,
Privileged
Spohrer, JC (2011) On looking into Vargo and Lusch's concept of generic actors in markets, or
“It's all B2B …and beyond!” Industrial Marketing Management, 40(2), 199–201.
54
55. Knowledge
crea3on
mode:
Gibbons,
et
al.
1994)
Some
characteris3cs
of
Mode
1
and
Mode
2
research
ac3vi3es
Ref:
p3-‐14,
the
new
produc3on
of
knowledge
Mode 1 Mode 2
Problem are set and solved in a Knowledge is carried out in a context
context governed by the largely of application
academic interests of a specific Transdisciplinary
community Heterogeneity
Disciplinary
Heterarchical, organizational diversity
Homogeneity and transient
Hierarchical and preserve More socially accountable and
Less socially accountable and reflexive
reflexive Quality is determined by a wider set
Quality is determined essentially of criteria which refracts the
through peer review judgments on a broadening social composition of the
disciplinary basis review system
Knowledge creation done by a person Exploitation of knowledge requires
participation in its generation.
55
56. Defini3ons
of
Services
• Deed,
act,
or
performance
(Berry,
1980)
• An
ac3vity
or
series
of
ac3vi3es…
provided
as
solu3on
to
customer
problems
(Gronroos,
1990)
• Deeds,
processes,
performances
(Zeithaml
Bitner,
1996)
• All
economic
ac3vi3es
whose
output
is
not
physical
product
or
construc3on
(Quinn,
James
Brian
1992
Intelligent
Enterprise:
A
Knowledge
and
Service
Based
Paradigm
for
Industry
Free
Press)
• A
change
in
condi3on
or
state
of
an
economic
en3ty
(or
thing)
caused
by
another
(Hill,
1977)
• Intangible
and
perishable…
created
and
used
simultaneously
(Sasser
et
al,
1978)
• A
3me-‐perishable,
intangible
experience
performed
for
a
customer
ac3ng
in
the
role
of
co-‐producer
(Fitzsimmons,
2001)
• Services
are
defined
as
acts,
deeds,
performances,
or
efforts,
which
have
different
characteris3cs
from
goods
defined
as
physical
products,
such
as
devices,
materials,
objects
or
things
(Berry
1980,
Zeithmal
Bitner
1996,
Brian
et
al
1987)
57. Applicability
of
“Unique
Characteris3cs
of
Services”
to
Different
Types
of
Services
Service Category Involving
Physical Acts Physical Acts Nonphysical Processing
to Customers’ to Owned Acts to of Information
Bodies Objects Customers’
Minds
Intangibility Misleading Misleading Yes Yes
Heterogeneity Numerous Numerous Numerous
Yes exceptions exceptions
exceptions
Inseparability of
Only when
production and Many
Yes No performance is
consumption delivered “live” exceptions
Perishability –
cannot be Yes Yes Numerous Many
inventoried after exceptions exceptions
production
Ref: Principles of Service Marketing and Management by Christopher H. Lovelock
58. Three
Broad
Op3ons
(Lovelock)
1. Declare
victory:
Integrate
services
and
goods
marke3ng,
with
services
as
dominant
logic
(Vargo
Lusch,
Jan
2004)
– “Everybody
is
in
service”
Levip
(1972)
– Emphasize
“service”
not
“services”
(Rust
1998)
2. Look
for
alterna3ve
paradigms
3. Discard
services
as
a
general
category
and
get
scholars
to
focus
on
specific
service
subfields,
e.g.:
– High
contact
services
involving
interac3ons
with
personnel
– Low
contact
services
involving
self-‐service
with
machines,
websites,
etc.
