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47

Original scientific article                                             DOI: https://doi.org/10.35469/ak.2022.365
received: 2022-11-24                                  UDC: 796.062:005.7

THE DECISION-MAKING STYLE STRUCTURE OF 
SLOVENIAN SPORTS MANAGERS 

Edvard KOLAR1, Matej TUŠAK2

1 University of Maribor, Faculty of Organizational Science, Slovenia
2 University of Ljubljana, Faculty of Sport, Slovenia

Corresponding author:
Edvard KOLAR

University of Maribor, Faculty of Organizational Science, Kidričeva cesta 55A, 4000 Kranj
Phone: +386 41 376 381

E-mail: edvard.kolar@guest.um.si

ABSTRACT

Purpose: Decisions that we make are always burdened with consequences, which 
are the inevitable result of our decision-making. The decision-making style (DMS) is 
the way in which managers acquire, process and use information in decision-making 
processes. The goals of the present research are to define the factor structure of DMS 
for a sample of Slovenian sports managers and to determine the characteristics of their 
DMS structure.

Methods: 80 managers of Slovenian sports organizations filled in an anonymous 
internet survey. The DMS was measured with the use of the General Decision-Ma-
king Style Inventory (GDMS), which was translated into the Slovenian language. The 
GDMS questionnaire measures five different decision-making styles: rational, intuitive, 
dependent, avoidant and spontaneous. The factor analysis (FA) method was used to test 
the assumption about the structure of the DMS. The internal consistency was measured 
using Cronbach’s alpha coefficient. The Pearson correlation coefficient was used to 
study the relationship between the DMS.

Results: After three successive implementations of FA, we developed an optimized 
DMS model with 20 items confirming that when making decisions, sports managers 
use a combination of all five DMS. Slovenian sports managers mostly use the rational 
and dependent DMS, indicating that they are mostly rational decision-makers. We also 
recognized the correlation between the rational and the dependent style, but since the 
structure of the DMS in our sample is dominated by the rational DMS, we could con-
clude that this is a dependent-rational DMS, where mangers seek advice, opinions and 
knowledge from colleagues when making decisions to increasing their rationality. 

mailto:edvard.kolar@guest.um.si


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Conclusions: We can conclude that the recognized average structure of the DMS is 
functional and healthy; furthermore, Slovenian sports managers are on average rati-
onal decision-makers who, due to the specific organizational characteristics of sports 
organizations, look for confirmation and opinions on future decisions in the broader 
environment of the organizations’ stakeholders.

Keywords: Slovenian sports managers, decision-making styles, structure. 

STRUKTURA STILOV ODLOČANJA SLOVENSKIH ŠPORTNIH 
MENEDŽERJEV

IZVLEČEK

Namen: Odločitve, ki jih sprejemamo, so vedno obremenjene s posledicami, ki so 
neizogiben rezultat našega odločanja. Stil odločanja (DMS) je način, na katerega me-
nedžerji pridobivajo, obdelujejo in uporabljajo informacije v procesih odločanja. Cilja 
te raziskave sta opredelitev faktorske strukture DMS na vzorcu slovenskih športnih me-
nedžerjev in opredelitev značilnosti strukture njihovih stilov.

Metode: 80 menedžerjev slovenskih športnih organizacij je izpolnilo anonimno 
spletno anketo. DMS je bil merjen z uporabo splošnega vprašalnika stilov odločanja 
(GDMS), ki je bil preveden v slovenski jezik. Vprašalnik GDMS meri pet različnih 
stilov odločanja: racionalnega, intuitivnega, odvisnega, izogibajočega in spontanega. 
Za preverjanje predpostavke o strukturi DMS je bila uporabljena metoda faktorske 
analize (FA). Notranja konsistentnost je bila preverjena s Cronbachovim koeficientom. 
Pearsonov korelacijski koeficient je bil uporabljen za proučevanje povezanosti med 
stili odločanja.

Rezultati: Po treh zaporednih izvedbah FA smo razvili optimiziran model stilov od-
ločanja z 20 postavkami vprašalnika, ki potrjuje, da športni menedžerji pri odločanju 
uporabljajo kombinacijo vseh petih stilov odločanja. Večinoma uporabljajo racionalni 
in odvisni stil, kar kaže, da so večinoma racionalni odločevalci. Ugotovljena je bila 
tudi korelacija med racionalnim in odvisnim stilom, ker pa v strukturi našega vzorca 
prevladuje racionalni stil, bi lahko sklepali, da gre za odvisno-racionalni stil odloča-
nja, v okviru katerega menedžerji pri sprejemanju odločitev iščejo nasvete, mnenja in 
znanje pri sodelavcih zaradi povečanja racionalnosti svojih odločitev.

Zaključek: Ugotovili smo, da je ugotovljena povprečna struktura stilov odločanja 
funkcionalna in zdrava. Slovenski športni menedžerji so v povprečju racionalni od-
ločevalci, ki zaradi posebnih organizacijskih značilnosti športnih organizacij iščejo 
potrditev in mnenja o prihodnjih odločitvah v širšem okolju deležnikov organizacije.

Ključne besede: slovenski športni menedžerji, stili odločanja, struktura.



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INTRODUCTION

Decision-making is a process resulting in a decision (Tomić, 2007). “Decisions are 
an essential part of our lives, both in the work environment and outside of it. Decisions 
are made by those who are responsible for choosing between two or more options,” 
(Heller & Hindle, 2001). A decision, as a result of a decision-making process, can be 
defined as “a judgment or choice between two or more options that develops from an 
infinite number of situations, from solving a problem to taking action in a certain di-
rection,” (Heller & Hindle, 2001). Bohanec (2012) writes that a decision is a conscious 
and irreversible sharing of resources with the aim of achieving the desired goals. The 
decisions we make are always burdened with consequences, which are inevitable re-
sults of our decision-making. Therefore, it is particularly important how we decide on 
matters (or problems).

The decisions we make define our past and significantly design our future. Deci-
sions made by managers about a company define the company’s past performance, 
its current market, economic and social position and its future place in the industry, 
national economy and global environment. The essence of the managerial function is 
the coordination of technically divided work and the implementation of the joint work 
tasks of the association with the help of others; i.e., delegating and solving problems 
that arise, or making decisions. Thus, we could define the content of management work 
as coordination and delegation (responsibilities, duties and powers), while the method 
of managerial work is decision-making (Kolar & Jurak, 2014). Because of this, mana-
gers are often called decision-makers (Daft, 2010). The results of their decisions are 
reflected in the growth, prosperity or collapse of the organizations they deal with (Daft, 
2008). Simon (1960) wrote that decision-making and management are synonymous 
terms. The general idea of the decision maker is an individual who evaluates and cho-
oses between possible decisions. When solving problems, decision-makers are faced 
with situations representing a gap between the desired (the goal of the decision) and 
the actual state (initial state); in order to bridge this gap, they perform intellectual (co-
gnitive) activities, while the future steps that need to be taken are unknown (Klein & 
Methlie, 1992). Every decision refers to an object, and the reason for its adoption is a 
certain purpose, which manifests itself as an intended change of that object in favour of 
the one who makes the decision (Rozman & Kovač, 2012). A fundamental condition for 
ensuring the success and efficiency of n organization is that the managers at all levels of 
management make valid decisions.

