sustainability
Article
Conceptual Comparison of Internal Audit and Internal Control
in the Marketing Environment
Václav Kupec 1
'* , Přemysl Písař1
, Michal Lukáč 2
and Gabriela Pajtinková Bartáková 3
1
Faculty of Economic Studies, University of Finance and Administration, 101 00 Prague, Czech Republic;
premyslpisar@mail.vsfs.cz
2
Faculty of Social Sciences, University of Ss. Cyril and Methodius in Trnava, 917 01 Trnava, Slovakia;
michal.lukac@ucm.sk
3
Faculty of Management, Comenius University in Bratislava, 820 05 Bratislava, Slovakia;
gabriela.bartakova@fm.uniba.sk
Correspondence: vkupec@mail.vsfs.cz; Tel.: +420-210-0 :-800
check for
updates
Citation: Kupec, V.; Písař, P.; Lukáč,
M ; Pajtinková Bartáková, G.
Conceptual Comparison of Internal
Audit and Internal Control i n the
Marketing Environment.
Sustainability 2021,13, 6691.
https: / / d o i . o r g / 10.3390/sul3126691
Academic Editors: Ionel Bostan and
Marc A . Rosen
Received: 26 A p r i l 2021
Accepted: 9 June 2021
Published: 12 June 2021
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4.0/).
Abstract: There is a conceptual problem in the adequate application of internal audit and internal
control in the real business of the marketing environment. Although both of these managerial tools
are theoretically defined, they are practically interchangeable in business. This limits their application.
It is therefore necessary to focus on both concepts and make the theory and practice more precise
or remove any overlaps. The aim of this paper is therefore a theoretical and practical comparison
of internal audit and internal control concepts in the marketing environment. To fulfil this purpose
and verify the hypotheses, this paper uses computer assisted self interviewing. The research was
conducted in Q l 2021 with a sample of 3052 small and medium enterprises from the international
environment of the EU 27. The research conclusions show a strong correlation of the theoretical
perception of the terms of internal audit and internal control. At the same time, they show a weak
correlation with the audit and control tools used in practice. They also define audit as planned
independent assurance (soft consultation) and control as operational managerial assurance (hard
comparison). This defines and clarifies scientific theories for managerial practice, thus enhancing
and increasing the efficiency of internal audits and internal control in the business environment.
Keywords: CASI; correlation; internal audit; internal control; management; marketing
JEL Classification: M420; M12; M14; M15; 310
1. Introduction
A n integral part of sustainable economies is the marketing environment [1,2]. The
processes of supply and demand intermingle with the support of modern marketing
approaches [3]. The marketing environment is divided by Kalieva et al. [4] into the
Microenvironment and the Macroenvironment. Al-Waely [5] includes customers and
organizations in the Microenvironment, while the Macroenvironment mainly includes
the economic, technological, legal, and cultural environment. Mose and Syaifuddin [6]
subsequently state on this problem that the monitoring of the marketing environment is
strategic and necessary.
The concepts of internal auditing and internal control can be applied to monitoring,
according to the definition of a professional organization. The Institute of Internal Auditors
(IIA) [7] defines the audit concept as follows: "Internal auditing is an independent, objective
assurance and consulting activity designed to add value and improve an organization's
operations". The Committee of Sponsoring Organizations of the Treadway Commission
(COSO) [8] (p. 3) defines the control concept as follows: "Internal control is a process
effected by an entity's board of directors, management, and other personnel, designed to
Sustainability 2021,13, 6691. https://doi.org/10.3390/sul3126691 https://www.mdpi.com/journal/sustainability
Sustainability 2021,13, 6691 2 of 18
provide reasonable assurance regarding the achievement of objectives relating to operations,
reporting, and compliance".
The internal audit concept (hereinafter "audit") is primarily defined by IIA [7] and
by Furtuna and Ciucioi [9], while the internal control concept (hereinafter "control") is
primarily defined by COSO [8] and by Lobo et al. [10]. Audit and control are two theoretical
concepts (see H I ) [11]. In practice, however, both concepts may be combined into one
(see H2), defined inaccurately on a conceptual level, or merged. This occurs due to local
translation where the term "control" is explicitly translated using the term "audit" [12].
Ultimately, there may be overlap in explaining both concepts, see Vachal et al. [13], which
defines audit as control, hence the chaos.
The chaos in theory then moves into practice as well. If the audit and control concepts
are combined into one at the theoretical level [13], they can be combined at the practical
level as well (see H3). Although both concepts can gain knowledge from each other, they
should always be applied correctly. Thus, audit concepts should be applied for audit
purposes, and control concepts for control purposes; for management [14], the application
of the right concept to processes is crucial [15,16], particularly in the expansive and risky
marketing environment [17] (see below). Management [18,19] applies control concepts [20]
rather than audit concepts [21] (see H4).
Depending on the presentation of the issue, research questions or problems arise
here: Ql/Prescriptive—What audit and control concepts are used? Q2/P2r e ia t i o n a i—What
is the conceptual relationship between audit and control? The aim of this paper ( A l )
is therefore a theoretical and practical comparison of internal audit and internal control
concepts in the marketing environment. The achievement of this aim will shed light on the
following hypotheses:
Hypothesis 1 (HI). The theoretical concepts of audit and control differ (see [7,8]).
Hypothesis 2 (H2). There is a significant correlation between the concepts of audit and control.
Hypothesis 3 (H3). The practical application ofaudit and control uses these concepts interchangeably.
Hypothesis 4 (H4). Implementation of the control concept takes place more often than implementation
of the audit concept.
2. Literature Review
This chapter presents the author's selection of initial literature on the issue examined
and the current state of the issues. The text focuses on the concepts of audit and
control [22,23], especially in the European context of the current marketing environment
of SMEs. The marketing environment is full of risks (Risk of enterprise products lowering
demand; Risk of enterprise imperfect pricing policy; Risk of enterprise low-quality
products; Risk of enterprise low degree products sales promotion) [24] (p. 231). Risks
threaten this environment [25,26] and make it difficult to achieve business goals [27,28].
To mitigate these risks [29], it is necessary to use the right audit concepts and control
concepts (the concepts stand for theories, principles, and models). The precise definition of
audit and control, including historical and etymological definition, is therefore the basis of
this research.
Audit [30] is etymologically, procedurally, and conceptually based on the Latin word
"audire" which means "to listen" or "to hear" [31,32]. The term is derived primarily from
the historical theories of the Roman Empire: theories about soldiers, where officers would
listen to the complaints of the soldiers [33]; theories about officials, where one listened
to a reading of the other's accounting [34,35]; theories about the administrators whose
reports on management were followed [36]; and theories about auditors, who listened to
accountants when investigating live practices [37,38]. The audit concept is primarily based
on soft communication methods.
