The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
A closer look at the use of data envelopment analysis for technology selection
Computers and Industrial Engineering
Decision support for real-time telemarketing operations through Bayesian network learning
Decision Support Systems - Special issue: knowledge discovery and its applications to business decision making
Bayesian learning in negotiation
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
A fuzzy goal programming approach for vendor selection problem in a supply chain
Computers and Industrial Engineering
BBN-based software project risk management
Journal of Systems and Software - Special issue: Applications of statistics in software engineering
Supply chain diagnostics with dynamic Bayesian networks
Computers and Industrial Engineering
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
An intelligent supplier evaluation, selection and development system
Applied Soft Computing
Application of decision-making techniques in supplier selection: A systematic review of literature
Expert Systems with Applications: An International Journal
Integration of semi-fuzzy SVDD and CC-Rule method for supplier selection
Expert Systems with Applications: An International Journal
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In this study, we analyze the supplier selection process by combining Bayesian Networks (BN) and Total Cost of Ownership (TCO) methods. The proposed approach aims to efficiently incorporate and exploit the buyer's domain-specific information when the buyer has both limited and uncertain information regarding the supplier. This study examines uncertainty from a total cost perspective, with regards to causes of supplier performance and capability on buyer's organization. The proposed approach is assessed and tested in automotive industry for tier-1 supplier for selecting its own suppliers. To efficiently facilitate expert opinions, we form factors to represent and explain various supplier selection criteria and to reduce complexity. The case study in automotive industry shows several advantages of the proposed method. A BN approach facilitates a more insightful evaluation and selection of alternatives given its semantics for decision making. The buyer can also make an accurate cost estimation that are specifically linked with suppliers' performance. Both buyer and supplier have clear vision to reduce costs and to improve the relations.