• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.118-127
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• 2018

Recently, service quality must reflect several demands of customers who show rapid and various changes so as to be compared with the past. So, objective and rapid measuring methods for service quality are necessary. For them, first of all, service company must calculate their standard of service quality accurately by measuring service quality exactly. Kano classified the degree of influence that is the degree of correspondence of the quality attributes of products and services to the subjective satisfaction of customers. As a result, the types of qualities are classified as attractive, must be, one dimensional, and indifference attributes. They have been widely used quality attributes in various industrial fields up to now. However, Kano model has a limit that it ignores the characters of the next frequent numbers even though there are not much gap comparing to the most frequent number in the questionnaire answers. The limit is attributed to the character of Kano model that the most frequent number is accepted as the only quality character. Timko calculated the customer satisfaction coefficient by using Kano's method and studied the differences in quality character by classifying the quality characteristics in a graphical way through the relationship between the satisfaction and the dissatisfaction coefficient. In this study, we used the quality level determination method of the 7-point Likert scale, which takes the weight into account, to complement the deficiencies of the existing Kano model. We also developed and applied a Potential Satisfaction Level (P) and Potential Customer Demand Improvement (PCDI) Index to present a new approach to the determination of service quality attributes. To measure the level of potential service satisfaction and to understand the degree of improvement, we collected specimens of 51 participants who has been trained in the National Strategy Business Training Program, which has been managed by government agent, and analyzed the results.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.55-66
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• 2015

In the perspective of industrial health management, it is important for the employee to decrease their job stress, to improve their productivity and quality of labor. In this study, the job stress, and it's influence on PWI(Psychosocial Wellbeing Index) were investigated by the questionnaire survey of 138 industrial workers who had studied assistive technology in college. The contents of questionnaire consist of the demographic characteristics, job-related characteristics, job stress and psycho-social stress. We evaluated job stress by KOSS-SF(Korean Occupational Stress Scale-Sort Form) and psychosocial stress by PWI-SF(Psychosocial Well-being Index-Short Form). To analyze the results, we evaluated the exposure level of KOSS and PWI by demographic characteristics and job-related characteristics using significance tests. Also, we estimated the relationship among demographic characteristics, job-related characteristics, job stress and psychosocial stress, using correlation analysis. As a results, all workers were found to be in a group under the high risky stress. It showed that the scale index of female's job non-autonomy and pwi were much larger than those of male's. Therefore, to guarantee job autonomy of female workers should be more emphasized, to improve their working environment. Job type had significant relationships with many job stress category; physical environment, job demand, job instability and organization culture. Regarding pwi, the scale index of the workers who is in charge of the civil service such as contacting the disabled and the aged in person, were much larger than that of the other workers. Accordingly, the job stress management program including physical environment, job demand, job instability and organization culture, should be suggested, to decrease the stress of the workers in charge of the disabled and the elders service. The strongest predictors of pwi was organization system through maximum positive relations between organization system and pwi. Therefore, it indicates that improvement of organization system such as a fair merit rating, a manpower supply, demand plan and department cooperation is urgently needed to reduce pwi.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.103-112
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• 2016

This study used a job demand-resources model as the basis to examine the effects of job demand and job resources on health problems and turnover intention. A total of 320 nurses who were employed at university hospitals in Seoul participated in the study. The results showed that job demand and job resources had a direct effect on the levels of work burnout and work engagement. Work burnout had a direct effect by increasing the levels of health problems and turnover intentions of nurses; conversely, work engagement had no direct impact on either of the two levels. Job demand and job resources had an indirect effect on increased levels of health problems and turnover intention. The results can be used by hospital administrations to confirm the organizational significance of job resources in increasing job performance and work involvement, as well as to understand the consequences of perceived job demand by nurses.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.79-85
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• 2009

