Digitized Accounting and Obstacles to Optimized Strategic Decisions

Abstract

The rapid developments in technology have brought about significant changes regarding accounting information extraction as a tool for optimized administrative and strategic decisions. The implementation of electronic bookkeeping as a dynamic application, combined with the continuous renewal of the International Financial Reporting Standards (IFRS), has modified accounting functions. The impacts of technology, the imposition of innovative reforms in the public administration system, the effects of COVID-19 and the continuous need for accounting reforms, shaped in Greece an economic and accounting system of particular research interest. The research approaches accounting management, the impacts of digitalization and the main advantages and obstacles of the ever evolving technological transition. The aim of this paper is to create a tool that utilizes the existing levels of technological training and correlate it with digitization’s weaknesses and opportunities discerning an optimized approach of modern technologies in accounting administration. Results highlight the positive response to the updates of digitization demonstrated in accounting, with the simultaneous resistance to change due to increasing workloads. In the aforementioned economic environment, focused monitoring of both methods and rate of utilizing an evolving technology, combined with the human factor could enable a smoother transition of accounting digitalization and optimized administrative decisions.

1. Introduction

The considerable rise in digitization has inevitably impacted the science of accounting; thus, upgrades to accounting systems are vital. To keep accounting in line with modern economies and technology, professional accounting consulting services must be enhanced through the proper integration of digitized tools to align with accounting rules and specifications [1].

However, as usual, technological growth comes with a certain level of risk, as was the case, for example, back when cloud technologies were first introduced. Reliability and functionality are questioned in relation to emerging operational and exposure issues that could result in accounting data and information being compromised. The importance of avoiding the exposure of sensitive financial and personal data due to a lack of security measures (encryption, the verification of credentials, etc.) means that an accountant’s role in analysis and bookkeeping is becoming even more vital [2]. Economic entities operate within a vast worldwide environment, challenging accountants and requiring the development of a proper accounting management system complying with international legislation and regulations [1,3].

International and local accounting standards should be harmonized with tax legislation and digitization. In this way, matters of legislation, tax law, and statistical and financial frameworks can be simplified [4]. It is essential for professional accountants and tax professionals to be trained and qualified in the effective use of technology. There is an urgent need to develop multi-role skills. At the same time, a lack of knowledge of both communication technologies and information technologies that are consistent with modern accounting requirements exacerbates the issue [5]. An inevitable effect of digital accounting is increased pressure on accounting professionals to remain competitive and keep up with the times [5,6].

Digitized accounting is hindered by considerations regarding the original investment cost, as well as the expenses incurred in updating and redesigning existent processes. Furthermore, the need to train personnel and implement protection measures further hinders the adoption of digitization. Apart from cost and expenditure, a possible reduction in available positions for accountants due to automation is an important factor that affects negatively the integration of digitized solutions. The need for Internet connectivity, a dependence on impersonal administrators and the lack of adaptability of each entity [4], issues related to licensing (e.g., cloud technology), and the storage of personal and business data on non-local servers that differ from domestic ones are further obstacles that can limit the acceptance of digitization.

Although modern information systems are expected to operate in such environments (local databases or cloud databases), accounting records must be readable, secure, properly classified, and easily searchable, in accordance with specific accounting standards and secure protocols, restricting easy access for outside parties. Records should be linked to bank accounts, and electronic transactions automatically recorded in accounting logs.

On the other hand, digital accounting offers remote access, automatic updates, and accessibility while reducing the risk of errors [1], facilitating information distribution, the filling out of data and forms, and the preparation of documents, saving time and resources [6]. Digitized accounting positively impacts an entity’s turnover and reduces its cost cycle [3,7]. Modern information systems and technologies create real-time frameworks and models of coordination suitable for reporting and forecasting [2,8].

Time and cost savings are reinvested in entrepreneurship, which is expected to increase employee earnings. Estimates suggest an increase of 5% in cost savings using digitized methods. With the increase in trained users, operating costs decrease, and the return on equity increases, resulting in an increase in profit margins of up to 8% per month [9].

