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Forecasting Substitution and Competition among Previous and New products using Choice-based Diffusion Model with Switching Cost: Focusing on Substitution and Competition among Previous and New Fixed Charged Broadcasting Services (전환 비용이 반영된 선택 기반 확산 모형을 통한 신.구 상품간 대체 및 경쟁 예측: 신.구 유료 방송서비스간 대체 및 경쟁 사례를 중심으로)

  • Koh, Dae-Young;Hwang, Jun-Seok;Oh, Hyun-Seok;Lee, Jong-Su
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.2
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    • pp.223-252
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    • 2008
  • In this study, we attempt to propose a choice-based diffusion model with switching cost, which can be used to forecast the dynamic substitution and competition among previous and new products at both individual-level and aggregate level, especially when market data for new products is insufficient. Additionally, we apply the proposed model to the empirical case of substitution and competition among Analog Cable TV that represents previous fixed charged broadcasting service and Digital Cable TV and Internet Protocol TV (IPTV) that are new ones, verify the validities of our proposed model, and finally derive related empirical implications. For empirical application, we obtained data from survey conducted as follows. Survey was administered by Dongseo Research to 1,000 adults aging from 20 to 60 living in Seoul, Korea, in May of 2007, under the title of 'Demand analysis of next generation fixed interactive broadcasting services'. Conjoint survey modified as follows, was used. First, as the traditional approach in conjoint analysis, we extracted 16 hypothetical alternative cards from the orthogonal design using important attributes and levels of next generation interactive broadcasting services which were determined by previous literature review and experts' comments. Again, we divided 16 conjoint cards into 4 groups, and thus composed 4 choice sets with 4 alternatives each. Therefore, each respondent faces 4 different hypothetical choice situations. In addition to this, we added two ways of modification. First, we asked the respondents to include the status-quo broadcasting services they subscribe to, as another alternative in each choice set. As a result, respondents choose the most preferred alternative among 5 alternatives consisting of 1 alternative with current subscription and 4 hypothetical alternatives in 4 choice sets. Modification of traditional conjoint survey in this way enabled us to estimate the factors related to switching cost or switching threshold in addition to the effects of attributes. Also, by using both revealed preference data(1 alternative with current subscription) and stated preference data (4 hypothetical alternatives), additional advantages in terms of the estimation properties and more conservative and realistic forecast, can be achieved. Second, we asked the respondents to choose the most preferred alternative while considering their expected adoption timing or switching timing. Respondents are asked to report their expected adoption or switching timing among 14 half-year points after the introduction of next generation broadcasting services. As a result, for each respondent, 14 observations with 5 alternatives for each period, are obtained, which results in panel-type data. Finally, this panel-type data consisting of $4{\ast}14{\ast}1000=56000$observations is used for estimation of the individual-level consumer adoption model. From the results obtained by empirical application, in case of forecasting the demand of new products without considering existence of previous product(s) and(or) switching cost factors, it is found that overestimated speed of diffusion at introductory stage or distorted predictions can be obtained, and as such, validities of our proposed model in which both existence of previous products and switching cost factors are properly considered, are verified. Also, it is found that proposed model can produce flexible patterns of market evolution depending on the degree of the effects of consumer preferences for the attributes of the alternatives on individual-level state transition, rather than following S-shaped curve assumed a priori. Empirically, it is found that in various scenarios with diverse combinations of prices, IPTV is more likely to take advantageous positions over Digital Cable TV in obtaining subscribers. Meanwhile, despite inferiorities in many technological attributes, Analog Cable TV, which is regarded as previous product in our analysis, is likely to be substituted by new services gradually rather than abruptly thanks to the advantage in low service charge and existence of high switching cost in fixed charged broadcasting service market.

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Why A Multimedia Approach to English Education\ulcorner

