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Markov Modeling and Analysis of Team Communication.

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Title: Markov Modeling and Analysis of Team Communication.
Authors: Martinez Ayala, Diego Fernando1 (AUTHOR) diego.f.martinez@uconn.edu, Balasingam, Balakumar1 (AUTHOR) bala@engr.uconn.edu, McComb, Sara2 (AUTHOR) sara@purdue.edu, Pattipati, Krishna R.1 (AUTHOR) krishna.pattipati@uconn.edu
Source: IEEE Transactions on Systems, Man & Cybernetics. Systems. Apr2020, Vol. 50 Issue 4, p1230-1241. 12p.
Subjects: Markov processes, Working hours, Teams, Information storage & retrieval systems, Communication planning, Tardiness
Abstract: This paper presents a predictive data analytics process for examining the relationship between team communication and performance in planning tasks. Team performance is measured in terms of the time each team spends in completing the planning task and the cost of the concomitant work schedule. The predictive data analytics process encompasses three data abstraction techniques for data preparation, three probabilistic models that represent the temporal features of data abstracted from team communication interactions, and a validation process that selects the best pair of data abstraction and model for subsequent insight analysis. Experimental data obtained from 32 teams of three members each, tasked to solve a personnel scheduling problem, is used for validating the proposed methodology. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Systems, Man & Cybernetics. Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: Markov Modeling and Analysis of Team Communication.
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  Data: <searchLink fieldCode="AR" term="%22Martinez+Ayala%2C+Diego+Fernando%22">Martinez Ayala, Diego Fernando</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> diego.f.martinez@uconn.edu</i><br /><searchLink fieldCode="AR" term="%22Balasingam%2C+Balakumar%22">Balasingam, Balakumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> bala@engr.uconn.edu</i><br /><searchLink fieldCode="AR" term="%22McComb%2C+Sara%22">McComb, Sara</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> sara@purdue.edu</i><br /><searchLink fieldCode="AR" term="%22Pattipati%2C+Krishna+R%2E%22">Pattipati, Krishna R.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> krishna.pattipati@uconn.edu</i>
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  Data: <searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br /><searchLink fieldCode="DE" term="%22Working+hours%22">Working hours</searchLink><br /><searchLink fieldCode="DE" term="%22Teams%22">Teams</searchLink><br /><searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems%22">Information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+planning%22">Communication planning</searchLink><br /><searchLink fieldCode="DE" term="%22Tardiness%22">Tardiness</searchLink>
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  Label: Abstract
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  Data: This paper presents a predictive data analytics process for examining the relationship between team communication and performance in planning tasks. Team performance is measured in terms of the time each team spends in completing the planning task and the cost of the concomitant work schedule. The predictive data analytics process encompasses three data abstraction techniques for data preparation, three probabilistic models that represent the temporal features of data abstracted from team communication interactions, and a validation process that selects the best pair of data abstraction and model for subsequent insight analysis. Experimental data obtained from 32 teams of three members each, tasked to solve a personnel scheduling problem, is used for validating the proposed methodology. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Systems, Man & Cybernetics. Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1109/TSMC.2017.2748985
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      – Code: eng
        Text: English
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        PageCount: 12
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    Subjects:
      – SubjectFull: Markov processes
        Type: general
      – SubjectFull: Working hours
        Type: general
      – SubjectFull: Teams
        Type: general
      – SubjectFull: Information storage & retrieval systems
        Type: general
      – SubjectFull: Communication planning
        Type: general
      – SubjectFull: Tardiness
        Type: general
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      – TitleFull: Markov Modeling and Analysis of Team Communication.
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            NameFull: Balasingam, Balakumar
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            NameFull: McComb, Sara
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            NameFull: Pattipati, Krishna R.
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              Text: Apr2020
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              Y: 2020
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