3.3.1. Content Analysis of News Coverage Articles about Security Incidents
With regards to criteria for collecting data, keywords as well as online keyword search tools were defined for the collection of news coverage articles. To clarify the above criteria, the relevant keywords were applied to the selection of news coverage articles that were appropriate to them. Thus, attempts were made to minimize errors and burdens when collecting the news coverage articles. News coverage articles are composed of a paragraph consisting of several sentences combined with another several ones. For a content analysis, the content should be reconfigured by setting a minimal unit for an analytical procedure. Therefore, unit of analysis was defined based on a paragraph and then coded. The title, running head and the images embedded in its text are major expressions that were already included in its main body; these were therefore excluded from the analysis.
Based on the contents of the news coverage articles collected, the information for the analytical procedure was composed of the name of firm experiencing the security incident, the unique ID for the identification of the firm experiencing the incident, the date of the news publications, their contents and their uniform resource locators (URL). Upon completion of the coding based on the above information, a relevant category was determined. Each category was combined using a single category. In addition, each theme was provided with a tone that best matched it. To describe the results of the content analysis performed in the current study, 12 categories were created with four theme subcategories that included the delinquency of the firm, additional damages and resulting losses, AIR and the mentioning of damages. Each theme was further classified into three tones: ‘More negative’, ‘Less negative’ and ‘Neutral’.
Table 4 provides a detailed description of the meaning of each variable.
Keywords and online keyword search tools, and news coverage articles about a firm experiencing a security incident were collected based on a unit of analysis. Then, news coverage articles about security incidents were coded based on the relevant category. A coding of collected news coverage articles is a process where the theme and category are persistently created or combined. With regards to a single security incident, a multitude of news coverage articles were identified. Considering an event study based on time-series data and the convenience of analysis, coding was performed in the order ranging from the first news coverage articles about each security incident to the latest one.
Reliability testing was the method used for securing the consistency and objectivity of the results in the coding of news coverage articles about security incidents. Of the total news coverage articles, 10% were selected as a sample. There should be a more than an 80% match between the results of the coding, performed by two investigators. It was determined that reliability can be secured using this method (
Lacy et al. 2015). Two investigators were therefore appointed as secondary coders and then trained for approximately two hours. This was followed by the preparation of the coding sheet. Holsti’s reliability coefficient was used, as proposed by
An and Gower (
2009). Until the overall average agreement rate exceeded 80%, criteria were established in a stepwise manner, and reconfiguration of the news coverage articles, and collection and coding of the sample data were repetitively performed, as previously proposed (
Lacy et al. 2015). The current study showed an overall average agreement rate of 86%; this corresponds to a good level of agreement.
After the coding of the results of the content analysis, the number of paragraphs, serving as the minimal unit of analysis of news coverage articles about security incidents, was summed and then quantified for a regression analysis in comparison with the results of the event study. The paragraph forming the main body of a single news coverage article was assigned with a 1 if it corresponded to the category, a single news coverage article was assigned with a 1 based on a multitude of the relevant categories. In two paragraphs sharing the same theme, duplicate sharing was permitted for the category. For a single security incident, a regression analysis was performed in comparison with the information about stock prices seen on an event study in such a manner that a value of 1 assigned to a multitude of news coverage articles was set as a sum of those of each category.
3.3.2. An Event Study of a Security Incident
In the current study, abnormal variations in stock prices due to security incidents were estimated using an event study. An earnings ratio of the daily stock prices for the estimation of the abnormal variation was used, based on the market model established by
Fama et al. (
1969). In the market model, after the estimation of the sensitivity of the corresponding item to the market earnings ratio, the normal one was calculated during the event period. In addition, the market model assumed that the current value of a firm is based on its assets and the flow of future predictable cash; this pretense was based on an efficient market hypothesis that the stock prices of a firm are directly reflected in the market.
