Dataset of 1,019 Coded Claims on Digital Product Passport Enablers and Barriers from 22 Sources

This repository contains the dataset supporting the research on Digital Product Passport (DPP) adoption based on a qualitative synthesis of grey literature. The dataset comprises 1,019 manually extracted and coded claims from 22 documents (screened from 85 documents corpus collected from six authoritative repositories), including European regulations, policy communications, technical reports, standards, methodology documents, surveys, and industry publications. The repository contains the following files: extracted_claims.csv – Complete dataset of 1,019 extracted claims and their qualitative coding. sources.csv – List of the source documents referenced throughout the dataset, including document identifier, title, publishing organization, and publication year. Each claim in extracted_claims.csv is uniquely identified and linked to its originating document via the document identifier. Each claim represents a distinct statement describing a factor that influences DPP implementation and is classified as either an enabler or a barrier. For each claim, the dataset includes: Unique claim identifier Claim text Classification as Enabler or Barrier Mapping to the Technology–Organization–Environment (TOE) framework Mapping to the Diffusion of Innovation (DOI) framework, where applicable Granularity level Source document and source location Coding confidence Brief contextual information Coding rationale Scope, sector, and thematic cluster The dataset was developed as part of doctoral research investigating organizational readiness for Digital Product Passports.