Search results
1 – 6 of 6Shashi K. Shahi, Mohamed Dia, Peizhi Yan and Salimur Choudhury
The measurement capabilities of the data envelopment analysis (DEA) models are used to train the artificial neural network (ANN) models for the best performance modeling of the…
Abstract
Purpose
The measurement capabilities of the data envelopment analysis (DEA) models are used to train the artificial neural network (ANN) models for the best performance modeling of the sawmills in Ontario. The bootstrap DEA models measure robust technical efficiency scores and have benchmarking abilities, whereas the ANN models use abstract learning from a limited set of information and provide the predictive power.
Design/methodology/approach
The complementary modeling approaches of the DEA and the ANN provide an adaptive decision support tool for each sawmill.
Findings
The trained ANN models demonstrate promising results in predicting the relative efficiency scores and the optimal combination of the inputs and the outputs for three categories (large, medium and small) of sawmills in Ontario. The average absolute error in predicting the relative efficiency scores varies from 0.01 to 0.04, and the predicted optimal combination of the inputs (roundwood and employees) and the output (lumber) demonstrate that a large percentage of the sawmills shows less than 10% error in the prediction results.
Originality/value
The purpose of this study is to develop an integrated DEA-ANN model that can help in the continuous improvement and performance evaluations of the forest industry working under uncertain business environment.
Details
Keywords
Paula M. Di Nota, Bryce E. Stoliker, Adam D. Vaughan, Judith P. Andersen and Gregory S. Anderson
The purpose of this study isto synthesize recent empirical research investigating memory of stressful critical incidents (both simulated and occurring in the field) among law…
Abstract
Purpose
The purpose of this study isto synthesize recent empirical research investigating memory of stressful critical incidents (both simulated and occurring in the field) among law enforcement officers.
Design/methodology/approach
The study used the approach of systematic state-of-the-art review.
Findings
In total, 20 studies of police and military officers show reduced detail and accuracy of high- versus low-stress incidents, especially for peripheral versus target information. Decrements in memory performance were mediated by the extent of physiological stress responses. Delayed recall accuracy was improved among officers that engaged in immediate post-incident rehearsal, including independent debriefing or reviewing body-worn camera footage.
Research limitations/implications
Most studies were not found through systematic database searches, highlighting a need for broader indexing and/or open access publishing to make research more accessible.
Practical implications
By understanding how stress physiology enhances or interferes with memory encoding, consolidation and recall, evidence-based practices surrounding post-incident evidence gathering are recommended.
Social implications
The current review addresses common public misconceptions of enhanced cognitive performance among police relative to the average citizen.
Originality/value
The current work draws from scientific knowledge about the pervasive influence of stress physiology on memory to inform existing practices surrounding post-incident evidence gathering among police.
Details