Simon (1987) claims that it is highly unlikely to find two types of managers (at 
least not good managers) who can be classified as making decisions solely based on 
intuition or making decisions solely based on rational/analytical techniques. It is more 
likely that we will find a range of combinations or the related use of intuition and 
rational-analytical techniques in decision-making processes. Rowe, Boulgarides and 
McGrath (1984) point out that the decision-making style reflects the way a person uses 
information to make decisions. Avsec (2012) accordingly stated that, despite the fact 
that the nature of the problem and situational factors play an important role in decision-



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-making, we can assume that, regardless of the decision-making problem, individuals 
differ in the frequency of use of individual decision-making styles. Remenova and Jan-
kelova (2019) state that the decision-making style can be understood as the result of a 
cognitive process that leads to the choice of solutions from among several alternatives. 
The authors also note that managers generally use a combination of at least two de-
cision-making styles, varying based on the characteristics and weight of the decision 
problem. Driver (1979) defined decision-making styles as learned patterns of response 
that people use when making decisions. The decision-making style is therefore the way 
managers acquire, process and use information in decision-making processes. This is a 
set of qualitative indicators that manifest themselves within the decision-making pro-
cess in the form of a decision-making style and represent a typical method of enforcing 
decisions. Managers’ decision-making styles significantly contribute to their individual 
performance and thus to the performance of organizations (Abdelsalam, Daeoud & 
ElKadi, 2013); therefore, as pointed out by Rowe and Boulgarides (1992), they need to 
be measured, because decision-making styles should form the backbone of effective de-
cision-making. Knowledge of decision-making styles and their use in the management 
structure directly contributes to increasing the competitive advantage of organizations 
(Remenova & Jankelova, 2019) and can also represent one of the main sources of risk 
for the successful operation of organizations.

Several authors have worked on defining decision-making styles. It is typical of 
research in the field of decision-making styles that in addition to defining the styles, 
authors often build different models and constructs, including a varying number of 
decision-making styles, as well as different inventories for determining the dominant 
styles of individual subjects (Harren, 1979; Rowe & Mason, 1987; Hunt, Krzystofiak, 
Meindl, & Yousry, 1989; Scott & Bruce 1995; Nygren, 2000). Berisha, Pula and Kra-
sniqi (2018), based on a review of a large number of studies, concluded that one of 
the most frequently used and validated questionnaires for discovering decision-making 
styles is the General Decision-Making Style Inventory (GDMS) developed by Scott 
and Bruce (1995). Scott and Bruce (1995) defined decision-making styles as a learned 
response or behavioural pattern of an individual who is faced with a decision-making 
situation. They claimed that it is not a personality trait, but rather a tendency to react in 
a specific way in a decision-making situation, whereby the characteristics of the situa-
tion itself can have a significant influence. The authors also stated that individual styles 
are not mutually exclusive and that individuals do not rely exclusively on one decision-
-making style. The results of their study showed that individuals use a combination of 
decision-making styles when making important decisions. Based on the questionnaire, 
which contained 37 items and was used on the initial sample of subjects (military of-
ficers), with the use of factor analysis, the authors discovered a structure based on five 
factors (decision-making styles) and then reduced the questionnaire to 25 items. In 
the subsequent steps of the analysis, the questionnaire was tested with the use of the 
factor analysis method (the principal axes method with varimax factor rotation) on the 
remaining three different samples. The results of the study showed that the structure of 
the decision-making styles consists of five styles and that the questionnaire can be used 



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regardless of the decision-making context or situation (Scott & Bruce, 1995). The five 
decision-making styles included in the GDMS inventory are defined as (Thunholm, 
2004; Faletič & Avsec, 2013):

 – rational style: characteristic of people who search for information in detail and 
comprehensively and logically evaluate all the alternatives. They mainly focus 
on logic, order and the systematic analysis of information;

 – intuitive style: characteristic of those who pay a lot of attention to details in 
the information flow and, instead of systematically searching and processing 
information, mainly consider their feelings about whether a certain decision is 
correct or not;

 – dependent style: characteristic of people who seek advice, support and confirma-
tion from others before making an important decision;

 – spontaneous style: characteristic of those who have a sense of urgency and thus 
a desire to complete the decision-making process as soon as possible and make 
a decision;

 – avoidant style; characteristic of people who want to avoid making a decision 
whenever possible.

In various studies on samples from different countries, numerous authors (Loo, 
2000; Thunholm, 2004; Spicer & Sadler-Smith, 2005; Gambetti, Fabbri, Bensi & To-
netti, 2008; Curşeu & Schruijer; 2012; Erenda, Meško & Bukovec; 2014; Bavoľár & 
Orosová, 2015; Alacreu-Crespo et al., 2019) have confirmed the validity (using factor 
analysis) and reliability (using Cronbach’s alpha coefficient) of the GDMS inventory as 
suggested by Scott and Bruce (1995).

In the aforementioned preliminary research, the authors tested the validity of the 
five-factor structure of decision-making styles on samples of managers, various profiles 
of students, the general population, military officers and others. In the present study, 
we will determine the factor structure of decision-making styles using a sample of 
Slovenian sports managers. Sports managers usually work in the specific environment 
of non-profit sports organizations, which in terms of legal, structural and procedural 
characteristics, are significantly different to for-profit organizations (companies). One 
of the important characteristics of sports organizations is that they are interest-type 
associations, in which the interests of different stakeholders are in constant conflict 
(Tavčar & Trunk Širca, 2002). Participants in sports organizations are individuals (offi-
cials, coaches and athletes), groups (professional and other) and associations (societies 
and clubs), all with their own interests and with the possibility of significantly acting 
and influencing the operation of the organization. Furthermore, in non-profit sports or-
ganizations, it is necessary to deal with a large number of volunteers (Santos, Batista & 
Carvalho, 2022) and to generate and obtain financial resources from a large number of 
different sources (sponsorships, donations, national and local budgets, sales of products 
and services, etc.). Finally, a “unique” governmental-managerial process is established 
in non-profit sports organizations; they are led by a committee of elected volunteers 
(governmental organizational function) who form very sensitive relations with profes-
sional (management) staff (Young, 1998; Kolar & Jurak, 2014).



