A large city government was putting on a number of seminars for managers of various departments throughout the city. At one of these sessions the topic discussed was motivation—how to motivate public servants to do a good job.
A large city government was putting on a number of seminars for managers of various departments throughout the city. At one of these sessions the topic discussed was motivation—how to motivate public servants to do a good job.
A large city government was putting on a number of seminars for managers of various departments throughout the city. At one of these sessions the topic discussed was motivation—how to motivate public servants to do a good job. The plight of a police captain became the central focus of the discussion: I’ve got a real problem with my officers. They come on the force as young, inexperienced rookies, and we send them out on the street, either in cars or on a beat. They seem to like the contact they have with the public, the action involved in crime prevention, and the apprehension of criminals. They also like helping people out at fires, accidents, and other emergencies. The problem occurs when they get back to the station. They hate to do the paperwork, and because they dislike it, the job is frequently put off or done inadequately. This lack of attention hurts us later on when we get to court. We need clear, factual reports. They must be highly detailed and unambiguous. As soon as one part of a report is shown to be inadequate or incorrect, the rest of the report is suspect. Poor reporting probably causes us to lose more cases than any other factor.
I just don’t know how to motivate them to do a better job. We’re in a budget crunch, and I have absolutely no financial rewards at my disposal. In fact, we’ll probably have to lay some people off in the near future. It’s hard for me to make the job interesting and challenging because it isn’t-it’s boring, routine paperwork, and there isn’t much you can do about it.
Finally, I can’t say to them that their promotions will hinge on the excellence of their paperwork. First at all, they know it’s not true. If their performance is adequate, most are more likely to get promoted just by staying on the force a certain number of years than for some specific outstanding act. Second, they were trained to do the job they do out in the streets, not to fill out forms. All through their careers the arrests and interventions are what get noticed.
Some people have suggested a number of things, like using conviction records as a performance criterion. However, we know that’s not fair—too many other things are involved. Bad paperwork increases the chance that you lose in court, but good paperwork doesn’t necessarily mean you’ll win. We tried setting up the team competitions based on the excellence of the reports, but the officers caught on to that pretty quickly. No one was getting any type of reward for winning the competition, and they figured why should they bust a gut when there was on payoff. I just don’t know what to do.
Question:
What performance problems is the captain trying to correct?
Use the MARS model of individual behavior and performance to diagnose the possible causes of the unacceptable behavior.
Has the captain considered all possible solutions to the problem? If not, what else might be done?
A large city government was putting on a number of seminars for managers of various departments throughout the city. At one of these sessions the topic discussed was motivation—how to motivate public servants to do a good job.
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A handful of major players, compete head-to-head around the world in the chemical industry. These companies are Dow Chemical and Du Pont of the United States
A handful of major players, compete head-to-head around the world in the chemical industry. These companies are Dow Chemical and Du Pont of the United States
A handful of major players, compete head-to-head around the world in the chemical industry. These companies are Dow Chemical and Du Pont of the United States, Great Britain’s ICI, and the German trio of BASF, Hoechst AG, and Bayer. The barriers to the free flow of chemical products between nations largely disappeared in the 1970s. This, along with the commodity nature of bulk chemicals and a severe recession in the early 1980s, ushered in a prolonged period of intense price competition. In such an environment, the company that wins the competitive race is the one with the lowest costs. Dow Chemical was long among the cost leaders.
For years Dow’s managers insisted that part of the credit belonged to its “matrix” organization. Dow’s organizational matrix had three interacting elements: functions (such as R&D, manufacturing, and marketing), businesses (like ethylene, plastics, and pharmaceuticals), and geography (for example, Spain, Germany, and Brazil). Managers’ job titles incorporated all three elements (plastics marketing manager for Spain), and most managers reported to at least two bosses. The plastics marketing manager in Spain might report to both the head of the worldwide plastics business and the head of the Spanish operations. The intent of the matrix was to make Dow operations responsive to both local market needs and corporate objectives. Thus the plastics business might be charged with minimizing Dow’s global plastics production costs, while the Spanish operation might determine how best to sell plastics in the Spanish market.
