• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.5-16
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• 2009

Corporate social responsibility (CSR) activities have been shown to be potential factors that can improve corporate image and increase the ability of corporations to compete. However, most previous studies related to CSR activities investigated how these activities influence product and corporate evaluation, as well as corporate image. In addition, some researchers treated consumers' perceptions of corporate motives as moderator variables in evaluating the relationship between corporate social responsibilities and consumer response. However, motive-based theories have some weaknesses. Corporate social responsibility activities cause two motives(egoistic vs. altruistic) for consumers, but recently, Vlachos et al. (2008) argued that these motives should be segmented. Thus, it is possible to transform the original theory into a modified theory model (persuasion knowledge model, PKM). Vlachos et al. (2008) segmented corporate social responsibility motives into four types and compared the effects of these motives on customer loyalty. Prior studies have proved that CSR activities with positive motives have positive influences on customer loyalty. However, the psychological reasons underlying this finding have not been determined empirically. Thus, the objectives of this research are twofold. First, we attempt to determine why most customers favor companies that they feel have positive motives for their corporate social responsibility activities. Second, we attempt to measure the effects of consumers' reciprocity when society benefits from corporate social responsibility activities. The following research hypotheses are constructed. H1: Values-driven motives for corporate social responsibility activities have a positive influence on the perceived reciprocity. H2: Stakeholder-driven motives for corporate social responsibility activities have a negative influence on the perceived reciprocity. H3: Egoistic-driven motives for corporate social responsibility activities have a negative influence on perceived reciprocity. H4: Strategic-driven motives for corporate social responsibility activities have a negative influence on perceived reciprocity. H5: Perceived reciprocity for corporate social responsibility activities has a positive influence on consumer loyalty. A single company is selected as a research subject to understand how the motives behind corporate social responsibility influence consumers' perceived reciprocity and customer loyalty. A total sample of 200 respondents was selected for a pilot test. In addition, to ensure a consistent response, we ensured that the respondents were older than 20 years of age. The surveys of 172 respondents (males-82, females-90) were analyzed after 28 invalid questionnaires were excluded. Based on our cutoff criteria, the model fit the data reasonably well. Values-driven motives for corporate social responsibility activities had a positive effect on perceived reciprocity (t = 6.75, p < .001), supporting H1. Morales (2005) also found that consumers appreciate a company's social responsibility efforts and the benefits provided by these efforts to society. Stakeholder-driven motives for corporate social responsibility activities did not affect perceived reciprocity (t = -.049, p > .05). Thus, H2 was rejected. Egoistic-driven motives (t = .3.11, p < .05) and strategic-driven (t = -4.65, p < .05) motives had a negative influence on perceived reciprocity, supporting H3 and H4, respectively. Furthermore, perceived reciprocity had a positive influence on consumer loyalty (t = 4.24, p < .05), supporting H5. Thus, compared with the general public, undergraduate students appear to be more influenced by egoistic-driven motives. We draw the following conclusions from our research findings. First, value-driven attributions have a positive influence on perceived reciprocity. However, stakeholder-driven attributions have no significant effects on perceived reciprocity. Moreover, both egoistic-driven attributions and strategic-driven attributions have a negative influence on perceived reciprocity. Second, when corporate social responsibility activities align with consumers' reciprocity, the efforts directed towards social responsibility activities have a positive influence on customer loyalty. In this study, we examine whether the type of motivation affects consumer responses to CSR, and in particular, we evaluate how CSR motives can influence a key internal factor (perceived reciprocity) and behavioral consumer outcome (customer loyalty). We demonstrate that perceived reciprocity plays a mediating role in the relationship between CSR motivation and customer loyalty. Our study extends the research on consumer CSR-inferred motivations, positing them as a direct indicator of consumer responses. Furthermore, we convincingly identify perceived reciprocity as a sub-process mediating the effect of CSR attributions on customer loyalty. Future research investigating the ultimate behavior and financial impact of CSR should consider that the impacts of CSR also stem from perceived reciprocity. The results of this study also have important managerial implications. First, the central role that reciprocity plays indicates that managers should routinely measure how much their socially responsible actions create perceived reciprocity. Second, understanding how consumers' perceptions of CSR corporate motives relate to perceived reciprocity and customer loyalty can help managers to monitor and enhance these consumer outcomes through marketing initiatives and management of CSR-induced attribution processes. The results of this study will help corporations to understand the relative importance of the four different motivations types in influencing perceived reciprocity.

