• Journal of the Korean Operations Research and Management Science Society
• /
• v.24 no.1
• /
• pp.27-38
• /
• 1999

In this paper, Primal-Interior Dual-Simplex method(PIDS) and Dual-Interior Primal-Simplex method(DIPS) are developed for the general bounded linear programming. Two methods were implemented and compared with other pricing techniques for the Netlib. linear programming problems. For the PIDS, it shows superior performance to both most nagative rule and dual steepest-edge method since it practically reduces degenerate iterations and has property to reduce the problem. For the DIPS, pt requires less iterations and computational time than least reduced cost method. but it shows inferior performance to the dynamic primal steepest-edge method.

• Korean Management Science Review
• /
• v.30 no.1
• /
• pp.167-181
• /
• 2013

We investigate the dynamic asset allocation problem under inflation risk when the wealth of an investor is constrained with minimum requirements. To capture the investor's risk preference, the CRRA utility function is considered and he maximizes his expected utility at predetermined date of the refund by participation in the financial market. The financial market is supposed to consist of three kinds of financial instruments which are a risk free asset, a risky asset, and an index bond. The role of an index bond is managing inflation risk represented by price process. The optimal wealth and the optimal asset allocation are derived explicitly by using the method to get the European call option pricing formula. From the numerical results, it is confirmed that the investments on index bond is high when the investor's wealth level is low. However, as his wealth increases, the investments on index bond decreases and he invests on risky asset more. Furthermore, the minimum wealth constraint induces lower investment on risky asset but the effect of the constraints is reduced as the wealth level increases.

• Environmental and Resource Economics Review
• /
• v.27 no.4
• /
• pp.639-666
• /
• 2018

This paper analyses the investment options of groundwater development project under water price uncertainty. The optimal investment threshold price which trigger the investment are calibrated base on monopolistic real options model. Stochastic dynamic model is set to reflect the uncertainty of water price which follows the GBM (Geometric Brownian Motion) process. Our finding from non-cooperative investment decision model is that uncertainty of water price could deter the groundwater investment by considering the existence of option values. For policy markers, it is easy to manage 'charges for utilization of groundwater' rather than 'performance guarantee ratio' when managing groundwater investment with pricing policy. And it is necessary to make comprehensive and well-designed policies considering the characteristics of regional groundwater reservoir and groundwater developers.

• Advances in nano research
• /
• v.16 no.3
• /
• pp.303-311
• /
• 2024

This paper conducts a thorough economic evaluation of integrating nanoparticles into concrete structures within the construction industry, aiming to elevate the material properties of concrete. Employing the Halpin-Tsai micromechanics theory for deriving the effective material properties of the nanocomposite concrete structure, the research investigates the nuanced impact of nanoparticles on various mechanical properties, including the modulus of elasticity, compressive strength, and their indirect effects on the percentage of reinforcement. Implementing the Euler theory to formulate the governing equation based on Hamilton's principle, the study delves into the pricing dynamics of nanoparticles and their influence on the overall cost structure of concrete structures. Notably, the findings reveal that a measured increase in the volume percentage of nanoparticles, up to 1%, results in a remarkable 78% improvement in elastic modulus and a substantial 142% reduction in armature percentage. Remarkably, from an economic perspective, the incremental cost associated with the integration of nanoparticles is relatively modest (around $1 per ton of concrete), considering the substantial enhancements in mechanical properties achieved.

• The Journal of Society for e-Business Studies
• /
• v.27 no.1
• /
• pp.29-41
• /
• 2022

Since the first sale of a banner advertisement in 1995, electronic commerce has become a new transaction channel for consumers. With more than 20 years of its history, electronic commerce has become an important consumption channel for everyone and inexperience is no more a reason that discourages the consumption through this channel. The great expansion of this channel is now a formidable thereat to traditional channels. However, products with high asset specificity and complexity are still having difficulty to be traded over the online channel where the experience of the products for a consumer is limited. Especially, variations of the same product's quality depending on how pre-owners used the product and high complexity to describe the quality of the products prevent used goods from being traded over e-channels. Added to that, the information asymmetry between sellers and buyers for used goods makes the establishment of market transaction difficult. Considering the challenges, the current case study discusses thredUP, a clothing resale platform company. In this paper, we study how the company could overcome those limitations in this toughest resale market through the use of AI for dynamic pricing and standarized product quality ratings. In addition, we also hope to provide readers with the opportunity to understand the secondhand industries and its market, and see where it is heading for in the future.