A handful of major players
When Dow introduced this structure, the results were less than promising: Multiple reporting channels led to confusion and conflict. The many bosses created an unwieldy bureaucracy. The overlapping responsibilities resulted in turf battles and a lack of accountability. Area managers disagreed with managers overseeing business sectors about which plants should be built where. In short, the structure, didn’t work. Instead of abandoning the structure, however, Dow decided to see if it could made more flexible.
Dow’s decision to keep its matrix structure was prompted by its move into the pharmaceuticals business is very different from the bulk chemicals business. In bulk chemicals, the big returns come from achieving economies of scale in production. This dictates establishing large plants in key locations from which regional or global markets can be served. But in pharmaceuticals, regulatory and marketing requirements for drugs vary so much from country to country that local needs are far more important than reducing manufacturing costs through scale economies. A high degree of local responsiveness is essential. Dow realized its pharmaceutical business would never thrive if it were managed by the same priorities as its mainstream chemical operations.
Accordingly, instead of abandoning its matrix, Dow decided to make it more flexible to better accommodate the different businesses, each with its own priorities, within a single management system. A small team of senior executives at headquarters helped set the priorities for each type of business. After priorities were identified for each business sector, one of the three elements of the matrix—function, business, or geographic area—was given primary authority in decision making. Which element took the lead varied according to the type of decision and the market or location in which the company was competing. Such flexibility that all employees understand what was occurring in the rest of the matrix. Although this may seem confusing, for years Dow claimed this flexible system worked well and credited much of its success to the quality of the decisions it facilitated.
By the mid-1990s, however, Dow had refocused its business on the chemicals industry, divesting itself of its pharmaceutical activities where the company’s performance had been unsatisfactory. Reflecting the change in corporate strategy, in 1995 Dow decided to abandon its matrix structure in favor of a more streamlined structure based on global product divisions. The matrix structure was just too complex and costly to manage in the intense competitive environment of the time, particularly given the company’s renewed focus on its commodity chemicals where competitive advantage often went to the low-cost producer. As Dow’s then-CEO put it in a 1999 interview, “We were an organization that was matrixed and depended on teamwork, but there was no one in charge. When things went well, we didn’t know whom to reward; and when things went poorly, we didn’t know whom to blame. So we created a global divisional structure and cut out layers of management. There used to be eleven layers of management between me and the lowest-level employees; now there are five.
Questions
Why did Dow Chemical first adopt a matrix structure? What benefits did it hope to derive from this structure?
What problems emerged with this structure? How did Dow try to deal with them? In retrospect, do you think those solutions were effective?
Why did Dow change its structure again in the mid-1990s? What was Dow trying to achieve this time? Do you think the current structure makes sense given the industry in which Dow operates and the strategy of the firm? Why?
A handful of major players, compete head-to-head around the world in the chemical industry. These companies are Dow Chemical and Du Pont of the United States
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A guest walked up to the front desk agent in an upscale hotel, ready to check out. As she would normally do when checking out a guest, the agent asked the guest what his room number was.
A guest walked up to the front desk agent in an upscale hotel, ready to check out. As she would normally do when checking out a guest, the agent asked the guest what his room number was.
A guest walked up to the front desk agent in an upscale hotel, ready to check out. As she would normally do when checking out a guest, the agent asked the guest what his room number was. The guest was in a hurry and showed his anxiety by responding, “I stay in a hundred hotel rooms and you expect me to remember my room number?” The agent then asked for the guest’s name, to which he responded, “My name is Mr. Johnstein.” After thanking him, the agent began to look for the guest’s last name, but the name was not listed in the computer. Because the man had a heavy accent and the agent assumed that she had misunderstood him, she politely asked the guest to spell his last name. He answered, “What? Are you an idiot? The person who checked me in last night had no problem checking me in.” Again, the agent looked on the computer to find the guest.
