Marketing

Multiple-criteria decision analysis

Process (computing)

Engineering

Procurement

Pure mathematics

Data envelopment analysis

Computer security

Field (mathematics)

Operating system

Selection (genetic algorithm)

Economics

Transparency (behavior)

Data mining

Computer science

Mathematical optimization

Risk analysis (engineering)

Management science

Business

Ranking (information retrieval)

Operations research

Process management

Analytic hierarchy process

Mathematics

Operations management

Artificial intelligence

Decision support system

Call for bids

Applied Soft Computing

Multi-Criteria Decision Making (MCDM) techniques are mathematical tools that help decision makers evaluating and ranking in an automatic way many possible alternatives over multiple conflicting criteria in highly complex situations. Several MCDM approaches exist, and their application fields are numerous, including the Supplier Selection Problem (SSP), which is an important problem in the management field. The aim of this paper is to perform a comparative analysis among some selected well-known MCDM techniques to show how they can properly support the specific decision making process of Public Procurement (PP) tenders, which is a particular type of the SSP, characterized by very stringent rules, thus requiring a specific assessment. Indeed, PP is a field characterized by the need for transparency, objectivity, and non-discrimination, which requires tendering organizations to explicitly state the adopted awarding method, the chosen decision criteria, and their relative importance in the call for proposals. However, this field has been seldomly investigated in the pertinent literature and thus the aim of this paper is to overcome such a limitation. In particular, this work focuses on the most commonly adopted methods in the field of supplier selection, namely the Analytic Hierarchy Process (AHP), the Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), the Multi Attribute Utility Theory (MAUT), and the Data Envelopment Analysis (DEA). First, we adapt these techniques to the PP problem and its requirements. Then, by means of some real tenders at a European Institution, the selected techniques are compared with each other and with the currently adopted methodology in their classical deterministic setting, to identify which method best suits the specific requirements of PP tenders. Hence, since nowadays uncertainty is inherent in data from real applications, and can be modelled by expert evaluations through fuzzy logic, the comparison is extended to the fuzzy counterparts of two of the most promising selected approaches, i.e., the Fuzzy AHP and the Fuzzy DEA, showing that these methods can be effectively applied to the PP sector also in the presence of uncertainty on the tenders data.

Multi-Criteria Decision Making techniques for the management of public procurement tenders: A case study