A Model of 96 Models of Innovation, Including Causal Path Models for Each

Posted: 4 Mar 2018

See all articles by Richard Greene

Richard Greene

Beijing DeTao Masters Academy; Keio University - Graduate School of System Design and Management

Date Written: March 20, 2012

Abstract

Presented: Design Creativity Kobe 2010; TMCE 2012 Karlsruhe; ASME 2013; ICCC 2013; Design Society, Thailand 2009 Part of the EXCELLENCE SCIENCES Research Project at the University of Chicago Grad School of Business -- 54 Routes to the Top of Nearly Any Field.

Extended Abstract, Below — of questions, data sources, results, analyses for each result type, main conclusions from the 14 hypotheses generated.

Now brief research questions: 1) What distinguishes home run scale innovators (their effort, direction, doings, tactics) from the vast body of smaller scale innovatings? 2) What distinguishes environs they find, ride, or foster from environs small scale innovators/innovatings engage, endure? 3) Where in home run scale innovating is real thought, effort, and tactical inventiveness required and directed? Why? 4) When all innovation noises (from claimed “innovativeness” for career or product promotion, from ordinary system effects of all long large scale projects innovative or not, and others treated as innovation work) are substracted out, revealing CORES of home run scale innovatings, what variety in those CORES worldwide and across professions appears? What role does that variety play in reaching home run scale, and escaping omnipresent innovation noises? 5) What do individuals who engender or crystalize home run scale innovations do and overcome and launch that others who reach far smaller scale levels of change, novelty, innovation do not do? 6) What generates the Innovation Noise of gross exaggerations of scale of innovations aimed for and achieved in both university research and industry innovation practice? 7) What role do various common cultures of business and common cultures of academia play in generating such Innovation Noise and trivializing of scale of innovation? 8) Do the common cultures of US academia generate and sustain many of the common cultures of business that all home run scale research and practice/achievement of innovation must overcome? 9) Do the answers to the above offer solutions to the vast majority of published research studies of innovation going unread and entirely unused in industry -- knowledge that is literally useless? Do those answers offer solutions to the erosion of Silicon Valley innovativity via venture businesses from colleges supplanting venture technology firms, MBAs supplanting engineers as leaders, technically ignorant venal hedge fund money playing “disruptions” supplanting bold engineer inventions in harsh market competitions that wean in best idea embodiments? 10) What do answers to the above from 8000 eminent creators from 63 fields and 41 nations, and detailed interviews of 450 great innovators of 3 sets of 150 each tell us about: A) fixes to shallow unread unused “research” on innovation and B) fixes of eroding levels of innovativity as colleges invade it with their plans, analyses, models, elitisms, snobberies, and drive to publish unread unused “knowledge”? 11) Which are the real forces generating major scale novelty/change in home run scale innovatings -- a) non-linear systems effects of many agents interacting till emergent inventions appear in special districts of dense interactions of the “right” factors or b) human ideas or tactics engendering/crystalizing larger scale populations and forces into new configurations? Which is more real, larger in magnitude? Are individuals and groups wrongly taking credit for emergents? Hence, are models of innovation and theories/studies of it as “done” by humans acting, mis-directed -- missing non-linear systems types that themselves, like Natural Selection and the Flows & Homes in Silicon Valley, “innovate” without need of special humans, human ideas, or human tactics? RESULTS: 2 Scales of Innovation Magnitude, the 96 Models Listed & Causal Forms, Theory of Innovation Noises, Theory that Innovation is Culture Work -- 11 Cultures Home Run Scale Innovations Counter, the Femininity of Productivity and Innovation, The Biggest Innovations from Global Religions of Business Invasions, Innovations as De-Academy-izing.

DATA: from 8000 eminent creators from 41 nations 64 professions, and 450 Top Innovators.

ANALYSIS: AI protocol analysis of expert case handlings & total quality process causal analysis modeling applied to respondent ways of handling new innovation cases, observations of self and others, evolution of own ways of innovating, plus "challenge" questions asking respondents to get beyond pop familiar, self-inflating, flaw-hiding norms of thinking-handling-reporting innovation worth and magnitude of results.

PRIMARY DATA SOURCE -- A redo of Plato in the University of Chicago Grad School of Business’ EXCELLENCE SCIENCES Research Project -- seeking to define “the good” and “excellence” in our time empirically, not politically, culturally, religiously, philosophically, ideologically-asked 8000 eminent creators in 63 professions and 41 nations -- who is top in your field, how did they get there, what capabilities distinguish them from good but not top ones there? 54 distinct “routes to the top of nearly any field” were obtained. 150 people in each of the 54 were then found by a triple nomination process and given detailed interviews on capabilities on the way to “top” and while at “top” levels. ONE of those 54 was at the top by “innovating”. Capabilities of top innovators of 3 sorts were extracted from the data of the 8000: a) 150 founders across 3 generations in Silicon Valley, b) top innovators elsewhere globally in 63 fields, and c) 150 leaders needing “far larger scale innovations” than people and systems were currently making available to them. Additionally top innovators in manufacturing received extra research items and administerings emphasizing getting beyond “socially accepted” and “social pressure fostered” and “fitting in” responses.

Questionnaires and interviews both were based on “protocol” analysis of sample cases handled by respondents inside each instrument, borrowed from artificial intelligence knowledge systems, and “process causal modeling” borrowed from total quality. Both of these have been validated elsewhere as “qualitative responses with correlational validity and reliability upon retesting on similar other data sources.

Note: richardtgreene@alum.mit.edu

Keywords: meta-models, meta-innovating, plural models, innovation noises

Suggested Citation

Greene, Richard, A Model of 96 Models of Innovation, Including Causal Path Models for Each (March 20, 2012). Available at SSRN: https://ssrn.com/abstract=3132155

Richard Greene (Contact Author)

Beijing DeTao Masters Academy ( email )

1 Nanjin Road ShaheZhen
Changping District
Beijing, 102206
China

HOME PAGE: http://www.detaoma.com/Master_Forum/Richard_Tabor_Greene

Keio University - Graduate School of System Design and Management ( email )

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Hiyoshi, Honcho, Kohoku-Ku
Yokohama, Kanagawa 223-0001
Japan

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