• Journal of Distribution Research
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• v.15 no.5
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• pp.175-193
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• 2010

This paper has two objectives. One is to understand status of the distribution industry in Korea and compare it with industrialized countries. The other is an attempt to apply input-output(I-O) analysis to investigate the economic impacts of the distribution industry in the national economy for the year 2008. In the economy as a whole, the distribution industry represented about around 15 per cent employment and accounted for near 8 percent in GDP. The employment portion of the distribution in overall industry is almost same that of US, UK, and Japan, but shared portion in GDP is at least 3 per cent below these countries. Next, a static I-O framework is employed, focusing on two topics in its application. First, the impacts of the product or investment in the distribution industry on the product, value-added, and employment of other sectors are explored by using demand-driven model. Second, the national economic impacts of the distribution industry in Korea are looked into by using open model and inter-industry analysis. It can be summarized that the distribution industry has a high production-inducing effect, more worker and employment-inducing effect, a high forward and a low backward linkage effect. Finally, the implications and limitations of this study are discussed.

• Environmental and Resource Economics Review
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• v.28 no.2
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• pp.231-276
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• 2019

This paper analyzed the impact of the penetration of EV(electric vehicle) and FCEV(fuel cell electric vehicle) into the automobile industry, using a static CGE approach. There are contrasting view on the economic impact of EV/FCEV penetration: negative economic impact due to shrunken intermediate inputs versus positive impact because of input saving technical progress. Regarding environment, there is no clear consensus whether EV or FCEV will contribute to the reduction of $CO_2$ emissions in Korea. This study attempts to provide an answer to these questions. By giving shocks to the input coefficients of automobile industries and automobile using sectors, as well as to the final demands for energies. we integrated the Bass diffusion model into the CGE framework, The result suggests that the EV penetration has adverse impact on the $CO_2$ emission while the FCEV penetration has positive impact. On the other hand, both EV and FCEV have positive impacts on GDP. When considering automobile manufacturing sectors only, adverse impacts on $CO_2$ are demonstrated both for EV and FCEV. However, since the size of $CO_2$ increase is small, these results does not alter the overall effects.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.15-24
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• 2018

Despite the recognition of the need for productivity information and its importance, the feedback of productivity information is not well-established in the construction industry. Effective use of productivity information is required to improve the reliability of construction planning. However, in many cases, on-site productivity information is hardly management effectively, but rather it relies on the experience and/or intuition of project participants. Based on the literature review and expert interviews, the authors recognized that one of the possible solutions is to develop a systematic approach in dealing with productivity information of the construction job-sites. It is required that the new system should not be burdensome to users, purpose-oriented information management, easy-to follow information structure, real-time information feedback, and productivity-related factor recognition. Based on the preliminary investigations, this study proposed a framework for a novel system that facilitate the effective management of construction productivity information. This system has utilized Sketchup software which has good user accessibility by minimizing additional data input and related workload. The proposed system has been designed to input, process, and output the pertinent information through a four-stage process: preparation, input, processing, and output. The inputted construction information is classified into Task Breakdown Structure (TBS) and Material Breakdown Structure (MBS), which are constructed by referring to the contents of the standard specification of building construction, and converted into productivity information. In addition, the converted information is also graphically visualized on the screen, allowing the users to use the productivity information from the job-site. The productivity information management system proposed in this study has been pilot-tested in terms of practical applicability and information availability in the real construction project. Very positive results have been obtained from the usability and the applicability of the system and benefits are expected from the validity test of the system. If the proposed system is used in the planning stage in the construction, the productivity information and the continuous information is accumulated, the expected effectiveness of this study would be conceivably further enhanced.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.115-137
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• 2010

Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

• Journal of Korean Academy of Nursing
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• v.24 no.4
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• pp.584-596
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• 1994

