V olume 27 Issue 4 Ar ticle 1 December 2025 The Impact of Cumulativ e Car eer Experience of Internal Contr ol The Impact of Cumulativ e Car eer Experience of Internal Contr ol Managers on Firms' Efficiency in Diff er ent Information Managers on Firms' Efficiency in Diff er ent Information Envir onments Envir onments Inkyung Y oon Gachon Univ ersity , College of Business, South K or ea Hansol Lee Kangwon National Univ ersity , Depar tment of Accounting, South K or ea , hlee@kangwon.ac.kr Dongjoon Choi Chungnam National Univ ersity , School of Business, South K or ea F ollow this and additional works at: https:/ /www .ebrjournal.net/home P ar t of the Accounting Commons , Business Administr ation, Management, and Oper ations Commons , and the Human Resour ces Management Commons Recommended Citation Recommended Citation Y oon, I., Lee, H., & Choi, D . (2025). The Impact of Cumulativ e Car eer Experience of Internal Contr ol Managers on Firms' Efficiency in Diff er ent Information Envir onments. E conomic and Business Re view , 27 (4), 184-198. https:/ /doi.or g/10.15458/2335-4216.1360 This Original Ar ticle is br ought t o y ou for fr ee and open access b y E conomic and Business Re view . It has been accepted for inclusion in E conomic and Business Re view b y an authoriz ed edit or of E conomic and Business Re view . ORIGINAL ARTICLE The Impact of Cumulative Career Experience of Internal Control Managers on Firms’ Efciency in Different Information Environments InkyungYoon a ,HansolLee b, * ,DongjoonChoi c a Gachon University, College of Business, South Korea b Kangwon National University, Department of Accounting, South Korea c Chungnam National University, School of Business, South Korea Abstract This study investigates the effect of internal control (IC) managers’ cumulative career experience on the operational efciency of Korean listed rms between 2018 and 2020. Building on the premise that managers with extensive ex- perience positively inuence ICs and the internal information environment, this study hypothesises that cumulative career experience of an IC manager is also positively associated with a rm’s operational efciency. To empirically assess efciency, this study applies data envelopment analysis (DEA), a nonparametric technique that evaluates relative efciency based on multiple input and output measures. The results suggest that IC managers with greater cumulative experience signicantly enhance a rm’s efciency. Moreover, this effect is more pronounced in rms operating within weaker accounting information environments, where managerial experience plays a critical role in improving efciency. Keywords: Internal control, Internal control manager, Operational efciency, Information environment, Data envelopment analysis (DEA) JEL classication: D02, G34, M10 1 Introduction T he effectiveness of a rm’s internal control (IC), integrated with corporate governance, has re- cently gained increased importance. Environmental, social, and governance (ESG) factors have emerged as critical considerations for businesses, inuencing nancial stability, growth, and stakeholder value. The emphasis on IC among accounting profession- als and researchers intensied following high-prole accounting scandals, such as those involving Enron and WorldCom. In response, the U.S. Congress en- acted the Sarbanes–Oxley (SOX) Act in 2002 to restore market trust and enhance transparency. The SOX Act highlights the critical role of IC in improving the integrity and quality of nancial reporting. Sections 302 and 404 of the SOX Act require management to disclose signicant changes or deciencies in IC and obligate rms to submit an assessment report on the structure and effectiveness of IC, accompanied by an external audit attestation (Securities and Exchange Commission, 2002, 2003). Since the enactment of the SOX Act in 2002, stake- holders have gained the ability to identify IC de- ciencies within companies. Extensive research has explored various topics related to IC, particularly through disclosures of material weaknesses. Nu- merous studies have demonstrated that effective IC improves rm performance, enhances the reliability of nancial information, and promotes compliance with legal requirements (Ashbaugh-Skaife et al., 2007, 2008; Chalmers et al., 2019; Cheng et al., 2018; Feng et al., 2015; Lawson et al., 2017; Li et al., 2010; Ogneva et al., 2007). Additionally, research has highlighted that both the quantitative and qualitative aspects of Received 18 November 2024; accepted 8 September 2025. Available online 1 December 2025 * Corresponding author. E-mail address: hlee@kangwon.ac.kr (H. Lee). https://doi.org/10.15458/2335-4216.1360 2335-4216/© 2025 School of Economics and Business University of Ljubljana. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/). ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 185 IC-related human resources play critical roles in busi- ness operations and performance (D. J. Choi et al., 2021; J. H. Choi et al., 2013; Shin et al., 2017). When examining the inuence of IC-related hu- man resources on a rm’s IC system, it is essential to consider the cumulative career experience of IC managers. These managers are responsible for estab- lishing and maintaining the overall IC framework. As such, their qualications can be a crucial factor in determining both the effectiveness of a company’s IC system and the impact that system has on the rm’s performance. Research on the impact of IC managers’ char- acteristics on rm performance remains relatively limited. Shin and Park (2020) explore the inuence of an IC manager’s tenure and concurrent role as CFO on a company’s efciency. This study extends their work by focusing on the cumulative work ex- perience IC managers have acquired at the current company prior to their appointment, as well as the accounting-related experience gained from previous rms. In contrast to Shin and Park (2020), who emphasise the concurrent roles and tenure of man- agers, this study expands the scope by examining the broader cumulative career experience, incorporating both rm-specic and external accounting experi- ence. Even when newly appointed, IC managers can manage and operate the control system effectively if they develop rm-specic knowledge through ex- tended roles within the company or possess prior experience in IC and accounting from other rms (Coff, 1997; Cohen & Levinthal, 1989; Grant, 1996; Hitt et al., 2001; Kor & Mahoney, 2005; Lazear, 2009; Wang et al., 2009). This study conrms that accumulated experience enhances the capabilities of IC managers, improving the company’s information environment and ultimately contributing to increased operational efciency. Additionally, the experience of IC man- agers proves to be more valuable when the quality of the information environment is suboptimal. This study contributes to the existing literature in several key ways. It offers new insights into the im- pact of IC managers’ characteristics on rm efciency, with a specic emphasis on their cumulative ca- reer experience—an area that has received relatively limited attention. Additionally, the study presents empirical evidence demonstrating that the impor- tance of cumulative career experience becomes more pronounced in environments where the quality of information is weaker. These ndings suggest that IC managers with extensive cumulative experience play a critical role in enhancing a rm’s operational efciency by improving the internal information en- vironment. From a practical perspective, this research highlights the importance of investing in the devel- opment and retention of experienced IC managers, especially in rms with suboptimal information envi- ronments. Furthermore, these results provide useful insights for regulators and policymakers aiming to improve corporate governance and IC standards by emphasising the role of experienced human capital in strengthening operational efciency. The remainder of this paper is structured as follows. Section 2 reviews prior literature and formulates our primary hypotheses. Section 3 outlines the research design and provides descriptive statistics. Section 4 presents the empirical ndings, and Section 5 offers the conclusion. 2 Literature review and research hypothesis Operational efciency is fundamental to prot max- imisation, as it directly inuences overall rm per- formance (Demerjian et al., 2012). The imperative for efciency has intensied in response to mount- ing competitive pressures, fuelled by an expanding number of market participants (Lin & Tsai, 2016) and the accelerating pace of globalisation (Ensari, 2018). This heightened global competition compels rms to pursue operational excellence as a strategic neces- sity (Kulkarni et al., 2019). Recent research highlights that operational efciency is signicantly enhanced by supply chain integration practices (Agyei-Owusu et al., 2022), employee-level operational engagement and training (Al Doghan & Sundram, 2023), and effec- tive working-capital management supported by in- formation technology infrastructure (Deb et al., 2023). These ndings underscore the multifaceted drivers of operational efciency in contemporary rms. Conse- quently, improving operational efciency has become indispensable for maintaining rm viability in in- creasingly dynamic and competitive environments (Samoilenko & Osei-Bryson, 2013). The operational efciency measure employed in this study reects a rm’s ability to optimise the transformation of inputs into outputs, thereby cap- turing its resource utilisation effectiveness (Demerjian et al., 2012; Yu et al., 2018). Traditional measures of rm performance, such as share returns, Tobin’s Q, and return on assets (ROA), are heavily inuenced by external factors, including investor expectations, managerial discretion, and broader market conditions (Faleye et al., 2013). In contrast, the operational ef- ciency metric employed in this study is based solely on the relationship between operational inputs and outputs, thereby enabling a more direct evaluation of how improvements in IC quality, driven by the expertise of IC managers, impact rm performance. As Baik et al. (2013) argue, operational ef- ciency is positively associated with both current and 186 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 future protability, which makes it a reliable indicator of performance that reduces the inuence of exter- nal variables and isolates the contribution of internal managerial characteristics. This study utilises data envelopment analysis (DEA) to measure operational efciency; DEA is a nonparametric efciency ranking score based on a rm’s distance from the Pareto- efcient frontier. This score reects how effectively a rm utilises its operational resources to generate outputs (Mali & Lim, 2021). Firms that convert inputs into outputs more efciently are generally regarded as achieving superior performance compared to their less efcient counterparts (Derouiche et al., 2021). IC managers are tasked with establishing and main- taining an effective IC system, while also assessing and ensuring its efcacy within a rm. Existing re- search highlights the critical role of IC as a key factor in enhancing a rm’s operational efciency, with an emphasis on the importance of the IC manager’s qual- ications in ensuring streamlined operations (Cheng et al., 2018; Shin & Park, 2020). Drawing from hu- man capital theory, studies suggest that the quality of human resources is indispensable in elevating and sustaining IC effectiveness (Pennings et al., 1998; Wang et al., 2009). Human capital characterised by superior knowledge and extensive experience is more likely to provide high-quality services. Such indi- viduals enhance a rm’s operational procedures by optimising resource allocation and designing efcient organisational structures (Williams, 2013). Recent studies have also underscored that human capital in the IC domain is evolving in response to emerging demands, such as ESG reporting and dig- italisation. Moftt et al. (2024) show that rms with superior ESG performance tend to have fewer ma- terial weaknesses in IC systems. This suggests that ESG initiatives are not peripheral but embedded in core risk management functions, highlighting the ex- panded role of IC personnel in ensuring ESG-related reporting quality. Similarly, Feng and Mohd Saleh (2024) nd that the effectiveness of ESG risk man- agement, conditioned by managerial ability, is signif- icantly enhanced when IC quality is high, illustrating the strategic complementarity between human capital and control infrastructure in ESG contexts. Prior research demonstrates that rm-specic knowledge and expertise enhance managers’ ability to address challenges through innovative solutions, grounded in a deep understanding of