7 research outputs found
μ¬ν λ€νΈμν¬ μ΄λ‘ μ κ·Όκ±°ν μΆ©λ¨ μλμ°¨ λΆνμ°μ μ μ§μ λ€νΈμν¬ λΆμ -λν 곡λ μ°κ΅¬κ°λ° νλ‘μ νΈλ₯Ό μ€μ¬μΌλ‘
1. μ°κ΅¬ λ°°κ²½ λ° λͺ©μ
μ§μ λ°μ μ μ±
μ μλ‘μ΄ ν¨λ¬λ€μμΌλ‘ λ€νΈμν¬κ° λ°°νλλ ννΈ, μ±μ₯μ κ·ΌμμΌλ‘ μ§μμ μν μ΄ κ°μ‘°λλ κ°μ΄λ°, κ΅λ΄β€μΈμμλ μ§μ λ€νΈμν¬λ₯Ό κ°ννκΈ° μν λ
Έλ ₯λ€μ΄ κ²½μ£Όλκ³ μλ€. κ·Έλ¬λ κ·Έκ°μ λ
Έλ ₯μ λμ²΄λ‘ κ±°λ²λμ€ μ²΄κ³λ₯Ό ꡬμΆνκ±°λ μλ‘μ΄ λ¬Όλ¦¬μ μμ€μ μ μΉνλ λ°μ μ£Όμμ μ λμ΄ μκ³ , μ§μ λ€νΈμν¬λ₯Ό μ€μ²΄μ μΌλ‘ λ€λ£¨λ €λ λ
Έλ ₯μ λ―Έμ½ν μΈ‘λ©΄μ΄ μμλ€. μΆ©λ¨μ μ μ°μ
μΈ μλμ°¨ λΆνμ°μ
λν μ§μ λ€νΈμν¬μ λν μ½λλ€μ΄ν
μ΄ κ΅¬μ²΄μ μ΄λΌκ³ 보기λ μ΄λ €μ΄ μν©μ΄λ€
- μ΄ν μλ΅μ 1 μ₯ μ λ‘
1. μ°κ΅¬λ°°κ²½ 1
(1) μ§μλ°μ μ μ±
μ μλ‘μ΄ ν¨λ¬λ€μμΌλ‘μμ λ€νΈμν¬ 1
(2) μ±μ₯μ κ·ΌμμΌλ‘μμ μ§μ 1
(3) μΆ©λ¨μ μ μ±μ₯ : μλμ°¨ λΆνμ°μ
2
2. λ¬Έμ μ κΈ° λ° μ°κ΅¬ λͺ©μ 3
(1) λ¬Έμ μ κΈ° 3
(2) μ°κ΅¬ λͺ©μ 4
3. μ°κ΅¬λ°©λ²λ‘ 4
(1) λ€νΈμν¬ μ°κ΅¬μ μΌλ°μ λν₯κ³Ό μ¬ν λ€νΈμν¬ λΆμ 4
(2) μ νμ°κ΅¬μμ λ°©λ²λ‘ μ μ°¨λ³μ± 5
4. μ°κ΅¬μ νλ¦ 7
μ 2μ₯ λ€νΈμν¬ μ΄λ‘ μ λν λ¬Έν μ°κ΅¬
1. λ€νΈμν¬ ν¨λ¬λ€μμ λμΈκ³Ό μ΄λ‘ μ²΄κ³ 8
(1) λ€νΈμν¬ ν¨λ¬λ€μμ λμΈ 8
(2) λ€μ€μ λ€νΈμν¬ λΆλ₯ 체κ³μ κ·Όλ³Έκ°λ
: μ¬ν λ€νΈμν¬ μ΄λ‘ 11
(3) μ¬ν λ€νΈμν¬ μ΄λ‘ μ νΉμ± 13
2. λ€νΈμν¬ μ΄λ‘ μ 곡κ°μ κ³λ³΄ 15
3. λ€νΈμν¬ μ°κ΅¬μ λν₯ λ° κ΄λ ¨ μ°κ΅¬ 18
(1) λ€νΈμν¬ μ°κ΅¬μ λν₯ 18
(2) κ΄λ ¨ μ°κ΅¬ : μ¬ν λ€νΈμν¬ λΆμμ μ€μ¬μΌλ‘ 19
μ 3μ₯ μ°κ΅¬μ€κ³
1. λ€νΈμν¬ μλ£μ μμ κ³Ό λ
Όλ¦¬ 23
(1) μμ 1 : μ΄λ€ λ€νΈμν¬ κ΄κ³λ₯Ό λμμΌλ‘ ν κ²μΈκ°? 23
(2) μμ 2 : μ΄λ€ μ°κ²° κ°λλ₯Ό κ΄κ³μ λ¨μλ‘ μ€μ ν κ²μΈκ°? 24
(3) λ
Όλ¦¬ 1 : μ§μμ λ°°νλ μ§μμμ° κ±°μ μΌλ‘μμ λν 24
(4) λ
Όλ¦¬ 2 : κ°ν μ°κ²°μ μν νμ ν¨κ³Ό 25
2. μμλ£μ μ±κ²© λ° κ°κ³΅ 26
