• Title/Summary/Keyword: Competitive Climate

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Ambidextrous Leadership and Innovative Work Behavior: Evidence from South Korea Semiconductor Industry (양손잡이 리더십과 혁신적인 업무 행동: 한국 반도체 산업의 증거)

  • Henry Ameyaw Domfeh;Henry Ofori;Sora Yoon;Juyoung Kang
    • Journal of Information Technology Services
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    • v.22 no.3
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    • pp.1-27
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    • 2023
  • The semiconductor industry is a competitive, complicated and a cyclical sector with a highly dynamic business climate which requires an effective leadership style to operate and succeed. This study explores the important issue of how leadership facilitates employee innovative work behaviors in the semiconductor industry. Based on the assumptions of the ambidextrous leadership theory and social exchange theory, we collected data from 300 workers employed in the semiconductor industry of South Korea. The study investigated (1) the impact of ambidextrous leadership on innovative work behavior, (2) the mediating effects of workers decision-making autonomy and workplace learning in the relationship between ambidextrous leadership and innovative work behavior, (3) the moderating role of resistance to change in the relationship between ambidextrous leadership and workplace learning, and (4) the moderating role of openness to experience in the relationship between ambidextrous leadership and innovative work behavior. SmartPLS 4 and SPSS v24 was used to analyze our data. The study revealed that ambidextrous leadership positively influences workers innovative work behavior. In addition, decision-making autonomy and workplace learning partially mediated the relationship between ambidextrous leadership and innovative work behavior. Moreover, resistance to change was found to be a significant moderator in the relationship between ambidextrous leadership and workplace learning. Based on these findings, we conclude that ambidextrous leadership is very imperative for semiconductor businesses seeking to foster employee innovative work behaviors. Theoretical and practical implications of the study are also discussed.

Can Artificial Intelligence Boost Developing Electrocatalysts for Efficient Water Splitting to Produce Green Hydrogen?

  • Jaehyun Kim;Ho Won Jang
    • Korean Journal of Materials Research
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    • v.33 no.5
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    • pp.175-188
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    • 2023
  • Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

A Study on the Automation of Fish Species Identification and Body Length Measurement System (어종 인식 및 체장 측정 자동화 시스템에 관한 연구)

  • Seung-Beom Kang;Seung-Gyu Kim;Sae-Yong Park;Tae-ho Im
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.17-27
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    • 2024
  • Overfishing, climate change, and competitive fishing have led to a continuous decline in fishery production. To address these issues, the Total Allowable Catch (TAC) system has been established, which sets annual catch quotas for individual fish species and allows fishing only within those limits. As part of the TAC system, land-based investigators measure the length and height of fish species at auction markets to calculate the weight and TAC depletion. However, the accuracy of the acquired data varies depending on the skill level of the land-based investigators, and the labor-intensive nature of the work makes it unsustainable. To address these issues, this paper proposes a fish species recognition and length measurement system that automatically measures the length, height, and weight of eight TAC-managed fish species using the camera of a smart pad that can measure the distance to the water surface. This system can help to automate the current labor-intensive work, minimize data loss, and facilitate the establishment of the TAC system.

Comparison of Solar Power Generation Forecasting Performance in Daejeon and Busan Based on Preprocessing Methods and Artificial Intelligence Techniques: Using Meteorological Observation and Forecast Data (전처리 방법과 인공지능 모델 차이에 따른 대전과 부산의 태양광 발전량 예측성능 비교: 기상관측자료와 예보자료를 이용하여)

  • Chae-Yeon Shim;Gyeong-Min Baek;Hyun-Su Park;Jong-Yeon Park
    • Atmosphere
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    • v.34 no.2
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    • pp.177-185
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    • 2024
  • As increasing global interest in renewable energy due to the ongoing climate crisis, there is a growing need for efficient technologies to manage such resources. This study focuses on the predictive skill of daily solar power generation using weather observation and forecast data. Meteorological data from the Korea Meteorological Administration and solar power generation data from the Korea Power Exchange were utilized for the period from January 2017 to May 2023, considering both inland (Daejeon) and coastal (Busan) regions. Temperature, wind speed, relative humidity, and precipitation were selected as relevant meteorological variables for solar power prediction. All data was preprocessed by removing their systematic components to use only their residuals and the residual of solar data were further processed with weighted adjustments for homoscedasticity. Four models, MLR (Multiple Linear Regression), RF (Random Forest), DNN (Deep Neural Network), and RNN (Recurrent Neural Network), were employed for solar power prediction and their performances were evaluated based on predicted values utilizing observed meteorological data (used as a reference), 1-day-ahead forecast data (referred to as fore1), and 2-day-ahead forecast data (fore2). DNN-based prediction model exhibits superior performance in both regions, with RNN performing the least effectively. However, MLR and RF demonstrate competitive performance comparable to DNN. The disparities in the performance of the four different models are less pronounced than anticipated, underscoring the pivotal role of fitting models using residuals. This emphasizes that the utilized preprocessing approach, specifically leveraging residuals, is poised to play a crucial role in the future of solar power generation forecasting.

