Relevant bibliographies by topics / PERFORMANCE MEASUREMENT

Academic literature on the topic 'PERFORMANCE MEASUREMENT'

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Published: 4 June 2021
Last updated: 27 July 2024

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Journal articles on the topic "PERFORMANCE MEASUREMENT"

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Bittlestone, Robert. "From PERFORMANCE MEASUREMENT to PERFORMANCE MEASUREMENT." Measuring Business Excellence 1, no. 4 (April 1997): 8–13. http://dx.doi.org/10.1108/eb025502.

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Bromberg, Daniel. "Performance Measurement." Public Performance & Management Review 33, no. 2 (December 1, 2009): 214–21. http://dx.doi.org/10.2753/pmr1530-9576330202.

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De Lancer Julnes, Patria. "Performance Measurement." Evaluation 12, no. 2 (April 2006): 219–35. http://dx.doi.org/10.1177/1356389006066973.

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Martin, Lawrence L., and Peter M. Kettner. "Performance Measurement." Administration in Social Work 21, no. 1 (March 12, 1997): 17–29. http://dx.doi.org/10.1300/j147v21n01_02.

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Moxham, Claire. "Performance measurement." International Journal of Operations & Production Management 29, no. 7 (June 19, 2009): 740–63. http://dx.doi.org/10.1108/01443570910971405.

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Hatry, Harry P. "Performance Measurement." Public Performance & Management Review 25, no. 4 (June 2002): 352–58. http://dx.doi.org/10.1080/15309576.2002.11643671.

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Tankersley, W. B. "Performance Measurement." Journal of Public Administration Research and Theory 7, no. 1 (January 1, 1997): 163–70. http://dx.doi.org/10.1093/oxfordjournals.jpart.a024338.

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Parker, Charles. "Performance measurement." Work Study 49, no. 2 (April 2000): 63–66. http://dx.doi.org/10.1108/00438020010311197.

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Valckenaers, Paul. "Performance measurement." Computers in Industry 58, no. 7 (September 2007): 603–4. http://dx.doi.org/10.1016/j.compind.2007.05.001.

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Gleich, Ronald. "Performance Measurement." Controlling 14, no. 8-9 (2002): 447–54. http://dx.doi.org/10.15358/0935-0381-2002-8-9-447.

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Dissertations / Theses on the topic "PERFORMANCE MEASUREMENT"

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Sturm, Anke. "Performance Measurement und Environmental Performance Measurement." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2000. http://nbn-resolving.de/urn:nbn:de:swb:14-994768126734-55001.

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Die Zielsetzung der vorliegenden Dissertationsschrift besteht in der Entwicklung einer systematisierten Vorgehensweise, eines Controllingmodells, zur unternehmensinternen Umweltleistungsmessung. Das entwickelte Environmental Performance Measurement (EPM)-Modell umfaßt die fünf Stufen Festlegung der Ziele der Umweltleistungsmessung (1. Stufe), Erfassung der Umwelteinflüsse nach der ökologischen Erfolgsspaltung (2. Stufe), Bewertung der Umwelteinflüsse auf der Grundlage des qualitätszielbezogenen dreistufigen Bewertungsmodells (3. Stufe), Beurteilung der festgestellten Umweltleistung (4. Stufe) und Entscheidungsfindung bzw. potentielle Revision der Ziele (5. Stufe). Diese Stufen können den Controlling-Phasen Planung [Zielfestlegung und potentielle Revision (1. und 5. Stufe)], Realisation [Erfassung und Bewertung (2. und 3. Stufe)] sowie Kontrolle [Beurteilung (4. Stufe)] zugeordnet werden. Das EPM-Modell wurde in Anlehnung an die Kriterien des Performance Measurement und bisheriger Ansätze der betrieblichen Umweltleistungsmessung konzipiert. Insbesondere die Anlehnung an die Kriterien des Performance Measurement wurde bei der Entwicklung des EPM-Modells gesucht, um zum einen die neuen Ansätze im Bereich der betrieblichen Leistungsmessung zu berücksichtigen und zum anderen eine Kompatibilität zwi-schen betrieblicher Leistungsmessung und Umweltleistungsmessung zu erzeugen. Diese Kompatibilität zeigt sich z. B. in der Entwicklung der Eco Balanced Scorecard. Wichtige Charakteristika des EPM-Modells sind auf der Grundlage der identifizierten Kriterien : · die Ausrichtung der Ziele für die Umweltleistungsmessung sowie der Erfassungs- und Bewertungsverfahren auf die Stakeholder-Interessen; dadurch Abbildung der Umweltleistungsfähigkeit, · die Durchführung der ökologischen Erfolgsspaltung bei der Erfassung der Umwelteinflüsse, · die Ermittlung des Zielerreichungsgrades auf Basis der ökologischen Erfolgsspaltung sowie die Bestimmung der Ursa-chen für potentielle Zielverfehlungen und -erreichungen. Die 2. (Erfassung), 3. (Bewertung) und 4. Stufe (Beurteilung) des EPM-Modells wurden empirisch für die deutsche Maschinenbaubranche überprüft; eine Umsetzbarkeit der genannten Stufen konnte dabei konstatiert werden.
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Snethlage, Tim. "Balanciertes Performance measurement : Grundzüge eines an nachhaltigem Unternehmenserfolg orientierten Performance measurements /." Aachen : Shaker, 2004. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=010671315&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Ping, Ivan Chang Kok. "HLA performance measurement." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA376484.

