Earticle

Machine translation (MT) output falls short of human translation (HT) in terms of accuracy and readability, despite continued technological advances in its field. Against this backdrop, significant attention has recently been directed toward machine translation post-editing (MTPE), where a text pre-translated by an MT engine is post-edited by a human translator to meet client needs. In this study, a text translated from English to Korean via MT was post-edited, and the post-edited output was analyzed to identify any errors that were not properly corrected. The accuracy of the post-editing process was then quantitatively analyzed against HT of the same text. The HT group was found to spend approximately 1.5 times more time on average compared to the MTPE group. The post-editing accuracy, i.e., the ratio of corrected errors to the total number of errors, tended to increase as more time was spent on the task. The average post-editing accuracy of the MTPE group was 39.6%, significantly lower than the translation accuracy of the HT group at 73.6%. This suggests that even trained individuals find it challenging to thoroughly identify and correct accuracy errors in densely packed, machine-translated technical texts.

A previous study evaluated the quality and productivity of machine translation post-editing (MTPE) for published science-technology articles classified under Reiss’ informative text type. MTPE accuracy was compared against human translation (HT) accuracy in that study. This study succeeds that study with a broader scope of analysis, including a weekly newspaper article presented in a magazine format as another variant of informational text. This broadened effort seeks to identify differences in machine translation (MT) error types across different text types while also providing further supporting evidence for the major findings of the previous study. Based on those identified differences, this study explores how post-editors respond to these errors. Similar to the results of the previous study, the HT group in this study spent approximately 50% more time than the MTPE group, and the average post-editing accuracy of the MTPE group was significantly lower (36.7%) compared to the HT group (84.6%). However, in contrast to the findings of the previous research, where all corrections attempted by post-editors were considered appropriate, some corrections made by post-editors in this study were deemed inappropriate and thus classified as accuracy errors.

With the advancement of large language models, it has become increasingly critical to assess their capabilities and limitations to identify areas where human expertise remains essential. This study compares the performance of GPT-4 and 13 translation students in correcting accuracy errors in Korean-to-English financial texts to inform post-editing pedagogy in the era of generative AI. The analysis highlights GPT-4’s strong potential as a post-editing tool for domain-specific informational texts, demonstrating superior performance in correcting omissions, grammatical and terminological errors. However, its performance was inconsistent in addressing lexical ambiguity where students often outperformed it. In the case of syntactic errors, both GPT-4 and students well corrected errors that were easily identifiable, but neither group handled syntactic ambiguity effectively. These findings underscore the need to reconsider priorities in post-editing training and call for further investigations to better understand GPT’s strengths and limitations.

This study examines Korean EFL learners’ systematic production of errors and accurate responses. A total of one hundred and one participants (aged between 11 and 13) completed a picture elicitation task designed for the English progressive. The method of Error Analysis was employed to analyze the written production. The findings indicated that Korean learners produced intralingual errors most frequently. The most common errors involved the use of bare verbs without tense and aspectual marking (e.g., Dance, She dance). The next most frequent errors involved the use of be followed by a bare verb (e.g., She is dance). Omission of be alone was rare in the current study (e.g., She dancing). The middle school student group performed better than the elementary group (50% accuracy versus 8.82%). The difference can be attributed to the input frequency and classroom practices. Pedagogical implications of the results are discussed in terms of the effectiveness of English teaching and the necessity of explicit and implicit error corrections and grammatical instructions.

In sharp contrast to great attention to the quality of Machine Translation (MT) raw output, the quality of post-edited output has drawn relatively little attention in Korean translation studies, although some errors in MT output can remain even after post-editing. Against this backdrop, this study sets out to investigate accuracy errors in post-edited output, based on Korean-English parallel translation corpus for AI training released in June 2021 by the National Information Society Agency. For this purpose, 200 parallel sentences with accuracy errors were collected and classified by error type. According to the analysis results, mistranslation errors account for about two-thirds, with the rest in omissions, indicating that quite a number of omissions are still left in post-edited output. While lexical errors ranging from words to clauses are found most frequently in mistranslations, syntax errors represent a surprisingly large portion, with many errors in modifiers and subjects. This study draws attention to quality in MT post-editing, suggesting the need for further investigation into factors affecting the quality of post-edited output.

