Information aggregation in industrial performance measurement: Rationales, issues and definitions

International Journal of Production Research

Volumn 42, Issue 20, 2004, Pages 4271-4293

  Berrah, L ^a   Mauris, G ^a   Vernadat, F ^b  

^a Université de Savoie   (France)

^b UNIVERSITÉ DE LORRAINE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL SYSTEMS; DECISION MAKING; FINANCE; FUZZY CONTROL; MATHEMATICAL MODELS; PERFORMANCE;

IMPROVEMENT CONTROL; INDUSTRIAL PERFORMANCE; LINEAR OPERATORS; PROFITS;

PRODUCTION ENGINEERING;

EID: 13644273266     PISSN: 00207543     EISSN: None     Source Type: Journal    
DOI: 10.1080/00207540410001716534     Document Type: Article

References (56)

1. ATKINSON, A., 1998, Strategic performance measurement and incentive compensation. European Management Journal, 16, 552-561.
2. AZZONE, G. and RANGONE, A., 1996, Measuring manufacturing performance: a fuzzy approach. International Journal of Production Research, 34, 2517-2532.
3. BARBER, S., HAMMOND, P. and SEIDL, C., 1999, Handbook of Utility Theories (Boston: Kluwer).
4. BERRAH, L., CLIVILLE, V., HARZALLAH, M., HAURAT, A. and VERNADAT, F., 2001, A cyclic enterprise reengineering method. In Proceedings of the International Conference on Engineering Design and Automation (EDA'01), Las Vegas, NV, USA, 5-8 August 2001 [CD-ROM].
5. BERRAH, L., MAURIS, G. and FOULLOY, L., 2003, The aggregation of industrial performance information by the Choquet fuzzy integral. In L. Reznik and V. Kreinovich (eds), Soft Computing in Measurement and Information Acquisition (Berlin: Physica), pp. 121-135.
6. BERRAH, L., MAURIS, G., FOULLOY, L. and HAURAT, A., 2000, Global vision and performance indicators for an industrial improvement approach. Computers in Industry, 43, 211-225.
7. BITITCI, U. S., 1995, Modelling of performance measurement systems in manufacturing enterprises. International Journal of Production Economics, 42, 137-147.
8. BLOCH, I., 1996, Information combination operators for data fusion: a comparative review with classification. IEEE Transactions on Systems, Man, Cybernetics, Part A, 26, 52-67.
9. BORGELT, C. and KRUSE, R., 2002, Methods for Data Analysis and Mining (New York: Wiley).
10. BRADFORD, J. and CHILDE, S. J., 2001, A non-linear redesign methodology for manufacturing systems in SMEs. In Proceedings of the International Conference on Stimulating Manufacturing Excellence in Small and Medium Enterprises (SMESME'01), Aalborg, Denmark, 14-16 May 2001, pp. 52-59.
11. BROWNE, J., DEVLIN, J., ROLSTADAS, A. and ANDERSEN, B., 1997, Performance measurement: the ENAPS approach. International Journal of Business Transformation, 69, 73-84.
12. CHA, Y. and JUNG, M., 2003, Satisfaction assessment of multi-objective schedules using neural fuzzy methodology. International Journal of Production Research, 41, 1831-1849.
13. CHANDLER, A. C., 1988, The Visible Hand, The Managerial Revolution in American Business (Cambridge: Belknap).
14. CROSS, K. F. and LYNCH, R. L., 1989, The SMART way to define and sustain success. National Productivity Review, 8, 23-33.
15. DASARATHY, B. V., 1997, Sensor fusion potential exploitation: innovative architectures and illustrative applications. Proceedings of the IEEE, 85, 24-38.
16. DASARATHY, B. V., 2001, Information fusion: what, where, why, when and how. International Journal of Information Fusion, 2, 75-76.
17. DE TONI, A., NASSIMBENI, G. and TONCHIA, S., 1997, An integrated production performance measurement system. Industrial Management and Data Systems, 97, 180-186.
18. DEMING, E. W., 1982, Quality, Productivity and Competitive Position (Cambridge, MA: MIT Press).
19. DOUMEINGTS, G., 1997, ECOGRAI - a method to design and implement performance indicators systems for industrial organizations. Internal Report, LAP/GRAI, Bordeaux, France.
20. DUBOIS, D. and PRADE, H., 1988, Possibility Theory: An Approach to Computerized Processing of Uncertainty (New York: Plenum).
21. DUCQ, Y., VALLESPIR, B. and DOUMEINGTS, G., 2001, Coherence analysis methods for production systems by performance aggregation. International Journal of Production Economics, 69, 23-37.
22. FITZGERALD, L., JOHNSTON, R., BRIGNALL, T. J., SILVESTRO, R. and Voss, C., 1991, Performance Measurement in Service Industry (London: CIMA).
23. FORTUIN, L., 1988, Performance indicators - why, where and how. European Journal of Operational Research, 34, 1-8.
24. GHALAYINI, A. M., NOBLE, J. S. and CROWE, T. J., 1997, An integrated dynamic performance measurement system for improving manufacturing competitiveness. International Journal of Operations and Production Management, 15, 80-116.
25. GLOBERSON, S., 1985, Issues in developing a performance criteria system for an organisation. International Journal of Production Research, 23, 639-646.
