Understanding Customer Loyalty and Disloyalty The Effect of Loyalty-Supporting and -Repressing Factors (first edition sold out, 'print on demand' 60 €)

Customer loyalty has been a central topic of both marketing theory and practice for several decades. Customer disloyalty, or relationship ending, has received much less attention. Despite the close relation between customer loyalty and disloyalty, they have rarely been addressed in the same study. The thesis bridges this gap by focusing on both loyal and disloyal customers and the factors characterising them. Based on a qualitative study of loyal and disloyal bank customers in the Finnish retail banking market, both factors that are common to the groups and factors that differentiate between them are identified. A conceptual framework of factors that affect customer loyalty or disloyalty is developed and used to analyse the empirical data. According to the framework, customers’ loyalty status (behavioural and attitudinal loyalty) is influenced by positive, loyalty-supporting, and negative, loyalty-repressing factors. Loyalty-supporting factors either promote customer dedication, making the customer want to remain loyal, or act as constraints, hindering the customer from switching. Among the loyalty-repressing factors it is especially important to identify those that act as triggers of disloyal behaviour, making customers switch service providers. The framework further suggests that by identifying the sources of loyalty-supporting and -repressing factors (the environment, the provider, the customer, the provider-customer interaction, or the core service) one can determine which factors are within the control of the service provider. Attitudinal loyalty is approached through a customer’s “feeling of loyalty”, as described by customers both orally and graphically. By combining the graphs with behavioural loyalty, seven customer groups are identified: Stable Loyals, Rescued Loyals, Loyals at Risk, Positive Disloyals, Healing Disloyals, Fading Disloyals, and Abrupt Disloyals. The framework and models of the thesis can be used to analyse factors that affect customer loyalty and disloyalty in different service contexts. Since the empirical study was carried out in a retail bank setting, the thesis has managerial relevance especially for banks. Christina Nordman is associated with CERS, Center for Relationship Marketing and Service Management at the Swedish School of Economics and Business Administration. The doctoral thesis is part of the Göran Collert Research Project in Customer Relationships and Retail Banking and has been funded by The Göran Collert Foundation.

Fault-tolerant Video on Demand in RSerPool Architecture

With the advent of Internet, video over IP is gaining popularity. In such an environment, scalability and fault tolerance will be the key issues. Existing video on demand (VoD) service systems are usually neither scalable nor tolerant to server faults and hence fail to comply to multi-user, failure-prone networks such as the Internet. Current research areas concerning VoD often focus on increasing the throughput and reliability of single server, but rarely addresses the smooth provision of service during server as well as network failures. Reliable Server Pooling (RSerPool), being capable of providing high availability by using multiple redundant servers as single source point, can be a solution to overcome the above failures. During a possible server failure, the continuity of service is retained by another server. In order to achieve transparent failover, efficient state sharing is an important requirement. In this paper, we present an elegant, simple, efficient and scalable approach which has been developed to facilitate the transfer of state by the client itself, using extended cookie mechanism, which ensures that there is no noticeable change in disruption or the video quality.

Certificate-less on-demand public key management (CLPKM) for self-organized MANETs

In this paper, we have proposed a novel certificate-less on-demand public key management (CLPKM) protocol for self-organized MANETs. The protocol works on flat network architecture, and distinguishes between authentication layer and routing layer of the network. We put an upper limit on the length of verification route and use the end-to-end trust value of a route to evaluate its strength. The end-to-end trust value is used by the protocol to select the most trusted verification route for accomplishing public key verification. Also, the protocol uses MAC function instead of RSA certificates to perform public key verification. By doing this, the protocol saves considerable computation power, bandwidth and storage space. The saved storage space is utilized by the protocol to keep a number of pre-established routes in the network nodes, which helps in reducing the average verification delay of the protocol. Analysis and simulation results confirm the effectiveness of the proposed protocol.

Low-Cost Cloud-Based Design of Smart Rural Energy Device in Microgrid: Perspective India An Energy-On-Demand Service for Rural India

In this paper we present a combination of technologies to provide an Energy-on-Demand (EoD) service to enable low cost innovation suitable for microgrid networks. The system is designed around the low cost and simple Rural Energy Device (RED) Box which in combination with Short Message Service (SMS) communication methodology serves as an elementary proxy for Smart meters which are typically used in urban settings. Further, customer behavior and familiarity in using such devices based on mobile experience has been incorporated into the design philosophy. Customers are incentivized to interact with the system thus providing valuable behavioral and usage data to the Utility Service Provider (USP). Data that is collected over time can be used by the USP for analytics envisioned by using remote computing services known as cloud computing service. Cloud computing allows for a sharing of computational resources at the virtual level across several networks. The customer-system interaction is facilitated by a third party Telecom Service provider (TSP). The approximate cost of the RED Box is envisaged to be under USD 10 on production scale.

