The 8th IEEE MUCS Workshop intended to concentrate on the management of ubiquitous devices, communications, and services. And the program has shown that the context management as well as the managing behavior was selected out of that field as the major, based on those paper topics accepted. Thus, the major intentions of MUCS had been implemented. While the relevant papers and their topics are accessible via the URL http://ubiquitous-management.org/mucs/2011/program.php, the major findings of the key note are summarized here. In addition, Table 1 shows in a very specific point of view the socio-economic facets of all of those presentations.

Table 1: Presentation Relations to Socio-economic Aspects (Mentioned vs. Addressed)

Paper	Social aspects mentioned	Economics mentioned	Social aspects addressed	Economics addressed
Session 1, #1	User behavior	No	No	No
Session 1, #2	User-specific behavior changes the outcome	No	Partially in modeling utility function alternatives	No
Session 1, #3	Taxis drives, but not considered as a social facet!	No, even though implicitly assumed that they can increase their revenues	No	Implicitly assumed by proposing the respective strategies and their advantages
Session 1, #4
Session 1, Keynote	Partially (privacy, risks)	Partially (costs for data collection)	No	Minimalistic (addressed by cost-savings in algorithms)
Session 2, #1	User behavior in terms QoE	No	QoE outcomes discussed	No
Session 2, #2	Ease of modification	No	SCXML-based descriptions	No
Session 2, #3	The mobile phone user	Comparison of voice vs. text (SMS)	No	CDRs show that LA commutes 1.5 times further than NY

In terms of the key note, John Krumm revealed that behavioral priorities are the key information to be determined in case of users. At the same time, application-specific risks, e.g., minimizing the death of fatality accidents in a map-based routing application in use, become critical, way beyond the pure technology and application operated. Furthermore, mainly with respect to the privacy of data and location information, the obfuscation measures in use today do not work very well, except for the case, where the adding of very many noise can be considered partially successful. Of course, except for all those people, who do not care about their location information being revealed, obfuscation is needed strongly, Finally, John sees that different social groups of users and providing input to any application or data analysis approach need to be considered in detail, assuring that relevant social statements can be made (e.g., women’s new driving destinations decline faster over time compared to men’s driving destinations).