Knowledge Transfer in Regulatory Analytical Sciences through the

Implementation of Communities of Practice

Joanna Jesionkowska

, Brigitte Denis

and Philip Taylor

The Institute for Reference Materials and Measurements, Joint Research Centre, European Commission

Department of Education and Training, University of Liège, Liège, Belgium

1 STAGE OF THE RESEARCH

This doctoral project started at the beginning of the

academic year 2013-2014 at the Department of

Education and Training, University of Liege under

the supervision of B. Denis and P. Taylor. The first

step of the work, the need analysis (see section 5.2.)

is almost finished. The literature review on the two

main aspects of the thesis (communities of practice

supported by technologies, knowledge transfer) is

ongoing. The research question and hypotheses are

defined as the general methodology linked to them.

The thesis is planned for three years.

2 OUTLINE OF OBJECTIVES

This project purpose is studying how the

development of a Community of Practice supported

by Information and Communication Technologies

enhances the transfer, capitalisation and production

of knowledge between scientists (experts and

novices) in the context of the European Commission

- Joint Research Centre - Institute for Reference

Materials and Measurements (EC-JRC-IRMM)

measurement and standards activities.

The aim is create the space where scientists

(analytical chemists) would have the opportunity to

interact, share the experience, search specific

information in the area of their interest, map the

knowledge and identify the gaps, solve the problems

together, seek for experience and coordinate shared

projects. The scientists who are geographically

dispersed could work together using appropriate

technology to access each other: remote tools,

databases, and instruments (National Research

Council, 1993). Community of practice could

provide such space for discussion and professional

development of its members.

3 RESEARCH PROBLEM

Today, organisations, workgroups, teams, and

individuals work together in new ways. Inter-

organisational collaboration is increasingly

important. Communities of practice provide a new

model for connecting people in the spirit of learning,

knowledge sharing, and collaboration as well as

individual, group, and organizational development.

This gives new possibilities which could be used in

scientific environment.

Most scientists are involved in international and

interinstitutional projects. They share information,

work together in teams and manage tasks throughout

different organizations and diverse geographic

locations. Very often the work and documentary

output mainly rely on traditional communication

tools, mainly cumbersome email, which does not

give the visibility on the conversations and

document postings. There is also no benefit from a

community which grows around given

network/activity.

Promoting affiliation between scientists is

relatively easy, but creating larger organizational

structures is much more difficult, due to traditions of

scientific independence, difficulties of sharing

implicit knowledge, and formal organizational

barriers. (Bos, Zimmerman, Olson, Yew, Yerkie,

Dahl & Olson 2007). There is a long tradition of

informal, one-to-one collaborations between

scientists, but the scientific environment lack the

model of more tightly coordinated, large-scale

organizational structures.

There is a need to search for a new way of

working together that would solve the problems: a

network-based space that spans distance, supports

rich and recurring human interaction oriented to a

common research area, fosters contact between

researchers who are both known and unknown to

each other, and provides access to data sources,

artifacts and tools required to accomplish research

tasks (Wulf, 1989)

Jesionkowska J., Denis B. and Taylor P..

Knowledge Transfer in Regulatory Analytical Sciences through the Implementation of Communities of Practice.

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

Hence there is a need to research possibilities given

by CoPs in the area of sciences and develop and

optimize the solutions to supports its activities.

4 STATE OF THE ART

4.1 Knowledge Transfer in an

Organisation

Knowledge is socially embedded and highly

context-specific, and these characteristics make it

difficult to transfer knowledge (Brown & Dugid,

1998). The process of knowledge transfer requires

commitments of resources, managerial time,

attention, and effort (Chen, 2004; Easterby-Smith,

Lyles, & Tsang, 2008). Knowledge transfer is a

socially collaborative construct, management

scholars have long recognized its contextual nature

(Björkman, Barner-Rasmussen, & Li, 2004; Foss &

Pedersen, 2002; Lyles & Salk, 1996). Knowledge-

sharing behaviours, in terms of knowledge giving

and knowing receiving, are significantly predicted

by prosocial commitment and performance

expectation (Tseng & Kuo, 2014).