59. Service
Dominant
Logic
Goods-dominant (G-D) logic
Service-dominant (S-D) logic
Making something (goods or services) Assisting customers in their own
value-creation processes
Value as produced Value as co-created
Customers as isolated entities Customers in context of their own
networks
Firm resources primarily as operand Firm resources primarily as operant
Customers as targets Customer as resources
Primacy of efficiency Efficiency through effectiveness
Ref: Stephen L. Vargo, Robert F. Lusch, “Evolving to a New Dominant Logic for Marketing”, Journal of Marketing, 68,
January, 2004, 1-17.
59
60. “On
Value
and
Value
co-‐crea3on:
A
service
systems
and
service
logic
perspec3ve”
by
S.
Vargo,
P.
Maglio,
M.
Akaka
• Service
is
the
applica3on
of
competences
(knowledge
and
skills)
by
one
en3ty
for
the
benefit
of
another
• Service
systems
is
value-‐crea3on
configura3ons
(an
arrangement
of
resources
connected
to
other
systems
by
value
proposi3ons)
• Service
science
is
the
study
of
service
systems
and
of
the
co-‐
crea3on
of
value
within
complex
constella3ons
of
integrated
resources
60
61. S3FIRE:
Research
clusters
and
Service
science
related
disciplines
Business
Organiza0on
Informa0on
Creative
Service Management
service
Agriculture
water
Value co-
Basic Service creation and
system
value co-
Theory
creation
support
Service
methods
model
oriented
Service Design crowds
Value latency
Service design
service
methods tools
Altruistic Service Engineering
mechanism
Communication
People
innovation by voice
Technology
A Type
B Type
61
Ref:
“Succeeding
through
service
innova3on”
hpp://www.ifm.eng.cam.ac.uk/ssme/
62. Innova3on
for
Service
Space
Communica3on
by
voice
tweets
in
nursing
and
caring
:
Naoshi
Uchihira
• Objec3ves:
– Develop
hands-‐
free
interac3on
for
behavioral
services
through
the
fusion
of
voice
and
murmuring
– Create
behavioral
service
design
methodology
combining
the
fields
of
service
(IT,
health,
Social)
62
Japan
Science
and
Technology/RISTEX
12.5.31
63. S3FIRE:
Research
approach
x
Industry
Industry area
Energy
Food/ Retail/ Educati Cross
Transpor Wat / Financ Healthc
Produc IT
City
Hospita on/ Public
industr
t/ SCM
er
Environ e
are
ts
lity
Work
y
ment
Value latency Service
service
value co-
Basic
theory
creation
Altruistic model
mechanism
Creative
Methods service
/ Large Service Systems Typical Services
Technol Value co-
Service design creation and
ogy
methods tools
support
Technology methods
Agriculture Service Communication
Technol
water oriented innovation by voice
ogy
system
crowds
A Type
B Type
63
64. Innova3on
model
Open Open
Innova3on
User Innovation (Hippel,
(Chesbrough,
2003)
1988)
Company
Chain-linked model
(Kline, 1986)
Quasi-Open
Gate keeper (Allen,
1977)
Closed
Liner model (Bush, Market pull
1946) (1960s)
Science
Society
Knowledge source
64
65. Social
Knowledge： Nowotny,
et
al,
2001
• Boundary
Knowledge
between
based
on
scien3fic
consensus
and
social
consensus
• Including
“Local
Knowledge”
Science Society
Scientific Knowledge
Local Knowledge
Based on scientific consensus
Based on social consensus
Under artificial lab environment
Under field environment
Artificial selection of parameters
Parameter selection from field viewpoints
Uncertain, risk involved
Diversity from human viewpoints
Including value decision, design
65
66. Innova3on
model
Social Knowledge (2001)
Open Open
Innova3on
User Innovation (Hippel,
(Chesbrough,
2003)
1988)
Company Service Innovation Model
Chain-linked model
(Kline, 1986)
Quasi-Open
Gate keeper (Allen,
1977) Technology Assessment (1960s)
Trans-Science (1972)
RD based
Closed
Liner model (Bush, Market pull
1946) (1960s)
Science
Society
Knowledge source
66
