Active and Passive Safety Systems in the U.S. - Customer Desirability and Willingness to Pay
Active and Passive Safety Systems in the U.S. - Customer Desirability and Willingness to Pay
RELEASE DATE
28-Sep-2005
28-Sep-2005
REGION
North America
North America
Research Code: F384-01-00-00-00
SKU: AU00508-EU-MR_09108
$20,000.00
Special Price $15,000.00 save 25 %
In stock
SKU
AU00508-EU-MR_09108
Description
The central goal of this study is to identify the core sets of safety features that consumers desire, as well as their willingness to pay. Multiple analytic methods were triangulated to ensure robust results. Central to this is a pioneering market modeling approach using Adaptive Conjoint Analysis (ACA) data. Purchase intent questions were asked outside of the conjoint exercise to calibrate the market model, as well as to identify purchase interactions using cluster analysis. A proprietary Shapley Value decomposition technique was then used on the conjoint data to derive the willingness to pay, and the marginal value of a safety feature in a successful package of features.
Table of Contents
Introduction
- Overview
- Methodology
- Driver Context
Executive Summary
- Executive Summary
Detailed Findings
- Customer Perception
- Customer Preferences
- Purchase Preferences
- Purchase Package
Conclusions
- Conclusions
Consumer Choice Awards
- Brand Offering Best Overall Automotive Safety
- Brand Offering Technology Leadership in Automotive Safety
- Volume Brand Offering Best Overall Automotive Safety
- Volume Brand First-to-Market Leadership in Safety Systems
Definitions
Analytical Methodologies
Related Research
Popular Topics
The central goal of this study is to identify the core sets of safety features that consumers desire, as well as their willingness to pay. Multiple analytic methods were triangulated to ensure robust results. Central to this is a pioneering market modeling approach using Adaptive Conjoint Analysis (ACA) data. Purchase intent questions were asked outside of the conjoint exercise to calibrate the market model, as well as to identify purchase interactions using cluster analysis. A proprietary Shapley Value decomposition technique was then used on the conjoint data to derive the willingness to pay, and the marginal value of a safety feature in a successful package of features.
No Index | Yes |
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Podcast | No |
Industries | Automotive |
WIP Number | F384-01-00-00-00 |
Is Prebook | No |