• The Korean Journal of Food & Health Convergence
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• v.10 no.1
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• pp.1-6
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• 2024

Purpose: The research aims to address the intricacies of AI and Big Data application within the food industry. This study explores the strategic implementation of AI and Big Data in the food industry. The study seeks to understand how these technologies can be employed to bolster consumer engagement and contribute to market expansion, while considering ethical implications. Research Method: This research employs a comprehensive approach, analyzing current trends, case studies, and existing academic literature. It focuses on the application of AI and Big Data in areas such as supply chain management, consumer behavior analysis, and personalized marketing strategies. Results: The study finds that AI and Big Data significantly enhance market analytics, consumer personalization, and market trend prediction. It highlights the potential of these technologies in creating more efficient supply chains, improving consumer satisfaction through personalization, and providing valuable market insights. Conclusion and Implications: The paper offers actionable insights and recommendations for the effective implementation of AI and Big Data strategies in the food industry. It emphasizes the need for ethical considerations, particularly in data privacy and the transparency of AI algorithms. The study also explores future trends, suggesting that AI and Big Data will continue to revolutionize the industry, emphasizing sustainability, efficiency, and consumer-centric practices.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.87-96
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• 2024

Information power has been a major criterion for wealth disparity in human history, and since the advent of the Fourth Industrial Revolution, referred to as the data economy era, personal information has also gained economic value. Additionally, companies collect and analyze customer information to use as a marketing tool, providing personalized services, making the collection of quality customer information crucial to a company's success. However, as the amount of data held by companies increases, crimes of stealing personal information for financial gain have surged, making corporate customer information a target for criminals. The leakage of personal information and its circumstances lead to a decline in corporate trust from the customer's perspective, threatening corporate sustainability with falling stock prices and decreased sales. Therefore, companies find themselves in a paradoxical situation where the utilization of personal information is increasing while the risk of personal information leakage is also growing. This study used the news big data analysis system, BIG KINDS, to analyze major keywords before and after media coverage on personal information leaks, examining domestic media coverage trends. Through this, we identified the impact of personal information leakage on corporate sustainability and analyzed the connection between personal information protection and sustainable corporate management. The results derived from this study are expected to serve as foundational data for companies seeking ways to enhance sustainable management while increasing the utilization of personal information.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.95-117
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• 2022

With the emergence of various media types due to the development of Internet technology, advertisers have difficulty choosing media suitable for corporate advertising strategies. There are challenging to effectively reflect consumer contextual information when advertising media is selected based on traditional marketing strategies. Thus, a recommender system is needed to analyze consumers' past data and provide advertisers with personalized media based on the information consumers needs. Since the traditional recommender system provides recommendation services based on quantitative preference information, there is difficult to reflect various contextual information. This study proposes a methodology that uses deep learning to recommend personalized media to advertisers using consumer contextual information such as consumers' media viewing time, residence area, age, and gender. This study builds a recommender system using media & consumer research data provided by the Korea Broadcasting Advertising Promotion Corporation. Additionally, we evaluate the recommendation performance compared with several benchmark models. As a result of the experiment, we confirmed that the recommendation model reflecting the consumer's contextual information showed higher accuracy than the benchmark model. We expect to contribute to helping advertisers make effective decisions when selecting customized media based on various contextual information of consumers.

• Journal of Distribution Science
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• v.8 no.3
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• pp.37-47
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• 2010

