• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.79-98
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• 2009

Web traffic is becoming an important indicator to make inferences about internet companies' future prospects so that traditional firm valuation methods need to be modified to integrate the ideas of web traffic information as a major asset of internet companies. It is because web traffic is a measure of attracting visitors to firm's web site and is the basis for internet companies' marketing expenditure and customer acquisition and retention. Also the web traffic represents the internet companies' technological advances and marketability. The major purpose of this study is to show the relevance of web traffic for valuation of internet companies. For this, we test hypothesis with the firm's web traffic and financial data using the analysis model of Hand(2000a) derived from the log-linear model introduced by Ye and Finn(1999). Test results show that the web traffic, more specifically the number of unique visitors, visits, and page views are all positively related to the firm's value. This implies that the web traffic information should be considered as one of the important non-financial indicator for the internet firm valuation.

• International Commerce and Information Review
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• v.16 no.3
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• pp.357-380
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• 2014

Buyers' Trust in suppliers is critical in all commerce, but particularly in the relationship between foreign provider and local consumer due to the liability of foreignness. This study examines (1)how local consumers trust in the product of MNCs is affected by their perceptions of the product attributes, (2)does the product trust affects customers loyalty, and (3)whether Global Corporate Citizenship moderates the relationship between the product attributes and trust. Based on previous researches, hypotheses are formulated and the statistical method used to test them was a moderated regression analysis using SPSS 20. 330 respondents from the university student group in Korea were used for this analysis. The results of this study are follows: Service communication and product perceptions such as quality, technological newness, design, and brand value have a significant effect on the product trust. The Effectiveness of product-related service communication had greater than that of the physical characteristics of product. But, price fairness is not significantly. The trust then has a positive relation to customers loyalty. When global corporate citizenship as the moderating role is introduced into the model, the interaction terms with 'price fairness' are verified to be significant. Therefore, global corporate citizenship moderates the relationship between price fairness and product trust. The results of the empirical study provide important implications for Korean firms operating in foreign markets. But, the findings are limited to the University students and to manufacturing sectors. Thus, the generalization of the results of this research remains limited.

• Journal of Distribution Science
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• v.11 no.4
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• pp.61-72
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• 2013

Purpose - It is widely accepted that the process of developing marketing strategy is composed of three steps: market segmentation, target market selection and positioning. However, mass marketing strategy based on cost reduction through economies of scale and standardized products, can be also an effective strategic option. Many marketing scholars including Theodore Levitt emphasize the importance of applying the mass production concept to various industries including service industries. Especially, in times of economic downturn, the capability of providing consumers with low-priced, value products can be an important source of competitive advantage, as well as the ability of providing high-priced premium products. Marketers should decide whether they will implement mass marketing strategy or target marketing strategy. The present study theoretically shows that firms should understand the target customers' price elasticity as well as the firm's cost structure in order to make such a strategic decision. Research design, data, and methodology - Instead of implementing an empirical study, this study provides a theoretical(mathematical) investigation on the effect of consumers' price elasticity on a firm's optimal price level, profit, sales volume, revenue, and cost. The results are mostly deduced from derivative calculations and several graphs are utilized to represent the results on the relationships between the variables under study. Results - The analytical results suggest that it is more profitable for a firm to adopt the segment/target marketing strategy (more specifically the differentiation strategy) when the degree of consumers' heterogeneity is high and the proportion of the fixed cost in the total cost is low. On the other hand, if the degree of consumers' heterogeneity is low and the fixed cost is high, it is better to adopt the mass marketing strategy or the cost leadership strategy. The strategy of concentrating on a single target market will be effective when consumers' needs are highly heterogeneous but the fixed cost is high. Any of the three types of generic strategies proposed my Porter(1980, 1985) can be applied when both the consumers' heterogeneity and the fixed cost are low. This study also proposes the contribution-margin-based method for developing the optimal pricing strategy. Conclusions - One of the primary roles of marketers is to find a proper compromise between the two conflicting goals of maximizing customer satisfaction and minimizing cost. In order to do so, he or she should understand the characteristics of the target customers as well as the cost structure of the firm. In addition to the theoretical analyses, this study discusses several business cases and explains how superior companies find the optimal compromise position between these two goals and dominate the market. One of the radical changes recently taking place in business arena is the reduction of production and distribution costs of both physical goods and information due to the advancement and the wide diffusion of information technology. The cost reduction combined with lowered priced elasticity incurred by customized products and services, will enable many firms to adopt the mass customization strategy.

• Korean Journal of Environment and Ecology
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• v.34 no.2
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• pp.179-187
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• 2020

The study was conducted on Godeoksan, Gangdong-gu, Seoul, for the study of elderly people's park use and satisfaction. For the analysis, frequency analysis was performed on all items, and reliability analysis was performed to check the validity of the items. Factor analysis was used to identify items that have a significant effect on the customer's satisfaction. Multiple regression analysis was performed using the derived factors. As a result of factor analysis, it was found that the factors affecting satisfaction were composed of three factors and 69.50% of the total variance was explained. The KMO value, which means the sample fit between items, was analyzed as .756. Factors were classified into usage aspect, ecological aspect, and amenityt aspect by reflecting the characteristics of the item. As a result of the multiple regression analysis through the derived factors, the multiple regression equation for the elderly's park use satisfaction was analyzed to be Y = 3.678 + 0.202X₁ + 0.125X₂ + 0.236X₃. In this study, there are limitations in conducting a questionnaire survey for the elderly who lack professional knowledge. In the future, evaluation studies should be conducted for the elderly with specialized knowledge, and it is judged that a comparative study of ecological, utilization, and climatic aspects by age is necessary.

