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Autor
Zhong Hao (PRISM Center & School of IE), Levalle Rodrigo Reyes (PRISM Center & School of IE), Moghaddam Mohsen (PRISM Center & School of IE), Nof Shimon Y. (PRISM Center & School of IE)
Tytuł
Collaborative Intelligence - Definition and Measured Impacts on Internetworked e-Work
Źródło
Management and Production Engineering Review, 2015, vol. 6, nr 1, s. 67-78, rys., tab., bibliogr. 33 poz.
Słowa kluczowe
Współpraca, Współpraca przedsiębiorstw, Zarządzanie
Cooperation, Enterprises cooperation, Management
Uwagi
summ.
Abstrakt
Internetworked e-Work is enabling new channels in cyber space for collaboration among physical and cyber agents, e.g., humans, robots, software agents. Research on Collaborative Control Theory (CCT) indicates that building and augmenting the Collaborative Intelligence (CI) of participants in cyber-physical networks can provide better support for achieving their individual and common goals. In spite of its rising significance and popularity, however, no clear and precise definition and universal quantitative measure has been proposed for the CI. In this article, we first formalize the CI by suggesting a formal definition, based on the definitions of its elements - collaboration and intelligence. We then propose a quantitative measure for the CI, adapted from the universal intelligence measure. For illustration, we analyze three recent collaborative e-Work studies at three different scales: (1) Telerobotenabled computer supported collaborative design; (2) Collaborative product line control in supply networks; (3) Demand and capacity sharing in multi-enterprise collaboration. From these case studies, common advantages such as work efficiency, network robustness and stability, service level, resource utilization, and collaboration cost are observed, analyzed, and translated into formal CI measures. Results indicate significant impacts of CI on the efficiency, effectiveness, and quality of collaborative activities in emerging e-Work networks. (original abstract)
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Bibliografia
Pokaż
  1. Nof S.Y., Ceroni J., Jeong W., Moghaddam M., Revolutionizing Collaboration through e-Work, e-Business, and e- Service, Springer Series in ACES, Automation, Collaboration, & E-Service, in press, 2015.
  2. Nowak M.A., Five rules for the evolution of cooperation, Science, 8, 314 (5805), 1560-3, 2006.
  3. Nof S.Y., Collaborative control theory for e-Work, e-Production, and e-Service, Annual Reviews in Control, 31, 2, 281-292, 2007.
  4. Nof S.Y., Design of effective e-Work: review of models, tools, and emerging challenges, Production Planning & Control, 14, 8, 681-703, 2003.
  5. Nof S.Y., Morel G., Monostori L., Molina A., Filip F., From Plant and Logistics Control to Multi-Enterprise Collaboration, Annual Reviews in Control, 30, 55-68, 2006.
  6. Chituc C.M., Nof S.Y., The join/leave/remain (JLR) decision in collaborative networked organizations, Computers and Industrial Engineering, 53, 1, 173-195, 2007.
  7. Devadasan P., Zhong H., Nof S.Y., Collaborative intelligence in knowledge based service planning, Expert Systems with Applications, 40, 17, 6778-6787, 2013.
  8. Elrod P.D., Tippet D.D., An empirical study of the relationship between team performance and team maturity, IEEE Engineering Management Review, 36, 1, 52, 2008.
  9. Zhu X., Goldberg A.B., Introduction to semisupervised learning, Morgan & Claypool, 2009.
  10. Pinto M.B., Pinto J.K., Project team communication and cross-functional cooperation in new program development, Journal of Product Innovation Management, 7, 200-212, 1990.
  11. Nguyen N.T., Inconsistency of knowledge and collective intelligence, Cybernetics and Systems, 39, 6, 542-562, 2008.
  12. Devadasan P., Collaborative intelligence measure for knowledge based service industry, MS Thesis, School of Industrial Engineering, Purdue University, 2011.
  13. Zhao X., Atkins D., Transshipment between competing retailers, IIE Transactions, 41, 8, 665-676, 2009.
  14. Nof S.Y., Information and Collaboration Models of Integration, Kluwer, Dordrecht, 1994.
  15. Camarinha-Matos L.M., Afsarmanesh H., Collaborative networks: Value creation in a knowledge society, Proc. PROLAMAT 2006, IFIP Int. Conf. Knowl. Enterp. - New Challenges, Shanghai, 2006.
  16. Bingham W.V., Aptitudes and aptitude testing, New York: Harper & Brothers, 1937.
  17. Sternberg R.J. (Ed.), Handbook of intelligence, Cambridge University Press, 2000.
  18. Wechsler D., The measurement and appraisal of adult intelligence (4 ed.), Baltimore, Williams & Wilkinds, 1958.
  19. Slatter J., Assessment of children: Cognitive applications (4th ed.), San Diego, Jermone M. Satler Publisher Inc., 2001.
  20. Simonton D.K., An interview with Dr. Simonton, In Human intelligence: Historical influences, current controversies, teaching resources, J.A. Plucker [Ed.], 2003.
  21. Legg S., Hutter M., Universal intelligence: A definition of machine intelligence, Minds and Machines, 17, 4, 391-444, 2007.
  22. Sutton R., Barto A., Reinforcement learning: An introduction, MIT Press, Cambridge, 1998.
  23. Legg S., Vennes J., An Approximation of the Universal Intelligence Measure. Algorithmic Probability and Friends, Bayesian Prediction and Artificial Intelligence Lecture Notes in Computer Science, 7070, 236-249, 2013.
  24. Zhong H.,Wachs J.P., Nof S.Y., A collaborative telerobotics network framework with hand gesture interface and conflict prevention, International Journal of Production Research, 51, 15, 4443-4463, 2013.
  25. Zhong H., Wachs J.P., Nof S.Y., Telerobot-enabled HUB-CI model for collaborative lifecycle management of design and prototyping, Computers in Industry, 65, 4, 550-562, 2014.
  26. Huang C.-Y., Nof S.Y., Evaluation of agent-based manufacturing systems based on a parallel simulator, Computers & Industrial Engineering, 43, 3, 529-52, 2002.
  27. Jeong W., Nof S.Y., Performance evaluation of wireless sensor network protocols for industrial applications, Journal of Intelligent Manufacturing, 19, 335-345, 2008.
  28. Ponomarov S.Y., Holcomb M.C., Understanding the concept of supply chain resilience, International Journal of Logistics Management, 20, 1, 124-143, 2009.
  29. Sterbenz J.P.G., Cetinkaya E.K., Hameed M.A., Jabbar A., Qian S., Rohrer J.P., Evaluation of network resilience, survivability, and disruption tolerance: analysis, topology generation, simulation, and experimentation, Telecommunication Systems, 52, 2, 1-32, 2011.
  30. Nair A., Vidal J.M., Supply network topology and robustness against disruptions - An investigation using multi-agent model, International Journal of Production Research, 49, 5, 1391-1404, 2011.
  31. Adenso-Diaz B., Mena C., Garcia-Carbajal S., Liechty M., The impact of supply network characteristics on reliability, Supply Chain Management, 17, 3, 263-276, 2012.
  32. Reyes Levalle R., Scavarda M., Nof S.Y., Collaborative production line control: Minimisation of throughput variability and WIP, International Journal of Production Research, 51, 23 -24, 7289-7307, 2013.
  33. Moghaddam M., Nof S.Y., Combined demand and capacity sharing with best matching decisions in enterprise collaboration, International Journal of Production Economics, 148, 93-109, 2014.
Cytowane przez
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ISSN
2080-8208
Język
eng
URI / DOI
http://dx.doi.org/10.1515/mper-2015-0009
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