Defined by Miles as "a requirement of the activities of one subunit that is affected by the activities of other subunits" is a <u>contingency</u>.
According to the contingency theory of management, situational circumstances can have an impact on the relationships between dependent and independent variables at work, which will have an effect on employee behavior, effectiveness, and behavior at work in general. Also known as the situational approach to management, this idea. 
It is crucial to take into account the particular contingency factors that apply to each business in order to assess organizational data effectively and increase employee engagement. A need for one component's operations that affects those of another subunit is known as a contingency.
The above question is incorrect, the correct question is:
Defined by Miles as "a requirement of the activities of one subunit that is affected by the activities of other subunits" is a _________.
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Explanation:
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Answer:
"E "
Explanation:
Just in time inventory is an inventory management system where inventory required for production are ordered at the point of production.
This practice helps to maximize profit as investment on inventory carriage and storage are minimized , aiding an improved working capital management.
It is of importance that machine break down is avoided and there is a reliability of man power in order to avoid operation down time when there is a demand.
Also , there must be a solid arrangement with supplier for it to be effective.
 
        
             
        
        
        
The appropriate response is Affective. This part manages sentiments or feelings that are conveyed to the surface about something, for example, dread or despise. Utilizing our above illustration, somebody may have the disposition that they despise young people since they are languid or that they cherish all infants since they are adorable.
        
             
        
        
        
In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product. Optimization of process parameters is one of the ways to achieve desired quality of a part. 
In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product. 
Optimization of process parameters is one of the ways to achieve desired quality of a part. Finite Element Method (FEM) and machine learning techniques are applied to evaluate and optimize AM process parameters. While FEM requires specific information, Powder Bed Fusion Machine Learning is based on big amounts of data. This paper provides a conceptual framework on combination of mathematical modelling and Machine Learning to avoid these issues. 
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