The guest, becoming even more frustrated, said, “I have a plane to catch and it is ridiculous that it has to take this long to check me out. I also need to fax these papers off, but I need to have them photocopied first.” The agent responded, “There is a business center at the end of the counter that will fax and photocopy what you for it. Haven’t you ever heard of customer service? Isn’t this a five-star hotel? With your bad attitude, you should be working in a three-star hotel. I can’t believe they let you work here at the front desk. Haven’t you found my name yet?” The agent, who was beginning to get upset, asked the guest again to spell out his full name. The guest only replied, “Here are my papers I want faxed if you are capable of faxing them.” The agent reached to take the papers, and the guest shouted, “Don’t grab them from my hand! You have a bad attitude, and if I had more time, I would talk to someone about getting you removed from your position to a hotel where they don’t require such a level of customer service.” The agent was very upset, but kept herself calm in order to prevent the guest from getting angrier.
The agent continued to provide service to the guest, sending the faxes and making the photocopies he had requested. Upon her return, the agent again asked the guest to repeat his last name, since he had failed to spell it out. The guest replied by spelling out his name, “J-o-h-n-s-t-o-n-e.” The agent was finally able to find his name on the computer and checked him out, while he continued to verbally attack her. The agent finished by telling the guest to have a nice flight.
Questions:
Is it appropriate to have the manager finish the check-out? Or, should the front desk agent just take the heat?
Would you have handled the situation in the same manner?
What would you have done differently?
Communication improvement is required for both of the parties involved or any one of them? Justify your opinion.
A guest walked up to the front desk agent in an upscale hotel, ready to check out. As she would normally do when checking out a guest, the agent asked the guest what his room number was.
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A fictitious data set consisting of thirty respondents was created. The data was mainly constructed to find the relationship between the dependent and independent variable.
A fictitious data set consisting of thirty respondents was created. The data was mainly constructed to find the relationship between the dependent and independent variable.
A fictitious data set consisting of thirty respondents was created. The data was mainly constructed to find the relationship between the dependent and independent variable. Age was taken as the independent variable and choice of a drink as dependent variable. Six brands of soft drinks were considered as the different choices for the respondents.
The age group coded into six categories as 1 to 6 and the brands of soft drinks were coded into six categories and the codings are as follows:
(a) Independent variable Age Coding
<15 1
16 – 25 2
26 – 35 3
36 – 45 4
46 – 55 5
>55 6
(b) Dependent variable Different brands Coding
Coke 1
Pepsi 2
Mirinda 3
Sprite 4
Slice 5
Fruit Juice 6
Chi-square test has been used to cross-tabulate and to understand the relationship between the independent and the dependent variable.
Calculation of contingency coefficient and the lambda asymmetric coefficient is done to find the strength of the association between the two variables.
Sample size is taken as thirty.
Analysis of cross-tabulation.
SPSS software package for the cross tabulation analysis.
Problem
This is a bivariate problem. The basic intention of the problem is to understand the relationship between AGE and BRAND PREFERENCE of different brands of soft drinks.
Input Data Table
Serial No.
Age
AGECODE
SOFT DRINK
DRINK CODE
1
<15
1
FRUIT JUICE
6
2
<15
1
SPRITE
4
3
<15
1
MIRINDA
3
4
<15
1
PEPSI
2
5
<15
1
FRUIT JUICE
6
6
16-25
2
COKE
1
7
16-25
2
SLICE
5
8
16-25
2
COKE
1
9
16-25
2
PEPSI
2
10
16-25
2
MIRINDA
3
11
26-35
3
SLICE
5
12
26-35
3
SPRITE
4
13
26-35
3
FRUIT JUICE
6
14
26-35
3
PEPSI
2
15
26-35
3
SLICE
5
16
36-45
4
MIRINDA
3
17
36-45
4
FRUIT JUICE
6
18
36-45
4
FRUIT JUICE
6
19
36-45
4
SLICE
5
20
36-45
4
PEPSI
2
21
46-55
5
COKE
1
22
46-55
5
SPRITE
4
23
46-55
5
SLICE
5
24
46-55
5
FRUIT JUICE
6
25
46-55
5
SLICE
5
26
>55
6
MIRINDA
3
27
>55
6
COKE
1
28
>55
6
COKE
1
29
