a b s t r a c tThe urgent need to combat climate change is now globally accepted. Collective action at a global level is the key ability to respond to the threat of climate change. No individual company alone has the necessary resources and capabilities to tackle the unprecedented challenge of climate change. Companies need to engage in give-and-take exchange relationships with other companies to address climate change. Research on how companies interact with each of their counterparts to respond to the challenge of climate change is limited. Existing research on climate raises questions about 1) how companies interact in response to climate change and 2) why companies fail to craft collective responses to climate change? In an attempt to shed light on these questions, we use the network approach as a theoretical perspective to account for the ever increasing connectivity and interdependence in the business landscape and theorize on the consequences these phenomena may have for the study. The study is based upon an empirical investigation of public-private networks in Germany. Findings indicate that companies fail to collectively respond to climate change due to the multiplicity of interests of actors involved in the network which is aggravated by 1) economic reasoning; 2) weak actor bonds; and 3) differing perceptions of the rules of the game. As such, the present study contributes to our understanding of collective responses to the ever evolving challenge of climate change.

Mapping the expansion of impervious surfaces in urbanizing areas is important for monitoring and understanding the hydrologic impacts of land development. The most common approach using spectral vegetation indices, however, is difficult in arid and semiarid environments where vegetation is sparse and often senescent. In this study object-oriented classification of high-resolution imagery was used to develop a cost-effective, semi-automated approach for mapping impervious surfaces in Sierra Vista, Arizona for an individual neighborhood and the larger sub-watershed. Results from the neighborhood-scale analysis show that object-oriented classification of QuickBird imagery produced repeatable results with good accuracy. Applying the approach to a 1,179 km 2 region produced maps of impervious surfaces with a mean overall accuracy of 88.1 percent. This study demonstrates the value of employing object-oriented classification of high-resolution imagery to operationally monitor urban growth in arid lands at different spatial scales in order to fill knowledge gaps critical to effective watershed management.

We compare and contrast the UK and China as maximum variation cases for understanding long energy transitions from the state and the firm perspectives. We present case histories and corpus-based computer-assisted textual analyses on the long energy transitions in both countries. With these, we explore and explain how and why energy supply firms respond the way they do to the institutional ambiguities and complexities that characterize the long energy transitions in each case. Our findings demonstrate that a centrally coordinated and imposed approach by the state can generate institutional clarity in long energy transition, which is quickly seized on by firms striving to preserve and increase their resources and influence. Such clarity and transition processes lose momentum owing to the perennial trilemma of energy affordability, security and sustainability. Market-based mechanisms to trigger and sustain long energy transitions, complemented with focused and continuous state interventions (e.g., incentives, taxation) provide a more effective and accountable institutional framework for the state and energy firms to deal with the energy trilemma. Irrespective of the logic of the type of economy that manifests the backdrop for any long energy transition process, institutional ambiguity and complexity never disappear completely, owing to both the energy trilemma and the institutional multiplicities.

State-of-the-art CT-equipment substantially reduce radiation dose without affecting image quality.

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