Sustainability 2021,13, 6691 3 of 18
Control [39] differs from audit etymologically, and therefore also procedurally and
conceptually. It is based on the Latin "contra" and "rotulus" which mean "opposite" and "a
script" [40]. The explanation of this concept is also derived from historical theories: theories
about employees who play a role and follow a script [40]; theories about accountants who
reconcile records against identical accounting records [41]; or theories about actors, where
one follows a script and the other monitors role compliance [42,43]. The control concept is
therefore primarily based on hard comparison methods.
Both audit and control concepts also need to be put into the current marketing environment.
Anchoring the concept of audit in the marketing context today is presented
by Kitchenko and Kuchina [44], as a study of the activities of an enterprise in order to
develop a proposal for drawing up an action plan aimed at increasing the efficiency of the
enterprise's marketing. In contrast, control in the marketing context is today defined as
monitoring, directing, and evaluating to ensure that the marketing plan is implemented as
envisioned and, when it is not, corrective action is taken [45]. Based on this text, the H I
hypothesis will be verified after the whole research is fully completed.
3. Materials and Methods
The materials studied are the audit concepts by Furtuna and Ciucioi [9] and the control
concepts by Lobo et al. [10]. As part of answering research questions and elaborating the
objective, the selected hypotheses (particularly HI) are methodically processed using
literary research and content analysis. Literature review [46] is defined in this research
as a summary of knowledge about the subject of research based on the study of the
literature. Content analysis [47] focuses on the occurrence of certain concepts in the text
and subsequently also on the relationships between these occurrences (the choice of the
words "audit" and "control" in peer-reviewed texts younger than the year 2000). The
recorded results are summarized below.
The terms audit and control are specifically situated in the European marketing environment
of SMEs. SMEs are the backbone of the marketing environment in today's
world and especially in the economy and Industry 4.0, as mentioned by Ferreira et al. [48],
Kosacka-Olejnik and Pitakaso [49], and Garbellano and Da Veiga [50]. This economic environment
has been purposefully narrowed down to the marketing environment according to
Godwin [3]. The marketing environment is dynamic, volatile, and affected by a number of
ongoing changes [51,52]. The research presented is therefore materially focused on defined
enterprises (SMEs) in a defined environment (marketing environment).
Subsequently, the hypotheses are verified using the CASI method (Computer Assisted
Self Interviewing) by Raffaelli et al. [53]. The CASI Questionnaire (link) was delivered
via e-mail. The e-mail was addressed to TOP management (directors, owners, head
of departments). The European Amadeus database by Bureau van Dijk was used to
select the data [54]. From this database, the selection was made using filters according
to the paper topic of respondents, i.e., n0 = 21,372 (the core set) of SMEs as defined
by Commission Recommendation 2003/361/EC from the marketing environment doing
business in the E U 27 (i.e., without the UK). A CASI questionnaire (Google form) was sent
to the aforementioned set «o with prepared questions from the areas of audit and control
(see Table 1). After that, in the first quarter of 2021, a total of n = 3052 (control sample
according to the specifications of Tables 2 and 3) of complete answers were obtained, the
data of which were statistically analysed. Return on Equity (ROE) was used to establish
what impact the use of auditing and control had on a company's performance.
Sustainability 2021,13, 6691 4 of 18
Table 1. CASI questionnaire.
No Concept Hypothesis Table Question
Qi N / A 2 Turnover size at n>.
Q2
General
N / A 3 Number of employees at n>.
Q3
General
HI 4
Do you perceive a difference between audit and
control?
Q4 H4 9 Are you practicing audit?
Q5
Audit
HI 5 What do you imagine under the "audit" concept?
Q6
Audit
H3 8 What audit tools do you use?
Q7 H4 10 How much did you invest in the audit in 2019?
Q8 H4 9 Are you practicing control?
Q9
Control
HI 6 What do you imagine under the "control" concept?
Q10
Control
H3 8 What control tools do you use?
Q l l H4 10 How much did you invest in the control in 2019?
Source: Authors proceeding.
Table 2. Ql—Turnover (in EUR x 1000) size at n?
Valid
Frequency Percent Cumulative Percent
0-5000 126 4.1 4.1
5-10,000 405 13.3 17.4
10-25,000 1230 40.3 57.7
25-50,000 534 17.5 75.2
50-100,000 296 9.7 84.9
100-250,000 379 12.4 97.3
250-500,000 70 2.3 99.6
500-1,000,000 12 0.4 100.0
Total 3052 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
Table 3. Q2—Number of employees at n?
Frequency Percent Cumulative Percent
0-5 846 27.7 27.7
6-15 808 26.5 54.2
16-30 667 21.9 76.0
31-50 512 16.8 92.8
51-100 97 3.2 96.0
101-250 122 4.0 100.0
Total 3052 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
The reliability and consistency of the analysed data are examined according to Cronbach's
alpha [55,56]. Cronbach's alpha takes values in the range 0-1, where values above
0.7 show high reliability and data consistency [57,58]. After that, the values of linear
dependence and strength of the selected variables are tested according to Pearson's correlation
[59,60]. The minimum values of Pearson's correlation coefficient were determined
for data analysis as 0.4 and higher by Evans [61]. For the research overview, the models
Sustainability 2021,13, 6691 5 of 18
for audit and control concepts were computed using the stepwise regression procedure.
In some cases, frequency analysis by Darlington and Hayes [62] is used for comparison
and interpretation.
The final step of data analysis was the stepwise regression method, which was used to
construct the managerial H R competencies model, and the analysis of other data methods.
A l l output results and models were tested for significance. The value for passing this test
was set at a level of 5%. The detail and information according to Darlington and Hayes [62]
and the IBM SPSS ver. 25 user manual.
4. Results
The initial step of the study was to perform a test of the reliability and consistency
of the data examined using the Cronbach alpha calculation method. Here, the minimum
test value was set at 0.7. The examined sample of 11 variables (see Table 1) + ROE passed
this test and reached a Cronbach's alpha value of 0.816. This result demonstrates high
reliability of the investigated data and supports the conclusions of the data analysis for
the evaluation of hypotheses H I to H4. The following results are presented in the text
according to the verification of individual hypotheses.
4.1. HI—Theoretical Concepts of Audit and Control Differ
The first result is to verify the differences between the two concepts as used by
management. From the above theoretical perspective and literature analyses, it is clear that
the concepts of audit and control are different. It can be deducted from the analyses that, in
addition to minor differences, the major differences are mainly in timing (audit is planned;
control is operational), responsibility (audit and the auditor; control and the manager). A
practical view of the differences between the concepts is captured in the frequency analysis
of the examined variables in Tables 3-5, which verifies theoretically and practically that the
basic concepts of audit and control are different. It is interesting to note that according to
Table 4, 47.2% of respondents claimed they perceived audit and control as two different
concepts, 37.2% of respondents said that these two concepts were partly different, and only
16.6% understood audit and control as a single approach. This confirms H I .
Table 4. HI—Do you perceive a difference between audit and control?
Frequency Percent Cumulative Percent
no 476 15.6 15.6
partly 1134 37.2 52.8
yes 1442 47.2 100.0
Total 3052 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
Table 5. HI—What do you imagine under the "audit" concept?
