Determinants of the Digitalization of Accounting in an Emerging Market: The Roles of Organizational Support and Job Relevance

Abstract

Digitalization has considerable potential to help achieve the sustainability of the planetary and human systems, including organizations. As digitalization is one of the most promising factors for transformation, there is no doubt that ICT and big data can help promote sustainability. Linking digitalization with a sustainable workplace, the purpose of this investigation is to identify the determinants of the adoption of digitalization of accounting procedures by accounting professionals in Saudi Arabia, an economy rapidly moving towards digital transformation. A holistic model based on the technology acceptance model (TAM), elaboration likelihood model (ELM), and social exchange theory (SET) is proposed and tested. The extension in TAM is proposed by integrating job relevance and organizational support as moderators. A survey method was used to collect data from 365 accounting professionals working in Saudi Arabia. Structural equation modeling and PROCESS macro were used as data analysis techniques. The findings reveal that perceived ease of use has both direct and indirect effects through perceived usefulness on intentions to use e-accounting. Both job relevance and organizational support act as moderators for perceived usefulness and intentions to use e-accounting when treated separately. However, job relevance becomes an insignificant moderator in the presence of organizational support. This finding highlights the importance of organizational support for the successful implementation of e-accounting in an organization.

1. Introduction

The digital transformation of the world has impacted our daily lives where our daily activities are now highly dependent on computers and digital technologies [1]. This integration of computer and digital technologies in our daily lives is called digitalization, and the idea of sustainability is to use or produce goods or services in a way that causes no or minimal damage to the environment. Both digitalization and sustainability emerged as major trends that have a transformational impact on the economy and society. Digitalization is considered to be one of the most up-and-coming transformations for sustainability [2,3]. Research has identified a positive link between digitalization and sustainability. Jovanovic et al. [4], by using DESI (digital economy and society index), identified that more digitalized economies perform better in achieving sustainability goals. Digitalization is linked with operational efficiency where the accessibility, collection of data in real time, energy management and resource consumption, and knowledge regarding the entire life cycle of the product is available without any disruptions and inefficiencies [5]. This efficient use of resources in organizations due to digitalization contributes positively to a sustainable workplace [6]. As sustainability is the outcome of digitalization, the purpose of the current investigation is to observe the factors affecting the acceptance of digitalization of accounting procedures in an emerging market in Saudi Arabia.

The accounting system, as one of the most fundamental, has a great impact on the success of any organization by not only contributing to the enhancement and tracking of the economic efficiency, but also to reducing the excess costs and mitigating the financial risks [7]. The development of an accounting system is very important and critical for all firms. The corporate governance development and the emergence of information technology have forced firms to move from traditional accounting systems to electronic accounting systems [8]. There is no doubt that technological progress has contributed to the expansion of the scope of electronic accounting [9]. Initially known as computerized accounting, and nowadays also referred to as an accounting information system, the electronic accounting procedures fulfil the accounting functions through the Internet, mobile, and online technologies [10].

In e-accounting, accounting software and computers are used for recording, storing, and analyzing financial data, while making sure that this information and data are safe from corruption, controlled, and accurate [11]. E-accounting systems help in accurately handling business operations and hence speeding up the procedures, while lowering the cost [12] by eliminating the routine time-consuming manual tasks and calculations [13,14]. Similarly, it helps in preparing financial statements with high reliability [15], and different individuals can access this information on-site or off-site more securely [16].

There is no doubt that e-accounting systems are very beneficial for firms, however, it has challenges too. According to Fiducci [17], the creator of a firm’s e-accounting system can be replaced without having a claim on ownership of data or claim to be a primary creator. Similarly, there is no duplicate or original copy [18]. The firm data can be manipulated, modified, or even deleted by intruders or hackers [19,20]. As e-accounting works on the exchange of data between individuals using online options, special care and the use of scientific precautions for preventing hacking and information theft is required [21].

