Sustainability and economic growth—the integration and balance of social, environmental, and economic needs—is a salient concern for sustainable development and social well-being. By focusing on a sustainable innovation project, we explore how entrepreneurial ecosystems become sustainable entrepreneurial ecosystems and investigate the interactions of entrepreneurial actors. We conducted an inductive, single-case study of a specific collaborative innovation project in the denim industry specialized in a specific geographic location. From our data, we show that the presence of four conditional aspects foster sustainable entrepreneurial ecosystems. These include sustainability orientation of actors, recognition of sustainable opportunities and resource mobilization, collaborative innovation of sustainability opportunities, and markets for sustainable products. We make two observations that contribute to the literature. First, we see that in a sustainable entrepreneurial ecosystem, entrepreneurial experimentation is a highly interdependent and interactive process. Second, we see that recognition of sustainable opportunities is distributed among different actors in the ecosystem. Our findings also have implications for practitioners and policy-makers.
Supply chains have inherent risk given the number of actors that interface. While there are some chains that have low frequencies of unfavorable events, many continuously face uncertainty. Food production has many uncertainties along the global supply chain. The global nature of the large logistical networks increases its complexity. Two main sources of uncertainty arise: External and internal to the SC. External factors mainly come from nature (such as "El Niño" phenomenon) and from human activities (such as food and nutrition policy and standards). Internal factors mainly come from operations such as a cold chain disruption. Thus, one needs to minimize risk and improve resilience in order to achieve food security and sustainability. It is then imperative that risk management practices be integrated into the supply chain design and management process. This chapter presents an overview of the main risks involved in global food supply chains, as well as some techniques for risk management.
Client: Blue Plan regional activity centre (UNEP/MAP), subcontracted through TEC Conseille, Marseille As part of a regional workshop organized by the Blue Plan in July 2008, one of the conclusions of the Group "Tourism and Climate Change” was the need for saving energy in tourism transportation and particularly of air transport, as air transport is responsible for the largest share of greenhouse gas emissions caused by tourism. In the period 1998-2005, the share of international arrivals by air in the Mediterranean area rose from 23% to 40%, respectively, or in numbers, from 47 to 122 million tourists. Some countries, particularly islands, almost entirely depend on air transport for their international tourism. For example in 2005 air transport is used by 87%, 78%, 73%, 64% and 51% of international tourists arriving in, respectively, Israel, Egypt, Spain, Tunisia and Morocco. According to Plan Bleu forecasts on international arrivals, assuming that the share of air transport remains the same, the number of tourists travelling by plane will reach over 158 million by 2025. Given the role of aviation in the emissions of greenhouse gases (GHG), such a development is clearly not sustainable in the light of the necessary reduction of emissions to avoid dangerous climate change. The overall aim of the study is to inform policy makers and entrepreneurs in both destination and in origin countries, on possible options to reduce emissions of greenhouse gases from air travel, while at the same time not impairing the economic development of tourism. To do this, CSTT has developed a tourism scenario model for all countries with Mediterranean coasts describing inbound and outbound international tourism and domestic tourism by all available transport modes and giving both contributions to GDP and total GHG emissions. This model responses to global mitigation policies (increasing the cost of carbon emissions) as well as national policies (taxes, subsidies and changes in transport quality per transport mode). Using the model both global and national policies can be assessed as well as the risks of global mitigation policies for specific countries.
