• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.68-74
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• 2024

This study develops a model to determine the input rate of the chemical for coagulation and flocculation process (i.e. coagulant) at industrial water treatment plant, based on real-world data. To detect outliers among the collected data, a two-phase algorithm with standardization transformation and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is applied. In addition, both of the missing data and outliers are revised with linear interpolation. To determine the coagulant rate, various kinds of machine learning models are tested as well as linear regression. Among them, the random forest model with min-max scaled data provides the best performance, whose MSE, MAPE, R² and CVRMSE are 1.136, 0.111, 0.912, and 18.704, respectively. This study demonstrates the practical applicability of machine learning based chemical input decision model, which can lead to a smart management and response systems for clean and safe water treatment plant.

• Journal of The Korean Institute of Defense Technology
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• v.6 no.1
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• pp.7-12
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• 2024

In March 2023, the Ministry of National Defense highlighted the Synthetic Training Environment (STE) platform for practical training of combatants between training exercises in its Defense Innovation 4.0 Basic Plan. However, there are many issues to be resolved, such as the use of different simulators and terrain information systems for each military. Therefore, this study examined the cases of the U.S. Army, Air Force, and Navy, each of which has an advanced synthetic training environment, to derive suggestions for the ROK military.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.41-52
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• 2024

Purpose - Population is the foundation for maintaining and growing the strength of a nation, and a certain number must be maintained for the growth of the national economy. and Amidst the changing population structure where the elderly population is steadily increasing while the productive population is gradually decreasing, there is a practical need for devising solutions to overcome the low birth rate. Design/methodology/approach - For conducting this study, data was collected from a total of 1,000 residents of Goyang city, aged 19 and above. Out of these, empirical analysis was conducted using the SPSS 29.0 statistical program on the response data of a total of 247 individuals, including 156 individuals in their 20s and 191 individuals in their 30s, who belong to the MZ generation. Findings - The results showed that first, the awareness of the childbirth encouragement policy did not significantly affect the child-rearing environment. The perception of the importance of the childbirth encouragement policy had a positive and significant effect on the child-rearing environment. Moreover, the child-rearing environment had a positive effect on marital attitudes. Research implications or Originality - Thus, rather than the effects of awareness through the promotion and education of national childbirth policies, it is preemptively necessary to realize substantial childbirth encouragement policies for improving the child-rearing environment.

• Journal of Smart Tourism
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• v.4 no.2
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• pp.25-33
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• 2024

This study examines the factors influencing the use of mobile food ordering applications and their impact on consumption behavior amidst recent societal changes. It re-evaluates the relevance of factors from the UTAUT2 theory in predicting customers' behavioral intentions. Additionally, the study explores the moderating effect of confidence in food safety measures (CFSM). Quantitative research methods are employed. A structured questionnaire that measures the psychological factors, behavioral intention, and actual usage of mobile food ordering applications was used to collect customer data. Regression and moderation analyses are conducted to test the hypotheses and examine the moderating role of CFSM. The findings reveal that performance expectation, effort expectation, and habit significantly predict customers' intention to use mobile food ordering applications. Moreover, for customers with high CFSM, social influence, facilitating conditions, and hedonic motivation add additional contributions to their behavioral intention. This study extends the UTAUT2 theory by applying it to mobile food ordering applications and examining the influence of CFSM. It identifies the specific factors that drive customers' intention to use these applications and highlights the importance of CFSM as a moderating factor. The findings offer theoretical insights and practical implications for researchers and practitioners in the mobile food ordering industry.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.121-138
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• 2024

Artificial intelligence is crucial to manufacturing productivity. Understanding the difficulties in producing disruptions, especially in linear feed robot systems, is essential for efficient operations. These mechanical tools, essential for linear movements within systems, are prone to damage and degradation, especially in the LM guide, due to repetitive motions. We examine how explainable artificial intelligence (XAI) may diagnose wafer linear robot linear rail clearance and ball screw clearance anomalies. XAI helps diagnose problems and explain anomalies, enriching management and operational strategies. By interpreting the reasons for anomaly detection through visualizations such as Class Activation Maps (CAMs) using technologies like Grad-CAM, FG-CAM, and FFT-CAM, and comparing 1D-CNN with 2D-CNN, we illustrates the potential of XAI in enhancing diagnostic accuracy. The use of datasets from accelerometer and torque sensors in our experiments validates the high accuracy of the proposed method in binary and ternary classifications. This study exemplifies how XAI can elucidate deep learning models trained on industrial signals, offering a practical approach to understanding and applying AI in maintaining the integrity of critical components such as LM guides in linear feed robots.

