What is Media Richness Theory?

Media richness theory is a theory of media communication that compares media based on how ‘richly’ they communicate. It emerged from literature on workplace organizational information processing.

A medium with ‘rich’ communication has:

  • Multiple means of communicating the one message
  • The ability to convey equivocality (nuance, details and minutiae) to receivers of the message

A medium with ‘lean’ communication has:

  • Limited means of communicating a message
  • The ability to convey certainty (blunt, direct messages with little nuance) to receivers of the message.

Rich media are great for conveying messages to a single person who you want to provide personal support to. They’re also great for explaining, discussing and debating complex concepts.

Rich media are not necessarily the best. Sometimes, you’ll want to use lean media if you want to make a short, quick and blunt point. Lean media is also often better for communicating to large audiences.

1. Definition of Media Richness Theory

Media Richness Theory is defined as a theory that explores how forms of media are fit for different communication purposes. It argues that media that are ‘rich’ are best for resolving equivocal issues with high complexity, while ‘lean’ media are best for communicating simple, certain and unequivocal messages.

2. How to measure the ‘Richness’ of a Form of Media

The degree of richness of a medium is dependent upon four factors:

  1. Immediacy of feedback (synchronous interactional media is richer than asynchronous non-interactional media),
  2. Cues (the more cues such as sight, sound and touch the richer the media),
  3. Language variety (the greater variety of words, signs and symbols the richer the media), and
  4. Personal focus (the greater humanisation through warmth and sensitivity, and personalisation through differentiation for the receiver, the richer the media).

3. Examples of Rich Media

Here are some examples of rich media. The top of the list is the richest and the bottom of the list is still rich, but less so, because some elements of the above four criteria may be missing:

  • Face-to-face discussion between two people in person (Daft and Lengel (1986) consider face-to-face communication to be the richest form of media)
  • A Skype chat or video call
  • A mentorship meeting
  • University seminars (losing personal focus as the seminar group gets larger)
  • Long-form documentaries (missing synchronicity and personalization but retaining language variety and cues))

4. Examples of Lean Media

Here are some examples of lean media. The top of the list is the leanest media and the bottom is still lean, but gaining some levels of complexity (based on the four criteria points above):

  • Numeric reports (Daft and Lengel (1986) consider numeric reports to be the leanest form of media)
  • Morse code
  • Emergency radio broadcasts
  • One-off text messages and memos
  • Bulk emails sent to all employees from a CEO
  • University lectures (lacking immediacy of feedback or personalization but gaining language variety)

5. Task Relevancy: Is Rich Media better than Lean Media?

While we might think that the richer the media the better, this is not necessarily true. If you want to link appropriate media to specific tasks based on task complexity.

Daft and Lengel (1986) propose that communications media should do one of two things:

  1. Reduce uncertainty (provide certainty), or
  2. resolve equivocality.

Media richness theory attempts to identify how well a media can conduct one of these two tasks.

a) Providing certainty

Sometimes we want to communicate in a way that resolves any uncertainty. We want to say: “This is the truth”, “This is the right way to do things”, or “This is exactly what I want right now”.

When we want to communicate like this, we want to resolve uncertainty.

The ‘scholarly’ definition: Uncertainty is defined by Daft and Lengel (1986) as the gap between knowledge attained and knowledge required for an answer. Uncertainty therefore signifies a need for additional information to resolve a problem.

Sometime we need Lean Media: For problems with a clear and direct answer, we want lean media that get to the point without any additional details that might complicate things.

Information lean media have minimal distractions which enable straightforward and unambiguous information communication.

This might be the case when outlining set-in-stone rules in a memo to all employees, for example.

b) Resolving Equivocality

Sometimes we’re discussing something that doesn’t really have a clear answer. For example, when talking about climate change or the meaning of life, we’re dealing with very complicated subject matter! To reach conclusions, there needs to be a long and complicated discussion.

When we’re discussing something that is very complex, we can say that the topic contains a lot of equivocality.

The ‘scholarly’ definition: Equivocality is defined as the difficulty experienced while working through problems that are so complex or subjective that there are no clear solutions.

Sometimes we need Rich Media: For equivocal problems, we want rich media that add context to a situation (Dennis & Robert, 2005). This will help us arrive at deeper knowledge or understanding of a problem, which can then lead to nuanced and well-informed decision making.

Remember, rich media provide: (1) Immediate feedback, (2) variety of cues for conveying messages, (3) variety of language for conveying messages, and (4) personalization of interaction. All four of these features enable complexity, nuance and context to be conveyed to receivers of a message.

