• International Journal of Contents
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• v.4 no.3
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• pp.1-9
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• 2008

The Korean life insurance industry has undergone profound changes, such as the beginning of the variable insurance in July 2001 and the bancassurance enforcement in August 2003. However, little empirical research has analyzed data that includes the bancassurance of life insurance companies operating in Korea. In response to this lack of research, this paper applies DEA (data envelopment analysis) models to measure and decompose their efficiency. We discovered that life insurance companies operating in Korea are a little different in their composition ratio of inputs and outputs, due to the increased variety of distribution channels and new products. We provided efficiency scores, return to scale, and reference frequencies. We also decomposed CCR, BCC, and SBM efficiency into scale efficiency and MIX efficiency. So, we try to investigate whether the sources of inefficiency were caused by the inefficient operation of DMU, disadvantageous conditions, the difference of the composition ratio in inputs and outputs with reference sets, or any combination of the above. Most companies in the sample display had either constant or decreasing returns to scale. The efficiency rankings were less consistent among models and efficient DMUs. In response to this problem, we used the super-efficiency model to rank them and then compared the rankings of the DMUs among the various models. It was also concluded that the availability of panel data, rather than cross-sectional data, would greatly improve the validity of the efficiency estimates.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.314-333
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• 2014

When analyzing default predictions in real estate companies, the number of non-defaulted cases always greatly exceeds the defaulted ones, which creates the two-class imbalance problem. This lowers the ability of prediction models to distinguish the default sample. In order to avoid this sample selection bias and to improve the prediction model, this paper applies a minority sample generation approach to create new minority samples. The logistic regression, support vector machine (SVM) classification, and neural network (NN) classification use an imbalanced dataset. They were used as benchmarks with a single prediction model that used a balanced dataset corrected by the minority samples generation approach. Instead of using prediction-oriented tests and the overall accuracy, the true positive rate (TPR), the true negative rate (TNR), G-mean, and F-score are used to measure the performance of default prediction models for imbalanced dataset. In this paper, we describe an empirical experiment that used a sampling of 14 default and 315 non-default listed real estate companies in China and report that most results using single prediction models with a balanced dataset generated better results than an imbalanced dataset.

• 한국산학경영학회:학술대회논문집
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• 2004.11a
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• pp.4-22
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• 2004

The Internet provides a new distribution channel of digital contents for conventional media firms such as newspaper, magazine and encyclopedia publishers and broadcasting companies with very low marginal production and distribution cost. In comparison to traditional offline channel, there have been various revenue models in online content markets such as advertising model, subscription model, affiliation fee model, etc. In the earlier of the Internet era, most of online content firms provided their services free in order to boost offline revenue or they depend on advertising revenue sources in lieu of attaining revenue from their contents. However, as many online content firms are confronted with many difficulties in attaining revenues from online advertising model, they began to charge their contents. This paper shows why they charge their contents and explores entry conditions when conventional firms enter online content markets. And also this paper discusses managerial implications related to pricing strategies in online content markets.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.109-115
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• 2019

Most demand forecasting studies for telecommunication services have focused on estimating market size at the introductory stage of new products or services, or on suggesting improvement methods of forecasting models. Although such studies forecast business growth and market sizes through demand forecasting for new technologies and overall demands in markets, they have not suggested more specific information like relative market share, customers' preferences on technologies or service, and potential sales power. This study focuses on the telecommunication service industry and explores ways to calculate the relative market shares between competitors, considering competitive situations at the introductory stage of a new mobile telecommunication service provider. To reflect the competitive characteristics of the telecommunication markets, suggested is an extended conjoint analysis using service coverage and service switching rates as modification variables. This study is considered to be able to provide strategic implications to businesses offering existing service and ones planning to launch new services. The result of analysis shows that the new service provider has the greatest market share at the competitive situation where the new service covers the whole country, offers about 50% of existing service price, and allows all cellphones except a few while the existing service carrier maintains its price and service and has no response to the new service introduction. This means that the market share of the new service provider soars when it is highly competitive with fast network speed and low price.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.125-133
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• 2019

