Case study analysis of the Erasmus student mobility within the ECIU consortium for the academic years 2007/2008 to 2011/2012

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Goran Đaković
Master thesis colloquium
Enschede, 30. 6. 2014
1
THE IMPACT OF CONSORTIUM
CHARACTERISTICS ON CREDIT RECOGNITION
PERFORMANCE
Case study analysis of the Erasmus student mobility
in frames of the ECIU consortium
for the academic years 2007/2008 to 2011/2012

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General research question
How do consortium characteristics (structural embeddedness
attributes with the interrelating social mechanisms) influence the
credit recognition performance at the individual partner
universities?

3. The European Consortium of Innovative Universities (geographically)

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“Black-box” of higher education consortium

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The higher education consortium
Network
administrative
organization
(NAO)
- Inter-organizational network (3 or more universities),
- Indefinite time-span,
- Selected partners,
- Multidisciplinary network,
- Integration, equity, intensity (E. Beerkens, 2004).
- Clearly identifiable contribution of all partners (Burley et al., 2011)
Formal
contract

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Student mobilities within the higher education consortium
- One of joint consortium activities are student mobilities, such as the Erasmus student mobilities
- Specific network form according to the frequency of mobility activities
- The usage of programme based credit recognition tools (ECTS, Course Catalogues, the ECTS Users’
Guide, the Transcript of Records, the Learning Agreement) (Education and Culture DG, 2009) or
- Additional, consortium specific credit recognition tools
Theory vs. practice

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Case study consortium:
the European Consortium of Innovative Universities (ECIU)
- Data analysis: five consecutive academic years from 2007/2008 to 2011/2012
- Source: official mobility records of the Erasmus programme (903.831 students from 3049 universities)
Consortium ECIU
Year of establishment 1997
Number of partners (network vertices) 11
Number of student exchanges between consortium partners from
2007/2008 to 2011/2012
573
Number of cooperation paths (lines) from 2007/2008 to
2011/2012*
53
Density** 0,48
Degree centrality partners (university number) 10 and 9

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Theoretical model of inter-organizational processes within
the consortium: the identification of consortium
characteristics
Institutional transaction
costs
Structural embeddedness
Social mechanisms
Credit recognition
performance
Institutional resource
dependency
+
-
+
+
+
Control mechanisms
(network centrality position,
status characteristics)
+
3 theories:
- structural embeddedness (Granovetter, 1985; Uzzi, 1997)
- transaction costs economics: frequency, specificity, uncertainty, bounded rationality, opportunism (Williamson, 1975)
- Resource dependency theory: heterogeneous institutions in relation to the resources they control (Barney, 1991)
Author: Dakovic, 2014

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Hypothesis 1:
If student mobility is implemented within the higher education consortium, the credit recognition
performance rises due to the structural embeddedness of consortium members through information
sharing, joint problem solving, the inter-organizational trust and the reciprocity of its members.
Hypothesis 2:
If student mobility is implemented within the higher education consortium, the credit recognition
performance rises due to the intermediary impact of social mechanisms inside the consortium; such as
the commitment, the idiosyncratic language, the restricted access to exchanges, collective sanctions,
and the reputation of its members.
Hypotheses

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Operationalization of the research model
Structural embeddedness variables:
- Information sharing
- Joint problem solving
- Inter-organizational trust
- Reciprocity
Social mechanisms variables:
- Commitment
- Idiosyncratic language
- Restricted access to exchanges
- Collective sanctions
- Reputation
Credit recognition performance variables:
- Matching ratio of study courses
- Length of administrative procedures
- Level of developed organizational
procedures
- Level of satisfaction with learning
outcomes by higher education teachers+
+
INDEPENDENT DEPENDENTINTERMEDIARY

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- Interpretative qualitative research: the concept of higher education consortium is underexplored; a
need for more substantive input; methodological reason
- Research design: the case study (Merriam, 2002)
- Why ECIU: innovative approaches; sufficient tradition; cohesive consortium structure with few network
newcomers; the European wide consortium; the accessibility to the consortium
- Data collection: the semi-structured interviews (open-ended questions) and document analyses
- Who: ECIU representative universities + NAO (selection procedure is based on control
mechanisms: the network centrality position of consortium members; and their status characteristics)
- Data analysis: SNA (Pajek software) and qualitative, code analysis (Atlas.ti software) – inductive
approach
The research design
Network centrality positionType of institutional mobility flowsThe duration of membership

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Empirical results for credit recognition performance
variables
Credit recognition
performance variables
(dependent variables)
 Level of satisfaction
with learning
outcomes (red)
 Length of
administrative
procedures (blue)
 Matching ratio of
study courses
 Level of developed
organizational
procedures
- The primacy of educational quality and the impact of HE teachers (PRIME Report from 2010)
- Network as a repository of additional information – shorter recognition processes

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Empirical results for structural embeddedness variables
Structural embeddedness variables
(independent variables)
 (+) Inter-organizational trust
(blue)
 (+) Joint problem solving
 Information sharing
 Reciprocity
- Reliability and predictability of consortium partners in delivering the requested educational quality
- The relevance of existing governance mechanisms despite their absence in the ECIU

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Empirical results for social mechanisms’ variables
Social mechanisms variables
(intermediary variables)
 (+) Idiosyncratic language
(red)
 (-) Collective sanctions
(yellow)
 Commitment
 Restricted access to
exchanges
 Reputation
- Social context of language offers additional information about the partners (perceived proximity)
- Collective sanctions have an opposite effect: good camaraderie between partners, education quality is
therefore a taboo topic

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Outcomes of the study
Structural embeddedness
variables:
- Inter-organizational trust
(academic reliability)
- Joint problem solving (in
connection with the trust
variable)
Credit recognition performance
variables:
- Level of satisfaction with the
learning outcomes by higher
education teachers
- Length of administrative procedures
++
Social mechanisms variables:
- Idiosyncratic language
-
Social mechanism variables:
- Collective sanctions

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Outcomes of the study
-The more the university is involved with the consortium mobilities, the more accessible
are the opportunities to this university to use the beneficial aspects of the consortium
mobilities
Characteristics
of the network
where the
results appear:
high network
density
The location of
empirical results
- Presence of the research outcomes within the ECIU consortium

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Recommendations for the ECIU
The list of recommendations for the better credit recognition performance
within the ECIU consortium
1. Reinforce the value of the existing Memorandums of Understanding (the
actual implementation of the agreements)
2. Sign the Shared Erasmus Agreement
3. Empower the role of the network administrative organization (NAO) in the
consortium mobilities (for the promotion of the academic quality of the
consortium members)
4. Include all network members in the consortium mobilities
5. Use deliberately the benefits of the idiosyncratic dimension of language
6. Openly discuss the academic and administrative performance of all network
members
7. Introduce the new Erasmus+ mobility documents (rather than designing the
separate mobility documents)
8. Do not discriminate Erasmus students in regards to their home university

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Reflections
- Contribution to the science on higher education policies and practices
- Triggering the discussion on the organizational matters of student mobilities (an
opportunity for rearrangement of the existing student mobilities (appearing subgroups of
islands) into different, more structured mobility approaches)
- the equality of all Erasmus students during their mobility periods (the “nature” of the
Erasmus student mobility programme)
- the influence of network density and the network governance forms on research
outcomes
- Follow-up research: quantitative research (e.g. multiple linear regression analysis;
structural equation modelling (SEM) techniques) for statistically relevant outcomes

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The influence of network density
U-DRIVE ECIU LERU

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The influence of network governance forms – “the network
governance triangle”
x
Source: adjusted from Kenis and Provan (2009, p. 447)

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Discussion