• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.5
• /
• pp.253-263
• /
• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• Asian Journal of Innovation and Policy
• /
• v.8 no.1
• /
• pp.1-30
• /
• 2019

The advent of digitalisation has transformed economies into more integrated, but increasingly complex systems. This new trend has brought dynamic changes in the manufacturing sector through advanced ICT infrastructure, smart factories, digitally-controlled logistics, and skilled ICT-labour. The impacts of the digital economy on manufacturing could be best illustrated through "Industry 4.0." With this wave of technological advancement, countries aim to establish an industrial ecosystem where every manufacturing process and function is connected and interacts through digital networks. Industry 4.0 presents opportunities for Emerging Asia, as the region has emerged as a fast-growing manufacturing hub and particularly a production base for ICT goods. However, growing production capacity, increased exports, and increases in FDI in the field of ICT goods manufacturing have so far contributed little to the development and diffusion of ICT. A huge gap exists in the ICT uptake amongst countries and between small and large firms. This paper highlights the level of Industry 4.0 readiness of Emerging Asia and key factors that determine its enhancement.

• The Journal of Economics, Marketing and Management
• /
• v.9 no.4
• /
• pp.19-30
• /
• 2021

Purpose: This study aimed to examine how a superior employee's ethical leadership affects members' innovative behaviors, mainly on organization-based self-esteem. It also aimed to verify the mediating effect of organization-based self-esteem in the process that ethical leadership affects members' innovative behavior in distribution-related organizations. Research design, data and methodology: After collecting materials from companies' executives and staff members in distribution-related organizations located in Seoul, South Korea, a research hypothesis was analyzed. Results: A superior employee's ethical leadership affects a positive (+) effect on innovative behaviors of the organization's members and the study confirmed that the relation of this effect was mediated by organization-based self-esteem. It means that the possibility that an organization's members will do innovative behaviors will be increased if a leader conducts ethical leadership. It also means that a leader with ethical leadership enables an organization's members to pay attention all the time and be awake for their work environment. Conclusions: The result of this study discusses how ethical leadership affects innovative behaviors of an organization's members from the perspective of organization-based self-esteem and has a theoretical implication that it has empirically examined it. More importantly, it has a theoretical implication because it verified how this effect was made using organization-based selfesteem and flexible human resource management.

• The Journal of Industrial Distribution & Business
• /
• v.13 no.12
• /
• pp.59-71
• /
• 2022

Purpose: Re-handling is an important factor that reduces the productivity of container terminals. The purpose of this paper is to propose an algorithm to find the order of container movement in order to minimize the number of re-handling in the process of carrying-out. Research design, data and methodology: This paper proposes an algorithm to set the optimal carry-out order and conducted tests to evaluate the performance of the algorithm proposed in this paper. 1. tests comparing the performance of an algorithm proposed in an existing study with that proposed in this paper. 2. Performance tests for bays with complex structures. Results: Test 1 shows that the algorithm proposed in this paper performs better than the existing algorithm. Test 2 shows that the proposed algorithm can also be used in bays with considerably high complexity and that there is no major problem with using it in the field. Conclusion: While we can conclude that the proposed algorithm as a carry-out algorithm is more effective than conventional methods, research is needed on how to handle more complex bays more effectively. This is because the larger the bay, the more container combinations increase, making it difficult to find the best carry-out order.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.1
• /
• pp.187-192
• /
• 2022

In the current container port, the containers standardized by the automated operating system using the latest information and communication technology are systematically made according to the optimal stowage planning. However, loading of steel coils with a unit weight of several tens of tons is still performed manually, which is very inefficient. As a result, work is delayed and safety accidents occur frequently. In this study, an automated simulation system for loading steel coils was designed to prevent misjudgment, congestion, and safety accidents that occur during the manual loading process of steel coils.

