From Intelligent Reporting to Investor Trust: The Mediating Power of Information Transparency
Abstract
The aim of this study is to examine the impact of intelligent financial reporting on investors’ trust with the mediating role of information transparency. In terms of purpose, this research is applied, and in terms of nature and method, it is descriptive–survey and correlational, and it is considered a field study. The statistical population includes financial managers, senior accountants, internal auditors, and financial analysts of listed companies on the stock exchange, and sampling was conducted using a purposive method. The sample size was determined based on Partial Least Squares Structural Equation Modeling (PLS-SEM) criteria. The data collection instrument was a researcher-made standardized questionnaire based on a five-point Likert scale, measuring three main variables: intelligent financial reporting, information transparency, and investors’ trust. The validity of the instrument was confirmed through content validity and Confirmatory Factor Analysis (CFA), while its reliability was assessed using Cronbach’s alpha and Composite Reliability (CR). Data analysis was performed using PLS-SEM approach and SmartPLS software. The findings indicated that intelligent financial reporting has a positive and significant effect on investors’ trust (β = 0.42, t = 5.87). The results also showed that information transparency plays a significant mediating role in this relationship, and the indirect effect of intelligent reporting on investors’ trust was confirmed (β = 0.31, t = 4.92). Model fit indices also indicated an acceptable structural model and adequate explanatory power of the dependent variables (R² = 0.56). Overall, the results suggest that intelligent financial reporting can enhance investors’ trust through improving information transparency. Therefore, modern reporting technologies are most effective when accompanied by transparency mechanisms that help reduce information asymmetry in capital markets.
Keywords:Intelligent financial reportingInvestors’ trustInformation transparencyFinancial informationCapital
market.
1. Introduction
Corporate Social Responsibility (CSR) has been an important component of business strategy in recent years. Researchers and business practitioners have increasingly focused on the relationship between CSR and financial success in emerging countries. CSR refers to a business’s commitment to conducting its operations in a socially and environmentally responsible manner. This indicates that, in addition to generating profits, a business considers its impacts on various stakeholders and society. Scholars have extensively examined the impact of CSR on business success, with mixed results. The relationship between CSR and financial performance varies depending on the context and industry. Empirical evidence and theoretical foundations suggest that CSR and financial outcomes may be positively correlated in developing economies. However, it is essential to recognize that the impact of CSR on financial performance is complex and may not always be immediately apparent. This is because it often involves intangible outcomes and long-term strategic considerations. Observational data from emerging economies have provided insights into the correlation between CSR and financial outcomes. Conflicting claims have been made regarding these outcomes. Studies have identified a favorable correlation. Companies that allocate resources to CSR initiatives, such as community development programs or environmentally sustainable practices, achieve superior financial performance compared with their peers. Furthermore, the implementation of CSR policies can help companies operating in emerging markets mitigate potential risks associated with environmental and social concerns.
As stated by Cheng et al. [1], this, in turn, can enhance their financial stability and ability to withstand challenges. According to previous studies, companies with strong CSR performance may have an advantage in obtaining capital and financing under more favorable terms. Investors have greater confidence in these companies because they perceive them as having lower risk. Consumers in developing markets are becoming increasingly aware of social and environmental issues. Companies that align themselves with these priorities through CSR initiatives may attract more customers, leading to increased sales and revenues. In developing markets, regulatory authorities may encourage or mandate CSR practices. Companies that comply with these regulations may benefit from certain advantages, such as tax exemptions or government contracts.
However, CSR can lead to reduced financial performance for early adopters due to the absence of a robust system for measuring and reporting the benefits of sustainability reporting and disclosure. In addition, substantial investments in CSR activities may divert resources away from core business activities. Cavaco and Crifo [2] argue that engaging in CSR activities that satisfy one group of stakeholders may dissatisfy another group, potentially harming financial performance. Companies operating in developing markets may engage in CSR activities merely to comply with social expectations and government regulations rather than as a result of strategic business decision-making. Empirical evidence in the literature supports these arguments.
