Specific Performance Measures Research Articles

Classification of seed members of five riboswitch families as short sequences based on the features extracted by Block Location-Based Feature Extraction (BLBFE) method.

Introduction: Riboswitches are short regulatory elements generally found in the untranslated regions of prokaryotes’ mRNAs and classified into several families. Due to the binding possibility between riboswitches and antibiotics, their usage as engineered regulatory elements and also their evolutionary contribution, the need for bioinformatics tools of riboswitch detection is increasing. We have previously introduced an alignment independent algorithm for the identification of frequent sequential blocks in the families of riboswitches. Herein, we report the application of block location-based feature extraction strategy (BLBFE), which uses the locations of detected blocks on riboswitch sequences as features for classification of seed sequences. Besides, mono- and dinucleotide frequencies, k-mer, DAC, DCC, DACC, PC-PseDNC-General and SC-PseDNC-General methods as some feature extraction strategies were investigated. Methods: The classifiers of the Decision tree, KNN, LDA, and Naïve Bayes, as well as k-fold cross-validation, were employed for all methods of feature extraction to compare their performances based on the criteria of accuracy, sensitivity, specificity, and f-score performance measures. Results: The outcome of the study showed that the BLBFE strategy classified the riboswitches indicating 87.65% average correct classification rate (CCR). Moreover, the performance of the proposed feature extraction method was confirmed with average values of 94.31%, 85.01%, 95.45% and 85.38% for accuracy, sensitivity, specificity, and f-score, respectively. Conclusion: Our result approved the performance of the BLBFE strategy in the classification and discrimination of the riboswitch groups showing remarkable higher values of CCR, accuracy, sensitivity, specificity and f-score relative to previously studied feature extraction methods.

Health systems and global progress towards malaria elimination, 2000\u20132016

BackgroundAs more countries progress towards malaria elimination, a better understanding of the most critical health system features for enabling and supporting malaria control and elimination is needed.MethodsAll available health systems data relevant for malaria control were collated from 23 online data repositories. Principal component analysis was used to create domain specific health system performance measures. Multiple regression model selection approaches were used to identify key health systems predictors of progress in malaria control in the 2000–2016 period among 105 countries. Additional analysis was performed within malaria burden groups.ResultsThere was large heterogeneity in progress in malaria control in the 2000–2016 period. In univariate analysis, several health systems factors displayed a strong positive correlation with reductions in malaria burden between 2000 and 2016. In multivariable models, delivery of routine services and hospital capacity were strongly predictive of reductions in malaria cases, especially in high burden countries. In low-burden countries approaching elimination, primary health center density appeared negatively associated with progress while hospital capacity was positively correlated with eliminating malaria.ConclusionsThe findings presented in this manuscript suggest that strengthening health systems can be an effective strategy for reducing malaria cases, especially in countries with high malaria burden. Potential returns appear particularly high in the area of service delivery.

A Meta-Analysis on the Impact of Social Capital on Firm Performance in China’s Transition Economy

There is almost no research consensus on the influence of social capital on firm performance in China, which motivates our study in this paper. Our research aim here is to identify the effect of contextual and methodological moderators on the relationship between social capital and firm performance in China’s transition economy. Meta-analysis is employed to explore the impact of social capital on firm performance and to identify moderators affecting the relationship based on 106 independent studies between 2008 and 2018. The results demonstrate that the social capital–performance link is positive and significant in China. Particularly, social capital has a stronger positive relationship with performance in high-tech industries or in low-level marketization. Meanwhile, the social capital–performance link depends on the specific performance measures and dimensions. The paper clearly indicates the value of cultivating social capital and reveals that distinct types of social capital are needed at different points in different industries and market areas.

Frameworks for health systems performance assessment: how comprehensive is Ghana\u2019s holistic assessment tool?