Regarding the transition from an accountant to a “financial analyst” and “business partner” [10], generally, employees of large accounting firms gain experience over years through taking opportunities with increased earnings and career prospects [7]. In the era of digitization, it will become important to be able to implement in-depth accounting knowledge in control processes, information systems, and data accessibility. Traditional forms of sampling require thought and judgment but could slowly be replaced by data analysis and artificial intelligence tools [10].

This research attempts to identify the main challenges faced by the accounting profession and accountants when implementing digitalization as part of a strategic shift in an economic entity. The literature reveals a concern among accountants regarding their replacement or the depreciation of their knowledge. Through a questionnaire distributed to accountants and accounting professionals, an attempt was made to understand the threats and advantages of digitalization. Digitized accounting was then compared with traditional accounting regarding the possibility of producing higher-quality work and addressing the traditional issues faced by an accountant in a modern technological environment.

2. Materials and Methods

2.1. Theoretical Framework

Most accountants are familiar with modern technology. However, many do not fully utilize these tools to their professional advantage [2]. By now, accountants should be able to, or may be required to, act as mangers and re-evaluators of accounting systems [11].

As technology advances, the time required for simpler accounting tasks is reduced [4]. This time can be used instead to interact with clients and provide entities with information essential for entrepreneurship [12], as well as to balance one’s professional and personal life and provide meaningful reports and better consulting services and investment opportunities. By prioritizing the most important tasks [13], artificial intelligence and accounting software saves valuable time by automating basic and complex activities such as data analysis and business consulting [2].

Advanced Professional Technology: Digitalization is expected to become a cornerstone of strategic importance [14,15]. The trend toward implementing intelligent software is crucial in the growth and survival of an entity. Many networking platforms are familiar with big data management and can extract more data and identify potential investors and opportunities [16]. Knowledge of digitization is a competitive advantage, since it allows reports displaying quantitative data and the interpretation of qualitative characteristics. So far, few academic institutions have developed related curricula, including dominant technologies affecting the accounting industry, such as mobility applications, Cloud technology, and other digital services (including specialized programming languages, big data, electronic payments, cybersecurity, and AI) [17].

Decision makers’ analytical and practical skills should be used to determine which technology is suitable in each case [18]. For example, cloud accounting information systems offer the prospect of flexibility and competitive service among their users [3,9]. High competition levels, economic development, continuous technological breakthroughs, and increasing demands affect the smooth operation of modern entities. The volume of information and its flow are extremely high, while competition is determined by the ability to manage information [1,19]. Based on our literature review, the first research hypothesis was created based on the main elements of technology application and the accounting profession:

H1. 

Further development and increased application of technology in the accounting industry affects the speed of processing corresponding professional activities.

Risks for Accounting Profession: The strategic success of an organization is a result of the proper design of an accounting information system that supports strategies increasing organizational effectiveness [20]. To achieve a stronger and more flexible corporate culture in the face of persistent external environmental changes, entities seek and invest in accounting information systems. Innovation is the incentive that can lead to better and consistent performance, reducing financial and organizational barriers [21]. Technological changes create business opportunities for the accounting industry, as economic entities find it difficult to send quarterly reports and outsource bookkeeping. However, the pressure on accountants due to multiple deadlines and reports becomes more intense throughout the fiscal year. In any case, issues regarding the submission of reports and clearance systems require modern and specialized accounting software. These technologies increase operating costs and place all stakeholders in a constant systemic redesigning cycle [22]. Certain characteristics such as confidentiality, honesty, interpersonal relationships, critical thinking, reasoning and creativity create strong bonds between accountants and clients and therefore cannot currently be replaced by any information system [1,2,7]. Remote, secure and real-time updatable information systems allow faster client–accountant communication. The direct recording of data in the information system allows for speedy tax advice and strengthened work bonds [1].

Several accountant roles are expected to disappear [1]; however, there will still be a need for professional judgment and specialized accounting knowledge to interpret the results of automated processes. The question remains of how to develop advanced judgment and expertise for accountants with shortages of entry-level positions in the future, since these skills are acquired through experience [23]. Digitization is replacing routine tasks. With the evolution of big data processing algorithms, non-routine tasks are becoming susceptible to automation, especially through the development of artificial intelligence. Consequently, accounting professions with increased critical thinking requirements could face the risk of elimination. Basic accounting processes (payroll, bookkeeping, auditing, and taxation) are very close to becoming completely automated [22,24]. Based on this, two hypotheses were formed regarding the main elements of technology and their impact on the accounting profession:

H2. 

