• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.95-109
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• 2013

The practices and processes of HRM (Human Resource Management) for university faculty in Korea depend heavily on assessment of research and teaching rather than the UIC (University-Industry Cooperation) performance. In this regard, HRM of Korean universities is said to be far distant from UIC. Although policy initiatives by the Korean government, notably the MoE (Ministry of Education) have implemented in most universities, the desirable level of UIC could not be achieved yet. Moreover, the very notion of 'university' in Korea is much more to do with 'pure' education and research institution than with 'applied' and 'vocational' purpose. Considering upon HRM practices and organizational culture, for enhancing UIC in Korea, the government's policy should be linked to alter deep-rooted university culture. So the aims of the research are to describe the current state of HRM in Korean and foreign universities; to find out the critical factors of UIC in Korean universities; to analyze the gaps between university research and industrial commercialization based on a conceptual framework, the 'valley of the death'; and to recommend HRM policies fostering UIC for the MoE. For achieving these objectives, we deploy multiple methodologies, namely, in-depth interview, literature survey, and statistical data analysis with regard to UIC. Analyzing the data we have collected, the present research sheds light on all aspects of HRM processes and UICs. And the main policy implication is restricted to the Korean universities, even if we have collected and analyzed foreign universities, notably universities in the USA. The research findings are mainly two folds. Firstly, the HRM practices among Korean universities are very similar due to the legally institutionalized framework and the government's regulations. Secondly, the difficulties of UIC can be explained by notion of the 'valley of death' ways in which both parties of university and industry are looking for different purposes and directions. In order to overcome the gap in the valley of death, the HRM policy is better to be considered as leverage. Finally, the policy recommendations are as follows. Firstly, various kinds of UIC programs are able to enhance the performances of not only UIC, but also education and research outcome. Secondly, fostering organizational climate and culture for UIC, employing various UIC programs, and hiring industry-experienced faculty are all very important for enhancing the high performance of university. We recommend the HRM policies fostering UIC by means of indirect way rather than funding directly for university. The HRM policy of indirect support is more likely to have long-term effectiveness while the government's direct intervention to UIC will have likely short-term effectiveness as the previous policy initiatives have shown. The MEST's policy means of indirect support might vary from financial incentives to the universities practicing HRM for UIC voluntarily, to information disclosure for UIC. The benefits of the present research can be found in suggesting HRM policy for UIC, highlighting the significance of industry-experienced faculty for UIC, and providing statistical analysis and evidences of UIC in Korean universities.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of The Korean Association For Science Education
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• v.35 no.4
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• pp.629-648
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• 2015

This study is a case study examining how research-based 'authentic' science education program contextually facilitates students' learning on NOS as a process. We developed 'Becoming a Scientist' mentor-mentee program and applied it to six Korean 7th graders for 8 months. A mentor, who is also a researcher, provided scaffolding and coaching, and her mentees were to perform the whole process of science research, including selecting the research subject and questions, planning research design, doing experiments, collecting and analysing data, writing research paper, and experiencing poster presentation at an academic conference. The research questions are 1) What would the students experience at every step of their research process?, and 2) Which perceptions would they construct NOS as a process? Data include classroom observations, interview, mentor's journal, and students' learning products. The results show that the mentees have experienced their views of NOS as a process in various ways such as role of research question and purpose, validity of measured value, researcher's subjectivity in interpreting data, experience of making public and peer review, and significance of academic conference. This study has shown that students' actual experience in scientific research enhanced their views about NOS as process without explicit and reflective approaches. We defined 'authenticity' associated with not only with its similarity to what scientists do but to learner's identity as scientific researcher. Based on the situated learning theory, this study sheds light on the necessity of reconsideration about the meaning of authenticity and embodying authentic context in science education for better NOS learning.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.57-81
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• 2008

