• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.1-11
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• 2009

When micro data are released to users, record by record data are disclosed and the disclosure risk of respondent's information is inevitable. Statistical disclosure control techniques are statistical tools to reduce the risk of disclosure as well as to increase data utility in case of data release. In this paper, we reviewed the concept of disclosure and disclosure risk as well as statistical disclosure control techniques and then investigated selection strategies of a statistical disclosure control technique related with data utility. The risk-utility frontier map method was illustrated as an example. Finally, we listed some check points at each step when microdata are released.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.355-365
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• 2023

This study examined the relationship between corporate governance and risk disclosure via a systematic literature review and bibliometric visualization analysis. The study aimed to present evidence of risk disclosure intellectual structure, volume, and development knowledge trends. Data was extracted from Scopus and analyzed with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and RTools. In turn, 64 articles were extracted from the Scopus database. The results demonstrated that the number of corporate governance and risk disclosure publications increased significantly from 2015 to 2019 compared to before 2015. RTools revealed the most prominent journals, authors, and interests in the field. The co-occurrences map was constructed based on 208 keywords from 64 articles, where the keywords were required to appear once in the research. Interestingly, the keyword search yielded new concepts relatively unexplored in the risk disclosure field. The 13 clusters were generated, which contained 1987 total links and 1567 direct citations. Based on the scientific analysis discussion, corporate governance and risk disclosure is an interesting topic that has produced many publications. Applying research keywords arguably aided in producing and publishing papers in top journals. Despite the number of publications decreasing due to the COVID-19 pandemic, the pandemic also presented new opportunities for future research.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.67-72
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• 2018

The purpose of this study is to investigate the effect of quality of management discussion and analysis (MD&A) disclosure on stock price crash risk. The MD&A can be seen to reflect the management's intention on public announcement and reveals directly what the management says to communicate with outside investors. A firm's high-quality MD&A implies the management's commitment to communicating with the market, not allowing the managers to have incentives to hoard unfavorable news, which if revealed to the public, may lead to downward stock price corrections, damaging corporate values. The high-quality MD&A is, thus, likely to reduce the stock price crash risk. We use a logistic regression to test whether MD&A influences crash risk using listed companies in the Korean Stock Exchange (KSE) stock market between 2010 and 2013. Findings of the empirical test show that the higher the quality of MD&A, the less likely crash risk appears, implying that the MD&A disclosed adequately can be one of the factors mitigating firm's stock price crash risk. This study has implications as it presents the MD&A disclosure as a factor influencing stock price crash risk and suggests voluntary disclosure as well as mandatory disclosure acts as a variable that explains the risk of stock price crash.

• Korean Management Science Review
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• v.29 no.2
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• pp.1-20
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• 2012

While feeling anxious about the risk of exposure of personal information and privacy, users of microblogs and social network services are continuously using them. This study aims to develop a model to investigate this phenomenon. Specifically, this study explores the relationship between personal characteristics (represented by privacy concern and self-presentation) and an individual's self-disclosure. An individual's personal belief (represented by perceived risk and perceived trust) is also tested as an mediator between the relationship. Through a questionnaire survey to 183 twitter users in Korea, the results indicate that self-presentation has a direct influence on self-disclosure as well as an indirect influence through perceived trust. In contrast, privacy concern has not a direct but an indirect negative influence on self-disclosure through perceived risk. In conclusion, self-presentation has a stronger influence on self-disclosure then privacy concern to Twitter users. An individual who has a higher propensity for self-presentation will form a stronger perceived trust on Twitter, which in turn, affects the individual's self-disclosure. On the other hand, an individual who is more concerned with personal privacy will feel more serious about perceived risk, which in turn, negatively influences one's perception of the trust in Twitter as well as his desire for self-disclosure.

• The Journal of Economics, Marketing and Management
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• v.11 no.2
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• pp.23-32
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• 2023

Purpose: This study examines the effect of full information disclosure on seller profit when there exists information asymmetry between sellers and buyers, focusing on the risk averseness of buyers. By investigating the interaction between product quality and perceived risk through online sales data, we attempt to figure out the incentive structure of full information disclosure specifically when buyers are risk-averse, so that we can suggest more feasible information disclosure strategy to sellers. Research design, data and methodology: Our empirical model analyzes the sales data of collectible goods from a major online seller using Poisson regression. In our model, we have specifically considered risk-averseness of buyers by estimating the interaction effect between the product quality and perceived risk on seller profit, aiming for a more precise empirical analysis on sellers' incentive structure of full disclosure. Results: Our empirical analysis strongly supports the effect of interaction between product quality and perceived risk, showing that the incentive for full disclosure is much stronger when product quality is higher, and vice versa. Therefore, sellers are strongly encouraged to voluntarily reveal product weaknesses when their product quality is higher than average, while it is more profitable to hide any product defects when quality claim is lower than average. Conclusions: This study supports the related literature by confirming economic incentives for full disclosure, and also supplements and strengthens previous studies by presenting that the effect of interaction between product quality and perceived risk strongly affects seller profit. Our unique finding supports both mandatory disclosure and voluntary disclosure arguments and presents practical implications to marketing managers by suggesting that seller's incentive for revealing weaknesses depends on the level of seller's product quality.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.3
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• pp.442-458
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• 2023