The improvement of the speed and automation of processing accounting professional activities may cause the degeneration of accounting science.

H3. 

Further development and increased application of technology in the accounting industry may cause the degeneration of accounting science.

Potential for Enhancement of Activities through technology: Digitization has increased online shopping and e-commerce, and nowadays, all kinds of information is being distributed digitally between consumers, businesses, banks, and stakeholders. The majority of accountants believe that digital competence is as important as their knowledge regarding accounting, while 48% of business executives are worried about being left behind, double the number from last year. In developed countries’ tax and customs information system has been upgraded to a new system, under which all business transactions are almost fully automatically and recorded in an electronic tax account, with these accounts then be submitted quarterly for tax clearance [25].

When it was operational, the UK HMRC IT system was able to monitor and cross-check transactions with tax data, thus eliminating the tax gap that resulted from the manual expansion of incorrect or unrecorded transactions. However, the initial accountability of accountants during the transition to the electronic system was seen as negative, as it replaced much of the way in which processes were carried out. Electronic accounting as an evolution of digital accounting is gaining ground, but it has not yet fully taken its place. Consequently, accountants are now unnecessarily spending money on records to conduct quality checks, when the factor of human error in genetic data has already been eliminated [12].

Based on the literature review, the two last research hypotheses were created based on the main elements of technology applications and the accounting profession:

H4. 

The increased speed and automation of processing accounting professional activities improves the supervision procedures of accounting activities and transactions.

H5. 

The further development and application of technology in the accounting industry improves the supervision procedures of accounting activities and transactions.

2.2. Methodology

During this study, a mixed-methods approach was adopted, which included both qualitative and quantitative methods to increase the reliability and validity of the findings through various tools [26,27]. A theoretical model incorporated factors based on the literature and interviews with accounting experts to achieve the appropriate level of expertise and accuracy. Deductive reasoning was adopted to encode the information extracted from the international bibliography. The initial theoretical areas that emerged from the literature were related to accountants’ technological training and familiarization with digitalized accounting applications. Subsequently, our research identified the disadvantages and risks inherent in accounting standardization and information extraction. The third part of the theoretical model concerned the interactive forces and perspectives that digitization provides in accounting operations.

The inductive approach in this research was carried out through semi-structured interviews [28] with a total of ten interviews, of which two (2) were with Tax Economists—Auditors, three (3) with Certified Public Accountants, three (3) with Accountants—Tax Professionals and two (2) with Accounting and Auditing Professors. Since there were no set limits for the sample size [29], experts were added “to the point where the additional data collected provided minimal new ideas or evidence”. The questions contained deductive elements, as the questions were mainly formulated based on the review of the international literature and articles but at the same time were orientated toward the specific approach of the accounting profession in Greece, since the country’s tax legislation is complex and prompt to constant changes [4]. The questions were twelve open-ended questions based on the thematic sections of the literature. From the open-ended questions, closed-ended questions were created and some others that had come from the bibliography were confirmed. All interviews were conducted at scheduled appointments either in person, via video conference (Skype), or by telephone and lasted an average of 30 min each. The interviews took 3 weeks to complete. Thematic analysis [30] was applied to analyze the information obtained from the interviews.

The above theoretical fields, in combination with the interviews and the literature review, informed the basics of the questionnaire. A thematic analysis was used to analyze the information obtained from the interviews. The experts’ recommendations led to some minor changes in the formulation of the questions and minor verbal changes, while 2 questions were added by the experts regarding time spent on accounting activities, which were considered interesting for further investigation. A pilot survey was conducted in a small sample of eight (8) accountants, via the Internet, preceded by telephone communication, from which the need to reject three questions became apparent, since they were based on local tax and accounting systems and not applicable to larger-scale samples. Specifically, these questions concerned property tax rates, luxury tax (boats, real estate), VAT reductions on islands or tourist areas and constant tax reforms. These taxes are particularly high or fixed in their payment requirements. In some cases, they are applied within the framework of domestic fiscal and environmental strategies, and goes beyond the scope of this research. The final questionnaire consisted of thirty eight (38) Likert-scaled items (response options: “Strongly Disagree,” “Disagree,” “Neither Agree nor Disagree,” “Agree,” “Strongly Agree”). The questionnaire included 10 demographic questions that included work experience, educational level, and level of familiarity with information technologies. The target population of this research consisted of 400 accountants, and therefore a sample size of 208 could be considered representative at a 95% confidence level.

