Disc 2015 program book 1102

• Welcome Message . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
05
• About DISC .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
06
• Program at a Glance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11
• Keynote Speeches .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17
• Poster Session . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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• Recorded Presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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• Round Table .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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• Panel Discussion 1 .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
91
• Panel Discussion 2 .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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117
127
139
151
• Memo .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Contents

5
October 29-31, 2015. Hotel Susung & Daegu Gyeongbuk Development Institute
Welcome Message
Dear DISC Members,
I am Han Woo Park, the President of the World Association
for Triple Helix & Future Strategy Studies. I would like to
sincerely invite and welcome keynote speakers, presenters
and participants for 2015 Daegu Gyeongbuk International
Social Network Conference (DISC). We are greatly honored
to have several Distinguished Social network Scholars
with us as well. They are very productive scholars around
world. This is such a precious and memorable moment for
us because your visit to our city, Daegu is at the juncture
of our society’s launching the new scholarly age. There is
no doubt that 2015 DISC will be the milestone for Big Data
and Social Network field here in Daegu. I hope you feel
comfortable and wish you had and unforgettable time at
the upcoming conference.
Thank you.
Full Professor Pr. Han Woo PARK,
BA-HUFS, MA-Seoul Nat’l Univ. PhD-SUNY Buffalo
The Chairman of DISC 2015
The President of World Association for Triple Helix & Future Strategy Studies

6
About DISC
DISC(Daegu Gyeongbuk International Social Network Conference) was founded in February 2013
in Daegu, South Korea. DISC and other events are always organized in collaboration with glocal
academic, private sector and public sector partners.
DISC (Daegu Gyeongbuk International Social Network Conference) has rapidly become the Asian
Hub conference on big-data and socio-innovation network area. DISC is aimed at pursuing the
continuous scholarly growth and building the university-industry-government relations.
Furthermore, this international conference of Daegu expects local development in a wide range of
areas in humanities/social sciences and their neighboring natural/engineering areas. The 2nd DISC
was successfully held in 2014 hosting more than 250 participants.
The DISC in 2013 and 2014 have produced several special issues, published by Quantity & Quality,
Technological Forecasting and Social Change and Journal of Contemporary Eastern Asia.
This year’s DISC is going to be held from October 29th to 31th in the historic Korean city of Daegu.
The conference theme is on big data and network-based future strategies.
We are inviting renowned scholars from all over the world. In addition, this year’s DISC will feature
the 2nd Korea- China Symposium on Big Data.
This is WATEF’s strategic step to reach out to the Chinese scientific community, which is becoming
increasingly visible with China’s uprising political and economic power.
With the rising profile of DISC on the global stage, as the organizer, we are hoping to expand our
reach and support network.
Therefore, I, along with my colleague at WATEF, sincerely invite you to consider attending DISC2015.
The scope and aims of the Daegu Gyeongbuk International Social Network Conference 2015
(DISC2015) are endorsed by INSNA (International Network for Social Network Analysis).

7
DISC 2015 Overview
DISC 2014 Overview
Theme
Maintheme:SocialNetwork>>BigData>>FutureForecasting>>Collaboration!
Special Theme: The 2nd Korea-China Big Data Conference on Research and Applications(제2회 한·중 빅데이터
컨퍼런스)
Dates October29(Thu)–31(Sat),2015
Venue
Hotel Susung, Daegu, Republic of KOREA, Daegu Gyeongbuk Development Institute, Daegu, Republic of KOREA
(호텔수성, 대구경북연구원)
Organized by
World Association For Triple Helix & Future Strategy Studies(세계트리플헬릭스미래전략학회), Y.U. Cyber Emotions
Research Center(영남대학교 사이버감성연구소), Y.U. BK21 Plus Project Team for “Global East Asian Cultural
Contents”(BK21플러스 글로컬동아시아문화콘텐츠 사업단), Korea Institute Science and Technology Information(KISTI)
(한국과학기술정보연구원), Gyeongbuk Techno Park(경북테크노파크), Korea Research Institute of Bioscience &
Biotechnology(한국생명공학연구원)
Sponsored by
Korea Tourism Organization(한국관광공사), Daegu Convention & Visitors Bureau(대구컨벤션관광뷰로), The
IMC(더아이엠씨), APISA, ARS PRAXIA, TBC Culture Foundation(TBC 문화재단), Gyeongsangbuk-Do(경상북도),
Social media research foundation, Rayworld(레이월드), INSNA(International Network for Social Network Analysis),
Journal of Contemporary Eastern Asia (JCEA), International Academy of Social Sciences(IASS), Mice Industry Research
Institute(마이스산업연구원), Daegu-Gyeongbuk Free Economic Zone Authority(대구경북경제자유구역청), Korea
Appraisal Board(한국감정원), Institute for Socio Technical Complex Systems(ISTCS), Daegu Gyeongbuk Development
Institute(대구경북연구원),HankookAD(한국애드)
Website http://www.watef.org
Theme Data as Social Culture : Networked Innovation and Government 3.0
Dates December 11(Thu.) ~ 13(Sat.), 2014
Venue Eldis Regent Hotel, Daegu, Korea / YeungNam Univ. (13th)
Organized by
- Asia Triple Helix Society
- Y.U. Cyber Emotions Research Center
- Y.U. BK21 Plus Project Team for“Glocal East Asian Cultural Contents”
- Korea Institute Science and Technology Information (KISTI)
Sponsored by
Korea Tourism Organization, Daegu Convention & Visitors Bureau, Korea Culture &
Tourism Institute(KCTI), The IMC, POSTECH, TREUM, ACADEMIC EBOOK CORPORATION
(ACADEPIA), Culture Plex, South-East
Asia Creative Economy Forum, Inside Solution, Dapoomeun Yukgaejang, Young IL
Engineering, The Yeongnamilbo, The Maeil Shinmun, TBC, Daegu Gyeongbuk Media Club
Website Asia Triple Helix Society (ATHS): http://asia-triplehelix.org

8
DISC 2013 Overview
Theme Knowledge Network Analysis in the Emerging Big Data Research
Dates 12(Thursday) to 14(Saturday) December. 2013
Venue Prince Hotel (12 - 13, December), Daegu Digital Industry promotion Agency(14, December)
Organized by
The Asia Triple Helix Society, Daegu Digital Industry promotion Agency, Daegu
Gyeongbuk Development Institute, CyberEmotions Research Center of YeungNam
University, Daegu Gyeongbuk Social Media Forum
Sponsored by
Daegu Convention and Visitors Bureau, The IMC, Treum, POSTECH, KAIST, Korea Tourism
Organization
Website Asia Triple Helix Society (ATHS): http://asia-triplehelix.org
DISC 2015 SNS
DISC 2015 Facebook : https://www.facebook.com/disckorea
DISC 2015 Hashtag : #disc#daegu #disc2015 #SNA #WATEF #Bigdata
DISC 2014 SNS
DISC 2014 Facebook : https://www.facebook.com/disckorea
DISC 2014 Twitter : https://twitter.com/DISC2014
DISC 2014 Hashtag : #disc @disc
DISC 2014 Wordpress : disckorea.wordpress.com
DISC 2014 App. : https://guidebook.com/g/disc2014
• DISC 2015 SNS
• DISC 2014 SNS
• DISC 2015 Papers - 38papers from 10 countries
• DISC 2014 Papers - 63 papers from 13 countries

9
• DISC 2015 The IMC Awardee
Author Title Co-Author
The 1st place
Kyujin Jung
(Tennessee State
University, USA)
Structural Effects of
Interorganizational Collaboration
Network on Disaster Resilience
-
The 2nd place
Harald Meier
(Digital Space Lab,
Germany)
Global Civil Society from Hyperlink
Perspective: Exploring the Online
Networks of International NGOs
-
The 3rd place
Sae OKURA
(University of
Tsukuba, Japan)
Analysis of the Policy Network for
the“Feed in Tariff Law”in Japan:
Evidence from the GEPON Survey
Leslie TKACH-KAWASAKI
(University of Tsukuba, Japan)
Yohei KOBASHI
(Waseda University, Japan)
Manuela HARTWIG
(Free University of Berlin)
Yutaka TSUJINAKA
(University of Tsukuba)
The 1st place
WayneWeiaiXu
(SUNY-Buffalo, U.S.A)
The Networked Creativity in
the Censored Web 2.0
MiaoFeng
(Univ. of Illinois at Chicago, U.S.A)
The 3rd place
Daegon Cho(조대곤)
(POSTECH, Korea)
An Empirical Analysis on
Smartphone Diffusions
-
Marko M. Skoric
(City Univ. of Hong
Kong, Hong Kong
S.A.R.)
The Role of Social Network
Sites and Mobile Phones in
Promoting the Acquisition of
Job-related Information, Job
Mobility and Entrepreneurship
JiPan (Nan yangTechnological Univ.,
Singapore)
WayneFu (Nan yangTechnological
Univ., Singapore)
ClariceSim (Nan yangTechnological
Univ., Singapore)
YongJinPark(Howard Univ., USA)
The 1st place
KeJiang
(University of
California, Davis)
International Student Flows from
a Macro Perspective : A Network
Analysis
-
The 2nd place
KyujinJung
(University of North
Texas)
Who Leads Nonprofit Advo cacy
Through Social Media :
S o m e E v i d e n c e f r o o m t h e
Australian marine Conservation
Society’s Twitter Networks
WonNo (Arizona State University)
JiWon Kim (University ofTexas at
Austin)

