• Archives of design research
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• v.15 no.1
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• pp.319-326
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• 2002

This study is clarifying the relationship between domain and in-house design based on the perspective on organization and task of a design organization. Accordingly, the growth and expansion of organization requires a new strategy in respect of design sector and business domain. It is a guideline for developing advanced business domain and design management in the limited strategic system of design department to analyze relatively the structural model of design, and to seek for any feasibility of strategic application. And this study comes to be basic data for defining the relationship between domain and in-house design. Consequently, both of strategic design management to back up the task of design organization and the module to support the design planning should be flexibly systemized.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.461-472
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• 2020

In recent decades, the research field of entrepreneurship phenomenon has significantly increased in both quantity and sophistication. In Vietnam, paradoxically, while creating a new business venture has become a tendency, the interest in studying entrepreneurs seems not to be thoroughly investigated. This research aims to evaluate the factors that affect the entrepreneurial intention of information technology (IT) students in Vietnam. The authors make use of mixed methods including both quantitative research method and qualitative research method. The qualitative research method is employed to identify meanings, confirmations, adjustments, and compliments for concept-measurement variables in the conceptual model. Quantitative research is conducted from a sample of 424 IT senior students across many universities in Vietnam. Questionnaires have been sent to students to evaluate the measurement scale and appropriateness of the research model. Results from multiple regression highlighted five independent variables affecting the dependent variable, the entrepreneurial intention, in a descending order as following: entrepreneurial educational environment, personal characteristics, perception of feasibility, entrepreneurial supports, and financial accessibility. In addition, this research has proved that the variable attitudes towards entrepreneurship partially mediated among the interrelationship of the aforementioned variables. From this research, the authors make some recommendations to enhance entrepreneurial intentions of IT students in Vietnam.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.213-216
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• 2015

Despite the significant increase of Korean contractors in the international construction market, many SMCCs (Small & Medium Construction Companies) have suffered in the global financial crisis, and some of them have been kicked out of the international market after experiencing huge losses on projects. SMCCs face obstacles in the international market, such as an insufficient ability to gather information and inappropriate management of associated risks, which lead to difficulties in establishing effective business strategies. In other words, making immature decisions without an effective business strategy may cause not only the failure of one project but also the bankruptcy of the SMCC. To overcome this, the research presented herein aims to propose a decision support system for SMCCs, which would screen projects and make a go/no-go decision at the early stages of international projects. The proposed system comprises a double axis: (1) a profit prediction model, which evaluates 10 project properties using an objective methodology based on a historical project performance database and roughly suggests expected profit rate, and (2) a feasibility assessment model, which evaluates 17 project environment factors in a subjective and quantitative methodology based on experience and supervision. Finally, a web-based system is established to enhance the practical usability, which is expected to be a good reference for inexperienced SMCCs to make proper decisions and establish effective business strategies.

• Journal of Technology Innovation
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• v.25 no.1
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• pp.35-60
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• 2017

In this study, the effects of Venture Start-up's Technological Capabilities on Financial Stability and Possibility of Insolvency was investigated by use of SEM(Structural Equation Model). Technological Business Capabilities include CEO's Technological Capability, Management Specialization and the Feasibility of the Investment plan. The empirical data for this study were taken from the technology assessment data of Korea Technology Guarantee Fund(KTGF) on 1,419 Venture Start-ups from 2011 until 2012 and the financial data of the following 2 years of the sample. Venture Start-ups established within 7 years, were selected for this study's sample from viewpoint of their 'High-Risk High-Return' characteristic. The results are as follows : Manpower including CEO's Technology-related Knowledge and Experience, Management Organization's Technological Specialization and Cooperativeness, Reasonable Investment and Financing Planning etc. were proved to improve Financial Stability, and therefore reduce Possibility of Insolvency.

