Broadcasters’ content distribution and programming decisions in multi-channel environments: a literature review

ABSTRACT

Despite the increasing digitisation, traditional media remains relevant. However, the importance of non-linear media is steadily growing. Thus, media companies face the challenge to target fragmented audiences by distributing content across different channels. By systematically reviewing existing research, this article identifies relevant determinants influencing broadcasters’ programming and content distribution decisions. In total, 103 articles were identified and reviewed. Based on underlying factors derived from programming and content distribution theories significant and important factors were extracted from the articles. The review (at hand) shows: decisions of broadcasting companies to distribute their content via multiple channels are influenced by many different factors. From a research perspective, the most relevant factors are the consumer demand, the revenue, the competitive environment and the attraction of an increasingly fragmented audience.

KEYWORDS:

• Media
• broadcasting
• multi-channel
• programme decision-making
• content distribution

Disclosure statement

No potential conflict of interest was reported by the author.

Supplementary material

Supplemental data for this article can be accessed here.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. For further information, see Hotelling (1929). Hotelling suggested that more concentration would lead to minimal differentiation (of locations), while in a more recent approach by d’Aspremont et al. (1979) with different assumptions (e.g., regarding preferences), maximal differentiation is suggested.

2. Gal-Or and Dukes (2003) described a similar model of media decisions regarding programming variety with a focus on the advertising market (Gal-Or & Dukes, 2003, p. 293).

3. The complete list of included articles can be accessed in the supplemental material.

4. The data extraction template provides the basis for step III, since this table is used to record the reviewed articles in rows and the general information for each article as well as all extracted factors in columns (Tranfield et al., 2003, p. 218).

Additional information

Notes on contributors

Verena Telkmann

Verena Telkmann is a research assistant in the field of production structures for digital media and a Ph.D. candidate at TH Köln – University of Applied Sciences, Cologne. In research she focuses on digital media production and media economics. She completed her bachelor’s degree in business administration with a focus on marketing in 2014 at the institute for dual study programmes at the university of applied sciences Osnabrück and her master’s degree in communication, multimedia and market management in the year 2017 at the university of applied sciences Dusseldorf. She gained practical experience in online marketing of CHECK24 Mobilfunk GmbH.