A methodological approach for the design of sustainability initiatives: in pursuit of sustainable transition in China

2017 
The foundation of sustainability science is the effort to understand the fundamental interactions between nature and society, and to guide these interactions along sustainable trajectories (Miller et al. Sustain Sci 9(2):240–246, 2014). More importantly, sustainability science aims at creating knowledge needed to improve relevancy and quality of sustainability decision-making processes through broader representation of knowledge and values. This study contributes to the sustainability science literature in the areas of strategic planning and decision-making. Both the values and the role of decision-making science in promoting sustainability are examined through the design of a strategic framework and application of a graphical multi-agent decision-making model (GMADM). This approach allows for analysis, valuation, and ranking of potential sustainability initiatives according to their projected benefits and gains for organizations and for society. The model is structured on three interrelated pillars: (I) stakeholder views and concerns (government, industry, academic institutions); (II) sustainable development trends and requirements (World Bank data); and (III) valuations of the benefits expected from sustainability efforts. The framework is applied to case studies of Shandong and Guangdong provinces in China. Qualitative and quantitative analysis of data obtained from three groups of stakeholders in each province confirmed the utility of the proposed decision-making approach for promoting sustainable transition in China. Results also demonstrated the convenience and effectiveness of the proposed framework for guiding organizations’ efforts toward optimizing their sustainability initiatives while supporting regional economic growth and sustainable development policies.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    78
    References
    8
    Citations
    NaN
    KQI
    []