The agricultural industry is highly underdeveloped and requires transformation in technology for food safety and reliability. A digital world is relying on blockchain technology for the successful implementation of sustainable e-agricultural supply chain management (e-Agri-SCM). In current advancements of blockchain in digital marketing, product website design (web design) is essential to streamline the requirements of the customer and the expectations of supply chain partners. The current research has incorporated the blockchain effect by web design elements into the agricultural supply chain management (Agri-SCM) study. In addition, partners in the digital marketing supply chain (DM-SCM) are also facing issues to identify significant web design elements-based blockchain technology to gain maximum profit. Therefore, a cooperative (Co-op) sustainable e-agricultural SCM model is developed in this study by considering the web design index and variable demand to decide shipments, selling price, cycle time, and advertisement cost for agriculture products. The uncertainties in the model due to intangible web design elements and basic costs are dealt with by the application of the fuzzy system whereas carbon emission is also considered for providing cleaner production. A real-time application of the proposed model is done by undertaking five different cases based on mutual share, demand curve, and advertisement budget among participants. The sensitivity analysis is also performed to identify important factors of the total profit. Findings of this work include significant web design elements (WDEs) i.e., web graphics, search engine optimization, cyber-security, fast loading, and navigation, as essentials for digital marketing to convince customers towards the product in a global SCM. The numerical results and managerial insights are advantageous for managers to get maximum profit by cooperative and digital marketing strategies to attain e-Agri-SCM.

Nowadays, many industries are focusing on automation in manufacturing for high production and good quality to meet the needs of customers in a short period of time. This trend has produced a forward shift in technology in the form of advancement, which ultimately increases energy demand. For that reason, researchers have started working on sustainable development associated with cleaner-energy policies to avoid increasing energy consumption for enhanced manufacturing technology in developed countries. The other important issue affecting our world is global warming, which is the result of greenhouse gas emissions. That is the reason, renewable energies like solar energy have dramatically increased during recent years to compensate for the energy demand and reduced carbon footprint for cleaner production. This paper considers a supply chain management of automobile part manufacturing industry with suppliers to optimize the production quantity with multiple objectives i.e., minimizing the total cost of production including minimum quantity lubrication is a first objective, reduction of the carbon footprint is the second, and minimizing the cost of energy considering renewable energy is the last objective. This study considers a situation, where imperfect quality items are managed and controlled by the suppliers as outsourcing operations. A weighted goal programming methodology is utilized to solve the proposed mathematical model including sustainable suppliers. Sensitivity analysis of the model is performed for different scenarios with respect to the energy utilization. The optimal result of minimum production cost and carbon emissions is the evidence of successful pragmatic application in automobile industry. The results validate the model to provide the basis for sustainability in supply chain environment considering manufacturer and suppliers.

The management of a controllable production in the manufacturing system is essential to achieve viable advantages, particularly during emergency conditions. Disasters, either man-made or natural, affect production and supply chains negatively with perilous effects. On the other hand, flexibility and resilience to manage the perpetuated risks in a manufacturing system are vital for achieving a controllable production rate. Still, these performances are strongly dependent on the multi-criteria decision making in the working environment with the policies launched during the crisis. Undoubtedly, health stability in a society generates ripple effects in the supply chain due to high demand fluctuation, likewise due to the Coronavirus disease-2019 (COVID-19) pandemic. Incorporation of dependent demand factors to manage the risk from uncertainty during this pandemic has been a challenge to achieve a viable profit for the supply chain partners. A non-linear supply chain management model is developed with a controllable production rate to provide an economic benefit to the manufacturing firm in terms of the optimized total cost of production and to deal with the different situations under variable demand. The costs in the model are set as fuzzy to cope up with the uncertain conditions created by lasting pandemic. A numerical experiment is performed by utilizing the data set of the multi-stage manufacturing firm. The optimal results provide support for the industrial managers based on the proactive plan by the optimal utilization of the resources and controllable production rate to cope with the emergencies in a pandemic.