• The Journal of Industrial Distribution & Business
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• v.8 no.5
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• pp.87-93
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• 2017

Purpose - This paper investigates whether managerial overconfidence is associated with firm-specific crash risk. Overconfidence leads managers to overestimate the returns of their investment projects, and misperceive negative net present value projects as value creating. They even use voluntary disclosures to convey their optimistic beliefs about the firms' long-term prospects to the stock market. Thus, the overconfidence bias can lead to managerial bad news hoarding behavior. When bad news accumulates and crosses some tipping point, it will come out all at once, resulting in a stock price crash. Research design, data and methodology - 7,385 firm-years used for the main analysis are from the KIS Value database between 2006 and 2013. This database covers KOSPI-listed and KOSDAQ-listed firms in Korea. The proxy for overconfidence is based on excess investment in assets. A residual from the regression of total asset growth on sales growth run by industry-year is used as an independent variable. If a firm has at least one crash week during a year, it is referred to as a high crash risk firm. The dependant variable is a dummy variable that equals 1 if a firm is a high crash risk firm, and zero otherwise. After explaining the relationship between managerial overconfidence and crash risk, the total sample was divided into two sub-samples; chaebol firms and non-chaebol firms. The relation between how I overconfidence and crash risk varies with business group affiliation was investigated. Results - The results showed that managerial overconfidence is positively related to crash risk. Specifically, the coefficient of OVERC is significantly positive, supporting the prediction. The results are strong and robust in non-chaebol firms. Conclusions - The results show that firms with overconfident managers are likely to experience stock price crashes. This study is related to past literature that examines the impact of managerial overconfidence on the stock market. This study contributes to the literature by examining whether overconfidence can explain a firm's future crashes.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.417-425
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• 2020

In order to predict and prevent hydrological disasters such as flood, it is necessary to accurately estimate rainfall. In this paper, an areal average rainfall estimation method using multiple elevation observation data of an electromagnetic wave rain gauge is presented. The small electromagnetic rain gauge system is a very small precipitation radar that operates at K-band with dual-polarization technology for very short distance observation. The areal average rainfall estimation method is based on the assumption that the variation in rainfall over the observation range is small because the observation distance and time are very short. The proposed method has been evaluated by comparing with ground instruments such as tipping-bucket rain gauges and a Parsivel. The evaluation results show that the methodology works fairly well for the rainfall events which are shown here.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.47-62
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• 2013

In this paper, we analyze the comparative advantage of industry innovation (R & D) activities. The method is that companies are classified suppliers dominated- industry, productionintensive industries and science-based industries, and data of Statistical analysis were collected HCCP (KRIVET). The result is that Tipping phenomena of science-based is apparent and suppliers dominated- industry is the lack of comparative advantage. The implications are as follows. suppliers dominated- industries that specialize in R & D capabilities, support R & D capability is required. Second, the policy in terms of support for R & BD (linking technology commercialization support innovation) should be strengthened. Third, SMEs in the leveling down of industry R & D capabilities should be supplemented.

• The korean journal of orthodontics
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• v.34 no.2 s.103
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• pp.165-175
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• 2004

Information on the limits of treatment could allow for more rational treatment Planning and better results after treatment. From this point of view, this article has attempted to discuss the limits of orthodontic tooth movement. A relatively wider range of tooth movement is expected after Class III surgical-orthodontics than after conventional orthodontic treatment in general. The purposes of this Paper were: first, to evaluate the reliability of teeth position measuring gauge; and second, to elucidate the limits of orthodontic tooth movement. Dental casts of fifty-fine subjects were analyzed by using Set-up model checker (InVisitec Co., Korea) before and aster the Class III surgical-orthodontic treatment. The changes of maxillary and mandibular dental arch widths were also measured from the canines to the second molars. To test the inter-examiner reliability, randomly selected casts were measured by another examiner. Descriptive statistics and paired t tests were used to explain the tooth movement during treatment. The results showed a relatively good reliability of measuring instruments and a very diverse range of tooth movement. Collective changes by the orthodontic tooth movement evaluated in Class III surgical-orthodontics allowed for a suggestive interpretation of specific treatment patterns. Arch width changes during the inter-arch coordination were mainly the result of tipping in both buccal segments. Based on the results of this study, the possibility of a change in dentition as a result of orthodontic treatment should be understood in order to launch a well-organized plan of treatment.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.127-140
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• 2010

The benefit that a consumer derives from the use of a good often depends on the number of other consumers purchasing the same goods or other compatible items. This property, which is known as network externality, is significant in many IT related industries. Over the past few decades, network externalities have been recognized in the context of physical networks such as the telephone and railroad industries. Today, as many products are provided as a form of system that consists of compatible components, the appreciation of network externality is becoming increasingly important. Network externalities have been extensively studied among economists who have been seeking to explain new phenomena resulting from rapid advancements in ICT (Information and Communication Technology). As a result of these efforts, a new body of theories for 'New Economy' has been proposed. The theoretical bottom-line argument of such theories is that technologies subject to network effects exhibit multiple equilibriums and will finally lock into a monopoly with one standard cornering the entire market. They emphasize that such "tippiness" is a typical characteristic in such networked markets, describing that multiple incompatible technologies rarely coexist and that the switch to a single, leading standard occurs suddenly. Moreover, it is argued that this standardization process is path dependent, and the ultimate outcome is unpredictable. With incomplete information about other actors' preferences, there can be excess inertia, as consumers only moderately favor the change, and hence are themselves insufficiently motivated to start the bandwagon rolling, but would get on it once it did start to roll. This startup problem can prevent the adoption of any standard at all, even if it is preferred by everyone. Conversely, excess momentum is another possible outcome, for example, if a sponsoring firm uses low prices during early periods of diffusion. The aim of this paper is to analyze the dynamics of the adoption process in markets exhibiting network effects by focusing on two factors; switching and agent heterogeneity. Switching is an important factor that should be considered in analyzing the adoption process. An agent's switching invokes switching by other adopters, which brings about a positive feedback process that can significantly complicate the adoption process. Agent heterogeneity also plays a important role in shaping the early development of the adoption process, which has a significant impact on the later development of the process. The effects of these two factors are analyzed by developing an agent-based simulation model. ABM is a computer-based simulation methodology that can offer many advantages over traditional analytical approaches. The model is designed such that agents have diverse preferences regarding technology and are allowed to switch their previous choice. The simulation results showed that the adoption processes in a market exhibiting networks effects are significantly affected by the distribution of agents and the occurrence of switching. In particular, it is found that both weak heterogeneity and strong network effects cause agents to start to switch early and this plays a role of expediting the emergence of 'lock-in.' When network effects are strong, agents are easily affected by changes in early market shares. This causes agents to switch earlier and in turn speeds up the market's tipping. The same effect is found in the case of highly homogeneous agents. When agents are highly homogeneous, the market starts to tip toward one technology rapidly, and its choice is not always consistent with the populations' initial inclination. Increased volatility and faster lock-in increase the possibility that the market will reach an unexpected outcome. The primary contribution of this study is the elucidation of the role of parameters characterizing the market in the development of the lock-in process, and identification of conditions where such unexpected outcomes happen.