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Data Collection Instrument: Evaluating Methodological Differences in Discrete Choice Experiments

Published

Author(s)

Xiatian Iogansen, Ireland Crowther, Christina Gore, Joshua Kneifel, John Helveston

Abstract

This Data Collection Instrument (DCI) establishes a guideline and survey framework for quantifying consumer preferences and willingness-to-pay (WTP) for recycled plastic commodities. The instrument combines behavioral experience metrics, attitudinal scales, and a Discrete Choice Experiment (DCE). The DCE employs a multi-dimensional split-sample design that varies across three critical axes: (1) product context, contrasting low-cost discretionary items (phone cases) with high-cost functional goods (sneakers); (2) valuation methodology, comparing baseline attribute-based preferences against post-information valuations; and (3) the information framing, which provides respondents with external data showing either a significant decrease or increase in the energy required for production. By isolating the causal effect of sustainability disclosures through a within-subject "information shock" mechanism, this research captures the dynamic elasticity of green preferences. Beyond the immediate empirical findings, this DCI provides a reproducible methodological blueprint for researchers and practitioners, enhancing the reliability of stated preference studies for emerging circular economy technologies. Additionally, this DCI contains a series of questions aimed at validating that the data is from human subjects rather than from bots or large-language models.
Citation
Data Collection Instruments - 010
Report Number
010

Keywords

discrete choice experiment (DCE), conjoint analysis, recycled plastic, information treatment, willingness-to-pay (WTP), consumer preferences

Citation

Iogansen, X. , Crowther, I. , Gore, C. , Kneifel, J. and Helveston, J. (2026), Data Collection Instrument: Evaluating Methodological Differences in Discrete Choice Experiments, Data Collection Instruments, National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.DCI.010, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=962354 (Accessed July 16, 2026)
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Created July 15, 2026
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