1
Using Group Decision Support Systems to Facilitate
Organizational ChangeJeroen Monteban University of Twente
P.O. Box 217, 7500AE Enschede The Netherlands
ABSTRACT
Organizational change is an important topic in a world of ever
changing customer needs and globalization. Group Decision
Support Systems (GDSSs) seem to present themselves as an
excellent tool to facilitate this change, but are little used. This
paper investigates both organizational change and Group
Decision Support Systems and suggests how the latter can
facilitate the first. To do so, a literature review is conducted
and an experiment is performed to test whether the use of a
GDSS increases the quality of a brainstorm session. We
conclude in the literature review that the use of GDSSs in
organizational change seems promising and has the potential
to increase its quality and its support within the organization.
However, the experiment found no support that the use of a
GDSS increased the quality of brainstorm results.
Keywords
Organizational change, Group Decision Support System,
GDSS, OCAI, Spilter
1. INTRODUCTION Many organizations are faced with the challenge of adapting
to the ever changing needs of our globalized economy. Not
only are they subject to intensified competition due to
increasing globalization over the last decades [40] and ever
changing customer demands, all other stakeholder such as
employees and shareholder also have certain demands and
requirements, as do governments. In order to satisfy all
involved parties an organization finds itself in constant need
of change and adaption [35].
Lines et al. define organizational change as ‘a change in
organizational structures, systems, routines, technology or
product market domain that was intended to further the
achievement of important organizational objectives’ [25].
Many theories yet exist describing organizational change and
providing guidelines for successful change.
Group Decision Support System (GDSS) is a term used to
describe systems which ‘combine communication, computer,
and decision technologies to support problem formulation
and solution in group meetings’ [7].
The use of GDSSs seems perfect for the facilitation of
organizational change, as many decisions have to be made in
the process. All identifying, examining and implementing of
new ideas requires problem formulation and solution in group
meetings. The question that rises is why there is so little
information to be found about the application of GDSS in the
process of organizational change.
1.1 Problem statement Group Decision Support Systems have been a field of
research and development for the past two decades and are
regularly used in certain aspects of modern business.
However, in the often difficult process of organizational
change, GDSSs are scarcely used, which is proven by the lack
of information to be found on the use of it.
1.2 Research questions The problem statement above leads to the following main
research question:
How can Group Decision Support Systems be used to
effectively facilitate organizational change?
This main research question can be divided in the following
research questions:
1) Which stakeholders are involved in the process of
organizational change?
2) Which actions are required in the process of
organizational change?
3) What are the key strengths and advantages of
available Group Decision Support Systems?
4) How can a Group Decision Support System
effectively facilitate the required steps for
organizational change?
2. RESEARCH METHODS The research performed in this paper is twofold. First, a
literature review will be conducted on both organizational
change and GDSSs. With this review, we will create an
overview of the research that is already performed on these
subjects. Also, we will draft a view on the use of GDSS in
organizational change. Secondly, an experiment will be
performed, which will either confirm or refute the formulated
view.
2.1 Literature Conducting a literature review should be a structured process
resulting in an overview of the available literature on the
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topic. This paper will do a literature review based on the five-
stage grounded-theory method for reviewing literature by
Wolfswinkel et al. [38], which can be summarized by Table 1.
Table 1 Five-stage grounded-theory method for reviewing
literature
Number Task
1. DEFINE
1.1 Define the criteria for inclusion/exclusion
1.2 Identify the fields of research
1.3 Determine the appropriate sources
1.4 Decide on the specific search terms
2. SEARCH
2.1 Search
3. SELECT
3.1 Refine the sample
4. ANALYZE
4.1 Open coding
4.2 Axial coding
4.3 Selective coding
5. PRESENT
5.1 Represent and structure the content
5.2 Structure the article
2.2 Experiment To support the results found in the literature review, an
experiment will be conducted. This experiment aims to test
whether the use of a GDSS improves the results of a stage of
organizational change: brainstorming. With the data gathered
during the experiment we hope to confirm the results found in
the literature review.
The experiment will be designed using ‘Preliminary
Guidelines for Empirical Research in Software Engineering’
by Kitchenham et al. [21]. Here, Kitchenham et al. provide
guidelines for empirical research, such as we wish to conduct,
and pinpoint a number of common mistakes and pitfalls.
Although their guide is specifically focused on Software
Engineering and our experiment does not concern this, their
guidelines are still very useable with minor adjustments.
According to Kitchenham et al, six phases can be
distinguished in empirical research. Figure 1 shows these six
phases and provides a short description of the suggestions
made by Kitchenham et al. on the phases. The experiment
presented later in this paper is designed, executed and
described following this structure.
3. LITERATURE REVIEW This literature review will look into both research done on
organizational change and on Group Decision Support
Systems on the basis of the introduced research questions and
review method.