The abnormal return (AR) was calculated by subtracting the daily normal earnings ratio, estimated based on the market model, from the actual earnings ratio during the event period. Moreover, it also estimated the CAR, a cumulative sum of AR, in each firm. Thus, it measured the effects of a specific incident on variations in stock prices serving as the value of the stock market prices of the corresponding firm. In an event study where the earnings ratio to the market factor (R
m,t) serves as an independent variable, the stock prices earnings ratio due to the unique factors of the corresponding firm (R
i,t) is reflected. β
i,t is referred to as a sensitivity to the stock price earnings ratio of the corresponding firm. In addition, α
i,t is referred to as an earnings ratio of the corresponding item that can be expected at a market earnings ratio of 0. Furthermore, ε
i,t is referred to as variations in stock prices due to unique factors. The normal earnings ratio before and after the occurrence of the security incident for the estimation of the abnormal one can be calculated as follows:
Ri,t: Stock return of firm i on day t
Rm,t: Rate of return the market index on day t
αi: Intercept for firm i
βi: Slope for firm i
εi,t: Disturbance term for stock i on day t
β
iR
m,t represents changes in the earnings ratio of stock i depending on those in the index of the total market. The error term is used to describe changes in the earnings ratio of a certain firm, i, which cannot be explained based on those in the total stock market, at the time of t. in addition,
αi +
βiR
m,t is referred to as an expected return that can be obtained when there is a persistent presence of the past performance before the occurrence of a certain security incident. The market portfolio earnings ratio, R
m,t, represents KOSPI or KOSDAQ, thus corresponding to the earnings ratio of a listed firm. The abnormal earnings ratio, AR, represents the degree of deviation from the range of errors of the predicted earnings ratio of a certain firm in the market model. The AR is used to calculate the profit that is deviated from the expectation due to the occurrence of a certain event based on the predicted variables in the market model (
Campbell et al. 2003).
The estimation period for the determination of difference in the actual stock prices after the prediction of AR is commonly set at 100–300 days. In the current study, it was set at 200 days, as this is most commonly used. Thus, the estimation period prior to the occurrence of the security incident was estimated. To ensure that there were no effects related to the security incident, a total of −230 days, extending from −200 to −30 days before the date of the news publication, were determined to be the estimation period (
Bose and Leung 2013). AR, serving as the prediction of errors, and CAR, the cumulative sum of the event window of AR, and the mean CAR of a total of 74 events were then individually expressed, as previously described (
Pandey and Kumari 2021):
The event window used for the analysis of the event is [0, 1]. Therefore, the date of the initiation of a CAR corresponds to 0 days before the date of the news publication (Day + 0). The date of the completion of a CAR corresponds to the following day of the date of the news publication (1 day) (Day + 1). Thus, the market reaction was analyzed during this period. The period of analysis is sensitive to the results. According to a review of the literature on event studies, as summarized in
Table 1, the date of the initiation and completion were determined as the period of analysis (
Bose and Leung 2013;
Campbell et al. 2003).
3.3.3. A Multiple Linear Regression Analysis of the Effects of News Coverage Articles on the Stock Prices
To identify the correlation between a content analysis of news coverage articles about security incidents and an event study, the following regression analysis was performed. Quantitative results of a content analysis for news coverage articles about security incidents are based on 4 themes and 3 categories under each theme, whose meanings are described in detail in
Table 4. Four themes include damage mention (DM), additional damage and loss (ADL), firm fault (FF) and aggressive incident response (AIR), each of which underwent regression analysis using 12 regression coefficients corresponding to 3 categories under each theme. The regression analysis formula is as follows:
DMtij: j subcategory variables of DM theme on t in a firm i (j = 1–3)
ADLtij: j subcategory variables of ADL theme on t in a firm i (j = 1–3)
FFtij: j subcategory variables of FF theme on t in a firm i (j = 1–3)
AIRtij: j subcategory variables of AIR theme on t in a firm i (j = 1–3)
If the security incident has a negative effect on the CAR, the results of an event analysis, β0 (coefficient of interest), would have a negative value. DM refers to details of damages due to the security incident. ADL refers to a concern for additional losses. FF refers to content about the delinquency of a firm. Finally, AIR is referred to as AIR. Of the news coverage articles about security incidents of a firm i, published on the first date of publication, the first is (C1) and the second is (C2) with a DM theme.
If there is a paragraph that corresponds to a category, β1 DM0i1 and β2 DM0i2, serving as DM values of a firm i, were given a value of 1 each. Thus, contents of news coverage articles were quantified. After a content analysis of the news coverage articles, a multiple regression analysis of the CAR was performed, corresponding to 0 days of a firm i, in comparison with the results of a quantitative analysis. Thus, the statistical significance was confirmed.
To analyze the statistical significance of the proposed regression model, a p-value of the regression coefficient was measured using a stepwise regression with a robust standard error where the variables of 12 categories were calculated in a fixed order during the regression analysis with the use of the SPSS software package for windows version 26.0 (SPSS Inc., Chicago, IL, USA). A stepwise regression is referred to as a regression analysis of variables after the removal of those with a higher degree of correlation or multiple collinearity. With regards to the level of statistical significance, results of the analysis were described for values with a p-value of ≤0.05.