To extract the direction of arrival of multiple sensors from analysis data by a sensor array is a multiple parameter estimation problem. Some important algorithms for spatial temporal processing have been developed in the past decades. A new direction of arrival estimation method using effects of model errors and sensitivity analysis is proposed. Two subspace are used to form a signal space whose phase shift between the reference signal and its effects of model error signal. Since a desired signal is obtained after interference rejection through correction effects of model error, the effect of channel interference on the estimation is significantly reduced. The proposed method in the number of signal sources detectable is not bounded by the number of antenna elements used. Through simulation, we show that the proposed method offers significantly improved estimation resolution and accuracy relative to existing method.

There is growing interest in the role of written corrective feedback (CF). Although many studies have investigated the effect of written CF on the development of L2 accuracy, there is still little classroom-based research. Most of studies investigated the effectiveness of focused written CF in laboratory settings, limiting the application of the findings to real classrooms. Thus, the present study investigated whether or not unfocused written CF was useful with respect to L2 accuracy development in four composition classes in a university. More specifically, the study examined written CF practiced in intact classrooms. It focused on the relationships between the effects of CF and types of errors (i.e., verb, noun, article, lexicon, and sentence) and types of error correction (i.e., direct vs. indirect CF). The data were collected from forty university learners enrolled in four composition classes taught by two native English speaking teachers. The research found that learner errors decreased in the use of verb, article, and sentence; but not in noun and lexicon. The reduction, however, was only observed in the classroom where direct CF was provided. In this paper, the findings are discussed with respect to the complexity of grammar rules and the degree of explicitness of instruction. The results of the research added another piece of evidence to the claim that all grammar rules are not learned in the same way; thus, learner errors need to be treated differently according to the nature of the targeted rules. Feedback providers need to carefully consider the relationship among the complexity of the rules, the explicitness of feedback, and given instruction time.

Accurate electroencephalography (EEG) forward calculation is of importance for the accurate estimation of neuronal electrical sources. Conventional studies concerning the EEG forward problems have investigated various factors influencing the forward solution accuracy, e.g. tissue conductivity values in head compartments, anisotropic conductivity distribution of a head model, tessellation patterns of boundary element models, the number of elements used for boundary/finite element method (BEM/FEM), and so on. In the present paper, we investigated the influence of modeling errors in the boundary element volume conductor models upon the accuracy of the EEG forward solutions. From our simulation results, we could confirm that accurate construction of boundary element models is one of the key factors in obtaining accurate EEG forward solutions from BEM. Among three boundaries (scalp, outer skull, and inner skull boundary), the solution errors originated from the modeling error in the scalp boundary were most significant. We found that the nonuniform error distribution on the scalp surface is closely related to the electrode configuration and the error distributions on the outer and inner skull boundaries have statistically meaningful similarity to the curvature distributions of the boundary surfaces. Our simulation results also demonstrated that the accumulation of small modeling errors could lead to considerable errors in the EEG source localization. It is expected that our finding can be a useful reference in generating boundary element head models.

Since the GPS absolute positioning with pseudorange measurements can significantly be affected by the observation error, the time series analysis of the GPS receiver clock errors was performed in this study. From the estimated receiver clock errors, the time series model is generated, and constrained back in the absolute positioning process. One of the CORS (Continuously Operating Reference Stations) network is used to analyze the behavior of the receiver clock. The dominant part of the model is the linear trend during 24 hours, and the seasonal component is also estimated. After constraining the modeled receiver clock errors, the estimated position error compared to the published coordinates is improved from ${\pm}11.4\;m\;to\;{\pm}9.5\;m$ in 3D RMS.