Furthermore, there are factors that affect the relationship between CSR and financial performance. The audit committee is an important factor that has received comparatively less attention. The audit committee is responsible for overseeing financial reporting, internal controls, and the company’s risk management. Therefore, for effective corporate governance, the expertise of audit committee members is highly important. This study examines the relationship between CSR and corporate financial performance in the Iranian capital market. In addition, it investigates how audit committee members’ expertise alters the relationship between CSR and business performance in developing markets. The objective of this study is to determine whether audit committee members’ expertise moderates the relationship between CSR and corporate financial performance. This study employs various regression analysis techniques to assess the moderating effect of audit committee members’ expertise on the relationship between CSR and corporate financial performance. By focusing on developing markets, particularly within the distinctive context of regions such as Iran, the findings of this study contribute to the existing literature on CSR and corporate performance. Although the impact of CSR on business performance in developed economies has been extensively examined, our research addresses a significant knowledge gap by investigating how it affects developing markets. Understanding the relationship between CSR and corporate performance in these contexts is crucial because they present both opportunities and challenges for businesses seeking to implement CSR practices.
Furthermore, our findings have practical implications for businesses operating in developing regions. We emphasize the value of having audit committee members who possess the necessary skills and expertise to address the complexities of CSR measurement and reporting. Our research enables businesses to understand how CSR affects their bottom line, communicate CSR strategically, and benefit from the returns generated by their efforts. The knowledge gained from our study can be used by policymakers to develop regulations that encourage CSR in emerging economies. Our research emphasizes the importance of appointing audit committee members with specialized knowledge and calls on policymakers to consider such expertise as a critical factor in overseeing and promoting CSR practices within their regulatory frameworks.
The relationship between audit committees and CSR has received increasing attention in recent years. Audit committees are responsible for overseeing a company’s financial reporting and disclosure and play a key role in ensuring that the company complies with legal and regulatory requirements. Accordingly, audit committee members’ expertise is believed to be a major factor in promoting sustainable performance and disclosure within a company. By providing oversight and guidance regarding social and environmental risks and opportunities, audit committee members with greater expertise can help ensure that companies manage their CSR activities effectively and responsibly. Studies have found a positive relationship between ACE and CSR. For example, a study by Mohammadi et al. [3] found that the financial expertise of audit committees has a positive effect on CSR performance in Iranian companies during 2012–2018. The authors argued that audit committee members with greater expertise are better able to identify and monitor social and environmental risks and opportunities, which can lead to improved CSR performance. They also claimed that other audit committee characteristics, such as size and independence, may affect CSR.
Similarly, in a study by Dwekat et al. [4], it was found that ACE has a positive effect on CSR disclosure for a sample of European companies listed on the STOXX 600 Index during 2012–2018. The authors suggested that audit committee members with greater expertise are better able to understand the importance of CSR disclosure and can work more effectively with management to ensure that the company discloses accurate and relevant information regarding its CSR activities. In contrast, Bualay and Al-Ajmi [5] report a negative relationship between audit committee financial expertise and sustainability reporting in banks in Gulf Cooperation Council countries between 2013–2017. This suggests that, within the context of GCC countries during that period, having a higher level of financial expertise on the audit committee may not have resulted in increased sustainability reporting by banks.
Although the concept of CSR has been widely discussed in theory and practice, there is still no universally accepted conceptual definition of it [6]. In the classification of the components of social responsibility, three dimensions, economic, social, and environmental, have been identified. The measurement of CSR can be conducted in three areas: The interests of shareholders and employees, the interests of society and the public, and environmental considerations. Regarding the interests of shareholders and employees, improved financial performance, reduced operating costs, enhancement of the company’s reputation and brand, increased sales and customer trust, greater productivity and higher quality, reduced need for new regulations, access to capital, improved product safety, and reduced need for new guarantees are considered criteria.
In terms of the interests of society and the public, participation in charitable activities, provision of voluntary employee programs, public participation in general education, employment and assistance programs for homeless individuals, as well as product safety and quality, are taken into consideration. Regarding environmental considerations, increased recycling of materials, greater product functionality and durability, greater use of renewable resources, and the application of environmental management tools in business plans, including life-cycle and cost assessments and environmental management standards, are used as indicators of corporate responsibility.
