• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.297-305
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• 2021

The study aims to investigate loyalty rewards programs on customers' satisfaction in Jordanian banks, and to investigate the statistical differences in loyalty rewards programs and customers' satisfaction according to demographics such as age, sex, education level, duration of engagement with bank, and the type of bank. The study is based on the data obtained from the sample. The questionnaire is the tool for collecting data from the respondents. The study materials include website resources, regular books, journals, and articles. The study population consists customers in the banking sector. The figures indicate that number of actual customers reaches 2.06 million. The sample size requirement is 386 items. Customers are split between traditional and Islamic banks, with 231 and 155 customers respectively. The stratified random sampling technique and the structural equations modeling methodology were used. The results show moderated impact of the loyalty rewards programs on customers' satisfaction. The results show statistical differences in the loyalty rewards programs and customers' satisfaction according to the engagement period with the bank only. The findings suggest better managing the loyalty programs and developing one credit card for all banks in Jordan.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.217-238
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• 2019

With the advent of so-called "default" Bayesian hypothesis tests, scientists in applied fields have gained access to a powerful and principled method for testing hypotheses. However, such default tests usually come with a compromise, requiring the analyst to accept a one-size-fits-all approach to hypothesis testing. Further, such tests may not have the flexibility to test problems the scientist really cares about. In this tutorial, I demonstrate a flexible approach to generalizing one specific default test (the JZS t-test) (Rouder et al., Psychonomic Bulletin & Review, 16, 225-237, 2009) that is becoming increasingly popular in the social and behavioral sciences. The approach uses two results, the Savage-Dickey density ratio (Dickey and Lientz, 1980) and the technique of encompassing priors (Klugkist et al., Statistica Neerlandica, 59, 57-69, 2005) in combination with MCMC sampling via an easy-to-use probabilistic modeling package for R called Greta. Through a comprehensive mathematical description of the techniques as well as illustrative examples, the reader is presented with a general, flexible workflow that can be extended to solve problems relevant to his or her own work.

• 한국의상디자인학회지
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• 제22권4호
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• pp.79-91
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• 2020

This research aims to study the effect of consumer ethnocentrism and animosity towards the purchase of Korean visual arts products by Chinese consumers. Total of 302 questionnaires were distributed for measuring the constructs using the online survey website (www.sojump.com). All the questionnaires were validated and tested for further statistical analysis through exploratory factor analysis (EFA) and later a confirmatory factor analysis (CFA) using SPSS 22.0 and AMOS 22.0 statistical systems. In addition, structural equation modeling technique (SEM) was applied for testing the hypotheses. Among all variables, consumer ethnocentrism plays the most negatively significant role, followed by animosity toward buying Korean products. Fortunately, there is a positive variable, cosmopolitanism, that can help mitigate the impact of this hostility, and more interesting results are described in detail in the current paper. This study has been added value between theory and practice exploring ethnocentrism and animosity effects, and more theoretical and managerial implications are discussed.

• Korean Chemical Engineering Research
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• 제61권2호
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• pp.328-339
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• 2023

Methanol steam reforming (MSR) is a promising method for hydrogen supplying as a critical step in hydrogen fuel cell commercialization in mobile applications. Modelling and understanding of the reactor behavior is an attractive research field to develop an efficient reformer. Three-layer feed-forward artificial neural network (ANN) and Box-Behnken design (BBD) were used to modelling of MSR process using the Cu-SiO₂ aerogel catalyst. Furthermore, impacts of the basic operational variables and their mutual interactions were studied. The results showed that the most affecting parameters were the reaction temperature (56%) and its quadratic term (20.5%). In addition, it was also found that the interaction between temperature and Steam/Methanol ratio is important on the MSR performance. These models precisely predict MSR performance and have great agreement with experimental results. However, on the basis of statistical criteria the ANN technique showed the greater modelling ability as compared with statistical BBD approach.

• 산업경영시스템학회지
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• 제40권4호
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• pp.46-54
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• 2017

'Consulting', which is the main research topic of the knowledge service industry, is a field of study that is essential for the growth and development of companies and proliferation to specialized fields. However, it is difficult to grasp the current status of international research related to consulting, mainly on which topics are being studied, and what are the latest research topics. The purpose of this study is to analyze the research trends of academic research related to 'consulting' by applying quantitative analysis such as topic modeling and statistic analysis. In this study, we collected statistical data related to consulting in the Scopus DB of Elsevier, which is a representative academic database, and conducted a quantitative analysis on 15,888 documents. We scientifically analyzed the research trends related to consulting based on the bibliographic data of academic research published all over the world. Specifically, the trends of the number of articles published in the major countries including Korea, the author key word trend, and the research topic trend were compared by country and year. This study is significant in that it presents the result of quantitative analysis based on bibliographic data in the academic DB in order to scientifically analyze the trend of academic research related to consulting. Especially, it is meaningful that the traditional frequency-based quantitative bibliographic analysis method and the text mining (topic modeling) technique are used together and analyzed. The results of this study can be used as a tool to guide the direction of research in consulting field. It is expected that it will help to predict the promising field, changes and trends of consulting industry related research through the trend analysis.

