• 산경연구논집
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• 제13권1호
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• pp.1-9
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• 2022

Purpose: This study aims to find empirical evidence and clarity on the phenomenon of the direct and indirect effect of perceived behavioral control on fraud prevention through whistleblowing intention. This study also aims to understand the influence of organizational ethical culture moderating between whistleblowing intention and fraud prevention. Research design, data, methodology: The samples of this research are 236 respondents consisting of the Head of the Finance Subdivision and Head of the Reporting Planning Subdivision and the finance staff who were determined using the purposive sampling method. The data obtained were analyzed using the Structural Equation Modeling technique. Results: The study results show that perceived behavioral control positively and significantly affects whistleblowing intention. In addition, perceived behavioral control does not affect fraud prevention mediated by whistleblowing intention. Furthermore, organizational ethical culture moderates whistleblowing intention and has a positive and significant effect on fraud prevention. Conclusions: This study concludes that the phenomenon of scandal that often occurs on a television is not a habit that must be followed. It requires an active role from the community as a form of concern for whistleblowing. Futher researchers can add other construct variables, such as good corporate governance to assess the performance improvement of the organizational layers, both internally and externally

• 국제초고층학회논문집
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• 제12권2호
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• pp.163-168
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• 2023

Today 55 percent of the population in the world lives in urban areas which is expected to increase to 68 percent by the year 2050. In the cities, high-rise buildings as symbols of the modern cityscape are dominating the skylines, but the data to demonstrate their embodied energy and environmental impacts are scarce, compared to low- or mid-rise buildings. Reducing the embodied energy and environmental impacts of buildings is critical as about 42 percent of primary energy use and 39 percent of the global greenhouse gas (GHG) emissions come from the building sector. However, it is an overlooked area in embodied energy and environmental impacts of high-rise buildings. Life cycle assessment (LCA) is a widely used tool to quantify the embodied energy and environmental impacts of the building sector. LCA combined with Building Information Modeling (BIM) can simplify data acquisition of the building as well as provide both tools with feedback. Several studies recognize that the integration of BIM and LCA can simplify data acquisition of the building as well as provide tools with feedback. This article provides an overview of literature on BIM-based of embodied energy and environmental impacts of high-rise buildings. It also compares with different LCA methodologies. Finally, major strategies to reduce embodied energy and environmental impacts of high-rise buildings, research limitations and trends in the field are covered.

• 산경연구논집
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• 제14권7호
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• pp.9-18
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• 2023

Purpose: The ability of a firm to acquire resources through marketing networks is crucial for its competitiveness. Nonetheless, the influence of these networks on the performance of a firm's innovation is still uncertain, particularly in the face of environmental uncertainty. This research investigates the impact of marketing networks, specifically network embeddedness and structural holes, on the performance of innovation in situations characterized by environmental uncertainty. Research design, data and methodology: The empirical examination was carried out within the framework of internal network entities, specifically the manufacturer-supplier-sub supplier relationships, involving the primary suppliers of a Korean engineering firm. Construct measures utilized in this study were derived from existing measures and prior research. A questionnaire survey was conducted with a major first-tier supplier of a Korean engineering firm. Proposed hypotheses were tested using structural equation modeling. Results: The survey findings suggest that only network embeddedness has an impact on the perception of major first-tier suppliers regarding the buyer's innovation performance. Conclusions: To strengthen the empirical evidence regarding the effects of marketing networks on innovation performance, future research should take into account cultural factors such as collectivism, which is indicative of the distinctive business-to-business marketing relationships observed in the Korean context.

• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.93-103
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• 2022

The main purpose of this study was to gauge the patient satisfaction index and subsequently discuss the Importance-Performance (IP) matrix analysis of the inpatient services in the context of the private hospital setting. The Malaysian Customer Satisfaction Index Model was employed as the theoretical framework for the above purposes. This study involving 242 patients in Malaysian's private healthcare sector used a Web-based survey as the main method of data collection. Partial least square structural equation modeling (PLS-SEM) was utilized for data analysis. Using Fornell et al. (1996)'s formula, the resulting patient satisfaction index was slightly lower than the "very satisfied" category, the target level required for positioning as one of the world's premier medical tourism players. The IP matrix showed that medical quality is the main competitive advantage of the private hospitals that can propel their growth in the global healthcare marketplace. The results also indicate that outcome quality, patient rights, and privacy, and service quality are the three quality domains that need to be prioritized for further improvement. On the other hand, the servicescape quality domain needs to be strategized as the unique selling proposition as the performance of the private hospitals in this regard is already extremely good.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.185-185
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• 2020