• The Journal of Information Systems
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• v.27 no.2
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• pp.1-28
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• 2018

Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.161-170
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• 2023

In this study, based on existing studies on music streaming services and e-services, the selection factors for music streaming platforms were derived, and the AHP technique was implemented to calculate the importance of each factor. As a result of this study, economic feasibility was found to be the most important factor among security, economic feasibility, informativeness, convenience, and responsiveness, which are the first-step selection factors of music streaming platforms. As a result of synthesizing the weights of the first and second factors, reasonable price was found to be the most important factor. Finally, an additional analysis was conducted to determine whether there was a difference in importance between the selection factors of the music streaming platform according to gender and age. Through this study, it will be possible to figure out the factors that consumers consider most important when using a music streaming platform.

• Journal of Cadastre & Land InformatiX
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• v.45 no.1
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• pp.75-97
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• 2015

Recently public institutions' debt is growing therefore it became an important issue to the level that the government concerns about the possibility of financial burden to reduce the debt. Especially debt of public enterprises in metropolitan areas was in a serious state where debt in late 2013 was 43.2 trillion, which takes approx. 58.4% of 73.9 trillion of debt of all local public enterprises. Sound financial state of local public enterprises is important to public enterprises in metropolitan areas and it may affect seriously financial stability of local governments when public enterprises have financial problems. However, land supply business to form local industrial complexes or local demand for development of public rental housing business always exist; and vitalizing local economy and creating jobs through these businesses are very necessary to develop the areas. However, for local economic development, industirial land business and public rental housing business are needed. In this study, Gwangju Metropolitan City Corporation Ltd is used as a case study to evaluate the local public financial soundness via debt management assessment i.e.(using) the feasibility analysis in the urban development and housing development. As an improvement measure following the result of analysis, for the enhancement of financial soundness of urban innovation corporation, the government and local government shall evaluate and differentiate market demand, price competitiveness, and infrastructure of new town land development project to improve accuracy of project feasibility analysis. Another important insight is that there should be local government-centered management of liabilities of the local government and local public enterprises with the integrated liability management system to reduce the liability of the corporation and solve the issue of debts for local government. This study is significant in that it has analyzed cases from the theoretical aspect to secure financial soundness of national and local public enterprises.

• Korean Journal of Construction Engineering and Management
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• v.14 no.2
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• pp.131-140
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• 2013

Econometric forecast models based on past time-series data have been applied to a wide variety of applications due to their advantages in short-term point estimating. These models are particularly used in predicting the impact of governmental research and development (R&D) programs because program managers should assert their feasibility due to R&D program's huge amount of budget. The construction governmental R&D programs, however, separately make an investment by dividing total budget into five sub-business area. It make R&D program managers difficult to understand how R&D programs affect the whole system including economy because they are restricted with regard to many dependent and dynamic variables. In this regard, system dynamics (SD) model provides an analytic solution for complex, nonlinear, and dynamic systems such as the impacts of R&D programs by focusing on interactions among variables and understanding their structures. This research, therefore, developed SD model to capture the different impacts of five construction R&D sub-business by considering different characteristics of sub-business area. To overcome the SD's disadvantages in point estimating, this research also proposed the method for constructing quantitative forecasting model using qualitative data. Understanding the different characteristics of each construction R&D sub-business can support R&D program managers to demonstrate their feasibility of capital investment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.115-125
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• 2024

This study defined the appraisal items of technology appraisal for investment as innovation characteristics and derived the determining factors for predicting high-growth companies. Through this, we presented a direction for improving the technology appraisal model for investment. High-growth companies were classified into high-growth companies in sales, high-growth companies in operating profit, and high-growth companies in both sales and operating profit. At this time, the concept of a gazelle company was applied and defined as a company with an average growth rate of 20% or more over three years after the appraisal year. As for the analysis results, in terms of technicality (appraisal items), it was significant in predicting high-growth companies in sales and high-growth companies in sales and operating profit. Therefore, it will be possible to increase the discrimination power of predictions by strengthening the technicality (appraisal items). On the other hand, the business feasibility (appraisal items) was significant in predicting high-growth companies in sales and high-growth companies in sales and operating profit, but in a negative direction. This is due to the composition and criteria of the business feasibility (appraisal items), and it was concluded that changes to the composition and criteria for the relevant items are necessary for future model improvement.