Technological distance measures: new perspectives on nearby and far away

Simon, H; Sick, N

Technological distance measures: new perspectives on nearby and far away

Simon, H Sick, N

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Publisher:: Springer Science and Business Media LLC
Publication Type:: Journal Article
Citation:: Scientometrics, 2016, 107, (3), pp. 1299-1320
Issue Date:: 2016-06-01

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Field	Value	Language
dc.contributor.author	Simon, H
dc.contributor.author	Sick, N https://orcid.org/0000-0002-0713-6918
dc.date.accessioned	2022-07-13T05:36:57Z
dc.date.available	2022-07-13T05:36:57Z
dc.date.issued	2016-06-01
dc.identifier.citation	Scientometrics, 2016, 107, (3), pp. 1299-1320
dc.identifier.issn	0138-9130
dc.identifier.issn	1588-2861
dc.identifier.uri	http://hdl.handle.net/10453/158851
dc.description.abstract	Understanding the competitive environment of one’s company is crucial for every manager. One tool to quantify the technological relationships between companies, evaluate industry landscapes and knowledge transfer potential in collaborations is the technological distance. There are different methods and many different factors that impact the results and thus the conclusions that are drawn from distance calculation. Therefore, the present study derives guidelines for calculating and evaluating technological distances for three common methods, i.e. the Euclidean distance, the cosine angle and the min-complement distance. For this purpose, we identify factors that influence the results of technological distance calculation using simulation. Subsequently, we analyze technological distances of cross-industry collaborations in the field of electric mobility. Our findings show that a high level of detail is necessary to achieve insightful results. If the topic in scope of the analysis does not represent the core business of the companies, we recommend filters to focus on the respective topic. Another key suggestion is to compare the calculated results to a peer group in order to evaluate if a distance can be evaluated as ‘near’ or ‘far’.
dc.language	en
dc.publisher	Springer Science and Business Media LLC
dc.relation.ispartof	Scientometrics
dc.relation.isbasedon	10.1007/s11192-016-1888-3
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0807 Library and Information Studies, 1605 Policy and Administration
dc.subject.classification	Science Studies
dc.title	Technological distance measures: new perspectives on nearby and far away
dc.type	Journal Article
utslib.citation.volume	107
utslib.for	0807 Library and Information Studies
utslib.for	1605 Policy and Administration
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-13T05:36:56Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	107
utslib.citation.issue	3

Abstract:

Understanding the competitive environment of one’s company is crucial for every manager. One tool to quantify the technological relationships between companies, evaluate industry landscapes and knowledge transfer potential in collaborations is the technological distance. There are different methods and many different factors that impact the results and thus the conclusions that are drawn from distance calculation. Therefore, the present study derives guidelines for calculating and evaluating technological distances for three common methods, i.e. the Euclidean distance, the cosine angle and the min-complement distance. For this purpose, we identify factors that influence the results of technological distance calculation using simulation. Subsequently, we analyze technological distances of cross-industry collaborations in the field of electric mobility. Our findings show that a high level of detail is necessary to achieve insightful results. If the topic in scope of the analysis does not represent the core business of the companies, we recommend filters to focus on the respective topic. Another key suggestion is to compare the calculated results to a peer group in order to evaluate if a distance can be evaluated as ‘near’ or ‘far’.

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http://hdl.handle.net/10453/158851