• International Commerce and Information Review
• /
• v.11 no.3
• /
• pp.3-24
• /
• 2009

Import Agency Service Mall, providing customers not only with convenient shopping experiences but also with purchasing, warehousing, shipping, and customs clearance services, have been playing a significant role in rapidly transforming Korean consumers into global consumers. The consumers' great demand for foreign goods(services) has created Import Agency Service Mall(referred to hereafter as IASM) as a new business model of distribution and consumption, which seems to be grown rapidly. This empirical research investigates online shoppers for their trust dimensions for IASM. Consequences of the research are as follows: First, perceived reputation, web-site quality have influenced upon e-trust dimension of the IASM. Second, the level of e-trust consumers is more higher, and then the level of perceived risk is more lower. Third, perceived risk have not influenced upon intention to reuse the IASM. Fourth, the level of e-trust consumers is more higher, and then the level of intention to reuse the IASM is more higher. It is necessary for IASM to be developed its reputation and web-site quality in order to obtain customer's trust. Accordingly, this research will be helping IASM have insight for marketing strategies, and constantly should be studied about action and mind of consumer.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.4
• /
• pp.1693-1713
• /
• 2018

An important technique used by database administrators (DBAs) is to improve performance in decision-support workloads associated with a Star schema is multi-level partitioning. Queries will then benefit from performance improvements via partition elimination, due to constraints on queries expressed on the dimension tables. As the task of multi-level partitioning can be overwhelming for a DBA we are proposing a wizard that facilitates the task by calculating a partitioning scheme for a particular workload. The system resides completely on a client and interacts with the costing estimation subsystem of the query optimizer via an API over the network, thereby eliminating any need to make changes to the optimizer. In addition, since only cost estimates are needed the wizard overhead is very low. By using a greedy algorithm for search space enumeration over the query predicates in the workload the wizard is efficient with worst-case polynomial complexity. The technology proposed can be applied to any clustering or partitioning scheme in any database management system that provides an interface to the query optimizer. Applied to the Teradata database the technology provides recommendations that outperform a human expert's solution as measured by the total execution time of the workload. We also demonstrate the scalability of our approach when the fact table (and workload) size increases.

• The Journal of Information Systems
• /
• v.16 no.1
• /
• pp.91-109
• /
• 2007

This study investigates the extent to which the implementation of enterprise resource planning(ERP) systems enhance the corporate performance by examining financial variables of the implemented firms against those of the control fm. A total of 346 observations were obtained from 160 firms, 80 implemented firms and 80 control firms, for the period of 1998-2002. Results from the study partly support the assertion that ERP improves the full spectrum of business functions such as selling, marketing, purchasing, warehousing, accounting and human resources by tightly integrating enterprise-wise information databases. First the profitability of the implemented group was different from that of the control group. The indicator (dummy) variable was able to explain the differences in total cash flows between the implemented group fm and the control group firms. Second, ERP turned out In improve the efficiency in managing assets. The indicator variable has the power in explaining the differences in the amount of accounts receivables between the implemented group firms and the control group firms. Third, the product turnover ratio of the implemented group was different from that of the control group. Fourth, the average value added per employee and the net income per employee of the implemented group firms were greats- than those of the control group firms. Finally, the average magnitude of the administrative expenses of the implemented group firms was smaller than that of the control group firms.

• IE interfaces
• /
• v.15 no.2
• /
• pp.159-171
• /
• 2002

Data Warehouses integrate data from multiple heterogeneous information sources and transform them into a multidimensional representation for decision support applications. Data warehousing has emerged as one of the most powerful tools in delivering information to users. Most previous researches have focused on marketing, customer service, financing, and insurance industry. Further, relatively less research has been done on data warehouse systems in the complex manufacturing industry such as ship production, which is characterized complex product structures and production processes. In the ship production, data warehouse systems is a requisite for effective cost analysis because collecting and analysis of diverse and large of cost-related(material/production cost, productivity) data in its operational systems, was becoming increasingly cumbersome and time consuming. This paper proposes architecture of the data warehouse systems to support cost analysis in the ship production. Also, in order to illustrate the usefulness of the proposed architecture, the prototype system is designed and implemented with the object of the enterprise of producing a large-scale ship.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.4
• /
• pp.89-95
• /
• 2008

