Cross-tabulation analysis between clusters based on the levels within the attributes and demographic characteristics (Ojijo and Steiger, 2023)
| Cross-tabulation analysis between identified clusters and demographic characteristics (n = 299) | ||||||
|---|---|---|---|---|---|---|
| Clusters: attribute levelsa | Total per demographic profile | |||||
| Cluster 1 | Cluster 2 | Cluster 3 | ||||
| Gender | Male | Count (% within gender) | 84 (55.6%) | 48 (31.8%) | 19 (12.6%) | 151 |
| % within clusters | 52.8% | 48.5% | 46.3% | |||
| Female | 75 (50.7%) | 51 (34.5%) | 22 (14.9%) | 148 | ||
| 47.2% | 51.5% | 53.7% | ||||
| Age range | 18–24 | Count (% within age range) | 9 (33.3%) | 13 (48.1%) | 5 (18.5%) | 27 |
| % within clusters | 5.7% | 13.1% | 12.2% | |||
| 25–34 | 37 (58.7%) | 22 (34.9%) | 4 (6.3%) | 63 | ||
| 23.3% | 22.2% | 9.8% | ||||
| 35–44 | 38 (53.5%) | 25 (35.2%) | 8 (11.3%) | 71 | ||
| 23.9% | 25.3% | 19.5% | ||||
| 45–54 | 49 (62.8%) | 19 (24.4%) | 10 (12.8%) | 78 | ||
| 30.8% | 19.2% | 24.4% | ||||
| 55–64 | 14 (48.3%) | 10 (34.5%) | 5 (17.2%) | 29 | ||
| 8.8% | 10.1% | 12.2% | ||||
| 65–74 | 7 (58.3%) | 1 (8.3%) | 4 (33.3%) | 12 | ||
| 4.4% | 1.0% | 9.8% | ||||
| 75 and above | 5 (26.3%) | 9 (47.4%) | 5 (26.3%) | 19 | ||
| 3.1% | 9.1% | 12.2% | ||||
| Level of education | No formal education | Count (% within education) | 13 (48.1%) | 8 (29.6%) | 6 (22.2%) | 27 |
| % within clusters | 8.2% | 8.1% | 14.6% | |||
| Primary education | 13 (39.4%) | 10 (30.3%) | 10 (30.3%) | 33 | ||
| 8.2% | 10.1% | 24.4% | ||||
| Secondary education | 75 (59.1%) | 39 (30.7%) | 13 (10.2%) | 127 | ||
| 47.2% | 39.4% | 31.7% | ||||
| Higher education | 58 (51.8%) | 42 (37.5%) | 12 (10.7%) | 112 | ||
| 36.5% | 42.4% | 29.3% | ||||
| Occupation and employment status | Agriculture | Count (% within occupation) | 16 (57.1%) | 9 (32.1%) | 3 (10.7%) | 28 |
| % within clusters | 10.1% | 9.1% | 7.3% | |||
| Homemaker | 9 (50.0%) | 8 (44.4%) | 1 (5.6%) | 18 | ||
| 5.7% | 8.1% | 2.4% | ||||
| Teacher/educator | 16 (50.0%) | 12 (37.5%) | 4 (12.5) | 32 | ||
| 10.1% | 12.1% | 9.8% | ||||
| Manufacture | 5 (55.6%) | 4 (44.4%) | 0 (0.0%) | 9 | ||
| 3.1% | 4.0% | 0.0% | ||||
| Retail | 21 (55.3%) | 12 (31.6%) | 5 (13.2%) | 38 | ||
| 13.2% | 12.1% | 12.2% | ||||
| Tourism | 22 (68.8%) | 8 (25.0%) | 2 (6.3%) | 32 | ||
| 13.8% | 8.1% | 4.9% | ||||
| Military and other police services | 18 (62.1%) | 4 (13.8%) | 7 (24.1%) | 29 | ||
