• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.147-154
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• 2021

Recently, it has been observed that as the level of Science and Technology in Korea is improving, the demand for technology transfer from overseas buyers is also increasing. A technical value is an important factor for the technology transfer process and the valuation of technology should be performed reasonably. Specifically, a non-economical value has to be examined thoroughly when conducting the valuation for a technology that depends on public values. Since public technology has public benefit as its purpose when compared to technology from the private sector, its discount rate should be appropriately assessed and reflected in its valuation process. In this context, this study presents the methodology of valuation of public technology particularly relating to the transfer of technology from the national defense industries. To be specific, both an application method of the discount rate according to the characteristics and the purpose of the target technology and a qualitative and quantitative evaluation method to reflect the public values are presented. The proposed method for the valuation of defense technology could be used practically both in strengthening bargaining capability based on the reasonably derived technical values for transfer of national defense technology abroad and in the compilation of budgets for technology development in the future.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.103-110
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• 2022

Online transactions are more familiar in various fields due to the development of the ICT and the increase in trading platforms. In particular, the amount of transactions is increasing due to the increase in used transaction platforms and users, and reliability is very important due to the nature of used transactions. Among them, the used car market is very active because automobiles are operated over a long period of time. However, used car transactions are a representative market to which information asymmetry is applied. In this paper presents a DID-based transaction model that guarantees reliability to solve problems with false advertisements and false sales in used car transactions. In the used car transaction model, sellers only register data issued by the issuing agency to prevent false sales at the time of initial sales registration. It is authenticated with DID Auth in the issuance process, it is safe from attacks such as sniping and middleman attacks. In the presented transaction model, integrity is verified with VP's Proof item to increase reliability and solve information asymmetry. Also, through direct transactions between buyers and sellers, there is no third-party intervention, which has the effect of reducing fees.

• Korean Journal of Audiology
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• v.24 no.1
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• pp.29-34
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• 2020

Background and Objectives: Bilateral microphones with contralateral routing of signal (BiCROS) hearing aid is an option for hearing rehabilitation in individuals with asymmetric sensorineural hearing loss (ASNHL). The clinical factors influencing the trial and purchase of BiCROS were investigated. Subjects and Methods: We reviewed the medical records of 78 patients with ASNHL who were recommended to use BiCROS and analyzed the demographic and audiological factors influencing the trial and purchase of BiCROS. Results: Among the 78 patients, 52 (66.7%) availed of the free BiCROS trial and 21 (26.9%) purchased BiCROS. The mean pure tone audiometry (PTA) air conduction (AC) threshold of the better- and worse-hearing ears were 44.2±12.8 dB and 90.7±22.5 dB HL, respectively. The decision for trial or purchase of BiCROS was not influenced by age, sex, duration of hearing loss of the worse-hearing ear, or PTA AC threshold or speech discrimination score of both ears. The first and third quartiles of the PTA AC thresholds for the better-hearing ear of BiCROS buyers were 38.75 dB and 53.75 dB HL, respectively. The counterpart values for the worse-hearing ear were 72.50 dB and 118.75 dB HL, respectively. Conclusions: The clinical factors analyzed in this study were found to be irrelevant to the trial and purchase of BiCROS in patients with ASNHL. Nevertheless, the distribution range of the auditory thresholds of the subjects using BiCROS can be a useful basis for the counseling of patients with ASNHL and selection of candidates for BiCROS use.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.367-373
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• 2022

The purpose of this study is to derive the factors for purchasing a meal kit in their 20s and 30s and analyze the purchasing behavior from which factors they want to buy a meal kit in each lifestyle type. The first methodology of this study is inducing 7 factors derived from previous research on purchasing a meal kit. The second is the in-depth interview on 3 male and 3 female participants with clear purchasing criteria. As a result of the study, meal kit buyers in their 20s-30s evaluated the importance of purchasing factors in the order of quality, convenience, and taste on average in the survey. In in-depth interviews, more than half answered that they could be satisfied with the experience of using the meal kit at least freshness met. In conclusion, MZ generation meal kit consumers have a high rate of pursuing rational consumption. This study is valuable in understanding the priorities of the MZ generation's meal kit purchasing attributes and examining lifestyle type's purchasing behaviors.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.29-41
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• 2022

Since the first sale of a banner advertisement in 1995, electronic commerce has become a new transaction channel for consumers. With more than 20 years of its history, electronic commerce has become an important consumption channel for everyone and inexperience is no more a reason that discourages the consumption through this channel. The great expansion of this channel is now a formidable thereat to traditional channels. However, products with high asset specificity and complexity are still having difficulty to be traded over the online channel where the experience of the products for a consumer is limited. Especially, variations of the same product's quality depending on how pre-owners used the product and high complexity to describe the quality of the products prevent used goods from being traded over e-channels. Added to that, the information asymmetry between sellers and buyers for used goods makes the establishment of market transaction difficult. Considering the challenges, the current case study discusses thredUP, a clothing resale platform company. In this paper, we study how the company could overcome those limitations in this toughest resale market through the use of AI for dynamic pricing and standarized product quality ratings. In addition, we also hope to provide readers with the opportunity to understand the secondhand industries and its market, and see where it is heading for in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.269-280
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• 2022

