• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1079-1090
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• 2021

This study examines the influence of individual investors' sentiment on Japanese IPO aftermarket performance (measured by return and trading volume on the first trading day and return on the first trading year). This study proposes that IPOs will be, on average overpriced on the listing day when individual investors' sentiment is highly optimistic. Higher initial return and trading volume are expected in IPOs with higher investors' optimism. Further, the positive initial return will occur in the short term as individual investors usually are uninformed investors who demand shares based on their personal preferences, which will last only in a short period. Following the overvaluation hypothesis, price reversals should be predicted once the effect of individual investors' optimism has disappeared, causing the IPOs to underperform in the long term. Using 520 Japanese IPOs issued from January 2010 to December 2019, this study reveals that individual investors' sentiment is positively and significantly related to returns and trading volume on the first trading day. Return reversals are found on the first trading year despite the insignificant influence of individual investors' sentiment on IPO return on the first trading year.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.267-275
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• 2021

This study investigates the relationship between cultural distance and entry mode choice, where the foreign investor firm and the host country are both from emergent economies. Within this framework, research is limited and the issue is whether companies, regardless of their specific situations, have the same strategy when they meet a high degree of uncertainty in the host environment. In this study, we focused on the influence of informal institutional factors: cultural distance, that has been extensively analyzed in international business, measured by Kogut and Singh index and defined according to Hofstede, Globe Project and Schwartz approaches. The general trend derived from prior research proves that when a company from a developed country is involved; overall more enthusiasm is shown for wholly-owned subsidiaries rather than joint venture. This result still stands validated for corporations from this emergent economy area. Our analysis of a sample of 163 FDI in the Kingdom of Saudi Arabia (KSA) using logistic binary regression model reveals that the foreign firms prefer to establish wholly-owned subsidiaries in the host country over entering into a joint venture with a local firm, taking into consideration the large cultural distance.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.411-417
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• 2021

This study aims to estimate the production function and total factor productivity (TFP) of Vietnamese seafood processing firms. At the same time, the study analyses the impact of internal factors of firms and the quality of economic institutions on the TFP of the Vietnamese seafood processing industry. The study uses the Function Control (FC) approach in TFP estimation and the Feasible Generalized Least Squares (FGLS) regression model in the analysis of factors affecting TFP. The study was carried out on the census data of enterprises of the Vietnamese seafood processing industry collected by the Vietnamese General Statistics Office and Provincial Competitiveness Index data of Vietnam Chamber of Commerce and Industry in the period from 2013 to 2018. Estimated results from the models show that: i) Vietnamese seafood processing firms are, currently, mainly labor-intensive, the TFP contribution and output is only about 2.258. ii) Factors such as the firm's age, firm's size, and the firm's ownership affect TFP. In which, firms that have few numbers of years of operation, small and medium firms, and private firms have low TFP. iii) Institutional quality and the provincial business environment have a positive impact on the TFP of Vietnamese seafood processing firms in this period.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.25-39
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• 2021

This purpose of this study is to investigate the association among mutual funds (MFs) risk measures and return parameters, evaluate mutual fund performance and also explore the best appropriate mutual fund performance measure for investment in Pakistan. Therefore, thirty-five mutual funds have been selected for the period 2007-2015. The Sharpe, Treynor, Jensen Alpha, Information ratio and Fama's Net Selectivity measures has been used to analyze MF performance. Our study findings show significant positive relation exist between Sharpe and Jenson alpha & information ratio (IR); Treynor ratio is negatively correlated to Jenson alpha and Jenson alpha is positively allied with IR. Moreover, association among performance measures, Fama's net selectivity is a major driver in leading to other measures but Sharpe and IR lead to Treynor ratio as well. Furthermore, performance measures are ranked in accordance standard deviation with the arrangement of Fama's net selectivity at top, Jenson Alpha at second, Sharpe ratio at third, IR at fourth and Treynor ratio at fifth position according to risk parameters in Pakistan. Overall, Jensen Alpha measure appears to be the best suitable mutual fund performance measure in Pakistan due to its practical nature. Finally, the Pakistani stock market index KSE100 (as benchmark) performs better than MF industry of Pakistan.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.127-137
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• 2022

This paper aims to investigate the impact of corporate governance on the quality of integrated reporting. Corporate governance includes internal (board size, board independence, and board diversity) and external (audit quality and enforcement) governance factors. This paper develops an index to capture the quality of integrated reporting by employing the completeness of information required by the International Integrated Reporting Council (IIRC). For an international sample, the paper manually collects 160 integrated reports along with internal and external governance factors and employs multivariate analyses to examine the association between these governance factors and the quality of integrated reporting. The empirical results suggest that firms with a larger board of directors, a larger proportion of female members on board, and located in countries with enforcement for integrated reporting requirements have a higher quality of integrated reporting. Our conclusions still hold after accounting for several conditions, including the industry-fixed and year-fixed effects. Together, these results suggest that both internal and external governance factors are important determinants for the quality of integrating reporting. These results have several theoretical and practical implications as they fulfill the absence of relevant studies on addressing the impact of internal and external corporate governance factors on the quality of integrated reporting.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.253-265
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• 2022

This paper examines South Korea's past developmental experience and its current strategy and policy initiatives to overcome global and domestic challenges and sustain economic growth in the twenty-first century, the digital and global era, to explain how the country became a high-income economy. The findings of this research highlight the following three factors: First, the most significant factor in rapid industrialization was the adoption of an outward-looking strategy, with the help of a highly skilled workforce and the development of high-tech manufacturing and services sectors, which was supported by the government plans. Second, the high R&D intensity helped South Korea become a global leader in information and communication technologies, which has emerged from a top-down innovation system that promotes close collaboration between government, industry, and the academic community. Third, according to the recently released Global Entrepreneurship Index, South Korea tops the region in entrepreneurship environment. Among the list of criteria, South Korea dominates in the ease of starting a business and enforcing contracts. They all play a significant role in encouraging investment, production, communication, and, eventually, economic growth. Finally, this paper suggests forward-looking developments promoting transformation and diversification into high-tech manufacturing and digital and green technologies.

• Journal of Korea Trade
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• v.26 no.1
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• pp.99-112
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• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.441-448
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• 2022

The aim of this study was to examine determinants of secondhand Bulk carrier and Oil tanker prices. This study compiled S& P transaction data taken from the Clarksons Research during J anuary 2018 to April 2022 to see how independent variables influenced secondhand ship prices. In the secondhand ship pricing model of entire segments, size, age, and LIBOR showed significant effects on prices. A vessel built in J apan and Korea was traded at a higher price than a vessel built in other countries. In the bulk segment, size, age, Clarksea index, LIBOR, and inflation were meaningful variables. In the Tanker segment, unlike Bulk carrier, only size and age were useful variables. This study performed regression analyses for various sizes of Bulk carriers and Oil tankers. It verified that impacts of variables other than ship size and age were significantly associated with ship type and size while macroeconomic variables had no influence except for bulk carriers. By applying diverse variables affecting secondhand ship price estimation according to various sizes of Bulk carriers and Oil tankers, this study will expand the scope of practical application for investors. It also reaffirms prior research findings that the secondhand ship market is primarily market-driven.

• Smart Structures and Systems
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• v.29 no.2
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.