Frequency Percent Cumulative Percent
Nothing 212 6.9 6.9
Check 704 23.1 30.0
bureaucracy 884 29.0 59.0
Help 726 23.8 82.8
Consultation 430 14.1 96.9
Other 96 3.1 100.0
Total 3052 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
Sustainability 2021,13, 6691 6 of 18
Tables 5 and 6 show that companies that have started using audit and control mostly
just use the control concept and regard the audit concept as a more advanced discipline.
When analysing the data in Tables 5 and 6, we can conclude that the investigated companies
understand the concepts of audit and control as more or less positive actions that enhance
a company's performance and efficiency. Neither concept is perceived as repressive by
the majority of respondents. What is definitely positive is the frequency of the notions of
"help, consultation" which in the case of the audit concept was 37.9%, while in the case of
the control concept the percentage was 35.5%. One interesting finding is the perception
of audit (17.7%) and control (29%) as bureaucratic. A tighter focus on this finding shows
the frequency of responses by SME size in Table 3 and found that the results follow the
values in Tables 5 and 6 within + / — 6%, regardless of the size of the SME by number of
employees. The authors see the results as a question of the company culture, where some
employees follow their own goals against the enterprise ones.
Table 6. HI—What do you imagine under the "control" concept?
Frequency Percent Cumulative Percent
Nothing 88 2.9 2.9
Check 818 26.8 65.1
bureaucracy 539 17.7 82.8
Help 664 21.8 24.6
Consultation 418 13.7 38.3
Other 525 17.2 100.0
Total 3052 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
4.2. H2—There Is a Significant Correlation between the Concepts of Audit and Control
Another result is a theoretical approach to audit and control in an international context.
The word "audit" is translated from English as "audit" [34]. In contrast, the translation of
the word "control" is not so unambiguous. It can be rendered as "check", "inspection",
"supervision", etc. [12], which may lead to inaccuracies. Some authors use "audit" and
"control" as synonyms [63,64]. This can theoretically confirm the correlation of both
concepts. The mutual correlation of both concepts (H2) is also confirmed by calculating
Pearson's correlation coefficient and the value of linear dependence between the examined
variables (see Table 7).
Table 7 offers some interesting findings. One of them is the negative correlation
between Q l l (How much did you invest in control in 2019?) and Q4 (Do you practice
auditing?)—0.013, and also Q6 (What audit tools do you use?)—0.010. Although the
value of these negative correlations is not very significant, the very existence of negative
correlations suggests that the higher usage of the audit concept reduces the frequency of
implementation of the control concept.
The correlation detected between Q2 (Number of employees at n?) and Q5 (What do
you imagine under the concept of "auditing"?) 0.465 and Q9 (What do you imagine under
the concept of "control"?) 0.492 is interesting. These values can be interpreted as indicating
that the use of the concepts of audit and control increases with the number of employees at
the company.
Sustainability 2021,13, 6691 7 of 18
Table 7. H2—Variables Pearson Correlations.
Ql Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Qll
Pearson c. l 0.697 ** 0.566 ** 0.372 ** 0.657 ** 0.237 ** 0.122 ** 0.591 ** 0.673 ** 0.120 ** 0.039 *
Q l Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.032
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.697 ** 1 0.457 ** 0.233 ** 0.465 ** 0.162 ** 0.113 ** 0.417 ** 0.492 ** 0.113 ** 0.043 *
Q2 Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.018
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.566 ** 0.457 ** 1 0.354 ** 0.514 ** 0.228 ** 0.173 ** 0.605 ** 0.591 ** 0.107 ** 0.954
Q3 Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.372 ** 0.233 ** 0.354 ** 1 0.376 ** 0.130 ** 0.106 ** 0.504 ** 0.499 ** 0.100 ** -0.013
Q4 Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.473
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.657 ** 0.465 ** 0.514 ** 0.376 ** 1 0.241 ** 0.172 ** 0.625 ** 0.667 ** 0.156 ** 0.027
Q5 Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.134
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.237 ** 0.162 ** 0.228 ** 0.130 ** 0.241 ** 1 0.010 0.217 ** 0.364 ** 0.030 -0.010
Q6 Sig. 0.000 0.000 0.000 0.000 0.000 0.563 0.000 0.000 0.093 0.569
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.122 ** 0.113 ** 0.173 ** 0.106 ** 0.172 ** 0.010 1 0.202 ** 0.205 ** 0.031* 0.048
Q7 Sig. 0.000 0.000 0.000 0.000 0.000 0.563 0.000 0.000 0.085 0.009
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.591 ** 0.417 ** 0.605 ** 0.504 ** 0.625 ** 0.217 ** 0.202 ** 1 0.738 ** 0.140 ** 0.007
Q8 Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.688
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Sustainability 2021,13, 6691 8 of 18
Table 7. Cont.
Qi Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Qll
Pearson c. 0.673 ** 0.492 ** 0.591 ** 0.499 ** 0.667 ** 0.364 ** 0.205 ** 0.738 ** 1 0.155 ** 0.017
Q9 Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.350
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.120 ** 0.113 ** 0.107 ** 0.100 ** 0.156 ** 0.030 0.031 0.140 ** 0.155 ** 1 0.360 **
Q10 Sig. 0.000 0.000 0.000 0.000 0.000 0.093 0.085 0.000 0.000 0.000
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
Pearson c. 0.039 * 0.043 * 0.001 -0.013 0.027 -0.010 0.048 ** 0.007 0.017 0.360 ** 1
Q l l Sig. 0.032 0.018 0.954 0.473 0.134 0.569 0.009 0.688 0.350 0.000
N 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052 3052
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Source: Research data, authors proceeding, SPSS ver. 25.
Sustainability 2021,13, 6691 9 of 18
Additionally, the higher value of correlation between Q l (Turnover size at n?) and
Q3 (Do you see a difference between audit and control?) 0.566, Q5 (What do you imagine
under the concept of "auditing"?) 0.657, Q8 (Do you practice control?) 0.591, and Q9 (What
do you imagine under the concept of "control"?) 0.673 should be pointed out. These values
suggest a significant rate of linear dependence (the correlation coefficient) between the
studied variables. A possible interpretation of this finding is that the higher a company's
turnover, the more important the use of the concepts of audit and control. These findings
further support the conclusions made for models (1) and (2).
Correlation analysis of the relationship between Q4 (Do you practice auditing?) and Q7
(How much did you invest in auditing in 2019?) 0.106 provides further interesting findings.
This low level of correlation suggests that the use of the audit concept in companies is not
significantly linked to how much money is invested in auditing. It can thus be concluded
that auditing is a low-cost tool through which companies can increase their competitiveness
and efficiency. We reached a similar finding when interpreting the level of correlation
between Q l l (How much did you invest in control in 2019?) and Q8 (Do you practice
control?) 0.007. This level of correlation means that there is almost no relationship between
the costs and use of the control concept. Thus, as in the case of the audit concept, it can
be concluded that the control concept is a low-cost tool for companies to increase their
competitiveness and efficiency. It can be expected that more extensive use of the concepts
of audit and control regardless of financial resources will lead to their more frequent use in
the operation of companies. This would in turn mean that both concepts will transition
over time from statistical concepts to dynamic ones.
