Earticle

본 연구는 전북지역의 해상풍력산업이 지역산업 활동에 미치는 영향을 파악하고자 사 회연결망 분석을 하였다. 이를 통해 현재 지역경제에서 해상풍력산업의 위상과 다른 산 업들과의 연계 관계를 파악하였다. 사회연결망 분석을 위해 먼저 2015년 지역산업연관표 를 활용하여 소분류 기준으로 해상풍력산업을 재정의하였다. 또한 투입계수, 생산유발계 수, 부가가치유발계수, 그리고 산업간 연쇄효과를 도출하였다. 다음으로 지역산업연관표 를 응용하여 단위구조 행렬을 도출하고 사회연결망 네트워크를 분석하였다. 그 결과로 사회연결망 네트워크 시각화를 통해 전북의 해상풍력산업은 다른 지역산업들과 전체적 으로 유기적인 네트워크를 가지는 것으로 나타났다. 또한, 연결정도 중심성, 근접중심성, 매개중심성의 분석을 통해 해상풍력산업은 생산 활동성이 높아 지역경제를 활성화하고 영향력을 줄 수 있는 산업의 역할을 하는 것으로 분석되었다.

This study was conducted to identify the impact of the offshore wind industry on regional industrial activities in Jeonbuk region using the social network analysis. By this, the current position of the offshore wind industry in the local economy and the relationship with other industries were identified. For the social network analysis, the offshore wind industry was redefined based on small classifications using the 2015 input-output table. Then input coefficient, production inducement coefficient, added value inducement coefficient, and inter-industry chain effects were derived. Next, the social network network was analyzed by deriving the unit structure matrix by applying the input-output table. As a result, the visualization of the social network network was found that Jeonbuk's offshore wind industry has an overall organic network with other local industries in the region. In addition, through the analysis of degree centrality, proximity centrality, and mediation centrality, it was analyzed that the offshore wind industry plays a role in the region and the industry can vitalize and influence the local economy due to its high production activity.

본 연구는 산업연관분석을 활용하여 창고 및 운송 관련 서비스업의 관점에서 전체 산업들과의 상호관계구조 및 경제 전반에 미치는 영향효과와 함께 단위구조행렬과 사회연결망 분석을 접목하여 연결성(중앙성) 지수, 방향성, 시각화 분석을 시행함으로써 창고 및 운송 관련 서비스업의 위치와 현황 및 전체 산업들과의관계구조를 연구하는 것이다. 한국은행에서 발간한 산업연관분석 해설 및 2015년 산업연관표를 활용하였으며, 역행렬 함수를 활용하여 투입계수, 생산유발계수, 부가가치유발계수, 산업간 연쇄효과를 창고 및 운송 관련서비스업의 관점에서 분석을 시행하고 결과를 제시하였다. 또한 산업연관표를 활용한 단위구조행렬함수를 작성하였으며, Ucinet6 및 NetDraw를 활용하여 산업들 간의연결정도로써 사회연결망 연결성(중앙성) 지수 및 시각화 분석을 시행하였다. 이러한 연구를 통해 창고 및운송 관련 서비스업에 종사하고 있는 경영 실무자들이 자신이 일하고 있는 산업과 다른 산업 부문들과 관련된부분을 명확하게 이해할 수 있도록 하였다. 즉 상호 간에 영향력을 많이 주고받는 산업들과 전략적 제휴 관계를 강화할 필요성이 있을 경우 이러한 산업들 간의 연결성의 수준을 사회연결망 연결성(중앙성) 지수와 사회연결망 시각화 분석을 통하여 논리적이고 명확하게 제시하였다.

This study utilizes industry linkage analysis to combine the unit structure matrix and social network analysis with the interrelationship structure with all industries from the perspective of warehousing and transportation-related service industry and the effect on the overall economy to determine the connectivity (centrality) index. The purpose of this study is to study the location and current status of warehouse and transportation-related service industries and the structure of relationships with all industries by performing analysis on , direction, and visualization. The industry linkage analysis commentary published by the Bank of Korea and the industry linkage table in 2015 were used, and an inverse matrix function was used to analyze the input coefficient, production inducement coefficient, value added inducement coefficient, and inter-industry chain effect from the perspective of warehousing and transportation-related service industries. and presented the results. In addition, a unit structure matrix function using the industry association table was created, and using Ucinet6 and NetDraw, the social network connectivity (centrality) index and social network visualization analysis were performed as the degree of connection between industries. Through this study, management practitioners who are engaged in warehousing and transportation-related services can clearly understand the industry in which they are working and the parts related to other industrial sectors. In other words, if there is a need to strengthen strategic alliances with industries that have a lot of mutual influence, the level of connectivity between these industries was logically and clearly presented through social network connectivity (centrality) index and social network visualization analysis.

This study utilizes industry linkage analysis to analyze not only the network connectivity index, but also the direction and visualization The purpose of this study is to study the location and current status of the land transportation industry and the structure of relationships with all industries through network analysis. The industry linkage table was revised and prepared using the industry linkage analysis commentary published by the Bank of Korea and the industry linkage table in 2015, and various inducement coefficients were analyzed using an inverse matrix function. In addition, a unit structure matrix function was created, and using this, Ucinet6 and NetDraw were used to analyze the social network connectivity (centrality) index and network visualization. The implications of the study are summarized as follows. First, a study was conducted on the relationship structure between the land transportation industry and all industries, so that logistics-related management practitioners could clearly understand the related parts between the industry they were working in and other industry sectors. Second, the input coefficient, production inducement coefficient, value-added inducement coefficient, and inter-industry chain effect were analyzed in the land transportation sector, and the results were synthesized. Third, the connectivity (centrality) index for the network structure of social networks between all industries and logistics industries was analyzed using Ucinet6 and NetDraw, and it appears to have network connections with 30 industries.