• Knowledge Management Research
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• v.21 no.1
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• pp.117-136
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• 2020

In the studies for the recommender systems which solve the information overload problem of users, the use of transactional data has been continuously tried. Especially, because the firms can easily obtain transactional data along with the development of IoT technologies, transaction-based recommender systems are recently used in various areas. However, the use of transactional data has limitations that it is hard to reflect domain knowledge and they do not directly show user preferences for individual items. Therefore, in this study, we propose a method applying the word embedding in the transaction-based recommender system to reflect preference differences among users and domain knowledge. Our approach is based on SAR, which shows high performance in the recommender systems, and we improved its components by using FastText, one of the word embedding techniques. Experimental results show that the reflection of domain knowledge and preference difference has a significant effect on the performance of recommender systems. Therefore, we expect our study to contribute to the improvement of the transaction-based recommender systems and to suggest the expansion of data used in the recommender system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3068-3085
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• 2021

The economics of big data knowledge, especially cloud computing and statistical data of consumer preferences, has attracted increasing academic and industry practitioners' attention. Firms nowadays require purchasing not only external private patent knowledge from other firms, but also proprietary big data knowledge to support their new product development. Extant research investigates pricing strategies of external private patent knowledge and proprietary big data knowledge separately. Yet, a comprehensive investigation of pricing strategies of these two types of knowledge is in pressing need. This research constructs an overarching pricing model of external private patent knowledge and proprietary big data knowledge through the lens of firm profitability as a knowledge transaction recipient. The proposed model can help those firms who purchase external knowledge choose the optimal knowledge structure and pricing strategies of two types of knowledge, and provide theoretical and methodological guidance for knowledge transaction recipient firms to negotiate with knowledge providers.

• Information Systems Review
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• v.7 no.1
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• pp.195-217
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• 2005

Individual recognizes knowledge sharing as a transaction action. This transaction occurring in knowledge sharing is considered as a special and complicated transaction derived from employee's relationship rather than a economic transaction. In addition, It is important that knowledge sharing among individuals is established through a closed interrelationship with situation. In this point of view, knowledge sharing can be explained by a social exchange relationship. Therefore, there are two study's purpose as follows. First, The study draws factors affecting to knowledge sharing in the view of social exchange theory. The study reviews factors that are presented at previous social exchange theories and affecting to knowledge sharing focused on organization contingency traits, relationship traits, and individuals traits among individuals in an organization. Second, even though trust and organization involvement is resulted in above affecting factors, most previous studies are mainly examined as the same level to other factors affecting to knowledge sharing. Thus, this paper focused that the above factors affect to trust and organization involvement that affect to knowledge sharing intention. That is, this study presents that when affecting factors mediate trust and involvement, there is a knowledge sharing intention for creating organization knowledge. For the study, 160 government employees are administered for the survey so that the research model and hypothesis are developed. Empirical study shows that in public organizations knowledge sharing affects to relationship traits factors and individuals traits affects trust and organization involvement. Also, it is examined that trust and organization involvement affecting to knowledge sharing intention in such a sequence.

• The Korean Journal of Franchise Management
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• v.12 no.4
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• pp.1-11
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• 2021

Purpose: The franchise system started by Singer Sewing Machine in the US is acting as a national economic growth engine in terms of job creation and economic growth. In China, the franchise system was introduced in the mid-1980s. And since joining the WTO, it has grown by 5-6% every year. However, compared to the growth rate of franchises, studies on shared growth between the chain headquarters and franchisees were insufficient. Accordingly, recent studies related to shared growth between the chain headquarters and franchisees have been active in China. The purpose of this study is to examine the knowledge transfer system between the knowledge creation, knowledge sharing, and the use of knowledge by franchise chain headquarters in China. In addition, the relationship between franchise satisfaction and performance is identified. Research design, data, and methodology: The data were collected from franchise stores in Sichuan, China, and were conducted with the help of ○○ Incubation, a Sichuan Province-certified incubator. From November 2020 to January 2021, 350 copies of the questionnaire were distributed in China, and 264 copies were returned. Of these, 44 copies with insincere answers and response errors were excluded, and 222 copies were used for analysis. The data were analyzed with SPSS 22.0 and AMOS 22.0 statistical packages. Result: The results of this study are as follows. First, knowledge creation has been shown to have a statistically significant impact on knowledge sharing and knowledge utilization. In particular, the effectiveness of knowledge creation was higher in knowledge sharing than in knowledge utilization. And we can see that knowledge sharing also has a statistically significant e ffect on knowledge utilization. Second, knowledge sharing was not significant for transaction satisfaction and business performance, and knowledge utilization was significant for transaction satisfaction and business performance. These results can be said to mean less interdependence of the Chinese franchise system. Finally, transaction satisfaction was statistically significant to business performance. The purpose of this study was to examine the importance of knowledge management to secure long-term competitive advantage for Chinese franchises. This study shows that knowledge sharing is important for long-term franchise growth. And we can see that there is a lack of knowledge sharing methods in the case of franchises in China. I n addition, it was found that the growth of Chinese franchises requires systematization of communication, information sharing measures and timing, help from chain headquarters, and mutual responsibility awareness.