10
• The list of participants for 2 consecutive years :
• DISC 2015 Youth Convention Members :
• DISC 2015 Certificate of Appreciation :
Han Woo Park, Leslie M. Tkach-Kawasaki, Jana Diesner, Pieter E. Stek, Meeyoung Cha, Jang Hyun
Kim, Minho So, INYONG NAM, INHO CHO, Xanat Vargas Meza, Yon Soo Lim, Shin-Il Moon, Kyujin
Jung, Chung Joo Chung, Sungkyu Shaun Park, Woo-Sung Jung, HeyJeong An, kijun son, Chae Nam
Jeon, Wayne Weiai Xu, Ke Jiang, Leo Kim, Seong Eun Cho, Min-Woo Ahn, Hye-Jin Park, jiwon Park,
Daehyeon Nam, Kim In Yeob, Jiyoung Park, Hwang Sungsoo, Fred Phillips
Ji Eun Kang, Seung Dong Lee, Su Min Bae, Seok Joo Jeong, Ji Hyun Lee, Gwang Min Park
Na-Yeong Oh, Ye-eun Kang , Kyum-myung Kwak, Yeo-eun Kee , Sung-min Hong, In-sung Hwang
Ji youn No, Young hoon Kim, Da young Sung, So Yun Choi, Hye lim Kim
Min Ho So, Mi Kyung Lee, Marina van Geenhuizen, Fred Phillips, Pieter E. Stek, Daehyeon Nam
Leslie M. Tkach-Kawasaki, Hee Yoon Choi, Mee Young Cha, Jana Diesner, Woo-Sung Jung, Yoon Jae
Nam, Daegu Convention & Visitors Bureau, DEXCO
George Barnett, Hee Dae Kim, Jang Hyun Kim, Vladimir Batgelj, The IMC, Treum Company
• The list of participants for 3 consecutive years :
Han Woo Park, Leslie M. Tkach-Kawasaki, Pieter E. Stek, Jang Hyun Kim, Minho So, Kyujin Jung,
Chung Joo Chung, Woo-Sung Jung, kijun son, Chae Nam Jeon, Wayne Weiai Xu, Ke Jiang, Leo Kim,
Daehyeon Nam, Jiyoung Park, Fred Phillips

11
Program at a Glance
THEME : Social Network >> Big Data >> Future forecasting >> Collaboration
Date Day1(10/29) Thursday Day2(10/30) Friday
Day3(10/31)
Saturday
Time Sky Hall Honeymoon Hall Sky Hall Honeymoon Hall
Daegu Gyeongbuk
Development Institute
09:00-17:00 Registration (13:00 OPEN) Registration Registration
09:00-09:20
Pre - Conference Tour
Opening Session
WorkshopⅠ
Textom Mining
Analysis
Dr. Kim Chan Woo
09:20-09:40 The 2nd
Korea-China
Big Data Conference
Keynote Speech
Keynote Speech1
Leo Kim
09:40-10:00
10:00-10:20 The 2nd
Korea-China
Big Data Conference
1. KRIBB(Korea
Research Institute
of Bioscienceand
Biotechnology)
Session
10:20-10:40 Coffee & Tea Break
10:40-11:00
Panel Discussion4
Triple Helix
Approaches
11:00-11:20
11:20-11:40
11:40-12:00
12:00-13:00 Luncheon
13:00-13:20 Registration
The 2nd
Korea-China
Big Data Conference
2. KADS
(Korean Association
of Data Science)
Session
Keynote Speech2
Marinavan
Geenhuizen
Workshop2
Social Network
Analysis
(NodeXL)
Marc Smith
13:20-13:40 Recorded
Presentation
Poster Session
13:40-14:00
14:00-14:20
Panel Discussion1
Open Big Data
& Government3.0
Panel Discussion 5
Scientometrics &
Semantic Network
Analysis
14:20-14:40
14:40-15:00
15:00-15:20
15:20-15:40 Coffee & Tea Break Coffee & Tea Break
15:40-16:00 Round Table
Triple Future
Talk Series
Poster
Session Panel Discussion6
Media & Future
Society
16:00-16:20
The 2nd
Korea-China
Big Data
Conference
3. WATEF Session
Post-Conference
Visit(Optional)
16:20-16:40
Panel Discussion2
Policy & Network
Analysis
Panel Discussion3
Disaster, Crisis,
Organizations, &
Social Network
Analysis
16:40-17:00
17:00-17:20
General Assembly17:20-17:40
17:40-18:00
18:00~
Icebreaking Party
(Wine reception type)
Gala Dinner
(The IMC Award, WATEF Prize, Closing
Ceremony)

12
ConferenceProgram29–30October,2015/HotelSusung
Keynote Speeches
Poster Session
Recorded Presentation
Round Table. Triple future talk series
Topic No. Speaker Affiliation Title
Keynote Speech1 1 Leo Kim Ars Praxia
Flattening reflections on social categories: data
visualization and critical social analysis
Keynote Speech2 2
Marina van
Geenhuizen
Delft University of
Technology
Living labs as boundary spanners between knowledge
flows: in search of critical performance factors'
Topic No. Panels Affiliation Title
Poster
Session
1 Jongtaik Lee KISTI
Core technology and industry trend of probiotics under the system
with massive and worldwide social and environmental changes
Market growth potential analysis deciding to
enter LED lens compound market
Current competitive state analysis out of various data
regarding foreign and domestic markets in animal additive industry
4
Pan Pan
University of Science and
Technology of China
From Research to Industry:
Chinese Semantic
Network Analysis of Technological AchievementsTransformation
Junfei Yang
University of Science and
Technology of China
Ke Jiang
University of
California, Davis
5
Young Hoon
Lee
KEIT Within and across regional innovation system:
measuring the dynamics of regional innovation systems in Korea
YoungJun Kim Korea University
6
Heewon Cha Ewha Womans University
An Analysis of Korea Brand and KoreanWave Using Big Data
Yunna Rhee
Hankuk University of
Foreign Studies
Chung Joo
Chung
Kyungpook National
University
Recorded
Presentation
1
Otto F. von
Feigenblatt
Carlos Albizu University Racial Relations in the United States: A System in Flux
Round Table.
Triple future
talk series
Moderator: Ke Jiang(University of California)
Respondent : Marc Smith(Connected Action Consulting Group),
Leslie Tkach-Kawasaki(University of Tsukuba), Weiai Wayne Xu(Northeastern University)
1
Fred Philips Yuan Ze University Key Ideas from a 25-Year Collaboration at
Technological Forecasting & Social ChangeHal Linstone Portland State University

13
[DAY 1] October 29(Thu), 2015 / Hotel Susung
Panel 1.
Open Big Data &
Government3.0
Chair: IckKeun Oh(Keimyung University)
Discussants : JangHyun Kim(Sungkyunkwan University), Kyu Jin Jung(TennesseeState University),
HoYoung Yoon(University of Wisconsin-Madison)
1
Hyungwang Shin Yeungnam University Ego Network Analysis of United States
Healthcare Open-Data CompaniesHan Woo Park Yeungnam University
2
Srijana Acharya Yeungnam University Webometric Analysis of the Current
pen Data Trends in NepalHan Woo Park Yeungnam University
3
A-Reum Jang Yeungnam University Webometric Analysis of Open Data 500
Companies in the United States:
A Case of Lifestyle and Consumer CategoryHan Woo Park Yeungnam University
4
Miao Feng
University of Illinois at
Chicago Saying, Searching, and Selling:
Electronic Cigarettes on Social Media in China
Weiai Wayne Xu Northeastern University
Panel 2.
Policy & Network
Analysis
Chair : JaeHwan Park(Middlesex University)
Discussants : ChungJoo Chung(Kyungpook National University),
Ping Zhou(Zhejiang University), Yoon Jae Nam(Kyunghee University)
1
Sae Okura University of Tsukuba
Analysis of the Policy Network for the
“Feed in Tariff Law”in Japan:
Evidence from the GEPON Survey
Leslie Tkach-
Kawasaki
University of Tsukuba
Yohei Kobashi Waseda University
Manuela Hartwig Free University of Berlin
Yutaka Tsujinaka University of Tsukuba
2
Minju Yoo Sungkyunkwan University How Do Korean Telecommunication
Giants Manage and Perceive the Internet of
Things (IoT) through Social Media
and Commercial Videos?Jang Hyun Kim Sungkyunkwan University
3
Kang-Nyeon Lee Sungkyunkwan University Semantic Network Analysis of Debates
on Net Neutrality in Cyber SpaceJang Hyun Kim Sungkyunkwan University
4
Jiyoung Park Yeungnam University How does fractional counting affect
the structure of collaboration networks?
A case of publications indexed in 2013 SSCI
and A&HCI on East Asia
Loet Leydesdorff University of Amsterdam
Han Woo Park Yeungnam University
5
In Ho Cho Data & Beyond
Participation in Facebook groups:
How differently do we engage with group
members?
Kwang-Taek Roh Kyungil University
Ki Jun Son The IMC
JI Young Kim Yeungnam University

14
Panel 3.
Disaster, Crisis,
Organizations, &
Social Network
Analysis
Chair : Marc Smith(Connected Action Consulting Group)
Discussants : Ke Jiang(University of California, Davis), Weiai Wayne Xu (Northeastern University)
1 Kyujin Jung
Tennessee State
University
Structural Effects of Interorganizational
Collaboration Network on Disaster Resilience
2 Ho Young Yoon
University of
Wisconsin-Madison
If it had informed: (Un)openness of contagious
MERS disease information
3 Harald Meier Digital Space Lab
Global Civil Society from Hyperlink Perspective:
Exploring the Online Networks of International NGOs
4 Kyujin Jung
Tennessee State
University
Why so serious?: Stakeholders and bystanders of the
Volkswagen scandal on Facebook
[DAY 2] October 30(Fri), 2015 / Hotel Susung
Panel 4.
TripleHelix
Approaches
Chair : Fred Philips(YuanZe University)
Discussants : ‌Leslie Tkach-Kawasaki(University of Tsukuba),
Marc Smith (Connected Action Consulting Group)
1
Ping Zhou Zhejiang University
A comparative study of university-industry
collaborations in China and the USA
Robert Tijssen Leiden University
Loet Leydesdorff University of Amsterdam
2
Jae-Hwan Park Middlesex University
The Caching-Up Patterns of China-based
Pharmaceutical Industry:
Is it a Catching-up Trend in the Collaborative
Research Activities?
Jee-Yeon Choi University of Cambridge
Jinseok Kim
University of Illinois at
Urbana-Champaign
3
Jungwon Yoon Sogang University Development Patterns and Trends in the
Triple Helix Dynamics of the South Korea’s
Innovation System:
Based on the Collaboration Network Analysis
Joshua Sung woo Yang Yonsei University
4
Woo-Sung Jung
POSTECH
Complex network analysis on research
activity of public research institutionHyeonchae Yang
Panel 5.
Scientometrics
Semantic
Network
Analysis
Chair: Leo Kim (Ars Praxia)
Discussants : ‌Damien Spry (The University of Sydney), Jae Hwan Park (Middlesex University)
1 Pieter E. Stek
Delft University of
Technology
The Influence of International Knowledge Networks on the
Innovation Performance of Medical Devices Clusters:
A Bibliometrics Approach
2
Youngim Jung KISTI
Detecting Emerging ResearchTopics by
Utilizing Novel Big Data
Seonheui Choi KISTI
Jin-seop Shin KISTI
3
Gabjin Oh Chosun University
Patent Network Analysis Based on Citation
Ho Yong Kim Chosun University
4
Jiang Li ZhejiangUniversity
A vector for identifying “sleeping beauties”and
“flashes in the pan”in science
Chao Min Nanjing University
Jianjun Sun Nanjing University
5
Jean-Charles
Lamirel
University of
Strasbourg
Exploring the dynamics of scientific collections using
a new combination of approaches mixing graph
representation and feature selection