This study aimed to elucidate the information privacy attitudes and behaviors of users of size recommendation services based on body information. Focusing on the privacy calculus theory, the effects of information privacy concerns as well as perceived risk and benefit of information disclosure on information disclosure intention were analyzed. Consumers who used size recommendation services based on body information were surveyed from August 18 to 24, 2022. Analysis of the 251 responses collected revealed that information privacy concerns did not significantly affect information disclosure intention. Information privacy concerns had a positive effect on perceived privacy risk; however, perceived privacy risk had a negative effect on information disclosure intention, while perceived privacy benefit had a positive effect on information disclosure intention. Therefore, the privacy calculus theory confirms the existence of the privacy paradox, revealing perceived privacy benefit has a greater impact on information disclosure intention than perceived privacy risk.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.1029-1041
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• 2013

Recently, along with emergence of big data, there are incresing demands for releasing information and micro data for public use so that protecting privacy and measuring risk of disclosure for released database become important issues in goverment and business sector as well as academic community. This paper reviews statistical methods for protecting privacy and measuring risk of disclosure when micro data or data analysis sever is released for public use.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.323-333
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• 2024

Recently, Syntheic data has been in the spotlight as a technology that can protect personal information while maintaining the patterns and characteristics of actual data. Accordingly, technical and institutional research on synthetic data is actively being conducted, but it is difficult to actively use synthetic data due to the lack of clear standards and guidelines. This study is a preliminary study for quantifying the disclosure risk of synthetic data, and derives a privacy disclosure risk index through statistical methodology and suggests specific application measures to comply with the General Data Protection Regulation(GDPR). It is expected that the disclosure risk and the balance of data utility can be controlled through the privacy disclosure risk index of this study in an open data environment.

• The Journal of Industrial Distribution & Business
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• v.10 no.6
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• pp.51-58
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• 2019

Purpose - Prior studies reported that the opacity of information caused stock price crash. If managers fail to disclose unfavorable information about the firm over a long period of time, the stock price is overvalued compared to its original value. If the accumulated information reaches a critical point and spreads quickly to the market, the stock price plunges. Information management by management's disclosure policy can cause information uncertainty, which will lead to a plunge in stock prices in the future. Thus, this study aims at examining the impact of disclosure quality on crash risk by focusing on the unfaithful disclosure firms. Research design, data, and methodology - This study covers firms listed on KOSPI and KOSDAQ from 2004 to 2013. Firms excluded from the sample are non-December firms, capital-eroding firms, and financial firms. The financial data used in the research was extracted from the KIS-Value and TS2000 database. Unfaithful disclosure firm designation data was collected from the Korea Exchange's electronic disclosure system (kind.krx.co.kr). Stock crash is measured as a dummy variable that equals one if a firm experiences at least one crash week over the fiscal year, and zero otherwise. Results - Empirical results as to the relation between unfaithful disclosure corporation designation and stock price crashes are as follows: There was a significant positive association between unfaithful disclosure corporation designation and stock price crash. This result supports the hypothesis that firms that have previously exhibited unfaithful disclosure behavior are more likely to suffer stock price plunges due to information asymmetry. Second, stock price crashes due to unfaithful disclosures are more likely to occur in Chaebol firms. Conclusions - While previous studies used estimates as a proxy for information opacity, this study used an objective measure such as unfaithful disclosure corporation designation. The designation by Korea Exchange is an objective evidence that the firm attempted to conceal and distort information in the previous year. The results of this study suggest that capital market investors need to investigate firms' disclosure behaviors.

• The Journal of Information Systems
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• v.21 no.4
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• pp.55-79
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• 2012

LBS(Location-Based Service) is one of the smartphone application services which has been receiving great attention recently. Various applications of smartphone use LBS to provide innovative services. However, use of LBS raises privacy concerns because the location information of users is constantly exposed. Privacy calculus perspective attempts to understand the characteristics of the user's privacy. It is based on the risk-benefit analysis in the economics' perspective. That is, when the benefit expected through personal information disclosure is higher than risk, we are willing to provide personal information. This research suggested a research model based on the privacy calculus perspective to clarify the effect of information disclosure intention of smartphone LBS application users. Based on the main factors of privacy calculus, perception of privacy risk and privacy benefit, the relationship of the perceived value and the information disclosure intention was empirically analyzed by utilizing structural equation modeling(SEM) methodology. According to the results of the empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between privacy concern and information disclosure intention. This study showed a strong evidence of antecedent factors based on privacy calculus of personal information disclosure in smartphone LBS applications.