• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of Wetlands Research
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• v.25 no.1
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• pp.35-47
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• 2023

Korean facility horticulture and hydroponic cultivation methods increase, requiring the management of waste water generated. In this study, the amount of fertilizer contained in the discharged waste liquid was determined. By evaluating this as a price, it was suggested to reduce water treatment costs and recycle fertilizer components. It was evaluated based on the results of major water quality analysis of waste liquid by crop, such as tomatoes, paprika, cucumbers, and strawberries, and in the case of P component, it was analyzed by converting it to the amount of phosphoric acid (P₂O₅). The amount of nitrogen (N) can be calculated by discharging 1,145.90kg·ha^-1 of tomatoes, 920.43kg·ha^-1 of paprika, 804.16kg·ha^-1 of cucumbers, 405.83kg·ha^-1 of strawberries, and the fertilizer content of P₂O₅ is 830.65kg·ha^-1 of paprika, 622.32kg·ha^-1 of tomatoes, 477.67kg·ha^-1 of cucumbers. In addition, trace elements such as potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), and manganese (Mn) were also analyzed to be emitted. The price per kg of each item calculated by averaging the price of fertilizer sold on the market can be evaluated as KRW, N 860.7, P 2,378.2, K 2,121.7, Ca 981.2, Mg 1,036.3, Fe 126,076.9, Mn 62,322.1, Zn 15,825.0, Cu 31,362.0, B 4,238.0, Mo 149,041.7. The annual fertilizer loss amount for each crop was calculated by comprehensively considering the price per kg calculated based on the market price of fertilizer, the concentration of waste by crop analyzed earlier, and the average annual emission of hydroponic cultivation. As a result of the analysis, the average of the four hydroponic crops was 5,475,361.1 won in fertilizer ingredients, with tomatoes valued at 6,995,622.3 won, paprika valued at 7,384,923.8 won, cucumbers valued at 5,091,607.9 won, and strawberries valued at 2,429,290.6 won. It was expected that if hydroponic drainage is managed through self-treatment or threshing before discharge rather than by leaking it into a river and treating it as a pollutant, it can be a valuable reusable fertilizer ingredient along with reducing water treatment costs.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.115-139
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• 2008

Since financial crisis of IMF resulted in intensive competitiveness and adverse management environment, many hotel industries have responded it with restructuring. Since this restructuring is accompanied by reduction of employees, hence comes the recognition of justice in the procedure of restructuring. When the surviving employees in the restructuring process recognize unfairness in the procedure and practical operations, organization effectiveness can not be maintained due to losing trust of their employers. In this paper I will examine the relationship between validity of restructuring and compensatory programs for layoffs and surviving employees' trust of the employers. Also I will find out the relationship between remaining employees' trust of the employers and their job satisfaction and organization commitment. Through this relationship, we can prepare an alternative to reduce negative effect of restructuring. The hypotheses of this study are proposed as follows: H1: The higher surviving employees' recognition of procedural justice in restructuring process is, the higher their trust with a manager of the company is. H2: The higher surviving employees' recognition of distributive justice in restructuring process is, the higher their trust with a manager of the company is. H3: The higher surviving employees' recognition of procedural justice in restructuring process is, the higher their job satisfaction is. H4: The higher surviving employees' recognition of distributive justice in restructuring process is, the higher their job satisfaction is. H5: The higher surviving employees' recognition of procedural justice in restructuring process is, the higher their organization commitment is. H6: The higher surviving employees' recognition of distributive justice in restructuring process is, the higher their organization commitment is. H7: The higher surviving employees' trust with a manager of the company in restructuring process is, the higher their job satisfaction is. H8: The higher surviving employees' trust with a manager of the company in restructuring process is, the higher their organization commitment is. For the purposes of this study, employees working in luxury hotels located in Seoul were targeted. Self-administered questionnaires were distributed to those who consented with the investigation after explaining the purpose of the survey. A total of 500 questionnaires were distributed and 450 questionnaire were returned to the researcher for analysis. 