Knowledge is an essential strategic weapon for sustaining competitive advantage and is the key determinant for organizational growth. When knowledge is shared and disseminated throughout the organization, it increases an organization's value by providing the ability to respond to new and unusual situations. The growing importance of knowledge as a critical resource has forced executives to pay attention to their organizational knowledge. Organizations are increasingly undertaking knowledge management initiatives and making significant investments. Knowledge sourcing is considered as the first important step in effective knowledge management. Most firms continue to make an effort to realize the benefits of knowledge management by using various knowledge sources effectively. Appropriate knowledge sourcing strategies enable organizations to create, acquire, and access knowledge in a timely manner by reducing search and transfer costs, which result in better firm performance. In response, the knowledge management literature has devoted substantial attention to the analysis of knowledge sourcing strategies. Many studies have categorized knowledge sourcing strategies into intemal- and external-oriented. Internal-oriented sourcing strategy attempts to increase firm performance by integrating knowledge within the boundary of the firm. On the contrary, external-oriented strategy attempts to bring knowledge in from outside sources via either acquisition or imitation, and then to transfer that knowledge across to the organization. However, the extant literature on knowledge sourcing strategies focuses primarily on large organizations. Although many studies have clearly highlighted major differences between large and small firms and the need to adopt different strategies for different firm sizes, scant attention has been given to analyzing how knowledge sourcing strategies affect firm performance in small firms and what are the differences between small and large firms in the patterns of knowledge sourcing strategies adoption. This study attempts to advance the current literature by examining the impact of knowledge sourcing strategies on small firm performance from a holistic perspective. By drawing on knowledge based theory from organization science and complementarity theory from the economics literature, this paper is motivated by the following questions: (1) what are the adoption patterns of different knowledge sourcing strategies in small firms (i,e., what sourcing strategies should be adopted and which sourcing strategies work well together in small firms)?; and (2) what are the performance implications of these adoption patterns? In order to answer the questions, this study developed three hypotheses. First hypothesis based on knowledge based theory is that internal-oriented knowledge sourcing is positively associated with small firm performance. Second hypothesis developed on the basis of knowledge based theory is that external-oriented knowledge sourcing is positively associated with small firm performance. The third one based on complementarity theory is that pursuing both internal- and external-oriented knowledge sourcing simultaneously is negatively or less positively associated with small firm performance. As a sampling frame, 700 firms were identified from the Annual Corporation Report in Korea. Survey questionnaires were mailed to owners or executives who were most erudite about the firm s knowledge sourcing strategies and performance. A total of 188 companies replied, yielding a response rate of 26.8%. Due to incomplete data, 12 responses were eliminated, leaving 176 responses for the final analysis. Since all independent variables were measured using continuous variables, supermodularity function was used to test the hypotheses based on the cross partial derivative of payoff function. The results indicated no significant impact of internal-oriented sourcing strategies while positive impact of external-oriented sourcing strategy on small firm performance. This intriguing result could be explained on the basis of various resource and capital constraints of small firms. Small firms typically have restricted financial and human resources. They do not have enough assets to always develop knowledge internally. Another possible explanation is competency traps or core rigidities. Building up a knowledge base based on internal knowledge creates core competences, but at the same time, excessive internal focused knowledge exploration leads to behaviors blind to other knowledge. Interestingly, this study found that Internal- and external-oriented knowledge sourcing strategies had a substitutive relationship, which was inconsistent with previous studies that suggested complementary relationship between them. This result might be explained using organizational identification theory. Internal organizational members may perceive external knowledge as a threat, and tend to ignore knowledge from external sources because they prefer to maintain their own knowledge, legitimacy, and homogeneous attitudes. Therefore, integrating knowledge from internal and external sources might not be effective, resulting in failure of improvements of firm performance. Another possible explanation is small firms resource and capital constraints and lack of management expertise and absorptive capacity. Although the integration of different knowledge sources is critical, high levels of knowledge sourcing in many areas are quite expensive and so are often unrealistic for small enterprises. This study provides several implications for research as well as practice. First this study extends the existing knowledge by examining the substitutability (and complementarity) of knowledge sourcing strategies. Most prior studies have tended to investigate the independent effects of these strategies on performance without considering their combined impacts. Furthermore, this study tests complementarity based on the productivity approach that has been considered as a definitive test method for complementarity. Second, this study sheds new light on knowledge management research by identifying the relationship between knowledge sourcing strategies and small firm performance. Most current literature has insisted complementary relationship between knowledge sourcing strategies on the basis of data from large firms. Contrary to the conventional wisdom, this study identifies substitutive relationship between knowledge sourcing strategies using data from small firms. Third, implications for practice highlight that managers of small firms should focus on knowledge sourcing from external-oriented strategies. Moreover, adoption of both sourcing strategies simultaneousiy impedes small firm performance.

• Korean Security Journal
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• no.15
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• pp.29-50
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• 2008