Table 7 provides the main results of the study and the existing correlations between the
concepts of audit and control (H2). To verify this hypothesis (H2), the following Pearson's
correlation values were intentionally selected from these results: the result of Q5 and Q9
(0.667) above all indicates an important correlation between the theoretical perception of
the concepts of audit and control. Secondly, however, it is necessary to analyse the result of
Q6 and Q10 (0.030), which shows a very weak correlation between the audit and control
tools used in practice. These facts can be interpreted as meaning that although respondents
perceive audit and control similarly (theory), they use different tools for both concepts
(practice). This confirms H2.
4.3. H3—The Practical Application of Audit and Control Uses These Concepts Interchangeably
As can be seen from Table 7, the results from Q6 and Q10 (0.030) show a very weak
correlation between the audit and control methods used (here it is worth repeating that
the study examined SMEs in the marketing environment). It is clear that in the case of
audit and control tools we distinguish between their applications. The table and frequency
analysis below only confirm this result. Audit concepts focus mainly on the application of
methods related to questioning and observation (Table 8, Audit section). Control concepts
focus mainly on the application of methods related to analytics and statistics (Table 8,
Control section). These results align with the results of the literature review, that audit is
based on soft communication methods and control on hard comparative methods. This
refutes H3.
4.4. H4—Implementation of the Control Concept Takes Place More Often Than Implementation of
the Audit Concept
The latest results concern the frequency with which both concepts are used. This fact
cannot be verified theoretically. Therefore, it is necessary to focus on the practical results of
the survey. It is quite clear that the frequency of application of the control concept (Table 9,
Control section) is higher than the frequency of application of the audit concept (Table 9,
Audit section). Furthermore, the correlation of 0.504 is significant at 1% (Table 7), which
indicates an important level of linear dependence (correlation). This confirms that the
control concept is applied in practice more often than the audit concept, thereby validating
H4. This issue is also illustrated by the volume of estimated investments (Table 10) in
Sustainability 2021,13, 6691 10 of 18
both concepts (however it is not possible to quantify investments exactly given the scale of
the inquiries).
Table 8. H3—What audit tools (Q6)/ control tools (Q10) do you use?
Frequency Percent Cumulative Percent
Valid
Audit Control Audit Control Audit Control
Nothing 277 629 9.1 20.6 9.1 20.6
Analytic 967 1171 31.7 38.4 40.8 59.0
Statistic 799 949 26.2 31.1 66.9 90.1
Requesting 530 280 17.4 9.2 84.3 99.2
Observing 307 12 10.1 0.4 94.4 99.6
Other 172 11 5.6 0.4 100.0 100.0
Total 3052 3052 100.0 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
Table 9. H4—Do you use audit (Q4)/control (Q8)?
Frequency Percent Cumulative Percent
Valid
Audit Control Audit Control Audit Control
No 1036 426 33.9 14.0 33.9 14.0
partly 1219 991 39.9 32.5 73.9 46.4
full 797 1635 26.1 53.6 100.0 100.0
Total 3052 3052 100.0 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
Table 10. H4—How much did you invest in audit (Q7)/control (Qll) in 2019 (EUR)?
Frequency Percent Cumulative Percent
Valid
Audit Control Audit Control Audit Control
to 500 908 1447 29.8 47.4 29.8 47.4
501-1000 897 1196 29.4 39.2 59.1 86.6
1001 to
5000
835 339 27.4 11.1 86.5 97.7
5001 to
10,000
315 21 10.3 0.7 96.8 98.4
up to
10,001
97 49 3.2 1.6 100.0 100.0
Total 3052 3052 100.0 100.0
Source: Research data, authors proceeding, SPSS ver. 25.
As a final analysis step for the audit and control comparison, the models were compounded
using stepwise regression (see Tables 11 and 12).
Sustainability 2021,13, 6691 11 of 18
Table 11. The control modela
.
Model
Unstandardized
Coefficients
Standardized
Coefficients t Sig.
B Std. Error Beta
1
(Constant) 1.894 0.037 51.624 0.000
1
Q9 0.330 0.011 0.464 28.915 0.000
(Constant) 1.771 0.038 46.713 0.000
2 Q9 0.202 0.017 0.284 12.140 0.000
Q8 0.351 0.034 0.244 10.437 0.000
(Constant) 1.816 0.039 46.473 0.000
Q9 0.223 0.017 0.313 12.946 0.000
3 Q8 0.400 0.035 0.278 11.357 0.000
Q3 -0.132 0.029 -0.093 -4.523 0.000
(Constant) 1.885 0.041 45.496 0.000
Q9 0.244 0.018 0.342 13.788 0.000
4 Q8 0.404 0.035 0.281 11.490 0.000
Q3 -0.100 0.030 -0.070 -3.350 0.001
Q2 -0.069 0.014 -0.090 -4.871 0.000
a
Dependent Variable: ROE. Source: Research data, authors proceeding, SPSS ver. 25.
Table 12. The audit modela
.
Model
Unstandardized
Coefficients
Standardized
Coefficients t Sig.
B Std. Error Beta
1
(Constant) 2.158 0.036 59.673 0.000
1
Q5 0.304 0.014 0.363 21.532 0.000
(Constant) 2.054 0.037 55.924 0.000
2 Q5 0.242 0.015 0.290 16.210 0.000
Q4 0.263 0.024 0.196 10.964 0.000
(Constant) 2.005 0.040 50.134 0.000
Q5 0.220 0.017 0.263 13.234 0.000
3 Q4 0.248 0.024 0.185 10.135 0.000
Q3 0.086 0.028 0.060 3.053 0.002
(Constant) 2.038 0.043 47.492 0.000
Q5 0.231 0.017 0.276 13.287 0.000
4 Q4 0.249 0.024 0.185 10.168 0.000
Q3 0.103 0.029 0.072 3.527 0.000
Q2 -0.032 0.015 -0.041 -2.122 0.034
a
Dependent Variable: ROE. Source: Research data, authors proceeding, SPSS ver. 25.
Based on Table 11, the Control model and its influence for enterprise performance for
the dependent variable ROE is:
Sustainability 2021,13, 6691 12 of 18
Model 1
ROE =1.885 * Constant + 0.244 * Q9 (What do you imagine under the concept of
"control"?) + 0.404 * Q8 (Are you practicing control?) + —0.100 * Q3 (Do you perceive a
difference between audit and control?) + —0.069 * Q2 (Number of employees)
This model shows the "weight" of all variables entered into the model and their
importance. The model is significant at 1%. Closer model 1 computing results see
Tables A l and A2.