Toward Post-Pandemic Sustainable FDI Workforce: An Examination of Factors Affecting the Well-Being of Migrant Workers in Ho Chi Minh City

  • Pham Thanh Thoi;Tran Dinh Lam;Nguyen Hong Truc
    • SUVANNABHUMI
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    • v.16 no.1
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    • pp.303-343
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    • 2024
  • Globalization and the flow of foreign direct investment (FDI) in the post-pandemic context continue to play a critical role in shaping the workforce of emerging countries. In Vietnam, evidence obtained during the pandemic revealed that the well-being of employees, especially migrant workers, was extremely poor due to both work and non-work factors. This paper examines the most significant factors that impact the well-being of workers employed by various FDI companies in two Vietnamese industrial parks. The survey evidence (n=200) shows that worker well-being is influenced by seven key factors categorized in three dimensions, namely material stressors, social stressors, and human stressors. A further qualitative analysis of 60 participants provides an understanding of the ways in which each factor affects workers' well-being and how elements of well-being in the Vietnamese context are different compared with other countries. Low salaries, lack of social support, work-life imbalance due to job demands, and the interplay between these three determinants significantly affect the overall well-being of workers. In the current business climate, it is important to have well-targeted policies that encourage high-tech investments as well as persuade domestic firms to address low salaries and economic migration. To manage valuable human resources and keep competitive advantages, foreign firms need to authentically implement corporate social responsibility (CSR) initiatives focusing on workers' benefits, especially providing workforce housing. This will bring about win-win outcomes of improved employee well-being and business sustainability.

Comparison on Ecological Index Characteristics between Zacco platypus and Zacco koreanus by Stream order in Korea (하천차수에 따른 피라미와 참갈겨니 개체군의 생태지표 특성 비교)

  • Lee, Seung-Hyun;Jeong, Hyun-Gi;Shin, Hyun-Seon;Shin, Yuna;Lee, Su-Woong;Lee, Jae-Kwan
    • Korean Journal of Ecology and Environment
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    • v.50 no.4
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    • pp.403-410
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    • 2017
  • We collected fishes at the 12,873 sites in stream order (1~7) from 2008 to 2016. In the results, two populations(Zacco platypus and Zacco koreanus) represented distributional differences in the stream order gradient, and correlation analysis showed that the two populations had a potential competitive relationship. The ecological characteristics of the fish except for the Z. platypus and the Z. koreanus, according to the gradient of stream order showed a pronounced gradient in the species such as intermediate species, sensitive species, carnivores, herbivores and omnivores. The two populations showed a high correlation between intermediate species, sensitive species of the tolerance guild and omnivores, insectivores of the trophic guild. Fish assessment index (FAI) was negative relation with stream order. According to the stream order gradient, the two populations showed different correlations with FAI.

Employee's Long Term Orientation's Effect on Change Oriented Organizational Citizenship Behavior with Emotional Regulation Mediating (대기업 구성원의 장기지향성이 감성활용과 변화 조직시민행동에 미치는 영향)

  • Kang, Yoonhee
    • The Journal of the Korea Contents Association
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    • v.19 no.10
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    • pp.315-324
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    • 2019
  • In this research, one of five Hofstede's cultural dimension, Long term orientation (LTO) was selected to examine its influence on individual's change oriented organizational citizenship behavior with emotional regulation mediating. East Asian countries and Korea especially received higher score on LTO cultural dimension, meaning it valued harmony, long term relations and saving for future. Also, in today's hyper competitive and evolving global climate, the ability to adapt quickly and also to be able to control one's emotion is highly valued individual competency. Previous research on Hofstede's cultural dimensions were conducted at mostly national or large group levels. However, in this study, Yoo's CVSCALE which allowed for individual level analysis on Hofstede's cultural dimensions were used to analyze multinational company's employees's long term orientations' influence on emotional regulation and change oriented organizational citizenship behavior. The survey conducted from 200 employees from major electronic company based in S city in Korea for two weeks period and the results indicated long term orientation positively influenced change oriented organizational citizenship behavior. Also emotional regulation mediated between long term orientation felt by individuals and change oriented organizational citizenship behavior. Such results validated previous studies that indicated emotional regulation as possible antecedents of individual proactive behaviors such as change organizational citizenship behavior and long term oriented view as another potential antecedent of change oriented organizational citizenship behavior in multinational corporation setting.

