1. Introduction
Business failures represent a significant challenge many organizations face in recognizing the dangers that could arise from pursuing strategic endeavors (
Drogalas and Siopi 2017). Given the threat that risks pose to an organization’s sustainability or viability, effectively managing these risks is of the utmost importance. Shifts in organizational circumstances, the entities, and technological advances and changes in regulatory/legislative structures have significantly altered the functions and methods of internal auditing (
Chaudhari 2017;
Abidin 2017). Ultimately, adopting and implementing RBIA processes will expand the range of internal audits to encompass comprehensive monitoring of all organizational activities and tasks (
Lois et al. 2021;
Stojanović and Andrić 2016). Basically, structured RBIA processes will reinforce the supervisory responsibilities carried out by internal auditors and enhance the accuracy of what has been audited for documenting official business transactions.
In a similar vein, there has been a transition in the internal audit from procedures to work risks, making the latter a central aspect of proper business governance (
Benli and Celayir 2014;
Dinçer and Hacioğlu 2016;
Mujalli 2024). Simultaneously, modifications in regulatory frameworks and the implementation of new standards in risk management, internal audit, and organizational governance mean that there is now an interplay between internal audit and risk management. This has been made possible by a systematic and structured audit methodology known as RBIA (
Jankensgård 2019;
Wilkinson and Coetzee 2015). RBIA involves evaluating the whole organization’s risk management framework to examine how well management identifies, evaluates, manages, and monitors risks so that risk-based control plans can be established (
Coetzee and Lubbe 2014;
Kabuye et al. 2017;
Raiborn et al. 2017;
Abidin 2017).
Moreover, as IIA recognizes the significance of comprehending the global situation of internal auditing (
Turetken et al. 2020), investigating internal audits in emerging nations will contribute valuable practical insights into this subject. There is an absence of comprehensive research on the factors that affect the RBIA in public sector organizations. While numerous studies have focused on these factors in the private sector, there has been limited examination of them in the public sector. Examples of studies in the RBIA that have concentrated mainly on the private sector are
Abdullatif and Kawuq (
2015),
Apreku-Djan et al. (
2022),
Ayagre (
2014),
Drogalas and Siopi (
2017),
Kirogo et al. (
2014),
Koutoupis and Tsamis (
2009),
Lois et al. (
2021),
Wang et al. (
2023), and
Abidin (
2017). Only restricted research on RBIAs in the public sector has been published. There are variations in the standard of internal auditing in the public and private sectors regarding their size, technology, competency, proficiency, legal regulations, and culture (
Goodwin 2004;
Nerantzidis et al. 2022). Results derived from the private sector cannot be immediately applied to the public sector. Hence, it is imperative to ascertain the occurrences of RBIA implementation within the public sector environment. According to the argument made above, the following research question is formulated:
RQ1. To what extent do various identified factors influence RBIA implementation in public sector organizations in Saudi Arabia?
This study makes significant contributions to the literature. First, it shows that internal auditing practices greatly vary from country to country, with some procedures being mandatory or voluntary, depending on the legislation. Previous empirical work on internal audits has predominantly concentrated on the European, Malaysian, American, and other advanced economic settings. By exploring what is happening in the public sector organizations in Saudi Arabia, this study expands the knowledge base to include the mandatory milieu in an economy that is becoming more powerful as it develops. Secondly, previous empirical research has mainly tested the effects of organization-specific characteristics on RBIA implementation. This study is one of the first to deem risk management, internal control systems, management support, and risk management training as aspects of empirical research that help measure the impact of internal monitoring tools on RBIA implementation in Saudi Arabia.
These above factors are chosen to test the RBIA implementation as recommended by several studies (
Abdullah and Al-Araj 2011;
Arena and Azzone 2009;
Drogalas and Siopi 2017;
Lois et al. 2021;
Sarens et al. 2012;
Sarens and De Beelde 2006;
MetricStream 2018;
Abidin 2017). These factors could focus on the real problems shaping RBIA implementation in Saudi public sector organizations. Consequently, the present study aims to investigate the influence of risk management and associated training, internal control systems, management support, and the internal auditor role on RBIA implementation in these organizations. Thirdly, while earlier studies on this topic primarily chose a qualitative method, this work offers quantitative-based empirical results to substantiate the qualitative findings documented in prior research. Fourthly, prior empirical research on RBIA implementation primarily concentrated on risk evaluation-type activities during audit planning. Insufficient attention was paid to the RBIA implementation processes through the whole gamut of the internal audit procedure, which this paper seeks to rectify.
