• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.49-62
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• 2018

The purpose of this study is to develop an assessment index for the selection of promising start-ups, which will enhance the efficiency of program that support start-ups. In order to develop assessment models for selecting start-ups, three major research steps were conducted. First, this study attempted to theoretically redefine the assessment index from the perspective of the Balanced Scorecard (BSC) through a literature review. Second, major assessment index were derived using Delphi technique for experts in start-up areas. Third, weights were derived by applying AHP technique to calculate the importance of each index. The results of this study are summarized as follows. First, this study attempted to apply the assessment model for selecting start-ups from the Balanced Scorecard (BSC) view through the previous study review. Second, the final major questions were derived with sufficient opinions collected and structured survey of leading start-up experts in areas related to research subjects and elicited the most representative questions. Third, the results of applying the weights of the main selected assessment index, commercialization viewpoint is the most priority, followed by market view, technology development viewpoint, and organizational capability viewpoint. In the middle section, th ability to make products in the commercialization viewpoint, market competitiveness in the market, product discrimination capacity in the technology development perspective, and the ability of the entrepreneur in the organizational capacity perspective were important. Overall important items were found to be in the order of the capabilities of entrepreneurs, market competitiveness, product fire capability, and product discrimination. The importance of small items was highest priority for comparative excellence of competing products, and the degree of marketability, capacity of entrepreneurship, ability to raise capital, desire for entrepreneurship, and passion were shown. The results of this study presented a conceptual alternative to the preceding study on the development of existing selection assessment indexes. And it provides meaningful and important implications as an attempt to develop more sophisticated indicators by overcoming the limitations of empirical research on only some of the evaluation metrics.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.177-196
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• 2021

In the era of the 4th industrial revolution, high technology is causing many changes in modern society and economy. Among them, changes in industries and jobs require new competencies of future human resources. As an educational alternative to these changes, maker education and design thinking methods are spreading around the world, and it is necessary to actively apply such education in university curriculum. Therefore, this study examines the effects of the maker education using the design thinking method on the learners' competencies required as future human resources and, relationship between the development of university students' entrepreneurial competencies and learners' competencies. And the purpose of this study is to contribute to the vitalization of entrepreneurship education for university students by suggesting an educational model. For this purpose, this study investigated the prior research on maker education/environment and design thinking methods to examine concepts and characteristics, and analyzed the influences between maker education/environment and design thinking methods and the development of learners' personal, social and technological capabilities. In addition, this study analyzed the relationship between learners' developed capabilities and university students' entrepreneurial capabilities, and based on the results, suggested directions and conceptual models for education that combine maker education/environment and design thinking methods. In conclusion, maker education/environment and design thinking methods in university education have a positive effect on the cognitive, social, and technological development of learners, and this has a significant relationship with the factors of personal, social, and technological dimensions of university students' entrepreneurial competency. It is analyzed that it has a positive effect on the promotion of entrepreneurship activities of university students. Therefore, it is judged that university's interest and support should be given to the vitalization of maker education using the design thinking method for university student entrepreneurship education and future human resources nurturing.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.191-209
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• 2023

Amid rapid changes in technological innovation due to the influence of the 4th Industrial Revolution and COVID-19, research related to absorption capacity and patent activities to promote technological innovation of Korean technology start-ups is important in this uncertain environment. This study aims to examine the effects on entrepreneurial performance and patent activities by reconstructing absorptive capacity, an organizational capability, for technology-based startups in fields such as BT and ICT with less than seven years of establishment, distinguishing between potential absorptive capacity and realized absorptive capacity. The study also seeks to develop a theoretical research model. To accomplish this, data was collected from managerial executives, including CEOs of 215 technology startups. The following hypotheses were tested: Firstly, potential absorptive capacity had a significant impact on patent activities, while realized absorptive capacity did not. Secondly, potential absorptive capacity had a significant impact on technological performance, while realized absorptive capacity did not. Thirdly, both potential and realized absorptive capacity had a significant impact on financial and non-financial performance. Fourthly, patent activities indirectly influenced potential absorptive capacity and technological performance, but did not affect realized absorptive capacity. Fifthly, patent activities indirectly influenced potential absorptive capacity and financial performance, but did not affect realized absorptive capacity. Lastly, patent activities indirectly influenced potential absorptive capacity and non-financial performance, but did not affect realized absorptive capacity. The practical significance of this study lies in providing useful guidelines for building the core capabilities of organizations through absorptive capacity and patent activities. Furthermore, it is expected that startups that have not recognized the formation process of absorptive capacity for patent activities will perceive the formation mechanism of absorptive capability anew and show considerable interest in future potential and realized absorptive capacity as part of their management strategies. This is anticipated to play an important role in adapting to rapidly changing technological advancements, the startup ecosystem, and securing sustainable competitive advantages.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.167-190
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• 2010

