• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Fashion & Textile Research Journal
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• v.21 no.6
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• pp.743-753
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• 2019

This study investigates differences in demographic characteristics, shopping orientation, perceived risk, and satisfaction after purchase among consumer types. This study classifies consumer types according to their channel transition behaviors between the online and offline channels with a focus on the steps of information research and buying decision in buying decision-making process. The four consumer groups are as follows: off-off type (offline research-offline purchase), on-on type (online research-online purchase), on-off type (online research-offline purchase) and on/off-off type (online and offline research-offline purchase), off-on type (offline research-online purchase) and on/off-on type (online and offline research-online purchase). Data were collected from adults over 20 years old who had bought clothes within one year. The questionnaire was carried out from July, 2019 using a professional internet research panel; in addition, 500 sets of useful data were analyzed by descriptive statistics, factor analysis, reliability analysis, chi-squared test, ANOVA and Duncan-test using SPSS 21.0. The findings showed significant differences among the classified consumer groups for consumer demographics, shopping orientation, perceived risk, and purchase after satisfaction. The results imply that consumers show a variety of channel transition behaviors based on demographic variables, shopping orientation, and perceived risk. Understanding and adapting to consumer purchase behaviors will allow company distribution channels to be effectively managed and eventually increase consumer satisfaction as well as company sales volume.

• Journal of the Ergonomics Society of Korea
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• v.23 no.2
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• pp.37-54
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• 2004

Fuzzy theory provides an intelligence treatment model for judgement about information when it needs a solution or a decision making about vague problems. Therefore, fuzzy theory is used for appropriate evaluation and decision on obscure information as human's emotion in human factors, In previous study, fuzzy membership function is defined for judgement infOlmation as human's emotion then ultimate results are deducted through fuzzy inference model. This method uses general CWTent through literature review or max, min and average as representative statics value about considering variables. But, this method makes away with nonlinear's or inegular's factors of human sensibility. Accordingly, application of this method leads to considerable loss of information in the ultimate evaluation. For that reason, this method has a limitation in objective evaluation of human factors. So, this study focuses on development of fuzzy membership function, which evaluates human's emotion or feeling accurately and objectively. We used the regression analysis and reasoned a fuzzy membership function about the relation of the variables. Then we verified the adequacy with the reliability through the experiment after this.

• Asian Journal of Business Environment
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• v.8 no.4
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• pp.5-15
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• 2018

Purpose - The research aimed to reveal real decisional behavioral of management institutes in India for social media marketing usage, and analyses of empirical elements of social media consumption pattern. Research design, data, and methodology - The investigation was based around a research methodology using quantitative analysis with appropriate statistical techniques on random surveys of consumers, detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model and multiple regression employed using R studio edition to validate the reliability of the developed models. Results - A new conceptual framework is proposed - the management institutions decision model, providing a tool for effective and more focused decision-making strategies for developing better utilization techniques for social media. Management institutions have different requirements based upon objectives and resources available. The evidence suggests that the administrators need to be more aware of consumer indicators when targeting and designing social media marketing strategy. Conclusions - The research was based on samples and not the entire population of target consumers, providing limitations. As an inferential statistical method was chosen, the results might be susceptible to inaccuracy. The model developed from different age users, thereby providing rich perspectives into social media usage pattern.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.1-8
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• 2011

In this paper, we propose an effective method for cooperative spectrum sensing in cognitive radios where cognitive user(CR) with the highest reliability sensing data is only selected and allowed to report its local decision to FC as only decision making node. The proposed scheme enables CR users to implicitly compare their sensing data reliabilities based on their likelihood ratio, without any collaboration among cognitive radio users. Due to the mechanism, the proposed cooperative scheme can achieves a high spectrum sensing performance while only requiring extremely low cooperation resources such as signaling overhead and cooperative time in comparison with other existing methods such as maximum ratio combination (MRC) based, equal gain combination (EGC) based and conventional hard combination based cooperative sensing methods.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.221-230
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• 2014

With the progress and prosperity of commerce and industry, time and money increasingly form an equal partnership. Using air carriers to shorten the round-trip time has become an important choice for many people in the tourism process. Faced with increasing competition within the aviation service environment, airline evaluation criteria and the requirements of customers are gradually dominating the evaluation mechanism for air transport service quality. Over the past few years, attention on the transport quality of service has been primarily focused more on land-based transport, and less on the relevant evaluation criteria of airlines. Many studies have shown that quality of service will directly affect customer satisfaction, resulting in the fact that good quality aviation services have become increasingly important. Therefore, in practical industrial operations with limited resources, there is an urgent need to delve into the assessment guidelines that have an impact on customers when they choose an airline, which can be used as a basis for improving customer satisfaction. Through a literature review and a reliability and validity analysis, this study summarized 19 evaluation criteria, using the purposive sampling method and the decision laboratory method (DEMATEL). In addition, this study viewed the causal relationship between the evaluation criteria and the degree of association as a continuing project for airlines. This study selected appropriate empirical samples from two domestic airlines. The conclusions may provide recommendations for all airlines.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.139-147
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• 2019

