Research Article
A Network-Based Approach to Modeling and Predicting Product Coconsideration Relations
Table 3
Descriptive statistics of independent variables for 389 car models in 2013.
| | | Mean (SD) | Min | Max |
| | Vehicle attributes | | Import (binary) | 145 import & 244 domestic | | Price () | 17.61 (1.34) | 14.50 | 20.84 | | Power () | 7.27 (0.58) | 5.25 | 8.76 | | Fuel consumption (per 100 BHP) | 6.61 (1.62) | 2.99 | 18.56 | | Market segment (categorical) | 17 car segments | | Make origin (categorical) | 13 American, 22 American-Chinese, 98 Chinese, 90 European, 50 European-Chinese, 31 Japanese, 54 Japanese-Chinese, 11 Korean, 20 Korean-Chinese |
| | Vehicle attribute matching and difference | | | Market segment matching | 10.1% pairs of cars coconsidered are in the same segment | | Make origin matching | 16.5% pairs of cars coonsidered have the same make origin | | Price () difference | 1.53 (1.12) | 0 | 6.34 | | Power () difference | 0.66 (0.49) | 0 | 3.51 | | Fuel consumption difference | 1.71 (1.52) | 0 | 15.58 |
| | Customer association | | Distance of customers’ perceived characteristics | 0.20 (0.13) | 0 | 1 | | Distance of customers’ demographics | 0.27 (0.16) | 0 | 1 |
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