• International Journal of Quality Innovation
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• v.8 no.1
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• pp.40-75
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• 2007

In the early industrial age which with high intensity of machine and labor, using financial measurement index was good enough to tie in company's mechanization and philosophy of management and been in efficiency. But being comply with "New Economic age," a new economic environment is full of knowledge and information, the enterprise competition had changed from tangible assets, plants to intangible innovation ability of knowledge. As recognizing the new tendency by enterprise, they value gradually the growth and influence from learning. Practice of organization learning not only needs firm structure and be in coordination with both hardware and software, but also needs an affect measurement model to offer enterprise to estimate learning performance. It's a good instrument of financial performance measure mold in the past years, But it's for measuring the past, couldn't formulate enterprise trend to future, hard to estimate investment for future, such as development of products, organization learning, knowledge management etc, as which intangible assets and knowledge ability just the key factors of being win around competition environment in the future. In 1992, Kaplan and Norton brought up Balance Scorecard (BSC) on Harvard Business Review, as an instrument helping enterprise to measure performance, which is being considered to be a most influence management instrument. It added non-financial index such as customer, internal process and learning growth besides traditional financial index, as offering enterprise an index to measure and manage intangible assets and intellectual property. As being aware of organization learning is hard to be ignored in the new economic age, this research is based on learning and growth of BSC, and citing one national material company try to let the most difficult measurement performance of organization learning, to be estimate through BSC, analyze of factor and individual case, to discuss the company how to make the related strategy and vision of organization learning to develop learning and growth of the structure of BSC, subject the matter of out put factors to be discussed, and measure the outcomes as a result of research. The research affect offers (1) the base implement procedure of carrying out BSC; (2) the reference of formulating measurement index while enterprise using BSC to estimate performance of organization learning; (3) the possibility bottleneck maybe forcing while carrying out BSC, to be an improvement or preventive for enterprise.

• Asia Marketing Journal
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• v.11 no.1
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• pp.1-27
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• 2009

The research compared the motivational network of traits predictive of complaint attitudes across consumers in the U.S. and South Korean cultures. Overall, the results revealed a similar pattern of traits predictive of complaint attitudes in the two cultures. The traits of value consciousness, general self-efficacy, emotional instability, and the need for material resources were positively related to attitudes toward complaining. In contrast, conscientiousness was negatively related to complaint attitudes. The only trait predictor of complaining attitude that was significantly different between the Korean and U.S. samples was shopping enjoyment. It was negatively related to complaining attitude in the U.S. sample but unrelated to complaining attitude in the Korean sample. Understanding the personality traits predictive of complaint attitudes has the potential to help marketers develop messages that will encourage the low complaint prone to voice their dissatisfaction. This is important, because when a consumer complains about and unsatisfactory purchase, it gives the firm a chance to take actions to avoid losing a customer.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• CRM연구
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• v.4 no.1
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• pp.1-18
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• 2011

The consumer's expectation of companies' social responsibilities has been continuously getting higher as the consumerism has been matured. So, the company has faced the shift to move forward to the positive social activity such as charity, donation, and sponsorship. In addition, the company which does make a success needs to reach goals not only to maximize profits but also to make justices of social and cultural boundaries. Thus, success of an enterprise aims at the maximization of profits as the economic objective and the creation of competitive, powerful brands. Accordingly, as enterprises consider social responsibility as the concept of effective investment to enhance the asset value of corporation, they seek to extend their brands in order to pursue cause-related marketing, which accomplishes and complements two objectives each other the performance of social responsibility and the pursuit of powerful brand assets. In Korea, there are traditional ritual ceremonies such as ceremonies of coming-of-age, marriage, funeral, and ancestor worship and they consider those ceremony occasions as very important. Moreover, social positional grade of rank like the two upper classes of old Korea made people pretend to be noble and sensitive to other people around themselves. This old custom could influence Korean people's way of life, especially, consumer-action. This deep rooted custom also could influence consumption life considerably. Through this study, we can understand the consumer behaviors of Korean who consider ritual ceremonies and saving face as essential and are influenced by this culture. on another hand, we intend to check the effects on buying luxury brands.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.597-602
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• 2005

In this study, file size for measurement and the service system's billing data were submitted to a comparative analysis by performing a verification test on the billing system of three major mobile communication services providers, based on the wireless Internet service packet. As shown in the result of the verification test, there were some differences in the billing data due to transmission overhead, according to the network quality that is affected by the wireless environment of mobile operators. Consequently, the packet analysis system was proposed as a means of applying consistent packet billing to all service providers being compared. If the packet analysis system is added to supplement the current billing system various user requirements can be met. Billing by Packet among mobile operators and differentiated billing based on the content value are available, since the packet data can be extracted through protocol analysis by service, and it can be classified by content tape through traffic data analysis. Furthermore, customer's needs can be satisfied who request more information on the detailed usage, and more flexible and diverse billing policies can be supported like application of charging conditions to the non-charging packet handling. All these services are expected to contribute to the popularization of the wireless Internet service, since user complaints about the service charge could be reduced.