All Matches

Solution Library

Expert Answer

Textbooks

Search Textbook questions, tutors and Books

Oops, something went wrong!

Change your search query and then try again

Result Not Found

Books FREE
Tutors
Study Help
Hire a Tutor
AI Study Help New

Search
Sign In
Register

study help
business
organization theory and design

Questions and Answers of Organization Theory and Design

● What kind of oversight do corporate boards provide? What kinds of relationships between investors, board and managers exist, and what influences their structures?
● When do companies choose to make an alliance with another company rather than buy their products? What are the costs and gains? What are the conditions that make this a good choice?
● How do firms gain, store, and use knowledge? What makes a company innovative?
● Why do so many firms look alike and why are there differences? How do these differences shape different performance?
8. I am most effective when I emphasizea. Inventing original solutions.b. Making practical improvements
7. One of my strengths isa. Commitment to making things work.b. Commitment to a dream for the future.
6. I can best help strategy by making sure there isa. Openness to a wide range of assumptions and ideas.b. Thoroughness when implementing new ideas.
5. I take pride in developinga. Ways to overcome a barrier to a solution.b. New hypotheses about the underlying cause of a problem.
4. In my office or home things area. Here and there in various piles.b. Laid out neatly or at least in reasonable order.
3. My thinking style could be more accurately described asa. Linear thinker, going from A to B to C.b. Thinking like a grasshopper, hopping from one idea to another.
2. If I run a group or a project, Ia. Have the general idea and let others figure out how to do the tasks.b. Try to figure out specific goals, timelines, and expected outcomes.
1. When keeping records, I tend to bea. Very careful about documentation.b. More haphazard about documentation.
5. Can the Teleflex Canada approach to innovation be implemented in other organizations?
4. Are there threats to continued innovation at Teleflex Canada?
3. What role do organizational factors play in supporting innovation?
2. Why has Teleflex Canada been so successful in introducing new products?
1. What does innovation mean at Teleflex Canada?Why is innovation necessary at Teleflex Canada?
2. Would you recommend that one or both of the organizations have different ratings on any of the scales?Why?
1. What are the main differences between the two organizations you evaluated?
7. What are the primary differences between an organization designed for efficiency and one designed for flexibility? Discuss the pros and cons of each approach for today’s organizations.
6. What does contingency mean? What are the implications of contingency theories for managers?
5. What is the difference between formalization and specialization? Do you think an organization high on one dimension would also be high on the other? Discuss.
4. A handful of companies on the Fortune 500 list are more than 100 years old, which is rare. What organizational characteristics do you think might explain 100-year longevity?
3. Explain how Mintzberg’s five basic parts of the organization illustrated in Exhibit 1.5 work. If an organization had to give up one of these five parts, which one could it survive the longest
2. What is the difference between an open system and a closed system? Can you give an example of a closed system? How is the stakeholder approach related to this concept?
1. What is the definition of organization? Briefly explain each part of the definition.
10. Tool coating experiment D. Dragulji´c, S. Nekkanty, T. J. Santner, A. M. Dean, and R. Shivpuri, in Quality Engineering in 2015, described a computer experiment used to develop multilayer
8. Minimum average reciprocal distance designs An alternative measure of space-fillingness is that of minimum average reciprocal distance. If design points are spaced out, then the distance between
7. Minimax designs Referring back to the intuitive explanation of the maximin designs in Exercise 6, consider now the distance between each customer and the location of the stores in a county. A
6. Maximin Latin hypercube designs Consider the three LHDs shown below. Note that the location of the points is not in the center of each cell but is randomly chosen. X1 = ⎡ ⎢ ⎢ ⎣ 0.66 0.65
5. Euclidean interpoint distance For two points xi = (xi1, xi2,..., xid ) and x j = (x j1, x j2,..., x jd ) in a d-dimensional space, the Euclidean distance between xi and x j is defined by (20.4.8),
