Media naturalness theory

Media naturalness theory was developed by Ned Kock. This theory is sometimes referred to as the psychobiological model^[1], or compensatory adaptation theory^[2]. It has been used to understand human behavior toward technology in various contexts, such as: education^[3], knowledge transfer^[4], communication in virtual environments^[5], e-negotiation ^[6], business process improvement^[7], trust and leadership in virtual teamwork^[8], online learning^[9][10], maintenance of distributed relationships^[11], performance in experimental tasks using various media^[12][13], and modular production^[14]. Media naturalness theory can be considered a Darwinian theory of behavior toward certain types of communication media^[15]. Its development is also consistent with ideas from the field of evolutionary psychology.^[1][16]

The theory builds on human evolution ideas and has been proposed as an alternative to media richness theory. Media naturalness theory argues that since our Stone Age hominid ancestors have communicated primarily face-to-face, evolutionary pressures have led to the development of a brain that is consequently designed for that form of communication^[1][17][18]. Other forms of communication are too recent and unlikely to have posed evolutionary pressures that could have shaped our brain in their direction. Using communication media that suppress key elements found in face-to-face communication, as many electronic communication media do, thus ends up posing cognitive obstacles to communication. This is particularly the case in the context of complex tasks (e.g., business process redesign, new product development, online learning), because such tasks seem to require more intense communication over extended periods of time than simple tasks^[1].

Biological basis

A simple thought experiment highlights the biological basis of media naturalness theory, and the fundamental difference between the media naturalness and media richness theories. Let us assume that the human species had evolved in an ancestral environment without light. If that were the case, modern humans would all be blind, and therefore a communication medium’s ability to convey facial expressions and body language would be irrelevant for effective communication. Conversely, a medium’s ability to convey smell might be fairly important for effective communication. This illustrates the fact that one cannot define a medium’s ability to support effective communication without taking into consideration characteristics of the communicators. Of these, biological characteristics often have an evolutionary basis.

Medium naturalness

The naturalness of a communication medium is defined, in media naturalness theory, as the degree of similarity of the medium with the face-to-face medium. The face-to-face medium is presented as the medium enabling the highest possible level of communication naturalness, which is characterized by the following five key elements ^[1][18]: (1) a high degree of co-location, which would allow the individuals engaged in a communication interaction to see and hear each other; (2) a high degree of synchronicity, which would allow the individuals to quickly exchange communicative stimuli; (3) the ability to convey and observe facial expressions; (4) the ability to convey and observe body language; and (5) the ability to convey and listen to speech.

Media naturalness theory predicts that any electronic communication medium allowing for the exchange of significantly less or more communicative stimuli per unit of time than the face-to-face medium will pose cognitive obstacles to communication^[1]. In other words, media naturalness theory places the face-to-face medium at the center of a one-dimensional scale of naturalness, where deviations to the left or right are associated with decreases in naturalness (see Figure 1).

Figure 1. Face-to-face medium naturalness.

Electronic media that enable the exchange of significantly more communicative stimuli per unit of time than the face-to-face medium are classified by media naturalness theory as having a lower degree of naturalness than the face-to-face medium. As such, those media are predicted to be associated with higher cognitive effort; in this case due primarily to a phenomenon known as information overload, which is characterized by individuals having more communicative stimuli to process than they are able to^[1].

Main predictions

Media naturalness effects on cognitive effort, communication ambiguity, and physiological arousal. Media naturalness theory’s main prediction is that, other things being equal, a decrease in the degree of naturalness of a communication medium leads to the following effects in connection with communication interactions in complex tasks^[18]: (a) an increase in cognitive effort, (b) an increase in communication ambiguity, and (c) a decrease in physiological arousal.

Naturalness of electronic communication media. Electronic communication media often suppress key face-to-face communication elements, with the goal of creating other advantages. For example, Web-based bulletin boards and discussion groups enable asynchronous (or time-disconnected) communication, but at the same time make it difficult to have the same level of feedback immediacy found in face-to-face communication. That often leads to frustration from users who expect immediate feedback on their postings^[2][18].

The high importance of speech. Media naturalness theory predicts that the degree to which an electronic communication medium supports an individual’s ability to convey and listen to speech is particularly significant in determining its naturalness. The theory predicts, through its speech imperative proposition^[1], that speech enablement influences naturalness significantly more than a medium’s degree of support for the use of facial expressions and body language.

