2. • Ludovic Dibiaggio
– Professor of economics & innovation @ SKEMA
– Director of the KTO research Center
– Member of OTESIA (artificial intelligence observatory)
• Contact
– Ludovic.dibiaggio@skema.edu
– Ph.: 04 93 95 45 04
2
Who am I?
3. The determinants and effects of (technological) innovation
and diffusion
– What are organizational conditions to facilitate
innovation?
– What is the effects of technical change on performance
– How technical change affect knowledge systems and
organization
How region can create a favorable environment to
innovation and entrepreneurship
Emergence and development of innovation ecosystems
(artificial intelligence ecosystems in the French Riviera)
3
What am I doing?
Research
Business transformation in a digital economy
(M1)
Innovation ecosystems (MSc Entrepreneurship)
Knowledge bases and innovation (PhD)
Research
4. Course material:
K2 platform: “BUSINESS TRANSFORMATION IN A DIGITAL ECONOMY”
Slides
Articles
Videos
Evaluation:
Class participation and group work delivery (10%)
Participation in TDs (10%)
Final Quiz (multiple choice questionnaire) 40%
Final report 40%
Course Objectives
1-5
5. Session 1 – Industry 4.0. Digital revolution or
digital transformation?
Session 2 – Artificial Intelligence: Implications for
Business (Francesca Melillo)
Session 3 – Artificial Intelligence: Implications for
Jobs (TD)
Session 4 – Creating and capturing value
Session 5 – Business models in a digital economy
(TD)
Session 6 – How disruptive digital technologies are?
Course Outline
1-6
Session 7– Digital Disruption (TD)
Session 8– Platform Revolution (1)
Session 9– Platform Revolution (1) (TD)
Session 10– Platform revolution (2): how do platforms
strategize to capture value
Session 11– Platform revolution (2): how do platforms
strategize to capture value (TD)
Session 12– Final project presentation (TD)
6. Case selection
Comparison between the platform-based business model of a disruptor and “a
pipeline” business model of an incumbent firm.
Group of 4/5
Evaluation:
A 10-minute presentation in class 12
Presentation document (sent 24 hours before class 12)
Final report
1-7
See more details in the final team project guideline on K2
7. 1-8
See more details in the final team project guideline on K2
WHAT DO WE EXPECT FROM YOU
1. To read the materials provided before class and bring comments and
questions (see next session on K2)
2. To attend class and actively participate in the TDs.
3. To be punctual and to respect the deadlines
4. To have academic honesty. We do not tolerate plagiarism.
10. Photo: AP/DPA - Source: Der Spiegel: Digitale Erleuchtung 2013
Papal election 2005
Is digitization a revolution?
11. Photo: AP/DPA - Source: Der Spiegel: Digitale Erleuchtung 2013
Papal election 2013
Is digitization a revolution?
12. Digital Revolution
How revolutionary the digital revolution is?
(John Zysman and Abraham Newman, 2006)
• IT does more than just change the costs of transportation, and
communication: it alters the manner in which economic value
is created, changes how international production is organized,
and reopens basic societal bargains struck around individual
liberty and economic rights.
• Digital revolution shakes up politics, creating new economic
and political winners and losers
13. Digital Revolution
How revolutionary the digital revolution is?
"The possibilities of the digital revolution must be put to good use.
That involves designing, developing and manufacturing our
products much more efficiently and much faster. In the aerospace
industry, we are currently seeing a level of competition that we
have never experienced before."
TOM ENDERS, CEO, Airbus Group
c
i
t
e
d
b
y
t
h
e
Roland Berger Strategy Consultants’ report (2015) "The digital
transformation of industry - How important is it? Who are the
winners? What must be done?”
14. Digital Revolution
Evolution of top 12 (market capitalization of US public firms)
Reshuffling the cards
Dominance of digital technology platforms
15. Digital Revolution
Average Company Lifespan on S&P 500 Index
Rolling 7-year average
Source: Innosight analysis based on public S&P 500 data sources.