As the Kingdom of Saudi Arabia is moving toward digital transformation, there is a lack of research that provides insights into the behaviors and intentions of the individuals who are part of this process of digital adoption. Saudi Vision 2030 has a strong emphasis on digital transformation by adopting and implementing state-of-the-art telecommunication and ICT technology systems to facilitate digital transformation. The Kingdom has evolved by replacing traditional processes with digital ones. The focus of Saudi Vision 2030 is to digitally innovate to facilitate services inside the Kingdom. E-accounting is part of the digitalization of workplace processes and the antecedents that affect the adoption of this digitalization are required to be highlighted and identified. Since there is a lack of research on the factors affecting the adoption of e-accounting in Saudi Arabia during its digital transformation, this research can provide important insights at policy levels.

Based on the review of the prior literature in e-accounting, there is limited research available on intentions to adopt e-accounting in general, and the acceptance of e-accounting by accounting managers in particular [22]. Similarly, firms from developing countries are already far ahead in the adoption and use of e-accounting procedures and systems. However, information technology usage and technological adoption have yet to reach their desired level in Middle-East economies [23,24]. While studying the (TAM) model in the Iranian accounting professional context, Allahyari and Ramazani [25] identified the importance of organizational factors (internal support, internal training, and management support). They empirically investigated the direct impact of organizational factors on perceived ease of use and perceived usefulness, and did not consider organizational support as a boundary condition. Similarly, according to Eltweri and Cavaliere [26], e-accounting and business performance are directly related; however, more in-depth studies are required in order to examine other kinds of factors that can have an impact on e-accounting.

The technology acceptance model (TAM) is one of the most influential models for the identification of intentions to use technology. The TAM has identified perceived ease of use and perceived usefulness of technology as important predictors of intentions to adopt technology [27]. Similarly, the social exchange theory (SET) is also one of the most significant theories in describing workplace behaviors that explain the interaction among actors with social exchanges involving resources [28]. The elaboration likelihood model (ELM) identifies the importance of external factors, including job relevance, as the motivation dimension of elaboration that acts as a primary driver of attitudes and behaviors.

As highlighted above, the aim of the current investigation is two-fold: first, a holistic model based on the technology acceptance model (TAM), elaboration likelihood model (ELM), and social exchange theory (SET) is proposed for the identification of determinants of acceptance of digitalization (e-accounting), where organizational support and job relevance are proposed as important enablers for acceptance of e-accounting. Second, the model was tested using data from an important emerging market, Saudi Arabia, having a strong focus on digital transformation in its “Vision 2030”.

2. Research Model and Hypotheses

2.1. Technology Acceptance Model

A variety of theoretical perspectives have been used by researchers for investigating information system use and its adoption, including the unified theory of acceptance and use of technology (UTAUT) and the technology acceptance model (TAM). According to Thottoli and Ahmed [23], there is no generally accepted theory that can explain the use and adoption of ICT. However, of all the theoretical perspectives, the TAM is considered the most employed theory for explaining the acceptance of information systems by individuals [29,30].

The technology acceptance model by Davis [27] is based on two psychosocial theories: the theory of planned behavior by Ajzen [31], and the theory of reasoned action by Fishbein and Ajzen [32]. Both theories are focused on explaining and predicting a specific behavior in individuals. According to Davis [27], an individual’s acceptance of information systems is predicted by two perceptions of the user: perceived usefulness and perceived ease of use of the system. According to Davis [27], perceived usefulness is “the degree to which a person believes that using a particular system would enhance his or her job performance” [27] (p. 320), and perceived ease of use is “the degree to which a person believes that using a particular system would be free of effort” [27] (p. 320). In the meta-analysis of the technology acceptance model, King and He [33] reported that both perceived ease of use and perceived usefulness are important predictors of behavioral intentions. However, perceived usefulness is a much stronger predictor.