During the control stage of the 210 questionnaires, we observed that 2 of them had more than 50% unanswered questions, and they were removed from the total sample. The construct validity of the variables was determined by conducting Exploratory Factor Analysis. For the extraction method Principal Component Analysis was used and the Varimax rotation technique was adopted, which created factors as independent as possible from each other, so that they can be used in further analysis (hierarchical regression), minimizing the possibility of the presence of collinearity between the variables. As criteria for factor retention a scree plot was used. Rejection limits for factor loadings greater than ±0.40 were set. Finally, the Kaiser rule was applied to decide the number of factors to be extracted, along with the scree test (eigen values). To check the internal consistency reliability of the variables, the Cronbach alpha coefficient was adopted. For the regression analysis a multiple linear regression analysis was used.

3. Results

3.1. Descriptive Statistical Analysis

The following section presents frequencies and percentages for the personal and demographic data of the respondents (

Table 1. Descriptive Statistics Alanylsis.

Personal and Demographic Data	Responses	Percent	Frequency
Gender	Male	58.2	121
	Female	41.8	87
Age	18–30 years of age	15.9	33
	31–45 years of age	56.7	118
	46–60 years of age	26.0	54
	61 or more years of age	1.4	3
Work Experience	0–10 years	36.1	75
	11–20 years	30.3	63
	21–30 years	21.6	45
	31 or more years	12.0	25
Work Description	Employee Accountant with position of responsibility	11.1	23
	Employee Assistant Accountant	2.4	5
	Outsourced Accountant with position of responsibility	16.8	35
	Outsourced Assistant Accountant	69.7	145
Corporation/Organization Size	1–5 employees	73.1	152
	6–20 employees	15.9	33
	More than 20 employees	11.1	23
Skills in Information and Communication Technologies	Novice	0	0
	Moderate	10.1	21
	Good	44.7	93
	Skilled	45.2	94
Level of Education	Middle School of High School	1.9	4
	Vocational Institution	7.2	15
	Technological Education Institution	32.7	68
	University	30.3	63
	Master’s Degree	26.9	56
	PhD	1.0	2

). Regarding the age range of the respondents, the majority (56.7%) were 31–45 years old. The age groups 18–30, 46–60, and 61 or more showed comparatively lower rates of 15.9%, 26%, and 1.4%, respectively. Regarding the variable “work experience”, the majority of respondents, about two in three professionals, had work experience of up to 20 years, while those who were relatively more experienced, with over 20 years of experience, comprised only one in three. The majority (69.7%) were external accountants or owners of accounting firms. There was an increased majority working as accountants in small businesses (73.1%).

None of the respondents self-rated as a novice user, which means that the level of knowledge of information and communication technologies in the accounting industry is virtually indispensable to everyone, with almost half reporting that they were good at using it (44.7%). Almost one third of the sample (32.7%) comprised graduates of Higher Technological Institutes. A percentage (30.3%) of the graduates comprised AEI graduates, followed by a very high percentage (26.9%) of postgraduate diploma holders.

3.2. Factor Analysis

In order to investigate and identify the “groups” to form the items of the questionnaire, exploratory factor analysis was adopted using SPSS 18 statistical software. Firstly, the variables were checked for the presence of correlations with the “Pearson” coefficient. A factor analysis was performed, based on which 17 items were included in the factor analysis.

The factor analysis revealed that no “communality” was low, and therefore all variables were correlated with a factor. The results showed that there were a large number of statistically significant correlations and that it was possible to group variables with common covariance into factors.

From the Total Variance Explained Table, it can be seen that ten factors were extracted in principle, which explained 62.82% of the total variance (a percentage above 50% is considered satisfactory for extracted factors). Based on this, ten factors demonstrated loadings >0.3. From the reliability analysis with the “Cronbach a” coefficient, it was found that four factors were reliable given that the coefficient values were greater than or close to the value 0.70.

