• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.66-73
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• 2022

In order to induce users to purchase excellent products in the water industry that satisfy the technical standards of excellent products, in this study, it is to present the advantages of the cost aspect of the pumps as the objective basis. It will be to promote technology development of domestic water companies and to create a virtuous cycle structure in the water industry. In order to present an objective basis for the merits in terms of cost, an economic evaluation was conducted through life cycle cost analysis. For the LCC analysis, initial cost (pump cost and installation cost), operation cost (energy cost and maintenance cost) and demolition cost (disposal cost and residual value) are searched and calculated. As the results of comparison on two capacity of pumps, the energy cost of the excellent pump is 212 million KRW lower than the that of general pump in the large pump. The cost of excellent pump was 17 million KRW lower than that of general pump in small capacity pump. As the results of sensibility test, if the product is developed in the direction of improving pump efficiency and increasing the replacement cycle of consumables, it is predicted that the effect on LCC will be large.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.361-372
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• 2023

In this study, three luxury fashion start-up platforms, Balaan, Trenbe, and Must-it, were selected as research subjects. The purpose of this study is to compare and analyze the marketing mix strategies of each of the three online sites. The results of our study are as follows. First of all, the product strategies of the three luxury platform companies are characterized by the composition of products from high-end brands to SPA brands, and product composition such as kids, home living, Used goods and art in addition to women's and men's wear. In addition, the pricing strategies of luxury platforms show price differences depending on the luxury platform even for the same product. It is shown as a structure that directly determines margin. Therefore, in order to secure an edge in price competitiveness, each platform provided discount coupons and savings that are not available in offline stores such as department stores, providing opportunities to purchase luxury goods at a lower price than offline stores.Lastly, the sales promotion strategies of the three luxury platform companies was used include price discount promotions such as price discounts, discount coupons, and regular sales, and value-added sales such as membership registration/review points, events, product information, delivery services, social contribution activities, and SNS utilization.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.371-401
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• 2022

If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.

• Asia Marketing Journal
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• v.15 no.4
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• pp.33-49
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• 2014

Environmental concern has been an important issue for a few decades, and the extent of consumer demand for eco-friendly consumption has been increased. This study seeks to investigate consumers' willingness to pay (WTP) a premium for eco-friendly cosmetics. This study evaluates how much more a consumer is willing to pay for eco-friendly cosmetics and examines significant factors influencing consumers' WTP for eco-friendly cosmetics. Consumers' WTP is measured using four different ecofriendly cosmetics: low-priced skin care cosmetics, low-priced makeup cosmetics, high-priced skin care cosmetics, and high-priced makeup cosmetics. This study uses the contingent valuation method (CVM) to estimate consumer's WTP for eco-friendly cosmetics. Survey questions were designed using both dichotomous choice and payment card method of CVM. Through face to face interviews and on-line surveys, the data were collected from women between 20 and 49 years old residing in Seoul and Kyeonggi area, Korea, in May 2010. A total of 226 questionnaires (132 from interviews and 94 from on-line) were included for the analytical sample in this study. The data were analyzed using descriptive analysis, T-test and Log-Logit analysis. The findings are as follows: First, the WTP measured by dichotomous choice method was estimated using the Log-Logit analysis. The results showed that the estimated WTP for low-priced skin care cosmetics was 19,152 won, which was 27.7% higher than the reference price, 15,000 won. For low-priced makeup cosmetics, the estimated WTP was 18,524 won, and its green premium was 21.0%. The estimated WTP for high-priced skin care cosmetics was 59,128 won, which was 18.3% higher than the reference price, 50,000 won. For high-priced makeup cosmetics was 57,666 won, and its green premium was 15.3%. Second, the WTP measure by payment card method was estimated using descriptive analysis. The results showed that the respondents were willing to pay 17,955 won for low-priced skin care cosmetics, which was 19.7% higher than the reference price, 15,000 won and 17,595 won for low-priced makeup cosmetics, which was 17.3% higher than the reference price. For high-priced skin care cosmetics, the average WTP was 56,950 won which was 13.9% higher than the reference price, 50,000 won. For high-priced makeup cosmetics, the average WTP was 55,650 won, which was 11.3% higher than the reference price. Overall, the WTP was higher in order of low-priced skin care, low-priced makeup, high-priced skin care, and high-priced makeup. It means that consumers decide degree of premium based on the price and the attributes of eco-friendly products. Third, the findings showed that age, monthly income, and having children or not were statistically significant factors that influenced consumers' willingness to pay for eco-friendly cosmetics. Other explanatory variables such as education, marital status, job, purchase experience of eco-friendly products, and environmental concerns did not show any statistical significance. The major contribution of this study is the investigation of the value of green attributes of the products by using CVM. Unlike most previous researches, this research used two methods of CVM, the dichotomous choice and the payment card, so it enhanced the reliability of research. According to this study, consumers showed price sensitivity when they pay green premium. These findings can be used as useful information to establish marketing strategies for green cosmetics.

