| 441 |
|
The Poisson-exponential distribution: A Bayesian approach
|
Louzada-Neto, F.; Cancho, V.G.; Barrige, G.D.C.
|
Executive Sciences Institute
|
2012
|
|
|
|
| 442 |
|
The power of intangibles in high-profitability firms
|
Cabanelas, J.; Lorenzo, P.C.; Liste, A.V.
|
Executive Sciences Institute
|
2012
|
|
|
|
| 443 |
|
The power of prediction: Minimize the impact of inconsistent supplier delivery by using statistical quality models
|
Kruger, G.A.
|
Executive Sciences Institute
|
2014
|
|
|
|
| 444 |
|
The prediction properties of classical and inverse regression for the simple linear calibration problem
|
Parker, P.A.; Wilson, S.A.; Vining, G.G.; Szarka, J.L.; Jonhson, N.G.
|
Executive Sciences Institute
|
2012
|
|
|
|
| 445 |
|
The Q.LIFE engine: A work of statistical engineering
|
Pocinki, S.B.; Scinto, P.R.; Wilkinson, R.G.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 446 |
|
The quality of higher education and employability of graduates
|
Storen, L.A.; Aamodt, P.O.
|
Executive Sciences Institute
|
2012
|
|
|
|
| 447 |
|
The relationship between SERVQUAL, national customer satisfaction indices, and consumer sentiment
|
Kristensen, K.; Eskildsen, J.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 448 |
|
The reliability estimation, prediction and measuring of component-based software
|
Palviainen, M.; Evesti, A.; Ovaska, E.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 449 |
|
The right blend: Lean Six Sigma is used in a chemotherapy mixing room to optimize operations
|
Vanicek, V.
|
Executive Sciences Institute
|
2014
|
|
|
|
| 450 |
|
The right ingredients: Food quality requires building a culture while adhering to standards
|
Zaidi, S.W.A.
|
Executive Sciences Institute
|
2014
|
|
|
|
| 451 |
|
The road to maturity: Process management and integration of strategic human resources processes
|
Ford, M.W.; Evans, J.R.; Masterson, S.S.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 452 |
|
The role of experience in six sigma project success: An empirical analysis of improvement projects
|
Easton, G.S.; Rosenzweig, E.D.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 453 |
|
The role of national culture on relationships between customers' perception of quality, values, satisfaction, and behavioral intentions
|
Wen, C.; Qin, H.; Prybutok, V.R.; Blankson, C.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 454 |
|
The role of quality management practice in the performance of supply chains: A multiple cross-case analysis
|
Terziovski, M.; Hermel, P.
|
Executive Sciences Institute
|
2012
|
|
|
|
| 455 |
|
The role of quality measures in pre- and post-decision analysis of an organizational change
|
Gray, E.H.; Gray, I.; Yodice, P.C.; Rezai, F.; Fless, K.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 456 |
|
The sensitivity of respondent-driven sampling
|
Lu, X.; Bengtsson, L.; Camitz, M.; Thorson, A.; Britton, T.; Liljeros, F.; Kim, B.J.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 457 |
|
The way to engage: An inside look at how Boeing's supplier rating system keeps the aviation giant focused on continuous improvement
|
Parks, K.; Connor, T.
|
Executive Sciences Institute
|
2012
|
|
|
|
| 458 |
|
Three-stage industrial strip-plot experiments
|
Arnouts, H.; Goos, P.; Jones, B.
|
Executive Sciences Institute
|
2014
|
|
|
|
| 459 |
|
Thresholds for error probability measures of business process models
|
Mendling, J.; Sanchez-Gonzalez, L.; Garcia, F.; La Rosa, M.
|
Executive Sciences Institute
|
2013
|
|
|
|
| 460 |
|
Time-relevant metrics in an era of continuous process improvement: The balanced scorecard revisited
|
Schonberger, R.J.
|
Executive Sciences Institute
|
2014
|
|
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|
