Interrelated Performance Measures, Interactive Effort, and Incentive Weights

2009 ◽  
Vol 21 (1) ◽  
pp. 125-149 ◽  
Author(s):  
Shane S. Dikolli ◽  
Christian Hofmann ◽  
Susan L. Kulp
Keyword(s):  
Performance Measures ◽  
Performance Metrics ◽  
Performance Measure ◽  
The Other ◽  
Principal Agent ◽  
Directional Effect ◽  
Complementary Interactions ◽  
Total Effort

ABSTRACT: This study uses principal-agent analysis to investigate how the principal's use of performance measures in the agent's compensation contract are affected by (1) links between performance measures and (2) substitute and complementary characteristics of an agent's efforts. We show that the directional effect of changes in performance measure interrelations on linear incentive weights depends on how the agent's tasks interact with each other (i.e., substitute or complementary interactions). For example, increases in performance measure interrelations do not necessarily imply higher incentive weights on more sensitive and precise performance measures. If efforts are substitutes for each other, the costs of effort are relatively high and the principal induces lower levels of total effort by offering lower incentives. We also show that differences in the combination of performance measure interrelations and effort interactions affect profits in distinctly different ways. When efforts are substitutes for each other, increases in the sensitivities of profit to the other performance metrics (i.e., increased interrelations), and thus to effort, may actually lead to lower profits.

Abstract 174: Comparison of Performance Measures and 30-Day Patient Outcomes among Hospitals that Do and Do not Participate in ACTION Registry- Get With The Guidelines

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Robin Mathews ◽  
Gregg C Fonarow ◽  
Shuang Li ◽  
Eric D Peterson ◽  
John S Rumsfeld ◽  
...  
Keyword(s):  
Performance Measures ◽  
Performance Metrics ◽  
Performance Measure ◽  
Absolute Difference ◽  
Clinical Registry ◽  
Process Measures ◽  
Hospital Size ◽  
Coronary Syndrome ◽  
Baseline Performance ◽  
Very High

Background: ACTION Registry-GWTG (ARG) is a clinical registry and Quality Improvement (QI) program co-sponsored by the American College of Cardiology and the American Heart Association, designed to measure and improve the treatment and outcomes of patients with acute myocardial infarction (AMI). However, it is unknown whether hospital participation in ARG is associated with better performance on publicly reported AMI quality metrics and 30-day outcomes. Methods: Using Hospital Compare, we matched hospitals participating in ARG from 2007-2010 to non-ARG participating hospitals based on teaching status, hospital size, percutaneous coronary intervention capability, and composite adherence to AMI performance measures in 2007. We then used linear mixed modeling to compare 2010 performance measure adherence, 30-day mortality, and all-cause readmission among ARG and non-ARG hospitals. As secondary analyses, we repeated the matching process without using baseline adherence to AMI measures and also stratified the hospitals according to duration of ARG participation and level of baseline performance. Results: We successfully matched 502 hospitals participating in ARG to 502 non-ARG hospitals. Adherence to AMI process measures was very high overall with minimal differences between ARG and non-ARG hospitals for most performance measures. In pairwise mixed modeling, ARG hospitals were more likely to achieve primary PCI within 90 minutes, though the absolute difference was small (Table). Overall, 30-day mortality and readmission rates were similar among ARG and non-ARG centers. Results were consistent whether hospitals were matched based on baseline performance or if centers were stratified by duration of ARG participation. Conclusion: Hospitals across the U.S. report very high achievement rates for nearly all current performance measures for AMI care. These data suggest ongoing local and national QI efforts are having success within and beyond the ARG program. More sensitive process and outcome performance metrics with longer term outcomes may be needed to differentiate quality of care and drive the next phase of improvement in outcomes after acute coronary syndrome.

