산갈치(Regalecus russellii)는 대부분을 심해에서 보내며 가끔 연안에 나타나는데, 그 이유는 명확히 알려져 있지 않다. 우리나라 에서 산갈치는 주로 동해 연안을 따라 출현하는데, 특히 자망 등 어구에 의해 포획되는 경우와 연안에 좌초되어 출몰하는 경우가 높고 그 빈도는 극히 낮다. 또한 발견된다고, 하더라도 산갈치와 형태학적으로 유사한 투라치(Trachipterus ishikawae)로 판별되는 경우가 높다. 산갈 치의 표본을 구하여 분석하는 것은 제한적이기 때문에, 이러한 이유로 우리나라 연안에 출현하는 산갈치의 생태학적 특징에 대해 거의 알려져 있지 않다. 본 연구는 2023년 3월 14일 강원도 앞바다에서 어획된 산갈치의 해부학적 특징을 관찰하였고, 해양 부이 자료를 이용 한 수온 분석을 진행하였다. 분석 결과 산갈치는 수컷이었고, 전장은 320 cm, 전중은 27.52 kg, 체고는 26.62 cm, 생식소 중량은 619.45 g, 간 중량은 218.71 g이었다. 산갈치의 위는 난바다 곤쟁이류로 가득 차 있었고, 산갈치가 어획되기 약 일주일 전부터 15~30 m 수심에서 강한 수온 변동이 있었으며, 저층 수온은 10℃ 미만이었다. 본 기술보고는 우리나라 동해 연안에서 나타날 수 있는 산갈치의 생태학적 특징을 이해하기 위한 기초 자료로 활용될 수 있을 것이다.

The dynamic capabilities of sensing market signals, creating new opportunities and reconfiguring resources and capabilities to new opportunities in a rapidly changing economic environment determines the competitiveness of the enterprise to create added value and survival. This study conceptualized a two-stage performance measurement framework based on the casual model of resource (input)-process-performance (output). We have developed a ‘Process capability index’ that reflect the dynamic capabilities factors as a key intermediary product linking resource inputs and performance outputs in enterprise performance measurement. The process capability index consists of four elements : manpower (level of human resource), operation productivity, structure and risk management. The DEA (Data Envelopment Analysis) model was applied to the developed performance indicators to analyze the branch office performance of a telecom company. Process capability efficiency (stage 1) uses resource inputs to reach a certain level of process capabilities. In performance result efficiency (stage 2), the process capabilities are used to generate sales revenues and subscribers. The two-stage DEA model derives intermediate output values that optimize the individual stages simultaneously. Some branch offices in the telecom company have focused on process capability efficiency or some other branch offices focused on performance result efficiency. Positioning map using two-stage efficiency decomposition and benchmarking can help identify the sources of inefficiencies and visualize strategic directions for performance optimization. Applications of two-stage DEA in conjunction with the case study that are meaningfully used in performance measurement areas have been scarce. In particular, this paper has the contribution to present a new performance measurement model considering the organization theory, the dynamic capabilities.

Improving efficiency of the telecommunication is crucial to the development and growth of Korean economy. Recently, it has become important with the huge development of information technology and its greater potential for extensive impact on the rest of the economy. Hence, it is useful to determine the factors that help enhance efficiency in telecommunication and consider them in improving the evaluation model. This study applies DEA (data envelopment analysis) to evaluate the relative efficiency of 51 branches of a Korean telecommunication company. Using the super-efficiency approach, we tested outliers which may affect the results and ranked the efficient branches. A method of deriving key variables applied to business operation is proposed to identify the key performance indicators for evaluation that takes environmental (non-discretionary) factors into account. We used the extended CCR model proposed by Banker and Morey to investigate the influence of non-discretionary factor. The information provided by the model (slacks, weights) and the sensitivity analysis shows that the most important indicator that affects the branch performance is operating cost. The results of sensitivity analysis show that average efficient score decreases from 0.972 (base case) to 0.863 for CASE2-COST. The average score of the data proves the priority of operating cost over other indicators. The effect of environmental (non-discretionary) variable was found to be significant. The population effect was positive and improved overall efficiency by 0.91% on average. Non-discretionary factor plays a meaningful role explaining the performance of branches. The performance optimization report can help a manager of an inefficient branch to develop branch strategies. Managers can identify the top-performing units, study best practices and adopt the strategy to the organization.