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Though logistics security only took care of trading phase in the past, many countries in the world have begun to introduce logistics security system as its coverage has been extended from production stage to delivery at the final destination. Logistics security system has become indispensable element for global corporations involved in international trading and studies on logistics security keep going on. Most of the studies, however, are focused on discussion of system, cost and influence of logistics security and few of them have been specifically dealing with substantial effectiveness thereof. This study developed the models of supply chain security activities and their outcome by means of using Balanced Scorecard (BCS) which is a well known performance indicator to identify relationship between supply chain security activities and their accomplishment. In this study we have presented 8 supply chain frameworks, human resources management, information system management, facilities/freight management, security process, crisis management capability, relationship with partners, sharing of logistics information and logistics security accomplishment, with reference to standards of C-TPAT and AEO based on WCO framework, 10 supply chain security capabilities. This study further indicates that relationship with partners has more effect on logistics security accomplishment than sharing of logistic information. Just as relationship between corporations in chain of supply and sharing of information among them are important elements in management of supply chain, relationship with partners and sharing of logistic information will have positive effect on supply chain security accomplishment and raise its effectiveness.

The main streams of the supply chain are defined as material, information and financial flow. There have been many studies and practical cases regarding the flow of material and information including information sharing. However, financial flow related studies have not been widely examined relatively, compared with their importance.

The information sharing is recognized as the method that can reduce the Bullwhip effect in supply chain management. The author intends to analyze the impact of financial information sharing on the results of the supply chain.

In the point of supply chain risk management view, the author examined the impact of financial flow among the various factors that can impede the stability of the supply chain.

In this study, the author embodied the simulation regarding the impact of financial information flow on supply chain performance and stability based on the system dynamics methodology and analyzed the performance.

Assuming the supply chain, composed of supplying company, manufacturing company and sales company , the author embodied the simulation model and assumed that working capital and cash information sharing were achieved. The author embodied the model to affect the settlement conditions according to the results of financial information sharing.

Global value changes continued to expand until the late 2000s. On the other hand, regional value chains have formed around major regional hubs due to the expansion of domestic demand in emerging economies, such as China, and strengthened trade protectionism since the global financial crisis. Such changes lead to the reorganisation of value chains, focusing on domestic markets (reshoring) or neighbouring countries (nearshoring). In particular, the importance of supply chain risk management has been highlighted following disruptions to the supply network due to the COVID-19 outbreak in December 2019. In this regard, major countries such as the USA and the EU are rapidly shifting to regional value chains for stable and sustainable production, rather than primarily aiming for production efficiency targeted at reducing costs. Industries in particular are more exposed to such supply chain risks under the existing structure and it now has become extremely important for businesses to take reaction to such risks. This is especially important for major industries in a country such as automobile or semiconductor manufacturing industries in South Korea. The aim of this study, therefore, is to establish the basis for the simultaneous growth of ports and linked industries by examining the existing structure of the global value chain for the automotive industry, which has a strong presence in South Korea’s domestic economy. In this regard, this research carries out a supply chain analysis focusing on the imports and exports of automotive parts. It also analyses the current structural risks and suggests risk management measures to secure a stable supply chain.

This paper investigates a retrospective on the Journal of Derivatives and Quantitative Studies (JDQS) on its 30th anniversary based on bibliometric. JDQSs yearly publications, citations, impact factors, and centrality indices grew up in early 2010s, and diminished in 2020. Keyword network analysis reveals the JDQS's main keywords including behavioral finance, implied volatility, information asymmetry, price discovery, KOSPI200 futures, volatility, and KOSPI200 options. Citations of JDQS articles are mainly driven by article age, demeaned age squared, conference, nonacademic authors and language. In comparison between number of views and downloads for JDQS articles, we find that recent changes in publisher and editorial and publishing policies have increased visibility of JDQS.

This paper aims to replicate 148 anomalies and to examine whether the performance of the Korean market anomalies is statistically and economically significant. First, the authors observe that only 37.8% anomalies in the universe of the KOSPI and the KOSDAQ and value-weighted portfolios have t-statistics that exceed 1.96. When the authors impose a higher threshold (an absolute value of t-statistics of 2.78), only 27.7% of the 148 anomalies survive. Second, microcaps have large impacts. The results vary significantly depending on whether the sample included stocks in the KOSDAQ and whether value-weighted or equal-weighted portfolios are used. The results suggest that data mining explains large portion of abnormal returns. Any tactical asset allocation strategies based on market anomalies should be applied very cautiously.