• Journal of Distribution Science
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• v.10 no.2
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• pp.29-41
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• 2012

This paper undertakes a conceptual review of transaction cost to broaden the understanding of the transaction cost analysis (TCA) approach. More than 40 years have passed since Coase's fundamental insight that transaction, coordination, and contracting costs must be considered explicitly in explaining the extent of vertical integration. Coase (1937) forced economists to identify previously neglected constraints on the trading process to foster efficient intrafirm, rather than interfirm, transactions. The transaction cost approach to economic organization study regards transactions as the basic units of analysis and holds that understanding transaction cost economy is central to organizational study. The approach applies to determining efficient boundaries, as between firms and markets, and to internal transaction organization, including employment relations design. TCA, developed principally by Oliver Williamson (1975,1979,1981a) blends institutional economics, organizational theory, and contract law. Further progress in transaction costs research awaits the identification of critical dimensions in which transaction costs differ and an examination of the economizing properties of alternative institutional modes for organizing transactions. The crucial investment distinction is: To what degree are transaction-specific (non-marketable) expenses incurred? Unspecialized items pose few hazards, since buyers can turn toalternative sources, and suppliers can sell output intended for one order to other buyers. Non-marketability problems arise when specific parties' identities have important cost-bearing consequences. Transactions of this kind are labeled idiosyncratic. The summarized results of the review are as follows. First, firms' distribution decisions often prompt examination of the make-or-buy question: Should a marketing activity be performed within the organization by company employees or contracted to an external agent? Second, manufacturers introducing an industrial product to a foreign market face a difficult decision. Should the product be marketed primarily by captive agents (the company sales force and distribution division) or independent intermediaries (outside sales agents and distribution)? Third, the authors develop a theoretical extension to the basic transaction cost model by combining insights from various theories with the TCA approach. Fourth, other such extensions are likely required for the general model to be applied to different channel situations. It is naive to assume the basic model appliesacross markedly different channel contexts without modifications and extensions. Although this study contributes to scholastic research, it is limited by several factors. First, the theoretical perspective of TCA has attracted considerable recent interest in the area of marketing channels. The analysis aims to match the properties of efficient governance structures with the attributes of the transaction. Second, empirical evidence about TCA's basic propositions is sketchy. Apart from Anderson's (1985) study of the vertical integration of the selling function and John's (1984) study of opportunism by franchised dealers, virtually no marketing studies involving the constructs implicated in the analysis have been reported. We hope, therefore, that further research will clarify distinctions between the different aspects of specific assets. Another important line of future research is the integration of efficiency-oriented TCA with organizational approaches that emphasize specific assets' conceptual definition and industry structure. Finally, research of transaction costs, uncertainty, opportunism, and switching costs is critical to future study.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• Asia Marketing Journal
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• v.13 no.4
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• pp.55-76
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• 2012

