Microfoundations of collaborative networks: The impact of social capital formation and learning on investment risk assessment

dc.contributor.authorRodgers Waymond
dc.contributor.authorDegbey William Y.
dc.contributor.authorHousel Thomas J.
dc.contributor.authorArslan Ahmad
dc.contributor.organizationfi=kansainvälinen liiketoiminta|en=International Business|
dc.contributor.organization-code1.2.246.10.2458963.20.72646005131
dc.converis.publication-id48944672
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/48944672
dc.date.accessioned2022-10-28T13:44:28Z
dc.date.available2022-10-28T13:44:28Z
dc.description.abstract<p>Both traditional financial and intangible asset (IA) performance measures aid in the design of micromanagement organizational systems. We shed light on the microfoundational processes of collaborative networks and their impact on investment risk assessment by exploring IA performance measures in response to decomposing macro-level constructs. The IA measures focus on the exploration of individual human capital and their actions and interactions that influence investment risk assessments, which is critical for long-term prosperity. Additionally, human capital herein includes social factors such as social capital, which research has demonstrated can be developed from intellectual capital, and vice versa. Findings from an experiment with 40 professional investors (resulting in 160 independent observations) suggested that belonging to a company’s collaborative networks—where they would gain access to IA performance information—led them to adjust their investment risk assessments downward or upward in response to material weakness or strength disclosures pertaining to IA performance. Additionally, a laboratory experiment revealed that 121 novice investors who learned how to interpret and use their social networks to gain access to IA performance information also led them to adjust their investment risk assessments in response to material IA information deficiencies in target companies. The results showed IA knowledge can be learned and transferred to impact social change.<br></p>
dc.identifier.eissn1873-5509
dc.identifier.jour-issn0040-1625
dc.identifier.olddbid184008
dc.identifier.oldhandle10024/167102
dc.identifier.urihttps://www.utupub.fi/handle/11111/41468
dc.identifier.urlhttps://doi.org/10.1016/j.techfore.2020.120295
dc.identifier.urnURN:NBN:fi-fe2021042823268
dc.language.isoen
dc.okm.affiliatedauthorDegbey, William
dc.okm.discipline512 Business and managementen_GB
dc.okm.discipline512 Liiketaloustiedefi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherElsevier
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.articlenumber120295
dc.relation.doi10.1016/j.techfore.2020.120295
dc.relation.ispartofjournalTechnological Forecasting and Social Change
dc.relation.volume161
dc.source.identifierhttps://www.utupub.fi/handle/10024/167102
dc.titleMicrofoundations of collaborative networks: The impact of social capital formation and learning on investment risk assessment
dc.year.issued2020

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