3.1 Organizational change As introduced, organizational change can be defined as a
change in an organization’s structure, system, routine,
technology or product market that is intended to accomplish
important organizational objectives [25]. As is clear, the
extent of the term organizational change is rather large and
involves most changes in organizations. In order to determine
in which way organizational change can be facilitated by
GDSSs, we will first dive deeper into the concepts of
organizational change. We will do this on the basis of the two
introduced research questions themed around organizational
Figure 1 Kitchenham’s six phases of empirical research
change: Which stakeholder are involved in the process of
organizational change? and Which actions are required in
the process of organizational change?
3.1.1 Involved stakeholders Firstly, we will examine the stakeholders involved in the
process of organizational change. Weiss defined stakeholders
as individuals, groups or organizations which can influence
the stages of development of a company [2]. Freeman
elaborated this view by considering stakeholders to be any
group or individuals who can affect or be affected by an
organization [11]. Stakeholders encompassed by this
definition can be found within the organization, such as
employees, managers and departments, but also outside the
organization, such as shareholders, suppliers and customers,
but also governments and competitors.
Of course, every organization has different stakeholders.
These different types of stakeholders are dependent on the
industrial context of an organization. Clearly, a University
will have different stakeholders than an oil company.
However, some stakeholders overlap, such as employees. The
art of analyzing stakeholders, conveniently called stakeholder
analysis, has gained an increased interest of management and
development [3]. The goal of this analysis is to gain insight in
the involved stakeholders and their relevance to the project.
This is done by reviewing their position, interest, influence,
interrelations, etc., while looking at the past, present as well
as the future.
Oliveira and Perondi propose a stakeholder analysis
compromising 6 steps. First, stakeholders need to be
identified. This step is an important part of the analysis since
in order to successfully implement organizational change, all
stakeholders should be taken into account [24]. This step is
executed by carefully analyzing all groups or individuals in
contact with the organization [33] [27] [29]. Reyes-Alcázar et
al. did this by designing an ad-hoc questionnaire, Oliveira and
Perondi did this by careful reading and studying the context of
the organization.
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When all stakeholders are identified, they need to be classified
into more general categories. Wood [39] distinguishes two
categories of stakeholders, primary and secondary. Primary
stakeholders include those who are (partially) dependent on
the organization, or vice versa. Secondary stakeholders are,
for example, governments, media and all kinds of institutions.
Freeman et al. [12] identified a basic list of five stakeholders
for both of these categories. They consider employees,
suppliers, funders, communities and customers to be the basic
primary stakeholders and competitors, consumer advocate
groups, special-interest groups, the media and the government
to be the basic secondary stakeholders. However, these are
guidelines and different categories can be used.
After categorizing stakeholders, they should be ranked and
classified according to their interests, influence and
importance. Finally, the analysis should describe the actions
or functions to be performed by the organization in order to
fulfill the expectations of all stakeholders and manage them
[27].
Varvasovsky and Brugha provide an insight in the desired
handling of stakeholders depending on their position towards
the project, as showed in table 2 [33]. This makes clear that
no general approach should be used in the management of
stakeholders, but that they should be managed based in the
information gained during the stakeholder analysis.
Table 2 Desired handling of stakeholders
As is clear, the process of stakeholders analysis and
stakeholder management has been studied intensively the past
decades, which provides us with a lot of guidance in the
identification, classification and managing of stakeholders. In
this research, however, we focus on organizational change
without specifying the type of industrial context of the
organization. Therefore, we will not go into deeper in the
specifics of stakeholder analysis.
We asked ourselves which stakeholders are involved in the
process of organizational change. This research question
cannot be answered in general, but should be looked at for
each individual organization by performing a stakeholder
analysis. However, general groups of stakeholders can be
identified, of which employees, suppliers, funders,
communities and customers seem to be the most important
and to be involved in most organizations.
3.1.2 Required actions Now that we have a view on the stakeholders involved in the
process of organizational change, we can take a look at the
steps required to successfully perform or implement this
change.
An early and widely known idea about change was created by
Kurt Lewin, who proposed three stages of change: unfreeze,
change and (re)freeze [23]. Lewin argued that in order to
accomplish change, an organization first has to ‘unfreeze’
from its old habits and mind set. Then, change is
implemented. After the change has been completed, the
organization once again freezes in the new situation. It is
argued that Lewin’s idea of change is still the basis of many
theories of organizational change [19]. This theory does
however not fully comply with the idea of continuous change,
which presumes organizational change to be ‘ongoing,
evolving and cumulative’ [37], an idea that is also broadly
supported nowadays.
In 1995, Van de Ven and Poole provided four types of
process theories on the change and development of
organizations. All of these theories have a different view on
and approach to organizational development and change.
Figure 2 shows these four types of theories and the steps they
undertake to accomplish change [34]. Depending on the mode
of change and unit of change, this overview can provide a
very global idea of the approach to organizational change.
