perspectives on triple helix
TRANSCRIPT
Perspectives on Triple Helix
Fred Phillips DISC 2013, Daegu
Gen
eral
Info
rmat
ics
LLC
Agenda1. 3-Helix as a meso-level notion
– Epicycle in a grander tech-psych-inst cycle
2. Speed (differentials) as high-level system metric
– Roles of buffering institutions and ICT– Need for smart engagement
3. Applying 3-helix in the developing world
4. SUNY Korea’s joint TS/CS research
3-Helix papers published in Technological Forecasting &
Social Change• Wilfred Dolfsma, Loet Leydesdorff “Lock-in and break-out from
technological trajectories: Modeling and policy implications,” 76( 7), Sept. 2009, 932-941.
• Raul Gouvea, Sul Kassicieh, M.J.R. Montoya “Using the quadruple helix to design strategies for the green economy,” 80(2), Feb. 2013, 221-230.
• Øivind Strand, Loet Leydesdorff “Where is synergy indicated in the Norwegian innovation system? Triple-Helix relations among technology, organization, and geography,” 80(3), Mar. 2013, 471-484.
• Inga A. Ivanova, Loet Leydesdorff “Rotational symmetry and the transformation of innovation systems in a Triple Helix of university–industry–government relations,” In Press, Corrected Proof, Available online 19 Sept. 2013.
In D.S. Oh & F. Phillips (Eds), Technopolis: Best Practices for Science and Technology Cities (Springer, 2014)• E. Becker, B. Burger and T. Hülsmann,
“Regional Innovation and Cooperation among Industries, Universities, R&D Institutes, and Governments”
• F. Phillips, S. Alarakhia and P. Limprayoon,“The Triple Helix: International Cases and Critical Summary”
• José Alberto Sampaio Aranha, “Arrangement of Actors in the Triple Helix Innovation”
IC2 Model• Preceded 3-helix by several years• But only parts were made mathematical (Bard et al)
Academia Industry Government
Community Talent Technology Capital Know-How
Market Needs
Value-Added Economic Development
The math of Academic-Government-Industry
dynamics is interesting, but...
It is just part of a bigger picture.
The cycle of innovation and change: Lab to society & back again
TechnologicalInnovation
New ways to organize (Public & private)
New ways of producing and usingproducts & services
New Products& Services
New desires& dreams
New ways toInteract socially
Note how thisschema extendsEverett Rogers’
more linear model.
We might think all the elements move together in an orderly way.
Technological Change
OrganizationalChange
Psychological Change
Institutional Change
Social Needs
But in a free-market economy, they do not.
• They continually engage and disengage.
• Sometimes they move each other only by friction.
• 90% of MOT and Tech Policy problems stem from the differing speeds of the 3 sectors.
Example: Transportation
• Mobile-web rideshare services– Gain VC investment– Start operations– Get shut down by city
governments trying to regulate them under old taxi rules.
• Institutions have changed slower than technology and social demand.
Example: Health
• An elderly person dies because he was too proud to wear– A medical bracelet– or– An emergency signaller.
• Psychology has changed slower than technology.
Example: Software
• Record companies and publishers– Sue student MP3 pirates– Develop DRP software that further alienates
customers– Can’t adapt away from paper and CD
publishing.• Business organizations change more
slowly than technology and social demand.
Example: More and more often, social/institutional change outpaces
tech change - or will do so soon.• In most of the world, an excess of funds
is chasing too few growth investment opportunities.
• Fewer US companies are making IPOs.• Small-government activists rail
indiscriminately against direct government monetary support for new technologies.
See Phillips (2011).
This can be good.
• Individual creativity may bloom.
• Mistakes... – Can be undone
efficiently.– Don’t necessarily infect
the whole system.
It (disengagement)can be bad.
• Alienation• Lack of coordination and cooperation• Little institutional or organizational
creativity• Waste and pollution• Lives lost
Speed as the system metric• Really, speed
differentials among the sectors.
• A “clutch” and “transmission” are needed.
• The question is less how to engage, but rather, when.
• The key is not engagement per se, but smart (well-timed) engagement.
Not bridging organizations, but buffering organizations
• Civic groups• Workforce training programs• Economic development agencies• Technology brokers• Open innovation integrators• Accountancies • Industry associations• NGOs
• Incubators• Law firms• Venture capital• TTOs
The IC2 Model partially captured this.
3-Helix as meso-level construct: An epicycle within the Technology-
Psychology-Institutional dynamic
(3-Helix)
• Macro: Tech-Psych-Inst• Meso: Aca-Gov-Indus
– “Triple Helix”• Micro:
– Dynamics within people and within organizations;
– Technology life cycles• The buffering institutions
span all 3 levels.
Tech
Psych
Inst
Tech
PsychInst
What causes TOPI* disengagement?*Technological-Organizational-Psychological-
Institutional• Bad marketing, bad market research • Mistrust, bad service• Technology inaccessible to underserved
populations• Competition among de facto standards
(e.g., VHS vs Beta)• Lack of vision• Poor design of information &
communication products and programs.