The remainder of the paper is structured as follows.
Section 2 deals with the literature review to determine the possible factors associated with RBIA implementation and what the research hypotheses are based on.
Section 3 explains the methodology and how each variable is chosen and measured.
Section 4 is the analysis of the results.
Section 5 discusses the empirical results of the current study, and finally,
Section 6 concerns the implications of the findings, limitations, suggestions for future research, and conclusion.
4. Data Processing and Analysis of Results
In academic research, the PLS-SEM technique is becoming more widely recognized and applied, especially in work requiring complicated models that interact with several latent constructs (
Chin 1998;
Hair et al. 2019;
Ockey and Choi 2015;
Shmueli et al. 2019). One of PLS-SEM’s main advantages is its ability to efficiently handle these complicated models, making it ideal for exploratory research where relationships between variables might not yet be well established (
Hair et al. 2019). Compared to traditional statistical methods, PLS-SEM does not need data with a normal distribution, increasing its applicability and usefulness when analyzing real-world datasets that frequently deviate from normalcy (
Hair et al. 2019). Additionally, this method is beneficial for studies with limited sample sizes since it produces reliable findings without needing the large sample sizes that are usually connected with covariance-based SEM (CB-SEM) approaches (
Chin 1998).
PLS-SEM is highly regarded for its efficacy in predictive modeling, which makes it an excellent choice for studies that seek to predict findings or determine the main drivers of target constructs (
Hair et al. 2019). Moreover, its ability to support formative and reflective constructs is also a significant advantage over CB-SEM, which mainly concentrates on reflective constructs (
Kock 2015;
Shmueli et al. 2019). Another crucial component of PLS-SEM’s emphasis on maximizing the explained variation of dependent constructs is a vital aspect of utilized research, where it is essential for understanding the variance in significant constructs (
Hair et al. 2019). Furthermore, the user-friendly interfaces of PLS-SEM methods, for example, SmartPLS, make them more accessible and interpretable (
Hair et al. 2019;
Ogbeibu et al. 2020;
Shmueli et al. 2019). These features collectively create PLS-SEM as a robust and adaptable analysis method for diverse research contexts.
4.1. Measurement Model Results
Figure 2 and
Table 2 show the analysis measurement model results for the internal auditors’ role, the internal control system, management support, risk-based internal auditing, risk management, and risk management training. The assessment utilized a variety of metrics—factor loadings, variance inflation factor (VIF), Cronbach’s alpha (Cα), composite reliability (rho_c), and average variance extracted (AVE)—to verify the data’s reliability and validity. The factor loadings, which demonstrate the associations between items and their respective constructs, ranged from 0.602 to 0.971. This range highlights various relationships, and
Hair et al. (
2019) stated that the AVE value must be equal to or more than 0.50. The VIF values, deployed to assess multicollinearity, were found to be below the established threshold of 5, as suggested by
Kock (
2015), subsequently demonstrating negligible worries in this area.
Concerning internal consistency, as recommended by
Hair et al. (
2019), the researcher assessed Cronbach’s alpha (CA) values, seeking values higher than 0.7.
Table 3 shows that all constructs have CA alpha values greater than 0.7, with metrics varying from 0.790 to 0.916. Nevertheless, due to underestimation problems, Cronbach’s alpha has drawn criticism. For this reason, it is recommended that rho_Alpha be evaluated in addition to CA. For confirmatory purposes (
Hair et al. 2019), rho values should exceed 0.7, and this requirement is met by the acceptable rho_Alpha values shown in
Table 2 for all constructs, where metrics varied from 0.876 to 0.936. In this way, robustness and reliability were affirmed. In terms of convergent validity, a construct is deemed to have it when the AVE values surpass the standard benchmark of 0.5 (
Hair et al. 2019).
Table 2 shows that all reflective measures fulfill the lowest requirement, with the AVE values ranging from 0.559 to 0.829, guaranteeing their convergent validity and indicating strong reliability and validity of the analyzed constructs. This comprehensive evaluation thus supports the overall soundness and robustness of the measurement model devised for this research.
