• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.467-474
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• 2023

After the revision of the Software Promotion Act, small and medium-sized enterprises (SMEs) with little experience in e-government projects began to participate in public projects. Accordingly, the government introduced the public Project Management Office (PMO) in July 2013 to reduce the risks and secure the quality of informatization business, and the public PMO is still spreading. However, the public PMO service currently experiences sluggish business, such as low-priced orders, due to cut-throat competition, and thus needs improvement plans. In this research, we establish a research model for quality factors of public PMO services that can be considered for the improvement plans, measure and evaluate quality factors based on the model, and then analyze the impact of service quality on customer satisfaction and customer loyalty. For that, we measure quality factors using the SERVPERF model for those who have used public PMO services, establish a structural equation research model, and empirically analyze and evaluate the impact of quality factors. Lastly, we suggest improvement plans and implications for public PMO services.

• The Journal of Society for e-Business Studies
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• v.11 no.2
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• pp.49-69
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• 2006

The virtual community has been recognized as an effective marketing tool and has been an important motive of using internet to Internet users, but very few attempts have been done for the development of virtual community success. Although many studies have been made on influencing factors of virtual community success, the comprehensive studies have never been done so far. Therefore, this study focused on developing the comprehensive model and verifying empirically. This study proposed five influencing factors(Virtual Community Operational factor, Characteristics of Users, Usefulness, Trust, Commitment) that affect virtual community success and three success factors(Sense of Virtual Community, Loyalty, Purchasing Intention) by carrying out literature review extensively and suggesting the relationship among factors. The relationship among factors were empirically validated by structural equation modeling. The data used in this study were collected from 292 users of the existing virtual communities. As the result of statistical analysis. It was found that Virtual Community Operational Factor and Characteristics of Users statistically significantly influenced Virtual Community Success. Also, it was shown that the intervening effects of Usefulness, Trust and Commitment were statistically significant, but that the relationship between commitment and Loyalty was not statistically significant. Finally, it turned out that the causality among success variables of Virtual Community was supported, but that sense of Virtual Community was required to be measured by new measurements.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.527-532
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• 2007

Differentiation strategies have been suggested as the critical sources of competitive advantage in B2C industry where customers can switch internet shopping mall with one click with virtually no transaction cost. Indeed, competition on low pricing cannot be a viable strategy in B2C industry. Moreover, cultivating customer loyalty to attain profitability is still a challenging task for most internet shopping mall. In this study, we provide empirical analysis results on key managerial variables that indicate the difference between the product categories in terms of customer perception on relative value importance. We first identified comprehensive managerial variables and organized them in terms of customer decision stage. Next, with reference to extant literatures on product characteristics based e-commerce strategy, hypotheses are developed to formalize the customer value differences on the key managerial variables. Empirical testing results indicated that there are significant differences on customer perceived value of the key managerial variables between the product groups. The findings provide useful insight for further study on e-commerce differentiation strategy.

• Journal of the Ergonomics Society of Korea
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• v.23 no.3
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• pp.1-12
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• 2004

In recent years, with the advent of e-Commerce the need for personalized services and one-to-one marketing has been emphasized. To be successful in increasingly competitive Internet marketplace, it is essential to capture customer loyalty. In this paper, we provide an intelligent agent approach to incorporate human sensibility into an one-to-one recommendation service in cyber shopping mall. Our system exploits human sensibility ergonomics and on-line preference matching technologies to tailor to the customer the suggestion of goods and the description of store catalog. Customizing the system`s behavior requires the parallel execution of several tasks during the interaction （e. g., identifying the customer`s emotional preference and dynamically generating the pages of the store catalog）. The recommendation agent system composed of five modules including specialized agents carries on these tasks. By presenting goods that are consistent with user interests as well as user sensibility, the accuracy and satisfaction of the recommendation service may be improved.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.203-210
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• 2004

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems - content-based recommending and collaborative filtering. Collaborative filtering recommender systems have been very successful in both information filtering domains and e-commerce domains, and many researchers have presented variations of collaborative filtering to increase its performance. However, the current research on recommendation has paid little attention to the use of time related data in the recommendation process. Up to now there has not been any study on collaborative filtering to reflect changes in user interest. This paper proposes dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations. The proposed methodology detects changes in customer behavior using the customer data at different periods of time and improves the performance of recommendations using information on changes. The results of the evaluation experiment show the proposed model's improvement in making recommendations.

• Knowledge Management Research
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• v.6 no.1
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• pp.105-122
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• 2005

The LG Electronics case shows the process whereby an organization evolves as a learning organization through the integration of e-learning and knowledge management. In other words, it shows the process whereby e-learning is recognized as an important means of solving a problem concerning actual worksite operations, as it became one of the daily activities in the organization. In terms of organizational learning, this process points to the fact that e-learning is emerging as the fastest and most effective means of transferring the internally shared value of a company. Recently, advanced corporations and organizations have been endeavoring to boost their internal and external customer satisfaction and customer loyalty, paving the way for changes in their organizational cultures, and establishing learning organizations through e-learning. Therefore, from an advanced viewpoint, e-learning within a company is not a simple system of transferring educational contents, but is a knowledge portal concept connected with knowledge management. To achieve this end, the organization is required to undergo changes that is, it should make the acquisition of learning possible through e-learning and a knowledge management system (KMS) in order to improve corporate performance. Since LG Electronics is utilizing e-learning as a strategic means to change the paradigm of corporate education, and, in particular, is attempting to integrate this with knowledge management, insights that will facilitate the understanding of the core success factors in and challenges to the integration of knowledge management and e-learning can be obtained through this case.