Table 2. Principal Component Analysis.

Factor	Questionnaire Items	1	2	3	4
1	Approximately how much time do you estimate you will spend on the following accounting activities with the development of technology in the future? (Issuance/Registration/Archiving of documents)	0.792
	Approximately how much time do you estimate you will spend on the following accounting activities with the development of technology in the future? (Preparation/Submission of all types of declarations)	0.783
	Approximately how much time do you estimate you will spend on the following accounting activities with the development of technology in the future? (Performance/Agreement of banking transactions)	0.702
	Approximately how much time do you spend on the following accounting activities with the current technology you use? (Preparation/Submission of all types of declarations)	0.583
	Approximately how much time do you spend on the following accounting activities with the current technology you use? (Issuance/Registration/Archiving of documents)	0.516
2	To what extent do you use the following information and communication technologies for professional purposes? (mobile applications)		0.805
	To what extent do you use the following information and communication technologies for professional purposes? (social media networks)		0.781
	To what extent do you use the following information and communication technologies for professional purposes? (email, network meetings)		0.625
	To what extent do you use the following information and communication technologies for professional purposes? (data analytics)		0.552
	To what extent do you use the following information and communication technologies for professional purposes? (cloud applications)		0.458
3	Approximately how much time do you spend on the following accounting activities with the current technology you use? (Bill/invoice payment)			0.821
	Approximately how much time do you estimate you will spend on the following accounting activities with the development of technology in the future? (Bill/invoice payment)			0.745
	Approximately how much time do you spend on the following accounting activities with the current technology you use? (Correction of errors/entries)			0.665
	Approximately how much time do you spend on the following accounting activities with the current technology you use? (Performance/Agreement of banking transactions)			0.516
4	Is there a risk that increasingly automated accounting tasks via computer will degrade your fundamental accounting knowledge?				0.797
	Is the extensive use of electronic applications in the accounting profession capable of replacing the relationship between businesses and clients with their Accountant in the future?				0.734
	Is there a risk of job losses due to automation of basic accounting tasks in the future?				0.699
	Eigen Value: 62.815; % of Variance explained: 62.815

and Figure 1 present the results of the factor analysis obtained via the “principal axis factoring” method and the scree plot respectively. Initially, the KMO index takes a value greater than 0.7 and the “Bartlett” test is statistically significant, indicating that factor analysis can be applied to the sample of observations.

Table 2 presents the results of the factor analysis using the principal component analysis method. The Varimax rotation technique identified four clustered factors, which have eigenvalues greater than unity (eigenvalues > 1). These four factors explain 79% of the total variance in the data.

The communalities that determine the amount of variance of the variables explained by each item in the questionnaire are large (≥0.50). The scree plot clearly confirms the existence of four factors. Its slope changes after the fifth factor, as illustrated in the diagram below.

3.3. Factors and Research Model

Based on the conceptual framework provided by the variables presented above, each factor was followed by the names of its items. The first five items, associated with the first factor, appear to be correlated with the extent to which new information and communication technologies have helped accountants and tax professionals reduce the time required to engage in specific activities, and therefore this factor was named “Time Consumed for Accounting Activities” (TCAA).

The next five items, associated with the second factor, appear to be related to the extent to which accountants and tax professionals use specific information and communication technologies for professional purposes, and therefore this factor was named “Information Derived from Accounting Activities” (IDAA).

The next four items, which are linked to the third factor, appear to be related to the extent to which accountants and tax professionals are engaged in specific audit and transaction tasks, and therefore this factor was named “Potential for Enhancement of Activities through technology” (PEAT). The last three items, linked to the fourth factor, appear to be correlated with the degree to which accountants and tax professionals are concerned with risks of technological automation that negatively affect the accounting profession, and therefore this factor was named “Technology Based Risk for the Accounting Profession” (TBRAP).

In general, factor analysis revealed strong factors with high loadings and fairly well-structured information. The 17 clustered items in the four theoretical domains created through the literature review, interviews, and research were significantly retained together in the groups. With the construct validity of the measurement model and the reliable composition of the factors confirmed in

Table 3. Reliability test.