Figure 2 Four types of process theories on the change and
development of organizations
Fernandez and Rainey provide a more detailed approach to
organizational change, containing eight factors that are
important in the process of organizational change, which is
supported by a large body of research [9]. These eight factors
each describe aspects that are of vital importance in order to
successfully implement change. From these factors, a few
steps can be derived which have to be performed to
accomplish organizational change, which are shown in Figure
3.
Figure 3 Steps in the process of organizational change
The first step to be taken is to ensure the need of the change.
Organizational change requires members of (a part of) an
organization to be convinced the change is necessary of useful
in order for the change to be successful [22]. This resembles
to Lewin’s phase of unfreezing, as mentioned earlier.
Secondly, a course of action has to be determined. Naturally,
such a course will be different for all organizations and for all
changes, and has to be based on the organization’s current
situation [1].
Then, support has to be built within and outside of the
organization. Earlier, we discussed the identification of
stakeholders within an organization. As Fernandez and
Strategies
Positions
Involve Collaborate Defend Monitor
Supportive Optimal fit Missed
opportunities
Missed
opportunities
Missed
opportunities
Mixed Risk Optimal fit Missed
opportunities
Missed
opportunities
and Risk
Non-
supportive Risk Risk Optimal fit Risk
Marginal Resource
waste
Resource
waste
Resource
waste Optimal fit
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Rainey point out, it is important to gain support in all vital
stakeholder groups. First and foremost, internal support must
be established. Often, internal resistance to change is the first
sign that an intended change will be dysfunctional [28].
Internal support also includes the support and commitment of
high management positions, which is often crucial in the
change process [5]. Support from identified external
stakeholders is also part of this step.
Of course, sufficient resources to support the intended change
have to be provided during the entire process. And finally, it
is important to institutionalize the change in order to ensure
the continuation of the initiated change.
The steps described are of course not the only possible
approach to organizational change and might differ in
different change project, however they do provide a general
course of action applicable to many situations.
3.2 Group Decision Support Systems Now that we have more detailed information on
organizational change, we will go into more detail on Group
Decision Support Systems. As introduced, a Group Decision
Support System is a system which can ‘combine
communication, computer, and decision technologies to
support problem formulation and solution in group meetings’
[7]. To discover the use of these systems in the process of
organizational change, we first have to gain more information
about them. Therefore, we will first try to answer the research
questions introduced earlier: What are the key strengths and
advantages of available Group Decision Support Systems?
and How can a Group Decision Support System effectively
facilitate the required steps for organizational change?
3.2.1 Key strengths and advantages DeSanctis and Gallupe define a decision-making group as
‘two or more people who are jointly responsible for detecting
a problem, elaborating on the nature of the problem,
generating possible solutions, evaluating potential solutions,
or formulating strategies for implementing solutions’. The
goal of a GDSS is to support these two or more people in
fulfilling their responsibility of detecting and elaborating
problems, generating and evaluating solutions and
formulating strategies for implementation [7]. They suggest
three approaches to support this goal, resulting in three
different types of GDSSs, varying by their level of
sophistication. Level 1 GDSSs support decision-making by
removing common communication barriers by i.e. displaying
suggested ideas or providing anonymity. Level 2 GDSSs
combine these features with detailed tools for analyses, such
as a risk analysis. Finally, a Level 3 GDSS includes elaborate
rule-making processes, allowing the system to ‘think’ with the
group. By composing rules for patterns, timing or content the
system can provide more sophisticated support [7].
Several studies in the past years indicated that the use of a
GDSS has positive effects on group decision-making. Eden
argues that the use of GDSSs is in its ability to encourage
‘creativity, developing emotional commitment, and attending
to political feasibility’ [8]. He argues that political feasibility
is an important and required quality of a decision, if the
organizational change intended by the decision is to follow.
After all, if a decision does not accomplish the intended goal
it is not an effective decision, no matter how rational the
decision was. By involving stakeholders in the decision-
making process using a GDSS, the political feasibility of a
decision is increased. As found by Gallupe and McKeen, a
GDSS supports a more ‘democratic’ participation in face-to-
face sessions [15].
As indicated by studies, we expect the use of a GDSS to be in
the increased decision quality and lower decision time. Of
course, decision quality is factor which is very hard to
determine. Other studies have tried this by comparing the
decision to a correct answer, if the decision has a definite,
correct answer, by comparing the results by the decision made
by a panel of experts or by assigning a value score to the
decision [4] [16]. Several studies show different results on the
advantages of the use of a GDSS. Increase in decision quality
was found, however only for high complexity decisions,
whereas no significant difference could be found on low
complexity decisions [13] [4] [14]. Regarding decision time,
the same studies found that high complexity decision had no
significant difference between GDSS and non-GDSS groups.
However, low complexity decisions took more time with
GDSS than without one. This combination leads to the
suggestion that a GDSS is more useful in the decision-making
process of a problem with high complexity.