430 of the returned questionnaires were used for analysis. As for the education for this survey, 250 junior college graduates or under (58.1%), 143 college graduates (33.3%) and 37 graduate school graduates (8.6%). As for the marital status, 315 persons (73.3%) are single and 115 are married (26.7%). As for the monthly income, 49 people (11.48%) are less than 2 million won, 148 (34.4%) are between 2 million and less than 2.5 million won, 153 (35.6%) are between 2.5 million to less than 3 million won, 80 (18.6%) are more than 3 million won. As for the workplace, 293 people (68.1%) work for the F&B department, 73 (17.0%) for rooms department, 41 (9.5%) for operation/ marketing department, 23 (5.3%) for account/ general affair department. As for the period of employment, 85 people (19.8%) are less than 5 years, 150 (34.9%) are between 6 to 9 years, 143 (33.3%) are between 10 to 14 years. and 52 (3.%) are more than 15 years. An exploratory factor analysis was used to survey validity and reliability of calculating tool on perceived values. This study used correlation between individual items and whole items and Cronbach's alpha value of multiple-item scale which is usually used to assess scale and reliability. Reliability of conceptual sub-dimension was assessed by basing on repeated procedure of correlation between individual items and whole items and factor loading. 1. Verification of correlation between validity of restructuring and trust This research showed that procedural and distributive justice of restructuring affects trust positively. The path coefficient between procedural justice of restructuring and trust is 0.719(t=10.135, p=0.000), and thereby the higher procedural justice results in higher trust. The path coefficient between distributive justice of restructuring and trust is 0.160(t=3.291, p=0.001), and thereby the higher distributive justice results in higher trust. Hence H1 and H2 are accepted. 2. Verification of correlation between validity of restructuring and job satisfaction The path coefficient between procedural justice of restructuring and job satisfaction is 0.179(t=2.202, p=0.028), and thereby the higher procedural justice results in higher job satisfaction. The path coefficient between distributive justice of restructuring and job satisfaction is 0.074(t=1.620, p=0.105), and thereby distributive justice of restructuring has no relationship with job satisfaction. Hence H3 is accepted, but H4 is removed. 3. Verification of correlation between validity of restructuring and organization commitment The path coefficient between procedural justice of restructuring and organization commitment is 0.188(t=2.466, p=0.014), and thereby the higher procedural justice results in higher organization commitment. The path coefficient between distributive justice of restructuring and organization commitment is 0.118(t=2.720, p=0.007), and thereby the higher distributive justice results in higher organization commitment. Hence H5 and H6 are accepted. 4. Verification of correlation between trust and job satisfaction The path coefficient between trust and job satisfaction is 0.610(t=6.736, p=0.000), and thereby the correlation has a meaningful result. Since the higher trust of the employer results in higher job satisfaction, H7 is accepted. 5. Verification of correlation between trust and organization commitment The path coefficient between procedural justice of restructuring and job satisfaction is 0.446(t=5.547 p=0.000), and thereby the higher trust of the employer results in higher organization commitment. Hence H8 is accepted. This research aimed to help the employers of hotel industries by analyzing the effects of validity of restructuring on employees' trust, job satisfaction and organization commitment. The research found that employer's validity of restructuring has significant affects on the degree of employee's trust with a manager, thereby reducing the negative effects of restructuring and enhancing organization commitment and job satisfaction. The principal purpose of this research is to confirm the correlation between employees' perceived validity of restructuring and their trust with a manager. Also whether this correlation results in competitive edge of the company is also investigated. It is also pointed out that employees had to participated the procedure of restructuring, sharing the philosophy and reason of restructuring. This participation and furthermore compensatory methods can reduce employees' anxiety of organization operations. Variable of trust appeared to have impact on intermediation effect between perceived variable of validity and job satisfaction, organization commitment, so that increase of trust with a manager plays an crucial role in increasing organization effectiveness. Since this research did not cover whole hotel industries which underwent restructuring, it showed a limit. Unlike previous studies which dealt with validity and trust of superior bosses, this research focussed on employers. Also the organization citizenship which is not considered in this study will be dealt with in the future study.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of Distribution Research
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• v.17 no.4
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• pp.29-53
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• 2012

