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Journal articles on the topic 'Performance measures'

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Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Pandey, Manoj, and Rajesh Kr Dubey. "Performance Measures in Supply Chain Management." Indian Journal of Applied Research 4, no. 2 (October 1, 2011): 14–17. http://dx.doi.org/10.15373/2249555x/feb2014/91.

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2

Kelley, Patricia M. "Performance Measures:." Journal of Library Administration 14, no. 2 (May 7, 1991): 21–36. http://dx.doi.org/10.1300/j111v14n02_03.

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3

O??LEARY, DENNIS S. "Performance Measures." Medical Care 33, Supplement (January 1995): JS18. http://dx.doi.org/10.1097/00005650-199501001-00003.

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4

Thompson, Betsy L., and Jeffrey R. Harris. "Performance measures." American Journal of Preventive Medicine 20, no. 4 (May 2001): 291–93. http://dx.doi.org/10.1016/s0749-3797(01)00294-x.

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5

Starbuck, William H. "Performance Measures." Journal of Management Inquiry 14, no. 3 (September 2005): 280–86. http://dx.doi.org/10.1177/1056492605279099.

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6

Baghai, Mehrdad, Lar Bradshaw, Stephen Coley, and David White. "PERFORMANCE MEASURES:." Journal of Business Strategy 20, no. 4 (April 1999): 17–21. http://dx.doi.org/10.1108/eb040013.

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7

Redberg, Rita F. "Performance Measures." JAMA Internal Medicine 173, no. 16 (September 9, 2013): 1549. http://dx.doi.org/10.1001/jamainternmed.2013.7769.

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8

Park, Sang-June, and Youjae Yi. "A composite measure of performance–expectation and performance-only measures." Service Industries Journal 37, no. 15-16 (September 2017): 936–47. http://dx.doi.org/10.1080/02642069.2017.1369968.

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9

Behn, Robert D. "Why Measure Performance? Different Purposes Require Different Measures." Public Administration Review 63, no. 5 (September 2003): 586–606. http://dx.doi.org/10.1111/1540-6210.00322.

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10

Lemmer, Hofﬁe. "Cricket performance measures." Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 28, no. 1 (September 2, 2009): 13–34. http://dx.doi.org/10.4102/satnt.v28i1.46.

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The purpose of this paper is to present a summary of batting and bowling performance measures that have been developed over a period of eight years. The measure of batting performance (BP) consists of three components. Firstly, an exponentially weighted average (EWA) is calculated in which recent scores have higher weights than scores further back in time in order to get a measure that adequately reﬂects the batsman’s present form. EWA is then adjusted up- or downwards depending on the batsman’s consistency and strike rate. This measure was subsequently generalized to BPW which includes weights for runs scored against speciﬁc countries in home or away matches separately. In the case of bowling, the ﬁrst challenge was to develop a single comprehensive measure of bowling performance, the combined bowling rate (CBR) for limited overs matches and the dynamic bowling rate (DBR) for unlimited overs matches. Hence, by alsotaking bowling consistency into account, the current bowling performance measure (CBP) wasdeveloped. This measure was also extended to include weights for wickets taken and runs concededagainst each international team in home or away matches. These measures contain parametersthat were based on players’ scores up to the speciﬁc date of calculation. Before using the latestavailable data for the present presentation, it is logical to update these parameters. This hasbeen done in the present study. If a player performs well at local level, it is important to be ableto compare his performance with those of players already in the national team. Weights havebeen determined for runs scored by batsmen and also for runs conceded and wickets taken bybowlers in local matches, whereby the performances of players can be compared irrespective ofthe proportion of international matches played by each player. After having used the measures onvarious occasions the need arose to revise some of them slightly. The updated measures are thenused to give rankings of South African batsmen and bowlers in First Class and List A matchesalike. Methods have also been developed to compare the batting and bowling performances ofplayers after a short series of matches. It was shown that the traditional average could haveunrealistic values in the case of a batsman who had a large percentage of not out scores in ashort series. Alternative measures have been developed and shown to give much more realisticvalues. In the case of bowling it is important not only to count the number of wickets a bowlerhas taken, but to distinguish between the wickets of top and middle order batsmen on the onehand and lower order batsmen on the other. A system has been established whereby weights areattached to the wickets according to the batting position of the batsman. Instead of just countingthe number of wickets taken, the sum of the weights of the wickets taken by the bowler is usedin the calculation of CBR* or DBR*. Finally, the latest form of the game, Twenty20 cricket, isalso discussed.