Compensatory adaptation. According to media naturalness theory, electronic communication media users can adapt their behavior in such a way as to overcome some of the limitations of those media^[2]. That is, individuals who choose to use electronic communication media to accomplish complex collaborative tasks may compensate for the cognitive obstacles associated with the lack of naturalness of the media. One of the ways in which this can be achieved through email is by users composing messages that are redundant and particularly well organized, compared to face-to-face communication. This often contributes to improving the effectiveness of communication, sometimes even beyond that of the face-to-face medium^[12].

Cognitive effort

Human beings possess specialized brain circuits that are designed for the recognition of faces and the generation and recognition of facial expressions, which artificial intelligence research suggests require complex computations that are difficult to replicate even in powerful computers. The same situation is found in connection with speech generation and recognition. Generation and recognition of facial expressions, and speech generation and recognition, are performed effortlessly by humans^[1].

Cognitive effort is defined in media naturalness theory as the amount of mental activity, or, from a biological perspective, the amount of brain activity involved in a communication interaction^[1]. It can be assessed directly, with the use of techniques such as magnetic resonance imaging. Cognitive effort can also be assessed indirectly, based on perceptions of levels of difficulty associated with communicative tasks, as well as through indirect measures such as that of fluency. Fluency is defined as the amount of time taken to convey a certain number of words through different communication media, which is assumed to correlate (and serve as a surrogate measure of) the amount of time taken to convey a certain number of ideas through different media^[12]. According to media naturalness theory, a decrease in the degree of naturalness of a communication medium leads to an increase in the amount of cognitive effort required to use the medium for communication^[1].

Communication ambiguity

Individuals brought up in different cultural environments usually possess different information processing schemas that they have learned over their lifetimes. Different schemas make individuals interpret information in different ways, particularly when information is expected but not actually provided^[1][18].

While different individuals are likely to look for the same types of communicative stimuli, their interpretation of the message being communicated in the absence of those stimuli will be largely based on their learned schemas, which are likely to differ from those held by other individuals (no two individuals, not even identical twins raised together, go through exactly the same experiences during their lives). According to media naturalness theory, a decrease in medium naturalness, caused by the selective suppression of media naturalness elements in a communication medium, leads to an increase in the probability of misinterpretations of communicative cues, and thus an increase in communication ambiguity^[18].

Physiological arousal

To say that our genes influence the formation of a phenotypic trait (i.e., a biological trait that defines a morphological, behavioral, physiological, etc. characteristic) does not mean the same as saying that the trait in question is innate. Very few phenotypic traits are innate (e.g., blood type); the vast majority, including most of those in connection with our biological communication apparatus, need interaction with the environment to be fully and properly developed^[18].

While there is substantial evidence suggesting that our biological communication apparatus is designed for face-to-face communication, there is also ample evidence that such an apparatus (including the neural functional language system) cannot be fully developed without a significant amount of practice. Thus, according to media naturalness theory, evolution must have shaped brain mechanisms to compel human beings to practice the use of their biological communication apparatus; mechanisms that are similar to those compelling animals to practice those skills that play a key role in connection with survival and mating^[18]. Among these mechanisms, one of the most important is that of physiological arousal, which is often associated with excitement and pleasure. Engaging in communication interactions, particularly in face-to-face situations, triggers physiological arousal in human beings. Suppression of media naturalness elements makes communication interactions duller than if those elements were present^[18].

Speech importance

Complex speech was enabled by the evolution of a larynx located relatively low in the neck, which considerably increased the variety of sounds that our species could generate; this is actually one of the most important landmarks in the evolution of the human species^[1]. However, that adaptive design also significantly increased our ancestors’ chances of choking on ingested food and liquids, and suffering from aerodigestive tract diseases such as gastroesophageal reflux. This leads to an interesting conclusion, which is that complex speech must have been particularly important for effective communication in our evolutionary past, otherwise the related evolutionary costs would prevent it from evolving through natural selection^[1]. This argument is similar to that made by Amotz Zahavi in connection with evolutionary handicaps. If a trait evolves to improve the effectiveness in connection with a task, in spite of imposing a survival handicap, then the trait should be a particularly strong determinant of the performance in the task to offset the survival cost it imposes.

Media naturalness theory builds on this evolutionary handicap conclusion to predict that the degree to which an electronic communication medium supports an individual’s ability to convey and listen to speech is particularly significant in defining its naturalness^[1]. Media naturalness theory predicts, through its speech imperative proposition, that speech enablement influences naturalness significantly more than a medium’s degree of support for the use of facial expressions and body language^[1]. This prediction is consistent with past research showing that removing speech from an electronic communication medium significantly increases the perceived mental effort associated with using the medium to perform knowledge-intensive tasks. According to this prediction, a medium such as audio conferencing is relatively close to the face-to-face medium in terms of naturalness (see Figure 2).

