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.
This study points out the problems of absence of the legislation for standard regulation on Video on Demand(VoD) advertisement which grows so fast lately, for this it recommends making legal references, which have the definition of non-linear broadcasting & VoD advertisement and VoD advertisement standard regulation in the merged Broadcasting Act, and adopting co-regulation system. Pay TV operators providing VoD service have the opportunities to make money as subscribers uses it increasingly. In case of linear service, the Broadcasting Act regulates the advertisement strictly, but not the VoD ads. The reason why is that Korean legislation including the Broadcasting Act does not have legal reference to regulate it, instead of that, it rely on the self-regulation system which is operated by pay-tv players who provide the VoD ads. So, there is the limitation to protect the minors such as children and youth from the harmful VoD ads, to be invulnerable for advertisers to influence to advertising agents, and to ensure the regulatory effectiveness under player-centric self-regulatory regime. In this context, this study analyses the how to regulate VoD ads standard with a three-pronged approach. First, it analyses the VoD ads regulation system in overseas countries, UK, Canada, EU and Ireland. Each country has the legal reference to regulate it in the Broadcasting Act or lower statures and adopts the co-regulatory regime the NRA and the 3rd entity operate together. Second, it reviews the objectives and scope of VoD ads standard. This study recommends that the objective of it is users protection and the scope of it is standard regulation not commercial practice. Third, this study researches how to legislate for regulation of VoD ads standard. Considering VoD service's characteristics(non-linear service) and legal position of Ads agency(i.e. pay tv operators), it suggest that legal reference will be in the integrated Broadcasting bill, which is the general law, not individual. If it is available to regulate VoD ads standard with co-regulatory regime, it expects the enhancement of user protection from the harmful VoD ads and make up sustainability of the pay-tv players' self-regulation.
Conceptualization of store image have been suggested in the past by many marketing scholars. The dominant perspective about store image is treated as the results of a multi-attribute model. Store image is expressed as a function of the salient attributes of a particular store that are evaluated. Though, there is a little confusions about what elements compose the store image, most scholars agree that merchandise, service, atmosphere, physical facilities, comfort, and location are generally accepted elements as store image. A considerable researches support that shopping can provide both hedonic and utilitarian value. Hedonic shopping value reflects the value received from fantasy and emotive aspects of shopping experience, while utilitarian shopping value reflects the acquisition of products. These two types of shopping value can affect shopping satisfaction. This study examines the relationships among stores images(store atmosphere, salespeople services, facilities, product assortment, and store location), shopping values(utilitarian shopping value and hedonic shopping value), and shopping satisfaction based on discount stores (E-Mart, Home plus, and Lotte Mart). The author hypothesized that five store image components affect shopping values, and these shopping values affect shopping satisfaction. The author focused on the roles of perceived retail crowding between these relationships. Specifically, the author hypothesized that perceived retailing crowding moderated the relationship between shopping values and shopping satisfaction. The author also hypothesized the direct effect of perceived retail crowding on shopping satisfaction. Finally, the author hypothesized that five store image components affect directly shopping satisfaction. Research model is presented in
. To test model and hypotheses, data were collected from 114 consumers located mid-size city in local area. The author employs PLS methodology (SmartPLS 2.0) to test hypotheses. Data analysis results indicate that among five store images salespeople services, and store location affect utilitarian shopping value. Store atmosphere, salespeople services, and store location affect hedonic shopping value. Two shopping values affect shopping satisfaction. Hedonic shopping value affect more shopping satisfaction than utilitarian shopping value. Data analysis results is presented in
. The author examines the moderating effects of perceived retail crowding between shopping values and shopping satisfaction. Results indicate that there are no moderating effects between shopping values and shopping satisfaction. Moderating effects of perceived retail crowding between utilitarian shopping value and shopping satisfaction are presented in
. Moderating effects of perceived retail crowding between hedonic shopping value and shopping satisfaction is presented in . The author examines the direct effect of perceived retail crowding on shopping satisfaction. Results are presented in
. The author analyzed the relationship between perceived retail crowding and shopping satisfaction using WarpPLS 3.0 which can analyze the non-linear relationship. Result indicates that perceived retail crowding affects directly shopping satisfaction and there is a non-linear relationship between them. Among five store image components, store atmosphere and salespeople services affect directly shopping satisfaction. The author describes about the managerial implications, limitations, and future research issues.
Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in
and
. The type of chinese cabbages are categorized by 5 types, i.e. alpine, gimjang for winter, spring, summer, and winter crop, and all of the regression models are shown significant relationship. In addition, meterological factors in shipment and wholesale period are entered more in regression model than those in seeding and harvest period. This result implies that weather in consuming region is also important in the distribution of chinese cabbages. Based on the result of this study, we find several implications and recommendations for policy makers of agricultural product distribution. The goal of agricultural product distribution policy is to insure proper price and production cost for farmers and provide proper price and quality, and stable supply for consumers. Therefore, coping with the uncertainty of weather is very essential to make a fruitful effect of the policy. In reality, very big part of consumer price of chinese cabbage is made up of the margin of intermediaries, because they take the risk. In addition, policy makers make efforts for farmers to utilize AWIS (Agricultural Weather Information System). In order to do that, it should integrate the relevant information including distribution and marketing as well as production. Offering a consulting service to farmers about weather management is also expected to be a good option in agriculture and weather industry. Reflecting on the result of this study, the distribution authorities can offer the guideline for the timing and volume of harvest, and it is expected to contribute to the stable equilibrium of supply and demand of agricultural products.
Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.
While e-commerce market(B2C) grows rapidly, many experts argue that EC(B2C) transactions have not reached its full potential. A notable difference between online and offline consumer markets that is suppressing the growth of EC(B2C) is the decreased presence of human and social elements in the online shopping environments. Generally online shopping lacks human warmth and sociability. In this study, social presence in online shopping mall was proposed as a substitute for face-to-face social interaction in the traditional commerce and author explored what variables affect social presence(human warmth and sociability) on online shopping malls and how human warmth and sociability can influence on online store loyalty. To achieve research objectives, we reviewed literatures related with marketing, psychology and communication research areas. Based on literature review, we proposed a research model on the online shopping mall. To examine the proposed research model, we gathered data by using a self-report questionnaire. Respondents consists of online shoppers with at least five or more times of purchase experience in online shopping malls. Because social presence is a feeling which needs frequent contacts with malls to experience, respondents must have enough purchase experiences. The empirical results are as follows : First, shopping mall's customization efforts influence perceived social presence on the mall significantly. Second, shopping mall's responsiveness influences perceived social presence significantly. Third, perceived activity of community of online shopping mall influences perceived social presence significantly. Mall managers have to activate their customer community to reinforce social presence, resulting in trust building. Finally, perceived social presence influences trust and enjoyment on the mall significantly. And then trust and enjoyment on the mall affect store loyalty significantly. From these findings it can be inferred that perceived social presence appears determinant which is critical to the formation of core variables(trust and loyalty) in existing online shopping papers.
Proceedings of the Korea Society of Poultry Science Conference
/
2003.07b
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pp.67-88
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2003
The consumption of poultry meat (chicken and turkey) grew the most during the past few decades due to several contributing factors such as low price. product research and development. favorable meat characteristics, responsive to consumer needs, vertical integration and industry consolidation, new processing equipments and technology, and aggressive marketing. The major processing technologies developed and used in chicken processing include forming/restructuring, tumbling, curing, smoking, massaging, injection, marination, emulsifying, breading, battering, shredding, dicing, and individual quick freezing. These processing technologies were applied to various parts of chicken including whole carcass. Product developments using breast, thigh, and mechanically separated chicken meat greatly increased the utilization of poultry meat. Chicken breast became the symbol of healthy food, which made chicken meat as the most frequent menu items in restaurants. However, the use of and product development for dark meat, which includes thigh, drum, and chicken wings were rather limited due to comparatively high fat content in dark meat. Majority of chicken are currently sold as further processed ready-to-cook or ready-to-eat forms. Major quality issues in chicken meat include pink color problems in uncured cooked breast, lipid oxidation and off-flavor, tenderness PSE breast, and food safety. Research and development to ensure the safety and quality of raw and cooked chicken meat using new processing technologies will be the major issues in the future as they are now. Especially, the application of irradiation in raw and cooked chicken meat products will be increased dramatically within next 5 years. The market share of ready-to-eat cooked meat products will be increased. More portion controlled finished products, dark meat products, and organic and ethnic products with various packaging approaches will also be introduced.
Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.
Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.
Among the styles of performing arts, perhaps the genre that has attracted the largest audience would be musical. Popularity of musical has brought diverse changes in our performing arts market, and, upon emerging another musical genre, called 'Korean Traditional Musical Comedy,' it has been well-received by the audiences. 'Korean Traditional Musical Comedy' is a word that are formed by merging two other terms such as 'Korean Traditional Music' and 'Musical (Comedy).' In the meantime, however, it has yet some problems in order to be defined as the genre that has concrete concepts. It is because the term such as Korean Traditional Musical Comedy was created being closely associated with a marketing purpose rather than a term that defines the characteristics of a genre of performing arts. Although this new musical genre has drawn attentions of many audiences by adding 'Musical Comedy' to 'Korean Traditional Music' that was not quite popular to the public, it still does not have any established forms so that there is a fine line between "Korean Traditional Musical Comedy" and another genre like traditional style folk opera ("Changgeuk"). Looking at the characteristics of the musical work called 'Korean Traditional Musical Comedy, in general, first of all, it is a performance where music and drama are played. Here, the distinctive characteristic of this musical is that 'Korean Traditional Music' is sung. And the kinds of Korean traditional musics being sung are mainly Pansori (dramatic story-singing) and folk-songs, and, in most cases, Korean traditional musical instruments are being used as accompanying music. In this paper, the researcher investigated the aspects of experiment centering around Korean Musical Group, Taroo. These days, various experiments has been repeated not only for the works of Taroo but other musical work presently called 'Korean Traditional Musical Comedy' also. Having encompassed overall performance factors including use of musical instruments, dance, acting, materials for drama as well as music in drama, the researcher has gone through experiments repeatedly. Meanwhile, however, the subject matters that make 'Korean Traditional Musical Comedy' mostly attractive to the audiences are music and songs or sounds. ["Sori" also called "Chang" (唱)] Particularly, under the current situation of our musicals, the role of "Sori" is extremely important. The factor that plays absolutely most important role in acceptance and transformation of "Sori" is the created Pansori. Since the created Pansori is composed with new rhythmic patterns and new narrative poems, it tells the present story. Also it draws good responses from the audiences owing to easy conveyance of dialogues. And, its new style brings diversification to organization of musical instruments, so then this leads to the arrangements of music for Korean traditional music instruments, as well as instrumental music ensemble, orchestra, and jazz band, etc. Likewise, upon appearing creative musics in 'Korean Traditional Musical Comedy,' professional music and vocal compositions have begun to emerge naturally. And, the song specialist and writer, of course, staffs including direction, lighting, and sounds, etc are required. That is, professional composition method are forced to be introduced to all areas. Other than this, there are many music pieces which are based on our unique songs and sounds ("Sori") and such traditional factors as use of lead singer for ceremony or chorus, and the method that puts weight on Pansori. Accordingly many things accomplished. However, it is required that 'Korean Traditional Musical Comedy' go through numerous discussions and more experiments. Above all, the most important things are the role of actor and actress, and their changes, and training of actor and actress further. Good news is there are good audience responses. 'Korean Traditional Musical Comedy' is an open genre. As musicals are divided into several domains according to the characteristics thereof, 'Korean Traditional Musical Comedy' will be able to show its distinctive features in various styles according to embodiment.
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