Answer:
Personal liability
Explanation:
Jeri and Knute are shareholders in lighthouse tours LLC. As lighthouse tours LLC is a limited liability company, Jeri and Knute enjoy limited liability.
Legally, lighthouses LLC is independent of its shareholders. It has the right to own assets and incur liabilities. Should the company get to the dissolution stage, its assets will be used to settle its obligations. If the assets of the company are not sufficient, the shareholders' private properties cannot be used to pay the debts. Jeri and Knute will be liable only to the extent of capital contribution.
Answer: Decentralized structure
Explanation: In simple words, it refers to the organisational structure in which most of the decisions regarding the operations are made by the managers working on mid and lower level. The top managers in such a structure takes only those decisions which are of highest priority to the organisation.
In the given case, Joanna is the lower level managers but still contributes frequently in decision making.
Hence we can conclude that her organisation has decentralized structure.
Answer:
$463.67 million
Explanation:
The computation of the expected terminal enterprise value is shown below:
Terminal Enterprise value is
= Free cash flow × (1 + growth rate) ÷ (Weighted average cost of capital - growth rate)
= $26 million × (1.07) ÷ (0.13 - 0.07 )
= $27.82 million ÷ 0.06
= $463.67 million
We simply applied the above formula to determine the expected terminal value
Answer:
The Minimum Wage Used To Be Enough To Keep Workers Out Of Poverty in 1979.
Explanation:
<span>data inconsistency
Let's look at the available options and see what makes or does not make sense.
data normalization
* Data normalization is the process of having each piece of data in the database entered only once. If you need the same data element multiple times, you put the data element into a table and each time you need that element, you make a reference to that table which holds the only copy of that piece of data. This process is used to simplify making changes to that data element. If the element changes, you make the change to a single piece of data in the database and that change is reflected everywhere else in the database that uses that element. That's not the issue with this problem, so it's a bad choice.
data accuracy
* Close, but not quite. The data in the database is accurate and does have the correct address and a correct variant of the person's name. So this isn't the right choice either.
data redundancy
* This is a problem that addressed by data normalization. And just like data normalization doesn't address this question's problem, neither does this address it. So another bad choice.
data inconsistency
* BINGO! The root issue is that minor variations in the format of a name result in what the database considers to be an unique name. And hence an unique person. This is the correct choice.
data duplication
* Another name for redundancy. So another bad choice.</span>