The purpose of this study is to investigate which accuracy errors are more likely to be left uncorrected in post-edited output. To this end, this study analyzed post-edited results produced by 13 student translators with no formal post-editing education. The participants were asked to conduct full post-editing of Korean-to-English machine-translated texts with 23 accuracy errors without time constraints. The results showed that omissions were almost completely corrected, indicating that omission is less likely to remain unedited when enough time is allowed for the post-editing task. In lexical errors, terminology errors were most notably found uncorrected, compared with mistranslated polysemous words and other lexical errors. In syntax errors, errors that require subject knowledge for their identification were most frequently uncorrected, regardless of whether the errors were caused by modifiers or subjects. Such findings shed light on the importance of the education of terminology translation and subject knowledge in post-editing training. This study draws attention to the type of errors as a significant predictor of post-editing quality, pointing to the need for further investigation into the impact of error types on post-editing process and results.

본고에서는 어휘에 중점을 두고 인공신경망 기계번역에 의한 한국어에서 일본어로의 번역을 토대로 번역의 정확도와 오역의 정도를 살펴보고자 신문의 사설을 대상으로 네이버의 파파고(Papago)에 의한 번역과 고찰을 진행했다. 고찰에 앞서 한국어 사설, 파파고 번역, 일본어판 사설을 대상으로 어휘조사를 실시했다. 어휘조사는 자립어만을 대상으로 하고 있으며 그 중에서 가장 큰 비중을 차지하는 명사를 대상으로 고찰을 진행했다. 한국어 사설의 명사 891어 중 90%에 해당하는 802어는 파파고 번역과 일본어판 사설 양쪽에 대응하는 번역어가 존재했다. 그 중 697어는 한국어 사설, 파파고 번역, 일본어판 사설이 거의 일치하고 있으며, 파파고가 한국어 사설의 명사 중 일본어에도 있는 말과 약어(略語)를 그대로 번역하지 않고 일본어에서 더 많이 사용되고 통용되는 말로 번역하고 있다. 나머지 105어는 파파고와 일본어판 사설에서 다른 번역을 하고 있는데 의미 면에서는 동일하다고 간주할 수 있는 것이 대부분이었다. 단, 이 105어에 대한 파파고 번역은, 일본어판 사설과 비교했을 때 직역이 많이 보였다. 또한 아주 적기는 하지만 파파고 번역의 오류도 확인할 수 있었다. 그렇다고는 하지만 명사 어휘의 고찰을 통해서 본 파파고의 한일 번역은 정확도와 질적인 면에서 매우 우수하다는 것을 수치적으로 확인할 수 있었다.

In this study, newspaper editorials translated by Naver Papago were analyzed to examine the accuracy and errors of translations from Korean to Japanese by artificial neural network machine translation. The focus was vocabulary. Prior to the analysis, a vocabulary survey targeting Korean editorials, Papago translations, and Japanese editorials was conducted. The survey was conducted only on independent words, and the analysis was conducted on nouns with the highest proportion. Ninety percent of the 891 nouns in the Korean editorials (802 nouns) had translations that corresponded to both the Papago and Japanese editorials. Among them, 697 nouns were almost identical in the Korean editorials, Papago translations, and Japanese editorials. Papago does not directly translate words or abbreviations in Korean editorials; it translates them into words that are more commonly used in Japanese. The remaining 105 nouns were translated differently in the Papago and Japanese editorials, but most were the same in terms of meaning. However, compared to the Japanese editorials, Papago provided many literal translations for these 105 nouns. In addition, a few errors in the Papago translation were identified. Nevertheless, by considering the noun vocabulary, we numerically confirmed that Papago’s Korean-Japanese translation was excellent in terms of accuracy and quality.