4. Bohman correlation function The Bohman correlation function is given by R(xi − x j|ξ) = d k=1 R(xik − x jk |ξ) where R(xik − x jk |ξ) is given by 1 − xik−x jk θk cos π(xik−x
3. Cubic correlation function The cubic correlation function is given by R(xi − x j|ξ) = d k=1 R(xik − x jk |ξ) where R(xik − x jk |ξ) = ⎧ ⎪⎪⎪⎨ ⎪⎪⎪⎩ 1 − 6 xik−x jk
2. Power exponential correlation function The Gaussian correlation function (20.3.3) is a special case of a Power exponential correlation function. The latter is given by R(xi − x j|ξ) = d k=1
1. Gaussian correlation function The Gaussian correlation function R(xi − x j|ξ) introduced in Sect. 20.3, p. 768, quantifies the correlation between outputs at two points xi and x j based on the
9. Mobile Computing Field Study, continued The Mobile Computing Field Study was introduced in Sect. 19.7, and data on an additional response variable, time, was provided in Exercise 8. Using model
8. Mobile Computing Field Study, continued The Mobile Computing Field Study, introduced in Sect. 19.7, was run using a 2×3 split-plot design with 12 subjects as blocks, 24 days as whole plots, three
7. UAV switch experiment, continued The UAV switch experiment, introduced in Sect. 19.8.3, was run using a 2 × 2 split-plot design with 16 subjects as whole plots, with two levels of alert type (A)
6. UAV switch experiment, continued The UAV switch experiment, introduced in Sect. 19.8.3, was run using a 2×2 split-plot design with 16 subjects as whole plots, with two levels of alert type (A)
5. UAV experiment, continued The UAV experiment, introduced in Sect. 19.6, was run using a 22 × 4 split-plot design with 16 subjects (W) as whole plots, with two levels of cue condition (A) assigned
4. Injection molding experiment, continued The injection molding experiment, introduced in Exercise 10 of Chap. 15, was run in order to examine the effect of six factors on the shrinkage of a part
3. Cigarette experiment The cigarette experiment was run by J. Edwards, H. Hwang, S. Jamison, J. Kindelberger, and J. Steinbugl in 1996 in order to determine the factors that affect the length of
2. Fishing line experiment The fishing line experiment was run by C. Reynolds, B. Grunden, and K. Taylor in 1996 in order to compare the strengths of two brands of fishing line exposed to two
1. Drug experiment An experiment designed as a split-plot design was described by W.M. Wooding in the Journal of Quality Technology in 1973. The experiment concerned the evaluation of eight drugs
8. Red blood cell experiment The trout experiment reported by Gutsell (Biometrics, 1951) was described in Exercise 15 of Chap. 3. As part of the same experiment, the red blood cell counts in the
7. For the two-way nested fixed-effects model (18.2.1) on p. 672, show that the least squares estimator of μ + αi + βj(i) is given by Yi j.. [Hint: Differentiate the sum of squared errors with
6. Operator experiment An experiment to identify the causes of variability in readings of a spectrometer was described in Exercise 10 of Chap. 7, p. 241. The same authors (Inman et al., Journal of
5. Titanium alloy experiment, continued Suppose that factors C and D are to be investigated further in a followup experiment. Suppose that two new factors P and Q (“heat setting during
4. Titanium alloy experiment An experiment described by Johnson and Leone (1977, p. 758) was performed by a company to investigate the effects of various factors on the “yield strength” of a
3. Consider the model(a) Calculate the expected mean squares for all effects in the model. (b) Which ratio would you use to test H0 : {δl + (αδ).l all equal}? (c) Which ratio would you use to test
2. Sleep experiment Sleeping patterns can be classified according to periods of “deep sleep” and of “REM sleep” (rapid eye movement). An experiment is done to see how sleeping tablets and
1. Viscosity experiment An experiment was described by Johnson and Leone (1977, p. 744) to determine the viscosity of a polymeric material. The material was divided into two samples. The two samples
9. Temperature experiment, continued The temperature experiment was described and analyzed in Example 17.9.1, with corresponding SAS and R software analysis provided in Sects. 17.10.2 and 17.11.2,
8. Ice cream experiment, continued The ice cream experiment was described in Example 17.3.1, p. 621, and was analyzed in Examples 17.3.2–17.3.4 and 17.4.1. In Sect. 17.10, p. 657, a new model was
