Evaluation of City Sustainability from the Perspective of Behavioral Guidance

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Evaluation of City Sustainability from the Perspective of Behavioral Guidance sustainability Article Evaluation of City Sustainability from the Perspective of Behavioral Guidance Ying Zhou 1,*, Weiwei Li 2 , Pingtao Yi 2 and Chengju Gong 3 1 School of Management, Shenyang Jianzhu University, Shenyang 110168, China 2 School of Business Administration, Northeastern University, Shenyang 110168, China; [email protected] (W.L.); [email protected] (P.Y.) 3 School of Economics and Management, Harbin Engineering University, Harbin 150001, China; [email protected] * Correspondence: [email protected] Received: 8 November 2019; Accepted: 28 November 2019; Published: 30 November 2019 Abstract: 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. Keywords: city sustainability; city sustainability evaluation; data distribution analysis; behavioral guidance weight; multi-criteria decision-making 1. Introduction The emergence of cities is a sign of human maturity and civilization, as well as an advanced form of human social life. Urbanization has become a global trend with the development of social productivity, the advancement of science and technology, and the adjustment of the industrial structure. In fact, urbanization has both positive and negative effects on cities’ social, economic and environmental systems. Therefore, city sustainability is an important part of urbanization. Related research is gaining increasing attention and prevalence worldwide [1–18], such as work on the sustainable city [1,2], smart city [3–5] and smart sustainable city [7–9]. Bibri et al. argue that sustainable cities can be defined as a city environment designed with the aim of contributing to improved environmental quality, social equity and well–being over the longrun [1]. Chourabi et al. define a smart city as a city that strives to become more efficient, livable, equitable and sustainable [3]. Although there are many works of research literature on the smart city, the European Smart Cities Sustainability 2019, 11, 6808; doi:10.3390/su11236808 www.mdpi.com/journal/sustainability Sustainability 2019, 11, 6808 2 of 17 Ranking developed by Giffinger et al. is widely used [5]. According to D’Auria [6], both concepts of sustainable city and smart city cannot be thought of as contrasting because they share many commonalities. The attention focused on social, economic and environmental issues has framed the debate over sustainability and converged in both concepts. The smart sustainable city is a new techno–urban phenomenon that was widely used in the mid-2010s [7]. It is rapidly gaining momentum as a holistic approach to city development and academic pursuit, especially in ecologically and technologically advanced societies [8,9]. Furthermore, sustainability evaluation is an essential part of city sustainability research, because the evaluation can support the next sustainable development policy while monitoring the status of the objects [10–18]. 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 [19–28], indicators’ weights setting [29–43] and information aggregation [44–52]. A detailed review of the related work is shown in Section2. Prior studies have made significant contributions to city sustainability. However, existing studies have not considered the interaction among different systems in the construction of evaluation indicators. At the same time, the thoughts of the evaluator on behavioral guidance are not introduced in the objective weighting methods. In this paper, we try to find corresponding solutions based on the above problems. We focus on the evaluation of city sustainability in Liaoning Province from the perspective of behavioral guidance. There are two main research goals of our research. On the one hand, through the evaluation, each city evaluation stakeholder can comprehend the sustainable development level of their city from multiple perspectives, such as the dimension of systems’ sustainability, the sub-dimension of the system base, and its supply to other systems. Simultaneously, it is convenient to compare with other cities or their evaluation values in different years. On the other hand, the idea of behavioral guidance is integrated into the evaluation model, which aims to objectively guide cities to develop towards the goals established. The rest of this paper is organized as follows. Section2 provides an overview of the related work on city sustainability evaluation. Section3 constructs the evaluation indicator system for city sustainability, which considers the base of each system and its interaction with other systems, that is, it refines the traditional evaluation indicator system. Section4 proposes an evaluation method with behavioral guidance. An objective weighting method with behavioral guidance is proposed by considering the data distribution. Section5 conducts an empirical study on the sustainable level of 14 cities in Liaoning Province. In Section6, conclusions and suggestions are outlined. 2. Related Work on City Sustainability Evaluation The research on city sustainability evaluation can be mainly divided into three categories, namely, evaluation indicators selection, indicators’ weights setting and information aggregation. For city sustainability evaluation, the selection of sustainable indicators is a key factor influencing the conclusions of the evaluation. The three-pole or three-pillar model that combines social system, economic system, and environment system together are widely used because of its concise and comprehensive features [19–23]. Ding et al. indicate that the sustainable development of the city is a harmonious and comprehensive development of the three elements [24]. Among them, environmental sustainable development is the foundation, economic sustainable development is the guarantee, and social sustainable development is the ultimate goal. Sun et al. use social, economic and natural indicators to monitor the sustainable development of cities and applied it to data from 2000 to 2010 for 277 Chinese cities, including megalopolises, large cities, small cities and medium-sized cities [25]. Because the data acquisition channels are different, there will be some differences in the evaluation indicators of different countries and cities [26–28]. 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: Sustainability 2019, 11, 6808 3 of 17 subjective weighting method [29–32], objective weighting method [33–36] and combined weighting method [37–39]. 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. However in these methods the objectivity and reproducibility of the evaluation result are relatively poor. The objective weighting method, such as the entropy method [42], deviation maximization method [43], etc., uses relatively perfect mathematical theories and methods, but does not consider the subjective information of the evaluator. In order to simultaneously embody the advantages of the two kinds of methods mentioned above, the combination weighting method has been proposed and widely applied. The information aggregation method in multi-criteria decision making (MCDM) can be widely used to aggregate the evaluation indicator values and the indicator weights together, so as to obtain the corresponding sustainable performances of cities. There are many methods to aggregate information, among which simple additive weighting (SAW) [44] is commonly used. Other aggregation methods are used in city sustainability evaluation as well, such as the weighted geometric average (WGA) method [45], the order preference by similarity to ideal
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