26. GRABISCH, M., 1995, On equivalence classes of fuzzy connectives - the case of fuzzy integrals. IEEE Transactions on Fuzzy Systems, 3, 96-109.
27. GRABISCH, M. and ROUBENS, M., 2000, Application of the Choquet integral in multi-criteria decision making. In M. Grabisch, T. Murofushi and M. Sugeno (eds), Fuzzy Measures and Integrals: Theory and Applications (New York: Physica), pp. 348-374.
28. GRABOT, B., 1998, Objective satisfaction assessment using neural nets for balancing multiple objectives. International Journal of Production Research, 36, 2377-2395.
29. GRABOT, B., BLANC, J. C. and BINDA, C., 1996, A decision support system for production activity control. Decision Support Systems, 16, 87-101.
30. HALL, D. L., 1992, Mathematical Techniques in Multi-sensor Data Fusion (Norwood: Artech House).
31. HWANG, C. L. and YOON, K., 1981, Multiple Attribute Decision Making Methods and Applications (Berlin: Springer).
32. JONSSON, P. and LESSHAMMAR, M., 1999, Evaluation and improvement of manufacturing performance measurement systems -the role of OEE. International Journal of Operations and Production Management, 19, 55-78.
33. KAPLAN, R. S. and NORTON, D. P., 1992, The balanced scorecard - measures that drive performance. Harvard Business Review, January/February, 71-79.
34. KEEGAN, D. P., EILER, R. G. and JONES, C. R., 1989, Are your performance measures obsolete? Management Accounting, June, 45-50.
35. KENDALL, M. and STUART, A., 1977, The Advanced Theory of Statistics (New York: Griffin).
36. KIM, G., PARK, C. S. and YOON, K. P., 1997, Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance measurement. International Journal of Production Economics, 50, 23-33.
37. KRANTZ, D. H., LUCE, R. D., SUPPES, P. and TVERSKY, A., 1971, A Foundation of Measurement (New York: Academic Press).
38. KRAUSE, O. and MERTINS, K., 1999, Performance management. In Proceedings of the International Conference on Advances in Production Management Systems, 6-10 September 1999, Berlin, Germany, pp. 243-251.
39. KUENO, P. and KHRAN, A. J. W., 1999, Building a process performance measurement system: some early experiences. Journal of Scientific and Industrial Research, 58, 149-159.
40. LABREUCHE, C. and GRABISCH, M., 2003, The Choquet integral for the aggregation of interval scales in multi-criteria decision making. Fuzzy Sets and Systems, 137, 11-26.
41. LE CLAINCHE, J. F., 2001, Balance scorecards et autres méthodes pour évaluer le score d'une entreprise. In C. Bonnefous and A. Courtois (eds), Indicateurs de Performance (Paris: Hermés), pp. 257-281.
42. LEBAS, M. J., 1995, Performance measurement and performance management. International Journal of Production Economies, 41, 23-35.
43. NEELY, A., 1999, The performance revolution: why now and what next? International Journal of Operations and Production Management, 19, 205-228.
44. NEELY, A., GREGORY, M. and PLATTS, K., 1995, Performance measurement system design: a literature review and research agenda. International Journal of Operations Production Management, 15, 80-116.
45. NEELY, A. D., ADAMS, C. and CROWE, P., 2001, The performance prism in practice. Measuring Business Excellence, 5, 6-12.
46. NEELY, A. D., RICHARDS, A. H., MILLS, J. F., PLATTS, K. W. and BOURNE, M. C. S., 1997, Designing performance measures: a structured approach. International Journal of Operations and Production Management, 17, 1131-1152.
47. RANGONE, A., 1996, An analytical hierarchy process framework for comparing the overall performance of manufacturing departments. International Journal of Operations and Production Management, 16, 104-119.
48. SAATY, T. L., 1980, The Analytic Hierarchy Process (New York: McGraw-Hill).
49. SANTOS, S. P., BELTON, V. and HOWICK, S. 2002, Adding value to performance measurement by using system dynamics and multi-criteria analysis. International Journal of Operations and Production Management, 22, 1246-1272.
50. SHAFER, G., 1976, A Mathematical Theory of Evidence (Princeton: Princeton University Press).
51. SUWIGNJO, P., BITITCI, U. S. and CARRIE, A. S., 2000, Quantitative models for performance measurement system. International Journal of Production Economics, 64, 231-241.
52. VALET, L., MAURIS, G. and BOLON, P., 2001, A statistical overview of recent literature in information fusion. IEEE Magazine on Aeronautics and Electronic Systems, 16, 7-14.
53. WALD, L., 1998, An European proposal for terms of reference in data fusion. International Archives of Photogrammetry and Remote Sensing, 7, 651-654.
54. WEISS, S. M. and KULIKOWSKI, C. A., 1991, Computer Systems that Learn (Los Altos: Morgan Kaufmann).
55. YOON, K. P. and HWANG, C. L., 1995, Multiple Attribute Decision Making (Thousand Oaks: Sage).
56. ZULCH, G., GROBEL, T. and JONSSON, U., 1995, Indicators for the evaluation of organizational performance. In A. Rolstadas (ed.), Benchmarking Theory and Practice (London: Chapman & Hall), pp. 311-321.