Supply chain management (SCM) increasingly needs to address both climate change mitigation and adaptation issues. While mitigation aims at sustainability by reducing the environmental impact of supply chains (SCs), adaptation entails improving resilience by increasing the ability to cope with climate-induced disruptions. Although sustainable SCM (SSCM) and resilient SCM (RSCM) are of increasing importance, there has been little effort to conceptually connect SSCM and RSCM. Our study explores the interconnections between both concepts by outlining theoretical elements and conducting a case study of four companies in the automotive SC based on company documents and interviews. Results show that SSCM is prioritised
Emerging megacities in the global south face unprecedented transformation dynamics, manifested in rapid demographic, economic, and physical growth. Anticipating the associated sustainability and resilience challenges requires an understanding of future trajectories. Global change models provide consistent high-level urbanization scenarios. City-scale urban growth models accurately simulate complex physical growth. Modeling approaches linking the global and the local scale, however, are underdeveloped. This work introduces a novel approach to inform a local urban growth model by global Shared Socioeconomic Pathways to produce consistent maps of future urban expansion and population density via cellular automaton and dasymetric mapping. We demonstrate the approach for the case of Pune, India. Three scenarios are explored until 2050: business as usual (BAU), high, and low urbanization. After calibration and validation, the BAU scenario yields a 55% growth in Pune’s population and 90% in built-up extent, entailing significant impacts: Pune’s core city densifies further with up to 60,000 persons/km2, adding pressure to its strained infrastructure. In addition, 66–70% more residents are exposed to flood risk. Half of the urban expansion replaces agriculture, converting 167 km2 of land. The high-urbanization scenario intensifies these impacts. These results illustrate how spatially explicit scenario projections help identify impacts of urbanization and inform long-term planning.
Urbanization proceeds globally and is often driven by migration. Simultaneously, cities face severe exposure to environmental hazards such as floods and heatwaves posing threats to millions of urban households. Consequently, fostering urban households’ resilience is imperative, yet often impeded by the lack of its accurate assessment. We developed a structural equation model to quantify households’ resilience, considering their assets, housing, and health properties. Based on a household survey (n = 1872), we calculate the resilience of households in Pune, India with and without migration biography and compare different sub-groups. We further analyze how households are exposed to and affected by floods and heatwaves. Our results show that not migration as such but the type of migration, particularly, the residence zone at the migration destination (formal urban or slum) and migration origin (urban or rural) provide insights into households’ resilience and affectedness by extreme weather events. While on average, migrants in our study have higher resilience than non-migrants, the sub-group of rural migrants living in slums score significantly lower than the respective non-migrant cohort. Further characteristics of the migration biography such as migration distance, time since arrival at the destination, and the reasons for migration contribute to households’ resilience. Consequently, the opposing generalized notions in literature of migrants either as the least resilient group or as high performers, need to be overcome as our study shows that within one city, migrants are found both at the top and the bottom of the resilience range. Thus, we recommend that policymakers include migrants’ biographies when assessing their resilience and when designing resilience improvement interventions to help the least resilient migrant groups more effectively.
Liveability assessments of informal urban settlements are scarce. In India, a number of slum upgrading schemes have been implemented over the last decades aiming at better living conditions. However, these schemes rarely consider improvement in liveability as an explicit criterion, assuming that better physical conditions and the provision of basic services inevitably lead to better liveability. We use Fuzzy Cognitive Maps (FCMs) to analyse liveability in four different informal settlements in Pune (India). We compare the liveability by conducting semi-structured interviews with residents and by analysing them in individual and aggregated FCMs. Each settlement represents an archetypical form of the upgradation process: non-upgraded (base case), in-situ upgraded, relocated, and temporary resettlement. The FCMs show that the liveability indicators availability of community space, proximity to public transportation, feeling of belonging, and good relationship with neighbours and community are central elements of these neighbourhoods’ liveability. The results suggest that upgradation may lead to an improved overall liveability but can also reduce it if not designed properly. The fostering of community agency, an integration of the neighbourhood into the formal city fabric, and the maintaining of cohesion during the shift from horizontal to vertical living emerged as critical factors. To ensure sustainable integration of liveability considerations in slum upgrading schemes, we suggest using indicators well-adapted to the local context, co-created with local experts and stakeholders, as well as periodic post-occupancy liveability evaluations.
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