In this regard, senior corporate managers, through the participation of human and financial resources and through negotiation and reaching common outcomes with other components of civil society, such as nongovernmental organizations, the United Nations, and local and regional governments, can play an important role in implementing organizational social responsibility strategies [7].
On the other hand, measuring market performance in the decision-making process is one of the most important issues in the field of financial economics; therefore, the use of financial and market measures to evaluate corporate performance is essential. In competitive environments, managers should consciously use the performance measurement process to properly direct operations toward progress and in line with the organization’s intended objectives and strategies [8]. Corporate social accountability and adherence to business ethics generate positive signals in society that attract public opinion and, particularly, investors toward the company. Under such circumstances, the company’s share value increases in the market and shareholder wealth is maximized. Therefore, the first hypothesis of our study examines the effect of CSR on financial performance. In line with the main hypothesis of the study, we intend to examine the effect of audit committee expertise on financial performance through CSR. Accordingly, the second hypothesis of the study examines the moderating role of audit committee expertise in the relationship between CSR and financial performance.
2. Liturature
The theoretical framework of this study is based on three key areas, including Information Asymmetry Theory, Agency Theory, and the Technology–Organization–Environment (TOE) framework. These three perspectives, taken together, provide a basis for explaining the mechanism through which financial reporting intelligentization affects investor trust through information transparency. According to Information Asymmetry Theory, there is always a difference between the level of information available to managers and investors in financial markets, which can lead to inappropriate decision-making and increased perceived risk. Within this framework, financial reporting serves as a tool for reducing this information gap. With the introduction of digital technologies into the reporting system, it has become possible to produce and disseminate more accurate, faster, and more verifiable information. Studies indicate that the digitalization of financial reporting, by reducing information asymmetry, contributes to improving disclosure quality and increasing transparency [9]. Agency Theory emphasizes conflicts of interest between managers (agents) and investors (principals). From this perspective, increased information transparency is considered one of the main tools for reducing managers’ opportunistic behavior and strengthening organizational accountability. Financial reporting intelligentization, through the creation of digital monitoring systems, automated transaction recording, and data traceability, enables better monitoring of managerial performance. Recent studies have shown that the use of digital reporting systems increases managerial accountability and strengthens stakeholder trust [10].
The TOE model states that the adoption and effectiveness of new technologies in organizations are influenced by three factors: Technology, organization, and environment. In the context of digital financial reporting, the success of intelligentization does not depend solely on technology but also on organizational readiness, management culture, and institutional requirements. Therefore, the effect of intelligentization on transparency and investor trust may differ across countries. Studies indicate that in environments with weaker infrastructure, the effect of technology on financial transparency is strengthened only when institutional support and strong corporate governance are present [11]. Financial reporting intelligentization involves the application of technologies such as XBRL, ERP systems, artificial intelligence, and real-time data analytics, with the objective of increasing the quality and reliability of financial information. These technologies improve financial transparency by increasing data processing speed, reducing human errors, and improving information accessibility. Findings from empirical studies indicate that the digitalization of financial reporting has a positive and significant effect on information transparency [12]. Information transparency, as one of the most important factors in reducing information risk, plays a determining role in the formation of investor trust. The more accurate, understandable, and accessible financial information is, the more confidently investors make decisions. Studies have shown that increased financial transparency reduces uncertainty, improves investment evaluation, and increases market confidence [13].
Based on the synthesis of the literature, information transparency serves as a key mediating variable that explains the pathway through which financial reporting intelligentization affects investor trust. This means that digital technologies do not, by themselves, have a complete effect on trust; rather, this effect is realized through improving the level of information transparency. In other words, intelligentization improves disclosure quality, strengthens transparency, and ultimately enhances investor trust. Beattie et al. [14] showed that narrative disclosures in annual reports play an important role in enhancing the transparency and accountability of corporate reporting. Their findings highlight the importance of the content and quality of narrative disclosures in meeting the information needs of capital market participants and improving the overall quality of corporate reporting.
