Presentation at ICServ 2013.

1. Designing Methodology for
Innovative Service Systems
Hideyuki Nakashima (Future University Hakodate)
Haruyuki Fujii (Tokyo Institute of Technology)
Masaki Suwa (Keio University)

2. GENERALIZED DEFINITION OF
SERVICE

3. Our Definition of Service
• “X service” = Provision and
Utilization of X
-This definition captures “co-
creation of value”

4. Example
• transportation service
- provision and utilization of a
transportation system
• vehicles
• operation (software systems)
• infrastructure
• operators
• design of the whole system

5. Other Services
• food/drink systems
- providing food (physical object) alone is not service
• accommodation systems
• communication/postal systems
• meeting/conference systems
• information systems
- search, translation etc.
• education systems
• entertainment systems
• medical systems
• administration/governance systems

6. GENERALIZED DEFINITION OF
DESIGN

7. Design
• Definition: construction of a new system that has
some preferred function or feature
• Since design is manipulation of concept, meta-design,
design of design, is also important
• Design of a type
- Designing a new type of objects that did not exist or were not
thought about before
• Design of individual entities
- once a design method of a type is known, then there can be a
procedural method to design one instance of the type

8. Herbert Simon:
The Sciences of the Artificial
– 1st
edition 1969
– 2nd
edition 1981
– 3rd
edition 1996
• Everyone designs who
devises courses of
action aimed at changing
existing situations into
preferred ones.

9. Education Policy of FUN Design
EPFD 2011
11

10. FNS Loop for Synthesis
• future noema [Concept]
- target design
• generation [action: C→P]
- implementation
• noesis [Physical
(system/object)]
- outcome
• interaction [action: P→P]
- unpredictable phenomena
• analysis [action: P→C]
- scientific analysis
• current noema [Concept]
- description of noesis
• scripting [action: C→C]
- re-design

11. Service (Provision and Utilization) Loop
Implicit service
Latent function
Explicit service

12. Comparison with Ueda’s Class III

13. Comparison with Ueda’s Class II

14. Comparison with Ueda’s Class I

15. Smart city hakodate
Partially supported by JST program:

16. Provision and utilization
Analysis
Design
Simplified Service Loop

17. Service at Hakodate
Modeling by MA
Simulation
Design with MA
Simulation
Ristex Service Loop

18. Person trip research Bus simulations
SAVS operation test SAVS simulation
SAVS small size field-
test
FUN AIST
SAVS system design
SAVS medium size
field-test
SAVS full operation
restaurantsrestaurants
shopsshops
tourismtourism
1st
Cycle
2nd
cycle
3rd
cycle
NITECH
PersonPerson
triptrip
simula-simula-
tiontion
PersonPerson
triptrip
simula-simula-
tiontion
Ristex target line
hospitalshospitals
Oct 2013
Ristex project designed as Service Loop

19. Smart Access Vehicle System
Traditional system ：
Bus and taxi are separated
Location and routeLocation and route
management withmanagement with
GPSGPS
Which ？
Bus: cheap but slow
Taxi: fast but expensive
Proposed systemProposed system （（ SAVS):SAVS):
Computer selects the best vehicleComputer selects the best vehicle

20. Unification of Services through Transportation
SAVSSAVS

21. SAVS for All
• Users
– Less need of private cars
• Transportation Providers
– More efficient operation
– Much more customers
• Local Government
– No need to supply tax
24
Win-Win-Win

22. Local optimization vs. Global optimization
• Search for best routs is local optimization
• SAV system is globally optimum
• But the intermediate state (mixture) is worse
25
Traditional fixed-
route bus SAV
S
Best routing
U-shaped transition

23. Jumping over the U-curve (power of IT)
• Transition procedure must be within service loop
• SAV subsumes traditional bus/taxi systems as special cases
• Neutral evolution method
– Traditional fixed-route operation on SAV
• Optimum routing
• Occasional SAV operation test
– When ready, switch to the new operation
Traditional operation
on SAV system
SAV
operation
JUMP

24. Service Loop with MAS
1. Analysis: Observe person trip in Hakodate
2. Scripting: MAS of full scale Hakodate PT +
MAS of SAV system (vs. traditional)
3. Generation: Field test (Routing algorithm uses
the same MAS of 2)
Provider’s Noesis: SAV system
4. Back to 1.

25. 20 people for 4 months
Person-trip Observation

26. Field-test in Oct. 2013
FUNFUN
airportairport
traintrain
stationstation
test
area

27. GPS trace of a car

28. END
Q&A&D time