The role of integrated reporting and earnings management on the combined assurance and capital market liquidity relationship

Abstract

Purpose

This study examines the role of integrated reporting (IR) and earnings management (EM) practices on the combined assurance model (CA) and the firms’ capital market liquidity (FCML) performance nexus. Based on a moderated mediation analysis, it examines the channels through which CA quality influences FCML performance.

Design/methodology/approach

The study uses data from the top 100 firms on the Johannesburg Stock Exchange (JSE) based on market capitalisation, and a bootstrap moderated mediation model through Hayes Process Macro was adopted.

Findings

The findings show that although IR quality mediates the CA quality and FCML performance nexus, the mediation is conditional on firms’ practices of EM, implying that the value of CA through IR to capital market participants is more pronounced for firms engaged in high EM practices.

Practical implications

The findings emphasise the importance of the CA model in streamlining assurance processes, reducing assurance costs and enhancing the credibility of financial and sustainability reports, thereby improving capital market performance. Hence, it is a valuable assurance framework for International Financial Reporting Standards (IFRS) S1 and S2 compliance.

Originality/value

This study uniquely lines up the CA model, IR quality and EM practices to project the value relevance and channel(s) through which the effective communication of the CA model influences FCML performance.

Citation

Donkor, A., Trireksani, T. and Djajadikerta, H.G. (2025), "The role of integrated reporting and earnings management on the combined assurance and capital market liquidity relationship", Asian Journal of Accounting Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/AJAR-08-2024-0318

1. Introduction

The combined assurance (CA) model has been suggested to influence firms' capital market liquidity [FCML] (Hoang and Phang, 2021; Phang and Hoang, 2021; Zhou et al., 2019), but the empirical assessments on this issue are scant (Zhou et al., 2019). Hoang and Phang (2021, p. 175), in an experimental setting, concluded that CA’s model of effective communication through integrated reporting (IR) “restores investors perceived reliability of reported information and willingness to invest even when there is, …. manipulated financial reporting”. This study focuses on IR and earnings management (EM) practices through a moderated mediation analysis to explore the channels or conditions that advance the value relevance of the CA model. It empirically assesses whether the value relevance of the CA model through IR quality is more pronounced in a high or low EM practice setting through a mediated moderation analysis.

With the introduction of IFRS S1 (General Requirements for Disclosure of Sustainability-related Financial Information) and IFRS S2 (Climate-related Disclosures), the importance of coordinated assurance practices has become more significant (Aliyu, 2024) as these standards are intended to provide global consistency and comparability in the disclosure of sustainability-related information. The literature generally agrees that assurance of information is a key means of enhancing the quality and credibility of reported information ((IAASB), 2016, 2018; Donkor et al., 2021; Maroun and Prinsloo, 2020; Sierra García et al., 2022; Zorio et al., 2013). Quality assurance plays a pivotal role in the effective and efficient functioning of capital markets (Kolk, 2008). However, the continuous developments in corporate reporting practices (i.e. the introduction of corporate social responsibility (CSR) reports, sustainability (ESG) reports, and IR) have brought to bear some limitations of traditional assurance models in assuring current trends in corporate reporting practices, including assuring compliance with IFRS S1 and S2 ((IAASB), 2016, 2018; Maroun and Prinsloo, 2020; Sierra García et al., 2022). Besides, the separate and uncoordinated assurance models increase the cost of assurance, impacting the efficient functioning of capital markets. On these bases, there have been incessant calls for cost-effective assurance models that effectively coordinate all assurance processes and providers for optimised assurance ((IAASB), 2018) and address issues of information asymmetry (Phang and Hoang, 2021).

Aligned with the signalling theory, the CA model is envisioned as the ideal cost-effective assurance model for current trends in corporate reporting practices (Donkor et al., 2021; Zhou et al., 2019), which coordinates, integrates, and aligns assurance processes to optimize the assurance coverage obtained from all assurance providers within a firm (Hoang and Phang, 2021; Phang and Hoang, 2021; Zhou et al., 2019). The model requires firms to provide detailed statements demonstrating how the different assurance processes, activities and providers have been coordinated for an optimised assurance (IODSA, 2016; Phang and Hoang, 2021). For such a coordinated assurance, especially with the introduction of IFRS S1 and S2, participants of capital markets are assured of more consistent and reliable information for informed decisions (Phang and Hoang, 2021; Zhou et al., 2019).

The effective communication of the CA model (i.e. CA quality) channelled through IR is thus expected to address assurance fatigue and stakeholders’ confusion due to the different assurance opinions on the various aspects of current corporate reporting practices, as has been the case with the traditional assurance models (Decaux and Sarens, 2015; Sarens et al., 2012; Simnett and Huggins, 2015). However, the quality and the economic benefit of such a reporting framework (i.e. IR) may be hampered by the existence of EM practices (Jo and Kim, 2007; Kim and Sohn, 2013), as EM is known to impair the transparency of corporate disclosure, leading to information asymmetry and further impeding the efficient functioning of capital markets (Jo and Kim, 2007; Kim and Sohn, 2013). So far, the literature on the value relevance of the CA model through quality IR and conditioned on EM practices is still scant.

This study focuses on FCML performance to advance the CA model literature by assessing the direct and indirect effect of the CA model on information asymmetry. It assesses the value relevance of the effective communication of the CA model and the channels or conditions through which the model influences FCML performance. It answers the questions, does the effective communication of the CA model through IR quality influence FCML, and does the effect differ among high and low information asymmetry firms? As the CA model is posited to influence the quality of IR (Donkor et al., 2021), and IR influences firms’ capital market performance (Barth et al., 2017; Zhou et al., 2017), IR quality is expected to mediate the CA- FCML performance relationship. However, the mediation is expected to be conditional on the levels of firms' practices of EM, as the level of information asymmetry influences the activities of capital market participants (Ajina and Habib, 2017; Ascioglu et al., 2012; Bar-Yosef and Prencipe, 2013).

