• 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.

• Korean Management Science Review
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• v.31 no.3
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• pp.27-39
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• 2014

We derive a generalized statistic form of Q control chart, which is especially suitable for short run productions and start-up processes, for the detection of process mean shifts. The generalization means that the derived control chart statistic concurrently uses within lot variability and between lot variability to explain the process variability. The latter variability source is noticeably prevalent in lot type production processes including semiconductor wafer fabrications. We first obtain the generalized Q control chart statistic when both the process mean and process variance are unknown, which represents the case of implementing statistical process control charting for short run productions and start-up processes. Also, we provide the corresponding generalized Q control chart statistics for the rest of three cases of previous Q control chart statistics : (1) both the process mean and process variance are known (2) only the process mean is unknown and (3) only the process variance is unknown.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.97-103
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• 2006

Recently, the control chart is developed for monitoring processes with normal short production runs by the coefficient of variation(CV) characteristic for a normal distribution. This control chart does not work well in non-normal short production runs. And most of industrial processes are known to follow the non-normal distribution. Therefore, the control chart is required to be developed for monitoring the processes with non-normal short production runs by the CV characteristics for a non-normal distribution. In this paper, we suggest the control chart for monitoring the processes with a gamma short runs by the CV characteristics for a gamma distribution. This control chart is denoted by the gamma CV control chart. Futhermore evaluated the performance of the gamma CV control chart by average run length(ARL).

• Journal of the Korean association of regional geographers
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• v.12 no.6
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• pp.748-756
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• 2006

This study mainly deals with price behavior developed in a agricultural location model (or closed model) considering the production and demand aspects. The short-run situation of price and output is associated with the yearly fluctuation of yield from agricultural production. Demand is generally regarded as constant in the short-run because of being inelastic over short time. The long-run situation is associated with a period in which all related variables can be varied. Then a price behaviors from the two contrasting closed models have been further explored in the long-run economy. Agricultural price for each activity in the closed model is affected by change in agricultural production. Also, falling agricultural price is connected with lower rents and lower land values.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.97-103
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• 1987

Skip-Lot sampling plan is formulated in terms of renewal process. This approach facilitates studying the average outgoing quality in a short production run of length t, AOQ (t). By numerical studies it is found that the long-run average outgoing quality (AOQ) greatly overestimates AOQ (t) for short runs.

• Environmental Engineering Research
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• v.22 no.1
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• pp.40-54
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• 2017

According to FAO, "agricultural sectors are particularly exposed to the effects of climate change and increases climate variability". As a result, the study makes an attempt to answer the question: Is there a causal effect between agricultural production and carbon dioxide emissions in Ghana? By employing a time series data spanning from 1960 to 2015 using the Autoregressive Distributed Lag method. There was evidence of a long-run equilibrium relationship running from copra production, corn production, green coffee production, milled rice production, millet production, palm kernel production and sorghum production to carbon dioxide emissions. The short-run equilibrium relationship shows that, a 1% increase in copra and green coffee production will increase carbon dioxide emissions by 0.22% and 0.03%, a 1% increase in millet and sorghum production will decrease carbon dioxide emissions by 0.13% and 0.11% in the short-run while a 31% of future fluctuations in carbon dioxide emissions are due to shocks in corn production. There was bidirectional causality between milled rice production and carbon dioxide emissions, millet production and carbon dioxide emissions and, sorghum production and carbon dioxide emissions; and a unidirectional causality running from corn production to carbon dioxide emissions and carbon dioxide emissions to palm kernel production.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.1
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• pp.89-103
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• 1989

In this paper the approximate average outgoing quality and properties of a class of continuous sampling plans in a short production run are investigated when the quality of successive units follows a two-state time-homogeneous Markov chain. The results of previous studies can be obtained as special cases. It is observed that the long-run average outgoing quality limit values under the statistical control differ significantly as compared to the case of short production runs in a Markov-dependent production process.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.215-220
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• 2004

Production management confronted the environment of infinite competition should be prepared to abrupt variations of management environment and have the ability to be changed in short term. It has to be studied, the control method of products that correspond to multi-functionalization and reduced product life which is caused by high-quality and varied customers demands. As a process control method, we most be able not only to control varies characteristic in a control at once but also to detected special values quickly for high-quality. In this paper a control method referred above is presented.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.11-21
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• 2007

The PDCA (Plan, Do, Check and Act) cycle is often used in the field of quality management. Recently, business environments have become more competitive, and the due time of products has shortened. In a short production run process, to increase efficiency of management, the necessity for distinguishing the PDCA design that starts with PLAN and the CAPD design that starts with CHECK has been clarified. Starting from Duncan (1956), there have been a number of papers dealing with the economic design of control charts from the viewpoint of production run. Some authors (Gibra, 1971; Ladany and Bedi, 1976; etc.) have studied the economic design for finite-length runs; other authors (Crowder, 1992; Del Castillo and Montgomery, 1996; etc.) have studied the economic design for short runs. However, neither the PDCA nor the CAPD design of control charts has been considered. In this paper, both the PDCA and CAPD designs of the $\bar{\x}$ chart are defined based on Del Castillo and Montgomery's design (1996), and their mathematical formulations are shown. Then from an economic viewpoint, the optimal values of the sample size per each sampling, control limits width, and the sampling interval of the two designs are studied. Finally, by numerically analyzing the relations between the key parameters and the total expected cost per unit time, the comparisons between the two designs are considered in detail.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.7-17
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• 2018

This paper examines short-run and long-run dynamic relationships between selected macroeconomic variables and stock prices in the Korea Stock Exchange. The data is restricted to the period for which monthly data are available from January 1986 to October 2016 (370 observations) retrieved from the Economic Statistics System database sponsored by the Bank of Korea. The study employs unit root test, cointegration test, vector error correction estimates, impulse response test, and structural break test. The results of the Johansen cointegration test indicate at least three cointegrating equations exist at the 0.05 level in the model, confirming that there is a long-run equilibrium relationship between stock prices and macroeconomic variables in Korea. The results of vector error correction model (VECM) estimates indicate that money supply and short-term interest rate are not related to stock prices in the short-run. However, exchange rate is positively related to stock prices while the industrial production index and inflation are negatively related to stock prices in the short-run. Furthermore, the VECM estimates indicate that the external shock, such as regional and global financial crisis shocks, neither affects changes in the endogenous variables nor causes instability in the cointegrating vector. This study finds that the endogenous variables are determined by their own dynamics in the model.