기후변화의 영향으로 국지적 규모의 홍수, 가뭄 등의 피해 규모가 증가하고 있으며, 복사에너지 변화에 기인한 전지구적 대류활동의 변화는 단발성 피해에 확산되어 특정 지역의 기후 패턴 변화로 이어질 수 있다. 대류활동의 변화는 국가별 물순환의 변화로 이어질 수 있으며, 이로 인한 수자원의 변동성은 국가적 수자원 이용에 있어 중요한 요소로 작용될 수 있다. 수자원의 중요성으로 인해 국제적인 기관들은 전지구적 대류활동에 기인한 물순환 과정을 파악하고자 노력하였으며, 그 일환으로 GCMs (Global climate modeling) 등과 같은 모형이 개발되었고, 위성을 통한 전지구 강우량 측정망을 구축하였다. 위성을 통한 전구 강우량 자료와 GCMs에서 산출된 대류과정과 연관된 기후변량 자료들은 빅데이터로 구축되어 제한 없이 제공되고 있다. 정상성 강우 모의 기법은 데이터에 한정된 패턴을 반영하는 모형들로서 기후변화로 인한 기후 변동성 증가를 반영하는데 한계가 존재한다. 본 연구에서는 기상 빅데이터 자료를 기반으로 한반도의 강우량과 기상학적 특성을 연관할 수 있는 머신러닝의 일종인 딥러닝 방법을 접목시킨 강우 모의 기법을 적용하였다. 본 연구의 모형은 기후변화로 인한 기상학적 패턴의 변화를 딥러닝 기법을 통해 식별하고 식별된 기상학적 특성에 기반한 한반도의 강우량을 모의할 수 있다. 본 모형은 단기 및 장기 예측 모형과 결합하여 불확실성을 고려한 단/장기 강우량 평가에 활용될 수 있을 것으로 기대된다.

• 한국수소및신에너지학회논문집
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• 제34권3호
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• pp.267-273
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• 2023

As the impacts of global climate change become increasingly apparent, the reduction of carbon emissions has emerged as a critical subject of discussion. Nuclear power has garnered attention as a potential carbon-free energy source; however, the rapidity of load following in nuclear power generation poses challenges in comparison to fossil-fueled methods. Consequently, power-to-gas systems, which integrate nuclear power and hydrogen, have attracted growing interest. This study presents a preliminary design of a very high temperature reactor (VHTR) integrated blue hydrogen production process utilizing DWSIM, an open-source process simulator. The blue hydrogen production process is estimated to supply the necessary calorific value for carbon capture through tail gas combustion heat. Moreover, a thermodynamic assessment of the main recuperator is performed as a function of the helium flow rate from the VHTR system to the blue hydrogen production system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• 산경연구논집
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• 제14권12호
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• pp.11-21
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• 2023

Purpose: This study aims to investigate the impact of mobile shopping app components on shopping flow and the continuous usage intention of the shopping apps in the rapidly growing mobile market facilitated by advancements in the mobile environment. Research Methodology: A survey was conducted, targeting users aged 20 and older with experience in using mobile shopping apps. The responses of 456 participants were analyzed through frequency analysis, exploratory factor analysis, reliability analysis, confirmatory factor analysis, and structural equation modeling. Results: The study found that within the components of mobile shopping apps, enjoyment significantly impacted both shopping flow and the continuous usage intention of shopping apps. The diversity of product assortment had a significant effect only on shopping flow. The usefulness and ease of use influenced on the intention to continue using shopping apps. Conclusions: Based on the findings, it is recommended that shopping app operators try to identify essential components for stimulating user interest and engagement when developing or modifying apps. Additionally, a diverse range of products enhances the shopping experience and drives spontaneous purchases. Furthermore, providing an easy interface and minimizing the effort required, this experience can enhance user perception of its value and sustain consumers' continuous usage intention of the shopping app.

• 유통과학연구
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• 제22권2호
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• pp.1-10
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• 2024

Purpose: As Thailand endeavors to solidify its position in the global supply chain, unraveling the determinants of innovation and performance becomes imperative for sustained competitiveness. This research delves into the multifaceted landscape of logistics and supply chain organizations in Thailand, aiming to identify and understand the key factors that significantly influence innovation and organizational performance in this dynamic sector. Research design, data, and methodology: A questionnaire is developed to survey to 400 employees who have at least one-year experience in selected ten logistics and supply chain organizations in Thailand. The sampling techniques involved judgmental, convenience and snowball sampling. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were employed to assess and validate the model's adequacy and to conduct hypothesis testing. Results: The findings reveal that ICT use significantly influenced entrepreneurial orientation and innovation but has no significant influence on organizational performance. Additionally, innovation was significantly influenced by collective entrepreneurship but not by entrepreneurial orientation. Finally, innovation significantly influenced organizational performance. Conclusions: The study concludes with actionable insights for logistics and supply chain organizations in Thailand. This research serves as a valuable resource for practitioners, policymakers, and researchers seeking to advance the understanding of organizational dynamics in this critical industry.

• 한국공간구조학회논문집
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• 제23권4호
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• pp.81-88
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• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.