their organisation (Coff, 1997; Cohen & Levinthal, 1989; Grant, 1996; Wang et al., 2009). Consistent with these ndings, studies on CFOs, who oversee IC systems in the U.S., conrm that a CFO’s attributes, such as nancial knowledge, expertise, and experience, signicantly impact the quality of ICs. For example, Aier et al. (2005) nd a negative relationship between CFO quality, as measured by past and current nancial knowledge, and the incidence of earnings restatements. Similarly, Krishnan (2005) highlights a link between CFO quality and IC quality, showing that high-quality CFOs are considerably less likely to be associated with material weaknesses in ICs. Given the role of CFOs in designing, establishing, and main- taining IC systems in the U.S., these studies suggest that IC managers with rm-specic knowledge and accounting expertise are well-positioned to manage IC systems more effectively and efciently. Individuals in decision-making or managerial po- sitions hold the ability to inuence a rm’s operating systems. Accordingly, when an IC manager possesses extensive cumulative career experience, the effective- ness of the rm’s IC is enhanced, which results in more reliable and accurate internal information. Im- provements in the quality of internal information facilitate more efcient resource allocation (Francis et al., 2009), which, in turn, boosts a rm’s over- all efciency. Firm-specic knowledge and expertise are typically acquired through hands-on experience within the company and specic tasks (Hitt et al., 2001; Kor & Mahoney, 2005; Lazear, 2009). More- over, the required competencies of IC managers now extend beyond traditional accounting expertise. Ditkaew and Suttipun (2023) demonstrate that audit data analytics adoption substantially improves audit quality and continuity, suggesting that digital uency has become a core component of effective IC and as- surance functions. Supporting this trend, guidance from professional standard-setting bodies, such as the Institute of Internal Auditors (IIA, 2021) and the Euro- pean Confederation of Institutes of Internal Auditing (Debruyne, 2022), emphasise the growing expectation for internal audit and control functions to incorpo- rate ESG assurance, digital governance, and data analytics capabilities. These evolving expectations ne- cessitate that IC managers possess a broader portfolio of skills encompassing ESG literacy and analytical prociency. Within this context, cumulative career experience, especially experience that integrates ac- counting expertise and rm-specic knowledge, is likely to enhance the manager’s ability to design and operate effective control systems, thereby improving the rm’s operational efciency. Research on the effects of IC on a rm’s opera- tional efciency has consistently demonstrated that ineffective ICs are more likely to result in errors in internal management reports, which in turn neg- atively affect the rm’s operational decisions. For instance, Cheng et al. (2018) document that rms with IC material weaknesses exhibit lower operational efciency, as measured by frontier analysis, compared ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 187 to rms without such weaknesses. Their ndings reveal that the negative impact of material weak- nesses on operational efciency is more pronounced for rms with a greater demand for high-quality in- formation, more severe weaknesses, and, to some ex- tent, smaller rms. Moreover, their study shows that remediation of material weaknesses leads to improve- ments in operational efciency. Similarly, D. J. Choi et al. (2021) afrm that human resource investment in IC, particularly in the IT department, signicantly en- hances investment efciency by improving the qual- ity of the rm’s information environment. Shin and Park (2020) nd that operational efciency increases when IC managers possess task-related and diverse rm knowledge, consistent with human capital the- ory. These ndings suggest that the establishment and maintenance of effective ICs enhance operational efciency by improving a rm’s internal informa- tion environment, which positively inuences overall performance and decision-making processes. Given that the quality of IC affects a rm’s operational efciency by improving the internal information en- vironment and that the qualitative aspects of IC managers play a crucial role in determining the stan- dard of ICs, the impact of IC managers’ qualitative traits on a rm’s operational efciency is likely to be more pronounced in rms with weaker information environments. H1. There is a positive relationship between the cumu- lative career experience of an IC manager and a rm’s efciency. H2. The positive relationship between the cumula- tive career experience of an IC manager and a rm’s efciency is more pronounced in weak information environments. 3 Research design 3.1 Data sources and sample selection Following the enactment of the SOX Act in the United States, the Financial Supervisory Service (FSS) of Korea revised its accounting regulations. These revisions mandated that listed rms with assets ex- ceeding KRW 50 billion disclose IC information in their annual reports, including material weaknesses. The reform also led to amendments to the External Audit Act of 2003, which now requires detailed re- ports on IC personnel, including department names, personnel counts, the presence of Certied Public Accountants, and their average work experience. In addition, the FSS strengthened disclosure require- ments by mandating rms to report information about IC managers. Firms must disclose the career information of IC managers, including total rm- specic and accounting-related work experience, as well as the qualications and procedures for their appointment and dismissal. These enhanced disclo- sure requirements were designed to encourage rms to appoint IC managers with essential qualications, including rm-specic knowledge and accounting expertise. The objective was to fortify ICs by ensur- ing that IC managers possess the necessary skills to effectively oversee these processes. Korea is the only country that mandates the disclo- sure of such detailed information on IC personnel. Notably, 2018 marks the rst year in which Korean listed rms were required to report detailed infor- mation on IC managers, including their personal backgrounds and professional qualications. As a re- sult, this study meticulously collected data on IC managers from the “Report on the Operation of the IC System,” which is included in the annual reports of rms for the years 2018 to 2020. Financial data and employee counts were obtained from the TS2000 and FnGuide databases, which are comparable to Com- pustat in the United States. After excluding nancial rms, due to their unique characteristics, and rms lacking sufcient data, the nal sample consisted of 4021 rms. Table 1 provides an overview of the sam- ple selection process and its composition. 