The research conducted here focuses on the effect of factors that affect the behavior of UCC (User Created Content) website users, other than user's rational recognition of how useful a UCC website can be. Most discussions in the existing literature on information systems have focused on users' evaluation how a UCC website can help to attain the users' own goals. However, there are other factors and this research pays attention to an individual's 'personality,' which is stable and biological in nature. Specifically, I have noted here that 'extroversion' and 'neuroticism,' the two common personality factors presented in Eysenck's most representative 'EPQ Model' and 'Big Five Model,' are the two personality factors that affect a site's 'usefulness,' by this I mean how useful does the user consider the website and its content. How useful a site is considered by the user is the other factor that has been regarded as the antecedent factor that influences the adoption of information systems in the existing MIS (Management Information System) research. Secondly, as using or creating a UCC website does not guarantee the user's or the creator's extrinsic motivation, unlike when using the information system within an organization, there is a greater likelihood that the increase in user's activities in relation to a UCC website is motivated by emotional factors rather than rational factors. Thus, I have decided to include the relationship between an individual's personality and what they find pleasurable in the research model. Thirdly, when based on the S-O-R Paradigm of Mehrabian and Russell, the two cognitive factors and emotional factors are finally affected by stimulus, and thus these factors ultimately have an effect on an individual's respondent behavior. Therefore, this research has presented an assumption that the recognition of how useful the site and content is and what emotional pleasure it provides will finally affect the behavior of the UCC website users. Finally, the relationship between the recognition of how useful a site is and how pleasurable it is to useand UCC usage may differ depending on certain situational conditions. In other words, the relationship between the three factors may vary according to how much users are involved in the creation of the website content. Creation thus emerges as the keyword of UCC. I analyzed the above relationships through the moderating variable of the user's involvement in the creation of the site. The research result shows the following: When it comes to the relationship between an individual's personality and what they find pleasurable it is extroverted users who have a greater likelihood to feel pleasure when using a UCC website, as was expected in this research. This in turn leads to a more active usage of the UCC web site because a person who is an extrovert likes to spend time on activities with other people, is sensitive to new experiences and stimuli and thus actively responds to these. An extroverted person accepts new UCC activities as part of his/her social life, rather than getting away from this new UCC environment. This is represented by the term 'Foxonomy' where the users meet a variety of users from all over the world and contact new types of content created by these users. However, neuroticism creates the opposite situation to that created by extroversion. The representative symptoms of neuroticism are instability, stress, and tension. These dispositions are more closely related to stress caused by a new environment rather than this creatingcuriosity or pleasure. Thus, neurotic persons have an uneasy feeling and will eventually avoid the situation where their own or others' daily lives are frequently exposed to the open web environment, this eventually makes them have a negative attitude towards the web environment. When it comes to an individual's personality and how useful site is, the two personality factors of extroversion and neuroticism both have a positive relationship with the recognition of how useful the site and its content is. The positive, curious, and social dispositions of extroverted persons tend to make them consider the future usefulness and possibilities of a new type of information system, or website, based on their positive attitude, which has a significant influence on the recognition of how useful these UCC sites are. Neuroticism also favorably affects how useful a UCC website can be through a different mechanism from that of extroversion. As the neurotic persons tend to feel uneasy and have much doubt about a new type of information system, they actively explore its usefulness in order to relieve their uncomfortable feelings. In other words, neurotic persons seek out how useful a site can be in order to secure their own stable feelings. Meanwhile, extroverted persons explore how useful a site can be because of their positive attitude and curiosity. As a lot of MIS research has revealed that the recognition of how useful a site can be and how pleasurable it can be to use have been proven to have a significant effect on UCC activity. However, the relationship between these factors reveals different aspects based on the user's involvement in creation. This factor of creationgauges the interest of users in the creation of UCC contents. Involvement is a variable that shows the level of an individual's mental effort in creating UCC contents. When a user is highly involved in the creation process and makes an enormous effort to create UCC content (classed a part of a high-involvement group), their own pleasure and recognition of how useful the site is have a significantly higher effect on the future usage of the UCC contents, more significantly than the users who sit back and just retrieve the UCC content created by others. The cognitive and emotional response of those in the low-involvement group is unlikely to last long,even if they recognize the contents of a UCC website is pleasurable and useful to them. However, the high-involvement group tends to participate in the creation and the usage of UCC more favorably, connecting the experience with their own goals. In this respect, this research presents an answer to the question; why so many people are participating in the usage of UCC, the representative form of the Web 2.0 that has drastically involved more and more people in the creation of UCC, even if they cannot gain any monetary or social compensation. Neither information system nor a website can succeed unless it secures a certain level of user base. Moreover, it cannot be further developed when the reasons, or problems, for people's participation are not suitably explored, even if it has a certain user base. Thus, what is significant in this research is that it has studied users' respondent behavior based on an individual's innate personality, emotion, and cognitive interaction, unlike the existing research that has focused on 'compensation' to explain users' participation with the UCC website. There are also limitations in this research. Firstly, I divided an individual's personality into extroversion and neuroticism; however, there are many other personal factors such as neuro-psychiatricism, which also needs to be analyzed for its influence on UCC activities. Secondly, as a UCC website comes in many types such as multimedia, Wikis, and podcasting, these types need to be included as a sub-category of the UCC websites and their relationship with personality, emotion, cognition, and behavior also needs to be analyzed.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Journal of Family Resource Management and Policy Review
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• v.25 no.3
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• pp.87-102
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• 2021

