morphological analysis for complex futures
TRANSCRIPT
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A Morphological Analysis Tool for Complex Future-Oriented Scenario Research
HOW MANY SOLUTIONS?
RSD5 Symposium 13th – 15th October 2016, TorontoMehdi Mozuni - Wolfgang Jonas
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?possible alternatives to the cruising business model in a 2030 perspective
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CRUISING BUSINNES MODEL
MEGA TRENDS
GENERATION OF NOVEL FUTURE SERVICE CONCEPTS
2030 Perspective
Through
Domain of Service Design
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?
HOW IT WILL PROBABLY LOOK LIKE?
HOW IT COULD LOOK LIKE?
PROGNOSIS
PROJECTION
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Multidimensionality
non-present user/ testing platform (2030 perspective)
Constraints are not determined (technology advances)
Need for recalculation of design process (changing analytical base)
CHARACTERISTICS OF OUR PROBLEM SPACE
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“The ever-changing dimensions of such research cases and their inter-relations make it very difficult to justify influence factors upon which the projection is made! “
(Tom Ritchey 2011)
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What is
GENERAL MORPHOLOGICAL ANALYSIS (GMA)?
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PARAMETERS DEFINING THE BUSINESS MODEL
A. Business expansion bias (exclusive transport services)A1. onboard hospitality and entertainmentA2. onboard/onshore real estate investing A3. on-shore service logisticA4. no on-board involvement (limited to transportation)
B. Mobility performance (average vessel speed within a 2 weeks sailing)B1. very slow or immobile (0 -5 knots)B2. slower (12 ± 2 knots)B3. same speed (20 ±2 Knots)
C. Ecologic factor emissions/energy efficiency (Passenger-day)C1. Status-quo(worse than on-shores)169-340kgC2. equal with on-shoreC3. very energy efficient(better ecologic factor than on-shore
D. Average capacity (capacity of crews and passengers per ship)D1. highly decrease (CPS≤150)D2. no change(CPS ~ 2000)D3. highly increase(15000≤ CPS)
E. Vessel ownership (CL Pre-investment share for 1000 Passenger)E1. CL entirely(m$150-250/1000p)E2. CL only operation(m$5≤/1000p)E3. CL partially Owner(m$ 5-150/1000p)
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r o w
s
Column A Column B Column C Column D Column E Column F Column G ColumnH Column I Column J
Bu
siness
Mo
del
Bia
sing
Ship Attributes Megatrends
Mobility
perfo
rman
ce
Eco
logic F
actors
averag
e capacity
CL
investm
ent sh
are
emerg
e of
cheap
renew
able en
ergy
dom
inan
t
one-p
erson fam
ilies
fall of
work
/ leisure sep
aration
hig
h lev
el
eco-to
urism
trend
fall of m
iddle class in
Euro
pe
( shift to
wealth
y ch
ina)
1
Onboard Hospitality and
Entertainment (OHE)
(status quo)
predominantly
immobile
Minus (status
quo)CPS≤150
m$150-
250/1000p
(status quo)
occurs occurs occurs occurs occurs
2Condominium/
Residential Model (CM)avg 15 ± 2 knots Neutral
CPS ~ 3000
(status quo)m$5≤/1000p
doesn't
occur
doesn't
occur
doesn't
occur
doesn't
occur
doesn't
occur
3Shore to Shore Floating
Services (SSFS)
avg 20 ±2
Knots (status
quo)
Plus 15000≤ CPS m$ 5-150/1000p
4Limited Onboard
Involvement (LOI)avg ≥ 35 knots
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Cross Consistency Analysis(CCA)- Carma
engine
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STATUS QUO
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What is the contribution of GMA to a design research process?
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A P S
Human Innovation
Human Inquiry
Human Assessment
GMA Aided idea generation
Improved human assessment
GMA
Conventional Design Practice
GMA Supported Design Practice
GMA
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1 Systemizing the arbitrary step of projection
2 Narrating the attributes of a possible service
3 Ranking the ideas
4 Modifiable and rearrangeable modeling
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GMA CONSTRAINTS
Limited calculable number of parameters and their values
Determining the extent and severity of external influence factors
Determining lowest and highest threshold of values
Judging during CCA step
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“This process represents two strangely superimposed (and what might seem to be mentally contradictory) tasks:
on the one hand, of identifying combinations of attributes which are seen to be logically impossible or empirically implausible – and discarding them;
and on the other hand, of keeping one’s mind open for the discovery of strange and novel combinations that we may not hitherto have imagined.”
(Álvarez & Ritchey 2015)
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INTERACTIVE ONLINE DELPHI SURVEY
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Benefits of Delphi Integration into GMA
Strengthening the diversity of expertise
Integrating decision-makers (stakeholders) into the service generation process
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Multiple driver “parameter activity check” PAC analysed by Carma engine
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© 2016 Wolfgang Jonas, Mehdi Mozuni –Institute of Transportation Design, Braunschweig Germany
[email protected]@hbk-bs.de
special thanks to Gunilla and Tom Ritchey for their support and contribution.
THANK YOU