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Thesis (M.S. in Modeling, Virtual Environments and Simulation (MOVES))--Naval Postgraduate School, March 2000.
Thesis advisor(s): Zyda, Michael ; Bachmann, Eric. "March 2000." Includes bibliographical references (p. 77). Also available in print.
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Snethlage, Tim [Verfasser]. "Balanciertes Performance Measurement : Grundzüge eines an nachhaltigem Unternehmenserfolg orientierten Performance Measurements / Tim Snethlage." Aachen : Shaker, 2003. http://d-nb.info/1170545912/34.

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Fowke, Robert Andrew. "Performance Measures for Managerial Decision Making: Performance Measurement Synergies in Multi-Attribute Performance Measurement Systems." PDXScholar, 2010. https://pdxscholar.library.pdx.edu/open_access_etds/164.

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This research tests for correlation between corporate performance and use of financial measures, nonfinancial measures, and number of balanced scorecard categories used. Literature notes a preference for managing by nonfinancial measures because financial measures are lagging indicators, but little empirical evidence is available on the relationship between nonfinancial measures and financial performance, and few companies are found to realize the benefits of nonfinancial measurements. The balanced scorecard has been studied to find the impact of diversity of performance measures, and anecdotal improvements have been reported, but there is a paucity of empirical evidence regarding how the use of a balanced scorecard impacts organizational performance. These issues are investigated in this research with a web based survey distributed to a sample of publicly traded companies using a systematic selection process based on randomly selected numbers generated for each 3-digit NAICS category. The dependent variable is a rank of high, medium or low performance based on 12-month rolling average stock price comparisons from January 2005 to January 2009. These averages are analyzed as a percent change for each company, with performance standardized by 3-digit NAICS category to eliminate cross industry variance in performance ranking. Kruskal-Wallis one-way ANOVA is used to test for correlation. High performers show greatest utilization of both financial and nonfinancial measures, followed by medium performers, with low performers utilizing both measures the least. Nonfinancial performance measures are more correlated to firm value than financial measures with the high performers' mean score for nonfinancial measures being higher than for financial measures. By contrast, medium and low performers exhibit the opposite: higher mean scores for financial measures than for nonfinancial measures [p ≤ 0.05 for nonfinancial measures and p ≤ 0.1 for financial measures]. Correlation is found to be borderline significant (p = 0.06) for the number of balanced scorecard categories used with high performers utilizing the highest number of categories and low performers utilizing the lowest number of categories [p = 0.009 with inclusion of two respondents reporting no usage of balanced scorecard categories].
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Carter, Stephen Douglas. "Corporate treasury performance measurement /." Title page, contents and conclusions only, 1990. http://web4.library.adelaide.edu.au/theses/09EC/09ecc3251.pdf.

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Saad, Amna. "Secure VoIP performance measurement." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/13426.

