As global climate change impacts become more apparent, countries are implementing various policies to achieve carbon neutrality that can be categorized into direct regulations and market-based indirect regulations. The latter, utilizing economic incentives, is considered more efficient in transforming corporate behavior and promoting voluntary efforts for carbon reduction. In alignment with international trends, South Korea has introduced the Emission Trading System (ETS) in 2015. Despite this, the domestic carbon market remains underdeveloped, with low ETS participation, particularly in the aquaculture sector. In order to activate external projects under the ETS, this study proposes short-term strategies including linking ETS with popular eco-friendly energy distribution projects, developing standardized monitoring techniques, and integrating carbon reduction initiatives with other support mechanisms such as direct payment programs. Long-term strategies focus on developing new methodologies for external projects, promoting the use of renewable energy, and enhancing technologies to reduce energy consumption in aquaculture operations. By implementing these strategies, the study aims to enhance the participation of the aquaculture sector in carbon reduction efforts, contributing to the overall goal of carbon neutrality.

본 연구는 한국에서 시행 중인 탄소배출권 거래제도가 탄소중립을 달 성하는데 효과적으로 기여하고 효율적으로 작동할 수 있도록 정책적 시 사점을 제공하고자 한다. 이를 위해서, 탄소배출권 가격과 전산업생산지 수의 관계를 분석하였다. 즉, 탄소배출권 가격과 전산업생산지수의 선형 및 비선형 관계를 고려하여 경제학적 모형을 통해 추정 및 분석을 진행 하였다. 분석 방식은 구조변화를 반영한 방식과 임계값(문턱값)을 반영하 는 방식으로 나누어 모형을 구축하고 추정하였다. 그 결과, 한국의 탄소 배출권 가격과 전산업생산지수는 추정한 모형에서 비선형적 관계가 포착 되었다. 이러한 결과는 한국에서 시행 중인 탄소배출권 거래제도가 효율 적으로 작동할 수 있도록 추가적인 정책이 필요함을 시사한다. 예를 들 어, 산업 분야에서 저탄소 공정으로의 전환(또는 저탄소 경제로의 전환) 이 완전히 이루어지지 않은 현실을 고려할 때, 여전히 경제가 성장하는 상황에서 비선형 관계가 포착된다는 것은 탄소배출권 가격이 적정한 수 준을 유지하지 못하고 지속적으로 하락하는 추세를 나타낸다는 것이기 때문이다. 따라서, 탄소배출권 거래제도의 본래 취지인 탄소배출량의 감 축에 기여할 수 있도록 적정한 탄소배출권 가격이 배출권 거래제도하에 서 유지되도록 하는 정책을 고려해야 한다.

Geopolitical risk is now among the most important factors in the formulation of multinational corporate strategy and the US trade policy. The US has aggressively enacted national-security-based trade sanctions, which recently include export controls on semiconductor chips and restrictions on outbound and inbound investment. The US has also adopted major legislation providing historical subsidies and tax breaks. Congress and the courts have upheld the president’s use of national security as a basis of trade actions and generally supported his protectionist policies. Trade should not be restricted or weaponized. Global and national rules need to be strengthened and, perhaps, a bit updated, but protectionism in the name of national security is a losing argument. The growing movement by the US to rely more on national security and protectionism in formulating trade policy is a very worrisome development. No one in Washington is proposing a return to pre-Trump policies. The real question is how far US trade policy will continue to change in the near future. Geopolitics will give us the answer.

