Towards a generic multi-criteria evaluation model for low carbon cities

Azizalrahman, Hossny; Hasyimi, Valid

doi:10.1016/j.scs.2018.02.026

Cited by 55 publications

(24 citation statements)

References 26 publications

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“…Benchmarks were derived from multiple sources: (1) World Bank and WHO; (2) top city performances, such as green city index; (3) International targets for developed countries set out by EU ( Table 1). A multi-criteria evaluation model has been proposed by modifying the framework of Azizalrahman and Hasyimi [23].…”

Section: Smart City Criteria and Indicatorsmentioning

confidence: 99%

Towards a Generic Framework for Smart Cities

Azizalrahman¹,

Hasyimi²

2020

Smart Urban Development

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Cities are formidable drivers of economic, social and cultural development but face a rising multitude of challenges: urban sprawl, transportation problems and climate change to mention but a few. Evolving concepts such as smart cities, sustainable communities and low carbon cities have been employed to formulate initiatives to tackle these challenges. Smart cities appear to address efficiency in reducing time, cost, and energy in delivering services-smart transportation, intelligent buildings, and green infrastructure with a view to reaching low carbon city development and eventually sustainability. This article attempts to construct a general framework for smart cities. First, the overall smart city system is depicted. Second, the dynamics of urban sector drivers in smart and low carbon cities are elucidated. Third, the performance of smart cities is measured in relation to low carbon development. By applying the smart city framework to the cities of Vienna, London, New York and Tokyo, the model proved robust and flexible. The investigation is concluded with policies to realign city plan and development policies.

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Section: Smart City Criteria and Indicatorsmentioning

confidence: 99%

Towards a Generic Framework for Smart Cities

Azizalrahman¹,

Hasyimi²

2020

Smart Urban Development

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“…The determination of the indicators' weights is also an important part of the rationality of city sustainability evaluation. The weighting method can be divided into three categories: subjective weighting method [29][30][31][32], objective weighting method [33][34][35][36] and combined weighting method [37][38][39]. The subjective weighting method, such as the Delphi method [40], analytic hierarchy process (AHP) method [41], etc., reflects the subjective judgment and intuition of the evaluator.…”

Section: Related Work On City Sustainability Evaluationmentioning

confidence: 99%

“…Yi et al develop the deviation maximization weighting method to observe the sustainable levels of 17 cities in Shandong Province, China [11]. Several studies on city sustainability evaluation can be found, and the related literature can be grouped into three categories, i.e., evaluation indicators selection [19][20][21][22][23][24][25][26][27][28], indicators' weights setting [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43] and information aggregation [44][45][46][47][48][49][50][51][52]. A detailed review of the related work is shown in Section 2.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of City Sustainability from the Perspective of Behavioral Guidance

Zhou

et al. 2019

Sustainability

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High-quality evaluation of city sustainability is an important part of city policy making and development. In this paper, we evaluated the sustainability of the 14 cities in Liaoning, China, from 2015 to 2017. Based on the comprehensive consideration of the interactions among the social, economic and environmental systems, the traditional evaluation indicator system is refined. We incorporate the attitude of decision makers into the evaluation model and propose an objective weighting method by considering data distribution to objectively guide the cities to develop towards the established goals. The empirical research results show that cities located in eastern Liaoning performed the best and in western Liaoning performed the worst. The performances of the 14 cities in Liaoning were not perfect. Both the evaluation values and growth rates of 7 cities (accounting for 50.00%) were lower than the overall average level. The evaluation values of the three systems of the 14 cities were not balanced. The evaluation values of the social, economic and environmental systems fluctuated within the range of [0.0159, 0.0346], [0.0151, 0.0677] and [0.0123, 0.0483], respectively. The social and economic systems of most cities supplied more for the environmental system than for the other system. Cities with higher environmental base rankings offered less supply to other systems. At the same time, we also provide some individualized and concrete suggestions for the guidance of city sustainable development. By comparing the empirical data with the reality, it confirms the credibility of the method and the recommendations in this paper.

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“…Multi-criteria evaluation models were built to measure low carbon using the entropy weight coefficient method [7][8][9]. A generic multi-criteria evaluation model (GMLC) was also developed to quickly identify whether a city is low carbon or not [10].…”

Section: Literature Reviewmentioning

confidence: 99%

A Strategy-Based Model for Low Carbon Cities

Hasyimi

Azizalrahman

2018

Sustainability

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Low carbon cities are increasingly forming a distinct strand of sustainability literature. Models have been developed to measure the performance of low carbon cities. The purpose of this paper is to formulate a strategy-based model to evaluate current performance and predict future conditions of low carbon cities. It examines the dynamic interrelationships between key performance indicators (KPIs), induces changes to city plan targets, and then instantly predicts the outcome of these changes. Designed to be generic and flexible, the proposed model shows how low carbon targets could be used to guide the transformation of low carbon cities under four strategies: (1) Passive intervention, (2) problem solving, (3) trend modifying, and (4) opportunity seeking. Further, the model has been applied to 17 cities and then tested on five cities: London, New York, Barcelona, Dubai, and Istanbul. The paper concludes with policy implications to realign city plans and support low carbon innovation.

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Towards a generic multi-criteria evaluation model for low carbon cities

Cited by 55 publications

References 26 publications

Towards a Generic Framework for Smart Cities

Towards a Generic Framework for Smart Cities

Evaluation of City Sustainability from the Perspective of Behavioral Guidance

A Strategy-Based Model for Low Carbon Cities

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