Identification of specific metrics for sustainable lean manufacturing in the automobile industries

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Naveen Kumar ◽  
Mathiyazhagan Kaliyan ◽  
M. Thilak ◽  
Ángel Acevedo-Duque
Keyword(s):  
Literature Review ◽  
Performance Measures ◽  
Lean Manufacturing ◽  
Performance Metrics ◽  
Research Direction ◽  
Performance Measure ◽  
Extensive Study ◽  
Future Research ◽  
Content Type ◽  
Specific Performance

PurposeThis study explains the importance of performance measures and identifies the specific performance measures of sustainable lean manufacturing (SLM) for automobile industries. Awareness towards sustainability and continuous improvement approaches demand monitoring of the sustainable lean impact on organization/industry, and hence, identifying the specific performance metrics is of peak importance.Design/methodology/approachIn this study, specific metrics for social, economic and environmental performance are identified from a systematic literature review of 82 significantly related journal articles. The importance of the identified metrics is assessed with the help of questionnaire responses from a group of industrial experts.FindingsPerformance indicators are statistically analyzed category wise and assessed. The key metrics are summarized based on the survey data followed by a discussion with industrial experts. From this study, performance measures have been identified and validated through hypothesis testing for Indian automobile industries. Certification of IATF16949 implementation found an important vertical for SLM implementation. In this study, SLM implementation initiatives are discussed, and reward scheme for outstanding performers are identified as important initiatives are followed by small improvement culture.Practical implicationsThe proposed discussion of this study is useful for industrialist and researchers, as SLM performance measures are well explained for Indian automobile industries. In this study, future research direction is also explained related to other industries. These summarized performance measures will help to maintain SLM in industries.Originality/valueThis paper presents the original literature review based on the study of SLM, as no extensive study is available where SLM performance measure explained for automobile industries. Key initiatives and vertical of SLM are well explained for Indian automobile industries. This study proposed a complete framework for SLM implementation considering competitive manufacturing targets.

Interim Performance Measures and Private Information

2013 ◽  
Vol 88 (5) ◽  
pp. 1683-1714 ◽  
Author(s):  
Christian Hofmann ◽  
Naomi R. Rothenberg
Keyword(s):  
Performance Measures ◽  
Private Information ◽  
Performance Measure ◽  
The Other ◽  
Trade Off ◽  
Jel Classifications ◽  
Forward Looking

ABSTRACT: This study investigates whether having an upstream or downstream agent privately observe an interim performance measure and disseminating this measure to the other agent is valuable to the principal. The signal is informative about the upstream agent's action and positively correlated with output. If the upstream agent privately observes the signal, then there can be a higher cost of the downstream agent if the signal is sufficiently forward-looking. If the downstream agent privately observes the signal, then the trade-off involves rents to the downstream agent versus a reduced cost for the upstream agent. Private observation of an interim signal is valuable to the principal if it is not too forward-looking. The choice between upstream and downstream agent depends nontrivially on the signal's backward-looking quality. The results suggest that the value of observation and dissemination of an interim signal depends on the informativeness of output and the signal about upstream and downstream production. JEL Classifications: D82, D83, L20, M40.

scholarly journals Implementation of 5.1 Sidra Intersection Software for Appraisal of Road Corridors under Current Form

2021 ◽  
Vol 18 (18) ◽  
Author(s):  
Dagimwork Asele MANUKA
Keyword(s):  
Performance Measures ◽  
Performance Metrics ◽  
Performance Measure ◽  
Level Of Service ◽  
Effective Capacity ◽  
Spare Capacity ◽  
Current Form ◽  
The Road ◽  
Capacity Curves ◽  
Flow Parameters

The major goal of this study was to compute the flow appearances of the chosen midblock and to evaluate the road sections using various performance metrics that analyzed these road sections in both current and future conditions. Performance measure of flow parameters was at the operational period of the road. Therefore, this work examined the 2-way 2-lane roads with various performance measures. The capacity of mid blocks was also determined by plotting capacity curves and the level of service arrived and Sidra Intersection 5.1 tools were used for the analysis. All midblock evaluated with different performance measures both in current and future conditions with basic considerations. The analysis was done by adopting Sidra Intersection 5.1 tool and showed that 2-way 2-lane roads in future conditions were studied and the result indicated that their average travel speed, degree of saturation, practical spare capacity, total effective capacity, demand of flow, and level of service (LOS) displayed major changes from the base condition. HIGHLIGHTS Compute the flow appearances of the chosen midblock To evaluate the road sections using various performance metrics that analyzed these road sections in both current and future conditions Performance measure of flow parameters was at the operational period of the road. Therefore, this work examined the 2-way 2-lane roads with various performance measures The capacity of mid blocks was also determined by plotting capacity curves The level of service arrived and Sidra Intersection 5.1 tools were used for the analysis GRAPHICAL ABSTRACT