The remainder of the paper is structured as follows. Section 2 describes the literature and hypotheses development. It is followed by Section 3, which discusses the methodology. Results and discussions are presented in Section 4, and finally, the conclusion of the study is presented in Section 5.

2. Literature review and hypotheses development

The role of corporate disclosure (i.e. mandatory and non-mandatory) in the effective functioning of capital markets is important (see, Barth et al., 2017; Bernardi and Stark, 2018; Leuz and Wysocki, 2016; Schoenfeld, 2017) in affecting the judgement or perception of stakeholders (Beyer et al., 2010). Assurance, over the years, has served as a credibility-enhancing tool that influences stakeholders’ judgement or perception of the quality of the reported information (Burke and Clark, 2016; Harindahyani and Agustia, 2023; Sierra García et al., 2022; Zorio et al., 2013). Consequently, for the effective functioning of capital markets, quality assurance cannot be overlooked (DeFond and Zhang, 2014; Simnett et al., 2016). Besides, in this era of greenwashing and corporate scandals, stakeholders look for genuine credibility-enhancing models for informed decisions (Cohen and Simnett, 2015; Wang et al., 2019). IFRS S1 and S2 by the International Sustainability Standards Board (ISSB) are pivotal in this context, particularly by introducing comprehensive sustainability and climate-related disclosure frameworks. These standards aim to enhance the reliability and comparability of non-financial information, reinforcing the trust of stakeholders in reported data and aligning financial and non-financial reporting mechanisms (Tirado-Valencia et al., 2024). Since their introduction in June 2023 (i.e. IFRS S1 and S2), over 1,000 companies have started aligning with ISSB standards, while about 30 jurisdictions are actively incorporating ISSB standards into their regulatory structures (IFRS Foundation, 2024) [1]. These rapid changes show a blend of mandated and voluntary progress in climate-related disclosures and a critical step in transitioning from Task Force on Climate-related Financial Disclosures (TCFD) frameworks to globally accepted standards (IFRS Foundation, 2024) [1].

Despite their introduction and rapid acceptance of IFRS S1 and S2, the essence of quality assurance to capital markets cannot be over-emphasised (Maroun, 2018; Simnett and Huggins, 2015). Regardless, the traditional assurance mechanisms seem not adequate for the current needs of capital markets and their participants ((IAASB), 2018; IAASB, 2020; Maroun, 2018; Simnett and Huggins, 2015). The lack of effective coordination among assurance providers (i.e. consultants, internal, and external assurance providers), the separate assurance mechanisms for financial (FR) and non-financial (ESG) reports, and the non-existence of a suitable assurance framework for IR impede assurance quality, limiting its usefulness to stakeholders ((IAASB), 2016, 2018; IAASB, 2020; Richard and Odendaal, 2020; Simnett and Huggins, 2015). Hence, there is a call for a cost-effective assurance model that effectively collaborates all assurance processes and providers to address the present limitations in traditional assurance models for optimised assurance. This is expected to advance the quality of assurance of reported information and the value relevance of assurance to capital markets and its participants (Hoang and Phang, 2021; Phang and Hoang, 2021; Zhou et al., 2019).

The developments of such an assurance mechanism underscore the growing significance of comprehensive frameworks to mitigate information asymmetry and enhance the usefulness of disclosures for stakeholders. In such a situation, the CA model highlights its relevance in ensuring cost-effective integrated assurance across financial and sustainability reports, enhancing credibility, and advancing capital market functionality (Decaux and Sarens, 2015; Zhou et al., 2019). The CA model has been framed to overcome the challenges of existing assurance models and promote assurance and reporting quality through the coordination of all assurance processes and providers for optimised assurance, thereby improving the credibility of reported information (Decaux and Sarens, 2015; Sarens et al., 2012; Zhou et al., 2019). It is expected to advance the quality of current trends in corporate reporting (Donkor et al., 2021; Hoang and Phang, 2021; Phang and Hoang, 2021) and influence the performance of capital markets. The CA model allows organisations to communicate the effective coordination of all assurance providers (i.e. management, internal and external) for effective risk management and internal controls to report to users and to all stakeholders (Hoang and Phang, 2021), leading to improved confidence of capital market participants in the reported information (Hoang and Phang, 2021; Phang and Hoang, 2021; Zhou et al., 2019) by reducing information asymmetry in capital markets.

Following the signalling theory, the effective communication of the coordination of all assurance providers for improved assurance quality is expected to advance firms’ capital market performance, especially on firms’ capital market liquidity performance (Balaciu et al., 2014; Cotter et al., 2011; Leuz and Wysocki, 2016; Schoenfeld, 2017). The effective communication of the CA model is expected to advance the liquidity performance of firms on the capital market. Thus, as the CA model coordinates all assurance processes and assurance providers, capital market participants need not rely on different assurance providers regarding the quality of reported information. This relieves capital markets of extra time and costs in decision-making. In line with that, this study examines the value relevance of the CA model by focusing on the association between CA quality and FCML performance and hypothesises the following.

H1.

CA quality increases firms’ capital market liquidity performance.

