Generally, a software development process is composed with requirements analysis, design, coding, test and maintenance. However, some changes of the design step are difficult to complicate the next step in the development process. It always causes the disagreement between design and implementation step. In this paper, we have developed a tool which can generate an application program. The tool can reduce the disagreement between system design and implementation and recognize the business logic to develop the software rapidly and flexibly In addition, we proposed a non-program-based application program system approach was proposed, In. We can generate and modify an application program with this method which can edit the meta data of a system design by the dynamic method for the execution time.
Park, Chulho;Han, Joon;Ku, Jisun;Lee, Sanghoon;Lee, Hakyeon
Journal of Korean Institute of Industrial Engineers
/
v.43
no.1
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pp.49-61
/
2017
This paper proposes an R&D project selection methodology for green technology centered on developing country-oriented technology commercialization. Eight selection criteria are derived from the R&BD logic model : technology needs of developing countries, effectiveness of green technology, technological potentials, domestic technological capability, commercialization feasibility, economic benefits, business feasibility, and spillover effects of developing countries. 21 qualitative and quantitative indicators are then defined for each criterion. The analytic hierarchy process is conducted to produce relative importance of evaluation indicators and to set final priority scores of R&D project candidates. The working of the proposed methodology is provided with the help of a case study example of Green Technology Center. The proposed methodology is expected to be effectively utilized for policy practices of R&D project selection in the field of green technology.
Firms can create additional customer values by changing the visibility characteristic of business transactions. Both visible and invisible transactions can provide distinctive values to the customers. Visible transactions are those that are open to the customer: the customer can see the detailed logic of the transaction and may manipulate specific variables to control the transaction process. Invisible transactions mean that customers have little ability to control the transaction flow and may even be insulated from seeing the transaction. These invisible transactions will be taken care of only by suppliers, and be regarded as a process performed by suppliers. This paper pursues finding out the contingencies of successful transaction visibility change by answering to the following question; "when does increasing(or decreasing) transaction visibility make sense to customers?" This archival case study finds out that transaction visibility change should fit to the need and capabilities of customers. Increasing transaction visibility makes sense when customers need a certain supplier's performance and have a confidence in the capabilities of executing the performance. By the same token, decreasing transaction visibility makes sense when customers have substantial troubles in conducting their current transaction actions or when customers don't feel it necessary to conduct them separately because they can be derived from other action.
NGUYEN, Phong Thanh;HUYNH, Vy Dang Bich;NGUYEN, Quyen Le Hoang Thuy To
The Journal of Asian Finance, Economics and Business
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v.8
no.2
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pp.195-200
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2021
In recent years, Vietnam's economic growth rate has been attributed to the growth of many well-managed industries within Southeast Asia. Among them is the civil construction industry. Construction projects typically take a long time to complete and require a huge budget. Many socio-economic variables and factors affect total construction project costs due to market fluctuations. In recent years, crucial socioeconomic development indicators of construction reached a fairly high growth rate. Also, most infrastructure and construction projects have a high degree of complexity and uncertainty. This makes it challenging to predict the accurate project price. These challenges raise the need to recognize significant factors that influence the construction price index of civil buildings in Vietnam, both micro and macro. Therefore, this paper presents critical factors that affect the construction price index using the fuzzy extent analysis process in an uncertain environment. This proposed quantitative model is expected to reflect the uncertainty in the process of evaluating and ranking the influencing factors of the construction price index in Vietnam. The research results would also allow project stakeholders to be more informed of the factors affecting the construction price index in the context of Vietnam's civil construction industry. They also enable construction contractors to estimate project costs and bid rates better, enhancing their project and risk management performance.
Journal of Korean Society of Industrial and Systems Engineering
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v.43
no.2
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pp.98-109
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2020
What is purchase motivation for luxury brands? and what kind of process through makes higher cult intention(i.e.,loyalty). How does consumption value affect loyalty? Theoretically, it was studied whether it could be explained. The luxury products and services were divided into categories and surveys were conducted at the national level. This research analyzed the influence of positive affect on cult intention by mediating luxury consumption value with S-O-R frame. The logic was developed with excitation transfer theory. Positive affect, compatibility mediating effect were investigated. Unlike the previous studies that have been recognized as important in terms of symbolic value in luxury brands, it was confirmed that experiential consumption value had the greatest impact. In addition, the influence of functional value and symbolic value had a significant effect. The effect of consumption value on cult intention was mediated by positive affect and compatibility. Therefore, emotional response can be seen as having an effect on cult intention through excitement transfer. These findings suggest that luxury brand marketers need to develop consumer values that can lead to arousal and positive emotional responses to suit consumer lifestyle. The research results are expected to contribute to the experience marketing and the hospitality service of luxury brands.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.7
no.7
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pp.691-700
/
2017
International sports events is one of the core products in the sports industry the scale of sports event business is steadily increasing. However, In terms of sports event management, knowledge and experience generated through sports events are ineffective and non-systematically managed. For this reason, unnecessary resources are wasted and trial and error are repeated in hosting, preparing and operating in sports event management. The purpose of this study is to develop a sports event management process and evaluate conformance. To accomplish the purpose of this study, developed the core processes of sports events in step by step and then applied and conformance evaluated of the designed process. Developed and evaluated sports events management processes are five Functional Area of registration, accommodation, transport, broadcasting, and food and beverage. Of these FA, 63 activities were selected and analyzed. The modeling was used as IDEF method, the conformity analysis was used as Fuzzy logic, analysis tool was used ProM.
