Gamifica ti on is a rela ti vely new concept that refers to the use of game elements in non ‐game produc ti ve ac ti vity. It 
also can be implemented as a behavioral modeling tool influencing behavioral change in an organiza ti onal context. 
A remaining challenge in gamifica ti on is the absence of measurement focus to empirically quan ti fy gamifica ti on at ‐
tributes. This paper measures key behavioral changes that gamifica ti on influence among employees and assesses 
their theore ti cal founda ti on. We combined validated measurement tools to empirically measure behavior changes, 
especially engagement, performance, and sa ti sfac ti on. The combined measurement tool includes the Utrecht Work 
Engagement Scale (UWES), the Individual Work Performance Ques ti onnaire (IWPQ), and the Minnesota Sa ti sfac ti on 
Ques ti onnaire (MSQ). Research results proved that there is a significant behavioral di fference between employees 
that were influenced by gamifica ti on and employees that were not. Employees that were exposed to gamifica ti on 
demonstrated higher engagement and sa ti sfac ti on levels and verified the potency of gamifica ti on. Research results 
evidenced no significant di fferences between the two groups in terms of performance levels. This research paper will 
guide prac titi oners to be tt er evaluate gamifica ti on a tt ributes and improve gamifica ti on organiza ti onal assimila ti on. 
 
Keywords: gamifica ti on, engagement, job performance, sa ti sfac ti on, organiza ti onal behavior
EMPIRICAL ANALYSIS OF THE INFLUENCE OF GAMIFICATION ON EMPLOYEES’ 
BEHAVIOR 
Ibrahim Hamza 
Faculty of Economic and Social science, Budapest University of Technology and Economics, Hungary 
hamza.ibrahim@gtk.bme.hu  
Sarolta Tóvölgyi 
Faculty of Economic and Social science, Budapest University of Technology and Economics, Hungary 
tovolgyi.sarolta@gtk.bme.hu 
Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 71
logical experiences as games generally do (Huotari & 
Hamari, 2012). Gamifica ti on is portrayed through and 
defined by game elements, the choice of which di ffers 
from one researcher to another. However, the most 
iden ti fied ones in the literature are points, badges, 
leader boards, avatars, quests, performance graphs, 
and cer ti ficates (Scheiner, 2015; Cardador, Northcra ft , 
& Whicker, 2017; Mekler, Brühlmann, Opwis, & Tuch, 
2013). With its potent game design aspects, gamifica ‐
ti on s ti mulates individual incen ti ves and drives user 
behavior. Therefore, to be tt er understand gamifica ‐
ti on, it is of supreme importance to acknowledge and 
fully comprehend user behavior, specifically user be ‐
havioral changes in organiza ti onal contexts. These 
changes are induced by interpersonal and organiza ‐
ti onal factors. 
1 INTRODUCTION 
Gamifica ti on can be defined as embedding game 
elements into ac ti vi ti es that are not themselves 
games (Werbach & Hunter, 2012). This engaging phe ‐
nomenon helps in implemen ti ng mo ti va ti onal a ffor ‐
dances in services to evoke game ‐like experiences and 
improve behavioral results. Gamifica ti on processes 
are being applied today in numerous fields, including 
educa ti on, health, business, and management 
(Bozkurt & Durak, 2018). This e ffec ti ve problem ‐solv ‐
ing and goal ‐achieving tool (Zainuddin, Chu, Shujahat, 
& Perera, 2020) also is implemented for behavioral 
change by influencing and promo ti ng desired learning 
behavior ( Ērgle & Ludviga, 2018; Buckley & Doyle, 
2017), and invoking in individuals the same psycho ‐
Abstract
Vol. 11, No. 2, 71 ‐78 
doi:10.17708/DRMJ.2022.v11n02a05

Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 72
Ibrahim Hamza, Sarolta Tóvölgyi: Empirical Analysis of the Influence of Gamifica ti on on Employees’ Behavior
Behavioral change is the abandonment of certain 
behaviors and the adop ti on of new ones (Prochaska 
& Velicer, 1997). Changing behavior is not about 
changing one act; it is about altering the behavioral 
rou ti nes in which the acts are embedded (Heimlich & 
Ardoin, 2008). Behavioral change is saturated with 
complexi ti es, and for that reason there is no single 
theory that can fully account for it. However, such a 
change could be well described when it is caused by 
gamifica ti on. Self ‐determina ti on theory and flow the ‐
ory could be classified as principal theories that eluci ‐
date how gamifica ti on influences behavioral change 
(Krath, Schürmann, & von Korflesch, 2021).  
According to self ‐determina ti on theory (SDT), 
relatedness, autonomy, and competence are three 
primary psychological needs that all individuals as ‐
pire to fulfil. SDT is applicable to the se tti ngs of 
learning and games because it explains the social 
contexts that can either boost or lessen intrinsic mo ‐
ti va ti on (Kam & Umar, 2018). On the other hand, 
flow theory delineates the state in which users be ‐
come entangled in a certain ac ti vity and lose their 
sense of ti me (Csikszentmihalyi, 1991). When indi ‐
viduals are fully engaged in an ac ti vity, they perceive 
the intrinsic nature of hoped ‐for rewards (Csikszent ‐
mihalyi, 2014). Flow theory illustrates one of the 
principal goals of gamifica ti on, and the recent liter ‐
ature has examined the e fficacy of using gamifica ‐
ti on elements to retain users in a flow experience 
(Huang et al., 2018). 
Empirically evalua ti ng the behavioral changes 
imposed by gamifica ti on on employees has re ‐
mained a hurdle. There are no studies that clearly 
show how such a measurement can be quan ti fied 
exclusively. In our work, we applied a combined tool 
that is formed by three validated measurement 
tools to empirically measure employees’ engage ‐
ment, performance, and sa ti sfac ti on, because these 
are important factors of organiza ti onal behavior.  
 
2 METHODOLOGY 
2.1 Hypotheses 
Previous research addressed the importance of 
implemen ti ng gamifica ti on in business and its po ‐
ten ti al posi ti ve influence on employees’ engage ‐
ment (Robson et al., 2016; Ponis et al., 2020), 
performance (Nacke & Deterding, 2017; Hosseini et 
al., 2021) and sa ti sfac ti on (Nacke & Deterding, 2017; 
Schöbel et al., 2020). Gamifica ti on is a kind of tech ‐
nology that influences change without enforcing it 
(Liu, Santhanam, & Webster, 2017). We developed 
a novel approach that validates gamifica ti on e ffects 
on employees’ behavior, and which can quan ti ta ‐
ti vely measure behavioral aspects. Gamifica ti on is a 
behavioral ‐change modeling tool when tailored ad ‐
equately. In this research, the hypotheses are as fol ‐
lows: 
 
H1. Gamifica ti on has a posi ti ve e ffect on employees’ 
behavior. 
 
H1 ‐1. Gamifica ti on has a posi ti ve e ffect on employ ‐
ees’ engagement. 
 
H1 ‐2. Gamifica ti on has a posi ti ve e ffect on employ ‐
ees’ performance. 
 
H1 ‐3. Gamifica ti on has a posi ti ve e ffect on employ ‐
ees’ sa ti sfac ti on. 
 
2.2 Measurement 
To address these hypotheses, we constructed a 
measurement tool that can analyze employees’ key 
behavioral changes in an organiza ti onal context. Our 
measurement tool is a combina ti on of three self ‐re ‐
por ti ng validated tools: the Utrecht work engagement 
scale (UWES), the Individual Work Performance Ques ‐
ti onnaire (IWPQ), and the Minnesota Sa ti sfac ti on 
Ques ti onnaire (MSQ). We name this novel theore ti cal 
contribu ti on EPS, which highlights the three variables 
measured: engagement, performance, and sa ti sfac ‐
ti on. We applied the Utrecht scale to measure empir ‐
ically how gamifica ti on implementa ti ons influences 
engagement. The method consists of 17 items and 
provides a more concrete overview of employees’ 
vigor, dedica ti on, and absorp ti on (Schaufeli & Bakker, 
2003; Seppälä et al., 2009). Vigor refers to energy lev ‐
els and mental resilience while working. Respondents 
answer the scale using a 7 ‐point Likert in which 0 in ‐
dicates Never and 7 indicates Always. The second ap ‐
plied measurement tool is the IWPQ, which 
incorporates task performance, interpersonal perfor ‐
mance, and counterproduc ti ve work behavior (Koop ‐
mans et al., 2012; Koopmans, Bernaards, Hildebrandt, 
De Vet, & Van Der Beek, 2014). Originally the IWPQ 
consisted of 47 items, however, to address our re ‐

Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 73
search aim we selected a shorter 25 ‐item version. The 
items were scored on a 5 ‐point Likert scale in which 1 
indicates Strongly disagree and 5 indicates Strongly 
agree. Finally, we applied the MSQ to measure the ef ‐
fect of gamifica ti on on employees’ sa ti sfac ti on. The 
measurement tool is used widely in the literature 
(Gillet & Schwab,1975; Weiss, Dawis, England, & 
Lofquist, 1967; Inayat & Khan, 2021) and provides ac ‐
tual evidence of any changes in employees sa ti sfac ‐
ti on levels. The MSQ is a 5 ‐point Likert ‐type scale 
formed of 20 items and is a ti me ‐stable instrument. 
 
2.3 Par ti cipants and Procedures 
Our sample was formed of 62 European em ‐
ployees who were pursuing their higher educa ti on 
in Hungary. Our data were obtained using ques ti on ‐
naires. The surveys were distributed using Google 
forms, emails, and social media. Because gamifica ‐
ti on is not yet a widely recognized concept, we con ‐
veniently conducted this research among 
employees who were con ti nuing their higher edu ‐
ca ti on at Budapest University of Technology and 
Economics. Our sample comprised 56.5% males, 
41.9% females, and 1.6% who iden ti fied themselves 
as other; 54.8% of our ques ti onnaire respondents 
were between 18 and 25, 37.1% were between 26 
and 35, and only 8.1% were between 36 and 45. 
Most of our respondents were university graduates; 
48.4% had finished their bachelor’s degree, and 
33.9% had completed their master’s degree. The 
level of work experience also indicated that 53.2% 
of our respondents had 1–5 years of experience, 
whereas 24.2% had less than 1 year.  
Our demographical data can help us unravel 
employees’ percep ti on factors, which are examined 
in the Analysis and Results sec ti on. Table 1 presents 
our sample’s age distribu ti on, Table 2 presents their 
educa ti onal distribu ti on, and Table 3 presents our 
respondents’ years of experience. 
 
Table 1: Age distribu ti on 
Table 2: Educa ti onal level distribu ti on 
 
Table 3: Employment years distribu ti on 
 
 
3 ANALYSIS AND RESULTS 
Our research data indicates that 21% of our 
respondents were never exposed to gamification 
at work, whereas 79% acknowledged being ex ‐
posed to gamification and game design elements 
in an organizational context. Furthermore, 41.9% 
of the respondents acknowledged a high level of 
familiarity with the concept of gamification and 
procedures, and 27.5% of respondents indicated 
low familiarity levels. The collected data demon ‐
strate that most of our sample had a good level 
of familiarity and understanding of gamification 
in an organizational context. Our population was 
divided into two groups: Group 1 (G1) is the em ‐
ployees that were not exposed to gamification, 
and Group 2 (G2) is formed of employees that 
were exposed to gamification in an organizational 
context. Our research goal was to empirically 
measure the effects of gamification and compare 
Groups G1 and G2 in terms of engagement, per ‐
formance, and satisfaction levels. Firstly, we con ‐
ducted Kolmogorov–Smirnov and Shapiro–Wilk 
normality tests to address our sample distribution 
better. 
 
