Present Status and Prospect of Valuation for Tangible Fixed Asset in South Korea (유형고정자산 가치평가 현황: 우리나라 사례를 중심으로)
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- Journal of Korean Society of Industrial and Systems Engineering
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- v.46 no.1
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- pp.91-104
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- 2023
The records system is believed to have started in Italy in the 14th century in line with trade developments in Europe. In 1491, Luca Pacioli, a mathematician, and an Italian Franciscan monk wrote the first book that described double-entry accounting processes. In many countries, including Korea, the government accounting standards used single-entry bookkeeping rather than double-entry bookkeeping that can be aggregated by account subject. The cash-based and single-entry bookkeeping used by the government in the past had limitations in providing clear information on financial status and establishing a performance-oriented financial management system. Accordingly, the National Accounting Act (promulgated in October 2007) stipulated the introduction of double-entry bookkeeping and accrual accounting systems in the government sector from January 1, 2009. Furthermore, the Korean government has also introduced International Financial Reporting Standards (IFRS), and the System of National Accounts (SNA). Since 2014, Korea owned five national accounts. In Korea, valuation began with the 1968 National Wealth Statistics Survey. The academic origins of the valuation of national wealth statistics which had been investigated by due diligence every 10 years since 1968 are based on the 'Engineering Valuation' of professor Marston in the Department of Industrial Engineering at Iowa State University in the 1930s. This field has spread to economics, etc. In economics, it became the basis of capital stock estimation for positive economics such as econometrics. The valuation by the National Wealth Statistics Survey contributed greatly to converting the book value of accounting data into vintage data. And in 2000 National Statistical Office collected actual disposal data for the 1-digit asset class and obtained the ASL(average service life) by Iowa curve. Then, with the data on fixed capital formation centered on the National B/S Team of the Bank of Korea, the national wealth statistics were prepared by the Permanent Inventory Method(PIM). The asset classification was also classified into 59 types, including 2 types of residential buildings, 4 types of non-residential buildings, 14 types of structures, 9 types of transportation equipment, 28 types of machinery, and 2 types of intangible fixed assets. Tables of useful lives of tangible fixed assets published by the Korea Appraisal Board in 1999 and 2013 were made by the Iowa curve method. In Korea, the Iowa curve method has been adopted as a method of ASL estimation. There are three types of the Iowa curve method. The retirement rate method of the three types is the best because it is based on the collection and compilation of the data of all properties in service during a period of recent years, both properties retired and that are still in service. We hope the retirement rate method instead of the individual unit method is used in the estimation of ASL. Recently Korean government's accounting system has been developed. When revenue expenditure and capital expenditure were mixed in the past single-entry bookkeeping we would like to suggest that BOK and National Statistical Office have accumulated knowledge of a rational difference between revenue expenditure and capital expenditure. In particular, it is important when it is estimated capital stock by PIM. Korea also needs an empirical study on economic depreciation like Hulten & Wykoff Catalog A of the US BEA.
The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.
This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the "Gaon Chart," a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before 'the music bulk buying phenomenon', a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the "Gaon Chart", a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: 'Steady Seller' and 'One-Hit Wonder'. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artist's superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the 'Climbing the Chart' phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in the ranking of music over time, a field that has been relatively alienated centering on digital music. In addition, a new approach to music research was attempted by subdividing the pattern of ranking change rather than predicting the success and ranking of music.
INTRODUCTION Due to the high broadband internet penetration rate and its group-oriented culture, various types of online communities operate in Korea. This study use 'Uses and Gratification Approach, and argue that members' usage-needs satisfaction with brand community is an important factor for promoting community commitment. Based on previous studies identifying the effect of brand image on consumers' responses to various marketing stimuli, this study hypothesizes that brand image can be a moderate variable affecting the relationship between usage-needs satisfaction with brand community and members' commitment to brand community. This study analyzes the influence of usage-needs satisfaction on brand community commitment and how apparel brand image affects the relationships between usage-needs satisfactions and community commitments. The hypotheses of this study are proposed as follows. H1-3: The usage-needs satisfaction of apparel brand community (interest, transaction, relationship needs) influences emotional (H1), continuous (H2), and normative (H3) commitments to apparel brand communities. H4-6: Apparel brand image has a moderating effect on the relationship between usage-needs satisfaction and emotional (H4), continuous (H5), and normative (H6) commitments to apparel brand communities. METHODS Brand communities founded by non-company affiliates were excluded and emphasis was placed instead on communities created by apparel brand companies. Among casual apparel brands registered in 6 Korean portal sites in August 2003, a total of 9 casual apparel brand online communities were chosen, depending on the level of community activity and apparel brand image. Data from 317 community members were analyzed by exploratory factor analysis, moderated regression analysis, ANOVA, and scheffe test. Among 317 respondents answered an online html-type questionnaire, 80.5% were between 16 to 25 years old. There were a total of 150 respondents from apparel brand communities(n=3) recording higher-than-average brand image scores (Mean > 3.75) and a total of 162 respondents from apparel brand communities(n=6) recording lower-than-average brand image scores(Mean < 3.75). In this study, brand community commitment was measured by a 5-point Likert scale: emotional, continuous and normative commitment. The degree of usage-needs satisfaction (interest, transaction, relationship needs) was measured on a 5-point Likert scale. The level of brand image was measured by a 5-point Likert scale: strength, favorability, and uniqueness of brand associations. RESULTS In the results of exploratory factor analysis, the three usage-needs satisfactions with brand community were classified as interest, transaction, and relationship needs. Brand community commitment was also divided into the multi-dimensional factors: emotional, continuous, and normative commitments. The regression analysis (using a stepwise method) was used to test the influence of 3 independent