3.2 Research model The primary objective of this study is to examine the effect of IC managers’ qualications on a rm’s opera- tional efciency. Utilising the research methodologies of Cheng et al. (2018) and Cho et al. (2015), this study applies the following model to test the hypothesis. To control for variables known to inuence efciency and rm-level IC characteristics, and to account for the potential impact of COVID-19, a COVID indica- tor variable is included. The model also incorporates industry and year xed effects. 1 Detailed descriptions 1 To determine the appropriate analytical methodology, the Hausman test (Hausman, 1978) was employed, conrming the xed-effects model as the most suitable approach for the sample. Given the observed variation in the dependent variable, Efciency, across industries, an ANOVA test was subsequently conducted to rigorously assess industry-specic differences. Results indicate signicant variation in Efciency between industries ( FD 40.15, pD .000). Additionally, Bartlett’s chi-square test yielded a value of 352.03 (pD .000), leading to the rejection of the null hypothesis of equal variances across industries. These ndings highlight statistically signicant differences in Efciency across industries within the sample, warranting the inclusion of industry xed effects. Although a random-effects model with industry xed effects was considered, the short sample period poses limitations under the random-effects assumption, which assumes that variations across observations are random (Arellano & Carrasco, 2003). Consequently, a pooled OLS model with year and industry xed 188 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 Table 1. Sample selection and distribution of sample. Panel A. Sample selection process. Sample selection process Obs. Korean listed rms in 2018 to 2020 (KSE and KOSDAQ) 5158 Less: samples without data to compute operational efciency variable 175 Less: samples without internal control manager data 562 Less: samples with fewer than 10 observations by industry 83 Less: samples without other nancial data 317 Total 4021 Panel B. Composition of sample by year. Year Obs. % 2018 1260 31.34% 2019 1346 33.47% 2020 1415 35.19% Total 4021 100.00% of all variables are provided in Appendix A. Efficiency t Db 0 Cb 1 ICAE t ;ICFE t Cb 2 SIZE t Cb 3 LEV t Cb 4 AGE t Cb 5 FCF t Cb 6 FOR t Cb 7 MS t Cb 8 LARGE t Cb 9 OUT t Cb 10 ROA t Cb 11 MB t Cb 12 KSE t Cb 13 COVID t C X INDC X YEARC+ t (1) Efficiency t Db 0 Cb 1 ICAE t ; ICFE t Cb 2 ICAE t ; ICFE t INFO t Cb 3 INFO t Cb 4 SIZE t Cb 5 LEV t Cb 6 AGE t Cb 7 FCF t Cb 8 FOR t Cb 9 MS t Cb 10 LARGE t Cb 11 OUT t Cb 12 ROA t Cb 13 MB t Cb 14 KSE t Cb 15 COVID t C X INDC X YEARC+ t (2) The dependent variable, Efciency, represents a rm’s relative operational efciency. This study con- ceptualises operational efciency as a rm’s ability to convert corporate resources into revenue, based on the denition provided by Demerjian et al. (2012). In alignment with Demerjian et al. (2012), opera- tional efciency is measured using DEA, a widely applied technique for assessing the relative efciency of decision-making units (DMUs), with each rm treated as an individual DMU. Efciency score in the DEA model is calculated as the ratio of output to input. This study employs an input-oriented DEA un- der the assumption of constant returns to scale (CRS), reecting that managers primarily control input lev- els and that rms are assumed to operate at a constant scale within the same industry and year. Consistent with the methodologies of Demerjian et al. (2012) and Cheng et al. (2018), this study uses sales revenue as the output variable. The input variables include the cost of goods sold, selling, general, and administra- tive expenses, net property, plant, and equipment, right-of-use assets, and intangible assets, including research and development (R&D) and goodwill. To examine how the experience of IC managers inuences a rm’s operational efciency, this study utilises manually collected data on IC managers, sourced from the “Report on the Operation of the IC System,” which has been included in rms’ annual reports since 2018. The IC managers’ total accounting- related expertise (ICAE) is measured by their cumula- tive working experience in months. The current rm- related experience (ICFE), also measured in months, captures their rm-specic knowledge. Appendix A provides detailed descriptions of each variable. This study accounts for factors that may affect cor- porate operational efciency and the qualications of IC managers. Furthermore, to address potential sam- ple selection bias associated with focusing on rms that disclose IC manager information and preliminary earnings data, the inverse Mills ratio was calculated and incorporated as a control variable. 4 Results 4.1 Main analysis Table 2 presents the descriptive statistics for each variable. In this study, outliers for all variables are winsorised at the 1% level on both tails. The average Efciency score is .7927. The mean values for ICAE effects was adopted, controlling for essential industry and year effects without relying on the assumptions required in a random-effects model (Wooldridge, 2010). ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 189 Table 2. Descriptive statistics. Variables N Mean Median Max Min SD Efciency 4021 .7927 .7913 1.0000 .3732 0.0613 ICAE 4021 5.1286 5.4381 6.1485 2.4849 0.8845 ICFE 4021 4.6302 5.0499 6.1485 0.6931 1.2158 INFO 4021 .7272 1.0000 1.0000 .0000 0.4455 SIZE 4021 19.2973 19.0633 23.4751 16.3673 1.3584 LEV 4021 .3681 .3666 .9260 .0269 0.2046 AGE 4021 31.2863 26.0000 78.0000 3.0000 17.6377 FCF 4021 .5750 1.0000 1.0000 .0000 0.4944 FOR 4021 .5262 1.0000 1.0000 .0000 0.4994 MS 4021 .0290 .0042 .4681 .0000 0.0721 LARGE 4021 .2833 .2549 .7768 .0499 0.1456 OUT 4021 .2440 .2500 .6667 .0000 0.1613 ROA 4021 .0022 .0189 .3700 .6136 0.1264 MB 4021 1.9271 1.2472 13.6117 0.2917 2.1136 KSE 4021 .3949 .0000 1.0000 .0000 0.4889 COVID 4021 .3519 .0000 1.0000 .0000 0.4776 IMR 4021 .2760 .2669 .9407 .0003 0.1495 Note. (1) All continuous variables are winsorised at the 1% level. (2) Variable denitions are presented in Appendix A. and ICFE, the key variables of interest, are 5.1286 and 4.6302, respectively. These values indicate that, before the natural logarithm was applied, IC managers had an average of 168.78 months of accounting-specic work experience and 102.53 months of tenure within the rm. Table 3 presents the Pearson correlation coefcients. The results indicate that Efciency is signicantly and positively correlated with both ICAE and ICFE, which capture the IC manager’s experience. Additionally, larger rm size (SIZE), older rm age (AGE), and higher free cash ow (FCF) are all positively cor- related with increased efciency, which aligns with previous research on operational efciency. The INFO variable, representing the rm’s information environ- ment, does not exhibit a signicant relationship with either the dependent variable, Efciency, or the inde- pendent variables, ICAE and ICFE. This suggests that the rm’s information environment alone does not signicantly impact its efciency or the IC manager’s experience. However, as shown in the empirical anal- ysis in Section 4, the information environment exerts a differential effect on the relationship between a rm’s efciency and the IC manager’s experience. Table 4 illustrates the direct relationship between IC managers’ experience and a rm’s operational ef- ciency, analysed using the ICAE and ICFE variables. The results indicate that both qualitative aspects of IC managers’ careers, accounting-specic expertise (.0025, tD 2.85) and rm-specic working experi- ence (.0021, tD 3.20), are signicantly and positively associated with operational efciency. Specically, increasing ICAE from the 25th percentile value of 4.828 to the 75th percentile value of 5.743 is associ- ated with an estimated .0023 increase in Efciency. Similarly, increasing ICFE from the 25th percentile value of 3.871 to the 75th percentile value of 5.617 corresponds to an estimated 0.0037 increase in Ef- ciency. These ndings suggest that IC managers with extensive accounting-related expertise and cumula- tive rm-specic knowledge signicantly enhance a rm’s operational efciency. Further analysis was conducted to verify the ar- gument that higher-quality IC managers enhance a rm’s operational efciency by improving the inter- nal information environment through robust ICs. This study incorporates an interaction term between the variables of interest (ICAE and ICFE) and INFO, an indicator variable. INFO was assigned a value of 1 if the discrepancy between preliminary and actual earn- ings was below the industry average, and 0 otherwise. A value of 1 for INFO signies a superior internal information environment. The literature underscores that the accuracy of earn- ings forecasts and preliminary earnings is positively correlated with the quality of internal information (Clinton et al., 2014; Feng et al., 2009). Consequently, if high-quality IC managers play a critical role in enhancing a rm’s operational efciency through improvements in internal information, the positive impact of their cumulative career experience on rm efciency is expected to be more pronounced in en- vironments where the rm’s information quality is comparatively suboptimal. Table 5 shows that the coefcients of the interac- tion terms between the variables of interest (ICAE and ICFE) and INFO are .0046 (tD 2.35) and .0040 (tD 2.80), respectively, both of which are 190 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 Table 3. Pearson correlations. Efciency ICAE ICFE INFO SIZE LEV AGE FCF FOR MS LARGE OUT ROA MB KSE COVID IMR Efciency 1.000 ICAE .018 1.000 (.250) ICFE .123 .172 1.000 (.000) (.000) INFO .027 .004 .011 1.000 (.091) (.821) (.492) SIZE .063 .000 .123 .135 1.000 (.000) (.981) (.000) (.000) LEV .050 .017 .017 .004 .162 1.000 (.002) (.296) (.276) (.800) (.000) AGE .185 .043 .225 .011 .193 .033 1.000 (.000) (.006) (.000) (.481) (.000) (.035) FCF .117 .001 .073 .014 .096 .102 .036 1.000 (.000) (.941) (.000) (.381) (.000) (.000) (.021) FOR .043 .010 .059 .006 .037 .046 .044 .022 1.000 (.007) (.511) (.000) (.685) (.020) (.004) (.005) (.173) MS .003 .048 .052 .021 .535 .134 .094 .043 .052 1.000 (.847) (.002) (.001) (.181) (.000) (.000) (.000) (.007) (.001) LARGE .105 .071 .027 .067 .163 .056 .097 .059 .003 .085 1.000 (.000) (.000) (.091) (.000) (.000) (.000) (.000) (.000) (.853) (.000) OUT .024 .022 .020 .008 .049 .035 .027 .011 .021 .005 .034 1.000 (.133) (.161) (.210) (.626) (.002) (.028) (.091) (.491) (.195) (.745) (.031) ROA .288 .017 .128 .077 .219 .288 .014 .148 .034 .085 .179 .034 1.000 (.000) (.274) (.000) (.000) (.000) (.000) (.375) (.000) (.030) (.000) (.000) (.033) MB .295 .025 .156 .050 .201 .101 .202 .114 .021 .056 .119 .056 .237 1.000 (.000) (.114) (.000) (.002) (.000) (.000) (.000) (.000) (.182) (.000) (.000) (.000) (.000) KSE .104 .024 .129 .038 .590 .117 .329 .080 .006 .291 .132 .054 .063 .178 1.000 (.000) (.127) (.000) (.016) (.000) (.000) (.000) (.000) (.714) (.000) (.000) (.001) (.000) (.000) COVID .100 .021 .025 .014 .000 .002 .014 .015 .016 .010 .002 .010 .035 .136 .025 1.000 (.000) (.180) (.107) (.372) (.998) (.885) (.384) (.330) (.302) (.522) (.885) (.526) (.028) (.000) (.108) IMR .003 .020 .082 .137 .877 .142 .124 .066 .008 .373 .125 .090 .190 .163 .314 .026 1.000 (.862) (.214) (.000) (.000) (.000) (.000) (.000) (.000) (.608) (.000) (.000) (.000) (.000) (.000) (.000) (.099) Note. (1) The number in parentheses is the p value. (2) All continuous variables are winsorised at a 1% level. (3) Variable denitions are presented in Appendix A. ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 191 Table 4. Effect of cumulative career experience of IC managers on rms’ operational efciency. Dependent variable: Efciency (1) (2) Coeff. t Coeff. t ICAE .0025 2.85 ICFE .0021 3.20 SIZE .0140 6.20 .0139 6.17 LEV .0113 2.64 .0113 2.65 AGE .0002 4.06 .0002 3.72 FCF .0080 4.99 .0078 4.87 FOR .0017 1.05 .0014 0.91 MS .1036 5.97 .1055 6.08 LARGE .0376 6.65 .0377 6.68 OUT .0271 5.18 .0268 5.11 ROA .0291 10.02 .0290 9.98 MB .0031 7.20 .0030 6.91 KSE .0109 3.97 .0110 3.99 COVID .0082 4.27 .0081 4.19 IMR .1333 8.54 .1320 8.45 Constant .5136 10.87 .5198 11.05 Industry and year FE Included Included # Obs. 4021 4021 Adj. R 2 .3652 .3655 Note. (1) All continuous variables are winsorised at the 1% level. (2) Variable denitions are presented in Appendix A. *p < .1. **p < .05. p < .01. statistically signicant and negative. These results suggest that the positive impact of IC managers’ cu- mulative career experience on a rm’s efciency is more pronounced in environments where the infor- mation quality is lower. 