15
October 29-31, 2015. Hotel Susung Daegu Gyeongbuk Development Institute
Panel 6.
Media
Future
Society
Chair : Weiai Wayne Xu(Northeastern University)
Discussants : GabJin Oh(Chosun University), Pieter E. Stek(Delft University of Technology)
1
Damien Spry The University of Sydney A big data approach to news analysis –
Australia in Korean online news reportingTimothy Dwyer The University of Sydney
2
Ke Jiang University of California, Davis 20Years News Frames of Media Coverage of
Peace In the United States and China :
ASemantic Network AnalysisGeorge A. Barnett University of California, Davis
3 Sujin Choi Kookmin University
Audience polarization in actuality:
Explaining TV viewing pattern from network
analytic approach
4 Sungjoon Lee Cheongju University
A Rethink on Media Users in the context of
Web 2.0: A Case of Social Media
5
Karen Yooshim Huh Google Korea (Previously) The rise of MCN(Multi Channel Networks) :
The coming of the new digital
broadcasting ecosystem?Han Woo Park Yeungnam University
DISC 2015 Gala Dinner (만찬)
Workshop Program October 31(Sat), 2015 / Daegu Gyeongbuk Development Institute
1. Date : October 30(Friday), 2015, 18:00
2. Venue : ‌Hotel Susung, Sky Hall (Address: 106-7, Yonghak-ro, Suseong-gu, Daegu, Korea)
TEL. 1899-1001
3. Contents : The IMC Award, WATEF Prize, Closing Ceremony
4. Time Table
Time Contents Remark
18:00~18:05
Opening Ceremony
VIP
18:05~18:10 VIP
18:10~18:15
VIP Photo Time
18:15~18:20
18:20~18:50 The IMC Award, WATEF Prize
18:50~20:50 Gala Dinner Performance
- Fusion Korean Traditional Performing Arts
- Vocal Music
20:50~21:00 Closing Ceremony President Han Woo Park
Workshop topic Time Organizers Language
Workshop1
- Textom Mining Analysis
09:00 - 12:00
Dr. Kim Chan Woo
The IMC
Korean
Workshop2
- Social Network Analysis(Node XL)
13:00 - 16:00
Marc Smith
Connected Action Consulting Group
English

Keynote Speeches
2nd
day October 30 (Friday) / Honeymoon Hall, Susung Hotel
09:20 - 10:20 Flattening reflections on social categories: data visualization and critical social
analysis
Leo Kim, (CEO of Ars Praxia)
13:00 - 14:00 Living Labs as boundary-spanners between Triple Helix actors
Marina van Geenhuizen, ‌(Professor of Innovation and Innovation Policy, Faculty of
Technology, Policy and Management,TU Delft,The Netherlands)

18
Keynote Speaker 1
Leo Kim
Leo Kim is the CEO of Ars Praxia, a consulting company that specializes in social network and
semantic network analysis. His research interests lie at the interaction of actors, strategies,
narratives, and knowledge, especially in the public sphere of science and in developing the
method of semantic network analysis and big data processing for pragmatic applications. He has
also published articles related to these topics in a number of international journals.

19
Flattening reflections on social categories:
data visualization and critical social analysis
Leo Kim
CEO of Ars Praxia, South Korea
E-mail : leo.kim.praxis@gmail.com
Abstract
The agenda of social integration draws both significant attentions and concerns in South Korea.
However, the rise of cultural ultra-rights, exacerbating conflicts among government, industry and
labour reflect some impasses in social integration. Existing sociological categories turn out to be
vulnerable to identify and explain core concerns of actors that are not confined by existing category
of class or political ideology. A network approach to represent both convergent and divergent
concepts and variables across actors turn out to be crucial. This presentation reviews Bruno
Latour’s recent discussion of Gabriel Tard’s revitalized perspective and the relevance of new data
representation, and shows how it could be put forward by Ars Praxia’s approach of data analysis and
visualization tools.

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27

29

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Memo

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Keynote Speaker 2
Marina van Geenhuizen
(Professor of Innovation and Innovation Policy, Faculty of Technology, Policy
and Management, TU Delft, The Netherlands)
Dr. Marina van Geenhuizen is full professor in Innovation and Innovation Policy in Urban Economies in the
Faculty of Technology, Policy and Management at Delft University of Technology, The Netherlands, since 2007.
Her work in the past years deals with theory and practice of utilization of university knowledge and Triple
Helix issues, through business collaboration, spin-off firms’ growth, and Living labs, mainly in subject matter
of sustainable energy sources, transformation in the healthcare sector and ICT. Her research is also partly
on challenges of urban economic growth, the knowledge economy and the policymaking concerned. She
is (co)author of about 75 papers on these issues in refereed English journals, among others Technovation,
Technological Forecasting Social Change and Environment and Planning C, and she is principal editor of
seven international volumes, with two volumes currently as ‘work in progress’. In addition, she acts as reviewer
for the Netherlands Organization for Scientific Research for five years, and has been member of various local
and national advisory boards on innovation and urban development.
Stek, P. and Geenhuizen, M. van (2015) The Influence of International Research Interaction on National
Innovation Performance: A Bibliometric Approach, Technological Forecasting and Social Change (forthcoming).
- ‌Soetanto, D.P. and Geenhuizen, M. van (2015) Getting the right balance: university networks’ influence on
spin-offs’attraction of funding for innovation, Technovation, 36/47, 26-38.
- ‌Geenhuizen, M. van, S. Filippov and B. Enserink (2015) Cost Reduction as Major Driver in Traditional
Technology Business: Will Outsourcing Come to an End? Journal of Enterprise Transformation, 5 (1) 30-51.
- ‌Geenhuizen, M. van, and Ye, Q. (2014) Responsible innovators: open networks on the way to sustainability
transitions, Technological Forecasting Social Change, Sept. 2014, 28-40.
- ‌Geenhuizen, M. van (2013) From Ivory Tower to Living Lab. Accelerating the Use of University Knowledge.
Environment Planning C (Government Policy), 31, 1115-1132.
- ‌Geenhuizen, M. and D. Soetanto (2013) Benefit from Learning Networks in‘Open Innovation’: Spin-off Firms in
Contrasting Regions, European Planning Studies, 21, 666-682.
- ‌Geenhuizen, M. van, Schoonman, J. and A. Reijnders (2013) Diffusion of Solar Energy Use in Built Environment
and New Design, Canadian Journal of Civil Engineering, 8, 253-260.
Selected articles (reviewed):

35
Living Labs as boundary-spanners
betweenTriple `Helix actors
Marina van Geenhuizen
Professor of Innovation and Innovation Policy
Faculty of Technology, Policy and Management
TU Delft, The Netherlands
E-mail : M.S.vanGeenhuizen@tudelft.nl
Abstract
Living labs are an increasingly popular tool to enhance innovation. Many universities, companies
and cities in Europe are involved in Living labs to benefit from the input of user groups. Living labs
are conceived in this lecture as real-life environments (physical places) that include a network of
stakeholders, specifically a strong involvement of user-groups in co-creation activities aimed at
increasing user-value. Derived from the literature and four in-depth case studies of Living labs in
healthcare in Northwest Europe and Canada, a set of critical factors will be presented. We mention
as examples 1) an adequate user-group selection and involvement, specifically a rich interaction
and absorption of the results in the innovation process, and 2) a balanced involvement of relevant
stakeholders in terms of power, commitment and differentiation in roles. In the healthcare sector,
people-oriented Living labs differ from institution-oriented Living labs regarding these critical
factors. In addition, universities may take on different roles, in terms of strength of involvement,
domains and management tasks.

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47

Poster Session
1st
day October 29 (Thursday) / Honeymoon Hall, Susung Hotel
13:20 - 16:20 1 Core technology and industry trend of probiotics under the system with
massive and worldwide social and environmental changes
Jongtaik Lee, (KISTI, South Korea)
2 Market growth potential analysis deciding to enter LED lens compound
market
3 Current competitive state analysis out of various data regarding foreign and
domestic markets in animal additive industry
4 From Research to Industry: Chinese Semantic Network Analysis of
Technological Achievements Transformation
Pan Pan (University of Science andTechnology of China)
JunfeiYang (University of Science andTechnology of China)
Ke Jiang (University of California, Davis)
5 Within and across regional innovation system: measuring the dynamics of
regional innovation systems in Korea
Young Hoon Lee (KEIT, South Korea)
YoungJun Kim (Korea University, South Korea)
6 An Analysis of Korea Brand and Korean Wave Using Big Data
Heewon Cha (EwhaWomans University, South Korea)
Yunna Rhee (Hankuk University of Foreign Studies, South Korea)
Chung Joo Chung (Kyungpook National University, South Korea)

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Poster 1
Jongtaik Lee
(KISTI, South Korea)
- ‌Purdue University, West Lafayette, IN (August 1998 – January 2003)
Ph. D., Inorganic Chemistry
- ‌Sogang University, Seoul, Korea (February 1992 – February 1997)
B. Sc., Chemistry (major); English and English literature (minor)
-‌‌Korea Institute of Science and Technology Information (March 2010 – Present) - Senior Researcher
Industry Information Analysis
Focus on research and analysis of industry, market and technology
Evaluation of new technology and commercialization
RD-support projects for SMEs
Appraisal and modeling research of technology valuation
Searching for newly emerging items for technology commercialization
- ‌LG Chem Research Park (August 2004 – February 2010)
Nano Material/Electronic Material-related Research
Focused on conductive nanoparticle synthesis and its application to conductive ink or paste.
- ‌Michigan State University (February 2003 – May 2004)
Post-Doctorate Research Associate
Focused on Iridium-based catalysts for arene borylations, diborations of olefins and their suzuki
coupling reactions, inventing new catalytic transformations and investigating mechanistic features
that dictate selectivity.

