Spatial Preference Modelling for equitable infrastructure provision: an application of Sen’s Capability Approach

Wismadi, Arif; Zuidgeest, Mark; Brussel, M.J.G.; Maarseveen, M.F.A.M. van

doi:10.1007/s10109-013-0185-4

Cited by 20 publications

(11 citation statements)

References 40 publications

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“…5). In such cases, as no local spatial inequality is detected, SPM with a global or goal standardization (Wismadi et al 2013) might be applied.…”

Section: Discussionmentioning

confidence: 99%

“…To include spatial equity measures, Wismadi et al (2013) extended the standardization procedures into global, glocal and local spatial standardization. A global spatial standardization compares inequity with the reference of one value within the study region.…”

Section: Standardization With Inclusion Of Spatial Neighbourhoodcompamentioning

confidence: 99%

“…To simultaneously address social and spatial equity, Wismadi et al (2013) proposed a new type of preference modelling to allocate resources by explicitly taking neighbourhood inequity into account. Here, this spatial preference modelling (SPM) addresses equity not only among people but also across locations.…”

Section: Introductionmentioning

confidence: 99%

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Equitable distribution of growth for utilitarian and non-utilitarian infrastructure planning

Wismadi

Brussel

Zuidgeest

et al. 2015

Infrastruct. Complex

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To simultaneously address social equity and spatial equity, we develop a new type of preference modelling to distribute infrastructure resources that takes into account neighbourhood inequity effects. We compare this so-called spatial preference modelling (SPM) with the more common non-spatial preference modelling (NSPM) in terms of their compliance to two distinct perspectives of welfare theory, i.e., utilitarian and non-utilitarian welfare theory. With respect to utilitarian theory, we apply a total utility equality approach, whereas for non-utilitarian equality, we conduct a curve dominance analysis to evaluate the effect on (1) pro-poor policy, (2) inequity and (3) prosperity. A case study for the Special Region of Yogyakarta in Indonesia is used to show the difference in the effectiveness of SPM and NSPM in resolving resource allocation problems in the fields of transportation, electricity, telecommunication and freshwater infrastructures, four fields of infrastructure that differ in terms of their typology (point, linear, plane and space), initial level of development and spatial inequity. The results confirm that SPM complies better with both welfare theories than NSPM. Moreover, the curve dominance analysis reveals that infrastructure characteristics and the level of development contribute to model effectiveness. Hence, the findings can contribute to a more effective policy for equitable growth.

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“…5). In such cases, as no local spatial inequality is detected, SPM with a global or goal standardization (Wismadi et al 2013) might be applied.…”

Section: Discussionmentioning

confidence: 99%

Section: Standardization With Inclusion Of Spatial Neighbourhoodcompamentioning

confidence: 99%

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Equitable distribution of growth for utilitarian and non-utilitarian infrastructure planning

Wismadi

Brussel

Zuidgeest

et al. 2015

Infrastruct. Complex

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“…The benefits include but are not limited to the satisfaction of residents and the population served by the public service facility. By reference to the researches of relevant scholars (Wismadi et al, 2014;Han and Yu, 2012;Wang et al, 2012;Liu and Li, 2010;Han et al, 2014), this paper sets resource efficiency and maximum benefits as the overall objectives of the model, and sets the relevant sub-objectives and restrictions based on the overall objectives, as follows:…”

Section: Setting Of Model Objective Function and Restrictionsmentioning

confidence: 99%

Study on Optimal Spatial Configuration of Indemnificatory Community Public Service Facility Based on Modified MOGA

2017

Revista de la Facultad de Ingeniería

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Due to the diversity of its objectives, the optimal spatial configuration process of public service facilities in indemnificatory communities is a multi-objective decision issue. As for the study on optimization for spatial configuration of indemnificatory community public service facility, it is important to find an objective, reasonable and effective method that can address multi-objective decision-making challenges. The method is also the foundation for achieving the effect of indemnification and building a harmonious society. Based on the overall objectives of "resource efficiency" and "maximum benefits", this paper builds the modified Multi-objective Genetic Algorithm (MOGA) model for optimizing spatial configuration of indemnificatory community public service facility, conducts an empirical simulation based on the case of the New Jiangqiao City in Jiading District of Shanghai, with the purpose of introducing the optimal spatial configuration solution for public service facilities. Compared with the ordinary GA-based results, the optimal spatial configuration of public service facilities based on modified MOGA is more reasonable and compact. The model improves the configuration theory for public service facilities in indemnificatory communities, which is of substantial theoretical and practical significance for creating more scientific and reasonable configuration of public service facilities in indemnificatory communities.Keywords:indemnificatory community;public service facility; Multi-objective Genetic Algorithm (MOGA), spatial configuration optimization AIMS AND BACKGROUNDPublic service facility configuration is essentially a complicated multi-objective non-linear dynamic optimization decision-making issue. On the one hand, the configuration process must take into account the effects of various factors such as the location, accessibility and fairness of the public facilities as well as the interaction and interconnection with one another. On the other hand, during the multi-objective optimization for the configuration of public service facilities, the sub-objectives to be optimized simultaneously usually conflict with one another. The key to solving the optimization problem of spatial configuration of public service facilities lies in finding an objective and quantified balance solution (i.e. the Pareto optimal set) under the effects of multiple factors and during the multi-objective optimization.Current researches on the public service facility configuration mainly focus on the subjects of location, accessibility and fairness of facilities. For example, the study on location of public service facilities focuses mainly on their location optimization. Alcada-Almeida et al., (2009)designed a Gaussian diffusion model for optimal configuration of multi-objective spatial locationby using mixed integer and multi-objective planning. Teixeira and Antunes(2008) introduced a discrete rating configuration model for public service facility location and validated the effectiveness of the model through a scho...

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“…To simultaneously address social and spatial equity, Wismadi, Zuidgeest et al (2013) proposed a new type of preference modelling to allocate resources by explicitly taking neighbourhood inequity into account. Here, this spatial preference modelling (SPM) addresses equity not only among people but also across locations.…”

Section: Introductionmentioning

confidence: 99%

Equity-based resource allocation for infrastructure development

Wismadi¹

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With regard to regional development, two possible approaches to promote the role of infrastructure and economic interaction are available, placebased policies and people-centred policies. These policy options have been detailed in the publication of the World Development Report (WDR) 2009 (Garretsen, Roberts et al. 2011) and separated into three policy instruments for reshaping economic geography: 1) spatially blind institution, 2) spatially connective infrastructure and 3) spatially targeted 1.4 Research Framework To produce the framework, four groups of works and its deliverable in a series of papers, these and the associated research questions are outlined as one Context Paper, one Background Paper, three Working Papers and, finally, one Policy Paper (Figure 1.1 Research Framework). Chapter 7 establishes a decision support framework to recommend where and when a "place-based" or "people-centred" policy for equitable infrastructure development should be applied. This chapter synthesizes all finding into a decision support framework, Equity Based Resources Location-Allocation Simulation (EQLAS), for integrated infrastructure development.

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Spatial Preference Modelling for equitable infrastructure provision: an application of Sen’s Capability Approach

Cited by 20 publications

References 40 publications

Equitable distribution of growth for utilitarian and non-utilitarian infrastructure planning

Equitable distribution of growth for utilitarian and non-utilitarian infrastructure planning

Study on Optimal Spatial Configuration of Indemnificatory Community Public Service Facility Based on Modified MOGA

Equity-based resource allocation for infrastructure development

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