• IE interfaces
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• v.22 no.2
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• pp.153-164
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• 2009

An effective management for reverse flows of products such as reuse, repair and disposal, has become an important issue for every aspect of business. In this paper, we study the Location-Routing Problem (LRP) in the multi-stage closed-loop supply chain network. The closed-loop supply chain in this study integrated both forward and reverse flows. In forward flow, a factory, Distribution Center (DC) and retailer are considered as usual. Additionally in reverse flow, we consider the Central Returns collection Center (CRC) and disposal facility. We propose a mixed integer programming model for the design of closed-loop supply chain integrating both forward and reverse flows. Since the LRP belongs to an NP-hard problem, we suggest a heuristic algorithm based on genetic algorithm. For some test problems, we found the optimal locations and routes by changing the numbers of retailers and facility candidates. Furthermore, we compare the efficiencies between open-loop and closed-loop supply chain networks. The results show that the closed-loop design is better than the open one in respect to the total routing distance and cost. This phenomenon enlarges the cut down effect on cost as an experimental space become larger.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.189-200
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• 2015

Stationary bootstrapping is applied to a Lagrangian multiplier (LM) test to test market microstructure noise (MMN) in financial asset prices. A Monte-Carlo experiment shows that the bootstrapping method improves the size of the original LM test which has some size distortion for conditional heteroscedastic models. The proposed test is illustrated for real data sets like KOSPI index and Won-Dollar exchange rate.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.310-315
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• 2008

Authors design a rotary-type small-scaled linear induction motor(LIM) and a performance test machine before manufacturing a real-scaled LIM for a railway transit. The designed LIM is a single-sided, short primary type and its primary has 4 poles. The rated power is 10(kW). In order to analyze characteristics of the LIM, authors use a mixed 2D-3D FEM analysis. 3-D FEM analysis is used for calculating a distribution of eddy-current on the semi-caped AL-sheet of the secondary reaction. Authors calculate a correction factor of conductivity and an equivalent conductivity on the secondary AL-sheet using a normalized eddy-current. The equivalent conductivity which is calculated in this way includes a transverse edge-effect of the LIM. Authors apply the equivalent conductivity on the secondary AL-sheet of 2D-FEM model and get performance characteristics of the LIM. Basic characteristics such as thrust and normal force, input current, efficiency and power factor of the LIM have been analyzed with the variation of frequency and speed. In order to apply an air-gap control system, the variation of the basic characteristics have been analyzed with the air-gap length variation of the LIM. Finally, authors introduce an operation mode using the air-gap control system and conduct a research on feasibility of the system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.106-116
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• 2021

This paper considers a joint problem for blood inventory planning at hospitals and blood delivery planning from blood centers to hospitals, in order to alleviate the blood service imbalance between big and small hospitals being occurred in practice. The joint problem is to determine delivery timing, delivery quantity, delivery means such as medical drones and legacy blood vehicles, and inventory level to minimize inventory and delivery costs while satisfying hospitals' blood demand over a planning horizon. This problem is formulated as a mixed integer programming model by considering practical constraints such as blood lifespan and drone specification. To solve the problem, this paper employs a Lagrangian relaxation technique and suggests a time efficient Lagrangian heuristic algorithm. The performance of the suggested heuristic is evaluated by conducting computational experiments on randomly-generated problem instances, which are generated by mimicking the real data of Korean Red Cross in Seoul and other reliable sources. The results of computational experiments show that the suggested heuristic obtains near-optimal solutions in a shorter amount of time. In addition, we discuss the effect of changes in the length of blood lifespan, the number of planning periods, the number of hospitals, and drone specifications on the performance of the suggested Lagrangian heuristic.

• Journal of Distribution Science
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• v.18 no.12
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• pp.31-43
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• 2020

Purpose: This study examined how many determinant factors (service dimensions, food quality, and price perception) affect revisit intention. This practical concept is service quality (SERVQUAL), customer satisfaction, and repeated/revisit behavioral intention based on the theory of reasoned action (TRA). Research design, data and methodology: This research applied a hybrid mixed-method comprising exploratory and explanatory sequential design by Creswell (2014). The 400 responses were collected in four townships in Myanmar. This study drilled down to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA) prior to test the hypothesized factor structure of all the variables resulted in the form of the goodness of fit. For further data analysis, structural equation modeling (SEM) was applied to test the relationships among the variables of the proposed model. Results: The results showed that perceived service quality, food quality, and price perception have direct effects on customer satisfaction and indirect effect on revisit intention. The perceived service quality has the most significant influence while the food quality has the least influence on customer satisfaction. Conclusions: The results are useful for the restaurant managers to better understand the significant strategic choice factors to improve higher quality service amongst restaurants both domestic and international under the stiff competition.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.635-641
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• 2021

This paper aims to find out the main factors that are important in determining the size of investment in the Jordanian productive sectors. For this purpose, the study used panel data for four Jordanian productive sectors over the period 2000-2017. Also, fixed-effects modeling was carried out to identify the relationship between investment and its potential determinants. Empirical investigations of the four productive sectors reveal the following results: The real value of sector's production and the real value of credit facilities have a positive and significant impact on investment, while the real interest rate has a negative effect on investment in the Jordanian productive sectors. Also, at the sector level, agriculture was more responsive to changes in the real value of credit facilities, while other sectors were more responsive to changes in the real value of sector's production. According to these results, it seems that some policy actions should be taken to enhance the size and the role of investment in the economy. For example, policymakers should adopt a mixed policy and expand the provision of credit facilities, especially to the agricultural sector, to enhance agricultural activity in a manner that ensures the improvement of infrastructure and land reclamation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.809-817
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• 2021