The objective of the study is to explore the relationships between the variables of nursing productivity on the framework of system del in the tertiary university based care hospital in Korea. Productivity is basically defined as the relation-ship between inputs and outputs. Under the proposition that the nursing unit is a system that produces nursing care output using personal and material resources through the nursing intervention and nursing care management. And this major conception of nursing productivity system comproises input, process and output and feed-back. These categorized variables are essential parts to produce desirable and meaningful out-put. While nursing personnel from head nurse to staff nurses cooperate with each other, the head nurse directs her subordinates to achieve the goal of nursing care unit. In this procedure, the head nurse uses the leadership of authority and benevolence. Meantime nursing productivity will be greatly influenced by environment and surrounding organizational structures, and by also the operational objectives, the policy and standards of procedures. For the study of nursing productivity one sample hospital with 15 general nursing care units was selected. Research data were collected for 3 weeks from May 31 to June 20 in 1993. Input variables were measured in terms of both the served and the server. And patient classification scores were measured drily by degree of nursing care needs that indicated patent case-mix. And also nurses' educational period for profession and clinical experience and the score of nurses' personality were measured as producer input variables by the questionnaires. The process varialbes act necessarily on leading input resources and result in desirable nursing outputs. Thus the head nurse's leadership perceived by her followers is defined as process variable. The output variables were defined as length of stay, average nursing care hours per patient a day the score of quality of nursing care, the score of patient satisfaction, the score of nurse's job satis-faction. The nursing unit was the basis of analysis, and various statistical analyses were used : Reliability analysis(Cronbach's alpha) for 5 measurement tools and Pearson-correlation analysis, multiple regression analysis, and canonical correlation analysis for the test of the relationship among the variables. The results were as follows : 1. Significant positive relationship between the score of patient classification and length of stay was found(r=.6095, p.008). 2. Regression coefficient between the score of patient classification and length of stay was significant (β=.6245, p=.0128), and variance explained was 39%. 3. Significant positive relationship between nurses’ educational period and length of stay was found(r=-.4546, p=.044). 5. Regression coefficient between nurses' educational period and the score of quality of nursing care was significant (β=.5600, p=.029), and variance explained was 31.4%. 6. Significant positive relationship between the score of head nurse's leadership of authoritic characteristics and the length of stay was found (r=.5869, p=.011). 7. Significant negative relationship between the score of head nurse's leadership of benevolent characteristics and average nursing care hours was found(r=-.4578, p=.043). 8. Regression coefficient between the score of head nurse's leadership of benevolent characteristics and average nursing care hours was significant(β=-.6912, p=.0043), variance explained was 47.8%. 9. Significant positive relationship between the score of the head nurse's leadership of benevolent characteristics and the score of nurses' job satis-faction was found(r=.4499, p=050). 10. A significant canonical correlation was found between the group of the independent variables consisted of the score of the nurses' personality, the score of the head nurse's leadership of authoritic characteristics and the group of the dependent variables consisted of the length of stay, average nursing care hours(Rc²=.4771, p=.041). Through these results, the assumed relationships between input variables, process variable, output variables were partly supported. In addition it is also considered necessary that-further study on the relationships between nurses' personality and nurses' educational period, between nurses' clinical experience including skill level and output variables in many research samples should be made.

• Korean Journal of Social Welfare
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• v.52
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• pp.117-141
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• 2003

This study is to identify the efficiency in Busan social welfare agencies between input factors and output factors. For this purpose, gathered are the 2001 services reports of those study agencies. This study used 4 difference model, model 1; comparing input factor(social worker number & labor cost) about output factor(the total number of program used person), model 2; comparing input factor(the total number of social welfare agencies staff & the total working expenses) about output factor(the total number of program used person), model 3; comparing input factor(the total number of volunteer, social welfare agencies staff & a period of operation) about output factor(the total number of program used person), model 4; comparing input factor(the total number of volunteer, social welfare agencies staff, a period of operation & the total working expenses) about output factor(the total number of program used person). Charnes's study(1978) provided an analytical tool for efficiency services output of non-profit organizations, and DEA(Data Envelopment Analysis) was a analytical framework for evaluating the impact of social service outcome. the finding are as follows : (1) In the results of comparing 4 models as same standard, we can find 35-55%(16-25) efficiency agencies among the 45 social welfare agencies. (2) For all DMU becoming the efficiency 1 to standard of output factor, model 1; 33 agencies are increasing the social worker number($\Delta$0.8 number), 10 agencies are raising the labor cost of social worker($\Delta$1,189,000 Won), model 2; 30 agencies are increasing the total number of social welfare agencies staff($\Delta$1.25 number), 14 agencies are raising the total working expenses($\Delta$1,447,000 Won), model 3; 8 agencies are increasing the total number of social welfare agencies staff($\Delta$2.26 number), 14 agencies are increasing the total number of volunteer($\Delta$52 number), and 10 agencies are increasing a period of operation($\Delta$13 month), model 4; 24 agencies are increasing the total number of social welfare agencies staff($\Delta$1.8 number), 12 agencies are raising the total working expenses($\Delta$5,017,000 Won), 12 agencies are increasing the total number of volunteer($\Delta$43.2 number), and 23 agencies are increasing a period of operation($\Delta$16 month).

