• Nutrition Research and Practice
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• v.18 no.1
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• pp.149-164
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• 2024

BACKGROUND/OBJECTIVES: The economic recession caused by the coronavirus disease 2019 pandemic disproportionately affected poor and vulnerable populations globally. Better uunderstanding of vulnerability to shocks in food supply and demand in the Asia Pacific region is needed. SUBJECTS/METHODS: Using secondary data from rapid assessment surveys during the pandemic response (n = 10,420 in mid-2020; n = 6,004 in mid-2021) in India, Indonesia, Myanmar, and Vietnam, this study examined the risk factors for reported income reduction or job loss in mid-2021 and the temporal trend in food security status (household food availability, and market availability and affordability of essential items) from mid-2020 to mid-2021. RESULTS: The proportion of job loss/reduced household income was highest in India (60.4%) and lowest in Indonesia (39.0%). Urban residence (odds ratio [OR] range, 2.20-4.11; countries with significant results only), female respondents (OR range, 1.40-1.69), engagement in daily waged labor (OR range, 1.54-1.68), and running a small trade/business (OR range, 1.66-2.71) were significantly associated with income reduction or job loss in three out of 4 countries (all P < 0.05). Food stock availability increased significantly in 2021 compared to 2020 in all four countries (OR range, 1.91-4.45) (all P < 0.05). Availability of all essential items at markets increased in India (OR range, 1.45-3.99) but decreased for basic foods, hygiene items, and medicine in Vietnam (OR range, 0.81-0.86) in 2021 compared to 2020 (all P < 0.05). In 2021, the affordability of all essential items significantly improved in India (OR range, 1.18-3.49) while the affordability of rent, health care, and loans deteriorated in Indonesia (OR range, 0.23-0.71) when compared to 2020 (all P < 0.05). CONCLUSIONS: Long-term social protection programs need to be carefully designed and implemented to address food insecurity among vulnerable groups, considering each country's market conditions, consumer food purchasing behaviors, and financial support capacity.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.

• KDI Journal of Economic Policy
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• v.13 no.1
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• pp.35-63
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• 1991

Currently, Korea's banking industry holds a sizable amount of non-performing loans which stem from the government-led bailout of many troubled firms in the 1980s. Although this burden was somewhat relieved with the aid of banks' recapitalization in the booming securities market between 1986-88, the insolvent credits still resulted in low profitability in the banking sector and have been detrimental to the progress of financial liberalization and internationalization. This paper surveys the corporate bailout experiences of major advanced countries and Korea in the past and derives a rationale for readjustment measures against non-performing loans, in which rescue plans depend on the nature of the financial system. Considering the features of Korea's financial system and the banking sector's recent performance, it discusses possible means of liquidation in keeping with the rationale. The conflict of interests among parties involved in non-performing loans is widely known as one of the major constraints in writing off the loans. Specifically, in the case of Korea, the government's excessive intervention in allocating credits has preempted the legitimate role of the banking sector, which now only passively manages its past loans, and has implicitly confused private with public risk. This paper argues that to minimize the incidence of insolvent loan readjustment, the government's role should be reduced and that the correspondent banks should be more active in the liquidation process, through the market mechanism, reflecting their access to detailed information on the troubled firms. One solution is that banks, after classifying the insolvent loans by the lateness or possibility of repayment, would swap the relatively sound loans for preferred stock and gradually write off the bad ones by expanding the banks' retained earnings and revaluing the banks' assets. Specifically, the debt-equity swap can benefit both creditors and debtors in the sense that it raises the liquidity and profitability of bank assets and strengthens the debtor's financial structure by easing the debt service burden. Such a creditor-led or market-led solution improves the financial strength and autonomy of the banking sector, thereby fostering more efficient resource allocation and risk sharing.

• 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.

