Design and Evaluation of Technology Creation “Ba” in Academia
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Design and Evaluation of Technology Creation “Ba” in Academia. Knowledge Science and an Important Application Field Redefinition of “Ba ” (a Japanese word meaning place, center, environment, space, etc.) for Technology Creation via Systems Concepts

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Design and Evaluation of Technology Creation “Ba” in Academia

  • Knowledge Science and an Important Application Field

  • Redefinition of “Ba ” (a Japanese word meaning place, center, environment, space, etc.) for Technology Creation via Systems Concepts

  • A System for Evaluating “Ba”, A Preliminary Survey, and Implication

Y. Nakamori

School of Knowledge Science

Japan Advanced Institute of Science and Technology


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Target Academia

Knowledge Science

A new research field: study of scientific knowledge creation.

Modeling and management of

knowledge creation process.

School of Knowledge Science

COE Program

Knowledge conversion theory, knowledge systematizing methods, and methods for development of creativity in management science.

A vehicle which integrates theory and practice, and combines knowledge in social science and knowledge in natural science.

New Direction

Necessary Environment

Knowledge science should help researchers produce creative theoretical results, in important natural sciences.

An environment “Ba”, including place, people, context, etc., that supports the development and practice of knowledge creation.


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Target Academia

A Creative System for Research and Education

This system will continuously create scientific knowledge, offering an advanced model for setting important research priorities and promoting research and development, and thereby affecting management of research and development in other universities, research institutions, or enterprises.

This system trains graduate students to be:

Knowledge Creators:

Talented people with the advanced research-and-development capability.

Knowledge Coordinators:

Talented people having broad judgment and can support creative research.


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Knowledge Creators Academia

New

Scientific Knowledge

Talented people with advanced research-and-development capability

Talented people who can manage creative research activities

Interaction of theory and practice

Y

Knowledge Coordinators

Knowledge creation theory

Y=F(X)

ZW

F

Z

W

F

F

Accumulation of social information

Knowledge creation support systems

X

Knowledge systematization

Thinking support system

Knowledge management system Visualization system

Knowledge discovery Knowledge representation Technology road mapping Knowledge database

Existing Scientific Knowledge

Enhance the Function:

Y=F(X)


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Information Gathering Academia

Data/text mining technology

Data/knowledge-base systems

Theories of Technology Strategy

Knowledge management theory

Strategic innovation theory

Knowledge Creation Theory

Design of environment

Systems methodology

Research Planning Support

Imagination supporting media

Road mapping methods

Research Management

Document management

Information exchange system

Knowledge Representation

Knowledge systematization

Visualization technology

Announcement of

Research Results,

Archive System

Management of

Technology and

Intellectual Property

Project

Framework

Lab

Information

Planning

Experiment

Knowledge Coordinators

Deep Woods

commercialization

industrialization

Announcement

“Ba”

Knowledge Creators

Death Valley


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"Ba" for Knowledge Creation (1) Academia

Toyama and Nonaka (2000) called the dynamic context which is shared and redefined in the knowledge creation process "Ba", which does not refer just to a physical space, but includes virtual spaces based on the Internet, for instance; and more mental spaces which involve sharing experiences and ideas.

They regard "Ba" as a "concept of locationality which includes the space-time which acts as the ground of human existence". Knowledge is not something which can exist independently; it can only exist in a form embedded in "Ba", which acts as a context that is constantly shared by people.

Consequently, in order to conduct effective knowledge creation, there is a need to create a "Ba" to act as the existential ground of that knowledge. The "Ba" provides energy to the knowledge creation process, and determines the quality of knowledge which is produced.


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"Ba" for Knowledge Creation (2) Academia

Toyama and Nonaka (2000) listed the following as conditions for "Good Ba" to facilitate knowledge creation:

  • A self-organized location with its own intention, purpose, directionality and mission, etc.

  • Commitment of participants (Commitment to the purpose of the "Ba", and active participation in events occurring in the "Ba").

  • Simultaneously providing two viewpoints: from the inside and from the outside.

  • Direct experience by participants.

  • Dialog is conducted relating to the essence of things.

  • Boundaries are open (Participants come and go freely, and the shared context is endlessly changing).

  • A "Ba" for practice where explicit knowledge can be internalized through practice.

  • Heterogeneous mixing occurs.

  • Impromptu interaction occurs.


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Redefinition of "Ba" via Systems Concepts (1) Academia

What is the best definition of "system" in knowledge science?

Knowledge science addresses not only scientific knowledge, but also subjective knowledge based on experience and insight, so systems in knowledge science must include the participating people, the knowledge of the participants, and previous data and information which have been codified as knowledge.