Many countries throughout the world have enacted laws on terrorism in the light of the changes that time has brought to them, geographical features, cultural values, and environmental elements. Especially some advanced European nations prescribe the definition of terrorism, the purpose of terrorism, the behavior of terrorism, and the types of crimes related to terrorism and so on for the following reason that it is more vital for the authorities concerned to investigate and punish terrorists after the rise of terrorism. In this regard, this paper analyzes legislative countermoves against terrorists of advanced countries such as France, Germany, and England and through this sheds light on the need of future anti-terrorism bills. The legislative basic guidelines directly to manipulate future terrors based on theories derived from this study could be summarized as follows. In the first place, providing laws on direct investigative power and harsher punishment to those involved in terrorism is a prerequisite for social security and thus the presidential directive of the state anti-terrorism action guidelines just deals with administrative measures without any effective response to terrorism. Hence it is urgent to make anti-terrorism bill concerning investigation and punishment of terrorists. In the second place, it is associated with the objectives of terror. The expression "all sorts of" stated in Korean law is so quite unclear that it can not fulfill the required conditions for naming it "crime". Comprehending provisoes of the crime that meets the purpose of the terrorists is necessary in order to investigate and inflict punishment on them. Therefore, it is advisable to establish specific and precise principles such as political, social, ideological, and religious purpose of terrorists in the bill. In the third place, to meet the flow of times of technicalization, informatization, such provisoes as destruction of electronic data system, crimes related to nuclear materials, purchases of weapons by terrorists, tax administration for prohibition of sale, and arson should be considered in terror bill. In the fourth place, nonselective attack toward unspecified individuals has become a serious issue in our society. Terrorists leave poisonous foods or beverages to crowded place or dump toxic chemicals into river intentionally. Therefore more strict regulations must be included in terror bill to prevent possible terrorist attacks.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.73-91
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• 2013

Advertising market has been facing new challenges due to dramatic change in advertising channels and the advent of innovative media such as mobile devices. Recent research related to mobile devices is mainly focused on the fact that mobile devices could identify users'physical location in real-time, and this sheds light on how location-based technology is utilized to achieve competitive advantage in advertising market. With the introduction of smartphone, the functionality of smartphone has become much more diverse and context awareness is one of the areas that require further study. This work analyses the influence of context awareness value resulted from the transformation of advertising channel in mobile communication market, and our research result reflects recent trend in advertising market environment which is not considered in previous studies. Many constructs has intensively been studied in the context of advertising channel in traditional marketing environment, and entertainment, irritation and information are considered to be the most widely accepted variables that has positive relationship with advertising value. Also, in smartphone advertisement, four main dimensions of context awareness value are recognized: identification, activity, timing and location. In this study, we assume that these four constructs has positive relationship with context awareness value. Finally, we propose that advertising value and context awareness value positively influence smartphone advertising attitude. Partial Least Squares (PLS) structural model is used in our theoretical research model to test proposed hypotheses. A well designed survey is conducted for college students in Korea, and reliability, convergent validity and discriminant validity of constructs and measurement indicators are carefully evaluated and the results show that reliability and validity are confirmed according to predefined statistical criteria. Goodness-of-fit of our research model is also supported. In summary, the results collectively suggest good measurement properties for the proposed research model. The research outcomes are as follows. First, information has positive impact on advertising value while entertainment and irritation have no significant impact. Information, entertainment and irritation together account for 38.8% of advertising value. Second, along with the change in advertising market due to the advent of smartphone, activity, timing and location have positive impact on context awareness value while identification has no significant impact. In addition, identification, activity, location and time together account for 46.3% of context awareness value. Third, advertising value and context awareness value both positively influence smartphone advertising attitude, and these two constructs explain 31.7% of the variability of smartphone advertising attitude. The theoretical implication of our research is as follows. First, the influence of entertainment and irritation is reduced which are known to be crucial factors according to previous studies related to advertising value, while the influence of information is increased. It indicates that smartphone users are not likely interested in entertaining effect of smartphone advertisement, and are insensitive to the inconvenience due to smartphone advertisement. Second, in today' ubiquitous computing environment, it is effective to provide differentiated advertising service by utilizing smartphone users'context awareness values such as identification, activity, timing and location in order to achieve competitive business advantage in advertising market. For practical implications, enterprises should provide valuable and useful information that might attract smartphone users by adopting differentiation strategy as smartphone users are sensitive to the information provided via smartphone. Also enterprises not only provide useful information but also recognize and utilize smarphone users' unique characteristics and behaviors by increasing context awareness values. In summary, our result implies that smartphone advertisement should be optimized by considering the needed information of smartphone users in order to maximize advertisement effect.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.2
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• pp.125-133
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• 1984

To obtain the basic date for the improvement of cultural and managemental problems caused by soil characteristics and soil productivity in rice cultivation of Honam area, morphological characteristics of rice soils were investigated in Mangeng-Dongjin and Yeongsan Water-sheds, and compaired differences between two major Watersheds. The results obtained are summarized as follows: 1. According to U.S.D.A. Soil Taxonomy Classification System, eight great groups are distributed in rice soils of two major Watersheds. More than 50% of rice paddy soils are classified as Haplaquepts. 2. Two Watersheds are quite different in soil parent materials. In Mangeong-Dongjin Watershed, most soils (55.1%) are derived from fluvic-marine deposits. Remainders are derived from local alluvium (24.7%) and alluvium (14.2%). But in Yeongsan Watershed, the order is local alluvium>alluvium>fluvio-marine deposits. 3. Rice soils occur mostly in coastal and inland flat-site with the slope of less than 2% (57.8%) in Mangeong-Dongjin Watersheds. However, in Yeongsan Watershed, flat-site and low undulating terrace are mostly distributed (52.9%). 4. About 81.9, 61.4 and 53.3% of rice soils are classified as fine textured in Yeongsan, Dongjin, and Mangeong Watersheds, respectively. 5. More normal paddy soils and less sandy paddy soils are distributed in Yeongsan Watershed. The results indicate that more rice soils are classified as productivity classes of I and II in Yeongsan Watershed than in Mangeong-Dongjin Watersheds.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.101-124
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• 2009