Although some literature finds FR and ESG information useful, existing empirical evidence suggests that the inability of firms to interrelate FR with ESG reports affects their value relevance (Cheng et al., 2014; de Villiers et al., 2014), leading to a value trade-off due to the unintegrated nature of the two indispensable reports. The promulgation of IR is geared towards addressing these concerns and enhancing the quality and value relevance of the reported information (Appiagyei and Donkor, 2024; Barth et al., 2017; IIRC, 2013, 2021; Zhou et al., 2017). IR interrelates and connects both FR and ESG information and explains how organisations create and sustain short-, medium-, and long-term values (Barth et al., 2017; IIRC, 2013, 2021; Zhou et al., 2017). This study envisages IR quality to mediate the relationship between the CA model and firms’ liquidity performance on capital markets.

This aligns with the signalling theory that suggests that firms’ market performance improves from the disclosure of relevant and quality information (Balaciu et al., 2014; Cotter et al., 2011). Leuz and Wysocki (2016) indicate that firms’ capital market liquidity is a key beneficiary of quality disclosed information. Several studies support this assertion and posit that the relationship is made possible by the existence of an information asymmetry (e.g. Beyer et al., 2010; Drake et al., 2010; Schoenfeld, 2017). Information asymmetry leads to an adverse selection that guides uninformed or less-informed investors into actions that reduce firms’ market liquidity (Barth et al., 2017). Thus, because of the nature of the information disclosed in IR and quality assurance made possible by the CA model, information asymmetry in the capital market is expected to be affected. The quality of IR is projected to influence the relationship between the CA model and firms’ liquidity performance on the capital market. The study thus proposes the following hypothesis.

H2.

The relationship between CA quality and firms’ capital market liquidity performance is mediated by IR quality.

The practice of EM is identified to increase information asymmetry, leading to negative consequences on FCML performance (Ascioglu et al., 2012; Ajina and Habib, 2017; Bar-Yosef and Prencipe, 2013). Specifically, Ascioglu et al. (2012) postulate that higher levels of EM weaken the quality of earnings reports and disclosures in general, affecting information asymmetry and hence the FCML performance of firms. Quality IR, on the other hand, is found to influence firms' practices of EM (Donkor et al., 2024b; Obeng et al., 2020; Pavlopoulos et al., 2017, 2019) and CA quality advances the quality of the IR (Donkor et al., 2021). Firms' practices of EM should moderate the IR quality and FCML performance. Thus, the influence of IR quality on FCML performance is expected to be conditional on the levels of firms' EM practices. In essence, the value relevance of the CA model through IR quality is expected to be influenced by firms' EM practices. This study thus posits that the mediation role of IR quality in the CA-FCML performance nexus would be conditional on the levels of firms' EM practices.

H3.

The mediation role of IR quality is conditional on firms’ EM practices.

Based on the above, the proposed relationships are depicted as follows.

3. Research method

3.1 Sample size

This study samples firms from the Johannesburg Stock Exchange (JSE) – South Africa, a suitable CA model and IR setting (Donkor et al., 2021, 2024a, b; Stolowy and Paugam, 2018). The JSE is the only exchange that encourages the use of the CA model and mandates IR (Barth et al., 2017; Donkor et al., 2022, 2024a; Zhou et al., 2017). Based on market capitalisation, sample firms are limited to the top 100 firms on the JSE (Barth et al., 2017). Data is gathered from the Bloomberg database and IR reports of sample firms. Firms with incomplete IR assessing the CA and IR quality are excluded. The final sample size is 85 firms for the period of 2011–2020.

3.2 Measurement of variables

Four main variables are of interest in this study: CA quality – the independent variable; IR quality – the mediating variable; earnings management – the moderating variable; and firms’ capital market liquidity performance (FCML) – the dependent variable.

The study followed Zhou et al. (2019) and Donkor et al. (2021) to measure CA quality based on a weighted score. The checklist and scoring scheme by Zhou et al. (2019) is adopted. The measure is based on the effective communication of the combined assurance model, which is the “extent of disclosure of all assurance processes and providers in the CA description contained in IR reports” (Donkor et al., 2021, p. 480). The IR quality is also measured based on the alignment of sample firms’ IR reports to the IR framework. Using a content analysis methodology, a scoring scheme and a checklist by Ahmed Haji and Anifowose (2016) and Zhou et al. (2017) was adopted. EM was measured based on performance-adjusted discretionary accruals (EMp) and the modified cross-sectional (EMc) model of EM (Dechow and Dichev, 2002; Francis et al., 2005). To operationalise the EM measure, a dummy variable was adopted, where 1 is assigned 1 if a firm’s EM score is greater than the median score, otherwise, 0 is assigned. 1 denotes high EM and 0 low EM practice firm.

For robustness, firms’ capital market liquidity performance is assessed based on price and volume spread measures: the Amivest and Amihud liquidity measures (Ali et al., 2016; Amihud et al., 1997; Chang et al., 2008; Donkor et al., 2024a; Lesmond, 2005). Amivest is a volume-based measure that assesses the trading volume associated with a unit change in the stock price (Amihud et al., 1997, p. 382; Lesmond, 2005). Amihud, on the other hand, is a price measure that aligns with the Bid-Ask-spread but negatively relates Amivest measure of firms’ capital market liquidity (Amihud, 2002; Lesmond, 2005). Amihud liquidity measure assesses the absolute daily return to the dollar trading volume. Amivest portrays market resilience; hence, the higher the score, the higher the liquidity performance of a firm. For Amihud, the higher the score, the lower the liquidity performance of a firm (Amihud, 2002; Lesmond, 2005). Aligned with the literature, the Amihud measure is multiplied by 1,000,000,000 while the Amivest measure is divided by 1,000,000,000 to scale the values for easy interpretation (Kim and Lee, 2014; Lesmond, 2005).