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All of the aforementioned specifics of the structure and operation of non-profit 
sports organizations have a significant impact on the management and decision-ma-
king processes in these types of organizations and thus probably on the structure of the 
decision-making styles of the sports managers. The goals of the present research are to 
define the factor structure of decision-making styles using a sample of Slovenian sports 
managers and to determine the characteristics of their structure of decision-making 
styles. According to the described structural and operational differences in the functio-
ning of non-profit sports organizations, we can define the hypothesis that in the struc-
ture of decision-making styles of the sample of managers in our research, the depen-
dent decision-making style will be more emphasized than the intuitive and spontaneous 
style, which enables faster and quick decisions. We assume that sports managers have 
to coordinate decisions with much more diverse stakeholder interests than is typical for 
for-profit organizations (companies).

METHODS

Participants

The sample consisted of 80 managers of Slovenian sports organizations, which 
is more than the minimum requirement for executing the factor analysis (de Winter, 
Dodou & Wieringa, 2009, Andrew, Pedersen & McEvoy, 2010). The average age of 
the subjects was 47.5±10.6 years and the average work experience as a manager was 
15.61±9.7 years. The upper age limit was 68 years, whereas the lower age limit was 28 
years. The most experienced manager had 40 years and the least experienced 1 year of 
work experience. The sample consisted of 56 men (70%) and 24 women (30%). The 
sample is comparable to samples of sports managers by other authors (Barros & Lucas, 
2001; Case & Branch, 2003; Retar, Plevnik & Kolar, 2013). The Slovenian Olympic 
Committee sent the managers of Slovenian sports organizations an invitation to parti-
cipate in the study and to fill in an anonymous internet survey. The invitation was sent 
three times at one-month intervals. All the subjects participated in the study voluntarily 
and without any compensation.

Instrument

The decision-making style was measured with the use of the General Decision-
-Making Style Inventory – GDMS (Scott & Bruce, 1995), which was translated into 
the Slovenian language.  The GDMS questionnaire measures five different decision-
-making styles: rational, intuitive, dependent, avoidant and spontaneous. The questio-
nnaire consists of 25 items (5 for each decision-making style) ranging on a five-point 
Likert scale from strongly disagree (1) to strongly agree (5). The total score of all five 
decision-making styles was obtained by adding the item score of the decision-making 



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style and the score ranges from 5 to 25. GDMS scales have previously shown good 
psychometric characteristics (Scott & Bruce, 1995; Loo, 2000; Thunholm, 2004; Spi-
cer & Sadler-Smith, 2005; Gambetti, et. al, 2008; Curşeu & Schruijer; 2012; Avsec, 
2012; Erenda, et al.; 2014; Bavoľár & Orosová, 2015; Alacreu-Crespo, et. al, 2019). In 
this study, the alpha coefficients of the scales ranged between 0.572 (spontaneous) and 
0.814 (avoidant). The Cronbach’s alpha for the whole GDMS is 0.69, which is a good 
indicator of internal consistency. The Slovenian version of the GDSM inventory has 
already been used and validated in several research projects and using different samples 
in Slovenia (Avsec, 2012; Faletič & Avsec, 2013; Erenda, et al.; 2014); in the present 
study, general information questions about gender, age, experiences in management, 
level of education and field of education were added.

Statistical Analysis

Statistical data processing was carried out using the Statistical Package for the Soci-
al Sciences 29 (IBM SPSS Inc., Armonk, NY, USA). The factor analysis method – Prin-
cipal Component Factoring (PCF) and varimax rotation of factors – was used to test the 
assumption about the structure of decision-making styles (Scott & Bruce, 1995). Factor 
extraction was carried out with the use of Kaiser-Guttman’s criterion (Eigenvalue > 1). 
Before applying the factor analysis (FA), the data adequacy was tested with the Keiser-
-Meyer-Olkin Measure of Sampling Adequacy (KMO) and Bartlett’s test of sphericity. 
Values   of the KMO test above 0.6 indicate that the analyzed data is suitable for the use 
of FA (Tabachnick & Fidell, 2007). Bartlett’s test must show significant differences at a 
risk level of less than 5% (p < 0.05), showing that the correlation matrix is   not uniform 
and that the observed variables are related to a certain extent. The internal consistency 
of the overall scale and subscales was measured using Cronbach’s alpha coefficient. 
Pearson correlation coefficient was used to study the relationship between the GDMS’ 
styles.

RESULTS

Table 1 shows descriptive statistics for five decision-making styles. The average 
values   of the individual decision-making style use (Mean/Value) were calculated from 
the original model of items assigned to an individual decision-making style (Scott & 
Bruce, 1995). The average share of the individual decision-making style use (Mean/% 
of maximum) in relation to the maximum possible total value of the sum of items origi-
nally dedicated to the individual decision-making style (maximum = 25) was calculated 
for each decision-making style.



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Table 1: Descriptive statistics and internal consistency of decision-making styles.

Variable
Po

ss
ib

le
 r

an
g

A
ct

ua
l r

an
ge

Mean

St
an

da
rd

 
D

ev
ia

tio
n

Sk
ew

ne
ss

K
ur

to
si

s

C
ro

nb
ac

h 
α

Va
lu

e

%
 o

f 
m

ax
im

um

DMS Rational  5–25 15–25 21.35 85.40% 2.081 -0.283 0.885 0.777

DMS Intuitive  5–25  7–21 15.30 61.20% 3.235 -0.537 0.024 0.667

DMS Dependent  5–25  10–23 17.53 70.10% 3.027 -0.211 -0.365 0.694

DMS Avoidant  5–25  5–18 9.21 36.85% 3.129 0.439 -0.508 0.814

DMS Spontaneous  5–25  6–20 12.80 51.20% 2.558 0.122 -0.044 0.572

Key: DMS Rational = rational style; DMS Intuitive = intuitive style; DMS Dependent = dependent 
style; DMS Avoidant = avoidant style; DMS Spontaneous = spontaneous style.  

The structure of the decision-making styles (Table 1) revealed that Slovenian sports 
managers on average most often use the rational and dependent decision-making styles. 
These are followed by the intuitive and spontaneous decision-making styles whereas 
sports managers in Slovenia are least likely to use the avoidant decision-making style. 
Similar results on the structure of decision-making styles in different samples (middle 
managers, teachers, students, military officers and engineers) were also found by other 
authors (Scott & Bruce, 1995; Hariri, Monypenny & Prideaux, 2014; Ghazi & Hu, 
2016; Berisha, et al., 2018; Krasniqi, Berisha & Pula, 2019). The internal consisten-
cy, calculated using Cronbach’s alpha coefficient, was 0.686 for the overall scale and 
between 0.572 (DMS Spontaneous) and 0.814 (DSM Avoidant) for the five subscales. 
The reliability coefficient of the questionnaire items for the spontaneous style can be 
assessed as sufficient, while the other coefficients indicate moderate to robust internal 
consistency (Taber, 2018).

