Relevant Performance Measures Research Articles

Sampling, discounts or pay-what-you-want: Two field experiments

Free sampling and price discounts are important, popular promotional tools used to attract new customers by reducing their risk of trial. The authors investigate pay-what-you-want (PWYW) as an alternative promotional tool to free sampling and price discounts in two field experiments. The authors find significant differences in perceived promotional characteristics and relevant performance measures, such as trial and repeat purchases by new customers. The entertaining and innovative character of PWYW induces many people to try it. PWYW may yield a higher repeat purchase rate of new customers, and sellers using PWYW benefit from higher word-of-mouth behavior. Finally, PWYW yields the highest promotional revenues.

Price competition for retailers with profit and revenue targets

Price competition for retailers has been extensively studied in the literature assuming the objective of (expected) profit maximization. In this paper, we make a major contribution by studying price competition for retailers with both profit and revenue targets. Consequently, each retailer maximizes her profit and revenue probability, namely, the probability of achieving the profit and revenue targets simultaneously. More specifically, we analyze a scenario where two competing retailers purchase a perishable product from a common supplier and sell to a common market. Employing the isoelastic demand model, we derive the closed-form solutions of the optimal order quantity, the optimal selling price, and the maximal profit and revenue probability for each retailer. It is shown that when revenue is a relevant performance measure, positive and non-positive salvage values lead to different optima for competing retailers. Moreover, as price elasticity and/or price competition intensity becomes higher, the optimal retail price decreases and the optimal order quantity increases for each retailer.

Getting Performance Metrics Right: A Qualitative Study of Staff Experiences Implementing and Measuring Practice Transformation

Quality improvement is a central goal of the patient-centered medical home (PCMH) model, and requires the use of relevant performance measures that can effectively guide comprehensive care improvements. Existing literature suggests performance measurement can lead to improvements in care quality, but may also promote practices that are detrimental to patient care. Staff perceptions of performance metric implementation have not been well-researched in medical home settings. To describe primary care staff (clinicians and other staff) experiences with the use of performance metrics during the implementation of the Veterans Health Administration's (VHA) Patient Aligned Care Team (PACT) model of care. Observational qualitative study; data collection using role-stratified focus groups and semi-structured interviews. Two hundred and forty-one of 337 (72 %) identified primary care clinic staff in PACT team and clinic administrative/other roles, from 15 VHA clinics in Oregon and Washington. Data coded and analyzed using conventional content analysis techniques. Primary care staff perceived that performance metrics: 1) led to delivery changes that were not always aligned with PACT principles, 2) did not accurately reflect patient-priorities, 3) represented an opportunity cost, 4) were imposed with little communication or transparency, and 5) were not well-adapted to team-based care. Primary care staff perceived responding to performance metrics as time-consuming and not consistently aligned with PACT principles of care. The gaps between the theory and reality of performance metric implementation highlighted by PACT team members are important to consider as the medical home model is more widely implemented.

A bi-objective stochastic programming model for optimising automated material handling systems with reliability considerations

The optimisation of material handling systems (MHSs) can lead to substantial cost reductions in manufacturing systems. Choosing adequate and relevant performance measures is critical in accurately evaluating MHSs. The majority of performance measures used in MHSs are time-based. However, moving materials within a manufacturing system utilise time and cost. In this study, we consider both time and cost measures in an optimisation model used to evaluate an MHS with automated guided vehicles. We take into account the reliability of the MHSs because of the need for steadiness and stability in the automated manufacturing systems. Reliability is included in the model as a cost function. Furthermore, we consider bi-objective stochastic programming to optimise the time and cost objectives because of the uncertainties inherent in the optimisation parameters in real-world problems. We use perceptron neural networks to transform the bi-objective optimisation model into a single objective model. We use numerical experiments to demonstrate the applicability of the proposed model and exhibit the efficacy of the procedures and algorithms.

Approximate queueing models for capacitated multi-stage inventory systems under base-stock control

A queueing analysis is presented for base-stock controlled multi-stage production-inventory systems with capacity constraints. The exact queueing model is approximated by replacing some state-dependent conditional probabilities (that are used to express the transition rates) by constants. Two recursive algorithms (each with several variants) are developed for analysis of the steady-state performance. It is analytically shown that one of these algorithms is equivalent to the existing approximations given in the literature. The system studied here is more general than the systems studied in the literature. The numerical investigation for three-stage systems shows that the proposed approximations work well to estimate the relevant performance measures.