Figure 2. Media naturalness scale.

Compensatory adaptation

Increases in cognitive effort and communication ambiguity are usually accompanied by an interesting behavioral phenomenon, called compensatory adaptation^[2][12]. The phenomenon is characterized by voluntary and involuntary attempts by the individuals involved in a communicative act to compensate for the obstacles posed by an unnatural communication medium. One of the key indications of compensatory adaptation is a decrease in communication fluency, which can be measured through the number of words conveyed per minute through a communication medium. That is, communication fluency is believed to go down as a result of individuals making an effort to adapt their behavior in a compensatory way^[12].

For example, an empirical study^[2] suggests that when individuals used instant messaging and face-to-face media to perform complex and knowledge-intensive tasks, the use of the electronic (i.e., instant messaging) medium caused several effects. Those effects were consistent with media naturalness theory, and the compensatory adaptation notion. Among those effects, the electronic medium increased perceived cognitive effort by approximately 40% and perceived communication ambiguity by approximately 80% - as predicted by media naturalness theory. The electronic medium also reduced actual fluency by approximately 80%, and the quality of the task outcomes was not affected, suggesting compensatory adaptation.

See also

• Communication theory
• Computer-supported collaboration
• Evolutionary psychology
• Media richness theory
• Theories of technology

References

1. ^ ^{a b c d e f g h i j k l m n o p} Kock, N. (2004). The psychobiological model: Towards a new theory of computer-mediated communication based on Darwinian evolution. Organization Science, 15(3), 327-348.
2. ^ ^{a b c d e} Kock, N. (2005b). Compensatory adaptation to media obstacles: An experimental study of process redesign dyads. Information Resources Management Journal, 18(2), 41-67.
3. ^ Paretti, M.C., McNair, L.D., & Holloway-Attaway, L. (2007). Teaching technical communication in an era of distributed work: A case study of collaboration between U.S. and Swedish students. Technical Communication Quarterly, 16(3), 327-353.
4. ^ Schwartz, D.G. (2007). Integrating knowledge transfer and computer-mediated communication: Categorizing barriers and possible responses. Knowledge Management Research & Practice, 5(4), 249-260.
5. ^ Verhulsdonck, G. (2007). Issues of designing gestures into online interactions: Implications for communicating in virtual environments. In D. Novik & C. Spinuzzi (Eds.), Proceedings of the 25th annual ACM International Conference on Design of Communication (pp. 26–33). New York, NY: Association for Computing Machinery.
6. ^ Citera, M., Beauregard, R., & Mitsuya, T. (2005). An experimental study of credibility in e-negotiations. Psychology & Marketing, 22(2), 163-179.
7. ^ DeLuca, D. (2003). Business process improvement using asynchronous e-collaboration: Testing the compensatory adaptation model. Doctoral Dissertation. Philadelphia, PA: Temple University.
8. ^ DeRosa, D.M., Hantula, D.A., Kock, N., & D’Arcy, J.P. (2004). Trust and leadership in virtual teamwork: A media naturalness perspective. Human Resource Management, 34(2), 219-232.
9. ^ Hrastinski, S. (2008). The potential of synchronous communication to enhance participation in online discussions: A case study of two e-learning courses. Information & Management, 45(7), 499-506.
10. ^ Kock, N., Verville, J., & Garza, V. (2007). Media naturalness and online learning: Findings supporting both the significant- and no-significant-difference perspectives. Decision Sciences Journal of Innovative Education, 5(2), 333-356.
11. ^ McKinney, V.R., & Whiteside, M.M. (2006). Maintaining distributed relationships. Communications of the ACM, 49(3), 82-87.
12. ^ ^{a b c d e} Kock, N. (2007). Media naturalness and compensatory encoding: The burden of electronic media obstacles is on senders. Decision Support Systems, 44(1), 175-187.
13. ^ Simon, A.F. (2006). Computer-mediated communication: Task performance and satisfaction. Journal of Social Psychology, 146(3), 349-379.
14. ^ Kotabe, M., Parente, R., & Murray, J.Y. (2007). Antecedents and outcomes of modular production in the Brazilian automobile industry: A grounded theory approach. Journal of International Business Studies, 38(1), 84-107.
15. ^ Kock, N., Hantula, D.A., Hayne, S., Saad, G., Todd, P.M., & Watson, R.T. (2008). Introduction to Darwinian perspectives on electronic communication. IEEE Transactions on Professional Communication, 51(2), 133-146.
16. ^ Kock, N., & Hantula, D.A. (2005). "Do we have e-collaboration genes?". International Journal of e-Collaboration 1 (2): i-ix. http://cits.tamiu.edu/kock/pubs/journals/2005JournalIJeC2/KockHantula2005.pdf. 
17. ^ Kock, N. (2001). The ape that used email: Understanding e-communication behavior through evolution theory. Communications of the Association for Information Systems, 5(3), 1-29.
18. ^ ^{a b c d e f g h i} Kock, N. (2005). Media richness or media naturalness? The evolution of our biological communication apparatus and its influence on our behavior toward e-communication tools. IEEE Transactions on Professional Communication, 48(2), 117-130.

