• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.141-154
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• 2014

The adoption of International Financial Reporting Standards (IFRS) is the one of important issues in the recent accounting research because the change from local GAAP (Generally Accepted Accounting Principles) to IFRS has a substantial effect on accounting information. Over 100 countries including Australia, China, Canada and the European Union member countries adopt IFRS (International Financial Reporting Standards) for financial reporting purposes, and several more including the United States and Japan are considering the adoption of IFRS (International Financial Reporting Standards). In Korea, 61 firms voluntarily adopted Korean International Financial Reporting Standard (K-IFRS) in 2009 and 2010 and all listed firms mandatorily adopted K-IFRS (Korea-International Financial Reporting Standards) in 2011. The adoption of IFRS is expected to increase financial statement comparability, improve corporate transparency, increase the quality of financial reporting, and hence, provide benefits to investors This study investigates whether recognized accounts receivable discounting (AR discounting) under Korean International Financial Reporting Standard (K-IFRS) is more value relevant than disclosed AR discounting under Korean Generally Accepted Accounting Principles (K-GAAP). Because more rigorous standards are applied to the derecognition of AR discounting under K-IFRS(Korea-International Financial Reporting Standards), most AR discounting is recognized as a short term debt instead of being disclosed as a contingent liability unless all risks and rewards are transferred. In this research, I try to figure out industrial responses to the changes in accounting rules for the treatment of accounts receivable toward more strict standards in the recognition of sales which occurs with the adoption of Korea International Financial Reporting Standard. This study examines whether accounting information is more value-relevant, especially information on accounts receivable discounting (hereinafter, AR discounting) is value-relevant under K-IFRS (Korea-International Financial Reporting Standards). First, note that AR discounting involves the transfer of financial assets. Under Korean Generally Accepted Accounting Principles (K-GAAP), when firms discount AR to banks before the AR maturity, firms conventionally remove AR from the balance-sheet and report losses from AR discounting and disclose and explain the transactions in the footnotes. Under K-IFRS (Korea-International Financial Reporting Standards), however, most firms keep AR and add a short-term debt as same as discounted AR. This process increases the firms' leverage ratio and raises the concern to the firms about investors' reactions to worsening capital structures. Investors may experience the change in perceived risk of the firm. In the study sample, the average of AR discounting is 75.3 billion won (maximum 3.6 trillion won and minimum 18 million won), which is, on average 7.0% of assets (maximum 38.6% and minimum 0.002%), 26.2% of firms' accounts receivable (maximum 92.5% and minimum 0.003%) and 13.5% of total liabilities (maximum 69.5% and minimum 0.004%). After the adoption of K-IFRS (Korea-International Financial Reporting Standards), total liabilities increase by 13%p on average (maximum 103%p and minimum 0.004%p) attributable to AR discounting. The leverage ratio (total liabilities/total assets) increases by an average 2.4%p (maximum 16%p and minimum 0.001%p) and debt-to-equity ratio increases by average 14.6%p (maximum 134%p and minimum 0.006%) attributable to the recognition of AR discounting as a short-term debt. The structure of debts and equities of the companies engaging in factoring transactions are likely to be affected in the changes of accounting rule. I suggest that the changes in accounting provisions subsequent to Korea International Financial Reporting Standard adoption caused significant influence on the structure of firm's asset and liabilities. Due to this changes, the treatment of account receivable discounting have become critical. This paper proposes an intelligent diagnostic system for estimating negative impact on stock value with self-organizing maps and case based reasoning. To validate the usefulness of this proposed model, real data was analyzed. In order to get the significance of this proposed model, several models were compared to the research model. I found out that this proposed model provides satisfactory results with compared models.

• The Journal of Small Business Innovation
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• v.20 no.3
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• pp.1-17
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• 2017

