• Management & Information Systems Review
• /
• v.35 no.3
• /
• pp.57-79
• /
• 2016

It is required to derive various conclusions by identifying the type of power and the relationship between SCMs and presenting practical implications. Thus, we can identify the differential effects of each type of power on SCM performance. We can contribute to develop the practical implications at more sophisticated multi-dimension by comparing results of this study with various SCM theories. Through previous studies, the source of power is largely divided into binding power and non-binding power. Binding power is classified into behavior coercion, binding reward and relationship legitimacy. Non-binding power is classified into work expertise, information superiority and value compliance. Enterprises should fully understand and recognize partners within supply chains including understanding of the source of power, imbalance and results. Thus, we look into types of power and effects on trust and commitment, and identify a causal relationship leading to collaboration and SCM performance. Specific research results are as follows. First, the binding power did not give a significant effect to the trust. However, the binding power gave a positively(+) significant effect to the commitment. Second, non-binding power showed a significant effect on both trust and commitment. As a result of analysis on total effects, it was shown that non-binding power gave indirect effects to collaboration and SCM performance. Third, it was shown that both trust and commitment significantly affected collaboration. From the perspectives of social exchange theory and trading cost theory among inter-organizational relationship theory, it may lead to SCM performance of trust, commitment and collaboration. Moreover, it was found that association of each attribute of power led to the significant result. Fourth, it was shown that trust and collaboration significantly affected SCM performance. However, commitment did not directly affect SCM performance, but it indirectly significantly affected SCM performance through collaboration. Proper use of this power can firmly build partnerships between members of the supply chain and induce the improvement on supply chain performance and satisfaction of members.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.36 no.4
• /
• pp.488-498
• /
• 2007

The purposes of this study were to: a) provide evidences concerning the effects of emotional leadership b) examine the impacts of emotional leadership on employee-related variables, 'job satisfaction', 'organizational commitment', 'organizational performance' and 'turnover intention', and c) identify a conceptual framework underlying emotional leadership. A survey was conducted from August 23 to November 3, 2005 to collect data from mid-level managers in food service company headquarters (N=219). Statistical analyses were completed using SPSS Win (12.0) for descriptive, reliability, factor and correlation analyses and AMOS (5.0) for confirmatory factor analysis and structural equation modeling. The main results of this study were as follows. First, the managers gave the highest point to their leaders in the emotional leadership competence 'organizational awareness : reading the currents, decision networks, and politics at the organizational level' and gave the lowest point in the emotional leadership competence 'influence: wielding effective tactics for persuasion'. Second, the means of job satisfaction was above the midpoint (3 points). Employees' job satisfaction with 'coworkers' was relatively high. However, the extents of satisfaction with 'payroll' 'promotion', and 'work environment' were relatively low. Third, the organizational commitment was above the midpoint (3 points). In the organizational commitment, 'loyalty' factor was higher than 'commitment' factor. Fourth, the means of organizational performance was above the midpoint. The highest organizational performance variable was 'internal efficiency; trying to reduce cost' and the lowest organizational performance variable was 'internal fairness ; equitable treatment and all are treated with respect with no regard to status and grade'. Fifth, most respondents intended on 'thinking of quitting ; towards turnover process'. Sixth, the test of hypothesis using structural equation modeling found that emotional leadership produced p[Isitive effects on job attitude and job performance. Emotional leadership enhanced job satisfaction and organizational commitment, and in turn, employees' attitude positive effects on organizational performance; emotional leadership also had a direct impact on organizational performance

