• The Journal of Industrial Distribution & Business
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• v.6 no.2
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• pp.5-11
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• 2015

Purpose - This research investigates the effect of disclosure quality with two main components, reliability and timeliness, on economic value added in Iran. Research design, data, and methodology - The sampling includes 170 Tehran Stock Exchange listed companies from 2008-12. Multiple regression analysis was applied to test the hypotheses and estimates of the coefficients. Firm size and return on assets were the control variables. Results - The results show that timeliness of information has a positive impact on economic value added. We did not find any significant relationship between disclosure quality and reliability of information and economic value added. The regressed model shows that there is no significant association between firm size and economic value added. The results also show that there is a positive association between return on assets and economic value added. Conclusions - Theoretically, timely information is effective in decision-making. This study shows that timeliness of information has positive effect on the creation of economic value added. However, disclosure quality, reliability, and firm size do not effect on economic value added. Companies with greater return on assets produce greater economic value added.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.291-301
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• 2020

This paper aims to investigate the impact of chief executive officer's (CEO) attributes on firms' performance. Specifically, it examines the influence of CEOs' education, professional experience, and tenure on Saudi firms' performance. We look at a sample of 120 listed firms on Tadawul stock exchange from 2014 to 2017. Data on financial and accounting variables are obtained from the annual reports of the selected companies. We follow the existing empirical literature and use a panel model and formulate three different equations using the GMM estimator. Findings prove that CEO educational background does matter. In particular, companies employing CEOs with business administration, economics, finance, or accounting degree will perform outstandingly better. Similarly, stock performance gets improved when the CEO has a postgraduate qualification, i.e., when the CEO holds an MBA, a master, or a PhD degree. Besides, results reveal that executives who have an experience in a related field will positively affect the firm's performance. Finally, evidence shows that high CEOs tenure improves corporate performance. Overall, these findings demonstrate that executives' attributes are key factors that would explain differences in Saudi firms' performance. These results would help shareholders to make the right decision in selecting CEOs to manage the company.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.141-148
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• 2020

This paper analyzes factors affecting the debt maturity structure of enterprises listed on the Vietnam stock market. The panel data of research sample includes 549 non-financial listed enterprises on the Vietnam stock market from 2009 to 2019. The Generalized Least Square (GLS) tool is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, debt maturity structure is the dependent variable. Capital structures, fixed assets, liquidity, firm size, asset maturity, profitability, corporate income tax, gross domestic product, inflation rate, credit growth scale are independent variables in the study. The model results show, that among the factors affecting the structure of debt maturity, the capital structure, asset structure, and firm size have the highest estimation coefficients, which shows that capital structure, asset structure, and firm size plays an important role in the decision-making process of debt maturity structure. The empirical results show that there are differences in the impact of these factors on the debt maturity structures in state-owned enterprises and non-state enterprises listed on the Vietnam stock market. The findings of this article are useful for business administrators, helping business managers make the right financial decisions to determine the target debt maturity structure in enterprises.

• Journal of Korea Trade
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• v.23 no.2
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• pp.46-58
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• 2019

Purpose - This paper analyzes how Research and Development (R&D) cartelization and Research Joint Ventures (RJV) affect firms that engage in Cournot competition in their product market using a model in which the Home and Foreign firm produce differentiated products and export their total output to a third country's market. Design/Methodology - In a two-stage game, research expenditures incurred in the first stage improve product quality and are subject to various degrees of spillovers. We consider four different scenarios. Findings - In a symmetric equilibrium we observe the following: (i) an RJV that cooperates in R&D decision yields the highest R&D expenditure. However, the scenario which yields the lowest expenditure depends on the extent of differentiation between the goods and the degree of spillovers; (ii) RJV cartelization yields the highest product quality, output, and consumer surplus in the third country; however, the lowest is produced by R&D competition if spillovers are strong and by R&D cartelization if spillovers are weak; and (iii) each firm's profit is at its minimum in R&D competition and its maximum in RJV cartelization. Furthermore, if spillovers are strong, the profit of each firm in R&D cartelization is greater than that in RJV competition, and vice versa. Originality/value - By analyzing product innovation in international markets, we can find similarities and differences between process R&D and product R&D in international markets.

• Journal of Korean Institute of Industrial Engineers
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• v.2 no.1
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• pp.85-92
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• 1976

In this paper, the employment planning model is developed which is a decision-making model for determining the optimum employment level with respect to varying net manpower requirement for each planing period such that total cost in a planning horizon is minimized. It is constructed as a nonlinear programming model and a dynamic programming model on the basis of studies in the areas of production smoothing and manpower scheduling. Costs for a planning period are categorized into regular wage cost, hiring cost, and overtime cost. The first is a linear function. The other two cost functions are of quadratic nature. The planning horizon of this planning model is intermediate range (five years) for which a fair planning accuracy can be guaranteed. The model considers learning period for each job class. It is simple and an optimum solution can be easily obtained by direct search techniques.

