A sequential selection process in group decision making with a linguistic assessment approach
Information Sciences—Intelligent Systems: An International Journal
Critical success factors in implementing MRP and government assistance: a Singapore context
Information and Management
A model of consensus in group decision making under linguistic assessments
Fuzzy Sets and Systems
A rational consensus model in group decision making using linguistic assessments
Fuzzy Sets and Systems
A framework for identifying software project risks
Communications of the ACM
Linguistic decision analysis: steps for solving decision problems under linguistic information
Fuzzy Sets and Systems - Special issue on soft decision analysis
A multiple-case design methodology for studying MRP success and CSFs
Information and Management
A model-driven ERP Environment with search facilities
Data & Knowledge Engineering
The critical success factors for ERP implementation: an organizational fit perspective
Information and Management
A note on the internal consistency of various preference representations
Fuzzy Sets and Systems - Special issue: Soft decision analysis
ERP plans and decision-support benefits
Decision Support Systems
Incomplete linguistic preference relations and their fusion
Information Fusion
Expert Systems with Applications: An International Journal
A fuzzy model to evaluate the suitability of installing an enterprise resource planning system
Information Sciences: an International Journal
Critical factors for successful ERP implementation: Exploratory findings from four case studies
Computers in Industry - Special issue: Current trends in ERP implementations and utilisation
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This paper applies an analytic hierarchical prediction model based on the Multi-Criteria Decision Making with Incomplete Linguistic Preference Relations (InLinPreRa) to help the organizations become aware of the essential factors affecting the Enterprise Resource Planning (ERP), as well as identify the actions necessary before implementing ERP. The subjectivity and vagueness in the prediction procedures are dealt with linguistic variables quantified in an interval [-t, t]. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate ERP, inhibit adoption or take remedial actions to increase the success possibility of ERP. Pairwise comparisons are used to determine the priority weights of influential factors, and the possible occurrence ratings of success or failure outcome amongst decision makers. There are not any inconsistency occurred in this procedures because this proposed approach allows every decision expert to choose an explicit criterion or alternative for the without restriction. When there are n criteria in a decision matrix, only n-1 times of pairwise comparisons are taken. This approach not only improves the efficiency of pairwise comparison compared with the traditional AHP, but also avoids the checking the consistency of linguistic preference relation when the decision makers undertake the pairwise comparison processes.