• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.193-212
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• 2021

Purpose - This study investigates the effect of auditor change on client firm's accounting (financial statement) comparability. Design/methodology/approach - The comparability of accounting information is measured by the difference in accruals between the two firms. Additionally, the study uses earnings-stock return relationship as another proxy of accounting comparability. In particular, the paper examines whether there is a systematic difference between initial audit years and the other years with respect to the client firm's accounting comparability. Moreover, current study tests how changes in auditor size or industry expertise before and after the switch of auditors affect the accounting comparability. Findings - The results show that the level of accounting comparability is lower in the year of auditor change than in the other years. Furthermore, this lower level of comparability is derived by the observations that switch their auditors from non-Big4 to non-Big4 or from non-specialist to non-specialist. These results are consistent when accounting comparability is measured by different proxies. Research implications or Originality - The findings of this study provide important policy implications for the regulations related with auditor selection.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.121-130
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• 2016

Amidst a competitive environment, success and innovation of a company hinge on establishment of competitive strategies through CEO's capabilities for discovering new businesses. In other words, several alternatives that are being considered as new businesses and the ensuing selection that a top management makes lead to a company's success and innovation. Examples of this are numerous among global corporations as well as Korean small and medium-sized enterprises (SMEs). This research has analyzed the role of a CEO to be a condition for success in the growth and innovation of a company. Starting from the topic of entrepreneurship, the research on the role of a CEO has been actively conducted in context with the latest innovations. A prime example involves research related to the innovativeness of a CEO. In this regard, this research was an empirical analysis on the impact that a CEO's ability to discover new business opportunities and competitive strategies has on the performance of a firm. This analysis was conducted based on nationwide data of 286 large conglomerates and smaller-sized companies alike. Based on the analysis, "experimenting" and "association", among abilities of discovery, have been found to strengthen competitive strategies. Also in the context of abilities needed for discovery, differentiation strategy has a greater effect on a firm's performance than the cost leadership strategy. Furthermore, the mediating effect of competitive strategies was prominently displayed in experimenting and corporate performance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.197-212
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• 2019

The purpose of this study is to identify the maturity stages of venture firms through classification analysis, which is widely used as a big data technique. Venture companies should develop a competitive advantage in the market. And the maturity stage of a company can be classified into five stages. I will analyze a difference in the growth stage of venture firms between the survey response and the statistical classification methods. The firm growth level distinguished five stages and was divided into the period of start-up and declines. A classification method of big data uses popularly k-mean cluster analysis, hierarchical cluster analysis, artificial neural network, and decision tree analysis. I used variables that asset increase, capital increase, sales increase, operating profit increase, R&D investment increase, operation period and retirement number. The research results, each big data analysis technique showed a large difference of samples sized in the group. In particular, the decision tree and neural networks' methods were classified as three groups rather than five groups. The groups size of all classification analysis was all different by the big data analysis methods. Furthermore, according to the variables' selection and the sample size may be dissimilar results. Also, each classed group showed a number of competitive differences. The research implication is that an analysts need to interpret statistics through management theory in order to interpret classification of big data results correctly. In addition, the choice of classification analysis should be determined by considering not only management theory but also practical experience. Finally, the growth of venture firms needs to be examined by time-series analysis and closely monitored by individual firms. And, future research will need to include significant variables of the company's maturity stages.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.119-132
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• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Management & Information Systems Review
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• v.33 no.4
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• pp.21-38
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• 2014

This study investigates whether and how a firm's cost of equity is influenced by the extent of a firms's name change. Even though corporate name change doesn't give any benefit to investors, it can be a signaling about firm's future valuation. And also, if that signaling has high credibility, it can be decrease information cost and the firm's cost of equity. on the contrary to this, if corporate name change is kind of break with the past and corporate image laundering, it is bad signaling to investors. So it can be increase information risk and the firm's cost of equity. Using yearly cross-sectional regressions of the cost of equity on our proxies for corporate name change, size, beta, market-to-book ratio and other innate risk factor over the 2005-2010, we find that the cost of capital is positively associated with corporate name change after controlling for all other factors. This result implies that corporate name change increase information risk of the business, and thus increase information asymmetries between managers and outside investors with respect to a firm's true future value. This increases information risk, and creates an adverse selection problem, on the part of outside investors. Rational investors therefore demand a premium for bearing this corporate name change-related information risk, which in turn leads us to observe a positive relation between the intensity of corporate name change and the cost of equity.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.241-250
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• 2005