Further reading

• Daft, R.L., Lengel, R.H., & Trevino, L.K. (1987). Message equivocality, media selection, and manager performance: Implications for information systems. MIS Quarterly, 11(3), 355-366.
• Dennis, A.R., Fuller, R.M., & Valacich, J.S. (2008). Media, tasks, and communication processes: A theory of media synchronicity. MIS Quarterly, 32(3), 575-600.
• El-Shinnawy, M., & Markus, L. (1998). Acceptance of communication media in organizations: Richness or features?, IEEE Transactions on Professional Communication, 41(4), 242-253.
• Lee, A.S. (1994). Electronic mail as a medium for rich communication: An empirical investigation using hermeneutic interpretation. MIS Quarterly, 18(2), 143-157.
• Lengel, R.H., & Daft, R.L. (1988). The selection of communication media as an executive skill. Academy of Management Executive, 2(3), 225-232.
• Markus, M.L. (1994). Finding a happy medium: Explaining the negative effects of electronic communication on social life at work. ACM Transactions on Information Systems, 12(2), 119-149.
• Markus, M.L. (2005). Technology-shaping effects of e-collaboration technologies: Bugs and features. International Journal of e-Collaboration, 1(1), 1-23.
• Ngwenyama, O.K., & Lee, A.S. (1997). Communication richness in electronic mail: Critical social theory and the contextuality of meaning. MIS Quarterly, 21(2), 145-167.
• Nosek, J.T. (2005). Collaborative sensemaking support: Progressing from portals and tools to collaboration envelopes. International Journal of e-Collaboration, 1(2), 25-39.
• Nunamaker, J.F., A.R. Dennis, J.S. Valacich, D.R. Vogel, & J.F. George (1991). Electronic meeting systems to support group work. Communications of ACM, 34(7), 40-61.
• Pinsonneault, A., Barki, H., Gallupe, R.B., & Hoppen, N. (1999). Electronic brainstorming: The illusion of productivity. Information Systems Research, 10(2), 110-133.
• Rice, R.E. (1993). Media appropriateness: Using social presence theory to compare traditional and new organizational media. Human Communication Research, 19(4), 451-484.
• 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.
• Sallnas, E.L., Rassmus-Grohn, K., & Sjostrom, C. (2000). Supporting presence in collaborative environments by haptic force feedback. ACM Transactions on Computer-Human Interaction, 7(4), 461–476.
• Tan, B.C.Y., Wei, K., Huang, W.W., & Ng, G. (2000). A dialogue technique to enhance electronic communication in virtual teams. IEEE Transactions on Professional Communication, 43(2), 153-165.
• Te’eni, D. (2001). A cognitive-affective model of organizational communication for designing IT. MIS Quarterly, 25(2), 251-312.
• Ulijn, J.M., Lincke, A., & Karakaya, Y. (2001). Non-face-to-face international business communication: How is national culture reflected in this medium? IEEE Transactions on Professional Communication, 44(2), 126-138.
• Van Alstyne, M., & Brynjolfsson, E. (2005). Global village or cyberbalkans: Modeling and measuring the integration of electronic communities. Management Science, 51(6), 851-868.
• Walther, J.B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23(1), 3-43.
• Walther, J.B., Slovacek, C., & Tidwell, L.C. (2001). Is a picture worth a thousand words? Photographic images in long term and short term virtual teams. Communication Research, 28(1), 105-134.
• Zigurs, I., & Buckland, B.K. (1998). A theory of task-technology fit and group support systems effectiveness. MIS Quarterly, 22(3), 313-334.