“Engaging” doesn’t mean “attractive nuisance.”
Intrusive ‘engagement’
Updatethis app!
Marketing guru Geoffrey Moore says,
• “People have disengaged, for ... self-preservation.”
– With “consequences for consumer and brand marketing,
– “and long-term implications for education, health care, citizen participation, and workforce involvement.
• “So engagement is rightfully going to be a big
investment theme.”
Moore: Engagement is taking center stage in business.
• Off-line retailers are using digital interactions/devices in their in-
store experiences. – Example: Starbucks.
• “Social marketing foster[s] engagement around topics that ...
reflect well upon the sponsor.” – Example: Sephora.
• “Big data analytics drive communications that can break through the wall of detachment.” – Example: Obama campaign 2012.
Moore is saying• Advertising used to be like
this.– Annoying! Consumers
disengaged.• Now with social media,
mobile web, Yelp.com,– Consumers share product
reviews & complaints.– Advertisers have to treat
consumers more gently.– To make us want to continually
re-engage.• Engaging doesn’t mean
shouting.
ICT for an Intelligently Engaged Society?
What kinds of IT fosterpositive, voluntary
engagement? Why?
What kinds of IT discourageit? Why?
People are proud to participate electronically.
• Fighting crime– Zapruder film; Rodney King videos
• Supporting favorite businesses, authors– Amazon reviews
• For post-disaster aid– Crowd-mapping of post-earthquake Haiti
• Crowd-funding research projects and entrepreneurs
• Though there are abuses.
Source: Ganti et al, Mobile Crowdsensing: Current State and
Future Challenges.
Micro Level: Workforce Engagement
• Definition: The measure of whether employees merely do the minimum required of them, versus proactively driving innovation and new value for the organization.
• Thus, engagement – “can only ever be partially accounted for by
deploying the latest new collaborative technology, – “and probably significantly less than many of its
proponents would have you believe.”
Source: Hinchcliffe
Current state of worker engagement
ICT for engagement? Summary
• ICT alone cannot create/sustain engagement.– Human intervention, via buffering institutions, can achieve
ICT-aided engagement.
• ICT, especially sensing and crowdsourcing, may assist in deciding when to engage.– Thus achieving smart engagement.
• This applies to all 3 levels (macro, meso, micro) of our multi-level Technology & Society diagram.
For many countries where central government direction is
the norm, 3-helix thinking is premature.
• Indonesia, Mongolia• USA: Industry lobbying government
presents a slightly different problem...
Big man little man game
In sum, the problem is not dis-engagement, but mis-engagement
among governments, people, organizations and products, due to:
• Speed differentials (i.e., poor timing)• Lack of vision• Poor design of information & communication products and
programs.– Lack of feedback– Excess complexity, leading to slow comprehension and adoption– Excess technology push (solutions without problems)– Excess demand pull (unrealistic expectations)– Other factors
SUNY Korea’s research agenda• Combine social science and computer science...• To find principles of IT design that more quickly lead
to engagement that is...– Well-timed– Smart– Satisfying
• Among– Individuals – Businesses– Government institutions – Technology developers
• With secure applications in several techno-policy domains (health, energy, etc.).
Some Implications
• For IT: Meeting users halfway• For managers: Engagement plans for
each constituency• For theorists:
– Modeling the moderating effect of buffering institutions
– Impact of coalitions on the 3-helix dynamic
The math of Academic-Government-Industry
dynamics is interesting, but...
It is just part of a bigger picture.
An aside: Spatializing an innovation
diffusion modelF. Phillips, On S-curves and Tipping Points. Tech.
Forecasting & Social Change, 74(6), July 2007, 715-730.
Alan M. Turing, The chemical basis of morpho-genesis. Philosophical Transactions of the Royal Society of London. B 327, 37–72 (1952)
http://www.cgjennings.ca/toybox/turingmorph/
References• http://davidsasaki.name/2013/01/beyond-technology-for-transparency/ • A. Charnes, S. Littlechild and S. Sorensen, “Core-stem Solutions of N-
person Essential Games.” Socio-Econ. Plan. Sci. Vol. I, pp. 649-660 (1973).
• David Watson The Engaged University. Routledge, 2013.• Dion Hinchcliffe, “Does technology improve employee engagement?”
Enterprise Web 2.0, Nov. 5, 2013. http://www.zdnet.com/does-technology-improve-employee-engagement-7000021695/
• Jonathan Bard, Boaz Golany and Fred Phillips, “Bubble Planning and the Mathematics of Consortia.” Third International Conference on Technology Policy and Innovation, Austin, Texas, September, 1999.
• F. Phillips, The state of technological and social change: Impressions. Technological Forecasting & SocialChange. 78(6), July 2011, 1072-1078.