51
Core technology and industry trend of probiotics under the system
with massive and worldwide social and environmental changes
Jongtaik Lee
Korea Institute of Science and Technology Information, South Korea
E-mail : jtlee@kisti.re.kr
Abstract
Probiotics are microorganism(live bacteria and yeasts) that are good for your health, especially your
digestive system. Bacteria should show a beneficial effect on the body by surviving in stomach acid
and bile acid, reaching, growing and settling in intestines. In addition, it must be non-toxic and
apathogenic.
Three main effects of probiotics are metabolism activation, intestinal regulation, and immune
modulation. Metabolism activation leads to lessening colorectal cancer occurrence, decreasing
cholesterol and lactose intolerance. Intestinal regulation improvement means that autoimmune
system strengthens and food allergy or inflammatory bowel disease get moderate. Irritable bowel
syndrome and pathogenic microorganism are suppressed by increasing lactose tolerance. Recently,
range of probiotics industry is expanded to prebiotics helping improving effect of viable cells,
or dead bacteria-related products to show health improvement. More and more, not only health
supplement products, but also cosmetic industry, medicine industry, and livestock industry are
getting involved with probiotics.
Due to these effective impacts, probiotics industry is expected to show high growth even though
general health functional food market seems stagnant.
The main technology competitiveness is reinforcement of reaching and surviving ability of viable
cells to intestines by coating, prebiotics, and refrigeration technologies.

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Poster 2
Jongtaik Lee
- ‌Korea Institute of Science and Technology Information (March 2010 – Present) - Senior Researcher

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Market growth potential analysis
deciding to enter LED lens compound market
Jongtaik Lee
Korea Institute of Science and Technology Information, South Korea
Abstract
LED lens compound is used for LED lighting chip packaging cap. Its main role is to protect the
inner part and to disperse light brightly. It should not be deteriorated under the long-term high
temperature. In order to have mechanical strength, epoxy resin as a LED lens should have high
purity with a minimal amount of chlorine.
Among LED-related markets, LED lighting field is expected to show the most significant growth
since a number of countries try to reduce energy consumption and to have eco-environmental
regulation, and the prices of LED lighting keep decreasing.
LED lighting world markets are forecast to reach 160.3 billion US dollars in 2017 from 69.4 billion US
dollars in 2012 with 17.3% CAGR(compound annual growth rate). So far, LCD BLU and lightings for
auto vehicles have been the main portion of the market, but general lighting market is expected
to grow bigger than other fields. The revenue for lighting among LED businesses of major LED
companies gets to increase. The market size of LED lens is forecast to reach 2.11 billion US dollars in
2016 from 1.02 billion US dollars in 2012 with 20.8% CAGR.
In case of silcon materials, Dow Corning has released 5 new products of next generation LED
encapsulants with various hardness. The major LED element companies are Nichia, Toyota Kosei,
Philips Lumileds, Cree, Osram, which lead the LED market. LED packaging industry is lead by Nichia,
Osram, Cree, Toyota Kosei, and philips Lumileds. Nippon Light and OPT are the major companies
in LED BLU. Cree has tried to expand their business models to LED lighting finished products from
LED packaging. The revenue for Lighting business of Philips has been increasing compared to other
parts in Philips, especially industrial light business.

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Poster 3
Jongtaik Lee
- ‌Korea Institute of Science and Technology Information (March 2010 – Present) - Senior Researcher

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Current competitive state analysis out of various data regarding
foreign and domestic markets in animal additive industry
Jongtaik Lee
Korea Institute of Science and Technology Information, Seoul, Korea
Abstract
Animal functional food world markets are forecast to reach 17.3 billion US dollars in 2019 from
11.7 billion US dollars in 2011 with 5.1% CAGR(compound annual growth rate). The leading global
consumption market is US(45.6%) and the next is Europe(40.4%). For functional food for submerged
cultivation or pets, North America and Europe is expected to grow faster than Asia-Pacific. But in
Asia-Pacific region is expected to show continuos growth due to income level growth and increasing
meat consumption. More than 70% of animal functional food consists of pig/chicken(73.4%), and
the next is cow(19.2%). In pet-related market, feed additive has 31% market share in US and 38%
market share in Japan.
The top 3 major companies occupies about 30% market share : Novus International, Evonik
Industries, and Adisseo/China National Bluestar Co. Ltd. Companies in Europe and US are mostly
major ones, but there are newly emerging companies in Asia-Pacific. Archer Daniel Midland
Company, BASF, Nutreco Holding N.V., Royal DSM N. V. are another major ones. Major pet-feed
additive companies are Mars Petcare Inc., Nestle Purina Petcare, Hill’s Pet Nutrition, PG Pet Care,
and Del Monte Foods Co. There are also very active mergers and acquisitions in animal functional
food market. Some examples are that Cargill(major assorted feed company) took over Provimi(major
feed additive company), that BASF took over Cognis, that DSM took over Martek, Tortuga, and
that Biomin took over Phytogen, etc. In South Korea, Copebet-special, miraejawon ML, CheilBio,
EasyBio, CTCBio, AmiBio, JinBiotech, Daeho are the major animal functional food companies.
Major companies in South Korea has reached 70~80% technology level compared to world top
technology by active RD, and shown continuous revenue growth.

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Poster 4
Pan Pan
(University of Science and Technology of China, China)
Junfei Yang
(University of Science and Technology of China, China)
Ke Jiang
(University of California, Davis, USA)
Graduated from University of Science and Technology of China, now in Institute of Advanced
Technology ,University of Science and Technology of China as Director of Project Implementation
and Management office to do research work in the technology transformation.
Email: xyz668@foxmail.com
Institute Homepage: http://iat.ustc.edu.cn
Graduated from University of Science and Technology of China, had studied in mathematical
physics involving some geometric aspects of string theory, Hodge theory etc. He is now interested
in ANN and deep learning.
Email: jfyang2010@foxmail.com
Personal Homepage: http://www.jfyang.org
Ke Jiang (江珂) is a Ph.D. candidate in the department of Communication at University of California,
Davis. Her research focuses on communication network analysis, network dynamics, network
visualization, intercultural communication, and cultural convergence. She also examines Guanxi
network that is a special form of social network in China manifesting itself as a mixture of sentimental,
instrumental and obligational ties.

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From Research to Industry: Chinese Semantic Network Analysis of
Technological AchievementsTransformation
Pan Pan
Junfei Yang
Ke Jiang
Institute of Advanced Technology
University of Science and Technology of China, China
E-mail : xyz668@foxmail.com
Institute of Advanced Technology
University of Science and Technology of China, China
E-mail : jfyang2010@foxmail.com
Department of Communication
University of California, Davis, USA
E-mail : kejiang@ucdavis.edu
Abstract
Research universities and institutes have accumulated a large number of technological
achievements that can be industrialized. This paper conducts a semantic network analysis to
describe the technological transformation path of research universities and institutes, and explore
an industrialization model to provide source of enlightenment for future transformation of
technological achievements. Specifically, based on the development data of 154 high-tech venture
enterprises starting up with original innovative achievements in Institute of Advanced Technology
at University of Science and Technology of China, five Chinese semantic networks were created
based on Chinese word segmentation. They are: Company Description, Product Application, Project
Progress, Prospect, and Team. Through the modularity analysis and calculating word centralities,
this paper found that while the 154 technological venture projects demonstrate diversified
development trends, information application services have become the mainstreams among these
projects. Most core members of the 154 high-tech venture enterprises have postgraduate education
backgrounds and overseas study or work experience. Although the technological venture projects
are being industrialized and the market development prospect is good, the industrialization process
is slow and the product development cycle is long.

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Poster 5
Young Hoon Lee
(KEIT, South Korea)
Young Jun Kim
(Korea University, South Korea)
Young Hoon Lee is a PhD candidate in Management of Technology at Korea University. He is also
a senior researcher at the Korea Evaluation Institute of Industrial Technology (KEIT) focusing on
RD planning, evaluation, and global co-operation. Previously, he worked as a senior researcher
at Samsung Electronics for six years. His research interests include technology management, RD
policy, Triple Helix, robotics, and mechanical design.
Dr. YoungJun Kim is currently a professor and an associate dean at the Department of Management
of Technology, Graduate School of Management of Technology, Korea University, Seoul, Korea.
Before joining to Korea University, he taught at Seoul National University in Korea, and Texas
AM International University in USA. Dr. Kim’s areas of research interests include technology
management, technology strategy, technology economics, and RD and Innovation Policy. He has
published more than 30 papers at SSCI(SCI) journals, book chapters (OECD, Taylor Francis), book
reviews and reports.

