이 연구는 경남의 4대전략산업 중 지식기반기계산업 분야에 근무하고 있는 종사자 수를 2009년부터 2015년까지 예측하였다. 일변량 시계열분석(ARIMA모형과 지수평활법)을 통해 가장 적절한 Holt선형추세 모형을 선택하여 종사자 수를 전망 하였다. 지식기반기계산업의 종사자 수는 매년 2%범위 내에서 증가할 것으로 관측되었다. 1971년부터 2008년까지 38개의 data를 이용하여 종사자 수를 예측하였으며, 외환위기 전후를 제외하고 모든 기간 동안 지식기반기계산업에 근무하는 종사자 수는 꾸준한 증가세를 보였고, 2015년에는 289,175명이 될 것으로 예측되었다. 지식기반기계산업에 종사하는 수요자 부분만 예측한 것이 본 논문의 한계점이며, 지역산업의 여건과 특성을 고려하여 향후, 인력공급에 대한 연구도 병행되어야 할 것으로 본다.

This study forecasted an employee number working at to machine industry-based the knowledge that was a part of 4 match strategic industry of Gyeongnam until 2015 from 2010. You selected a trend model linear the most suitable Holt, and a forecast did an employee number through univariate time series analysis(an ARIMA model and Exponential smoothing method. The employee shroud rate of increase is annual 2%. You increase in the stomachs, and you were forecasted, and you increase, and employee number of machine industry-based knowledge was observed. You were forecasted as you used 38 data so that you forecasted an employee number, and an employee number of machine industry-based knowledge looked so as to be steady, and 289,175 people become in 2015. A manpower demand forecast of machine industry-based knowledge is important, but a forecast regarding manpower supply shall be preceded systematically together, and it is a study assignment.

This study forecasted an employee number working at to machine industry-based the knowledge that was a part of 4 match strategic industry of Gyeongnam until 2015 from 2010. You selected a trend model linear the most suitable Holt, and a forecast did an employee number through univariate time series analysis(an ARIMA model and Exponential smoothing method. The employee shroud rate of increase is annual 2%. You increase in the stomachs, and you were forecasted, and you increase, and employee number of machine industry-based knowledge was observed. You were forecasted as you used 38 data so that you forecasted an employee number, and an employee number of machine industry-based knowledge looked so as to be steady, and 289,175 people become in 2015. A manpower demand forecast of machine industry-based knowledge is important, but a forecast regarding manpower supply shall be preceded systematically together, and it is a study assignment.

Knowledge-based industry, ARIMA, Exponential Smoothing Method(ESM), Manpower demand forecast