Online video channel management: An integrative decision support system framework |
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| Affiliation: | 1. College of Business, Mississippi State University, 114 McCool Hall, 40 Old Main, P.O. Box 5288, MS 39762, USA;2. College of Business, Texas A&M University – Commerce, 2008 University Dr, Commerce, TX 75428, USA;3. College of Business, University of Texas at Arlington, 701 S W St, Arlington, TX 76010, USA;4. Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee, P. O. Box 742, Milwaukee, WI 53201-0742, USA;1. University at Albany (SUNY), 399A School of Business, Albany, NY, 12222, USA;2. University of Tennessee at Knoxville, School of Information Sciences, 444 Communications Building, Knoxville, TN, USA;3. Development Management Institute, 5th Floor, Gandhi Maidan, Patna, Bihar, India;1. Wright State University, 3640 Colonel Glenn Highway, Dayton, OH, 45435, USA;2. Department of Information Technology and Operations Management, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798;1. Universitat Politècnica de València, Spain;2. University of Valencia, Spain;3. ESIC Business & Marketing School, Spain;1. School of Management, National Institute of Technology Rourkela, Rourkela, 769008, India;2. Human Resource Management, School of Management, National Institute of Technology Rourkela, Rourkela, 769008, India;1. Department of Business Information & Analytics, Daniels College of Business, University of Denver, 2101 S. University Blvd, Denver, CO, USA;2. Department of Computer Information Systems, J. Mack Robinson College of Business, Georgia State University, 35 Broad Street, Atlanta, GA, USA |
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| Abstract: | In the current fragmented media landscape, online video is becoming an important outlet for content dissemination. Online video channels provide content creators a way of organizing content and building an online following through subscriptions and social sharing. This paper describes a decision support systems (DSS) based framework for online video channel management and content creation. The relevant DSS literature was reviewed along with both modeling and behavioral aspects of online videos and video channels. An empirical case study was run on a dataset consisting of views, shares, and subscriptions from over 1000 videos from nine YouTube channels. This paper contributes to DSS theory by proposing a flexible framework for incorporating both behavioral and empirical work into an integrative process for online video content creation. This framework builds on existing data-driven DSS theory, but includes specific entities and processes for online content creation. |
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| Keywords: | Social media Viral videos Forecasting Decision support |
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