These are mathematically expressed as:

${Amivest}_{iy}=\frac{{\displaystyle \sum _{d=1}^{D_{iy}}}{V}_{idy}}{{\displaystyle \sum _{d=1}^{D_{iy}}}\left|R_{idy}\right|}{Amihud}_{iy}=\frac{1}{D_{iy}}{\displaystyle \sum _{d=1}^{D_{iy}}}\frac{\left|R_{idy}\right|}{P_{idy}*V_{idy}}$

where $\left|R_{idy}\right|$ is the absolute daily stock returns of firm i on day d of year y, $V_{idy}$ is the daily trading volume of firm i on day d of year y, $P_{idy}$ is the price of firm i on day d of year y, while $D_{iy}$ is the number of days with available data for firm i in year y.

Control variables are based on firm characteristics, market characteristics, and corporate governance variables identified to influence firms’ capital market liquidity (Ali et al., 2016; Chung et al., 2010). Board size is measured as a natural logarithm of the total number of board members and board independence is assessed as the percentage of non-executive board members to total board size served as the corporate governance variables controlled for. Firm size, leverage and performance are also controlled. Firm size is measured as the natural logarithm of total assets, leverage as total debts to total assets and performance proxied by return on assets (ROA). Market characteristics controlled for include volatility of returns – standard deviation of daily stock returns, price risk – annualised standard deviation of changes in relative price, and price – measured as the natural logarithm of average annual share price (Ali et al., 2016; Chung et al., 2010).

3.3 Model specification

To assess the value relevance of the CA model and the mediating role of IR quality, the study adopted Baron and Kenny’s (1986) mediating approach, as depicted in Figure 1, with a bootstrap indirect effect (Hayes and Rockwood, 2017; Hayes and Scharkow, 2013). Choosing the ideal estimating model (i.e. Pooled OLS, Fixed Effect [FE] or Random Effect [RE]), the study followed the literature (Baltagi, 2013; Clarke et al., 2010; Wooldridge, 2010). Based on the Breusch-Pagan (i.e. X² = 2315.14, p < 0.0000) and Hausman test (i.e. X² = 24.73, p < 0.0033), the FE model was adopted. To alleviate potential issues of correlated omitted variables, the study, following Serafeim (2015), Dal Maso et al. (2017) and Zhou et al. (2019) used the least square dummy variable (LSDV) variance of the FE models as follows;

(1)${FCML}_{it+1}={\alpha }_0+{\lambda }_1{CAQ}_{it}+{\sum \lambda }_i{Control}_{it}+\sum Industry+\sum Year+{\epsilon }_{it}$

(2)${IRQ}_{it}={\alpha }_0+{\lambda }_1{CAQ}_{it}+{\sum \lambda }_i{Control}_{it}+\sum Industry+\sum Year+{\epsilon }_{it}$

(3)${FCML}_{it+1}={\alpha }_0+{\lambda }_1{CAQ}_{it}+{\lambda }_2{IRQ}_{it}*{\lambda }_3{EM}_{it}+{\sum \lambda }_i{Control}_{it}+\sum Industry+\sum Year+{\epsilon }_{it}$

where $FCML$ is firms’ capital market liquidity performance assessed as Amivest and Amihud measures of firms’ capital market liquidity. $CAQ$ is combined assurance quality, $IRQ$ is integrated reporting quality, the mediating variable and $EM$ is the moderation variable of the study. $Control$ variables comprise firm size, leverage, ROA, board independence, board size, price, return volatility and price risk. $\sum Industry$ and $\sum Year$ represent industry and year-fixed effects.

4. Empirical results and analysis

4.1 Summary statistics and correlation analysis

Table 1 presents the summary statistics of the study’s variables. On average, the Amivest liquidity ratio recorded a value of 0.125 with a deviation of 0.197. Amihud measure, on the other hand, recorded a mean of 0.049 with a standard deviation of 0.140. The relatively high mean score of Amivest to Amihud low mean score suggests moderate levels of liquidity on the stock exchange, as high values of Amivest and low values of Amihud portray greater levels of liquidity. The combined assurance quality (CAQ) of firms recorded a mean of 0.213, affirming the early stages of the practice of the CA model. Notwithstanding, a number of the sample firms recorded a high value of 1 for the CA quality measure. IRQ recorded a mean of 0.610 with minimum and maximum scores of 0.050 and 0.870. These scores generally portray that firms have high levels of quality IR reports, although some are still at very low-quality levels. Based on the median score measure, close to 42% of the sample were classified as practising high levels of EM-based on EMp and 37% based on EMc models. These levels indicate moderately high EM practices among sample firms and align with the study of Donkor et al. (2021).

Table 2 examines the correlation among the variables for the study. From Table 2, the established negative relationship between Amivest and Amihud liquidity ratios was affirmed (r = −0.437, p < 0.01). CAQ positively related to Amivest measure of liquidity (r = 0.202, p < 0.01) and negatively to Amihud measured of liquidity (r = −0.260, p < 0.01). The quality of firms’ IR significantly related to Amivest liquidity measure at 0.219 and Amihud liquidity measure at −0.427. The positive and negative associations portray that increases in quality CA and IR relate to increases in firms’ liquidity performances on the capital market. The correlation matrix further affirmed the established positive significant association between CAQ and IRQ (r = 0.350, p < 0.01) (Donkor et al., 2021). EM practices were significantly associated with the Amivest liquidity measure at −0.070 and −0.068, respectively, for Emp and EMc, while they were associated with the Amihud liquidity measure at 0.208 and 0.139. The negative association with Amivest and positive relation with Amihud affirm that EM practices are linked to higher information asymmetry (Ascioglu et al., 2012; Ajina and Habib, 2017; Bar-Yosef and Prencipe, 2013).

