• 유통과학연구
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• 제17권8호
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• pp.87-97
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• 2019

Purpose - This study focuses on the effectiveness of the athlete endorsement on the purchase intention of customers and investigates the attributes of the athlete identification. The Athlete Identification is defined by the expertise, trustworthiness, attractiveness, toughness and transgression. Athlete identification and athlete endorsement help marketers with a thorough look at the trend of using famous sports player to promote products. Research design and methodology - 450 questionnaires were delivered to respondents in Ho Chi Minh city and 433 were returned completed. Descriptive statistics, reliability, exploratory factor analysis, confirmatory factor analysis and structural equation modeling were conducted to test the relationship between independent and dependent variables. Results - The expertise, trustworthiness, attractiveness and toughness exert positive impacts on athlete identification. Transgression affects negatively athlete identification and athlete endorsement. This research confirmed results of previous studies. Conclusions - The athlete first needs to create their own Identification from a set of attributes in order to be out-standing in the sport and leisure industry before becoming an endorser for a particular product. From the company's perspectives, decision makers should choose an acclaimed sports player to boost the purchase intention of consumers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권4호
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• pp.575-594
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• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• Smart Structures and Systems
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• 제8권4호
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• pp.343-365
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• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• 한국의류학회지
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• 제30권7호
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• pp.1126-1134
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• 2006

The purpose of this study was to examine the effect of brand identification of fashion luxury product on brand loyalty and the mediating effect of brand affect. The questionnaire developed through the literature search and a survey was conducted both in on-line and off-line questionnaire simultaneously. Finally 227 data from women who had a buying experience of fashion luxury products were analyzed using frequency, factor analysis, ANOVA, t-test, regression analysis by SPSS for WIN program. The results were as follows. First, the consumers' brand identification was composed of three factors; actual, ideal, social. Second, the brand identification significantly influenced on the brand loyalty. Third, the brand identification significantly influenced on the brand affect. Fourth, the brand affect significantly influenced on the brand loyalty. Fifth, the brand identification had both direct and indirect effects on brand loyalty mediated by brand affect. The results indicated that causal relationship was existed among these three variables.

• 경영과학
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• 제31권4호
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• pp.117-134
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• 2014

Today the concept of corporate social responsibility has become an essential element for coexistence of corporations and the society. In this study the impact of four responsibilities of business organizations proposed by Archie Carroll (economic, legal, ethical, and discretionary) on customer loyalty through the mediating effect of trust and company-consumer identification is analyzed. A questionnaire survey was conducted for four well-known Korean companies (Dong Suh Food, LG Household and Health Care, Samsung Electronics, and Hyundai Motor). After factor analysis, legal and ethical responsibilities were grouped as the same factor, thus three social responsibilities were finally used for hypotheses testing. Major findings were as follows: First, economic responsibilities had positive impact on honesty trust, professionalism trust, favorableness trust, and company-consumer identification, Second, legal/ethical responsibilities were found to have significant effects on honesty trust, favorableness trust, and company-consumer identification. Third, in the case of discretionary responsibilities, professionalism trust, favorableness trust, and company-consumer identification were revealed to have a significant positive relationship. Fourth, only two trust variables (honesty and professionalism) and company-consumer identification had positive influence on the loyalty of customers. These findings are expected to help decision makers to set up corporate objectives and choose action items for corporate social responsibility. At the last part, implications of the study and future research directions were discussed.

• 과학교육연구지
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• 제36권2호
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• pp.251-262
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• 2012

본 연구에서는 중학교 학생들의 변인 판별 및 변인 통제 능력을 신장시킬 수 있는 15가지의 학습 프로그램을 개발하고, 이를 적용하여 수업효과를 분석하였다. 변인 판별 및 통제 학습 효과를 높이기 위하여 자신의 사고 과정을 모니터하고 인지 활동 결과에 대해 객관적으로 평가할 수 있도록 구성하였다. 이 프로그램의 수업 효과를 분석한 결과, 프로그램을 투입한 실험집단이 비교집단에 비해 변인 판별 점수가 높았으며, 변인통제 논리 형성정도도 증가하였는데, 특히 변인통제 논리 형성정도가 미형성 단계인 학생들에게 효과가 크게 나타났다. 이는 우리가 개발한 학습 프로그램을 통해 학생들의 변인 판별 및 통제 능력을 향상시키는 것이 가능함을 보여준다. 또한, 변인 통제 능력 점수와 메타 인지 수준 점수 간에 정(+)적인 상관관계를 보였다. 이는 메타인지 전략이 변인 통제 능력을 유의미하게 향상시키는 효과가 있다고 할 수 있다.

• 간호행정학회지
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• 제11권4호
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• pp.371-384
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• 2005

Purpose: The aim of this study was to analysis path model of the research variables. Methods: The subjects of this study were 647 nurses who were working in the 8 general hospitals located in Seoul and Incheon area. The data were collected by self-reporting questionnaires. The data were analyzed using descriptive statistics and path analysis. Results: In the modified path model, overall fitness indexes were $X^2$= 223.27, goodness of fit index=0.90, root mean square residual=0.039, root mean square error of approximation=0.12, non-normed fit index=0.96, and normed fit index=0.90. From the model, among research variables that influence organizational effectiveness motivator, job satisfaction and organizational identification affected directly work performance. In internal marketing factors, paid-leave, communication and reward affected directly motivator. Motivator and hygiene factors affected directly job satisfaction, organizational commitment and organizational identification. Conclusion: With these findings, paid-leave, communication, reward, motivator, job satisfaction and organizational identification were direct or indirect predictors of the work performance. Therefore nursing managers ought to develop internal marketing strategies and motivation enhancing system for nurses based on this path model in order to improve the nursing organizational effectiveness.

• 산업경영시스템학회지
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• 제28권3호
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• pp.166-171
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• 2005

With development of the database, there are too many data on process variables and the manufacturing process for the traditional statistical process control methods to identify the process variables related with assignable causes. Data mining is useful in this situation and provides variety of approaches for improving the process. In this paper, we applied control charts to monitor the process and if assignable causes are detected, then we applied the SVM technique and the sequence pattern analysis to find out the process variables suspected. These techniques made possible to predict the behavior of process variables. We illustrated our proposed methods with real manufacturing process data.

• Journal of Astronomy and Space Sciences
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• 제35권1호
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• pp.19-30
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• 2018

The analysis of the high-resolution spectra of 31 Magellanic Clouds Cepheid variables enabled the identification of thorium lines. The abundances of thorium were found with spectrum synthesis method. The calculated thorium abundances exhibit correlations with the abundances of other chemical elements and atmospheric parameters of the program stars. These correlations are similar for both Clouds. The correlations of iron abundances of thorium, europium, neodymium, and yttrium relative to the pulsational periods are different in the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC), namely the correlations are negative for LMC and positive or close to zero for SMC. One of the possible explanations can be the higher activity of nucleosynthesis in SMC with respect to LMC in the recent several hundred million years.