• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.277-286
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• 2019

The study aims to analyze the influence of egoistic, altruistic and biospheric value on green functional benefit, green monetary cost, green satisfaction and green loyalty. The study analyzes the effect of green functional benefit and green monetary cost on green satisfaction and green loyalty, as well as green satisfaction on green loyalty. The study employs quantitative methods with customers who have green brand purchase experience in Indonesia. Non-probability sampling was conducted using purposive sampling method based on predetermined criteria, which are customers who have already purchase and use green brand products. A total of 402 samples were analyzed using Structural Equation Modelling. The result shows that the data support hypotheses on egoistic and biospheric value, hypotheses on green functional benefit effect to green satisfaction and green loyalty, as well as green monetary cost effect to green loyalty. The other hypotheses are not supported by data. As a conclusion, it is egoistic and biospheric value that has positive effect on green loyalty, while green functional benefit and green monetary cost act as mediation between the value orientation and green loyalty. As managerial implication, green brand marketing strategy should incorporate egoistic and biospheric values in messages in advertising and promotion.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.143-150
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• 2021

This study aims to determine (1) the inhibiting factors and solutions in the development of eco-tourism, and (2) how green entrepreneurship can be used for eco-tourism development. The increasing issue of global warming is pushing awareness of environmental preservation. This condition changes the people's paradigm in traveling from the concept of mass-tourism to the concept of eco-tourism. The development of eco-tourism has consequences for entrepreneurial activities which is known as green entrepreneurship. This study is applied research conducted in East Lombok, one of the regions in Indonesia. The sampling technique used is purposive sampling covering a total of 34 informants. Data collection methods are carried out through interviews, observation, and documentation studies. Based on the data analysis, the findings of this study show that (a) inhibiting factors of eco-tourism development are limitation of eco-tourism knowledge, lack of awareness in environmental preservation, and absence of supporting government policy; and (b) solution for eco-tourism development discovered in this research is divided into five factors i.e., condition, demand, related industry and support, strategy, government. Besides, for applying the green entrepreneurship model i.e., developing the spirit of green entrepreneurship, training in making products and services that are environmentally friendly is needed.

• International Journal of Contents
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• v.15 no.2
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• pp.59-74
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• 2019

The objective of this study was to analyze the influence of physical education classes based on Flipped Learning on self-directed learning abilities and learning attitude towards these classes, for middle school students. The study selected 90 students as an experimental group (3 classes) and 97 students as a control group (3 classes), among 240 students of the first-year students attending a middle school located at Jeonju City of South Korea, applying convenience sampling, one of the non-probability sampling methods. For the experimental group, 36 sessions of physical education classes were held for 14 weeks, while the control group received teacher-centered classes. Comparing the results with the control group, the experimental group showed significant differences in terms of all sub factors of self-directed learning abilities, namely; desire for learning, learning objective establishment, basic self-management abilities, selection of learning strategy and self-reflection. Moreover, the experimental group manifested significant differences in terms of all sub factors of attitude towards the physical education subjects, namely; positive emotions, negative emotions, health & physical strength, interpersonal relations, physical activities & movements, and active participation & positive performance. From the findings, it can be considered that physical education classes based on Flipped Learning contributed to improving self-directed learning abilities and attitude towards physical education classes. This result can serve as a significant basic material for designing and performing classes in raising the understanding of Flipped Learning and effectively applying Flipped Learning in physical education classes.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.443-450
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• 2021

The paper investigates the factors that affect the decision of young Chinese consumers to buy high-end cosmetics. The study is based on the responses obtained by questionnaires from 400 respondents in Guangzhou, China. The information was collected and classified on the basis of gender, occupation, age and education in order to understand the main characteristics of the sample in a better way. The purposive, convenient and quota sampling techniques of non-probability sampling method were used. Besides this, the predictive test was carried out with 30 respondents to ensure the reliability and validity of the questionnaires. The data was put to descriptive statistical analysis and multiple regression analysis in order to verify the hypotheses. The data revealed that, while brand awareness does not affect the consumer attitude about the high-end cosmetics, other factors like product involvement, perceived quality, subjective norm, and word-of-mouth have significant effect on consumer's attitude and consumers' intention about high-end cosmetics. The findings of the study show that subjective norm, perceived value, word-of-mouth, and consumer attitude of cosmetic products highly affect consumers purchase intention of high-end cosmetic products. The research paper helps to form concrete and effective marketing strategy based on various aspects of consumer behavior for high-end cosmetics in China.