내부회계관리제도는 한시적으로 구촉법에 규정되었다가 2003년 외감법에 항구적으로 법제화되었고 2005년부터 일정조건의 기업을 대상으로 적용되었다. 본 연구에서는 회계정보의 신뢰성 증대를 목적으로 도입된 내부회계관리제도가 재무분석가의 이익예측오차와 이익예측정확성에 영향을 미치는지 분석하였다. 연구기간은 2002년부터 2007년이며 이익예측치는 t+1년의 것을 이용하였다. 본 연구의 실증분석 결과는 다음과 같다. 첫째, 내부회계관리제도의 도입은 도입 이전에 비해 재무분석가의 이익예측오차는 감소하고 이익예측정확성은 높게 나타났다. 이러한 결과는 이익예측치의 예측시기가 12월말인 경우가 9월말이나 6월말에 비해 더 뚜렷한 것으로 보였다. 따라서 이익예측오차가 감소하고 정확성이 높아지는 관련성이 가장 뚜렷한 예측시기를 추가분석한 결과 12월말이었으며, 이러한 결과는 내부회계관리제도의 도입 이후에 더 크게 나타났다. 추가분석에서는 제도의 도입연도를 제외하고 도입이전과 도입이후로 구분하여 분석하였으나 기존의 결과와 큰 차이를 보이지 않았다. 한편 제도의 도입연도인 2005년에서 2007년으로 갈수록 이익예측오차가 감소하고 정확성이 높아지는 관련성이 뚜렷하게 나타났다. 내부회계관리제도가 정착되면서 재무분석가의 이익예측치에 미치는 영향력이 점점 커질 것으로 예상된다. 둘째, 기업지배구조관련변수들이 재무분석가의 이익예측오차와 정확성에 미치는 영향이 내부회계관리제도의 도입여부에 따라 달라지는지를 분석해 보았다. 분석결과에 의하면 사외이사비율(OUT)만이 내부회계관리제도의 도입이후가 이전보다 증가할수록 이익예측오차는 감소하고 정확성은 높아지는 관련성을 나타냈다. 이러한 유익한 연구결과들에도 불구하고 제도의 도입이 어떠한 경로를 거쳐 재무분석가의 의사결정에 영향을 미치는지는 명확히 밝히지 못하였다.

It is said that the high quality of internal control over financial reporting is an impetus for enhancement of a reliability of accounting information. This study examines the relation between analysts' earnings forecasts and Internal Accounting Control System(IACS) applied in 2005. Effectiveness of IACS has reviewed observing changes analysts' earnings forecast errors(accuracy) a year before and after to a system adoption. The samples in this study are 889∼1,294 the analysts' earnings forecasts of firms registered in Korean Stock Exchange in the period from 2002 to 2007. The empirical results are summarized as follows. First, from the analysis, companies after to a system adoption than before to it tend to decrease earnings forecast errors and increase earnings forecast accuracy. the meanings of this analysis is to suggest the positive effect of IACS adoption on analysts' earnings forecasts. In addition, the most distinct results shows in the December timing among the three earnings forecast announcements. Second, this analysis is whether IACS adoption affect the relation between variables related corporate governance and analysts' earnings forecasts. this result is that IACS adoption do not affect statically the relation between variables related corporate governance and analysts' earnings forecasts. In addition, this study examine the effect of IACS on the relation between analysts' earnings forecasts and the minimal required selection condition of outside directors, audit committee adoption and audit quality. this result is that the manager controlled and the high outside director in board ratio firm do affect statically the relation between IACS and analysts' earnings forecasts. The last, the more time go by, the strong the effect on IACS on analysts' earnings forecasts. This research contributes to prior research by providing the effect of the internal control systems on analysts' earnings forecasts for the first time. But I can not clearly find how analysts' earnings forecasts by IACS adoption.

