TY - JOUR
T1 - Modelling and analyzing the GHG emissions in the VUCA world: Evidence from tomato production in Morocco
AU - Hathat, Zakaria El
AU - Sreedharan, V. Raja
AU - Venkatesh, V.G.
AU - Zouadi, Tarik
AU - Arunmozhi, Manimuthu
AU - Shi, Yangyan
PY - 2023/1/1
Y1 - 2023/1/1
N2 - As the world is driving towards climate change, customers are concerned over the issues around greenhouse gas (GHG) emissions and energy consumption in production cycles. Business leaders and governments are eager to reduce emissions through specific strategies. The production literature also discusses comprehensive tracking of emissions during supply chain operations. The study focuses on offsetting carbon emissions in the food supply chain in Morocco. To complete this objective, the study follows the PAS 2050 protocol in mapping the food supply chain and agricultural production process to measure the environmental impact. Based on this, the study analyzed) three different phases of tomato production in Morocco (Cradle to the gate such as cultivation, harvesting, transport, and shipping using machine learning-based prediction models (MLPMs). The analysis offered insights into GHG emissions in tomato production cycles and developed a plan for carbon offsetting. The study also proposed a novel decision-making approach using MLPMs and an information dashboard, which can monitor the carbon footprint and provide a new way of exploring carbon neutrality. Finally, the study proposed a decision-making approach for sustainable production by integrating satellite images for supply chain practitioners.
AB - As the world is driving towards climate change, customers are concerned over the issues around greenhouse gas (GHG) emissions and energy consumption in production cycles. Business leaders and governments are eager to reduce emissions through specific strategies. The production literature also discusses comprehensive tracking of emissions during supply chain operations. The study focuses on offsetting carbon emissions in the food supply chain in Morocco. To complete this objective, the study follows the PAS 2050 protocol in mapping the food supply chain and agricultural production process to measure the environmental impact. Based on this, the study analyzed) three different phases of tomato production in Morocco (Cradle to the gate such as cultivation, harvesting, transport, and shipping using machine learning-based prediction models (MLPMs). The analysis offered insights into GHG emissions in tomato production cycles and developed a plan for carbon offsetting. The study also proposed a novel decision-making approach using MLPMs and an information dashboard, which can monitor the carbon footprint and provide a new way of exploring carbon neutrality. Finally, the study proposed a decision-making approach for sustainable production by integrating satellite images for supply chain practitioners.
KW - Carbon neutrality.
KW - Carbon offsetting
KW - Greenhouse gas emission
KW - VUCA world
UR - https://doi.org/10.1016/j.jclepro.2022.134862
UR - http://www.scopus.com/inward/record.url?scp=85143318268&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2022.134862
DO - 10.1016/j.jclepro.2022.134862
M3 - Article
SN - 0959-6526
VL - 382
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 134862
ER -