7. Mixed model Consider the following mixed model: Yijkmt = μ + αi + Bj + Ck + δm + (αB)ij + (αδ)im + (Bδ)jm + (Cδ)km + (αBδ)ijm + ijkmt , i = 1,...,a, j = 1,...,b, k = 1,...,c, m =
6. Golf ball experiment An experiment was planned by Tim Kelaghan in 1995 to examine whether different brands of golf balls travel on average the same distances when hit by amateur golfers. The
5. Candle experiment An experiment to determine whether different colored candles (red, white, blue, yellow) burn at different speeds was conducted by Hsing-Chuan Tsai, Mei-Chiao Yang, Derek Wheeler,
4. Buttermilk biscuit experiment The buttermilk biscuit experiment was run by Stacie Taylor in 1995 to find out which brands of refrigerated buttermilk biscuit give rise to the fluffiest biscuits.
3. Random effects model Consider the following random-effects model: Yijkmt = μ + Ai + Bj + Ck + Dm + (AB)ij + (BC)jk + (BD)jm + ijkmt , i = 1,...,a, j = 1,...,b, k = 1,...,c, m = 1,...,d, t =
2. Ice cream experiment, continued As in Example 17.4.1, p. 630, suppose the ice cream experiment is to be repeated, with γ = 1.0 and with a Type I error probability of α = .05. Suppose that we
1. Alcohol experiment Solutions of alcohol are used for calibrating Breathalyzers. The data in Table 17.19 show the alcohol concentrations (mg/ml) of samples of alcohol solutions taken from six
13. Box–Behnken design (a) Construct a Box–Behnken design for five factors based on the balanced incomplete block design for five treatments in 10 blocks of size two. (b) Determine whether the
12. Box–Behnken design (a) Construct a Box–Behnken design for three factors based on the balanced incomplete block design for three treatments in three blocks of size two and the 22 factorial
11. Resin moisture experiment A Box–Behnken design was used to determine whether specific drying conditions for a process could yield a resin that is sufficiently devoid of moisture and
10. Resin impurity experiment An experiment was conducted using a design close to a central composite design to study the effects of drying time (hours) and temperature (◦C) on the content y (ppm)
9. Central composite design Repeat Exercise 8 for a central composite design for four factors, to include 16 factorial points and eight axial points.
8. Central composite design Consider using a central composite design for three factors, to include eight factorial points and six axial points. (a) Determine the value of α to make the design
7. Flour production experiment, continued Consider again the flour production experiment of Sect. 16.5. The data were given in Table 16.11 (p. 590), along with the statistics y.z and 100 log10(sz)
6. Film viscosity experiment Cuq et al. (1995, Journal of Food Science) used a central composite design to study the effects of protein concentration (g/100 g solution), pH, and temperature (◦C),
5. Fractionation experiment, continued The fractionation experiment was described in Exercise 3, and analysis of the first-order model for “Yield” was considered in Exercise 4. Based on the
4. Fractionation experiment, continued The fractionation experiment was described in Exercise 3, where the response PCE was used. Consider here, instead, the analysis of “Yield”. (a) Fit the
3. Fractionation experiment Sosada (1993) studied the effects of extraction time, solvent volume, ethanol concentration, and temperature on the yield and phosphatidylcholine enrichment (PCE) of
2. Paint followup experiment The data of the second paint experiment described by Eibl et al. (1992) are given in Table 16.23. This experiment involves factors A–D, as these had significant effects
1. Paint experiment, continued The paint experiment of Eibl et al. (1992) was discussed in Example 16.2.1 (p. 569), where the first-order model was fitted to the data. For the fitted first-order
12. Suggest a confounding scheme for a 22 × 32 × 6 experiment in 12 blocks of size 18. Under what circumstances would the design be useful? Write out two blocks of the design.
11. Suggest a confounding scheme for a 22 × 32 × 6 experiment in 9 blocks of size 24. Under what circumstances would the design be useful? Explain how to find the blocks of the design.
10. Suggest a confounding scheme for a 22 × 32 × 4 experiment in 12 blocks of size 12. Under what circumstances would the design be useful? Write out two blocks of the design.
9. Suggest a confounding scheme for a 23 × 33 experiment in 12 blocks of size 18. Under what circumstances would the design be useful? Write out two blocks of the design.