4.2 Robustness test Given the revision of the lease accounting standard in 2019, consistent comparisons across years, partic- ularly involving 2018, may be limited. To mitigate this concern, the main analysis computed operational efciency on a year-by-year basis. Nevertheless, to further alleviate concerns about comparability, we conducted an additional analysis using only the post adoption period of 2019 and 2020, based on a sub- sample of 2,456 rm-year observations. In Table 6, Columns (1) and (2) address Hypothesis 1, while Columns (3) and (4) relate to Hypothesis 2. The results remain consistent with the main analysis. 2 To address potential concerns about omitted vari- able bias, this study employed a two-stage least Table 5. Effect of cumulative career experience of IC managers on rms’ operational efciency in different information environments. Dependent variable: Efciency (1) (2) Coeff. t Coeff. t ICAE .0059 3.51 INFO .0275 2.67 ICAE*INFO .0046 2.35 ICFE .0051 4.08 INFO .0222 3.22 ICFE*INFO .0040 2.80 SIZE .0137 6.10 .0137 6.08 LEV .0112 2.62 .0119 2.78 AGE .0002 4.02 .0002 3.74 FCF .0080 5.01 .0078 4.84 FOR .0017 1.08 .0015 0.93 MS .1050 6.05 .1058 6.11 LARGE .0367 6.49 .0362 6.39 OUT .0267 5.10 .0268 5.12 ROA .0291 10.03 .0291 10.03 MB .0031 7.09 .0029 6.75 KSE .0108 3.90 .0107 3.90 COVID .0082 4.29 .0081 4.23 IMR .1333 8.54 .1331 8.53 Constant .4991 10.47 .5069 10.72 Industry and year FE Included Included # Obs. 4021 4021 Adj. R 2 .3664 .3671 Note. (1) All continuous variables are winsorised at the 1% level. (2) Variable denitions are presented in Appendix A. *p < .1. p < .05. p < .01. squares (2SLS) procedure to mitigate endogeneity is- sues. In the 2SLS approach, the average wage of employees and total sales were used as instrumen- tal variables for the cumulative career experience of IC managers, based on established literature. Wag- ner (2012) identies the average wage of employees as a suitable proxy for the qualication of human capital within a rm, while Antoncic and Antoncic (2011) nd a signicant association between em- ployee tenure, loyalty, and rm growth, as measured by total sales. Additionally, the validity of these instrumental variables was supported by the Sargan test, which failed to reject the null hypothesis of no correlation with the error term in the main regression, indicating their appropriateness. 3 The results in Table 7, which present the second-stage ndings of the 2SLS using the tted values of ICAE and ICFE, are qualitatively consistent with the primary analysis. This consistency 2 To account for the potential effects of the lease accounting standard revision, we tested our main hypothesis using alternative specications of the efciency measure, including industry-year-based efciency with lease assets, industry-year-based efciency without lease assets, and year-based efciency without lease assets. Results in Appendix B reveal no material differences from the main ndings. 3 In the rst-stage regressions, the instrumental variables, average wage of employees and total sales, yielded coefcients of .122 and .065 for ICAE, and .091 and .105 for ICFE, respectively. The rst-stage F statistic of 10.75 (ICAE) and 15.09 (ICFE), along with the Sargan test results in Table 7, support the validity of the instruments. 192 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 Table 6. Subsample analysis for the post-2019 period. Dependent variable: Efciency (1) (2) (3) (4) Coeff. t Coeff. t Coeff. t Coeff. t ICAE .0025 2.22 .0079 3.67 INFO .0417 3.19 ICAE*INFO .0073 2.92 ICFE .0026 3.13 .0058 3.70 INFO .0240 2.78 ICFE*INFO .0044 2.42 SIZE .0162 5.80 .0159 5.72 .0159 5.70 .0156 5.61 LEV .0100 1.91 .0101 1.93 .0101 1.94 .0107 2.05 AGE .0002 3.70 .0002 3.34 .0002 3.55 .0002 3.33 FCF .0078 3.92 .0075 3.79 .0078 3.92 .0075 3.78 FOR .0014 .74 .0011 0.58 .0015 .78 .0011 0.56 MS .1074 4.95 .1087 5.02 .1103 5.09 .1082 5.00 LARGE .0393 5.62 .0395 5.65 .0386 5.52 .0378 5.40 OUT .0214 3.34 .0211 3.29 .0210 3.28 .0211 3.29 ROA .0258 8.37 .0257 8.34 .0258 8.39 .0260 8.42 MB .0027 5.28 .0026 5.00 .0027 5.19 .0025 4.83 KSE .0122 3.57 .0121 3.56 .0119 3.49 .0119 3.48 COVID .0104 5.38 .0103 5.33 .0103 5.35 .0104 5.40 IMR .1449 7.45 .1423 7.32 .1445 7.44 .1431 7.37 Constant .4725 8.07 .4796 8.23 .4474 7.56 .4668 7.98 Industry and year FE Included Included Included Included # Obs. 2761 2761 2761 2761 Adj. R 2 .3575 .3587 .3598 .3603 Note. (1) All continuous variables are winsorised at the 1% level. (2) Variable denitions are presented in Appendix A. p < .1. p < .05. p < .01. supports the main argument and suggests that en- dogeneity does not signicantly compromise the validity of the results. 4 In addition, this study utilised the system gener- alised method of moments (system GMM; Arellano & Bond, 1991; Blundell & Bond, 1998) to effectively ad- dress endogeneity in panel data and ensure consistent estimates. By incorporating the lagged dependent variable (LagEfciency) as an instrument, a two-step estimation approach was employed to generate the results. The ndings are detailed in Table 8 and ex- hibit consistency with prior analyses. Additionally, the Hansen J test produced a p value above .05, thereby validating the exogeneity of the instrumental variables. 4.3 Additional test This study conducts an additional analysis using ROA as a simpler and more general performance measure, rather than operational efciency, to assess the impact of an IC manager’s cumulative career experience from various perspectives. As shown in Columns (1) and (2) of Table 9, the results indicate that while ICAE does not signicantly affect ROA, ICFE has a signicant positive impact on ROA (.0093, tD 6.14). Furthermore, in Column (4), the ICFE*INFO variable shows a signicant negative effect ( .0083, tD 2.58), suggesting that the less favourable the company’s information environment, the more the IC manager’s experience contributes to improving ROA. These ndings suggest that the accumulated experience of IC managers within a specic com- pany is more effective in enhancing ROA, as ROA, calculated by dividing net income by total assets, captures the unique characteristics of each company more strongly than relative operational efciency. The results also indicate that this effect becomes more pronounced when the company’s information envi- ronment is weaker. 