Based on Table 12, the Audit model and its influence for enterprise performance for
the dependent variable ROE is:
Model 2
ROE = 2.038 * Constant + 0.231 * Q5 (What do you imagine under the concept of
"auditing"?) + 0.249 * Q4 (Do you practice auditing?) + 0.103 * Q3 (Do you see a difference
between auditing and control?) + * —0.032 * Q2 (Number of employees)
This model shows the "weight" of all variables entered into the model and their
importance. The model is significant at 5%. Closer model 1 computing results see
Tables A3 and A4.
The two models 1 and 2 defined show a higher value of constants 6 (2.038) and 5
(1.885). This constant represents unknown variables (not included i n the research)—i.e.,
factors that impact ROE trends. This finding was expected as a number of internal and
external factors other than audit and control impact a company's performance.
In the control model 1, the value of —0.100 of the variable Q3 (Do you see a difference
between auditing and control?) is worth noting. This negative value implies that in
the case of companies that mainly use the control concept, the attempt to distinguish
between the concepts of auditing and control leads to a negative (low) impact on increased
ROE. However, this impact is usually only temporary and is later replaced by a positive
impact on ROE according to model 2. In model 2, the value 0.103 of the variable Q3 (Do
you see a difference between auditing and control?) is positive and supports increased
ROE. In connection with the conclusions of model 1 and Tables 7 and 9, it is evident
that when they start using the concepts of audit and control, companies at first prefer
the control concept. This trend is then replaced with the use of both concepts (with a
temporary negative impact on ROE). Models 1 and 2 show that the joint use of the audit
and control concepts has a positive impact on the company's performance represented by
the dependent variable ROE.
The fact that the variable Q2 (Number of employees) has a negative (low) value in
both models 1 and 2 is yet another noteworthy finding. This fact can be interpreted as
implying that as the number of employees increases, the importance of the concepts of
audit and control as a factor supporting increased ROE slightly decreases. This should be
interpreted in connection with the law of diminishing returns.
5. Discussion
The results are an important probe for modern management [65,66]. Concepts, methods,
and approaches that have been used for a long time are evolving. It is therefore
necessary to pay attention to this development and make the theory and practice more
precise. Here, it can be stated that the conceptual intertwining of audit and control is
based on the historical connection of both concepts with accounting [34,41]. However,
new developments have transitioned auditing to planned independent assurance (soft
consultation) and control to operational management assurance (hard comparison). This
audit result is confirmed by Plant et al. [67] and Jokic et al. [68]. For the control, the result
is confirmed by Liangcheng et al. [69].
At the same time, the results clearly show that dynamic practice establishes theories
that become static and cannot remain current for practice [70,71]. The results show differences
in the theoretical concepts of audit and control (HI—confirmed hypothesis), their
correlation (H2—confirmed hypothesis), as well as the more frequent application of the
Sustainability 2021,13, 6691 13 of 18
control concept over the audit concept (H4—confirmed hypothesis). In practice, however,
different methods are applied and both research concepts are mixed (H3—refuted hypothesis).
This can be interpreted as meaning that the practical application of the concepts is
correct, regardless of the theories. The results here refine the theories presented by Furtuna
and Ciucioi [9] and Lobo et al. [10].
Here, we can discuss the limits of the research presented, which we can see in the
accuracy of the results. Precise separation of audit and control, as well as the determination
of a correlation, would allow independent measurement, not questioning. Independent
measurement, for example in the form of quantification of costs, capacities, or other quantities,
is exact. However, such a measurement is difficult to implement over the mediumand
long-term and also entails additional costs. Higher accuracy of the measurements performed
can be expected with the implementation of a higher form of digitization [72,73] and
Industry 4.0 [49,74]. Despite these limits, the results presented refine current knowledge
about audit and control.
Throughout the discussion, future perspectives of audit and control in the marketing
environment [75,76] can also be outlined. If it is possible to start from the above results,
changes can be expected particularly in the timing of both concepts. With the comprehensive
digitization of business processes [77,78], planned audits and operational controls will
move toward continuous implementation. This has already been confirmed by the theories
of Kaban [79] and Bieliaieva [80] about the audit or those of Christensen et al. [81] about
control. Audit and control will thus move from partially static concepts to fully dynamic
concepts [82,83]. Both concepts will enable management to provide online assurance about
ongoing processes as well as online elimination of process risks [84,85]. This, in turn, will
increase managerial efficiency, enterprise performance, and stability [86,87].
6. Conclusions
The objective of this paper (Al) is a theoretical and practical comparison of internal
audit and internal control concepts in the marketing environment. To fulfil this goal, CASI
polling is used on a sample of n = 3052 E U 27 SMEs. Cronbach's alpha and Pearson's
correlation methods are also used. From the results presented it is possible to read the
answers to the questions raised and the problems recorded ( Q l / P I , Q2/P2). The research
and data presented show an important correlation between the theoretical perception of
the concepts of internal audit and internal control (H2 and Table 7). A t the same time,
they show a very weak correlation between the audit and control tools used in practice
(H2 and Table 7). The final analysis step was to compile audit and control models for the
dependent variable ROE. These models point to the variables "weight" and importance for
enterprise performance and competitiveness. Both models should be used for audit and
control concepts with increased emphasis on ROE. Moreover, they define audit as planned
independent assurance (soft consultation) and control as operational managerial assurance
(hard comparison). These results complement industry and conceptual findings related to
internal audit and control [9,10]. This clarifies scientific research theories for managerial
practice. Both concepts need to be addressed on a continuous basis. It is possible to focus
mainly on the digitization of these concepts and their agile transformation from partially
dynamic/online concepts to fully dynamic/online concepts.
Author Contributions: Conceptualization, V.K.; methodology, P.P.; software, P.P.; validation, M.L.
and G.P.B., formal analysis, M.L. and G.P.B.; investigation, P.P.; resources, V.K.; data curation, P.P.;
writing—original draft preparation, V.K. and P.P.; writing—review and editing, M.L. and G.P.B.;
visualization, P.P.; supervision, V.K.; project administration, M L . ; funding acquisition, M.L. All
authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Sustainability 2021,13, 6691 14 of 18
Data Availability Statement: Data is contained within the article.
Acknowledgments: The result was created in solving the project "Digital Audit and Risk Management
in Industry 4.0" (7427/2020/02 IGA VSFS) using objective oriented support for specific
university research of the University of Finance and Administration.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
Table Al. Model 1 Summary.
Adjusted
R Square
Std. Error of the
Estimate
Change Statistics
Model R R Square
Adjusted
R Square
Std. Error of the
Estimate E
c2™ F C h
^ dfl df2
Sig.F
Change
1 0.464 a
0.215 0.215 0.918 0.215 836.064 1 3050 0.000
2 0.492 b
0.242 0.242 0.902 0.027 108.922 1 3049 0.000
3 0.497 c
0.247 0.247 0.899 0.005 20.455 1 3048 0.000
4 0.503 d
0.253 0.252 0.896 0.006 23.725 1 3047 0.000
a
Predictors: (Constant), Q9; b
Predictors: (Constant); Q8, Q 7 ; c
Predictors: (Constant), Q9, Q8, Q3, d
Predictors: (Constant), Q9, Q8, Q3, Q2.
