• Asia Marketing Journal
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• v.14 no.3
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• pp.49-68
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• 2012

When a channel is vertically separated, there can be inefficiencies, double marginalization. Channel coordination to amend this inefficiency has been an important issue in marketing and economics. Channel coordination deals with maximization of joint profit and achieving proper profit sharing among participants. In this paper, a manufacturer and heterogeneous multiple retailers with exclusive territory are assumed, and channel coordination with two-part tariff is considered. When multiple heterogeneous retailers are assumed, profit sharing can be an issue even though the tariffs based on marginal cost can maximize joint profit. In case of multiple heterogeneous retailers, the manufacturer earns the same profit (fixed fee) from each retailer. This means that a large retailer occupies all the gaps of channel profit between small and large markets. Then, the manufacturer, which generally plays the role of Stackelberg leader, will consider increasing fixed price or marginal price to earn more profit from large retailer. Those reactions can sacrifice maximization of joint profit by making small retailer withdraw or by changing the sales quantities. In this paper, to maximize joint profit and achieve proper profit sharing, two kinds of optional tariffs are considered. The first is an optional two-part tariff based on marginal cost and the second is an optional modified two-part tariff in which marginal prices are higher than the manufacturer's marginal cost. In both types of optional tariffs, maximization of joint profit in each market can be achieved. Moreover, optional tariffs alleviate the problem of profit sharing. Optional tariffs can provide a manufacturer more profit from a large retailer when profit from a small retailer is given. However, the analysis shows that the maximum share of manufacturer from a large retailer is restricted by the condition for self-selection. In case of optional two-part tariffs based on marginal cost, if the gap between demands is large, the maximum share of the manufacturer is sufficient to achieve proper profit sharing. If the gap between demands is not sufficiently large, the manufacturer cannot earn sufficient share from increased profit. An optional modified two-part tariff where marginal price is more than marginal cost of manufacturer is considered because of this scenario. The marginal price above the marginal cost may additionally control the distribution of the increased profit. However, the analysis shows that a manufacturer's maximum profit from a large retailer with given profit from a small retailer is the same as or lower than the maximum profit when optional two-part tariffs based on marginal cost are applied. Therefore, it can be concluded that the optional modified tariffs do not have additional contribution to profit sharing relative to the tariffs based on marginal cost. Although this paper does not cover all kinds of optional tariffs that are different from tariffs based on marginal cost, it shows the advantage of optional tariffs based on marginal cost and has important theoretical implications. The result of this paper also gives guide for channel coordination. Optional two-part tariff based on marginal cost can increase efficiency in channel coordination.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Asia Marketing Journal
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• v.15 no.4
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• pp.61-101
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• 2014

This study investigates when and how disagreements in online customer ratings prompt more favorable product evaluations. Among the three metrics of volume, valence, and variance that feature in the research on online customer ratings, volume and valence have exhibited consistently positive patterns in their effects on product sales or evaluations (e.g., Dellarocas, Zhang, and Awad 2007; Liu 2006). Ratings variance, or the degree of disagreement among reviewers, however, has shown rather mixed results, with some studies reporting positive effects on product sales (e.g., Clement, Proppe, and Rott 2007) while others finding negative effects on product evaluations (e.g., Zhu and Zhang 2010). This study aims to resolve these contradictory findings by introducing preference heterogeneity as a possible moderator and causal attribution as a mediator to account for the moderating effect. The main proposition of this study is that when preference heterogeneity is perceived as high, a disagreement in ratings is attributed more to reviewers' different preferences than to unreliable product quality, which in turn prompts better quality evaluations of a product. Because disagreements mostly result from differences in reviewers' tastes or the low reliability of a product's quality (Mizerski 1982; Sen and Lerman 2007), a greater level of attribution to reviewer tastes can mitigate the negative effect of disagreement on product evaluations. Specifically, if consumers infer that reviewers' heterogeneous preferences result in subjectively different experiences and thereby highly diverse ratings, they would not disregard the overall quality of a product. However, if consumers infer that reviewers' preferences are quite homogeneous and thus the low reliability of the product quality contributes to such disagreements, they would discount the overall product quality. Therefore, consumers would respond more favorably to disagreements in ratings when preference heterogeneity is perceived as high rather than low. This study furthermore extends this prediction to the various levels of average ratings. The heuristicsystematic processing model so far indicates that the engagement in effortful systematic processing occurs only when sufficient motivation is present (Hann et al. 2007; Maheswaran and Chaiken 1991; Martin and Davies 1998). One of the key factors affecting this motivation is the aspiration level of the decision maker. Only under conditions that meet or exceed his aspiration level does he tend to engage in systematic processing (Patzelt and Shepherd 2008; Stephanous and Sage 1987). Therefore, systematic causal attribution processing regarding ratings variance is likely more activated when the average rating is high enough to meet the aspiration level than when it is too low to meet it. Considering that the interaction between ratings variance and preference heterogeneity occurs through the mediation of causal attribution, this greater activation of causal attribution in high versus low average ratings would lead to more pronounced interaction between ratings variance and preference heterogeneity in high versus low average ratings. Overall, this study proposes that the interaction between ratings variance and preference heterogeneity is more pronounced when the average rating is high as compared to when it is low. Two laboratory studies lend support to these predictions. Study 1 reveals that participants exposed to a high-preference heterogeneity book title (i.e., a novel) attributed disagreement in ratings more to reviewers' tastes, and thereby more favorably evaluated books with such ratings, compared to those exposed to a low-preference heterogeneity title (i.e., an English listening practice book). Study 2 then extended these findings to the various levels of average ratings and found that this greater preference for disagreement options under high preference heterogeneity is more pronounced when the average rating is high compared to when it is low. This study makes an important theoretical contribution to the online customer ratings literature by showing that preference heterogeneity serves as a key moderator of the effect of ratings variance on product evaluations and that causal attribution acts as a mediator of this moderation effect. A more comprehensive picture of the interplay among ratings variance, preference heterogeneity, and average ratings is also provided by revealing that the interaction between ratings variance and preference heterogeneity varies as a function of the average rating. In addition, this work provides some significant managerial implications for marketers in terms of how they manage word of mouth. Because a lack of consensus creates some uncertainty and anxiety over the given information, consumers experience a psychological burden regarding their choice of a product when ratings show disagreement. The results of this study offer a way to address this problem. By explicitly clarifying that there are many more differences in tastes among reviewers than expected, marketers can allow consumers to speculate that differing tastes of reviewers rather than an uncertain or poor product quality contribute to such conflicts in ratings. Thus, when fierce disagreements are observed in the WOM arena, marketers are advised to communicate to consumers that diverse, rather than uniform, tastes govern reviews and evaluations of products.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.37-66
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• 2021