As so many marketers get to use diverse sales promotion methods, manufacturer and retailer in a channel often use them too. In this context, diverse issues on sales promotion management arise. One of them is the issue of unplanned buying. Consumers' unplanned buying is clearly better off for the retailer but not for manufacturer. This asymmetric influence of unplanned buying should be dealt with prudently because of its possibility of provocation of channel conflict. However, there have been scarce studies on the sales promotion management strategy considering the unplanned buying and its asymmetric effect on retailer and manufacturer. In this paper, we try to find a better way for a manufacturer in a channel to promote performance through the retailer's sales promotion efforts when there is potential of unplanned buying effect. We investigate via game-theoretic modeling what is the optimal cost sharing level between the manufacturer and retailer when there is unplanned buying effect. We investigated following issues about the topic as follows: (1) What structure of cost sharing mechanism should the manufacturer and retailer in a channel choose when unplanned buying effect is strong (or weak)? (2) How much payoff could the manufacturer and retailer in a channel get when unplanned buying effect is strong (or weak)? We focus on the impact of unplanned buying effect on the optimal cost sharing mechanism for sales promotions between a manufacturer and a retailer in a same channel. So we consider two players in the game, a manufacturer and a retailer who are interacting in a same distribution channel. The model is of complete information game type. In the model, the manufacturer is the Stackelberg leader and the retailer is the follower. Variables in the model are as following table. Manufacturer's objective function in the basic game is as follows: ${\Pi}={\Pi}_1+{\Pi}_2$, where, ${\Pi}_1=w_1(1+L-p_1)-{\psi}^2$, ${\Pi}_2=w_2(1-{\epsilon}L-p_2)$. And retailer's is as follows: ${\pi}={\pi}_1+{\pi}_2$, where, ${\pi}_1=(p_1-w_1)(1+L-p_1)-L(L-{\psi})+p_u(b+L-p_u)$, ${\pi}_2=(p_2-w_2)(1-{\epsilon}L-p_2)$. The model is of four stages in two periods. Stages of the game are as follows. (Stage 1) Manufacturer sets wholesale price of the first period($w_1$) and cost sharing level of channel sales promotion(${\Psi}$). (Stage 2) Retailer sets retail price of the focal brand($p_1$), the unplanned buying item($p_u$), and sales promotion level(L). (Stage 3) Manufacturer sets wholesale price of the second period($w_2$). (Stage 4) Retailer sets retail price of the second period($p_2$). Since the model is a kind of dynamic games, we try to find a subgame perfect equilibrium to derive some theoretical and managerial implications. In order to obtain the subgame perfect equilibrium, we use the backward induction method. In using backward induction approach, we solve the problems backward from stage 4 to stage 1. By completely knowing follower's optimal reaction to the leader's potential actions, we can fold the game tree backward. Equilibrium of each variable in the basic game is as following table. We conducted more analysis of additional game about diverse cost level of manufacturer. Manufacturer's objective function in the additional game is same with that of the basic game as follows: ${\Pi}={\Pi}_1+{\Pi}_2$, where, ${\Pi}_1=w_1(1+L-p_1)-{\psi}^2$, ${\Pi}_2=w_2(1-{\epsilon}L-p_2)$. But retailer's objective function is different from that of the basic game as follows: ${\pi}={\pi}_1+{\pi}_2$, where, ${\pi}_1=(p_1-w_1)(1+L-p_1)-L(L-{\psi})+(p_u-c)(b+L-p_u)$, ${\pi}_2=(p_2-w_2)(1-{\epsilon}L-p_2)$. Equilibrium of each variable in this additional game is as following table. Major findings of the current study are as follows: (1) As the unplanned buying effect gets stronger, manufacturer and retailer had better increase the cost for sales promotion. (2) As the unplanned buying effect gets stronger, manufacturer had better decrease the cost sharing portion of total cost for sales promotion. (3) Manufacturer's profit is increasing function of the unplanned buying effect. (4) All results of (1),(2),(3) are alleviated by the increase of retailer's procurement cost to acquire unplanned buying items. The authors discuss the implications of those results for the marketers in manufacturers or retailers. The current study firstly suggests some managerial implications for the manufacturer how to share the sales promotion cost with the retailer in a channel to the high or low level of the consumers' unplanned buying potential.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Asia Marketing Journal
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• v.13 no.2
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• pp.99-130
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• 2011