This study is conducted to analyze how Social Media characteristics of restaurant franchise affect customer decision making and redelivery intention and find out how to do Social Media marketing which is getting important. Through this study, we will understand the direction of Social Media management. In this study, we had 220 users to respond questionnaires who looked up about restaurant franchise through Social Media. In the previous research, we classified the Social Media characteristics about the restaurant franchise into the fields of liveliness, agreement, reliability, communication, accuracy, and entertainment. In order to verify the hypothesis, we conducted single regression analysis and multiple regression analysis and verified the relationship between variables. First, we found that Social Media characteristics of restaurant franchise has a positive relationship with favorability. Second, Social Media characteristics of restaurant franchise has a positive relationship with satisfaction. Third, favorability has a positive effect on satisfaction. Fourth, favorability has a positive effect on the intention of re-inquiry and redeliver. Fifth, satisfaction has a positive effect on the revisit and intention to redirect. As a result of the study, we found that restaurant franchise will gain trust of customers if they take into account the characteristics of Social Media of restaurant franchise and conduct customized marketing according to the head office of restaurant franchise and perform continuous feedback and management in order to improve customer's favorability and loyalty.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.4
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• pp.517-536
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• 2020

The radionuclide inventory in radioactive waste from nuclear power plants should be determined to secure the safety of final repositories. As an alternative to time-consuming, labor-intensive, and destructive radiochemical analysis, the indirect scaling factor (SF) method has been used to determine the concentrations of difficult-to-measure radionuclides. Despite its long history, the original SF methodology remains almost unchanged and now needs to be improved for advanced SF implementation. Intense public attention and interest have been strongly directed to the reliability of the procedures and data regarding repository safety since the first operation of the low- and intermediate-level radioactive waste disposal facility in Gyeongju, Korea. In this review, statistical methodologies for SF implementation are described and evaluated to achieve reasonable and advanced decision-making. The first part of this review begins with an overview of the current status of the scaling factor method and global experiences, including some specific statistical issues associated with SF implementation. In addition, this review aims to extend the applicability of SF to the characterization of large quantities of waste from the decommissioning of nuclear facilities.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.65-86
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• 2021

This study aims at testing a hypothesis that the resilience of agricultural water systems is characterized by trade-offs and synergies of effects from climate and socioeconomic change. To achieve this, an Agricultural Water System Climate Resilience Assessment (ACRA) framework is established to evaluate comprehensive resilience of an agricultural water system to the combined impacts of the climate and socioeconomic changes with a case study in South Korea. Understanding dynamic behaviors of the agricultural water systems under climate and socioeconomic drivers is not straightforward because the system structure includes complex interactions with multiple feedbacks across components in water and agriculture sectors and climate and socioeconomic factors, which has not been well addressed in the existing decision support models. No consideration of the complex interactions with feedbacks in a decision making process may lead to counterintuitive and untoward evaluation of the coupled impacts of the climate and socioeconomic changes on the system performance. In this regard, the ACRA framework employs a System Dynamics (SD) approach that has been widely used to understand dynamics of the complex systems with the feedback interactions. In the ACRA framework applied to the case study in South Korea, the SD model works along with HOMWRS simulation. The ACRA framework will help to explore resilience-based strategies with infrastructure investment and management options for agricultural water systems.

• Journal of Distribution Science
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• v.21 no.11
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• pp.103-111
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• 2023

Purpose: This research aims to study the selection attributes influencing the purchasing decisions of the MZ generation in online luxury stores and explores the moderating effects of consumer value. The research aims to validate the impact of reasonable pricing, brand reliability, product variety, comprehensive product information, and user-friendly interfaces on customers' decision to purchase products from online luxury stores. Research design, data and methodology: A survey was conducted with 101 participants, and data analysis included exploratory and confirmatory factor analysis, as well as covariance structure model analysis. Results: The findings reveal that brand trust, product variety, and information sufficiency significantly influence brand affect, which in turn influences purchase intention. Additionally, the study identifies that consumers prioritizing hedonic value are more influenced by brand trust and information, while those prioritizing utilitarian value are more responsive to factors like reasonable price, product variety, and ease of use. Conclusions: The study provides insights into the preferences and behaviors of the MZ generation, highlighting their digital proficiency, mobile-centric lifestyle, desire for product variety, price-consciousness, social media influence, and the availability of personalized shopping experiences as factors contributing to their preference for online luxury stores. These findings contribute to understanding consumer behavior and decision-making processes in the context of online luxury shopping.