This study aims to provide self-development opportunities to hair salons service workers through e-learning and provide the foundation of sustainable hair salons management by cultivating good talents to hair salons service business executives. In particular, the factors affecting e-learning achievement are identified according to learner characteristics to see whether these factors affect the satisfaction of e-learning learners and also affect the performance of management. The results of the study are summarized as follows. As a result of hypotheses testing on the relationship between e-learning learning environment and e-learning satisfaction, it was found that the higher the level of e-learning content quality is, the higher the satisfaction of e-learning is, the higher the satisfaction of e-learning is, and that the higher the quality level of the support infrastructure is, the higher the satisfaction of e-learning is. The results of the hypotheses testing on the moderating effect of learner factors showed that the influence of the quality of the support infrastructure on the e-learning satisfaction differs according to the level of the learner's goal consciousness. However, it was found that the influence of content quality on e-learning satisfaction according to the level of the learners goal awareness, the influence of content quality on e-learning satisfaction according to the level of the aggressiveness of the learners learning attitude, and the influence of the quality of the support infrastructure on the e-learning satisfaction according to the level of the aggressiveness of learners learning attitude were found to identically demonstrate no moderating effects. The results of hypotheses testing on the relationships among e-Learning performance show that the higher the satisfaction of e-learning was, the higher the customer orientation was, and the higher the satisfaction of e-learning was, the higher the contribution of management performance was, and the higher the customer orientation was, the higher the contribution of management performance was. The implications of this study are as follows. First, the actual path of realiting e-learning performance could be identified that is this study provided organizational decision makers involved in the hair salons service operations with practical guidance for the introduction and expansion of successful educational systems. Second, the e-learning environment derived from the theoretical background is different from the e-learning environment required by the learners.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.31-54
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• 2007