According to Wikipedia, virtual reality (VR) is defined as a technology that allows a user to interact with a computer-simulated environment. Due to a rapid growth in information technology (IT), the cost of virtual reality has been decreasing while the utility of virtual reality advertisements has dramatically increased. Nevertheless, only a few studies have investigated the effects of virtual reality advertisement on consumer behaviors. Therefore, the objective of this study is to empirically examine the effects of virtual reality advertisement. Compared to traditional online advertisements, virtual reality advertisement enables consumers to experience products realistically over the Internet by providing high media richness, interactivity, and telepresence (Suh and Lee, 2005). Advertisements with high media richness facilitate consumers' understanding of advertised products by providing them with a large amount and a high variety of information on the products. Interactivity also provides consumers with a high level of control over the computer-simulated environment in terms of their abilities to adjust the information according to their individual interests and concerns and to be active rather than passive in their engagement with the information (Pimentel and Teixera, 1994). Through high media richness and interactivity, virtual reality advertisements can generate compelling feelings of "telepresence" (Suh and Lee, 2005). Telepresence is a sense of being there in an environment by means of a communication medium (Steuer, 1992). Virtual reality advertisements enable consumers to create a perceptual illusion of being present and highly engaged in a simulated environment, while they are in reality physically present in another place (Biocca, 1997). Based on the characteristics of virtual reality advertisements, a research model has been proposed to explain consumer responses to the virtual reality advertisements. The proposed model includes two dimensions of consumer responses. One dimension is consumers' rational response, which is based on the Information Processing Theory. Based on the Information Processing Theory, product knowledge and perceived risk are selected as antecedents of intention to purchase. The other dimension is emotional response of consumers, which is based on the Attitude-Structure Theory. Based on the Attitude-Structure Theory, arousal, flow, and positive affect are selected as antecedents of intention to purchase. Because it has been criticized to have investigated only one of the two dimensions of consumer response in prior studies, our research model has been built so as to incorporate both dimensions. Based on the Attitude-Structure Theory, we hypothesized the path of consumers' emotional responses to a virtual reality advertisement: (H1) Arousal by the virtual reality advertisement increases flow; (H2) Flow increases positive affect; and (H3) Positive affect increases intension to purchase. In addition, we hypothesized the path of consumers' rational responses to the virtual reality advertisement based on the Information Processing Theory: (H4) Increased product knowledge through the virtual reality advertisement decreases perceived risk; and (H5) Perceived risk decreases intension to purchase. Based on literature of flow, we additionally hypothesized the relationship between flow and product knowledge: (H6) Flow increases product knowledge. To test the hypotheses, we conducted a free simulation experiment [Fromkin and Streufert, 1976] with 300 people. Subjects were asked to use the virtual reality advertisement of a cellular phone on the Internet and then answer questions about the variables. To check whether subjects fully experienced the virtual reality advertisement, they were asked to answer a quiz about the virtual reality advertisement itself. Responses of 26 subjects were dropped because of their incomplete answers. Responses of 274 subjects were used to test the hypotheses. It was found that all of six hypotheses are accepted. In addition, we found that consumers' emotional response has stronger impact on their intention to purchase than their rational response does. This study sheds much light into practical implications for both IS researchers and managers. First of all, while most of previous research has analyzed only one of the customers' rational and emotional responses, we theoretically incorporated and empirically examined both of the two sides. Second, we empirically showed that mediators such as arousal, flow, positive affect, product knowledge, and perceived risk play an important role between virtual reality advertisement and customer's intention to purchase. In addition, the findings of this study can provide a basis of practical strategies for managers. It was found that consumers' emotional response is stronger than their rational response. This result indicates that advertisements using virtual reality should focus on the emotional side, and that virtual reality can be served as an appropriate advertisement tool for fancy products that require their online advertisements to give an impetus to customers' emotion. Finally, even if this study examined the effects of virtual reality advertisement of cellular phone, its findings could be applied to other products that are suited for virtual experience. However, this research has some limitations. We were unable to control different kinds of consumers and different attributes of products on consumers' intention to purchase. It is, therefore, deemed important for future research to control the consumer and product types for more reliable results. In addition to the consumer and product attributes, other variables could affect consumers' intention to purchase. Thus, the future research needs to find ways t control other variables.