Fuzzy Consensus Model for Governance in Smart Service Systems

Procedia Manufacturing

Volumn 3, Issue , 2015, Pages 3567-3574

  Calza, Francesco ^a   Gaeta, Matteo ^b   Loia, Vincenzo ^b   Orciuoli, Francesco ^b   Piciocchi, Paolo ^b   Rarità, Luigi ^b   Spohrer, James ^c   Tommasetti, Aurelio ^b  

^a UNIVERSITY OF NAPLES PARTHENOPE   (Italy)

^b UNIVERSITY OF SALERNO   (Italy)

^c IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

Fuzzy consensus model; Group decision making; Service science; Smart service systems

Indexed keywords

EID: 84979958614     PISSN: None     EISSN: 23519789     Source Type: Conference Proceeding    
DOI: 10.1016/j.promfg.2015.07.715     Document Type: Conference Paper

References (25)

1. [1] Alter, S., Service System Fundamentals: Work System, Value Chain, and Life Cycle, IBM Systems Journal. 47:1 (2008), 71–85.
2. [2] Barile, S., Polese, F., Smart Service Systems and Viable Service Systems: Applying Systems Theory to Service Science Service Science 2:1–2 (2010), 21–40.
3. [3] Cabrerizo, F.J., Moreno, J.M., Pèrez, I.J., Herrera-Viedma, E., Analyzing consensus approaches in fuzzy group decision making: Advantages and drawbacks Soft Comput. 14:5 (2010), 451–463.
4. [4] Cabrerizo, F.J., Ureña, R., Pedrycz, W., Herrera-Viedma, E., Building consensus in group decision making with an allocation of information granularity Fuzzy Sets and Systems. 255 (2014), 115–127.
5. [5] Capuano, N., Gaeta, M., Orciuoli, F., Ritrovato, P., Semantic Web Fostering Enterprise 2.0 Proceedings of 2010 International Conference on Complex Intelligent Software Intensive Systems, 2010, 1087–1092.
6. [6] Chiclana, F., Herrera-Viedma, E., Herrera, F., Alonso, S., Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations Eur. J. Oper. Res. 182:1 (2007), 383–399.
7. [7] D'Aniello, G., Loia, V., Orciuoli, F., A Multi-Agent Fuzzy Consensus Model in a Situation Awareness Framework Applied Soft Computing. 30 (2014), 430–440.
8. [8] M. De Santo, A. Pietrosanto, P. Napoletano, L. Carrubbo, Knowledge Based Service Systems, in: Book of Abstracts of the 2011 Naples Forum on System theory and Service Science: Integrating three perspectives in a new service agenda, Capri, Napoli. 1, 2011, pp. 24-39.
9. [9] Edvardsson, B., Gustafsson, A., Enquist, B., Success Factors in New Service Development and Value Creation through Services, in: Advances in Service Innovation, Springer, 2007, 165–183.
10. [10] Gaeta, A., Gaeta, M., Piciocchi, P., Vollero, A., Ritrovato, P., Exploiting semantic models and techniques to evaluate relevance of human resources in Knowledge intensive organizations, in: Proceedings of 8th International Conference on Signal Image Technology and Internet Based Systems, 2012, 960–966.
11. [11] Gaeta, M., Loia, V., Tomasiello, S., Multisignal 1-D compression by F-transform for wireless sensor networks applications Applied Soft Computing. 30 (2014), 329–340.
12. [12] Loia, V., Senatore, S., A fuzzy-oriented semantic analysis to capture the human emotion in Web-based content Knowledge-based systems. 58 (2014), 75–85.
13. [13] Herrera-Viedma, E., Chiclana, F., Herrera, F., Alonso, S., Group decision-making model with incomplete fuzzy preference relations based on additive consistency, IEEE Trans. Syst. Man Cybern. Part B Cybern. 37 (2007), 176–189.
14. [14] Maglio, P.P., Spohrer, J., Fundamentals of service science Journal of the Academy of Marketing Science. 36:1 (2008), 18–20.
15. [15] C. Mele, F. Polese, Key dimensions of Service Systems: Interaction in social and technological networks to foster value co-creation, in: Demirkan, H., Spohrer, J., Krishna V. (Eds.). The Science of Service Systems, Springer, 2010, pp. 37-59.
16. [16] A. G. Nilson, Enterprise Systems in a Service Science Context, in: W.W. Song et al. (Eds.), Information Systems Development, Springer Science+Business Media, 2011, pp.15-26.
17. [17] Pèrez, I.J., Cabrerizo, F.J., Alonso, S., Herrera-Viedma, E., A New Consensus Model for Group Decision Making Problems With Non-Homogeneous Experts, IEEE Transactions on Systems Man, and Cybernetics Systems. 44:4 (2004), 494–498.
18. [18] Piciocchi, P., Spohrer, J., Bassano, C., Giuiusa, A., Smart Governance to Mediate Human Expectations and Systems Context Interactions, in: Freund L.E Advances in Human Side of Service Engineering, CRC Press Taylor and Francis Group, 2012, 319–328.
19. [19] Spohrer, J., Anderson, L., Pass, N., Ager, T., Service Science and Service Dominant Logic, in: Otago Forum 2, 2008, 4–18.
20. [20] Spohrer, J., Maglio, P.P., Bailey, J., Gruhl, D., Steps Toward a Science of Service Systems IEEE Computer. 40:1 (2007), 71–77.
21. [21] J. Spohrer, P. Piciocchi, C. Bassano, Three frameworks for service research: exploring multilevel governance in nested, networked systems, Service Science. 4(2) 147—160.
22. [22] J. Spohrer, S.L. Vargo, P.P. Maglio, N. Caswell, The service system is the basic abstraction of service science, in: Proceedings of the 41st Hawaii International Conference on System Sciences (2008).
23. [23] Tommasetti, A., Festa, G., An Analysis of Wine Tourism in Italy from a Strategic Service-Based Perspective Service Science. 6 (2014), 122–135.
24. [24] O. E. Williamson, The Mechanisms of Governance, Oxford University Press, New York, 1996.
25. [25] Yager, R.R., Weighted maximum entropy owa aggregation with applications to decision making under risk, IEEE Trans. Syst. Man, Cybern., A Syst. Humans. 39:3 (2009), 555–564.