Influence of Group Composition on Participant Reactions to Training: A Study in an Indian Power Transmission Organization

2018 ◽  
Vol 43 (3) ◽  
pp. 141-155
Author(s):  
Malabika Sahoo ◽  
Sumita Mishra ◽  
Sasmita Mishra
Keyword(s):  
Group Composition ◽  
Power Transmission ◽  
Training Design ◽  
Factors Affecting ◽  
Scant Attention ◽  
Level Model ◽  
Level I ◽  
Programme Content ◽  
Organizational Tenure ◽  
Participant Reactions

Investments in organizational training and its evaluation is important in recent times. One of the most popular models of training evaluation is the four-level model developed by Kirkpatrick. It includes participant reactions (Level I), extent of learning (Level II), the extent of transfer of training through appropriate behaviour (Level III) and improvement in organization performance (Level IV). Despite its overwhelming use in the industry, organizations have frequently gathered data on Level I of this model only. While extant literature researched on factors affecting participant reactions; group composition influences merited scant attention. To address this gap, the current study conducted at an Indian power transmission organization, focused on the influence of group composition on participant reactions to training of a programme titled ‘Empowering Self for Better Performance’. Reaction data were collected from all the 120 participants who attended the programme. Data analyses pointed out to significant resultant differences in perception on two major dimensions of reaction—programme content and programme duration among participants with differences in age, organizational tenure, job position and educational qualifications. Our results not only provide empirical credence to the importance of group composition in influencing participant reactions but also bear implications for training design of millennials and soft skills programmes in heterogenous groups.

scholarly journals Factors Affecting the Number of Citations to Clinical Therapeutic Articles Mentioning Level of Evidence

2020 ◽  
Vol 17 (2) ◽  
Author(s):  
Hossein Beydokhti ◽  
Nosrat Riahinia ◽  
Hamid R Jamali ◽  
Saeid Asadi ◽  
Seyed Mohammad Riahi
Keyword(s):  
Web Of Science ◽  
Pearson Correlation ◽  
Background Level ◽  
Clinical Papers ◽  
Level Of Evidence ◽  
Factors Affecting ◽  
Article Type ◽  
Pearson Correlation Test ◽  
Level I ◽  
Number Of Citations

Background: Level of evidence (LoE) is a hierarchical system for classifying the quality of studies. Objectives: This study examined the factors affecting the number of citations to clinical articles related to the treatment of human diseases that have included the LoE in their abstracts. Methods: A total of 3,683 therapeutic articles published between 2011 and 2013 that mentioned the LoE in their abstract and were indexed in PubMed and Web of Science were retrieved. The LoE and type of study design were extracted from abstracts and other bibliographic and citation information was obtained from PubMed and Web of Science databases. Independent samples t-test, one-way ANOVA, Pearson correlation test and linear regression were used to analyze the relationship between the variables. Results: Articles with level I evidence had the lowest frequency (290, 7.9%) and articles with level IV had the highest frequency (1,831, 49.7%). Five-year citations ranged from zero to 215, with a median of 13 citations. The median values of five-year citations from level I to level V were 20.5, 15, 14, 11, and 6 citations, respectively. Evaluation of the models to examine the factors affecting the number of citations showed that the change of evidence-level from level I to V reduced the number of citations (P < 0.001). Conclusions: Journal Impact Factor, LoE, number of references, number of authors, number of title words, number of pages, article type and subject category accounted for about 25% of the variation in five-year citations of clinical papers. Clinical papers with high LoE (levels I & II) received more citations over a five-year period than those with lower LoE (levels III & IV).

Correcting for Selection Bias in Social Movement Research

1998 ◽  
Vol 3 (2) ◽  
pp. 141-161 ◽  
Author(s):  
Simon Hug ◽  
Dominique Wisler
Keyword(s):  
Social Movement ◽  
Selection Bias ◽  
Truncated Regression ◽  
Factors Affecting ◽  
Local Newspapers ◽  
Data Analyses ◽  
Regression Approach ◽  
Scant Attention ◽  
The Media ◽  
Cross National

Longitudinal and cross-national research on new social movements often relies on newspaper reports for data on the frequency and type of events. Reporting by newspapers is, however, known to be strongly affected by selection bias. Newspapers report events that they find "newsworthy." Surprisingly, the effect of these selection biases on data analyses has received scant attention, and the methodology to correct for these biases hardly has been discussed. Based on data covering events in four cities in Switzerland we propose two types of corrections for the selection bias. The first is based on a simple weighting scheme for events reported in local newspapers. These weights are likely to provide useful corrections even in other contexts. The second correction attempts to model explicitly the selection bias of the media. This truncated regression approach is shown to be a useful strategy when the selectivity by the newspapers is severe, and the factors affecting this selection are largely known.

