Can Big Data and Predictive Analytics Improve Social and Environmental Sustainability?

Although literature indicates that big data and predictive analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions. Grounding our investigation in the dynamic capability views and organisational culture and based on sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains

COVID19 and the city; from the short term to the long term

[Extract] The current COVID19 pandemic cause an enormous number of cases of diseases and premature deaths (EPIWIN, 2020). The number of cases tests health care systems and has led to dramatic actions in many countries e.g. China, Singapore, Japan, Italy, Spain and many other countries. The actions had considerable success in some countries such as China, South Korea and Japan, but still led to a large impact in others like Spain and Italy

The impact of channel capture on estuarine hydro-morphodynamics and water quality in the Amazon delta

•Natural diversion connected Araguari River to Amazon River in Eastern Amazon.•Up to 98% in flowrate reduction to lower estuary and flow direction inversion.•Flowrate reduction to estuary causes accelerated siltation process in river mouth.•Water quality changed downstream and not affected upstream river diversion.•Future studies are necessary to evaluate impacts to water communities. [Display omitted] Due to progressive erosion of the new Urucurituba Channel, the Amazon River has recently captured almost all discharge from the lower Araguari River (Amapá-AP, Brazil), which previously flowed directly to the Atlantic Ocean. These recent geomorphological changes have caused strong impacts on the landscape and hydrodynamic patterns near the Araguari River mouth, especially the alteration of the riverine drainage system and its water quality. Landsat images were used to assess the estuarine landscape morphodynamic, particularly the expansion of the Urucurituba Channel, 80km from the Araguari River mouth, chronicling its connection to the Amazon River. The results suggest that the Urucurituba developed by headward migration across the Amazon delta; this is perhaps the first observation of estuarine distributary network development by headward channel erosion. The rate of Urucurituba Channel width increase has been ≈5m/month since 2011, increasing drainage capacity of the channel. We also collected in situ hydrodynamic measurements and analyzed 17 water quality parameters. Having 2011 as baseline, the flowrate of Araguari River has been diverted by up to 98% through Urucurituba Channel, with substantial changes in net discharge recorded at 3 monitoring stations. Statistically significant differences in water quality (p<0.05) were observed between 2011 and 2015, associated with the change in the flow pattern. Estuarine salinity and solids concentrations have increased. Overall, we demonstrate changes in landscape, hydrodynamics and water quality of the lower Araguari River