The current business scenario is characterized by several important factors; among them, the necessity to shrink the time-to-market of new products and services, the need to focus on promising ideas since the early design phases of new solutions, and the involvement of a high number of actors with different perspectives. The latter factor, in particular, underpins the fact that an increasing number of decisions require the participation of multiple stakeholders that frequently have conflicting aims and interests. These factors contribute to increase the complexity of new solutions management. This is even more emphasised in services, especially during the early stages of the engineering process when a new service has to be evaluated and selected with limited support from the available information. Further, the presence of multiple decision makers exacerbates the issues, rendering difficult the attainment of an objective, consensus-based decision. To address this issue, Multi-Criteria Decision-Making (MCDM) methods hold a crucial role in supporting decisions making processes. This paper proposes a comparison of two methods based on an empirical test in order to identify the most suitable and user-friendly to be adopted by heterogeneous engineering teams to make decisions in the field of services. The first, developed in the engineering field, is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) while the second is a “Condorcet winner” based method rooted in voting system theory, which traditionally has been used in social science. The comparison is meant at understanding what method best reflect the preferences of the participants.

(2018). Comparison between the TOPSIS method and a “Condorcet winner” based voting method for the evaluation and selection of new services . In ...SUMMER SCHOOL FRANCESCO TURCO. PROCEEDINGS. Retrieved from http://hdl.handle.net/10446/132122

Comparison between the TOPSIS method and a “Condorcet winner” based voting method for the evaluation and selection of new services

Rondini, A.;Lagorio, A.;Pezzotta, G.;Pinto, R.
2018-01-01

Abstract

The current business scenario is characterized by several important factors; among them, the necessity to shrink the time-to-market of new products and services, the need to focus on promising ideas since the early design phases of new solutions, and the involvement of a high number of actors with different perspectives. The latter factor, in particular, underpins the fact that an increasing number of decisions require the participation of multiple stakeholders that frequently have conflicting aims and interests. These factors contribute to increase the complexity of new solutions management. This is even more emphasised in services, especially during the early stages of the engineering process when a new service has to be evaluated and selected with limited support from the available information. Further, the presence of multiple decision makers exacerbates the issues, rendering difficult the attainment of an objective, consensus-based decision. To address this issue, Multi-Criteria Decision-Making (MCDM) methods hold a crucial role in supporting decisions making processes. This paper proposes a comparison of two methods based on an empirical test in order to identify the most suitable and user-friendly to be adopted by heterogeneous engineering teams to make decisions in the field of services. The first, developed in the engineering field, is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) while the second is a “Condorcet winner” based method rooted in voting system theory, which traditionally has been used in social science. The comparison is meant at understanding what method best reflect the preferences of the participants.
2018
Rondini, Alice; Lagorio, Alexandra; Pezzotta, Giuditta; Pinto, Roberto
File allegato/i alla scheda:
File Dimensione del file Formato  
Comparison between the TOPSIS method.pdf

accesso aperto

Versione: publisher's version - versione editoriale
Licenza: Licenza default Aisberg
Dimensione del file 549.74 kB
Formato Adobe PDF
549.74 kB Adobe PDF Visualizza/Apri
TOC 2018.pdf

accesso aperto

Versione: publisher's version - versione editoriale
Licenza: Licenza default Aisberg
Dimensione del file 117.14 kB
Formato Adobe PDF
117.14 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/132122
Citazioni
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact