• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.783-795
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• 2021

This study aims to examine the relationship between performance evaluation systems and managerial effectiveness of responsible administrative agencies. Previous studies mainly emphasize the institutional changes of evaluation system and its impacts. This study articulate important factors in performance evaluation systems like interactive communications the credibility of performance indicators top manager's concern. A survey was conducted by 510 employees of local statistical office agencies and a structural equation modeling was used in order to test hypotheses. Results show that the credibility of performance indicators and top manager's concern about evaluation are positively related to performance results and procedural transparency and to managerial effectiveness. Interactive communication did not show statistically significant on managerial effectiveness. The empirical test results indicated that the interactive communication about the evaluation system of responsible administrative agencies should be considered.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.29-38
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• 2020

Purpose: The purpose of this study is to empirically analyze the effect of chatbot service quality, chatbot trust, and chatbot satisfaction on chatbot reuse intention and store reuse intention. Research design, data, and methodology: We reviewed the literature on domestic and international chatbots, established hypotheses, and analyzed them. We empirically analyzed the process model in which chatbot service quality (interaction quality, information quality) has a positive effect on chatbot trust and chatbot satisfaction, and that chatbot trust and satisfaction positively affect chatbot reuse intention and store reuse intention. A survey was conducted on 212 people who had used shopping mall chatbots and financial service chatbots after demonstrating the shopping mall chatbot video. Structural equation modeling was conducted by using AMOS 24.0 to test the proposed relationships. Results: As a result of the empirical analysis, the effects of interaction quality on chatbot trust and information quality on chatbot satisfaction were not supported, but the rest of the hypotheses were statistically significant. It was found that the information quality of chatbot service had a positive effect on chatbot trust, but did not significantly affect chatbot satisfaction. In addition, the interaction quality of the chatbot positively affects the satisfaction of the chatbot, but it does not significantly affect the trust of the chatbot. Chatbot trust was found to have a positive effect on chatbot satisfaction. Chatbot trust and chatbot satisfaction were found to have a positive influence on the intention to reuse the chatbot. And, chatbot trust and chatbot satisfaction were found to have a positive influence on store reuse intention. Conclusions: The findings of this study offer significant theoretical and managerial contributions in the context of chatbot. Chatbots should enhance customer contact quality management from the perspective of total customer experience management rather than partial function. When providing a chatbot service, it is more desirable to give priority to providing accurate information to increase trust, and at the same time to improve customer satisfaction by increasing the quality of interaction. And in order to increase the competitive advantage of companies, the purpose of introducing chatbots should be clarified and approached strategically.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.97-109
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• 2020

On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.4
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• pp.1-17
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• 2021

This study was examined whether the experiential marketing factors proposed by Bernd Schmitt were applicable to the consumer behavior of active seniors. The study was analyzed the influence of SEMs have on value perception of brand and attitude formation as well as the behavioral intentions of active senior consumers and whether this effect differed between the level of commitment. For empirical analysis, frequency analysis, EFA, reliability, CFA, SEM, and multiple-group comparison analysis were performed. The results showed that sense and feel factor did not have a significant influence on the value perception of brand, while think factor had a positive effect on the value perception of brand. Act factor did not affect the value perception of brand; on the other hand, relate factor had a significant effect on the value perception of brand. The result of structural equation modeling also revealed that the value perception of brand had a positive influence on attitude formation and behavioral intentions. The result of multiple-group comparison analysis confirmed that the influence of act factor on value perception of brand differed according to the level of commitment, but the positive influence of act factor on value perception of brand was limited to the high-level of commitment group. As a result of the influence relate factor had on the value perception of brand, differences existed between the two groups, and the low-level of commitment group had a greater influence than the high-level of commitment group. So it will be effective for active senior consumers to form fashion communities and let them participate in to enhance positive consumer behavior toward fashion brands.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.726-741
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• 2022

The purpose of this study is to provide instructive theoretical models for art (music) education institutions especially when unpredictable risks, such as pandemics, occur again. Based on the customer behavior theory of the business-to-business-to-customer (B2B2C) platform, and in combination with the technology acceptance model (TAM) and expectation confirmation model (ECM), this study proposes an online education model from the perspective of art education. The framework is based on the three decision-making processes of the customer, and includes the product owner, content owner, and customer area. This paper highlights the factors that influence customers in making decisions when art education institutions are product owners. Regression analysis was introduced to study the factors influencing the expectation confirmation, and the overall fitting testing and six hypotheses testing of 385 effective samples were performed using the structural equation modeling (SEM). The results show that the course-design and after-service positively influenced the expectation confirmation, and the domain image positively influenced the continuance behavior. Negative emotions skipped the mediator (expectation confirmation) and directly exerted a significant negative impact on customers' willingness to continue system usage (continuance behavior). In addition, expectation confirmation positively influenced continuance behavior. The paths of detailed items comprising course-design, after-service, and negative emotion were also analyzed and discussed. In this path analysis, ordinary art learners did not believe that AI partners can play a very good auxiliary role. The findings contribute to the scope of information systems acting as an art education platform academically, and provide effective and theoretical support for the actual operation of art education institutions.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.589-600
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• 2022

Investigations on the molten-pool sloshing behavior are of essential value for improving nuclear safety evaluation of Core Disruptive Accidents (CDA) that would be possibly encountered for Sodium-cooled Fast Reactors (SFR). This paper is aimed at synthesizing the knowledge from our recent studies on molten-pool sloshing behavior with solid particles conducted at the Sun Yat-sen University. To better visualize and clarify the mechanism and characteristics of sloshing induced by local Fuel-Coolant Interaction (FCI), experiments were performed with various parameters by injecting nitrogen gas into a 2-dimensional liquid pool with accumulated solid particles. It was confirmed that under different particle-bed conditions, three representative flow regimes (i.e. the bubble-impulsion dominant, transitional and bed-inertia dominant regimes) are identifiable. Aimed at predicting the regime transitions during sloshing process, a predictive empirical model along with a regime map was proposed on the basis of experiments using single-sized spherical solid particles, and then was extended for covering more complex particle conditions (e.g. non-spherical, mixed-sized and mixed-density spherical particle conditions). To obtain more comprehensive understandings and verify the applicability and reliability of the predictive model under more realistic conditions (e.g. large-scale 3-dimensional condition), further experimental and modeling studies are also being prepared under other more complicated actual conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3194-3210
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• 2022

Wall obstruction is the main factor leading to the non-line of sight (NLoS) error of indoor localization based on received signal strength indicator (RSSI). Modeling and correcting the path loss of the signals through the wall will improve the accuracy of RSSI localization. Based on electromagnetic wave propagation theory, the reflection and transmission process of wireless signals propagation through the wall is analyzed. The path loss of signals through wall is deduced based on power loss and RSSI definition, and the theoretical model of path loss of signals through wall is proposed. In view of electromagnetic characteristic parameters of the theoretical model usually cannot be accurately obtained, the statistical model of NLoS error caused by the signals through the wall is presented based on the log-distance path loss model to solve the parameters. Combining the statistical model and theoretical model, a hybrid model of path loss of signals through wall is proposed. Based on the empirical values of electromagnetic characteristic parameters of the concrete wall, the effect of each electromagnetic characteristic parameters on path loss is analyzed, and the theoretical model of regional path loss of signals through the wall is established. The statistical model and hybrid model of regional path loss of signals through wall are established by RSSI observation experiments, respectively. The hybrid model can solve the problem of path loss when the material of wall is unknown. The results show that the hybrid model can better express the actual trend of the regional path loss and maintain the pass loss continuity of adjacent areas. The validity of the hybrid model is verified by inverse computation of the RSSI of the extended region, and the calculated RSSI is basically consistent with the measured RSSI. The hybrid model can be used to forecast regional path loss of signals through the wall.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3855-3863
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• 2022

An evaluation of the radiation shielding performance of high-Z-particle-loaded polylactic acid (PLA) composite materials was pursued. Specimens were produced via fused deposition modeling (FDM) using copper-PLA, steel-PLA, and BaSO₄-PLA composite filaments containing 82.7, 75.2, and 44.6 wt% particulate phase contents, respectively, and were tested under broad-band flash x-ray conditions at the Sandia National Laboratories HERMES III facility. The experimental results for the mass attenuation coefficients of the composites were found to be in good agreement with GEANT4 simulations carried out using the same exposure conditions and an atomistic mixture as a model for the composite materials. Further simulation studies, focusing on the Cu-PLA composite system, were used to explore a shield design parameter space (in this case, defined by Cu-particle loading and shield areal density) to assess performance under both high-energy photon and electron fluxes over an incident energy range of 0.5-15 MeV. Based on these results, a method is proposed that can assist in the visualization and isolation of shield parameter coordinate sets that optimize performance under targeted radiation characteristics (type, energy). For electron flux shielding, an empirical relationship was found between areal density (AD), electron energy (E), composition and performance. In cases where ${\frac{E}{AD}}{\geq}2MeV{\bullet}cm{\bullet}g^{-1}$, a shield composed of >85 wt% Cu results in optimal performance. In contrast, a shield composed of <10 wt% Cu is anticipated to perform best against electron irradiation when ${\frac{E}{AD}}<2MeV{\bullet}cm{\bullet}g^{-1}$.

• Advances in nano research
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• v.12 no.5
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• pp.515-527
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• 2022

The application of fibers in concrete obviously enhances the properties of concrete, also the application of natural fibers in concrete is raising due to the availability, low cost and environmentally friendly. Besides, predicting the mechanical properties of concrete in general and shear strength in particular is highly significant in concrete mixture with fiber nanocomposite reinforced concrete (FRC) in construction projects. Despite numerous studies in shear strength, determining this strength still needs more investigations. In this research, Adaptive Neuro-Fuzzy Inference System (ANFIS) have been employed to determine the strength of reinforced concrete with fiber. 180 empirical data were gathered from reliable literature to develop the methods. Models were developed, validated and their statistical results were compared through the root mean squared error (RMSE), determination coefficient (R²), mean absolute error (MAE) and Pearson correlation coefficient (r). Comparing the RMSE of PSO (0.8859) and ANFIS (0.6047) have emphasized the significant role of structural parameters on the shear strength of concrete, also effective depth, web width, and a clear depth rate are essential parameters in modeling the shear capacity of FRC. Considering the accuracy of our models in determining the shear strength of FRC, the outcomes have shown that the R² values of PSO (0.7487) was better than ANFIS (2.4048). Thus, in this research, PSO has demonstrated better performance than ANFIS in predicting the shear strength of FRC in case of accuracy and the least error ratio. Thus, PSO could be applied as a proper tool to maximum accuracy predict the shear strength of FRC.

• Knowledge Management Research
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• v.23 no.3
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• pp.89-109
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• 2022

Many companies are trying to enter into overseas markets to overcome the limited size of domestic markets. However, there are many barriers to enter the overseas markets such as difficulty to find buyers and make contract with them, payment risks, unfriendly foreign policies, and etc. Companies have used to various strategies to get opportunities of overseas markets. One of them is UN public procurement. Despite many advantages, limited number of companies are participating in the procurement. Individual governments are providing policies to support local companies to participate in the UN public procurement. However it is not easy to encourage firms, especially SMEs to participate in the procurement. This study is designed to analyze firm and product determinants of participating in UN public procurement. Based on literature reviews and empirical findings, this study shows social responsibility and global orientation can play an important role regarding the participation. In addition, the positive relationship between UN public procurement participation and sustainability in a given firm could be empirically supported. Last, we suggest combining country- and industry-level data to investigate UN public procurement participation as an interesting topic for future research. This study represents various determinants to encourage UN public procurement participation. They may contribute to enhance firm performance such as sustainability.