Knowledge transfer (KT) seeks to organise,

create, capture or distribute knowledge and ensure

its availability for future users. KT is complex

because knowledge resides in organisational

members, tools, tasks, and their subnetworks

(Argote & Ingram, 2000) and much knowledge in

organisations is tacit or hard to articulate (Nonaka &

Takeuchi, 1995). The knowledge gained by research

is often isolated from the practitioners in the field.

Likewise, tacit knowledge from the field rarely

reaches the researchers or those making decisions.

More effective bridges between knowledge, policy

and practice are needed, with communities of

practice (CoPs) well positioned to do that (Hearn &

White, 2009).

Knowledge in the organisation can refer to the

theoretical or practical understanding of a subject. It

can be implicit (as with practical skill or expertise)

or explicit (as with the theoretical understanding of a

subject); it can be more or less formal or systematic.

There are three kinds of knowledge: "knowledge as

object", "knowledge embedded within individuals",

and "knowledge embedded in a community" (Wasko

& Faraj, 2000). Communities of Practice have

become associated with finding, sharing,

transferring, and archiving knowledge, as well as

creating explicit "expertise", or tacit knowledge.

Tacit knowledge is considered to be those valuable

context-based experiences that cannot easily be

captured, codified and stored (Davenport & Prusak,

2000; Hildreth & Kimble, 2002).

Because knowledge management is seen

"primarily as a problem of capturing, organising,

and retrieving information, evoking notions of

databases, documents, query languages, and data

mining" (Thomas, 2001), the community of practice,

collectively and individually, is considered as a rich

potential source of helpful information in the form

of actual experiences. Thus, for knowledge

management, a community of practice is one source

of content and context that if codified, documented

and archived can be accessed for later use.

4.2 Communities of Practice and

Information and Communication

Technologies

A community of practice is a group of people who

share a common concern, a set of problems, or

interest in a topic and who come together to fulfil

both individual and group goals (Wenger, 1998;

Wenger, 2002). CoPs often focus on sharing best

practices and creating new knowledge to advance a

domain of professional practice. According to

Wenger (1998), people who want to participate in

CoPs get ready to share their knowledge, sharpen

their expertise, build up interpersonal networks and

pursue their interest. Different roles appear among

the CoP members and, in certain contexts, the

presence of an animator is necessary to facilitate

their activities (Snoeck, 2010). A CoP emerges

spontaneously or/and through a participatory design

process (Ashwin, 2009). Communities have

lifecycles—they emerge, they grow, and they have

life spans (Kaplan & Suter, 2005). Wegner (2004)

described that CoPs continually evolve through five

stages: potential, coalescing, maturing, stewardship

and transformation.

Face-to-face or virtual interactions on an on-

going basis are an important part of this. An

important feature of virtual communities is to bring

knowledge seekers and providers into one virtual

space that is equipped with knowledge databases

over networks (Shin & Kook 2014). Virtual CoPs

help knowledge management by capturing and

sharing of the expertise of members, spreading

know-how, ideas, problems, innovations, talents,

and experiences. Nowadays, much knowledge

sharing and knowledge construction takes place in

online environments (Kimmerle et al., 2013). These

communities use a variety of communication tools

(e.g., via discussion board, article commenting,

rating, poll, wiki, webinar) to foster discussion and

KnowledgeTransferinRegulatoryAnalyticalSciencesthroughtheImplementationofCommunitiesofPractice

the exchange of ideas (Wenger et al, 2010).

Since the widespread adoption of the Internet,

management scholars in general, and information

systems researchers in particular, have emphasized

how knowledge-work depends not only on new

communication affordances but also on the

behaviors and motivations of those who undertake

and manage it (Newell et al., 2009). Learning in

online environments is supported by three presences

– social presence, teaching presence, and cognitive

presence – that work together to support deep and

meaningful inquiry and learning online (Swan et al.,

2014). Prominent works focus on co-located or

distributed work groups (Dourish & Bly, 1992;

Gupta et al., 2009), project teams (Kietzmann, et al.,

2013; Evaristo et al., 2004; Oshri et al., 2008),

consortia, alliances, and joint ventures (Ibrahim &

Ribbers, 2009; Miles & Snow, 1995).