Research Trend on ESG Management of Corporation (기업의 ESG 경영에 대한 국내·외 연구동향)

  • Byun, Youngjo;Woo, Seung Han
    • Clean Technology
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    • v.28 no.2
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    • pp.193-200
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    • 2022
  • The term environmental, social and governance (ESG) was first used in the 2003 United Nations Environmental Programme Finance Initiative (UNEP FI). Among the three areas of ESG, environment refers to the impact of companies on the environment. Environmental factors address climate change policies and attempts to reduce emissions, waste and natural resource consumption. Social factors refer to the direction in which a company can improve the social impact of stakeholder includes employees, customers, communities, and governments involved in direct or indirect interaction with the organization itself and the company. Governance factors refer to stakeholders who make major decisions, the composition of the board of directors, their diversity and independence, and the internal policies that set limits and expectations for decision-making. Research related to ESG management is part of corporate social responsibility, sustainability, corporate or financial performance, and social responsibility investment. Through case studies and data-based empirical studies, it was confirmed that ESG management companies had positive results for most of the ESG related fields. Through literature analysis of domestic and international ESG history, introduction background, and management performance, this paper presents theoretical, practical implications by confirming that ESG's introduction and operation strategies are strong competitive strategies that directly affect corporate growth by creating attractive factors.

Recent Trends in The Production of Polyhydroxyalkanoates Using Marine Microorganisms (해양 미생물에 의한 폴리하이드록시알카노에이트 생산의 최근 동향)

  • Seon Min Kim;Hye In Lee;Hae Su Jeong;Young Jae Jeon
    • Journal of Life Science
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    • v.33 no.8
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    • pp.680-691
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    • 2023
  • Peak oil, climate change, and microplastics caused by the production and usage of petroleum-based plastics have threatened the sustainability of our daily life, and this has emerged as a recent global issue. To solve this global issue, the production and usage of biodegradable eco-friendly bioplastics such as polyhydroxyalkanoates (PHAs) has been suggested as an alternative. Therefore, in this review, the present status of global PHA manufacturers, the advantages of the production of PHAs using marine-origin microorganisms (with their productivity potential) and further required research and development strategies for cost-competitive production of PHAs using marine-based microorganisms were investigated. In this review, PHAs produced from marine microorganisms were found to have similar physical properties to petroleum-based plastics but with several advantages that can reduce the costs of PHA production. Those advantages include, seawater used in the medium preparation step, and osmotic-based cell lysis technology used in the separation and purification steps. However, the PHA productivities from marine microorganisms showed somewhat lower efficiencies than those from the commercial strains isolated from terrestrial environments. In order to solve the problem, further research strategies using synthetic microbiology-based technology, the development of long-term continuous culture technology, and solutions to improve PHA efficiency are required to meet future market demands for alternative bioplastics.

Life Cycle Assessment (LCA) of the Wind Turbine : A case study of Korea Yeongdeok Wind Farm (한국 영덕 풍력단지 사례 연구를 통한 풍력 발전의 환경 영향 평가)

  • Jun Heon Lee;Jun Hyung Ryu
    • Korean Chemical Engineering Research
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    • v.61 no.1
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    • pp.142-154
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    • 2023
  • As the importance of the environment has been recognized worldwide, the need to calculate and reduce carbon emissions has been drawing an increasing attention throughout various industrial sections. Thereby the discipline of LCA (Life Cycle Assessment) involving raw material preparation, production processes, transportation and installation has been established. There is a clear research gap between the need and the practice for Korean Case of renewable energy industry, particularly wind power. To bridge the gap, this study conducted LCA research on wind power generation in the Korean area of Yeongdeok, an example of a domestic onshor wind power complex using SimaPro, which is the most widely used LCA system. As a result of the study, the energy recovery period (EPT) of one wind turbine is about 10 months, and the GHG emitted to generate power of 1 kwh is 15 g CO2/kWh, which is competitive compared to other energy sources. In the environmental impact assessment by component, the results showed that the tower of wind turbines had the greatest impact on various environmental impact sectors. The experience gained in this study can be further used in strengthening the introduction of renewable energy and reducing the carbon emission in line with reducing climate change.