BackgroundMeasuring the performance of a health system is an essential requirement in creating systems that generate efficient, equitable, patient-focused, accessible and sustainable results. A fundamental requirement for a performance measurement system is the development of an assessment framework within which specific performance measures could be defined and applied regularly. This paper examines the comprehensiveness of Ghana’s health system assessment framework called the Holistic Assessment Tool in relation to some of the internationally recognized frameworks. The paper also analyzes trends in the performance of the health system to understand whether or not an improvement has been recorded following the adoption and implementation of the Holistic Assessment Tool.MethodsMainly secondary data were used in this analysis. Searches were conducted on Google Scholar, PubMed, Scopus and Science Direct between May and July, 2019 for published documents on health system performance assessment. We also obtained unpublished documents from Ghana’s Ministry of Health, Ghana Health Service website, and Ghana Statistical Service database. Descriptive statistics were used to examine trends in the performance of the Ghanaian health system.ResultsWhile the tool provides a national framework for evaluating the performance of the Ghana Health system in several domains, the Holistic Assessment Tool does not cover key health system domains such as information systems for health, access to essential medicines, and patient-centeredness. Also, the scope of the assessment program seems limited to the evaluation of the Ministry of Health’s annual plans, programs and projects. However, the health system has recorded improvements in population health indicators, such as life expectancy at birth, infant mortality, under-5 mortality, HIV prevalence and disease burden (in terms of disability adjusted life years).ConclusionsThe Holistic Assessment Tool is a useful framework, but needs further refinement, both in scope and in conceptual robustness. Future studies should consider exploring factors influencing performance of the Ghanaian health system. Such information will help in strategizing for better and more improvements.

Medição de desempenho:

A presente pesquisa tem por objetivo identificar o nível de aderência ao framework de medidas de desempenho utilizadas pelas aceleradoras do estado do Paraná para acompanhar o desenvolvimento das startups. Possui como objeto de estudo as aceleradoras do estado do Paraná, tendo como população estimada 09 empresas. A coleta de dados foi realizada por meio de questionários semiestruturados. Utilizou-se de estatística descritiva para realizar a análise dos dados. Os resultados apontaram uma baixa aderência ao framework entre as aceleradoras paranaenses, tanto para medidas financeiras quanto para não financeiras. Contudo, verificou-se que alguns indicadores financeiros e não financeiros possuem um nível satisfatório de aderência, concluindo-se então que as aceleradoras paranaenses se utilizam de medidas de desempenho no processo de aceleração. Verificou-se também que as aceleradoras em sua grande maioria prezam por utilizar medidas de desempenho específicas em cada etapa do ciclo de vida das startups e de acordo com cada modelo de negócio, conforme sugere a literatura.

Prioritizing Physical Determinants of International Elite Pole Vaulting Performance.

Gross, M, Büchler Greeley, N, and Hübner, K. Prioritizing physical determinants of international elite pole vaulting performance. J Strength Cond Res 34(1): 162-171, 2020-The pole vault is a complex track and field discipline requiring speed, strength, and efficient technique. Strength is a fundamental physical requirement, which facilitates general sprinting ability; this in turn represents the exploitable potential during the approach, where kinetic energy for the subsequent vault is generated. This study investigated the relationships between pole vault height, approach speed, sprint-speed potential, and indicators of both explosive and reactive strength in 20 international female pole vaulters. Furthermore, changes in step characteristics between flying sprints and approach runs were analyzed. Data were collected during and after an international pole vault competition. The correlations between approach speed and vault height, between sprint speed and approach speed, and between explosive strength indicators and sprint speed were large or very large. However, the correlation between reactive strength and sprint speed was small. Differences in speed during the vault approach compared with the flying sprint are mainly due to reduced step length rather than lower step frequency. With the help of a flow chart and regression equations, sound decisions can be made regarding the prioritization of various training components of pole vaulters. With this tool, coaches and athletes can easily evaluate whether or not a facilitator ability is sufficient for improving a more specific performance measure on the way to the central criterion: pole vault height. Furthermore, the results of this study suggest that maintaining step length should be emphasized during approach drills to best exploit sprint-speed potential during the pole vault approach.

Exploring the Rationale of Performance Based Funding for Malaysian Public Universities

The intention of this paper is to discuss the rationale for Malaysian public universities to implement Performance Based Funding (PBF) mechanism. Here, the funding mechanisms are systems based on allocating a proportion of education budgets relative to specific performance measures such as course completion, credit attainment, and degree completion, instead of allocating funding entirely based on enrolment alone. The implementation of PBF mechanisms has recently become a topic of heated debate in the education sector worldwide which has also increased the interest of researchers and policymakers to work on it. Since almost no study has looked into the applicability of PBF in Malaysia with the aims to contribute knowledge and fill the gap in the current research. Semi-structured interviews were conducted to answer the objective of this study. The positive functions of qualitative research methodology are to show that it can assist the researcher in obtaining in-depth information and to understand the subjective experience of the respondents. Thus, in this procedure, semi-structured interviews were adopted and targeted to obtain information regarding the applicability of the PBF mechanism from the budgeting and financial aspects. Participants who encompassed in semi-structured interviews were the senior officer from the Bursar Office of selected universities. The findings from the qualitative data showed that PBF mechanism is suitable to be implemented at Malaysian public universities. However, there were several issues that the government needs to be addressed before the PBF mechanism can be successfully implemented.