Table A2. M o d e l 1 ANOVA a
.
Model Sum of Squares df Mean Square F Sig.
Regression 704.092 1 704.092 836.064 0.000 b
1 R e s i d u a l 2568.559 3050 0.842
Total 3272.651 3051
Regression 792.686 2 396.343 487.285 0.000c
2 R e s i d u a l 2479.965 3049 0.813
Total 3272.651 3051
Regression 809.217 3 269.739 333.747 0.000 d
3 R e s i d u a l 2463.434 3048 0.808
Total 3272.651 3051
Regression 828.250 4 207.063 258.108 0.000 e
4 R e s i d u a l 2444.401 3047 0.802
Total 3272.651 3051
a
Dependent Variable: ROE;b
Predictors: (Constant), Q 9 ; c
Predictors: (Constant), Q9, Q8; d
Predictors: (Constant), Q9, Q8, Q3;e
Predictors:
(Constant), Q9, Q8, Q3, Q2; Source: Research data, authors proceeding, SPSS ver. 25.
Table A3. Model 2 Summary.
Adjusted
R Square
Std. Error of the
Estimate
Change Statistics
Model R R Square
Adjusted
R Square
Std. Error of the
Estimate R Square
Change
F Change dfl df2
Sig.F
Change
1 0.363 a
0.132 0.132 0.965 0.132 463.606 1 3050 0.000
2 0.406 b
0.165 0.164 0.947 0.033 120.207 1 3049 0.000
3 0.409 c
0.167 0.167 0.945 0.003 9.323 1 3048 0.002
4 0.411 d
0.169 0.168 0.945 0.001 4.504 1 3047 0.034
a
Dependent Variable: R O E ;b
Predictors: (Constant), Q 9 ; c
Predictors: (Constant), Q9, Q8;d
Predictors: (Constant), Q9, Q8, Q3; Source:
Research data, authors proceeding, SPSS ver. 25.
Sustainability 2021,13, 6691 15 of 18
Table A4. Model 2 ANOVA a
.
Model Sum of Squares df Mean Square F Sig.
Regression 431.813 1 431.813 463.606 0.000b
1 Residual 2840.838 3050 0.931
Total 3272.651 3051
Regression 539.566 2 269.783 300.967 0.000c
2 Residual 2733.085 3049 0.896
Total 3272.651 3051
Regression 547.900 3 182.633 204.300 0.000 d
3 Residual 2724.751 3048 0.894
Total 3272.651 3051
Regression 551.921 4 137.980 154.527 0.000e
4 Residual 2720.730 3047 0.893
Total 3272.651 3051
a
Dependent Variable: ROE;b
Predictors: (Constant), Q 9 ; c
Predictors: (Constant), Q9, Q8; d
Predictors: (Constant), Q9, Q8, Q3;e
Predictors:
(Constant), Q9, Q8, Q3, Q2; Source: Research data, authors proceeding, SPSS ver. 25.
References
1. Agwu, M.E.; Onwuegbuzie, H.N. Effects of international marketing environments on entrepreneurship development. /. lnnov.
Entrep. 2018, 7,1-14. [CrossRef]
2. Réklaitis, K.; Pileliené, L. Principle Differences between B2B and B2C Marketing Communication Processes. Manag. Organ. Syst.
Res. 2019, 81, 73-86. [CrossRef]
3. Godwin, L.R. The ultimate definition of marketing. Mark. Rev. 2019,19,43-49. [CrossRef]
4. Kalieva, O.M.; Ivanchenko, O.V.; Mirgorodskaya, O.N. The role of marketing environment and target audiences in the process of
territory brand formation. Eur. Res. Stud. 2018, 21,63. Available online: https://search.proquest.com/docview/2162695317
?accountid=37662 (accessed on 19 October 2020).
5. Al-Waely, D. The Impact of Careful Application of Growth Management Policies and Sustainable Development on the Changing
Marketing Environment. Eur. f. Econ. Stud. 2019, 8, 3-18.
6. Mose, A.; Syaifuddin, M. Analysis of Macro and Mcro Environment on the Marketing Strategy Formulation and the Influence to
the Competitive Advantage (Case Study). Acad. Stratég. Manag. }. 2016,15, 35-41. Available online: https://search.proquest.
com/docview/1954424257?accountid=37662 (accessed on 19 October 2020).
7. IIA. Definition of Internal Auditing. 2020. Available online: https:/ /na.theiia.org/standards-guidance/mandatory-guidance/
Pages/Definition-of-Internal-Auditing.aspx (accessed on 19 October 2020).
8. COSO. Internal Control—Integrated Framework. 2013. Available online: https://www.coso.org/Documents/990025P-ExecutiveSummary-final-may20.pdf
(accessed on 19 October 2020).
9. Furtunä, C ; Ciucioi, A. Internal Audit in the Era of Continuous Transformation. Survey of Internal Auditors in Romania. Audit.
Financiar. 2019,17,452-472. [CrossRef]
10. Lobo, G.; Wang, C ; Yu, X.; Zhao, Y. Material Weakness in Internal Controls and Stock Price Crash Risk. /. Account. Audit. Financ.
2020, 35,106-138. [CrossRef]
11. Kuang, Y.F.; Lee, G.; Qin, B. Whistleblowing Allegations, Audit Fees, and Internal Control Deficiencies. Contemp. Account. Res.
2021, 38, 32-62. [CrossRef]
12. Kolektiv, A. Cesko-Anglický Slovník Pojišťovnictví; Grada Publishing: Praha, Czech Republic, 2007.
13. Váchal, M.; Vochozka, M. Podnikové Řízení; Grada Publishing: Praha, Czech Republic, 2013.
14. Kamps, T. Systematic Chasingfor Economic Success: An Innovation Management Approach; Anchor: Hamburg, Germany, 2013; p. 120
15. Lenz, R.; Hahn, U. A synthesis of empirical internal audit effectiveness literature pointing to new research opportunities. Manag.
Audit. }. 2015, 30, 5-33. [CrossRef]
16. Wachol, J. Modern Management Methods and Process Organization in a Global Enterprise. Sei. Pap. Sil Univ. Technol. Organ.
Manag. 2019, 236,643-651. [CrossRef]
17. Ferrell, O.C.; Speh, T.W. Marketing Strategy: Text and Cases; Cengage Learning: Boston, MA, USA, 2017.
18. Kor, Y; Mahoney, J.T. How dynamics, management, and governance of resource deployments influence firm level performance.
Stratég. Manag. }. 2005, 26, 489^96. [CrossRef]
19. Zulfikar, R.; Millatina, F.; Mukhtar, M.; Astuti, K.D.; Ismail, T; Meutia, M.; Fazri, E. Antecedents of Disclosure on Internal Control
and Earnings Management. /. Asian Financ. Econ. Bus. 2021, 8, 391-397.