• Composites Research
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• 제31권5호
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• pp.251-259
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• 2018

본 논문에서는 섬유강화복합재의 멀티스케일 해석을 위해 필요한 대규모/소규모 통계적 체적요소 모델을 개발하였다. 미시영역모델의 크기효과를 최소화하기 위해서 섬유를 최대한 포함한 거대모델을 구성하였다. 이를 위해 국부 영역의 요소 절단법을 이용하여 전체 유한요소 크기에 상관없이 신속한 격자 섬유/기지의 모델링이 가능한 요소생성기를 구성하였다. 이를 통해 대규모 통계 체적 모델을 도출하여 체적모델의 크기에 따른 국부하중 공유의 차이를 고찰하고, 섬유방향의 연속체손상역학모델을 BSVEs 모델 해석으로부터 도출 하였다. BSVEs 모델을 보편적인 RVE모델과 비교 검증하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.197-202
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• 2006

The low-altitude earth observation satellite is generally equipped with high performance camera as a main payload which is vulnerable to vibration environment. During the launch process of a satellite, the combustion and jet noise of launch vehicle produce severe acoustic environment and the acoustic loads induced may damage the critical equipments of the satellite including the camera. Therefore to predict and simulate the effect of the acoustic environment which the satellite has to sustain at the lift-off event is very important process to support the load-resistive design and test-qualification of components. Statistical Energy Analysis(SEA) has been widely used to estimate the vibro-acoustic responses of the structures and gives statistical but reliable results in the higher frequency region with less modeling efforts and calculation time than the standard FEA. In this study, SEA technique has been applied to a 3-Dimensional model of a low-altitude earth observation satellite to predict the acceleration responses on the structural components induced by the high level acoustic field in the launch vehicle fairing. In addition, the expected response on each critical component panel was calculated by the classical method in consideration of the mass loading and imposed sound pressure level, and then compared with SEA results.

• 화약ㆍ발파
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• 제38권3호
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• pp.15-29
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• 2020

본 논문에서는 Hoek-Brown (HB) 파괴기준을 Holmquist-Johnson-Cook (HJC) 콘크리트 재료모델에 접목시킴으로써 LS-DYNA 상에서 암반발파를 모델링할 때 현장암반의 고유한 특성이 잘 반영될 수 있도록 도모하였다. 이것은 많은 지질학적 불연속면을 포함하고 있는 현장암반이 지니고 있는 독특한 특징을 강조하기 위함이다. 두 모델의 접목은 HB 파괴기준으로 HJC 재료모델의 정적 강도 부분을 교체함으로써 이루어지며, 교체과정은 통계학적 곡선적합 기법에 의해 수행된다. 본 논문에서는 접목의 과정이 상세하게 소개되며, 획득된 HJC 재료모델의 사용에 대한 실례도 제시된다. 제시된 수치계산은 현장의 석회암 암반의 단일공 발파에 대한 평면변형률 모델링으로서 LS-DYNA가 제공하는 유체-구조물 상호작용(FSI) 기법과 다중재료 라그랑주-오일러(MMALE) 정식화 기법을 조합하여 수행된다.

• 한국분무공학회지
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• 제20권4호
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• pp.247-253
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• 2015

Recently, the engine calibration technique has been much more complicated than that of the past engine case in order to satisfy the strict emission regulations. The current calibration method for the diesel engine which has an increasing market is both costly and time-consuming. New engine calibration method is required to develop for high-quality diesel engines with low cost and release it at the appropriate time. This study provides the optimal calibrating technique for complex engine systems using statistical modeling and numerical optimization. Firstly, it design a test plan based on Design of Experiments, a V-optimality methodology which is suitable looking for set-points, and determine the shape of test engine response. Secondly, it uses functions to make linear regression model for data analysis and optimization to fit the models of engines behavior. Finally, it generates the optimal calibrations obtained directly from empirical engine models using Grey Relational Analysis and compares the calibrations with data. This method can develop a process for systematically identifying the optimal balance of engine emissions.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.963-971
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• 2021

This study aims to determine the effect of financial literacy and taxation on competitive advantage, in order to determine the effect of financial literacy and taxation on the performance of MSMEs, and to determine the effect of competitive advantage on the performance of MSMEs. This study uses primary data through a questionnaire. The population is Creative MSME actors in DIY. Creative MSMEs in Yogyakarta were chosen because Yogyakarta is an area that is rich in traditional culture and various characters of its inhabitants, thus encouraging the development of the potential of Creative MSMEs. This research uses primary data sources on Creative MSMEs in Yogyakarta. The samples were determined by the proportional simple random sampling technique; taking a sample of 20% of the total Creative MSMEs in each district/city. The samples that deserve to be respondents in this study were 210 samples of Creative MSMEs actors in DIY. The statistical technique for analyzing data is the AMOS Structural Equation Modeling (SEM). The results showed that financial literacy had an effect on the competitive advantage and performance of MSMEs, tax literacy had an effect on competitive advantage, competitive advantage had an effect on the performance of MSMEs. However, tax literacy has no effect on the performance of MSMEs.