• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.1-31
• /
• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.33-49
• /
• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Information Systems Review
• /
• v.7 no.2
• /
• pp.41-59
• /
• 2005

Mobile games have emerged as the most innovative entertainment technology adding new revenue streams, taking advantage of the potential of wireless consumer applications and service offerings. Mobile games, like any other types of computer game, offer a unique value for users in providing an exciting digital experience in virtual worlds. Players can become empowered through the development of new characters and strategies within games to achieve rewarding successes against the computers and other players. In this paper, we attempt to investigate the factors influencing the usage and acceptance of the mobile games in Korea, based on the extended version of the Technology Acceptance Model(TAM). Based on data collected from survey, we show that perceived usefulness is the major determinant for users to play mobile games. Two factors, including perceived enjoyment and self-expressiveness, are empirically shown to determine perceived usefulness. In addition, perceived ease of use, rewards, operational quality of device, and design/story have been showed to significantly and directly affect perceived enjoyment. It was also confirmed that self-efficacy and operational quality of device are the antecedents of perceived ease of use. Based upon the statistical results, some useful guidelines for game development and market penetration strategies are also provided.

• Journal of Korea Port Economic Association
• /
• v.24 no.2
• /
• pp.209-239
• /
• 2008

The purpose of this paper is to investigate the effectiveness of Korean port investment by using the newly developed slack-based multi-year panel congestion model of DEA(Data Envelopment Analysis). Inputs[port investment amount, cargo handling capacity, and berthing capacity], and outputs[cargo handling amount, number of ship calls, revenue, and score of customer service satisfaction] are used during 1994-2004 for 20 Korean seaports. Empirical analysis identified congestion especially in port investment as input at the ports of Gunsan, and Busan in the all 3 models, and the ports of Pyungtag, Mogpo, Yeosu, and leju in over 2 models. Port investment induced the rapid increase of port efficiency from the ports of Masan, Incheon, Donghae, and Samcheok. Therefore other ports except these ports should examine the reason about the inefficiency of port investment by searching out the situation of each ports directly. The main policy implication based on the findings of this study is that The Ministry of Land, Transport and Maritime Affairs in Korea should introduce the new measurement way after reviewing the multi-year slack-based congestion approach when the amount of port investment for each port is decided.

• Journal of KIISE
• /
• v.44 no.8
• /
• pp.803-812
• /
• 2017

T-commerce is technology-fusion service on which the user can purchase using data broadcasting technology based on bi-directional digital TVs. To achieve the best revenue under a limited environment in regard to the channel number and the variety of sales goods, organizing broadcast programs to maximize the expected sales considering the selling power of each product at each time slot. For this, this paper proposes a method to predict the sales of goods when it is assigned to each time slot. The proposed method predicts the sales of product at a time slot given the week-in-year and weather of the target day. Additionally, it combines a statistical predict model applying SVD (Singular Value Decomposition) to mitigate the sparsity problem caused by the bias in sales record. In experiments on the sales data of W-shopping, a T-commerce company, the proposed method showed NMAE (Normalized Mean Absolute Error) of 0.12 between the prediction and the actual sales, which confirms the effectiveness of the proposed method. The proposed method is practically applied to the T-commerce system of W-shopping and used for broadcasting organization.

• Journal of Korea Port Economic Association
• /
• v.26 no.3
• /
• pp.18-41
• /
• 2010

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using Super SBM(Slack-based Measure) with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 11 years(1997-2007) for 3 inputs(port investment amount, birthing capacity, and cargo handling capacity) and 5 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue, Customer Satisfaction Point for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, Super SBM model has well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the significance level. Second,Super-SBM has shown about 87% of predicting ratio for the ports efficiency and the optimal size of investment in domestic seaport. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like Super-SBM method with Wilcoxon signed rank test for predicting the efficiency of port performance and the optimal size of investment as indicated by Panayides et al.(2009, pp.203-204).

• The Journal of Society for e-Business Studies
• /
• v.24 no.4
• /
• pp.119-133
• /
• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.

