Temporal trajectories of enacted complexity in creative project teams

With technologies to capture fine-grained measures of behavior now more ubiquitous, organizational researchers are now able to consider networks of actions performed by multiple actors as a unit of analysis. We apply the action network construct as a measure of enacted complexity. Because previous c...

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Main Authors: GOH, Kenneth T., PENTLAND, Brian T.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/6217
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7216/viewcontent/AOM_big_data_submission.pdf
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spelling sg-smu-ink.lkcsb_research-72162019-07-18T07:33:28Z Temporal trajectories of enacted complexity in creative project teams GOH, Kenneth T. PENTLAND, Brian T. With technologies to capture fine-grained measures of behavior now more ubiquitous, organizational researchers are now able to consider networks of actions performed by multiple actors as a unit of analysis. We apply the action network construct as a measure of enacted complexity. Because previous conceptualizations of complexity viewed the construct as a descriptive organizational property, capturing this property over time was a non-issue. But given the emergent nature of enacted complexity, questions about how complexity unfolds over time become meaningful. This paper thus examines how enacted complexity unfolds over time by investigating the temporal trajectory of actors and actions. We present our findings from an analysis of 11,023 task sequences of four videogame development projects with qualitative data collected over two years. 2018-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/6217 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7216/viewcontent/AOM_big_data_submission.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Strategic Management Policy Technology and Innovation
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Strategic Management Policy
Technology and Innovation
spellingShingle Strategic Management Policy
Technology and Innovation
GOH, Kenneth T.
PENTLAND, Brian T.
Temporal trajectories of enacted complexity in creative project teams
description With technologies to capture fine-grained measures of behavior now more ubiquitous, organizational researchers are now able to consider networks of actions performed by multiple actors as a unit of analysis. We apply the action network construct as a measure of enacted complexity. Because previous conceptualizations of complexity viewed the construct as a descriptive organizational property, capturing this property over time was a non-issue. But given the emergent nature of enacted complexity, questions about how complexity unfolds over time become meaningful. This paper thus examines how enacted complexity unfolds over time by investigating the temporal trajectory of actors and actions. We present our findings from an analysis of 11,023 task sequences of four videogame development projects with qualitative data collected over two years.
format text
author GOH, Kenneth T.
PENTLAND, Brian T.
author_facet GOH, Kenneth T.
PENTLAND, Brian T.
author_sort GOH, Kenneth T.
title Temporal trajectories of enacted complexity in creative project teams
title_short Temporal trajectories of enacted complexity in creative project teams
title_full Temporal trajectories of enacted complexity in creative project teams
title_fullStr Temporal trajectories of enacted complexity in creative project teams
title_full_unstemmed Temporal trajectories of enacted complexity in creative project teams
title_sort temporal trajectories of enacted complexity in creative project teams
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/lkcsb_research/6217
https://ink.library.smu.edu.sg/context/lkcsb_research/article/7216/viewcontent/AOM_big_data_submission.pdf
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