There is a serious information asymmetry between internal managers and outside investors in the process during IPOs. One mechanism that mitigates this information asymmetry is a high quality auditor. Since prior research document auditors' effect on newly listed firms at the IPO year, what has not yet been revealed in previous studies is the behavior of firms and auditors after listing. In this study, we investigate (i) the firms tendency of contracting with Big N auditors, and (ii) the effect of Big N auditors on accounting quality after the years of IPOs. Using a sample of 7,678 (1,892 firm-years of after IPOs, and 5,786 control firm-years) KOSDAQ observations between 2002 and 2012, we find that the likelihood of contracting with Big N auditor lasts only for two years after IPO compare to that of non-IPO control years. Secondly, we find that the effect of Big N auditors on clients' earnings management lasts for a very short period after IPO. These findings suggest that although prior literature argue that Big N auditors reduce earnings management of their clients, at least the period right after IPO, it is not consistent. Our study contributes to the existing literature in several ways. First, we provide new evidences of firms' auditor selection decisions by investigating years after the listing. In second, as an evidence of accruals reversal, we document decrease in discretionary accruals after IPOs. Third, we find that there is not always a positive relation between Big N auditor and accounting quality by showing the insignificant Big N auditor effect after IPOs. Our results also suggest several implications to IPO related stakeholders. First, to IPO firms, we provide evidences that decisions of hiring auditors affect firms earnings. Also, lead IPO underwriters may consider how these decisions influence future performance. Second, investors may want to use information not only in the preofferings but also after public offerings. Our study insists that auditor hiring decisions affects their own welfare. Finally, accounting standard setters may find these results useful for evaluating how much discretion they should allow corporate managers to hire auditors. In addition, our result casts doubt on auditor designation.

• Management & Information Systems Review
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• v.35 no.1
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• pp.51-68
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• 2016

In this paper, we aim to analyze the effect of accounting policy change subsequent to the adoption of K-IFRS in Korea, whereby the firms are required to recognize impairment losses on goodwill on a periodic basis rather than to amortize over a specific period. As a principle-based accounting standard, the K-IFRS expands the scope of fair value measurement with a view to enhance the relevance and timeliness of accounting information. In the same vein, intangibles with indefinite useful life, of which goodwill is an example, are subject to regulatory impairment tests at least once a year. Related literature on the impact of mandatory change in goodwill policy document that impairment recognition is more likely to be practiced opportunistically, mainly because managers have a greater discretion to conduct the tests under K-IFRS. However, existing literature examined the frequency and/or magnitude of the goodwill impairment before versus after the K-IFRS adoption, failing to notice the impairment symptoms at individual firm level. Borrowing the definition of impairment symptoms suggested by Ramanna and Watts(2012), this study performs a series of tests to determine whether the goodwill impairment recognition achieves the goal of communicating timelier information under the K-IFRS regime. Using 947 firm-year observations from domestic companies listed in KRX and KOSDAQ markets from 2008 to 2011, we document overall delays in recognizing impairment losses on goodwill after the adoption of K-IFRS relative to prior period, based on logistic and OLS regression analyses. The results are qualitatively similar in robustness tests, which use alternative proxy for goodwill impairment symptom. Afore-mentioned results indicate that managers are likely to take advantage of the increased discretion to recognize the impairment losses on goodwill rather than to provide timelier information on impairment, inconsistent with the goal of regulatory authority, which is in line with the improvement of timeliness and relevance of accounting information in conjunction with the full implementation of K-IFRS. This study contributes to the extant literature on goodwill impairment from a methodological viewpoint. We believe that the method employed in this paper potentially diminishes the bias inherent in researches relying on ex post impairment recognition, by conducting tests based on ex ante impairment symptoms, which allows direct examination of the timeliness changes between before and after K-IFRS adoption.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Management & Information Systems Review
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• v.36 no.4
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• pp.117-127
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• 2017

In recent times the size of the world IPO in general has skyrocketed. Specifically, China's financial market development is becoming important as both the size of China's capital market and the number of companies going public are gradually increasing. This has led to a rapid development of venture vapital(VC) institutions in China for the past couple of decades. This study focuses on one of the three markets of China's Shenzhen Stock Exchange-the Growth Enterprise Board((GEB) hereafter, ChiNext). The ChiNext is established in October, 2009 to enable hi-tech or high growth potential technology companies that find it relatively difficult to fulfil the listing requirements of either the Shenzhen Main Board or Small and Medium Size Enterprise Board(SMEB) to go public. This study covers a three-year period(2012/01/-2015/01) and analyze first day initial return of 83 venture capital-backed companies and 53 non-venture capital-backed companies using T-test. Regression analysis is used as to examine the variables affecting IPO's first-day return. The empirical results are four-fold. First, the level of first day return of venture-backed is significantly lower than non venture capital backed support in the Chinese venture capital market. Second, the level of first-day return of listed companies supported by foreign venture capital is significantly higher than that of companies receiving domestic venture capital support. Third, the firms that have a large number of venture capital firms showed a low level of first-day return. Fourth, regression result for the IPO first-day return which is as dependent variable indicates that the venture capital support(VCAP), number of venture capital(VCNum), offering size(Lnsize) and PER all affect have negative effect on the first day initial return. Also, the venture capital type(VCType), turnover ratio and the the firm type(Tech-firms) statistically affect IPO first day return positively. Finally, by shedding more light on the IPO first-day return, this paper provides meaningful information to investors about the Chinese IPO market.