Purpose: The goal of this study is to examine the effect of articulation treatment using Oral Motor Training (OMT) on articulation accuracy and distortion errors of children who have speech sound disorders with class III malocclusion. Methods: Three children with class III malocclusion in the stage of deciduous dentition aged from 6;0-6;3 (year;month) participated in this study. These 3 children commonly exhibited unilateral mastication, mandible laterality on jaw movement and especially distortion errors of lateralizing for alveolar and palatal consonants mainly in vowel /i/ environment. Articulation therapy using OMT for both of improved non-speech and speech movement involved in target sound production was provided. The ABA design of single case experimental design was used. The articulation accuracy and the frequency of lateralization distortion errors at both of the word and sentence level were measured within baseline (A1), intervention (B), and maintenance (A2) phases. Results: It was found that all participants showed the higher articulation accuracy and the lower frequency of distorted lateralization errors for alveolar and palatal consonants at the both of word and sentence levels in intervention phases than in baseline ones and also these effects maintained after intervention. Conclusion: It was concluded that the OMT targeting appropriate non-speech and speech movement might be beneficial for young children who have class III malocclusion.

SBRT는 1회나 또는 3~5회에 걸쳐 치료 Fraction이 30분에서 최대 1시간 걸리므로 치료 중 자세오차가 발생할 가능성이 있다. 이러한 set-up의 오차를 줄이고 정확한 선량을 주기위해 SBRT 환자 치료 시 치료 전 CBCT를 사용하여 보정 후 좌표 값들을 적용하여 치료한 값과 치료 후 긴 치료시간으로 인해 자세 움직임 여부를 확인하기 위해 다시 CBCT를 촬영하여 치료 전.,후 오차 값들의 유용성을 평가하고자 한다. 계통오차 범위는 평균적으로 X, Y, Z축에서 0.032~0.17 cm으로 나타나 치료 후에도 움직임의 변화가 매우 적음을 확인하였다. 호흡동조에 의한 종양 중심체 변화 (±SD)는 X, Y 및 Z 방향에서 0.11(±0.12) cm, 0.27(±0.15) cm, 0.21cm(±0.31cm)였다. 종양 에지 (±SD)은 각각 X, Y및 Z 방향에서 0.21(±0.18) cm, 0.30(±0.23) cm, 0.19cm(±0.26) cm이었다. 종양 교정된 변위의 (±SD)은 각각 RL, AP 및 SI 방향에서 0.03(±0.16) cm, 0.05(±0.26) cm, 0.02(±0.23) cm이었다. 3차원 벡터 값의 범위는 치료 전과 CBCT를 비교했을 때 평균적으로 0.11~0-.18 cm 교정된 셋업 오차는 0.3 cm 이내에 있음을 확인하였다. 따라서, 일부 나이가 많은 환자, 치료 당일 컨디션, 체형에 따라 다소 값들의 변화가 있었지만 유의 범위 내에 있음을 확인하였다.

Since SBRT takes up to 1 hour from 30 minutes to treatment fraction once or three to five times, there is a possibility of setup error during treatment. To reduce these set-up errors and give accurate doses, we intend to evaluate the usefulness of pre-treatment and post-treatment error values by imaging CBCT again to determine postural movement due to pre-treatment coordinate values using pre-treatment CBCT. On average, the range of systematic errors was 0.032 to 0.17 on the X and Y,Z axes, confirming that there was very little change in movement even after treatment. Tumor centripetal changes (±SD) due to respiratory tuning were 0.11 (±0.12) cm, 0.27 (±0.15) cm, and 0.21 cm (±0.31 cm) in the X, Y and Z directions. The tumor edges ±SD were 0.21 (±0.18) cm, 0.30 (±0.23) cm, and 0.19 cm (±0.26) cm in the X, Y and Z directions. The (±SD) of tumor-corrected displacements were 0.03 (±0.16) cm, 0.05 (±0.26) cm, and 0.02 (±0.23) cm in RL, AP, and SI directions, respectively. The range of the 3D vector value was 0.11 to 0-.18 cm on average when comparing pre-treatment and CBCT, and it was confirmed that the corrected set-up error was within 0.3 cm. Therefore, it was confirmed that there were some changes in values depending on some older patients, condition on the day of treatment, and body type, but they were within the significance range.

