Measuring Performance of Broadcast Media on Social Networks Using Data Envelopment Analysis Models

Haghighinia, Hanieh; Rostamy-Malkhalifeh, Mohsen; Soltanifar, Mohamad

doi:10.22054/nms.2021.47296.844

Document Type : Research Paper

Authors

¹ Department of Management of Cultural and Media Affairs, Faculty of Management and Economics (FME), Science and Research Branch, Islamic Azad University, Tehran, Iran

² Associate Professor, Department of Mathematics, Faculty of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

³ Associate professor, Department of Social Communication Sciences, Faculty of Literature, Humanities, and Social Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran

https://doi.org/10.22054/nms.2021.47296.844

Abstract

Over the last two decades, the media landscape in the world has changed due to use of the internet and mainly the development of online social networks (OSNs) and has dramatically affected the media production, distribution, and consumption. Hence, media planners should carefully identify appropriate measures in the decision making process. The first step to change the processes is the information obtained through performance measurement.
In this article, the performance of broadcast media has measured on Instagram and Soroush using CCR and BCC models in data envelopment analysis (DEA). Results has measured in the form of input and output-oriented, which called company activity level and audience response level. Then, the results of two models has compared. In fact, the performance of each unit in the optimal use of resources (inputs) to produce outputs (outputs) has evaluated. In this research, the statistical population is Radio and TV channels and these organizations considered as decision-making units (DMUs).
Results show that a number of units has identified as efficient on both company activity and audience response level implementing CCR and BCC models. As well, some others have identified as efficient implementing BCC model. Then, the efficient units have been ranked using super-efficiency analysis. Finally, some inefficient DMUs has identified on each OSN individually and an appropriate strategy has introduced in order to improve the performance of inefficient units. This pattern will help media managers in order to identify inefficiency factors in compare of competitors and will become to an efficient DMU.

Keywords

20.1001.1.25382209.1400.7.28.9.4

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