Most people prefer to choose zero-cost products they may get without paying any money. The 'zero-cost effect' can be explained with a 'zero-cost model' where consumers attach special values to zero-cost products in a different way from general economic models (Shampanier, Mazar and Ariely 2007). If 2 different products at the regular prices of ￦200 and ￦400 simultaneously offer ￦200 discounts, the prices will be changed to ￦0 and ￦200, respectively. In spite of the same price gap of the two products after the ￦200 discounts, people are much more likely to select the free alternative than the same product at the price of ￦200. Although prior studies have focused on the 'zero-cost effect' in isolation of other factors, this study investigates the moderating effects of a self-regulatory resource and a construal level on the selection of free products. Self-regulatory resources induce people to control or regulate their behavior. However, since self-regulatory resources are limited, they are to be easily depleted when exerted (Muraven, Tice, and Baumeister 1998). Without the resources, consumers tend to become less sensitive to price changes and to spend money more extravagantly (Vohs and Faber 2007). Under this condition, they are also likely to invest less effort on their information processing and to make more intuitive decisions (Pocheptsova, Amir, Dhar, and Baumeister 2009). Therefore, context effects such as price changes and zero cost effects are less likely in the circumstances of resource depletion. In addition, construal levels have profound effects on the ways of information processing (Trope and Liberman 2003, 2010). In a high construal level, people tend to attune their minds to core features and desirability aspects, whereas, in a low construal level, they are more likely to process information based on secondary features and feasibility aspects (Khan, Zhu, and Kalra 2010). A perceived value of a product is more related to desirability whereas a zero cost or a price level is more associated with feasibility. Thus, context effects or reliance on feasibility (for instance, the zero cost effect) will be diminished in a high level construal while those effects may remain in a low level construal. When people make decisions, these 2 factors can influence the magnitude of the 'zero-cost effect'. This study ran two experiments to investigate the effects of self-regulatory resources and construal levels on the selection of a free product. Kisses and Ferrero-Rocher, which were adopted in the prior study (Shampanier et al. 2007) were also used as alternatives in Experiments 1 and 2. We designed Experiment 1 in order to test whether self-regulatory resource depletion will moderate the zero-cost effect. The level of self-regulatory resources was manipulated with two different tasks, a Sudoku task in the depletion condition and a task of drawing diagrams in the non-depletion condition. Upon completion of the manipulation task, subjects were randomly assigned to one of a decision set with a zero-cost option (i.e., Kisses ￦0, and Ferrero-Rocher ￦200) or a set without a zero-cost option (i.e., Kisses ￦200, and Ferrero-Rocher ￦400). A pair of alternatives in the two decision sets have the same price gap of ￦200 between a low-priced Kisses and a high-priced Ferrero-Rocher. Subjects in the no-depletion condition selected Kisses more often (71.88%) over Ferrero-Rocher when Kisses was free than when it was priced at ￦200 (34.88%). However, the zero-cost effect disappeared when people do not have self-regulatory resources. Experiment 2 was conducted to investigate whether constual levels influence the magnitude of the 'zero-cost effect'. To manipulate construal levels, 4 different 'why (in the high construal level condition)' or 'how (in the low construal level condition)' questions about health management were asked. They were presented with 4 boxes connected with downward arrows. In a box at the top, there was one question, 'Why do I maintain good physical health?' or 'How do I maintain good physical health?' Subjects inserted a response to the question of why or how they would maintain good physical health. Similar tasks were repeated for the 2nd, 3rd, and 4th responses. After the manipulation task, subjects were randomly assigned either to a decision set with a zero-cost option, or to a set without it, as in Experiment 1. When a low construal level is primed with 'how', subjects chose free Kisses (60.66%) more often over Ferrero-Rocher than they chose ￦200 Kisses (42.19%) over ￦400 FerreroRocher. On contrast, the zero-cost effect could not be observed any longer when a high construal level is primed with 'why'.

• Korean small business review
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• v.33 no.4
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• pp.77-93
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• 2011