The community knowledge is a social concept of

knowledge as conceptual artifacts that have a public

life (Bereiter, 2002; Hyman, 1999; Popper, 1972). It

is public knowledge ideas made accessible to all

community members through contributions to

collective knowledge spaces. Community

knowledge involves a dynamic process interactions

between ideas and people knowledge (i.e., knowing

people’s expertise) with participants monitoring who

is working on what ideas or problems and advancing

knowledge in the community (Hong & Lin-Siegler,

2012). The community knowledge is the cultural or

intellectual capital of the community (Scardamalia

& Bereiter 2003, Hong & Scardamalia 2014).

4.3 Domain: Regulatory Analytical

Sciences

Modern societies are highly dependent on analytical

measurements. They play an important role not only

in science, but also in daily life. Based on the results

of such measurements decisions are taken regarding

health, food safety, manufacturing of goods, the

development of innovative products, the quality of

our environment, trade of goods and commodities;

Analytical chemistry is the study of the

separation, identification, and quantification of the

chemical components of natural and artificial

materials (Holler, Skoog, & West, 1996). Qualitative

analysis gives an indication of the identity of the

chemical species in the sample and quantitative

analysis determines the amount of one or more of

these components.

The Regulatory Analytical Sciences (RAS) objective

is to apply analytical science in the public interest,

acting as the referee analyst in cases of dispute and

providing advice to policy makers and industry. The

principal roles of RAS are:

• To act as an independent and impartial

referee analyst, authorised analyst and analyst by

reference to or pursuant to certain legislation,

• To be a source of advice for policy makers

and the wider analytical community on the analytical

chemistry implications on matters of policy and of

standards and of regulations.

Performing reliable measurements is not trivial and

requires knowledge and skills. Therefore training

and education in this area is important. The Joint

Research Centre (JRC) runs a life long learning

activity (www.trainmic.org) and fosters educational

activities in this area.

4.3.1 Context of the EC-JRC-IRMM's

Measurement and Standards Activities

The Joint Research Centre (JRC) is a European

Commission's in-house science service and a

reference centre interacting closely with Member

State institutions. As a service of the European

Commission, the JRC functions as a reference centre

of science and technology to provide customer-

driven scientific and technical support for the

conception, development, implementation and

monitoring of EU policies and legislation. JRC is

constituted of seven institutes. One of them, the

Institute for Reference Materials and Measurements

(IRMM) supports industrial competitiveness, quality

of life, safety and security in the EU by developing

advanced measurement standards and providing

state-of-the-art scientific advice concerning

measurements and standards for EU policies. One of

IRMM's objectives is to act as a learning and

knowledge hub on standardisation and measurement

in Europe, particularly in analytical sciences. A unit

of IRMM, the Knowledge Transfer & Standards for

Security (KNOTSS) is in charge of training

laboratory staff, researchers, educators, decision-

makers and accreditation assessors in metrology in

chemistry, in order to strengthen the measurement

infrastructure.

Thirteen years ago, KNOTSS has developed the

TrainMiC® programme. It is based on organisation

of one day workshops (theory and exercises) and

providing learning materials to the participants. The

training methodology does not provide a large space

to share knowledge between scientists. The

opportunity to interact and share experiences and

knowledge is not enhanced outside this meeting.

Professionals stay isolated in their laboratories. Then

the objective of exploiting the potential of the actors

IC3K2014-DoctoralConsortium

(especially the experts), of transfer, capitalisation

and knowledge production is difficult to reach. A

solution could be found in developing a Community

of Practice between these professionals.

5 METHODOLOGY

This study resorts to qualitative and quantitative

methods, such as interviews, focus groups,

questionnaires, observation grids. It is based on

participatory design. Actors are involved at the

different steps of the work. Details are provided in

section 5.3, after the presentation of the project’s

steps and tasks below.

The data collected will help us to test the

following hypotheses.

5.1 Hypotheses

H1. The creation of a CoP supported by ICT

matches learning needs of Actors of Regulatory

Analytical Sciences.

H2. The CoP’s life is conditioned by a participatory

design process.

