Does affective evaluation matter for the success of university-industry collaborations? A sentiment analysis of university-industry collaborative project reports
| Autor: | Ainurul Rosli, Muthu De Silva, Federica Rossi, Nick Yip |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Value (ethics)
affective evaluation 020209 energy media_common.quotation_subject 05 social sciences Sentiment analysis Applied psychology Context (language use) 02 engineering and technology perception Futures studies Negative relationship Management of Technology and Innovation Perception sentiment analysis 0502 economics and business 0202 electrical engineering electronic engineering information engineering ComputingMilieux_COMPUTERSANDEDUCATION Positive relationship university-industry collaborations (UICs) Business and International Management Psychology 050203 business & management Applied Psychology media_common |
| Popis: | University-industry collaborations (UICs) play a crucial role in the knowledge-based economy; however, past research has paid surprisingly little attention to the role played by the ‘subjective’ determinants of collaborations and their influence on ‘objective’ collaboration outcomes. By performing a sentiment analysis on a dataset of 415 final reports from completed UICs, we find that there is a negative relationship between the collaborators’ perceived challenges and benefits of UICs, mediated by negative affective evaluation. Instead, a positive affective evaluation of the UIC is positively correlated with its perceived benefits, which, in turn, are a predictor of an important objective outcome of UICs: the likelihood of future collaboration. A positive affective evaluation also negatively moderates the positive relationship between perceived challenges and negative affective evaluation. Therefore, a positive affective evaluation may increase the likelihood of future collaboration, even in a context in which a UIC is perceived to be challenging. Besides generating theoretical implications, our findings are of significant value for practitioners, as we highlight the need to regulate perception and affective evaluation to achieve successful UICs. We showcase sentiment analysis as a helpful foresight tool to identify those UICs that are more likely to continue over time. |
| Databáze: | OpenAIRE |
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