2 resultados para Weighted histogram analysis method

em WestminsterResearch - UK


Relevância:

100.00% 100.00%

Publicador:

Resumo:

This paper explains how the practice of integrating ecosystem-service thinking (i.e., ecological benefits for human beings) and institutions (i.e., organisations, policy rules) is essential for coastal spatial planning. Adopting an integrated perspective on ecosystem services (ESs) both helps understand a wide range of possible services and, at the same time, attune institution to local resource patterns. The objective of this paper is to identify the extent to which ESs are integrated in a specific coastal strategic planning case. A subsequent objective is to understand whether institutions are capable of managing ESs in terms of uncovering institutional strengths and weaknesses that may exist in taking ESs into account in existing institutional practices. These two questions are addressed through the application of a content analysis method and a multi-level analysis framework on formal institutions. Jiaozhou Bay in China is used as an illustrative case. The results show that some ESs have been implicitly acknowledged, but by no means the whole range. This partial ES implementation could result from any of four institutional weaknesses in the strategic plans of Jiaozhou Bay, namely a dominant market oriented interest, fragmented institutional structures for managing ESs, limited ES assessment, and a lack of integrated reflection of the social value of ESs in decision-making. Finally, generalizations of multi-level institutional settings on ES integration, such as an inter-organisational fragmentation and a limited use of ES assessment in operation, are made together with other international case studies. Meanwhile, the comparison highlights the influences of extensive market-oriented incentives and governments' exclusive responsibilities on ES governance in the Chinese context.

Relevância:

40.00% 40.00%

Publicador:

Resumo:

In this study we analyse the emerging patterns of regional collaboration for innovation projects in China, using official government statistics of 30 Chinese regions. We propose the use of Ordinal Multidimensional Scaling and Cluster analysis as a robust method to study regional innovation systems. Our results show that regional collaborations amongst organisations can be categorised by means of eight dimensions: public versus private organisational mindset; public versus private resources; innovation capacity versus available infrastructures; innovation input (allocated resources) versus innovation output; knowledge production versus knowledge dissemination; and collaborative capacity versus collaboration output. Collaborations which are aimed to generate innovation fell into 4 categories, those related to highly specialised public research institutions, public universities, private firms and governmental intervention. By comparing the representative cases of regions in terms of these four innovation actors, we propose policy measures for improving regional innovation collaboration within China.