DeFond et al. [15] found that mandatory adoption of International Financial Reporting Standards (IFRS) can improve the comparability of financial statements, which in turn enhances the attractiveness of firms to foreign investors. Their findings suggest that greater comparability of financial information can facilitate investors’ evaluation of firms and support more informed investment decisions. Boroujeni et al. [16] examined the relationship between financial reporting quality and firms’ investment decisions, with an emphasis on the governance role of accounting information in the Tehran Stock Exchange. The results of this study indicate that high-quality accounting information, by performing a governance function, helps investors identify inefficient investments and improves the efficiency of capital allocation within companies.
Nozari et al. [17] examined the effect of financial reporting quality on investors’ decisions, focusing on the informational role of earnings volatility. The findings show that financial reporting quality has a positive and significant effect on investors’ reactions, and that earnings volatility can moderate this relationship and increase the influence of financial information. Sheikh [18] examined the effect of artificial intelligence on financial reporting quality, with user trust as a mediating variable. The results indicate that artificial intelligence directly and indirectly improves financial reporting quality, while user trust plays a key role in strengthening this effect. Ghal’e-Ghafi [19] has shown that the transparency of financial reports has a significant effect on increasing investor trust in Iran’s emerging markets. The results indicate that improved disclosure quality and access to information reduce perceived risk and increase the willingness to invest.
Naderi [20] examined the effect of IFRS on financial information transparency and investors’ decision-making. The findings show that the implementation of these standards increases transparency, reduces information ambiguity, and improves the quality of investors’ decision-making. Maoufera [21] examined the effect of digital financial reporting on financial transparency and accountability in public companies. The results indicate that the use of digital financial reporting systems, including XBRL, automated data processing, and real-time access to information, significantly increases financial transparency by improving disclosure quality, increasing information accessibility, and enhancing the timeliness of reports. The findings also show that transparency plays a key role in improving financial accountability and contributes to better corporate governance by strengthening monitoring, improving data integrity, and increasing managerial responsibility. This study emphasizes that the digitalization of financial reporting, in addition to increasing efficiency, strengthens monitoring and accountability mechanisms within companies.
Jamaluddin et al. [22] examine the relationship between financial transparency and the performance of listed companies in Malaysia. The results indicate that both financial transparency and corporate governance transparency have a positive and significant effect on corporate performance. The findings show that increased transparency contributes to improved organizational decision-making. Wu et al. [23] examine the effect of digital transformation on financial reporting and analysis. The results indicate that technology adoption, data integration, skills training, and digital culture improve the accuracy and efficiency of financial reporting. These factors also enhance the quality of financial decision-making. Baudiuro et al. [24] show that the use of accounting technologies such as cloud systems, ERP, and artificial intelligence increases the transparency and accuracy of financial reporting. It was also found that these technologies contribute to increasing investor trust and business sustainability.
Yuro [13] examines the effect of financial reporting transparency on investors’ decision-making. The results indicate that financial transparency increases investor trust, reduces information asymmetry, and improves investment decisions. Gao [9] examines the role of digital transformation in the financial sector and its effect on financial reporting transparency in companies. This study focuses on China and employs an Autoregressive Distributed Lag (ARDL) model over the period from 1990 to 2021. The findings indicate that digital financial development has a positive and significant long-term effect on increasing financial transparency; however, no significant effect on improving transparency is observed in the short term. The results also indicate that the expansion of Information and Communication Technology (ICT) plays a key role in increasing accounting transparency. In contrast, an increase in the corporate income tax rate can reduce financial statement transparency in both the short and long term. Finally, the author suggests that the development of digital financial markets, the expansion of ICT policies, and the improvement of financial literacy in society are among the important strategies for enhancing financial transparency.
Alasouli et al. [25] examine how digital transformation in accounting affects financial transparency and analyze the role of good governance as a mediating variable. The results indicate that the organizational, technical, and human dimensions of digitalization have positive effects on financial transparency. Corporate governance also plays a partial mediating role in strengthening this relationship. Judijanto et al. [12] examine the effect of financial statement digitalization and internal control on reporting accuracy and shareholder trust. The findings indicate that digitalization increases the transparency and accessibility of financial information, while internal control plays an important role in improving reporting accuracy. These factors ultimately strengthen shareholder trust. Li and Li [26] examine how digital transformation affects firms’ capital structure adjustment. The results indicate that digitalization helps accelerate capital structure adjustment, and this effect is strengthened through the reduction of information asymmetry and the enhancement of financial stability. The effect of digitalization is also stronger in firms facing greater financial constraints.