• Journal of Global Scholars of Marketing Science
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• v.14
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• pp.125-144
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• 2004

The purpose of this study is to classify customer bye-mailing responsiveness on time-series analysis and RFM module and testify the effectiveness of grouping by ROI analysis. RFM (Recency, Frequency, Monetary Value) analysis are used for customer classification that is fundamental process of e-CRM application. ROI analysis were consisted of open, click-through, duration time, conversion rate, personalization and e-mail loyalty index. Major findings are as follows; Customer segmentation were loyal customer, odds customer, dormant customer, secession customer and observation customer by Activity email module. And Loyal, dormant and secession customer are segregated by RFM module. Loyal customer group have higher point of all ROI index than other groups. These results indicated that customer responsiveness of e-mailing and RFM analysis were appropriate methods to grouping the customer. Mid-small Internet Biz adapted marketing strategy by optimization of consumer information.

• Fashion, Industry and Education
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• v.15 no.1
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• pp.1-11
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• 2017

The proliferation of social media has given rise to the new consumer group, namely, social consumers. This study identified the distinct characteristics of social consumers (i.e., online social search, online social navigation, online social connection) and examined the impacts of social consumer attributes on the engagement with fashion brands via brands' SNSs (BSNSs). A sample of 141 U.S. consumers who had browsed and/or participated in a fashion brand's BSNS (i.e., the Facebook page for fashion brands) was used to examine hypothesized relationships. The analyses involved running a confirmatory factor analysis and a structural equation modeling. The result indicates that the impacts of the social consumer attributes on the benefits of BSNSs (i.e., experiential and functional benefits) as perceived by consumers were significant, except the link between online social connection and functional benefits. In addition, consumers' existing relationship with a brand served as a moderating variable, strengthening the impacts of social consumer attributes on BSNS benefits. The perceived benefits of BSNSs positively affected perceived relationship investment which in turn influenced brand loyalty. Practical marketing suggestions are provided for fashion brands.

• IE interfaces
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• v.18 no.2
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• pp.205-220
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• 2005

This study presents a web log analysis model for e-CRM, which combines the on-line customer's purchasing pattern data and transaction data between companies in B2B environment of make-to-order company. With this study, the customer evaluation and the customer subdivision are available. We can forecast the estimate demands with periodical products sales records. Also, the purchasing rate per each product, the purchasing intention rate, and the purchasing rate per companies can be used as the basic data for the strategy for receiving the orders in future. These measures are used to evaluate the business strategy, the quality ability on products, the customer's demands, the benefits of customer and the customer's loyalty. And it is used to evaluate the customer's purchasing patterns, the response analysis, the customer's secession rate, the earning rate, and the customer's needs. With this, we can satisfy various customers' demands, therefore, we can multiply the company's benefits. And we presents case of the 'H' company, which has the make-to-order manufacture environment, in order to verify the effect of the proposal system.

• Knowledge Management Research
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• v.21 no.3
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• pp.249-269
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• 2020

Recently, as the online market has matured, it is facing many problems to prevent the growth. The most common problem is the homogenization of online products, which fails to increase the number of customers any more. Moreover, although the portion of the online market has increased significantly, it now becomes essential to expand offline for further development. In response, many online firms have recently sought to expand their businesses and marketing channels by securing offline spaces that can complement the limitations of online platforms, on top of their existing advantages of online channels. Based on their competitive advantage in terms of analyzing large volumes of customer data utilizing information technologies (e.g., big data and artificial intelligence), they are reinforcing their offline influence as well through this online for offline (O4O) business model. On the other hand, most of the existing research has primarily focused on online to offline (O2O) business model, and there is still a lack of research on O4O business models, which have been actively attempted in various industrial fields in recent years. Since a few of O4O-related studies have been conducted only in an experience marketing setting following a case study method, it is critical to conduct an empirical study on O4O selection attributes and their impact on customer satisfaction and loyalty. Therefore, focusing on China's representative O4O business model, 'Fresh Hema,' this study attempts to identify some key selection attributes specialized for O4O services from the customers' viewpoint and examine the impact of these attributes on customer satisfaction and loyalty. The results of the structural equation modeling (SEM) with 300 O4O (Fresh Hema) experienced customers, reveal that, out of seven O4O selection attributes, four (mobile app quality, mobile payment, product quality, and store facilities) have an impact on customer satisfaction, which also leads to customer loyalty (reuse intention, recommendation intention, and brand attachment). This study would help managers in an O4O area well adapt to rapidly changing customer needs and provide them with some guidelines for enhancing both customer satisfaction and loyalty by allocating more resources to more significant selection attributes, rather than less significant ones.