• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.595-625
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• 2012

Recently environment-friendly pellet boilers have interests as emissions of greenhouse gases are regulated internationally and energy security becomes more important to oil addicted countries including Republic of Korea. But the Korean market for pellet boilers is on the initial stage due to the high production costs relative to other conventional boilers. Hence the Korean government has supported financially and promoted the pellet boiler business. In this sense, it would contribute market stratergy and effective promotion policy for both of the government and private companies if we can forecast market shares of pellet boilers appropriately. For this purpose, this study surveyed potential consumers' preferences on pellet boilers among various alternatives using a choice experiment reflecting intangible costs. As the market share of new technology increases, intangible costs decline. According to different intangible cost scenarios, we experimented people's preferences on oil, gas, electric, and pellet boilers. A multinomial logit model was employed to estimate coefficient parameters of common attributes for various alternative boilers. Based on the estimates, we forecasted market shares of individual boilers. We found that as intangible costs decline, the market share of pellet boiler increase substantically while market shares of electric and gas boilers decrease dramatically. The market share of oil boiler did not change significantly. Meanwhile, as people are more rich, more educated, and exposed to advertisement on pellet boilers, the likelihood of choosing the pellet boiler increases.

• Survey Research
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• v.7 no.1
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• pp.55-84
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• 2006

This study has classified development stages (Embryonic-Growth-Maturity) of mobile telecommunication industry based on Industry Life Cycle theory. There are two steps to be analyzed in this study, In the first step, cluster was investigated through cluster analysis using mobile density to categorize development stages of mobile telecommunication industry. In the second step, we compared on indexes of market structure, market efficiency and market performance to find out characteristics of each stage of development. The results are as follows. First, HHI is higher at embryonic stage than at growth and maturity stages, Second, ARPU(Average Revenue Per User) and RPM(Revenue Per Minute) are getting higher as the stages move on. Third, EBITDA margins, an index of market performance, is decreasing along the three stages. Finally, this study presents a clue to define the stage of development of mobile telecommunication industry and build a proper strategy for the market change.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.1-13
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• 2021

The concept of integrated pest management (IPM) first developed in the 1950s, and the concept of economic control via pest management was established in the 1960s. Research on IPM began in the United States and Europe, and IPM studies in Korea started with citrus insects and paddy field pests following the distribution of high-yield varieties of rice. Apple IPM in Korea began with research on pest control using chemical pesticides and pesticides resistant to insect pests, studies on the ecology of insect pests and their natural enemies, and the exploitation of sex pheromones on insect pests. Since the 1990s, IPM research and field projects have been carried out simultaneously for farming households. In the 2000s, the development of pest monitoring and forecasting models centered on mating disturbances, database programs for pests, and networks for sharing information. IPM technology has expanded via the development of unmanned forecasting systems and automation technologies in the 2010s.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.549-559
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• 2014

The rapid expansion of cities led to the shortage of housing in urban areas. The government compensated for this shortage through large scale residential developments that increased the housing supply. The supply of condominium apartments remains above 83% of the entire housing supply, and the proportion of apartments are at a steady increase, at about 50%. Due to the increase, illegally parked cars resulting from the shortage of parking spaces within the apartment complex have become increasingly problematic as they block the transit of emergency vehicles, and heighten the tension among neighboring residents in obtaining a parking space. Especially, the future residents are considered to plan the parking based on the estimated demand for parking. However, the parking unit method utilized to estimate the parking demand accounts for the exclusive use of space, which is believed to be far from the parking demands in reality. The reason for this discrepancy is that, as the number of households decrease, and area of exclusive space is expanded, the planned parking increases. On the other hand, when the number of households increase, and the area of exclusive space is reduced, the planned parking decreases, thus methods to recalculate the parking units based on estimated parking demand is an urgent concern. To estimate the parking units based on condominium apartments, this study first examined the existing research literature, and appointed the field of investigation to collect the necessary data. In addition, field study data and surveys collected and analyzed, in order to identify the problems underlying parking units, and problems regarding the current traffic impact assessment parking unit calculation method were deduced. Through identifying the influential factors on parking demand estimates, and performing a factorial analysis based on the collected data, the variables were selected in relation to the parking demand estimates, to develop the parking unit estimate model. Finally, through comparing and verifying the existing traffic impact assessment parking unit estimate against the newly developed model using collected data, a far more realistic parking unite estimate was suggested, reflecting the characteristics of the residents. The parking unit estimate model developed in this study is anticipated to serve as the guidelines for future parking lot legislature, as wel as the basis to provide a more realistic estimate of parking demands based on the resident characteristics of an apartment complex.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.153-163
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• 2013

As the number of Smartphone users increases, mobile advertising market has been expanding rapidly. In line with this, the ways to evaluate mobile advertising effectiveness are diversified, and engagement is one of the crucial qualitative and multi-dimensional evaluation methods of mobile advertising. Thus, the purpose of this study is to identify key antecedents and consequences of mobile advertising engagement, and examines the structural relationships among those research variables. Informativeness and personalization were selected as antecedents of engagement, trust and e-WOM intention were selected as consequences of engagement based on the review of previous studies. Data collected from survey was used to assess research hypotheses. Results show that informativeness and personalization have significant and positive effects on engagement, and engagement influences on trust and e-WOM intention. In addition, trust is proven to be positively related to e-WOM intention.

• The Journal of Korean Institute for Practical Engineering Education
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• v.1 no.1
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• pp.19-24
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• 2009

It is necessary that the industry has to develop various automated control technology for efficient creation of manufacture automation system according to rapid market situation. One of the technologies is the fused complex control based on PLC-based controlled system. According to rapid growth and distribution of various automated control technologies using PLC, the engineers in automation, Production and manufacturing technologies fields have difficulties in systematic studying on the technologies by choosing an optimal route due to various industry-applied examples and ranges, in spite that the technology is essential. Therefore, the researchers indicate applied outputs and effects extracted by systematically developing systematic company-specified training program by analyzing education procedure drawbacks for S-company engineers.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.187-199
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• 2013

Since the supply of smart phones, a change in mobile environment brought a turning point called a mobile generation. Smart mobile office is a combined form of smart phones' new mobile environment and its social media. A construction of mobile office environment using smart phones brought revitalization of the smart phone market. CRM construction also became new requirements for a customer management. However, based on the current information system audit standard, check fields or check lists are insufficient to apply to audit for CRM construction in a smart mobile office environment. Therefore, this paper proposes a model for auditing CRM system construction in smart mobile office environment. It proposes audit domain and check lists of CRM construction. It also verified whether the proposed model is suitable or not by doing a survey if deduced audit domain and check lists correspond with the purpose of the CRM construction audit during smart mobile office environment. As the result, this study appear to have more than average satisfaction the suitability results were.

• The Journal of Society for e-Business Studies
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• v.16 no.1
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• pp.71-100
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• 2011

There are expectations about future internet technology with IT development by end-users. Cloud computing is attracted to satisfy those demands. However, adoption of cloud computing is not active that much. Therefore, this study verified how cloud computing environment affects performance of team project. We conducted empirical study on performance of team project with cloud computing as technology tool focusing on Task-Technology Fit Model. We collected samples that were undergraduate and graduate school students and had experience on initial cloud computing such as Google-Docs and Webhard when they conducted team project for assignment. We focused on accessibility and reliability as task-technology fit and those variables treated as first order factor. Result showed that cloud computing is suitable technology tool for team project. This study suggests positive effects of cloud computing for collaboration by proving perceived fit and performance in initial cloud computing.