Rachmawati et al. [27] examine the factors affecting financial reporting quality, focusing on ethical leadership, authentic leadership, and organizational ethical climate. This study uses data from 122 accounting professionals and the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The findings indicate that ethical leadership and organizational ethical climate have positive and significant effects on improving financial reporting quality. Organizational ethical climate also plays a mediating role in strengthening the relationship between ethical leadership and financial reporting quality. In contrast, authentic leadership does not have a significant effect on financial reporting quality. Overall, the results indicate that the proposed research model is capable of explaining 58% of the variations in financial reporting quality and highlights the role of ethical factors in enhancing the transparency and quality of financial information. Abdelamer et al. [28] examine the effect of applying digital fair value on the transparency of published financial information. This study shows that the use of market value-based measures for digital assets increases reliability and verifiability and reduces information asymmetry among stakeholders. The findings indicate that the implementation of digital fair value results in more objective and reliable financial information and consequently contributes to improving investors’ decision-making. However, the authors also point to challenges such as market volatility and the absence of integrated valuation standards.
H1: Financial reporting intelligentization has an effect on investor trust.
H2: Financial reporting intelligentization has an effect on investor trust through the mediating role of information transparency.
3. Research Methodology
This study is applied in terms of its purpose and is classified as descriptive-survey research and correlational research in terms of its nature and method of implementation. The main objective of the study is to investigate the effect of financial reporting intelligence on investor confidence, with the mediating role of information transparency. Given that the relationships among the variables are examined in the real-world context of companies listed on the stock exchange and that the study relies on the perceptions and experiences of financial experts, the research falls within the framework of field studies. The statistical population of the study consists of financial managers, senior accountants, internal auditors, and financial analysts of listed companies who, due to their direct access to digital financial reporting processes, are considered the most appropriate individuals to respond to the research questions.
In this study, purposive sampling is employed, and individuals with relevant knowledge and experience in digital financial reporting are selected. The sample size is determined based on the criteria of PLS-SEM or Cochran’s formula and is expected to range from 100 to 300 respondents.
The data collection instrument consists of a standardized researcher-developed questionnaire designed based on the theoretical literature and previous studies and covering three main variables: financial reporting intelligence, information transparency, and investor confidence. The items are measured using a five-point Likert scale ranging from “strongly disagree” to “strongly agree.” The validity of the instrument is examined through expert opinions and accounting professors in terms of content validity, while construct validity is assessed using Confirmatory Factor Analysis (CFA). The reliability of the questionnaire is evaluated using Cronbach’s alpha coefficient and Composite Reliability (CR), with values above 0.70 indicating an adequate level of reliability.
Data are collected through field research by distributing the questionnaire online or in person among the selected sample, and, where necessary, supplementary data are extracted from companies’ financial reports. Data analysis is conducted using Structural Equation Modeling (SEM) and the PLS-SEM approach, which enables the examination of complex relationships among variables and the analysis of both direct and indirect effects. The analytical procedures include descriptive statistics, reliability and validity testing, assessment of multicollinearity, evaluation of the measurement model, evaluation of the structural model, and hypothesis testing through bootstrapping. All analyses are performed using SmartPLS software, version 3 or 4, which provides the capability to accurately analyze causal relationships and mediating effects.
4. Findings
4.1 Descriptive Statistics of the Research Variables
In this section, in order to obtain an initial understanding of the status of the research variables and examine the general tendency of the collected responses, descriptive statistical indicators, including the mean, standard deviation, minimum, and maximum values, are calculated and presented for the main research variables. In addition to describing the data, these indicators provide an appropriate basis for inferential analyses and SEM.
Table 1. Descriptive statistics of the research variables.