• Korea Journal of Hospital Management
• /
• v.3 no.1
• /
• pp.100-120
• /
• 1998

Tertiary been increasing rapidly. There has been shortage of beds in hospitals and effective management of beds had to b considered. For the efficient utilization of the exsisting hospital beds, bed turnover rate ha to be high and their length of stay in hospital has to be shortened. The sample of this study was in-patients admitted in 13 clinical departments of a tertiar hospital in Wonju. Daily medical fees through length of stay in hospital were observed an we analyzed the increase of hospital revenues per bed for the shortening of length of stay. The results of the analysis were as follows: 1. The average length of stay by dept. was 11.0 in dept. of internal medicine. 12.4 in dept. of general surgery, 7.1 in dept. of gynecoloty, 6.8 in dept. of pediatrics, 26.1 in dept. of nervous surgery, 21.6 in dept. of orthopedic surgery, 25.5 in dept. of plastic sersury, 7.6 in dept. of ophthalmology, 7.1 in dept. of E.N.T, 8.1 in dept. dermatoloty, 9.0 in dept. urology. 2. The trend of daily medical fees of in-patients was the highest from the first day to the third day. Because most necessary examination and various treatment or operation took place in these period. 3. The estimative model for medical fees by the length of stay at each clinical department was inferred. 4. The increased revenue per bed by shortening the length of stay was calculated by the estimative model. Shortening one day would increase 305,999 thousand won in dept. of internal medicine 232,138 thousand won in dept. of general surgery., 177,795 thousand won in dept. of gynecology medicine, 69,031 thousand won in dept. of pediatrics 360,381 thousand won in dept. of nervous surgery 211.339 thousand won in dept. of orthopedic surgery, 100,249 thousand won in dept of plastic surgery, 10,569 thousand won in dept. of ophthalmology -814,122 thousand won in dept. of E.N.T, 1,582 thousand won in dept. of dermatology, -5,821 thousand won in dept. of urology. It is expected that they can improve their profitability by shortening the length of stay of the in-patients.

• Environmental and Resource Economics Review
• /
• v.21 no.1
• /
• pp.175-210
• /
• 2012

As London and post-Koyto protocols presumably affect emission of organic waste in Korea in 2012, appropriate treatment of organic waste becomes very important. Organic wastes are regarded as non-point pollutants. It has been criticized that direct emission charges on the emission of non-point pollutants are not effective due to the high uncertainty in the relationship between pollution sources and pollution levels. This study suggests indirect emission charges on production of livestocks or consumption on foods. Furthermore, it is assumed that revenue from the emission charges will be recycled to support biogas production. Biogas can be fueled to produce energy. In order to evaluate potential economic and environmental impacts of recycling the indirect emission charges on organic wastes, a static CGE model was developed. Simulation results of emission charges on the production of livestock show that livestock, agriculture, and food industry will confront relatively high burden while emission charges on consumption of food will affect more broadly and consumers will suffer more. Production charge on livestock sector will lead to higher reduction in GDP and total expenditure relative to the consumption charge. GHGs reduction effect was higher for the consumption charge relative to the production charge. Synthetically, consumption charge on food sector is more desirable as an alternative charge for the emission of organic wastes.

• International Journal of Highway Engineering
• /
• v.8 no.3 s.29
• /
• pp.63-76
• /
• 2006

For a private toll road project, deciding optimal toll is an important element of economic analysis for the project and a challengeable work. In this study, the optimal toll of a private toll bridge, Geoga Bridge which connects Geoje Island of Gyeongnam Province and Gaduk Island of Busan was estimated using Stated Preference (SP) data. The SP data were collected by interviewing the passenger car drivers travelling on the National Road 14. They are latent users of the bridge. A fuzzy approximate reasoning model to estimate the optimal toll was built using the SP data. For the input variable of the model, the saved travel time and toll level were employed and the diversion rate to the bridge was employed for the output variable. The diversion rates for each toll level and saved travel time were estimated and the toll level which had maximized the toll revenue was decided as optimal toll. The optimal toll was tested by comparing with the average pay rate of passenger car drivers. Since the optimal toll for passenger cars at one hour saving, the 6,250 won is about 50 % of the average pay rate of passenger car divers, the toll was evaluated not to be high. The technique employed in this study may be used for the estimation of the optimal tolls for other kinds of vehicles.