scholarly journals Learning from Lessons Learned: Project Management Research Program

2012 ◽  
Vol 4 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Gowrishankar
Keyword(s):  
Project Management ◽  
Research Program ◽  
Lessons Learned ◽  
Management Research

Driving in the Dust: Challenges and Lessons Learned from Field Testing in Degraded Visual Environments

2020 ◽  
Vol 64 (1) ◽  
pp. 1916-1920
Author(s):  
Kayla L. Riegner ◽  
Kelly S. Steelman
Keyword(s):  
Research Program ◽  
Field Tests ◽  
Field Testing ◽  
Driving Performance ◽  
Lessons Learned ◽  
Current Paper ◽  
Ground Vehicle ◽  
Significant Safety ◽  
Dust Clouds

Degraded visual environments (DVEs) pose significant safety and efficiency problems in military ground vehicle operations. As part of a larger research program, two field tests were conducted to evaluate driving aids while indirect driving in DVEs. The current paper presents the results of one of these field tests, and focuses on the challenges and lessons learned in designing a challenging test course and producing consistent dust clouds for assessing Soldier driving performance and workload in degraded visual environments.

Explanation Plus Prediction—The Logical Focus of Project Management Research

2021 ◽  
pp. 875697282199994
Author(s):  
Joseph F. Hair ◽  
Marko Sarstedt
Keyword(s):  
Project Management ◽  
Statistical Models ◽  
Predictive Power ◽  
Mean Absolute Error ◽  
Explanatory Power ◽  
Absolute Error ◽  
Model Parameters ◽  
Mean Square ◽  
Management Research ◽  
The Mean

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R 2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.

The Evolution of Project Management Research

2011 ◽  
Author(s):  
Rodney Turner ◽  
Jeffrey Pinto ◽  
Christophe Bredillet
Keyword(s):  
Project Management ◽  
Management Research

scholarly journals Editorial

2016 ◽  
Vol 3 ◽  
pp. 5198
Author(s):  
Beverly Pasian
Keyword(s):  
Project Management ◽  
Management Research ◽  
Socially Responsible ◽  
Research And Practice

Conversations about projects and project management are changing. Project Management researchers and practitioners are no longer only focused on the processes and practices, but increasingly looking for ‘some truths’ of project management (Morris, 2016) – truth that can be as likely found when considering values as much as knowledge. And what is considered to be so valuable that a new journal is needed to reveal those truths? Quite simply…a better world where humanity’s problems are alleviated through shared and publicly available innovative projects, and socially responsible project management research and practice. And what is PMRP’s role in this quest? To provide a forum where informed dialogue can occur with project management researchers, practitioners and other stakeholders. 

Project-as-Practice: In Search of Project Management Research that Matters

2010 ◽  
Vol 41 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Tomas Blomquist ◽  
Markus Hällgren ◽  
Andreas Nilsson ◽  
Anders Söderholm
Keyword(s):  
Project Management ◽  
Management Research
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