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11

French, Beverlee. "Library performance measures." College & Research Libraries News 48, no. 2 (February 1, 1987): 72–74. http://dx.doi.org/10.5860/crln.48.2.72.

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12

Corley-Lay, Judith. "Pavement Performance Measures." Transportation Research Record: Journal of the Transportation Research Board 2431, no. 1 (January 2014): 1–5. http://dx.doi.org/10.3141/2431-01.

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13

Bauly, John A. "Measures of Performance." World Class Design to Manufacture 1, no. 3 (June 1994): 37–40. http://dx.doi.org/10.1108/09642369210056647.

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14

Heffner, John E., Richard A. Mularski, and Peter M. A. Calverley. "COPD Performance Measures." Chest 137, no. 5 (May 2010): 1181–89. http://dx.doi.org/10.1378/chest.09-2306.

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15

Wells, Margaret, and Margaret Wade. "Physical performance measures." Nurse Practitioner 38, no. 6 (June 2013): 48–53. http://dx.doi.org/10.1097/01.npr.0000429895.41373.7e.

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16

Datar, Srikant, Susan Cohen Kulp, and Richard A. Lambert. "Balancing Performance Measures." Journal of Accounting Research 39, no. 1 (June 2001): 75–92. http://dx.doi.org/10.1111/1475-679x.00004.

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17

HANNABUSS, STUART. "Personal Performance Measures." New Library World 88, no. 5 (May 1987): 86–87. http://dx.doi.org/10.1108/eb038724.

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18

Narin, F., and Kimberly S. Hamilton. "Bibliometric performance measures." Scientometrics 36, no. 3 (July 1996): 293–310. http://dx.doi.org/10.1007/bf02129596.

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19

Park, Sang-June, and Youjae Yi. "Performance-only measures vs. performance-expectation measures of service quality." Service Industries Journal 36, no. 15-16 (December 9, 2016): 741–56. http://dx.doi.org/10.1080/02642069.2016.1275579.

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20

Baumann, Michael H., and Ed Dellert. "Performance Measures and Pay for Performance." Chest 129, no. 1 (January 2006): 188–91. http://dx.doi.org/10.1378/chest.129.1.188.

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21

Lane, Norman E., Robert S. Kennedy, and Marshall B. Jones. "Overcoming Unreliability in Operational Measures: The Use of Surrogate Measure Systems." Proceedings of the Human Factors Society Annual Meeting 30, no. 14 (September 1986): 1398–402. http://dx.doi.org/10.1177/154193128603001412.

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Improved assessment of operational performance is critical for studies of selection, training and human engineering as well as those examining the performance effects of environmental changes, chemicals or other stressors imposed by military duties. The present discussion focuses on what we consider to be the major problem with such enterprises – the lack of sensitivity of operational measures because of poor reliability. The well-documented impact of low field measure reliability includes the inability to demonstrate differences resulting from experimental treatments and the chronic underrepresentation of validity in predictive studies. This paper describes a general methodology for using specially-developed performance batteries as surrogates for real-world performances, in particular for determining whether such performance may be disrupted by environmental or chemical agents. The logical and metric rationale of surrogate measurement is presented, and the advantages and disadvantages are discussed and compared to alternative approaches (job samples, synthetic tasks, etc.).