Before applying FA, the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphe-
ricity (Table 2) were carried out to evaluate the factorability. The KMO measure of 
sampling adequacy was 0.689 (the required minimum is above 0.6) and the significance 
of Bartlett’s test of sphericity was 0.000 (p < 0.01). The results of both tests show that 
the studied sample is suitable for performing FA.



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Table 2: The Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity.

KMO and Bartlett‘s Test

Kaiser-Meyer-Olkin 
Measure of Sampling 
Adequacy.

0,689 Bartlett‘s Test of 
Sphericity

Approx. Chi-Square 824.326

df 300

Sig. 0.000

The structure of the decision-making styles of Slovenian sports managers was ve-
rified by FA using the method of principal components with varimax rotation (Table 
3). The FA procedure based on Kaiser-Guttman’s criterion extracted seven (7) factors, 
which cumulatively explain 66.65% of the total variance. Table 3 shows a scree plot 
diagram with the factor eigenvalue curve bend at the fifth factor, meaning that a five-
-factor solution corresponds to the basic GDMS model and could also be considered a 
valid result of the FA (Scott & Bruce, 1995; Spicer & Sadler-Smith, 2005). Thus, the 
rotated solution with five factors explains 54.57% of the total variance of the observed 
variables.

Table 4 shows the factor structure and factor loadings of the items included in the 
GDMS inventory, which were obtained by the orthogonal rotation of the factors using 
the varimax method. It can be observed that all the items measuring a rational decision-
-making style (DMSRAT1 to DMSRAT5) from the original model are related to the 
first factor (factor loadings from 0.637 to 0.725). The first factor explains 13.91% of the 
total variance of the rotated solution (Table 3) and can be named the “rational style”. 
The second factor is associated with four items measuring the avoidant style (DMSA-
VO2, 3, 4 and 5) and one of the spontaneous decision-making style items (DMSSPO2). 
The projections of avoidant style items on the second factor are high (factor loadings 
from 0.663 to 0.876), while the projection of the DMSSPO2 on the same factor is very 
low (0.382). Therefore, the second factor can be named the “avoidant style”, explaining 
13.61% of the total space of the rotated solution (Table 3). The third factor (Table 4) is 
explained with three items measuring the intuitive decision-making style (DMSINT1, 
2 and 5). Projections of items on this factor are very high for all three items (factor 
loadings from 0.797 to 0.871). The third factor explains 10.61% of the total variance of 
the rotated solution (Table 3) and can be named the “intuitive style”. The fourth factor 
is explained with four dependent decision-making style variables (DMSDEP1, 2, 3 and 
4) with relatively high projections on the factor (factor loadings from 0.636 to 0.788). 
The fourth factor explains 8.90% of the total variance (Table 3) and can be named the 
“dependent style”. The fifth factor is explained with only two items, both belonging to 
the spontaneous decision-making style (DMSSPO1 and 3). Their projections on the 
factor are high (factor loadings 0.735 and 0.801). The fifth factor explains 7.54% of 
the total variance of the rotated solution (Table 3) and can be named the “spontaneous 
style”. The sixth factor of the rotated solution is explained with four variables, which, in 



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Total Variance Explained

C
om

po
ne

nt

Initial Eigenvalues Extraction Sums of 
Squared Loadings

Rotation Sums of 
Squared Loadings

To
ta

l

%
 o

f V
ar

ia
nc

e

C
um

ul
at

iv
e 

%

To
ta

l

%
 o

f V
ar

ia
nc

e

C
um

ul
at

iv
e 

%

To
ta

l

%
 o

f V
ar

ia
nc

e

C
um

ul
at

iv
e 

%

1 5.022 20.087 20.087 5.022 20.087 20.087 3.479 13.917 13.917

2 3.451 13.803 33.890 3.451 13.803 33.890 3.403 13.612 27.529

3 2.943 11.774 45.664 2.943 11.774 45.664 2.654 10.615 38.144

4 1.704 6.816 52.480 1.704 6.816 52.480 2.226 8.903 47.048

5 1.347 5.389 57.869 1.347 5.389 57.869 1.884 7.538 54.586

6 1.155 4.621 62.490 1.155 4.621 62.490 1.628 6.511 61.097

7 1.039 4.155 66.645 1.039 4.155 66.645 1.387 5.549 66.645

8 0.915 3.662 70.307      

9 0.860 3.441 73.748       

10 0.813 3.253 77.001       

11 0.700 2.799 79.800       

12 0.634 2.537 82.336       

13 0.620 2.481 84.817       

14 0.572 2.287 87.104       

15 0.471 1.886 88.990       

16 0.429 1.716 90.705       

17 0.398 1.594 92.299       

18 0.367 1.467 93.765       

19 0.329 1.318 95.083       

20 0.300 1.200 96.283       

21 0.267 1.068 97.351       

22 0.215 0.859 98.211       

23 0.171 0.683 98.894       

24 0.164 0.656 99.550       

25 0.112 0.450 100.000       

Table 3: FA of the original GDMS inventory with 25 items.



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Table 4: Factor structure and factor loadings of the 25 items of the GDMS inventory.

Rotated Component Matrixa

 
Component

1 2 3 4 5 6 7

DMSRAT3 0.725       

DMSRAT5 0,716       

DMSRAT4 0.714       

DMSRAT1 0.670       

DMSRAT2 0.637       

DMSAVO3  0.876      

DMSAVO2  0.769      

DMSAVO5  0.760      

DMSAVO4  0.663      

DMSSPO2  0.382      

DMSINT2   0.871     

DMSINT5   0.821     

DMSINT1   0.797     

DMSDEP1    0.788    

DMSDEP4    0.679    

DMSDEP3    0.671    

DMSDEP2    0.636    

DMSSPO3     0.801   

DMSSPO1     0.735   

DMSDEP5      0.613  

DMSINT4      0.563  

DMSAVO1      0.479  

DMSSPO4      0.373  

DMSINT3       0.746

DMSSPO5       0.662

Notes: DMSRAT1-5 = rational style items 1 to 5; DMSINT1 – 5 = intuitive style items 1 to 
5; DMSDEP1 – 5 = dependent style item 1 to 5; DMSAVO1-5 = avoidant style items 1 to 5; 
DMSSPO1 – 5 = spontaneous style items 1 to 5.  