Shrinking Life Spans
Average age at which US Public companies were delisted by year
Reshuffling the cards
16. Digital Revolution
Concentration and profitability
Markup
(baseline)
Source: DeLoecker and Eeckhout, 2017, Productivity Paradox Report
Entry and Exit rates and industry concentration (HHI)
in the USA for 1985-2015
Average industry markups across the world 1950- 2015
Source: Gutierez and Philippon, 2017 Productivity Paradox Report
Reshuffling the cards
17. 1st industrial revolution
Introduction of mechanical
production facilities (Water
and steam power)
First mechanical weaving
loom
First assembly line 1870
2nd industrial revolution
Introduction of mass
production (electrical energy)
3rd industrial revolution
Application of electronics
and IT to further automated
production
4th industrial revolution
Cyber-physical production
systems (CPPS), merging of
real and virtual worlds)
First programmable logic
control system 1969
Industry 4.0
Industry 3.0
Industry 2.0
Industry 1.0
What is a revolution?
Industry 4.0?
Degree
of
complexity
End of 18th century Beginning of 20th century Beginning of 1970s Today
Ford Model T
Hoe’s 6 cylinder steam rotary press
myJoghurt Virtual yoghurt production
Dave Emmett, and
the first PLC1971
18. lndustry 4.0 : digital transformation and the use
of exponential technologies - Deloitte
“…intelligent machines coordinating
independently-running production processes –
people, machines, and products are directly
connected with each other: the fourth industrial
revolution has begun.”
Federal Ministry for Economic Affairs and Energy
What is a revolution?
Industry 4.0
19. 1-21
Innovation is not a linear process: there
are waves of increasing and decreasing
rate of technical change.
Each wave is initiated and propelled by
General Purpose Technologes. Innovation rate
declines when the potential for exploitation is
drying.
What is a revolution?
Schumpeter’s business cycles
Growth Depression
Schumpeter popularized the term
"creative destruction"
“General Purpose Technology: technology
with a range of characteristics which makes it
particularly well placed to generate longer-
term productivity increases and economic
growth across a range of industries.”
(OECD, 2010)
Innovation waves can explain (business)
cycles of successive economic growth and
depression periods.
21. Source: Gordon (2012) NBER Working
Paper 18315
23
Economic impact
Secular stagnation
Gordon (2012) suggests
that unlike the steam
engine or the electricity,
the growth potential of
digital technology will be
limited and has almost
been exhausted.
The pessimistic view
23. A more optimistic view considers that the positive effects of digital
technologies are still to come.
Innovations are the result of “new combinations” of new or existing
knowledge, resources, equipment, etc.
“The carrying out of new combinations means, therefore, simply the
different employment of the economic system’s existing supplies of
productive means. ” (Schumpeter, 1934)
“In the early stages of development, growth is constrained by number of
potential new ideas, but later on it is constrained only by the ability to
process them.”
Weitzman (1998)
Digital => more
combination options =>
more complex solutions.
Increasing computer power
will generate more
combination capacity =>
Increasing innovative
output
The optimistic view
Economic impact
Secular stagnation
24. 0
1
10
100
1 000
10 000
100 000
1959 1964 1969 1974 1979 1984 1989 1994 1999
Log
Scale
(1996=1)
Computer Memory Logic
Relative prices of computers & semiconducteurrs
27
… at a decreasing price
more diffusion: exponentially
growing technology
Computation, memory, and bandwith
capacities double every 18-24 months
Moore’s Law
The optimistic view
Economic impact
25. Source: Roland Berger
Drivers of digitization
Digital technologies as general
purpose technologies
Digital transformation
Enabler applications
Propositions or end-user applications
The optimistic view
Economic impact
Secular stagnation
27. • Most sectors are affected by a slowdown in productivity growth
• ICT-creating and even more ICT-using sectors have benefited from a period of high productivity growth that
came to an end.
• At the firm level, there is a divergence in productivity between firms at the frontier and the rest.
• Simultaneously, concentration, market power, and profits are also increasing across most industries.
Why the factors boosting the productivity of superstar
firms are not diffusing, or not as quickly as in the past?
• Superstar firms increasingly are able
to erect barriers to entry?
