IT 영업 역량 모델과 측정도구를 활용하면 IT 영업 인력의 수행 향상과 다양한 방식의 형식, 무형식학 습을 제공할 수 있다. 하지만 국내 IT 영업 인력의 역량에 대한 모델과 이를 측정할 수 있는 도구 개발 연구는 미진하다. 이에 따라 IT 영업 인력에게 필요한 영업 역량을 탐색하여 역량 모델을 구성하였다. 또한 구성된 IT 영업 역량 모델을 통해 국내 영업 현장에 적합하고 신뢰도와 타당도가 검증된 IT 영업 역량 측정도구를 개발하였다. 이를 위해 역량 모델의 개발, 측정도구의 예비문항 개발, 측정도구의 타당화의 세 단계를 거쳤다. 연구 결과 다음과 같은 결론을 내릴 수 있었다. 첫째, 국내 IT 영업 환경에 맞는 IT 영업 역량 모델은 성취와 행동 역량군, 대인 서비스 역량군, 관계 역량군, 지적 능력 활용 역량군, 자기 통제감 역량군, 영업 활동의 6개 역량군과 14개 역량으로 구성된다. 둘째, IT 영업 현장 전문가와 교육 전문가로 구성된 전문가 협의회를 각각 실시하여 예비문항을 개발하였고, 예비 IT 영업 역량 측정도구의 타당도를 확보하였다. 셋째, 검증된 예비문항을 사용하여 IT 영업 현장 인력 580명을 대상으로 본조사를 실시하여 신뢰도 및 교차타당도 검증으로 최종 도구를 확정하였다. 최종 확정된 IT 영업 역량 측정도구는 6개 역량군, 14개 역량, 78문항이다.

This study aims to examine factors affecting the seafood processing business of primary cooperatives. For this purpose, I divided primary cooperatives that participate to seafood processing business into three group by sales scale. And then analyzed survey results for the four items that might be affecting the seafood processing business, type of seafood processing methods, HACCP certification status, distribution channels, processing difficulties during project implementation, etc. The result offers four implications. First, It is desirable to reduce the burden of the initial investment by leveraging the consignment process at the initial entry to seafood processing business. Second, HACCP certification is essential factor in order to promote seafood processing business as a long-term economic business. Third, To the steady growth of the seafood processing business, it is important to secure fixed large customers, as well as a individual customer. Fourth, For the continued growth of the seafood processing business it should be approached differently by way of sales, when the National Federation of Fisheries Cooperatives support to primary cooperatives.

Purpose – This paper aims to examine several time series models to predict sales of department stores and discount store markets in South Korea, while other previous trial has performed sales of convenience stores and supermarkets. In addition, optimal predicted values on the underlying model can be got and be applied to distribution industry. Research design, data, and methodology - Two retailing types, under investigation, are homogeneous and comparable in size based on 86 realizations sampled from January 2010 to February in 2017. To accomplish the purpose of this research, both ARIMA model and exponential smoothing methods are, simultaneously, utilized. Furthermore, model-fit measures may be exploited as important tools of the optimal model-building. Results - By applying Holt-Winters’ additive seasonality method to sales of two large-scale retailing types, persisting increasing trend and fluctuation around the constant level with seasonal pattern, respectively, will be predicted from May in 2017 to February in 2018. Conclusions - Considering 2017-2018 forecasts for sales of two large-scale retailing types, it is important to predict future sales magnitude and to produce the useful information for reforming financial conditions and related policies, so that the impacts of any marketing or management scheme can be compared against the do-nothing scenario.