Evaluation of Road Safety Performance Based on Self-Reported Behaviour Data Set

Self-reported behavioural data, being often linguistic variables that represent a qualitative measure of respondents’ opinions/attitudes, are vague, uncertain, and fuzzy in nature. A road safety performance index, based on these fuzzy data, should consider this uncertainty. In this study, fuzzy numbers were used to describe self-reported behaviour on Montenegrin roads, which was further integrated into the data envelopment analysis (DEA), a technique for measuring the relative performance of decision-making units (DMUs). The vagueness of the performance scores obtained in this way was treated with grey relational analysis (GRA). GRA was applied to the cross-efficiency (CE) matrix constructed by the DEA to distinguish Montenegrin municipalities’ performance, with the main goal of describing road safety in the observed territories in the environment of uncertain/grey data. It is concluded that the proposed DEA–GRA model, based on fuzzy data, provides a more reasonable and encompassing measure of performance, and with which the overall ranking position of municipalities can be obtained.

Cooperatives' performance relative to investor-owned firms: a non-distorted approach for the wine sector

Purpose This study aims to investigate whether significant performance differences between cooperatives and investor-owned firms (IOFs) may exist.Design/methodology/approach Based on data from a sample of Italian wine firms for the period from 2009 to 2018, an adjusted measure of performance called earnings before interests, taxes, depreciations and amortizations gross the raw materials cost was adopted to consider the different objectives of cooperatives relative to those of IOFs.Findings Empirical evidence shows that in the context under analysis, cooperatives have performed better than IOFs.Originality/value Despite the theoretical literature suggesting that the cooperative form of organizations suffers from many weaknesses, these results highlight that cooperatives operating in the wine sector are at least as economically efficient as other organizations, and more specifically, they perform better than for-profit firms. Consequent implications for theory and practice are discussed.

Novel Applications of Accelerometry Data for Health Outcomes in Older Adults: Thinking Beyond MVPA

Physical activity is a well-established predictor of health and longevity. Wearable accelerometers produce high-frequency, time series data that capture multiple aspects of daily physical activity across the spectrum of intensity. Historically, the majority of accelerometry-based physical activity research has employed summary threshold metrics such as moderate-to-vigorous physical activity, or “MVPA.” Although these measures are important for understanding compliance with physical activity guidelines, they underutilize the potential of this data. To advance the science of physical activity in older adults, more sensitive, clinically translatable measures are needed. This symposium will examine the associations between novel measures of accelerometry-derived physical activity and various aging-related health outcomes. Dr. Wanigatunga will discuss the association of physical activity volume and fragmentation with the frailty phenotype in the Study to Understand Vitamin D and Fall Reduction in You (STURDY). Dr. Cai will present evidence on the association of physical activity quantities and patterns with measures of visual impairment in the Baltimore Longitudinal Study of Aging. Ms. Qiao will present a novel accelerometry-derived measure of performance fatigability in the Developmental Epidemiologic Cohort Study. Finally, Dr. Urbanek will discuss the role of accelerometry-derived free-living gait cadence in defining fall risk in STURDY. Collectively, these presentations highlight critical associations between objective measures of physical activity and health outcomes in older adults and illuminate the need for thinking beyond MVPA to improve prevention and intervention efforts.

Introducing the Contextual Ambidexterity Scale for Public Organizations (CASPO): Scale development and initial evidence

Contextual ambidexterity describes the organizational capacity of being simultaneously able to adapt and change in the face contextual requirements while keeping alignment and predictability. Contextual ambidexterity has been recognized as an appropriate explanation of organizational performance, and its influence has already permeated accounts of public organizations’ dynamics. We join this line of reasoning by suggesting that some specific characteristics of public organizations call for refinement of the contextual ambidexterity concept, and the correspondent evolution in measuring this organizational ability, thus introducing the Contextual Ambidexterity Scale for Public Organizations (CASPO). We suggest going beyond the original measure of alignment and adaptability created by Gibson and Birkinshaw (2004), to include psychological safety, reflexive spaces, and flexibility as sub-dimensions of adaptability and imprinting, rulefollowing and shared vision as sub-dimensions of alignment. On the basis of a sample of civil servants (n=200), we used exploratory factor analysis to identify a six-dimensional solution covering alignment and adaptability. Using another sample of civil servants (n=200), we used confirmatory factor analysis to test CASPO’s construct validity and regression analysis in testing the criterion validity. The results reveal that CASPO shows appropriate metric qualities and that it surpasses Gibson and Birkinshaw’s (2004) scale in predicting both their measure of generic organizational performance and a measure of performance specific for public organizations. This study contributes to the creation of sound measures of relevant concepts explaining the performance of public organizations.