This table is shown in the PDF version of the article.
Based on the results of Table 1, the mean values of all research variables are above the midpoint of the Likert scale (3), indicating a relatively favorable status of all three constructs among the respondents. Among these, the “Investor Confidence” variable has the highest mean value of 3.91, indicating a relatively high level of investors’ confidence in financial information and reporting processes within the study context. In contrast, the “Information Transparency” variable, with a mean value of 3.74, has the relatively lowest value, which may indicate the existence of challenges in the accessibility, clarity, or timeliness of financial information. The standard deviation values range from 0.61 to 0.69, indicating a moderate dispersion of the data and an acceptable degree of homogeneity in the respondents’ views. This indicates that although there are differences of opinion among the individuals in the sample, their perceptions are generally concentrated around a relatively consistent level. Furthermore, the minimum and maximum values, ranging from 2.00 to 5.00, indicate an appropriate diversity of responses and full coverage of the Likert scale, which supports the validity of the descriptive description of the data.
Overall, the descriptive statistics indicate that the general research environment, in terms of respondents’ perceptions of financial reporting intelligence and its consequences, is at a favorable level, providing an appropriate basis for testing structural relationships and examining the mediating role of information transparency.
4.2 Validity and Reliability Testing of the Research Instrument
Prior to entering the inferential analysis, examining the validity and reliability of the measurement instrument is of fundamental importance, as ensuring the accuracy, consistency, and validity of the questionnaire is a prerequisite for the validity of the structural modeling results. In this study, the validity of the instrument was examined at two levels, namely content validity and construct validity, while its reliability was assessed using standard indices in SEM. Content validity was assessed through the opinions of experts and specialists in the fields of accounting, auditing, and financial information systems, and the necessary revisions were made to the questionnaire items. Accordingly, the appropriateness of the questions with respect to the theoretical constructs of the study was confirmed. Subsequently, construct validity was examined using CFA within the PLS-SEM approach. At this stage, the factor loadings of the items were examined, and values above 0.70 were considered as the acceptance criterion, indicating an appropriate convergence of the variables with their respective constructs.
Regarding the reliability of the instrument, two main indices, namely Cronbach’s alpha and CR, were used. The Cronbach’s alpha values for all research variables were reported to be above 0.70, indicating appropriate internal consistency of the items and adequate consistency among them. Furthermore, the CR values were also above 0.70, indicating the strong capability of the constructs to measure the latent variables of the study. In addition, the Average Variance Extracted (AVE) index was used to assess convergent validity. The AVE values for all constructs were above 0.50, indicating that more than half of the variance in the observed variables is explained by their corresponding construct. This finding confirms the adequacy of convergent validity in the measurement model. Overall, the results of the validity and reliability tests indicate that the research instrument possesses sufficient validity and reliability and is suitable for testing the hypotheses and analyzing the structural model.
Table 2. Reliability and construct validity indices.
This table is shown in the PDF version of the article.
Based on the results presented in Table 2, all research variables are at a desirable level in terms of reliability. The Cronbach’s alpha coefficients for all three constructs are above 0.80, indicating appropriate internal consistency among the items of each variable and an acceptable level of stability of the measurement instrument.
This finding indicates that the questions designed for each construct consistently measure a common underlying concept. Furthermore, the CR values for all variables are above the standard threshold of 0.70 and range from 0.89 to 0.91, indicating the strong ability of the constructs to explain the latent variables and the appropriate accuracy of the measurement model. These results confirm that the questionnaire structure has reliable internal consistency.
Regarding convergent validity, the AVE values for all constructs are reported to be greater than 0.50, ranging from 0.62 to 0.67. According to the Fornell–Larcker criterion, this indicates that more than 50% of the variance in the items is explained by their corresponding construct. Therefore, the convergent validity of the research instrument is also at a desirable and acceptable level. Overall, the results presented in Table 2 indicate that the measurement instrument has appropriate reliability and convergent validity and is suitable for proceeding to the structural model analysis and hypothesis testing.