Table 3 summarizes the assessment of the discriminant validity of the all the constructs. The study utilized two distinct methods: the heterotrait–monotrait (HTMT) ratio and the Fornell–Larcker criterion. The HTMT ratios are considerably lower than the conventional cutoff of 0.85 (
Henseler et al. 2015), indicating a high degree of discriminant validity between the constructs. This recommends that these constructs be discrete and that disparate phenomena be evaluated. At the same time, the analysis utilizing the Fornell–Larcker criterion, which includes a comparative assessment of the AVE’s square root values for all constructs against the inter-construct correlations, substantiates this discriminant validity. The AVE’s square root values for all constructs (shown as diagonal elements) exceed the matching off-diagonal values in the corresponding rows and columns. This observation aligns with the criteria suggested by
Fornell and Larcker (
1981). The outcomes displayed in
Table 3 robustly confirm that the constructs are fulfilled. This distinction highlights the robustness and consistency of the measurement model, guaranteeing that every construct contributes to the overall analytical framework.
4.2. Structural Model
The research entailed examining and validating five direct hypotheses, employing path coefficients and statistical significance as measures through SmartPL.S.
Figure 3 and
Table 4 display the findings resulting from the structural model, concentrating on the influence of several factors on RBIA implantation. The data analysis supported four out of the five hypotheses under investigation. The first hypothesis posited a significant impact of MS on the RBIA. The data corroborated this with a path coefficient of 0.176, a T statistic of 2.691, and a
p value of 0.007. The second hypothesis suggested that the IAR positively influences the RBIA. The data validated this hypothesis, as reflected in a path coefficient of 0.155 and a
p value of 0.031. Similarly, the third and fourth hypotheses, which proposed significant positive impacts of RMT and RMS on the RBIA, respectively, were confirmed. This is evidenced by path coefficients of 0.228 and 0.281 and
p values below 0.001 for both hypotheses. Contrastingly, the fifth hypothesis, which theorized a positive influence of the ICS on the RBIA, did not find support in the data. This lack of support is illustrated by a relatively low path coefficient of 0.032 and a non-significant
p value of 0.596, pointing out that the ICS does not have a significant influence on the RBIA as per the data gathered.
4.3. The Explanatory and Predictive Power of the Model
In
Table 5, the R-square value for the RBIA is reported to be 0.402, implying that about 40.2% of the variance in the dependent variable is accounted for by the model. This proportion is a moderate indicator of the model’s explanatory power. Accompanying this, the adjusted R-square value, recorded at 0.389, offers a slightly refined estimate, considering the number of predictors incorporated into the model.
Hair et al. (
2019) recommend that an R-square value in the vicinity of 0.40 is generally perceived as moderate, denoting the model aligns reasonably well with the empirical data. Furthermore, the model’s predictive relevance is gauged through the Q
2 value of 0.239, derived using the formula 1—SSE/SSO, where SSE equals 712.661 and SSO stands at 936.000. The Q
2 value surpassing 0, as in this instance, is strongly suggestive of the model’s predictive capacity for the dependent variable (
Chin 1998). It is essential to recognize that the benchmarks for both R-square and Q
2 values are not rigidly fixed and may vary depending on the particular context of the study and the model’s intricacies. Even lower values might be deemed acceptable in scenarios involving complex models or disciplines where prediction is inherently challenging (
Hair et al. 2019).
The subsequent analysis focuses on the effect size (f2), which quantifies the influence of an independent variable on a dependent variable in the model.
Cohen (
1992) categorizes influence size as small (0.02), medium (0.15), and large (0.35). These classifications assist in ascertaining the magnitude of relationships between latent constructs in the structural model.
Table 5 reveals that the effect sizes for the model’s latent constructs range from small to moderate. This range implies that the interconnections between independent and dependent variables are significant, contributing meaningfully to the explanation of variance within the model. These effect size values further reinforce the model’s reliability, highlighting its robustness in capturing the dynamics of the studied phenomena.