In this paper, we propose an integrated techniques for managing data quality in traffic data warehousing environments. We describe how to collect and construct the traffic data warehouses from the operational databases, such as FTMS and ARTIS. We explain how to configure the traffic data warehouses efficiently. Also, we propose a quality management techniques to provide high quality traffic data for various analytical transactions. Proposed techniques can contribute in providing high quality traffic data to the traffic related users and researcher, thus reducing data preprocessing and evaluation cost.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.27 no.8
• /
• pp.892-903
• /
• 2003

Korean Internet shopping malls, which provide customers not only with convenient shopping experiences but also with purchasing, warehousing, shipping, and customs clearance services, have been playing a significant role in rapidly transforming Korean consumers into global consumers especially in purchasing fashion goods. Utilizing Ajzen and Fishbein(1980)'s Behavioral Intention Model, which postulates that behavioral intention is determined by attitude and subjective norm, this study identified behavioral intentions toward purchasing foreign fashion goods through Korean Internet shopping malls and the differences of behavioral intentions according to consumers’purchasing experiences on the Internet shopping malls. The data were gathered by surveying female university students living in the Seoul metropolitan area, Korea, and 222 questionnaires were used in the statistical analysis. Mean, standard deviation, factor analysis, t-test, cross tabulation, and $\chi$$^2$ analysis were used. The results indicated that purchasers had more favorable attitudes and subjective norms and higher behavioral intentions than non-purchasers. With respect to attitude, there were significant differences in behavioral beliefs and evaluation of outcomes for the variety and scarcity value factor. With respect to subjective norm, there were no significant differences in normative beliefs and motivation to comply toward friends, people who had purchasing experiences, fashion magazines. and celebrities between the two groups.

• Korean Management Science Review
• /
• v.20 no.2
• /
• pp.1-16
• /
• 2003

Previous research on data extraction and integration for data warehousing has concentrated mainly on the relational DBMS or partly on the object-oriented DBMS. Mostly, it describes issues related with the change data (deltas) capture and the incremental update by using the triggering technique of active database systems. But, little attention has been paid to data extraction approaches from other types of source systems like hierarchical DBMS, etc. and from source systems without triggering capability. This paper argues, from the practical point of view, that we need to consider not only the types of information sources and capabilities of ETT tools but also other factors of source systems such as operational characteristics (i.e., whether they support DBMS log, user log or no log, timestamp), and DBMS characteristics (i.e., whether they have the triggering capability or not, etc), in order to find out appropriate data extraction techniques that could be applied to different source systems. Having applied several different data extraction techniques (e.g., DBMS log, user log, triggering, timestamp-based extraction, file comparison) to S bank's source systems (e.g., IMS, DB2, ORACLE, and SAM file), we discovered that data extraction techniques available in a commercial ETT tool do not completely support data extraction from the DBMS log of IMS system. For such IMS systems, a new date extraction technique is proposed which first creates Index database and then updates the data warehouse using the Index database. We illustrates this technique using an example application.

• Journal of the Korea Safety Management & Science
• /
• v.10 no.3
• /
• pp.117-126
• /
• 2008

RFID system the key technology of ubiquitous era, has been emphasized in logistics. Logistic enterprises are required to apply RFID systems considering their investment costs, actual effectiveness, operational satisfaction and so on. For such a purpose, many applicable methods of RFID system have been developed A method that RFID tags are directly attached to products or pallets is utilized in most cases. However, this method requires expensive investment cost, frequent replacement of damaged tags for the small and medium (SM) third party logistics. In this paper, we analyze statistically the current status and requirements of SM third party logistics. Based on their requirements, we propose the realtime warehousing-delivery management by the method to attach a RFID tag to each warehouse rack, together with the economy analysis index in order to evaluate economical efficiency. Consequently, this method is expected to reduce Investment cost and to improve operational effectiveness and satisfaction.

• The Journal of Information Systems
• /
• v.26 no.2
• /
• pp.105-121
• /
• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.

• The Journal of Information Systems
• /
• v.6 no.1
• /
• pp.223-256
• /
• 1997

Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.