The exchange between buyers and sellers in the industrial market is changing from short-term to long-term relationships. Long-term relationships are governed mainly by formal contracts or informal agreements, but many scholars are now asserting that controlling relationship by using formal contracts under environmental dynamism is inappropriate. In this case, partners will depend on each other's flexibility or interdependence. The former, flexibility, provides a general frame of reference, order, and standards against which to guide and assess appropriate behavior in dynamic and ambiguous situations, thus motivating the value-oriented performance goals shared between partners. It is based on social sacrifices, which can potentially minimize any opportunistic behaviors. The later, interdependence, means that each firm possesses a high level of dependence in an dynamic channel relationship. When interdependence is high in magnitude and symmetric, each firm enjoys a high level of power and the bonds between the firms should be reasonably strong. Strong shared power is likely to promote commitment because of the common interests, attention, and support found in such channel relationships. This study deals with environmental dynamism in high-tech industry. Firms in the high-tech industry regard it as a key success factor to successfully cope with environmental changes. However, due to the lack of studies dealing with environmental dynamism and supply chain commitment in the high-tech industry, it is very difficult to find effective strategies to cope with them. This paper presents the results of an empirical study on the relationship between environmental dynamism and supply chain commitment in the high-tech industry. We examined the effects of consumer, competitor, and technological dynamism on supply chain commitment. Additionally, we examined the moderating effects of flexibility and dependence of supply chains. This study was confined to the type of high-tech industry which has the characteristics of rapid technology change and short product lifecycle. Flexibility among the firms of this industry, having the characteristic of hard and fast growth, is more important here than among any other industry. Thus, a variety of environmental dynamism can affect a supply chain relationship. The industries targeted industries were electronic parts, metal product, computer, electric machine, automobile, and medical precision manufacturing industries. Data was collected as follows. During the survey, the researchers managed to obtain the list of parts suppliers of 2 companies, N and L, with an international competitiveness in the mobile phone manufacturing industry; and of the suppliers in a business relationship with S company, a semiconductor manufacturing company. They were asked to respond to the survey via telephone and e-mail. During the two month period of February-April 2006, we were able to collect data from 44 companies. The respondents were restricted to direct dealing authorities and subcontractor company (the supplier) staff with at least three months of dealing experience with a manufacture (an industrial material buyer). The measurement validation procedures included scale reliability; discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.70. A series of exploratory factor analyses was conducted. We conducted confirmatory factor analyses to assess the validity of our measurements. A series of chi-square difference tests were conducted so that the discriminant validity could be ensured. For each pair, we estimated two models-an unconstrained model and a constrained model-and compared the two model fits. All these tests supported discriminant validity. Also, all items loaded significantly on their respective constructs, providing support for convergent validity. We then examined composite reliability and average variance extracted (AVE). The composite reliability of each construct was greater than.70. The AVE of each construct was greater than.50. According to the multiple regression analysis, customer dynamism had a negative effect and competitor dynamism had a positive effect on a supplier's commitment. In addition, flexibility and dependence had significant moderating effects on customer and competitor dynamism. On the other hand, all hypotheses about technological dynamism had no significant effects on commitment. In other words, technological dynamism had no direct effect on supplier's commitment and was not moderated by the flexibility and dependence of the supply chain. This study makes its contribution in the point of view that this is a rare study on environmental dynamism and supply chain commitment in the field of high-tech industry. Especially, this study verified the effects of three sectors of environmental dynamism on supplier's commitment. Also, it empirically tested how the effects were moderated by flexibility and dependence. The results showed that flexibility and interdependence had a role to strengthen supplier's commitment under environmental dynamism in high-tech industry. Thus relationship managers in high-tech industry should make supply chain relationship flexible and interdependent. The limitations of the study are as follows; First, about the research setting, the study was conducted with high-tech industry, in which the direction of the change in the power balance of supply chain dyads is usually determined by manufacturers. So we have a difficulty with generalization. We need to control the power structure between partners in a future study. Secondly, about flexibility, we treated it throughout the paper as positive, but it can also be negative, i.e. violating an agreement or moving, but in the wrong direction, etc. Therefore we need to investigate the multi-dimensionality of flexibility in future research.

• Management & Information Systems Review
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• v.34 no.5
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• pp.1-21
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• 2015

This study is to testify whether according to the variables of population statistics there emerge differences in the ethical leadership, ethical climate, organizational citizenship behavior and LMX by Social Entrepreneurs. For this we have performed survey 652 social entrepreneurs at authorized Social Enterprises. The results of analysis are as follows. First, it was analyzed that the sub-factors of the ethical leadership, such as contribution and integrity by Social entrepreneurs have revealed significant difference according to gender. Also the sub-factor of ethical climate, such as utilitarianism has revealed significant difference by gender, too. The analysis result signifies no significance in OCB, LMX. Second, there were significant difference in the sub-factor of ethical leadership such as integrity, the sub-factor of ethical climate such as, utilitarianism, the sub-factor of OCB such as effectiveness, and LMX by religious. Third, the analysis result signifies no significance in ex-work place, whether they worked at Social enterprise or not. Finally, as the result of our analysis whether there are any differences according to gender, religious, and ex-work place of the Social entrepreneurs in the ethical leadership, ethical climate, OCB, and LMX by Social entrepreneurs, it was revealed that there are some significant. This study emphasizes the importance of ethical leadership, ethical climate, OCB and LMX. It reveled these variables have differences by demographic characteristics of Social entrepreneurs. In conclusion, this study suggests that the consideration of the variables of population statistics according to the various variables about Social enterprise.

