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Article
Publication date: 24 October 2023

Jared Nystrom, Raymond R. Hill, Andrew Geyer, Joseph J. Pignatiello and Eric Chicken

Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction…

409

Abstract

Purpose

Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Design/methodology/approach

Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lightning prediction.

Findings

The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

Research limitations/implications

The research is limited to the data collected in support of weather prediction work through the 45th Weather Squadron of the United States Air Force.

Practical implications

These methods are important due to the increasing reliance on sensor systems. These systems often provide incomplete and chaotic data, which must be used despite collection limitations. This work establishes a viable data imputation methodology.

Social implications

Improved lightning prediction, as with any improved prediction methods for natural weather events, can save lives and resources due to timely, cautious behaviors as a result of the predictions.

Originality/value

Based on the authors’ knowledge, this is a novel application of these imputation methods and the forecasting methods.

Details

Journal of Defense Analytics and Logistics, vol. 7 no. 2
Type: Research Article
ISSN: 2399-6439

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Book part
Publication date: 15 December 2015

Jared Friedman, Anthony Ian Jack, Kylie Rochford and Richard Boyatzis

Recent neuroscience research shows that two large-scale cortical networks are involved in organizational behavior. These two networks are naturally antagonistic – when one is…

Abstract

Recent neuroscience research shows that two large-scale cortical networks are involved in organizational behavior. These two networks are naturally antagonistic – when one is active the other tends to be suppressed. The focus of the chapter is to apply the opposing-domains hypothesis to problems associated with: (1) trying to balance creative thinking and global processing with analytic reasoning and focused attention; (2) avoiding ethical dangers associated with an imbalance in task positive network (TPN) and default mode network (DMN) thinking; and (3) properly motivating and incentivizing employees so as not to lead to an imbalance between the TPN and DMN. We contend that the opposing-domains hypothesis can inform organizational and leadership theory in areas where single-dimensional dual-process models are inadequate.

Details

Organizational Neuroscience
Type: Book
ISBN: 978-1-78560-430-0

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Article
Publication date: 23 May 2022

Jared M. Hansen, Joseph W. Hansen and Susan R. Madsen

The purpose of this research is to outline and investigate a set of five experience elements from neuroscience research labeled SCARF that could impact the quality of perception…

748

Abstract

Purpose

The purpose of this research is to outline and investigate a set of five experience elements from neuroscience research labeled SCARF that could impact the quality of perception, evaluation and engagement of executives, managers and employees in business-to-business (B2B) companies during and after the COVID-19 pandemic. The proposed experience elements are perceived status, certainty, autonomy, relatedness and fairness. The authors demonstrate that all five elements are influential factors in B2B employees’ workplace environment during the COVID-19 pandemic. The authors outline several specific managerial implications and describe how companies can make better decisions related to several important market crisis decisions via a growth mindset built on the five experience elements. The authors also pay attention to implications to several B2B areas of research focus, including salesforce management and buying/supplier relationships.

Design/methodology/approach

The authors first examine existing B2B research to gauge if the five elements have been examined in B2B business contexts. They then analyze a combination of quantitative and qualitative survey data from 335 employees of different B2B companies to see if the five experience elements surface in discussion on how the pandemic has impacted their work experience and careers.

Findings

The authors find that several B2B research studies have looked at each of the individual components of the SCARF model, but none of them have yet included all five elements together in research or looked at them in the context of COVID-19. The results of analysis of surveys from employees in 335 B2B companies provide strong evidence that all five elements are influential factors in B2B employees workplace environment during the COVID-19 pandemic.

Originality/value

This study contributes to prior research focusing on how B2B companies can thrive during and after the COVID-19 pandemic. The research offers valuable practical insights and detailed examples of how to apply a set of five elements/experiences that industrial and business-to-business organization leaders should adopt in their conscious decision-making evaluation and in their communications with employees, suppliers and customers during and after the pandemic.

Details

Journal of Business & Industrial Marketing, vol. 37 no. 10
Type: Research Article
ISSN: 0885-8624

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