To evaluate the measurement framework robustness, the researcher applied the PLS predict methodology, following the suggestion of
Sarstedt et al. (
2019). Thus, the researcher suggested an advanced calculation procedure tailored to enhance the predictive relevance evaluation of research models in the context of PLS-SEM (
Shmueli et al. 2019). This method emphasizes the need to initially calculate the Q
2 values of the latent variables (LVs). A Q
2 value greater than zero is a prerequisite before calculating the individual items. The proposed procedure delineates a nuanced approach to interpreting a model’s predictive power based on its items’ PLS-LM values. Specifically, if the PLS-LM of a minority or fewer items is smaller, the low predictive power is indicated here. Conversely, if the PLS-LM of all items is higher, it suggests predictive power is absent. In contrast, a lower PLS-LM value for all items suggests greater or higher predictive power in the model. In the context of this study, as presented in
Table 6, the PLS-LM of all items is found to be lower, and the Q
2 predict is greater than zero, which collectively points to a higher predictive power for the model. Furthermore, the study identifies that the Q
2 value for the RBIA stands at 0.239, notably higher than zero. This value signifies a substantial predictive power at the construct level, thereby affirming the robustness and effectiveness of the model in capturing and predicting the dynamics associated with the RBIA. As a result, the predictive relevance and accuracy of the measurement framework can be reliably established, aligning with the results of
Shmueli et al. (
2019).
5. Empirical Results and Discussion
The emphasis is on the change from rules and compliance to efficiency and strategic planning, which has, in turn, led to a growing recognition that meaningful corporate governance mechanisms must strategically resolve relevant disputes. From an agency standpoint, the necessity for operational monitoring of exposure to inherent organization strategy risks has underlined the significance of internal auditing and RBIA processes. The function of internal auditing’s role is to meet the requirement for monitoring management’s behaviors/actions and evaluating the efficiency of organizational mechanisms. In light of this, the internal audit function has recently primarily embraced the risk-based internal auditing strategy as the preferred methodology. Adopting a methodical and disciplined internal auditing method ought to enable internal audit tasks to be efficiently executed. Prior research primarily focused on key success factors related to risk assessment during the audit planning phase (
Allegrini and D’onza 2003;
Benli and Celayir 2014;
Castanheira et al. 2009;
Drogalas et al. 2021;
Drogalas and Siopi 2017;
Koutoupis and Tsamis 2009). In contrast, as proposed by other scholars (
Abidin 2017;
Coetzee and Lubbe 2014;
Lois et al. 2021;
Wilkinson and Coetzee 2015), this study empirically examines the factors linked to RBIA implementation processes throughout all activities of internal auditing, incorporating planning, implementation, and reporting.
This study examined the impact of top management support, the internal auditors’ role in risk management, risk management training, and internal control systems. In this regard, the findings confirm that top management support significantly influences RBIA implementation. This result aligns with other studies (
Alqudah et al. 2019;
Alzeban and Gwilliam 2014;
Endaya and Hanefah 2016).
Alqudah et al. (
2019) assert the need for sufficient internal resources to accomplish more significant efficiency. In such a scenario, the performance of internal auditors can be perceived as being determined by senior management adequately empowering them.
Alzeban and Gwilliam (
2014) discovered that senior management support is a crucial driver of the effectiveness of internal auditing. Once the internal auditing departments in the Saudi Arabian public sector organizations receive support from senior management, this will lead to efficiently performing the duties and accountabilities of internal auditing based on risk management effectiveness. Hence, prioritizing improving the efficiency of internal auditors becomes essential as it guarantees proper resource allocation and the organization’s commitment.
The finding of the role of internal auditors in risk management exerts a significant influence on RBIA implementation. This finding is consistent with other studies (
Abdullatif and Kawuq 2015;
Lois et al. 2021;
MetricStream 2018). As
Abdullatif and Kawuq (
2015) discovered, internal auditors appear to reasonably comprehend essential workplace strategies and tasks, although there is room for enhancement.
MetricStream (
2018) recommended that internal auditors typically report to top management about risks threatening the organization’s viability, so this issue should be emphasized. Thus, substantial endeavors are underway to enhance the monitoring, evaluation, and reporting of the amount and efficiency of risk management and the mechanism of internal control. This enables internal auditing to meet its enlarged role by promoting control consciousness and reinforcing an honest, trusted, and dependable risk management mechanism (
MetricStream 2018).
The finding for risk management training significantly influences RBIA implementation, and it is consistent with what
Lois et al. (
2021) reported. The competency of internal auditing plays a vital role in the RBIA implementation process. Managers in Saudi Arabian public sector agencies believe that training in risk management contributes to developing an audit environment concentrating on risk management, establishing accurate insights concerning risk management, and improving internal auditing quality and the procedures of risk management. All of these simplify and make RBIA implementation suitable, and it is evident that the implementation is well established.
