Achieving a designed customer experience across multiple delivery platforms: A telco perspective

'Customer experience' is a term that covers a wide range of activities that take place between suppliers and users of products and services. LaSalle and Britton define it as 'a holistic experience which involves a person - as opposed to a customer - as a whole at different levels and in every interaction between such person and a company' (2003). This research considers a key aspect of such an holistic experience: that which is embodied in the product or service under consideration. In the context of increasing mobile technology convergence, the paper considers new approaches that focus on developing the necessary underlying enablers and common interaction flows that are required to deliver a designed experience, taking into account the increasing number of mobile operating systems and service delivery platforms. Ultimately these models move towards allowing users to 'co-create their own unique experiences' (Pralahad and Ramswamy, 2004). The convergence between IT and telecommunications domains presents a unique challenge to product and service designers. Services are increasingly accessible via multiple delivery devices and delivery networks. This trend has been seen most recently in the advent of Internet based services being delivered via mobile phones where 'mobile service delivery and technologies have become the glue between previously secluded 'telecom' and "IT' domains' (Karrberg and Liebenau, 2006). At the same time network operators are trying to tighten their relationship with their customers by offering 'sticky' services aimed at raising the barriers to customer mobility. These two trends lead to a new design challenge: how to design a recognisably consistent and compelling product customer experience that applies over all delivery services, operating systems and networks. Solutions to this problem have to date been either technology led, focussing on integrated delivery platforms, or reliant on rule-based design. Crucial to this analysis is the 'role Please use this identifier to cite or link to this item

The Lensed Arc Production Efficiency of Galaxy Clusters: A Comparison of Matched Observed and Simulated Samples

We compare the statistical properties of giant gravitationally lensed arcs produced in matched simulated and observed cluster samples. The observed sample consists of 10 X-ray selected clusters at redshifts z ~ 0.2 imaged with HST by Smith et al. The simulated dataset is produced by lensing the Hubble Deep Field, which serves as a background source image, with 150 realizations (different projections and shifts) of five simulated z = 0.2 clusters from a LambdaCDM N-body simulation. The real and simulated clusters have similar masses, the real photometric redshift is used for each background source, and all the observational effects influencing arc detection in the real dataset, including light from cluster galaxies, are simulated in the artificial dataset. We develop, and apply to both datasets, an objective automatic arc-finding algorithm. We find consistent arc statistics in the real and in the simulated sample, with an average of ~ 1 detected giant (length to width ratio >= 10) arc per cluster and ~ 0.2 giant luminous (R<22.3 mag) arc per cluster. Thus, taking into account a realistic source population and observational effects, the clusters predicted by LambdaCDM have the same arc-production efficiency as the observed clusters. If, as suggested by other studies, there is a discrepancy between the predicted and the observed total number of arcs on the sky, it must be the result of differences between the redshift dependent cluster mass functions, and not due to differences in the lensing efficiency of the most massive clusters.Comment: 13 pages, Accepted by ApJ, High resolution version of the paper can be found at: ftp://wise3.tau.ac.il/pub/assafh/horesh_arcs_stat_2005.ps.gz, Arc-finding algorithm available at: http://wise-obs.tau.ac.il/~assafh/ ; A comment was added ; A missing x-axis label in Fig. 7 was adde