Performance Indicators for Colposcopy in Ontario.

This study sought to evaluate the delivery of colposcopy assessments and treatments in Ontario from 2009 to 2017 according to specific performance measures, derived from guidelines on colposcopy use. This population-based descriptive analysis included screen-eligible women ages 21 to 69 in Ontario who underwent cervical screening between 2009 and 2017. Performance measures that describe the quality of colposcopy services in the province were calculated. Five performance measures were used to assess the use of colposcopy in Ontario from 2009 to 2017. From 2013 to 2017, the percentage of women seen for colposcopy after a first diagnosis of atypical squamous cells of undetermined significance (ASCUS), without evidence of repeat cytology, remained stable, ranging from 5.9% to 6.3%. The median wait time to colposcopy for atypical glandular cells (AGC), atypical squamous cells (ASC-H), cannot rule out high-grade squamous intraepithelial lesions, and high-grade squamous intraepithelial lesions (HSIL), remained relatively stable from 2013 to 2017. In addition, the percentage of women with high-grade Pap test results who were seen in colposcopy within 6 months increased from 74.7% to 83.5%. The percentage of women who were not seen in follow-up within 12 months after treatment for cervical dysplasia remained stable, as did the percentage of women who discontinued colposcopy after three normal Pap test results following treatment for cervical dysplasia. This study developed five performance indicators and used them to assess the delivery of colposcopic services in Ontario from 2009 to 2017. Performance indicators have previously been used effectively in the field of colorectal cancer screening to identify strengths and weaknesses in the delivery of healthcare services. This had never previously been done in colposcopy.

Communication Patterns in Remote, Interactive Surgical Training

The present study examines process and outcome measures associated with three forms of support for conducting an unfamiliar surgical task: an unaided control condition, a video resource condition and a remotely-located mentor. Twenty-eight surgeons performed four different uncommon trauma procedures while thinking aloud in either the control or video condition or exchanging dialogue with an available mentor. Focusing on the upper and lower fasciotomies here, we analyzed verbal content using LIWC metrics and specially composed dictionaries based on Speech Act Theory. Both procedure-specific and subjective performance measures distinguish between experimental conditions, favoring the mentoring condition. Mentor presence also changes the surgeons’ verbal data. Verbal data are correlated with the procedure specific performance measures across all conditions but have no relationship to the subjective measure. Focus on the status of the procedure is reinforced by the mentor’s presence and indicates potential opportunities for augmenting the video intervention.

Development of a clinical prediction model for the onset of functional decline in people aged 65\u201375 years: pooled analysis of four European cohort studies

BackgroundIdentifying those people at increased risk of early functional decline in activities of daily living (ADL) is essential for initiating preventive interventions. The aim of this study is to develop and validate a clinical prediction model for onset of functional decline in ADL in three years of follow-up in older people of 65–75 years old.MethodsFour population-based cohort studies were pooled for the analysis: ActiFE-ULM (Germany), ELSA (United Kingdom), InCHIANTI (Italy), LASA (Netherlands). Included participants were 65–75 years old at baseline and reported no limitations in functional ability in ADL at baseline. Functional decline was assessed with two items on basic ADL and three items on instrumental ADL. Participants who reported at least some limitations at three-year follow-up on any of the five items were classified as experiencing functional decline. Multiple logistic regression analysis was used to develop a prediction model, with subsequent bootstrapping for optimism-correction. We applied internal-external cross-validation by alternating the data from the four cohort studies to assess the discrimination and calibration across the cohorts.ResultsTwo thousand five hundred sixty community-dwelling people were included in the analyses (mean age 69.7 ± 3.0 years old, 47.4% female) of whom 572 (22.3%) reported functional decline at three-year follow-up. The final prediction model included 10 out of 22 predictors: age, handgrip strength, gait speed, five-repeated chair stands time (non-linear association), body mass index, cardiovascular disease, diabetes, chronic obstructive pulmonary disease, arthritis, and depressive symptoms. The optimism-corrected model showed good discrimination with a C statistic of 0.72. The calibration intercept was 0.06 and the calibration slope was 1.05. Internal-external cross-validation showed consistent performance of the model across the four cohorts.ConclusionsBased on pooled cohort data analyses we were able to show that the onset of functional decline in ADL in three years in older people aged 65–75 years can be predicted by specific physical performance measures, age, body mass index, presence of depressive symptoms, and chronic conditions. The prediction model showed good discrimination and calibration, which remained stable across the four cohorts, supporting external validity of our findings.

