مقاله انگلیسی رایگان در مورد ارزیابی جامعه هوشمند برای توسعه پایدار – الزویر ۲۰۱۸

مقاله انگلیسی رایگان در مورد ارزیابی جامعه هوشمند برای توسعه پایدار – الزویر ۲۰۱۸

 

مشخصات مقاله
ترجمه عنوان مقاله ارزیابی جامعه هوشمند برای توسعه پایدار با استفاده از چارچوب تحلیلی ترکیبی
عنوان انگلیسی مقاله Smart community evaluation for sustainable development using a combined analytical framework
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۳۰ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) scopus – master journals – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۵٫۶۵۱ در سال ۲۰۱۷
شاخص H_index ۱۳۲ در سال ۲۰۱۸
شاخص SJR ۱٫۴۶۷ در سال ۲۰۱۸
رشته های مرتبط مدیریت، مهندسی شهرسازی، معماری
گرایش های مرتبط سیاست های تحقیق و توسعه، طراحی شهری، معماری پایدار
نوع ارائه مقاله
ژورنال
مجله / کنفرانس مجله تولید پاک – Journal of Cleaner Production
دانشگاه  School of Management – Hefei University of Technology – China
کلمات کلیدی توسعه جامعه پایدار، نظریه چشم انداز، استدلال مدرکی، ارزیابی ترکیبی
کلمات کلیدی انگلیسی Sustainable community development, Prospect theory, Evidential reasoning, Combined evaluation
شناسه دیجیتال – doi
https://doi.org/10.1016/j.jclepro.2018.05.023
کد محصول E9973
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فهرست مطالب مقاله:
Abstract
Keywords
۱ Introduction
۲ Literature review
۳ PTER analytical framework
۴ Prospect value calculation and modification for SCE
۵ Assessment combination for SCE
۶ Experiment analysis
۷ Conclusions
Acknowledgement
Appendix.
References

بخشی از متن مقاله:
Abstract

Current attempts for sustainable-focused smart community evaluation have failed to make significant advancements, and quantitative analysis for sustainable development is still a major challenge in China. In recent years, smart community evaluation (SCE) for sustainable development has attracted considerable attentions. Government decision-makers can make it easier to stimulate household sustainable consumption by conducting SCE. This paper develops a combined analytical framework that will assist in the process of multi-source data integration and uncertain reasoning of SCE. This framework is used to combine quantitative metrics and subjective judgment with evidential reasoning approach, and this frarmework can also take decision makers’ risk preferences into consideration using prospect theory. Four urban communities are evaluated by the proposed framework to demonstrate its applicability and effectiveness.

Introduction

As the rapid development of economy and the increasing growth of population, problems such as traffic jams and population density in metropolis areas, excessive consumption of non-renewable resources, deteriorating environment and many other social problems have arisen(Chen et al., 2017; Ding et al., 2017; Wang et al., 2017). In order to address these chanllenges, the concepts of “smart planet” and “smart city” have been proposed by IBM (C. et al., 2009). In 2014, the Chinese government issued an urbanization development plan, and declared that the sustainable-focused smart community construction is one of its urban development directions. On April 7th, 2015, the Ministry of Housing and Urban-Rural Development and the Ministry of Science and Technology of the People’s Republic of China jointly confirmed a total of 209 smart community pilots which are regarded as an indispensable part of sustainable city development. By the end of 2017, more than 500 cities in China had been constructing smart communities. And during the period of the13th Five-Year Plan for Economic and Social Development of the People’s Republic of China, the investment of government on smart communities will exceed 500 billion yuan. Under the effect of policies and market driven impetus, the development of smart communities is faster and faster. Along with the development of smart communities in China in recent years, there are also a series of problems hindering smart community construction. Facing realities such as different scales of investment, great diversity of participants and various phases of sustainable development, the research on construction mode of smart community and cooperation behavior of different participants are both important for smart community development(Xia et al., 2015). But smart community evaluation (SCE) plays a crucial role in ensuring the effectiveness of its implementation and development. Although the last decade has witnessed a number of results in the research on SCE, there are still many issues to be solved as the multi-source data integration and uncertain reasoning (Chilipirea et al., 2017; Ding et al., 2014; Linlin et al., 2017; Sta, 2017). SCE can allow governments to make more effective funding arrangements, increase the capability of community service and management, and promote the transition from traditional consumption to sustainable household consumption. Performance evaluation of smart community for sustainable development has been extensively studied by both academia and industry recently, due to their socio-ecological value and the associated research issues(Wang et al., 2017). In France, Toshiba Solutions Corporation has been selected as the leading contractors for a smart community project that has achieved sustainable development by employing multiple sophisticated technologies (Nobutaka et al., 2015). In Aizuwakamatsu Japan, local government is working to build smart communities for providing a high quality of life and security to residents (Tada et al., 2014). In addition, the TERE (technology, environment, resources and the economy) model provides some convenience for exploiting marine resources and construction of smart city in Qingdao, which has been developed for better management and eco-friendly development (Wang et al.) . Over the past decades, the existing research has made great contributions to the community development, such as reputation mechanism for cooperation(Wang et al., 2017; Xia et al., 2017), multidimensional smart community discovery scheme(Kim et al., 2017), and a new government affairs service platform(Lv et al., 2017). While the existing SCE methods still have some limitations, which can be summarized as: (1) It is difficult to find an adaptable methodology to solve the problems of multi-source data integration and uncertain reasoning in SCE. (2) Few works consider the risk preference of decision makers, which has a significant impact on the sustainable-focused evaluation.

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