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies – Bitcoin, Ethereum, Litecoin, and EOS – and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies – AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet – representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning- based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

Recently, research on prediction algorithms using deep learning has been actively conducted. In addition, algorithmic trading (auto-trading) based on predictive power of artificial intelligence is also becoming one of the main investment methods in stock trading field, building its own history. Since the possibility of human error is blocked at source and traded mechanically according to the conditions, it is likely to be more profitable than humans in the long run. In particular, for the virtual currency market at least for now, unlike stocks, it is not possible to evaluate the intrinsic value of each cryptocurrencies. So it is far effective to approach them with technical analysis and cryptocurrency market might be the field that the performance of algorithmic trading can be maximized. Currently, the most commonly used artificial intelligence method for financial time series data analysis and forecasting is Long short-term memory(LSTM). However, even t4he LSTM also has deficiencies which constrain its widespread use. Therefore, many improvements are needed in the design of forecasting and investment algorithms in order to increase its utilization in actual investment situations. Meanwhile, Prophet, an artificial intelligence algorithm developed by Facebook (META) in 2017, is used to predict stock and cryptocurrency prices with high prediction accuracy. In particular, it is evaluated that Prophet predicts the price of virtual currencies better than that of stocks. In this study, we aim to show Prophet's virtual currency price prediction accuracy is higher than existing deep learning-based time series prediction method. In addition, we execute mock investment with Prophet predicted value. Evaluating the final value at the end of the investment, most of tested coins exceeded the initial investment recording a positive profit. In future research, we continue to test other coins to determine whether there is a significant difference in the predictive power by coin and therefore can establish investment strategies.

본 연구는 중국 C2C 중고거래 플랫폼의 사용자 연구대상으 로 정보기술 수용과 사용 태도에 대해 설명력이 높다고 인정받 고 있는 기술수용모델(TAM)을 토대로 핵심 변수 외 다양화된 정보시스템 환경을 반영하는 변수로 주목받고 있는 지각된 유 희성을 추가 변수로 지정하였다. 본 연구는 가설을 검증하기 위해 중국 C2C 중고거래 플랫폼에 대한 경험 있는 사용자들을 대상으로 조사를 실시하였다. 총 400부의 설문지를 배포하였으 며 회수된 설문지를 선별하여 총 362부 유효 설문지가 선출되 었다. 또한, C2C 중고거래 플랫폼 특성 변인인 정보 대칭성을 규명하고, 이를 바탕으로 정보의 이용 가치를 높이고 활성하기 위한 전략 방향에 시사점을 제시하는 데 그 목적을 둔다. 그리 고 마케팅 연구의 학문적 발전에 기여하고 기업에는 중고 플랫 폼을 활용한 마케팅 전략 수립 시 실무적인 도움을 제공할 수 있을 것으로 기대한다.

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

Investigating major trading partners and items with North Korea is informative in terms that it can predict the path through which North Korea’s strategic items will transfer to non-nuclear-weapon states when North Korea denuclearizes. By analyzing North Korea’s trading partners and the items, it is possible to identify the relevant countries through which items arrive from the first importing country to the end-user in the process of exporting items and to predict the way how North Korea disguise or conceal their strategic items among general items during normal export procedures. As of 2020, North Korea’s major trading partners are China, Russia, Vietnam, India, Nigeria, and Switzerland. Compared to 2019, Mozambique, Tanzania, Ghana, and Thailand entered the top 10, while Brazil, Bangladesh, Pakistan, and South Africa pushed out of the top 10. North Korea’s trade dependence on China accounts for 88.2%, making it the largest trading partner for years, and it shows that North Korea is mainly conducting trade with Asian and African countries. North Korea’s most important export items are mineral products (HS 25-27) and steel & metal products (HS 72-83) and the most significant import items are mineral products (HS 25-27) and oils & fats & prepared foods (HS 15-24). In 2017, due to UN Security Council sanctions for North Korea’s international ballistic missile (ICBM) test-fire, North Korea’s exports from 3 billion dollars fell by 90% to less than 300 million dollars. This is the result of most of North Korea’s major export items included in the export ban, and changes have occurred in its export items. In 2020, export fell to less than 100 million dollars due to border lockdown measures to prevent the spread of COVID-19, which also affected the change of North Korea’s major export items. Although North Korea does not officially publish its foreign trade statistics, in order to review North Korea’s trade information, KOTRA statistics are utilized. KOTRA statistics provide only two digits of HS code number, so it is challenging to identify detailed item classification. Moreover, these statistics are based on the export amount, so it is difficult to determine the exact quantity of export items. It is expected that information on North Korean trading partners and items will be used to predict potential transferable export methods of North Korea’s strategic items when North Korea denuclearizes.