Performance evaluation framework of Wyoming connected vehicle pilot deployment program: summary of Phase 2 pre-deployment efforts and lessons learned

Purpose This paper aims to present a summary of the performance measurement and evaluation plan of the Wyoming connected vehicle (CV) Pilot Deployment Program (WYDOT Pilot). Design/methodology/approach This paper identified 21 specific performance measures as well as approaches to measure the benefits of the WYDOT Pilot. An overview of the expected challenges that might introduce confounding factors to the evaluation effort was outlined in the performance management plan to guide the collection of system performance data. Findings This paper presented the data collection approaches and analytical methods that have been established for the real-life deployment of the WYDOT CV applications. Five methodologies for assessing 21 specific performance measures contained within eight performance categories for the operational and safety-related aspects. Analyses were conducted on data collected during the baseline period, and pre-deployment conditions were established for 1 performance measures. Additionally, microsimulation modeling was recommended to aid in evaluating the mobility and safety benefits of the WYDOT CV system, particularly when evaluating system performance under various CV penetration rates and/or CV strategies. Practical implications The proposed performance evaluation framework can guide other researchers and practitioners identifying the best performance measures and evaluation methodologies when conducting similar research activities. Originality/value To the best of the authors’ knowledge, this is the first research that develops performance measures and evaluation plan for low-volume rural freeway CV system under adverse weather conditions. This paper raised some early insights into how CV technology might achieve the goal of improving safety and mobility and has the potential to guide similar research activities conducted by other agencies.

Asymptotic Network Robustness

This paper examines the dependence of network performance measures on network size and considers scaling results for large networks. We connect two performance measures that are well studied, but appear to be unrelated. The first measure is concerned with energy metrics, namely, the $\mathcal {H}_2$ -norm of a network, which arises in control theory applications. The second measure is concerned with the notion of “tail risk,” which arises in economic and financial networks. We study the question of why such performance measures may deteriorate at a faster rate than the growth rate of the network. We first focus on the energy metric and its well-known connection to controllability Gramian of the underlying dynamical system. We show that undirected networks exhibit the most graceful energy growth rates as network size grows. This rate is quantified completely by the proximity of the spectral radius to unity or distance to instability. In contrast, we show that the simple characterization of energy in terms of network spectrum does not exist for directed networks. We demonstrate that for any fixed distance to instability, energy of a directed network can grow at an exponentially faster rate. We provide general methods for manipulating networks to reduce energy. In particular, we prove that certain operations that increase the symmetry in a network cannot increase energy (in an order sense). Additionally, we demonstrate that such operations can effectively reduce energy for many network topologies. Second, we focus on tail risk in economic and financial networks. In contrast to the $\mathcal {H}_2$ -norm, which arises from computing the expectation of energy in the network, tail risk focuses on tail probability behavior of network variables. Although the two measures differ substantially, we show that they are precisely connected through the system Gramian. This surprising result explains why topology considerations rather than specific performance measures dictate the large-scale behavior of networks. Finally, we demonstrate the consistency of our theory with simulations on synthetic and real-life networks.

Identification and ranking of specific balanced scorecard performance measures for hospitals: A case study of private hospitals in the Klang Valley area, Malaysia.

Performance measurement is a necessity for private hospitals as they need to be efficient, attract customers, increase profitability, and survive in the competitive environment of the health care industry. Hospitals typically struggle to identify appropriate performance measures because of lack of reliable source of performance measures for private hospitals. Despite numerous studies on performance measurement, few studies have focused on performance measures in private hospitals. This paper aims to fill that gap by identifying and ranking a specific set of performance measures that are feasible and relevant for private hospitals. Forty-four health care performance measures in four balanced scorecard (BSC) performance perspectives (financial, customer, internal business processes, and learning and growth) were compiled and filtered based on "feasibility" and "relevance" criteria using a questionnaire survey in private hospitals in the Klang Valley area, Malaysia. Since all collected data were in numeric format, data analysis was performed quantitatively. Consequently, 31 BSC performance measures were identified for private hospitals. Next, the 31 performance measures went through a ranking survey in Klang Valley private hospitals. Therefore, a weight between 0 and 1 with a range of 0.095 to 0.207 was obtained for each performance measure to help hospitals quantify their overall performance more accurately.