The highest correlation value of 0.570 between two control variables (i.e. BOARDS and FIRMS) is closer to the 0.8 rule of thumb for the test of multicollinearity (Kılıç and Kuzey, 2018). Regardless, the highest variance inflation factor (VIF) of 3.95 for the models is below the multicollinearity threshold of 10 (Kılıç and Kuzey, 2018). Hence, there are no issues with multicollinearity.

4.2 Regression analysis and discussions

4.2.1 CA quality and FCML performance

Tables 3 and 4 present the results of the effect of CA quality (CAQ) on FCML performance and the moderated mediating role of IR quality (IRQ) and EM practices. Table 3 presents the results of Amivest, while the results of Amihud measure of FCML performance are reported in Table 4. Bootstrap indirect tests of mediation and moderation are provided in each table.

From Tables 3 and 4, estimating model 1, the essence of quality assurance for firms’ capital market performance is affirmed. Specifically, this study finds CAQ to positively associate FCML performance measured by Amivest liquidity ratio (β = 0.154, p < 0.01) and negatively with Amihud liquidity ratio (β = −0.425, p < 0.01). The results portray that the effective communication of the CA model influences the buy or sell decisions of capital market participants. Thus, CAQ associates with better capital market liquidity of firms.

This implies that the effective communication of the CA model improves firms’ liquidity performance in capital markets. The results align with the general literature on the essence of quality assurance to the capital market; however, it is unique as it focuses on an innovative assurance model that coordinates assurances of all assurance providers for optimised assurance. The findings support those of Phang and Hoang (2021). They, in an experimental setting, conclude that the “communication of combined assurance is effective in increasing favourable investment decisions towards a company with negative financial performance” (Phang and Hoang, 2021, p. 5631).

The use of separate assurance models for the different aspects of current corporate reporting practices is identified to hamper the value relevance of corporate reports ((IAASB), 2018; Cohen and Simnett, 2015; IAASB, 2020; Maroun, 2018; Richard and Odendaal, 2020). Hence, an assurance model that effectively coordinates all assurance processes for quality assurance should influence decisions on capital markets. This study’s findings align with theory, as the model is envisioned to not only assure capital markets participants and other stakeholders on the quality or otherwise of financial and sustainability reports but also on their integration for quality corporate reporting practices and the effective functioning of capital markets (Donkor et al., 2021, 2024a; Hoang and Phang, 2021; Phang and Hoang, 2021; Zhou et al., 2019). Specifically, the study asserts that by effectively coordinating all assurance models (i.e. the CA model), assurance quality improves, leading to reduced information asymmetry through the provision of quality reported information (i.e. quality financial, non-financial and the integration of financial and non-financial information).

With the introduction of IFRS S1 (focused on sustainability-related disclosures) and IFRS S2 (centred on climate-related financial disclosures), the Combined Assurance (CA) model becomes increasingly important. These standards emphasise the need for integrated reporting that combines both financial and non-financial information (Tirado-Valencia et al., 2024), making the CA model’s role in coordinating assurance processes crucial. The CA model ensures cohesive and high-quality assurance across all forms of corporate reporting, aligning with the objectives of IFRS S1 and S2. By improving assurance quality and reducing information asymmetry, the CA model supports transparency in sustainability and climate-related risks, ultimately enhancing the credibility and efficiency of capital markets.

4.2.2 The mediation role of IR quality

The literature postulates that the quality of IR influences firms’ liquidity performance in the capital markets (Barth et al., 2017; Donkor et al., 2024a; Zhou et al., 2017), while the existence of CA quality leads to improved IR quality (Donkor et al., 2021; Hoang and Phang, 2021; Zhou et al., 2019). On these bases, the study assessed the indirect channel of CA quality on FCML performance through IR quality (i.e. Hypothesis 2 – models 2 and 3).

Following the Baron and Kenny (1986) mediating approach with a bootstrap indirect effect, the results affirm a significant indirect effect of CA quality on FCML performance through IR quality. The study’s results on the initial assessment of mediation affirm the view of literature as CA quality is found to influence IR quality “a” (β = 0.111, p < 0.01 and 0.110, p < 0.01 respectively in Tables 3 and 4 columns 2 – model 2) while IR quality affects firms’ capital market liquidity performance (β = 0.128, p < 0.05, and β = 0.142, p < 0.05 for Amivest and β = −0.904, p < 0.01 and β = −0.957, p < 0.01 for Amihud measures of FCML performances – model 3). These results affirm the view of the literature that CA is an appropriate assurance model for quality IR, and quality disclosure is essential for effective capital market performance.

The results of the indirect effect “a*b” (i.e. bootstrapping) (Table 3) project a significant positive effect of CA on firms’ Amivest measure of liquidity through IR quality. From Table 4, the result on the mediating role of IR quality is affirmed by the alternative measure of firms’ capital market liquidity performance – Amihud liquidity ratio. Thus, Table 4 projects a significant negative effect of CA on firms’ Amihud measure of liquidity through IR quality. The finding postulates that CA quality does not only directly influence capital market activities, but it indirectly associates firms’ capital market liquidity performance through IR quality.

4.2.3 The mediated moderation of IR quality through EM

In the presence of high EM practices, does the CA model communicated through IR improve the FCML performance? We empirically address this to advance the value relevance literature of the CA model by assessing the mediated moderation of IR through EM of the CA-FCML performance nexus (model 3).