A complex whole including human beings and information can be understood as a system. However the system so understood is not a reality per se. This is because wholes like this have a complexity and diversity which must be recognized as a system which differs depending on the subject.

Systems like this are called soft systems. Checkland's definition of "system" is aware of soft systems, and can be regarded as having a philosophical background in common with the "Ba" of Nonaka.


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Redefinition of "Ba" via Systems Concepts (1) Academia

Now, in order to improve the possibilities for manipulation and concept sharing, we introduce the following schema:

Ba = Infrastructure + Actors + Information

Infrastructure which do not include people are designed and built. This is the design and building of real systems including things like locations, rules and information infrastructure. It is engineering.

The idea is to overlay this with the social science of what sort of people and what sort of information should be added. Substance and energy must be invested in the system but we assume that they have already been woven in as things which the infrastructure should have.

The theory of designing all these things is called "Ba design theory", and if it is applied to a site of science and technology development, that is exactly the "scientific knowledge creation theory" we are aiming for.


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Redefinition of "Ba" via Systems Concepts (1) Academia

  • To achieve a "Good Ba", it must become a self-organized space-time with its own intention, purpose, directionality and mission, due to the interaction of its elements: infrastructure, actors and information. Therefore, being aware of the interaction, we can also suggest:

  • Ba = Infrastructure x Actors x Information

  • If we accept this, there is no incongruity in saying "Ba = System". Here we organize the situation as follows, using systems concepts:

  • Ba = { Set of elements, Set of characteristics, Set of relationships }

    • Set of elements = { Infrastructure, Actors, Information }

    • Set of characteristics = { Emergence, Hierarchy, Communication, Control, etc. }

    • Set of relationships: Complex (Investigation of this is the issue)

    • Subsystems in scientific, social, and creative dimensions


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Will, Desire, Hope Academia

Social Dimension

Public Knowledge

Experience-based Knowledge

Wisdom-based Knowledge

Information

Recognition

Involvement

Scientific Dimension

Creative Dimension

Insight

Wisdom

Inference

Intuition

Sense

Imagination

Intelligence

Intervention

Integration

Requirement

Perspective

Synthesized

Discovered

Problem

Knowledge

A Systems Methodology for Knowledge Integration

i-System


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Evaluation of system elements: Academia

Infrastructure

Actors

Information

Measure:Ability to transmit and hand down knowledge in the laboratory.

Social dimension

Agency=Involvement

Creative dimension

Scientificdimension

Agency=Intelligence

Agency=Imagination

i-System

Measure:Ability to collect and manage knowledge in the laboratory

Measure: Ability to acquire and create knowledge in the laboratory

Action = Integration

Action = Intervention

Evaluation of system performance:

Research Progress and Member Growth

Definition of system structure and elements

Diagnosis of system structure and elements

Evaluation of Research and Education Environments Based on i-System


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Diagnosis of system elements considering system performance (emergence)

Diagnosis

Infrastructure

Actors

Information

Scientific Dimension

A1

A2

A3

E1:Activity

E2:Empathy

E3:Persistence

E4:Autonomy

E5:Thinking skill

Social Dimension

Evaluation sheet concerning member growth

B1

B2

B3

Creative Dimension

C1

C2

C3

D1:Research progressing

D2:Papers and patents

D3:Knowledge and skills

D4:Technical transfer

D5:Social contribution

D6:New research funds

D7:New theme creation

D8:Research successors

D9:Lab administration

Survey sheet concerning system elements

Effect of interaction

Effect of management

Evaluation sheet concerning research progress and results

Emergence

Time difference


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Evaluation of Knowledge Management Capability in the Laboratory

(A) Checklist on the ability to collect and manage knowledge in the laboratory

(A1: about infrastructure)

A11: Have the books/magazines/references and experimental equipment necessary for

research been consolidated? Or can they be obtained easily?

A12: Have things like the research papers of instructors and previous students, and

records of seminars and experiments, been consolidated?

A13: Is it fully furnished with collection systems and network systems for external

information?

(A2: about actors)

A21: Do members have a strong interest in science and society?

A22: Do members understand the mission of the laboratory, and are they working hard

to collect and manage the necessary information?

A23: Are members conducting research and development using diverse information?

(A3: about information)

A31: Has information relating to the current state of science and technology, research

trends, academic society trends, and key domains been collected and consolidated?

A32: Has information relating to government policy, regulations, society, economics, the

environment and other information relating to the development or constraint of

research been collected and consolidated?

A33: Has information relating to research planning/development management and

intellectual property management been collected and consolidated?


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Evaluation of Knowledge Management Capability in the Laboratory

(B) Checklist on the ability to transmit and hand down knowledge in the lab.

(B1: about infrastructure)

B11: Have locations for opinion exchange (seminar rooms, collaboration spaces, lounges

etc.) been consolidated?

