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This paper analyzes two external costs often associated with port development, cost to fisheries from marine dredge disposal and damages from air pollution, using estimates of development and operation for a proposed (but since cancelled) container port as a case study. For dredge disposal, a bio-economic model was used to assess short- and long-term and indirect (joodweb) damages to fisheries from marine disposal of clean sediments. In the case of air pollution, estimates of annual activity levels and emission coefficients are used to estimate incremental annual emissions of three key pollutants (NOx, HC and CO) for trucks, trains, yard vehicles, and vessels. These estimates allow for phasing in of strict new air pollution regulations. For both external costs, sensitivity analyses are used to reflect uncertainty. Estimates of shadow values in year 2002 dollars amount from $0.094 per cubic yard to $0.169 per cubic yard of clean dredged material for the selected disposal site and from $0.0584 per mile (jor current control standards) to $ 0. 0023 per mile (after phasing in of new regulations) for air pollution from heavy trucks.

The proliferation of customer-related data provides companies with numerous service opportunities to create customer value. The purpose of this study is to develop a framework to use this data to provide services.

This study conducted four action research projects on the use of customer-related data for service design with industry and government. Based on these projects, a practical framework was designed, applied, and validated, and was further refined by analyzing relevant service cases and incorporating the service and operations management literature.

The proposed customer process management (CPM) framework suggests steps a service provider can take when providing information to its customers to improve their processes and create more value-in-use by using data related to their processes. The applicability of this framework is illustrated using real examples from the action research projects and relevant literature.

“Using data to advance service” is a critical and timely research topic in the service literature. This study develops an original, specific framework for a company’s use of customer-related data to advance its services and create customer value. Moreover, the four projects with industry and government are early CPM case studies with real data.

The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap.

“Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services.

Drawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research.

“Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

The centralized processes of today’s power trading systems are complex and pose a risk of price tampering and hacking. The decentralized and unmodifiable nature of the blockchain technology that has recently been highlighted offers the potential to improve this power trading process. The purpose of this study is to implement a system to apply the blockchain technology to the problem of power trading.

The authors modeled the power trading problem as the interaction between admin, producer and consumer nodes. And a power trading scenario has been created for this model using a blockchain platform called Multichain which is both fast and highly scalable. To verify this scenario, they implemented a trading system using Savoir, a Python-based JsonRPC module.

Experimental results show that all processes, such as blockchain creation, node connectivity, asset issuance and exchange transactions have been correctly handled according to the scenario.

In this study, the authors have proposed and implemented a power trading method that determines price according to the pure market principle and cannot be manipulated or hacked. It is based on the nature of blockchain technology that is decentralized and cannot be tampered.

The major economies of East Asia, namely Japan and the Four Asian Tigers, have always prioritized the WTO-led multilateral trade liberalization over other trade arrangements primarily due to their unique economic structure with a high dependency on the world’s major markets such as the US. Along the same line, even the huge blow from the Asian Financial Crisis in 1997 only managed to trigger a few initiatives to aide East Asian regional integration while being led by different centering bodies, APEC and ASEAN. These dispersed efforts naturally resulted in no realistically significant achievements in the light of ‘integration’ until the present day. Under these circumstances, East Asia now faces a second opportunity to achieve its economic independence from the extra-regional influences via regionalization: the 2009 Global Credit Crunch. This paper hereupon critically reviews the actual progress and the likely impacts of the current global recession on the East Asian region.

This study aims to find how the turnover of host country nationals (HCNs) would be affected by the knowledge transfer from a headquarter to a subsidiary. Knowledge transfer in a multinational corporation (MNC) has been discussed as a critical factor in the MNC’s success. Because HCNs are essential to synergizing with a new knowledge inflow during this knowledge transfer process, their turnover entails negative consequences such as knowledge loss.

This paper empirically tests the unbalance between knowledge received (KR) and absorptive capacity (AC) as the most critical organizational predictor by using the secondary longitudinal records and survey data of 4,915 employees. Multilevel survival analysis is used to calculate the individuals’ turnover hazard.

While finding that the primary effect of transferred knowledge is to reduce turnover, the study demonstrates the unbalance between a subsidiary’s AC and KR increases the likelihood of HCNs’ turnover within the organization. The authors also recognize the possibility of nonlinear trends of KR and AC on the turnover hazard.

The authors answer how knowledge transfer shapes a subsidiary’s work environment to prevent or increase turnover, which has been barely examined for HCNs who comprise the crucial demographic group in knowledge transfer. To enhance the originality further, this study empirically observes the actual turnover of HCNs with a conceptually comprehensive view incorporating both learning and political approaches.

Among various distinctive formulations that have been developed simultaneously in East Asia as of 2009, this paper selected three major paths, ASEAN+3, ASEAN+6 and APEC, to quantitatively examine the economic impacts of Asian regionalization with the CGE model. This paper confirmed previous findings such as the magnitude of economic impact being proportional to the size of membership and the existence of trade diversion effect within all trade blocs. The subsequent KORUS and Korea-EU FTA imposition upon the built CGE base models further verified the effects of hub-and-spoke-ism in East Asia. Jointly, the simulation results implied that the economic impacts of a trade arrangement heavily depend on the subject economy’s reliance on trade with the participating states. It was also found that the impacts were directly proportional to the accrued trade balance of the subject spoke country with both the hub state and the hub-destination. This could have been exaggerated as the scope of this study was limited to East Asia where KORUS FTA was found to be more influential than Korea-EU FTA due to its exceptionally high reliance on the US. On the course of this research to verify the aforementioned findings, however, both GTAP 6 and 7 were adopted, and hence, the economic impacts of China’s accession to the WTO in the global trade system were also empirically proven.

The maritime freight transportation industry has played an important role in the Korean economy. The Korean maritime freight transportation industry is faced with a period of transforming it competitively and efficiently in this global age. This paper, therefore, aims to identify the impact of the maritime freight transportation industry in the Korean national economy. Hence, this paper provides policy-makers with accessible and reliable information regarding the role of the Korean maritime freight transportation industry. This study employs input-output (I-O) analysis to examine the role of the maritime freight transportation industry in the national economy for the period 1995-2003, with specific application to Korea. This study pays particular attention to the maritime freight transportation industry by taking the industry as exogenous variable and then investigates its economic impacts. We identify inter-industry linkage effects in 20 sectors, production-inducing effects, added value-inducing effects, and supply-shortage effects of the maritime freight transportation industry.

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.