On demand translation for querying incompletely aligned datasets

More and more users aim at taking advantage of the existing Linked Open Data environment to formulate a query over a dataset and to then try to process the same query over different datasets, one after another, in order to obtain a broader set of answers. However, the heterogeneity of vocabularies used in the datasets on the one side, and the fact that the number of alignments among those datasets is scarce on the other, makes that querying task difficult for them. Considering this scenario we present in this paper a proposal that allows on demand translations of queries formulated over an original dataset, into queries expressed using the vocabulary of a targeted dataset. Our approach relieves users from knowing the vocabulary used in the targeted datasets and even more it considers situations where alignments do not exist or they are not suitable for the formulated query. Therefore, in order to favour the possibility of getting answers, sometimes there is no guarantee of obtaining a semantically equivalent translation. The core component of our proposal is a query rewriting model that considers a set of transformation rules devised from a pragmatic point of view. The feasibility of our scheme has been validated with queries defined in well known benchmarks and SPARQL endpoint logs, as the obtained results confirm.

On-demand generation and removal of alginate biocompatible microvalves for flow control in microfluidics

[EN] This paper describes, for the first time, the use of alginate hydrogels as miniaturised microvalves within microfluidic devices. These biocompatible and biodegradable microvalves are generated in situ and on demand, allowing for microfluidic flow control. The microfluidic devices were fabricated using an origami inspired technique of folding several layers of cyclic olefin polymer followed by thermocompression bonding. The hydrogels can be dehydrated at mild temperatures, 37◦C, to slightly open the microvalve and chemically erased using an ethylenediaminetetraacetic acid disodium salt (EDTA) solution, to completely open the channel, ensuring the reusability of the whole device and removal of damaged or defective valves for subsequent regeneration.

Gene function prediction from synthetic lethality networks via ranking on demand.

MOTIVATION: Synthetic lethal interactions represent pairs of genes whose individual mutations are not lethal, while the double mutation of both genes does incur lethality. Several studies have shown a correlation between functional similarity of genes and their distances in networks based on synthetic lethal interactions. However, there is a lack of algorithms for predicting gene function from synthetic lethality interaction networks. RESULTS: In this article, we present a novel technique called kernelROD for gene function prediction from synthetic lethal interaction networks based on kernel machines. We apply our novel algorithm to Gene Ontology functional annotation prediction in yeast. Our experiments show that our method leads to improved gene function prediction compared with state-of-the-art competitors and that combining genetic and congruence networks leads to a further improvement in prediction accuracy.

The effects of corona treatment on impact and spreading of ink-jet drops on a polymeric film substrate

The effects of varying corona surface treatment on ink drop impact and spreading on a polymer substrate have been investigated. The surface energy of substrates treated with different levels of corona was determined from static contact angle measurement by the Owens and Wendt method. A drop-on-demand print-head was used to eject 38 μm diameter drops of UV-curable graphics ink travelling at 2.7 m/s on to a flat polymer substrate. The kinematic impact phase was imaged with a high speed camera at 500k frames per second, while the spreading phase was imaged at 20k frames per secoiui. The resultant images were analyzed to track the changes in the drop diameter during the different phases of drop spreading. Further experiments were carried out with white-light intetferometry to accurately measure the final diameter of drops which had been printed on different corona treated substrates and UV cured. The results are correlated to characterize the effects of corona treatment on drop impact behavior and final print quality.

Research on micro-optical lenses fabrication technology

We present a detail investigation on the development of a series of gradient index (GRIN) optical glass microlens and polymer microlens and microlens arrays in our laboratory in recent years. The special glass material GRIN lenses have been fabricated mainly by using ion-exchange technology, which are applied to construct micro-optic devices and other applications. On one hand, we demonstrated the light propagation and imaging properties of GRIN lenses and the results analyzed. On the other hand, we have explored a drop-on-demand ink-jet printing method to produce microlens array using nano-scale polymer droplets involved with a uniform ultraviolet light and heat solidifying process. The experimental setup for manufacturing polymer microlens array and the performance of refractive microlens elements are also given in this paper. (C) 2006 Elsevier GmbH. All rights reserved.

Optimal Scheduling of Secondary Content for Aggregation in Video-on-Demand Systems

Dynamic service aggregation techniques can exploit skewed access popularity patterns to reduce the costs of building interactive VoD systems. These schemes seek to cluster and merge users into single streams by bridging the temporal skew between them, thus improving server and network utilization. Rate adaptation and secondary content insertion are two such schemes. In this paper, we present and evaluate an optimal scheduling algorithm for inserting secondary content in this scenario. The algorithm runs in polynomial time, and is optimal with respect to the total bandwidth usage over the merging interval. We present constraints on content insertion which make the overall QoS of the delivered stream acceptable, and show how our algorithm can satisfy these constraints. We report simulation results which quantify the excellent gains due to content insertion. We discuss dynamic scenarios with user arrivals and interactions, and show that content insertion reduces the channel bandwidth requirement to almost half. We also discuss differentiated service techniques, such as N-VoD and premium no-advertisement service, and show how our algorithm can support these as well.

An On Demand Queue Management Architecture for a Programmable Traffic Manager

A queue manager (QM) is a core traffic management (TM) function used to provide per-flow queuing in access andmetro networks; however current designs have limited scalability. An on-demand QM (OD-QM) which is part of a new modular field-programmable gate-array (FPGA)-based TM is presented that dynamically maps active flows to the available physical resources; its scalability is derived from exploiting the observation that there are only a few hundred active flows in a high speed network. Simulations with real traffic show that it is a scalable, cost-effective approach that enhances per-flow queuing performance, thereby allowing per-flow QM without the need for extra external memory at speeds up to 10 Gbps. It utilizes 2.3%–16.3% of a Xilinx XC5VSX50t FPGA and works at 111 MHz.