Predictors of web analytics use in commercial and non-profit radio stations

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Date
2017
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Publisher
University of Alabama Libraries
Abstract

This study examines the work habits and news products produced by commercial and non-profit radio news operations at the local, or affiliate, level. Specifically, the focus is on the perception and utilization of internet audience data that measures stories on a radio station’s website. A survey of 332 commercial and non-profit radio newsroom decision-makers discovered how they feel about web audience data and how they act on it. A statistical analysis, informed by a theoretical background including Institutionalism and Resource Dependence Theory was conducted for this study. The predictor variables were the degree of perceived uncertainty, whether the respondent works in a for-profit or non-profit operation, the length of time the participant has worked in journalism, the tendency to search for information in the environment, and the tendency toward mimicry. The dependent variable was degree of use of web analytics. The findings indicate a positive relationship for both mimicry and information search with the primary dependent variable, use of web analytics data in newsroom decision making. Also, respondents with greater experience levels are marginally less receptive to relying on internet audience data for information search and less likely to mimic the practice of using web analytics. The statistical results did not support hypotheses that predicted effects from perceived uncertainty. While statistical support between perceived uncertainty and the use of web data was not found, a reverse relationship in one hypothesis suggests that use of internet audience data may reduce uncertainty rather than increase it.

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Electronic Thesis or Dissertation
Keywords
Journalism
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