2.2. Perceived Usefulness as Mediator

The parsimony of the TAM contributed to its wide applicability. Many studies have either directly used the initially proposed model by extending it to different contexts [34,35,36] or users [37,38]. Similarly, many studies have also proposed an extension to this model by either including factors from the related model (i.e., theory of planned behavior or theory of reasoned action constructs) or by including additional beliefs or external variables. These extensions were proposed in the form of moderators, mediators, or antecedents to improve the predicting power of the TAM [36].

The literature on the use of the TAM to examine intentions to use e-accounting systems is limited. A study conducted by Souza, Munay de Silva, and Ferreira [39], while using the TAM to explain the acceptance of information technology in the accounting area, identified the usefulness of the TAM in the context of electronic accounting. Their study identified the significance of perceived usefulness in predicting intentions to use information technology in accounting and the significance of perceived ease of use in predicting perceived usefulness. Similarly, the study conducted by Abduljalil and Zainuddin [40] found both perceived ease of use and perceived usefulness significant in determining the behavioral intentions to adopt accounting information systems by SME owners in Malaysia. While testing the acceptance of cloud-based computing technology in accounting, Le and Cao [41] found both perceived ease of use and perceived usefulness as important predictors. Hence, based on the above literature findings, the following hypotheses are proposed:

Hypothesis 1 (H1).

Perceived ease of use has a significant positive impact on intention to use e-accounting.

Hypothesis 2 (H2).

Perceived usefulness has a significant positive impact on intention to use e-accounting.

Hypothesis 3 (H3).

Perceived ease of use has a significant positive impact on perceived usefulness.

2.3. Organization Support as a Moderator

Organizational support is the extent to which management is willing to provide or allocate resources to employees, so they can achieve organizational goals and objectives [42,43]. Prior studies have identified a link between organizational support and the use of computer systems [44,45] through beliefs and behaviors [27,46]. Similarly, a lack of organizational support is linked with negative implications [46]. Support from top management plays a critical role in encouraging employees to use computer technology in the workplace.

Social exchange theory (SET) is one the most influential theories describing workplace behaviors that explain the interaction among actors with social exchanges involving resources [28]. These exchanges involve at least two actors who are in some way dependent on each other [47]. In the workplace, such exchanges may occur between the organization (management) and employees, where any goodwill gesture by any actor may be reciprocated by others. Such reciprocity sometimes goes beyond the initial action [48] and may show behaviors that are voluntary. The caring and benevolent behavior by the organization, in general, creates an atmosphere of goodwill and employees may in turn show a good attitude and behavior [49,50].

The previous literature has also indicated a positive association between organizational support and an individual’s perception of usefulness and ease of use of computer technologies [44,51,52,53]. Organizational support is a critical facilitating factor that enhances the probability of usage of computer technology. Organizational support builds the trust that is required by employees for taking the risk of integrating computer technologies into practice [53]. Hence, it is proposed that the relationship of perceived usefulness (PU) and behavioral intentions to use e-accounting becomes stronger when organizational support is available; that is, when employees feel support from the organization, their perception of the usefulness of computer technology becomes more positive, which triggers their intention to use it. Based on the above discussion, the following hypothesis is proposed:

Hypothesis 4 (H4).

Organizational support will have a moderating effect on perceived usefulness of intentions to use an e-accounting relationship.

2.4. Job Relevance as a Moderator

According to Chismar and Wiley-Patton [54], “Job relevance is an individual’s perception of the degree to which the technology is applicable to his or her job” (p. 155). The elaboration likelihood model (ELM) identifies the importance of external factors as the primary drivers of attitudes and behaviors. Hence, based on work-related experiences and new information, individuals may alter their attitudes and behaviors [55].

Drawing upon the ELM, Bhattacherjee and Sanford (2006) proposed job relevance as a motivation dimension of elaboration, having a moderating effect on the association of argument quality and perceived usefulness of IT acceptance. According to the authors, the relevance of an IT system to work performance acts as an important motivator for the potential users to be actively involved in adopting new technology for making more informed decisions regarding technology’s perceived usefulness and usage intention. The relevance of technology to the job makes individuals view technology as being useful and is linked with their increased intention to use it. Similarly, those who view technology as irrelevant to their job may perceive it as useless and will be less likely to use it [55].