In recent years, a new way of differentiating product design has emerged -better known as 'masterpiece marketing,' this is a strategy where famous art pieces are borrowed on to product designs. Because the recent trends of well-being and LOHAS have encouraged the consumers' desires to enjoy culture and live a more opulent lifestyle, famous and notable paintings have grown to be more of "approachable masterpieces" to the public. As a strategy intended to develop a new consumerism, while still prioritizing customers' values and their satisfaction, companies have been drawn to this new type of marketing. The current consumption society has converted renowned art pieces from simply works of 'high culture' to a further way of marketing, aimed to differentiate products and dominate the market. Though many products have had masterpieces applied to their designs and have been noticed for their marketability, there has been less systematic research done on the scientific background behind this marketing approach. This research focused on the art pieces' fundamental nature of inducing emotions in the viewer, and hypothesized about how the evaluation of a product may be influenced by the affect provoked by the art piece used. To be more specific, if art pieces with different levels of pleasure and arousal -the two axis of emotion suggested by existing research on emotion -were used on each product, the goal was to see how the different levels influenced the consumer's assessment of the products, focusing on product's type as well as the evaluation of their attributes. First, a pretest was done to verify the relationship between the emotion provoked by the art piece and the consumer's preference. There were two types of surveys, each with five drawings from the ten that were assumed to differ in levels of the two axis of emotion. The survey was composed of questions asking for positive emotion, negative emotion, level of arousal, and preference. The correlation between the measurements of positive and negative emotions was -0.792, so an integrated entry was used in the analysis by subtracting the measurement of negative emotions from that of positive emotions. The first hypothesis that paintings that provoke positive emotions will be more preferred than paintings that bring out negative emotions was supported; and through this research, paintings that were to be used for the products were selected. The second pretest was conducted to settle on an item that would be used in the research. Items meant to measure utilitarian and hedonic attributes of milk and chocolate, the two products to be used in the research, were extracted. Because milk is a utilitarian product with strong practical attributes while chocolate is a hedonic product with strong hedonic attributes, these two were selected to be used in this research. The first study was executed to see if there is a difference in attitude about products that have different painting on their designs, which either induces positive or negative emotions. It was also to verify whether this difference in attitude was mediated by the viewer's preference for the art piece. This study showed that when positive emotion inducing painting was used, the product was better evaluated compared to the product with a painting that provokes a negative emotion, thus supporting the second hypothesis. It was also supported that the effect of affect on product evaluation was mediated by preference for the art piece. The second study was done to see the influence of the level of arousal on the evaluation of the product's attributes. Art pieces that differ in the level of arousal were selected through the pretest, and later it verified the hypothesis that the level of arousal has an effect on the assessment of the attributes of the product. In the case of milk, a utilitarian product, the fourth hypothesis that a high-arousal painting will better evaluated for its hedonic attributes was supported, as well as the fifth, which hypothesized that a low-arousal painting will receive a higher assessment for its utilitarian attributes. However, for chocolate, a hedonic product, both fourth and fifth hypotheses were not supported. This study is significant for the following basis: first, it verified the importance of the emotion induced by the painting on the evaluation of the product's attributes, by applying a systematic and scientific method. Second, it expanded from the existing research on positive/negative emotions to confirm the additional influence of the state of arousal on product evaluation.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.11-23
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• 2009

HSDPA (High-Speed Downlink Packet Access) is a 3.5-generation asynchronous mobile communications service based on the third generation of W-CDMA. In Korea, it is mainly provided in through videophone service. Because of the diffusion of more powerful and diversified services, along with steep advances in mobile communications technology, consumers demand a wide range of choices. However, because of the variety of technologies, which tend to overflow the market regardless of consumer preferences, consumers feel increasingly confused. Therefore, we should not adopt strategies that focus only on developing new technology on the assumption that new technologies are next-generation projects. Instead, we should understand the process by which consumers accept new forms of technology and devise schemes to lower market entry barriers through strategies that enable developers to understand and provide what consumers really want. In the Technology Acceptance Model (TAM), perceived usefulness and perceived ease of use are suggested as the most important factors affecting the attitudes of people adopting new technologies (Davis, 1989; Taylor and Todd, 1995; Venkatesh, 2000; Lee et al., 2004). Perceived usefulness is the degree to which a person believes