Child abuse and neglect are recently increasing in Korea, and although the government has actively improved the child protection system, the number of abused children and the rate of cases judged as abuse have continuously risen. Given that 75% of child abusers are parents, child abuse and neglect are expected to recur. To prevent such a recurrence, various intervention programs for abused children and their parents are required. The purpose of this study were to design a recovery support service process and investigate the effectiveness of pilot program for families of origin, including neglected(protected) children, to improve the system by which these programs are operated, and formulate policy alternatives that reinforce "family preservation" principles. The pilot program was implemented from June to November 2020 in 4-local healthy family support center. The number of program participants and the frequency of participation in each other differed, because of the difference in number of confirmed coronavirus cases in each region and the requirement for social distancing. Through the program, a community-based service process was developed for neglected(protected) children and their parents, and cooperative networks between related facilities and institutions were established. The study formulated the following recommendations: First, a cooperation system among government departments mandated to provide different services to neglected(protected) children is needed. Second, wider and various channels through which abused children can avail of protective services should be developed within communities. Third, more stable environments for program operation should be cultivated, and cooperative partnerships should be sought for knowledge sharing among relevant government departments. Another necessary measure is for a center to develop its own business model, in which the duplication of services provided by involved organizations is avoided. Finally, clear guidelines, administrative standards, and specific plans for program operation should be arranged. Also regional characteristics are maintained, but services should be standardized.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.141-156
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• 2013

Researchers in welfare services of local government in Korea have rather been on isolated issues as disables, childcare, aging phenomenon, etc. (Kang, 2004; Jung et al., 2009). Lately, local officials, yet, realize that they need more comprehensive welfare services for all residents, not just for above-mentioned focused groups. Still cases dealt with focused group approach have been a main research stream due to various reason(Jung et al., 2009; Lee, 2009; Jang, 2011). Social Security Information System is an information system that comprehensively manages 292 welfare benefits provided by 17 ministries and 40 thousand welfare services provided by 230 local authorities in Korea. The purpose of the system is to improve efficiency of social welfare delivery process. The study of local government expenditure has been on the rise over the last few decades after the restarting the local autonomy, but these studies have limitations on data collection. Measurement of a local government's welfare efforts(spending) has been primarily on expenditures or budget for an individual, set aside for welfare. This practice of using monetary value for an individual as a "proxy value" for welfare effort(spending) is based on the assumption that expenditure is directly linked to welfare efforts(Lee et al., 2007). This expenditure/budget approach commonly uses total welfare amount or percentage figure as dependent variables (Wildavsky, 1985; Lee et al., 2007; Kang, 2000). However, current practice of using actual amount being used or percentage figure as a dependent variable may have some limitation; since budget or expenditure is greatly influenced by the total budget of a local government, relying on such monetary value may create inflate or deflate the true "welfare effort" (Jang, 2012). In addition, government budget usually contain a large amount of administrative cost, i.e., salary, for local officials, which is highly unrelated to the actual welfare expenditure (Jang, 2011). This paper used local government welfare service data from the detailed data sets linked to the Social Security Information System. The purpose of this paper is to analyze the factors that affect social welfare spending of 230 local authorities in 2012. The paper applied multiple regression based model to analyze the pooled financial data from the system. Based on the regression analysis, the following factors affecting self-funded welfare spending were identified. In our research model, we use the welfare budget/total budget(%) of a local government as a true measurement for a local government's welfare effort(spending). Doing so, we exclude central government subsidies or support being used for local welfare service. It is because central government welfare support does not truly reflect the welfare efforts(spending) of a local. The dependent variable of this paper is the volume of the welfare spending and the independent variables of the model are comprised of three categories, in terms of socio-demographic perspectives, the local economy and the financial capacity of local government. This paper categorized local authorities into 3 groups, districts, and cities and suburb areas. The model used a dummy variable as the control variable (local political factor). This paper demonstrated that the volume of the welfare spending for the welfare services is commonly influenced by the ratio of welfare budget to total local budget, the population of infants, self-reliance ratio and the level of unemployment factor. Interestingly, the influential factors are different by the size of local government. Analysis of determinants of local government self-welfare spending, we found a significant effect of local Gov. Finance characteristic in degree of the local government's financial independence, financial independence rate, rate of social welfare budget, and regional economic in opening-to-application ratio, and sociology of population in rate of infants. The result means that local authorities should have differentiated welfare strategies according to their conditions and circumstances. There is a meaning that this paper has successfully proven the significant factors influencing welfare spending of local government in Korea.