1

Using Group Decision Support Systems to Facilitate

Organizational ChangeJeroen Monteban University of Twente

P.O. Box 217, 7500AE Enschede The Netherlands

j.monteban@student.utwente.nl

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

Permission to make digital or hard copies of all or part of this work for

personal or classroom use is granted without fee provided that copies are

not made or distributed for profit or commercial advantage and that

copies bear this notice and the full citation on the first page. To copy

otherwise, or republish, to post on servers or to redistribute to lists,

requires prior specific permission and/or a fee.

21st Twente Student Conference on IT, June 23, 2014, Enschede, The

Netherlands.

Copyright 2014, University of Twente, Faculty of Electrical Engineering,

Mathematics and Computer Science.

2

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.

3

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

4

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

5

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

6

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

7

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.