Sustainability 2021,13, 6691 16 of 18
20. Eniola, A.A. Internal Control Procedures and Firm's Performance. Int. }. Sci. Technol. Res. 2020, 9, 6407-6415.
21. Nazarova, K.; Mysiuk, V.; Gordopolov, V.; Koval, V.; Danilevičiené, I. Preventional audit: Implementation of SOX control to
prevent fraud. Bus. Theory Pract. 2020,21,293-301. [CrossRef]
22. Bae, G.S.; Choi, S.U.K.; Lamoreaux, P.T.; Lee, J.E. Auditors' Fee Premiums and Low Quality Internal Controls. Contemp. Account.
Res. 2021, 38, 586-620. [CrossRef]
23. Sterin, M. The Influence of Audit Committee Expertise on Firms' Internal Controls: Evidence from Mergers and Acquisitions.
Account. Horiz. 2020, 34,193-211. [CrossRef]
24. Tkachenko, V.; Kwilinski, A.; Tkachenko, L; Puzyrova, P. Theoretical and Methodical Approaches to the Definition of Marketing
Risks Management Concept at Industrial Enterprises. Mark. Manag. lnnov. 2019, 2, 228-238. [CrossRef]
25. Kupec, V. Risk Audit of Marketing Communication. Eur. Res. Stud. }. 2018, XXI, 125-132. Available online: https://www.ersj.eu/
dmdocuments/2018_XXI_l_ll.pdf (accessed on 19 October 2020). [CrossRef]
26. Smidt, L.; Steenkamp, L.; Ahmi, A.; Van der Nest, D.P; Lubbe, D.S. Assessment of the Purpose of the Use of GAS: A Perspective
of Internal Audit Functions in Australia. Int. }. Inf. Syst. Sew. Sect. 2021,13,65-82. [CrossRef]
27. Mikušová, M. To be or not to be a business responsible for sustainable development? Survey from small Czech businesses. Econ.
Res. Ekon. Istražívanja 2019, 30,1318-1338. [CrossRef]
28. Dvorský, J.; Petrákova, Z.; Polách, J. Assessing the Market, Financial and Economic Risk Sources by Czech and Slovak SMEs. Int.
}. Entrep. Knowl. 2019, 7, 30-40. [CrossRef]
29. Chornous, G ; Ursulenko, G. Risk management in banks: New approaches. Ekonomika 2013, 92,120-132. [CrossRef]
30. Fitriyah, F.K.; Adrianto, Z.; Irawady, C. The Internal Audit Role in Fraud Detection and Prevention. Int. f. Innov. Creat. Chang.
2020,11,491-499.
31. Dumitru, M.I.; Burtescu, C. Offences and Penalties in the Internal Audit Activity. Sci. Bull Econ. Sci. 2015,14, 36-44. Available
online: https://EconPapers.repec.org/RePEc:pts:journl:y:2015:i:2:p:36-44 (accessed on 19 October 2020).
32. Božek, S.; Emerling, I. Protecting the Organization Against Risk and the Role of Financial Audit on the Example of the Internal
Audit. Oeconomia Copernic. 2016, 7, 485^199. [CrossRef]
33. Kaptein, M . Ethics Management: Auditing and Developing the Ethical Content of Organizations; Kluwer Academic Publishers:
Dordrecht, The Netherlands, 1998.
34. Sawyer, L.B. Interní Audit; ČILA: Praha, Czech Republic, 2000.
35. Guo, R; Lin, C ; Masli, A.; Wilkins, M.S. Auditor Responses to Shareholder Activism. Contemp. Account. Res. 2021, 38, 63-95.
[CrossRef]
36. Putnová, A.; Seknička, P. Etické Řízení ve Tirmě; Grada Publishing: Praha, Czech Republic, 2007.
37. Můllerová, L. Auditing pro Manažery aneb Proč a f ak se Ověřuje Účetní Závěrka; Wolters Kluwer: Praha, Czech Republic, 2013.
38. Basu, S.K. Auditing: Principles and Techniques; Pearson Education: New Delhi, India, 2007.
39. Kamil, O A . ; Ahmed, E A . Extent of Adoption of External Auditor on Internal Control in Bank Auditing. Int. f. Innov. Creat.
Chang. 2020,10, 612-624.
40. Macintosh, N.N.; Quattrone, P. Management Accounting and Control Systems; John Wiley & Sons: Chichester, UK, 2010.
41. Varanini, F; Ginevri, W. Projects and Complexity; CRC Press: Boca Raton, FL, USA, 2012.
42. Kindisko, E. Organisational Control in University Management; Emerald Publishing: Bingley, UK, 2018.
43. Weickgenannt, A.B.; Hermanson, D.R.; Sharma, V.D. How, U.S. audit committees oversee internal control over financial reporting.
Int. }. Audit. 2021, 25, 233-248. [CrossRef]
44. Kitchenko, O.; Kuchina, S. Enterprise Communication Policy Indicators Analysis as a Part of Marketing Audit. Technol. Audit
Prod. Reserves 2019, 3, 51-54. [CrossRef]
45. Brown, J.R.; Crosno, J.L. Process and output control in marketing channels: Toward understanding their heterogeneous effects. /.
Bus. Ind. Mark. 2019,34, 735-753. [CrossRef]
46. Frouz, J.; Vindušková, O. Ctení a Psaní Odborného Textu v Environmentálních Vědách; Karolinum: Praha, Czech Republic, 2017.
47. Sedláková, R. Výzkum Médií; Grada Publishing: Praha, Czech Republic, 2014.
48. Ferreira, P; Crema, M.; Verbano, C. Risk management in SMEs: A systematic literature review and future directions. Eur. Manag.
}. 2020, 38, 78-94. [CrossRef]
49. Kosacka-Olejnik, M.; Pitakaso, R. Industry 4.0: State of the art and research implications. LogForum 2019,15,475^185. [CrossRef]
50. Garbellano, S.; do Rosário Da Veiga, M. Dynamic capabilities in Italian leading SMEs adopting industry 4.0. Meas. Bus. Excell.
2019, 23,472-483. [CrossRef]
51. Sheth, J.N. Borderless Media: Rethinking International Marketing. /. Int. Mark. 2020, 28, 3-12. [CrossRef]
52. Cluley, R.; Green, W.; Owen, R. The changing role of the marketing researcher in the age of digital technology: Practitioner
perspectives on the digitization of marketing research. Int. f. Mark. Res. 2020, 62, 27-42. [CrossRef]
53. Raffaelli, M.; Armstrong, J.; Tran, S.P; Griffith, A.N.; Walker, K ; Gutierrez, V. Focus on Methodology: Beyond paper and pencil:
Conducting computer-assisted data collection with adolescents in group settings. /. Adolesc. 2016, 49,1-9. [CrossRef] [PubMed]
54. Lukáč, M.; Mihálik, J. Data Envelopment Analysis-a Key to the Museum's 'Secret Chamber' of Marketing? Commun. Today 2018,
9,106-117. Available online: https://www.communicationtoday.sk/download/22018/08.-LUKAC-MIHALIK-E28093-CT-2-
2018.pdf (accessed on 19 October 2020).