Logistic Regression Modeling for Evaluation of Factors Affecting Trauma Outcome in a Level I Trauma Center in Shiraz

2016 ◽  
Vol 19 (1) ◽  
Author(s):  
Mahnaz Yadollahi ◽  
Mehrdad Anvar ◽  
Haleh Ghaem ◽  
Shahram Bolandparvaz ◽  
Shahram Paydar ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Trauma Center ◽  
Regression Modeling ◽  
Factors Affecting ◽  
Logistic Regression Modeling ◽  
Trauma Outcome ◽  
Level I

scholarly journals Factors Affecting Energy-Related Carbon Emissions in Beijing-Tianjin-Hebei Region

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Jing-min Wang ◽  
Yu-fang Shi ◽  
Xue Zhao ◽  
Xue-ting Zhang
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Factors Affecting ◽  
Economic Output ◽  
Level Model ◽  
The Impact ◽  
The Relationship

Beijing-Tianjin-Hebei is a typical developed region in China. The development of economy has brought lots of carbon emissions. To explore an effective way to reduce carbon emissions, we applied the Logarithmic Mean Divisia Index (LMDI) model to find drivers behind carbon emission from 2003 to 2013. Results showed that, in Beijing, Tianjin, and Hebei, economic output was main contributor to carbon emissions. Then we utilized the decoupling model to comprehensively analyze the relationship between economic output and carbon emission. Based on the two-level model, results indicated the following: (1) Industry sector accounted for almost 80% of energy consumption in whole region. The reduced proportion of industrial GDP will directly reduce the carbon emissions. (2) The carbon factor for CO2/energy in whole region was higher than that of Beijing and Tianjin but lower than that of Hebei. The impact of energy structure on carbon emission depends largely on the proportion of coal in industry. (3) The energy intensity in whole region decreased from 0.79 in 2003 to 0.40 in 2013 (unit: tons of standard coal/ten thousand yuan), which was lower than national average. (4) The cumulative effects of industrial structure, energy structure, and energy intensity were negative, positive, and negative, respectively.

scholarly journals Determination of the Operating Temperature of the Gas-Insulated Transmission Line

2020 ◽  
Vol 10 (24) ◽  
pp. 8877
Author(s):  
Tomasz Szczegielniak ◽  
Dariusz Kusiak ◽  
Paweł Jabłoński
Keyword(s):  
Power Transmission ◽  
Radiation Heat Transfer ◽  
Proximity Effects ◽  
High Current ◽  
Power Losses ◽  
Factors Affecting ◽  
Three Phase ◽  
Phase Conductors ◽  
High Power Transmission

Gas-insulated lines (GILs) have been increasingly used as high-current busducts for high-power transmission. Temperature is one of the most important factors affecting the performance and ampacity of GILs. In this paper, an analytical method was proposed to determine the temperature of a three-phase high-current busduct in the form of a single pole GIL. First, power losses in the phase conductors and enclosures were determined analytically with the skin, and proximity effects were taken into account. The determined power losses were used as heat sources in thermal analysis. Considering the natural convection and radiation heat transfer effects, the heat balance equations on the surface of the phase conductors and the screens were established, respectively. Subsequently, the temperature of the phase conductors and the enclosures were determined. The validation of the proposed method was carried out using the finite element method and laboratory measurements.