• Journal of Distribution Science
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• v.8 no.1
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• pp.21-33
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• 2010

The ICT(information & communication technology) led to a dramatic change of floral distribution service, a phase of competition between wholesales and retail stores, and distribution channels in floral industry. It was expected that a role of the intermediaries in this industry would have reduced due to the improvement of transaction process by ICT. However, the ICT made to overcome a regional limit of the floral retail distribution service leading to an increase in sales and enlargement of the stores. And even it made possible to bring out another type of intermediaries such as private associations. This case study focuses on what kinds of efforts the floral wholesale distributors have made to enable a distribution process more smoothly between the wholesale distributors and retail stores through the information system, and what the failure factors in adopting the information system have been. This paper is also to examine how the wholesale distributors have changed themselves to gain dominant positions in distribution channels. As a result of the study, it was found that the intermediaries mostly failed in successfully achieving the distribution channel innovation through the information system because of several main reasons. FLOMARKET Inc. tried to innovate a distribution channel to obtain high quality goods through consolidating a wholesale distribution market in that segregated both floral joint market from free markets. after implementing the information system with consideration of the failure factors, FLOMARKET Inc. was able to minimize goods in stock and make a major purchase of various goods. In addition, it made a possible pre-ordering process and an exact calculation of purchasing goods so they could provide their products with market price in real time, which helped for the company to gain credits from their customers. Also, FLOMARKET Inc. established the information system which well suited to its business stage in order to deal with a rapidly changing distribution environment. It's so obvious that the transaction processing system of FLOMARKET Inc. definitely helped to share information among traders more seamlessly and smoothly in realtime, standardize goods, and make a transaction process clearer. Besides, the transaction information helped the wholesale distributors and retail stores to make more strategic decisions in their business because through the system they enabled to gather the marketing intelligence information more easily and convenient. If we understand that the floral distribution market is characterized by the low IT- based industry, it's worth to examine a case study proving that the information system actually increases the productivity of the transaction process in the floral industry.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.151-166
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• 2019

New drug development requires 10 to 15 years of long time and more than $ 1 billion in funding, ranging from basic research${\rightarrow}$preclinical medicine${\rightarrow}$clinical medicine${\rightarrow}$product approval${\rightarrow}$sales. Many new drug development bio-venture companies will continue to pursue new drug development with funds secured through listing on the securities market. This study focuses on the impact of the listing on the market of bio-venture companies in the development of new drugs. It is necessary to determine whether the increase in registered patent, preclinical, clinical and technology transfer contracts at the time of listing (D) The results of this study are as follows. We also analyzed whether the registered patent, preclinical, and clinical effects had significant effect on technology transfer contracts at two years after listing and listing. The results of the analysis are as follows. First, Korea's new drug development bio-venture firms increased their registered patents but did not increase their pre-clinical, clinical and technology transfer contracts. Second, at the time of listing and two years after listing, pre-employment has a significant effect on Korea's technology transfer contracts and has a significant effect on overseas technology transfer contracts. However, registered patents and clinics have significant influence on technology transfer contracts. Korea 's new drug development bio-venture firms showed patent increase despite the stock market listing, but pre-clinical, clinical and technology transfer contracts did not increase. In order to strengthen technological commercialization of new drug development bio-venture companies in the future, it is required to establish R & D strategy for efficient use of IPO subscription funds, open innovation through strengthening industry-academia-partnerships, and more sophisticated preclinical and clinical strategy establishment.

• International Area Studies Review
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• v.15 no.1
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• pp.341-365
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• 2011

This study used a non-parametric linear program, Data Envelopment Analysis to compare the efficiency of South Korean and Chinese banks from 2000 to 2008, which is said to be the reformation period of their financial structure. The sample banks were 10 commercial banks and 6 regional banks in Korea, and 4 state-owned commercial banks and 11 stock commercial banks in China. The main objective of our research is to compare their efficiency, as well as the changes in efficiency periodically according to the types of the banks. According to the periodical analysis, both of the countries showed steady increase in efficiency. This shows that finance restructure and merging were positive factors for bank's efficiency during the revolution of finance structure. The study showed that between Korea and China, the bank of Korea has higher efficiency than that of China. Although the reconstruction period happened around the same time, due to the earlier acceleration period to opening Korea's financial market, made the difference in efficiency.