H3. The presence of an external facilitator is

considered as necessary by the CoP’s members to

start the CoP’s activities.

H4. Core CoP’s members take autonomously in

charge the CoP’s animation.

H5. Both CoP’s experts and novices members share

their own knowledge on M&S.

H6. Novices are more motivated to participate to the

CoP than experts in the field of M&S

H7. CoP’s members capitalise knowledge on M&S.

H8. CoP’s members generate new knowledge on

M&S.

5.2 Steps and Tasks of the Research

Four main phases are identified to conduct this

project.

Step 1: Need analysis

- Make actors’ cartography at different

systemic levels and roles description.

- Identify key stakeholders and final users

(among TrainMic® actors) to constitute the group of

people to carry on the participatory design process

(from needs analysis to implementation) of a new

learning environment.

- Among TrainMiC® actors, identify why

changing is necessary, specific needs, key issues and

the nature of the learning, major topics, knowledge

and tasks that the community would steward,

primary purpose, potential benefits, goals and vision

for relevant community.

- Analyse the context to ensure the feasibility

of the creation of a CoP supported by ICT (e.g.

actors’ level of ICT uses, available technologies,

technical team, budget…).

- Feed the needs analysis with existing

experiences inside and outside the IRMM unit.

Step 2: Design of the CoP

- Determine CoP’s actors’ roles.

- Identify degrees of expertise (expert,

novice…) in the field of M&S of potential CoP’s

members.

- Choose (or/and develop) a technological

solution to communicate, share and collaborate that

will generate interactions, energy and engagement,

learning goals…

- Start the recruitment of a core team of

individuals who represent the community audience.

- Create a mission and vision: alignment of

interests.

- Choose together the major topic areas for

community content and exploration, potential

categories of activities that community members are

likely to want to carry out in the community,

communication paths…

- Familiarise the members to the use of the

ICT tools (e.g. create a directory or folder structure

for organizing resources, interact in forums, edit

shared documents…)

- Lay out a tentative schedule for the

community (weekly, monthly, quarterly, and/or

annually), create a timeline for the community’s

development.

Step 3: Piloting the activity

Engaging members in collaborative learning and

knowledge sharing activities, group projects and

networking events that meet individual, group and

organisational goals, while creating and increasing

cycle of participation and contribution.

- Test community-oriented technology

features to support the goals of the pilot, test the

functionalities through case scenarios.

- Implement the community prototype and

give access to the core team and pilot audience.

- Seed the community with content.

- Facilitate events and activities to exercise

the prototype, focusing on achieving short-term

value-added goals.

Step 4: Evaluation and regulation

Observe the CoP development process (actors’

enrolment, community identity, types of activities,

KnowledgeTransferinRegulatoryAnalyticalSciencesthroughtheImplementationofCommunitiesofPractice

online environment uses, community culture, etc.).

Refine the strategy. Establish a success story.

5.2 Methods and Instruments

In step 1: Need analysis

- Interviews of IRMM coordinators, TrainMic®

team members (stakeholders, trainers, trainees).

- Institutional documents analysis.

- Interviews and/or focus groups, TrainMic®

documents.

- Questionnaires

- Interviews

- Analysis and literature review about CoPs

In step 2: designing of the CoP

Participatory design methodology (Charlier, Henry

et al. 2009)

- communication and collaboration through face-to-

face and virtual meetings

- use of learning design models

- interviews

- questionnaires

In step 3: Piloting the activity

- Opinion questionnaires and interviews.

- Focus groups.

- Traces analysis of members’s activity:

* connections, use of the technological tools, types

of interactions…

* counting and categorisation of shared resources.

* organisation of shared resources.

- Direct observation.

In step 4: Evaluation and regulation

Permanent regulation through observations and

CoP’s members constraints and needs.

Measure success and report on the results of the

prototype to stakeholders.

6 EXPECTED OUTCOME

The Community of Practice supported by

Information and Communication Technologies

should enhance the transfer, capitalisation and

production of knowledge between scientists.