CRM refers to the operating activities that always maintain and promote good relationship with customers to ultimately maximize the company's profits by understanding the value of customers to meet their demands, establishing a strategy which may maximize the Life Time Value and successfully operating the business by integrating the customer management processes. In our country, many big businesses are introducing CRM initiatively to use it in marketing strategy however, most medium and small sized companies do not understand CRM clearly or they feel difficult to introduce it due to huge investment needed. This study is intended to present CRM promotion strategy and activities plan fit for the medium and small sized companies by analyzing the success factors of the leading companies those have already executed CRM by surveying the precedents to make the distributors out of the industries have close relation with consumers to overcome their weakness in scale and strengthen their competitiveness in such a rapidly changing and fiercely competing market. There are 5 stages to build CRM such as the recognition of the needs of CRM establishment, the establishment of CRM integrated database, the establishment of customer analysis and marketing strategy through data mining, the practical use of customer analysis through data mining and the implementation of response analysis and close loop process. Through the case study of leading companies, CRM is needed in types of businesses where the companies constantly contact their customers. To meet their needs, they assertively analyze their customer information. Through this, they develop their own CRM programs personalized for their customers to provide high quality service products. For customers helping them make profits, the VIP marketing strategy is conducted to keep the customers from breaking their relationships with the companies. Through continuous management, CRM should be executed. In other words, through customer segmentation, the profitability for the customers should be maximized. The maximization of the profitability for the customers is the key to CRM. These are the success factors of the CRM of the distributors in Korea. Firstly, the top management's will power for CS management is needed. Secondly, the culture across the company should be made to respect the customers. Thirdly, specialized customer management and CRM workers should be trained. Fourthly, CRM behaviors should be developed for the whole staff members. Fifthly, CRM should be carried out through systematic cooperation between related departments. To make use of the case study for CRM, the company should understand the customer and establish customer management programs to set the optimal CRM strategy and continuously pursue it according to a long-term plan. For this, according to collected information and customer data, customers should be segmented and the responsive customer system should be designed according to the differentiated strategy according to the class of the customers. In terms of the future CRM, integrated CRM is essential where the customer information gathers together in one place. As the degree of customers' expectation increases a lot, the effective way to meet the customers' expectation should be pursued. As the IT technology improved rapidly, RFID (Radio Frequency Identification) appears. On a real-time basis, information about products and customers is obtained massively in a very short time. A strategy for successful CRM promotion should be improving the organizations in charge of contacting customers, re-planning the customer management processes and establishing the integrated system with the marketing strategy to keep good relation with the customers according to a long-term plan and a proper method suitable to the market conditions and run a company-wide program. In addition, a CRM program should be continuously improved and complemented to meet the company's characteristics. Especially, a strategy for successful CRM for the medium and small sized distributors should be as follows. First, they should change their existing recognition in CRM and keep in-depth care for the customers. Second, they should benchmark the techniques of CRM from the leading companies and find out success points to use. Third, they should seek some methods best suited for their particular conditions by achieving the ideas combining their own strong points with marketing. Fourth, a CRM model should be developed that will promote relationship with individual customers just like the precedents of small sized businesses in Switzerland through small but noticeable events.

• Management & Information Systems Review
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• v.23
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• pp.25-40
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• 2007

In the highly competitive and divers world of financial market, customer is the single most important factor to company's survival. Especially, creating a relationship with valued customers is a key to success. CRM provides the mean to retain high value customers. It takes a prospect of what customers expect. Utilizing those knowledge can help the products and service meet the customers' needs, thereby maximizing customer satisfaction and company's profit. In this report, I am going to suggest a few ways to develop successful CRM in the life insurance industry. First, CRM should innovate the way of communication to keep pace with Web 2.0 era. In other words, the customer's needs should be caught by real-time communication than traditional off-line market research. Thus, the functionality and specification of products can be decided by customer's direct choice so that the customers are able to purchase the understanding and experience of the products. Second, CRM project should consider whether the initial strategy plan can promise the stable growth of customer at the first step. When planning strategy, the project needs to identify what customer wants and how to fulfill the needs with stable growth of the customer. In addition, the CRM should be developed by realizing that customer centric benefits ultimately guarantee the growth of the organization. Third, CRM systems should enhance the organization's ability to take the customer's insight in a 360 degree view and to capture the voice of the customer directly. In order to develop the best matched product package, more precise customer segmentation should be ahead of market segmentation strategy. Forth, the biggest reward from CRM will be a customer royalty program. Many successful banks are already planning and practicing customer royalty strategy. A comprehensive analysis of customers and their behavior allow organization to identify high value potential customers' needs and determine a strategy required to meet those needs. Even life insurance companies such as Prudential Korea are developing products designed for royal customers. Fifth, understanding and managing the experience of customer called Customer Experience Management also can increase customer satisfaction. Measuring only customers' experience and adapting it to marketing strategy make products position in the gap between the customers' expectation and experience not required by market. A key component of CEM is its application across all organizational functions. At last, the direction of change and development of CRM can be defined from the conceptualization of information technology represented by Ubiquitous and Web 2.0. Instead of just managing customer information, companies should take the initiative in personalized system with customer oriented strategy. Furthermore, with the regular communication between CRM stakeholders (Sales-Marketing-IT), customer's demand should be directly reflected to enterprise strategy in real time.