• Journal of Distribution Science
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• v.13 no.9
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• pp.95-101
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• 2015

Purpose - This study provides evidence of the impact of the mandatory adoption of Korean equivalents to International Financial Reporting Standards (K-IFRS) on accounting quality. K-IFRS uses fair value as a basis of measurement and is characterized by principle-based standards. These characteristics can lead to a decrease in conservatism. Therefore, this study aims to examine whether or not there is a change in the level of conservatism before and after the enforcement of K-IFRS (2007~2014). By comparing 2007 through 2008 and 2013 through 2014 (excluding 2009 to 2012), we test "the temporary adjustment phenomenon" and document an overall decline in the degree of conservatism after the adoption of K-IFRS. Research design, data, and methodology - Our sample is comprised of data of all listed Korea Composite Stock Price Index (KOSPI) manufacturing distribution companies in Korea from 2007 to 2014, which yields the pooled sample of 4,412 (panel A) and 1,915 (panel B) firm-year observations for hypotheses 1 and 2. In line with recent literature, we adopt the Givoly and Hayn (2000) model, which recomputes the non-operating accruals, excluding two components that are most likely to capture the effect of restructuring activities: special items and gains or losses from discontinued operations. In addition, we also use these variables: SIZE, LEV, INV_CYCLE, ROA, OWN, and FOR. Results - Our sample period spans 2007 to 2014. This offers evidence on the effect of the mandatory adoption of IFRS on conservatism. Our findings can be summarized as follows. First, in panel A, for mandatory K-IFRS adoption (2011), we do not find any significant evidence of conservatism. We can guess that the "temporary adjustment phenomenon" is the reason that we do not find significant evidence of conservatism. Second, we investigate panel B from 2009 to 2012. We document an overall decline in the degree of conservatism after the adoption of K-IFRS. We can assume that these results are due to "the temporary adjustment phenomenon." Conclusions - This study finds that conservatism significantly decreased after IFRS adoption. In particular, this study makes the initial effort to elucidate "the temporary adjustment phenomenon" to analyze the effect of K-IFRS on conservative accounting. We argue that K-IFRS are conceptually conservative but that inappropriate application of the conservatism principles is likely to prevent financial reporting from reaching the level of conservatism targeted by the IASB. Overall, this paper contributes to the literature on IFRS and can be useful to capital market supervisors who are monitoring the trends of the firms implementing K-IFRS. Additionally, our results inform stakeholders of the potentially negative effect of the greater flexibility permitted by IFRS and/or lack of appropriate enforcement on key dimensions of accounting quality. This has important implications for Korean regulators and standard setters as they review the cost and benefits of IFRS. Our study also sheds light on the importance of the institutional environment in achieving the targeted objectives for improving financial reporting quality.

• Clinics in Shoulder and Elbow
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• v.16 no.2
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• pp.163-169
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• 2013

Designs of total elbow arthroplasty have been evolving with clinical experiences. Newer implants are expected to resolve current limitations and improve long term outcomes. This review article focuses on the basic knowledge of unlinked and convertible total elbow arthroplasty. There have been a variety of designs of unlinked total elbow prostheses. Some implants are still used in the market, while others are no longer commercially available. Modified and newer designs include more congruent contact surface, stemmed implant, and radiocapitellar arthroplasty. Two convertible elbow prostheses have been developed, and one implant is currently available in Korea. Conversion from an unlinked to a linked mode is performed by adding a linking cap. Unlinked total elbow arthroplasty, which restores native elbow kinematics, has a biomechanical rationale of lowering polyethylene wear and loosening of implants. It can be indicated in younger and higher demand patients, who have adequate bone stock and soft tissues. Convertible total elbow arthroplasty broadens implant selection and simplifies revision surgery. These newer prostheses possibly improve the long term outcomes and resolve disadvantages of linked prostheses in total elbow arthroplasty.