However, as is often the case, not all researchers agree.
George et al. performed similar experiments, but found no
significant evidence that the use of a GDSS increased decision
quality, though they suggest that their problem might not have
been of a high enough complexity for the GDSS to make a
difference [16]. This same study did however show a
significant increase of user participation when a GDSS is
used. Referring back to Eden, who argues political feasibility
is an important and required quality of a decision, high user
participation can be an important advantage. Regarding user
satisfaction, George et al. found no significant difference
between GDSS and non-GDSS groups, whereas Gallupe and
DeSanctis found that using GDSS for face-to-face meetings
resulted in a lower satisfaction when using a GDSS [14].
An interesting new development in the area is the shift from
owned hardware to the use of Software as a Service (SaaS) in
the Cloud. Cloud computing is defined by the US National
Institute of Standards and Technology (NIST) as ‘a model for
enabling convenient, on-demand network access to a shared
pool of configurable computer resources (e.g. networks,
servers, storage, applications, and services) that can be
rapidly provisioned and released with minimal management
effort or service provider interaction’ [26]. Though this trend
is from the last years and is still in its early stages, it shows
promise to become very important and useful in the future
[20] and has a great potential for enabling GDSS on a large
scale.
As is clear, not all empirical research available on the subjects
agrees on the effects of the use of a GDSS. However, most
studies do agree on its use resulting in increased decision-
quality and user participation, especially for high-complexity
decisions.
3.2.2 Facilitating organizational change using a
GDSS Our fourth research question is closely relating to the main
research question: How can a Group Decision Support System
effectively facilitate the required steps for organizational
change?
The literature from our previous section suggests that GDSSs
increase decision quality for high-complexity problems. Of
course, the complexity of a problem leading to the need of
organizational change can be of different complexities.
However, considering the amount of stakeholders involved in
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the change of an organization and the fact that these decisions
often have a great impact on the organization, most of these
problems can be considered to be high-complexity problems
[36]. This means that a GDSS can have a positive influence
on the decision quality of the decisions to be made during
organizational change.
As GDSSs can also increase user participation during the
decision-making process, decisions involving different
stakeholders can get broader support by these stakeholders.
As was stated, internal resistance to change is often a first sign
the change will be dysfunctional. By creating a broader
support for decisions, this resistance to change can be
reduced, therefore increasing the change of a successful
implementation of the intended change.
To conclude the literature review, we can endorse our earlier
statement: a lot of literature is available on both
organizational change and Group Decision Support Systems,
however little is to be found on the combination of the two.
The previous sections on both subjects confirm that there are
certain steps in the process of organizational change that can
be facilitated and/or improved by using a GDSS.
4. RESEARCH APPROACH This experiment in this research is designed and executed
according to the guidelines by Kitchenham et al. in their
‘Preliminary Guidelines for Empirical Reseach in Software
Engineering’ [21]. This guide specifies a few different steps in
experiments: experimental context, experimental design,
conducting and data collection, analysis, presentation and
interpretation of results. In the description of this experiment,
we will describe the relevant information for the first of these
steps.
4.1 Experimental context This experiment will be a small-scale test of the use of a
GDSS in (a part of) the process of organizational change.
Despite the limited availability of resources we attempt to
gain an insight of the use of GDSS ‘Spilter’ in a
brainstorming session at the University of Twente. The tool
itself will be explained later in this paper. The experiment will
be performed within the University of Twente and will
therefore be set in an academic environment. With a staff of
about 3.300 academics and other employees and 9.000
students the University profiles itself as ‘the entrepreneurial
university’ [32]. The experiment will be performed with
different employees from the University, involving both
academic and supporting staff.
During this experiment we will try to answer the following
question: Does the use of GDSS Spilter increase the quality of
brainstorm results on organizational change? We will
discuss organizational change in the University based on the
results of the Online Culture Assessment Instrument (OCAI),
which measures the organizational culture of an organization.
4.1.1 Organizational Culture Assessment
Instrument The Organizational Culture Assessment Instrument (OCAI) is
a research method designed to examine organizational culture
in all types of organizations. Organizational culture is,
according to OCAI-designers Cameron and Quinn, an
essential part in the potential success of an organization and
improves their performance and long-term effectiveness [6].
OCAI both identifies the current organizational culture of
organizations and measure the culture that employees think
should be pursued [6]. It does so by assessing six key
dimensions of an organizational culture:
Dominant Characteristics
Organizational Leadership
Management of Employees
Organization Glue
Strategic Emphases
Criteria of Success
Participants are asked to assess all these dimension on four
types of cultures: Clan, Adhocracy, Market and Hierarchy.
OCAI asks them to divide 100 points among these four
cultures, based on the organization’s similarities to this
culture. Figure 4 shows an overview of these cultures and
their focus, which Cameron and Quinn call the ‘competing
values framework’.