Company A should maintain myriad conversion tools for the purpose of making a geometric compilation of navigation maps. Company A is already using complex compilation tools, which are tailored to geographical areas and various GPS models. However, due to frequent requirement and personnel changes, there is an endless challenge for perfect tool configuration and multiple map consolidation. To solve this problem, Company A launched a process automation project using Graphviz, which is an open source workflow graph visualization software. Before implementation, they had to document their current map compilation processes and then match it with the applicable conversion tool. For effective representation of process controls, a new graphical process notation is designed, i.e. Y Block diagram. The authors will compare Y Block diagram with other process notations and explain why Y Block diagram is more useful for tool based business processes such as digital map generation processes.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.55-60
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• 2022

Churn prediction is a critical long-term problem for many business like music, games, magazines etc. The churn probability can be used to study many aspects of a business including proactive customer marketing, sales prediction, and churn-sensitive pricing models. It is quite challenging to design machine learning model to predict the customer churn accurately due to the large volume of the time-series data and the temporal issues of the data. In this paper, a parallel artificial neural network is proposed to create a highly-accurate customer churn model on a large customer dataset. The proposed model has achieved significant improvement in the accuracy of churn prediction. The scalability and effectiveness of the proposed algorithm is also studied.

• Asia Marketing Journal
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• v.22 no.3
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• pp.87-105
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• 2020

With the development of Information Technology, customers require promptly higher quality products and services. Companies try to make newly digital marketing strategies, but there are no empirical researches on them. This article empirically presents a new perspective that companies can shape the customer decision journey ahead by coordinating customer experience. In this article, based on Elaborated Likelihood Model (ELM) theory, customer experience consists of the emotional or cognitive experience. We surveyed about 200 subjects (N = 217) in their 20s and 30s based on the International Music Industry Association's Music Listening 2019 report, then analyzed four different models (before personalization-cognitive experience, before personalization-emotional experience, after personalization- cognitive experience, after personalization-emotional experience) by JASP and R Studio. We conducted Structural Equation Model (SEM) and paired t-test. Personalization factors are about recommendation systems in Spotify. The results of survey represent that companies can shape the Customer Decision Journey (CDJ) ahead especially through enhance cognitive experience. It empirically proves Elaborated Likelihood Model (ELM). The conclusion can be drawn that 'pulling' customer experience can be a new marketing strategies in the digital era.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.895-899
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• 2009

This paper presents a business models of the robot industry for copying with aging society that facilitates to create new business opportunities in the convergence age. In order to identify the market drivers for both convergence and aging society, the trends of them analyzed. Through constructing and analyzing market value chain, we design a set of the business model of the robot industry focused on u-health robots of a convergence service type integrated ubiquitous, health and robot. In addition, we describe the evolution path of the proposed business model in terms of technology development and market. Finally, we develop a matrix based evaluation framework to measure and assess the effectiveness of the business model.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.530-539
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• 2015

A business model (BM) can be developed based on a business model framework (BMF) consisting of key components such as value proposition, customers, and resources. To systematically generate and analyze emerging BMs such as healthcare BM, an integration of diverse BMF components is needed. The present study is to establish a comprehensive BMF and evaluate its applicability to healthcare BMs. Based on a review of eight BMF studies, ten BMF components were identified and classified into five major components (value proposition, resources, organizing model, customers, and revenue model) and five minor components (technology, service platform, delivery, competitive strategy, and growth/exit) by analyses of frequency and functional importance. Lastly, the BMs of three emerging healthcare companies (WellDoc, Inc., CFW Shops, and Aravind Eye Care System) were analyzed and compared in terms of the proposed BMF components. The comprehensive BMF components presented in the study can be of help for developing new BMs and analyzing the strengths and weaknesses of BMs.

• Knowledge Management Research
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• v.22 no.1
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• pp.105-120
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• 2021

Recently, there has been a dramatic change in real estate markets with the development of information technology. The word, Proptech, is defined as the real estate transaction innovation motivated by various types of information technology including artificial intelligence, sensing technology and big data. The objective of this study is to provide a value-creation framework for Proptech business based on the understanding of how and what types of values are created and shared, which gives organization to develop strategies and business models. And a new classification scheme of Proptech business is also suggested based on the recognition of created values along the development of Proptech business. Then, the proposed matrix is applied to derive the business value such as intangibility value, relational value and enhancement value with the case analysis on the each components of Proptech business.