Measuring user acceptance of and willingness-to-pay for CVI technology : final research report.

Shin, Hyeon-Shic; Callow, Michael; Farkas, Z. Andrew; Lee, Young-Jae; Dadvar, Seyedehsan · 2016 · ROSA P / Connected Vehicle/Infrastructure University Transportation Center

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Summary

This research report addresses the critical need for effective deployment strategies for Connected Vehicle/Infrastructure (CVI) technology, motivated by the significant safety benefits CVs offer—estimated to reduce non-impaired driver crashes by 80 percent. Despite these benefits, widespread adoption is hindered by a lack of clear deployment roadmaps, overly optimistic penetration estimates, and a methodological void in understanding user acceptance. Previous studies relied on direct questioning regarding willingness-to-pay (WTP), which fails to capture the complex trade-offs consumers make during purchasing decisions. Consequently, this study aimed to accurately estimate drivers’ acceptance of and WTP for CV technologies by simulating real-world purchasing behaviors, identifying early adopters, and deriving policy implications based on socioeconomic characteristics. To achieve these objectives, the researchers employed an Adaptive Choice-Based Conjoint (ACBC) analysis, a robust market simulation method that forces participants to make trade-offs between various CV features and prices within a budget constraint. This approach was selected over direct stated preference surveys to minimize social desirability bias and better reflect actual consumer behavior. The study also utilized Structural Equation Modeling (SEM) to examine the relationships between personal characteristics, innate innovativeness, and adoption behavior. Data were compiled from a survey of participants who evaluated specific CV attributes, such as collision warning packages, through choice tournaments and "build-your-own" vehicle tasks. The analysis focused on determining the relative importance of attributes, estimating utility scores, and calculating WTP stratified by demographic variables including age, gender, race, education, and income. The findings reveal that "collision warning packages" received the highest acceptance among safety features. WTP was positively correlated with specific demographic groups: drivers aged 40–49, African-Americans, individuals with less than a bachelor’s degree, and those with higher vehicle purchase budgets. While women expressed greater concern for safety than men across all ages, they reported significantly less prior knowledge of CVs and had lower vehicle purchase budgets. Although no statistical difference in WTP was found between genders, women aged 50 and older appeared less interested in CV technologies. The SEM results further highlighted that personal characteristics and innovativeness significantly influence adoption behavior, confirming that early adopters are distinct from the general population in their risk tolerance and financial capacity. The significance of this study lies in its provision of empirically grounded data to guide CVI deployment strategies, replacing speculative timelines with evidence-based insights. The results suggest that government agencies should tailor marketing efforts to highlight safety benefits, specifically targeting mature women through media and family-oriented public events to address knowledge gaps and interest levels. By identifying the specific socioeconomic profiles of early adopters, the research offers a framework for policymakers to accelerate market penetration, thereby realizing the substantial safety and economic benefits of connected vehicle technology. This methodological shift from direct questioning to conjoint analysis sets a precedent for more accurate consumer behavior modeling in transportation technology adoption.

Key finding

Collision warning packages achieved the highest acceptance among connected vehicle safety features, with willingness-to-pay positively correlated with being aged 40-49, African-American, having less than a bachelor's degree, or possessing a higher vehicle purchase budget.

Methodology

survey

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• acceptance adoption

Information type

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• Empirical Findings: observational prevalence, self report data
• Methodological Resource: validation psychometrics