Multilayer analysis of supply chain strategies’ impact on sustainability

Integrating lean, green and resilient strategies into Supply Chain (SC) decisions is a key success factor for transformation toward sustainability. These strategies are increasingly common in the SC, although their implementation and results are not the same across different SC levels (Tier 1, 2 and 3 suppliers and the focal company). In spite of this, earlier studies have not explored in detail their effects on environmental, economic and social sustainability dimensions nor differentiated between SC levels and therefore implementation strategies overlook the difference between these levels. Accordingly, a novel multilevel analysis of the aerospace manufacturing SC based on Interpretive Structural Modeling (ISM) is carried out. This approach allows exploring the effects of combining lean, green and resilient strategies on specific sustainability performance measures in the aerospace manufacturing SC. The findings reveal differences between SC levels on the effects of lean, green and resilient strategies on the different sustainability dimensions. Additionally, Tiers 2 and 3 show a higher resistance or lower implication in the development of lean, green and resilient strategies than the focal company and Tier 1 companies. Final ISM models become a useful tool for managers to specifically establish coordinated long-term SC sustainability programs for each SC level.

Multi-valued measures in DEA in the presence of undesirable outputs

Data envelopment analysis (DEA) evaluates the relative efficiency of a set of comparable decision making units (DMUs) with multiple performance measures (inputs and outputs). Classical DEA models rely on the assumption that each DMU can improve its performance by increasing its current output level and decreasing its current input levels. However, undesirable outputs (like wastes and pollutants) may often be produced together with desirable outputs in final products which have to be minimized. On the other hands, in some real-world situations, we may encounter some specific performance measures with more than one value which are measured by various standards. In this study, we referee such measures as multi-valued measures which only one of their values should be selected. For instance, unemployment rate is a multi-valued measure in economic applications since there are several definitions or standards to measure it. As a result, selecting a suitable value for a multi-valued measure is a challenging issue and is crucial for successful application of DEA. The aim of this study is to accommodate multi-valued measures in the presence of undesirable outputs. In doing so, we formulate two individual and summative selecting directional distance models and develop a pair of multiplier- and envelopment-based selecting approaches. Finally, we elaborate applicability of the proposed method using a real data on 183 NUTS 2 regions in 23 selected EU-28 countries.

Exposure to in utero inflammation increases locomotor activity, alters cognitive performance and drives vulnerability to cognitive performance deficits after acute immune activation

Fetal exposure to intrauterine inflammation (IUI) affects brain development. Using intrauterine lipopolysaccharide (LPS) administration to induce a localized, rather than a systemic, inflammation, we have previously shown that IUI increases cytokine expression and microglia number, and reduces white matter in the brains of exposed offspring. Clinical data suggest that IUI may increase the risk for cognitive and neurodevelopmental disorders, however, IUI is often found in the context of preterm birth, making it difficult to disentangle the adverse effects of inflammation from those related to prematurity. Therefore, using a mouse model of IUI that does not involve preterm birth, operant tasks were used to evaluate motivation, attention, impulsivity, and locomotion. IUI-exposed offspring were found to have increased locomotion and increased motivation (females only), and testing in the 5-choice serial reaction time task (5-CSRTT) showed that IUI-exposed offspring performed more trials and could respond accurately at a shorter stimulus length. We have previously shown that IUI animals have a potentiated cytokine response to a “second hit” (acute LPS injection) in adulthood, so animals’ performance in the 5CSRTT was evaluated following an acute injection of LPS. As opposed to the improved performance observed under baseline conditions, IUI exposed animals demonstrated a greater decrease in performance after an acute LPS administration. To identify putative molecular mechanisms underlying this potentiated decline in cognitive performance, PFC samples were collected immediately after post-LPS cognitive testing and targeted gene expression analysis was correlated with specific measures of cognitive performance. Three receptors important for neuron-microglia crosstalk were found to correlate with task performance in the males following acute LPS administration. These data demonstrate that early life exposure to localized inflammation of the uterus, in the absence of prematurity, increases locomotor activity and improves some aspects of cognitive performance, but drives a vulnerability for adult cognitive performance deficits in response to acute infection.

