• 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.

• Tuberculosis and Respiratory Diseases
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• v.44 no.4
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• pp.785-795
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• 1997

Background : Tumor markers have been used in diagnosis, predicting the extent of disease, monitoring recurrence after therapy and prediction of prognosis. But the utility of markers in lung cancer has been limited by low sensitivity and specificity. TPA-M is recently developed marker using combined monoclonal antibody of Cytokeratin 8, 18, and 19. This study was conducted to evaluate the efficacy of new tumor marker, TPA-M by comparing the estabilished markers SCC, CEA, Cyfra21-1 in lung cancer. Method : An immunoradiometric assay of serum CEA, sec, Cyfra21-1, and TPA-M was performed in 49 pathologically confirmed lung cancer patients who visited Keimyung University Hospital from April 1996 to August 1996, and 29 benign lung diseases. Commercially available kits, Ab bead CEA (Eiken) to CEA, SCC RIA BEAD (DAINABOT) to SCC, CA2H (TFB) to Cyfra2H. and TPA-M (DAIICHI) to TPA-M were used for this study. Results : The mean serum values of lung cancer group and control group were $10.05{\pm}38.39{\mu}/L$, $1.59{\pm}0.94{\mu}/L$ in CEA, $3.04{\pm}5.79{\mu}/L$, $1.58{\pm}2.85{\mu}/L$ in SCC, $8.27{\pm}11.96{\mu}/L$, $1.77{\pm}2.72{\mu}/L$ in Cyfra21-1, and $132.02{\pm}209.35\;U/L$, $45.86{\pm}75.86\;U/L$ in TPA-M respectively. Serum values of Cyfra21-1 and TPA-M in lung cancer group were higher than control group (p<0.05). Using cutoff value recommended by the manufactures, that is $2.5{\mu}/L$ in CEA, $3.0{\mu}/L$ in Cyfra21-1, 70.0 U/L in TPA-M, and $2.0{\mu}/L$ in SCC, sensitivity and specificity of lung cancer were 33.3%, 78.6% in CEA, 50.0%, 89.7% in Cyfra21-1, 52.3%, 89.7% in TPA-M, 23.8%, 89.3% in SCC. Sensitivity and specificity of nonsmall cell lung cancer were 36.1%, 78.1% in CEA, 50.1%, 89.7% in Cyfra21-1, 53.1%, 89.7% in TPA-M, 33.8%, 89.3% in SCC. Sensitivity and specificity of small cell lung cancer were 25.0%, 78.5% in CEA, 50.0%, 89.6% in Cyfra21-1, 50.0%, 89.6% in TPA-M, 0%, 89.2% in SCC. Cutoff value according to ROC(Receiver operating characteristics) curve was $1.25{\mu}/L$ in CEA, $1.5{\mu}/L$ in Cyfra2-1, 35 U/L in TPA-M, $0.6{\mu}/L$ in SCC. With this cutoff value, sensitivity, specificity, accuracy and kappa index of Cyfra21-1 and TPA-M were better than CEA and SCC. SCC only was related with statistic significance to TNM stages, dividing to operable stages(TNM stage I to IIIA) and inoperable stages (IIIB and IV) (p<0.05). But no tumor markers showed any correlation with significance with tumor size(p>0.05). Conclusion : Serum TPA-M and Cyfra21-1 shows higher sensitivity and specificity than CEA and SCC in overall lung cancer and nonsmall cell lung cancer those were confirmed pathologically. SCC has higher specificity in nonsmall cell lung cancer. And the level of serum sec are signiticantly related with TNM staging.