59
Within and across regional innovation system: measuring the
dynamics of regional innovation systems in Korea
Young Hoon Lee
Young Jun Kim
KEIT(Korea Evaluation Institute of Industrial Technology), South Korea
E-mail : vsmyself@korea.ac.kr
Korea University, South Korea
E-mail : youngjkim@korea.ac.kr
Abstract
Regional Innovation System (RIS) is proposed to promote national competitiveness in 1990s based
on the innovation system and cluster concepts. Since then, a number of studies on RIS have done to
find out the effect and the weakness of RIS in various countries. However, national competitiveness
is progressed not only by the interactions among institutional actors within each RIS, but also by
the interactions across RISs. Korea is one of the countries which implement actively the RIS policies
according to the characteristics of regions. This study focuses national RD programs in Korea
between 2003, when the government implemented the first active policy for RIS, and 2012. We
suggest improved metaphor which can represent interactions within and across regional innovation
system, and analyze the interactions measuring mutual information.
Keywords : interaction, RD network, regional innovation system

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Poster 6
Hee Won Cha
(Ewha Womans University, South Korea)
Yunna Rhee
(Hankuk university of Foreign Studies, South Korea)
Chung Joo Chung
(Kyungpook National University, South Korea)
Chung Joo Chung (Ph.D., State University of New York at Buffalo) is an assistant professor in the
Department of Journalism and Mass Communication at Kyungpook National University. His
research areas include new media and technology, social networks, international communication,
and data science. He currently teaches new media research, media effect and theory, and mass
communication and society. E-mail: chungjoochung@gmail.com

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An Analysis of Korea Brand and KoreanWave using Big Data
Hee Won Cha
Yunna Rhee
Chung Joo Chung
Ewha Womans University, South Korea
Hankuk university of Foreign Studies, South Korea
Kyungpook National University, South Korea
idream4you@gmail.com
Abstract
This study conducts an analysis of Big Data and social media content associated with Korea’s nation
branding efforts and the Korean Wave on the public medium Google and the private medium
Facebook from 2004 to 2015. The results are applied to social media strategy to enhance the nation
branding efforts. This research clarifies the features and analytical differences of Big Data collected
from the Google and Facebook platforms to overcome limitations to existing policy research.
This research also provides a discourse on policy to improve the national brand and identifies
international cultural and political implications.
Keywords : Nation Brand, Big Data, Korean Wave, Digital Ecosystem Theory, Semantic Analysis

Recorded Presentation
1st
day October 29 (Thursday) / Sky Hall, Susung Hotel
13:20 - 14:00 Racial Relations in the United States: A System in Flux
Otto F. von Feigenblatt, (Carlos Albizu University, USA)

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Dr. Otto F. von Feigenblatt
(Carlos Albizu University, USA)
Dr. Otto F. von Feigenblatt, Count of Kobryn, is a Costa Rican academic and public intellectual.
He teaches undergraduate and graduate courses at several universities in the United States and
Europe. Dr. von Feigenblatt is the author of more than one hundred academic articles published in
peer-reviewed journals and he is currently serving as the Editor in Chief of the Journal of Alternative
Perspectives in the Social Sciences. Dr. von Feigenblatt is an Academician of the Royal Academy
of Doctors of Spain, an elected fellow of the Royal Asiatic Society of Great Britain and Ireland, an
elected fellow of the Royal Anthropological Institute of Great Britain, and a foreign member of the
Russian Academy of Natural Sciences.

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Racial Relations in the United States :
A System in Flux
Dr. Otto F. von Feigenblatt
Carlos Albizu University, USA
E-mail : vonfeigenblatt@hotmail.com
Abstract
This presentation analyzes the idea of race in contemporary America. A brief historical overview of
the concept is provided and early anthropological ideas of race are compared and contrasted to the
current popular idea of race in the United States. Theories taken from cultural studies are applied to
the idea of race in America to provide a new understanding on this complex construct. The study
concludes that the labels of “white” and “black” in contemporary American have more to do with
cultural identity than with phenotypical traits such as skin color and facial features.

Round Table
Triple FutureTalk Series
1st
day October 29 (Thursday) / Sky Hall, Susung Hotel
15:40 - 16:20 Key Ideas from a 25-Year Collaboration at Technological Forecasting Social
Change
Moderator : Ke Jiang (University of California, USA)
Respondent : ‌Marc Smith (Connected Action Consulting Group, USA)
LeslieTkach-Kawasaki (University ofTsukuba, Japan)
Presenter : Fred Phillips (Yuan Ze University,Taiwan)
Moderator : Ke Jiang (University of California)

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Dr. FRED PHILLIPS
(Distinguished Professor, Yuan Ze University, Taiwan)
Dr. FRED PHILLIPS joined Yuan Ze University in 2015 as Distinguished Professor. Earlier he was Professor and
Program Chair at State University of New York at Stony Brook; Vice Provost for Research at Alliant International
University; Associate Dean at Maastricht School of Management (Netherlands); and Dean of Management at
Oregon Graduate Institute of Science Technology. He is also a Senior Fellow (and formerly Research Director)
at the IC2 Institute of the University of Texas at Austin, a PICMET Fellow, and Profesor Afiliado at CENTRUM, the
business school of the Pontificia Universidad Católica de Lima.
In New York, Texas, Oregon, Holland and Korea, he has been a leader in developing graduate management
curricula for employees of international and high-tech companies. His contributions in operations research
include “Phillips’ Law” of longitudinal sampling, and the first parallel computing experiments with Data
Envelopment Analysis. He is co-recipient of grants totaling $5 million from the Air Force Office of Scientific
Research for the study of Japanese technology management practices. He brought many other grants to IC2,
OGI, MSM and Stonybrook, and was co-principal investigator on a $1 million NSF project, developing advanced
information systems for the US Forest Service. He has won several awards for outstanding research.
Dr. Phillips is Editor-in-Chief of Elsevier’s international journal Technological Forecasting Social Change.
He authored the textbook Market-Oriented Technology Management (Springer 2001), the popular title The
Conscious Manager: Zen for Decision Makers (General Informatics 2003), and a book on high-tech economic
development, The Technopolis Columns (Palgrave 2006).
In earlier years he held teaching, research, honorary, or management positions at the Universities of Aston and
Birmingham in England, General Motors Research Laboratories, Market Research Corporation of America, and
Battelle-Pacific Northwest National Laboratories.
Dr. Phillips has been a consultant to such organizations as Intel, Texas Instruments, and Frito-Lay Inc., and
has consulted worldwide on technology based regional development. Through his consulting firm, General
Informatics LLC, he and his team have worked on projects for World Bank, UNESCO, and the US Environmental
Protection Agency. Fred is a founder of the Austin Technology Council, and was also a Board member for the
Software Association of Oregon. He is a popular op-ed columnist and panel member in forums dealing with
trends in management, technology, higher education, and economic development.
Dr. Phillips attended The University of Texas and Tokyo Institute of Technology, earning the Ph.D. at Texas (1978)
in mathematics and management science. Married to Sue Phillips since 1979 and with two grown daughters,
Fred enjoys his mission as an educator. His avocational passions are aikido, Argentine tango, travel and writing.
Contact: fp@generalinformatics.com or fphillips@saturn.yzu.edu.tw

69
Key Ideas from a 25-Year Collaboration atTechnological Forecasting
Social Change
Fred Phillips1
and Hal Linstone2
1
Yuan Ze University, Taoyuan, Taiwan fphillips@saturn.yzu.edu.tw
2
Editor-in-Chief Emeritus, Technological Forecasting Social Change linstoneh@aol.com
Abstract
Since their first meeting in 1991, the authors have enjoyed a friendly dialog centered around
topics of interest to the journal Technological Forecasting Social Change. Now, five years after
Phillips succeeded Linstone as Editor-in-Chief of the journal, we recap the driving ideas that have
characterized the partnership.
The ideas span areas of systems, complexity, and scientific progress; the nature and measurement
of innovation, social change, and technological change; the limits to growth; and multiple
perspectives, as these pertain to technology forecasting and assessment. Collectively, the ideas and
discussions have shaped our editorial philosophy and have appeared piecemeal in TFSC research
papers, perspective pieces, and editorials. We now restate these key ideas in hopes of maximum
clarity for researchers, managers, and policy makers.
For want of a nail, the shoe was lost;
For want of the shoe, the horse was lost;
For want of the horse, the rider was lost;
For want of the rider, the battle was lost;
For want of the battle, the kingdom was lost;
And all for the want of a horseshoe nail.
Overview : The systems framework
Since their first meeting in 1991, the authors have enjoyed a long and friendly collaboration
centered around the topics of interest to the journal Technological Forecasting Social Change.1
Now, five years after Phillips succeeded Linstone as Editor-in-Chief of the journal, we look back to
1) ‌Linstone became Founding Editor of Technological Forecasting (later re-named Technological Forecasting Social Change) in 1969. Phillips’
first paper in the journal appeared in 1996, and Linstone invited him to the Board shortly after. Early in the next decade, Phillips was appointed
Associate Editor, and (in 2006) Senior Editor. In 2011, Linstone became EIC Emeritus, and Phillips the new Editor-in-Chief.

70
recap the driving ideas that have characterized the partnership. This paper remarks on those (i)
ideas that emerged from items the two of us discussed, (ii) ideas on which one of us responded
to the other’s invitation for comments or collaboration, and (iii) ideas of Fred’s that Hal, as mentor,
expressly endorsed.
We happened to have been influenced by some of the same thinkers and their works: Manfred
Eigen, whose The Laws of the Game (with R. Winkler, 1983) impressed us with its clarity and
profundity; Charles Perrow (1985, 1986), whose work on system failures in organizations was
pathbreaking; and Karl Popper (1957), whose “multiple engineering experiments” notion affected
our views on decentralization and regionalism.
We were acquainted with Herb Simon, whose ideas influenced the direction of our common interest
in system theory. That interest had grown due to the efforts of our respective teachers at university,
our involvement (in separate eras) with the International Society for Systems Science ISSS, Hal’s
experience at RAND and Fred’s at the General Motors Research Laboratories (Phillips 1972; see also
Phillips 2013a), plus our later experience with people and ideas at the Santa Fé Institute, and the
systems-oriented inclinations of the distinguished Advisory Board of TFSC.
A systems thinker is disinclined to consider individual trends in isolation. One wants to foresee
interactions among trends, as it is these interactions that shape society. However, the toolkit of
technology forecasting includes only two techniques that attempt the latter: Cross-impact analysis,
and scenario methods (Phillips 2011a; 2014a). Scenario methods are becoming more scientific (see
e.g., Kwakkel, Cunningham and Pruyt 2014), but the analysis of interactions of trends remains mostly
art, the domain of futurist practitioners. Nonetheless, as problems of a globalized economy and
changing climate become more complex, scenario building becomes our most valuable planning
tool,2
even as (because scenarios are, after all, fiction) it is the one arguably most open to criticism.
Variants of Table 1 have appeared in many publications; the Table illustrates the point above.
2) ‌Even the Saudis are conducting an “end of oil” foresight exercise. (Nick Cunningham, Saudi Arabia Planning For Transition To Renewables. 22 May
2015, http://oilprice.com/Alternative-Energy/Renewable-Energy/Saudi-Arabia-Planning-For Transition-To-Renewables.html)
Table 1. Techniques suited to different complexity regimes.
Scenario methods occupy the top right quadrant.
Organizational
Complexity
High Leadership
Dialog/Qualitative
Methods
Low Just do it Statistics Math
Low High
Technical Complexity