8. Consider a 22 × 32 design confounding AB, (CD2; C2 D), and (ABCD2; ABC2 D). (a) Give the design—namely, list the treatment combinations block by block. (b) Describe how to randomize the design.
7. Example 14.3.2, continued In Example 14.3.2, p. 483, we showed one way of associating design factors F, G, H, and J of a 23 ×4 factorial experiment to the 2-level pseudofactors A–E of a
6. Sugar beet experiment F. Yates, in a 1935 paper published in a supplement to the Journal of the Royal Statistical Society, describes an agricultural experiment on the yield of sugar beet. The
5. A set of hypothetical data is given in Table 14.18 for a partially confounded 32 experiment in 6 blocks of 3. The design is made up of two single-replicate designs: The first confounds the
4. Dye experiment, continued The experimenters who ran the dye experiment were interested in the linear and quadratic components of the main effects and interactions. Analyze the experiment
3. Dye experiment, continued (a) For the dye experiment of Sect. 14.2.4, check that the variances of the errors appear to be equal for the different levels of the three factors. Check also that the
2. Suggest a confounding scheme for a 35 experiment in 27 blocks of size 9 if all 2-factor interactions and the 3-factor interaction ABE are to be estimated.
1. Suggest a confounding scheme for a 35 experiment in 9 blocks of size 27 if all 2-factor interactions and the 3-factor interaction ABE are to estimated.
16. Design of an experiment (a) Design an experiment with five factors A, B,C, D, E, each having two levels, in 4 blocks of 8 and r = 1 observation per treatment combination. Make sure that you can
15. Design of a follow-up experiment An experiment was run in 2007 by Joanne Sklodowski, Josh Svenson, Adam Dallas, Tim Degenero and Paul Cotellesso to examine the compressive strength of various
14. Catalytic reaction experiment, continued In the experiment described in Exercise 13, the covariate “makeup gas purity” was measured. The covariate values were 17, 12, 10, 10, 13, 14, 10, 16,
13. Catalytic reaction experiment J.R. Bainbridge, in his 1951 article in the journal Industrial and Engineering Chemistry, described a factorial experiment conducted at a small plant carrying out a
12. Construct a four-replicate 23 design in eight blocks of size four, partially confounding each interaction effect. Compare the variance of each interaction contrast with that of each main effect,
11. Field experiment, continued The field experiment was described in Example 13.3.1, p. 437. There were four treatment factors(A, B, C, and D) at two levels each, and the v = 16 treatment
10. Peas experiment The following experiment was run at Biggelswade, in England, and reported by F. Yates in his 1935 paper Complex Experiments. The three treatment factors were the standard
9. Penicillin experiment An experiment is described in Example 9.2 of the book Design and Analysis of Industrial Experiments edited by O. L. Davies that investigates the effects of various factors on
8. Decontamination experiment—Beta particles An experiment was described by M. K. Barnett and F. C. Mead, Jr. in the journal Applied Statistics in 1956 to explore the effect of four factors on the
7. Mangold experiment, continued (a) For the mangold experiment of Sect. 13.5, verify that the sum of squares and the contrast estimate for CD are as shown in Table 13.12, p. 449. (b) Draw the CD
6. Suggest a confounding scheme for a 28 experiment in 16 blocks of 16, assuming that all 2-factor and 3-factor interactions are to be estimated. List all effects confounded. List the treatment
5. Suggest a confounding scheme for a 26 experiment in 8 blocks of 8, assuming that all 2-factor interactions are to be estimated, as are the 3-factor interactions involving both A and F. List all
4. Field experiment, continued (a) For the field experiment of Example 13.3.1, p. 437, verify that the sum of squares and the contrast estimate for BD are as shown in Table 13.5, p. 438. (b) Draw the
3. Projectile experiment N.L. Johnson and F.C. Leone, in their 1977 book Statistics and Experimental Design in Engineering and the Physical Sciences, described a single-replicate 24 experiment

Showing 200 - 300 of 2629

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Last

Services

Sitemap
Fun
Definitions
Become Tutor
Study Help Categories
Recent Questions
Expert Questions

Company Info

Security
Copyrights
Privacy Policy
Terms & Conditions
SolutionInn Fee
Scholarship

Get In Touch

About Us
Contact Us
Career
Jobs
FAQ
Campus Ambassador

Secure Payment

Download Our App

© 2024 SolutionInn. All Rights Reserved