• The Journal of Bigdata
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• v.7 no.2
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• pp.173-193
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• 2022

With the revision of the Data 3 Act, the financial MyData industry was created newly. MyData services collect the financial customers' data scattered in various financial companies and provide personalized services such as personal financial product recommendation, personal expenditure advice, etc. Although MyData service started in 2022, but the use of the service has not been significantly activated. This study attempted to analyze the factors affecting the use of MyData services from the perspective of financial consumers through VAM, UTAUT2 model. The factors related to the perceived value and intention to use MyData services of financial consumers were verified using benefit and sacrifice variables. Personal Innovativeness was used as a moderating variable. As a result of this study, it was found that personal product recommendation service has an important influence on the use of MyData services, and personal innovativeness has an effect as a modulating variable. It can be said that it is meaningful as a preceding study in terms of timing because it studied the perceived value of consumers less than a year after the MyData service began. From the practical perspectives, it was possible to show the change direction and marketing points of the MyData service. In practice, it was possible to confirm the direction of the service and the marketing point.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.20-27
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• 2008

Hospitals today use independent systems for each department and job such as Hospital Information Sytem(HIS), Picture Archiving Communications System(PACS), Ordering Communication System(OCS), Electronic Medical Record(EMR), Enterprise Resource Planning(ERP), etc and each system employs its own DB. So, it is impossible to integrate information within the institution and difficult to keep transparency and consistency of data. I in this study offered a data integration environment through flexible management linked with other systems, and by doing that, designed a medical CRM frame which offers the optimum service the customer wants at the optimum time. I designed 4 of medical CRM frame: customer relationship management, public relations/marketing, service management, and statistics/analysis by the customer relationship management process standardization and aimed to offer tailored mobile contents according to customer's characters and health situation on the basis of customer's data by securing mobile medical contents for personalized medical information service.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.147-167
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• 2020

The purpose of this study is to analyze the factors influencing the intention of revisiting and recommending by applying a structural equation model, targeting the service quality factors of university libraries derived from previous studies. For 11 days from April 30th, 2020 to May 10th, 2020, a total of 127 user groups (undergraduate students, graduate students, professors/instructors) were surveyed on their intention to revisit and recommend. The analysis results are as follows. 'Materials' and 'service customization' were shown as quality dimensions that influence revisit. In addition, revisiting was found to have an effect on recommendation intention, and it was analyzed that 'materials' and 'service customization' affect not only revisit but also recommendation intention. In addition, 'service customization' was found to be a factor that directly affects the intention to recommend. Based on this, a method of applying the concept of customization to library services and marketing was proposed in an environment where users' needs are diversifying and becoming personalized.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.149-159
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• 2001

There have been lots of researches for providing a personalized service to a customer using one-to-one marketing and collaborative filtering techniques in E-Commerce. However, there are technical difficulties for providing the recommendation of products far users, which often involve high complexity of computation. In this paper, we have presented an integrated method of classification problem solving method and constraint based configuration techniques. This method can reduce a complexity of computation by classifying a solution domain space that has a higher complexity of composition. Thereafter, we have modeled customers constraints and the components of products to configure a complete system by passing it to constraint processing module in Constraint Satisfaction Problems. Constraint-based configuration uses the constraint propagation using the constraints of buyers and the constraints among PC components to configure a proper product for a customer. We have transformed and applied vector space modeling method in the field of information retrieval to consider a customer satisfaction in addition to the CSP. Finally, we have applied our system to test data fur evaluating a customers satisfaction and performance of the proposed system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.521-528
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• 2016

Web-based services are used widely in many computer application fields due to the increasing use of PCs and mobile devices. Accordingly, topics on the analysis of access logs generated in the application fields have been researched actively to support personalized services in the field, and analyzing techniques based on the weight differentiation of information in access logs have been proposed. This paper outlines an analysis technique for web-click streams, which is useful for finding high utility old item sets in web-click streams, whose data elements are generated at a rapid rate. Using the technique, interesting information can be found, which is difficult to find in conventional techniques for analyzing web-click streams and is used effectively in target marketing. The proposed technique can be adapted widely to analyzing the data generated in a range of computing application fields, such as IoT environments, bio-informatics, etc., which generated data as a form of data streams.