Motor Reaction Times as an Embedded Measure of Performance Validity: a Study with a Sample of Austrian Early Retirement Claimants

Among embedded measures of performance validity, reaction time parameters appear to be less common. However, their potential may be underestimated. In the German-speaking countries, reaction time is often examined using the Alertness subtest of the Test of Attention Performance (TAP). Several previous studies have examined its suitability for validity assessment. The current study was conceived to examine a variety of reaction time parameters of the TAP Alertness subtest with a sample of 266 Austrian civil forensic patients. Classification results from the Word Memory Test (WMT) were used as an external indicator to distinguish between valid and invalid symptom presentations. Results demonstrated that the WMT fail group performed worse in reaction time as well as its intraindividual variation across trials when compared to the WMT pass group. Receiver operating characteristic analyses revealed areas under the curve of .775–.804. Logistic regression models indicated the parameter intraindividual variation of motor reaction time with warning sound as being the best predictor for invalid test performance. Suggested cut scores yielded a sensitivity of .62 and a specificity of .90, or .45 and .95, respectively, when the accepted false-positive rate was set lower. The results encourage the use of the Alertness subtest as an embedded measure of performance validity.

The Sea Striker: Foilers are back in the game

This paper presents how the recent evolutions of naval missions, threats and operation theatres have led to the need for a new kind of surface players in the modern warfare. Then, an innovative surface combatant, the Sea Striker, is introduced and her various assets and advantages explained and detailed, along with her limitations. Finally, some example of computation of Measure of Performance in different scenario are exposed, followed by a brief analysis and contextualization in order to justify the relevance of using ships like the Sea Striker in various naval operations.

An Analysis of e-Governance and Its Impact on the Profitability of MSMEs: A Structural Equation Modelling Approach

The article studies e-governance and its impact on the performance of MSMEs in India using a structural model. The model contains three main variables: use of e-governance by the MSMEs, the benefits attained by using e-governance (a mediating variable), and the change in performance due to the use of e-governance and benefits attained. The profitability of the firm is a measure of performance in the study. The study was done in collaboration with PHD Chamber of Commerce and Industry, Dehradun, Uttarakhand, India. The data was collected using the survey method, in which a close-ended questionnaire was circulated to the top executives of MSMEs. Out of 3,126 registered MSMEs (registered during FY 2017–2018), 350 random samples were taken into consideration for this study. A response rate of 83.7% was attained. Statistical techniques such as EFA, CFA and SEM have been used in this study to confirm the model, using SPSS and AMOS software. The model proposed in the study fits well both theoretically and empirically in the Indian context, and clearly shows the significant impact of e-governance use on the business performance of MSMEs. The study also shows that the benefits of e-governance have a partial mediating impact on the relationship between e-governance and the profitability of the business. The structured model presented in the study would be useful for practitioners (government bodies, government officials and e-government practitioners) in making vital decisions while designing an effective e-government structure for enterprises.

Trustworthy performance evaluations: The Performance Outcome Scoring Template (POS-T) for transparent assessments in real-world programs

In applied program settings, such as in natural environment control and education, performance evaluation is usually conducted by evaluators considering both self-comparison and comparison with peers. We have developed the Performance Outcome Scoring Template (POS-T) for assessments with high face-validity in these settings. POS-T puts achievements of individuals or groups in context, i.e. the resulting performance outcome score (POS) reflects a meaningful measure of performance magnitude with regards to internal and external comparisons. Development of a POS is performed in four steps supported by a statistical framework. Software is supplied for creation of scoring applications in different performance evaluation settings. We demonstrate the POS-T by evaluation of CO2 emissions reduction amongst 36 OECD member countries.

When Choosing the Best Subset Is Not the Best Choice

Background: Variable selection in linear regression settings is a much discussed problem. Best subset selection (BSS) is often considered as an intuitively appealing ‘gold standard’, with its use being restricted mainly by its N P-hard nature. Instead, alternatives such as the least absolute shrinkage and selection operator (Lasso) or the elastic net (Enet) have become methods of choice in high-dimensional settings. A recent proposal represents BSS as a mixed integer optimization problem so that much larger problems have become feasible in reasonable computation time. This has been exploited to study the prediction performance of BSS and its competitors. Here, we present an extensive simulation study assessing, instead, the variable selection performance of BSS compared to forward stepwise selection (FSS), Lasso and Enet. The analysis considers a wide range of settings that are challenging with regard to dimensionality, signal-to-noise ratio and correlations between relevant and irrelevant direct predictors. As measure of performance we used the best possible F1 score for each method so as to ensure a fair comparison irrespective of any criterion for choosing the tuning parameters.Results: Somewhat surprisingly, it was only in settings where the signal-to-noise ratio was high and the variables were (nearly) uncorrelated that BSS reliably outperformed the other methods. This was the case even in low dimensional settings where the number of observations exceeded the number of variables by a factor of ten. Further, the FSS approach performed nearly identically to BSS. Conclusion: Our results shed a new light on the usual presumption of BSS being, in principle, the best choice for variable selection. More attention needs to be payed to the data generating process when considering variable selection methods. Especially for correlated variables, convex alternatives like Enet are not only faster but also appear to be more accurate in practical settings.