  • Keem, Sung-uk
    • Proceedings of the KSPS conference
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    • 1997.07a
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    • pp.176-178
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    • 1997
  • To make a long story short I made up my mind to experiment with a multimedia approach to my classroom presentations two years ago because my ways of giving instructions bored the pants off me as well as my students. My favorite ways used to be sometimes referred to as classical or traditional ones, heavily dependent on the three elements: teacher's mouth, books, and chalk. Some call it the 'MBC method'. To top it off, I tried audio-visuals such as tape recorders, cassette players, VTR, pictures, and you name it, that could help improve my teaching method. And yet I have been unhappy about the results by a trial and error approach. I was determined to look for a better way that would ensure my satisfaction in the first place. What really turned me on was a multimedia CD ROM title, ELLIS (English Language Learning Instructional Systems) developed by Dr. Frank Otto. This is an integrated system of learning English based on advanced computer technology. Inspired by the utility and potential of such a multimedia system for regular classroom or lab instructions, I designed a simple but practical multimedia language learning laboratory in 1994 for the first time in Korea(perhaps for the first time in the world). It was high time that the conventional type of language laboratory(audio-passive) at Hahnnam be replaced because of wear and tear. Prior to this development, in 1991, I put a first CALL(Computer Assisted Language Learning) laboratory equipped with 35 personal computers(286), where students were encouraged to practise English typing, word processing and study English grammar, English vocabulary, and English composition. The first multimedia language learning laboratory was composed of 1) a multimedia personal computer(486DX2 then, now 586), 2) VGA multipliers that enable simultaneous viewing of the screen at control of the instructor, 3) an amplifIer, 4) loud speakers, 5)student monitors, 6) student tables to seat three students(a monitor for two students is more realistic, though), 7) student chairs, 8) an instructor table, and 9) cables. It was augmented later with an Internet hookup. The beauty of this type of multimedia language learning laboratory is the economy of furnishing and maintaining it. There is no need of darkening the facilities, which is a must when an LCD/beam projector is preferred in the laboratory. It is headset free, which proved to make students exasperated when worn more than- twenty minutes. In the previous semester I taught three different subjects: Freshman English Lab, English Phonetics, and Listening Comprehension Intermediate. I used CD ROM titles like ELLIS, Master Pronunciation, English Tripple Play Plus, English Arcade, Living Books, Q-Steps, English Discoveries, Compton's Encyclopedia. On the other hand, I managed to put all teaching materials into PowerPoint, where letters, photo, graphic, animation, audio, and video files are orderly stored in terms of slides. It takes time for me to prepare my teaching materials via PowerPoint, but it is a wonderful tool for the sake of presentations. And it is worth trying as long as I can entertain my students in such a way. Once everything is put into the computer, I feel relaxed and a bit excited watching my students enjoy my presentations. It appears to be great fun for students because they have never experienced this type of instruction. This is how I freed myself from having to manipulate a cassette tape player, VTR, and write on the board. The student monitors in front of them seem to help them concentrate on what they see, combined with what they hear. All I have to do is to simply click a mouse to give presentations and explanations, when necessary. I use a remote mouse, which prevents me from sitting at the instructor table. Instead, I can walk around in the room and enjoy freer interactions with students. Using this instrument, I can also have my students participate in the presentation. In particular, I invite my students to manipulate the computer using the remote mouse from the student's seat not from the instructor's seat. Every student appears to be fascinated with my multimedia approach to English teaching because of its unique nature as a new teaching tool as we face the 21st century. They all agree that the multimedia way is an interesting and fascinating way of learning to satisfy their needs. Above all, it helps lighten their drudgery in the classroom. They feel other subjects taught by other teachers should be treated in the same fashion. A multimedia approach to education is impossible without the advent of hi-tech computers, of which multi functions are integrated into a unified system, i.e., a personal computer. If you have computer-phobia, make quick friends with it; the sooner, the better. It can be a wonderful assistant to you. It is the Internet that I pay close attention to in conjunction with the multimedia approach to English education. Via e-mail system, I encourage my students to write to me in English. I encourage them to enjoy chatting with people all over the world. I also encourage them to visit the sites where they offer study courses in English conversation, vocabulary, idiomatic expressions, reading, and writing. I help them search any subject they want to via World Wide Web. Some day in the near future it will be the hub of learning for everybody. It will eventually free students from books, teachers, libraries, classrooms, and boredom. I will keep exploring better ways to give satisfying instructions to my students who deserve my entertainment.

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Social Tagging-based Recommendation Platform for Patented Technology Transfer (특허의 기술이전 활성화를 위한 소셜 태깅기반 지적재산권 추천플랫폼)

  • Park, Yoon-Joo
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.53-77
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    • 2015
  • Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

Personalized Recommendation System for IPTV using Ontology and K-medoids (IPTV환경에서 온톨로지와 k-medoids기법을 이용한 개인화 시스템)

  • Yun, Byeong-Dae;Kim, Jong-Woo;Cho, Yong-Seok;Kang, Sang-Gil
    • Journal of Intelligence and Information Systems
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    • v.16 no.3
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    • pp.147-161
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    • 2010
  • As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.