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the original GDMS inventory model, are classified as different decision-making styles. 
With the exception of the rational style variables, all the other decision-making styles 
are related to this sixth factor. Projections of individual items in the sixth factor are 
lower than for the first five factors (factor loadings from 0.373 to 0.613). The sixth fac-
tor explains 6.51% of the total variance of the rotated solution (Table 3) and can be na-
med the “non-rational style” or “descriptive style”, as the variables associated with this 
factor measure all the decision-making styles from the original model with the excep-
tion of the rational style. Items explaining this decision-making style deviate from the 
rational or normative model of decision-making, assuming that the decision-maker is 
entirely rational and fully follows the decision-making process. Observing this aspect, 
these items primarily belong to the descriptive rather than rational decision-making 
styles (Bohanec, 2001). The seventh factor is explained with two variables belonging to 
the intuitive and spontaneous decision-making styles. The projection of both variables 
in the seventh factor is relatively high (DMSINT3 = 0.746 and DMSSPO = 0.662) with 
the factor explaining 5.55% of the total variance (Table 3). The association of these two 
variables in the same factor is not surprising, as different authors have found statisti-
cally significant correlations between the intuitive and spontaneous decision-making 
styles (Scott & Bruce, 1995; Thunholm, 2004; Spicer & Sadler-Smith, 2005; Wood, 
2012; Verma, Rangnekar & Barua, 2012; Curşeu & Schruijer, 2012; Faletič & Avsec, 
2013; Reyna, Ortiz & Revilla, 2014; Hariri, et al., 2014; Bavoľár & Orosová 2015; 
Berisha, et al., 2018; Geisler & Allwood, 2018). Based on this, it can be concluded that 
both styles have the same cognitive structure in the background, which could be named 
the intuitive-experiential cognitive style (Sagiv, Amit, Ein-Gar & Arieli, 2013; Alacreu-
-Crespo, et. al, 2019). As Thunholm (2004) states, the spontaneous decision-making 
style could also be named the high-speed intuitive style due to the urgency of the deci-
sion-making process. As a result, we have named the seventh factor the “high-speed” 
decision-making style. Since the scree plot diagram analysis revealed that it is possible 
to interpret the factor structure with only five factors (Table 3) and as the sixth and se-
venth factors are unclear, we further checked how the variables are projected within the 
five-factor structure of the decision-making styles of sports managers. 

Table 5 shows the five-factor structure of the decision-making styles of Slovenian 
sports managers. The factor structure with a limited number of extracted factors (five) 
explains 57.87% of the total variance – 8.78% less than the full seven-factor model. 
This structure is also characterized by higher eigenvalues of all five extracted factors; 
also, a larger part of the total variance is explained than for the five factors within the 
seven-factor model (+ 3.30%). Eight items are projected onto the first factor, which 
explains 15.67% of the total variance. All the items measuring the avoidant decision-
-making style in the original GDMS inventory are related to this factor (factor loadings 
0.489 and 0.832). Furthermore, two variables measuring the spontaneous decision-ma-
king style (DMSSPO4 = 0.541 and DMSSPO2 = 0.489) and a single variable mea-
suring the dependent decision-making style (DMSDEP5 = 0.658) are also related to 
the first factor. In contrast, within the seven-factor solution, the variables DMSDEP5 
and DMSSPO4 were connected to the sixth factor (non-rational style) and the variable 



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Table 5: Factor structure and factor loadings with a limited number of extracted 
factors.

Rotated Component Matrixa

 
Component

1 2 3 4 5

DMSAVO5 0.832     
DMSAVO3 0.808     
DMSAVO2 0.752     
DMSDEP5 0.658     
DMSAVO1 0.619     
DMSSPO4 0.541     
DMSAVO4 0.495     
DMSSPO2 0.489     
DMSRAT3  0.742    
DMSRAT5  0.693    
DMSRAT4  0.678    
DMSRAT1  0.664    
DMSRAT2  0.659    
DMSINT2   0.858   
DMSINT1   0.817   
DMSINT5   0.788   
DMSINT4   0.566   
DMSDEP1    0.793  
DMSDEP2    0.627  
DMSDEP3    0.564  

DMSDEP4   0.503 0.556  

DMSSPO3     0.774

DMSSPO1     0.687

DMSINT3     0.686

DMSSPO5     0.435

Eigenvalues 3.918 3.436 2.762 2.335 2.017

% of Variance 15.672 13.744 11.048 9.339 8.066



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DMSSPO2 was connected with the lowest projection to the second factor (avoidant 
style).

As the first factor includes all five variables measuring the avoidant style (DMSA-
VO1 - 5), as well as a variable from a seven-factor model structure with a projection 
on the avoidant style factor (Table 4) and two variables with a projection on the sixth 
factor (non-rational style), it can be named the “avoidant style”. The second factor is 
explained with five items measuring the rational decision-making style (DMSRAT1 - 
5). The projections of items on this factor are high for all five items (factor loadings 
from 0.659 to 0.742). The second factor explains 13.74% of the total variance and can 
be named the “rational style”. The third factor is explained with four items measuring 
the intuitive decision-making style (DMSINT1, 2, 4 and 5). The projections of items on 
this factor are moderate to very high (factor loadings from 0.566 to 0.858). The third 
factor explains 11.05% of the total variance and can be named the “intuitive style”. The 
fourth factor is, as in the seven-factor model, explained with four dependent decision-
-making style variables (DMSDEP1, 2, 3 and 4). Projections of items on this factor 
are moderate to high (factor loadings from 0.556 to 0.793); the fourth factor explains 
9.34% of the total variance and can be named the “dependent style”. The fifth factor 
is a combination of the fifth (spontaneous style) and seventh (high-speed style) factors 
from the seven-factor model structure. This factor is explained with three variables 
measuring the spontaneous decision-making style in the original model (DMSSPO1, 3 
and 5) and a variable measuring intuitive style (DMSINT3), together explaining 8.07% 
of the total variance of the studied space. With the exception of the variable DMSSPO5, 
which has a slightly lower projection on the fifth factor (0.435), other variables have 
high projections (factor loadings from 0.686 to 0.774). The fifth factor is named the 
“spontaneous style”.

In this way, the developed five-factor decision-making styles structure model forms 
individual factors or decision-making styles more clearly and, at the same time, establi-
shes the same structure as the original GDMS inventory (Scott & Bruce, 1995), which 
was confirmed by other authors (Loo, 2000; Thunholm, 2004; Spicer & Sadler-Smith, 
2005; Gambetti, et al., 2008; Curşeu & Schruijer; 2012; Avsec, 2012; Erenda, Meško & 
Bukovec; 2014; Bavoľár & Orosová, 2015; Alacreu-Crespo, et. al, 2019). Regardless of 
the increased clarity of the five-factor structure model, some variables are nevertheless 
distributed outside the predicted decision-making styles. Some other authors have also 
faced a similar problem with different samples; they named the variables that were not 
distributed among the factors in accordance with the intended model as “problematic 
items”. One such item, which in the resulting five-factor structure (Table 5), was not 
projected onto the factors in accordance with the original model, is DMSDEP5 (I like 
to have someone to steer me in the right direction when I am faced with important de-
cisions) (Baiocco, Laghi, D´alesio, Gurrieri & Di Chiacchio, 2007; Fischer, Soyez & 
Gurtner, 2015; del Campo, Pauser, Steiner & Vetschera, 2016). This particular item did 
not project onto a dependent style factor in either seven-factor or five-factor structure 
models. Two further variables were also not projected onto a spontaneous style factor 
in either of the two models; namely, DMSSPO4 (I often make impulsive decisions) 