• The Korean Journal of Food & Health Convergence
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• v.10 no.4
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• pp.9-19
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• 2024

This qualitative study explores the impact of online food delivery platform attributes on customer satisfaction and repurchase intentions. Employing a phenomenological approach, we conducted in-depth interviews and focus group discussions with 15 participants to gain rich insights into user experiences. Thematic analysis revealed key factors influencing satisfaction and loyalty: service quality dimensions (efficiency, reliability, fulfillment, privacy), expectation disconfirmation, perceived usefulness and ease of use, multi-level customer value, relationship quality, electronic word-of-mouth, value co-creation, and phased loyalty formation. Our findings extend customer behavior theory in digital platforms, offering a comprehensive framework for understanding the complex mechanisms underlying user satisfaction and repurchase decisions. The study provides valuable implications for platform operators, highlighting the importance of exceeding customer expectations, enhancing user experience, building trust, leveraging user-generated content, and fostering co-creation processes. Methodologically, we demonstrate the efficacy of qualitative approaches in uncovering nuanced insights in digital service contexts. While acknowledging limitations in generalizability, this research establishes a solid foundation for future investigations into the rapidly evolving domain of online food delivery services. The integrated theoretical approach offers a robust model for analyzing customer behavior in emerging digital service environments, contributing significantly to both academic understanding and practical application in the field of digital service provision and platform management.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.541-564
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• 2024

Contact-tracing applications have significantly contributed to mitigating the spread of coronavirus disease 2019 (COVID-19), yet the extensive use of these location-based applications raises serious privacy concerns. Drawing on the Information-Motivation-Behavioral (IMB) skills model, our study investigated factors that influence users' protective behaviors toward location privacy, elucidating the privacy paradox and the mediating role of implementation intention. Through an online survey conducted in China with 311 participants, we found that privacy concerns and privacy awareness positively affected the use of mobile location service settings, with privacy concerns mediating the relationship between privacy awareness and the intention to protect privacy. Furthermore, our study demonstrated the privacy paradox, revealing the pivotal mediating role of implementation intentions in bridging the gap between users' intentions and their actual behaviors. This study offers new perspectives on the privacy paradox, particularly through the lens of implementation intention, and provides valuable insights for motivating greater use of contact-tracing applications. It offers both theoretical and practical guidance for stakeholders to address privacy concerns during global pandemics like COVID-19, thereby encouraging a more widespread and responsible engagement with technology in public health.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.421-446
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• 2024

Through Information and Communication Technology (ICT), the growth of music streaming platforms has revolutionized music consumption. "Digital Shadow Work" (DSW) refers to unpaid labor in digital spaces, with some prior research on its aspects. However, a comprehensive understanding is hindered by limitations in existing studies such as a lack of universality and dynamic exploration. To address these gaps and enable a comprehensive investigation into the role of DSW within highly versatile digital applications such as digital streaming platforms, this study employs a grounded theory methodology, a qualitative approach well-suited for exploring the intricacies of DSW among users of Chinese music streaming applications over a two-month period, involving longitudinal interviews with nine participants. The study findings elucidate the dynamic nature of DSW perceptions, which fluctuate across different stages of use and change in intensity over time. This study uncovers mixed attitudes towards DSW tasks, and observes a waning enthusiasm for social features over time, prompting some users to consider switching platforms. This study highlights the importance of thoughtful and user-centric feature development to enhance user satisfaction and the understanding of DSW, providing practical design and enhancement implications for music streaming applications.

• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.81-100
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• 2024

Purpose - This study investigates the direct effects of national governance quality on international logistics activities. The results provide practical insights for different stakeholders such as policymakers and offer detailed recommendations for improving national governance quality in projects aimed to enhance cross-border logistics operations. Design/methodology/approach - To test the hypotheses, a multivariate linear regression model using the ordinary least squares estimator is applied to 166 countries covering six periods: 2007, 2010, 2012, 2014, 2016, and 2018. Findings - All national governance indicators have a significant positive influence on the performance of cross-border logistics operations. At the dimensional level, government effectiveness, legal systems, anti-corruption efforts and regulatory quality have a greater impact than democracy and a stable political environment on all dimensions of logistics performance. Research implications or Originality - This study sheds light on how the quality of governance directly affects trading logistics. It advises governments to enhance governance quality and nurture a supportive institutional environment to improve transnational logistics proficiency. It also provides a better understanding of the institutional backgrounds of international logistics companies in target countries before their performance plans.

• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.253-269
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• 2024

Purpose - The purpose of this study is to investigate the relationship between family CEO and firm value as well as the moderating roles of external corporate governance mechanisms. Design/methodology/approach - Our research model was tested employing a sample of 717 companies listed on the KOSPI securities in South Korea. Family CEO was dummy coded if a family member of the controlling family serves as the firm's CEO. Firm value was measured by Tobin's Q. Findings - A company run by a family CEO has a lower Tobin's Q value compared to its counterpart run by a professional manager. In addition, the negative effect of family CEOs on firm value was alleviated as the level of foreign ownership increased. Similarly, for companies subject to the government's regulations, the negative effect of family CEOs on firm value was found to be mitigated. Research implications or Originality - This study contributes to expanding the existing literature by examining the negative effect of family CEO. In addition, by investigating the moderating effects of external corporate governance mechanisms, it was revealed that the negative effect of family CEOs is alleviated depending on the different types of external corporate governance mechanisms. Based on these findings, theoretical and practical implications are presented.