• Journal of Distribution Science
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• v.12 no.6
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• pp.49-57
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• 2014

Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.457-467
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• 2015

Despite the recent phenomena of Chonsei price increase, low interest rate and low growth, the indexes of financial and insurance industry production showed the results contrary to the common belief that the financial industry is sensitive to such financial crises. This is because the index of financial industry has continuously maintained a certain level of increase as opposed to the index of all industry production. Thus, this study aimed to analyze the dynamic correlation between the index of financial industry production and Chonsei price increase. A vector autoregression (VAR) model, which doesn't have a cointegrating relationship, was used to define the Chonsei price index and the indexes of all industry production and financial and insurance industry, which are macro economic variables, and describe the data. The results of the analysis on the time series data of 183 months from January 2000 to May 2015 showed that Chonsei price increase was not directly derived from the index of financial industry, but the finance industrial index affected Chonsei price increase.

• Land and Housing Review
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• v.11 no.3
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• pp.33-37
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• 2020

The aim of this paper is to scrutinize the relation between Business Survey Index and Industrial Production Index in construction industry, stated in another way, the relation between CEO's expectations of future business status and real business activity in construction industry. Previous papers on this research area have been examined the relation between released BSI and released IPI. However, this paper focuses 'the relation between released BSI and the long-run component of IPI' and 'the relation between released BSI and the short-run component of IPI'. The first step is to decompose released IPI by unobserved component model. The long-run component of IPI is set up as a random walk process. And short-run component is set up as a stationary AR(1) process. The findings are as follows. First, released BSI Granger causes unidirectionally released IPI. Second, there exists one-way Granger causality from released BSI to long-run component of IPI. Third, Granger causality does not exist between released BSI and 'short-run component of IPI'. BSI increases IPI in the second or third month. These findings of this paper mean that CEO's expectations may influence industrial production in construction industry.

• Journal of Distribution Science
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• v.15 no.3
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• pp.17-25
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• 2017

Purpose - The study is to examine the impact of the US Purchasing Managers' Index (PMI) on Korea and the US industrial economy including the distribution industry. We analyze its effect on the industrial economy centered on the distribution industry using economy indices in Korea and the US. Research design, data, and methodology - The variables are used to analyze the dynamic relationship which occurs among the US PMI, the industrial production index, producer price index, unemployment rate, and manufacturing Inventories Index in Korea and the US from January 1990 to July 2016 using Vector Error Correction Model. Results - As a main result, the impact of the US PMI on all the economy indices both Korea and the US has the same cyclical movement. The US PMI is positively related to the producer price and the industrial production index of Korea and the US, while it is negatively related to unemployment rate, and the manufacturing inventories index in Korea and the US. Conclusions - The US PMI as an advanced index has a power to predict the economies on Korea and the US. In the end, we find that the US PMI has a great impact on Korea and the US industrial economy.

• Journal of Korea Technology Innovation Society
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• v.1 no.3
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• pp.364-373
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• 1998

This study examines the international competitiveness of the Korean information and telecommunication industry by using competitiveness index such as the RCA index, the Trade Specialization index, and the Total Factor Productivity. The results of this study show that the industry's competitiveness slightly decreases since 1995, but not its the total factor productivity. In conclusion, the industry has kept the competitiveness over all. Therefore, to keep or improve the competitiveness continuously, the industry is required the government's intensive investment and administrative support. And the industry should bring up by venture and small-medium-size-enterprises to have great economic impacts on other industries. Also, the increasing production and export promoting policy will be enhance the industry and improve nation's balance of trade.

• Spatial Information Research
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• v.20 no.6
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• pp.69-76
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• 2012

In this study, we derived the characteristics of the geo-spatial information industry by using input-output analysis. For this analysis, we classified the geo-spatial information industry and reorganized the input-output table. And we derived the production inducement coefficient, index of the power of dispersion and index of the sensitivity of dispersion in the geo-spatial information industry. We confirmed that geo-spatial information industry has a small production inducement coefficient and a great forward linkage effect. Based on these facts, we suggested the strategy direction as follows: 1) building the industrial eco-system, 2) managing both advance and applicability enhancement, 3) Establishing from a long-term point of view.

• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.103-112
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• 2013

After 1990s, the influence of construction industry has been decreased on national economy and construction business condition has been changed on economic recession and boom repeatedly. Larger fluctuation of business condition makes a forecast of it to be more difficult. Uncertainty in business prediction results in damages on construction companies and stakeholders. Therefore, study on forecasting a construction business is very important. This study suggests the Construction Industry Production Index(CIPI) to predict a construction business in consider of temperature effects. The results show that construction business is much influenced by temperature effects certainly and GDP. With the CBFM, this study examines CIPI for 2013 with two scenarios: 1)with GDP growth rate of 3.5% 2)with GDP growth rate of 2.4%. Thus, CIPI would be used as the economic state index to display the construction business conditions. Also, CIPI will be utilized as basic methodology in the impact of climate change in the construction industry.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.17-27
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• 2014

The number of manufacturing companies that demand the ability to assess sustainability in their manufacturing system is rapidly increasing. However, there are still difficulties in assessing their sustainability in manufacturing for decision-making since it is not easy to determine a single index of sustainability in an operational way. To address these difficulties, this paper proposes an operational guidance and system to assess sustainability of production plan as a single index. The IDEF0 model was defined to explain processes and their input, output, control, and mechanism for sustainability assessment. A prototype system was developed based on the concepts presented in the IDEF0 model, and applied to a case study. To conclude, the prototype system proposed in this paper can help manufacturing companies assess sustainability of their production plans and make a decision using a single value resulted from that assessment.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2009.04a
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• pp.109-110
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• 2009

• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.4
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• pp.67-74
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• 2017

Purpose - The main purpose of this study is to contribute to the elevation of producers' production at various levels by proposing the creation of producer improvement indexes that can be used for the successful 6th industrialization of Korean agribusiness based on the Kano model and has synergistic effects on the development of the 6th industry through scientific researches. Research design, data, methodology - To this end, this study derived better and worse index from the same estimation of Timko's customer satisfaction index as in the evaluation charts used in previous researches and theoretical studies on the Kano model. Results - In this paper, we suggested that the formula for producing PSCI Index be applied to yield the producer improvement index in the 6th industry, in order to draw SIPPI. Conclusions - If this suggestion is realized, then a lot of researchers will be supported to more systematically study producers, and it is expected to contribute to the development of the 1th industry, a basis for the successful 6th industry. Moreover, the central government and municipalities are expected to provide a variety of clues for applying various policies for successful agribusiness.