Uncertainty Components in Performance Measures

作者: Sérgio Dinis Teixeira de Sousa , Eusébio Manuel Pinto Nunes , Isabel da Silva Lopes

DOI: 10.1007/978-94-007-6190-2_57

关键词: Data qualityComputer scienceCritical success factorSensitivity analysisRisk analysis (engineering)Quality managementRisk managementPerformance measurementFuzzy setUncertainty analysis

摘要: Data quality is a multi-dimensional concept and this research will explore its impact in performance measurement systems (PMSs). Despite the large numbers of publications on design PMSs definition critical success factors to develop Performance Measures (PMs), from data user perspective there are possibilities finding problems, that may have negative decision making. This work identifies classifies uncertainty components PMSs, proposes qualitative method for PMs’ assessment. Fuzzy PMs used represent present any physical system. A also proposed calculate an indicator compliance between fuzzy PM target value, can serve as risk decision-maker.

参考文章(39)
Andy Neely, Mike Gregory, Ken Platts, Performance measurement system design: A literature review and research agenda International Journal of Operations & Production Management. ,vol. 15, pp. 80- 116 ,(1995) , 10.1108/01443579510083622
M. A. Wazed, Shamsuddin Ahmed, Nukman Yusoff, Uncertainty Factors in Real Manufacturing Environment Social Science Research Network. ,(2009)
Robert E. Hoogstoel, A. Blanton Godfrey, Edward G. Schilling, Joseph Moses Juran, Juran's quality handbook McGraw-Hill. ,(1999)
Mouzhi Ge, Markus Helfert, Data and Information Quality Assessment in Information Manufacturing Systems Business Information Systems. pp. 380- 389 ,(2008) , 10.1007/978-3-540-79396-0_33
Mahdi Bashiri, Seyed Javad Hosseininezhad, A fuzzy group decision support system for multifacility location problems. The International Journal of Advanced Manufacturing Technology. ,vol. 42, pp. 533- 543 ,(2009) , 10.1007/S00170-008-1621-3
Carlo Batini, Cinzia Cappiello, Chiara Francalanci, Andrea Maurino, Methodologies for data quality assessment and improvement ACM Computing Surveys. ,vol. 41, pp. 16- ,(2009) , 10.1145/1541880.1541883