Title: Blending enterprise resource planning on supply chain management in the aerospace sector in India and analysis using multi-scale adaptive dilated convolutional LSTM

Authors: Joydeep Banerjee; Santanu Kumar Das

Addresses: School of Management Studies, GIET University, Gunupur, Odisha, India; Wing Structural Group, Hindustan Aeronautics Limited, Bengaluru, Karnataka, India ' Post-Graduation Department of Management Studies, Gandhi Global Business Studies, 761008, Odisha, Berhampur, Odisha, India; Affiliated to: BPUT, India

Abstract: Aerospace organisations, which have already executed enterprise resource management (ERP) tools along with the supply chain management (SCM) models are considered in this research work. At first, information is gathered from these organisations as a form of structured questions. These questions are then evaluated using relevant statistical methods to obtain the necessary goal. After that, the distribution of the questions to the authorised parties of these organisations is done. The authorities of these industries are requested provide information asked more precisely. At the final stage, the effectiveness of integrating the SCM with ERP is validated with the help of multi-scale adaptive dilated convolutional long-short-term memory (MADC-LSTM). The optimisation of the MADC-LSTM network's parameters is carried out by Golden Eagle with bee collecting pollen optimisation algorithm (GE-BCPOA). The effectiveness of integrating SCM with the ERP is analysed by conducting diverse experiments.

Keywords: enterprise resource planning; ERP; supply chain management; SCM; aerospace sector in India; statistical approach; multi-scale; adaptive dilated; convolutional long short-term memory; Golden eagle; bee collecting pollen optimisation algorithm; India.

DOI: 10.1504/IJBCRM.2025.144952

International Journal of Business Continuity and Risk Management, 2025 Vol.15 No.1, pp.63 - 94

Received: 26 Sep 2023
Accepted: 23 Apr 2024
Published online: 13 Mar 2025 *

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