• The korean journal of orthodontics
• /
• v.51 no.2
• /
• pp.115-125
• /
• 2021

Objective: To evaluate the reasons influencing the preferences for a certain type of orthodontic appliance over another among prospective patients (PP) and orthodontists. Methods: A total of 49 PP and 51 orthodontists were asked about their preferences for the following appliances: clear aligners (CA), lingual metallic brackets (LMB), polycrystalline and monocrystalline ceramic brackets, and buccal metallic brackets (BMB). The participants rated the importance of 17 potential reasons that would explain their choices. The reasons that contributed most to these preferences were identified. Non-parametric tests (Fisher's exact, χ2 and Mann-Whitney tests) and multivariate analyses (regression and discriminant analysis) were used to assess the data (α = 0.05). Results: CA and BMB were the most chosen appliances by PP and orthodontists, respectively. LMB was the most rejected option among both groups of participants (p < 0.001). Rates of the importance of pain/discomfort, smile esthetics, finishing details, and feeding/speech impairment showed the highest differences between PP and orthodontists (p < 0.0005). Discriminant analyses showed that individuals who considered treatment time and smile esthetics as more important were more likely to prefer CA, while those who prioritized finishing details and cost were more likely to choose BMB (p < 0.05). Conclusions: Reasons related to comfort and quality of life during use were considered as more important by PP, while those related to the results and clinical performance of the appliances were considered as more relevant by orthodontists.

• Clean Technology
• /
• v.28 no.4
• /
• pp.285-292
• /
• 2022

Adsorption tower systems based on activated carbon adsorption towers have mainly been employed to reduce the emission of volatile organic compounds (VOCs), a major cause of air pollution. However, the activated carbon currently used in these systems has a short lifespan and thus requires frequent replacement. An approach to overcome this shortcoming could be to develop metal oxide photocatalysis-activated carbon composites capable of degrading VOCs by simultaneously utilizing photocatalytic activation and powerful adsorption by activated carbon. TiO₂ has primarily been used as a metal oxide photocatalyst, but it has low economic efficiency due to its high cost. In this study, ZnO particles were synthesized as a photocatalyst due to their relatively low cost. Silver nanoparticles (Ag NPs) were deposited on the ZnO surface to compensate for the photocatalytic deactivation that arises from the wide band gap of ZnO. A microfluidic process was used to synthesize ZnO particles and Ag NPs in separate reactors and the solutions were continuously supplied with a pack bed reactor loaded with activated carbon powder. This microfluidic-assisted pack bed reactor efficiently prepared a Ag-ZnO-activated carbon composite for VOC removal. Analysis confirmed that Ag-ZnO photocatalytic particles were successfully deposited on the surface of the activated carbon. Conducting a toluene gasbag test and adsorption breakpoint test demonstrated that the composite had a more efficient removal performance than pure activated carbon. The process proposed in this study efficiently produces photocatalysis-activated carbon composites and may offer the potential for scalable production of VOC removal composites.

• Korean Journal of Community Nutrition
• /
• v.15 no.1
• /
• pp.124-136
• /
• 2010

The purposes of this study were to investigate importance level and performance frequency of the dietitians' duties and task elements, to examine the actual condition of education and need for education, to analyze the interrelation between their tasks and education, and to provide the direction of education for the contracted Business & Industry (B & I) foodservice dietitians. The task elements of receiving, ordering, HACCP management and directing serving process were done almost every day. In terms of the importance of tasks, food sanitation management, personnel sanitation management, receiving and ordering were high. Meanwhile, the computerization of their works was being carried out on the whole, showing a higher frequency in all the details of procurement management and accounting management, as well as task elements such as menu planning, leftover and food waste management, HACCP management and human resource management. In the past three years, HACCP management, cost management, planning work schedule and allotting a task, general business and sale bond management were increased most and rapidly. For the actual condition of education, dietitians got more education for the duty of sanitation, safe and facility/utility management than any other duty, while they did less education of procurement management and office management than others. Meanwhile, the education for sanitation, safe and facility/utility management and accounting management were very much required. For the relationships of frequency of duty and the necessity of education, seven task elements including food sanitation management were correlated positively. Eighteen tasks besides menu planning had a significant positive correlation between the importance of duties and the necessity of education.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.334-334
• /
• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• Korean Journal of Agricultural Science
• /
• v.44 no.3
• /
• pp.451-461
• /
• 2017

