Presentation at the 8th IADIS International Conference on Information systems. Pre-proceedings available at: http://bit.ly/1QPEZS5 Due to the relative success of agile methods in software development, the idea of having agile processes started to be tested in other areas, for example, agile business process development. This trend already reached the research community and there have appeared some materials that suggest using agility in research projects. Analysis of these suggestions, however, shows that they do not go beyond finding superficial analogy between the concepts of the software development and research projects. The paper presents a deeper analysis of the concept of agile research in Information Systems (IS) based on the analysis of the research projects from the knowledge transformation perspective. As a basis for analysis, the SECI model of Nonaka is used. Based on this analysis, several suggestions are made on how to conduct agile research in IS, e.g. prioritize relevance over vigor, test early for a practical purpose, use own experience and reflections, etc. It is also shown that some research types, like action research and design science, are more suitable for conducting agile research than others. The paper also gives analysis of risks of non-agile research, and presents an example where they are revealed.

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Agile Research in Information
Systems Field
Analysis from Knowledge Transformation
Perspective
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Ilia Bider
8th IADIS International
Conference on
Information Systems 2015

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Motivation – personal perspective
• Personal background – relevant practice
– Software development - (requirements engineering,
programming, management, introducing IT in organizations)
– Business process & BPS support systems development
(process modeling, system development, introduction in
practice)
• Personal background – relevant research
– Analysis of Traditional vs Agile from knowledge
transformation perspective for both software development and
business process development
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Motivation – personal perspective
• A seminar on agile research at our department -
Autumn 2014 by Michael Twidale
• An idea to try the same approach to analysis of the
notion of agile research as we used for agile system
and business process development
• The results of application of this idea is what I want to
present today
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Goal
Answer the questions
1. Is it possible to define a notion of “agile research”,
more specifically a notion of “agile research
project”?
2. If yes how it differs from non-agile research
(project)?
3. Is there any existing types of research projects
that can be called agile?
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Plan of presentation
1. Showing how knowledge transformation perspective
can be used for analysis agile vs non-agile project in
other domains.
2. Analysis of previous attempts to define agile research
3. Defining analogous of working software for research
4. Applying approach from 1 to the research world
5. Discussing already existing types of research projects
that can be considered as agile
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Background: SECI Model
SECI model of knowledge transformation of Nonaka:
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Nonaka, I., 1994. A dynamic theory of
organizational knowledge creation.
Organization science, 5(1), pp.14-37..
Two types of knowledge:
– Explicit
– Tacit
Tacit
Explicit
Externalization
Explicit
CombinationInternalization
Socialization
Tacit
ExplicitExplicit
Tacit
Tacit
Tacit
Tacit
Externalization
Tacit
Combination
Internalization Socialization
Explicit
ExplicitExplicit
Explicit
Tacit

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Knowledge transformation: TSD
ECEA - a model of Traditional Software Development (TSD)
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Additional type of knowledge:
Embedded knowledge
Each model is a simplification
Tacit
Explicit
Externalization
Explicit
CombinationInternalization
Socialization
Tacit
ExplicitExplicit
Tacit
Tacit

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Knowledge transformation: ASD
SEA - a model of Agile Software Development (ASD):
Avoiding explication of knowledge
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Difference:
1. Requirements: engineering ->
discovery
2. Design + Coding = Embedment
3. One big cycle -> many small
Tacit
Tacit
Externalization
Tacit
Combination
Internalization Socialization
Explicit
ExplicitExplicit
Explicit
Tacit

