Multicriteria analysis of sustainable development indicators in the construction minerals industry in China

Chen, Rong-Hui; Lin, Yuan-Hsu; Tseng, Ming‐Lang

doi:10.1016/j.resourpol.2014.10.012

Cited by 72 publications

(33 citation statements)

References 57 publications

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“…Waas et al [43] used sustainability assessment (SA) and sustainability indicators (SIs) as theoretical tools for evaluating the decision strategies of sustainable construction. Chen et al [10] combined fuzzy set theory, the Delphi method, and the discrete multi-criteria method, to analyze the sustainable development indicators in the uncertain economic environment. Lin et al [14] used a structured method and a quantitative analysis model to develop an indicator system to evaluate megaproject social responsibility effectively.…”

Section: Evaluation Indicators For Mscpsmentioning

confidence: 99%

What are the Key Indicators of Mega Sustainable Construction Projects? —A Stakeholder-Network Perspective

Qiang

Zuo

et al. 2018

Sustainability

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Mega sustainable construction projects (MSCPs) require complex system engineering. There are various indicators available to evaluate sustainable construction, and it is difficult to determine which the key indicators are among them. Existing studies do not adequately consider the stakeholders associated with the indicators of sustainable construction, leading to key decision-makers' lack of targeted management strategies to improve the sustainability level of MSCPs. Using literature analysis and expert interviews, this study identified the key evaluation indicators of MSCPs from a stakeholder-network perspective. Social network analysis (SNA) was used to explore the relationships between the key evaluation indicators and corresponding stakeholders. The results showed that the government and designers significantly impacted other stakeholders and played as the key stakeholders in MSCPs. Regarding the indicators, applying energy-saving and intelligent technologies plays a key role in the MSCPs. This study links key indicators of MSCPs with the associated stakeholders, which helps decision-makers to develop targeted strategies to improve the sustainability level of MSCPs, thereby not only improving the efficiency and effectiveness of the intervention strategies, but also helping to save decision-makers' monetary and human resources which are usually limited.

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Section: Evaluation Indicators For Mscpsmentioning

confidence: 99%

What are the Key Indicators of Mega Sustainable Construction Projects? —A Stakeholder-Network Perspective

Qiang

Zuo

et al. 2018

Sustainability

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“…Moreover, other challenges related to Big Data emerge, such as the 4 V or 5 V, where the Volume is too big, Variety is too many, Velocity is too fast, Veracity is too uncertain, and Value is difficult to evaluate (see e.g., [14]). Chen et al [15] added value to stress that correctly evaluating value in Service and Manufacturing Supply Chain Management (SM-SCM) is challenging. The correctness of decisions based on Big Data is difficult to argue, because how well micro and macro economic factors reflect the success of business varies.…”

Section: Big Datamentioning

confidence: 99%

“…Big Data can open new gateways for increasing knowledge. Chen et al [15] argue that the developments of Big Data will enrich current decision sciences. The value of Big Data will be only generated by relevant algorithms, which produce analytical results of stored raw data.…”

Section: Big Datamentioning

confidence: 99%

“…It is necessary to simultaneously use various types of data, and realize the available resources, and how they could impact on the sustainability of a company [46]. Emission-free production certainly improves the reputation of a company compared with other ones if effects on global warming and environmental impacts are mitigated [15,[47][48][49]. Rahdari, Anvary and Rostamy [49] also explain how many companies are building sustainability indicators that address the level at which the companies are operating, and help promote progress.…”

Section: Emission and Sustainability Measuring And Calculationsmentioning

confidence: 99%

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How to Generate Economic and Sustainability Reports from Big Data? Qualifications of Process Industry

Hämäläinen

Inkinen

2017

Processes

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Big Data may introduce new opportunities, and for this reason it has become a mantra among most industries. This paper focuses on examining how to develop cost and sustainable reporting by utilizing Big Data that covers economic values, production volumes, and emission information. We assume strongly that this use supports cleaner production, while at the same time offers more information for revenue and profitability development. We argue that Big Data brings company-wide business benefits if data queries and interfaces are built to be interactive, intuitive, and user-friendly. The amount of information related to operations, costs, emissions, and the supply chain would increase enormously if Big Data was used in various manufacturing industries. It is essential to expose the relevant correlations between different attributes and data fields. Proper algorithm design and programming are key to making the most of Big Data. This paper introduces ideas on how to refine raw data into valuable information, which can serve many types of end users, decision makers, and even external auditors. Concrete examples are given through an industrial paper mill case, which covers environmental aspects, cost-efficiency management, and process design.

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“…The Ruhr area was a center of coal and steel production since the mid-19th century. However, scholars have researched the frameworks and analytical methods that are applicable to resource-based cities and industries [20,21], and they have endeavored to establish the indicators of sustainable development. Some empirical research from various regional scales has been performed.…”

Section: Introductionmentioning

confidence: 99%

The Urban Transition Performance of Resource-Based Cities in Northeast China

Tan

Zhang

et al. 2016

Sustainability

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Abstract:Resource-based cities face unique challenges when undergoing urban transitions because their non-renewable resources will eventually be exhausted. In this article, we introduce a new method of evaluating the urban transition performance of resource-based cities from economic, social and eco-environmental perspectives. A total of 19 resource-based cities in Northeast China are studied from 2003 to 2012. The results show that resource-based cities in Jilin and Liaoning provinces performed better than those in Heilongjiang province. Liaoyuan, Songyuan and Baishan were ranked as the top three resource-based cities; and Jixi, Yichun and Heihe were ranked last. Multi-resource and petroleum resource-based cities performed better than coal and forestry resource-based cities. We also analyzed the factors influencing urban transition performance using the method of the geographic detector. We found that capital input, road density and location advantage had the greatest effects on urban transition performance, followed by urban scale, remaining resources and the level of sustainable development; supporting policies and labor input had the smallest effects. Based on these insights, we have formulated several recommendations to facilitate urban transitions in China's resource-based cities.

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Multicriteria analysis of sustainable development indicators in the construction minerals industry in China

Cited by 72 publications

References 57 publications

What are the Key Indicators of Mega Sustainable Construction Projects? —A Stakeholder-Network Perspective

What are the Key Indicators of Mega Sustainable Construction Projects? —A Stakeholder-Network Perspective

How to Generate Economic and Sustainability Reports from Big Data? Qualifications of Process Industry

The Urban Transition Performance of Resource-Based Cities in Northeast China

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