AMA Seeks APA Help in Long-Term Care of Former Inmates

Patients with criminal backgrounds are often denied admission to long-term-care facilities without considering their clinical needs or understanding how risk factors for violence can be mitigated.

A performance evaluation framework of development projects: An empirical study of Constituency Development Fund (CDF) construction projects in Kenya

The present work attempts to develop a multidimensional performance evaluation framework of development projects by considering all relevant measures of performance. In order to demonstrate the applicability of this performance evaluation framework, it has considered the case of Constituency Development Fund (CDF) projects constructed between 2003 and 2011 in Kenya and collected the viewpoints of 175 respondents comprising clients, consultants and contractors involved in the implementation of CDF projects with regard to their perception on 35 performance related variables. A five-point Likert scale was used as a response format for different variables with the assigned values ranging from 1=Strongly Disagree to 5=Strongly Agree. Exploratory factor analysis was applied to the collected data which gave rise to an instrument consisting of 27 items representing six factors. The findings further reveal that the items constituting these six factors essentially represent six key performance indicators (KPIs) namely time, cost, quality, safety, site disputes and environmental impact. The relative influence of each KPI towards overall performance of construction projects shows that time is the most important measure followed by cost while safety comes last in order of importance in the performance evaluation of CDF construction projects. The findings of this study have significant bearing on other similar kind of development projects undertaken in developing countries.

Best Practices of High‐Performing Employees: Rewards and Performance in a Balanced Scorecard Environment

AbstractThe balanced scorecard captures strategically relevant performance measures used as part of a per‐formance evaluation system. These systems often include financial and nonfinancial rewards intended to motivate employees to take actions aligned with corporate strategy. Yet recent literature finds that rewards can have the opposite of intended effects. We consider the best practices of high‐performing banking employees in the context of a balanced scorecard system that provides financial and nonfinan‐cial rewards for performance. Further, we consider the strategic, contextual environment in which these institutions compete. © 2013 Wiley Periodicals, Inc.

Achieving a step change in the optimal sensory design of buildings for users at all life-stages

A general gap in knowledge around the holistic impact of spaces on human performance is identified. It is argued that filling this gap demands that the conceptual and methodological complexity of real world users' experiences of built spaces is addressed. It is argued that a potentially productive way forward is to use multi-level modelling within a neuroscience-informed, holistic sensory approach. Published results are highlighted in support of this approach, focused particularly on primary schools.The potential of expanding this approach to a full range of life-stages is then explored, building on a view of the brain as it evolves across the human life-span. The separation of left/right-brain cognitive processes emerges as being potentially important as an intervening variable. The schools' data is re-analysed by subject using multi-level modelling to provide, maybe for the first time, proof of concept evidence of variations in the optimal space characteristics depending on brain lateralisation.In addition significant differences are identified in the particular types of spaces involved and the relevant measures of human performance. These range from: classrooms and learning for school pupils; to offices and productivity for workers; to housing and well-being for the elderly.The train of argument is brought together around a vision for the development of a general model for holistic sensory space design. This would address a number of life-stages and, through a progressive meta-analysis, it is suggested that, over time, an evidenced, whole-life perspective on the holistic impact of spaces on human performance can be achieved.

Psychometric effects of adding realism to a speech-in-noise test

The speech reception threshold (SRT) is routinely measured in the laboratory to assess speech understanding in noise, but is often reported to be a poor predictor of performance in real world listening situations. The overall goal of this work is to determine whether introducing realistic aspects to speech tests can better capture individual differences and ultimately produce more relevant performance measures. We examined the psychometric effects of (a) transplanting a standard sentence-in-noise test into a simulated reverberant cafeteria environment, and (b) moving from sentence recall to a new ongoing speech comprehension task. Participants included normal hearers and hearing-impaired listeners (who were tested with and without their hearing aids). SRTs in the cafeteria environment were significantly correlated with standard SRTs, but were poorer overall and more sensitive to hearing loss. The comprehension task, despite having very different demands to sentence recall, produced similar SRTs under these conditions. The benefit of hearing aids was weakly correlated across the two listening environments and the two listening tasks. These manipulations promise to be useful for the creation of realistic laboratory tests that are engaging and challenging, yet controlled enough to be useful for psychophysical experiments.

