Achieving IT diffusion within the fragments: an IT culture perspective

Many organizations still fail to make a return from the huge investments they make in implementing complex Information Technology (IT). This is usually due to cultural forces that inhibit the level of usage required to facilitate IT Diffusion. An emerging stream of research highlights the IT culture perspective, a perspective vital for understanding individuals’ social practices when they interact with IT. This paper adopted a case study approach to explore how the IT culture perspective may explain how organizational diffusion of an IT may happen despite opposing cultural forces causing a stalemate to the diffusion process. This study identified three IT culture archetypes - embracing, rejecting and confused, depicting a fragmented IT culture during the adaption, acceptance and routinization stages of diffusion of an IT. This study highlights how a salient element of a fragmented IT culture-embracing IT culture archetype could explain how diffusion of an IT happened despite the manifestations of negative IT culture archetypes - ‘confused’ and ‘rejecting’ during the diffusion process

The influence of organizational culture on the outcome of an IS implementation

A number of information system (IS) studies have adopted organizational culture (OC) theory to investigate IS implementations. The studies highlight that members will reach consensus or agreement in the use of an IS but also experience inevitable tensions and ambiguities in the use of the IS. However, literature related to IS implementation/OC has rarely examined the influence that the saliency of specific cultural practices may have on the success or failure of IS implementations. Using a case study approach, we adopted the “soft positivism” research philosophy to collect data, underpinned by Martin’s (1992) integration and differentiation perspectives of OC to study organizational implementation of an IS. These perspectives served as interpretive lenses through which to explain how members’ salient behaviors towards an IS evolved during the implementation process. Our study augments the IS implementation/OC literature by demonstrating how salient cultural practices influence the outcome of IS implementatio

Marking (1,2) Points of the Brownian Web and Applications

The Brownian web (BW), which developed from the work of Arratia and then T\'{o}th and Werner, is a random collection of paths (with specified starting points) in one plus one dimensional space-time that arises as the scaling limit of the discrete web (DW) of coalescing simple random walks. Two recently introduced extensions of the BW, the Brownian net (BN) constructed by Sun and Swart, and the dynamical Brownian web (DyBW) proposed by Howitt and Warren, are (or should be) scaling limits of corresponding discrete extensions of the DW -- the discrete net (DN) and the dynamical discrete web (DyDW). These discrete extensions have a natural geometric structure in which the underlying Bernoulli left or right "arrow" structure of the DW is extended by means of branching (i.e., allowing left and right simultaneously) to construct the DN or by means of switching (i.e., from left to right and vice-versa) to construct the DyDW. In this paper we show that there is a similar structure in the continuum where arrow direction is replaced by the left or right parity of the (1,2) space-time points of the BW (points with one incoming path from the past and two outgoing paths to the future, only one of which is a continuation of the incoming path). We then provide a complete construction of the DyBW and an alternate construction of the BN to that of Sun and Swart by proving that the switching or branching can be implemented by a Poissonian marking of the (1,2) points.Comment: added 3 references to Sections 1, 2, 3; expanded explanations in Subsections 7.3, 7.4, 7.

Euler hydrodynamics of one-dimensional attractive particle systems

We consider attractive irreducible conservative particle systems on $\mathbb{Z}$, without necessarily nearest-neighbor jumps or explicit invariant measures. We prove that for such systems, the hydrodynamic limit under Euler time scaling exists and is given by the entropy solution to some scalar conservation law with Lipschitz-continuous flux. Our approach is a generalization of Bahadoran et al. [Stochastic Process. Appl. 99 (2002) 1--30], from which we relax the assumption that the process has explicit invariant measures.Comment: Published at http://dx.doi.org/10.1214/009117906000000115 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org