Sustainability 2021,13, 6691 17 of 18
55. Kramer, R.; Mileva, M.; Ritchie, K.L. Inter-rater Agreement in Trait Judgements from Faces. PLoS ONE 2018, 13, e0202655.
[CrossRef]
56. Wijayatunga, P. A geometric view on Pearson's correlation coefficient and a generalization of it to non-linear dependencies. Ratio
Math. 2016, 30, 3-21.
57. Kline, P. The Handbook ofPsychological Testing; Routledge: London, UK, 1993.
58. Laval, V. How to Increase the Value-Added of Controlling; Gruyter: Berlin, Germany, 2018.
59. Tsintsadze, A.; Oniani, L.; Ghoghoberidze, T. Determining and Predicting Correlation of Macroeconomic Indicators on Credit
Risk Caused by Overdue Credit. Banks Bank Syst. 2018,13,114-119. [CrossRef]
60. Písař, P.; Bílková, D. Controlling as a tool for SME management with an emphasis on innovations in the context of Industry 4.0.
Q. }. Econ. Econ. Policy 2019,14, 763-785.
61. Evans, J.D. Straightforward Statisticsfor the Behavioral Sciences; Thomson Brooks Cole Publishing Co: Boston, MA, USA, 1996.
62. Darlington, R.B.; Hayes, A.F. Regression Analysis and Linear Models: Concepts, Applications, and Implementation; The Guilford Press:
New York, NY, USA, 2017.
63. Brabenec, P. Implementační Příručka: Pokyny k Použití Systému OLINA-Online Nástroje pro Řízení Kvality v Organizacích Zájmového a Neformálního
Vzdělávání; Národní institut dětí a mládeže Ministerstva školství, mládeže a tělovýchovy: Praha, Czech Republic, 2012.
64. Hradecká, M. Robotic internal audit-Control methods in the selected company. Agris Line Pap. Econ. Inform. 2019, 11, 31-42.
[CrossRef]
65. Batrancea, L.; Nichita, A.; Batrancea, I.; Cesar, A.M.R.V.C.; Forte, D. Sustainable tax behavior on future and current emerging
markets: The case of Romania and Brazil. Sustain. Soc. Responsib. Account. Rep. Syst. 2018,141-158. [CrossRef]
66. Benedic, N.O The Challenge of Controlling. Int. ]. Ind. Eng. Manag. 2015, 6,153-163. Available online: https: / /www.researchgate.
net/publication/293814491_The_Challenge_of.Controlling (accessed on 19 October 2020).
67. Plant, K ; Barac, K ; Sarens, G. Preparing work-ready graduates—Skills development lessons learnt from internal audit practice. /.
Account. Educ. 2019, 48, 33-47. [CrossRef]
68. Jokič, M.; Laban, B.; Arnautovic, I.; Popovic, D.; Popovic, S. The Importance of Preparing an Internal Audit Report in Reporting
to Top Management of a Company That Makes Key Management Decisions in Its Work. Ann. Constantin Brancusi Univ. Targu-]iu.
Econ. Ser. 2020, 2, 37^4.
69. Wang, L.; Wang, S.; Dai, Y. The Role of Internal Control in Firm's Sustainable Growth: Evidence from China. /. Account. Financ.
2019,19,189-204.
70. Batrancea, L.; Nichita, A.; Batrancea, I.; Gaban, L. The strength of the relationship between shadow economy and corruption:
Evidence from a worldwide country-sample. Soc. Indie. Res. 2018,138,1119-1143. [CrossRef]
71. Karjalainen, J.; Niskanen, M.; Niskanen, J. The effect of audit partner gender on modified audit opinions. Int. f. Audit. 2018,
22,449. [CrossRef]
72. Písař, P.; Kupec, V. Innovative Controlling and Audit-Opportunities for SMEs. Probl. Perspect. Manag. 2019, 17, 184-195.
[CrossRef]
73. Xhani, N.; Avram, M.; Mece, I.; Cela, L. Comparative Study on the Organization of Internal Public Audit in Albania and Romania.
Audit. Financiar. 2019,17, 473^85. [CrossRef]
74. Cohen, J.R.; Joe, J.R.; Thibodeau, J.C.; Trompeter, G.M. Audit Partners' Judgments and Challenges in the Audit of Internal Control
over Financial Reporting. Auditing 2020, 39, 57-85. [CrossRef]
75. Madleňák, A.; Žulová, J. The Right to Privacy in the Context of the Use of Social Media and Geolocation Services; Wolters Kluwer:
Budapest, Hungary, 2019.
76. Petrů, N.; Kramoliš, J.; Stuchlík, P. Marketing tools in the era of digitization and their use in practice by family and other
businesses. Econ. Manag. 2020, 23,199-214.
77. Mayer, K.J.; Salomon, R.M. Capabilities, contractual hazards, and governance: Integrating resource-based and transaction cost
perspectives. Acad. Manag. }. 2006, 49, 942-959. [CrossRef]
78. Blštáková, J.; Joniaková, Z.; Jankelová, N.; Stachová, K ; Stacho, Z. Reflection of Digitalization on Business Values: The Results of
Examining Values of People Management in a Digital Age. Sustainability 2020,12, 5202. [CrossRef]
79. Kaban, Í. Central Audit Activities as a Continuous Audit Approach in the Turkish Banking Sector: A Case Study about Frauds in
Savings Accounts. /. Marmara Univ. Soc. Sci. Inst. 2020,15, 254-275. [CrossRef]
80. Bieliaieva, N. International practice of the concepts use of "HR audit", "staff audit", "personnel audit". Econ. Ecol. Socium 2019,3,
94-101. [CrossRef]
81. Christensen, B.E.; Neuman, S.S.; Rice, S.C. The Loss of Information Associated with Binary Audit Reports: Evidence from
Auditors' Internal Control and Going Concern Opinions. Contemp. Account. Res. 2019, 36,1461-1500. [CrossRef]
82. DeZoort, T; Doxey, M.; Pollard, T. Root Cause Analysis and Its Effect on Auditors' Judgments and Decisions in an Integrated
Audit. Contemp. Account. Res. 2020. [CrossRef]
83. Almaqoushi, W.; Powell, R. Audit committee quality indices, reporting quality, and firm value. /. Bus. Financ. Account. 2021, 48,
185-229. [CrossRef]
84. Pickett, S.K.H. The Internal Auditing Handbook, 3rd ed.; John Wiley & Sons: Chichester, UK, 2010.
85. Gupta, A. Risk Management and Simulation; CRC Press: London, UK, 2019.
Sustainability 2021,13, 6691 18 of 18
86. Kupec, V.; Lukáč, M.; Štarchoň, P.; Pajtinková Bartáková, G. Audit of Museum Marketing Communication in the Modern
Management Context. Int. f. Financ. Stud. 2020, 8, 39. [CrossRef]
87. Lajili, K.; Lin, L.Y.-H.; Rostamkalaei, A. Corporate governance, human capital resources, and firm performance. /. Gen. Manag.
2020, 45,192-205.