| 11.3% | 4.0% | 17.1% | ||||
| Health and social work | 11 (50.0%) | 8 (36.4%) | 3 (13.6%) | 22 | ||
| 6.9% | 8.1% | 7.3% | ||||
| Government and public administration | 16 (59.3%) | 7 (25.9%) | 4 (14.8%) | 27 | ||
| 10.1% | 7.1% | 9.8% | ||||
| Banking and legal services | 7 (58.3%) | 3 (25.0%) | 2 (16.7%) | 12 | ||
| 4.4% | 3.0% | 4.9% | ||||
| Transportation | 4 (28.6%) | 6 (42.9%) | 4 (28.6%) | 14 | ||
| 2.5% | 6.1% | 9.8% | ||||
| Student | 7 (41.2%) | 9 (52.9%) | 1 (5.9%) | 17 | ||
| 4.4% | 9.1% | 2.4% | ||||
| Retired or unemployed | 2 (20.0%) | 4 (40.0) | 4 (40.0%) | 10 | ||
| 1.3% | 4.0% | 9.8% | ||||
| Other | 5 (45.5%) | 5 (45.5%) | 1 (9.1%) | 11 | ||
| 3.1% | 5.1% | 2.4% | ||||
| Proximity of participants' homes to the reserve | Live in the Maasai Mara National Reserve | Count (% within location) | 15 (45.5%) | 9 (27.3%) | 9 (27.3%) | 33 |
| % within clusters | 9.4% | 9.1% | 22.0% | |||
| Not more than 10 km from the reserve | 39 (53.4%) | 25 (34.2%) | 9 (12.3%) | 73 | ||
| 24.5% | 25.3% | 22.0% | ||||
| Not more than 20 km from the reserve | 73 (57.5%) | 39 (30.7%) | 15 (11.8%) | 127 | ||
| 45.9% | 39.4% | 36.6% | ||||
| More than 20 km from the reserve | 32 (48.5%) | 26 (39.4%) | 8 (12.1%) | 66 | ||
| 20.1% | 26.3% | 19.5% | ||||
| Total per cluster | Count | 159 | 99 | 41 | 299 | |
| Clusters: attribute levels | Total per demographic | |||||
|---|---|---|---|---|---|---|
| Cluster 1 | Cluster 2 | Cluster 3 | ||||
| Gender | Male | Count (% within gender) | 84 (55.6%) | 48 (31.8%) | 19 (12.6%) | 151 |
| % within clusters | 52.8% | 48.5% | 46.3% | |||
| Female | 75 (50.7%) | 51 (34.5%) | 22 (14.9%) | 148 | ||
| 47.2% | 51.5% | 53.7% | ||||
| Age range | 18–24 | Count (% within age range) | 9 (33.3%) | 13 (48.1%) | 5 (18.5%) | 27 |
| % within clusters | 5.7% | 13.1% | 12.2% | |||
| 25–34 | 37 (58.7%) | 22 (34.9%) | 4 (6.3%) | 63 | ||
| 23.3% | 22.2% | 9.8% | ||||
| 35–44 | 38 (53.5%) | 25 (35.2%) | 8 (11.3%) | 71 | ||
| 23.9% | 25.3% | 19.5% | ||||
| 45–54 | 49 (62.8%) | 19 (24.4%) | 10 (12.8%) | 78 | ||
| 30.8% | 19.2% | 24.4% | ||||
| 55–64 | 14 (48.3%) | 10 (34.5%) | 5 (17.2%) | 29 | ||
| 8.8% | 10.1% | 12.2% | ||||
| 65–74 | 7 (58.3%) | 1 (8.3%) | 4 (33.3%) | 12 | ||
| 4.4% | 1.0% | 9.8% | ||||
| 75 and above | 5 (26.3%) | 9 (47.4%) | 5 (26.3%) | 19 | ||
| 3.1% | 9.1% | 12.2% | ||||
| Level of education | No formal education | Count (% within education) | 13 (48.1%) | 8 (29.6%) | 6 (22.2%) | 27 |
