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Table 15.2 For a Management Class, a Group of Students Is Considering

question 2

Multiple Choice

Table 15.2
For a management class, a group of students is considering how to structure a proposed company. Their original idea was a design that would give complete responsibility for the development and marketing of a product to one unit. Tax considerations are a concern as well, and they want a structure that would help the accountants track them better through specific cost centers. They decide not to use this design because of the duplication of effort and the probability that it would be difficult to attract and retain talented employees. In their second design they want to stress the opportunity for employees to specialize, gain economies of scale, and conserve resources by eliminating duplication of effort. They reject that design because it is too cumbersome and slow to respond to the changes in the marketplace. Then one member of the group, Jack, suggests that they eliminate chains of command and spans of control and go to empowered teams. He argues that this will increase creativity and responsibility among employees. A fellow student argues that it won't work in the real world because managers won't give up that much authority. "Ok," a third student, Jane, offers, "let's try this idea but build around a hub. The hub will be the core business and the spokes will be groups of specialists that can be added to or subtracted from as the market changes." They settle on a structure with two lines of authority, one by task specialization and the other by product line. This gives them economies of scale and flexibility but some stress over reporting authority. Nevertheless, it gives them the best of what they want.
-Refer to Table 15.2. Jack's idea is an example of a:

Definitions:

Alpha Level

Alpha level, or significance level, is the threshold of probability at which you reject the null hypothesis, typically set at 0.05 or 5%.

Critical Values

Critical values are specific points on the scale of a test statistic that determine the boundary for rejecting the null hypothesis.

Type I Error

The incorrect rejection of a true null hypothesis, or a false positive, in statistical hypothesis testing.

P-value

A measure in hypothesis testing that indicates the probability of obtaining a result at least as extreme as the one observed, assuming the null hypothesis is true.