Aligned with the literature (e.g. Ajina and Habib, 2017; Ascioglu et al., 2012; Bar-Yosef and Prencipe, 2013; Donkor et al., 2024a), the study based on the results reported in Tables 3 and 4 found the practices of EM to worsen FCML performance (β = −0.157, p < 0.01, and β = −0.123, p < 0.01 for Amivest and β = 0.452, p < 0.01 and β = 0.314, p < 0.01 for Amihud measures of FCML performances). However, the study found a positive significant effect of the interaction variables (i.e. IRQ and EM) for Amivest measure (β = 0.234, p < 0.01 and β = 0.194, p < 0.05) and a negative significant effect of the interaction variables (i.e. IRQ and EM) for Amihud measure (β = −0.681, p < 0.01, and β = −0.501, p < 0.05) of FCML performances. These results affirm that the mediation of CA-FCML performance nexus through IR quality is moderated by firms' practices of EM. Thus, the results, as reported in panels A and B of Tables 3 and 4, portray that at higher levels of EM, the effect of CA quality on FCML performance through IR is enhanced. Though the mediated moderation effect holds for high and low levels of firms' EM practices (Donkor et al., 2024b), the results convincingly show that FCML performance is greatly influenced at higher levels of EM practices. Thus, the conditional effect of the focal predictor value and the indirect effect through IR quality is greater at higher levels of EM.

The introduction of IFRS S1 and IFRS S2 further underscores the importance of this result, as these standards emphasise the need for transparent reporting of non-financial risks (Aliyu, 2024; Tirado-Valencia et al., 2024), making the CA model crucial for assuring and aligning financial and sustainability disclosures. As seen in the empirical results, even under high EM conditions, the effective communication of the CA model through IR helps restore investors' trust by addressing information asymmetry and ensuring reliable reporting aligned with IFRS S1 and S2 requirements. This supports the empirical findings of Hoang and Phang (2021, p. 175) who concluded that “the communication of combined assurance can restore investors’ perceived reliability of reported information and willingness to invest even when there are risks of manipulated financial reporting”. Thus, even at higher levels of EM (i.e. information asymmetry) where FCML performance is expected to be negatively affected, the effective communication of the CA model through IR, restores investors’ reliability of reported information and increases their willingness to buy and sell.

The results align with the signalling theory, which deals with information asymmetry problems and explains how decisions are made in the face of such problems (Spence, 1974). Fundamentally, information asymmetry problems are mostly addressed by signalling more and better information to parties with less information (Cotter et al., 2011). In the current trend of corporate reporting, this study finds that an innovative assurance model that integrates all assurance processes for optimised assurance and quality IR are essential tools in dealing with information asymmetry, leading to higher performances on the capital market.

The summary of the hypotheses tests can be seen on Table 5.

5. Conclusion

Although quality assurance is generally useful, the value relevance of quality assurance is impeded by a lack of coordination among the various assurance providers on the different aspects of current trends in corporate reporting practices. Participants in capital markets must rely on several different assurance providers on the different aspects of corporate reports for effective decisions. This hampers the efficient functioning of capital markets. To address this, calls for modern assurance models that effectively coordinate all assurance processes and providers for quality assurance and to meet the needs of capital market participants have been rampant. The introduction of the CA model is a step in the right direction; however, little is known about the value relevance of this innovative assurance model and whether the effective communication of the CA model through IR quality will have a greater influence on FCML performance for settings of high information asymmetry.

Focusing on FCML performance, this study contributes to the literature by assessing the value relevance of the effective communication of the CA model through IR in high and low EM practice settings (i.e. high and low information asymmetry).

Using a unique environment, JSE, 85 sample firms (i.e. from the top 100 JSE firms) and 822 firm-year observations (i.e. 10 years, from 2011 to 2020), the study affirms the value relevance of the CA model even in an information asymmetry setting. The study affirms that the effective communication of the CA model through IR quality is not only value-relevant but also has an even greater influence on FCML performance for high EM practice settings. This outcome empirically affirms Hoang and Phang (2021) experimental study that concludes that the effective communication of the CA model through IR “restores investors perceived reliability of reported information and willingness to invest even when there is, …. manipulated financial reporting”. However, it extends the literature from an empirical perspective using a mediated moderation approach to provide evidence for Hoang and Phang (2021) assertion. It further justifies the essence of this innovative, cost-effective assurance model for the effective and efficient functioning of the capital market.

Such an assurance model relieves capital market participants of extra burden regarding the cost of quality information for decision making. The findings extend the literature to the value relevance of the effective coordination of all assurance processes and providers for an informed decision. This assurance model is expected to be essential mostly for capital markets participants who require non-financial reports (i.e. ESG and IR reports) for decision-making. The effective communication of the CA model should address the need to rely on several assurance processes and providers for informed decision-making on capital markets. The results of the study further affirmed the essence of IR to corporate reporting and capital markets by concluding that IR quality mediates the CA quality and FCML performance nexus.

These outcomes follow the signalling theory, which projects that quality reporting is an essential means of addressing information asymmetry problems. The usefulness of the CA model and IR as the effective integration and aligning of assurance processes of all assurance providers results in quality corporate reporting and efficient capital markets even for high EM practice settings. Practically, the study projects that capital markets and their participants are beneficiaries of firms’ effective implementation and communication of the CA model. Thus, the effective communication of the CA model through IR restores investors' reliance on reported information and willingness to invest even for high EM practice firms. This projects the suitability of the CA model as a cost-effective assurance mechanism for IR and, by extension, current corporate reporting practices, including IFRS S1 and S2. Regarding policy, the findings present to assurance standard setters (e.g. IAASB) the essence of the CA model for corporate reporting and capital market consequences. Hence, there is a need to invest and incorporate the CA model into assurance standards. To stock exchanges and policymakers, the study presents the relevance of the CA model for the effective and efficient functioning of capital markets, hence the need to mandate it or encourage its adoption. Current developments in corporate reporting practices (i.e. IFRS S1 and S2) add to the essence of the study. Thus, the findings also project the relevance of the CA model to IFRS Sustainability Disclosure Standards (IFRS S1 and S2). Whereas these standards aim to improve the quality and consistency of sustainability-related disclosures, which are essential to capital markets, adopting the CA model, can streamline assurance processes for both financial and sustainability reports, thereby reducing costs and enhancing the credibility of their disclosures and, by extension, expedite the global acceptance (i.e. mandatory or voluntary adoption) of the ISSB Standards. This integration is especially important in the era of IFRS S1 and S2, where the harmonisation of financial and sustainability reporting frameworks can promote better capital market performance and boost investor confidence.