The finding of risk management is that it has a significant influence on RBIA implementation, and it concurs with prior studies (
Abidin 2017;
Coetzee and Lubbe 2014;
Lois et al. 2021;
Sarens et al. 2009). The risk management process enhances risk consciousness and a risk-concentrated culture. Creating a structured framework for risk management duties and processes encourages management to take accountability or responsibility for more efficient practices in risk management (
Goodwin-Stewart and Kent 2006). A more risk-averse culture supports the department’s administration to consider risk exposure in all decisions and actions. The findings support the view expressed by
Abidin (
2017) and
Lois et al. (
2021) that an updated system incorporating risk management encourages a resilient risk-taking milieu and offers a solid basis for the RBIA’s implementation.
Thus, there is room for supporting the internal audit’s concentration on vital risks and the sufficiency of risk management procedures, which are essential for appropriate RBIA implementation. It also seems that the public sector organizations in Saudi Arabia have adequate procedures for creating a standardized risk management system. It is obvious that substantial enhancements are required to explicitly state the duties and accountabilities as well as procedures of the risk management mechanism. This requires the presence of a risk management-type administrator or a separate risk management unit within the department, as noted by
Crawford and Stein (
2002), and operates in such a way that it facilitates the internal auditors’ role in supporting risk management policies (
Woods 2007).
The last finding relates to the internal control system and has an insignificant influence on RBIA implementation. It is consistent with other research (
Abidin 2017;
Lois et al. 2021;
Sarens et al. 2009). They highlight the weakness of risk-identification control systems and the lack of a robust control setting in Saudi public sector organizations. Nevertheless, in organizations, ongoing monitoring of the internal control mechanism is an encouraging outcome. As
Fernández-Laviada (
2007) emphasizes, the concentration should be on enhancing internal control systems and creating a workplace that prioritizes control and risk.
Moreover, the absence of a substantial influence of the internal control system on the RBIA can be attributed to various variables, such as the particular characteristics and intricacies of Saudi Arabia’s public sector organization context. Internal control systems in Saudi Arabia’s public sector organizations frequently encounter obstacles like inflexible structures, legislative limitations, and varied interests of stakeholders. These issues might restrict their ability to support RBIA procedures effectively. Furthermore, resource limitations, the culture of the organization, and political pressures may additionally impact the development and incorporation of risk-based techniques in public sector organizations.
6. Implications, Limitations, Recommendation Avenue for Future Research, and Conclusion
In short, the findings support the anticipation from previous studies. There is a significant relationship between management support, the internal auditors’ role in risk management, risk management training, the risk management system, and risk-based internal auditing implementation. More importantly, the study found no significant connection between the internal control system and the RBIA in Saudi Arabia’s public sector organizations. However, this finding appears to emphasize the significance of taking contextual variables and organizational dynamics into account when executing risk-based auditing practices in Saudi Arabia’s public sector organizations. Moving forward, I acknowledge the necessity for additional investigation to examine and comprehend the particular obstacles and enablers of the RBIA in the public sector environment. By obtaining a more thorough understanding of these aspects, further studies can offer practical suggestions and tactics for improving the efficiency and relevance of RBIA procedures in public sector organizations.
These research findings have important implications for regulatory authorities and the profession of internal auditing in Saudi Arabian public sector organizations. They provide valuable insights into adopting a comprehensive and structured approach to risk-based auditing by internal auditors. Embracing a more structured approach to the RBIA can improve the internal auditors’ ability to mitigate inherent risks in strategic requirements and business processes effectively. This, in turn, can lead to an enhanced quality of work within internal audit teams, reinforcing more operative monitoring tasks. From a practical and societal viewpoint, establishing an operational internal monitoring system and achieving higher-quality internal auditing work that can help reduce risks hindering the attainment of organizational goals is highly desired. It can also reduce the temptation to manipulate financial information and enhance the quality and integrity of financial reports and statements.
The current study possesses specific limitations that create avenues for future research. To enhance the findings’ generalizability, given that all participants in this study work in Saudi Arabian public sector organizations, further research should be carried out to explore factors associated with the RBIA’s implementation in countries where diverse cultural backgrounds or circumstances are evident and regulatory/legislative rules greatly determine the RBIA’s implementation and practices. Moreover, future research could investigate whether these findings differ from industry to industry.
In summary, this empirical study, following the present literature, underscores the implications of the RBIA’s implementation as a structured approach. This approach enables internal auditors to offer valid consulting services and assertions of financial matters regarding the appropriate risk management strategy and the internal control system. It should be noted that, ultimately, organizational accountability rests with the management.