The Hierarchy culture is considered to be stable and is often
related with bureaucracy. Rules, specialization and hierarchy
are important attributes of this culture.
The Market culture is more focused on external activities
than on internal affairs. Through transactions with other
parties, such as suppliers or customers, it aims to establish
competitiveness and productivity.
The Clan culture focuses on shared values and goals and
cohesion. By establishing the organization as an ‘extended
family’ employees are encouraged to improve their own work
and are often more motivated.
The Adhocracy culture aims to respond to the fast-changing
markets by encouraging entrepreneurship and creativity. They
create their economic value by innovation and development.
Figure 4 The competing values framework
OCAI-analyses have been performed at Universities in earlier
studies. Both studies showed the same results: participants
preferred less Hierarchy and Market culture, more Clan
culture and no change in the Adhocracy culture [30][10]. An
example of the result of an OCAI-analysis is shown in figure
5 [30].
Figure 5 Example of an OCAI-analysis
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4.1.2 Spilter The GDSS we will use in this experiment is called the ‘Spilter
Besluitenversneller’ (Spilter Decision Accelerator, henceforth
called Spilter), developed by Spilter®. Spilter is a web-based
tool useable for management- or strategy-issues, team- or
project-meetings, innovation or marketing.
In Spilter, one can create a session which consists of four
stages: assessing, categorizing, prioritizing and deciding. The
facilitator can determine the structure of the meeting
beforehand and insert brainstorm sessions, questions or
analyses. It creates real-time output and reports, allowing for a
fast overview of results.
Spilter was chosen as GDSS because the University of Twente
already had a license for this tool.
4.2 Experimental design Goal of this experiment is to test whether the use of Spilter
increases the quality of brainstorm results on organizational
change. In order to do so, we must
a) Acquire participants for this experiment
b) Find (relevant) topics for brainstorming on
organizational change
c) Brainstorm on organizational change both with and
without help of Spilter
d) Determine the quality of the brainstorm results
e) Analyze whether the results using Spilter are
(significantly) better
First, participants must be found to participate in the
experiment. To find participants, email contact will be
established to a few departments of the University of Twente.
The following departments will be contacted for participating:
Industrial Engineering and Business Information
Systems (IEBIS)
Business Administration
Human Resources Management
These departments were chosen to get a diverse group with
different visions on the University. Unfortunately, due to time
issues, only 8 participants were found. Though we recognize
that this might give problems with the significance of our
results, we still believe this can provide a useful insight in the
use of Spilter.
All participants are asked to fill out the OCAI assessment.
Statements will be produced based on the results of this
assessment to be the topic of discussion (i.e. ‘The University
should improve employee satisfaction’ or ‘The University
should be less focused on producing enough papers’).
During the brainstorm sessions, a crossover design will be
used. First, a brief explanation and instruction will be given to
the participants. During this instruction, possible biasing of
the participants shall be prevented as much as possible. Then,
two groups are (randomly) formed, GR1 and GR2, which both
are to discuss two statements, ST1 and ST2. This leads to the
design shown in table 3. A crossover design was chosen
because this provides more precision when fewer subjects are
used [17].
Table 3 Crossover design
GR1 GR2
Traditional methods ST1 ST2
Using Spilter ST2 ST1
As table 3 shows, both groups will discuss both statements,
once using Spilter and once using traditional brainstorming
methods. These methods include pen and paper and
discussion. Both groups are requested to present their three
best solutions to the problems formulated in ST1 and ST2 at
the end of each session. This will result in six solution per
statement.
After both sessions are completed, all solutions will be rated
on a scale from 1 to 5. Participants are asked to rate the
solutions on their impact, usefulness, whether it solves the
problem and whether it is realistic. This will result in an
average score for all solutions, after which we can analyze
whether the solutions generated by Spilter sessions were rated
higher.
All results are handled anonymous. The exact procedure of
the Spilter sessions can be found in Appendix A.
5. RESULTS Below, the results of the experiment are described. Once
again, this is done according to Kitchenham’s guidelines.
5.1 OCAI results First, the OCAI-survey was distributed among the participants
through an online questionnaire. The response rate was 100%.
The results from the survey can be found in Table 4 and
Figure 6. The OCAI results showed that participants preferred
a strong cultural shift from Hierarchy to Clan (in accordance
to previous studies at universities). Both of these cultures
focus on internal maintenance and integration, however, Clan
culture focuses on flexibility and discretion, whereas
Hierarchy focuses on stability and control. This trend is
confirmed by the fact that the OCAI results show that
participants prefer a slight decrease of Market culture
(controlled) and a slight increase of Adhocracy culture
(flexible). Therefore, the two statements to be discussed were
based on a culture shift from a controlled environment to a
more flexible one. The following statements were chosen:
The University should give employees more
flexibility in their activities (ST1).
The University should improve employee
satisfaction (ST2).