• Journal of Distribution Science
• /
• v.20 no.7
• /
• pp.57-64
• /
• 2022

Purpose: The government of India has initiated the Covid-19 Vaccination drive from early January 2021. Vaccination is identified to be best option to protect the people across the globe. However, owing to fast wide spread of the Covid-19, the Vaccine Distribution is a major challenge owing various issues like temperature control, infrastructure, hesitancy, geographical diversity, and other critical factors. Various research is carried out globally to understand and study the Vaccine Distribution issues based on the respective country issues and factors. Research Design, Data, and Methodology: This research paper attempts to explore prominent factors that could be taken up on priority for better and effective vaccination program. The study tries to rank various factors and sub-factors affecting vaccine distribution in India. AHP methodology based on feedback from 22 experts from the Vaccine industry has been deployed to get the desired results. Result: The results show that factors vaccine approval process, geographical prioritization, power supply, infrastructure maintenance costs for vaccine storage, and vaccine pricing are the prominent factors of effective vaccination in the country. Conclusion: The role and need for district-level health officers towards vaccine storage has been brought forward. A long-term effective vaccination policy is needed for optimum vaccine distribution.

• Journal of the Society of Naval Architects of Korea
• /
• v.59 no.6
• /
• pp.393-399
• /
• 2022

During the ship hull design process, resistance performance estimation is generally calculated by simulation using computational fluid dynamics. Since such hull resistance performance simulation requires a lot of time and computation resources, the time taken for simulation is reduced by CPU clusters having more than tens of cores in order to complete the hull design within the required deadline of the ship owner. In this paper, we propose a method for estimating resistance performance of ship hull by simulation using a graph neural network. This method converts the 3D geometric information of the hull mesh and the physical quantity of the surface into a mathematical graph, and is implemented as a deep learning model that predicts the future simulation state from the input state. The method proposed in the resistance performance experiment of simple hull showed an average error of about 3.5 % throughout the simulation.

• Applied Chemistry for Engineering
• /
• v.34 no.1
• /
• pp.75-79
• /
• 2023

The International Maritime Organization (IMO) Marine Environmental Protection Committee (MEPC) may adopt actions after completing impact assessments and reviewing results in accordance with the original strategy and impact assessment procedure (MEPC.1/Circ.885). The assessment of the impact of greenhouse gas (GHG) reduction measures is an important step in determining whether to implement GHG regulations. This study identifies and proposes improvements in the impact assessment procedure for future mid- and long-term measures. Improvements for future measures should start with a review of "the procedure for assessing impacts on states of candidate measures" and "the actual process of the comprehensive impact assessment for short-term measures in 2021." The procedural improvements were largely derived from the order and period of task performance, the clear definition of terms, and the review of task results through lessons learned, analysis, and expert workshops. The impact assessment of future mid- and long-term measures should be procedurally improved to ensure uniformity and consistency, which will provide objective results for Member States and industries to help smooth the adoption of measures.

• Korea Trade Review
• /
• v.41 no.4
• /
• pp.91-110
• /
• 2016

AEO certification has a positive effect on firm's performance. Therefore, this study analyzed the effect of AEO certification on firm's performance using panel data analysis for firm to have international competitiveness. It uses the Hausman-Taylor test for effective solutions of endogenous matter. In terms of the result of analysis, AEO certification has a positive effect on domestic and foreign sales, especially direct benefit and business process improvement of AEO certification have a positive effect on domestic and foreign sales through the improvement of international logistics flow. In conclusion, this study proposes the policy of AEO certification by analyzing the effect of AEO certification on firm's performance by using the panel data analysis.

• Journal of Distribution Science
• /
• v.21 no.1
• /
• pp.53-63
• /
• 2023

Purpose: Big Data analytics (BDA) has been recognized to improve firm performance because it can efficiently manage and process large-scale, wide variety, and complex data structures. This study examines the determinants of Big Data analytics adoption toward marketing and financial performance of global logistic companies in Thailand. The research framework is adopted from the technology-organization-environment (TOE) model, including technological factors (relative advantages), organizational factors (technological infrastructure and absorptive capability), environmental factors (industry competition and government support), Big Data analytics adoption, marketing performance, and financial performance. Research design, data, and methodology: A quantitative method is applied by distributing the survey to 450 employees at the manager's level and above. The sampling methods include judgmental, stratified random, and convenience sampling. The data were analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The results showed that all factors significantly influence Big Data analytics adoption, except technological infrastructure. In addition, Big Data analytics adoption significantly influences marketing and financial performance. Conversely, marketing performance has no significant influence on financial performance. Conclusions: The findings of this study can contribute to the strategic improvement of firm performance through Big Data analytics adoption in the logistics, distribution, and supply chain industries.