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and DMSSPO2 (I often make decisions on the spur of the moment) (Fischer, et al., 
2015). In the continuation of the present study, we designed the “optimized structure 
model” by removing the mentioned variables from the structure of the decision-making 
styles of Slovenian sports managers. In order to balance the number of items for each 
decision-making style (four items per style), we also removed the variables that, in the 
five-factor structure model (Table 5), had the smallest projections on the avoidant style 
factor (DMSAVO4 - I generally make important decisions at the last minute) and the 
rational style factor (DMSRAT2 - I make decisions in a logical and systematic way). 
Both of these variables have also been characterized as problematic by other authors 
(Baiocco, et. al, 2007; Fischer, et al., 2015). Based on previous projections of the vari-
able DMSINT3 (I generally make decisions that feel right to me) onto the high-speed 
(Table 4) and spontaneous (Table 5) styles, we assumed that in the continuation of the 
research, this variable would also have a high projection on the spontaneous decision-
-making style.

Table 6: Descriptive statistics and internal consistency of the optimized structure model 
of decision-making styles.

Va
ri

ab
le

Po
ss

ib
le

 r
an

g

A
ct

ua
l r

an
ge

Mean

St
an

da
rd

 
D

ev
ia

tio
n

Sk
ew

ne
ss

K
ur

to
si

s

C
ro

nb
ac

h 
α

Va
lu

e

%
 o

f 
m

ax
im

um

DMS 
Rational  5–20  12–20 17.03 85.13% 1.736 -0.203 0.630 0.740

DMS 
Intuitive  5–20  4–18 12.43 62.13% 2.997 -0.591 0.258 0.775

DMS 
Dependent  5–20  9–20 15.28 76.38% 2.648 -0.087 -0.520 0.705

DMS 
Avoidant  5–20  4–14 7.18 35.88% 2.540 0.403 -0.706 0.814

DMS 
Spontaneous  5–20  5–17 12.56 62.81% 2.609 -0.575 0.051 0.609

Table 6 reveals no changes in the order of the average use of individual decision-
-making styles, between the optimized structural model of the decision-making styles 
of Slovenian sports managers (20 items; 4 items per decision-making style) and the 
original GDMS inventory model (25 items, 5 items per decision-making style). The 
internal consistency, calculated using Cronbach’s alpha coefficient, was 0.637 for 



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the overall scale and between 0.609 (DMS Spontaneous) and 0.814 (DSM Avoidant) 
for the five subscales. The reliability coefficients for the intuitive (DMS Intuitive α = 
0.775), dependent (DMS Dependent α = 0.705) and spontaneous (DMS Spontaneous 
α = 0.609) subscales were higher in comparison to the original model, whilst the reli-
ability coefficient was slightly lower for the rational style subscale (DMS Rational α = 
0.740) and equal for the avoidant decision-making style subscale. The KMO measure 
of sampling adequacy was 0.646 (the required minimum is above 0.6) and the signifi-
cance of Bartlett’s test of sphericity was 0.000 (p < 0.01) (Table 7). The results of both 
tests show that the studied sample is suitable for performing FA.

Table 7: The Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity for the 
optimized model.

KMO and Bartlett‘s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.646

Bartlett‘s Test of Sphericity

Approx. Chi-Square 592.612

df 190

Sig. 0.000

The optimized structure with 20 items of the decision-making styles of Slovenian 
sports managers was verified by FA using the method of principal components with 
varimax rotation (Table 8). The FA procedure, based on Kaiser-Guttman’s criterion, 
extracted five (5) factors that cumulatively explained 61.60% of the total variance, 
which is 3.73% more than in the five-factor structure of the original GDMS Inventory 
with 25 items (Table 5). 

Table 9 shows the factor structure and factor loadings of the 20 items included in the 
optimized model inventory, obtained by the orthogonal rotation of the factors using the 
varimax method. Four avoidant style variables (DMSAVO1, 2, 3 and 5) are associated 
with the first factor (factor loadings from 0.618 to 0.859), together explaining 14.39% 
of the total variance (Table 8). This first factor can be named the “avoidant style”. The 
second factor is explained with four items measuring the intuitive decision-making 
style (DMSINT1, 2, 4 and 5). The projections of items on this factor are very high for 
three items (factor loadings from 0.803 to 0.856) and moderate for DMSINT4 (0.569). 
The second factor explains 13.45% of the total variance and can be named the “intuitive 
style”. The third factor is explained with four items measuring the rational decision-ma-
king style (DMSRAT1, 3, 4 and 5). The projections of items on this factor are high for 
all four items (factor loadings from 0.661 to 0.754). The third factor explains 13.29% 
of the total variance and can be named the “rational style”. Four variables measuring 



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Table 8: FA of the optimized structure model inventory with 20 items.

Total Variance Explained

C
om

po
ne

nt

Initial Eigenvalues Extraction Sums of 
Squared Loadings

Rotation Sums of 
Squared Loadings

To
ta

l

%
 o

f 
Va

ri
an

ce

C
um

ul
at

iv
e 

% To
ta

l

%
 o

f 
Va

ri
an

ce

C
um

ul
at

iv
e 

% To
ta

l

%
 o

f 
Va

ri
an

ce

C
um

ul
at

iv
e 

%

1 3.547 17.735 17.735 3.547 17.735 17.735 2.878 14.388 14.388

2 3.129 15.646 33.380 3.129 15.646 33.380 2.689 13.446 27.834

3 2.785 13.925 47.305 2.785 13.925 47.305 2.658 13.288 41.121

4 1.577 7.887 55.192 1.577 7.887 55.192 2.188 10.942 52.063

5 1.282 6.408 61.600 1.282 6.408 61.600 1.907 9.536 61.600

6 0.984 4.920 66.519       

7 0.882 4.409 70.928       

8 0.809 4.044 74.972       

9 0.798 3.988 78.961       

10 0.658 3.289 82.250       

11 0.624 3.119 85.369       

12 0.580 2.901 88.271       

13 0.509 2.543 90.813       

14 0.374 1.871 92.684       

15 0.326 1.632 94.317       

16 0.307 1.536 95.852       

17 0.261 1.306 97.158       

18 0.238 1.190 98.348       

19 0.208 1.040 99.388       

20 0.122 0.612 100.000       



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Table 9: Factor structure and factor loadings of the optimized model inventory with 20 
items.

