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The Effect of Employee Education and Information Technology on Performance of Construction Companies - Empirical Analysis Using Financial Data -

교육훈련 및 운영정보화가 건설기업의 경영성과에 미치는 영향 - 재무자료를 이용한 실증분석 -

  • Park, Hong-Jo (College of Economics & Business, Daegu University)
  • Received : 2018.08.29
  • Accepted : 2018.10.22
  • Published : 2019.04.20

Abstract

This study empirically verified whether or not employee education and information technology have impact on the enhancement of financial performance to Korean construction companies. As a result, the increasing of education & IT expenses turned out to be affected the improvement of sales performance. The influences of these increased expenses are effective at the only year just after expenditure. The positive effect of education & IT expenses increasing have an effect on operating profitability as well such as increasing of operating income. Additionally, the effect of education expenses are more positive in general construction & building construction than other subdivision of construction industry. The positive effect of IT expenses increasing in specialty construction industry overwhelm the other subdivisions. The results suggest that increased investment to the education & IT systems of Korean construction companies can lead improvement of sales and operating income.

인적자원에 대한 교육훈련과 정보화를 통한 기업 운영효율성에 대한 중요성이 부각됨에 따라 본 연구에서는 교육훈련 및 정보화와 같은 무형적 자원에 대한 지출이 학습과 성장 관점의 발전을 이끌어 내고 내부경영프로세스를 개선시켜 최종적으로 건설기업의 실질적인 경영성과 향상으로 이어지는 지에 대하여 재무제표 회계자료를 이용하여 실증분석 하였다. 분석 결과, 우리나라 건설기업의 경우 종업원 교육훈련과 운영시스템 정보화에 대한 투자는 실질적인 매출액 증가로 이어져 경영성과 향상에 기여하고 있음을 확인하였다. 또한 이러한 긍정적인 효과는 영업이익의 증가에도 일정부분 기여하고 있으며, 관련 비용 지출 시점과 건설업 세부 업종에 따라 그 효과가 다소 차이가 있다는 것도 함께 검증하였다. 본 연구는 교육훈련과 정보화에 대한 투자는 실질적인 재무적 성과 개선에 기여한다는 사실을 구체적으로 입증하였다는 점에서 의의를 가진다.

Keywords

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Figure 1. Valuation link between learning & growth and firm value in BSC

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Figure 2. Selection of industry type in KIS value DB

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Figure 3. Selection of firm name, financial information item, and term in KIS value DB

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Figure 4. Downloaded financial information

Table 1. Sample selection

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Table 2. Descriptive statistics of variables

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Table 3. Correlation matrix

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Table 4. The results of regression analysis (test year = t+1, basic model) ΔSALESt+1 = α 0 + β 1ΔEDUt + β 2ΔITt + β 3INDt + β 4SIZEt + β 5LEVt + ε t

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Table 5. The results of regression analysis (test year = t+1, independent variable extended model) △OIt+1 = α0 + β1△EDUt + β2△ITt + β3INDt + β4SIZEt + β5LEVt + εt

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Table 6. The results of regression analysis (sample divided by industry) △SALESt+1 = α0 + β1△EDUt + β2△ITt+ β3SIZE+ β4LEVt + εt

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