New product development (NPD) is defined as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale. Managers charged with project selection decisions in the NPD process, such as go/no-go choices and specific resource allocation decisions, are faced with a complicated problem. Therefore, the ability to develop new successful products has identifies as a major determinant in sustaining a firm's competitive advantage. The purpose of this study is to develop a new evaluation model for NPD project selection in the high -tech industry using support vector machines (SYM). The evaluation model is developed through two phases. In the first phase, binary (go/no-go) classification prediction model, i.e. SVM for high-tech NPD project selection is developed. In the second phase. using the predicted output value of SVM, feasibility grade is calculated for the final NPD project decision making. In this study, the feasibility grades are also divided as three level grades. We assume that the frequency of NPD project cases is symmetrically determined according to the feasibility grades and misclassification errors are partially minimized by the multiple grades. However, the horizon of grade level can be changed by firms' NPD strategy. Our proposed feasibility grade method is more reasonable in NPD decision problems by considering particularly risk factor of NPD in viewpoints of future NPD success probability. In our empirical study using Korean NPD cases, the SVM significantly outperformed ANN and logistic regression as benchmark models in hit ratio. And the feasibility grades generated from the predicted output value of SVM showed that they can offer a useful guideline for NPD project selection.

• Journal of Technology Innovation
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• v.20 no.3
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• pp.57-91
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• 2012

This paper investigates determinants of litigation success in the two distinctive types of patent litigations, ex-parte and inter-parte cases, which are brought in the process where a filed application becomes a valid patent right. We regress winning rates of patent applicants on the characteristics of firms, trials, patent lawyer, and patent itself, using a probit model with sample selections. The paper finds that the relative suit rate of a firm, time to be sued, changes of patent agents by applicants, and multiple agents among explanatory variables affect ex-parte reexamination and in-parte post-grant patent trials differently in the point of average marginal effects. These variables lower the probability of applicant's victory in the ex-parte cases, while they raise the probability in the inter-parte trials. However, the experience that agents represent applicants is a winning rate-increasing factor both in inter-parte and ex-parte reexamination, unexpectedly. This result cannot be applied to the entire domain of the variable, since sample selection effects are reflected in the result. The number of claim increases the winning probability of the applicant in the both types of patent litigations. This study has some limitations because it ignores the information on the legal person to which a patent agent belongs, and confined agent's experience to patent filing. We leave it future studies to investigate the effects of lawsuit experience of patent agent, and those of characteristics of the law firm to which individual patent lawyer is affiliated.

• Journal of Technology Innovation
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• v.19 no.1
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• pp.29-53
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• 2011

This paper analyzes the effects of government-sponsored R&D on firm's employment and management performance, using the panel data of manufacturing firms in the area of Busan, Ulsan and Gyungnam. The paper applies PSM to estimate the treatment effects(ATT) without sample selection bias. The findings show that government-sponsored R&D in the area has positive effects on the participating firms' employment and R&D for several years after completing R&D projects.

• KSCI Review
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• v.2 no.2
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• pp.83-100
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• 1996

As the globalization of business increases, roles of managers from other culteres assume greater importance, This is the survey of expatriate selection and training of korean firms. We assummed that selecting criteria should be different for each part ho has different purposal. We cartegolized three parts with comparative two sides. Our results shows that there are differences in selecting vs. selected parts, selected part who should work foreign market assummed spouse & family's conditions more important. As top anagers emphasize the managemant & skill factors, middle and low level managers are more intrested in personal factors. The part who expatriate developing country choose cross culture factor more important than expatriate advenced country. In korean firms, there's a little program about expatiate training, spouse & family education and no repatriation adjustment program.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.687-696
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• 2020

Accounting policies are principles and practices by which an entity uses to recognize, measure and report economic transactions. Improper application of accounting policies can lead to misrepresentation of firms' financial position and performance which consequently results in incorrect accounting information to the users. This paper aims to investigate the factors influencing the choices of accounting policies in small and medium enterprises (SMEs) in Vietnam by reviewing relevant literature to build a research model. The research model comprises of one dependent variable that is income-decreasing accounting procedures and six independent variables namely the firm size, financial leverage, incentives, auditor, accountants, and tax policies. After this, the authors collected primary data from more than 200 questionnaires sent to directors and chief accountants of the SMEs for the period 2018 to 2019. We then used Ordinary Least Squares regression method (OLS) to analyze the data. The results showed that four factors influenced selection of accounting policies in which auditors are associated with income-increasing accounting policies; and there are three factors associated with income-decreasing accounting policies which are, company size, tax and accountant. Especially, the research results indicate that company size has a significant influence on the selection of accounting policies in the SMEs. Based on the results, we propose instructive suggestions for regulators and lawmakers improve choices of accounting policies in the SMEs.