that a particular technology will enhance his or her job performance. Perceived ease of use is the degree of subjective belief that using a particular technology will require little physical and mental effort (Davis, 1989; Morris and Dillon, 1997; Venkatesh, 2000). Perceived pleasure and perceived usefulness have been shown to clearly affect attitudes toward accepting technology (Davis et al., 1992). For example, pleasure in online shopping has been shown to positively impact consumers' attitudes toward online sellers (Eighmey and McCord, 1998; Mathwick, 2002; Jarvenpaa and Todd, 1997). The perceived risk of customers is a subjective risk, which is distinguished from an objective probabilistic risk. Perceived risk includes a psychological risk that consumers perceive when they choose brands, stores, and methods of purchase to obtain a particular item. The ability of an enterprise to revolutionize products depends on the effective acquisition of knowledge about new products (Bierly and Chakrabarti, 1996; Rothwell and Dodgson, 1991). Knowledge acquisition is the ability of a company to perceive the value of novelty and technology of the outside (Cohen and Levinthal, 1990), to evaluate the outside technology that has newly appeared (Arora and Gambaradella, 1994), and to predict the future evolution of technology accurately (Cohen and Levinthal, 1990). Consumer innovativeness is the degree to which an individual adopts innovation earlier than others in the social system (Lee, Ahn, and Ha, 2001; Gatignon and Robertson, 1985). That is, it shows how fast and how easily consumers adopt new ideas. Innovativeness is regarded as important because it has a significant effect on whether consumers adopt new products and on how fast they accept new products (Midgley and Dowling, 1978; Foxall, 1988; Hirschman, 1980). We conducted cross-national comparative research using the TAM model, which empirically verified the relationship between the factors that affect attitudes - perceived usefulness, ease of use, perceived pleasure, perceived risk, innovativeness, and perceived level of knowledge management - and attitudes toward HSDPA service. We also verified the relationship between attitudes and usage intention for the purpose of developing more effective methods of management for HSDPA service providers. For this research, 346 questionnaires were distributed among 350 students in the Republic of Korea. Because 26 of the returned questionnaires were inconsistent or had missing data, 320 questionnaires were used in the hypothesis tests. In UK, 192 of the total 200 questionnaires were retrieved, and two incomplete ones were discarded, bringing the total to 190 questionnaires used for statistical analysis. The results of the overall model analysis are as follows: Republic of Korea x2=333.27(p=0.0), NFI=0.88, NNFI=0.88, CFI=0.91, IFI=0.91, RMR=0.054, GFI=0.90, AGFI=0.84, UK x2=176.57(p=0.0), NFI=0.88, NNFI=0.90, CFI=0.93, IFI=0.93, RMR=0.062, GFI=0.90, AGFI=0.84. From the results of the hypothesis tests of Korean consumers about the relationship between factors that affect intention to use HSDPA services and attitudes, we can conclude that perceived usefulness, ease of use, pleasure, a high level of knowledge management, and innovativeness promote positive attitudes toward HSDPA mobile phones. However, ease of use and perceived pleasure did not have a direct effect on intention to use HSDPA service. This may have resulted from the fact that the use of video phones is not necessary for everyday life yet. Moreover, it has been shown that attitudes toward HSDPA video phones are directly correlated with usage intention, which means that perceived usefulness, ease of use, pleasure, a high level of knowledge management, and innovativeness. These relationships form the basis of the intention to buy, contributing to a situation in which consumers decide to choose carefully. A summary of the results of the hypothesis tests of European consumers revealed that perceived usefulness, pleasure, risk, and the level of knowledge management are factors that affect the formation of attitudes, while ease of use and innovativeness do not have an effect on attitudes. In particular, with regard to the effect value, perceived usefulness has the largest effect on attitudes, followed by pleasure and knowledge management. On the contrary, perceived risk has a smaller effect on attitudes. In the Asian model, ease of use and perceived pleasure were found not to have a direct effect on intention to use. However, because attitudes generally affect the intention to use, perceived usefulness, pleasure, risk, and knowledge management may be considered key factors in attitude development from which usage intention arises. In conclusion, perceived usefulness, pleasure, and the level of knowledge management have an effect on attitude formation in both Asian and European consumers, and such attitudes shape these consumers' intention to use. Furthermore, the hypotheses that ease of use and perceived pleasure affect usage intention are rejected. However, ease of use, perceived risk, and innovativeness showed different results. Perceived risk had no effect on attitude formation among Asians, while ease of use and innovativeness had no effect on attitudes among Europeans.