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22

Chen, Andrew, Peter Ray, Howard Rogers, Christie Bialowas, Parag Butala, Michael Chen, Steven D. Daveluy, et al. "Evidence-Based Performance Measures for Reconstruction after Skin Cancer Resection: A Multidisciplinary Performance Measure Set." Plastic & Reconstructive Surgery 153, no. 2 (January 24, 2024): 424e—441e. http://dx.doi.org/10.1097/prs.0000000000010916.

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Background: The American Society of Plastic Surgeons commissioned the multidisciplinary Performance Measure Development Work Group on Reconstruction after Skin Cancer Resection to identify and draft quality measures for the care of patients undergoing skin cancer reconstruction. Included stakeholders were the American Academy of Otolaryngology–Head and Neck Surgery, the American Academy of Facial Plastic and Reconstructive Surgery, the American Academy of Dermatology, the American Society of Dermatologic Surgery, the American College of Mohs Surgery, the American Society for Mohs Surgery, and a patient representative. Methods: Two outcome measures and five process measures were identified. The outcome measures included the following: (1) patient satisfaction with information provided by their surgeon before their facial procedure, and (2) postprocedural urgent care or emergency room use. The process measures focus on antibiotic stewardship, anticoagulation continuation and/or coordination of care, opioid avoidance, and verification of clear margins. Results: All measures in this report were approved by the American Society of Plastic Surgeons Quality and Performance Measures Work Group and Executive Committee, and the stakeholder societies. Conclusion: The work group recommends the use of these measures for quality initiatives, Continuing Medical Education, Continuous Certification, Qualified Clinical Data Registry reporting, and national quality reporting programs.

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23

Smith, T. Brett, and Will G. Hopkins. "Measures of Rowing Performance." Sports Medicine 42, no. 4 (April 2012): 343–58. http://dx.doi.org/10.2165/11597230-000000000-00000.

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24

Seidenwurm, D., P. Turski, J. Barr, J. Connors, M. Lev, S. Mukherji, and E. Russell. "Performance Measures in Neuroradiology." American Journal of Neuroradiology 28, no. 8 (September 1, 2007): 1435–38. http://dx.doi.org/10.3174/ajnr.a0672.

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25

Day, Christopher M., Darcy M. Bullock, and James R. Sturdevant. "Cycle-Length Performance Measures." Transportation Research Record: Journal of the Transportation Research Board 2128, no. 1 (January 2009): 48–57. http://dx.doi.org/10.3141/2128-05.

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26

McNeil, John J., Joseph Ibrahim, Jenny Majoor, and Flavia Cicuttinl. "Performance and outcome measures." Medical Journal of Australia 170, no. 10 (May 1999): 507. http://dx.doi.org/10.5694/j.1326-5377.1999.tb127858.x.

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27

Patel, Charmy, and Dr Ravi Gulati. "Software Performance Testing Measures." INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 8, no. 2 (January 31, 2014): 1297–300. http://dx.doi.org/10.24297/ijmit.v8i2.681.

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Software developers typically measure a Web application's quality of service in terms of webpage availability, response time, and throughput. Performance testing and evaluation of software components becomes a critical task. Poor quality of software performance can lead to bad opportunities. Few research papers address the issues and systematic solutions to performance testing and measurement for modern components of software. This paper proposes a solution and environment to support performance measurement for software. The objective is to provide all kind of important measures which must be tested at the coding phase instead of after completion of software. So developers can make software that can meet performance objectives.

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28

Smith, Michael J. "Gaming Nonfinancial Performance Measures." Journal of Management Accounting Research 14, no. 1 (January 1, 2002): 119–33. http://dx.doi.org/10.2308/jmar.2002.14.1.119.

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This multitask agency model examines the use of nonfinancial performance measures. The first effort affects only current-period profit. The second effort affects only customer satisfaction, which increases future profits. The third effort (shifting effort) simultaneously affects both performance measures, increasing one and decreasing the other. In some cases, shifting increases the principal's expected surplus. In others, the agent uses it to “arbitrage” the contract by shifting units into the more heavily weighted performance measure. Shifting's dual nature implies that it can either increase or decrease the incremental value of customer satisfaction as a performance measure. The optimal contract may entail a negative weight on customer satisfaction.

