Answer:
bureaucratic organizations
Explanation:
Bureaucratic organizations -
It is a form of management with a pyramidal command structure , it is a very organized form of management , having formality , is known as bureaucratic organisations .
They are the one with high efficiency with strict control and command .
hence ,
The correct term for the given statement is bureaucratic organizations .
The ratio of the percentage
change in the quantity demanded of a good to a percentage change in its price
refers to the price elasticity of demand.
<span>To add, price elasticity of demand (PED or Ed) is a measure used
in economics to show the responsiveness, or elasticity, of the quantity
demanded of a good or service to a change in its price, ceteris paribus.</span>
Answer:
Option "B" is the correct answer to the following statement.
Explanation:
The price elasticity of demand determines the flexibility of the volume needed to adjust the price.
The demand of an individual or market becomes inelastic if it will not adjust much to increasing prices, and it is elastic for an individual or market if the demand of a particular commodity will shift a lot as prices shift.
<span>Delta could implement self tagging whereby passengers could put destination tags on their own bags.This system would prevent theft by bag handlers who indulge in theft of expensive items like laptops,.cell phone etc.Due to correct tagging by passengers themselves bags are likely to reach their destination safely.</span>
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.
Learn more about Powder Bed Fusion here
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