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1 – 10 of 18Vincent Cassar, Katarzyna Tracz-Krupa and Frank Bezzina
In this study, we explored factors driving evidence-based management (EBM) decision-making in Poland which has experienced changes from state-controlled market environments to…
Abstract
Purpose
In this study, we explored factors driving evidence-based management (EBM) decision-making in Poland which has experienced changes from state-controlled market environments to more competitive ones. Evidence-based management requires the critical use and adaptability to information to deal with complex problems.
Design/methodology/approach
In total, 422 Polish managers responded to a telephone survey measuring their perceptions about decision-making culture, styles, competence, and their use of specific sources to derive the evidence to enable them to make evidence-based decisions. Informed by theoretical principles, we used Hayes’ PROCESS macro (Model 4) to examine whether each factor produced direct effects on EBM decision-making and the mediating influence of competence and style in the relationship between culture and perceived evidence-based decision-making.
Findings
All three factors correlated positively with perceived evidence-based decision-making. Moreover, style was not predictive of EBM decision-making compared to competence and culture while culture had an imposing effect on decision-making both as a direct effect and indirectly through competence.
Originality/value
This study provides important insights into the perceptual state of EBM among Polish managers. It emphasizes the importance of embracing diverse cultures and improving critical thinking to help managers make more evidence-based decisions during significant changes in the business world.
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Industry 4.0 or the Fourth Industrial Revolution is characterized by robotic process automation and machine-to-machine communications. Since computers, machines, and robots share…
Abstract
Industry 4.0 or the Fourth Industrial Revolution is characterized by robotic process automation and machine-to-machine communications. Since computers, machines, and robots share information and knowledge more swiftly and effectively than humans, the question is what human beings' role could be in the era of the Internet-of-Thing. The answer would be beneficial to institutions for higher education to anticipate. The literature reveals a gap between the intended learning outcomes in higher education institutions and the needs of employers in Industry 4.0. Evidence is shown that higher education mainly focused on knowledge (know-what) and theory-based (know-why) intended learning outcomes. However, competent professionals require knowledge (know-what), understanding of the theory (know-why), professional (know-how) and interpersonal skills (know-how and know-who), and need intrapersonal traits such as creativeness, persistence, a result-driven attitude et cetera. Therefore, intended learning outcomes in higher education should also develop interpersonal skills and intrapersonal characteristics. Yet, personality development is a personal effort vital for contemporary challenges. The history of the preceding industrial revolutions showed the drawbacks of personality and character education; politicians have abused it to control societies in the 19th and 20th centuries. In the discussion section, the institutions for higher education are alerted that the societal challenges of the twenty-first century could lead to a form of personality education that is not in the student's interest and would violate Isaiah Berlin's philosophical concept of ‘positive freedom’.
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This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this…
Abstract
Purpose
This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.
Design/methodology/approach
This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.
Findings
Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.
Research limitations/implications
Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.
Practical implications
A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.
Social implications
Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.
Originality/value
The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.
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Adam Biggs, Greg Huffman, Joseph Hamilton, Ken Javes, Jacob Brookfield, Anthony Viggiani, John Costa and Rachel R. Markwald
Marksmanship data is a staple of military and law enforcement evaluations. This ubiquitous nature creates a critical need to use all relevant information and to convey outcomes in…
Abstract
Purpose
Marksmanship data is a staple of military and law enforcement evaluations. This ubiquitous nature creates a critical need to use all relevant information and to convey outcomes in a meaningful way for the end users. The purpose of this study is to demonstrate how simple simulation techniques can improve interpretations of marksmanship data.
Design/methodology/approach
This study uses three simulations to demonstrate the advantages of small arms combat modeling, including (1) the benefits of incorporating a Markov Chain into Monte Carlo shooting simulations; (2) how small arms combat modeling is superior to point-based evaluations; and (3) why continuous-time chains better capture performance than discrete-time chains.
Findings
The proposed method reduces ambiguity in low-accuracy scenarios while also incorporating a more holistic view of performance as outcomes simultaneously incorporate speed and accuracy rather than holding one constant.
Practical implications
This process determines the probability of winning an engagement against a given opponent while circumventing arbitrary discussions of speed and accuracy trade-offs. Someone wins 70% of combat engagements against a given opponent rather than scoring 15 more points. Moreover, risk exposure is quantified by determining the likely casualties suffered to achieve victory. This combination makes the practical consequences of human performance differences tangible to the end users. Taken together, this approach advances the operations research analyses of squad-level combat engagements.
Originality/value
For more than a century, marksmanship evaluations have used point-based systems to classify shooters. However, these scoring methods were developed for competitive integrity rather than lethality as points do not adequately capture combat capabilities. The proposed method thus represents a major shift in the marksmanship scoring paradigm.
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