• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.529-538
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• 2010

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

• Journal of Environmental Science International
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• v.25 no.10
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• pp.1417-1426
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• 2016

Despite the low removal efficiencies reported by previous studies, electro-flotation still stands out among other microalgae removal methods for its economical and environmental benefits. To enhance removal efficiency, the important factors that limit the performance of this method must be investigated. In this study, the possible ways of increasing the removal efficiency of microalgae have been explored by investigating the effects of several important variables in electro-flotation. Eight parameters, namely flotation time, rising time, current density, pH, conductivity, electrode distance, temperature and initial concentration were evaluated using a one-parameter-at-a-time approach. Results revealed that the operational parameters that greatly affected the removal efficiency of microalgae were electro-flotation time, current density, pH, and initial concentration. The effect of conductivity, electrode distance, and temperature on removal efficiency were insignificant. However, they exhibited positive an indirect positive effect on power demand, which is nowadays considered an equally important aspect in the running of a feasible and economically efficient electro-flotation process.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.403-412
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• 2021

The COVID-19 pandemic has a great impact in various ways. It changes the normal routine of lives and businesses. Many businesses encounter tremendous financial pressure, some of them lay off workers or choose to close down. According to the statistics, e-commerce experiences a four-fold growth in sales during the pandemic period. There is an urgency for firms to digitalize their businesses to respond to the change in the landscape of purchasing patterns of consumers. The purpose of this study is to understand the success of a few popular apparel brands in digital businesses. This is a qualitative research, and secondary data is collected for the analysis. The findings reveal that all of them engage in omni-channel methods in digitizing their businesses while utilizing other forms of technologies in their product and operational management. All selected firms agree with the importance of digital business, and omni-channel retailing is their choice. In these unprecedented times, the sustainable success of the apparel firms in digital businesses requires a flexible and innovative approach and a commitment to achieving operational excellence. Continuous renewal and digital transformation are needed so that these companies have the capabilities to adapt to changes and reap the benefits of a satisfactory organizational performance.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.303-310
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• 2024

In this study, we conducted a work analysis at an active building construction site, utilizing three-axis acceleration sensors affixed to four plaster-board-pasting workers for five days. Although acceleration data is less accurate than visual or image recognition in identifying specific tasks, it can be easily captured using smartphones, even in challenging conditions such as poorly lit or obstructed construction sites. This accessibility facilitates continuous data collection over extended periods, enabling automated analysis without significant cost or time investment. In addition, this method can identify trends in worker behavior that elude conventional visual inspection. Our approach encompasses various evaluation indices, beginning with an analysis of average work time per plasterboard sheet and the differentiation of walking motions using acceleration data. Furthermore, we introduced a new evaluation index that quantifies the distribution of high- and low-intensity work based on acceleration readings. Through comparative analysis with evaluation indices from previous studies, we confirmed common trends and discussed the strengths and limitations of our proposed index. Our findings suggest a correlation between work experience and performance, as evidenced by smoother operational patterns among seasoned workers. In particular, proficient workers exhibited fewer instances of extremely intense or sporadic movements. This observation underscores the influence of experience on work dynamics.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.897-907
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• 2021

The purpose of this study is to investigate the quality of entrepreneurship - motivation, entrepreneurial orientation, and risk behavior - in relation to the odds of micro-, small- and medium-sized enterprises' (MSMEs) financial performance in Indonesia. Additionally, this paper investigates how these qualities apply for the current challenges perceived by MSMEs' entrepreneurs in Indonesia due to Covid-19 crisis; specifically, this paper examines the odds of MSMEs' financial performance during the pandemic in respect to when these qualities are implemented by the entrepreneurs. The empirical data was obtained from an online survey by means of a structured questionnaire. MSMEs surveyed were randomly selected on a national scale. To test the hypotheses, a quantitative approach is employed, using multinomial regression. The main result shows that, under normal economic environment, the more intrinsically-motivated and continuity-driven entrepreneur is, the more likely the MSME will achieve financial growth compared to remaining stagnant. To our surprise, innovativeness leads to less likelihood of MSME's financial growth, suggesting the significance of innovation does not apply to MSMEs in Indonesia. Lastly, MSMEs' risk behavior to operate in a stable business environment is found more likely to result in a better performance and is true for operational and financial risks, but not marketing risks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3619-3637
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• 2022

