• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.89-117
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• 2018

The Korean companies are intensifying competition with not only domestic companies but also foreign companies in globalization. In this environment, it is essential activities not only for large companies but also Small and Medium Enterprises (SMEs) to get and develop the core competency. Particularly, SMEs that are inferior to resources of various aspects, such as financial resources etc., can make innovation through effective R&D investment. And then, SMEs can occupy a competency and can be survive at the environment. Conventionally, the method of "self-development" by using only the internal resources of the company has been dominant. Recently, however, R&D method through cooperation, also called "Open Innovation", is emerging. Especially SMEs are relatively short of available internal resources. Therefore, it is necessary to utilize technology and resources through cooperation with external companies(such as joint development or contract development etc.) rather than self-development R&D. In this context, we confirmed the effect of SMEs' factors on sales in Korea. Specifically, the factors that SMEs hold are classified as 'Technical characteristic', 'Company competency', and 'R&D activity' and analyzed how they influence the sales achieved as a result of R&D. The analysis was based on a two-year statistical survey conducted by the Korean government. In addition, we confirmed the influence of the factors on the sales according to the R&D method(Self-Development vs. Open Innovation), and also observed the influence change in 29 industrial categories. The results of the study are summarized as follows: First, regression analysis shows that twelve factors of SMEs have a significant effect on sales. Specifically, 15 factors included in the analysis, 12 factors excluding 3 factors were found to have significant influence. In the technical characteristic, 'imitation period' and 'product life cycle' of the technology were confirmed. In the company competency, 'R&D led person', 'researcher number', 'intellectual property registration status', 'number of R&D attempts', and 'ratio of success to trial' were confirmed. The R&D activity was found to have a significant impact on all included factors. Second, the influence of factors on the R&D method was confirmed, and the change was confirmed in four factors. In addition, these factors were found that have different effects on sales according to the R&D method. Specifically, 'researcher number', 'number of R&D attempts', 'performance compensation system', and 'R&D investment' were found to have significant moderate effects. In other words, the moderating effect of open innovation was confirmed for four factors. Third, on the industrial classification, it is confirmed that different factors have a significant influence on each industrial classification. At this point, it was confirmed that at least one factor, up to nine factors had a significant effect on the sales according to the industrial classification. Furthermore, different moderate effects have been confirmed in the industrial classification and R&D method. In the moderate effect, up to eight significant moderate effects were confirmed according to the industrial classification. In particular, 'R&D investment' and 'performance compensation system' were confirmed to be the most common moderating effect by each 12 times and 11 times in all industrial classification. This study provides the following suggestions: First, it is necessary for SMEs to determine the R&D method in consideration of the characteristics of the technology to be R&D as well as the enterprise competency and the R&D activity. In addition, there is a need to identify and concentrate on the factors that increase sales in R&D decisions, which are mainly affected by the industry classification to which the company belongs. Second, governments that support SMEs' R&D need to provide guidelines that are fit to their situation. It is necessary to differentiate the support for the company considering various factors such as technology and R&D purpose for their effective budget execution. Finally, based on the results of this study, we urge the need to reconsider the effectiveness of existing SME support policies.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.143-159
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• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.650-661
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• 2020

The digital transformation of the 4th industrial revolution is leading to changes and innovations in the global economy. Various countries are focusing on reviving their manufacturing industries and economic recovery through smart factories. The purpose of this study is to empirically identify technological determinants for the successful implementation of the smart factory and to verify teose effects on manufacturing operations and the firms' operational/environmental performances. Five factors, including sensor network, platform technology, information system, intelligent automation, and safety, were defined as core technologies. The SEM analysis results of 157 small and medium-sized manufacturing firms that have implemented smart factories are as follows. First, sensor network, platform technology, and information system had significant effects on smart manufacturing operations. Second, smart manufacturing operations have improved firm performance. This study is valuable in that it has confirmed the effectiveness of government-funded projects and systemized key technologies for implementing smart factories. Meanwhile, it is helpful for practitioners to support an efficient and effective decision-making for the new adoption.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.47-63
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• 2015