Abbreviation	Factor	Croanbach Value a
TCAA	Time Consumed for Accounting Activities	0.802
IDAA	Information Derived from Accounting Activities	0.743
PEAT	Potential for Enhancement of Activities through technology	0.757
TBRAP	Technology Based Risk for the Accounting Profession	0.655

—Reliability test, the structural equation model was developed. Based on the results of the factor analyses and the literature review, a conceptual model was created, which proposes causal relationships between the latent variables. These relationships are formulated in the form of hypotheses and are depicted in a conceptual Model as seen in Figure 2, below.

Based on the factor analysis and the four (4) factors, the theoretical model was constructed. Through this model, some possible correlations between the factors were observed based on the bibliographic and empirical review of the subject. These correlations created the basic hypotheses of our research. The five research hypotheses derived from the literature, the conceptual relationships created, and their correlations are listed in

Table 4. Paths arising from the conceptual model.

Hypothesis		Path		Effect	Correlation	Significance
H1	Further development and increased application of technology in the accounting industry affects the speed of processing corresponding professional activities.	1st Path	IDAA → TCAA	Direct	Positive	Significant
H2	The improvement of the speed and automation of processing accounting professional activities may cause the degeneration of the accounting science	2nd Path	TCAA → TBRAP	Direct	Positive	Statistically detectable
H3	Further development and increased application of technology in the accounting industry may cause the degeneration of accounting science.	3rd Path	IDAA → TCAA → TBRAP	Indirect	Positive	Statistically detectable
H4	The increased speed and automation of processing accounting professional activities improves the supervision of accounting activities and transactions.	4th Path	TCAA → PEAT	Direct	Positive	Not Significant
H5	The further development and application of technology in the accounting industry improves the supervision of accounting activities and transactions.	5th Path	IDAA → PEAT	Direct	Positive	Significant
		6th Path	IDAA → TCAA → PEAT	Indirect	Positive	Not Significant

.

To determine the correlations between factors, both Kendall’s tau-b correlation coefficient and the Spearman correlation coefficient were used. From these, a positive correlation emerged between the TCAA and PEAT factors, with values for the above coefficients of 0.366 and 0.475, respectively, at a statistical significance level of α = 0.001 (

Table 5. Correlations.

			TCAA	IDAA	PEAT	TBRAP
Kendall’s tau_b	TCAA	Correlation Coefficient	1.000	−0.126 *	0.366 **	0.084
		Sig. (2-tailed)	.	0.012	0.000	0.099
		N	208	208	208	208
	IDAA	Correlation Coefficient	−0.126 *	1.000	−0.168 **	0.053
		Sig. (2-tailed)	0.012	.	0.001	0.290
		N	208	208	208	208
	PEAT	Correlation Coefficient	0.366 **	−0.168 **	1.000	0.012
		Sig. (2-tailed)	0.000	0.001	.	0.811
		N	208	208	208	208
	TBRAP	Correlation Coefficient	0.084	0.053	0.012	1.000
		Sig. (2-tailed)	0.099	0.290	0.811	.
		N	208	208	208	208
Spearman’s rho	TCAA	Correlation Coefficient	1.000	−0.172 *	0.475 **	0.114
		Sig. (2-tailed)	.	0.013	0.000	0.101
		N	208	208	208	208
	IDAA	Correlation Coefficient	−0.172 *	1.000	−0.228 **	0.072
		Sig. (2-tailed)	0.013	.	0.001	0.299
		N	208	208	208	208
	PEAT	Correlation Coefficient	0.475 **	−0.228 **	1.000	0.014
		Sig. (2-tailed)	0.000	0.001	.	0.846
		N	208	208	208	208
	TBRAP	Correlation Coefficient	0.114	0.072	0.014	1.000
		Sig. (2-tailed)	0.101	0.299	0.846	.
		N	208	208	208	208

*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).

). Among the remaining variables, as shown in the relevant table, the correlations are statistically insignificant.

The regression analysis shows that the above correlations are verified. However, in the case of PEAT as a dependent variable with TCAA as an independent variable, a positive correlation emerges (R value = 0.534 at a statistical significance level of α = 0.001). The standard error of the estimate is 2.336 while details can be found in

Table 6. Model Summary.