• Management & Information Systems Review
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• v.37 no.2
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• pp.187-207
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• 2018

This study examines the negative relationship between accounting conservatism and excess executive compensation and examines whether their relationship increases as managerial incentive compensation intensity increases. For this purpose, a total of 2,755 company-years were selected for the analysis of the companies listed on the Korea Stock Exchange from December 2012 to 2016 as the final sample. The results of this study are as follows. First, there is a statistically significant negative relationship between accounting conservatism and manager overpayment. This implies that managers' incentives to distort future cash flow estimates by over booking assets or accounting profits in order to maximize their compensation when manager compensation is linked to firm performance. In this sense, accounting conservatism can reduce opportunistic behavior by restricting managerial accounting choices, which can be interpreted as a reduction in overpayment to managers. Second, we found that the relationship between accounting conservatism and excess executive compensation increases with the incentive compensation for accounting performance. The higher the managerial incentive compensation intensity of accounting performance is, the more likely it is that the manager has the incentive to make earnings adjustments. Therefore, the high level of incentive compensation for accounting performance means that the ex post settling up problem due to over-compensation can become serious. In this case, the higher the managerial incentive compensation intensity for accounting performance, the greater the role and utility of conservatism in manager compensation contracts. This study is based on the fact that it presents empirical evidence on the usefulness of accounting conservatism in managerial compensation contracts theoretically presented by Watts (2003) and the additional basis that conservatism can be used as a useful tool for investment decision.

• Management & Information Systems Review
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• v.36 no.3
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• pp.151-165
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• 2017

This study investigates the effect of revenue recognition by percentage of completion method on financial analysts' earnings forecasting information in order industry. Specifically, we examines how the analysts' earnings forecast errors and biases differ according to whether or not to report the unbilled revenue account balance and the level of unbilled revenue account balance. The sample consists of 453 firm-years listed in Korea Stock Exchange during the period from 2010 to 2014 since the information on unbilled revenue accounts can be obtained after the adoption of K-IFRS. The results are as follows. First, we find that the firms with unbilled revenue account balances have lower analysts' earnings forecast accuracy than the firms who do not report unbilled revue account balances. In addition, we find that the accuracy of analysts' earnings forecasts decreases as the amount of unbilled revenue increases. Unbilled revenue account balances occur when the revenue recognition of the contractor is faster than the client. There is a possibility that managerial discretionary judgment and estimation may intervene when the contractor calculates the progress rate. The difference between the actual progress of the construction and the progress recognized by the company lowers the predictive value of financial statements. Our results suggest that the analysts' earnings forecasts may be more difficult for the firms that report unbilled revenue balances as applying the revenue recognition method based on the progress criteria. Second, we find that the firms reporting unbilled revenue account balances tend to have higher the optimistic biases in analysts' earnings forecast than the firms who do not report unbilled revenue account balances. And we find that the analysts' earnings forecast biases are increases as the amount of unbilled revenue increases. This study suggests an effort to reduce the arbitrary adjustment and estimation in the measurement of the progress as well as the introduction of the progress measurement method which can reflect the actual progress. Investors are encouraged to invest and analyze the characteristics of the order-based industry accounting standards. In addition, the results of this study empower the accounting transparency enhancement plan for order industry proposed by the policy authorities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.1-13
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• 2019

As a way to find new and innovative technologies, many companies have invested in and acquired skilled startups. Because startups are usually small in size and have a small history of past business experience, there are many risks involved in acquiring them as they have limited technical skills and business feasibility verification methods. Thus, venture capital plays an important role in discovering and investing competitive startups. While Independent Venture Capital generally values financial returns, Corporate Venture Capital, which plays investment roles in the firm, values business synergies with the parent company from a strategic perspective. In an industry sector where development of technology is rapid and whether new technology is held determines a company's competitiveness, existing companies incorporate startups with innovative technologies into their investment portfolios, collaborate together, and take over for comprehensive cooperation. In addition, new investments and acquisitions are carried out through the management of portfolio companies to obtain and utilize industry information. In this paper, major U.S. companies listed in the U.S. verified their investment activities through corporate venture capital and their impact on parent companies and startups through regression, while the parent company's acquisition performance was analyzed through an event study based on a stock price analysis. The criteria for startup were defined as companies with less than 12 years of experience, and the analysis showed that the parent companies with corporate venture capital with a larger number of investments actively take over startups. In addition, increasing corporate venture capital's financial investment activities shows a negative impact on the parent companies' acquisition activities, and the acquisition performance increased when the parent companies took over startups in its portfolio.