• IE interfaces
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• v.20 no.3
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• pp.387-394
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• 2007

Numerous countries promote business programs to revitalize local economy, increase employment, and nurture high-tech industries. Recently, a number of business incubators have been established and operated with aims to adapt to changing environment and increase economic competitiveness in Korea. To give satisfactory results of governmental policy, the requirement to develop the evaluation model to support effective operations of business incubators using the objective and rational criteria is growing. The purpose of this study is to develop evaluation model in Business Incubator using Data Mining Process. We suggested the evaluation model of business incubator, 'Score-5 RS' consists of making evaluation factor process using weighted sum and 5-grade classification and analyzing process by Decision Tree algorithm.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.198-205
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• 2021

With the development of blockchain technology, the scope of blockchain applications has expanded rapidly. Blockchain decentralization allows transaction participants to make transparent and safe transactions without a third trust agency. A distributed ledger-based system enables transparent and trusted business for anonymous users. For this reason, many companies apply blockchain to various fields such as logistics, electronic voting, and real estate. Despite this interest, there are still not enough case studies confirming the potential of blockchain as a concrete business model. Therefore, it is necessary to study how blockchain technology can change the existing business model and connect it to a new business model. In this paper, we propose blockchain-based business models and workflow types in various fields such as healthcare, logistics, and energy. We also present application cases. We expect to help companies apply blockchain to their business.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.225-231
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• 2014

When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confirm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.103-114
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• 2015

The role of small and medium enterprises as an economic growth factor has been accentuated; consequently, the need to develop a business forecast model and indexes that accurately examine business situation of small and medium enterprises has increased. Most current business model and indexes concerning small and medium enterprises, released by public and private institutions, are based on Business Survey Index (BSI) and depend on subjective (business model and) indexes; therefore, the business model and indexes lack a capacity to grasp an accurate business situation of these enterprises. The business forecast model and indexes suggested in the study have been newly developed with Principal Component Analysis(PCA) and weight method to accurately measure a business situation based on reference dates addressed by the National Statistical Office(NSO). Empirical studies will be presented to prove that the newly proposed business model and indexes have their basis in statistical theory and their trend that resembles the existing Composite Index.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.41-54
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• 2016

Because of the recession of the world economy, small businesses face with many problems in securing their required labor force, capital, technology, among others. As an alternative to address those difficulties, there is a research to introduce the "sharing economy", which shares and changes resources. However SMEs have difficulties in actually introducing the sharing economy and the introduction of inter-company because sharing economy business models do not exist. This research has presented the business model for the sharing economy that is necessary in the introduction and operation of the said economy among SMEs. In order to design the business model for the B2B sharing economy, this research has drawn the components needed to design the business model through a preceding study on existing business models. Based on this and the preceding study, this research has presented the business model, which can be introduced to the sharing economy among SMEs. In addition Business model presented in this study will be a guideline for introducing shared economic conditions for each SMEs.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.205-210
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• 2022

With the rapid development of the social economy and the continuous improvement of living standards, a favorable environment has been provided for the rapid development of the tourism industry. The highly developed Internet technology has provided people with more convenient online travel. With the rapid development of online tourism, tourism-related Internet businesses are also developing rapidly. This study first introduces the research background and significance of the study, and suggests the necessity of Ctrip's business model optimization study based on the development of social economy such as online tourism development hotspots and business model research issues. Ctrip explains the current status of research inside and outside the online travel industry and business model, in-depth introduction and analysis of related concepts and theories such as online travel and OTA business models, and expands them based on expert research. Several aspects such as insufficient Ctrip's existing business model, high current operating costs, major factors affecting suppliers, and slow development of new business were suggested, and alternatives were suggested to solve these problems. Ctrip maintained a sustainable competitive edge, including Ctrip's business model optimization strategy for value creation and innovation and Internet business model optimization strategy for customer value chains.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2551-2557
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• 2012

This study analyses the relative importance of R&D business model of the small and medium manufacturing firm. We also compare samples by classifying by its properties, technology and market circumstance. The most important factor of the R&D business model is marketing factor and infrastructure factor is relatively less important. Also the relative importance of the R&D business model is different according to firm's properties and technology. So when government establishes the R&D policy, he focuses on designing the R&D business model.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.152-163
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• 2005

The focus of enterprise collaboration of supply chain management, has changed from integrating and exchanging business information to integrating and managing business processes between business partners. However, the collaboration is difficult due to the inherent complexity such as diverse business processes and dynamic business environments. To settle these problems, a reference model based enterprise architecture framework for the collaboration of supply chains is proposed in this paper. The supply chain collaboration framework is composed of three reference models capturing the different views of supply chain collaboration: supply process reference model, service component reference model, and technology and standard reference model. As the framework adapts the OMG's metadata architecture, the processes in the supply chain can be extended and integrated with other value chains, such as design chains, when it is necessary. Using the proposed framework, business managers can rapidly integrate and manage their business processes with their suppliers and customers.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.41-55
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• 2023

In order to secure sustainable competitiveness of startups, business model innovation is an important task to achieve competitive advantage by transforming the various elements that make up the business model. This study conducted a multi-case analysis study on leading smart farm companies around the world using an analysis framework based on business model theory. Through this, we sought to identify business model types and their constituent elements. For this, 19 companies were selected from the list of top 10 investment startups of the year for the past three years published by Agfunder, a global investment research company specializing in AgTech. Then data collection and analysis of the company cases were conducted according to the case study protocol. As a result of the study, the business model types were analyzed into four types: large-scale centralized production model, medium-to-large local distributed production model, small-scale hyperlocal modular FaaS model, and small-scale hyperlocal turnkey solution supply model. A comparative analysis was conducted on five business model components for each type, and strategic implications were derived through this. This study is expected to contribute to improving the competitiveness of domestic smart farm startups and diversifying their strategies by identifying the business models of overseas leading companies in the smart farm field using an academic analysis framework.

• Asia pacific journal of information systems
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• v.29 no.1
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• pp.35-49
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• 2019

The paper attempts to document the application of relevant Machine Learning (ML) models on Yelp (a crowd-sourced local business review and social networking site) dataset to analyze, predict and recommend business. Strategically using two cloud platforms to minimize the effort and time required for this project. Seven machine learning algorithms in Azure ML of which four algorithms are implemented in Databricks Spark ML. The analyzed Yelp business dataset contained 70 business attributes for more than 350,000 registered business. Additionally, review tips and likes from 500,000 users have been processed for the project. A Recommendation Model is built to provide Yelp users with recommendations for business categories based on their previous business ratings, as well as the business ratings of other users. Classification Model is implemented to predict the popularity of the business as defining the popular business to have stars greater than 3 and unpopular business to have stars less than 3. Text Analysis model is developed by comparing two algorithms, uni-gram feature extraction and n-feature extraction in Azure ML studio and logistic regression model in Spark. Comparative conclusions have been made related to efficiency of Spark ML and Azure ML for these models.