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This project presents a mechanism for instrumentation of secure VoIP calls. The experiments were run under different network conditions and security systems. VoIP services such as Google Talk, Express Talk and Skype were under test. The project allowed analysis of the voice quality of the VoIP services based on the Mean Opinion Score (MOS) values generated by Perceptual valuation of Speech Quality (PESQ). The quality of the audio streams produced were subjected to end-to-end delay, jitter, packet loss and extra processing in the networking hardware and end devices due to Internetworking Layer security or Transport Layer security implementations. The MOS values were mapped to Perceptual Evaluation of Speech Quality for wideband (PESQ-WB) scores. From these PESQ-WB scores, the graphs of the mean of 10 runs and box and whisker plots for each parameter were drawn. Analysis on the graphs was performed in order to deduce the quality of each VoIP service. The E-model was used to predict the network readiness and Common vulnerability Scoring System (CVSS) was used to predict the network vulnerabilities. The project also provided the mechanism to measure the throughput for each test case. The overall performance of each VoIP service was determined by PESQ-WB scores, CVSS scores and the throughput. The experiment demonstrated the relationship among VoIP performance, VoIP security and VoIP service type. The experiment also suggested that, when compared to an unsecure IPIP tunnel, Internetworking Layer security like IPSec ESP or Transport Layer security like OpenVPN TLS would improve a VoIP security by reducing the vulnerabilities of the media part of the VoIP signal. Morever, adding a security layer has little impact on the VoIP voice quality.
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O'Callaghan, Gerard. "Measurement of hospital performance." Thesis, Aston University, 2011. http://publications.aston.ac.uk/18723/.

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The rationale for carrying out this research was to address the clear lack of knowledge surrounding the measurement of public hospital performance in Ireland. The objectives of this research were to develop a comprehensive model for measuring hospital performance and using this model to measure the performance of public acute hospitals in Ireland in 2007. Having assessed the advantages and disadvantages of various measurement models the Data Envelopment Analysis (DEA) model was chosen for this research. DEA was initiated by Charnes, Cooper and Rhodes in 1978 and further developed by Fare et al. (1983) and Banker et al. (1984). The method used to choose relevant inputs and outputs to be included in the model followed that adopted by Casu et al. (2005) which included the use of focus groups. The main conclusions of the research are threefold. Firstly, it is clear that each stakeholder group has differing opinions on what constitutes good performance. It is therefore imperative that any performance measurement model would be designed within parameters that are clearly understood by any intended audience. Secondly, there is a lack of publicly available qualitative information in Ireland that inhibits detailed analysis of hospital performance. Thirdly, based on available qualitative and quantitative data the results indicated a high level of efficiency among the public acute hospitals in Ireland in their staffing and non pay costs, averaging 98.5%. As DEA scores are sensitive to the number of input and output variables as well as the size of the sample it should be borne in mind that a high level of efficiency could be as a result of using DEA with too many variables compared to the number of hospitals. No hospital was deemed to be scale efficient in any of the models even though the average scale efficiency for all of the hospitals was relatively high at 90.3%. Arising from this research the main recommendations would be that information on medical outcomes, survival rates and patient satisfaction should be made publicly available in Ireland; that despite a high average efficiency level that many individual hospitals need to focus on improving their technical and scale efficiencies, and that performance measurement models should be developed that would include more qualitative data.
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Riedl, Jens B. "Unternehmungswertorientiertes Performance-Measurement : Konzeption eines Performance-Measurement-Systems zur Implementierung einer wertorientierten Unternehmungsführung /." Wiesbaden : Dt. Univ.-Verl, 2000. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=009166877&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Arraiz, Jose-Ignacio. "Electronic performance measurement systems : feasibility of electronic performance measurement systems : a case study." Thesis, Nottingham Trent University, 2017. http://irep.ntu.ac.uk/id/eprint/34038/.

