• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.457-464
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• 2020

This study aims to recognize customers' real sentiment and then discover the data-driven insights for strategic decision-making in the financial sector of Saudi Arabia. The data was collected from the social media (Facebook and Twitter) from start till October 2018 in financial companies (NCB, Al Rajhi, and Bupa) selected in the Kingdom of Saudi Arabia according to criteria. Then, it was analyzed using a sentiment analysis, one of data mining techniques. All three companies have similar likes and followers as they serve customers as B2B and B2C companies. In addition, for Al Rajhi no negative sentiment was detected in English posts, while it can be seen that Internet penetration of both banks are higher than BUPA, rarely mentioned in few hours. This study helps to predict the overall popularity as well as the perception or real mood of people by identifying the positive and negative feelings or emotions behind customers' social media posts or messages. This research presents meaningful insights in data-driven approaches using a specific data mining technique as a tool for corporate decision-making and forecasting. Understanding what the key issues are from customers' perspective, it becomes possible to develop a better data-based global strategies to create a sustainable competitive advantage.

• Journal of Fashion Business
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• v.20 no.6
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• pp.1-18
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• 2016

This study examines the impact of consumer ethics on the CSR motive attributions and, the subsequent consumer perception of the firm's ethicality. Data of 512 adults were collected nationwide using a self-administered questionnaire online. Exploratory and confirmative factor analysis were employed to identify six underlying dimensions of consumer ethics, as follows: actively benefiting from illegal actions, passively benefiting from illegal actions, no harm/no foul, economic benefiting from illegal actions, intellectual property infringement, and pro-environmental behavior. In order to examine the relationships between consumer ethics, CSR motive attribution, and consumer perceived ethicality, a structural equation modeling test was conducted. The results demonstrated that actively benefiting from illegal actions, economic benefiting from illegal action, and pro-environmental behavior had impacts on CSR motive attributions such as strategy-driven attribution, value-driven attribution, and stakeholder-driven attribution. Consequently, strategy-driven attribution and value-driven attribution influenced the consumer perception of the firm's ethicality, whereas stakeholder-driven attribution did not. This study provides an understanding of the CSR attribution mechanism from the view of consumer ethics that are multi-dimensional. The ethical judgements on different types of consumer behavior lead to attributions of CSR motives and subsequently their perception of a firm's ethicality.

• Geomechanics and Engineering
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• v.1 no.1
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• pp.17-34
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• 2009

There has been growing agreement that geotechnical reliability-based design (RBD) is necessary for establishing more advanced and integrated design system. In this study, resistance factors for LRFD pile design using CPT results were investigated for axially loaded driven piles. In order to address variability in design methodology, different CPT-based methods and load-settlement criteria, popular in practice, were selected and used for evaluation of resistance factors. A total of 32 data sets from 13 test sites were collected from the literature. In order to maintain the statistical consistency of the data sets, the characteristic pile load capacity was introduced in reliability analysis and evaluation of resistance factors. It was found that values of resistance factors considerably differ for different design methods, load-settlement criteria, and load capacity components. For the total resistance, resistance factors for LCPC method were higher than others, while those for Aoki-Velloso's and Philipponnat's methods were in similar ranges. In respect to load-settlement criteria, 0.1B and Chin's criteria produced higher resistance factors than DeBeer's and Davisson's criteria. Resistance factors for the base and shaft resistances were also presented and analyzed.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.331-351
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• 2012

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.295-309
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• 2020

In 2019, Japan announced trade regulations against Korean products; consequently, the sales of Japanese products in Korea dropped due to a Korean consumers' boycott. This study measured the Korean consumers' political consumption behavior toward Japanese fashion products. Unstructured text data from online media sources and consumer posted sources such as blog and SNS were collected. Text mining techniques and semantic network analysis were used to process unstructured data. This study used text mining techniques and semantic network analysis to process data. The results identified boycotting Japanese fashion products and buycotting alternative products and Korean brands due to consumers' political consumption. Two brand cases were investigated in detail. Online text data before and after the political action were compared and significant changes in consumption as well as emotional expressions were identified. Product related industry sectors were identified in terms of the political consumption of fashion: liquor, automobile and tourism industry sectors were closely linked to the fashion sector in terms of boycotting. More "boycott" and "buycott" fashion brands (reflected in consumer attitudes and feelings) were detected in consumer driven texts than in media driven sources.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06b
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• pp.191-195
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• 2006

