Analysing the factors affecting the selection of ERP package: a fuzzy AHP approach

Evaluating and Ranking of Critical Success Factors of Cloud Enterprise Resource Planning Adoption Using MCDM Approach

“…Quadri (2019) investigated the CSFs of Cloudbased E-Learning and employed AHP in the crisp and fuzzy environment for subsequent evaluating and ranking [15]. Nityesh (2021) Investigated and ranked several factors touching ERP adoption decision for SMEs, explicitly in the context of Indian market with the help of Fuzzy AHP method [19]. Fuzzy has also been used to create a framework for usability evaluation of different academic websites by classifying and prioritizing them [20].…”

“…The subsequent pair-wise comparisons yield n elements. A set of H matrices, 𝐴 ̌ℎ = {𝑞 ̌𝑖𝑗𝑘 }, where 𝐴 ̌𝑎 = 𝑞 ̌𝑖𝑗𝑎 = (𝑙 𝑖𝑗𝑘 , 𝑚 𝑖𝑗𝑘 , 𝑢 𝑖𝑗𝑘 ) represents the relative importance of element i to j, as derived by DM k. The aggregation may be obtained using Equation (19).…”

Critical success factor based resource allocation in ERP implementation: A nonlinear programming model

“…In this study, ERP implementation performance is defined from the system implementation point of view and evaluated as to whether the project is completed within time and budget limitations, and whether the adopted ERP system helps the SME achieve the required level of effectiveness ( Bhatt et al, 2021 ). A quantitative evaluation of the performance level is defined as the percentage of the organisation's target functional requirements met by the ERP implementation.…”

Construction of Credit Assessment Model for International Import and Export Trade Based on Fuzzy Hierarchical Analysis

“…It combines investment tools, capital markets, evaluation of investments, and opportunities to meet risk-reward and provides research on how investment practices and theories have been affected by globalization to provide a solid foundation for investment decisions. Bhatt et al [13] indicate that the problem of siting multiple facilities with capacity is a complex and imprecise decision problem that incorporates both quantitative and qualitative factors. Many objectives for optimizing multiple logistics networks are described in the literature: first, minimization objectives such as cost, inventory, transportation time, environmental impact, and financial risk; and second, maximization objectives such as profit, customer satisfaction, flexibility, and robustness.…”