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29

Mazimba, Sula, Nakash Grant, Analkumar Parikh, George Mwandia, Diklar Makola, Christine Chilomo, Cristina Redko, and Harvey S. Hahn. "Heart Failure Performance Measures." American Journal of Medical Quality 28, no. 4 (October 30, 2012): 324–29. http://dx.doi.org/10.1177/1062860612465066.

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30

Kunz, Jennifer. "Performance measures and learning." International Journal of Applied Management Science 3, no. 1 (2011): 1. http://dx.doi.org/10.1504/ijams.2011.037706.

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31

Manahan, Michele A., William A. Wooden, Stephen M. Becker, Jason R. Cacioppo, Stephen B. Edge, Amanda C. Grandinetti, Diedra D. Gray, et al. "Evidence-Based Performance Measures." Plastic and Reconstructive Surgery 140, no. 6 (December 2017): 775e—781e. http://dx.doi.org/10.1097/prs.0000000000003845.

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32

Bao, Shan, Zizheng Guo, Carol Flannagan, John Sullivan, James R. Sayer, and Dave LeBlanc. "Distracted Driving Performance Measures." Transportation Research Record: Journal of the Transportation Research Board 2518, no. 1 (January 2015): 68–72. http://dx.doi.org/10.3141/2518-09.

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33

Grønholdt, Lars, and Anne Martensen. "Key Marketing Performance Measures." Marketing Review 6, no. 3 (September 1, 2006): 243–52. http://dx.doi.org/10.1362/146934706778605287.

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34

Walsh, Paul. "Dumbing down performance measures." Measuring Business Excellence 9, no. 4 (December 2005): 37–45. http://dx.doi.org/10.1108/13683040510634826.

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35

Mukundan, Govind, and David Seidenwurm. "Performance Measures, Efficiency, Productivity." Neuroimaging Clinics of North America 22, no. 3 (August 2012): 451–56. http://dx.doi.org/10.1016/j.nic.2012.05.009.

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36

You-Ling Shyu, Jeffrey, Judith Burleson, Colleen Tallant, David J. Seidenwurm, and Frank J. Rybicki. "Performance Measures in Radiology." Journal of the American College of Radiology 11, no. 5 (May 2014): 456–63. http://dx.doi.org/10.1016/j.jacr.2013.11.019.

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37

Sturmey, Peter. "Outcome based performance measures." Research in Developmental Disabilities 16, no. 1 (January 1995): 81–82. http://dx.doi.org/10.1016/0891-4222(95)90023-3.

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38

Kane, Michael, Terence Crooks, and Allan Cohen. "Validating Measures of Performance." Educational Measurement: Issues and Practice 18, no. 2 (October 25, 2005): 5–17. http://dx.doi.org/10.1111/j.1745-3992.1999.tb00010.x.

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39

Park, Changkyu, Luis G. Occe??a, Cheryl Goodwin, and Anne Payne. "Analysis of Performance Measures." JONA: The Journal of Nursing Administration 28, no. 12 (December 1998): 28–35. http://dx.doi.org/10.1097/00005110-199812000-00011.

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40

Muriel, Alastair, and Jeffrey Smith. "On Educational Performance Measures*." Fiscal Studies 32, no. 2 (June 2011): 187–206. http://dx.doi.org/10.1111/j.1475-5890.2011.00132.x.

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41

Oakes, Jim, Rick Botta, and Terry Bahill. "11.1.1 Technical Performance Measures." INCOSE International Symposium 16, no. 1 (July 2006): 1466–74. http://dx.doi.org/10.1002/j.2334-5837.2006.tb02826.x.