• Korean Management Science Review
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• v.32 no.1
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• pp.83-100
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• 2015

We analyze a duopoly competition when two firms face input cost increases. The objective of this study is to determine the firms' optimal strategy between a price increase and downsizing under conditions of a spatially differentiated market and consumers' diminishing utility on the product size. We develop a theoretical model of two competing firms offering homogenous products using the standard Hotelling model to determine how firms' optimal strategies change when facing input cost increases. In this paper, there are two types of duopoly competitions: symmetric and asymmetric. In the symmetric case, the two firms have the same marginal cost and are producing and selling identical products. In the asymmetric case, the two firms have different marginal costs. The results show that the optimal strategy decision depends on the size of the input cost increase and the cost differences between the two firms. We find that when two firms are asymmetric (i.e., they have different marginal costs), the two firms might choose asymmetric pairs of strategies in equilibrium under certain conditions. When the cost differences between the two firms are sufficiently large and the cost increase is sufficiently small, the cost leader chooses price increase, and the cost-disadvantaged firm chooses downsizing in equilibrium. This asymmetric strategy reduces price competition between two firms, and consumers are better off. When the cost differences between the two firms are sufficiently large, downsizing is the dominant strategy for the cost-disadvantaged firm. The cost-disadvantaged firm finds it more profitable to reduce the product size than to increase its price to reduce price competition, because consumers prefer downsizing to price increases. This paper might be a good starting point for further analytical research in this area.

• Asia-Pacific Journal of Business
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• v.9 no.3
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• pp.71-82
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• 2018

This study verifies whether the sustainable tax strategy provides unique information on earnings persistence and brings about the difference of value relevance of accounting information. Sustainability is measured by the 5-year coefficient of variation in cash ETR, such as in McGuire et al.(2013), which measures variability in long-term performance of tax avoidance. The value relevance of accounting information in this study is modified by the Ohlson model(1995), which explains the value of the firm by using accounting information such as net assets and net income and other non-accounting information. The samples of this study are the firms listed on the securities market from 2004 to 2015 and the final samples are 3,133 firm-year. The results of this empirical analysis show that the value relevance of accounting information increases as firms have long-term and sustainable tax strategies. Most of the prior studies on tax strategies have examined the tax minimization strategy that minimizes the tax cost. However, this study is different in that the sustainability of the tax strategy affects the value relevance of accounting information. The results of this study will be useful for the users to make decision using the value relevance of accounting information.

• Journal of Korea Technology Innovation Society
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• v.16 no.1
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• pp.303-322
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• 2013

A relevance of supporting business of technology financing for technologically innovative SMEs is strongly required for its continuous expansion and development. This study analyzes empirically whether the selection of recipient firms from technology financing have been performed in accordance with its objectives and purposes. Results show that the probability of receiving technology financing is more likely to increase with higher technology rankings and higher operating income ratio. On the other hand, the probability of obtaining financing might be decreased gradually, as the size of capital and age of the firm are increasing. Results also show that technology rankings and firm's major characteristics are found to affect significantly on the decision-making of technology financing. Several useful comments are suggested to improve the relevance of the technology financing since the correct classification rate, which explains the appropriateness of the model, is not at high level. In addition, technology rankings are not uncorrelated with the amount of financing in regression analysis. These research results will contribute to ensure the appropriateness and credibility of the technology financing decision-making.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• The Journal of Information Systems
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• v.17 no.3
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• pp.205-233
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• 2008

This study suggests the dynamic value chain model, that will be able to not only show changing processes to organization's significant capital by integrating an individual, implicit, and explicit knowledge which affect organizational decision making, but also distinguish the key driver for raising organizational competitive power because it makes possible to analyze sensitivity of performance along with decision making alternatives and policy changes from dynamic view by connecting knowledge management capability, knowledge management activity, and relations with organizational performance with specific strategic map. Recently, a lot of organizations show interest in measuring and evaluating their performance synthetically. In organizations taking knowledge management, they introduce effective value chain model like a dynamic balanced scorecard (DBSC), and therefore they can reflect their knowledge management condition as well as show their changes by checking performance of established vision and strategy periodically. Furthermore, they can ask for their inner members' understanding and participation by communicating with and inspiring their members with awareness that members are one of their group, present a base of benchmarking, and offer significant information for later decision making. The BSC has been a successful framework for measuring an organization's performance in various perspectives through translating an organization's vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, this study employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC would serve as a useful strategic teaming tool for facilitating an organization's communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, this study applied the DBSC model to Prototype of Korea manufacturing and service firm.