The majority of the literature has either proposed job relevance as an antecedent of perceived usefulness [56] or has empirically tested variables that are similar to job relevance, e.g., [57,58]. While investigating mobile wireless technology adoption, Kim and Garrison [55] proposed job relevance as a moderator and reported the moderating impact of job relevance on perceived usefulness and behavioral intentions. Based on the above discussion, it is proposed that an individual’s perception of how well electronic accounting is applicable to his/her job enhances his/her perception of its usefulness and his/her intention to use it. Hence, the following is proposed:

Hypothesis 5 (H5).

Job relevance will have a moderating impact on perceived usefulness and intention to use an e-accounting relationship.

The proposed research model based TAM while considering OS and JR as moderators is presented in Figure 1.

3. Methodology

3.1. Study Context

This study used the Kingdom of Saudi Arabia, an oil-based emerging economy, to test this theoretical model. Saudi Arabia, with a population of 34 million individuals (2021), is in the furthermost part of southwestern Asia. It is bordered by Yemen and Oman in the south; Kuwait, Iraq, and Jordan in the north; the Red Sea in the west; and the Arabian Gulf, United Arab Emirates, and Qatar in the east. It is categorized by the World Bank as a high-income country. With a per capita GDP of USD 23,762, it is ranked 40th out of 188 countries in the Human Development Index (HDI) with a 0.854 HDI value for 2020 [59]. The country prioritizes education, with low levels of illiteracy (4.7%) and high rates of enrollment in tertiary education (70.4% of the population, 67.9% of men, and 75.6% of women). All these factors play a role in achieving the country’s 2030 vision of a vibrant society, thriving economy, and an ambitious nation.

One of the initiatives of the Saudi 2030 vision focuses on the country’s digital transformation, which highlights adopting and implementing state-of-the-art telecommunication systems and ICT technology. The Saudi government developed five-year plans (2006–2024) to replace traditional processes with smart ones (https://www.vision2030.gov.sa/ (accessed on 2 December 2021)), which led to The International Telecommunication Union awarding Saudi Arabia the Government Leadership Award for adopting the best policies and regulations that support the digital economy, stimulate investment and innovation, and contribute to achieving sustainable development goals. The country has also ranked among the top ten developed countries globally for its robust digital framework (https://www.mcit.gov.sa/en (accessed on 2 December 2021)). Given these factors, the Kingdom of Saudi Arabia represented a suitable opportunity for this study.

3.2. Data Collection

Data were collected using the self-report survey instrument. The final sample of 365 employees working in the accounting departments of various organizations operating in Saudi Arabia was used for data analysis. An incremental approach to data analysis was adopted where, first, the reliability and validity of data were assessed and, in the second step, hypothesis testing was conducted. SPSS and AMOS were used for reliability and validity checks and PROCESS Macro, an extension in SPSS, by Hayes [60] for hypothesis testing. Out of 365 respondents, 64% were males. A total of 49.9% of the respondents were in the age group of 25–34 years, followed by 30% who belonged to the age group of 35–44 years. A total of 27% of respondents had experience of 5–10 years, followed by 3–5 years of experience (26%). Similarly, around half of the respondents, 42.5%, had been using e-accounting systems for 1–3 years.

Table 1. Demographic information, n = 365.

Variables	Category	Frequency	Percentage
Gender	Male
	Female
Age	18–24	53	14.5
	25–34	182	49.9
	35–44	110	30.1
	45–54	13	3.6
	54 and above	7	1.9
Experience total	<1	28	7.7
	1–3	76	20.8
	3–5	93	25.5
	5–10	99	27.1
	>10	69	18.9
Experience current Org	<1	31	8.5
	1–2	92	25.2
	2–5	139	38.1
	>5	103	28.2
Use of e-accounting	<1	76	20.8
	1–3	155	42.5
	3–5	66	18.1
	>5	48	13.2
	Not used	20	5.5

Source: field data.

presents the demographic information of the respondents.