Planned activities of JRC stewarded knowledge

community would be:

 sharing and exchanging information on existing

and new technical/scientific and legislative

developments in this field

 building a consensus opinion on sensitive policy

issues starting from scientific-technical

interaction

 organising scientific events and seminars and

particularly science-policy interfacing events

 providing training and set up sustainable Life

Long Learning activities

 influencing educators and fostering education ,

e.g. via summer schools

 promoting the harmonisation of measurements

and co-ordinate QA/QC activities

 performing method development and validation,

harmonising practice, participating to

standardisation activities

 developing common research projects and pilot

studies

A model of a CoP created for the context of the EC-

JRC-IRMM's measurement and standards activities

could be used in a future to create CoPs in other

areas of interests of Regulatory Analytical Sciences.

REFERENCES

Argote, L., & Ingram, P. (2000). Knowledge transfer: A

Basis for Competitive Advantage in Firms.

Organizational Behavior and Human Decision

Processes 82 (1), 150–169.

Ashwin, P., Daele, A., Barlatier, P., Charlier, B., Denis,

B., Henri, F., Jacquemart, S., Künzel, M., Rieppi, S.,

Rossier, A., Van de Wiele, N. (2009). PALETTE:

Learning and Organisational Resources: Conceptual

Instruments for Self- Analysis, Learning and

Developments of CoPs, External report ERCIM,

Report number: D.PAR.06.

Bereiter, C. (2002). Education and mind in the knowledge

age. Mahwah, NJ: Lawrence Erlbaum Associates.

Björkman I., Barner-Rasmussen W., Li L. (2004):

Managing knowledge transfer in MNCs. A

comprehensive test of headquarters control

mechanisms. Journal of International Business Studies,

35 (5): 443-454.

Brown J.S., Duguid P., (1998) Organizing knowledge,

California Management Review 40 (3) 90–111.

Chen C. (2004) The effects of knowledge attribute,

alliance characteristics, and absorptive capacity on

knowledge transfer performance R&D Management

Volume 34, Issue 3, pages 311–321.

Davenport, T. H., & Prusak, L. (2000). Working

knowledge. How organizations manage what they

know, 2nd Edition. Cambridge, MA: Harvard Business

School Press.

Easterby-Smith, M., Lyles, M., Tsang, E. (2008) Inter-

Organizational Knowledge Transfer: Current Themes

and Future Prospects Journal of Management Studies,

Volume 45, Issue 4, pages 677–690.

Evaristo, R.J., Scudder, R., Desouza, K.C. (2004). A

dimensional analysis of geographically distributed

project teams: A case study. Journal of Engineering

Technology Management, 21(3), 175-189.

IC3K2014-DoctoralConsortium

Foss N, Pedersen T. (2002) Transferring Knowledge in

MNCs: The Roles of Sources of Subsidiary Knowledge

and Organizational Context. Journal of International

Management 8: 1-19.

Gupta, J. et. al. (2009). Evidence-Based Practice

Academic Partnerships. Presented at the 2009 AOTA

Annual Conference and Expo, Houston, TX April 23-

26.

Hearn, S., White, N. (2009) Communities of practice:

linking knowledge, policy and practice Overseas

Development Institute 2009. ISSN 1756-7610.

Hildreth, P., & Kimble, C. (2002). The duality of

knowledge . Information Research 8.

Holler, F. J., Skoog, D. A., West, D. M. (1996).

Fundamentals of analytical chemistry. Philadelphia:

Saunders College Pub.

Hong H., Scardamalia M. (2014) Community knowledge

assessment in a knowledge building environment

Computers & Education, Volume 71, February 2014,

Pages 279-288.

Hong, H., Lin-Siegler, X. (2012) How learning about

scientists' struggles influences students' interest and

learning in physics. Journal of Educational

Psychology, Vol 104(2).

Hyman, J. (1999) How Knowledge Works. The

Philosophical Quarterly 49: 433 – 51.

Ibrahim, M.K.M., Ribbers, P.M.A. (2009). The impacts of

competence-trust and openness-trust on

interorganizational systems. European Journal of

Information Systems, 18(3), 223-234.

Kaplan S., Suter. V. (2005). Community of Practice

Design Giude, A Step-by-Step Guide for Designing &

Cultivating Communities of Practice in Higher

Education. Darren Cambridge.