Multivariate data analysis tools were used to improve the understanding of the wet end chemistry and white water system of the Papermill at NorskeCanada Crofton Division. Specifically, the analysis was aimed at identifying what variables were contributing to increased retention aid use and wet end instability. Several models were developed using data sets with up to 88 process variables and over 3000 observations. It was found that increased retention aid use was driven primarily by PCC and TMP usage as well as the addition of Alaskan White Spruce to the TMP furnish.

• Journal of the Korean Society of Visualization
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• v.15 no.2
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• pp.59-67
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• 2017

To verify floatability of ABB (Air bubble barrier), we compared bubble swarm behavior with and without the air-driven ejector. Experiment was conducted using the fabricated air-driven ejector with 5 mm nozzle on the bottom of 1 m3 water tank. Reynolds number of air in the nozzle was ranged 1766-13248. We analyzed data with statistical method using image processing, particle mage velocimetry (PIV) and proper orthogonal decomposition (POD) analysis. As a result of POD analysis, there was no significant eigenmode in bubbly flow generated from the ejector. It means that more complex turbulent flows were formed by the ejector, thereby (1) making bubbles finer, (2) promoting three-dimensional energy transfer between bubble and water, and (3) making evenly distributed velocity profile of water. It is concluded that the air-driven ejector could enhance the performance of ABB.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.304-317
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• 2016

An accelerator-driven system consists of a subcritical reactor and a controllable external neutron source. The reactor in an accelerator-driven system can sustain fission reactions in a subcritical state using an external neutron source, which is an intrinsic safety feature of the system. The system can provide efficient transmutations of nuclear wastes such as minor actinides and long-lived fission products and generate electricity. Recently at Kyoto University Research Reactor Institute (KURRI; Kyoto, Japan), a series of reactor physics experiments was conducted with the Kyoto University Critical Assembly and a Cockcrofte-Walton type accelerator, which generates the external neutron source by deuteriu-metritium reactions. In this paper, neutronic analyses of a series of experiments have been re-estimated by using the latest Monte Carlo code and nuclear data libraries. This feasibility study is presented through the comparison of Monte Carlo simulation results with measurements.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.63-71
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• 2023

The construction industry stands out for its higher incidence of accidents in comparison to other sectors. A causal analysis of the accidents is necessary for effective prevention. In this study, we propose a data-driven causal analysis to find significant factors of fatal construction accidents. We collected 14,318 cases of structured and text data of construction accidents from the Construction Safety Management Integrated Information (CSI). For the variables in the collected dataset, we first analyze their patterns and correlations with fatal construction accidents by statistical analysis. In addition, machine learning algorithms are employed to develop a classification model for fatal accidents. The integration of SHAP (SHapley Additive exPlanations) allows for the identification of root causes driving fatal incidents. As a result, the outcome reveals the significant factors and keywords wielding notable influence over fatal accidents within construction contexts.

• Asian Journal of Business Environment
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• v.14 no.2
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• pp.1-10
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• 2024

Purpose: The purpose of this study is to investigate the essential factors contributing to the growth and success of smart cities, providing a comprehensive analysis of key elements that are crucial in fostering the development of smart cities. This study explored the impacts of technology-driven applications, corporate involvement, the role of experts, citizen co-creation, city-led strategy governance, and sustainable urban practices on overall attitudes towards smart cities. Additionally, the study examined the impact of overall attitude on the growth trajectory of the smart cities and satisfaction. Research design, data and methodology: To collect data, this study employed an online survey conducted by a reputable research organization. Data analysis involved the use of factor analysis, ANOVA, and regression analysis. Results: This study unveiled significant impacts of technology-driven applications, corporate involvement, the role of experts, citizen co-creation, city-led strategy governance, and sustainable urban practices on the overall attitudes. Furthermore, it demonstrated that the overall attitude significantly influences the growth trajectory of smart cities. Conclusions: This study identified key driving factors for smart city development, suggesting that the consideration of sustainable urban practices emerges as the most significant factor influencing the growth of the smart cities.