Knowledge transfer in globally distributed teams: the role of transactive memory

This paper explores the role of transactive memory in enabling knowledge transfer between globally distributed teams. While the information systems literature has recently acknowledged the role transactive memory plays in improving knowledge processes and performance in colocated teams, little is known about its contribution to distributed teams. To contribute to filling this gap, knowledge‐transfer challenges and processes between onsite and offshore teams were studied at TATA Consultancy Services. In particular, the paper describes the transfer of knowledge between onsite and offshore teams through encoding, storing and retrieving processes. An in‐depth case study of globally distributed software development projects was carried out, and a qualitative, interpretive approach was adopted. The analysis of the case suggests that in order to overcome differences derived from the local contexts of the onsite and offshore teams (e.g. different work routines, methodologies and skills), some specific mechanisms supporting the development of codified and personalized ‘directories’ were introduced. These include the standardization of templates and methodologies across the remote sites as well as frequent teleconferencing sessions and occasional short visits. These mechanisms contributed to the development of the notion of ‘who knows what’ across onsite and offshore teams despite the challenges associated with globally distributed teams, and supported the transfer of knowledge between onsite and offshore teams. The paper concludes by offering theoretical and practical implications.     

Clifford Fourier transform on vector fields

Image processing and computer vision have robust methods for feature extraction and the computation of derivatives of scalar fields. Furthermore, interpolation and the effects of applying a filter can be analyzed in detail and can be advantages when applying these methods to vector fields to obtain a solid theoretical basis for feature extraction. We recently introduced the Clifford convolution, which is an extension of the classical convolution on scalar fields and provides a unified notation for the convolution of scalar and vector fields. It has attractive geometric properties that allow pattern matching on vector fields. In image processing, the convolution and the Fourier transform operators are closely related by the convolution theorem and, in this paper, we extend the Fourier transform to include general elements of Clifford Algebra, called multivectors, including scalars and vectors. The resulting convolution and derivative theorems are extensions of those for convolution and the Fourier transform on scalar fields. The Clifford Fourier transform allows a frequency analysis of vector fields and the behavior of vector-valued filters. In frequency space, vectors are transformed into general multivectors of the Clifford Algebra. Many basic vector-valued patterns, such as source, sink, saddle points, and potential vortices, can be described by a few multivectors in frequency space.     

Online social networks: A survey of a global phenomenon

Online social networks became a global phenomenon with enormous social as well as economic impact within a few years. Alone, the most popular online social network, Facebook, counts currently more than 850 million users worldwide. Consequently, online social networks attract a great deal of attention among practitioners as well as researchers. The goal of this article is to provide an overview of online social networks in order to contribute to a better understanding of this worldwide phenomenon. In this context, we address for example the following questions: What are the major functionalities and characteristics of online social networks? What are the users’ motives for using them and how did online social networks emerge and develop over time? What is the impact and value of online social networks from a business perspective and what are corresponding challenges and risks?     

How Internet Users' Privacy Concerns Have Evolved since 2002

In 2002, the authors established a baseline for Internet users' online privacy values, finding information transfer, notice/awareness, and information storage were the top online privacy concerns. Since this survey, many privacy-related events have occurred, including changes in online trends and the creation of laws, prompting the authors to rerun the survey in 2008 to examine how these events might have affected users' online privacy concerns. In this article, they discuss the 2008 survey, which revealed that US Internet users' top three privacy concerns didn't change over the course of six years, although their level of concern did. The authors also examine differences in privacy concerns between US and international respondents. The Web extra groups the survey statements according to six dimensions of privacy concerns based on the following classifications—personalization, notice/awareness, information transfer, information collection, information storage, and access/participation.     

Valuation of online social networks taking into account users’ interconnectedness

Online social networks have been gaining increasing economic importance in light of the rising number of their users. Numerous recent acquisitions priced at enormous amounts have illustrated this development and revealed the need for adequate business valuation models. The value of an online social network is largely determined by the value of its users, the relationships between these users, and the resulting network effects. Therefore, the interconnectedness of a user within the network has to be considered explicitly to get a reasonable estimate for its economic value. Established standard business valuation models, however, do not account for these aspects sufficiently. Thus, we propose an economic model for the valuation of online social networks, which takes into account the users’ interconnectedness within the network. Furthermore, we analyze different centrality measures, which can be used to quantify users’ interconnectedness in online social networks and propose a measure which is based on the PageRank-algorithm. Finally, the practical application of the model is illustrated by an example of the European online social network XING.com.     

Trusting the Electronic Edition

This paper discusses the contested role of images in electronic editions, and summarizes some of the chief arguments for their inclusion. I then argue that, to truly determine the importance of images to the function of electronic editions, we must understand the contribution the image makes to the form of textual knowledge provided by the edition. I suggest a distinction between editions which are primarily pedagogical in their aims, those which aim above all at scholarly authority, and those which attempt to provide textual information as high-quality data which can be analysed and processed. I conclude that the latter represents the most significant future trend in electronic editing. This revised version was published online in July 2006 with corrections to the Cover Date.     

Bisimulation conversion and verification procedure for goal-based control systems

Fault tolerance and safety verification of control systems are essential for the success of autonomous robotic systems. A control architecture called Mission Data System (MDS), developed at the Jet Propulsion Laboratory, addresses these needs with a goal-based control approach. In this paper, a software algorithm for converting goal network control systems into linear hybrid systems is described. The conversion process is a bisimulation; the resulting linear hybrid system can be verified for safety in the presence of failures using existing symbolic model checkers, and thus the original goal network is verified. A moderately complex example goal network control system is converted to a linear hybrid system using the automatic conversion software that is based on the bisimulation and then is verified.