From above, the CA model’s value extends beyond a single country or exchange, positioning it as a cost-effective solution to the limitations of existing assurance models. Its implementation and communication can address credibility issues in new corporate reporting frameworks. By harmonising fragmented assurance frameworks, the CA model promotes more coherent and reliable corporate disclosures, potentially boosting investor confidence and improving market efficiency globally.

As a note, the findings are limited to data from one exchange – JSE, although it is a unique and appropriate setting for this study. We call for further assessment of the role of the effective coordination of all assurance providers by the CA model on the quality of assurance and the subsequent effect on the efficient functioning of capital markets from a global perspective. Such an extended outcome is expected to advance standards in assurance for not only FR but also ESG and the current integration of FR and ESG (i.e. IR).

Figures

Figure 1

Study framework

Table 1

Descriptive statistics

Variable	Mean	Std. dev.	Min	Max
AMIVEST	0.125	0.197	0	1.490
AMIHUD	0.049	0.140	0	0.984
CAQ	0.213	0.236	0	1
IRQ	0.610	0.138	0.05	0.870
EMp	0.417	0.493	0	1
EMc	0.365	0.481	0	1
FIRMS	4.419	0.620	2.776	6.328
LEV	0.200	0.154	0	0.761
ROA	0.071	0.085	−0.253	0.780
BOARDS	1.065	0.104	0.778	1.398
BOARDI	0.732	0.117	0.080	0.930
PRISK	0.302	0.106	0	0.850
PRICE	3.819	0.517	2.000	5.520
RETURNV	−1.734	0.134	−2.080	−0.320

Source(s): Created by authors

Table 2

Correlation analysis

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)
(1) AMIVEST	1
(2) AMIHUD	−0.437***	1
(3) CAQ	0.202***	−0.260***	1
(4) IRQ	0.219***	−0.427***	0.350***	1
(5) EMp	−0.070*	0.208***	−0.122***	−0.215***	1
(6) EMc	−0.068*	0.139***	−0.181***	−0.159***	0.361***	1
(7) FIRMS	0.444***	−0.588***	0.197***	0.295***	0.266***	0.186***	1
(8) LEV	0.073**	0.054	−0.072**	0.001	−0.098***	−0.091***	−0.219***	1
(9) ROA	−0.082**	−0.017	−0.109***	−0.112***	0.274***	*087**	−0.269***	−0.168***	1
(10) BOARDS	0.289***	−0.398***	0.229***	0.280***	−0.125***	−0.082**	0.570***	−0.072**	−0.155***	1
(11) BOARDI	0.117***	−0.096***	0.202***	0.206***	−0.147***	−0.071**	0.223***	0.025	−0.117***	0.125***	1
(12) PRISK	−0.089***	0.018	0.049	0.191***	0.091**	0.073**	−0.008	−0.082**	−0.113***	−0.066*	0.027	1
(13) PRICE	−0.201***	−0.529***	0.106***	0.186***	−0.105***	−0.082**	0.297***	−0.189***	0.162***	0.217***	0.024	−0.084**	1
(14) RETURNV	−0.235***	0.242***	0.008	0.128***	0.124***	0.080**	−0.164***	−0.083**	−0.121***	−0.185***	0.027	0.362***	−0.146***	1

Note(s): ^***p < 0.01, ^**p < 0.05, ^*p < 0.1

Source(s): Created by authors

Table 3

CAQ on Amivest liquidity moderated mediation through IRQ and EM

	Amivest	IRQ	Amivest	Amivest
CAQ	0.154***	0.111***	0.129***	0.128***
	(0.024)	(0.018)	(0.024)	(0.024)
IRQ			0.128**	0.142**
			(0.054)	(0.056)
EMp			−0.157***
			(0.048)
IRQ*EMp			0.243***
			(0.077)
EMc				−0.123***
				(0.048)
IRQ*EMc				0.194**
				(0.076)
FIRMS	0.192***	0.047***	0.182***	0.183***
	(0.013)	(0.010)	(0.013)	(0.013)
LEV	0.109***	0.073**	0.090**	0.089**
	(0.040)	(0.030)	(0.039)	(0.039)
ROA	0.299***	0.060	0.285***	0.289***
	(0.070)	(0.053)	(0.069)	(0.069)
BOARDS	0.025	0.191***	−0.008	−0.018
	(0.062)	(0.046)	(0.061)	(0.061)
BOARDI	0.026	0.128***	−0.012	−0.009
	(0.046)	(0.035)	(0.046)	(0.046)
PRISK	0.213**	0.010	0.230**	0.225**
	(0.094)	(0.071)	(0.093)	(0.093)
PRICE	−0.134***	−0.015	−0.132***	−0.132***
	(0.013)	(0.010)	(0.013)	(0.013)
RETURNV	−0.325***	−0.055	−0.321***	−0.321***
	(0.066)	(0.050)	(0.065)	(0.065)
Year effect	Yes	YES	YES	YES
Industry effect	Yes	YES	YES	YES
CONSTANT	−0.926***	−0.076	−0.861***	−0.862***
	(0.144)	(0.108)	(0.142)	(0.143)
R2	0.482	0.387	0.502	0.500
∆R2			0.006***	0.004**
F-stat	29.57	20.12***	28.58***	28.31***
Observations	822	822	822	822
Mean VIF	2.22	2.22	2.24