Re: "Clinical Usefulness of the Framingham Cardiovascular Risk Profile beyond Its Statistical Performance: The Tehran Lipid and Glucose Study"

Khalili et al. (1) evaluated the clinical utility of the Framingham cardiovascular risk model in a Middle Eastern cohort study. We commend the authors for their use of highly relevant measures of model performance, the net benefit (2, 3) and net benefit fraction (4, 5). However, we would like to make several points regarding their interpretation and reporting of these measures. Interpretation of the net benefit and net benefit fraction The population net benefit (NB) of a risk model, used to classify individuals as being at high 10-year risk of cardiovascular disease using the risk threshold rH, is (1) where B is the benefit of classifying as high-risk a subject who would develop cardiovascular disease absent treatment (a “cardiovascular event”), H is the harm of classifying as high-risk a subject who would not develop cardiovascular disease absent treatment (a “cardiovascular nonevent”), TPR(rH) and FPR(rH) are the true- and false-positive rates associated with this risk threshold, and ρ is the proportion of subjects who experience cardiovascular events. Vickers and Elkin (2) set B to 1, so that the units are true positive classifications, and use the optimal risk threshold rH = H/H + B (6) in order to rewrite equation 1 as (2) Baker et al. (4, 5) scale equation 2 by ρ, which is the maximum possible net benefit for a model that classifies as high-risk all cardiovascular events and all others as low-risk. The net benefit fraction (NBF) is therefore (3) Khalili et al. interpret NBF(0.2) = 0.156 for the Framingham risk model applied to women as “the fraction of the incidence rate that could be predicted and prevented” (1, p. 178). However, this is not a valid interpretation. Their interpretation seems to relate to the TPR of the model, whereas NBF(0.2) = 0.156 is more accurately interpreted as a discounted TPR; the TPR is offset by the FPR where false-positives are put on the same scale as true-positives (7). We prefer to interpret NBF(0.2) = 0.156 as the same benefit that would be achieved by classifying as high-risk 15.6% of cardiovascular events and none of the nonevents (2, 3). The authors' interpretation also suggests that all cardiovascular events classified as high-risk would necessarily be prevented; however, this would depend on the efficacy of subsequent interventions. Net benefit for different subsets of the population Net benefit curves, which plot the net benefit in equation 2 versus the risk threshold rH (2, 3), are also used by Khalili et al. The authors recommend these curves for examining the net benefit for a range of risk thresholds, given that different patient subgroups may have different side effects of interventions and therefore different risk thresholds. However, the net benefit curve shows the total population net benefit at each risk threshold. Two points on the curve cannot be interpreted as the net benefits for 2 different subpopulations because, if the risk distribution in the subpopulation differs from the risk distribution in the whole population, the net benefit in the subpopulation is different from the net benefit in the whole population at that threshold. For example, men and women in the Middle Eastern cohort have different values for TPR, FPR, and ρ and therefore have net benefits that differ from the population net benefit shown on the net benefit curve. Recommendation We have several practical recommendations. The first is to stratify any analysis by important patient characteristics that affect risk threshold—for example, gender as in the study by Khalili et al. (1). The second is to report the net benefit fraction together with its constituents, the TPR and FPR, over a range of risk thresholds. Seeing these individual components helps in digesting the net benefit. Knowing the TPR and FPR is also helpful when risk thresholds are chosen “irrationally.” That is, the net benefit in equation 2 assumes that the risk threshold reflects the cost-benefit ratio, rH = H/H + B. However, individuals or policy-makers may choose risk thresholds in ways that do not reflect the cost-benefit ratio. For example, in their commentary accompanying Khalili et al.'s article, D'Agostino and Pencina (8) suggest that the risk threshold rH = 0.2 was chosen without regard to cost-benefit considerations. Reporting the TPR and FPR as a function of risk threshold allows the reader to choose a threshold and to perform any calculus desired to take into consideration both components of model performance.

University performance evaluations: what are we really measuring?