Big data analytics offers endless opportunities for operational enhancement by extracting valuable insights from complex voluminous data. Hadoop is a comprehensive technological suite which offers solutions for the large scale storage and computing needs of Big data. The performance of Hadoop is closely tied with its configuration settings which depends on the cluster capacity and the application profile. Since Hadoop has over 190 configuration parameters, tuning them to gain optimal application performance is a daunting challenge. Our approach is to extract a subset of impactful parameters from which the performance enhancing sub-optimal configuration is then narrowed down. This paper presents a statistical model to analyze the significance of the effect of Hadoop parameters on a variety of performance metrics. Our model decomposes the total observed performance variation and ascribes them to the main parameters, their interaction effects and noise factors. The method clearly segregates impactful parameters from the rest. The configuration setting determined by our methodology has reduced the Job completion time by 22%, resource utilization in terms of memory and CPU by 15% and 12% respectively, the number of killed Maps by 50% and Disk spillage by 23%. The proposed technique can be leveraged to ease the configuration tuning task of any Hadoop cluster despite the differences in the underlying infrastructure and the application running on it.

• Journal of Distribution Science
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• v.18 no.8
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• pp.55-64
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• 2020

Purpose: This paper addresses issues that concern business-to-business marketing, namely informational justice in the supply chain or organizations. As previously reported by other studies, there is information asymmetry in organizations. The present study explores and addresses this in the medical industry, aiming to investigate how informational justice relates to information quality or logistics performance in the medical industry. This study also suggests a method for development of informational justice in medicine-related fields. Design, methodology, approach: The hypothesis and model were developed through a review of the literature. To this end, we surveyed 293 valid survey samples collected from occupational pharmacists and used structural equation modelling for analysis. Findings: The results of the empirical analysis of the hypotheses showed that symmetric sharing of information between pharmacists and employees of pharmaceutical companies has a positive effect on the perceived quality. Moreover, the results showed that quality information has a positive impact on logistics performance, whereas informational justice does not. Conclusions, implications: If information and explanations are exchanged fairly, information and logistics performance-as well as operational expenses-will be enhanced. Furthermore, our study has immense implications outside of academic applications since it suggests practical solutions to government and medical industry employees.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• Journal of Korean Society of Transportation
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• v.34 no.3
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• pp.278-290
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• 2016

Maximum traffic flow rate is an important performance measure of operational status in transport networks, and has been considered as a key parameter for transportation operation since a bottleneck in congestion decreases maximum traffic flow rate. Although previous studies for traffic flow analysis have been widely conducted, a detection method for changes in dynamic traffic flow has been still veiled. This paper explores the dynamic traffic flow detection that can be utilized for various traffic operational strategies. Turning point analysis (TPA), as a statistical method, is applied to detect the changes in traffic flow rate. In TPA, Bayesian approach is employed and vehicle arrival is assumed to follow Poisson distribution. To examine the performance of the TPA method, traffic flow data from Jayuro urban expressway were obtained and applied. We propose a novel methodology to detect turning points of dynamic traffic flow in real time using TPA. The results showed that the turning points identified in real-time detected the changes in traffic flow rate. We expect that the proposed methodology has wide application in traffic operation systems such as ramp-metering and variable lane control.

• Journal of Korean Association for Spatial Structures
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• v.19 no.4
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• pp.85-94
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• 2019

Then 3D printing is used practically at construction sites, there is a serious lack of studies on the conflict with construction-related laws and expected operational problems. Accordingly, the purpose of this study is to present obstacles and directions for improvement in construction-related laws (Building Act, Construction Technology Promotion Act, Housing Act, Construction Machinery Management Act, etc.) for practical operation of 3D printing. The important results are as follows. Amending existing construction-related laws for 3D printing is irrational and inefficient in terms of structure and material. This study proposed a method of satisfying performance required by laws or standards based on the performance design method presented in existing laws and systems through structure and material performance certification procedure. In addition, inclusion of 3D printing equipment in the Construction Machinery Management Act results in various restrictions such as equipment inspection and certification of machine parts. As such restrictions can block vitalization of 3D printing, a long-term and step-wise approach was suggested.