Table 4 Results from the OCAI-survey
Clan Adhocracy Market Hierarchy
Now 30.14 23.75 18.89 27.22
Preferred 38.89 26.67 15.69 18.75
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Figure 6 Graphical representation of the OCAI results
5.2 Brainstorm sessions Based on the statements mentioned above, brainstorm
sessions were organized. The eight participants were
randomly and evenly divided in two groups. The first group,
Group 1, started with discussing the first statement, ST1,
using Spilter. Group 2 started with discussing ST1 using
traditional brainstorming methods. Both groups worked on
different locations. Group 1 was accompanied in order to
answer questions about the User Interface and functionality of
Spilter. Group 2 was not accompanied and was not given any
instruction on how to perform their session, only to present
three solutions in the provided time. After fifteen minutes,
both groups switched rooms. Now, group 2 discussed ST2
using Spilter and group 1 discussed ST2 with traditional
brainstorming methods. Once again the Spilter-group was
accompanied in order to answer questions about Spilter. This
session also lasted fifteen minutes.
After both sessions, both traditional sessions had resulted in
three solutions written on paper. Both Spilter session had also
resulted in three solutions (see Appendix A for the exact
procedure). These twelve solution were then rated on a scale
of 1 to 5 by all participants. This resulted in an average score
for each solution, which can be found in Table 5.
5.3 Statistical analysis This experiment has one Independent Variable (type of
brainstorm session), with a sample size of two. Therefore, an
independent sample t-test is the most appropriate statistical
analysis [31]. ANOVA was not used because this test is not
optimal for a sample size of two [18].
As null hypothesis H0 we state H0: μ1 = μ2 where μ1 is the
mean of the Spilter session solutions and μ2 is the mean of the
traditional session solutions. Therefore, alternative hypothesis
HA is HA: μ1 ≠ μ2.
Table 6 shows the Group Statistics about the two different
groups. Table 7 shows the Independent Samples Test. First,
we look at the Levene’s Test for Equality of Variances. With
a significance of 95%, we can state that the variances are
equal. Therefore, we look at the upper row, which shows a p-
value of .205. This means that with a significance of 95%, the
null hypothesis is not rejected. Therefore, HA is rejected,
meaning that there is no significant difference between the
quality of the solution created by Spilter sessions and
traditional sessions.
5.4 Discussion Though the experiment did show a slightly higher rating for
solution provided with the help of Spilter, this difference is
not significant and therefore we cannot conclude that Spilter
increased the quality of the solutions provided to the
statements. However, since the experiment was very small-
scale it is hard to get significant results. The small scale
restricted this experiment and therefore restricted this
research. With more resources and a larger scale, more results
might have been booked.
The results from the OCAI-survey were in line with earlier
OCAI-studies at Universities [30][10].
The University should give employees more flexibility in their activities
Solution Average score St.dev. Source
More room for research outside long-term programs 3.50 1.12 Spilter
Reduce workload to make time to think on new ideas instead of having to allocate all
time to routine jobs 4.00 0.71 Spilter
Support entrepreneurial spirit 3.88 0.78 Spilter
Usage of online teaching 3.75 1.20 Trad.
Interchangeability of teaching personnel 3.88 1.17 Trad.
Offer teaching to more students (bigger lectures) 2.88 1.17 Trad.
3.65 1.11
The University should improve employee satisfaction
Solution Average score St.dev. Source
Less organizational change (especially teaching-related) 4.25 0.97 Spilter
Hire more employees to generate more time per employee 3.88 1.05 Spilter
Reduce working pressure by hiring more employees 3.88 1.05 Spilter
Less formalities, better administration 3.88 0.60 Trad.
Career opportunities 3.75 0.66 Trad.
Give (employees) the idea the workload is managed 3.75 0.66 Trad.
3.90 0.87
8
6. CONCLUSION Organizational change is a process that is and always will be
of interest to organizations of any kind. Being adaptable to the
environment is a much discussed subject in organizations,
making change of vital importance. Group Decision Support
Systems support the decision-making process in groups by
increasing their decision quality and increasing participation.
The use of GDSSs during organizational change appears to be
an ideal combination, which is why we asked ourselves: How
can Group Decision Support Systems be used to effectively
facilitate organizational change?
During a literature review, we found that a wide range of
stakeholders is involved in the process of organizational
change and discussed a few methods to identify these
stakeholders. Important stakeholders which are applicable to
most organizations include employees, suppliers and
customers. In order to successfully change an organization,
several steps have to be executed. Though there are different
theories on the process, important steps are ensuring the need
of the change, providing a plan, building support, providing
the resources and institutionalize the change.
GDSSs have shown to have a positive influence on the
decision quality of high-complexity problems and to increase
the participation during a decision-making process. Since
internal resistance to change is a danger to the success of the
change process, the increased participation has a positive
influence on the potential success of an organizational
change. Also, high-complexity problems are often part of
these changes, adding another benefit to the use of a GDSS
during organizational change.