Surveying students to garner feedback on teaching and subject quality is a common occurrence in many universities globally. Despite the criticisms surrounding whether measures associated with these surveys are indeed valid, university managers continue to utilise them in key decision making. These surveys mirror business practices where measuring customer satisfaction via surveys is common. However, some argue that universities are misdirected in measuring satisfaction as a proxy for teaching quality, possibly subverting the potentially conflicting objective of student learning. Even so, both student satisfaction and student learning can be relevant performance measures. Accordingly, we have developed two robust measures of these constructs. We argue that student learning can be measured and used to provide formative feedback for improving teaching effectiveness. Alternatively, student satisfaction can be appropriate for determining whether students are ‘enjoying’ their studies, and likewise offers distinct benefits to university managers measuring performance outcomes.

Natural resource based green supply chain management

PurposeThe aim of this paper is to conceptualise a structural model of natural resource based green supply chain management (GSCM), and its relationship, with an indication of cause and effect, to relevant performance measures and drivers.Design/methodology/approachThe literature, describing GSCM from a natural resource based view (NRBV), along with performance measures and institutional drivers, is critically evaluated and used to develop the model.FindingsConstructs are identified in terms of intra‐ and inter‐organisational environmental practices, performance measures and institutional drivers. Causal relationships, within and between the constructs, are also proposed in the form of hypotheses.Research limitations/implicationsAt this stage the model is purely conceptual and the causal relationships are only proposed. Empirical tests of the model and hypotheses are required.Practical implicationsOn empirical verification, this work can furnish managers with validated measurement scales to evaluate their strengths and weaknesses in their GSCM implementation and determine how firms can successfully implement GSCM to promote sustainable industrial development.Originality/valueGSCM from within the NRBV perspective, and incorporating performance measures and institutional drivers, has yet to be comprehensively synthesised in a coherent model. This conceptual work is the first step in that direction.

Model evaluation of RIMPUFF within complex terrain using an <SUP align="right">41</SUP>Ar radiological dataset

The newly updated atmospheric dispersion model RIMPUFF is evaluated using routine releases of 41 Ar from the former HIFAR research reactor located in Sydney, Australia. A large number of 41Ar measurements from a network of environmental gamma detectors are used to evaluate the model under a range of atmospheric stability conditions within the complex terrain area. Model sensitivity of input data is analysed including meteorological station data, land use maps, surface roughness and wind interpolation schemes. Various model evaluation tools are used such as gamma dose rate plots, exploratory data analyses and relevant statistical performance measures.

Effects on muscle performance of NSAID treatment with Piroxicam versus placebo in geriatric patients with acute infection-induced inflammation. a double blind randomized controlled trial

BackgroundInflammation is the main cause of disease-associated muscle wasting. In a previous single blind study we have demonstrated improved recovery of muscle endurance following celecoxib treatment in hospitalized geriatric patients with acute infection. Here we further evaluate NSAID treatment with piroxicam in a double blind RCT and investigate the role of cytokines and heat shock proteins (Hsp) with respect to muscle performance. We hypothesized that NSAID treatment would preserve muscle performance better than antibiotic treatment alone, by reducing infection-associated inflammation and by increasing expression of cytoprotective Hsp.MethodsConsecutive admissions to the geriatric ward were screened. 30 Caucasian patients, median age 84.5 years, with acute infection-induced inflammation and serum levels of CRP > 10 mg/L were included and randomized to active treatment with 10 mg piroxicam daily or placebo. Assessment comprised general clinical and biochemical parameters, 25 cytokines in serum, intra-and extracellular Hsp27 and Hsp70, Elderly Mobility Scale (EMS) scores, grip strength (GS), fatigue resistance (FR) and lean body mass (LBM). Patients were evaluated until discharge with a maximum of 3 weeks after treatment allocation.ResultsEMS scores, FR and grip work (GW), a measure taking into account GS and FR, significantly improved with piroxicam, but not with placebo. Early decreases in IL-6 serum levels with piroxicam correlated with better muscle performance at week 2. Basal expression of Hsp27 in monocytes without heat challenge (WHC) was positively correlated with FR at baseline and significantly increased by treatment with piroxicam compared to placebo. Profound modifications in the relationships between cytokines or Hsp and changes in muscle parameters were observed in the piroxicam group.ConclusionsPiroxicam improves clinically relevant measures of muscle performance and mobility in geriatric patients hospitalized with acute infection-induced inflammation. Underlying mechanisms may include modifications in the cytokine network and increases in monocytic expression of cytoprotective Hsp27.Trial registration numberISRCTN: ISRCTN96340690