With the rise of a decentralized finance market (so called, DeFi) using blockchain technology, users and capital liquidity of decentralized finance applications are increasing significantly. The Automated Market Maker (AMM) is a protocol that automatically calculates the asset price based on the liquidity of the decentralized trading platform, and is currently most commonly used in the decentralized exchanges (DEX), since it can proceed the transactions by utilizing the liquidity pool of the trading platform even if the buyers and sellers do not exist at the same time. However, Automated Market Maker have some disadvantages since the cost efficiency of each transaction using Automated Market Maker depends on the liquidity size of some liquidity pools used for the transaction, so the smaller the size of the liquidity pool and the larger the transaction size, the smaller the cost efficiency of the trade. To solve this problem, some platforms are adopting Transaction Path Routing Algorithm that bypasses transaction path to other liquidity pools that have relatively large size to improve cost efficiency, but this algorithm can be further improved because it uses only a single transaction path to proceed each transaction. In addition to just bypassing transaction path, in this paper we proposed a Multi-Path Routing Algorithm that uses multiple transaction paths simultaneously by distributing transaction size, and showed that the cost efficiency of transactions can be further improved in the Automated Market Maker-based trading environment.

• Journal of Korean Society for Quality Management
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• v.50 no.2
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• pp.287-304
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• 2022

Purpose: The size of the salad consumption market has expanded since Covid-19, and continuous growth is predicted. Therefore, by extracting influential core purchasers in the salad consumption market and analyzing their purchasing behaviors and consumer types, this study intended to provide basic data for establishing a marketing strategy. Methods: The analysis data is the purchasing data of 576 people who have purchased salads between 2016 and 2020 (panel data of the Rural Development Administration), and in the social network analysis, the centrality structure was analyzed. Results: First, in the results of analyzing the causes of the rapid increase in salad consumption in 2020, it was found that the increase in consumption of new purchasers (n=102) had little effect. The existing consumer type (n = 474), which has been the majority of the salad consumption market so far, were consumers with stable income. However, the results of study indicated that the type of consumers has expanded since low-income class as well as high-income class increased consumption of purchasing salad. Second, in the results of analyzing the types of key purchasers with great influence in the salad consumption market, there was a difference from the results of frequency analysis in age, number of family members, existence/absence of children, and income decile. This suggests that there should be a difference between the type of customers according to the apparent quantitative figure and the actual influential purchasers. Third, in the results of analyzing the salad purchasing behaviors of core purchasers, the purchasing site for existing purchasers was large-scale marts and for new purchasers it was corporate-type supermarkets. Purchases were concentrated on Saturdays for both existing and new purchasers. As for the purchased products, existing purchasers had a high preference for products made of chicken, and new purchasers had a high preference for vegetable/fruit salad. In particular, in the results of purchased products by age group, in the case of 50s and 60s, it was an interesting result that there was a difference between the products purchased by the existing and new purchasers even though they were the same age. Conclusion: When establishing a marketing strategy in the salad consumption market, it is necessary to pay attention to the purchasing behavior of key buyers.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Land and Housing Review
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• v.14 no.3
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• pp.55-75
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• 2023

Based on prior studies on real estate policy, tax policy, and financial policy, this study examined how tax policy and financial policy affected real estate prices using monthly data from January 2014 to December 2021. We performed a VAR model using unit root tests, cointegration tests, as well as conducted impulse response analysis and variance decomposition analysis. The results are as follows. First, the tax regulation index and the financial regulation index had no discernible impact on housing prices. Specifically, a one-sided stabilizing regulatory policy was ineffective and, instead, led to unintended side effects, such as price increases resulting from reduced transaction volume. Secondly, mortgage rates had a negative impact on the housing sale price index. In other words, an increase in interest rates might led to a decrease in housing prices. Thirdly, an increase in the transfer difference, which involves capital gains tax, has a positive effect on housing prices. This led to rising housing prices because the transfer taxes were shifted to buyers, causing them to hesitate to make purchases due to the increased tax burden. Fourthly, both acquisition taxes and mortgage loans had relatively little impact on housing prices.

• Information Systems Review
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• v.23 no.4
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• pp.45-67
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• 2021

As the transaction volume of the C2C second-hand market is growing, the number of frauds, which intend to earn unfair gains by sending products different from specified ones or not sending them to buyers, is also increasing. This study explores the model that can identify frauds in the online C2C second-hand market by examining the postings for transactions. For this goal, this study collected 145,536 field data from actual C2C second-hand market. Then, the model is built with the characteristics from postings such as the topic and the linguistic characteristics of the product description, and the characteristics of products, postings, sellers, and transactions. The constructed model is then trained by the machine learning algorithm XGBoost. The final analysis results show that fraudulent postings have less information, which is also less specific, fewer nouns and images, a higher ratio of the number and white space, and a shorter length than genuine postings do. Also, while the genuine postings are focused on the product information for nouns, delivery information for verbs, and actions for adjectives, the fraudulent postings did not show those characteristics. This study shows that the various features can be extracted from postings written in C2C second-hand transactions and be used to construct an effective model for frauds. The proposed model can be also considered and applied for the other C2C platforms. Overall, the model proposed in this study can be expected to have positive effects on suppressing and preventing fraudulent behavior in online C2C markets.