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Usability of the Models
• Analysis of advantages, drawbacks, and risks for each
type of SD
• Areas of applicability for ASD (and TSD)
Both without going into details, e.g. XP, SCRUM, etc.
References:
Bider I. Analysis of Agile Software Development from the Knowledge Transformation Perspective.
In: Proceedings of BIR 2014, LNBIP 194, Springer 2014, pp. 143-157.
Extended version as a chapter in a coming book: Software Engineering in the Systems Context.
Edited by Ivar Jacobson and Harold “Bud” Lawson. College Publishing, Systems series, 2015
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10. DSV SU + IbisSoft
Plan of presentation
1. Showing how knowledge transformation perspective
can be used for analysis agile vs non-agile project in
other domains.
2. Analysis of previous attempts to define agile research
3. Defining analogous of working software for research
4. Applying approach from 1 to the research world
5. Discussing already existing types of research projects
that can be considered as agile
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Analysis of previous attempts
• Rewriting agile manifesto http://agilemanifesto.org,
examples:
– http://xavier.amatriain.net/AgileResearch/
– http://www.infoq.com/articles/agile-academic-research
• Superficial and fail to define “working software” in
Value working software over
comprehensive documentation
Examples: “real-world working solutions over comprehensive theories”
document, such as research project report, a paper, or a PhD thesis
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12. DSV SU + IbisSoft
Plan of presentation
1. Showing how knowledge transformation perspective
can be used for analysis agile vs non-agile project in
other domains.
2. Analysis of previous attempts to define agile research
3. Defining analogous of working software for research
4. Applying approach from 1 to the research world
5. Discussing already existing types of research projects
that can be considered as agile
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Defining “working software”
• In software world:
1. The software is functioning and is free from the major bugs
2. The software is actually used in the context for which it was
intended
• In IS research world:
– Software = scientific knowledge, e.g. a theory, that exists in
an explicit form
– Usage: to explain, to describe, to predict, to analyze and to
design or take action, … (Gregor, S., 2006. The Nature of Theory in
Information Systems. MIS Quarterly, 30(3), pp.611-42.)
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Defining “working software”
• Working scientific knowledge:
1. The knowledge in its explicit form has no contradictions
2. There is at least one individual for whom this knowledge
became tacit and he/she has successfully used it for some
purpose
• Based on
– In the end all knowledge needs to become personal and tacit
(Polanyi, M.S., 1969. Knowing and Being. Chicago: University of Chicago.)
– Essentially all models are wrong, but some of them are useful
(Box, G. E. P., and Draper, N. R., (1987), Empirical Model Building and Response
Surfaces, John Wiley & Sons, New York, NY)
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15. DSV SU + IbisSoft
Plan of presentation
1. Showing how knowledge transformation perspective
can be used for analysis agile vs non-agile project in
other domains.
2. Analysis of previous attempts to define agile research
3. Defining analogous of working software for research
4. Applying approach from 1 to the research world
5. Discussing already existing types of research projects
that can be considered as agile
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Knowledge transformation: TR
ECCI - a model of Traditional Research (TR)
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Embedded knowledge:
1. Systems artifacts, e.g. documents, IT systems
2. Tacit knowledge of human participants
Tacit
Explicit
Externalization
Explicit
CombinationInternalization
Socialization
Tacit
ExplicitExplicit
Tacit
Tacit

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Advantages & Risks with TR
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+ Higher status: rigor
- Long cycle, sensitive to the right
decision taken at the first stages:
instability
- Formulated in a way that prevents
adoption: lack of relevance
- Could be applied only to existing
Information System: limitation

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Knowledge transformation: AR
AEI - a model of Agile Research (AR):
Postponing explication of knowledge
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Involvement:
1. Socialization
2. Being part of the system
3. Being part of the intervention
project
Tacit
Tacit
Externalization
Tacit
Combination
Internalization Socialization
Explicit
ExplicitExplicit
Explicit
Tacit

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Advantages & drawbacks of AR
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Mitigating the TR risks
+ Instability & Lack of relevance are mitigated by
smaller cycles
+ Could be applied to innovative Information System
through disruptive intervention projects
Drawbacks
- Lack of rigor on the first cycles
Requirements on researcher (limitations)
• Capability to be involved
• Capability to reflect
Different skills set than for a traditional research

20. DSV SU + IbisSoft
Plan of presentation
1. Showing how knowledge transformation perspective
can be used for analysis agile vs non-agile project in
other domains.
2. Analysis of previous attempts to define agile research
3. Defining analogous of working software for research
4. Applying approach from 1 to the research world
5. Discussing already existing types of research projects
that can be considered as agile
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Agile research projects type
1. Action research (Lewin, K., 1952. Field theory in social science: Selected
theoretical papers by Kurt Lewin. London: Tavistock)
2. Design science (Hevner, A.R., March, S.T. & and, P.J., 2004. Design
Science in Information Systems Research. MIS Quarterly, 28(1), pp.75-105)
3. Reflective theory building (Mott, V., 1996. Knowledge comes from
practice: Reflective theory building in practice. In R.W. Rowden, ed. Workplace
learning: Debating five critical questions of theory and practice. San Francisco,
CA: Jossey-Bass. pp.57-63)
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Action research
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Kolb’s cycle of experimental learning – researcher is part of the system

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Goal reached
Answer the questions
1. Is it possible to define a notion of “agile research”?
Yes, through a model of knowledge transformation
2. If yes how it differs from non-agile research?
Yes, through comparing the agile model with the
traditional one
3. Is there any existing types of research projects that can be
called agile?
Yes, action research, design science, reflective theory
building
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Potential usability
Of the presented agile research (reflections on my
research experience)
1. Analysis of successful and unsuccessful past
research projects (learning from success and failures)
2. Decision making (to use TR or AR)
3. Project planning for AR
4. Research education.
Needs testing
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Q & A
Thank you for your patience
Questions and comments
Please
Contact: ilia@{dsv.su|ibissoft}.se
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