• Korean Journal of Construction Engineering and Management
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• v.2 no.2 s.6
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• pp.47-58
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• 2001

Of all the site logistics technologies in high-rise building construction, both vertical and horizontal move plan, are the most imperative factors. And the horizontal plan follows lift-up plan as of the vertical plan. However though it may be, temporary lifts on site are numbered by heuristic formulas. The quantity of finishing material cannot be converted into lift-up load per finishing material. The lift-up plan cannot be evaluated the feasibility for finishing material move plan by a reasonable evaluation methodology. The horizontal plan is far from the vertical one. And the information as an input data for the horizontal plan is devoid of package unit size, length, and volume per finishing material. These can hardly result in reasonable and detail decision on how much to use temporary lifts, how long to use these, and where to deposit each finishing material. Therefore, this study is to suggest a decision-making model that can integrate vertical and horizontal material move plan in high-rise building construction and make a decision the plans systematically. And the study is to explain the concept, methodology, and contents of the model applied to a virtual project, named as MT 130 (Millennium Tower 130). By the model, the planner can shift his/her thinking framework on site logistics management products-oriented Into process-oriented. He/she can manage a project by the framework as system thinking, evaluate the feasibility of a lift-up plan, and decide the horizontal plan integrated with the lift-up.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1417-1426
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• 2011

Business still relies heavily on pen and paper for legal reasons or convenience. The handwritten document is to be converted into digitalized document for IT system to manage and process in real time. Because the previous document digitalization systems convert the handwritten documents into digitalized documents by scanning and post-processing the documents, it is difficult to seamlessly proceed the work process. This paper proposes the LiveForm, a framework for digitalizing handwritten document using digital pen and handwriting recognition technology. To prove the applicability of the proposed LiveForm, we also implement a LiveForm based service in industrial gas distribution process and analyze effects of the system. The LiveForm generates the same digital image as the handwritten document by writing up the paper with absolute coordinates by digital pen and converts the handwriting data to digital text to insert the information into back-end system. The LiveForm based system eliminates scanning for document digitalization and data input with keyboard into back-end system in paper-based information gathering. Therefore, it is possible for the LiveForm to improve work process in various business areas.

• Atmosphere
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• v.25 no.2
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• pp.221-233
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• 2015

Pollen is closely related to health issues such as allergenic rhinitis and asthma as well as intensifying atopic syndrome. Information on current and future spatio-temporal distribution of allergenic pollen is needed to address such issues. In this study, the Community Multiscale Air Quality Modeling (CMAQ) was utilized as a base modeling system to forecast pollen dispersal from oak trees. Pollen emission is one of the most important parts in the dispersal modeling system. Areal emission factor was determined from gridded areal fraction of oak trees, which was produced by the analysis of the tree type maps (1:5000) obtained from the Korea Forest Service. Daily total pollen production was estimated by a robust multiple regression model of weather conditions and pollen concentration. Hourly emission factor was determined from wind speed and friction velocity. Hourly pollen emission was then calculated by multiplying areal emission factor, daily total pollen production, and hourly emission factor. Forecast data from the KMA UM LDAPS (Korea Meteorological Administration Unified Model Local Data Assimilation and Prediction System) was utilized as input. For the verification of the model, daily observed pollen concentration from 12 sites in Korea during the pollen season of 2014. Although the model showed a tendency of over-estimation in terms of the seasonal and daily mean concentrations, overall concentration was similar to the observation. Comparison at the hourly output showed distinctive delay of the peak hours by the model at the 'Pocheon' site. It was speculated that the constant release of hourly number of pollen in the modeling framework caused the delay.