In this study, the differences of institutional development processes of fishery products wholesale markets were compared between Korea and Japan in order to suggest improvement direction of trading system in Korea. The wholesale markets have shrunk while wholesale and distribution has been becoming larger in size in both countries. A summary of differences in the wholesale market trading systems between Korea and Japan is as follows: first, middle wholesalers play pivotal roles in wholesale transaction in Korea, and wholesale corporations take such roles in Japan. Second, most wholesale corporations take charge of listing in Korea whereas such corporations are in charge of buying in Japan. Third, Korea has high proportion of auction for transactions, in contrast to Japan with high proportion of relative transactions. Forth, Korea maintains more sales within the wholesale markers and has more small and medium customers than Japan. Finally, Korea investigates inside causes to find solutions for the decreased competitive power of the wholesale market, whereas Japan copes with the problem by searching for outside customers. To seek solutions for the decreased competitiveness of Korean fishery products wholesale markets, middle wholesalers’ consignment should be limitedly allowed, and improvement direction of wholesale corporations should be investigated in the future study.

오늘날, 정보 기술은 급속도로 발전하고 있으며 기존의 인터랙션 디자인은 더 이상 사용자의 요구를 충족 시키지 못하며 사용자들은 사용자 체험에 대해 더 까다로운 요구를 하고 있다. 사용자 체험의 개념은 이미 디자인의 목적으로 가용성, 용이성에서 감정, 의미의 의도로 확장하고 있다. 감정 인터랙션 디자인은 정보시대 연구자와 디자이너의 관심의 초점이 되어가고 있으며, 이용자 체험 디자인의 새로운 트렌드가 되고 있다. 이런 상황에서 사용자의 정서적 욕구를 충족시키는 것이 중요하다. 본 연구는 기존 카드게임의 사례를 들어 논증하는 방법으로 트레이딩 카드게임에 존재하는 감정 인터랙션 디자인 및 관련 디자인을 분석하였다. 또한 공통적으로 분석 결과를 정리하여 이를 바탕으로 감정 인터랙션 디자인이 트레이딩 카드게임에서 어떤 역할을 하는지 입증했다. 플레이어가 게임을 하면서 느끼는 감정적인 요소를 통해 감정 인터랙션이 게임 디자인에서 갖는 중요한 가치를 밝히고, 디자이너가 게임 디자인을 하면서 감정 인터랙션 디자인을 얼마나 중요시하는지를 보여준다.

국제적으로 신품종과 품종 육성자의 권리가 지적 재산권으로 보호됨에 따라 화훼작물의 경우 국내 민간종묘에서 품종 개발이 거의 이루어지지 않아 농촌진흥청 원예시험장(구 국립 원예특작과학원) 화훼과에서 1992년부터 본격적으로 품종육성 연구가 시작되었다. 2017년 재배면적 44ha, 판매액 93.6억원 인 주요 난류의 하나인 심비디움은 다른 화종에 비해 육종년 한이 길어 2002년에 ‘뷰티프린세스’ 등 4품종이 육성된 후 2017년까지 51품종이 육성되었고, 농촌진흥청 연구비 지원으로 지산영농조합법인에서도 ‘핑크레이스’ 등 26품종이 육성된 바 있다. 이렇게 개발된 품종은 농가에 보급되어 분화나 절화 로 유통되고 있어 최근에는 국산 품종에 대한 재배농가의 인지도가 높아지고 있다. 2009년부터 2017년까지 aT화훼공판장 에서 거래되고 있는 국산 심비디움 품종들의 분화 거래내역을 조사한 결과, 농촌진흥청 개발 51품종 중 21품종이 지산영농 조합 개발 26품종 중 7품종이 1년에서 5년동안 거래된 것을 확인하였다. 국산 품종 거래 수는 2010년과 2015년을 제외하고는 2,568~5,693분으로 총 심비디움 판매량의 1.5~2.1%를 차지하였다. 심비디움 거래량의 65.2~97.6%를 차지하는 꽃대 2, 3, 4대 가격을 비교한 결과, 국산 품종이 외국산 품종에 비하 여 최고가는 낮았지만 평균가는 높았고, 최저가는 훨씬 높았다. 결론적으로 aT화훼공판장 거래가를 기준으로 국산 품종이 외국산 품종과 비교할 때 품질이 양호하였음을 알 수 있었다.