The Effect of Corporate Environmental Performance on Corporate Financial Performance

This review explores the effect of corporate environmental performance on financial performance. In particular, it reviews the empirical evidence on this effect. Conceptually, stronger environmental performance may lead to worse or better financial performance. The empirical literature generally finds a positive link from good environmental performance to financial success. However, many studies reveal a negative link. Given this mixed evidence, literature reviews and meta-analyses help to discern the conditions under which better environmental performance prompts financial success or disappointment. Similarly, this review organizes the empirical evidence by the specific measures of environmental performance and financial performance to discern which links are positive or negative. Lastly, the review identifies shortcomings in the empirical literature and offers suggestions for future research. For example, analyses should more fully explore the factors shaping the links from environmental to financial performance, such as firm size and economy type (e.g., mature market).

Benchmarking regions using a heteroskedastic grouped random parameters model with heterogeneity in mean and variance: Applications to grade crossing safety analysis

Comparing regions while adjusting for differences in characteristics of sites located in those regions is valuable since it identifies possible inter-regional dissimilarities in crash risk propensities according to specific safety performance measures (e.g., crash frequency of a specific type). This paper describes a framework to benchmark different regions (neighborhoods, provinces, etc.) in terms of a selected safety performance measure. To avoid issues relating to aggregated (macro-level) data, we use disaggregate (micro-level) data to draw inferences at a macro/region-level, which is often needed for developing large-scale transportation safety and planning programs and policies. To overcome unobserved heterogeneity, we employ a multilevel Bayesian heteroskedastic Poisson lognormal model with grouped random parameters allowing heterogeneity in both mean and variance parameters. The proposed approach is illustrated through a comprehensive study of highway railway grade crossings across Canada. The results indicate that the proposed model addresses unobserved heterogeneity more efficiently and provides more insight compared to conventional random parameters models. For example, we found that as traffic exposure increases, grade crossing safety deteriorates at a higher rate in the Canadian Prairies than in the other regions. Our benchmarking framework is also affected by different model specifications. The results indicate the need for further in-depth investigations, which could help to identify possible reasons for inter-region differences in terms of specific safety indicators. This study provides valuable guidelines to Canadian transportation authorities, revealing important underlying crash mechanisms at highway railway grade crossings in Canada.

Public Health Impact of Syndromic Surveillance Data—A Literature Survey

Public Health Impact of Syndromic Surveillance Data—A Literature Survey

Systematic mechanism for identifying the relative impact of supply chain performance areas on the overall supply chain performance using SCOR model and SEM

This research aims to introduce a systematic mechanism for developing an organization specific supply chain performance measurement (SCPM) model and for generating a single regression relationship between the overall supply chain performance (SCP) and each of the SCPM areas using an organization's numerical data. The research uses a case study conducted in a small-scale asphalt manufacturing plant located in West Texas, USA with a sample of 218 data records collected over a period of one year. In this article, the systematic mechanism is demonstrated using the data from the case study organization. It provides guidance for developing a hierarchical SCPM model for the organization using the Supply Chain Operations Reference (SCOR) model, and then to obtain the final regression equation for the overall SCP using the Structural Equations Modeling (SEM) technique. The results obtained from the SCPM mechanism are then compared with the managerial input on the SCP that was analyzed using the Analytical Hierarchical Process (AHP). The results of the comparison are used to validate the SCPM results.A major finding of this research is that the regression coefficients provide a clue for the level of sensitivity those measures have on the overall SCP under given organizational SC capacity and operating levels. The SCPM areas with higher regression coefficients reflect higher sensitivity, thus even a slight variation in the measures contributing to those areas will be contributing to a considerable impact on the overall SCP measures. The findings lead to the implication that managers should pay close attention to controlling the stability of the SC operational processes which are responsible for generating those SCP measures. The goal should be to maintain the desired output levels with the least amount of fluctuations. The regression results therefore provide insight to the managers for identifying the individual SCP measures to be managed more intensely than others based on their relative impacts on the overall SCP. The results are applicable as long as the organization does not change its organizational SC capacity and operating levels, thus can be used for better managing the SC in future.This research fulfills multiple research gaps highlighted in literature, mainly: the absence of a systematic approach to generate an organization specific SCPM model; and the absence of a SCPM system capable of generating a single cause–and-effect relationship between the overall SCP and the numerous hierarchical performance measures reflecting their relative impact. Therefore, this study can be viewed as an attempt to increase the level of awareness in the SC field. The article also proposes several future research directions to test the repeatability and validity of the proposed SCPM mechanism.