5 Discussion This study investigates the role of IC managers’ cumulative career experience in enhancing rm-level operational efciency, drawing on human capital 4 Since the dependent variable, Efciency, is bounded between 0 and 1, marginal effects may diminish near the boundaries, leading to attenuated OLS estimates. 2SLS mitigates this issue and corrects for potential measurement error, which may explain the larger coefcients observed under 2SLS compared to OLS. ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 193 Table 7. Effect of cumulative career experience of IC managers on rms’ operational efciency: two-stage least squares regressions. Dependent variable: Efciency (1) (2) Coeff. z Coeff. z ICAE_tted .3055 3.34 ICFE_tted .1719 4.97 SIZE .0032 0.24 .0017 0.18 LEV .0537 2.03 .0430 2.31 AGE .0005 1.29 .0016 3.70 FCF .0067 0.76 .0089 1.20 FOR .0004 0.05 .0178 2.33 MS .1871 1.52 .0881 1.26 LARGE .1546 3.32 .1229 4.27 OUT .0725 2.28 .0299 1.39 ROA .0260 1.64 .0160 1.31 MB .0059 2.39 .0049 2.03 KSE .0162 0.95 .0014 0.12 COVID .0180 1.65 .0033 0.42 IMR .1639 1.91 .0559 0.85 Constant .9188 1.91 .0562 0.26 Industry and year FE Included Included # Obs. 4021 4021 Sargan test (p value) .0705 .4098 Note. (1) All continuous variables are winsorised at the 1% level. (2) Variable denitions are presented in Appendix A. p < .1. p < .05. p < .01. theory and leveraging DEA as the primary efciency measure. To ensure robustness and mitigate potential endogeneity concerns, the empirical analysis incor- porates alternative estimation methods, including 2SLS and the system GMM approach. The ndings across these methodologies are consistent and mu- tually reinforcing, offering theoretical and practical implications. First, the DEA-based efciency scores reveal a posi- tive and statistically signicant association between IC managers’ experience and rm operational ef- ciency. This supports the premise that experienced managers, through accumulated rm-specic knowl- edge and functional expertise, improve IC quality, which in turn strengthens the internal information environment and facilitates more effective resource utilisation. The association is particularly pronounced in rms operating in weaker information environ- ments, as evidenced by the signicant interaction terms (Table 5), afrming that managerial experience is more valuable where internal processes are more vulnerable to informational frictions. The 2SLS analysis, which addresses potential omit- ted variable bias, yields coefcient estimates that are directionally and statistically consistent with the main DEA results. Similarly, the system GMM ap- proach, which offers further control over endogeneity by modelling the unobserved heterogeneity, conrms the main ndings. The convergence of results across Table 8. Effect of cumulative career experience of IC managers on rms’ operational efciency: system GMM (generalised method of moments). Dependent variable: Efciency (1) (2) Coeff. z Coeff. z ICAE .0026 2.44 ICFE .0117 2.11 LagEfciency .2940 2.19 .2410 1.81 SIZE .0129 3.31 .0125 3.07 LEV .0126 2.16 .0138 2.22 AGE .0001 2.14 .0000 0.48 FCF .0027 2.07 .0025 1.77 FOR .0002 0.13 .0012 0.55 MS .0710 2.80 .0789 2.78 LARGE .0231 3.00 .0289 3.16 OUT .0183 2.95 .0198 2.85 ROA .0611 5.51 .0553 4.90 MB .0007 1.34 .0004 0.69 KSE .0100 2.36 .0099 2.20 COVID .0102 10.10 .0097 8.68 IMR .1276 4.59 .1224 4.20 Constant .2519 2.02 0.2642 2.27 Industry and year FE Included Included # of Obs. 2450 2450 Hansen J test (p value) .8970 .8450 Note. (1) All continuous variables are winsorised at the 1% level. (2) Applying the system GMM method reduces the nal sample size due to the exclusion of certain observations. p < .1. p < .05. p < .01. these empirical strategies, including DEA, 2SLS, and system GMM, strengthens the validity of the study and reinforces condence in the interpretation of the relationship between IC manager experience and rm efciency. Beyond statistical robustness, these ndings con- tribute to human capital and IC literature by updating the theoretical framing in light of evolving expec- tations for IC personnel. As the role of IC expands to encompass ESG reporting, digital audit tools, and data governance, the evidence supports a broader conceptualisation of human capital, one that incorpo- rates not just traditional accounting knowledge but also adaptability to new regulatory and technological demands. The observed effects in the study are consis- tent with recent literature that highlights the strategic role of IC professionals in navigating post-SOX gov- ernance challenges and ESG accountability. Practically, the ndings carry meaningful implica- tions for corporate governance and talent manage- ment. Boards and audit committees may consider placing greater emphasis on the depth and breadth of IC managers’ professional backgrounds, particularly in rms facing complex operational environments or operating under weak information environments. Regulatory bodies may also benet from recognis- ing the strategic value of IC personnel disclosures 194 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 Table 9. Effect of cumulative career experience of IC managers on rms’ ROA. Dependent variable: ROA (1) (2) (3) (4) Coeff. t Coeff. t Coeff. t Coeff. t ICAE .0022 1.11 .0018 0.46 INFO .0073 0.32 ICAE*INFO .0007 0.16 ICFE .0093 6.14 .0153 5.47 INFO .0494 3.19 ICFE*INFO .0083 2.58 SIZE .0473 9.32 .0466 9.22 .0468 9.22 .0460 9.10 LEV .1875 19.66 .1859 19.58 .1875 19.67 .1849 19.49 AGE .0001 0.56 .0002 1.31 .0001 0.57 .0002 1.30 FCF .0171 4.72 .0161 4.48 .0174 4.81 .0162 4.49 FOR 0.0059 1.65 .0049 1.36 .0060 1.67 .0050 1.39 MS .1556 3.97 .1569 4.02 .1573 4.01 .1582 4.06 LARGE .0878 6.88 .0915 7.21 .0857 6.70 .0877 6.89 OUT .0104 0.88 .0103 0.87 .0105 0.89 .0102 0.87 MB .0074 7.59 .0069 7.13 .0073 7.52 .0067 6.97 KSE .0424 6.82 .0419 6.77 .0421 6.77 .0413 6.68 COVID .0094 2.16 .0090 2.09 .0095 2.19 .0092 2.14 IMR .1283 3.64 .1240 3.53 .1295 3.67 .1266 3.61 Constant .8376 7.85 .8526 8.06 .8311 7.72 .8782 8.26 Industry and year FE Included Included Included Included # Obs. 4021 4021 4021 4021 Adj. R 2 .2370 .2440 .2381 .2463 Note. (1) All continuous variables are winsorised at the 1% level. (2) Variable denitions are presented in Appendix A. p < .1. p < .05. p < .01. in strengthening transparency and accountability frameworks. In summary, the integration of DEA-based ef- ciency measures with several empirical analyses provides evidence that experienced IC managers serve as a key intangible asset, directly contribut- ing to the rm’s operational excellence. The ndings offer valuable practical implications for key stake- holders, including investors, board members, and regulatory authorities, by highlighting the strategic importance of experienced IC managers in enhancing rm efciency. Moreover, the results provide rms with actionable evidence that effective oversight and management of IC personnel can yield tangible oper- ational benets. 