4.3 Structural Model and Hypothesis Testing
At this stage of the study, SEM using the PLS-SEM and the bootstrapping method was employed to examine the relationships among the independent, dependent, and mediating variables. The main objective was to test the direct effect of financial reporting intelligence on investor confidence and to examine the mediating role of information transparency in this relationship.
This figure is shown in the PDF version of the article.
Table 3. Results of the structural model and path coefficients.
This table is shown in the PDF version of the article.
The results of the structural model test indicate that the first research hypothesis, which posits a positive and significant effect of financial reporting smartification on investor confidence, is supported. The path coefficient (β = 0.42) and t-statistic (5.87) indicate that an increase in the level of smartification in financial reporting processes significantly enhances investor confidence.
This finding suggests that the use of digital technologies in financial reporting plays an important role in reducing investors’ perceived risk by improving the accuracy, timeliness, and reliability of financial information. Regarding the second hypothesis, the bootstrapping results indicate that financial reporting smartification also has a positive and significant effect on investor confidence through the mediating variable of information transparency (β = 0.31, t = 4.92). This finding highlights the key role of information transparency in strengthening the effect of digital technologies on investor behavior. In other words, smartification has the greatest impact on investor confidence when it leads to greater transparency, accessibility, and comprehensibility of financial information.
Overall, the results of the structural model indicate that both the direct and indirect (mediating) effects of financial reporting smartification on investor confidence are statistically significant, confirming the role of information transparency as a transmission mechanism in this relationship. This finding suggests that technology alone is not sufficient; rather, its effectiveness becomes meaningful within the context of information transparency.
Based on the results presented in Table 3, the relationships among the research variables were examined within the structural model framework using the PLS-SEM approach and the bootstrapping method. The results indicate that the first research hypothesis, concerning the positive and significant effect of financial reporting smartification on investor confidence, is supported. The path coefficient (β = 0.42) indicates a relatively strong relationship, while the t-statistic (5.87) demonstrates statistical significance at the 99% confidence level. This finding indicates that enhancing the level of smartification in financial reporting processes strengthens investors’ confidence in the disclosed financial information by increasing accuracy and the speed of information processing and reducing human errors.
Furthermore, the results related to the second hypothesis indicate that information transparency plays a significant mediating role in the relationship between financial reporting smartification and investor confidence. The indirect effect (β = 0.31), together with the t-statistic (4.92), indicates that this pathway is statistically significant at the 99% confidence level. This result demonstrates that financial reporting smartification does not affect investor confidence solely through a direct pathway; rather, part of this effect is transmitted through enhanced information transparency.
In other words, when digitalization and smartification lead to greater accessibility, clarity, and reliability of financial information, they provide the necessary conditions for reducing information asymmetry and, consequently, increasing investor confidence. Overall, the findings of the structural model indicate that both research hypotheses are supported and that information transparency serves as a key transmission mechanism in the relationship between financial reporting smartification and investor confidence. These results suggest that emerging technologies in financial reporting are most effective when implemented within a framework of information transparency and an efficient disclosure system.
Table 4. Model fit indices.
This table is shown in the PDF version of the article.
Based on the results presented in Table 4, the SRMR index is 0.061, which is below the recommended threshold of 0.08 and indicates a satisfactory fit of the structural model with the empirical data. This result suggests that the proposed model has a relatively low level of error in terms of its correspondence with the observed data and that the theoretical structure of the study is adequately consistent with the collected data. Regarding the explanatory power of the model, the coefficient of determination (R²) for investor confidence is reported as 0.56, which, according to the criteria proposed, represents a moderate-to-strong level of explanatory power. This value indicates that more than half of the variance in investor confidence is explained by financial reporting smartification and information transparency.
In addition, the R² value for information transparency is 0.49, indicating a moderate explanatory power of the model in explaining this construct. Furthermore, the Q² value is 0.38, which is greater than zero and indicates an adequate predictive capability of the structural model. This finding confirms that the model is not only acceptable in terms of overall fit but also has the ability to predict variations in the dependent variables. Overall, the fit indices indicate that the research model has an appropriate level of quality and possesses strong explanatory and predictive capabilities for analyzing the relationships among the research variables.