As knowledge is paid attention as a new production factor that generates added value, studies continue to apply knowledge management to business environment. In addition, as ICT (Information Communication Technology) was engrafted in business environment, it leads to increasing task efficiency and productivity of individual workers. Accordingly, the way that a business achieves its goal has changed to one in which its individual members are willing to take part in the organization and share information to create new values (Han, 2003) and studies for the system and service to support such transition are carrying out. Of late, a new concept called 'Enterprise 2.0' newly appears. It is the extension of Wen 2.0 and its technology, which focus on participation, sharing and openness, to the work environment of a business (Jung, 2013). Enterprise 2.0 is being used as a collaborative tool to prop up individual creativity and group brain power by combining Web 2.0 technologies such as blog, Wiki, RSS and tag with business software (McAfee, 2006). As Tweeter gets popular, Enterprise Microblog (EMB), which is an example of Enterprise 2.0 for business, has been developed as equivalent to Tweeter in business circle and SaaS (Software as a Service) such as Yammer was introduced The studies of EMB mainly focus on demonstrating its usability in terms of intra-firm communication and knowledge management. However existing studies lean too much towards large-sized companies and certain departments, rather than a company as a whole. Therefore, few studies have been conducted on small and medium-sized companies that have difficulty preparing separate resources and supplying exclusive workforce to introduce knowledge management. In this respect, the present study placed its analytic focus on small-sized companies actually equipped with EMB to know how they use it. And, based on the findings, this study examined their knowledge management strategies for EMB from the point of codification and personalization. Hypothesis -"as a company grows, it shifts EMB strategy from codification to personalization'- was established on the basis of reviewing precedent studies and literature. To demonstrate the hypothesis, this study analyzed the usage of EMB by small companies that have used it from foundation. For case study, the duration of the use was divided into 2 spans and longitudinal analysis was employed to examine the contents of the blogs. Using the key findings of the analysis, this study is aimed to propose practical implications for the operation of knowledge management of small-sized company and the suitable application of knowledge management system for operation Knowledge Management Strategy can be classified by codification strategy and personalization strategy (Hansen et. al., 1999), and how to manage the two strategies were always studied. Also, current studies regarding the knowledge management strategy were targeted mostly for major companies, resulting in lack of studies in how it can be applied on SMEs. This research, with the knowledge management strategy suited for SMEs, sets an Enterprise Microblog (EMB), and with the EMB applied on SMEs' Knowledge Management Strategy, it is reviewed on the perspective of SMEs' Codification and Personalization Strategies. Through the advanced research regarding Knowledge Management Strategy and EMB, the hypothesis is set that "Depending on the development of the company, the main application of EMB alters from Codification Strategy to Personalization Strategy". To check the hypothesis, SME that have used the EMB called 'Yammer' was analyzed from the date of their foundation until today. The case study has implemented longitudinal analysis which divides the period when the EMBs were used into three stages and analyzes the contents. As the result of the study, this suggests a substantial implication regarding the application of Knowledge Management Strategy and its Knowledge Management System that is suitable for SME.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.157-175
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• 2013

Since Korean government announced 'Smartwork promotion strategy' in 2010, Korean firms and government organizations have started to adopt smartwork. However, the smartwork has been implemented only in a few of large enterprises and government organizations rather than SMEs (small and medium enterprises). In USA, both Yahoo! and Best Buy have stopped their flexible work because of its reported low productivity and job loafing problems. In addition, according to the literature on smartwork, we could draw obstacles of smartwork adoption and categorize them into the three types: institutional, organizational, and technological. The first category of smartwork adoption obstacles, institutional, include the difficulties of smartwork performance evaluation metrics, the lack of readiness of organizational processes, limitation of smartwork types and models, lack of employee participation in smartwork adoption procedure, high cost of building smartwork system, and insufficiency of government support. The second category, organizational, includes limitation of the organization hierarchy, wrong perception of employees and employers, a difficulty in close collaboration, low productivity with remote coworkers, insufficient understanding on remote working, and lack of training about smartwork. The third category, technological, obstacles include security concern of mobile work, lack of specialized solution, and lack of adoption and operation know-how. To overcome the current problems of smartwork in reality and the reported obstacles in literature, we suggest a novel smartwork service model based on NFC(Near Field Communication). This paper suggests NFC-based Smartwork Service Model composed of NFC-based Smartworker networking service and NFC-based Smartwork space management service. NFC-based smartworker networking service is comprised of NFC-based communication/SNS service and NFC-based recruiting/job seeking service. NFC-based communication/SNS Service Model supplements the key shortcomings that existing smartwork service model has. By connecting to existing legacy system of a company through NFC tags and systems, the low productivity and the difficulty of collaboration and attendance management can be overcome since managers can get work processing information, work time information and work space information of employees and employees can do real-time communication with coworkers and get location information of coworkers. Shortly, this service model has features such as affordable system cost, provision of location-based information, and possibility of knowledge accumulation. NFC-based recruiting/job-seeking service provides new value by linking NFC tag service and sharing economy sites. This service model has features such as easiness of service attachment and removal, efficient space-based work provision, easy search of location-based recruiting/job-seeking information, and system flexibility. This service model combines advantages of sharing economy sites with the advantages of NFC. By cooperation with sharing economy sites, the model can provide recruiters with human resource who finds not only long-term works but also short-term works. Additionally, SMEs (Small Medium-sized Enterprises) can easily find job seeker by attaching NFC tags to any spaces at which human resource with qualification may be located. In short, this service model helps efficient human resource distribution by providing location of job hunters and job applicants. NFC-based smartwork space management service can promote smartwork by linking NFC tags attached to the work space and existing smartwork system. This service has features such as low cost, provision of indoor and outdoor location information, and customized service. In particular, this model can help small company adopt smartwork system because it is light-weight system and cost-effective compared to existing smartwork system. This paper proposes the scenarios of the service models, the roles and incentives of the participants, and the comparative analysis. The superiority of NFC-based smartwork service model is shown by comparing and analyzing the new service models and the existing service models. The service model can expand scope of enterprises and organizations that adopt smartwork and expand the scope of employees that take advantages of smartwork.