ArticlePloS one2023
What drives researcher preferences for chemical compounds? Evidence from conjoint analysis.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigated the attributes and attribute levels that affect researcher preferences for chemical compounds. We conducted a conjoint analysis on survey data of Korean researchers using chemical compounds from the Korean Chemical Bank (KCB). The analysis estimated the part-worth utility for each attribute's level, calculated relative importance of attributes, and classified user segmentation with different patterns. The results show that the structure database offers the highest part-worth utility to researchers, followed by high new functionality, price, screening service, and drug action data provided only by the KCB. Notably, researchers view the offer of a structured database and high new functionality as more important than other attributes in decision-making about research and development of chemical compounds. Furthermore, the results of segmentation analysis demonstrated that researchers have distinct usage patterns of chemical compounds: researchers consider structure database and high new functionality in cluster 1; and high new functionality and price in cluster 2, to be the most appealing. We discussed some policy and strategic implications based on the findings of this study and proposed some limitations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.