(1) μμλ£μ μ±κ²© 26
(2) μλ£μ κ°κ³΅ 26
3. νμ λ°©λ² 30
(1) λΆμ μ§νμ μν νμ 30
(2) μκ°νμ μν νμ 35
μ 4μ₯ μΆ©λ¨ μλμ°¨ λΆνμ°μ
μ§μ λ€νΈμν¬μ νΉμ±
1. λ€νΈμν¬μ ꡬ쑰μ ·곡κ°μ λΆμ 37
(1) λ€νΈμν¬μ νν : μ’μμΈμ λ€νΈμν¬ 37
(2) λ€νΈμν¬ μ°Έμ¬κΈ°κ΄μ κ³΅κ° λΆν¬ 40
(3) λ€νΈμν¬ νμκΈ°κ΄μ λμΆ λ° κ³΅κ°μ νΉμ± 45
2. λ€νΈμν¬μ μκ³μ΄μ λΆμ 53
(1) λ€νΈμν¬μ ꡬ쑰μ μ°κ³ νν λ³ν, 2005λ
-2007λ
53
(2) λ€νΈμν¬μ 곡κ°μ μ°κ³ νν λ³ν, 2005λ
-2007λ
57
3. λ€νΈμν¬μ μ§ν κΈ°μ λΆμ 60
(1) λ€νΈμν¬μ μ§ν μ ν 60
(2) μΆ©λ¨ μλμ°¨ λΆνμ°μ
μ§μ λ€νΈμν¬μ μ§ν κΈ°μ 62
μ 5μ₯ μ°κ΅¬κ²°κ³Όμ μμ½ λ° μ μ±
μ μΈ
1. μ°κ΅¬κ²°κ³Όμ μμ½ 66
2. μ μ±
μ μΈ 68
μ°Έκ³ λ¬Έν 70
λΆλ‘ 1 : μΆ©λ¨ μλμ°¨ λΆνμ°μ
μ§μ λ€νΈμν¬μ μ°κ²°μ€μμ± 77
λΆλ‘ 2 : μΆ©λ¨ μλμ°¨ λΆνμ°μ
μ§μ λ€νΈμν¬μ μ¬μ΄μ€μμ± 81
λΆλ‘ 3 : κ΅λ΄ μλμ°¨ λΆνμ°μ
μμ 100κ° κΈ°μ
8
Relocation of Public Organizations and Construction of Innovative Cities : Urban Dynamics Analyses
μ΄ μ°κ΅¬μμλ μμ€ν
μ μ¬κ³ λ₯Ό ν΅ν΄ νμ λμ 건μ€νλ‘μ νΈκ° λλλ λ
Όλ¦¬λΆν° μ¬ κ³ μ°°νλ©°, νμ λμκ° κ±΄μ€λμ΄ λμ κΈ°λ₯μ μ±κ³΅μ μΌλ‘ μ μ°©μν€κ±°λ μλλ©΄ μ€ν¨ν μλ μλ λμλνμ±μ μμΈκ³Ό κ²°κ³Όλ₯Ό μΈκ³Όμνμ ꡬ쑰λ₯Ό ν΅ν΄ κ·λͺ
ν΄ λ΄μΌλ‘μ¨, νμ λμμ 건μ€κ³Ό κ΄λ¦¬γμ΄μκ³Ό μ°κ΄λ λ€μ°¨μμ μΈ μ΄μλ€μ λν μ μ±
λ
Όλ¦¬λ₯Ό κ°λ°νλ λ°μ κΈ°μ¬νκ³ μ νλ€.
μ΄λ¬ν μ°κ΅¬λͺ©μ μ λ¬μ±νκΈ° μνμ¬ μ΄ μ°κ΅¬μμλ ꡬ체μ μΌλ‘ μμ€ν
λ€μ΄λ΄λ―Ήμ€ λ° μ΄λ² λ€μ΄λ΄λ―Ήμ€ λ°©λ²λ‘ μμ κ°μ‘°νκ³ μλ μμ€ν
μ μ¬κ³ μ μ΄λ₯Ό λΆμγλꡬνν μΈκ³Όμ§λ(causal map) κΈ°λ²μ μ΄μ©νμ¬ κ³΅κ³΅κΈ°κ΄μ μ§λ°©μ΄μ κ³νμ κ΄ν μ°¬λ°μλ‘ μ μ’
ν©μ μΌλ‘ μ‘°λ§νλ€. λλΆμ΄, μ μ¬μ¬λ‘μμ λνλ λνμ νΉμ±μ κ²ν νλ©°, νμ λμμ 건μ€μ λ°λ₯Έ λμ κΈ°λ₯μ μ°©μ κ΄ν λνμ±μ νΌλλ°± ꡬ쑰λ 체κ³μ μΌλ‘ λΆμνλ€.
