• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.185-195
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• 2022

Purpose - This study attempts to analyze the determinants of inventory turnover by applying quantile regression analysis. Design/methodology/approach - By selecting the gross margin, capital intensity, and sale surprise as the determinants of inventory turnover, we investigate their effects on inventory turnover at the several quartiles (10%, 25%, 50%, 75%, 90%) of inventory turnover with quantile regression analysis. Findings - The effects of gross margin and capital intensity on inventory turnover are different for each quartile. But the effects of sale surprise on inventory turnover are not different for each quartile. Research implications or Originality -This study is the first attempt to examine the effects of inventory turnover determinants on inventory turnover by applying quantile regression analysis was not employed in the prior studies. Thus, this study is meaningful in that it shows the possible way to review inventory management strategies that can be applied differently to the firms with different inventory turnover levels.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• Journal of The Korean Association For Science Education
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• v.33 no.3
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• pp.679-693
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• 2013

The purpose of this study is to develop an inventory to classify task commitment types of science learning and to classify highschool students' task commitment types. Firstly, inventory questions were designed following the literature analysis on the task commitment components which involve self confidence, high goal setting, and focused attention. Prototype inventory underwent the content validity test, pilot test, and reliability test. Through these steps, final inventory was input to 462 high school students and underwent the factor analysis and cluster analysis. Factor analysis confirmed three components of task commitment as the three factors of inventory questions. In order to find how many clusters exist, factors of developed inventory became new variables. Each factor's factor mean was calculated and served as the new variable of the cluster analysis. Cluster analysis extracted five clusters as task commitment types. The 5 clusters were suggested by the agglomarative schedule and dendrogram gained from a hierarchical cluster analysis with the setting of the Ward algorithm and Squared Euclidean distance. Based on the factor mean score, traits of each cluster could be drawn out. Inventory developed by this study is expected to be used to identify student commitment types and assess the effectiveness of task commitment enhancement programs.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.358-366
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• 2011

Multi-criteria ABC inventory classification, which aims to classify inventory items by considering more than one criterion, is one of the most widely employed techniques for inventory control. The weighted linear optimization (WLO) model proposed by Ramanathan (2006) solves the problem of multi-criteria ABC inventory classification by generating a set of criterion weights for each inventory item and assigning a normalized score to the item for ABC analysis. However, the WLO model has some limitations. First, many inventory items can share the same optimal score, which can hinder a precise classification of inventory items. Second, the model allows too much flexibility in weighting multiple criteria; each item is allowed to choose its own weights so that it can maximize its score. As a result, if an item dominates the others in terms of a certain criterion, it may be classified into a higher class regardless of other criteria by assigning an overwhelming weight to the criterion. Consequently, an item with a high value in an unimportant criterion and low values in others may be inappropriately classified as class A, leading to an inaccurate classification of inventory items. To overcome these shortcomings, we extend the WLO model by using the cross-efficiency method in data envelopment analysis. We claim that the proposed model can provide a more reasonable and accurate classification of inventory items by mitigating the adverse effect of flexibility in the choice of weights and yielding a unique ordering of inventory items.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.980-983
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• 2008

KICT has been carrying out inventory research on the cut slopes of national roads. Inventory research results are basic data used in cut slope management system. Inventory data are classified by general status, cut slope characteristics and inspector opinion. Cut slope inventory data are utilized to figure out dangerous slopes and decide survey ranking of detailed safety diagnostication. This paper will draw dangerous cut slope and more important inventory data in Chungcheongdo via correlation analysis.

