Ergonomic Performance and Evaluation of Worksystem: A Few Applications

Author(s):  
P. K. Ray ◽  
V. K. Tewari ◽  
Esha Saha
1989 ◽  
Vol 34 (7) ◽  
pp. 711-711
Author(s):  
No authorship indicated

2013 ◽  
pp. 1000-1004
Author(s):  
M.A. Paya-Marin ◽  
J. B. P. Lim ◽  
B. Sen Gupta ◽  
R.M. Lawson

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Md. Toufiq Hassan Shawon ◽  
Shah Ali Akbar Ashrafi ◽  
Abul Kalam Azad ◽  
Sonja M. Firth ◽  
Hafizur Chowdhury ◽  
...  

Abstract Background In Bangladesh, a poorly functioning national system of registering deaths and determining their causes leaves the country without important information on which to inform health programming, particularly for the 85% of deaths that occur in the community. In 2017, an improved death registration system and automated verbal autopsy (VA) were introduced to 13 upazilas to assess the utility of VA as a routine source of policy-relevant information and to identify leading causes of deaths (COD) in rural Bangladesh. Methods Data from 22,535 VAs, collected in 12 upazilas between October 2017 and August 2019, were assigned a COD using the SmartVA Analyze 2.0 computer algorithm. The plausibility of the VA results was assessed using a series of demographic and epidemiological checks in the Verbal Autopsy Interpretation, Performance and Evaluation Resource (VIPER) software tool. Results Completeness of community death reporting was 65%. The vast majority (85%) of adult deaths were due to non-communicable diseases, with ischemic heart disease, stroke and chronic respiratory disease comprising about 60% alone. Leading COD were broadly consistent with Global Burden of Disease study estimates. Conclusions Routine VA collection using automated methods is feasible, can produce plausible results and provides critical information on community COD in Bangladesh. Routine VA and VIPER have potential application to countries with weak death registration systems.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Debasish Roy

AbstractThe marketing performance models, regardless of their nature and applications, should ultimately lead to creation of cash flows efficiently. This common objective emphasizes on a basic proposition: the output (dependent) variable must be intrinsically correlated to the financial behavior of the firm at the micro level. The four criteria for marketing performance and evaluation are Financial relevance, Actionable, Stable behavior, and Reliable long-term guidance respectively. By using those four criteria as the cornerstone, the Core Sales – Response Model was formulated under the Process perspective (the marketing procedure which helps to generate cash flows along with other antecedents of financial performance). This research paper is aimed at restructuring the fundamental Sales – Response model with the dependent variable Sales and three independent variables, namely, Marketing Support, Firm – controlled factors, and Uncontrolled factors in view of uncertainties related to global turmoil and widespread economic recession into a three – dimensional model by dropping ‘Marketing Support’ to fit the foundation of mathematical chaos theory and try to test its impact in the real world scenario by two ways: first, whether it can accurately define the current nature of functioning of a business firm under chaotic business environment, and second, given the condition of chaos; if the firm fails to prove its stability, what actions should be taken to stabilize its position in the feasible space. In order to serve the purposes, the manufacturing giant Apple, Inc. ® has been considered as the sample firm for the time – series study of 10 years (2009–2018).


2021 ◽  
pp. 109634802098857
Author(s):  
Zvi Schwartz ◽  
Timothy Webb

Index scores and competitive sets (compsets) play a critical role in the performance and evaluation of hotels. The reliance on these metrics has drawn skepticism in recent years as competitive sets may be opportunistically chosen, creating bias in performance evaluation. Drawing from the principal–agent theory and the theory of incentives, we explore whether the distance of the competitors chosen for a hotel’s compset influences revenue per available room (RevPAR) index scores. Based on the concepts of resource similarity and market commonality, we develop a novel mathematical model through which we empirically analyze a large dataset of 10,000 compsets. We find evidence that competitor distance influences index performance and that this relationship is bidirectional. Results show that hotels that outperform the competition may use distance to inflate RevPAR indices, while those that underperform may use distance to further reduce scores. These conflicting results may be reflected from the reverse motivations of the stakeholders.


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