이 연구는 e스포츠 리그에서 발생하는 대리 게임과 어뷰징(고의 패배)의 실태를 조사하고 이를 처벌할 수 있는 새로운 규정 신설을 주장하기 위한 목적이 있다. 연구 대상은 일반 게임 유저 40명, e 스포츠 리그 선수 17명, 총 57명의 인원을 대상으로 설문조사를 진행하였다. 연구 결과, 선수 유저는 가즈릴라 경험 비율이 높았으며, 가즈릴라를 통해 게임 등수를 쉽게 높일 수 있을 것이라 생각 하였으며 대리 게임이라 생각하지 않는다. 반면 일반 게임유저는 가즈릴라 경험 비율이 낮고, 가즈 릴라를 통해 게임 등수를 높일 수 있을 것이라 생각하지 않지만 대리 게임이라 생각하는 경향이 강하다. 선수 유저 집단과 일반 유저 집단이 가즈릴라를 다르게 바라보고 있으며, 선수 유저 집단과 일반 유저 집단 모두 가즈릴라와 대리 게임에 대한 규정의 필요성은 공감하고 있다. 가즈릴라와 대리 게임에 대한 규정 확립을 통해 선수 유저 집단과 일반 유저 집단의 인식의 차이를 좁혀나가야 한다.

This study advances the literature by addressing the issues surrounding Sunday trading and provides in-depth insights into family-run small and medium size businesses (SMEs), employees and consumers attitudes and perception towards Sunday Trading. The results of semi-structured interviews found immense support for extending Sunday Trading hours and highlighted the socio-economic change. The arguments against Sunday Trading were found to be redundant. Sunday is the second busiest shopping day of the week. Lack of experienced Sunday workforce was found to be a major concern. Non-resident parents and parents with small children were amongst the supporters for reforming Sunday Trading act. Sunday is the new Saturday. The findings justify recent trends towards the creation of more pleasurable shopping environments that offer family activities to entice the customers into stores. Finally, more efforts should be made to understand and cater for the needs of the shoppers who believe reforming the Sunday Trading law is a necessity of today’s modern Britain. The findings demonstrate that Sunday Trading offers different benefits to consumers, employees and SMEs. The findings provide important implications for policy makers and practitioners.

The objective of this study was to empirically analyze the shipping method and trading intent of landscaping tree farms. The analysis used survey data on landscaping tree seedling farms. Crosstabs were utilized to analyze the shipping method and characteristics of landscaping trees, and a binary logistic regression to analyze the trading intent. The results were as follows: The most common shipping method used by landscaping tree farms was “agricultural forward contract,” followed by “delivery of goods by individuals to middlemen.” However, “direct dealing with the ordering body” was the most desired in the long run. Among the characteristics of farms desiring direct dealing with the ordering body, variables that showed statistical significance were “experience in producing landscaping trees,” “whether landscaping tree production is a full-time profession,” “awareness of retail prices of landscaping trees,” and “difficulty in finding market and price information related to shipping.” In particular, more experience in producing landscaping trees led to a lower probability of direct dealing. Moreover, farms specializing in landscaping trees, farms aware of retail prices, and farms that had difficulty determining market or price information were more likely to focus on direct dealing.