The Second Stroke Audit of Catalonia Shows Improvements in Many, but Not all Quality Indicators

Periodic audits allow monitoring of healthcare quality by comparing performances at different time points. Aims To assess quality of in-hospital stroke care in Catalonia in 2007 and compare it with 2005 (post-/preguidelines delivery, respectively). Data on 13 evidence-based performance measures were collected by a retrospective review of medical records of consecutive stroke admissions (January-December 2007) to 47 acute hospitals in Catalonia. Adherence was calculated according to the ratio (patients with documented performance measures' compliance) (valid cases for that measure). Sampling weights were applied to produce estimates of compliance. The proportions of compliance with performance measures in both audits were compared using random-effects logistic regressions, with each performance measure as the dependent variable and audit edition as the explanatory variable to determine whether changes in stroke care quality occurred along time. We analyzed 1767 events distributed among 47 hospitals. In 2007, there was an increase in tissue plasminogen activator administrations (2·8% vs. 5·9%) and stroke unit admissions (16·6% vs. 22·6%) and a reduction in seven-day mortality (9·5% vs. 6·8%). Logistic regression models provided evidence of improved adherences to seven performance measures (screening of dysphagia, management of hyperthermia, baseline computed tomography scan, baseline glycemia, rehabilitation needs, early mobilization, and anticoagulants for atrial fibrillation), but worsening of management of hypertension, dyslipidemia, and antithrombotics at discharge. The remaining three performance measures showed no changes. The Second Stroke Audit showed improvements in most dimensions of care, although unexpectedly a few but relevant performance measures became worse. Therefore, periodic stroke audits are needed to check changes in quality of care over time.

Response—Education Research: Set a High Bar

Torgerson and Derting et al. 's concerns may be the result of the difference in publication styles between hard sciences and education research literature. Education publications are largely self-contained, whereas research papers in hard science journals present results in a condensed form, requiring readers to be familiar with the relevant literature to fully appreciate the paper. Torgerson and Derting et al. would like to apply experimental design expectations for research in K-12 classes to research in introductory science classes at large universities. However, these practices often are neither necessary nor useful in this context. It is well documented that the student characteristics in a large introductory university science course are remarkably consistent over time [e.g., ([ 1 ][1], [ 2 ][2])]. Barring a change in admissions standards, an introductory science course will have the same very limited and well-characterized slice of the population each year. The teacher content mastery is also uniformly high. The large class sizes further reduce the variability across sections. The number and influence of confounding variables is therefore low relative to the K-12 setting. This makes randomized control trials unnecessary in this setting, particularly if there are relevant pretreatment measures of student performance (as in Table 1). Torgerson raises the possibility of attrition bias. To clarify, the numbers did not reflect attrition, but rather a continuation of the attendance patterns displayed in the previous weeks. The number of students who took the test was consistent with data on previous attendance; in both sections students who took the test had higher overall attendance and higher average midterm scores than those who did not take the test. Both Letters raise concerns that we did not consider how the “teacher effect” might affect our results. References 1, 2, 5, and 10 in our Report show that the characteristics of teachers, other than the pedagogy they use, have little impact on the amount of learning in introductory physics courses. The pretreatment data on the two sections (Table 1) further supports this assertion. Derting et al. argue that well-designed studies must use “validated assessment tools.” Although there is value in using such instruments where possible, we strongly disagree with such a sweeping assertion. First, this would constrain science education research to an extremely small number of topics for which such instruments exist. Second, there is great value in research that demonstrates to faculty members that, by teaching differently, they can help their students perform better on the tests they already use. Finally, we are troubled by the lack of concern with ethical issues in the calls for this study to be replicated in other classrooms before the results can be accepted. This experiment involved real students in a real course. Given the results, we concluded that any student in the control group of such a replication experiment would suffer very real harm to their education. 1. [↵][3]1. E. F. Redish, 2. P. J. Cooney 1. C. Crouch, 2. J. Watkins, 3. A. P. Fagen, 4. E. Mazur , in Research-Based Reform of University Physics, Vol. 1, E. F. Redish, P. J. Cooney , Eds. (American Association of Physics Teachers, College Park, MD, 2007); [www.compadre.org/Repository/document/ServeFile.cfm?ID=4990&DocID=241][4]. 2. [↵][5]1. L. Ding, 2. N. W. Reay, 3. A. Lee, 4. L. Bao , Phys. Rev. ST Phys. Educ. Res. 4, 010112 (2008). [OpenUrl][6][CrossRef][7] [1]: #ref-1 [2]: #ref-2 [3]: #xref-ref-1-1 View reference 1 in text [4]: http://www.compadre.org/Repository/document/ServeFile.cfm?ID=4990&DocID=241 [5]: #xref-ref-2-1 View reference 2 in text [6]: {openurl}?query=rft.jtitle%253DPhys.%2BRev.%2BST%2BPhys.%2BEduc.%2BRes.%26rft.volume%253D4%26rft.spage%253D010112%26rft_id%253Dinfo%253Adoi%252F10.1103%252FPhysRevSTPER.4.010112%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [7]: /lookup/external-ref?access_num=10.1103/PhysRevSTPER.4.010112&link_type=DOI

