• The Journal of Industrial Distribution & Business
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• v.13 no.12
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• pp.1-8
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• 2022

Purpose: This study aims to analyze the importance of customers' selection attributes for meal kits, which is rapidly increasing in the home meal replacement food market, and empirically analyze the effect of food selection attributes on consumer satisfaction and repurchase intention toward meal kits. Research design, data, and methodology: Based on the results of previous research, factors that customers consider the most when purchasing a meal kit are nutritional components, ingredients, hygiene, taste, and price. The empirical analysis is conducted by using structural equation modeling to determine the extent that customer selection attributes for meal kits affect customer satisfaction and repurchase intention. The survey is conducted online from January 1 to March 15, 2022, and 282 valid samples are used for the analysis. Results: The result of the analysis confirms that nutritional components, hygiene, taste, and price have a statistically significant effect on customer satisfaction and repurchase intention. However, the effect of food ingredients on customer satisfaction and repurchase intention is rejected because no statistically significant results are obtained. Conclusions: As an empirical analysis of the importance of customer selection attributes of meal kits, this study has meaningful implications for related industries and business-to-business operators and provides basic data for the strategic development of related industries.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.413-421
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• 2021

Government expenditure on education has attracted much attention because it plays an important role in the economic development. The question is whether government expenditure on education has a positive or negative impact on the economic growth and vice versa. This study aims to provide reliable estimates of the relationship between government expenditure on education and economic growth with empirical evidence in Vietnam for the period 2006-2019. The data was taken from the official statistics of the General Statistics Office of Vietnam. The authors have used the VAR model and Granger causal model to determine the relationship between government expenditure on education and the economic growth. Research results show that there is a two-way nexus between the economic growth and government spending on education with a lag of about two years. From the results obtained from this research, the authors have made some policy suggestions for the Vietnamese government as how to increase investment for education. If there is a one-way causal relationship between expenditure on education and the economic growth, the government can use spending as a growth factor. However, if there is a bi-directional relationship between the government expenditure on education and the GDP growth, the government needs to ensure that resources are appropriately managed and allocated effectively to promote growth.

• Korea Trade Review
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• v.44 no.4
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• pp.169-188
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• 2019

This study aims to analyze the effects of the smart technologies acceptance on global supply chain innovation and export performance in Korean small and medium trading companies. As the world prepares for the advent of the 4th industrial revolution the level of smart technology acceptance by Korean small and medium trading companies has not yet reached the level that is compatible with the change of international paradigm. In this respect, this study aims to promote the acceptance of smart technologies and suggest a need of more practical policy for securing international market competitiveness through innovation of global supply chain structure of Korean trading companies. According to the empirical research results, the smart technology acceptance had a significant effect on both the internal supply chain innovation and the export performance. Also, the external supply chain innovation significantly affected export performance. These results suggested that Korean trading companies need to be more active and positive in accepting smart technology so that they can gain more competitive advantage in the 4th industrial revolution era.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.153-160
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• 2009

This study is to develop a human resource (HR) security framework, and related HR security indicators in the context of information security. The HR security framework consists of three constructs, personnel assurance, personnel competence, and personnel security control. Based on the framework, HR security management indicators are derived as 26 indicators in 9 items out of 3 categories. An empirical research has been performed to verify the relevance and consistency between the indicators by conducting a questionnaire-based survey. Also, interrelationships between the proposed indicators and HR related security level were analyzed by the multiple regression analysis. As a result, the proposed hypothesis were mostly accepted, showing the significant relationships between the indicators and security level.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.1-15
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• 2022

Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against the established Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the less explored but robust STES (Smooth Transition Exponential Smoothing) methods. (2) comparing forecast error performance between realized variance and squared residuals measures as a proxy for actual volatility. Data of seven private equity mutual fund indices (generated from 57 individual funds) from two different time periods (with and without financial crisis) are applied to 21 models. Robustness of the post-sample volatility forecasting of all models is validated by the Model Confidence Set (MCS) Procedures and revealed: (1) The weekly RVar-MIDAS model emerged as the best model, outperformed the robust DAILY-STES methods, and the weekly DAILY-GARCH models, particularly during a volatile period. (2) models with realized variance measured in estimation and as a proxy for actual volatility outperformed those using squared residual. This study contributes an empirical approach to one-week ahead volatility forecasting of mutual funds return, which is less explored in past literature on financial volatility forecasting compared to stocks volatility.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.171-182
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• 2022