• The Journal of Industrial Distribution & Business
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• v.13 no.11
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• pp.1-10
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• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.49-55
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• 2021

Recently, with the development of database, it is possible to store a lot of data generated in finance, security, and networks. These data are being analyzed through classifiers based on machine learning. The main problem at this time is data imbalance. When we train imbalanced data, it may happen that classification accuracy is degraded due to over-fitting with majority class data. To overcome the problem of data imbalance, oversampling strategy that increases the quantity of data of minority class data is widely used. It requires to tuning process about suitable method and parameters for data distribution. To improve the process, In this study, we propose a strategy to explore and optimize oversampling combinations and ratio based on various methods such as synthetic minority oversampling technique and generative adversarial networks through genetic algorithms. After sampling credit card fraud detection which is a representative case of data imbalance, with the proposed strategy and single oversampling strategies, we compare the performance of trained classifiers with each data. As a result, a strategy that is optimized by exploring for ratio of each method with genetic algorithms was superior to previous strategies.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.377-387
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• 2012

The purpose of this study is to investigate the relationship between self leadership and empowerment and organization innovation action in private security guard. This study established private security guards who is being located in Seoul, 2011 and work in the private security company by population. Using purposive sampling method, 293 samples were drawn and were used for the final analysis. Using SPSSWIN 18.0, frequency analysis, factor analysis, reliability analysis, multiple regression analysis and path analysis were performed. Cronbach's ${\alpha}$ value which shows the reliability of the questionnaire came out to be over .831. The conclusion is following. First, private security guard's self leadership affects to empowerment. That is, influence and semanticity are enlarged as action center strategy, natural compensation strategy is attained well. Also, capacity, self decision power is enlarged as constructive thinking strategy, natural compensation strategy is attained well. Second, private security guard's self leadership affects to organization innovation action. In other words, innovation action is increased as action center strategy is attained well. Also, organization's innovation result is enlarged as constructive thinking strategy, action center strategy, natural compensation strategy are attained well. Third, private security guard's empowerment affects on organization innovation action. That is, innovation action, innovation result appears high in case of influence, semanticity is enlarged. Fourth, private security guard's self leadership exerts direction indirect effect in empowerment and organization innovation action. Thus, empowerment is an important variable that mediate self leadership and organization innovation action.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.3
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• pp.147-154
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• 2011

Decision making in Environmental Impact Assessment (EIA) and Consultation on the Coastal Area Utilization (CCAU) is footing on the survey reports, thus requires concrete and accurate information on the natural habitats. In spite of the importance of reporting the ecological quality and status of habitats, the accumulated knowledge and recent techniques in ecology such as the use of investigated cases and indicators/indices have not been utilized in evaluation processes. Even the EIA report does not contain sufficient information required in a decision making process for conservation and development. In addition, for CCAU, sampling efforts were so limited that only two or a few stations were set in most study cases. This hampers transferring key ecological information to both specialist review and decision making processes. Hence, setting the effective number of sampling stations can be said as a prior step for better assessment. We introduced a few statistical techniques to determine the number of sampling stations in macrobenthos surveys. However, the application of the techniques requires a preliminary study that cannot be performed under the current assessment frame. An analysis of the spatial configuration of sampling stations from 19 previous studies was carried out as an alternative approach, based on the assumption that those configurations reported in scientific journal contribute to successful understanding of the ecological phenomena. The distance between stations and number of sampling stations in a $4{\times}4$ km unit area were calculated, and the medians of each parameter were 2.3 km, and 3, respectively. For each study, approximated survey area (ASA, $km^2$) was obtained by using the number of sampling stations in a unit area (NSSU) and total number of sampling stations (TNSS). To predict either appropriate ASA or NSSU/TNSS, we found and suggested statistically significant functional relationship among ASA, survey purpose and NSSU. This empirical approach will contribute to increasing sampling effort in a field survey and communicating with reasonable data and information in EIA and CCAU.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5015-5038
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• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.