2011년부터 작성되기 시작한 국가재무제표는 발생주의에 따라 중앙정부의 재정 상태와 운영결과를 효과적으로 보여줌으로써 국정 운영을 보조하는 중요한 역할을 일임하고 있다. 그러나 이러한 중요성에도 불구하고 국가 재무회계정보에 대한 품질 평가는 제한적으로 이루어져 온 것이 사실이다. 이에 본 연구는 회계오류라는 가장 직관적인 지표를 이용해 국가재무제표 전반의 정확성을 평가한다. 이를 위해 순자산변동표에 명시된 ‘중대한 오류[유형 ①]’, 재정운영표 하부 계정과목에 숨어 있는 ‘중대하지 아니한 오류[유형 ②]’, 실무 성격상 잠재 오류에 해당하는 ‘기타 순자산 조정[유형 ③]’ 등 세 가지 유형의 오류를 다각도로 분석하였다. 그 결과 첫째, 분석대상 기간(2011∼2014년) 중 전체 오류를 합산한 오류총액이 통계적으로 유의한 감소 추세를 보여 정확성 관점에서 바라본 국가재무제표의 품질은 외형상 개선되고 있는 것으로 나타났다. 다만, 이러한 결과는 오류총액에서 절대적으로 높은 비중을 차지하는 기타 순자산 조정[유형 ③]에 의해 주도된 것으로 해석에 유의를 요한다. 둘째, 국가재무제표의 정확성이 개선되고는 있으나, 오류의 금액적 중요성이 크고 발생 빈도가 높은 부처가 다수 발견됨에 따라 절대 규모 면에서는 여전히 개선의 여지가 많은 것으로 나타났다. 이러한 평가 결과는 향후 국가 재무회계정보의 지속적인 품질 향상을 위해 i) 명확하고 일관된 오류 분류 기준(즉, 오류 회계처리기준) 마련, ii) 오류표기 방식 개선(즉, 외부 정보이용자에 대한 충분한 수준의 세부 정보 제공), iii) 기타 순자산 조정 발생의 최소화, iv) 대규모 오류가 빈번한 부처에 대한 특화된 점검 및 관리 서비스 제공 등 여러 정책적 시사점을 제공한다.

Given the increasing importance of accrual-based government financial statements, this paper investigates accuracy of government reporting by utilizing accounting errors, the most intuitive and comprehensive proxy for information credibility. We conduct multilateral analyses on three types of errors: ① ‘significant errors’ which are explicitly recognized in the Statement of Changes in Net Assets, ② ‘insignificant errors’ which are hidden under sub-accounts in the Statement of Operations, and ③ changes in net assets, irrelevant with base net assets, reserves, or surplus, which practically are potential errors to be recognized in such future events as governments reorganization (hereafter ‘other net asset adjustments’). From the analytic results, we first report the amount of total errors covering all three types has shown a statistically significant downward trend from 2011 to 2014, indicating that accuracy of government financial statements has improved in appearance. However, caution is required in interpreting this outcome because the result has been driven mainly by other net asset adjustments which dominate the other two types of errors in total volume. We also find the necessity of further improvement in reporting accuracy by evidencing highly frequent material-error incidences in many central government agencies (hereafter ‘agencies’). Applying an equivalent ‘1% materiality’ criterion for the Korean financial regulatory authority to judge an accounting fraud, we show, on average, 27 agencies, 71.1% of total 38 sample agencies, have made such material errors over the sample period. Among them, 14 agencies are observed to repeat those errors every year. These results cast several important policy implications. First, clear and consistent standards are required to address inconsistent error-reporting practices across agencies; some classify less-than-1% errors as significant (fully recognized in the Statements of Changes in Net Assets), while others regard more-than-10% errors as insignificant (partially disclosed in the footnotes). Second, methods to guarantee complete disclosure of detailed information on errors should be devised. In case of other net asset adjustments, no information is given except its total amount. Insignificant errors also does not provide its entire details. Third, other net asset adjustments should be more strictly managed to further enhance information credibility due to its high portion in total error volume. Fourth, tailored guidances are necessary for agencies with highly frequent material errors because continued material errors signal possible structural problems such as lack of relevant professionals or conflicts of standards with their accounting environments. Caveats are in order. We excluded 16 agencies whose financial statements have suffered from drastic changes due to government reorganizations. So, representativeness of the sample could be challenged from the possibility of systematic difference when those agencies are included. Also, newly suggested evaluation models for aggregate samples are not free from correlated omitted variable bias. Nevertheless, such concerns are expectedly addressed with consistent results from a separate analysis on each individual agency, high explanatory power of regressions, and additional inclusion of government fixed effects. Finally, search for factors causing changes in accuracy is beyond the scope of this paper.

