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6. 결론
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주택들은 실제 사례이다. 따라서 리모델링 공동주택과 비교 공동주택 사례들의 가격정 보와 공동주택 속성들은 그 자체로서 매우 유용한 지표이고, 경제적 성과를 판별하는 데 있어 객관적인 자료로 활용 가능하다.
2) 리모델링 공동주택의 가격변화정보는 3점 시점(i.e., Before remodeling, After remodeling, Present)을 기준으로 조사되었으며, 변화 상황 자체만으로도 리모델링의 성과를 확인할 수 있다. 하지만 객관적인 분석을 위해 인근 기존 공동주택과의 상대적 비율을 활용하여 변화 양상을 나타냈고, 이를 패턴으로 만들었다. 리모델링 가격변화패 턴은 Ⅰ, Ⅱ, Ⅲ이 도출되었으며, 이 중 경제적 성과가 나타난 패턴은 Patter Ⅰ,Ⅱ이다.
가격변화패턴으로 누구나 쉽게 리모델링의 경제적 성과를 파악 할 수 있도록 하였다.
3) 이렇게 도출된 패턴을 인공신경망 분석을 이용하여 예측 모델을 구축하였다. 예 측 모델은 리모델링 사업의 기획단계에서 패턴 예측을 통해 리모델링 사업의 의사결정 을 쉽게 할 수 있도록 지원하는 역할을 하며, 총 100개의 사례 중, 패턴 Ⅰ은 30개, 패 턴 Ⅱ는 49개, 패턴 Ⅲ은 21개의 사례가 조사 되었고, 93.8%의 예측 정확도를 확인할 수 있었다.
4) 리모델링 공동주택 가격변화패턴 예측 인공신경망 모델을 의사결정나무 분석으로 보완하여, 누구나 쉽게 가격변화패턴에 영향을 미치는 요인을 파악할 수 있으며, 인공 신경망 예측 모델을 뒷받침할 객관적인 근거로서 활용하였다. 의사결정나무의 예측 정 확도 또한 93.8%로 도출되었다.
5) 리모델링 공동주택 가격변화패턴에 가장 큰 영향을 미치는 요인은 경과년수로 도 출되었으며, 단위세대면적 또한 매우 큰 영향을 미치는 것으로 나타났다. 또한 Pattern
Ⅰ, Ⅱ는 경과년수, 단위세대면적, 층수에 의해 공통적으로 분류되고, Pattern Ⅰ은 여 기에다 병원과의 거리, 근린공원과의 거리, 총 세대수의 요인들이 더해져 분류가 일어 나고, Pattern Ⅱ의 경우, 지하철역까지의 거리, 버스정류장까지의 거리 요인이 공통 요 인에 더해져서 분류되었다.
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6.2 연구의 한계 및 향후 연구방향
본 연구에서 제안한 리모델링 공동주택 가격변화패턴 예측에 관한 모델에는 다음과 같은 보완점이 필요하다. 3점 시점 추정이라는 시간의 개념을 도입 했지만, 시점에 가 까운 개념으로, 시간의 흐름이라는 연속적인 상황의 분석은 미흡했다. 시점을 좀 더 세 분화하게 된다면, 리모델링 공동주택의 가격변화를 더 다양한 패턴으로 만들 수 있고, 그에 따른 리모델링 사업의 성과 또한 다양하게 도출될 것이다.
이러한 한계점에도 불구하고 리모델링 사업의 경제적 성과를 판별할 구체적이고 가 시적인 정보가 없었던 상황에서 실제 리모델링 사례들을 활용하여, 리모델링 사업 기 획단계에서 의사결정을 지원할 수 있는 예측 모델을 만들었다는 점에서 매우 유용한 연구라고 사료된다. 또한 예측 모델과 더불어 공동주택 속성과 가격패턴의 관계 분석 까지 이루어 공동주택 소유주들로 하여금 쉽게 리모델링 사업의 의사결정을 내릴 수 있도록 도움을 주었다는 점도 유용하다고 사료된다. 앞으로 위에서 언급했던 부족한 점들을 보완하고, 리모델링 사례가 더욱 많아져 더 다양한 패턴과 데이터를 기반으로 한 차기 연구가 진행되기를 바라며, 공동주택 소유주들에게 불확실한 사업으로 인식되 고 있던 리모델링 사업을, 본 연구를 통해 공동주택 소유주들의 의사결정을 도와 리모 델링 시장의 활성화에 기여할 수 있었으면 한다.
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