Rotated Component Matrixa

 
Component

1 2 3 4 5

DMSAVO3 0.859     

DMSAVO5 0.833     

DMSAVO2 0.828     

DMSAVO1 0.618     

DMSINT2  0.856    

DMSINT1  0.811    

DMSINT5  0.803    

DMSINT4  0.569    

DMSRAT3   0.754   

DMSRAT5   0.732   

DMSRAT4   0.716   

DMSRAT1   0.661   

DMSDEP1    0.812  

DMSDEP3    0.635  

DMSDEP2    0.594  

DMSDEP4    0.581  

DMSSPO3     0.790

DMSINT3     0.705

DMSSPO1     0.677

DMSSPO5     0.433



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the dependent decision-making style have a projection on the fourth factor. The projec-
tions of the variables on this factor range from moderate for the variables DMSDEP4 
(0.581), DMSDEP2 (0.594) and DMSDEP3 (0.635) to very high for the variable DM-
SDEP1 (0.812). The fourth factor explains 10.94% of the total variance and can be 
named the “dependent style”. The fifth factor combines three variables measuring the 
spontaneous decision-making style (DMSSPO1, 3 and 5) and a variable measuring 
the intuitive style (DMSINT3); this factor is identical to the fifth factor extracted in a 
five-factor structure with 25 items (Table 5). With the exception of the variable DMS-
SPO5, which has a low but still satisfactory projection onto this factor (0.433), the other 
variables have high projections (factor loadings from 0.677 to 0.790). The fifth factor 
explains 9.54% of the total variance.

Table 10: Correlations between the decision-making styles in the optimized structure 
model inventory with 20 items.

Correlations

 DMS 
Rational

DMS 
Intuitive

DMS 
Dependent

DMS 
Avoidant

DMS 
Spontaneous

DMS Rational 1     

DMS Intuitive -0.143 1    

DMS Dependent .348** 0.012 1   

DMS Avoidant -0.211 0.020 0.175 1  

DMS Spontaneous -0.087 .278* -0.036 -0.025 1

Notes: * p < 0.05; ** p < 0.01.

Table 10 shows the correlations between the extracted factors within the optimized 
model of the decision-making styles of Slovenian sports managers. Correlation analysis 
showed that the rational and dependent decision-making styles are statistically signifi-
cantly related at a 1% risk level. A statistically significant association at a 5% risk level 
was also found between the intuitive and spontaneous decision-making styles. Similar 
conclusions were also reached by other authors (Scott & Bruce, 1995; Thunholm, 2004; 
Spicer & Sadler-Smith, 2005; Baiocco, Laghi & Alessio, 2009; Wood, 2012; Verma, et 
al., 2012; Curşeu & Schruijer, 2012; Faletič & Avsec, 2013; Reyna, et. al., 2014; Hariri, 
et al., 2014; Bavoľár & Orosová 2015; Berisha, et al., 2018; Geisler & Allwood, 2018). 
These findings are consistent with the expectations; namely, both types of connections 
are characterized by the same cognitive style in the background, defining the manife-
station of the aforementioned styles. Thus, the rational and dependent decision-making 
styles have a background in the rational-analytical cognitive style, while the intuitive 



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and spontaneous decision-making styles have a background in the intuitive-experiential 
cognitive style (Sagiv et. al, 2013; Alacreu-Crespo et al., 2019).

DISCUSSION

The decision-making style focuses attention on how an individual obtains, uses and 
interprets information. Thunholm (2004) defined a decision-making style as a response 
pattern that an individual shows when faced with a decision problem. This response 
pattern depends on the decision situation, the decision problem and the decision maker. 
Faletič and Avsec (2013) stated that although the nature of the problem and the situati-
onal factors play an important role in decision-making, we can assume that individuals 
differ in the frequency of using individual decision-making styles regardless of the 
decision-making problem. Managers’ decision-making styles contribute significantly 
to their individual performance and thus to the performance of organizations (Abdel-
salam, Dawoud & ElKadi, 2013); therefore, as pointed out by Rowe and Boulgarides 
(1992), they need to be measured, because decision-making styles should form the 
backbone of effective decision-making.

The present study deals with determining the structure of the decision-making styles 
of Slovenian sports managers. The GDMS Inventory (Scott & Bruce, 1995) with a five-
-factor structure was used to measure decision-making styles. After three successive 
implementations of FA using the method of principal components with the orthogonal 
rotation of factors using the varimax method, we developed a five-factor model of 
decision-making styles with 20 items. The results and a comparison of the individual 
obtained models are presented in Table 11.

Table 11 shows the basic characteristics of all three studied factor models. In all 
three models, the first five extracted factors form the original structure of the model de-
veloped by Scott and Bruce (1995), which was confirmed by the authors earlier menti-
oned. The developed optimized structure model inventory includes 20 items measuring 
the avoidant, intuitive, rational, dependent and spontaneous decision-making styles. 
This model has relatively good internal consistency, both at the level of the entire mo-
del and at the level of the individual decision-making styles. Individual factors also 
explain the variance of the space of decision-making styles in a more balanced way 
compared to the other two models with 25 items. Another advantage of the developed 
optimized model is the balanced number of items measuring the individual decision-
-making styles, allowing us to determine a clearer structure of decision-making styles, 
both at the level of the individual decision-maker and at the level of the entire sample. 
In all three factor models, the rational, avoidant and dependent styles showed the gre-
atest stability of the structure of the included items. The stability of the intuitive style 
was relatively good, while the spontaneous style scale proved to be very unstable and 
problematic (Fischer et. al, 2015).

Based on the optimized structure model inventory, we calculated the structure of the 
decision-making styles of Slovenian sports managers (Table 6), confirming that when 



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Edvard KOLAR, Matej TUŠAK: DECISION-MAKING STYLE STRUCTURE OF SLOVENIAN SPORTS MANAGERS , 47–73
Ta

bl
e 

11
: B

as
ic

 c
ha

ra
ct

er
is

tic
s o

f a
ll 

th
re

e 
fa

ct
or

 m
od

el
s o

f t
he

 d
ec

is
io

n-
m

ak
in

g 
st

yl
e 

st
ru

ct
ur

e 
of

 S
lo

ve
ni

an
 sp

or
ts

 m
an

ag
er

s.

Solution
7-

fa
ct

or
s s

ol
ut

io
n

5-
fa

kt
or

 so
lu

tio
n

O
pt

im
iz

ed
 st

ru
ct

ur
e 

m
od

el
 in

ve
nt

or
y

(2
5 

ite
m

s)
(2

5 
ite

m
s)

(2
0 

ite
m

s)

%
 o

f 
va

ri
an

ce
66

.6
45

%
57

.8
69

%
61

.6
00

%

Extracted factors
(decion-making styles)

Factor name

No of items

% of variance

α

Factor name

No of items

% of 
variance

α

Factor name

No of items

% of 
variance

α

R
at

io
na

l s
ty

le
5

13
.9

2%
0.

77
7

Av
oi

da
nt

 
st

yl
e

8
15

.6
7%

0.
82

8
Av

oi
da

nt
 

st
yl

e
4

14
.3

9%
0.

81
4

Av
oi

da
nt

 st
yl

e
5

13
.6

1%
0.