• Or diffusion takes a long time, and we should expect
long lags between an initial innovation and its full
impact on aggregate productivity
Innate ability of superstar firms to appropriate intangible
capital and keep it from diffusing (Haskel andWestlake, 2017)
Economic impact
Diffusion
28. The optimistic view considers that the positive effects of digital
technologies are still to come.
Innovations are the result of “new combinations” of new or existing
knowledge, resources, equipment, etc.
“The carrying out of new combinations means, therefore, simply the
different employment of the economic system’s existing supplies of
productive means. ” (Schumpeter, 1934)
“In the early stages of development, growth is constrained by number of
potential new ideas, but later on it is constrained only by the ability to
process them.”
Weitzman (1998)
Digital => more
combination options =>
more complex solutions.
Increasing computer power
will generate more
combination capacity =>
Increasing innovative
output
Innovation as re-combinations
Economic impact
Diffusion
29. Source: Syverson, 2017, Productivity Paradox Report, Ian Goldin, Pantelis Koutroumpis, François Lafond,
Nils Rochowicz and Julian Win (2019), Oxford Martin School Programme on Technological and Economic
Change
Shares of total horsepower generated by the main
sources in U.S. manufacturing, 1869–1954.
Adoption of Electricity compared to IT
(bottom y-axis and top y-axis)
Source : B. Jovanovic and P.L. Rousseau (2005) in Handbook of
Economic Growth, Volume 1B. Edited by Philippe Aghion and
Steven N. Durlauf
Economic impact
Diffusion
Time matters
30. As a percentage of enterprises in each employment size class
Diffusion of selected ICT tools and activities in enterprises, OECD
countries, 2010 and 2016
Source: OECD Science, Technology and Industry Scoreboard 2017
StatLink: http://dx.doi.org/10.1787/888933619600
Economic impact
Diffusion
Time matters
31. Copyright (c) Erik Brynjolfsson and Andrew McAfee
34
Innovation has always
created jobs. Digital
technologies are less and
less job intensive
Digitization and employment
Productivity, growth and employment
32. Copyright (c) Erik Brynjolfsson and Andrew McAfee
Productivity
Private
employment
1947
=
100
35
For the first time in history,
productivity gain do not
create as much job as it
destroys.
Is it a temporary
phenomenon?
Digitization and employment
Productivity, growth and employment
34. The e-commerce sector has created
more jobs than brick-and-mortar has
lost
Source: Wall Street Journal, “Workers, fear not the Apocalypse”, 5 September 2017
E-commerce
Brick-and-mortar
E-commerce
Digitization and employment
Productivity, growth and employment
Creative destruction process
35. 38
Source: Autor, Katz and Kearney (2007, RESTAT) from
Nick Bloom presentation, Stanford 201O
There is evidence that
employment is polarizing since
the early 1990s – employment
growth strongest below 30th
percentile above the 75th
The polarization of employment
Digitization and employment
Polarization still matters
36. Job polarisation in major OECD economies, 2002-14 Percentage points
changes in employment shares by occupation
polarisation in skill demands
Source: OECD estimates based on EU-LFS, Japanese Labour Force Survey, BLS Current Population Survey.
Digitization and employment
Polarization still matters
37. Copyright (c) Erik Brynjolfsson and Andrew McAfee 40
Skill biased technical
change: Innovation is
complementary with
high skilled job but
substitute for low
skilled jobs.
Digitization and employment
Polarization still matters
38. Share of jobs at significant
risk (50-70%) and of high risk
(>70%) of automation, by
country, (%)
Source: OECD calculations based on PIAAC and Arntz, Gregory and Zierahn (2016), see:
https://www.oecd.org/employment/Automation-and-independent-work-in-a-digital-economy-2016.pdf
Digitization and employment
Substitution effect
39. similar polarization occurs in the UK, US and 9 other OECD
countries
Autor, Levy and Murnrane (2003)
Michaels, Natraj and van Reenen (2010)
repetitive tasks can be replaced by computers,
non-repetitive ones cannot
wages and employment in repetitive tasks have fallen
faster – leading to a polarization of employment: “lovely
and lousy jobs”
Digitization and employment
Polarization still matters
Reinforcing processes
Division of labour => specialization => increasing returns