Conditional effect of focal predictor at values of the moderator (Emp)
	Effect estimate	Boot Se	t	p	95% CI
0	0.129	0.054	2.365	0.018	[0.022, 0.235]
1	0.373	0.067	5.584	0.000	[0.241, 0.503]

Indirect effect (CAQ – IRQ – AMIVEST)
	Effect estimate	BootSE	95% BootCI
0	0.014	0.005	[0.004, 0.024]
1	0.041	0.010	[0.022, 0.063]

Conditional effect of focal predictor at values of the moderator (Emc)
	Effect estimate	Boot Se	t	p	95% CI
0	0.141	0.056	2.546	0.011	[0.032, 0.251]
1	0.336	0.065	5.186	0.000	[0.209, 0.463]

Indirect effect (CAQ – IRQ – AMIVEST)
	Effect estimate	BootSE	95% BootCI
0	0.016	0.005	[0.005, 0.026]
1	0.037	0.010	[0.019, 0.057]

Note(s): The table presents the moderated mediation regression output of the CAQ and FCML performance (Amivest liquidity through IRQ and EM. Variables are winsorised at both 1% and 99% except dummy variables. Standard errors are robust and clustered by firms and reported in parentheses. ^***p < 0.01, ^**p < 0.05, ^*p < 0.1

Source(s): Created by authors

Table 4

CAQ on Amihud liquidity moderated mediation through IRQ and EM

	Amihud	IRQ	Amihud	Amihud
CAQ	−0.425***	0.110***	−0.297***	−0.293***
	(0.073)	(0.018)	(0.071)	(0.072)
IRQ			−0.904***	−0.957***
			(0.161)	(0.165)
EMp			0.452***
			(0.143)
IRQ*EMp			−0.681***
			(0.228)
EMc				0.314**
				(0.141)
IRQ*EMc				−0.501**
				(0.226)
FIRMS	−0.641***	0.045***	−0.590***	−0.592***
	(0.041)	(0.010)	(0.040)	(0.040)
LEV	−0.827***	0.071**	−0.743***	−0.734 **
	(0.120)	(0.030)	(0.117)	(0.116)
ROA	−0.752***	0.069	−0.680***	−0.677***
	(0.214)	(0.053)	(0.206)	(0.206)
BOARDS	−0.078	0.200***	0.131	0.154
	(0.189)	(0.047)	(0.182)	(0.183)
BOARDI	0.111	0.129***	0.288**	0.278**
	(0.140)	(0.035)	(0.135)	(0.136)
PRISK	−1.337***	0.012	−1.388***	−1.359***
	(0.288)	(0.071)	(0.276)	(0.276)
PRICE	−0.432***	−0.014	−0.442***	−0.444***
	(0.040)	(0.010)	(0.039)	(0.039)
RETURNV	1.479***	−0.055	1.440***	1.437***
	(0.203)	(0.050)	(0.193)	(0.194)
Year effect	Yes	YES	YES	YES
Industry effect	Yes	YES	YES	YES
CONSTANT	5.073***	−0.082	4.851***	4.867***
	(0.440)	(0.109)	(0.422)	(0.425)
R2	0.632	0.388	0.667	0.665
∆R2			0.004***	0.002**
F-stat	54.58	20.11***	56.48***	55.95***
Observations	820	822	820	820
Mean VIF	2.22	2.22	2.24

Conditional effect of focal predictor at values of the moderator (Emp)
	Effect estimate	Boot Se	t	p	95% CI
0	−0.904	0.161	−5.610	0.000	[−1.221, −0.588]
1	−1.585	0.198	−8.017	0.000	[−1.974, −1.197]

Indirect effect (CAQ – IRQ – AMIHUD)
	Effect estimate	BootSE	95% BootCI
0	−0.100	0.024	[−0.147, −0.054]
1	−0.175	0.036	[−0.250, −0.109]

Conditional effect of focal predictor at values of the moderator (Emc)
	Effect estimate	Boot Se	t	p	95% CI
0	−0.957	0.165	−5.799	0.000	[−1.281, −0.633]
1	−1.458	0.192	−7.584	0.000	[−1835, −1.081]

Indirect effect (CAQ – IRQ – AMIVEST)
	Effect estimate	BootSE	95% BootCI
0	−0.106	0.025	[−0.156, −0.058]
1	−0.161	0.032	[−0.227, −0.099]

Note(s): The table presents the moderated moderation regression output of the CAQ and FCML performance (Amihud liquidity) through IRQ and EM. Variables are winsorised at both 1% and 99% except dummy variables. Standard errors are robust and clustered by firms and reported in parentheses. ^***p < 0.01, ^**p < 0.05, ^*p < 0.1

Source(s): Created by authors

Table 5

Summary of the hypotheses tests

Hypotheses	Results
H1: CA quality increases firms’ capital market liquidity performance	Supported – CA quality positively associates FCML performance
H2: The relationship between CA quality and firms’ capital market liquidity performance is mediated by IR quality	Supported – The indirect effect “a*b” shows a significant effect of CA quality on FCML performance through IR quality
H3: The mediation role of IR quality is conditional on firms’ EM practices	Supported – Although EM practices worsen FCML performance, the moderation (IRQ*EM) effect was significant, indicating that the mediation role of IR quality is conditional on firms’ EM practices

Source(s): Created by authors

Note

1. https://www.ifrs.org/content/dam/ifrs/supporting-implementation/issb-standards/progress-climate-related-disclosures-2024.pdf