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3) ‌The Google search http://tinyurl.com/obyv626 yields book titles such as Managing Organizational Complexity; Embracing Complexity; and
Harnessing Complexity, but none on “preventing complexity.”The lurid title Organizational Complexity: The Hidden Killer hints that complexity is
best avoided.
4) ‌Phillips (1997) presented Eigen’s idea to managers and planners at the World Future Society, to their evident interest. Both present authors
emphasized it again on a panel at a later PICMET conference in Portland, when it appeared that the idea was not widely grasped.
5) ‌The future unfolds over time and space. Our s-curves over-emphasize the time dimension and under-emphasize spatial diffusion. (In fact we
suspect our epidemiologist colleagues are more sophisticated in diffusion modeling than technology management scholars are.) The future is
already happening somewhere. Travel, and look for it.
6) ‌Phillips is grateful for Linstone’s decision to publish it, and for Gordon’s concurrence.
There is much literature on “managing complexity.”The present authors agree that we do not want
to manage complexity. The theory of chaotic bifurcations suggests that managing complexity is
somewhere between very difficult and impossible. Linstone cites Casti’s (2012) many examples of
unanticipated catastrophes that occur when our systems become overly complex and increasingly
vulnerable.
It is sometimes possible, however, to forestall complexity. By smart organizational design, by
centralizing or decentralizing, or via regulation of industry, we may prevent problems from attaining
the dangerous “Type D” category of complexity that Perrow called “intricate interactions and tight
coupling”(Linstone and Phillips, 2013).3
The political process aiming at nuclear non-proliferation illustrates an to simplify an overly complex
system (Linstone 2014). “We must not drift unaware toward Type D situations, but rather see the
advance signals of tight coupling and intricate interactions, and take counter-measures – and do
so without falling prey to false simplifications” that stem from pathological denial or avoidance of
complexity (Linstone and Phillips, 2013).
Eigen and Winkler’s work made it clear that system theory had progressed beyond the old definition
of a system as a fixed set of entities (nodes) and connections (arcs). We now know that the system
is the set of generative rules that govern the birth and death of nodes and the evolution of their
interactions.4
From the journal’s perspective, this insight clarified the link between cellular automata
and innovation diffusion models, especially spatial diffusion models,5
and tied system theory more
closely to ideas of technological evolution. The latter consideration led to a special issue of TFSC on
evolutionary technology strategy (Phillips and Su 2009) and a later paper (Hu and Phillips 2011a) on
technological evolution in biofuels.
A paper of Gordon and Greenspan (1986) was the first in Technological Forecasting Social Change
dealing with the “new science of complexity.” It sparked Linstone’s interest in the link between
complex systems and technology forecasting. Phillips and Kim (1996) authored the journal’s second
such article.6
It was followed by a special issue on navigating complexity in organizations (Phillips
and Drake 2000).
In that same year, Gladwell (2000) popularized the phrase “tipping point” as it applies to social

72
change. Curious about how tipping points could exist in innovation diffusion processes, given that
Modis (2006) had pointed out that the single-parameter logistic function commonly used to model
diffusion is scale-free (i.e., evinces nothing that can be called a tipping point), Phillips (2007) applied
a systems view to a 3-parameter diffusion process which considers active organizational resistance
to change. With 2+ parameters, s-curves evince “intricate structure” (Modis’ term) yielding possibly
multiple tipping points of diverse kinds. The greater data requirement for fitting multi-parameter
curves presents a trade-off, in practice. Yet the tipping points are useful flags for managers.
In 1972 The Club of Rome had just published The Limits to Growth (Meadows, 1972), and the head
of General Motors Research Laboratories’ math department nervously asked Phillips to replicate
the model. (What was then the US’ biggest company couldn’t afford to believe there were limits to
growth!) The project was traditional system dynamics, to the extent that the era’s computers could
crunch it. It is worth mentioning here only because of the subsequent forty years of debate between
the “limits to growth” advocates and the “no limits” pundits who place all faith in innovation and
price-mediated input substitution. We observe that:
• ‌Though local resource shortages exist, and cause suffering, there are still few global shortages of
anything.
• ‌Technological innovation has indeed postponed collapse, though its benefits have been geographically
uneven, and uneven among social classes.
• ‌No one foresees “economic substitutes” for air or water. There are no known substitutes for e.g.,
dysprosium and neodymium, or phosphates for fertilizers, nor are such substitutes reasonably
foreseeable (Phillips, 2014a).
•‌“The key factor for the change in capitalism is that it is no longer dependent on large-scale production
and efficiency, but on technology, adaptability, and flexibility”(Kozmetsky, 1996). Localization of format,
content, and language; local solutions; complexity costs and transport costs all eat into economies of
scale.
In the long term our imagination is constrained so that we may not recognize that in a new era new
solutions will be found to problems that seem intractable today. Thus water and energy supplies
may no longer be the problems they are forecast today; robots may be effectively controlled and
global warming may prove reversible. However, it appears there are limits to price substitution
theory, and the second law of thermodynamics implies there is no totally sustainable growth in the
long run (Phillips, 2008).

73
What is innovation?
As Phillips emphasized in (1999 and 2001) (and as was foreshadowed by Ijiri and Simon (1977)
and Nakicenovic et al (1999), an innovation is a non-differentiable point in an experience curve.
somehow many jagged learning curves aggregate to suggest the relatively smooth trendlines that
we call business cycles and Kondratieff waves.
Fig. 1a.“The Kink”: Innovation increases the momentary rate of decline of unit costs.
Fig. 1b.“The One Step Back + Two Steps Forward”:
Innovation decreases productivity while the organization learns to use the new product, service, or procedure. Management
hopes that unit costs will then decline at a rate that more than compensates for the short-term productivity hit.
Fig. 1. Two possible effects of innovation on the learning curve.
(Adapted from Phillips 2001).
This tied in with our discussions on the limitations of trend extrapolation. The learning curve for
polyvinyl chloride, ubiquitous in textbooks, was a perfect example of Joe Martino’s dictum that
“a trend is a trend until it bends.” The kink in the PVC learning curve could only have come from a
manufacturing innovation. How to model this? Phillips (1999) devised (to Martino’s delight) a non-
parametric piecewise-linear regression for this purpose.

74
Fig. 2. An innovation in the manufacture of polyvinyl chloride,
as evidenced by its kinked learning curve.
Extensions to discounting
Linstone (e.g., 1973) has emphasized that for laymen, the perceived importance and probability
of an event drops off with its distance in time and space. Fig. 3 depicts this idea. We agreed to
add the scope of events, i.e., whether the event affects a single person or masses of people, to the
abcissa. As we have been conditioned throughout history to react to the standard arc of a narrative
(in plainer language, campfire stories), with a protagonist, a setting, a conflict, and a resolution, it
seems clear that we are more sensitive to the plights of individuals or small groups than to masses.
Both of us have written that the degree of discounting may vary with the individual’s cultural and
social status: Environmental pollution, climate change, and loss of biological diversity may be
concerns for the ethical affluent; for the poor in many countries, for whom daily survival is what
matters, they are not top concerns (Linstone 2014; Phillips 2014a).7
Hal (2014) emphasizes that
different discount rates can lead to quite different decisions about the future.
Hal conjectures that heavy discounting of distant events (a tendency also shown in the experiments
of Tversky and Kahneman) was a survival trait (and, Fred adds, often a moral imperative) through
most of our history. This is because it was probably not uncommon for an unexpectedly fatal event
tomorrow to make moot a plan made for next week. That fact has not changed; it is the global
scope of our problems that is new.
7) ‌We recognize the exception of poor countries that depend on eco-tourism revenue.

75
Fig 3. The Linstone Principle:
We discount the significance of people and events as their distance from us in time, scope,
and space increases. The shape of the curve differs for different demographics.
None of these extensions to the discounting principle change the conclusion Hal has enunciated for
more than 40 years: We cannot deal effectively with global issues that affect us locally (e.g., water
pollution and climate change) if we base our planning on a heavily discounted future.
It is possible that learning to delay gratification – that is, to lower the discount rate – enabled
civilization in the first place. Zinn (2015) writes, “Humans advanced mainly because… we could see
beyond our villages and wonder what was over the horizon. We learned to suppress the urge to eat
seeds, because planting them produced greater abundance. Our intellect overcame the [energy-
minimizing] man, driving the start of [agricultural] civilization.” We’ve done it once; let’s hope
we can do it again. As with agriculture, we can expect new, low-discount ideas and practices to
originate in individual communities and diffuse outward.
Multiple Perspectives: Extensions to TOP
Linstone is well known for his advocacy of multiple perspectives (MP) in decision making. with each
perspective yielding insights missed by the others. The technical, organizational, and personal views
T, O, and P of the system have been particularly useful.