6 Conclusion This study investigates the extent to which the cu- mulative career experience of IC managers affects rms’ operational efciency. While IC quality has long been recognised as essential for enhancing the reliability of internal information and supporting ef- fective decision making, relatively little attention has been given to the specic human capital charac- teristics of the personnel responsible for designing and implementing these systems. By focusing on IC managers, this study lls an important gap in the literature and provides evidence on how managerial experience, particularly rm-specic knowledge and accounting-related expertise, can improve rm-level efciency outcomes. The results nd that IC managers’ cumulative ca- reer experience is positively associated with rm efciency. The ndings remain robust across various empirical specications, including 2SLS and system GMM models, which address concerns related to endogeneity. Additionally, the effect is signicantly stronger in rms with weaker information environ- ments, suggesting that managerial experience plays an especially vital role in contexts where the IC system must compensate for poor external or internal infor- mational clarity. This study leverages a unique institutional setting, South Korea’s mandated disclosure of IC manager qualications, to provide evidence that would be dif- cult to obtain in other jurisdictions. This enhances the external validity of the ndings while also sug- gesting policy implications for regulators in other countries. The positive association between IC man- agers’ experience and operational efciency lends support to initiatives encouraging rms to formalise IC roles and ensure that such positions are lled by qualied personnel. ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 195 Moreover, robustness tests, including adjustments for the COVID-19 shock and accounting standard re- visions, indicate that the results are both statistically and economically signicant, validating the robust- ness of the results. Nonetheless, future research could benet from longer panels, broader cross-country comparisons, or more granular categorisations of experience, such as digital uency or ESG-related expertise. In sum, this study offers new empirical evidence that the career attributes of IC managers materially affect operational efciency, particularly in environ- ments where information asymmetry poses a risk. These ndings underscore the strategic relevance of human capital in IC functions and open several path- ways for future research in accounting, governance, and performance management. Conicts of interest The authors declare that they have no known com- peting nancial interests or personal relationships. 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Industrial Management & Data Systems, 118(1), 126–143. https://doi.org/10.1108/IMDS -02-2017-0064 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 197 Appendix A: Variable denitions Variable Denition Dependent variable Efciency Continuous variable of rm efciency, ranging from 0 to 1, for scal year t based on data envelopment analysis (Demerjian et al., 2012) Independent variables ICAE The natural logarithm of the internal control manager’s career in months ICFE The natural logarithm of the internal control manager’s tenure in months INFO Indicator variable that equals 1 if the absolute difference between preliminary operating income and conrmed operating income, divided by sales revenue, is below the industry average; equals 0 if it exceeds the industry average SIZE Natural logarithm of total assets LEV Total liability divided by total assets AGE The number of years a rm has appeared in the database at end of scal year t FCF Indicator variable that equals 1 if the rm’s free cash ow is not negative and 0 otherwise FOR Indicator variable that equals 1 if the rm reports a nonzero value for foreign currency adjustment in scal year t and 0 otherwise MS Percentage of revenue (Sales) earned by rm within its industry for scal year t LARGE Share of ownership held by largest shareholder OUT Ratio of number of outside board members to number of board members ROA Net income divided by total assets at the beginning of the year MB Market value of equity divided by book value of equity KSE Indicator variable that equals 1 if a rm trades its shares on the KSE, and 0 if it trades on the KOSDAQ COVID Indicator variable that equals 1 for the year 2020, which was affected by COVID-19, and 0 otherwise IMR Inverse Mills ratio obtained from rst-stage probit model 198 ECONOMIC AND BUSINESS REVIEW 2025;27:184–198 Appendix B: Various specications of Efciency Panel A. Results based on Efciency including lease assets. Year-based Efciency (Main result in Table 4) Industry-year-based Efciency (1) (2) (3) (4) Coeff. t Coeff. t Coeff. t Coeff. t ICAE .0025 2.85 .0031 2.65 ICFE .0021 3.20 .0027 3.15 Controls Included Included Included Included Industry and year FE Included Included Included Included Adj. R 2 .3652 .3655 .4522 .4526 p < .1. p < .05. p < .01. Panel B. Results based on Efciency excluding lease. Year-based Efciency Industry-year-based Efciency excluding lease excluding lease (1) (2) (3) (4) Coeff. t Coeff. t Coeff. t Coeff. t ICAE .0020 1.29 .0030 2.62 ICFE .0035 3.11 0.0027 3.14 Controls Included Included Included Included Industry and year FE Included Included Included Included Adj. R 2 .3432 .3434 .4575 .4589 p < .1. p < .05. p < .01.