3.3. Instrumentation

The target population consisted of individuals involved in accounting departments within public, private, and semi-government organizations in all 6 geographical regions of the Kingdom of Saudi Arabia: The Eastern, Central, Northern, Northwest, Midwest, and Southwest regions. Data were collected using an online survey via mobile devices on the Pollfish survey platform. Pollfish uses random device engagement (RDE) to reach mobile users identified by a unique device ID [61]. A random sample was selected from Saudi Arabia that fit the eligibility criteria set by the research team (do you work in the accounting department within your organization). The survey was conducted in English, which is the official business language medium in the country. For the ease of completion on a mobile device, the survey was designed to be completed in approximately ten minutes or less.

The survey ran from 13–25 December 2021, and collected data from 365 respondents. The instrument contained 8 questions: Total Experience, Experience at the Current Organization, the Use of Digital Accounting Systems, Perceived Ease of Use (PEU), Perceived Usefulness (PU), Organizational Support (OS), Behavioral Intention to Use (IU), and Job Relevance (JR). Age, gender, education, industry, and organizational role were known for all respondents due to their participation in previous surveys. The study protocol and survey instrument were approved by the Prince Sultan University Institutional Review Board (IRB).

A self-report scale with closed-ended potions was used for gathering the responses of accounting professionals. The questionnaire had two sections, with the first section focusing on the demographic information of respondents and the second section focusing on the variables under study. A 5-point Likert scale, with 1 as “strongly agree” and 5 as “strongly disagree”, was used for the measurement of variables, excluding the demographic constructs.

Behavioral intention to use e-accounting scale consisted of two items developed by Fishbein and Ajzen [32]. Perceived ease of use and perceived usefulness scales were based on the Davis (1993) scale with modifications to accommodate the context of the study. Seven and six items were used to measure perceived ease of use and perceive usefulness, respectively. The organizational support was measured using a scale adapted from Lee et al. [53], with few modifications to meet the requirements of the study. It consisted of five statements. The sample statements were: “My boss understands the benefits to be achieved by using the e-accounting system”, “I am always supported and encouraged by my boss to use the e-accounting system to perform my job”, and “I am convinced that my colleagues are aware of the benefits of the e-accounting system.” Lastly, job relevance was assessed using two Likert-scaled items, adopted from Venkatesh and Davis [62].

4. Data Analysis and Results

4.1. Scale Validation

Confirmatory factor analysis (CFA), also known as the measurement model, was used as an analytical strategy for the validation of the scale. AMOS 17 was used to conduct confirmatory factor analysis. CFA analysis identified PEU7 not successfully loaded into its latent construct, hence it was removed from further analysis. After the removal of PEU7, the results of the CFA analysis significantly improved and with acceptable model fit indices. The acceptable fit indicators were χ²/d.f. < or = 3 [63]; goodness of fit (GFI) > or = 0.9 [63,64]; root-mean-square error of approximation (RMSEA) < 0.08 [63,65]; root-mean-square residual (RMR) < 0.08 [63,65]; comparative fit index (CFI) > or = 0.9 [63,64]; goodness-of-fit index (GFI) > or = 0.9 [63,64]; and adjusted goodness-of-fit index (AGFI) > or = 0.8 [63,64]. The results of the CFA analysis are presented in

Table 2. Results of confirmatory factor analysis.

Construct/Variable	Factor Loadings	Alpha	CR	AVE
Perceived Ease of Use		0.84	0.84	0.50
PEU1	0.711
PEU2	0.669
PEU3	0.614
PEU4	0.693
PEU5	0.699
PEU6	0.684
Perceived Usefulness		0.86	0.86	0.50
PU1	0.716
PU2	0.746
PU3	0.669
PU4	0.761
PU5	0.704
PU6	0.656
Organizational Support		0.87	0.83	0.50
OS1	0.696
OS2	0.739
OS3	0.662
OS4	0.696
OS5	0.713
Job Relevance		0.70	0.70	0.51
JR1	0.679
JR2	0.742
Intentions to Use E-accounting		0.71	0.71	0.60
IU1	0.702
IU2	0.785
Goodness-of-Fit Indices
χ2 = 404; d.f. = 177; χ2/d.f. = 2.28; p < 0.001; CFI = 0.96; GFI = 0.91; AGFI = 0.88; RMR = 0.02; RMSEA = 0.06.