GRAM: A True Null Model for Relative Binding Affinity Predictions

2019 ◽  
Author(s):  
Guanglei Cui ◽  
Alan P. Graves ◽  
Eric S. Manas
Keyword(s):  
Binding Affinity ◽  
Performance Metrics ◽  
Null Model ◽  
Performance Measure ◽  
Interval Estimate ◽  
Empirical Observation ◽  
Binding Affinity Prediction ◽  
Affinity Prediction ◽  
Relative Binding Affinity ◽  
Relative Binding

Relative binding affinity prediction is a critical component in computer aided drug design. Significant amount of effort has been dedicated to developing rapid and reliable in silico methods. However, robust assessment of their performance is still a complicated issue, as it requires a performance measure applicable in the prospective setting and more importantly a true null model that defines the expected performance of random in an objective manner. Although many performance metrics, such as correlation coefficient (r2), mean unsigned error (MUE), and room mean square error (RMSE), are frequently used in the literature, a true and non-trivial null model has yet been identified. To address this problem, here we introduce an interval estimate as an additional measure, namely prediction interval (PI), which can be estimated from the error distribution of the predictions. The benefits of using the interval estimate are 1) it provides the uncertainty range in the predicted activities, which is important in prospective applications; 2) a true null model with well-defined PI can be established. We provide one such example termed Gaussian Random Affinity Model (GRAM), which is based on the empirical observation that the affinity change in a typical lead optimization effort has the tendency to distribute normally N (0, s). Having an analytically defined PI that only depends on the variation in the activities, GRAM should in principle allow us to compare the performance of relative binding affinity prediction methods in a standard way, ultimately critical to measuring the progress made in algorithm development.<br>

Effects of Accounting-Method Choices on Subjective Performance-Measure Weighting Decisions: Experimental Evidence on Precision and Error Covariance

2005 ◽  
Vol 80 (4) ◽  
pp. 1163-1192 ◽  
Author(s):  
Ranjani Krishnan ◽  
Joan L. Luft ◽  
Michael D. Shields
Keyword(s):  
Performance Measures ◽  
Error Variance ◽  
Spillover Effects ◽  
Performance Measure ◽  
Incentive System ◽  
Experimental Setting ◽  
Error Covariance ◽  
Psychology Theory ◽  
Optimal Weighting ◽  
Similarity And Difference

Performance-measure weights for incentive compensation are often determined subjectively. Determining these weights is a cognitively difficult task, and archival research shows that observed performance-measure weights are only partially consistent with the predictions of agency theory. Ittner et al. (2003) have concluded that psychology theory can help to explain such inconsistencies. In an experimental setting based on Feltham and Xie (1994), we use psychology theories of reasoning to predict distinctive patterns of similarity and difference between optimal and actual subjective performance-measure weights. The following predictions are supported. First, in contrast to a number of prior studies, most individuals' decisions are significantly influenced by the performance measures' error variance (precision) and error covariance. Second, directional errors in the use of these measurement attributes are relatively frequent, resulting in a mean underreaction to an accounting change that alters performance measurement error. Third, individuals seem insufficiently aware that a change in the accounting for one measure has spillover effects on the optimal weighting of the other measure in a two-measure incentive system. In consequence, they make performance-measure weighting decisions that are likely to result in misallocations of agent effort.

scholarly journals Two Factors in Face Recognition: Whether You Know the Person’s Face and Whether You Share the Person’s Race

Perception ◽  
2021 ◽  
pp. 030100662110140
Author(s):  
Xingchen Zhou ◽  
A. M. Burton ◽  
Rob Jenkins
Keyword(s):  
Face Recognition ◽  
Factorial Design ◽  
Performance Measures ◽  
Recognition Accuracy ◽  
The Other ◽  
Familiarity Effect ◽  
Race Effect ◽  
Two Factors ◽  
Unfamiliar Face

One of the best-known phenomena in face recognition is the other-race effect, the observation that own-race faces are better remembered than other-race faces. However, previous studies have not put the magnitude of other-race effect in the context of other influences on face recognition. Here, we compared the effects of (a) a race manipulation (own-race/other-race face) and (b) a familiarity manipulation (familiar/unfamiliar face) in a 2 × 2 factorial design. We found that the familiarity effect was several times larger than the race effect in all performance measures. However, participants expected race to have a larger effect on others than it actually did. Face recognition accuracy depends much more on whether you know the person’s face than whether you share the same race.