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42

Coleman, Grace, Fiona Dobson, Rana S. Hinman, Kim Bennell, and Daniel K. White. "Measures of Physical Performance." Arthritis Care & Research 72, S10 (October 2020): 452–85. http://dx.doi.org/10.1002/acr.24373.

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43

Kulkarni, Praveen M., Y. M. Satish, and Prayag Gokhale. "Performance measures of startups." International Journal of Entrepreneurial Venturing 15, no. 5 (2023): 409–22. http://dx.doi.org/10.1504/ijev.2023.134932.

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44

Basile, Robert, Robert M. Otto, and John W. Wygand. "The Relationship Between Physical and Physiological Performance Measures and Baseball Performance Measures." Medicine & Science in Sports & Exercise 39, Supplement (May 2007): S214. http://dx.doi.org/10.1249/01.mss.0000273807.89364.04.

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45

Judi, Hairulliza Mohamad, and Hazura Mohamed. "Optimising Computer Laboratory Layout Based on Multiple Performance Measures." International Journal of Information and Education Technology 6, no. 9 (2016): 713–16. http://dx.doi.org/10.7763/ijiet.2016.v6.780.

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46

Stede, Wim A. Van der, Chee W. Chow, and Thomas W. Lin. "Strategy, Choice of Performance Measures, and Performance." Behavioral Research in Accounting 18, no. 1 (January 1, 2006): 185–205. http://dx.doi.org/10.2308/bria.2006.18.1.185.

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We examine the relationship between quality-based manufacturing strategy and the use of different types of performance measures, as well as their separate and joint effects on performance. A key part of our investigation is the distinction between financial and both objective and subjective nonfinancial measures. Our results support the view that performance measurement diversity benefits performance as we find that, regardless of strategy, firms with more extensive performance measurement systems—especially those that include objective and subjective nonfinancial measures—have higher performance. But our findings also partly support the view that the strategy-measurement “fit” affects performance. We find that firms that emphasize quality in manufacturing use more of both objective and subjective nonfinancial measures. However, there is only a positive effect on performance from pairing a qualitybased manufacturing strategy with extensive use of subjective measures, but not with objective nonfinancial measures.

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47

Saidi Mehrabad, Mohammad, Mona Anvari, and Morteza Saberi. "Targeting performance measures based on performance prediction." International Journal of Productivity and Performance Management 61, no. 1 (December 2, 2011): 46–68. http://dx.doi.org/10.1108/17410401211187507.

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48

Ishii, Lisa, Fred Fedok, Benjamin Marcus, and Travis T. Tollefson. "Executive Summary: “Evidence-Based Performance Measures for Rhinoplasty: A Multi-disciplinary Performance Measure Set”." Otolaryngology–Head and Neck Surgery 165, no. 3 (February 9, 2021): 383–84. http://dx.doi.org/10.1177/0194599821991083.

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49

Ishii, Lisa, Fred Fedok, Benjamin Marcus, and Travis T. Tollefson. "Executive Summary: “Evidence-Based Performance Measures for Rhinoplasty: A Multi-disciplinary Performance Measure Set”." Facial Plastic Surgery & Aesthetic Medicine 23, no. 5 (October 1, 2021): 319–20. http://dx.doi.org/10.1089/fpsam.2021.29022.lis.

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50

TISSAINAYAGAM, PRITHIRAJ, and DAVID SUTER. "PERFORMANCE MEASURES FOR ASSESSING CONTOUR TRACKERS." International Journal of Image and Graphics 02, no. 02 (April 2002): 343–59. http://dx.doi.org/10.1142/s0219467802000627.

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In this paper we present techniques to compare the quality of tracking performances of B-spline based contour trackers. Three trackers reported to give good tracking performance have been considered for our empirical evaluation. They are the CONT-IMM tracker, the Condensation tracker and the Baumberg's tracker. Four different test conditions were set and for each test, the tracking performance of each tracker was measured against four performance measures. The results presented have revealed some interesting findings about the performance of the trackers under various conditions.

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