In this study, the effects of psychosocial stress (box color and precision demand) on muscle activity were evaluated in laboratory setting. Eight subjects performed sagittally symmetric lifting tasks. Box color (yellow, black), precision demand (yes, no), and box weight (5%MVC, 10%MVC, 15 %MVC) were varied and surface EMG signals from seven muscles(medial deltoid right, biceps brachii right, lateral triceps right, latissimus dorsi right, erector spinae right, external oblique right, internal oblique right) were recorded. EMG signals were band-pass filtered($10{\sim}400\;Hz$), rectified, RMS smoothed and normalized (NEMG). Analysis of variance tests were conducted on the total NEMG (TNEMG: the sum of the seven muscles' NEMGs) and on the individual muscle's NEMGs. Box color had no effect on the TNEMG and on the seven muscles activities(p>0.05). When precision demand was required at the end point of lifts, the mean NEMG showed higher values than no precision demand conditions: TNEMG (14% increase) and medial deltoid(40% increase), biceps brachii(10% increase), lateral triceps(26% increase), latissimus dorsi(25% increase) muscles. Those increases showed more conspicuous as the box weight increased in the muscles of medial deltoid, lateral triceps, and latissimus dorsi.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.469-474
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• 2020

This study explains the characteristics of micro-insurance based on the theoretical model of health insurance, such as the low demand of low-income people and the lower demand of higher risk aversion. In particular, these characteristics contradict the existing insurance theory which states that the lower the income, the higher the risk aversion, and the higher the demand for insurance. This study postulates a two-period model focusing on health insurance, contrary to a one-period model assumed in existing studies. As a result, first, we show that the decrease in income leads to a decrease in the preventive effort for illness. Second, we offer a model for micro-insurance in which the individual chooses a partial insurance under an actuarially fair insurance premium, while full insurance is optimal in existing studies. Third, we also show that the insurance demand decreases when the outlook for the future improves. Fourth, we finally show that the lack of trust and default risk of the insurer decrease the insurance demand as risk aversion increases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.155-167
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• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.

• Environmental and Resource Economics Review
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• v.27 no.2
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• pp.287-313
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• 2018

This paper measures and analyzes cooling and heating demand in Korean electricity demand using time-varying temperature response functions and cooling and heating temperature effects. We fit the model to Korean data for residential and commercial sector over 1999:01~2016:12 and the estimation results show that the growth rate of heating demand is much higher than that of base and cooling demand, and especially the growth rate of heating demand in commercial sector is much higher. And we define the temperature-normalized demand conditioning that monthly temperatures are assumed as average monthly temperatures. The growth rate of heating demand in the estimated temperature-normalized demand is higher than that in the real demand. Our results are expected to be a base data for Winter Demand Management and short-term electricity demand forecasting.

• Journal of the Korean Geographical Society
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• v.37 no.5
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• pp.465-479
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• 2002

This paper seeks to Produce a typology of enterprise-support services. Drawing upon this typology, this study will attempt to identify the status quo of the government enterprise-support services system and also examine the demand for and supply of these services according to regional differences and industrial characteristics (old versus new). Based on results of the survey taken in the Seoul software industry cluster especially around the Seocho, Gangnam-Gu, the Daejeon ICT industry cluster and the Gumi electronics industry cluster, it can be said that the demand for and supply of enterprise-support services are differentiated by the nature of an industry, the characteristics of a region and the growth stage of a firm. Finally, some policy suggestions will be addressed.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.92-99
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• 2004

We consider the ATM switching node location problem (ANLP). In this problem, there are two kinds of facilities, hub facilities and remote facilities, with different capacities and installation costs. We are given a set of customers with each demand requirements, a set of candidate installation sites of facilities, and connection costs between facilities. We need to determine the locations to place facilities, the number of facilities for each selected location, the set of customers who are connected to each installed hub via installed remote facilities with minimum cost, while satisfying demand requirements of each customer. We formulate this problem as a general integer programming problem and solve it to optimality. In this paper, we present a preprocessing procedure to tighten the formulation and develop a branch-and-price algorithm. In the algorithm, we consider the integer knapsack problem as the column generation problem. Computational experiments show that the algorithm gives optimal solutions in a reasonable time.