정교한 원가시스템이란 제품원가를 정확하게 보고하는 원가시스템이다. 반면 정교하지 않은 원가시스템은 원가시스템에 오류가 있는 시스템으로, 원가시스템의 오류에는 원가 풀을 통합시킴으로 인해 원가이전 현상이 발생하는 통합오류와 원가동인을 잘못 적용함으로 인한 식별오류가 있다. 본 연구에서는 이러한 원가시스템의 오류와 제품원가의 정확성과의 관계를 분석하여 원가시스템의 어떤 측면을 개선하면 제품원가의 정확성을 있는지에 대해 분석하였다. 분석결과는 다음과 같다. 첫째, 원가측정오류가 발생하지 않는 경우에는 원가시스템의 통합오류와 식별오류가 내재하지 않은 시스템이 정교한 원가시스템으로 원가배부의 왜곡을 막을 수 있다. 둘째, 제품원가의 왜곡 정도는 원가시스템의 통합오류가 원가시스템의 식별오류보다 더 낮았다. 이는 제품원가의 정확성을 높이기 위해 인과관계가 높은 원가동인을 찾는 노력이 더 중요하다는 점을 보여준다. 셋째, 원가식별오류가 내재한 경우 원가 풀을 통합하여 통합오류를 증가시켜 제품원가를 배분하면 제품원가의 정확성이 높아졌다. 이는 통합오류가 높다고 해서 반드시 제품원가가 왜곡 배부되지 않는다는 점을 보여준다. 넷째, 원가측정오류, 즉 원가 자체가 왜곡 측정된 경우에는 통합오류와 식별오류가 내재하지 않은 정교한 원가시스템을 적용한다고 해서 제품원가가 정확하지 않다는 점이다. 이 경우에는 통합오류가 높아지면 제품원가의 정확성이 더 높아졌다. 이는 정교한 원가시스템을 고안할 때 가장 중요한 첫 것은원가측정오류가 없도록 해야 한다는 점을 의미한다. 그리고 원가측정오류가 발생하는 경우 원가 풀을 통합하여 원가를 배분하면 제품원가의 정확성을 높이는 방안이 된다.

This Study examines the relationship between the Errors of Product Costing System and the accuracy of he Product Cost. The results are as follows. First, if the cost of measurement errors do not occur, it is possible to prevent the distortion of the cost－allocation by sophisticated cost system which is not inherent in specification error and aggregation error. Second, the degree of cost distortion by aggregation error was lower than specification error. This suggests that cost drives that increase the cause and effect is important to the accuracy of the product cost. Third, the increased accuracy of the product cost is increased by aggregating the cost center when the specification errors are identified, This means that cost distortion is not necessarily high because of aggregation error. Fourth, In case of cost measurement error which do not measure the cost in accurately, Product cost is not accurate although sophisticated cost system applied. The Accuracy of Product Cost can is more increased by increasing the aggregation error. This suggests that the decrease in cost measurement error is the most important stage to design the sophisticated cost system. In case of cost measurement error, the option to aggregating the cost center increases accuracy of the product cost.