• Journal of Distribution Science
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• v.20 no.7
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• pp.97-105
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• 2022

Purpose: This study aims to analyze and prove the effect of logistic capability and Total Quality Management practices on Micro, Small and Medium Enterprises (SME) performance directly or mediated by non-financial performance. Research design, data and methodology: This study tested the hypothesis using Hierarchical multiple regression analysis, the method of data collection in this study was using questionnaire, the sampling technique was purposive sampling technique, with SME that has been established for more than 5 years and manufacturing. The data analyzed were 180 respondents using SPSS 25. Results: The findings showed that logistic capability has direct and indirect effects on SME financial performance and has a positive effect on SME financial performance mediated by non-financial performance. While the total quality management practices have a positive effect on SME financial performance mediated by non-financial performance. Thus, companies can achieve maximum financial performance if they invest in developing employee knowledge and concerning on non-financial actions, such as employee satisfaction, innovation and proactively seeking market opportunities. Conclusions: In conclusion, one of the main factors that companies need to consider to improve financial performance is non-financial performance in mediating the effect of logistic capability and TQM practices on the financial performance of SMEs.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.75-87
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• 2005

Generally speaking, weapon system is defined as a combination of primary system and support system which are evaluated by capability and operational availability respectively. Recently comparison of total life cycle cost shows that logistic support system is proved to be more important than primary system. However, until now systematic approach to support system development has not been applied in the area of developing support system. We need to construct a universal metric for effectiveness of logistic support system and to cut out whatever activities or support elements which do not contribute to the metric. This paper describes a new approach based on system engineering approach to logistic support system and also classifies five factors of failure, stock-out frequency, administrative delay time, active repair time and logistic delay time that have influence on operational availability of logistic support system.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.5
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• pp.1214-1223
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• 2013

The purpose of this work is to analyze the factors, criteria and importance that shippers in the international logistics industry take into account in choosing third-party logistics, and thereby to propose the directions of the areas and functions that third-party logistics will need to enhance on the basis of Analytic Hierarchy Process (AHP) methodology. To do that, this work collected and analyzed materials about changing environments of logistic industry and previous studies, and especially conducted a questionnaire survey on the factors to choose third-party logistics with the study subjects of shippers in the international logistics industry. To draw attribute factors, this work repeatedly chose and classified candidate factors through Delphi technique on the basis of the data of previous studies. The analysis results are presented as follows: regarding pairwise comparison between logistic cost and logistic service in relation of conflict, logistic service was recognized to be more important than logistic cost; regarding pairwise comparison between corporate capability and logistic cost, logistic cost was recognized to be more important; and regarding comprehensive evaluation, logistic service factors, including accuracy of order handling, service reliability, freight damage and compensation, a degree of fulfillment of promise, quality of transportation, and problem-solving ability, were found to be in high position.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.61-68
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• 2024

In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Journal of Korea Port Economic Association
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• v.21 no.1
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• pp.45-58
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• 2005

The purpose of this study is to consider the problem on pursuit of logistics strategy by our international shipping company in international shipping business under the said circumstance due to the open international shipping market and to suggest the logistics strategy for the consideration of the logistics competition under new international shipping circumstances. The results of empirical analysis are mentioned as follows; First, it shall be considered to maintain the size of company bigger than a certain capability so that it may obtain the superior competition of logistics. Second, as there are the plus correlations between the competition of logistics and the logistic support, it is necessary to pursuit the upgrade service with using EDI system and making up the complex shipping and integrated logistics system in general. Third, with the rationalization of finance policy and the profitable management of shipping company the ratio of net worth can be raised and it can be achieved to make the sound financial structure as reducing the excessive debt ratio. Fourth, it can be effort continuously to perform the investment for the infrastructure of logistics support & the institutional supplement so that it may achieve to increase the efficiency of logistic support at pier and to reduce the cost of logistic support.

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

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.203-212
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• 2002

This study examined the predictive power of data mining algorithms by comparing the performance of logistic regression and decision tree algorithm, called CHAID (Chi-squared Automatic Interaction Detection), On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system (HIS ). This system can help improve decision making capability of doctors and improve accessibility of educational material for patients.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.40
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• pp.65-96
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• 2008

This paper analyses the results of a survey questionnaire which is made for logistics service providers in Shanghai, China. Based on 177 valid providers' responses, the study results show that the logistics industry of China consists mainly of small and medium-sized companies. Furthermore, most of the logistics companies are highly capable of providing traditional logistics services and lack of the capability to provide other value-added logistics services. Their self-assessments indicate that they generally perform well in different types of performance measures. This study indicates that the market for 3PL services in China has a reasonable potential for further development, though 3PL practices are still at a nascent stage in China. This paper presents full details and implications of the results of the survey and then tries to provide some helpful suggestion for the development of Chinese logistics companies.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.73-78
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• 2003

Ultrasonic measurement is one of important technologies in the lift-time maintenance of nuclear poler plant. Ultrasonic inspection system is consisted of the operator, equipment and procedure. The reliability of ultrasonic inspection system is affected by its ability. The performance demonstration round robin was conducted to quantify the capability of ultrasonic inspection for in-service. The small number of teams who employed procedures that met or exceeded ASME Sec. XI Code requirements detected the piping of nuclear power plant with various cracks to evaluate the capability of detection and sizing. In this paper, the statistical reliability assessment of ultrasonic nondestructive inspection data using Monte Carlo simulation is presented. The results of the probability of detection (POD) analysis using Monte Carlo simulation are compared to these of logistic probability model. In these results, Monte Carlo simulation was found to be very useful to the reliability assessment f3r the small hit/miss data sets.