미 연방 제2순회 항소법원은 2012년 10월에 중요한 내부자거래 판결 인 오부스(SEC v. Obus) 판결을 내렸는데, 그 판결은 내부자거래 요건 을 명확하게 제시하고 있다. 그리고 내부자를 기소하기 위하여는 개인적 이득에 관한 입증이 요구되는데도 불구하고 법원은 정보가 부당하게 공 개되었다거나 혹은 내부 정보원이 개인적 이득과 교환으로 정보를 제공 하였다는 것을 실제로 알지 못할 수도 있는 정보수령자에 대하여 잠재적 책임의 범위를 확대하였다. SEC는 지이(GE) 캐피털의 직원 토마스 스트릭랜드(Strickland), 그리 고 윈필드(Wynnefield) 캐피털의 직원 두 사람 피터 블랙(Black)과 넬 선 오부스(Obus)에 대하여 내부자거래 위반으로 기소하였다. SEC는 스 트릭랜드가 자신의 대학 친구인 블랙에게 지이 캐피털이 자금을 대출해 주고 있던 얼라이드(Allied) 캐피털 회사가 선소스(SunSource) 회사를 인수할 가능성에 관하여 정보를 전달하였다고 주장하였다. 블랙은 차례 로 이 정보를 오부스에게 넘겼고, 오부스는 그 정보를 토대로 선소스 주 식을 거래하였다는 혐의를 받았다. 미 연방 뉴욕 남부지방 지방법원이 피고인에 유리한 약식재판을 승인 하였고, SEC는 부정유용이론의 관점에서 항소하였다. 제2순회 항소법원 은 SEC가 제시한 증거는 각 피고인의 책임에 관한 중요한 사실에 관한 진정한 논쟁을 제기하며, 따라서 약식재판은 잘못되었다고 판결하였다. 그리하여 항소법원은 그 판결을 파기 환송하였다. 이 판결에서 그 항소 법원은 (1) 정보전달자와 정보수령자의 책임의 요소들을 분명하게 하였 고, (2) 양 정보전달자와 정보수령자의 고의 요건에 관하여 완화된 견해 를 채택하였고, (3) SEC는 정보전달자가 내부자거래의 부정유용이론과 전통적이론 두 이론에서 개인적 이득을 받았다는 것을 입증하여야 한다 고 판결하였고, 그러나 이것은 SEC가 입증하기에 어려운 요소는 아니라 는 것을 경고하였으며, (4) 내부정보원이 개인적 이익을 받았다는 것을 정보수령자가 알지 못하고 책임을 부담할 수 있는지 여부의 문제에 대하 여는 미해결 상태로 남겨놓았다.

OBJECTIVES: Currently, the market for carbon emissions trading has been increasing. In Korea, it is known that traffic mode rate in bike transportation is low. However, if bike transportation system is encouraged and the traffic mode rate is increased, it would be possible to reduce carbon emissions through the trading market. In this study, a practical policy to activate the bike transportation system in Korea will be proposed and verified. METHODS: Past studies regarding bike transportation system in international and domestic metropolitan cities were analyzed. Moreover, detailed reviews on recent carbon emissions trading market were performed. In particular, SWOT analysis on the bike transportation system in Korea and policy topology analysis were conducted. RESULTS: Based on the literature reviews and SWOT analysis, a new bike transportation policy was proposed. Several actual plans to adopt in Korea were proposed. In addition, a new bike transportation policy was analyzed using policy typology model, and a business model related to the cost of implementing the system and CERs were also proposed. CONCLUSIONS : It is concluded that the proposed bike transportation activation policy and several practical plans to connect CERs and a business model including bus, subway, T-money and bike riders to give some incentive were effective and reasonable. It is desired that this study will help Korea to get CERs through bike transportation activation in the future.