• Title/Summary/Keyword: 인센티브 메커니즘

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A Study on Technological Innovation Efficiency of Listed Companies in China's Digital Cultural Industry (중국 디지털 문화산업 상장기업의 기술혁신 효율성에 관한 연구)

  • Dong, Hao;Bae, Ki-Hyung;Zhang, Mengze
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.369-379
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    • 2022
  • With the deepening integration of technology and cultural industries, China's digital cultural industry has begun to rise. The digital culture industry has met new demands for cultural consumption and brought new experiences to consumers in the digital economy era. This paper uses the public data of 36 Chinese A-share listed companies in digital culture from 2018 to 2019 to construct a technical innovation efficiency evaluation index system for listed companies in China's digital cultural industry. Through the use of data envelopment analysis (DEA) method, the technical innovation efficiency of 36 listed companies in China's digital cultural industry was evaluated. The research results show that: (1) China's 36 listed companies have low technological innovation efficiency; (2) the allocation of R&D resources of listed companies is unreasonable; (3) there is a large difference in technological innovation efficiency among listed companies. Therefore, it is necessary to increase the efficiency of technology innovation of listed companies in China's digital culture industry by investing more R&D funds, distributing R&D resources, establishing effective dynamic incentive mechanism, promoting government-industrial-academic research.

Hybrid Offloading Technique Based on Auction Theory and Reinforcement Learning in MEC Industrial IoT Environment (MEC 산업용 IoT 환경에서 경매 이론과 강화 학습 기반의 하이브리드 오프로딩 기법)

  • Bae Hyeon Ji;Kim Sung Wook
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.9
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    • pp.263-272
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    • 2023
  • Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

Korean Companies' Understanding of Carbon Pricing and Its Influence on Policy Acceptance and Practices (한국 기업의 탄소가격 정책에 대한 이해가 정책 수락 및 대응에 미치는 영향)

  • Suk, Sunhee
    • Environmental and Resource Economics Review
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    • v.26 no.4
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    • pp.577-612
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    • 2017
  • In response to climate change, Korea is attempting to shift the paradigm of energy and climate change policies by introducing carbon pricing based on market mechanisms. While policy adoption is proceeding at a rapid pace, the introduction of carbon pricing has been faced with great opposition from industry. This study measures to what extent Korean companies understand and accept carbon pricing, using data from a questionnaire survey covering energy consuming companies in 2012, when discussions between the government and such companies about the introduction of a domestic emission trading system were active. It further identifies how preparations and practices for carbon and energy management of companies correlate with their policy understanding and acceptance. The analysis results show that the surveyed companies indicate moderate understanding of, as well as resistance to carbon pricing policies, while appreciating the economic incentives and accepting the mandatory regulations in this phase. Companies' understanding is more related to characteristics, i.e., sector, size, etc. than external pressures. This study found that the extent to which companies understand policy is the essential factor in their policy acceptance and related practices. In particular, understanding of carbon policy significantly influences their managerial practices and voluntary activities for carbon and energy practices. This study substantiates the correlation between the level of policy understanding of a company and its carbon and energy practices - something that all countries seeking to introduce carbon pricing in response to climate change should consider prior to policy actually being implemented; in other words, enhancing the understanding of major policy subjects of the new instrument is a key policy strategy that should be elaborated as it will lead to better performance of companies and smoother policy implementation.