Dependent Variable	Constant	R	R Square	Adjusted R Square	Std. Error of the Estimate
TCAA	TBRAP	0.076	0.006	0.001	3.360
PEAT	TCAA	0.534	0.285	0.282	2.336
TCAA	IDAA	0.168	0.028	0.024	3.322
PEAT	IDAA	0.232	0.054	0.049	2.688

—Model Summary.

The t-test examined the significance of the coefficient b. The t-value is 8.602, which is significant at the level of α = 0.001 (As found in

Table 7. Coefficients.

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
TCAA	Constant	18.799	0.871		21.594	0.000
	IDAA	−0.138	0.056	−0.168	−2.452	0.015	1.000	1.000
	Constant	15.974	0.734		21.759	0.000
	TBRAP	0.086	0.078	0.076	1.101	0.272	1.000	1.000
PEAT	(Constant)	16.745	0.704		23.772	0.000
	IDAA	−0.155	0.045	−0.232	−3.418	0.001	1.000	1.000
	(Constant)	7.091	0.824		8.602	0.000
	TCAA	0.438	0.048	0.534	9.070	0.000	1.000	1.000

). Moreover, the tolerance values (1.000) and VIF (1.000) show that there is no multicollinearity.

Continuing with the ANOVA method (

Table 8. ANOVA.

Model		Sum of Squares	df	Mean Square	F	Sig.
IDAA a	Regression	84.388	1	84.388	11.680	0.001 b
	Residual	1488.381	206	7.225
	Total	1572.769	207
TCAA a	Regression	448.854	1	448.854	82.269	0.000 b
	Residual	1123.915	206	5.456
	Total	1572.769	207
TBRAP b	Regression	13.682	1	13.682	1.212	0.272 b
	Residual	2326.298	206	11.293
	Total	2339.981	207

^a Dependent Variable: PEAT. ^b Dependent Variable: TCAA.

), the overall statistical significance of the model is shown. F = 82.269 is statistically significant at the level of statistical significance α = 0.001.

Moreover, the eigenvalues do not indicate a multicollinearity problem, since they are not close to 0, while regarding the paths demonstrate Eigenvalue: 1.948 (IDAA → TCAA) and 1.964 (IDAA → PEAT). Moreover, the histogram shows the normal distribution of the residuals, a fact that is also confirmed by the normal probability plot.

4. Discussion

Digitalization has come to play a significant role in the design of operational models, reports, and forecasts and is expected to become a cornerstone of strategic improvement. The trend toward implementing intelligent software is crucial in the growth and survival of an entity. A prerequisite for the strategic development of a business unit involves the management and monitoring of these factors. In recent years, both the volume of information and its flow speed have become extremely high, and competition is determined based on the ability to manage information [19,31]. The strategic success of an organization is a result of the proper design of an accounting information system that supports business strategies in ways that increase organizational effectiveness [32].

This research focused on the current transition in the digitized environment in which accounting professionals operate. The modern methods, procedures, and requirements that professional tax specialists and accountants are called upon to undertake place them in the position of a business consultant. At the same time, these new conditions pose difficulties regarding training and the integration of big data. The risks in this digital transition lie in the exploitation and misuse of technology and external threats (hackers, cybercrime). Standardized, rigid procedures that are uncritically applicable and the creation of feedback loops could circumvent these issues and protect the nature of accounting science [1,30].

Initially, as expected based on the 1st hypothesis (IDAA → TCAA), the increase in digitization in accounting speeds up processes and address vital accounting issues. Specifically, speed seems to have a greater impact on issues of data entry and archiving, statement preparation, and banking transactions. These improvements free up more time to deal with workload and more client–accountant time. The extent to which this increase in volume is related to strategic activities requires further study. However, a certain amount of time saved is now used for training in modern technologies and systems.