• IE interfaces
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• v.13 no.1
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• pp.17-28
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• 2000

As knowledge has been recognized as a new resource in gaining organizational competitiveness, Knowledge Management (KM) is suggested as a method to manage and apply knowledge for business management. KM research, however, has focused on identifying, storing, and distributing the transaction-related knowledge in an organization. There has been little research on applying the knowledge to decision-making or strategy development that is the main task of business management. The application of knowledge to decision making has higher impact on organizational performance rather than just the knowledge management for process transaction. In this research, we suggest System Dynamics (SD) for the knowledge-based decision-making. Based on the modeling method of SD, we can translate partial and implicit knowledge resident in individual's mental model into organized explicit knowledge. The simulation test of the organized knowledge model enables decision-makers to understand the structure of the target problem and its behavior mechanism, which facilitates effective decision-making. We will compare the proposed method and other KM methods and discuss this research based on the application case to a real telecommunication company.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.233-238
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• 2021

Recently, blockchain technology accumulates and stores all transactions. Therefore, in order to verify the contents of all transactions, the data itself is compressed, but the scalability is limited. In addition, since a separate verification algorithm is used for each type of transaction, the verification burden increases as the size of the transaction increases. Existing blockchain cannot participate in the network because it does not become a block sink by using a server with a low specification. Due to this problem, as the time passes, the data size of the blockchain network becomes larger and it becomes impossible to participate in the network except for users with abundant resources. Therefore, in this paper, we are improved transaction as studied the zero knowledge proof algorithm for general operation verification. In this system, the design of zero-knowledge circuit generator capable of general operation verification and optimization of verifier and prover were also conducted.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.249-255
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• 2016

Recently, transaction data is accumulated everywhere very rapidly. Association analysis methods are usually applied to analyze transaction data, but the methods have several problems. For example, these methods can only consider one-way relations among items and cannot reflect domain knowledge into analysis process. In order to overcome defect of association analysis methods, we suggest a transaction data analysis method based on probabilistic graphical model (PGM) in this study. The method we suggest has several advantages as compared with association analysis methods. For example, this method has a high flexibility, and can give a solution to various probability problems regarding the transaction data with relationships among items.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.433-437
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• 2005

Most research organizations, universities and enterprises manage the transaction informations (customer informations, account informations, transaction results and so on), which is a fundamental item in the part of buying and research capital expenditure for the execution of R&D project or relative works. But because they don't only manage transaction information systematically but also don't put to practical use as sharing knowledge, many researchers duplicate their operations and it is shown a drop in efficiency. Also there are many problems because useful informations are unapproachable in the side of research management. In this paper, we propose the database design, application plan and service method for joint utilize of transaction information. And we prove the proposed method by service which is operated within intranet system. The transaction information shared by the proposed method will be useful knowledge and a major factor of efficiency improvement in research management field.

• Knowledge Management Research
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• v.21 no.1
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• pp.61-78
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• 2020

Recently, in the global financial transaction field, global transactions using computer systems and server hubs between foreign exchanges beyond the one-dimensional offline transactions and two-dimensional online transactions have been actively conducted. In the previous research by Lee Hyung-wook and Lee Min-jae (2018), as the globalization has accelerated following the development of digital technology and the expansion of ubiquitous communication network, the role of companies, the attribute of economic value creation and economic structure are being reorganized. It is said that O2O (Online to Offline) transactions are increasing due to the development. As a result, a new financial transaction paradigm is emerging that solves the inconveniences of existing financial services and enhances speed and convenience. Considering the global network trend and the rapidly developing and evolving digital bank environment, the necessity of utilizing the business platform model is emerging. However, despite this necessity, there are very limited cases in which such an attempt has been applied in practice. Accordingly, this study seeks to explore the business platform of the new financial transaction system. Specifically, the case study systematically examines the actual implementation of a unique network connection model with Koscom's global investment bank, which is currently in charge of the domestic financial transaction system, and improves ICT innovation performance and process through this. I would like to suggest a solution. In particular, this study analyzed a variety of business model construction and use cases by pursuing a platform connection with digital banks, which has recently been increasingly in demand. Therefore, this study intends to pursue the original and long-term profitability of the company by utilizing ICT innovation and platform business model, and also analyzes the convenience and excellence of trading for institutional and individual investors using the platform of digital bank. The implications of this study are significant in that it explores and explores the actual cases of ICT innovation and additional digital bank platform-connected business models based on this, and suggests a unique and preemptive business strategy of the company in the future.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.