• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.193-200
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• 2021

This study investigates the impact of managerial ability and managerial incentives on firm performance. In particular, it studies how managerial ability factor can exert significant influence on the profitability and the risk of firms. By doing this, the study can provide several policy implications about how managerial ability can influence firm decisions and its corresponding business policies. Data of the study was collected from the Annual Enterprises Survey (AES), which is conducted by the General Statistics Office of Vietnam (GSO) during the 2009-2013 period. After removing firms with insufficient financial information, our final dataset includes over 50,000 firms in Vietnam. The main result of the study shows that there is a significant and positive relationship between managerial ability and firm leverage. This finding indicates that managerial ability significantly plays an important role in making financial decisions. In addition, our study provides empirical evidence about the causal relationship between managerial compensation and firm risk-taking behavior. Specifically, we find that firm risks are significantly associated with compensation schemes including lower delta and higher vega. In other words, our study implies that the sensitivity of CEO wealth to stock volatility can positively affect both delta and vega or managerial incentives schemes.

• The Journal of Information Systems
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• v.16 no.1
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• pp.91-109
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• 2007

This study investigates the extent to which the implementation of enterprise resource planning(ERP) systems enhance the corporate performance by examining financial variables of the implemented firms against those of the control fm. A total of 346 observations were obtained from 160 firms, 80 implemented firms and 80 control firms, for the period of 1998-2002. Results from the study partly support the assertion that ERP improves the full spectrum of business functions such as selling, marketing, purchasing, warehousing, accounting and human resources by tightly integrating enterprise-wise information databases. First the profitability of the implemented group was different from that of the control group. The indicator (dummy) variable was able to explain the differences in total cash flows between the implemented group fm and the control group firms. Second, ERP turned out In improve the efficiency in managing assets. The indicator variable has the power in explaining the differences in the amount of accounts receivables between the implemented group firms and the control group firms. Third, the product turnover ratio of the implemented group was different from that of the control group. Fourth, the average value added per employee and the net income per employee of the implemented group firms were greats- than those of the control group firms. Finally, the average magnitude of the administrative expenses of the implemented group firms was smaller than that of the control group firms.

• Journal of Distribution Science
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• v.15 no.1
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• pp.123-130
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• 2017

Purpose - This research aims to examine the effect of e-business adoption on firm's growth and profitability in the distribution industry. The value added from the distribution industry acts as the cost of other industries. As the distribution industry develops, its stage becomes shorter and the distribution margin becomes smaller. Therefore, e-business is expected to have a different effect on the distribution industry than other industries. Research design, data and methodology - The previous research generally used e-business adoption as an independent variable and firm's performance as a dependent variable. This study elaborated the model using a dynamic panel model that includes the performance variable of the previous year as an independent variable. By employing system GMM (Generalized Method of Moments), the endogeneity problem in the dynamic panel model can be solved. For the analysis, I extracted the distribution companies as the raw data in the National Statistical Office's Business Activity Survey over the period 2006 to 2012. Results - The growth rate of firms adopting e-business was 0.299%p higher than that of the non-adopter. However, only ERP (Enterprise Resource Planning), KMS (Knowledge Management System) and SCM (Supply Chain Management) contributed positively to the growth rate. In the case of profitability, it was 0.04%p higher than the distribution companies that did not adopt e-business. ERP and LMS (Learning Management System) improve profitability, while SCM reduces profitability. Consequently, while ERP improves both growth and profitability, SCM improves growth but reduces profitability. In addition, KMS improves firm's growth only, and LMS does only profitability, showing that each e-business has a differentiated effect. Conclusions - Since the distribution industry has different characteristics from manufacturing and other service industries, the introduction of e-business may not guarantee the growth and profitability of distribution companies. Careful introduction considering the characteristics of the distribution industry is required. In particular, it is necessary to select an e-business meeting the characteristics and needs of a distribution company, and thereafter, it is required for the company's own efforts to internalize it within the system.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.49-54
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• 2024

This paper investigated the impact of economic cycles in the shipbuilding industry on managerial performance of marine paint and coatings firms. As part of the upstream to ship construction, the marine equipment industry plays a critical role in determining the competitiveness of the shipbuilding industry. Despite a close interaction between the two sectors, the majority of research on the marine equipment industry has highlighted securing competitiveness edge and developing advanced technologies, paying little academic attention to the relationship between shipbuilding and managerial performance. In this regard, this paper examined how economic cycles in shipbuilding affected growth and profitability of marine paint and coatings firms. To this end, managerial performances of six marine paint and coatings firms for the period of 2003-2022 were analyzed in panel regressions. Results indicated that the shipbuilding economic cycle proxied by delivery amounts of Korean shipyards was positively associated with growth and profitability of marine paint and coatings firms. However, there was divergence in statistical significance by shipbuilding indicators. While coefficients of compensated gross tonnage, gross tonnage, and monetary amount were statistically significant, that of deadweight tonnage was not. Findings of this study imply that managerial performances of marine paint and coatings firms are affected by the amount of value added from the shipbuilding industry rather than its absolute size.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.19-27
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• 2020