• Journal of the Korean Home Economics Association
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• v.34 no.5
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• pp.1-12
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• 1996

The purpose of this study was to develop the Self-Esteem Inventory for Children in Korea. The 772 subjects were selected from 3rd-6th grades of elementory schools and the first and second grades of middle schools in Pusan. Statistics used for data analysis were Pearson's r, Cramer's V, X2, factor analysis, multi-regression, splithalf reliability, Cronbach's α. The major findings were that 1) eight factors(home self, personality self, academic self, teacher-related self, general self, physical-appearance self, peer-related self, physical-competence self) were extracted by factor analysis, multi-regression analysis conducted to reduce the iength of inventory have drawed 38 items for the Self-Esteem Inventory for Children in Korea. 2) the discriminant coefficients of the items (Cramer's V) ranged from 0.55 to 0.67. 3) the reliability coefficients of this inventory (Cronbach's α) ranged from 0.63 to 0.81. It was concluded that Self-Esteem Inventory for children is acceptable.

• Korean Journal of Adult Nursing
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• v.24 no.1
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• pp.31-37
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• 2012

Purpose: This Study was to examine to applicability of the Maslach Burnout Inventory on measuring burnout of the nurses who works in Korean university hospitals. Methods: The sample included 200 nurses and nurse managers. We used 22-item Maslach Burnout Inventory to evaluate the reported burnout. We evaluated the convergent validity through the factor analysis, and evaluated the discriminant validity through the Pearson's correlation analysis. Also, we evaluated the reliability for three subscales of Maslach Burnout Inventory with the Cronbach's ${\alpha}$, which assesses the internal consistency. Results: Factor analysis revealed three factors being extracted from the 22-item Maslach Burnout Inventory, and item loading for each factor is higher than 0.5. Therefore, the Maslach Burnout Inventory demonstrated high convergent validity. Also, emotional exhaustion, personal accomplishment, and depersonalization showed low correlation leading to the conclusion that there was discriminant validity. The Cronbach's ${\alpha}$ coefficients in the 22-item Maslach Burnout Inventory and three subscales were higher than 0.7. Conclusion: Maslach Burnout Inventory can be used as a valid instrument to measure the burnout level of the nurses working in Korean university hospitals.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.1
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• pp.1-6
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• 1979

This paper discusses an application of discrete variable Servo Theory to the analysis of the effectiveness of production-inventory control system which uses exponential smoothing as a specific forecasting technique by establishing a new model which consists of such three departments as production planning, production, and inventory. The objective of the new production-inventory model is to keep the production to the optimal level of minimum production cost in production planning problem for obtaining, the stability of inventory subject to demand variation. On this basis, the dynamic characteristic of the system with the change of the parameters is clarified by the numerical analysis. The results of the numerical analysis show the effect that is obtained by the simultaneous stability of production and inventory as soon as possible.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.15-23
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• 1992

This paper dvelops an inventory model with partial backorders considering both inflation rate and discount rate under the situation of deterministic demand and lead time and then make an economic analysis. Especially, the inventory model with partial backorders provided here is the inventory model minimizing annual total cash outflows, which is extended by the addition of inflation rate and discount rate into "Inventory Model with Partial Bakorders" of Park [6]. An iterative solution procedure is developed to find an optimal inventory policy. To provide guidelines for economic analysis of inventory model with partial backorders, sensitivity analysis for selected values of parameters is performed.performed.

• Korean Management Science Review
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• v.34 no.3
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• pp.1-14
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• 2017

This study empirically analyzes the impact of inventory management performance on the energy efficiency in Korean petrochemical companies. The concept of the distance function is used to define the energy efficiency and the estimation of the distance function is performed using the stochastic frontier analysis. The inventory turnover is selected as the variable indicating the inventory management performance of the company. The main results of this study are as follows. First, the inventory turnover has a positive impact on energy efficiency. Second, during the period over 2011~2015, while the gap in energy efficiency among the companies expanded, the average energy efficiency decreased. Third, the average energy efficiency in upstream process companies was greater than downstream process companies and the gap in energy efficiency among downstream process companies was greater than upstream process companies. Fourth, the average marginal effect of inventory turnover on energy efficiency increased gradually from 2011 to 2015. Finally, the average marginal effect of inventory turnover in downstream process companies was greater than upstream process companies, and the gap in the marginal effect of inventory turnover among downstream process companies was greater than upstream process companies. These results together imply the importance of inventory management in terms of energy efficiency.