Tangent linear modeling and adjoints of semi-Lagrangian methods

2020 ◽  
pp. 541-567
Author(s):  
Steven J. Fletcher
Keyword(s):  
Linear Modeling ◽  
Lagrangian Methods

The Relationship Between Leader–Member Exchange and Employees’ Proactive Behaviors

2019 ◽  
Vol 18 (2) ◽  
pp. 106-111
Author(s):  
Fong-Yi Lai ◽  
Szu-Chi Lu ◽  
Cheng-Chen Lin ◽  
Yu-Chin Lee
Keyword(s):  
Hierarchical Linear Modeling ◽  
Future Research ◽  
Leader Member Exchange ◽  
Voice Behavior ◽  
Linear Modeling ◽  
Team Members ◽  
Member Exchange ◽  
Multi Temporal ◽  
The Relationship ◽  
Practical Implications

Abstract. The present study proposed that, unlike prior leader–member exchange (LMX) research which often implicitly assumed that each leader develops equal-quality relationships with their supervisors (leader’s LMX; LLX), every leader develops different relationships with their supervisors and, in turn, receive different amounts of resources. Moreover, these differentiated relationships with superiors will influence how leader–member relationship quality affects team members’ voice and creativity. We adopted a multi-temporal (three wave) and multi-source (leaders and employees) research design. Hypotheses were tested on a sample of 227 bank employees working in 52 departments. Results of the hierarchical linear modeling (HLM) analysis showed that LLX moderates the relationship between LMX and team members’ voice behavior and creative performance. Strengths, limitations, practical implications, and directions for future research are discussed.

Impact of relatedness, uncertainty and slack on corporate entrepreneurship decisions

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Robert Garrett ◽  
Shaunn Mattingly ◽  
Jeff Hornsby ◽  
Alireza Aghaey
Keyword(s):  
Decision Making ◽  
Hierarchical Linear Modeling ◽  
Cognitive Strategies ◽  
Corporate Entrepreneurship ◽  
New Venture ◽  
Organizational Level ◽  
Linear Modeling ◽  
Slack Resources ◽  
Content Type ◽  
Positive Effect

PurposeThe purpose of this study is to evaluate the effect of opportunity relatedness and uncertainty on the decision of a corporate entrepreneur to pursue a venturing opportunity.Design/methodology/approachThe study uses a conjoint experimental design to reveal the structure of respondents' decision policies. Data were gathered from 47 useable replies from corporate entrepreneurs and were analyzed with hierarchical linear modeling (HLM).FindingsResults show that product relatedness, market relatedness, perceived certainty about expected outcomes and slack resources all have a positive effect on the willingness of a corporate entrepreneur to pursue a new venture idea. Moreover, slack was found to diminish the positive effect of product relatedness on the likelihood to pursue a venturing opportunity.Practical implicationsBy providing a better understanding of decision-making schemas of corporate entrepreneurs, the findings of this study help improve the practice of entrepreneurship at the organizational level. In order to make more accurate opportunity assessments, corporate entrepreneurs need to be aware of their cognitive strategies and need to factor in the salient criteria affecting such assessments.Originality/valueThis paper adds to the limited understanding of corporate-level decision-making with regard to pursuing venturing opportunities. More specifically, the paper adds new insights regarding how relatedness and uncertainty affect new venture opportunity assessments in the presence (or lack thereof) of slack resources.

scholarly journals A functional linear modeling approach to sleep–wake cycles in dogs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hope J. Woods ◽  
Ming Fei Li ◽  
Ujas A. Patel ◽  
B. Duncan X. Lascelles ◽  
David R. Samson ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Cognitive Dysfunction ◽  
Healthy Adult ◽  
Activity Patterns ◽  
Linear Modeling ◽  
Activity Monitors ◽  
Companion Dogs ◽  
Non Invasive ◽  
Normal Sleep ◽  
The Times

AbstractThe study of companion (pet) dogs is an area of great translational potential, as they share a risk for many conditions that afflict humans. Among these are conditions that affect sleep, including chronic pain and cognitive dysfunction. Significant advancements have occurred in the ability to study sleep in dogs, including development of non-invasive polysomnography; however, basic understanding of dog sleep patterns remains poorly characterized. The purpose of this study was to establish baseline sleep–wake cycle and activity patterns using actigraphy and functional linear modeling (FLM), for healthy, adult companion dogs. Forty-two dogs were enrolled and wore activity monitors for 14 days. FLM demonstrated a bimodal pattern of activity with significant effects of sex, body mass, and age; the effect of age was particularly evident during the times of peak activity. This study demonstrated that FLM can be used to describe normal sleep–wake cycles of healthy adult dogs and the effects of physiologic traits on these patterns of activity. This foundation makes it possible to characterize deviations from normal patterns, including those associated with chronic pain and cognitive dysfunction syndrome. This can improve detection of these conditions in dogs, benefitting them and their potential as models for human disease.

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