This explains why face-to-face communication, through which a learner can receive facial expressions, clarifications and deep discussion, is considered the most information rich media form.

6. Comparison of Media on a Rich-Lean, Certainty-Equivocality Matrix

This comparison is only a working model, but gives you some groundwork for thinking about which media fit where within the rich-lean continuum:

examples of rich and lean texts in media richness theory

7. Media Richness Theory in Studies of Educational Media (Examples)

Studies of media richness and education tend to support MRT’s claims that rich media is valuable for learning complex issues while lean media help students understand basic facts.

For example:

  • Shepherd & Martz (2006) found that rich media have been found to support increased communication in online forums and enhanced understanding of equivocal tasks .
  • Lean media have been found to support less equivocal fact-based learning (Sun & Cheng, 2007; Liu, Liao & Pratt, 2009).
  • Rich media has been found to be a distraction for low-equivocality tasks and to have slowed learning progress. Extraneous information can distract learners, waste working memory, and be a hindrance to learning (Kozma, 2001; Lan & Sie, 2010).

This does not mean rich media is best. Rather, it highlights that media choice needs to be task-relevant. If you want to resolve uncertainty, use lean media. If you want to discuss a complex topic, use rich media.

8. Media Richness Theory in Studies of Media Acceptance (Examples)

Media acceptance analysis is the analysis of whether someone likes or ‘accepts’ a form of media.

Usually, if people find a form of media (say, podcasts) useful for them, they’ll accept it and keep using it. If people fund that it is not useful, they’ll reject it and stop using it.

Media Richness Theory has enthusiastically been embraced for the study of media choice and acceptance.

Studies have found:

  • Media richness can impact upon choice and uptake of technologies (Shepherd & Martz, 2006; Lee, Cheung & Chen, 2007; Robert and Dennis, 2005; Balaji & Chakrabarti, 2010).
  • Rich media are more willingly accepted and taken-up by students if they see them as useful, easy to use, and more enjoyable (Lee, Cheung & Chen, 2007; Sun & Cheng, 2007; Shepherd & Martz, 2006).
  • However, Robert and Dennis (2005) have argued that increased motivation recorded by users of richer media can be negatively offset by the tendency of rich media to overwhelm cognitive faculties.

9. Strengths and Weaknesses of Media Richness Theory

Strengths:

  • The theory is very beneficial for understanding which media are best for which tasks. You don’t always want a rich media text, especially if you want to communicate something without any debate or discussion.
  • The four criteria for analyzing the richness of media make it a very practical theory. Anyone can classify and rank media based on the four criteria provided.
  • The theory acknowledges communication can be uni-directional, unlike linear theoies of media communication (such as Lasswell’s model) which only account for one-way media communication.

Weaknesses:

  • The theory was developed prior to Web 2.0 technologies, and therefore may not be as useful for modern technology studies are required to see whether the theory is of value today.
  • The theory would not give anyone a definitive answer about which media to use in which circumstance. Rather, it provides a framework for making that decision for yourself.
  • The theory is not used very widely today – there are many other approaches to media analysis and media acceptance that seem to be more popular.

Final Thoughts

The biggest mistake students make is that they assume rich media are always better than lean media. This is not true. It highlights that there are, in fact, disadvantages to ‘in vogue’ rich media that are now available thanks to the new affordances of the web.

The media richness theory therefore provides a great outline of how to select media for different purposes.

This nuanced approach to analysis of media communication is very practical, enabling people to think about which media to use in which circumstances.

References

Balaji, M. S., & Chakrabarti, D. (2010). Student interactions in online discussion forum: Empirical research from’media richness theory’perspective. Journal of Interactive Online Learning9(1).

Kozma, R. (2001). Robert Kozma’s counterpoint theory of ‘learning with media’. In Clark, R. (ed.) Learning from Media: Arguments, Analysis, and Evidence (pp. 137 – 178). United States of America: Information Age Publishing.

Lan, Y. F., & Sie, Y. S. (2010). Using RSS to support mobile learning based on media richness theory. Computers & Education55(2), 723-732.

Lee, M. K., Cheung, C. M., & Chen, Z. (2007). Understanding user acceptance of multimedia messaging services: An empirical study. Journal of the Association for Information Science and Technology58(13), 2066-2077.

Robert, L. P., & Dennis, A. R. (2005). Paradox of richness: A cognitive model of media choice. IEEE transactions on professional communication, 48(1), 10-21.

Shepherd, M. & Martz, W.B (2006) Media richness theory and the distance education environment. The Journal of Computer Information Systems, 47(1), pp. 114 – 122.

 

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Chris Drew, PhD (aka The Helpful Professor)

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