• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.589-597
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• 2003

This paper discusses revenue model of digital TV broadcast service(D-TV) and presents the basic framework for integrated strategy of applications. Also this paper presents the cases of D-TV in the frame of integrated model. The broadcasting operators should focus on interactive advertising and revenue generation utilizing customer participation. Also, they should utilize the strengths as a platform operator. The contents provider should be concerned about the retail revenue rather than commission revenue. The middle ware provider should develop new interactive D-TV service rather than system use fee or consulting fee.

• Asia pacific journal of information systems
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• v.25 no.2
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• pp.337-355
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• 2015

The Internet has become one of the most important channels for people to communicate and for companies to implement their sales promotion activities, such as advertising. Marketing and advertising attempt to influence customers' attitude to persuade them to choose to buy the advertisers' products instead of the competitors'. With the different forms of online marketing, such as search engine marketing, email marketing, and mobile marketing, advertisers can find more effective strategies to attract the attention of more targeted audiences. With the emergence of the social web (web 2.0), a new platform was introduced called social networks. This paper presents the current work in internet marketing activities until web 2.0, and conducts a social network analysis to aid in data extraction. Marketing and advertising companies have understood the power of information for a very long time. The more knowledge these companies have on the demographics, consumer habits, and preferences of particular customer types, the more they can tailor their product offerings, and the more sales they can make. This paper aims to understand the internet marketing concepts as well as present challenges and work directions in internet marketing.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.136-160
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• 2002

Most important to financial is to provide well designed and built services to the customers by accessing their core bank systems and affiliated systems in their partners. This will be essential to introduce new products and services and still be able to count on legacy and collaborative affiliated systems. Winning the war on such service competitions among financial institutions is attainable by seizing the 'e-bank' opportunities in B2Bi and CRM ( Customer Relationship Management ). Such application integrations among systems and 'e-bank' services need to be available in the new IT environment.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• Journal of Distribution Science
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• v.17 no.3
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• pp.41-47
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• 2019

Purpose - Based on the analysis of Kazakhstan's experience of digital transformation, this study suggests a concept for digital solution to optimize organizational process, create trust networking between the center of state scholarships programs and recipients. In addition, the authors contribute to the current discussions of an effective digital transformation of state services. Research design, data, and methodology - Policy analysis is based on the combination of both primary and secondary materials collected during a Policy Research Project conducted in Kazakhstan in 2017. It involved semi-structured interviews with the state scholarship' recipients, ICT experts and findings from academic articles. Results - Findings are represented via Policy Development Matrix - a table with three options (status quo, partial change, total change) to deal with policy challenges. Authors suggest a concept for digital solution following the Customer Relationship Management (CRM) principles for optimizing core business processes, communication and networking strategies of the state scholarships program. Conclusions - At the time when digitalization becomes trending for states, the transformation of the state education policy is inevitable. The rapid development of digital technologies creates new opportunities for a single integration platform with key principles of Smart Remote Management in the state scholarships programs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.809-820
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• 2016

The smart grid, a new open platform, is a core application for facilitating a creative economy in the era of the Internet of Things (IoT). Advanced Metering Infrastructure (AMI) is one of the components of the smart grid and a two-way communications infrastructure between the main utility operator and customer. The smart meter records consumption of electrical energy and communicates that information back to the utility for monitoring and billing. This paper investigates the impact of a cybersecurity attack on the smart meter. We analyze the cost to the smart grid in the case of a smart meter attack by authorized users based on a high risk scenario from NESCOR. Our findings could be used by policy makers and utility operators to create investment decision-making models for smart grid security.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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• pp.181-189
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• 2017

The systematic management of technology infrastructure increasingly becomes critical as it represents the driving power for creating competitive advantage of nations and enterprises. In this sense, public facility and equipment, which is one major asset of technology infrastructure, should be managed effectively, systematically and efficiently to increase its overall equipment effectiveness. However, the manual and off-line communication was the unique way to communicate between the suppliers who provide facilities in the public sector and the customers who utilize the facilities in the industrial sector. This communication way caused invisibility of available usage time and increase of idle time, thereby decreasing the equipment effectiveness. This paper presents an web-based scheduling system that enables real-time collaboration and information sharing for increasing the equipment effectiveness. The designed system performs scheduling, facility management, order management and customer relationship management in an on-line platform, and carries out the processing and storing of relevant information in an integrated database. The paper includes a development approach to identify business process models and standardized system models by using object-modeling technique. The deliverable of the present work will contribute to increasing the equipment effectiveness by enhancing visibility, transparency and predictability by means of the integration with a legacy Enterprise Resource Planning.

• The Journal of Industrial Distribution & Business
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• v.10 no.4
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• pp.25-31
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• 2019

Purpose - A framework is suggested in this paper which will help crowdfunding platforms to match projects according to expectations of funders, leading to successful campaigns and thus increase the profitability of the crowdfunding platform. Research design, data, and methodology - The paper is theoretical and conceptual in nature which proposes a model for crowdfunding platforms to match expectations of crowds with project fundraisers. Results - Crowdfunding platforms are going through incremental innovations in order to match customer (funders and fundraisers) expectations. Leading crowdfunding platforms like Kickstart holds benchmark for other players in the market but the secret of success lies in matching quality projects with the appropriate funders. Crowdfunding platforms have to securitize the projects and allow only quality projects but also provide a wide range of options for funders. Thus, to manage this trade-off between quality and quantity of options, a framework is proposed. Conclusions - Crowdfunding platforms have to adopt a model which will help them in providing a perfect match between crowds and fundraisers. Each member of the crowd and every project will be assigned a category and rating based on the past records. Securitization of projects will help to entertain only demanded projects which will reduce the number of failing campaigns.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.33-39
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• 2020

The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.

• The Journal of Economics, Marketing and Management
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• v.11 no.1
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• pp.21-30
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• 2023

Purpose: As one of the ongoing studies on the distribution industry, the purpose of this study is to identify the research trends on online shopping so far to propose not only the development of online shopping companies but also the possibility of coexistence between online and offline retailers and the development of the distribution industry. Research design, data and methodology: In this study, the English abstracts of 645 papers on online shopping registered in scienceON were obtained. For the analysis through BERTopic and LDA using Python 3.7 and identifying which topics were interesting to researchers. Results: As a result of word frequency analysis and co-occurrence analysis, it was found that studies related to online shopping were frequently conducted on factors such as products, services, and shopping malls. As a result of BERTopic, five topics such as 'service quality' and 'sales strategy' were derived, and as a result of LDA, three topics including 'purchase experience' were derived. It was confirmed that 'Customer Recommendation' and 'Fashion Mall' showed relatively high interest, and 'Sales Strategy' showed relatively low interest. Conclusions: It was suggested that more diverse studies related to the online shopping mall platform, sales content, and usage influencing factors are needed to develop the online shopping industry.