• Asia Marketing Journal
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• v.11 no.1
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• pp.1-27
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• 2009

The research compared the motivational network of traits predictive of complaint attitudes across consumers in the U.S. and South Korean cultures. Overall, the results revealed a similar pattern of traits predictive of complaint attitudes in the two cultures. The traits of value consciousness, general self-efficacy, emotional instability, and the need for material resources were positively related to attitudes toward complaining. In contrast, conscientiousness was negatively related to complaint attitudes. The only trait predictor of complaining attitude that was significantly different between the Korean and U.S. samples was shopping enjoyment. It was negatively related to complaining attitude in the U.S. sample but unrelated to complaining attitude in the Korean sample. Understanding the personality traits predictive of complaint attitudes has the potential to help marketers develop messages that will encourage the low complaint prone to voice their dissatisfaction. This is important, because when a consumer complains about and unsatisfactory purchase, it gives the firm a chance to take actions to avoid losing a customer.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.73-97
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• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.59-66
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• 2020

Recently, cultivation and management technologies have been needed to adapt due to climate change, which is causing abnormal weather conditions. One technique is to increase the utilization of evergreen broad-leaved species with high ornamental value. A total of five treatments were installed (1m×22.5m), including 60g/㎡ and 80g/㎡ using two types mulching material with an overlapping and hole-drilling mulching method and these were compared to un-mulching treatment a total of planted 92㎡ attheWol-aTestSiteForestattheForestforBiomaterialsResearchCenterinJinju-si, Gyeongsangnam-dofor 10monthsusing3-years-oldQuercusglaucaThunb. In comparison with the control site, the 60g/㎡ overlapping method was about 1.9 times higher than the root collar diameter, but there was no statistical significance between the treatments. Healthy seedlings were found to meet these conditions due to high biomass values and below and T/R ratios of 3.0 or lower and H/D ratios of 7.0 or lower. Comparing the values of LWR, SWR, and RWR, which can be evaluated for seedling due to the mulching treatments, as compared to the control, the growth of the ground areas including leaves and stems was enhanced, but the growth of the underground areas containing roots tended to have high control values. Based on this, the SQI value, which can be evaluated for the comprehensive quality of seedlings, was found to be significantly different between the control site and the mulching treatment sites, confirming that the growth and growth improvement effects were achieved with mulching treatments. The chlorophyll content analysis showed that there was a significant difference from the control site, and it was judged that weed generation in the control acted as an environmental stress, causing a decrease in chlorophyll content. It was found that the overlapping 80g/㎡ of polypropylene mulching material generated about 4 times fewer weeds than the control, and the manpower required for the mulching test field and weeding were equal at 3.3 people/100㎡/1 day. Mulching treatments have demonstrated a significant difference in the promotion of growth and quality of the seedlings and are judged as an alternative that can reduce the economic burden incurred by the purchase of the supplies and the manpower required to weed forestry plantations.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.141-156
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• 2008

Market structure analysis is a very useful tool to analyze the competition boundary of the brand or the company. But most of the studies in market structure analysis, the concern lies in nondurable goods such as candies, soft drink and etc. because of the their availability of the data. In the field of durable goods, the limitation of the data availability and the repurchase time period constrain the study. In the analysis of the automobile market, those of views might be more persuasive. The purpose of this study is to analyze the structure of automobile market based on some idea suggested by prior studies. Usually the buyers of the automobile tend to buy upper tier when they buy in the next time. That kind of behavior make it impossible to analyze the structure of automobile market under the level of automobile model. For that reason I tried to analyze the market structure in the brand or company level. In this study, consideration data was used for market structure analysis. The reasons why we used the consideration data are summarized as following. Firstly, as the repurchase time cycle is too long, brand switching data which is used for the market analysis of nondurable good is not avaliable. Secondly, as we mentioned, the buyers of the automobile tend to buy upper tier when they buy in the next time. We used survey data collected in the U.S.A. market in the year of 2005 through questionaire. The sample size was 8,291. The number of brand analyzed in this study was 9 among 37 which was being sold in U.S.A. market. Their market share was around 50%. The brands considered were BMW, Chevrolet, Chrysler, Dodge, Ford, Honda, Mercedes, and Toyota. �� ratio was derived from frequency of the consideration set. Actually the frequency is different from the brand switch concept. In this study to compute the �� ratio, the frequency of the consideration set was used like a frequency of brand switch for convenience. The study can be divided into 2 steps. The first step is to build hypothetical market structures. The second step is to choose the best structure based on the hypothetical market structures, Usually logit analysis is used for the choice best structure. In this study we built 3 hypothetical market structure. They are type-cost, cost-type, and unstructured. We classified the automobile into 5 types, sedan, SUV(Sport Utility Vehicle), Pickup, Mini Van, and Full-size Van. As for purchasing cost, we classified it 2 groups based on the median value. The median value was $28,800. To decide best structure among them, maximum likelihood test was used. Resulting from market structure analysis, we find that the automobile market of USA is hierarchically structured in the form of 'automobile type - purchasing cost'. That is, result showed that automobile buyers considered function or usage first and purchasing cost next. This study has some limitations in the analysis level and variable selection. First, in this study only type of the automobile and purchasing cost were as attributes considered for purchase. Considering other attributes is very needful. Because of the attributes considered, only 3 hypothetical structure could be analyzed. Second, due to the data, brand level analysis was tried. But model level analysis would be better because automobile buyers consider model not brand. To conduct model level study more cases should be obtained. That is for acquiring the better practical meaning, brand level analysis should be conducted when we consider the actual competition which occurred in the real market. Third, the variable selection for building nested logit model was very limited to some avaliable data. In spite of those limitations, the importance of this study lies in the trial of market structure analysis of durable good.