| Literature DB >> 20190858 |
David A Swanson, Peter A Morrison.
Abstract
Many faculty members consider using case studies but not all end up using them. We provide a brief review of what cases are intended to do and identify three ways in which they can be used. We then use an example to illustrate how we have used the case study method in teaching business demography. Among other benefits, we note that the case studies method not only encourages the acquisition of skills by students, but can be used to promote "deep structure learning," an approach naturally accommodates other features associated with the case studies method-the development of critical thinking skills, the use of real world problems, the emphasis of concepts over mechanics, writing and presentation skills, active cooperative learning and the "worthwhileness" of a course. As noted by others, we understand the limitations of the case study method. However, given its strengths, we believe it has a place in the instructional toolbox for courses in business demography. The fact that courses we teach is a testament to our perceived efficacy of this tool.Entities:
Year: 2009 PMID: 20190858 PMCID: PMC2822910 DOI: 10.1007/s11113-009-9155-4
Source DB: PubMed Journal: Popul Res Policy Rev ISSN: 0167-5923
Exhibit 1Moore’s view of the market life cycle
Exhibit 2Moore’s analytic framework
Current population by age (number and percent) in county K and county S
| Age | County K | County S | ||
|---|---|---|---|---|
| Number | Percent (%) | Number | Percent (%) | |
| Less than 25 | 229505 | 40 | 57442 | 23 |
| 25–34 | 97209 | 17 | 27731 | 11 |
| 35–44 | 70750 | 12 | 24512 | 10 |
| 45–54 | 58095 | 10 | 22532 | 9 |
| 55–64 | 57520 | 10 | 40359 | 16 |
| 65 and over | 62121 | 11 | 75024 | 31 |
| Total | 575200 | 100 | 247600 | 100 |
Current cellular phone subscriptions (%) by age, population by age (%), and market attractiveness index (% subscriptions × % age) by age: county K and county S
| Age | County K | County S | ||||
|---|---|---|---|---|---|---|
| Subscriptions (%) | Population (%) | Index | Subscriptions (%) | Population (%) | Index | |
| Less than 25 | 3 | 40 | 120 | 3 | 23 | 69 |
| 25–34 | 29 | 17 | 493 | 29 | 11 | 319 |
| 35–44 | 39 | 12 | 468 | 39 | 10 | 390 |
| 45–54 | 20 | 10 | 200 | 20 | 9 | 180 |
| 55–64 | 7 | 10 | 70 | 7 | 16 | 112 |
| 65 and over | 2 | 11 | 22 | 2 | 31 | 62 |
| Total | 100 | 1373 | 100 | 1132 | ||
The market attractiveness index is found by multiplying the percent of total subscriptions at a given age group by the percent of the total population in this same age group
Forecasted population 10 years from now by age (number and percent) in county K and county S
| Age | County K | County S | ||
|---|---|---|---|---|
| Number | Percent (%) | Number | Percent (%) | |
| Less than 25 | 217000 | 35 | 76000 | 20 |
| 25–34 | 99200 | 16 | 34200 | 9 |
| 35–44 | 68200 | 11 | 38000 | 10 |
| 45–54 | 68200 | 11 | 38000 | 10 |
| 55–64 | 68200 | 11 | 64600 | 17 |
| 65 and over | 99200 | 16 | 129200 | 34 |
| Total | 620000 | 100 | 380000 | 100 |
Forecasted cellular phone subscriptions 10 years from now (%) by age, population by age (%), and market attractiveness index (% subscriptions × % age) by age: county K and county S
| Age | County K | County S | ||||
|---|---|---|---|---|---|---|
| Subscriptions (%) | Population (%) | Index | Subscriptions (%) | Population (%) | Index | |
| Less than 25 | 2 | 35 | 70 | 2 | 20 | 40 |
| 25–34 | 15 | 16 | 240 | 15 | 9 | 135 |
| 35–44 | 18 | 11 | 198 | 18 | 10 | 180 |
| 45–54 | 27 | 11 | 297 | 27 | 10 | 270 |
| 55–64 | 23 | 11 | 253 | 23 | 17 | 391 |
| 65 and over | 15 | 16 | 240 | 15 | 34 | 510 |
| Total | 100 | 1298 | 100 | 1526 | ||
The market attractiveness index is found by multiplying the percent of total subscriptions at a given age group by the percent of the total population in this same age group
Exhibit 3Response from student “A”
Exhibit 4Response from student “B”