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This thesis explores the possibility of using digital technologies to improve and redefine the performance management process of employees within organisations. A review of the literature indicates that performance processes are not working; a key finding in the literature is the difficulty in collecting the right evidence in order to have the relevant conversation between manager and employee: that is, having access to enough data in order to run the performance measurement. A case study is used to explore two different perspectives: a technical one, looking for accuracy in the performance appraisal, and a social one, for acceptance of the results among the different stakeholders. The main findings of the research are as follows: • Technically, it is possible to gather data about how employees perform at work and develop an algorithm that predicts individual performance, that is: know-how compared with the job profile; behaviours compared with the company values; and output compared with the budget or business plan. • The use of technology to support performance measurement – which is very limited currently – is likely to increase dramatically. With predictive models, performance can be measured, and data be collected at any time. • Like any other new technology, the success of an electronic performance appraisal system depends on the determinants of adoption. These, being complex depend largely upon the different stakeholders, CEO (or eventually the Board), line managers and employees. Each has different interests, perceptions, wills and fears. • In the case study analysed, all stakeholders accepted the concept idea intellectually, an electronic system capable of capturing information and predicting performance at an individual level. However a common fear among line managers is that they will lose control over even basic decisions (i.e. promotion, salary review or bonuses for the consultants). This implies a significant loss of managerial power. • The performance process in most organisations has four different stages: planning, assessment, recognition and career planning. These are usually framed into the budget cycle. • The introduction of technology opens up a new perspective. The measurement phase can be run by the system, in its entirely virtually, and be run at any time. Managers could run performance appraisals and interviews at any time over the year, probably interviewing staff focused on specific issues more; likewise employees may receive feedback more often; the process is disconnected from the recognition phase. The discussion between line manager and employee looks forward rather than backward and focuses on action plans. The research gives practitioners the opportunity to rethink the performance management process, and shows that it is possible to reframe it thanks to technology. As a case study, however, there are still many limitations when generalizing the process.
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Books on the topic "PERFORMANCE MEASUREMENT"

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Klingebiel, Norbert. Performance Measurement. Wiesbaden: Gabler Verlag, 1999. http://dx.doi.org/10.1007/978-3-322-90401-0.

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Gladen, Werner. Performance Measurement. Wiesbaden: Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6766-4.

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Tonchia, Stefano, and Luca Quagini. Performance Measurement. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3.

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Gladen, Werner. Performance Measurement. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-05138-9.

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Bititci, Umit, and Jill MacBryde. Performance measurement. Edited by ebrary Inc. Bradford, England: Emerald Group Publishing, 2002.

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Investment performance measurement. Hoboken, N.J: J. Wiley, 2003.

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Grüning, Michael. Performance-Measurement-Systeme. Wiesbaden: Deutscher Universitätsverlag, 2002. http://dx.doi.org/10.1007/978-3-663-08089-3.

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Neely, Andy, ed. Business Performance Measurement. Cambridge: Cambridge University Press, 2007. http://dx.doi.org/10.1017/cbo9780511488481.

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Kreher, Ralf. UMTS Performance Measurement. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/9780470034866.

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Schomann, Marc. Wissensorientiertes Performance Measurement. Wiesbaden: Deutscher Universitätsverlag, 2001. http://dx.doi.org/10.1007/978-3-322-90250-4.

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Book chapters on the topic "PERFORMANCE MEASUREMENT"

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Tonchia, Stefano, and Luca Quagini. "Performance Measurement and Indicators." In Performance Measurement, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_1.

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Tonchia, Stefano, and Luca Quagini. "Cost and Productivity Performances." In Performance Measurement, 9–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_2.

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Tonchia, Stefano, and Luca Quagini. "Non-cost Performances." In Performance Measurement, 23–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_3.

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Tonchia, Stefano, and Luca Quagini. "Performance Measurement Systems." In Performance Measurement, 35–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_4.

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Tonchia, Stefano, and Luca Quagini. "Design and Integration of the PMS." In Performance Measurement, 61–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_5.

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Tonchia, Stefano, and Luca Quagini. "Performance Management: From Decision Support to Performance Governance." In Performance Measurement, 81–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_6.

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Tonchia, Stefano, and Luca Quagini. "Luxottica, a New “Vision” for the Supply Chain." In Performance Measurement, 95–111. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_7.

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Tonchia, Stefano, and Luca Quagini. "The Monte dei Paschi di Siena “Controlling Data Farm”, the CPM of the Oldest Bank in the World." In Performance Measurement, 113–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_8.

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Tonchia, Stefano, and Luca Quagini. "Sorgenia, Giving Energy to Performance." In Performance Measurement, 135–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13235-3_9.

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Klingebiel, Norbert. "Einführung." In Performance Measurement, 1–11. Wiesbaden: Gabler Verlag, 1999. http://dx.doi.org/10.1007/978-3-322-90401-0_1.

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Conference papers on the topic "PERFORMANCE MEASUREMENT"

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"Measurement." In 2008 IEEE-EPEP Electrical Performance of Electronic Packaging. IEEE, 2008. http://dx.doi.org/10.1109/epep.2008.4675877.