Purpose - The main purpose of this study is to test two competing hypotheses on the relationship between foreignness and corporate philanthropy drawing on the resource dependence theory. Design/methodology/approach - This study used Korean Enterprsie Survey data constructed by Korean Statistical Information Service. This study employed both OLS and Tobit models to test the hypotheses. Findings - A conventional wisdom can argue that MNC subsidiaries are more willing to give charitable donations than local firms do because they may perceive philanthropy in the host country is a good opportunity to reduce liabilities of foreignness (H1-1). On the other hand, one can argue that MNC subsidiaries are less willing to give charitable donations than local firms do because they have operational flexibility when they are coerced to engage in corporate philanthropy by host country government stakeholders (H1-2). Empirical results support the prediction that MNC subsidiaries are less likely to give charitable donations than local firms do in Korea. Research implications or Originality - Our findings can provide useful insights to researchers and managers in the sense that MNC managers can increase or decrease their charitable donations depending on the institutional contingencies in different host countries. These institutional contingencies are particularly important within a transforming context such as Korea.

• Journal of the Korea Safety Management & Science
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• v.24 no.3
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• pp.93-103
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• 2022

This study investigated the method of continuous improvement of small-medium company production processes through POSCO's QSS(Quick Six Sigma) activities. QSS is a field operation technique that encompasses the advantages of Six Sigma, TPS(Toyota Production System), TQM (Total Quality Management), and IE(Industrial Engineering). Through this, POSCO not only encourages activities centered on related small and medium-sized partners, etc., but is also expected to contribute to the continuous improvement of the company's own production process through QSS activities. In this study, rather than unconditionally carrying out activities according to the needs of large companies, the research is to help the continuous improvement of the actual production process of small and medium-sized enterprises by effectively applying and spreading QSS activities in consideration of the characteristics and environment of the company. For this purpose, empirical research is conducted on the process improvement activities and QSS activities of company Y, which has less than 100 assembly and production quality and inspection processes among SMEs. The changes in the production process improvement of SMEs through the application of the final QSS were investigated through empirical studies.

• Journal of Korea Trade
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• v.23 no.3
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• pp.52-67
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• 2019

Purpose - This study analyzes the effect of the authorized economic operator-mutual recognition arrangement (AEO-MRA) on the performance of Korean exporters and importers. The effect of the import-export companies' characteristics, such as annual sales, the number of foreign markets, and overseas experience, on the AEO-MRA is deduced; the relationship between this effect and firm performance is analyzed. Design/methodology - An empirical research model was constructed and analyzed using structural equation modeling. The effect of AEO-MRA on logistics and operational performance was derived from the aforementioned characteristics as leading factors of the AEO-MRA. The regulatory influence of cooperation with logistics companies was analyzed in the AEO-MRA effect on logistics performance. Thus, 172 valid samples were obtained from import-export companies certified by the AEO-MRA. Findings - Among the aforementioned characteristics, only "annual sales" has a positive effect on the AEO-MRA, whose effect enhances logistics and operational performances. The AEO-MRA effect did not directly affect operational performance. Owing to the adjustment effect analysis, the AEO-MRA effect and logistics performance relationship is strengthened if the cooperative relationship with the logistics company is higher than a certain level. If this cooperation falls below a certain level, the AEO-MRA effect on logistics performance reduces. Thus, logistics cooperation is an important factor in the AEO-MRA effect and logistics performance relationship. Originality/value - Hinging on the resource-based theory and relational viewpoint, an empirical model that explains the relationship between the AEO-MRA effect and firm performance is established.

• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.149-156
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• 2022

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).