Product Desirability Toolkit Listing: Results from a Systematic Mapping Study

This listing contains a total of 551 scholarly articles, published between 2002 and June 2026 that used the Product Desirability Toolkit (PDT) in some way. In the future, we plan to categorize the listing and provide a brief outline for each article along with a link. This listing serves as both a comprehensive repository of existing PDT work, and as a starting point for adding new PDT- related research to the list. Contact the first author to add a CSO GA to the next version of the list.

The listing was gathered using a methodical, comprehensive literature review using the Systematic Mapping Study (SMS) process to identify implemented and evaluated scholarly articles that used the PDT (in submission). Using traditional SMS approaches, our study was conducted May-June 2026 and searched for English literature published between 2002 and mid 2026, which made the use of the PDT, and found 550 scholarly works in total. Google Scholar noted 525 citations from the original Bendek and Miner 2002 source, but after pruning for missing author, year, title data, 458 works resulted. Scopus found 342 total scholarly papers/books from the citation after pruning, with 41 unique works there were not in the Google Scholar listing, and an additional 12 works that did not directly cite the original paper. ACM digital library and IEEE added 3 and 4 unique works, respectively. Using the PublishOrPerish tool, with a Google Scholar source, 23 additional works were discovered, and with Scopus as the source, 8 works, and with Semantic Scholar 1 additional source. Generative AI tools (GPT-5.5, Claude, Gemini, CoPilot) found 10, 10, 9,and 8 articles respectively, but no unique sources. When asked to go farther, the generative AI tools, instead suggested using “targeted Boolean search queries in databases like Scopus or via the PublishorPerish software" or they created hallucinations. The study found that the PDT has been used for evaluating user experiences in numerous and varied applications. The study found that in the SMS conducted on PDT usage, the AI tools were not effective and are not reliable substitutes for traditional SMS approaches but were helpful in outlining the SMS process.