From Collaborative Tools to Collaborative Working Environments

Prinz, Wolfgang; Martínez-Carreras, M. Antonia; Pallot, Marc

doi:10.4018/jec.2010091101

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…Collaboration is a human activity where the focus is on human behaviours such as sharing knowledge, learning and building consensus. A collaborative culture -not only technology, computer hardware, software or other tools -is an essential requirement for effective collaboration (Jung & Sosik, 2002;Noorderhaven & Harzing, 2009;Stringer et al, 2009;Prinz et al, 2010). For instance, because one can create an online dimension of community does not mean that one should.…”

Section: Collaboration Toolsmentioning

confidence: 97%

Destroying collaboration and knowledge sharing in the workplace: a reverse brainstorming approach

Evans

2012

Knowledge Management Research & Practice

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Organizations in the 21st century find themselves in the culture of collaboration. Collaboration and knowledge sharing are fundamental aspects of problem solving, decision making and innovation, and are therefore vital for success. Some organizational cultures foster collaboration while others actively or inadvertently destroy shared decision-making activities. Reverse brainstorming is a method where participants identify different ways to cause a problem. These negative ideas are then used to stimulate ideas for solving the problem. This paper reports on a reverse brainstorming session during which knowledge management practitioners, consultants and academics generated ideas on how collaboration and knowledge sharing is destroyed in organizations, followed by positive ideas to promote effective, collaborative workplaces.

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Section: Collaboration Toolsmentioning

confidence: 97%

Destroying collaboration and knowledge sharing in the workplace: a reverse brainstorming approach

Evans

2012

Knowledge Management Research & Practice

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“…In socially intelligent computing systems "social refers to the interactions among people and increasingly more sophisticated computing technologies; intelligent refers to the emerging intelligence exhibited by such systems as well as their increasing knowledge about people and their interactions with one another and with computers; computing refers to the computation technologies that act as mediators among people, as tools used by people, and as equal or complementary participants with people" [Maher, 2009], [Agarwal and Xu, 2011]. Research in socially intelligent computing broadens the scope and coverage of social computing [Wang, et al 2005] and spans a variety of issues ranging from intelligent collaborative systems [Prinz, et al 2010] to the use of semantic technologies and the web of linked open data in order to support computational sociality [Sheth and Nagarajan 2009], while related applications use intelligent computing infrastructures that exploit social media on the web [Bothos, et al 2010]. At the business level, socially intelligent computing systems can be considered the intelligent evolution of social business software that facilitate Enterprise 2.0 companies as defined by [McAfee 2006].…”

Section: Introductionmentioning

confidence: 99%

A socially intelligent approach for enterprise information search and recommendation

Apostolou¹,

Mentzas²

2012

2012 18th International ICE Conference on Engineering, Technology and Innovation

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This paper focuses on the development of socially intelligent computing systems at the enterprise level. Specifically, in order to improve the information search and recommendation functionalities of social business software, we extend corporate knowledge structuring approaches, such as folksonomies and taxonomies, with the addition of statistical topic models. We use probabilistic models in order to uncover hidden topics in the corporate 'knowledge base' and hence add an intelligent perspective in social collaboration. Probabilistic topic models are based upon the idea that documents are mixtures of topics, where a topic is defined as a probability distribution over words. We apply our approach in the Organik social business software platform and deploy it in five companies. Our results showed enhanced recommendations and improved search efficiency, while our approach effectively addresses problems in query expansion and recommends relevant resources and tags which in turn can leverage the creation and evolution of social knowledge structures like folksonomies.

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