• Proceedings of the Fisheries Business Administration Society of Korea Conference
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• 2007.12a
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• pp.167-184
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• 2007

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut-down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t-test is used to identify the differences in financial variables between the distressed group and the non-distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990$\sim$1993), period 2(1994$\sim$1997), period 3(1998$\sim$2002). The final model built from whole sample appled each three sub-samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub-sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• The Journal of Fisheries Business Administration
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• v.39 no.2
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• pp.61-79
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• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.185-193
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• 2011

The successful and sustainable growth of SMEs depends on their ability of strengthen their competitiveness in quality and cost and service more than anything else as a fundamental of operation. Among these key competitive factors of SMEs, quality is the most critical factor in manufacturing business fields. There are many different ways to improve the quality performance but it needs proper management decision to choose the best way what can maximize outputs with minimum inputs. And it needs effective measurement methods and some indicators to analysis the quality performance properly. The quality cost is one of the simplest key indicators to measure the quality performance and the effectiveness of quality related management decisions. In this study, through survey on local SMEs, we found that their average annual quality cost ratio versus turnover - total amount of annual quality cost divided by annual turnover - is around 3.69% excluded some SME's performances what have different quality control measures with others. And we found some results what corresponded with the early studies on the correlations between those categorized quality costs factors and some discrepancies between some of the literature model and the early case study results as follows. There were negative correlations between the Prevention costs and the External failure costs, and the Appraisal costs and the External failure costs, and there was positive correlation between the Appraisal costs and Internal failure costs same as early studies. But, we couldn't found any strong negative correlations between the Cost of control - Prevention costs & Appraisal costs - and the Cost of Failure of control - Internal & External failure costs -.

• Korean journal of communication and information
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• v.20
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• pp.7-32
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• 2003

This essay provides a critical introduction to some of the major issues relating to ITV Digital. The demise of ITV Digital has hit the economics of broadcasting industry in UK. ITV Digital's failure is seen as digital nightmare. This study approaches to three dimensions of the failed ITV Digital. There are the failure of policy, business strategy, technological debacle. As I have discussed, competitive environment of digital broadcasting squeezed ITV Digital into financial trouble. In order to examine current development of digital terrestrial television, three questions have been raised. First, What is the government of digital broadcasting? Second, What is the business strategy of ITV Digital? In particular, the failure of business model deserved careful watching. Third, What is the failure of digital technology?

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.207-217
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• 2005

Business mergers are a direct result of rapid changes in the current corporate environment. They are occurring in many industries, including financial institutions. As information systems prove increasingly indispensable in the integration of companies’ business systems, information system integration is becoming increasingly necessary. However, in many cases such integration does not work well. Therefore, this paper proposes a new framework using both IS integration model and IS integration phases to analyze systems failure in IS integration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.857-862
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• 2017

The management of the electric power facilities became important in accordance with the industrial development and electric power facilities were influenced by weather. Even if the same kind of electric power facilities is estimated for extracting the time-varying failure rate, the failure rate could be different depending on external effect such as climate. This research will show the data mining modeling of the weather-related outage and influence of weather on the electric power facility with recent data.

• International Journal of Quality Innovation
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• v.10 no.1
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• pp.37-51
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• 2009

The purpose of TQM (Total Quality Management)-centered organizational culture is to enhance the efficiency of business through the proper allocation and concentration of restricted resources. In order to maximize the corporate profitability through customer satisfaction, what kind of, when and how many resources should be allocated and managed to the preventive TQM activities and corrective TQM activities have become a very important decision making factors at the point of high management. This study aims to identify the causal relationships of quality-centered organizational culture on service quality and customer satisfaction relating to service failure in food service industry. And this study is intended to discover the factors of quality-centered organizational culture which impacts on service recovery justice after service failure happens, and it can be helpful for the top managers to make a decision to how to form corporate structural culture.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.173-177
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• 2010

It is well known that if the parent distribution has a nonnegative support and has increasing failure rate, then all the order statistics have increasing failure rate (IFR). The result is not necessarily true in the case of bivariate distributions with dependent structures. In this paper we consider a symmetric bivariate exponential distribution and show that, two marginal distributions are IFR and the distributions of the minimum and maximum are constant failure rate and IFR, respectively.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.45-61
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• 2017

Business intelligence has been attracting much attention these days. Despite such popularity of BI systems, it is widely known that about a half of BI system projects have failed. To grasp why many BI projects end in failure and what factors would make BI projects less failure-prone, a number of BI studies were made to produce a variety of CSFs. However, there is a paucity of information on whether these CSFs are distinctive from those of typical information systems. By identifying how BI CSFs differ from CSFs of typical information systems, we would be able to explain why most BI projects are more likely to be failure. It is believed that a corrective measure about CSFs will lead to more success in future BI projects. In addition, though there have been a number of similar types of BI systems such as decision support systems and executive information systems in existence, there was no study to determine whether there is ever a discrimination between CSFs of BI systems and the similarly-titled systems. This study is to answer these questions using a literature review analysis. The findings of our study are expected to be helpful in a successful implementation of BI systems.

• Journal of Distribution Science
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• v.15 no.1
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• pp.15-20
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• 2017

Purpose - Other customers within the same service environment do influence a customer' attitude and behavior toward a service firm. Specially, other customers' misbehaviour and various service problems stemmed from them could make the other customers suffer some bad experiences. However, there are few studies to answer how the spillover effect of a service failure arisen from other customers' misbehavior. This study is aimed to examine how service failure due to the dysfunctional behavior of other customers has negative effects on customer evaluation with the service provider. Research design, data, and methodology - Data were collected from a survey based on consumers' retrospective experiences in airline service context. The hypothesized relationships were tested conducting structural equation modeling. Results - Our results show that the attribution of a firm responsibility for other-customer failure has a positive influence on customer's recovery expectation, in turn, it is negatively related to customer satisfaction. Furthermore, perceived service provider's efforts positively influence customer satisfaction. Conclusions - Although a service failure was caused by other customer's misbehavior, employees should be able to alleviate any bad feelings of the affected customers. Furthermore, service providers should provide proper recovery efforts for solving problems caused by the other customers for the wounded customers.