B12: Have education programs been established (research guidance, exchange with

researchers from the outside etc.)?

B13: Have things like opinion exchange systems and groupware been consolidated?

(B2: about actors)

B21: Is leadership being demonstrated?

B22: Have members been trained in presentation skills and communication skills?

B23: Are members interested in the research of their fellow members, and do they

actively express their opinions?

(B3: about information)

B31: Is knowledge, relating to the conduct of research based on the experience of

instructors and senior participants, being effectively used?

B32: Is information which is not immediately necessary for the conduct of research being

accumulated?

B33: Is a dialog being conducted on things like the motivation of the research life, and

the value of living it?


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Evaluation of Knowledge Management Capability in the Laboratory

(C) Checklist on the ability to acquire and create knowledge in the laboratory

(C1: about infrastructure)

C11: Have places (individual rooms, booths, coffee break rooms etc.) been provided

where individuals can concentrate?

C12: Are things like experiment rooms, experiment equipment, computers and research

expenses satisfactory?

C13: Have things like idea generation support systems and knowledge systematization

systems been consolidated?

(C2: about actors)

C21: Are members actively taking the initiative to create knowledge?

C22: Are the planning skills, analysis skills and problem solving skills of members

satisfactory?

C23: Are the member's patience, persistence, sensibility and will to succeed

satisfactory?

(C3: about information)

C31: Is new knowledge coming into being due to the creativity and insight of members?

C32: Is new knowledge coming into being due to the impromptu interaction of members?

C33: Do members have information on planning methods, experiment methods,

organizing methods and presentation methods?


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Correspondence with the conditions of "Good Ba" by Toyama and Nonaka

Involvement Ba

Intelligence Ba

Imagination Ba

Infrastructure

Actors

Information


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Correspondence with and Nonaka “living skills” and with “knowledge science”

Intelligence Ba

Involvement Ba

Imagination Ba

Infrastructure

Actors

Information


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Correlation Coefficients (Good Ba and Research Progress) and Nonaka

Intelligence Ba

Imagination Ba

Involvement Ba

Infra. Actors Info. Infra. Actors Info.Infra. Actors Info.

Research progressing

Papers and patents

Knowledge and skills

Technical transfer

Social contribution

New research funds

New theme creation

Research successors

Lab administration

Members’ happiness


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Correlation Coefficients (Good Ba and Development of Students’ Ability)

Activity Empathy Persistence Autonomy Thinking skill

Infrastructure

Actors

Information

Infrastructure

Actors

Information

Infrastructure

Actors

Information

Intelligence

Ba

Involvement

Ba

Imagination

Ba


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Preliminary Survey (Linear Dependence) Students’ Ability)

ScientificDimension

Research Progress

Infrastructure

  • Knowledge and skill accumulation

  • Research laboratory vitalization

  • Personnel development

  • Research progress

  • Organizational education

Actors

Strong

effect

Information

Social Dimension

  • Collaboration with the outside

  • Improvement of social impact

  • Acquisition of research funding

Infrastructure

Weak

effect

Actors

Information

Member Growth

Creative Dimension

Activity (creativity, curiosity, foresight)

Empathy (support skills, communication skills)

Persistence (concentration, planning skills)

Autonomy (sense of responsibility, initiative)

Thinking skill (analysis skills, logical thinking)

Infrastructure

Actors

Strong

effect

Information


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Results of Preliminary Survey Students’ Ability)

Using the evaluation given by ten professors in materials research laboratories at JAIST, we found the following linear relationships

  • Three factors – "accumulation of knowledge and skills", "vitalization of the research laboratory", and "personnel development" -- are strongly and linearly related to the quality of "Ba".

  • Actors in "Intelligence Ba", information in "Involvement Ba", and infrastructure in "Imagination Ba" are linearly related to "knowledge and skill accumulation", "research laboratory vitalization" and "personnel development".

  • "Collaboration with the outside", "improvement of social impact", and "acquisition of research funding" are not linearly related to the quality of "Ba". These are things which are related to the hard work of professors, so these results are understandable.

  • Among the five skills of members, "persistence" is strongly and linearly related to the quality (good or bad) of "Ba".

  • Actors in "Intelligence Ba", information in "Involvement Ba" and infrastructure in "Imagination Ba" are linearly related to member growth.


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Conclusion Students’ Ability)

We tried to design a “Good Ba (Environment)” for scientific research in academia based on systems concepts.

We actually prepared a list of evaluation items (a check list), carried out a preliminary survey at the school of material science, and obtained an understandable result.

Future work should include:

Refinement of the list of evaluation items, consulting many scientists.

Modeling of the relation between “Ba’s” and research outputs.