The experiment performed in this research did not prove a
significant increase in idea-quality during brainstorm
processes when a GDSS was used. However, this might be
explained by the fact that these were not high-complexity
decisions that had to be made.
Taking into accounts all these points, our main research
question can be answered by the fact that GDSSs can
definitely be used to facilitate organizational change. By
increasing participation and therefore potentially decreasing
internal resistance to change, and providing higher decision
quality on high-complexity problems, the use of a GDSS can
increase the chance of success for an organizational change
and increase its quality. However, further research and
experimenting is necessary to confirm this.
7. FUTURE WORK This research focused on a literature review with a small-scale
experiment. Though the literature review resulted in useful
insights, the experiment did not result in a significant increase
of quality when a GDSS was used.
However, only a small part in the process of organizational
change, brainstorming, was used for testing during this
research. Furthermore, the experiment was very small-scale
due to a lack of resources, making it very hard to get
significant results. Future work can therefore focus on other
parts of organizational change and increase the scale of the
research, allowing for more reliable results. This may include
decision-making on different approaches to the change,
stakeholder management or decisions on restructuring the
organization.
Furthermore, many types of organizations exist. An
University is very different from a company aiming for
maximal profit, and also very different from government
agency. Future work may include research on different and/or
multiple organizations.
8. ACKNOWLEDGEMENTS First and foremost I wish to thank Jos van Hillegersberg for
his guidance, ideas and support during this research. I’d also
like to thank Fons Wijnhoven for his coordination on the
process. Finally, I wish to thank all the participants in my
experiment.
Without these people, this paper would not have been
possible. Thank you.
9. REFERENCES [1] Abramson, M.A., and Lawrence, P.R. 2001. The
Challenge of Transforming Organizations: Lessons
Learned about Revitalizing Organizations. In
Transforming Organizations, Rowman & Littlefield,
Lanham, MD, 2001, 4-8.
[2] Branco, M.S.A., Loureiro, G., Trabasso, L.G.
Stakeholder value analysis of architecture alternatives for
sustainable space systems developments, Sixth
International Aerospace Congress IAC'09, (Moscow,
2009), Moscow State University, 23-27.
[3] Brugha, R., Varvasovszky, Z. Stakeholder analysis: A
review. (2000) Health Policy and Planning, 15 (3), 239-
246.
[4] Bui, T., Sivasankaran, T.R. Relation between GDSS use
and group task complexity: An experimental study.
(1990) Proceedings of the Hawaii International
Conference on System Science, 3, 69-78.
[5] Burke, W.W. Organization Change: Theory and Practice.
Thousand Oaks, CA: Sage Publications, 2002.
Type of session N Mean Std. Deviation Std. Error Mean
Score of solution Spilter 6 3,8983 ,24236 ,09894
Traditional 6 3,6483 ,38175 ,15585
9
[6] Cameron, K.S., Quinn, R.E. Diagnosing and Changing
Organizational Culture. Jossey-Bass, San Francisco,
2006.
[7] DeSanctis, G. and Gallupe, R.B. 1987. A foundation for
the study of Group Decision Support Systems.
Management Science 05/1987, 33 (5), 589-602
[8] Eden, C. A framework for thinking about Group
Decision Support Systems (GDSS). (1992) Group
Decision and Negotiation, 1 (3), 199-218.
[9] Fernandez, S., Rainey, H.G. Managing successful
organizational change in the public sector. (2006) Public
Administration Review, 66 (2), 168-176.
[10] Fralinger, B., Olson, V. Organizational Culture at the
University Level: a Study Ssing the OCAI Instrument.
Journal of College Teaching & Learning, 4 (11), 85-96.
[11] Freeman, C., Innovation and the strategy of the firm, In:
Freeman, C., The economics of industrial innovation,
Panguin Books Ltda, Harmondsworth, 1988.
[12] Freeman R.E., Harrison J.S., Wicks A.C. Managing for
Stakeholders: Survival, Reputation and Succes. Yale
University Press, London, 2007.
[13] Gallupe, R.B., DeSanctis, G. Dickson, G.W. The Impact
of Computer Based Support on the Process and Out-
comes and Group Decision Making. International Con-
ference on Information Svstems,(San Diego, 1986),81-83
[14] Gallupe, R.B., Desanctis, G., Dickson, G.W. Computer-
based support for group problem-finding: An
experimental investigation. (1988) MIS Quarterly:
Management Information Systems, 12 (2), 277-296.
[15] Gallupe, R.B., McKeen, J.D. Enhancing Computer-
Mediated Communication: An experimental
investigation into the use of a Group Decision Support
System for face-to-face versus remote meetings. (1990)
Information and Management, 18 (1), 1-13.
[16] George, J.F., Easton, G.K., Nunamaker Jr., J.F.,
Northcraft, G.B. A study of collaborative group work
with and without computer-based support. (1990)
Information Systems Research, 1 (4), 394-415.