• The Journal of Bigdata
• /
• v.8 no.1
• /
• pp.23-34
• /
• 2023

Nowadays, the Designated Driver Services employ dynamic pricing, which adapts in real-time based on nearby driver availability, service user volume, and current weather conditions during the user's request. The uncertain volatility is the main cause of price increases, leading to customer attrition and service refusal from driver. To make a good Designated Driver Services, development of a demand forecasting model is required. In this study, we propose developing a demand forecasting model using data from the Designated Driver Service by considering normal and peak periods, such as rush hour and rush day, as prior knowledge to enhance the model performance. We propose a new methodology called Time-Series with Conditional Probability(TSCP), which combines conditional probability and time-series models to enhance performance. Extensive experiments have been conducted with real Designated Driver Service data, and the result demonstrated that our method outperforms the existing time-series models such as SARIMA, Prophet. Therefore, our study can be considered for decision-making to facilitate proactive response in Designated Driver Services.

• Management Science and Financial Engineering
• /
• v.18 no.1
• /
• pp.27-37
• /
• 2012

This paper is motivated by a military cargo-plane routing problem which is a pickup-and-delivery problem in which load splits and node revisits are allowed (PDPLS). Although this recent evolution of a VRP-model enhances the efficiency of routing, a solution method is more of a challenge since the node revisits entail closed walks in modeling vehicle routes. For such a case, even a compact IP-formulation is not available and an effective method had been lacking until Nowak et al. (2008b) proposed a heuristic based on a tabu search. Their method provides very reasonable solu-tions as demonstrated by the experiments not only in their paper (Nowak et al., 2008b) but also in ours. However, the computation time seems intensive especially for the class of problems with dynamic transportation requests, including the military cargo-plane routing problem. This paper proposes a more scalable algorithm hybridizing a tabu search for pricing subproblem paused as a single-vehicle routing problem, with a column generation approach based on Dantzig-Wolfe decomposition. As tested on a wide variety of instances, our algorithm produces, in average, a solution of an equiva-lent quality in 10~20% of the computation time of the previous method.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.2
• /
• pp.247-255
• /
• 2019

This study examines the different roles of cash flow in assessing investment returns in the Association of Southeast Asian Nations (ASEAN). The analysis covers over 900 listed firms across Malaysia, Indonesia, Philippines, Singapore and Thailand for the period post the Asian financial crisis of 2001-2017. Firm-level panel data analysis shows that cash flow factors are important in all contexts of cash return on assets, earnings quality and market value multiple across the region even after controlling for typical measures of profitability. The results suggest that firms should manage cash flow prudently in considerations of firm value from the shareholder's perspective, measured directly using stock return. Cash profitability on assets should become an important firm performance indicator, whilst higher cash component over reported earnings is preferred. The market also tends to respond favourably to cash flow yield as a price multiple in valuation, outpacing the role of earnings yield. Such findings are robust across the pre and post subprime crisis periods, across estimation methods pertaining to finance panel standard errors, as well as across static and dynamic considerations of returns. It is hence sensible to consider cash flow factors in the research pertaining to asset pricing and factor investing in the ASEAN region.

• Journal of Information Processing Systems
• /
• v.20 no.1
• /
• pp.93-104
• /
• 2024

China is playing more predominant role in the liquefied natural gas (LNG) market worldwide and LNG import price is subject to various factors both at home and abroad. Nevertheless, previous studies rarely heed a multiple of factors. A time-varying parameter factor augmented vector auto-regression (TVP-FAVAR) model is adopted to discover the determinants of China's LNG import price and their dynamic impacts from January 2012 to December 2021. According to the findings, market fundamentals have a greater impact on the import price of natural gas in China than overall economic demand, financial considerations, and world oil prices. The primary determinants include domestic gas consumption, consumer confidence and other demand-side information. Then, there are diverse and time-varying spillover effects of the four common determinants on the volatility of China's LNG import price at different intervals and time nodes. The price volatility is more sensitive and long-lasting to domestic natural gas pricing reform than other negative shocks such as the Sino-US trade war and the COVID-19 pandemic. The results in this study further proves the importance of domestic natural gas market liberalization. China ought to do more to support the further marketization of natural gas prices while working harder to guarantee natural gas supplies.

• Journal of Korea Port Economic Association
• /
• v.32 no.2
• /
• pp.59-71
• /
• 2016

This study empirically examines the dynamic specification of the ship price model based on a vector autoregressive model and data covering from January 2000 to October 2014. Our results are summarized as follows: first, the relationship between ship price and interest rate shows significantly negative and the relationship between ship price and freight rate shows positive. It provides consistent implication that ship price depends on interest rate and freight rate under the dynamic Gordon model. Second, we apply an impulse response analysis to ship price and find the responses of the ship price from both factors, interest rate and freight rate, which affect during seven periods approximately. Finally, the results of a variance decomposition indicate that freight rate is more important than interest rate on the ship price.