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de Carvalho, J. Pacheco, H. Veiga, C. Pacheco, and A. Reis. "A new performance assessment of 5 GHz IEEE 802.11n four-node point-to-multipoint links." In 2017 11th International Conference on Measurement. IEEE, 2017. http://dx.doi.org/10.23919/measurement.2017.7983560.

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Jindal, Anshul, Vladimir Podolskiy, and Michael Gerndt. "Autoscaling Performance Measurement Tool." In ICPE '18: ACM/SPEC International Conference on Performance Engineering. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3185768.3186293.

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Yao, Yuanshun, Zhujun Xiao, Bolun Wang, Bimal Viswanath, Haitao Zheng, and Ben Y. Zhao. "Complexity vs. performance." In IMC '17: Internet Measurement Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3131365.3131372.

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Siegmund, Norbert, Alexander von Rhein, and Sven Apel. "Family-based performance measurement." In the 12th international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2517208.2517209.

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Arora, Sandeep Kumar, Mubashir Yaqoob Mantoo, Mahnaz Chishti, and Neha Chaudhary. "Performance measurement in MANET." In 2014 5th International Conference- Confluence The Next Generation Information Technology Summit. IEEE, 2014. http://dx.doi.org/10.1109/confluence.2014.6949297.

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Phillips, I. "SMDS network performance measurement." In IEE Colloquium on Practical Experience with SMDS (Switched Multi-Megabit Data Service). IEE, 1995. http://dx.doi.org/10.1049/ic:19950998.

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Pooja and Asmita Pandey. "Virtual machine performance measurement." In 2014 Recent Advances in Engineering and Computational Sciences (RAECS). IEEE, 2014. http://dx.doi.org/10.1109/raecs.2014.6799630.

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Vancelee, Ruth, and Rosemarie Kelly. "PERFORMANCE MEASUREMENT SYSTEM DECOUPLING." In 15th annual International Conference of Education, Research and Innovation. IATED, 2022. http://dx.doi.org/10.21125/iceri.2022.0071.

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Hamel, W. "Measurement of autonomous operation." In the 10th Performance Metrics for Intelligent Systems Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/2377576.2377598.

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Reports on the topic "PERFORMANCE MEASUREMENT"

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Waldbusser, S. Application Performance Measurement MIB. RFC Editor, March 2004. http://dx.doi.org/10.17487/rfc3729.

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Countryman, Jason. Performance Evaluation and Measurement. Office of Scientific and Technical Information (OSTI), May 2019. http://dx.doi.org/10.2172/1571793.

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Fowke, Robert. Performance Measures for Managerial Decision Making: Performance Measurement Synergies in Multi-Attribute Performance Measurement Systems. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.164.

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Gamblin, Todd. Scalable Performance Measurement and Analysis. Office of Scientific and Technical Information (OSTI), January 2009. http://dx.doi.org/10.2172/990416.

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Braun, Jeff, Eric Lichtenstein, Joe Lomg, Glenn Le Prell, and Martha Henry. Human Performance-Based Measurement System. Fort Belvoir, VA: Defense Technical Information Center, December 1999. http://dx.doi.org/10.21236/ada373062.

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Fowler, Kimberly M., and Angela R. Kora. Wynkoop Building Performance Measurement: Water. Office of Scientific and Technical Information (OSTI), August 2012. http://dx.doi.org/10.2172/1050809.

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Bostelman, Roger, Ya-Shian Li-Baboud, Steve Legowik, Tsai Hong, and Sebti Foufou. Mobile manipulator performance measurement data. Gaithersburg, MD: National Institute of Standards and Technology, June 2017. http://dx.doi.org/10.6028/nist.tn.1965.

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Leat, Diana, Alexandra Williamson, and Wendy A. Scaife. Performance Measurement in Perspective: An exploratory study of Australian foundations� approaches to performance measurement. Queensland, Australia: Queensland University of Technology, September 2014. http://dx.doi.org/10.5204/rep.eprints.75993.

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Delgado, Brian. Extensible Performance-Aware Runtime Integrity Measurement. Portland State University Library, March 2020. http://dx.doi.org/10.15760/etd.7298.

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Raisanen, V., G. Grotefeld, and A. Morton. Network performance measurement with periodic streams. RFC Editor, November 2002. http://dx.doi.org/10.17487/rfc3432.

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