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4.2. Reliability and Validity

Cronbach’s alpha and composite reliability values were used for assessing the overall reliability of scales used for data collection. All variables presented acceptable reliability with Cronbach’s alpha values ranging between 0.70–0.87 and composite reliability values ranging between 0.70–0.86 [66]. Similarly, AVE, convergent, and discriminant validity values were used to assess the overall validity of collected data. For convergent validity, the standardized regression weights of each observed variable were assessed. It was concluded that all observed variables had regression weights greater than 0.60 and were successfully loaded into their respective latent variables. The AVE of all latent variables was greater than 0.5. For discriminant validity, the squared multiple correlation values were compared with AVE, and the values of squared multiple correlation values were either equal to or less than AVE [67], hence providing evidence for discriminant validity. Reliability and validity analysis results are presented in

Table 3. Descriptive statistics and correlations.

	Variable	No. of Items	Mean	S.d.	1	2	3	4	5
1	PEU	6	1.61	0.49	0.50
2	PU	6	1.63	0.60	0.69 * (0.48)	0.50
3	OS	5	1.52	0.56	0.65 * (0.42)	0.70 * (0.49)	0.50
4	JR	2	1.56	0.66	0.59 * (0.35)	0.68 * (0.46)	0.58 * (0.34)	0.50
5	IU	2	1.61	0.66	0.58 * (0.34)	0.67 * (0.45)	0.57 * (0.32)	0.65 * (0.42)	0.60

PEU: Perceived Ease of Use; PU: Perceived Usefulness: OS: Organizational Support; JR: Job Relevance; IU: Intentions to Use E-accounting; AVE Bold in diagonal; * p <0.01; s.d.: Standard deviation.

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4.3. Hypotheses Testing

SPSS extension, PROCESS Macro by Hayes [60] was used for hypothesis testing. PROCESS Macro was preferred over other analytical techniques because of its robustness and bootstrapping approach. The PROCESS Macro provides biased corrected 95% CI and can simultaneously analyze moderation and mediation effects for complex models. An incremental approach to hypothesis testing was used where the first mediation model was assessed. Then, two moderation models, by taking organizational support and job relevance, respectively, were analyzed. Finally, the full mediation moderation model was assessed.

4.4. Mediation Analysis

To test the first set of proposed hypotheses PROCESS Macro, an extension in SPSS, Model no. 4 was used. The results identify that PEU has a significant effect on PU and IU. Similarly, PU also has a significant effect on IU. Both the direct effect of PEU on IU and indirect effect through PU were significant, hence identifying partial mediation. The results of PROCESS Model 4 are presented in

Table 4. 5000 bootstrap results for direct and indirect effects Process Model 4.

Path	Estimate		SE
PEU => BI (Direct Effect)	0.313 *		0.07
PEU => PU	0.842 *		0.05
PU => IU	0.554 *		0.06
Standardized Total, Direct, and Indirect Effects using 5000 Bootstrap 95% CI
Path	Effect	SE	LL 95% CI	UL 95% CI
Total Effect	0.779	0.06	0.668	0.891
Direct Effect	0.235	0.07	0.174	0.452
Indirect Effect (PEU => PU => IU)	0.550	0.05	0.251	0.448

PEU: Perceived Ease of Use; PU: Perceived Usefulness: OS: Organizational Support; JR: Job Relevance; IU: Intentions to Use E-accounting; * p < 0.01.

