• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.560-581
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• 2007

The purpose of this paper is to present a conceptual framework and a stage of development of trust building and to study the factors affecting on the trust building in economics space. Conceptual framework on trust building in economics space is combined of in the three approaches. The macro(structural and institutional) approach includes normative and regulative factors(laws, norms), and positionality in social and economic systems(beliefs, political ideologies, institutions). The meso(intersubjective) approach contains the personal fronts(expressive factors, social cues, significant symbols) and settings(physical space, intermediary such as technologies & knowledges). The micro(subjective) approach comprises the willingness(internalization of value) and calculation(risk and uncertainties analysis) of economic actors. According to sustainable cooperation among economic actors, trust building to the macro(structural and institutional) level, the meso(intersubjective) level, and the micro(subjective) level develop by stages. The factors such as long-term and repeated interaction, information sharing and reciprocity, interdependence and asset specificity, uncertainty, proximity, and culture & norm of corporate and formal institution are determinants on the trust building across economic actors in economic space.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.447-462
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• 2021

In insurance, the surrender rate is an important variable that threatens the sustainability of insurers and determines the profitability of the contract. Unlike other actuarial assumptions that determine the cash flow of an insurance contract, however, it is characterized by endogenous variables such as people's economic, social, and subjective decisions. Therefore, a microscopic approach is required to identify and analyze the factors that determine the lapse rate. Specifically, micro-level characteristics including the individual, demographic, microeconomic, and household characteristics of policyholders are necessary for the analysis. In this study, we select panel survey data of Korean Retirement Income Study (KReIS) with many diverse dimensions to determine which variables have a decisive effect on the lapse and apply the lasso regularized regression model to analyze it empirically. As the data contain many missing values, they are imputed using the random forest method. Among the household variables, we find that the non-existence of old dependents, the existence of young dependents, and employed family members increase the surrender rate. Among the individual variables, divorce, non-urban residential areas, apartment type of housing, non-ownership of homes, and bad relationship with siblings increase the lapse rate. Finally, among the financial variables, low income, low expenditure, the existence of children that incur child care expenditure, not expecting to bequest from spouse, not holding public health insurance, and expecting to benefit from a retirement pension increase the lapse rate. Some of these findings are consistent with those in the literature.

• Journal of Korean Library and Information Science Society
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• v.30 no.2
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• pp.55-75
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• 1999

Although the importance of research methodoogy in library and information science(LIS) has been widely recognized, LIS has been also criticized that current research methodology in the field maintains only the positivistic orientation. Researchers on the other hand, assert that US should be studied as a human study, a subjective approach based on a phenomenological perspective, since US has very much to do. with the 'human factor,' with subjectivity in the form of librarian, patron, and administrator. In this paper, a review of the published qualitative research in the field which try to generate theories from the subjects in their own everyday life situation, attempts to shed light on the implication of a new terrain of everyday life research to US. Theory of everyday life is generated by the subjects who are involved in the social relationship, using their own language. It is a theory which shows the logic of the real world in which the everyday man recognize, act and communicate. This includes the perceptions, feelings, and meanings members experience as well as the 'small world' they create in process. Everyday life research performed using qualitative research methods which have strength to investigate this micro-structure applied to the field of library and information science, may bring enrichment to the library and information science research.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.555-567
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• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.