5. Discussion and Conclusion
The findings of this study indicate that financial reporting smartification has a significant effect on investor confidence and that this effect is strengthened through improvements in information transparency. This finding is consistent with the theoretical foundations of information economics as well as recent studies in the field of digital transformation.
In fact, the digitalization of financial reporting processes increases the speed of data processing, reduces human errors, and enhances the reliability and accessibility of financial information, ultimately leading to a reduction in information asymmetry in capital markets. This finding is consistent with studies such as Gao [9], who examined the role of digitalization in corporate financial transparency in China and found that the development of digital technologies significantly improves financial reporting transparency over the long term.
On the other hand, the results of this study are also consistent with the findings of Alassouli et al. [25], who demonstrated that digital transformation in accounting, when accompanied by appropriate governance mechanisms, leads to improvements in financial transparency. The mediating role of information transparency was also confirmed in the present study, indicating that financial reporting smartification indirectly enhances investor confidence through improved transparency.
This finding is consistent with the perspective of Oti-Akenteng et al. [29], who identify transparency as a key mediating variable linking digitalization to financial governance outcomes. Furthermore, the findings indicate that the digitalization of financial reports not only has a positive effect on transparency but also increases investors’ confidence in financial decision-making by improving the reliability of information and reducing information asymmetry.
This result is consistent with the study published in Heliyon by Li and Li [26], which demonstrates that digital transformation optimizes firms’ financial structures by reducing information asymmetry and enhancing market efficiency. In addition, the findings of this study are consistent with those of Judijanto et al. [12], who demonstrated that the digitalization of financial statements and the strengthening of internal controls play an important role in improving reporting accuracy and enhancing shareholder confidence. This finding emphasizes that technology alone is not sufficient; rather, the presence of control and transparency-oriented infrastructures is a fundamental prerequisite for its effectiveness in financial reporting. Another important finding of this study is the strong confirmation of the mediating role of information transparency. This result indicates that financial reporting smartification has the greatest impact on investor confidence when it leads to improvements in the quality, clarity, reliability, and timeliness of financial information.
This finding is also consistent with the results of Rachmawati et al. [27], who argue that financial reporting quality is strongly influenced by transparency-oriented and ethical factors within organizations. Overall, the findings of this study demonstrate that digital transformation in financial reporting is not merely a technological process but rather a structural transformation of the financial information system. When combined with information transparency, such transformation can significantly enhance investor confidence. Therefore, it can be concluded that the success of financial smartification depends on the simultaneous integration of three key elements: Technology, transparency, and trust. In general, this study confirms that financial reporting smartification has both a positive direct and indirect effect on investor confidence. The indirect effect through information transparency is particularly strong, highlighting the key role of this variable in the conceptual model of the study [30].
These findings indicate that in modern financial environments, digitalization alone is insufficient, and simultaneous attention must be given to the development of information transparency mechanisms and the enhancement of disclosure quality. From a practical perspective, the findings of this study are important for capital market policymakers and financial managers, as they demonstrate that investment in smart financial systems, when accompanied by strengthened information transparency, can contribute to increasing public confidence and reducing investors’ perceived risk.
Abbreviation
PLS-SEM Partial Least Squares Structural Equation Modeling CFA Confirmatory Factor Analysis CR Composite Reliability
TOE Technology–Organization–Environment ARDL Autoregressive Distributed Lag ICT Information and Communication Technology CR Composite Reliability SEM Structural Equation Modeling AVE Average Variance Extracted
Conflict of Interest
The authors declare no competing interests related to this study. The authors alone are responsible for the content and writing of this manuscript.
Data Availability
All relevant data generated or analyzed during this study are included in this published article. No supplementary datasets are available.
Funding
No external funding was received for this research. The study was conducted without financial support from any public, commercial, or non-profit funding organization.
Use of Artificial Intelligence
ChatGPT (GPT-4, OpenAI) was used solely for language editing and structural refinement of the manuscript. The AI tool was not used to generate research ideas, conduct the literature search, interpret findings, or produce any data or mathematical content. The author has reviewed and verified all AI-assisted text and takes full responsibility for the integrity and originality of the work.
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