νμ λμμ 건μ€κ³Ό κ΄λ ¨νμ¬, νμ λμ μ체λΏλ§ μλλΌ μλκΆ, λΉμλκΆ, μ£Όλ³μ§μμ λμλνμ±μλ λ€μν μμΈλ€μ μνΈμμ©μ΄ μ‘΄μ¬νλ©°, μ΄λ¬ν μνΈμμ© μμΈλ€μ΄ μΌλ¨μ μνμ μΈκ³Όκ΄κ³ ꡬ쑰λ₯Ό νμ±νκ³ , μλ‘ μν₯μ μ£Όκ³ λ°λλ€λ μ μ μ΄ μ°κ΅¬λ νμΈνμλ€. νμ λμμ κ΄ν μνμ μΈκ³Όκ΄κ³ νΌλλ°± ꡬ쑰μμ μ΄λλλ λ€μν λνμ λ©μΉ΄λμ¦μ μ λͺ¨λ₯Ό νμ
νμ§ μμ νμ λμ 건μ€μ κ΄ν μΌλ°©μ μΈ λ
Όμλ μ μ±
μ μ립 λ° μ§νμ κ°λΉνκΈ° μ΄λ €μ΄ μ¬νμ λΉμ©μ λ°μμν€κ±°λ μΉμ νκΈ° μ΄λ €μ΄ νμ μ¦μ λ³μ μλ μλ λ°, μ΄λ¬ν μ νμ μ°κ΅¬λ₯Ό κ±°λν¨μΌλ‘μ¨ μ¬νμ λΉμ©μ μ΅μννκ±°λ λΆμμ©μ κ·Ήμνν μ μλ μΌλ¨μ ꡬ쑰λ₯Ό λͺ
ννκ² νμ
ν μ μλλ‘ μ‘°μ²ν΄μΌ νλ€.
As part of the grand project for balanced territorial development, Korean government has been preparing tentative plans to build a dozen of innovative cities in the Non-Capital Region, all of which would accommodate the relocated Capital-based public organizations. Without due policy designs and application processes, however, the government initiatives have also caused d a series of supporting and opposing arguments. In sum, most of the current discussions are not fully adequate in explaining why the innovative cities are necessary and how they could benefit more balanced regional development. As an effort to address these issues, analytical logics for the proposed innovative cities are developed using urban dynamics models. To provide policy leverages, various development scenarios are simulated focusing on the expected growth and maturity of the innovative cities. The research findings indicate that the success of the proposed cities depends on the dynamic movement of the key variables, both from those cities and the Capital Region. They also point out that the Korean government may have to endure a huge amount of social cost or unwanted byproducts without due attention to the dynamic mechanisms embedded in the development process. Finally, it is concluded that the urban dynamics-oriented approach towards the innovative cities could assist the major stake-holders in developing robust and responsive policy initiatives given the current uncertainties
Boost, Control, or Both of Housing Market: Key Issues in 831 Housing Policies
Over several decades, Korean government has overwhelmed private sectors in dealing with housing issues within its jurisdiction. Especially, the current Roh government has repeatedly stressed the fact that housing per se has been degenerated into major means towards accumulation of wealth and various social problems have arisen from the skyrocketing housing prices. In order to cope with housing issues in a broader perspective, the government did not hesitate to announce Comprehensive Real Estate Programs on August 31, 2005. In Korea, the so-called 831 Countermeasures has brought unprecedented arguments both for and against, most of whom still seem to stick to anecdotal or self-centered judgment ahead of objective criteria.
In an integrated point of view, applying the traditional methodology of system dynamics (SD), the paper aims at proposing basic Korean housing dynamics models. It focuses on divulging major Causal Loop Diagrams (CLD) in Korean housing sector. Secondly, it observes how Korean housing market responds to a series of positive and negative impacts originated from the 8-31 Countermeasures. Between environmental and price factors, as the former exerts stronger impact on the positive loops, the study tries to develop policy guidelines hinged on an appropriate management of dynamic housing cycles, not to mention the price transfer into the neighboring areas. Thirdly, derived from simulation works, it proposes policy alternatives which would contribute to strengthening virtuous feedbacks and/or weakening vicious ones. Among them, the essential policy measure is given to how to minimize the governments direct involvement and how to boost housing markets role in deciding housing price. In the same vein, as the speculative or imputed demands always exist, policy alternative(s) based on housing attractiveness reflecting regional variation and price disparity should be given due attention