Analysis of passenger queues at airport terminals

This paper presents an approach for analyzing passenger queueing processes at several stages of the service chain in airport terminals with a focus on passenger check-in systems. The queueing process at the check-in is driven by the arrival process of the passengers and the service process, including the desired technical and personnel resources. The key features of these systems are the time-dependent process of arrivals, generally distributed processing times, and systems with multiple servers. Time dependent service quality measures are analyzed, which are related to managerial decisions about the required number of check-in operators. Different analytical methods are reviewed to derive service quality measures for such dynamic and stochastic systems. Due to the dynamics in the demand and in the provided capacity, the use of standard queueing models is rather limited. A stationary backlog carryover (SBC) approach is developed to approximate the relevant performance measures. Numerical experiments demonstrate the reliability of these different approaches. Based on economies of scale, positive effects for common check-in operations can be shown.

Mismatched Bit-Interleaved Coded Noncoherent Orthogonal Modulation

We consider several low-complexity decoding metrics for bit-interleaved coded modulation (BICM) with orthogonal signaling and noncoherent detection. Using the generalized mutual information (GMI) as the relevant performance measure, we demonstrate that only a small performance degradation is entailed by using these mismatched metrics instead of the maximum likelihood (matched) metric. Furthermore, for coded transmission with sum-product symbol-by-symbol (SBS) decoding, we illustrate that metric scaling with a constant factor can improve the throughput performance of these metrics.

Outcomes Research and Epidemiology

Outcomes research was defined in 1998 as “the study of the end results of health services that takes patients' experiences, preferences, and values into account … intended to provide scientific evidence relating to decisions made by all who participate in health care.”1 Inherent to this definition is the fact that outcomes research is multidisciplinary and relies on diverse domains of expertise, with an explicit goal of direct relevance to the care delivered to patients. Within this multidisciplinary framework, epidemiology is one of the disciplines related to the field of outcomes research. Epidemiology is the study of distribution and determinants of disease frequency in human populations, with a particular focus on the occurrence of disease as categorized by time, place, and persons.2 Sometimes referred to as the basic science in medicine,3,4 epidemiology is founded on principles and methods (including methods of statistical analysis) that form the basis of clinical research.3,4 The fundamental constructs that epidemiology embraces are key to the conduct of outcomes research today. Indeed, envisioning the burden of disease through the lenses of the traditional epidemiological constructs of time and person can provide powerful guidance to shape the direction of outcomes research and assess its impact. This Editor's Perspective shares a few examples to illustrate this point. In a Shattuck Lecture published in the New England Journal of Medicine , Eugene Braunwald5 designated heart failure as a new epidemic of cardiovascular disease. This eloquent statement generated thought-provoking questions: Was there, indeed, an epidemic of heart failure in the epidemiological sense of the word? If so, is the epidemic driven by increase in incidence, improvement in survival, or both? These questions inspired epidemiologists to conduct the needed formal investigation of the heart failure epidemic, which meant bringing to bear rigorous epidemiological …