In modern distributed enterprise applications that have multilayered architecture, business entities are a kind of crosscutting concerns running through service components that implements business logic in each layer. When business entities are modified, service components related to them should also be modified so that they can deal with those business entities with new types, even though their functionality remains the same. Our previous paper proposed what we call the DTT (Data Type-Tolerant) component model to efficiently process the variability of business entities, which are data externalized from service components. While the DTT component model, by removing direct coupling between service components and business entities, exempts the need to rewrite service components when business entities are modified, it incurs the burden of implementing data type converters that mediate between them. To solve this problem, this paper proposes a method to use ontology as the metadata of both SCDTs (Self-Contained Data Types) in service components and business entities, and a method to generate data type converter code using the ontology. This ontology-based DTT component model greatly enhances the reusability of service components and the efficiency in processing data variability by allowing the computer to automatically generate data type converters without error.
In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.
NGUYEN, Quyen Le Hoang Thuy To;NGUYEN, Du Van;CHU, Ngoc Nguyen Mong;TRAN, Van Hong
The Journal of Asian Finance, Economics and Business
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v.7
no.11
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pp.1049-1057
/
2020
The shift from elite education to mass education in Vietnam has met the demand for education for everybody as well as for quality human resource talent for an emerging nation. Under the resource constraint, understanding the quality dimensions of education and its priority level is important for effective and efficient policies. This study was carried out using both qualitative and quantitative methodologies to develop quality criteria and a ranking model. Two rounds of in-depth interviews were conducted with fifteen experts in the field, who were rectors, employers, and recruitment specialists to develop the quality framework applied in Vietnamese universities under total quality management (TQM), starting from the input of the senior secondary school leavers, through a teaching process to the output. The first round of interviews were unstructured questionnaires designed to explore the main factors in quality assessment model. The second round affirmed the experts' agreement on the assessment model. Then, fuzzy logic was applied to rank eight criteria in the quality assessment model into priority order: cost, teaching and administrative staff, leadership, curriculum, student-related factors, internationalization, admissions, and campus. The results are critical for identifying the necessary actions to enhance the education quality and to further research on the optimal quality model.
Kumar, Rajeev;Ansari, Md Tarique Jamal;Baz, Abdullah;Alhakami, Hosam;Agrawal, Alka;Khan, Raees Ahmad
KSII Transactions on Internet and Information Systems (TIIS)
/
v.15
no.1
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pp.240-263
/
2021
One of the biggest challenges that the software industry is facing today is to create highly efficient applications without affecting the quality of healthcare system software. The demand for the provision of software with high quality protection has seen a rapid increase in the software business market. Moreover, it is worthless to offer extremely user-friendly software applications with no ideal security. Therefore a need to find optimal solutions and bridge the difference between accessibility and protection by offering accessible software services for defense has become an imminent prerequisite. Several research endeavours on usable security assessments have been performed to fill the gap between functionality and security. In this context, several Multi-Criteria Decision Making (MCDM) approaches have been implemented on different usability and security attributes so as to assess the usable-security of software systems. However, only a few specific studies are based on using the integrated approach of fuzzy Analytic Network Process (FANP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) technique for assessing the significant usable-security of hospital management software. Therefore, in this research study, the authors have employed an integrated methodology of fuzzy logic, ANP and TOPSIS to estimate the usable - security of Hospital Management System Software. For the intended objective, the study has taken into account 5 usable-security factors at first tier and 16 sub-factors at second tier with 6 hospital management system softwares as alternative solutions. To measure the weights of parameters and their relation with each other, Fuzzy ANP is implemented. Thereafter, Fuzzy TOPSIS methodology was employed and the rating of alternatives was calculated on the foundation of the proximity to the positive ideal solution.
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