• CRM연구
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• v.3 no.2
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• pp.43-68
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• 2010

One of the recent research trends that universities are increasingly adopting the concept of 'customer' and the customer-oriented strategy has urged us to research enterprise-wide CRM strategy adaptable to university administration. As the first step of CRM strategy for university management, we try to validate the difference of CRM strategic factors among university types. Drawing upon both CRM process and customer equity drivers, which have been recognized as core frameworks for CRM strategy, we developed those survey instruments adoptable into university industry, and validated statistically-significant difference among 12 types of university group constructed by the levels of university evaluation and the location of the universities. We collected 261 responses from 177 universities from all over the country and analyzed the data to see the levels of CRM processes consisting of customer acquisition, retention, and expansion, and customer equity drivers consisting of value equity, brand equity, and relationship equity by using multivariate ANOVA(MANOVA). The result confirms the explicit differences of the levels of CRM processes and customer equity drivers between the groups by university evaluation levels(high/middle/low). However, the analysis failed to show the significant differences of those between the group by university locations(the capital/the suburbs/the six megalopolises/other countries). More specifically, the level of activities for customer acquisition and retention of the universities in the higher-graded group are significantly different from those in the lower-graded group from the perspective of CRM process. In terms of customer equity drivers, the levels of both brand equity and relationship equity of the higher-graded group are significantly higher than those of both middle and lower-graded group. In addition, we found that the value equity between the higher and lower-graded groups, and the brand equity between the middle and lower-graded groups are different each other. This study provides an important meaning in that we tried to consider CRM strategy which has been mainly addressed in profit-making industries in terms of non-profit organization context. Our endeavors to develop and validate empirical measurements adoptable to university context could be an academic contribution. In terms of practical meaning, the processes and results of this study might be a guideline to many universities to build their own CRM strategies. According to the research results, those insights could be expressed in several messages. First, we propose to universities that they should plan their own differentiated CRM strategies according to their positions in terms of university evaluation. For example, although it is acceptable that a university in lower-level group might follow the CRM process strategy of the middle-level group universities, it is not a good idea to imitate the customer acquisition and retention activities of the higher-level group universities. Moreover, since this study reported that the level of universities' brand equity is just correlated with the level of university evaluation, it might be pointless for the middle or lower-leveled universities if they just copy their brand equity strategies from those of higher-leveled ones even though such activities are seemingly attractive. Meanwhile, the difference of CRM strategy by university position might provide universities with the direction where they should go for their CRM strategies. For instance, our study implies that the lower-positioned universities should improve all of the customer equity drivers with concerted efforts because their value, brand, and relationship equities are inferior compared with the higher and middle-positioned universities' ones. This also means that they should focus on customer acquisition and expansion initiatives rather than those for customer retention because all of the customer equity drivers could be influenced by the two kinds of CRM processes (KIm and Lee, 2010). Surely specific and detailed action plans for enhancing customer equity drivers should be developed after grasping their customer migration patterns illustrated by the rates of acquisition, retention, upgrade, downgrade, and defection for each customer segment.

• 한국벤처창업학회:학술대회논문집
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• 2008.11a
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• pp.135-168
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• 2008

The Korean semiconductor industry has made a great contribution to growth of Korean economy for the last decades by maintaining a top position in terms of Korean total annual export volume. However, the advanced semiconductor equipment and materials that are used for the production of semiconductor devices still depend on the suppliers from Europe, Japan, and America who have an influential position in the Korean semiconductor industry. The objective of this study is to empirically investigate the attributes determining the extent of autonomy in decision making for the Korean subsidiaries of multinational corporations in the semiconductor industry. This study found there were differences in the extent of autonomy in decision making in terms of the global strategies the multinational corporations pursue. This study surveyed employees at the Korean subsidiaries and joint venture companies of semiconductor multinational corporations and collected 726 survey questionnaires. Several statistical analyses including frequency analysis, reliability analysis, factor analysis, multiple regression analysis and ANOVA were performed using the collected sample data. Based on the analyses, this study found as follow: Firstly, from the factor analysis, this study found Korean subsidiaries faced three sources of uncertainties stemmed from political conditions, competent conditions, demand and supply conditions. The internal resources were characterized by the independencies of production capability, financial capability, marketing capability and human resource management capability. The operational performance was determined by total revenue, net profit and market share growth. Secondly, it was found the uncertainties from political condition and competent condition and the independencies of financial capability and marketing capability partially influenced the extent of autonomy in decision making. The independencies of production capability and human resource management capability significantly influenced the autonomy of decision making in the most areas. It was also found an increase of total revenue, net profit and market share growth partially affected the extent of autonomy in decision making of the Korean subsidiaries. Finally, it was found that the polycentrism of global management by multinational corporations seemed to bring a higher extent of autonomy in decision making than ethnocentrism or geocentrism of global management. Based on the results, this study provided managerial implications regarding the extent of autonomy in decision making for Korean subsidiaries of multinational corporations in order to help management to enhance their business capabilities.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.