• The Journal of Bigdata
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• v.4 no.2
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• pp.141-158
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• 2019

Based on RBV(Resource Based View), IT of SMEs classified into IT resource and capabilities. And We confirmed that capabilities and resources affected each performance. In other words, based on the questionnaire of SMEs and IT professionals, divides capability from the overall IT resource that are possessed by SMEs. Among the four attributes (value, rare, non-substitutability, imperfect imitability) presented by Barney (1991), this study targeted at value and imperfect imitability and investigated how SMEs recognize IT resource and capability. Furthermore, this study tests how IT resource and capability influence corporate performance. The result of this study finds that resources that are needed on "Knowledge-based" are classified into IT capability, otherwise classified into IT resource. Analysis shows that server, DB(database), system administrators, programmers, CIO, BA were capabilities, Desktop PC, PC software, software for salary and accounting management, e-commerce, Homepage, and network inside th enterprise were resources. Secondly, this study reveals that both IT resource and IT capability affected company performance (employee satisfaction, CEO satisfaction). IT is certainly having an impact on corporate performance. In conclusion, resource can be either IT resource or IT capability based on they way of utilization. And both IT resource and IT capability have an influence on corporate performance (employee job satisfaction, CEO satisfaction). Therefore, when considering IT investment, a company can purchase necessary IT resource and actively utilize it to be IT capability, which can have an influence on corporate performance in return.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.599-610
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• 2003

The Web plays an important role as information source and most Web applications are document-centric. A document implies an intention of its own designer, which can be utilized actively in automation of business processes. Through an understanding of an intrinsic nature of a document function, we can see a document as an executable computer program in a special case. For this approach, we propose an active document model that is composed of form, knowledge base, rules, and queries. For reusability and interoperability of a document, each component of the proposed model is uniformly represented in XML. The proposed active document not only plays a passive role in providing user interfaces, but also is a document that a machine can infer and process with reading a procedure of document processing and business rules intended by document designers. Through this approach, document can interact with machines and can cooperate with other applications. For applicability of our active document, we show a case study for the processing of purchase orders in a B2B e-Commerce system. This paper is expected to provide the framework of accelerating the development of intelligent applications through our approach regards form document as a computer program. In short, the proposed active document contains knowledge representation and processing method, consequently our document will play an important role in providing a concept of document of pursuing in Semantic Web.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.13-25
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• 2017

The purpose of this study is to suggest the direction of O2O industry policy for solving the conflict problems with the traditional industry stakeholder and for enhancing the regulations as new industry development is inevitable. We make use of TAIDA that is one of scenario methods to accomplish the purpose and suggest the direction of policy. First, it is needed to prepare directly by government the environment that new business models are able to emerge easily with various consulting services and information supports like public system servers and IT infra, it is practical support policy. Second, positive legal application for new business and making the law for new business are needed in legal issues situation as soon as possible. Third, the conflicts with old and new industry would be managed to the direction of "predictable" progressively. Incongruity among laws, safety and security problems, and the conflict of stakeholder are urgent. Because of the limit in this study, it is expected that O2O industry is categorized in detail aligned to the characteristics and that new policies along to the separate industry areas are developed by the following study.

• Journal of Integrative Natural Science
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• v.4 no.2
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• pp.149-157
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• 2011