[17] Goad, C.L., Johnson, D.E. Crossover experiments: A
comparison of ANOVA tests and alternative analyses.
(2000) Journal of Agricultural, Biological, and
Environmental Statistics, 5 (1), 69-87.
[18] Hedayat, A.S., Yang, M. Universal optimality for
selected crossover designs. (2004) Journal of the
American Statistical Association, 99 (466), 461-466.
[19] Hendry C. Understanding and creating whole
organizational change through learning theory. (1996)
Human Relation 49, 621–41
[20] Khajeh-Hosseini, A., Greenwood, D., Smith, J.W.,
Sommerville, I. The Cloud Adoption Toolkit: Supporting
cloud adoption decisions in the enterprise. (2012)
Software - Practice and Experience, 42 (4), 447-465.
[21] Kitchenham, B.A., Pfleeger, S.L., Pickard, L.M., Jones,
P.W., Hoaglin, D.C., El Emam, K., Rosenberg, J.
Preliminary guidelines for empirical research in software
engineering. (2002) IEEE Transactions on Software
Engineering, 28 (8), 721-734
[22] Kotter, J.P. Leading Change: Why Transformation
Efforts Fail. (1995) Harvard Business Review, 73(2), 59-
67.
[23] Lewin K. Field Theory in Social Science. Harper&Row,
New York, 1951.
[24] Lindenberg M., Crosby B. Managing development: the
political dimension. Kumarian Press, Hartford, CT, 1981
[25] Lines, R., Selart, M., Espedal, B., Johansen, S.T. The
production of Trust during Organizational Change.
(2005) Journal of Change Management. 5 (2), 221-245
[26] Mell P., Grance T. The NIST Definition of Cloud
Computing. National Institute of Standards and
Technology, 2009.
[27] de Oliveira, M.E.R., Perondi, L.F. Proposal of a
methodology of stakeholder analysis for the Brazilian
satellite space program. (2012) Journal of Aerospace
Technology and Management, 4 (1), 95-104.
[28] Qureshi, S., Davis, A. Assessing resistance to change in a
multinational organization using a GSS game. (2006)
Association for Information Systems - 12th Americas
Conference On Information Systems, AMCIS 2006, 7,
4028-4036.
[29] Reyes-Alcázar, V., Casas-Delgado, M., Herrera-Usagre,
M., Torres-Olivera, A. Stakeholder analysis: The
Andalusian agency for healthcare quality case. (2012)
Health Care Manager, 31 (4), 365-374.
[30] Simamora, B.H., Jerry, M. Current and preferred
organizational culture: A case study at private university
in Indonesia. (2013) International Business
Management, 7 (4), 353-358.
[31] University of California - Los Angeles: What statistical
analysis should I use? Retrieved June 12, 2014, from
Institute for Digital Research and Education:
http://www.ats.ucla.edu/stat/mult_pkg/whatstat/
[32] University of Twente: Organization. Retrieved May 30,
2014: http://www.utwente.nl/en/organization/
[33] Varvasovszky, Z., Brugha, R. How to do (or not to do)...:
A stakeholder analysis. (2000) Health Policy and
Planning, 15 (3), 338-345.
[34] van de Ven, A.H., Poole, M.S. Explaining development
and change in organizations, (1995) Academy of
Management Review, 20 (3), 510-540.
[35] de Vreede, G.J. Facilitating Organizational Change: The
Participative Application of Dynamic Modelling. Delft
University of Technology, Delft, 1995.
[36] de Vreede, G.J. Participative Modeling for
Understanding: Facilitating Organizational Change with
GSS. (1996) Proceedings of the 29th Hawaii
International Conference on System Science, 69-78.
[37] Weich, K.E., Quinn, R.E. Organizational change and
development. (1999) Annual Review of Psychology, 50,
361-386.
[38] Wolfswinkel, J.F., Furtmueller, E., Wilderom, C.P.M.
Using grounded theory as a method for rigorously
reviewing literature. (2013) European Journal of
Information Systems, 22 (1), 45-55
[39] Wood, D.J. Business and Society, Haper Collins,
Pittsburg, 1990.
[40] World Trade Organization. 2008. World Trade Report
2008: Trade in a globalization world, p15.
10
APPENDIX
A. SPECIFICATION OF SPILTER BRAINSTORMSESSION
The Spilter brainstorm session consists of three parts. First, ideas can be generated by all users. All ideas posted will be immediately
visible for all users.
Secondly, users are asked whether the ideas generated in the previous section are feasible within 3 years. This is done to filter non-
realistic ideas from the session. Users can select all ideas they believe to be feasible within 3 years.
All ideas that are selected to be feasible at least once, are presented in the final list. Users are asked to rate all these potential, feasible
solutions on a scale from 1 to 10. Spilter will compute the average score of each solution, from which a top 3 can be selected.
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