variables (interest-needs satisfaction, transaction-needs, and relationship-needs satisfactions) on the 3 dependent variables (emotional, continuous and normative commitments). The three types of usage-needs satisfactions are positively associated with the three types of commitments to apparel brand communities. Therefore, hypothesis 1, 2, and 3 were significantly supported. Moderating effects of apparel brand image on the relationship between usage-needs satisfaction and brand community commitments were tested by moderated regression analysis. The statistics result showed that the influence of transaction-needs on emotional commitment was significantly moderated by apparel brand image. In addition, apparel brand image had moderating effects on the relationship between relationship-needs satisfaction and emotional, continuous and normative commitments to apparel brand communities. However, there were not significant moderate effects of apparel brand image on the relationships between interest-needs satisfaction and 3 types of commitments (emotional, continuous and normative commitments) to apparel brand communities. In addition, the influences of transaction-needs satisfaction on 2 types of commitments (continuous and normative commitments) were not significantly moderated by apparel brand image. Therefore, hypothesis 4, 5 and 6 were partially supported. To explain the moderating effects of apparel brand image, four cross-tabulated groups were made by averages of usage-needs satisfaction (interest-needs satisfaction avg. M=3.09, transaction-needs satisfaction avg. M=3.46, relationship-needs satisfaction M=1.62) and the average apparel brand image (M=3.75). The average scores of commitments in each classified group are presented in Tables and Figures. There were significant differences among four groups. As can be seen from the results of scheffe test on the tables, emotional commitment in community group with high brand image was higher than one in community group with low brand image when transaction-needs satisfaction was high. However, when transaction-needs satisfaction was low, there was not any difference between the community group with high brand image and community group with low brand image regarding emotional commitment to apparel brand communities. It means that emotional commitment didn't increase significantly without high satisfaction of transaction-needs, despite the high apparel brand image. In addition, when apparel brand image was low, increase in transaction-needs did not lead to the increase in emotional commitment. Therefore, the significant relationship between transaction-needs satisfaction and emotional commitment was found in only brand communities with high apparel brand image, and the moderating effect of apparel brand image on this relationship between two variables was found in the communities with high satisfaction of transaction-needs only. Statistics results showed that the level of emotional commitment is related to the satisfaction level of transaction-needs, while overall response is related to the level of apparel brand image. We also found that the role of apparel brand image as a moderating factor was limited by the level of transaction-needs satisfaction. In addition, relationship-needs satisfaction brought significant increase in emotional commitment in both community groups (high and low levels of brand image), and the effect of apparel brand image on emotional commitment was significant in both community groups (high and low levels of relationship-needs satisfaction). Especially, the effect of brand image was greater when the level of relationship-needs satisfaction was high. in contrast, increase in emotional commitment responding to increase in relationship-needs satisfaction was greater when apparel brand image is high. The significant influences of relationship-needs satisfaction on community commitments (continuous and normative commitments) were found regardless of apparel brand image(in both community groups with low and high brand image). However, the effects of apparel brand image on continuous and normative commitments were found in only community group with high satisfaction level of relationship-needs. In the case of communities with low satisfaction levels of relationship needs, apparel brand image marginally increases continuous and normative commitments. Therefore, we could not find the moderating effect of apparel brand image on the relationship between relationship-needs satisfaction and continuous and normative commitments in community groups with low satisfaction levels of relationship needs, CONCLUSIONS AND IMPLICATIONS From the results of this study, we draw several conclusions; First, the increases in usage-needs satisfactions through apparel brand communities result in the increases in commitments to apparel brand communities, wheres the degrees of such relationship depends on the level of apparel brand image. That is, apparel brand image is a moderating factor strengthening the relationship between usage-needs satisfaction and commitment to apparel brand communities. In addition, the effect of apparel brand image differs, depending on the level and types of community usage-needs satisfactions. Therefore, marketers of apparel brand companies must determine the appropriate usage-needs, depending on the type of commitment they wish to increase and the level of their apparel brand image, to promote member's commitments to apparel brand communities. Especially, relationship-needs satisfaction was very important factor for increasing emotional, continuous and normative commitments to communities. However the level of relationship-needs satisfaction was lower than interest-needs and transaction-needs. satisfaction. According to previous study on apparel brand communities, relationship-need satisfaction was strongly related to member's intention of participation in their communities. Therefore, marketers need to develope various strategies in order to increase the relationship- needs as well as interest and transaction needs. In addition, despite continuous commitment was higher than emotional and normative commitments, all types of commitments to apparel brand communities had scores lower than 3.0 that was mid point in 5-point scale. A Korean study reported that the level of members' commitment to apparel brand community influenced customers' identification with a brand and brand purchasing behavior. Therefore, marketers should try to increase members' usage-needs satisfaction and apparel brand image as the necessary conditions for bringing about community commitments. Second, marketers should understand that they should keep in mind that increasing the level of community usage needs (transaction and relationship) is most effective in raising commitment when the level of apparel brand image is high, and that increasing usage needs (transaction needs) satisfaction in communities with low brand image might not be as effective as anticipated. Therefore, apparel companies with desirable brand image such as luxury designer goods firms need to create formal online brand communities (as opposed to informal communities with rudimentary online contents) to satisfy transaction and relationship needs systematically. It will create brand equity through consumers' increased emotional, continuous and normative commitments. Even though apparel brand is very famous, emotional commitment to apparel brand communities cannot be easily increased without transaction-needs satisfaction. Therefore famous fashion brand companies should focus on developing various marketing strategies to increase transaction-needs satisfaction.