What drives consumer activism during trade disputes? We investigate this important and timely question using a survey experiment in the context of the recent Canada–US trade dispute. We find that Canadians are more likely to express willingness to take punitive actions in the form of boycotting during a trade conflict when they learn that Americans are taking such actions (retaliation), when many fellow citizens are taking such actions (peer pressure), and when they are rallied by their government (elite cue). Among the three conditions, peer pressure has the largest effect. These findings contribute to our understanding of the microfoundations of consumer activism during international trade disputes. They also have important policy implications in a world where both protectionism and populism are rising.
The wide and in-depth adoption of advanced information technologies within the construction industry has led to its revolution of all aspects; the construction site is not an exception. Recently, the notion of a smart construction site (SCS) has drawn the attention of all stakeholders within the industry. While the practice of SCS could be witnessed in various regions and the notion is mentioned frequently, the concept of SCS is still emerging, a sound framework for SCS development is still absent. As a bottom-up phenomenon, a systematic analysis of critical factors would provide all stakeholders with a comprehensive view of SCS development. In this research, previous research and existing practices of SCS are referred to, which helps to identify 17 critical factors for SCS development from the perspective of management, technology, and organization. The DEMATEL-ISM approach is introduced to conduct the factor analysis, and a questionnaire survey is conducted among 10 experts to investigate their attitudes on these factors. Following the proposed method, the 17 factors are classified into seven hierarchies and further categorized into three layers, i.e., effect layer, operational layer, and input layer, which helps to demonstrate the interrelationship among the critical factors for SCS development. The effect layer consists of the first to the third hierarchy, which contains the factors of cost (F2), safety (F4), schedule (F5), environment (F9), and quality (F3) management; these factors belong to the management perspective and reflect the expectations during SCS development. The operational layer consists of the fourth to the sixth hierarchy, which contains seven factors, namely, processing (F8), information (F10), communication and coordination (F15), personnel (F5), material (F6), equipment (F7), and management regulation (F17); these factors are critical in processing the input resources into the final effect of SCS development. The input layer only consists of the seventh hierarchy, which contains hardware and software facility (F11), integrated platform (F12), data sharing center (F13), smart decision system (F14), and technical team (F16); these factors represent the investment of SCS development. The systematic analysis of critical factors provides new insights on SCS development, which could be adopted as references for future SCS development by all stakeholders like government and construction enterprises.
International audience ; The Australian governmental agencies reported a total of 149 million ha forest in the Food and Agriculture Organization of the United Nations (FAO) in 2010, ranking sixth in the world, which is based on a forest definition with tree height>2 meters. Here, we report a new forest cover data product that used the FAO forest definition (tree cover>10 % and tree height>5 meters at observation time or mature) and was derived from microwave (Phased Array type L-band Synthetic Aperture Radar, PALSAR) and optical (Moderate Resolution Imaging Spectroradiometer, MODIS) images and validated with very high spatial resolution images, Light Detection and Ranging (LiDAR) data from the Ice, Cloud, and land Elevation Satellite (ICESat), and in situ field survey sites. The new PALSAR/MODIS forest map estimates 32 million ha of forest in 2010 over Australia. PALSAR/MODIS forest map has an overall accuracy of ~95% based on the reference data derived from visual interpretation of very high spatial resolution images for forest and nonforest cover types. Compared with the canopy height and canopy coverage data derived from ICESat LiDAR strips, PALSAR/MODIS forest map has 73% of forest pixels meeting the FAO forest definition, much higher than the other four widely used forest maps (ranging from 36% to 52%). PALSAR/MODIS forest map also has a reasonable spatial consistency with the forest map from the National Vegetation Information System. This new annual map of forests in Australia could support cross-country comparison when using data from the FAO Forest Resource Assessment Reports.
International audience ; The Australian governmental agencies reported a total of 149 million ha forest in the Food and Agriculture Organization of the United Nations (FAO) in 2010, ranking sixth in the world, which is based on a forest definition with tree height>2 meters. Here, we report a new forest cover data product that used the FAO forest definition (tree cover>10 % and tree height>5 meters at observation time or mature) and was derived from microwave (Phased Array type L-band Synthetic Aperture Radar, PALSAR) and optical (Moderate Resolution Imaging Spectroradiometer, MODIS) images and validated with very high spatial resolution images, Light Detection and Ranging (LiDAR) data from the Ice, Cloud, and land Elevation Satellite (ICESat), and in situ field survey sites. The new PALSAR/MODIS forest map estimates 32 million ha of forest in 2010 over Australia. PALSAR/MODIS forest map has an overall accuracy of ~95% based on the reference data derived from visual interpretation of very high spatial resolution images for forest and nonforest cover types. Compared with the canopy height and canopy coverage data derived from ICESat LiDAR strips, PALSAR/MODIS forest map has 73% of forest pixels meeting the FAO forest definition, much higher than the other four widely used forest maps (ranging from 36% to 52%). PALSAR/MODIS forest map also has a reasonable spatial consistency with the forest map from the National Vegetation Information System. This new annual map of forests in Australia could support cross-country comparison when using data from the FAO Forest Resource Assessment Reports.
International audience ; The Australian governmental agencies reported a total of 149 million ha forest in the Food and Agriculture Organization of the United Nations (FAO) in 2010, ranking sixth in the world, which is based on a forest definition with tree height>2 meters. Here, we report a new forest cover data product that used the FAO forest definition (tree cover>10 % and tree height>5 meters at observation time or mature) and was derived from microwave (Phased Array type L-band Synthetic Aperture Radar, PALSAR) and optical (Moderate Resolution Imaging Spectroradiometer, MODIS) images and validated with very high spatial resolution images, Light Detection and Ranging (LiDAR) data from the Ice, Cloud, and land Elevation Satellite (ICESat), and in situ field survey sites. The new PALSAR/MODIS forest map estimates 32 million ha of forest in 2010 over Australia. PALSAR/MODIS forest map has an overall accuracy of ~95% based on the reference data derived from visual interpretation of very high spatial resolution images for forest and nonforest cover types. Compared with the canopy height and canopy coverage data derived from ICESat LiDAR strips, PALSAR/MODIS forest map has 73% of forest pixels meeting the FAO forest definition, much higher than the other four widely used forest maps (ranging from 36% to 52%). PALSAR/MODIS forest map also has a reasonable spatial consistency with the forest map from the National Vegetation Information System. This new annual map of forests in Australia could support cross-country comparison when using data from the FAO Forest Resource Assessment Reports.
International audience ; The Australian governmental agencies reported a total of 149 million ha forest in the Food and Agriculture Organization of the United Nations (FAO) in 2010, ranking sixth in the world, which is based on a forest definition with tree height>2 meters. Here, we report a new forest cover data product that used the FAO forest definition (tree cover>10 % and tree height>5 meters at observation time or mature) and was derived from microwave (Phased Array type L-band Synthetic Aperture Radar, PALSAR) and optical (Moderate Resolution Imaging Spectroradiometer, MODIS) images and validated with very high spatial resolution images, Light Detection and Ranging (LiDAR) data from the Ice, Cloud, and land Elevation Satellite (ICESat), and in situ field survey sites. The new PALSAR/MODIS forest map estimates 32 million ha of forest in 2010 over Australia. PALSAR/MODIS forest map has an overall accuracy of ~95% based on the reference data derived from visual interpretation of very high spatial resolution images for forest and nonforest cover types. Compared with the canopy height and canopy coverage data derived from ICESat LiDAR strips, PALSAR/MODIS forest map has 73% of forest pixels meeting the FAO forest definition, much higher than the other four widely used forest maps (ranging from 36% to 52%). PALSAR/MODIS forest map also has a reasonable spatial consistency with the forest map from the National Vegetation Information System. This new annual map of forests in Australia could support cross-country comparison when using data from the FAO Forest Resource Assessment Reports.