Since 2000, the employment rate of small and medium enterprises (SMEs) has dwindled while the creation of new jobs and the emergence of healthy SMEs have been stagnant. The fundamental reason for these symptoms is that the economic structure is disadvantageous to SMEs. In particular, the greater gap between SMEs and large enterprises has resulted in polarization, and the resulting imbalance has become the largest obstacle to improving SMEs' competitiveness. For example, the total productivity has continued to drop, and the average productivity of SMEs is now merely 30% of that of large enterprises, and the average wage of SMEs' employees is only 53% of that of large enterprises. Along with polarization, rapid industrialization has also caused anti-enterprise consensus, the collapse of the middle class, hostility towards establishments, and other aftereffects. The general consensus is that unless these problems are solved, South Korea will not become an advanced country. Especially, South Korea is now facing issues that need urgent measures, such as the decline of its economic growth, the worsening distribution of profits, and the increased external volatility. Recognizing such negative trends, the MB administration proposed a win-win growth policy and recently introduced a new national value called "ecosystemic development." As the terms in such policy agenda are similar, however, the conceptual differences among such terms must first be fully understood. Therefore, in this study, the concepts of win-win growth policy and ecosystemic development, and the need for them, were surveyed, and their differences from and similarities with other policy concepts like win-win cooperation and symbiotic development were examined. Based on the results of the survey and examination, the study introduced a South Korean model of win-win growth, targeting the promotion of a sound balance between large enterprises and SMEs and an innovative ecosystem, and finally, proposing future policy tasks. Win-win growth is not an academic term but a policy term. Thus, it is less advisable to give a theoretical definition of it than to understand its concept based on its objective and method as a policy. The core of the MB administration's win-win growth policy is the creation of a partnership between key economic subjects such as large enterprises and SMEs based on each subject's differentiated capacity, and such economic subjects' joint promotion of growth opportunities. Its objective is to contribute to the establishment of an advanced capitalistic system by securing the sustainability of the South Korean economy. Such win-win growth policy includes three core concepts. The first concept, ecosystem, is that win-win growth should be understood from the viewpoint of an industrial ecosystem and should be pursued by overcoming the issues of specific enterprises. An enterprise is not an independent entity but a social entity, meaning it exists in relationship with the society (Drucker, 2011). The second concept, balance, points to the fact that an effort should be made to establish a systemic and social infrastructure for a healthy balance in the industry. The social system and infrastructure should be established in such a way as to create a balance between short- term needs and long-term sustainability, between freedom and responsibility, and between profitability and social obligations. Finally, the third concept is the behavioral change of economic entities. The win-win growth policy is not merely about simple transactional relationships or determining reasonable prices but more about the need for a behavior change on the part of economic entities, without which the objectives of the policy cannot be achieved. Various advanced countries have developed different win-win growth models based on their respective cultures and economic-development stages. Japan, whose culture is characterized by a relatively high level of group-centered trust, has developed a productivity improvement model based on such culture, whereas the U.S., which has a highly developed system of market capitalism, has developed a system that instigates or promotes market-oriented technological innovation. Unlike Japan or the U.S., Europe, a late starter, has not fully developed a trust-based culture or market capitalism and thus often uses a policy-led model based on which the government leads the improvement of productivity and promotes technological innovation. By modeling successful cases from these advanced countries, South Korea can establish its unique win-win growth system. For this, it needs to determine the method and tasks that suit its circumstances by examining the prerequisites for its success as well as the strengths and weaknesses of each advanced country. This paper proposes a South Korean model of win-win growth, whose objective is to upgrade the country's low-trust-level-based industrial structure, in which large enterprises and SMEs depend only on independent survival strategies, to a high-trust-level-based social ecosystem, in which large enterprises and SMEs develop a cooperative relationship as partners. Based on this objective, the model proposes the establishment of a sound balance of systems and infrastructure between large enterprises and SMEs, and to form a crenovative social ecosystem. The South Korean model of win-win growth consists of three axes: utilization of the South Koreans' potential, which creates community-oriented energy; fusion-style improvement of various control and self-regulated systems for establishing a high-trust-level-oriented social infrastructure; and behavioral change on the part of enterprises in terms of putting an end to their unfair business activities and promoting future-oriented cooperative relationships. This system will establish a dynamic industrial ecosystem that will generate creative energy and will thus contribute to the realization of a sustainable economy in the 21st century. The South Korean model of win-win growth should pursue community-based self-regulation, which promotes the power of efficiency and competition that is fundamentally being pursued by capitalism while at the same time seeking the value of society and community. Already existing in Korea's traditional roots, such objectives have become the bases of the Shinbaram culture, characterized by the South Koreans' spontaneity, creativity, and optimism. In the process of a community's gradual improvement of its rules and procedures, the trust among the community members increases, and the "social capital" that guarantees the successful control of shared resources can be established (Ostrom, 2010). This basic ideal can help reduce the gap between large enterprises and SMEs, alleviating the South Koreans' victim mentality in the face of competition and the open-door policy, and creating crenovative corporate competitiveness. The win-win growth policy emerged for the purpose of addressing the polarization and imbalance structure resulting from the evolution of 21st-century capitalism. It simultaneously pursues efficiency and fairness on one hand and economic and community values on the other, and aims to foster efficient interaction between the market and the government. This policy, however, is also evolving. The win-win growth policy can be considered an extension of the win-win cooperation that the past 'Participatory Government' promoted at the enterprise management level to the level of systems and culture. Also, the ecosystemic development agendum that has recently emerged is a further extension that has been presented as a national ideal of "a new development model that promotes the co-advancement of environmental conservation, growth, economic development, social integration, and national and individual development."