Age Percentage 
18 ‐25 54.8%
26 ‐35 37.1%
36 ‐45 8.1%
Educa ti on levels Percentage 
Elementary school 1.6%
High school graduate 11.3%
Bachelor’s degree graduate 48.4%
Master’s degree graduate 33.9%
PhD graduate 4.8%
Employment years Percentage 
1 24.2%
1 ‐5 53.2%
6 ‐10 17.7%
11 ‐15 4.8%

Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 74
Ibrahim Hamza, Sarolta Tóvölgyi: Empirical Analysis of the Influence of Gamifica ti on on Employees’ Behavior
According to the Kolmogorov–Smirnov test, our 
data on sa ti sfac ti on and engagement are not nor ‐
mally distributed (0.0113 < 0.05, and 0.153 < 0.05). 
Our test results analysis indicates that performance 
levels are normally distributed (0.150 > 0.05). We 
also conducted a Shapiro–Wilk normality test to val ‐
idate our results further (Table 5). 
The Shapiro–Wilk test indicates the same results as 
the Kolmogorov–Smirnov test. Our data on sa ti sfac ti on 
and engagement are not normally distributed (0.0113 
< 0.05, and 0.153 < 0.05), and, in contrast, our perfor ‐
mance levels are normally distributed (0.150 > 0.05). 
Based on our results, we conducted Mann–
Whitney U tests on our variables of sa ti sfac ti on and 
engagement levels, and an independent T ‐test on 
our variables of performance levels. These tests 
allow us to determine if there were any di fferences 
between Groups G1 and G2. Table 6 presents the re ‐
sults of the Mann–Whitney U test. 
Data analysis in Table 6 indicates moderate to 
strong di fferences between Groups G1 and G2 in 
terms of engagement levels (0.023 < 0.05), with a 
Mann–Whitney U value of 450.0 and a standard error 
of 57.792. Examining the data results carefully led us 
to conclude the validity of our first sub ‐hypothesis, 
H1 ‐1. Moderate to strong di fferences exist between 
employees that were exposed to gamifica ti on and 
employees that were not in terms of organiza ti onal 
engagement. The same di fferen ti ated result was ev ‐
ident when we replicated the data analysis on our 
sa ti sfac ti on variable as indicated in Table 6. There 
were moderate to strong di fferences between 
Groups G1 and G2 in terms of job sa ti sfac ti on (0.020 
< 0.05), with a Mann–Whitney U value of 452.5 and 
a standard error of 57.78. Based on this analysis, we 
can conclude that Hypothesis H1 ‐3 is accepted: mod ‐
erate to strong di fferences exist between employees 
that were exposed to gamifica ti on and employees 
that were not exposed to gamifica ti on in terms of or ‐
ganiza ti onal sa ti sfac ti on. Owing the results of the 
normality tests in Tables 4 and 5 that proved the nor ‐
mality of our performance variable distribu ti on, we 
conducted an independent T ‐test to validate our sec ‐
ond sub ‐hypothesis. Table 7 demonstrates the inde ‐
pendence of performance from the influence of 
gamifica ti on. No significant di fferences existed be ‐
tween Groups G1 and G2 in terms of organiza ti onal 
performance (significance value of 0.082 > 0.05, and 
a T ‐value of 1.731). Elabora ti ng on our results, we 
conclude that our second sub ‐hypothesis is rejected. 
We repeated our tests on sa ti sfac ti on and engage ‐
ment levels using the independent T ‐test to validate 
the achieved results further. 
 
Table 7: Performance: independent T ‐test 
 
The T ‐test measurements demonstrate a signifi ‐
cance value of engagement: (0.039 < 0.05, and a T ‐
value of −2.236), which also validates Sub ‐hypothesis 
H1 ‐1. Employees that were exposed to gamifica ti on 
Sta ti s ti cs df (Sig)
Sa ti sfac ti on 0.135 62 (0.46)
Engagement 0.150 62 (0.007)
Performance 0.113 62 (0.001)
Sta ti s ti cs df (Sig)
Sa ti sfac ti on 0.980 62 (0.398)
Engagement 0.914 62 (0.000)
Performance 0.915 62 (0.000)
Sa ti sfac ti on Engagement
Total N 62 62
Mann ‐Whitney U 452.500 450.000
Wilcoxon W 1677.500 1675.000
Test Sta ti s ti c 452.500 450.000
Standard Error 57.786 57.792
Standard Test Stat 2.319 2.275
Asympto ti c Sig. (2 ‐sided test) 0.020 0.023
Table 4: Test of normali ti es: Kolmogorov–Smirnov
Table 5: Test of normali ti es: Shapiro–Wilk
Table 6: Mann–Whitney test sta ti s ti cs t df
Sig. (2 ‐
tailed)
St. Error 
Differences
Equal Variances 
assumed
‐1.731 60 0.089 0.19277
Equal Variances 
not assumed
‐1.519 16.298 0.148 0.21974

Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 75
demonstrated higher engagement levels than em ‐
ployees that were not. Our results also were signifi ‐
cant (0.037 < 0.05, and a T ‐value of −2.268), which 
validates our third research sub ‐hypothesis, H1 ‐3. 
Employees demonstrates higher sa ti sfac ti on levels 
in a gamified work environment. Furthermore, as ex ‐
plained by Pallant (2016) we applied the eta ‐squared 
rule to measure how significantly game elements in ‐
fluenced employees’ engagement and sa ti sfac ti on. 
In the following equa ti ons, N1 is the number of re ‐
spondents of Group 1, and N2 is the number of re ‐
spondents of Group 2. 
 
 
 
 
 
 
Engagement analysis indicates that gamifica ‐
ti on exposure had moderate to strong e ffects on 
employees’ engagement levels. Results demon ‐
strate the e fficiency of gamifica ti on in changing em ‐
ployees’ behavior. We applied the same formula to 
measure employees’ sa ti sfac ti on levels. 
 
 
 
 
The analysis of sa ti sfac ti on levels also indicates 
that gamifica ti on had moderate to strong e ffects on 
employees’ organiza ti onal sa ti sfac ti on levels. We 
can conclude that gamifica ti on changes employees’ 
behavior by improving their engagement levels and 
sa ti sfac ti on levels.  
Because of the importance of ini ti al or accumu ‐
lated percep ti ons, we inves ti gated employees’ per ‐
cep ti ons of the gamifica ti on concept and if they 
realised its poten ti al nega ti ve a tt ributes. Results in ‐
dicate that only 4.3% of the respondents stated that 
gamifica ti onis a source of nuisance, and 8.5% indi ‐
cated no nega ti ve or posi ti ve a tt ributes. The solid 
majority of our respondents—precisely 87.2%—in ‐
dicated posi ti ve e ffects a ft er being exposed to gam ‐
ifica ti on. Posi ti ve responses included be tt er psycho ‐
logical well ‐being, improved interdepartmental 
communica ti on, knowledge sharing, and higher mo ‐
ti va ti on levels. 
 
4 DISCUSSION AND CONCLUSION 
4.1 Theore ti cal Contribu ti ons 
Our research methodology was based on a hy ‐
brid ‐type approach that u ti lized three scales to mea ‐
sure and compare employee’s engagement, 
performance, and sa ti sfac ti on. Combining the 
Utrecht Work Engagement Scale, Individual Work 
Performance Ques ti onnaire and Minnesota Sa ti sfac ‐
ti on Ques ti onnaire enabled us to conduct a holis ti c 
analysis of gamifica ti on behavioral influence. Con ‐
sistent with the previous literature (Huang et al., 
2018; Krath, Schürmann, & von Korflesch, 2021) 
self ‐determina ti on theory and flow theory are two 
of the most important theories in the field of gami ‐
fica ti on, and our proposed measurement tool, EPS, 
incorporates them both. Gamifica ti on influences be ‐
havior change rather than manda ti ng it, and every 
game element can be categorized according to its 
own influence and phycological e ffect. Therefore, 
game element selec ti on is crucial in promo ti ng the 
desired behavioral change.  
 
4.2 Prac ti cal Implica ti ons 
Our research elaborated a new approach in in ‐
ves ti ga ti ng the influence of gamifica ti on on employ ‐
ees, and is a cost ‐e ffec ti ve and fast empirical 
approach. Furthermore, the results of this study can 
help prac titi oners scien ti fically quan ti fy behavioral 
changes in an organiza ti onal environment. Research 
results proved the usefulness of gamifica ti on in in ‐
fluencing organiza ti onal behavior. Our results also 
indicate gamifica ti on assimila ti on among employees 
between 18 and 35. Gamifica ti on exposure moder ‐
ately to strongly increased employees’ organiza ‐
ti onal engagement and sa ti sfac ti on. Moreover, the 
research findings indicate that in this sample, gam ‐
ifica ti on had no significant influence on employees’ 
organiza ti onal performance, which is a notable ex ‐
cep ti on. 

Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 76
Ibrahim Hamza, Sarolta Tóvölgyi: Empirical Analysis of the Influence of Gamifica ti on on Employees’ Behavior
4.3 Limita ti ons 
Because gamifica ti on is a rela ti vely new con ‐
cept, measuring gamifica ti on influence among blue ‐ 
collar employees proved di fficult, which is a notable 
limita ti on. Therefore, the implementa ti on processes 
should include a comprehensive gamifica ti on de ‐
scrip ti on. We planned to assess the impact of gam ‐
ifica ti on on employees’ turnover rates, but 
acquiring such data contradicted corporate regula ‐
ti ons. Our combined measurement tool is accurate; 
nevertheless, owing to its hybrid nature, it was 
paired with a lengthy ques ti onnaire, making it more 
di fficult to obtain employees’ responses.  
 
4.4 Future Research Direc ti ons 
Our research was conducted among employees 
residing in Hungary, from di fferent cultural back ‐
grounds. Selec ti ng a more homogeneous sample 
would enable researchers to detect a media ti ng role 
of culture in gamifica ti on and should provide cultural 
percep ti on of integrated game elements by applying 
the same hybrid measurement tool. Researchers’ in ‐
terpreta ti ons of what cons ti tutes “gamifica ti on” 
varies depending on the game elements they select 
to include. Therefore, we recommend u ti lizing a 
larger sample of employees to evaluate the e ffects 
of game elements individually and collec ti vely. The 
aforemen ti oned method would provide empirical 
evidence of the appropriate game element combi ‐
na ti ons based on organiza ti onal objec ti ves. Employ ‐
ees did not provide consent before par ti cipa ti ng in 
a gamified process, which is a noteworthy observa ‐
ti on. Gamifica ti on incorpora ti on in on ‐site job tasks 
adds a fun layer to organiza ti onal ac ti vi ti es. Never ‐
theless, employees’ awareness of the process and its 
goals should be addressed.
EXTENDED SUMMARY/IZVLE ČEK 
Igrifikacija je razmeroma nov koncept, ki se nanaša na uporabo elementov igre v neigrnih pro ‐
duk ti vnih dejavnos ti h. Prav tako se lahko uporablja kot orodje za vedenjsko modeliranje, ki vpliva na 
vedenjske spremembe v organizacijskem kontekstu. Izziv, ki ostaja povezan s tem konceptom, je po ‐
manjkanje empiri čnih meritev lastnos ti igrifikacije. Prispevek meri klju čne vedenjske spremembe, 
na katere vpliva igrifikacija med zaposlenimi, in ocenjuje njihovo teore tič no podlago. Združili smo že 
prej potrjena merska orodja za empiri čno ugotavljanje sprememb vedenja, predvsem zavzetos ti , us ‐
pešnos ti in zadovoljstva. Skupno merilno orodje vklju čuje Utrechtsko lestvico delovne zavzetos ti 
(angl. Utrecht Work Engagement Scale; UWES), vprašalnik o individualni delovni uspešnos ti (angl. 
Individual Work Performance Ques ti onnaire; IWPQ) in Minnesota vprašalnik o zadovoljstvu (angl. 
Minnesota Sa ti sfac ti on Ques ti onnaire; MSQ). Rezulta ti raziskave so pokazali, da obstaja velika ve ‐
denjska razlika med zaposlenimi, na katere je vplivala igrifikacija, in zaposlenimi, na katere ni. Za ‐
posleni, ki so bili izpostavljeni igrifikaciji, so pokazali višjo stopnjo zavzetos ti in zadovoljstva ter tako 
potrdili mo č igrifikacije. Glede ravni uspešnos ti pa rezulta ti niso pokazali sta ti s tič no zna čilnih razlik 
med obema skupinama. Ta raziskovalni članek bo v praksi vodil k boljšemu ocenjevanju lastnos ti igri ‐
fikacije in k izboljšanju uporabe koncepta v organizacijah. 

Dynamic Rela ti onships Management Journal, Vol. 11, No. 2, November 2022 77
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