FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4293180364> ?p ?o ?g. }

• W4293180364 endingPage "121940" @default.
• W4293180364 startingPage "121940" @default.
• W4293180364 abstract "Although technology valuation has benefited considerably from recent advances in machine learning technology, the results of prior studies in this field are of limited use in practice because they rely solely on black box models whose internal mechanisms are hidden. We develop an analytical framework for successful expert–machine collaborations for technology valuation using interpretable machine learning that makes a model's behaviors and predictions understandable to humans. First, a technological characteristics–economic value matrix is constructed using patent and technology transaction databases. Second, machine learning models are developed to examine the nonlinear and complex relationships between the technological characteristics and economic value of technologies. Third, the performance of the machine learning models is assessed using quantitative metrics. Finally, the SHapley Additive exPlanation method is applied to the best-performing model to explain which technological characteristics influence the economic value of technologies. By these means, we investigate the importance of the features of technological characteristics (and their interactions) in technology valuation and offer theoretical and practical implications of the analysis results. A case study of the technologies registered in the Office of Technology Licensing at Stanford University confirms that our framework is a useful complementary tool for technology valuation." @default.
• W4293180364 created "2022-08-27" @default.
• W4293180364 creator A5003589806 @default.
• W4293180364 creator A5026787267 @default.
• W4293180364 creator A5043610240 @default.
• W4293180364 creator A5057728036 @default.
• W4293180364 date "2022-10-01" @default.
• W4293180364 modified "2023-09-30" @default.
• W4293180364 title "Towards expert–machine collaborations for technology valuation: An interpretable machine learning approach" @default.
• W4293180364 cites W1486016201 @default.
• W4293180364 cites W1502925692 @default.
• W4293180364 cites W1908915203 @default.
• W4293180364 cites W1954679496 @default.
• W4293180364 cites W1974366314 @default.
• W4293180364 cites W1976395435 @default.
• W4293180364 cites W1990948347 @default.
• W4293180364 cites W2008443823 @default.
• W4293180364 cites W2038322387 @default.
• W4293180364 cites W2040543671 @default.
• W4293180364 cites W2047766693 @default.
• W4293180364 cites W2049788844 @default.
• W4293180364 cites W2056909456 @default.
• W4293180364 cites W2065429153 @default.
• W4293180364 cites W2069725931 @default.
• W4293180364 cites W2073201008 @default.
• W4293180364 cites W2084110222 @default.
• W4293180364 cites W2098758051 @default.
• W4293180364 cites W2123402141 @default.
• W4293180364 cites W2141975087 @default.
• W4293180364 cites W2150593711 @default.
• W4293180364 cites W2157975090 @default.
• W4293180364 cites W2296251859 @default.
• W4293180364 cites W2602721037 @default.
• W4293180364 cites W2620871291 @default.
• W4293180364 cites W2768852601 @default.
• W4293180364 cites W2796755741 @default.
• W4293180364 cites W2894420444 @default.
• W4293180364 cites W2907453732 @default.
• W4293180364 cites W2935942167 @default.
• W4293180364 cites W2963095307 @default.
• W4293180364 cites W2974666380 @default.
• W4293180364 cites W2996061341 @default.
• W4293180364 cites W2999615587 @default.
• W4293180364 cites W3025723572 @default.
• W4293180364 cites W3035862677 @default.
• W4293180364 cites W3088599610 @default.
• W4293180364 cites W3122119023 @default.
• W4293180364 cites W3122666126 @default.
• W4293180364 cites W3124002336 @default.
• W4293180364 cites W3126145075 @default.
• W4293180364 cites W3127948630 @default.
• W4293180364 cites W3205939075 @default.
• W4293180364 cites W4200580215 @default.
• W4293180364 cites W4239510810 @default.
• W4293180364 doi "https://doi.org/10.1016/j.techfore.2022.121940" @default.
• W4293180364 hasPublicationYear "2022" @default.
• W4293180364 type Work @default.
• W4293180364 citedByCount "6" @default.
• W4293180364 countsByYear W42931803642022 @default.
• W4293180364 countsByYear W42931803642023 @default.
• W4293180364 crossrefType "journal-article" @default.
• W4293180364 hasAuthorship W4293180364A5003589806 @default.
• W4293180364 hasAuthorship W4293180364A5026787267 @default.
• W4293180364 hasAuthorship W4293180364A5043610240 @default.
• W4293180364 hasAuthorship W4293180364A5057728036 @default.
• W4293180364 hasConcept C10138342 @default.
• W4293180364 hasConcept C119857082 @default.
• W4293180364 hasConcept C127413603 @default.
• W4293180364 hasConcept C13736549 @default.
• W4293180364 hasConcept C154945302 @default.
• W4293180364 hasConcept C162324750 @default.
• W4293180364 hasConcept C186027771 @default.
• W4293180364 hasConcept C202444582 @default.
• W4293180364 hasConcept C2522767166 @default.
• W4293180364 hasConcept C33923547 @default.
• W4293180364 hasConcept C41008148 @default.
• W4293180364 hasConcept C75949130 @default.
• W4293180364 hasConcept C77088390 @default.
• W4293180364 hasConcept C9652623 @default.
• W4293180364 hasConceptScore W4293180364C10138342 @default.
• W4293180364 hasConceptScore W4293180364C119857082 @default.
• W4293180364 hasConceptScore W4293180364C127413603 @default.
• W4293180364 hasConceptScore W4293180364C13736549 @default.
• W4293180364 hasConceptScore W4293180364C154945302 @default.
• W4293180364 hasConceptScore W4293180364C162324750 @default.
• W4293180364 hasConceptScore W4293180364C186027771 @default.
• W4293180364 hasConceptScore W4293180364C202444582 @default.
• W4293180364 hasConceptScore W4293180364C2522767166 @default.
• W4293180364 hasConceptScore W4293180364C33923547 @default.
• W4293180364 hasConceptScore W4293180364C41008148 @default.
• W4293180364 hasConceptScore W4293180364C75949130 @default.
• W4293180364 hasConceptScore W4293180364C77088390 @default.
• W4293180364 hasConceptScore W4293180364C9652623 @default.
• W4293180364 hasFunder F4320321408 @default.
• W4293180364 hasFunder F4320322120 @default.
• W4293180364 hasLocation W42931803641 @default.
• W4293180364 hasOpenAccess W4293180364 @default.
• W4293180364 hasPrimaryLocation W42931803641 @default.

• next