>55
6
PEPSI
2
30
>55
6
FRUIT JUICE
6
Output Data
Age by Drink Preference
Age
Drink Preference
Code
<15
16-25
26-35
36-45
46-55
>55
Total
Coke
1
0
2
33.32%
0
0
1
20%
1
40%
5
16.67%
Pepsi
2
1
20%
1
16.67%
1
25%
1
20%
0
1
20%
5
16.67%
Mirinda
3
1
20%
1
16.67%
0
1
20%
0
1
20%
4
13.33%
Sprite
4
1
20%
0
1
25%
0
1
20%
0
3
30%
Slice
5
0
1
16.67%
2
50%
1
20%
2
40%
0
6
40%
Fruit Juice
6
2
40%
1
16.67%
0
2
40%
1
20%
1
20%
7
23.33%
Total
5
100%
6
100%
4
100%
5
100%
5
100%
5
100%
30
100%
Chi-Square
Value
DF
Significance
Pearson
18.22857
25
.08325
Likelihood Ratio
25.52646
25
.04332
Mantel-Haenszel test for linear association
.13961
1
.07086
Minimum Expected Frequency ─.500
Cells with Expected Frequency <5─36 of 36 (100.0%)
Approximate Statistics
Value
ASE 1
VAL/ASE 0
Significance
Contigency Coefficient
.61479
.08325*1
Lambda:
Symmetric
.18750
.08892
1.99754
With ‘DRINK CODE’ dependent
.21739
.12757
1.56813
With ‘AGE CODE’ dependent
.16000
.07332
2.14834
Goodman & Kruskal Tau:
With ‘DRINK CODE’ dependent
.12432
.03912
.08412*2
With ‘AGE CODE’ dependent
.12152
.02580
.08580*2
*1 Pearson Chi-square probability
*2 Based on Chi-square approximation
Number of Missing Observations: 0
Analysis
In a Chi-square test, for a 90 per cent confidence level, if the significance level is greater than or equal to 0.1, it signifies that there is no association between the two variables in the cross-tabulation and if significance level is less than 0.1, then it signifies that there is a significance relationship between the selected variables.
A fictitious data set consisting of thirty
The result of the cross-tabulation
From the output tables, the Chi-square test read a significance level of 0.08325 at 90 percent confidence level. For 90 per cent, significance level is 0.1, that is (1─0.9), so the above result shows that at 0.08 (which is less than 0.1), there is a significant relationship between the two variables. At 95 per cent confidence level, significance level being 0.05, and the above output giving a significance level of 0.08 which is greater than 0.05, there is no relationship between the variables:
If contingency coefficient value is greater than +0.5 then the variables are strongly associated. In the above case the contingency coefficient value being 0.6 which is greater than 0.5, hence the variables are strongly associated.
The asymmetric lambda value (with DRINKCODE dependent) 0.21739 means that 21.7% of error is reduced in predicting brand preference when age is known.
From the above result we can conclude that there is a significant relationship between AGE (independent variable) and BRAND PREFERENCE (dependent variable), of the respondents.
Thus we can conclude that the age of the respondent plays an important role in the purchasing intention of a particular brand of soft drink.
Question
Case 2: Conduct Chi-square test to cross-tabulate and to understand the relationship between the independent and the dependent variable. Also calculate contingency coefficient and the lambda asymmetric coefficient to find the strength of the associationbetween the two variables. Take Sample size as thirty. Analysis of cross-tabulation using SPSS software package would be required.
A fictitious data set consisting of thirty respondents was created. The data was mainly constructed to find the relationship between the dependent and independent variable.
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And for each service, each subject and each topic, we dedicate an expert writer who has knowledge in that specific field of study. Experience impeccable academic writing service like never before.
Our experts understand that the time of the customers is very precious. The professors of universities and colleges are very rigorous about the submission deadlines of projects or assignments. Hence, the key objective of our case study help service is to deliver the assignments to the customers even before the promised submission deadlines.
We keep the quality measures for all papers which mean we will provide best essays. Our editing services are also excellent. Before submitting any essays, we will check whether the papers writer well or not. The high standards of academic writing will exceed your expectations. With our quality service, we have satisfied more number of people across the world and also work with different universities in Australia, UK, USA, Dubai, Oman, etc.
