CMCSSClarksville-Montgomery County School System (Clarksville, TN, USA)
CMCSSCellular Mobile Carrier Switching System
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Participation in the decision to use CMCSs, user training and support, the nature of existing ties among group members, and the style of leadership or group management (electronic or otherwise) are seen as crucial determinants of the acceptance and impacts of a new communications technology.
In systems contingency theory, there is no such thing as "one best way" to design organizational communication systems in general or CMCSs in particular, because "what's best for an organization, or a subunit within it, is a highly complex function of many variables".
Multiple regression enables us to determine the best combination of variables for predicting whether or not CMCSs are perceived as contributing to productivity enhancement.
Thus, variables at the individual, group, and system level all play a part in determining perceptions of productivity increases from CMCSs.
From the systems rationalist perspective, productivity increases are the ultimate payoff of CMCSs for groups organizations, and society as a whole.
Productivity improvements, thus, are clearly quite distinct from other dimensions of acceptance of CMCSs.
This appears to be the main impact of software differences: given four basically well designed but quite different CMCSs, the social context and software differences will interact to affect the most productive applications of the system.
(See for an exploration of this question.) Also, even though most of the questions used to measure pre-use expectations about the systems and post-use perceptions of productivity increases were different, might the high correlation be a methodological artifact of the stability of attitudes, rather than evidence that those who are most receptive to CMCSs use them most effectively?
A field experiment is recommended as the next logical step in exploring the determinants of productivity impacts of CMCSs. Pre-use attitudes that appear to strongly predict subsequent acceptance could be used to screen potential users and groups and to make sure that different experimental groups are comparable at the outset.