• Journal of Venture Innovation
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• v.1 no.2
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• pp.47-59
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• 2018

With the recent, rapid changes in the socio-economic environment, organizations of today are now required to present a framework of realistic consumer behaviors based on psychology, economy, and finance, in order to understand their investing customers. Stock investors show differences in terms of their decisions or evaluations in the process of investing. This is due to what is called the 'framing effect.' The decision frames of the investors are defined differently, and, as a result, this affects the decisions made by the investors. Preceding studies on stock investment rarely touched the topic of the effect of message framing on market participants in their stock investment, especially regarding the differences in terms of their risk management behaviors based on the message framing in stock investment. Therefore, the purpose of this study is to examine the influence of stock investment message framing on market participants in their investment decision making and empirically validate whether this message framing effect has a moderating effect on the factors of investment satisfaction. For this, 494 participants with stock investment experiences were interviewed from May 1 to 26, 2018, and the results were used as the data for the empirical analysis. The analysis of the data was conducted using SPSS 22.0 statistical analysis software. The results of this study were as follows; First, of the stock investment behavioral factors, the stock comprehension, recommendation by others for a stock, and the degree of risks of a stock affected stock investment satisfaction in a positive manner. And, of the behavioral factors of stock investment, stock comprehension, stock brand, recommendation on the stocks from others, past performances, and risk levels of stocks affected the intent of continued stock investment in a positive manner. Second, message framing turned out to affect stock investment satisfaction in a positive manner, and it also had a significant moderating effect to the relationship between the stock investment behavior and stock investment satisfaction. Third, message framing was found to affect continued stock investment intent significantly, with a significant moderating effect in the relationship between stock investment behavioral factor and continued stock investment intent.

• The Journal of Industrial Distribution & Business
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• v.2 no.2
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• pp.5-14
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• 2011

Opening agricultural market expansion, reduced purchases through wholesale markets, expanding the influence large retailers of consumer's market such as changes in the distribution system to the farmer's market conditions are changing rapidly. Because of this, retailers of the scaled and chain-store operations was centered on distribution environmental changes of the consumer market place. In producing area due to changes in market conditions in the agricultural production of in producing area distribution organization and the size distribution can not be put off no longer challenge is imminent. If it do not raise forces banded together, the producer is bound to remain as the weak. To support the distribution of this production was introduced in 2000 enable the Activation Project of in producing area distribution. Recent in producing area Changes of Agricultural conditions in order to cope with the Small-scale farmers and small individual farmers are becoming Scaled and specialized. Also, is specific to each item and regional is showing aspects. Government support for Activation Project of in producing area distribution is greatly improved, but in terms of competitiveness on the market still is showing the limitations. The most common of these problems, the market response if in producing area producer's organization and scale of the problem. Equipped for the purpose of consumer market place responsiveness unreasonable propelled outward from the Painter-sized weakens the organizational power. also, Difficult to succeed organizational size is a dissolution or anything within a few years, farmers around the best producer organizations, such as deviation occurs is exposed to a variety of issues. In this study, previous studies refer to the recent changes in agricultural retail environment, background and needs of organization·scaled, Determine the status of the domestic in producing area organizations and derived Problems, look into Domestic and overseas of in producing area organization with best practices for enhancing the competitiveness of the proposed improvement are intended to. In the future, in producing area distribution policy would like to provide direction to the development. The results of the study showed the follwing : 1) enhance utilization and orrganized through the diversification of the agricultural Collection systems. 2) Scaled to achieve through Items of specialized a wide area marketing. 3) Management operating units, such as installation and operating that overseas the best practices " Comite Economique Agricole Regional 'Fruits et Legumes' de Bretagne". 4) To establish a support system that in producing area distribution organization model development for appropriate domestic. In particular, in case of domestic in producing area distribution organization, through the analysis of various case study that a successful organization and scaled. The process of the various challenges arising in organizational scaled and generalization, and by the way he goes about trying to overcome is required. At the end of the study's limitations and future research directions suggested.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.