Computational approaches to the network science of teams:
Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2020
|
| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 Volltext |
| Zusammenfassung: | Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 20 Nov 2020) Team performance characterization -- Team performance prediction -- Team performance optimization -- Team performance explanation -- Human agent teaming -- Conclusion and future work |
| Beschreibung: | 1 Online-Ressource (viii, 158 Seiten) |
| ISBN: | 9781108683173 |
| DOI: | 10.1017/9781108683173 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047075706 | ||
| 003 | DE-604 | ||
| 005 | 20231205 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 201229s2020 |||| o||u| ||||||eng d | ||
| 020 | |a 9781108683173 |c Online |9 978-1-108-68317-3 | ||
| 024 | 7 | |a 10.1017/9781108683173 |2 doi | |
| 035 | |a (ZDB-20-CBO)CR9781108683173 | ||
| 035 | |a (OCoLC)1229086450 | ||
| 035 | |a (DE-599)BVBBV047075706 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-92 | ||
| 082 | 0 | |a 658.4/022072 | |
| 100 | 1 | |a Li, Liangyue |d 1989- |0 (DE-588)1224238974 |4 aut | |
| 245 | 1 | 0 | |a Computational approaches to the network science of teams |c Liangyue Li, Hanghang Tong |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2020 | |
| 300 | |a 1 Online-Ressource (viii, 158 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Title from publisher's bibliographic system (viewed on 20 Nov 2020) | ||
| 500 | |a Team performance characterization -- Team performance prediction -- Team performance optimization -- Team performance explanation -- Human agent teaming -- Conclusion and future work | ||
| 520 | |a Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends | ||
| 650 | 4 | |a Teams in the workplace / Evaluation | |
| 650 | 4 | |a Performance / Measurement | |
| 650 | 4 | |a Business networks / Mathematical models | |
| 650 | 4 | |a Social sciences / Network analysis | |
| 650 | 4 | |a Network analysis (Planning) / Data processing | |
| 650 | 4 | |a Algorithms | |
| 700 | 1 | |a Tong, Hanghang |d ca. 20./21. Jh. |0 (DE-588)135615844 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-108-49854-8 |
| 856 | 4 | 0 | |u https://doi.org/10.1017/9781108683173 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-20-CBO | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032482669 | ||
| 966 | e | |u https://doi.org/10.1017/9781108683173 |l BSB01 |p ZDB-20-CBO |q BSB_PDA_CBO |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1017/9781108683173 |l FHN01 |p ZDB-20-CBO |q FHN_PDA_CBO_Kauf |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804182082126086144 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Li, Liangyue 1989- Tong, Hanghang ca. 20./21. Jh |
| author_GND | (DE-588)1224238974 (DE-588)135615844 |
| author_facet | Li, Liangyue 1989- Tong, Hanghang ca. 20./21. Jh |
| author_role | aut aut |
| author_sort | Li, Liangyue 1989- |
| author_variant | l l ll h t ht |
| building | Verbundindex |
| bvnumber | BV047075706 |
| collection | ZDB-20-CBO |
| ctrlnum | (ZDB-20-CBO)CR9781108683173 (OCoLC)1229086450 (DE-599)BVBBV047075706 |
| dewey-full | 658.4/022072 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.4/022072 |
| dewey-search | 658.4/022072 |
| dewey-sort | 3658.4 522072 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| doi_str_mv | 10.1017/9781108683173 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02838nmm a2200469zc 4500</leader><controlfield tag="001">BV047075706</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20231205 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">201229s2020 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781108683173</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-108-68317-3</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1017/9781108683173</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-20-CBO)CR9781108683173</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1229086450</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047075706</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">658.4/022072</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Li, Liangyue</subfield><subfield code="d">1989-</subfield><subfield code="0">(DE-588)1224238974</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Computational approaches to the network science of teams</subfield><subfield code="c">Liangyue Li, Hanghang Tong</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (viii, 158 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Title from publisher's bibliographic system (viewed on 20 Nov 2020)</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Team performance characterization -- Team performance prediction -- Team performance optimization -- Team performance explanation -- Human agent teaming -- Conclusion and future work</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Teams in the workplace / Evaluation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Performance / Measurement</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Business networks / Mathematical models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Social sciences / Network analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Network analysis (Planning) / Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Algorithms</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tong, Hanghang</subfield><subfield code="d">ca. 20./21. Jh.</subfield><subfield code="0">(DE-588)135615844</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-1-108-49854-8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1017/9781108683173</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CBO</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032482669</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108683173</subfield><subfield code="l">BSB01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">BSB_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108683173</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">FHN_PDA_CBO_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047075706 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:14:41Z |
| indexdate | 2024-07-10T09:01:53Z |
| institution | BVB |
| isbn | 9781108683173 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032482669 |
| oclc_num | 1229086450 |
| open_access_boolean | |
| owner | DE-12 DE-92 |
| owner_facet | DE-12 DE-92 |
| physical | 1 Online-Ressource (viii, 158 Seiten) |
| psigel | ZDB-20-CBO ZDB-20-CBO BSB_PDA_CBO ZDB-20-CBO FHN_PDA_CBO_Kauf |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Cambridge University Press |
| record_format | marc |
| spelling | Li, Liangyue 1989- (DE-588)1224238974 aut Computational approaches to the network science of teams Liangyue Li, Hanghang Tong Cambridge Cambridge University Press 2020 1 Online-Ressource (viii, 158 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 20 Nov 2020) Team performance characterization -- Team performance prediction -- Team performance optimization -- Team performance explanation -- Human agent teaming -- Conclusion and future work Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends Teams in the workplace / Evaluation Performance / Measurement Business networks / Mathematical models Social sciences / Network analysis Network analysis (Planning) / Data processing Algorithms Tong, Hanghang ca. 20./21. Jh. (DE-588)135615844 aut Erscheint auch als Druck-Ausgabe 978-1-108-49854-8 https://doi.org/10.1017/9781108683173 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Li, Liangyue 1989- Tong, Hanghang ca. 20./21. Jh Computational approaches to the network science of teams Teams in the workplace / Evaluation Performance / Measurement Business networks / Mathematical models Social sciences / Network analysis Network analysis (Planning) / Data processing Algorithms |
| title | Computational approaches to the network science of teams |
| title_auth | Computational approaches to the network science of teams |
| title_exact_search | Computational approaches to the network science of teams |
| title_exact_search_txtP | Computational approaches to the network science of teams |
| title_full | Computational approaches to the network science of teams Liangyue Li, Hanghang Tong |
| title_fullStr | Computational approaches to the network science of teams Liangyue Li, Hanghang Tong |
| title_full_unstemmed | Computational approaches to the network science of teams Liangyue Li, Hanghang Tong |
| title_short | Computational approaches to the network science of teams |
| title_sort | computational approaches to the network science of teams |
| topic | Teams in the workplace / Evaluation Performance / Measurement Business networks / Mathematical models Social sciences / Network analysis Network analysis (Planning) / Data processing Algorithms |
| topic_facet | Teams in the workplace / Evaluation Performance / Measurement Business networks / Mathematical models Social sciences / Network analysis Network analysis (Planning) / Data processing Algorithms |
| url | https://doi.org/10.1017/9781108683173 |
| work_keys_str_mv | AT liliangyue computationalapproachestothenetworkscienceofteams AT tonghanghang computationalapproachestothenetworkscienceofteams |