Korean agriculture has recently focused on the 6th dimension of industrialization, which includes the functions of healing and care. The green care and healing business is one of the most representative models, satisfying modern consumers' needs for care or healing in rural agricultural environments. Many studies have shown physical and social benefits from green care and healing, but studies regarding economic performance are rarely found. The present study aimed to analyze the economic feasibility of different green care and healing farm complexes proposed in recent domestic research, with various possible combinations of business scenarios. The results show that most of the scenarios are economically feasible as B/C (benefit-cost ratio) and IRR (internal rate of return) are 1.19 and 8.53%, respectively, under scenario 1. This study also performed a break-even analysis for providing more flexible decision-making information. Overall, scenario 1 from green care and healing site and scenario 4 from green care and healing cluster are found to be superior to the other scenarios in terms of B/C and IRR. The scenarios in this study reflect the domestic farms or complexes which have similar functions of care or healing. Therefore, the results of this study provide information on practical policies and business implications in making decisions on the specific size and operational patterns when adopting green care and healing complexes by central or local governments and private sectors in the future.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.2
• /
• pp.43-57
• /
• 2021

Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.

• Environmental Engineering Research
• /
• v.25 no.4
• /
• pp.536-544
• /
• 2020

To address organic dye wastewater, economic and effective adsorbents are required. Here, magnetic biochar from alkali-activated rice straw (AMBC) was successfully synthesized using one-step magnetization and carbonization method. The alkaline activation caused the large specific surface area, high pore volume and abundant oxygen-containing groups of the AMBC, and the magnetization gave the AMBC a certain degree of electropositivity and fast equilibrium characteristics. These characteristics collectively contributed to a relative high adsorption capacity of 53.66 mg g^-1 for this adsorbent towards rhodamine B (RhB). In brief, RhB can spontaneously adsorb onto the heterogeneous surface of the AMBC and reach the equilibrium in 60 min. Although the initial pH, ionic strength and other substances of the solution affected the adsorption performance of the AMBC, it could be easily regenerated and reused with considerable adsorption content. Based on the results, H-bonds, π-π stacking and electrostatic interactions were speculated as the primary mechanisms for RhB adsorption onto the AMBC, which was also demonstrated by the FTIR analysis. With the advantageous features of low cost, easy separation, considerable adsorption capacity and favorable stability and reusability, the AMBC would be a potential adsorbent for removing organic dyes from wastewater.

• Steel and Composite Structures
• /
• v.52 no.2
• /
• pp.145-163
• /
• 2024

This paper presents six novel hybrid machine learning (ML) models that combine support vector machines (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with the Harris Hawks Optimization (HHO) algorithm. These models, namely HHO-SVM, HHO-DT, HHO-RF, HHO-GB, HHO-XGB, and HHO-CGB, are designed to predict the ultimate strength of both rectangular and circular reinforced concrete (RC) columns. The prediction models are established using a comprehensive database consisting of 325 experimental data for rectangular columns and 172 experimental data for circular columns. The ML model hyperparameters are optimized through a combination of cross-validation technique and the HHO. The performance of the hybrid ML models is evaluated and compared using various metrics, ultimately identifying the HHO-CGB model as the top-performing model for predicting the ultimate shear strength of both rectangular and circular RC columns. The mean R-value and mean a20-index are relatively high, reaching 0.991 and 0.959, respectively, while the mean absolute error and root mean square error are low (10.302 kN and 27.954 kN, respectively). Another comparison is conducted with four existing formulas to further validate the efficiency of the proposed HHO-CGB model. The Shapely Additive Explanations method is applied to analyze the contribution of each variable to the output within the HHO-CGB model, providing insights into the local and global influence of variables. The analysis reveals that the depth of the column, length of the column, and axial loading exert the most significant influence on the ultimate shear strength of RC columns. A user-friendly graphical interface tool is then developed based on the HHO-CGB to facilitate practical and cost-effective usage.