81
0

R
at

io
na

l 
st

yl
e

5
13

.7
4%

0.
77

7
In

tu
iti

ve
 

st
yl

e
4

13
.4

5%
0.

77
5

In
tu

iti
ve

 st
yl

e
3

10
.6

1%
0.

82
4

In
tu

iti
ve

 
st

yl
e

4
11

.0
5%

0.
77

5
R

at
io

na
l 

st
yl

e
4

13
.2

9%
0.

74
0

D
ep

en
de

nt
 st

yl
e

4
8.

90
%

0.
70

5
D

ep
en

de
nt

 
st

yl
e

4
9.

34
%

0.
70

5
D

ep
en

de
nt

 
st

yl
e

4
10

.9
4%

0.
70

5

Sp
on

ta
ne

ou
s 

st
yl

e
2

7.
54

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Edvard KOLAR, Matej TUŠAK: DECISION-MAKING STYLE STRUCTURE OF SLOVENIAN SPORTS MANAGERS , 47–73

ANNALES KINESIOLOGIAE • 13 • 2022 • 1

making decisions, sports managers use a combination of all five decision-making styles 
(Scott & Bruce, 1995; Thunholm, 2004; Avsec, 2012; Faletič & Avsec, 2013). Slove-
nian sports managers mostly use the rational (Atilgan & Kaplan, 2022) and dependent 
decision-making styles, indicating that they are mostly rational decision-makers. Rati-
onal decision-makers characteristically follow a decision-making process involving the 
critical evaluation of evidence and a structured process that requires time and conscious 
effort before making and implementing decisions (Fitzgerald, Mohammed & Kremer, 
2017). Rational and intuitive decision-making styles are defined as functional decision-
-making styles, the use of which leads to various positive outcomes (Faletič & Avsec, 
2013; Alacreu-Crespo, et. al, 2019). In contrast to a number of other studies, in our 
sample, the dependent decision-making style emerged as the second most used style 
(Spicer & Sadler-Smith, 2005; Curşeu & Schruijer, 2012; Erenda, Meško & Bukovec, 
2014; Alacreu-Crespo et al., 2019; El Othman et. al, 2020). The dependent decision-
-making style has a statistically significant positive correlation with emotional (seeking 
moral support) and instrumental social support (seeking advice, help and information 
from others). Connection with both aspects of support indicates that individuals who 
predominantly use the dependent decision-making style, seek support within their envi-
ronment for the decision-making processes (Alacreu-Crespo et al., 2019). However, it 
has to be emphasized that the dependent style is not necessarily dysfunctional, as it also 
correlates with positive outcomes when it is defined on the basis of behaviour, such as 
seeking advice and support and not shifting responsibility to others (Faletič & Avsec, 
2013; Fischer et. al, 2015). Frequent use of the dependent decision-making style in 
Slovenian sports managers is probably related to specific characteristics for this type of 
organization (Young, 1998; Kolar & Jurak, 2014). Sports managers mostly work in in-
terest-type associations, where the interests of various participants and stakeholders (at-
hletes, volunteers, employees, associations, the state, local communities, sponsors, etc.) 
overlap or are even in conflict. Managers need to constantly coordinate and consider all 
these interests in the decision-making processes in order to achieve the organization’s 
strategic and operational goals (Parent, 2010). In these organizations, there is also a 
“unique” governmental-managerial process, led by a committee of elected volunteers 
(governmental organizational function) who form very sensitive relations with the pro-
fessional (management) staff (Young, 1998; Kikulis, Slack & Hinings, 1995). When re-
gulating this process, the managers are in a subordinate position, as they are appointed 
by the governmental function and therefore need to act in accordance with the interests 
of the government. In order to avoid a conflict between the managerial and governmen-
tal structures, the managers depend on the opinions, directions and decisions of the 
government, otherwise the negative consequences would mostly be reflected on the 
managers. The structure of decision-making styles also shows that sports managers use 
an intuitive and spontaneous decision-making style to a lesser extent, which means that 
they are less likely to make decisions quickly, unconsciously and based on experience 
(Simon, 1987; Epstein, 1994; Kahneman, 2003; Dane & Pratt, 2007). This is probably 
also related to the aforementioned specifics of this type of organization. Sports mana-
gers use an avoidant decision-making style least often or to a negligible extent, which 



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Edvard KOLAR, Matej TUŠAK: DECISION-MAKING STYLE STRUCTURE OF SLOVENIAN SPORTS MANAGERS , 47–73

is good, because this decision-making style is defined as pathological and dysfunctional 
and, as such, does not lead to decisions (Mitchell, Shepherd & Sharfman, 2011; Faletič 
& Avsec, 2013).

Finally, it is necessary to mention the recognized connection between the rational 
and the dependent styles, which are together also classified as a non-functional deci-
sion-making style. Since the structure of the decision-making styles in our sample is 
dominated by the rational decision-making style, we could conclude that this forms 
a dependent-rational decision-making style, which can be characterized as functional 
(Faletič & Avsec, 2013; Fischer et. al, 2015). It is typical for such decision-makers to 
seek advice, opinions and knowledge from colleagues when making decisions, thus 
using the dependent style and increasing the rationality of their decisions (Vroom, 
2003; Khasawneh, Alomari & Abu-tineh, 2011). Such an understanding is in accor-
dance with the theory of extended rationality (Secchi, 2010), where a decision-maker 
reduces the influence of the limitations of rationality, which arise from an individual’s 
abilities to acquire and process information (Simon, 1976).

CONCLUSION

The decision-making process of managers has an important impact on the deve-
lopment and growth of sports organizations; therefore, the knowledge of the way mana-
gers make decisions is very important. In the present study, we found that the structure 
of the decision-making styles of Slovenian sports managers is formed as a combina-
tion of five decision-making styles, with the rational and dependent decision-making 
styles being predominant. We can conclude that the recognized average structure of 
decision-making styles is functional and healthy; furthermore, Slovenian sports mana-
gers are, on average, rational decision-makers who, due to the specific organizational 
characteristics of sports organizations, look for confirmation and opinions on future 
decisions in the broader environment of the organizations’ stakeholders. This study also 
developed an instrument for measuring the decision-making styles of sports managers, 
which assumes a five-factor structure of decision-making styles and is consistent with 
the GDSM Inventory developed and proposed by Scott and Bruce (1995). By using the 
questionnaire, it is possible to predict the behaviour of individual decision-makers in 
decision-making situations, which can be an important tool when choosing a manager 
for an individual sports organization or placing them in the overall organizational struc-
ture of a sports organization.

Limitations of the Study

There are some limitations that should be considered for a more valid understanding 
of the results obtained. The participants completed the questionnaire online and this 
may have influenced the results. The study could be improved with a larger sample, 



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ANNALES KINESIOLOGIAE • 13 • 2022 • 1

which means that we need to be careful when generalizing the results to the entire po-
pulation of sports managers.

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