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4.5. Moderation Analysis

Similarly, for simple moderation analysis, PROCESS Macro Model no. 1 was used. Model no. 1 was used separately for both the proposed moderators, i.e., organizational support and job relevance. A total of 5000 bootstraps with biased corrected 95% confidence intervals and the Johnson–Neyman outputs for the interaction term plotting were used with the first mean centering the variables that define the product term. Separate moderation analyses were conducted for organizational support and job relevance. The results are presented in

Table 5. 5000 bootstrap results for PROCESS Model No. 1 simple moderation analysis.

	DV: IU				DV: IU
	Estimate	SE	LL 95% CI	UL 95% CI	Estimate	SE	LL 95% CI	UL 95% CI
PU	0.590 *	0.059	0.474	0.706
OS	0.332 *	0.068	0.198	0.467
PU * OS	0.208 *	0.052	0.310	0.106
PU					0.606 *	0.053	0.502	0.710
JR					0.280 *	0.058	0.167	0.393
PU * JR					0.124 **	0.054	0.231	0.017
Model Fit
F-value	114 *				110 *
R2	0.49				0.48
R2 Change	0.02 *				0.01 **

PEU: Perceived Ease of Use; PU: Perceived Usefulness: OS: Organizational Support; JR: Job Relevance; IU: Intentions to Use E-accounting; * p < 0.01,** p < 0.05.

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The interaction terms for both OS and JR were significant and without having zero in the 95% confidence interval lower and upper bounds. The low and high (mean +/− SD) values of OS and JR were used for the plotting of the interaction graph. The interaction plot of the PU and IU relationship in the presence of OS suggests that the relationship between PU and IU is more significant for high levels of OS compared to the low levels of OS (shown in Figure 2). The slope test identified OS as a moderator for the relationship between PU and IU; that is, the presence of OS boosted the positive relationship between PU and IU.

Similarly, the interaction plot/graph of the PU and IB relationship with reference to JR as the moderator suggests that this relationship is stronger for the high level of JR compared to low levels of JR (shown in Figure 3). The graph shows that the positive impact of PU on IU is improved in the presence of JR.

4.6. Moderated Mediation Analysis

Finally, to simultaneously test the mediation and moderation, we used PROCESS Model 16 again with 5000 bootstrap sampling and 95% biased corrected CI. The results of the moderated mediation analysis identify that there is a significant direct and indirect effect of PEU on IU. Out of the two proposed moderators, only organizational support was significant, while, in the presence of all constructs, job relevance becomes an insignificant moderator. Similarly, the conditional indirect effects (indirect effects in the presence of moderators) of PEU on IU were also insignificant. The results of PROCESS Model 16 are presented in

Table 6. 5000 bootstrap results for PROCESS Model No. 16.

	DV: IU
	Estimate	SE	LL 95% CI	UL 95% CI
PEU	0.180 **	0.076	0.029	0.331
PU	0.426 *	0.072	0.283	0.569
OS	0.241 *	0.077	0.091	0.392
JR	0.158 *	0.062	0.035	0.280
PU * OS	0.151 *	0.060	0.262	0.041
PU * JR	0.015	0.057	−0.105	0.134
Model Fit
F-value	335 *
R2	0.48 *
R2 Change	0.03 *

PEU: Perceived Ease of Use; PU: Perceived Usefulness: OS: Organizational Support; JR: Job Relevance; IU: Intentions to Use E-accounting; * p < 0.01, ** p < 0.05.

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5. Discussion

The present investigation sought to assess determinants of acceptance of digitalization of accounting procedures using a holistic model based on the technology acceptance model (TAM), elaboration likelihood model (ELM), and social exchange theory (SET). Organizational support and job relevance were proposed as second-stage moderators. The results identify that PEU has both a direct effect on IU and an indirect effect through PU on IU. These results are in line with the earlier investigation conducted by Abduljalil and Zainuddin [40] and Le and Cao [41], who identified PU as a partial mediator between the relationship of PEU and IU.