The worldwide spread of the COVID-19 pandemic has had a severe impact on the global economy. The COVID-19 pandemic has spread with alarming speed and. The economic damage is already evident and represents the largest economic shock the world has experienced in decades. This study analyzes the factors that influence behavior and its impact on start-up performance, through technology capabilities, technology development, organizational structure characteristics, and leadership technology. The mixed-method was used in this research to be applied to start-up companies in Jabodetabek with a population of 522 start-ups. Then the sample was selected through purposive sampling technique to obtain a sample of 187 start-ups. Primary data was collected through a questionnaire, then statistical analysis was carried out using Partial Least Square. There are ten variables used in the model as measured by the questionnaire. The results showed that the four factors (agility, entrepreneurship capability, business transformation, and opportunity) significantly influence start-up behavior. The results showed that the start-up behavior significantly influenced technology capabilities, technology development, organizational structure characteristics, and leadership technology. This study also found that start-up behavior had the greatest influence on organizational structure characteristics, partially affect start-up performance, but leadership technology does not have a significant effect on start-up performance.

• Computers and Concrete
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• v.34 no.3
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• pp.367-378
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• 2024

This study evaluates the direct tensile strength of ultra-high-performance concrete (UHPC) using tests. A total of 45 dogbone-shaped specimens are tested, with the test variables being the fiber volume fraction and notch length. The test results showed that the material properties of UHPC were largely dependent on the fiber volume fraction and compressive strength. When steel fibers with more than 1% fiber volume fraction are mixed in the manufacturing of UHPC, the tensile strength can be more than twice that of plain UHPC. In addition, the incorporation of steel fibers enabled the significant improvement of the initial cracking strength. However, the effect of the notch length on the tensile behavior was insignificant. An assessment of the direct tensile strength is conducted using machine-learning algorithms (ML). For evaluation of the direct tensile strength of UHPC using ML, a total of 98 test data, including 53 data from other research works and 45 data from this experimental program, were collected. In total, 67 data with a 70% confidence interval on a normal distribution curve were selected, with 47 data among 67 used for ML training and 20 data used for ML testing. As a result, the machine-learning algorithm with a steel fiber volume fraction predicted that the tensile strength has an average of 0.98 and the lowest values of regression evaluation metrics among analytical and ML-based models. It is considered that an ML-based model can help to predict a more accurate tensile strength of UHPC.

• Journal of Distribution Science
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• v.22 no.12
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• pp.71-83
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• 2024

Purpose: Purpose: This study examines the optimization of healthcare service distribution through digital channel adoption by integrating anticipatory governance perspectives with distribution channel frameworks, emphasizing the role of digital service delivery networks. Research design, data and methodology: The research employs a mixed-methods approach incorporating qualitative expert interviews and quantitative survey data from 295 users across diverse distribution regions of Vietnam. The conceptual framework analyzes the relationships between distribution service quality, security protocols, perceived distribution benefits, and future perception through Partial Least Squares Structural Equation Modeling, focusing on channel efficiency and service accessibility. Results: The findings reveal that service quality and security measures in digital channels significantly influence attitudes toward distribution systems, while traditional usability factors show minimal impact. The study introduces future perception as a novel construct in distribution science, demonstrating its significant effect on adoption intentions. Multi-group analysis reveals notable variations in distribution effectiveness across geographical regions and demographic segments, with distinct patterns between urban and rural areas. Conclusions: The research advances distribution theory by demonstrating how anticipatory elements and demographic variations influence digital service delivery optimization. These insights provide strategic implications for developing efficient, segment-specific digital distribution networks in healthcare service delivery.

• Journal of Dental Rehabilitation and Applied Science
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• v.26 no.3
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• pp.273-283
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• 2010

This study evaluated the effect of 3 different compatible screws on the detorque values in a multiple implant-supported superstructure and single implant abutments. An implant superstructure directly connected to 4 implants was screwed to 6 experimental dental stone casts made by acrylic resin splinted impressions, using 20 Ncm. The detorque values of screws were measured twice. Three compatible abutment screws used in this study were TorqTite screw, Gold-Tite screw, and, Titanium screw. And, using single implant abutments (GoldAdapt Engaging abutments), the detorque values of 3 different screws were measured twice on 2 implants of 5 experimental casts. According to statistical analysis of detorque values using mixed model at a .05 level of significance, no statistically significant differences among 3 different compatible screws were found in a multiple implant-supported superstructure (p>0.05). But, in single implant abutments, statistically significant differences among 3 different compatible screws were found (p=0.0175). The detorque values of TorqTite(p=0.0462) and Titanium(p=0.0348) screws were significantly higher than those of Gold-Tite screw, but no statisticantly significantlydifferences were found between TorqTite and Titanium screws(p>0.05). Therefore, various compatible screws showed significant effects on the detorque values for single implant abutment, but, showed no significant effects for a multiple implant-supported superstructure.