| % within clusters | 8.2% | 8.1% | 14.6% | |||
| Primary education | 13 (39.4%) | 10 (30.3%) | 10 (30.3%) | 33 | ||
| 8.2% | 10.1% | 24.4% | ||||
| Secondary education | 75 (59.1%) | 39 (30.7%) | 13 (10.2%) | 127 | ||
| 47.2% | 39.4% | 31.7% | ||||
| Higher education | 58 (51.8%) | 42 (37.5%) | 12 (10.7%) | 112 | ||
| 36.5% | 42.4% | 29.3% | ||||
| Occupation and employment status | Agriculture | Count (% within occupation) | 16 (57.1%) | 9 (32.1%) | 3 (10.7%) | 28 |
| % within clusters | 10.1% | 9.1% | 7.3% | |||
| Homemaker | 9 (50.0%) | 8 (44.4%) | 1 (5.6%) | 18 | ||
| 5.7% | 8.1% | 2.4% | ||||
| Teacher/educator | 16 (50.0%) | 12 (37.5%) | 4 (12.5) | 32 | ||
| 10.1% | 12.1% | 9.8% | ||||
| Manufacture | 5 (55.6%) | 4 (44.4%) | 0 (0.0%) | 9 | ||
| 3.1% | 4.0% | 0.0% | ||||
| Retail | 21 (55.3%) | 12 (31.6%) | 5 (13.2%) | 38 | ||
| 13.2% | 12.1% | 12.2% | ||||
| Tourism | 22 (68.8%) | 8 (25.0%) | 2 (6.3%) | 32 | ||
| 13.8% | 8.1% | 4.9% | ||||
| Military and other police services | 18 (62.1%) | 4 (13.8%) | 7 (24.1%) | 29 | ||
| 11.3% | 4.0% | 17.1% | ||||
| Health and social work | 11 (50.0%) | 8 (36.4%) | 3 (13.6%) | 22 | ||
| 6.9% | 8.1% | 7.3% | ||||
| Government and public administration | 16 (59.3%) | 7 (25.9%) | 4 (14.8%) | 27 | ||
| 10.1% | 7.1% | 9.8% | ||||
| Banking and legal services | 7 (58.3%) | 3 (25.0%) | 2 (16.7%) | 12 | ||
| 4.4% | 3.0% | 4.9% | ||||
| Transportation | 4 (28.6%) | 6 (42.9%) | 4 (28.6%) | 14 | ||
| 2.5% | 6.1% | 9.8% | ||||
| Student | 7 (41.2%) | 9 (52.9%) | 1 (5.9%) | 17 | ||
| 4.4% | 9.1% | 2.4% | ||||
| Retired or unemployed | 2 (20.0%) | 4 (40.0) | 4 (40.0%) | 10 | ||
| 1.3% | 4.0% | 9.8% | ||||
| Other | 5 (45.5%) | 5 (45.5%) | 1 (9.1%) | 11 | ||
| 3.1% | 5.1% | 2.4% | ||||
| Proximity of participants' homes to the reserve | Live in the Maasai Mara National Reserve | Count (% within location) | 15 (45.5%) | 9 (27.3%) | 9 (27.3%) | 33 |
| % within clusters | 9.4% | 9.1% | 22.0% | |||
| Not more than 10 km from the reserve | 39 (53.4%) | 25 (34.2%) | 9 (12.3%) | 73 | ||
| 24.5% | 25.3% | 22.0% | ||||
| Not more than 20 km from the reserve | 73 (57.5%) | 39 (30.7%) | 15 (11.8%) | 127 | ||
| 45.9% | 39.4% | 36.6% | ||||
| More than 20 km from the reserve | 32 (48.5%) | 26 (39.4%) | 8 (12.1%) | 66 | ||
| 20.1% | 26.3% | 19.5% | ||||
Notes:
Percentages and totals are based on respondents;
aDichotomy group tabulated at value 1