Regarding the 2nd hypothesis (TCAA → TBRAP), it was not confirmed whether increased speeds caused the degeneration of accounting science through the perceived risk of accounting circumvention and the depreciation of the accounting profession through standardized and rigid procedures. Uncritical automation can create a situation in which the nature of accounting theory is not renewed, while at the same time, without digitization, professionals will be consumed in carrying out standard procedures and not in the development of science. This will lead to delays and weaknesses in the flexible recording and utilization of available assets and, at the same time, weaknesses in the performance of both the data and their utilization. Finally, this hypothesis must be re-examined regarding the aforementioned risk of digital transition and risks of the misuse of technology. A similar, albeit weaker, correlation is also seen in the 3rd hypothesis (IDAA → TCAA → TBRAP), as the “Information Derived from Accounting Activities” (IDAA) factor indirectly, positively, but to a small extent affects “Technology Based Risk for the Accounting Profession” (TBRAP) through “Time Consumed for Accounting Activities” (TCAA).

The non confirmed 4th hypothesis (TCAA → PEAT) suggests that the increased speed and automation of processing accounting professional activities have little improvement to procedures involving the supervision of accounting activities and transactions. However, issues around the transparency of accounting statements must be addressed in real time, while the increase in technology may have also increased the volume of data and undertaken activities. Speed is ultimately one of the most important factors in the use of technology found in literature as a reporting and transparency tool in accounting.

Finally, the 5th hypothesis (IDAA → PEAT) in this research concerned the extent to which more elaborate digitized accounting improves the supervision of procedures and transactions. The correlation of the factor “Information Derived from Accounting Activities” (IDAA) with the direct, positive, and significant effect on the factor “Potential for Enhancement of Activities through technology” (PEAT) clearly shows the positive effect of technology and its evolution on issues of transparency and in the better monitoring and understanding of processes.

For the same hypothesis, an indirect, positive correlation is observed between “Information Derived from Accounting Activities” (IDAA) and “Potential for Enhancement of Activities through technology” (PEAT). However, this additional effect passes through the factor “Time Consumed for Accounting Activities” (TCAA). So even if the further development of technology helps the accounting profession and allows the better management of technologies, digitalization, in order to reach the most optimal levels that it can, must be translated through practical and accounting management tools, using the rules and principles of accounting provided based on the experience and knowledge of professionals in the industry, especially in countries with complex tax legislation [22,25] and frequent tax reforms. The model seems to have particular importance regarding the last factor, “Technology Based Risk for the Accounting Profession”, as the degree of influence of professionals’ concerns and the risks of automating processes must be further studied.

5. Conclusions

Digitization saves time, reducing costs and improving efficiency. Reporting and managing accounting data allows transparency and enables entities to monitor financial data and set safer strategies based on cost [33,34]. In addition, the optimization of secure transactions, reporting, and disclosure can be achieved through the implementation of practical digitized accounting through the careful re-examination of each case. International and local accounting standards must be translated through the experience and knowledge of accounting professionals. The present research, through the development of a model and the correlations developed through it, presents dynamics that can help in the management and application of digitalization in accounting. Initially, as is evident from the research hypotheses, development and application of technology in the accounting industry secure the volume and quality of the information derived from accounting activities. Through the model and the confirmation of the hypotheses this factor reduces the speed of processing regarding accounting activities. Furthermore, the same factor regarding accounting derived information is shown to improve the supervision of accounting activities and transactions, since respondents find a significant potential in technology that enables the enhancement of accounting activities. Finally, no significant correlations were found linking the development of technology with the degradation of the accounting profession. However, there is an evident need to ensure that accounting science remains robust and that an entity does not follow incorrect strategies in relation to accounting standardization. Through the support that it receives from accountants, transparency, and speed, digitized accounting aids in the formulation of strategies using real-time data.

5.1. Research Implications

The effects of digitized accounting appear interesting and complex, since it increases speed and transparency. Entities can invest in balanced training and the assimilation of modern technologies to develop robust strategies. Furthermore, the evolution of the accountant’s profession through the use of technology is highlighted.

5.2. Research Limitations

Digitization requires a state of constant evolution. Issues regarding the implementation of modern technologies into strategical planning seem to be subject to further discussion. Changes to, and strain on, the accounting system should be taken into account as possible factors with significant impacts on the interpretation of responses.

5.3. Future Research

The digitization of accounting requires further investigation regarding the volume of business activities, response times, and successful training. At the same time, the concerns of professionals in a comparative model for predicting the risk of automation should be further investigated.