간행물

한국산업경영시스템학회지 KCI 등재 Journal of Society of Korea Industrial and Systems Engineering

권호리스트/논문검색
이 간행물 논문 검색

권호

Vol. 47 No. 1 (2024년 3월) 6

1.
2024.03 구독 인증기관 무료, 개인회원 유료
This study analyzed the impact of Higher-order resources on profit sustainability for domestic companies using a mathematical statistical model. Higher-order resources refer to resources that do not directly affect profits but influence other resources that directly contribute to profits. As a result of analysis using 30 years of actual data from more than 650 domestic companies, the average duration of competitive advantage including high-order resources was found to be about twice as long as the period suggested by the autoregressive model excluding high-order resources. Through this, if companies want to earn more profits over a long period of time than their competitors, they must not only possess resources that are more valuable, rare, difficult to imitate, and non-substitutable compared to their competitors, but also that higher-order resources can contribute to changes in these resources over time. It was confirmed that it must lead the long-term profit difference. High-level resources include strategic planning, mergers and acquisitions (M&A) capabilities, and good forecasting.
4,000원
2.
2024.03 구독 인증기관 무료, 개인회원 유료
Deep learning-based computer vision anomaly detection algorithms are widely utilized in various fields. Especially in the manufacturing industry, the difficulty in collecting abnormal data compared to normal data, and the challenge of defining all potential abnormalities in advance, have led to an increasing demand for unsupervised learning methods that rely on normal data. In this study, we conducted a comparative analysis of deep learning-based unsupervised learning algorithms that define and detect abnormalities that can occur when transparent contact lenses are immersed in liquid solution. We validated and applied the unsupervised learning algorithms used in this study to the existing anomaly detection benchmark dataset, MvTecAD. The existing anomaly detection benchmark dataset primarily consists of solid objects, whereas in our study, we compared unsupervised learning-based algorithms in experiments judging the shape and presence of lenses submerged in liquid. Among the algorithms analyzed, EfficientAD showed an AUROC and F1-score of 0.97 in image-level tests. However, the F1-score decreased to 0.18 in pixel-level tests, making it challenging to determine the locations where abnormalities occurred. Despite this, EfficientAD demonstrated excellent performance in image-level tests classifying normal and abnormal instances, suggesting that with the collection and training of large-scale data in real industrial settings, it is expected to exhibit even better performance.
4,200원
3.
2024.03 구독 인증기관 무료, 개인회원 유료
Determining the number of operators who set up the machines in a human-machine system is crucial for maximizing the benefits of automated production machines. A man-machine chart is an effective tool for identifying bottlenecks, improving process efficiency, and determining the optimal number of machines per operator. However, traditional man-machine charts are lacking in accounting for idle times, such as interruptions caused by other material handling equipment. We present an adjusted man-machine chart that determines the number of machines per operator, incorporating idleness as a penalty term. The adjusted man-machine chart efficiently deploys and schedules operators for the hole machining process to enhance productivity, where operators have various idle times, such as break times and waiting times by forklifts or trailers. Further, we conduct a simulation validation of traditional and proposed charts under various operational environments of operators’ fixed and flexible break times. The simulation results indicate that the adjusted man-machine chart is better suited for real-world work environments and significantly improves productivity.
4,000원
4.
2024.03 구독 인증기관 무료, 개인회원 유료
Maintaining the permanence of a company in the current rapidly changing business environment is not an easy task. Rather, the lifespan of a company can be said to be gradually decreasing. As such, the author of this paper, which describes the current market environment, is the sales organization of a large company. While leading the company, I thought about how to overcome the rapidly changing market and create an organization that continues to grow. As a result, I succeeded in creating an organization that continued to grow over the past two years, and the main activity of this result was the use of sales computer. It was clear that it was an information sharing activity. This can be said to be a result of proving that a series of activities to create and share information is important for the sales organization of ICT companies to actively respond to the rapidly changing market environment. Therefore, this study attempted to examine the relationship between knowledge management and business performance in the sales field of ICT companies, which has not been covered so far. Knowledge management is a four-stage activity from a process perspective, divided into knowledge creation, knowledge storage, knowledge transfer, and knowledge utilization. did. As a result of the study, first, knowledge management activities, such as knowledge creation and knowledge storage, were found to have a significant impact on financial performance. Second, knowledge management activities such as knowledge creation, knowledge storage, knowledge transfer, and knowledge utilization were all found to have an impact on non-financial performance. In the end, this study confirmed that efforts to turn tacit knowledge into knowledge in order to respond to the ever-changing ICT market are ultimately an important factor in growing a company.
4,500원
5.
2024.03 구독 인증기관 무료, 개인회원 유료
Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.
4,000원
6.
2024.03 구독 인증기관 무료, 개인회원 유료
Recently, ESG management has become a global trend, receiving increasing attention from stakeholders such as consumers, investors, and governments, as regulations related to ESG disclosure and supply chain due diligence have been strengthened since the United Nations Principles of Responsible Investment (UN PRI) was announced in 2006. ESG is an acronym for the environment (E), social (S), and governance (G) and is accepted as a key factor for the continuous survival and growth of a company. As a result, there are over 600 ESG management evaluation indicators operated domestically and internationally, and numerous global initiatives have emerged. Korea’s Ministry of Trade, Industry and Energy also announced “K-ESG Guidelines (December 2011)” and “K-ESG Guidelines for Supply Chain Response (December 22)” to help SMEs introduce ESG management and respond to supply chain due diligence. However, small-scale manufacturing companies with poor financial, human resources, and technological capabilities face significant challenges in introducing ESG management. Accordingly, this study aims to examine the current status of ESG management adoption in small-scale manufacturing companies with less than 150 people in Korea and propose activation plan ESG management based on the diagnostic requirements of the “Supply Chain Response K-ESG Guidelines.”
4,000원