Urbanization of the world's population has given rise to more than 450 cities around the world with populations in excess of 1 million (megacity) and more than 25 so-called metacities with populations over 10 million (Brinkhoff, 2010). The United States today has a total resident population of more than 308,500,000 people, with 81 percent residing in cities and suburbs as of mid - 2005 (UN, 2008). Urban meteorology is the study of the physics, dynamics, and chemistry of the interactions of Earth's atmosphere and the urban built environment, and the provision of meteorological services to the populations and institutions of metropolitan areas. While the details of such services are dependent on the location and the synoptic climatology of each city, there are common themes, such as enhancing quality of life and responding to emergencies. Experience elsewhere (e.g., Shanghai, Helsinki, Tokyo, Seoul, etc.) shows urban meteorological support is a key part of an integrated or multi-hazard warning system that considers the full range of environmental challenges and provides a unified response from municipal leaders. Urban meteorology has come to require much more than observing and forecasting the weather of our cities and metropolitan areas. Forecast improvement as a function of more and better observations of various kinds and as a function of model resolution, larger ensembles, predicted probability distributions; Responses of emergency managers, government officials, and users to improved and probabilistic forecasts; Benefits of improved forecasts in reduction of loss of life, property damage, and other adverse effects. A national initiative to enhance urban meteorological services is a high-priority need for a wide variety of stakeholders, including the general, commerce and industry, and all levels of government. Some of the activities of such an initiative include: conducting basic research and development; prototyping and other activities to enable very--short and short range predictions; supporting and improving productivity and efficiency in commercial and industrial sectors; and urban planning for long term sustainability. In addition urban test-beds are an effective means for developing, testing, and fostering the necessary basic and applied meteorological and socioeconomic research, and transitioning research findings to operations. An extended, multi-year period of continuous effort, punctuated with intensive observing and forecasting periods, is envisioned.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.127-137
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• 2017

The role of smartphones is changing from a communication system for exchanging calls and information into a universal platform for cultural services. Also, satisfaction for mobile application services on smartphones is a very important factor in the smart business. In This paper, we analyze the effects of the outcome, service scape, costs, and especially the impact of whether costumers having to pay or free for the app on customer satisfaction. For this purpose, we analyzed survey data on service quality of mobile app service from Chinese mobile app service users. We also analyzed the moderating effects of paid and free mobile app services. As a result, it was confirmed that the quality, servicescape quality and cost of mobile app service that customers perceive have a positive effect on customer satisfaction. In addition, the effect of the cost of mobile app service perceived by the customer on customer satisfaction showed that free mobile app service was more significant than paid mobile app service. This paper can be used as an alternative to monetization for providing a mobile app service provider or a mobile app service provider who wants to switch mobile app service from free to paid service.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.127-143
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• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.

• The Journal of Bigdata
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• v.7 no.1
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• pp.213-224
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• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.375-393
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• 2023

The demand for Less than Container Load (LCL) has been on the rise due to the growing need for various small-scale production items and the expansion of the e-commerce market. Consequently, more companies in the International Freight Forwarder are now handling LCL. Given the variety in cargo sizes and the diverse interests of stakeholders, there's a growing need for a container loading algorithm that optimizes space efficiency. However, due to the nature of the current situation in which a cargo loading plan is established in advance and delivered to the Container Freight Station (CFS), there is a limitation that variables that can be identified at industrial sites cannot be reflected in the loading plan. Therefore, this study proposes a container loading methodology that makes it easy to modify the loading plan at industrial sites. By allowing the characteristics of cargo and the status of the container to be considered, the requirements of the industrial site were reflected, and the three-dimensional space was manipulated into a two-dimensional planar layer to establish a loading plan to reduce time complexity. Through the methodology presented in this study, it is possible to increase the consistency of the quality of the container loading methodology and contribute to the automation of the loading plan.

• The Journal of Bigdata
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• v.8 no.2
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• pp.149-163
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• 2023

Due to the continuous growth of the E-commerce market, the volume of orders that fulfillment centers have to process has increased, and various customer requirements have increased the complexity of order processing. Along with this trend, the operational efficiency of fulfillment centers due to increased labor costs is becoming more important from a corporate management perspective. Using historical performance data as training data, this study focused on real-time box recommendations applicable to packaging areas during fulfillment center shipping. Four types of data, such as product information, order information, packaging information, and delivery information, were applied to the machine learning model through pre-processing and feature-engineering processes. As an input vector, three characteristics were used as product specification information: width, length, and height, the characteristics of the input vector were extracted through a feature engineering process that converts product information from real numbers to an integer system for each section. As a result of comparing the performance of each model, it was confirmed that when the Gradient Boosting model was applied, the prediction was performed with the highest accuracy at 95.2% when the product specification information was converted into integers in 21 sections. This study proposes a machine learning model as a way to reduce the increase in costs and inefficiency of box packaging time caused by incorrect box selection in the fulfillment center, and also proposes a feature engineering method to effectively extract the characteristics of product specification information.