76
Hal has recently (Linstone 2014) elaborated on TOP:
O is typically process oriented whereas T is product oriented; O tends to mistrust academic techniques.
P draws in the important characteristic of leadership. T+O+P offer a superior basis for decision making
than T alone. The choice of perspectives requires judgment. O and P are case specific. Perspectives
are dynamic and change over time. T tends to dominate in the planning phase, O and P in the
implementation phase. P is particularly important for effective communication.
A few years back, Hal posited an “R” (religious) perspective. This addition was spurred by today’s
many religion-motivated armed conflicts, terrorist acts, and repressive policies, but also by the
necessity to recognize in decision making situations that people’s faiths are liable to make them
resistant to T-based evidence and arguments.
In the course of Phillips (2011b) and Phillips, Chang, Heetun, Kim, Lee, and Park’s (2013) research on
cooperation among aid agencies following disaster events, Hal agreed that it’s sensible in certain
applications to separate the O perspective into intra-organizational and inter-organizational.8
8) Disaster response was a key theme of Mitroff and Linstone (1993).
Table 3. Multiple Perspectives for Analysis – From TOP to PORTI
P = Personal
O = (Intra-)organizational
R = Religious
T = Technical
I = Inter-institutional
Table 4 augments Linstone’s (1999) detailed characterization of T, O, and P by adding the same for R
and I. Table 5 shows the application of MP to the post-disaster situation, mapping the tools that may
be used to influence aid agencies’behavior against the MPs. In this case, the mapping highlights the
relative lack of tools for responding to the R perspective.

77
The Table is also pertinent to calls to unify the social sciences. We hope this will not happen, because
we need the multiple perspectives brought to problems by the various social sciences – even
though these perspectives are sometimes contradictory (Mitroff and Linstone 1993) and though we
do expect some convergence as scientists from the various disciplines succumb to the lure of “big
data.”
Table 4. Multiple Perspectives. The T,O,P columns are due to Linstone (1999).
The R, I columns are added here by the authors.
T O P R I
World view
science/
technology
problem solving
group/institution
process, action
individual, self
power, prestige
Varied: Illusion,
duty, test,
preparation
Competitive
Ethical basis objectivity fairness, justice morality scripture law
Mode of
inquiry
analysis
observation
cause - effect
satisficing
bargaining
agenda
intuition
learning
challenge -
response
Revelation Negotiation
Planning
horizon
far
moderate
discounting
high discounting
for most
Next world
Based on
assessment
of likelihood,
frequency of
cooperation
Uncertainty
view
uncertainties
noted
uncertainties
used
uncertainties
disliked
Will
of the divine
Minimize via
communication,
business
intelligence
Risk criteria
logical
soundness
political
acceptability
loss-gain
imbalance
Various: Afterlife,
forgiving
God, etc.
Reliability of
partner
Scenarios exploratory preferable visionary
Survival.
Conversion of
unbelievers.
Trust.
Competition for
3rd
-party funding

78
Table 5. Mapping a toolset (for post-disaster performance of aid agencies)
against the Multiple Perspectives.
Nation-states, regionalism, and Popperian experiments.
Hal moderated a panel at the 1997 World Future Society conference and asked, “What is the future
of the nation-state?” Panelist Phillips punted on that question, focusing his remarks on Hal’s other
queries to the panel. After all, nation-states are the only voting members of international fora like
the United Nations, so what possible alternative could there be to nation-states? They must persist.
However, reasons to doubt quickly became visible. Western Europe had already become an
ambiguous semi-federal entity. Other signs:
• ‌Recent and pending Free Trade Agreements amounted to a signing-away of national sovereignty
(Phillips 2004).9
• ‌Northerners’ blithely ill-informed drawing of national boundaries in Africa and the Mid-East in post-
colonial and post-WWII years has led to one violent conflict after another. Yet, left to themselves,
the peoples of Kenya or Iraq might well form ethnic conclaves, setting modern civilization back
as effectively as today’s clumsy borders have done. The good news is that South Sudan has been
recognized as a nation-state; the bad news (aside from all the violence) is that it is just that kind of
ethnic retreat. Taiwan, where one of us now resides, is not recognized internationally as a nation-state
at all, much to the distress of its citizens.
• ‌As Phillips (e.g., 2006) has noted repeatedly, high-tech industry clusters develop in metropolitan areas,
9) ‌Phillips 2004 article “Trading Down” took the interdisciplinary approach, combining ideas from economics, physical science, marketing, security
policy, politics, and business strategy. That article is again on point as President Obama (unfortunately, in secret) negotiates the Trans-Pacific
Partnership.

79
not in nations as a whole (except for the smallest ones like Israel or Singapore). Often, as is the case
with San Diego-Tijuana, the metro areas cross national borders.
• ‌With the US government paralyzed by political polarization – and acting the handmaiden of corporate
lobbyists – and with many of the States strangling on reduced budgets, it is becoming recognized that
the only politicians taking constructive and effective actions are city mayors.
• ‌We have noted (Linstone and Phillips 2013) the growing internationalization of research teams.
Nation-states are in trouble. (Sci-fi dystopias in which people are ‘citizens’ of corporations rather
than nations may soon be not too far off the mark.) We are finding our research focuses more
constructively on regions.
“Region” is a term that enjoys a flexible definition in economic geography: It may be as small as
a neighborhood or as large as a contiguous grouping of (subsets of) countries. It may not have a
single government that is co-extensive with its boundaries. These characteristics allow regions with
diverse environments but common interests in, say, a technology, to share assessments with one
another, helping each to learn what works in what circumstances. This is what Karl Popper called,
with great foresight, multiple engineering experiments.
How does this help solve global problems? The late Bill Cooper, editor of Kohler’s Dictionary for
Accountants, defined a policy as a rule that must be followed 90% of the time. Phillips (2014a)
extended Cooper’s idea to craft a rigorous definition of the current term “adaptive policy”10
: In
adaptive policies of the first kind, the 90% figure changes as conditions change over time – going
sometimes to zero, either due to a sunset clause or to (constant monitoring and) adoption of
policies that are working well in other localities. An adaptive policy of the second kind would allow
the percent figure to vary over geography, in response to local conditions.
Naturally, the cross-region information sharing and the monitoring of adaptive policies is made
possible by information/communication technologies, ICT. Linstone (2010) summarized how
economic power is being pushed to the individual desktop and to micro-enterprises even as global
conglomerates continue to merge and grow. (And the micro-enterprises, whether digital wedding
photographers in India or textile designers in Ghana, are connected to suppliers and customers via
the Internet.) History is driven by local languages, neighborhoods, ethnicities, and new states. That
is, by regionalism.
10) ‌Which in practice, absent this definition, all too often seems to mean“no policy at all.”

80
Hourglass-shaped time: Bounded futures
Again with regard to the limitations of trend extrapolation: The past is undetermined, the present
is fuzzy, and the future is uncertain. Witnesses deliver conflicting testimony about a past event, and
physical evidence is ambiguous. Psychology and neurology tell us there is a time lag between an
event and our perception of that event, and moreover that perception is colored by our biases and
prior expectations. That is, the present is fuzzy. The future is commonly depicted (at least, in physics)
as a cone in space-time, encompassing many possibilities.
Fig. 4. Multiple valid explanations lead to divergent extrapolations. (Source: Phillips 2008)
Appropriately enough, time looks like an hourglass (laid on its side, in Fig. 4), widening as we go
farther back or forward, and narrow – but definitely not the dimensionless point that would denote
full certainty – at the“present moment.”
Fig. 4 shows (conceptually) two extrapolations of the same phenomenon from two different but
perhaps equally plausible histories. Extrapolation from past data is risky because all past data are
uncertain.
Time-as-hourglass is consistent with complexity theory’s “butterfly effect.” A butterfly may cause a
hurricane, but we can't identify the butterfly by analyzing the hurricane. At some moment we may
predict the loss of the kingdom, but that will be far later than the moment the nail is lost. We can no
more trace the kingdom’s fall back to the nail than we can predict the hurricane at the moment the
butterfly flutters off.
We are somewhat more certain about the boundaries of the cone on the right hand side of Figure
4. This observation gives rise to the three-legged “Bounded Futures” approach to planning. We
serve the future better by (i) attending to possible scenarios within the cone, AND (ii) accepting that
events outside the cone are currently impossible – and then deciding what to do about the latter.
Table 6 summarizes the approach via examples.

81
Scientific progress, and“big data”
Figure 5 depicts the four components of scientific progress, in the guise of leaping frogs.
As the leap-frog game progresses and Theory is temporarily in advance of Data, scientists enjoy
Theory’s guidance on where to look for new data. Then Methodology jumps to the front of the
queue. And so on. The leap-frog game is the central characteristic of scientific progress. (See Phillips
2008 for historical examples of each leap.) It is how science advances in an ongoing but somewhat
unbalanced manner.
Fig. 5. Leapfrog theory of scientific progress. Source: Learner and Phillips 1993.
(iii) The third leg of the Bounded Futures approach is to understand that the cone may not
represent a hard constraint; concerted effort or an unexpected discovery may soften parts of it. The
boundaries of the cone of possible futures then need to be redrawn. To be valuable for planning,
the constraints imposed by the cone must be reasonably non-obvious, as are the examples in Table 6.
Table 6. Illustrating the bounded futures approach (Source: Phillips 2014a)
Example constraint Example creative response
Traditional venture capital will not drive
entrepreneurial growth.
Develop government, corporate, angel, and
crowd-sourced funding for startups.
Economies of scale will not drive diffusion
of innovation through worldwide
distribution of standard tangible products.
Online networks for peer-sharing of local problems
and locally-developed solutions that may find
application in new locales.
Climate change will not be reversible.
Try to slow migration to vulnerable coastal areas.
Develop technologies for hardened infrastructure.
Emphasize adaptation, mitigation, rather than
reversal.
Neither governments nor corporations will
clean up legacy polluted sites.
Find ways to contain toxins until future possible
cleanups. Focus research on plants and bugs that
metabolize the toxins. Design controls against
unintended consequences of the plants and bugs.