Factors affecting mortality after penetrating cardiac injuries: 10-year experience at urban level I trauma center

2017 ◽  
Vol 213 (6) ◽  
pp. 1109-1115 ◽  
Author(s):  
Michael J. Mina ◽  
Rashi Jhunjhunwala ◽  
Rondi B. Gelbard ◽  
Stacy D. Dougherty ◽  
Jacquelyn S. Carr ◽  
...  
Keyword(s):  
Trauma Center ◽  
Factors Affecting ◽  
Urban Level ◽  
Level I

scholarly journals Getting to Know L2 Poor Comprehenders

2011 ◽  
Vol 4 (1) ◽  
pp. 98
Author(s):  
Masoud Zoghi ◽  
Ramlee Mustapha ◽  
Tengku Maasum
Keyword(s):  
Reading Comprehension ◽  
Strategy Training ◽  
Small Scale ◽  
Poor Reading ◽  
Factors Affecting ◽  
Efl Learners ◽  
Reading Comprehension Strategies ◽  
Poor Comprehenders ◽  
Scant Attention ◽  
Iranian Context

Among the plethora of studies conducted thus far to explore the factors affecting EFL reading effectiveness, scant attention seems to be paid to the why of poor reading comprehension of most EFL learners. In this regard, the present article capitalized on qualitative research on a small scale, for the purpose of addressing the not-so-often-debated issue of unsuccessful EFL reading competency in the Iranian context. In fact, the purpose of the article was to explore the degree of Iranian EFL learners' awareness of reading comprehension strategies and their potential comprehension failure. To this end, 12 EFL university-level students were interviewed, using a researcher-developed interview questionnaire. An analysis of student data interview revealed that there is an instructional void as regards to reading strategy training in the Iranian educational settings. Ultimately, based on the findings of the study, recommendations for future investigations are discussed.

Analysis of General Characteristics of Transmission Error of Gears With Convex Modification of Tooth Flank Form Considering Elastic Deformation Under Load

2009 ◽  
Vol 131 (6) ◽  
Author(s):  
Edzrol Niza Mohamad ◽  
Masaharu Komori ◽  
Hiroaki Murakami ◽  
Aizoh Kubo ◽  
Suping Fang
Keyword(s):  
Power Transmission ◽  
Transmission Error ◽  
Elastic Model ◽  
Qualitative Characteristic ◽  
Contact Ratio ◽  
Factors Affecting ◽  
Specific Loading ◽  
Tooth Flank ◽  
Form Deviation ◽  
Peak Value

The vibration/noise of power transmission gears is a serious problem for vehicles including automobiles, and therefore many studies on gear vibration have been reported. These studies, however, were carried out by investigation using numerical simulations in which gears with specific dimensions and tooth flank modifications under specific loading were considered. Therefore, the general characteristics of the transmission error of gears have not been clarified theoretically. In this report, a general model for the tooth meshing of gears is proposed; in which a quasi-infinite elastic model composed of springs with stiffness peculiar to the gear is incorporated. The transmission error of gears is formulated by theoretical equations. An investigation on the factors affecting the general characteristics of transmission error is accomplished using the formulated equations. The qualitative characteristic of the transmission error of gears with convex tooth flank form deviation is determined by the actual contact ratio and qualitative elements of gears, i.e., tooth flank form deviation and the distribution of stiffness. Even if the amplitude of torque, the amount of tooth flank form deviation, and other quantitative elements are not determined, the qualitative characteristic of transmission error can be derived. The peak-to-peak value of transmission error increases proportionately to the amount of tooth flank form deviation.

Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation

2006 ◽  
Vol 36 (12) ◽  
pp. 3063-3074 ◽  
Author(s):  
Bruce G Marcot ◽  
J Douglas Steventon ◽  
Glenn D Sutherland ◽  
Robert K McCann
Keyword(s):  
Bayesian Belief Networks ◽  
Management Decision ◽  
Influence Diagrams ◽  
Belief Networks ◽  
Validation Data ◽  
Factors Affecting ◽  
Expert Review ◽  
Management Decision Making ◽  
Practical Guidelines ◽  
Level Model

Bayesian belief networks (BBNs) are useful tools for modeling ecological predictions and aiding resource-management decision-making. We provide practical guidelines for developing, testing, and revising BBNs. Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model after expert review; testing and calibrating the model with case files to create a beta-level model; and updating the model structure and conditional probabilities with new validation data, creating the final-application gamma-level model. We illustrate and discuss these steps with an empirically based BBN model of factors influencing probability of capture of northern flying squirrels (Glaucomys sabrinus (Shaw)). Testing and updating BBNs, especially with peer review and calibration, are essential to ensure their credibility and reduce bias. Our guidelines provide modelers with insights that allow them to avoid potentially spurious or unreliable models.

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