The second finding of the current investigation is related to the significance of organizational support as an important factor that enhances the positive relationship between perceived usefulness and intentions to adopt e-accounting by accounting professionals. This finding is in line with the previous literature on organizational support (i.e., [44,51,52,53]).

The third important finding is related to job relevance. JR was also identified as a significant moderator when treated separately from organizational support. This result is supported by the investigation conducted by Kim and Garrison [55], who also found job relevance to be a significant moderator while testing the TAM for mobile wireless technology adoption.

The final findings are related to the evidence of perceived ease of use and perceived usefulness as important antecedents of intentions for the adoption of e-accounting procedures by accountants. The results also confirm the importance of organizational support and job relevance as moderators that enhance the positive relationship between PU and IU, but when they are treated separately. However, when both moderators were simultaneously tested only organizational support remained significant in enhancing the positive relationship between PU and IU. This finding identifies the importance of organizational support as job relevance becomes insignificant when employees feel supported by the organization. Overall, the constructs presented in the moderated mediation model accounted for a 51% change in intentions to use e-accounting procedures.

6. Managerial and Practical Implications

A sustainable workplace is an outcome of the digitalization of process and procedures. This finding, relates to the significance of organizational support, has important theoretical and practical implications. From a theoretical perspective, with this finding, we generalize SET in the Saudi and e-accounting contexts. Similarly, from a practical perspective, our finding highlighs the role of management in successful implementation and adoption of technology in organizations. Management needs to build trust in employees by providing support. For an effective adoption of e-accounting in organizations, building a trustful environment is important. Organizational support helps to build the trust that is required by employees for taking the risk of integrating computer technologies into practice [53]. Hence, the extent to which management is willing to provide or allocate resources to accounting professionals for the successful implementation and adoption of e-accounting is a critical enabler of their intentions to use technology for the successful completion of tasks.

Similarly, the finding related to the significance of job relevance as moderator also has its theoretical and practical implications. The finding identifies the relevance of an IT system to work performance as an important motivator for the potential users to be actively involved in adopting new technology for making more informed decisions regarding technology’s perceived usefulness and usage intention. Hence, when the accounting professionals perceive e-accounting as relevant to their jobs, they feel more motivated and are more likely to adopt these systems. From a practical perspective, the importance of training and advising before implementing an electronic system to the end-users of technology is highlighted and identified, so that they are aware of its relevance to their job [56].

For the achievement of sustainability of workplace through the digitalization work processes, the current investigation highlighted the importance of the technology acceptance model (TAM), elaboration likelihood model (ELM), and social exchange theory (SET) for the identification of determinants of acceptance of digitalization (e-accounting) at organizational levels in an important emerging market, Saudi Arabia, having a strong focus on digital transformation in its “Vision 2030”. The results identify organizational support as the most critical and important factor for the successful implementation and adoption of computer technologies in organizations. This result is in line with the prior literature [44,45,46] that identified the importance of organizational support. The importance of organizational support in the adoption of digitalization (e-accounting) highlights the role of management in successful implementation digitalization.

7. Limitations and Future Research

There are some important limitations to this report. The first limitation is related to the data collection procedures. Data were collected at a single point in time, which may raise the issue of common method bias. Future research can apply longitudinal or time-lagged data collection design as temporal separation in data collection that will help in controlling common method bias [68]. Secondly, self-report measures were used for data collection, which may result in measuring bias or validity issues. Hence, it is recommended that other methods of data collection, including qualitative methods (i.e., interviews, observation, and focus groups), could be utilized in future research.

Although the results contribute to the academic scope of the literature regarding the antecedents of intentions to use e-accounting procedures by accounting professionals, it is recommended that more in-depth studies should be carried out on the TAM for the identification of critical influential factors that affect intentions to use technology in the workplace. Similarly, future researchers can search for the additional variables, such as user satisfaction, organizational structure, prior training, and/or commitment of employees, to improve the predictability of the proposed model. Similarly, the extension of the proposed model by using these variables as moderators and/or mediators and considering a different industry/country can help in generalizability.