Kietzmann J., Plangger K., Eaton B., Heilgenberg K., Pitt

L., Berthon P. (2013) Mobility at work: A typology of

mobile communities of practice and contextual

ambidexterity The Journal of Strategic Information

Systems, Volume 22, Issue 4, Pages 282-297.

Kimmerle J., Thiel A., Gerbing K., Bientzle M.,

Halatchliyski M., Cress U. (2013) Knowledge

construction in an outsider community: Extending the

communities of practice concept Computers in Human

Behavior, Volume 29, Pages 1078-1090.

Lyles, M., Salk, J. (1996) Knowledge acquisition from

foreign parents in international joint ventures: an

empirical examination in the Hungarian context,

Journal of International Business Studies 29(2): 154–

174.

Miles, C. C., Snow, R. E. (1995) The new network firm: A

spherical structure built on a human investment

philosophy. Organizational Dynamics 23(4):5–20.

Popper, K. R. (1972) Objective Knowledge, Clarendon

Press, Oxford. 2nd edition.

National Research Council. National Collaboratories:

Applying Information Technology for Scientific

Research. Washington, DC: The National Academies

Press, 1993.

Newell, S., Robertson, M., Scarbrough, H., & Swan, J.

(2009). Managing Knowledge Work. 2nd edition.

Basingstoke: Palgrave.

Nieman, T. A., Skoog, D. A., & Holler, F. J. (1998).

Principles of instrumental analysis. Pacific Grove,

CA: Brooks/Cole.

Nonaka, I., & Takeuchi, H. (1995). The Knowledge-

Creating Company. New York, NY: Oxford

University Press.

Oshri, I., van Fenema P. C., Kotlarsky J. (2008).

Knowledge Transfer in Globally Distributed Teams:

The Role of Transactive Memory. Information Systems

Journal 18(6): 593-616.

Scardamalia, M., Bereiter, C., (2003). Learning to work

creatively with knowledge. In E. De Corte, L.

Verschaffel, N. Entwistle, & J. van Merriënboer

(Eds.), Powerful learning environments: Unraveling

basic components and dimensions (pp. 55-68).

(Advances in Learning and Instruction Series).

Oxford, UK: Elsevier Science.

Snoeck (2010). Guide d'utilisation de la plateforme

eGroupWare. Liège: Centre de Recherche sur

l'Instrumentation, la Formation et l'Apprentissage de

l'Université de Liège.

Shin, S., Kook W. (2014) Can knowledge be more

accessible in a virtual network?: Collective dynamics

of knowledge transfer in a virtual knowledge

organization network Decision Support Systems,

Volume 59, Pages 180-189.

Swan, K., Day, S., Bogle, L., Matthews, D. (2014) A

collaborative, design-based approach to improving an

online program The Internet and Higher Education,

Volume 21, Pages 74-81.

Thomas J. C., K. W. (2001). The knowledge management

puzzle: Human and social factors in knowledge

management. IBM SYSTEMS JOURNAL, VOL 40, NO

4, .

Tseng, F., Kuo F. (2014) A study of social participation

and knowledge sharing in the teachers' online

professional community of practice Computers &

Education, Volume 72, March 2014, Pages 37-47.

Wasko, M., & Faraj, S. (2000). It is what one does": why

people participate and help others in electronic

communities of practice. Journal of Strategic

Information Systems 9 (2-3), 155–173.

Wenger, E. (1998). Communities of Practice. Learning,

Meaning, and Identity. United States of America:

Cambridge University Press.

Wenger E., McDermott R. & Snyder W.M. (2002).

Cultivating Communities of Practice. Harvard

Business School Press, Boston.

Wenger, E. (2010) Communities of practice and social

learning systems: the career of a concept. In

Blackmore, C. (Editor) Social Learning Systems and

communities of practice. Springer Verlag and the

Open University.

Wulf, W. (1989, March). The national collaboratory. In

Towards a national collaboratory. Unpublished report

of a National Science Foundation invitational

workshop, Rockefeller University, New York.

KnowledgeTransferinRegulatoryAnalyticalSciencesthroughtheImplementationofCommunitiesofPractice