Abstract 3429: Implementation of Electronic Medical Record Stroke Templates Increases Compliance with Stroke Performance Measures

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Crismely A Perdomo ◽  
Vepuka E Kauari ◽  
Elizabeth Suarez ◽  
Olajide Williams ◽  
Joshua Stillman ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Performance Measures ◽  
New York State ◽  
Stroke Care ◽  
Performance Measure ◽  
Performance Comparison ◽  
York State Department ◽  
Free Text ◽  
And Performance

Background and Purpose The literature demonstrates how utilizing evidence-based, standardized stroke care can improve patient outcomes; however, the contribution of electronic medical record (EMR) systems may also impact outcomes by ensuring utilization and compliance with established stroke performance measures, facilitating and improving documentation requirements, and standardizing approach to care. In 2008, documentation in patients’ medical records was done in combination of paper and a template free EMR. Originally, the EMR was used for order entry, then transitioned to full electronic documentation in 2009. At that time we implemented our stroke templates and performance measures based on regulatory standards. We hypothesized that the stroke template implementation would help us achieve performance measure criteria above state benchmarks as set out by the New York State Department of Health (NYS DOH). Methods Implementation was phased in [over 18 months], initially using a template that only included neurological assessment and free text fields for stroke measures. By July 2010, existing templates were modified and additional stroke templates were implemented to meet new regulatory requirements and meaningful use criteria. Retrospective data review was conducted for performance comparison between 2008 -- one year prior to EMR/template implementation -- and 2010. In Quarter 1 of 2011 EMR was also implemented in the Emergency Department (ED). Data was reviewed for compliance with stroke measures. Results Documentation compliance substantially improved between 2008 and Quarter 1 2011: Compliance for these measures has been maintained ≥ 85% since November 2010, ≥ 90% Q1 2011 Conclusions The EMR implementation of stroke templates and performance measures can produce substantial improvement in performance measure compliance. Future steps will include automated documentation alerts to retrieve information and real time discovery of missing documentation for concurrent quality review and improvement

The Necessity of Performance Measures for Prosecutors

2021 ◽  
pp. 226-258
Author(s):  
Lauren-Brooke Eisen ◽  
Miriam Aroni Krinsky
Keyword(s):  
Performance Measures ◽  
Performance Metrics ◽  
Mass Incarceration ◽  
The United States ◽  
New Wave ◽  
Criminal Cases ◽  
Critical Data ◽  
District Attorneys ◽  
The Right ◽  
Individual Line

Local prosecutors are responsible for 95 percent of criminal cases in the United States—their charging decisions holding enormous influence over the number of people incarcerated and the length of sentences served. Performance metrics are a tool that can align the vision of elected prosecutors with the tangible actions of their offices’ line attorneys. The right metrics can provide clarity to individual line attorneys around the mission of the office and the goals of their job. Historically, however, prosecutor offices have relied on evaluation metrics that incentivize individual attorneys to prioritize more punitive responses and volume-driven activity—such as tracking the number of cases processed, indictments, guilty pleas, convictions, and sentence lengths. Under these past approaches, funding, budgeting, and promotional decisions are frequently linked to regressive measures that fail to account for just results. As more Americans have embraced the need to end mass incarceration, a new wave of reform-minded district attorneys have won elections. To ensure they are accountable to the voters who elected them into office and achieve the changes they championed, they must align measures of success with new priorities for their offices. New performance metrics predicated on the goals of reducing incarceration and enhancing fairness can shrink prison and jail populations, while improving public trust and promoting healthier and safer communities. The authors propose a new set of metrics for elected prosecutors to consider in designing performance evaluations, both for their offices and for individual attorneys. The authors also suggest that for these new performance measures to effectively drive decarceration practices, they must be coupled with careful, thoughtful implementation and critical data-management infrastructure.

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