82
Like the microscope and telescope before them, cheap computer memory and sensors have
enabled the observation, collection and recording of vast amounts of new, unexpected data.
The methodology frog jumped to the fore, setting the stage for the data frog to overtake it. The
problems frog is poised to leap, as industries struggle to hire enough “data scientists” and thus to
know their customers better.
The point of Figure 5, however, is that there is no “data science.”There is only science, and the data
frog temporarily leads.
The yin and yang of forecasting
We would love to predict the future with pinpoint accuracy, but we know it will not happen. We
would be happy enough to bracket the true future with confidence intervals and scenarios. These
hopes are stymied by sleeper events, black swans, and wild cards. The latter might include“very low
likelihood events such as a systemic failure of the internet or a widespread electromagnetic pulse
that destroys electronics over a wide area”(Linstone 2014).
Linstone said11
“the military are trained to work through many scenarios, not so that they will pick
‘the most likely’ (as business usually does) but to make them able to react well to unanticipated
ones.” Phillips and Tuladhar (2000), Phillips (2008) and others have written similarly in TFSC about
organizational flexibility and personal resilience as ways to prepare for the future, when our
forecasts are presumed to be just a little bit wrong – or maybe way off the mark.
The real point of forecasting is not to be “right,” but to deal with the future in a maximally positive
and economic way. This is a dual task, effected by (i) crafting our best-shot vision of the unfolding
future, and (ii) preparing our psyches and organizations to comprehend the range of possibilities
and react with flexibility and resilience to events falling in that range and maybe outside of it. TFSC
Associate Editor Tugrul Daim and Phillips recently turned thumbs-down on a DARPA RFI because the
document restricted inquiry to the passive yin (confidence-interval prediction) of low-probability
events, and precluded active yang responses (organizational preparation).
The multi’s, and combinatoric technology
Phillips (2008) wrote of “the Multis, the Biggers, the Smallers, and the More Connecteds.” (The
“smallers” were added at Linstone’s suggestion.) Building on a speech of a former president
of Microelectronics and Computer Consortium, he said technology and decision making are
trending toward “Multi-product, Multi-country, Multi-culture, Multi-company, Multi-industry, Multi-
technology, Multi-career, Multi-tasking, Multiple mechanisms for innovation diffusion, Multiple
11) In a private communication, around 2007.

83
The speed of change, and the Circle of Innovation
Many of our social and economic problems, and much of the grist for our research, comes from
the mis-matched speeds of technological, psychological, and institutional change. In 1985 Peter
Drucker wrote that for several decades social change had been slower than technological change.
Phillips (2008) claimed that that era was over, with social change now now the hare and tech
change the tortoise, relatively speaking.
business models, Multiple stakeholders with Multiple objectives and agendas, and still more“Multis.”
Hal replied that even as projects become Bigger (bigger national economies, bigger global
problems, bigger technological creations, and bigger computational models), other important
things become Smaller: Microcircuitry, nanofabrication, etc.
Meanwhile, they and we all become More Connected, thanks to ICT: Telecomm and data networks,
social networks, environmental problems, organizational structures, regional economies, and the
Internet of Things. If you need a single image to tie all this together, try: Large numbers of globally
connected nano-machines repairing the Sydney Harbor Bridge.
We now connect the ideas of this section to innovation practice and to opportunities for
technology-follower countries. Kodama (1992) showed that innovative RD need not mean linear
advances at the leading edge, and in fact much or most of today’s innovation is not. Instead, it is
“technology fusion,” combining advances from multiple labs and disciplines. (Kodama’s idea was
the forerunner of today’s “open innovation.”) Flagg et al (2013) went further, saying, “the literature
demonstrates that the technological innovation process involves a complex interaction between
multiple sectors, methods, and stakeholders.”We can generalize, to assert that almost all aspects of
modern innovative activity are combinatoric in nature.
Matching new products with their best markets, dismantling old supply chains and re-creating them
with new entrepreneurial business models, breaking down services into modules and re-ordering
them, putting together special-purpose international teams for new research collaborations,
or forming new business alliances and consortia, settling on the feature set of a new electronic
product or hotel brand – all of these innovative activities are processes of mixing and matching.
Technology-follower countries may or may not be able to build a capacity for leading-edge
research, using the most advanced instruments. And if they can, it may not be soon. Technology-
follower countries can engage in combinatoric innovation as successfully as tech leader countries.
There is no reason a researcher in a technology-follower country cannot be a better networker than
a researcher in a technology leader country. Or have a better imagination. In this way, technology-
follower countries can increase their pace of useful innovation.

84
Later developments seemed to support this position. The fact that America is said to have
institutions “too big to fail” means that incumbents’ advantage is reinforced. The fact that the
millennial generation would prefer to start small Main Street businesses rather than Silicon Valley
businesses (Kammer-Kerwick and Peterson 2015) means fewer brains focused on transformational
innovation.
Though Hal noted that an innovation slowdown is consistent with K-wave theory, he later (2014)
wrote, “Technology is [still] racing ahead at a clip that is outpacing our social systems.”Though Hal
came at the relative speed question from an angle slightly different from Fred’s, it appears we were
not in complete agreement.
Part of the resolution lies in sociologists’distinction between society and culture. Society is made up
of people and their physical environment – including their technological environment. Thus there’s
a confounding involved when comparing technology to society; they are not separate concepts.
Culture, on the other hand, is the intangible component of society, encompassing beliefs, attitudes,
practices including language, and opinions. The meaningful question, then, is whether technology
changes faster than culture.
A rather clever Bloomberg analysis makes a step in the right direction, with an interactive graphic
called How Fast America Changes its Mind, http://www.bloomberg.com/graphics/2015-pace-of-
social-change/. Another is in Sonnad’s How Brand New Words Spread Across America (2015). Both
address intangibles. However, as Bloomberg’s analysis spans a period encompassing vastly different
mass media, and Sonnad focuses on the diffusion of new vocabulary via Twitter, technology effects
are still present, and a definitive answer to the relative speed question may be beyond reach.
Linstone (2014) wrote, “As the half life of knowledge shrinks while health technology lengthens the
human life span, lifelong learning becomes not merely useful but essential. It has made remote and
continuous learning possible, thereby creating a superior work force.”His statement illustrates what
Phillips (2014b) calls the Circle of Innovation: Innovations create not just new products and services,
but new ways of using new products and services. The latter force changes in the ways we organize
and interact with one another. The newer kinds of organizations generate new needs, which are
answered by still further technical innovations.
Most published papers address either the left-hand arc of the Circle, or (more frequently) the right-
hand side. This is probably because of researchers’ professional specializations. However, TFSC is
concerned with the entire circle.12
12) ‌Historians do debate whether a change in technology or a change in values led the agricultural revolution. This seems a valid question for
paradigm-busting innovations that come once a millennium or more seldom. For the kinds of innovations usually treated in the pages of TFSC,
however, feedback effects occur more quickly, and the Circle of Innovation applies.

85
Fig. 6. Nonlinear innovation models portrayed as epicycles within the Circle of Innovation
Fig. 6 suggests how the grand feedback cycle of the Circle of Innovation can serve as a frame for the
several more detailed nonlinear models of innovation that grace the journal’s pages. Moreover, the
Circle of Innovation has immediate implications. For example, conventional market segmentation
targets customer characteristics. Ted Levitt (1983) and Clayton Christensen (2003) advised
differently; They said, target products to the customers’“circumstances,” or usage scenarios, not
to their demographics. The nonlinear view in Fig. 6 helps us see that the product will change the
circumstances. This further implies the importance of corporate foresight: Being first to envision the
changed circumstances means being first to market still newer products that meet the new needs.
Artificial intelligence and its dangers
“Advanced robots may gain the intelligence to initiate a devastating attack on their erstwhile
creators” (Linstone 2014). Or on each other, we might add. Then there is the “gray goo” scenario,
in which nano machines eat everything in sight, organic or otherwise, in order to reproduce
themselves.
Neither of us believes the “Singularity” will bring a qualitative change. Stupid people are more
dangerous than smart machines. Venal people caused the global financial crash, not to mention
wars. To be sure, a machine with evolutionary, self-modifying code is qualitatively different from one
with static programming. That does not change the fact that outcomes are influenced by the initial
programming, which may have been done wisely or with utter obtuseness.
An obvious regulatory remedy would have been to decree that for the present, intelligent machines
may be made no bigger or smaller than can be smashed with a baseball bat. That suggestion is
not only facetious; it is infeasible: The robots are already armed and able to fight back. Asimov’s
three laws have been trumped by the imperatives of the military-industrial complex, which wants

86
autonomous fighting machines; Michael Miner’s Robocop was more realistic fiction.
The greater danger, however, is AI in distributed systems (Manzalini and Stavdas’ 2014 title, “The
Network is the Robot,”cuts to the heart of the matter. See also Stuart Russell’s remarks in Bohannon
2015. Musgrave and Roberts’2015 Atlantic article goes on about the topic at greater length.) Again,
the culprits are human, specifically the interests backing 5G telecomm. 5G, the technology enabling
the universally networked robot, will eliminate free wifi (Johnson 2015), exacerbating the digital
divide and its attendant social ills.
All this will become perfectly clear, at least in the legal sense, as soon as there are damages to be
assessed. Will the crash of a driverless car be blamed on the car manufacturer or on the software
provider? A recent Dilbert comic asks the more poignant question, if a person with a networked
implant commits a crime, who be charged in court – the person, or the programmer?
We should settle these questions soon. As we leave the ICT era and enter the molecular era (Linstone
2010), we will face similar questions with artificial wet life. Better to have answers in hand in
advance.
People, we agree, may disrupt society before machines do. Hal wrote (2014), “We are witnessing
growing dissatisfaction with governance on one hand and eager local initiatives on the other as a
counter to federal political paralysis in Washington. The rising disenchantment with governance
may lead to institutional instability and chaos.” Phillips (2008) had noted the prospect of revolution
in the USA.
As for the Singularity, the MP principle gives us helpful advice: “A singularity anticipated with a
technical perspective may not occur at all with another perspective”(Linstone 2014).
Conclusion
Implications of the ideas described in this paper are explored more fully in the cited original
publications. We have recapped the ideas here for a number of reasons: As a convenience for
readers, as a historical record, and to further clarify, fore each idea, our intended meaning and our
current thinking. Collectively, these ideas frame our philosophy of technology forecasting and
assessment.
We will be happy to see future submissions to TFSC that either support or challenge these ideas.
The journal’s mission and scope remain as stated on its web site, and nothing in the present article
is intended to further limit the diversity of the papers the journal receives and publishes.

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