This paper aims to empirically study the determinants of liquidity of Indian listed firms. To account for profit persistence, we apply a (pooled, fixed and random) effect models to a panel of Indian listed firms that covers the time period from 2010 to 2016. This study consists of 2154 firms operating in Indian market. Liquidity (LQD) of Indian firms is measured by liquid assets to total assets, whereas bank size, capital adequacy, profitability, leverage, and firm age are used as internal determinants. Further, economic activity, inflation rate, exchange rate, and interest rate are the external factors considered. The findings reveal that leverage, return on assets, and firm age are the essential internal determinants that impact the liquidity of Indian listed firms. Furthermore, among the internal determinants, the results indicate that firm size, leverage ratio, return on assets ratio, and firm age are found to have a significant positive association with firms' LQD, except leverage ratio and firm age has a negative relationship with firms' LQD. From this result, this article has provides helpful ideas and empirical evidence on the inner and external determinants of the companies mentioned in India is very useful to bankers, analysts, regulators, investors and other stakeholders.

• International Area Studies Review
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• v.22 no.3
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• pp.175-200
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• 2018

Since the 1990s rising intangible asset has become one of the main driving forces of investment stagnation and jobless growth in advanced income countries. We investigate how does the impact of firms' profitability on employment growth depends on the intangibility and whether the relationship between profitability and tangibility has complementarity. With data on Korean firms over the period 1988~2017 we investigate the effects of intangibility and profitability on employment growth based on the econometric approach of system GMM. The empirical results are as follows. (1) the profit rate has gradually led to lower employment growth, while it had positive effect on employment before the period of financial crisis. The estimated values and signs of profit rate coefficients varies from traditional industries to high/medium tech. industries. (2) the effect of increasing asset intangibility ratio on employment growth is negative and statistically significant. (3) the coefficients of interaction term of (profit rate ${\times}$ intangibility ratio) have significant negative values. It means employment effect of profit rate are becoming higher(lower) as intangibility ratio is at the lower(higher) level; profits rate and intangibility are not complement with each other. The results imply that to boost employment industrial policy which has the capacity to coordinate business intangibility is preferred to expansionary demand policy.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.183-186
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• 2003

Customer profitability recognition is easier with CRM enabling technologies and the strategy of firing unprofitable customers prevails in the market. However, in the digital and Internet age, network externality is becoming more important. Therefore, the concern over firing unprofitable customers has increased. Our research is intended to develop strategic guidance for customer selection when firms implement CRM in the market with network externality.

• The Journal of Fisheries Business Administration
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• v.43 no.1
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• pp.75-85
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• 2012

In this paper, we study the extent to which the pecking order theory of capital structure provides a satisfactory account of the financing behavior of Korean fisheries firms using financing deficit. The major results of this study are as follows. Firstly, we find that the financing deficit is a important factor that explains the pecking order theory of fisheries firms'capital structure. However, the financing deficit does not wipe out the effects of conventional variables. The information in the financing deficit appears to be factored in along with many other things that fisheries firms take into account. Such result is consistent with the result of Frank and Goyal(2003). Secondly, we find that profitability is only one factor explaining the capital structure of fisheries firms among conventional variables when we test the regression of leverage with financing deficit during post IMF period. This result is different from the previous researches of Korean fisheries firms. (Kang and Jeong; 1997, Nam, Lee, and Hong; 2011) Finally, we examine the dynamics of capital structure of Korean fisheries firms firstly. It will allow a more detailed analysis for capital structure determinants for Korean fisheries firms.

• Proceedings of the Technology Innovation Conference
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• 2005.08a
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• pp.5-28
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• 2005

This paper estimates the effect of networks on innovative performance at the firm level , using Korean Innovation Survey (KIS) dataset Product innovation, product improvement , and process innovation are used as proxies for innovative activity. The explanatory variables such as firm size, market concentration ratio, lagged profitability, foreign ownership, export ratio, firm's age, formal R&D activity, and industrial R&D intensity are yet other considerations. With two year-long (2000 and 2001) data from 1,124 Korean manufacturing firms, we estimated the logistic regression model. The research finding indicates that the external networks have a strong positive effect on innovative output regardless of type of innovation. However, the network effects by partner (other firms or research institutions) vary across the type of innovation. Especially, we found that the user-supplier linkage plays an important role in product ion innovation, product improvement, and process innovation.