Warranty servicing strategies to improve customer satisfaction

Customer satisfaction with a purchased product depends on its performance under warranty and during the remainder of its useful life. Dissatisfaction with an item is important to a manufacturer since it can lead to the loss of potential customers through the negative word-of-mouth effect as well as existing customers switching to a competitor. In this paper, we define satisfaction in terms of the likelihood of a customer not switching to a different manufacturer when a new item needs to be purchased. Manufacturers can use specific servicing strategies to reduce warranty costs and this topic has already been addressed in the literature without considering the effect of customer dissatisfaction. In this paper, we propose particular strategies that will increase customer satisfaction and we discuss methods for obtaining the optimal parameters of these strategies.

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

The use of unwrapped phase in MR image segmentation: A preliminary study

This paper considers the problem of tissue classification in 3D MRI. More specifically, a new set of texture features, based on phase information, is used to perform the segmentation of the bones of the knee. The phase information provides a very good discrimination between the bone and the surrounding tissues, but is usually not used due to phase unwrapping problems. We present a method to extract textural information from the phase that does not require phase unwrapping. The textural information extracted from the magnitude and the phase can be combined to perform tissue classification, and used to initialise an active shape model, leading to a more precise segmentation.

Does customer satisfaction lead to improved brand equity? An empirical examination of two categories of retail brands

Purpose – The objective of the present research is to examine the relationship between consumers' satisfaction with a retailer and the equity they associate with the retail brand. Design/methodology/approach – Retail brand equity is conceptualized as a four-dimensional construct comprising: retailer awareness, retailer associations, retailer perceived quality, and retailer loyalty. Then the associative network memory model is applied from cognitive psychology to the specific context of the relationships between customer satisfaction and consumer-based retailer equity. A survey was undertaken using a convenience sample of shopping mall consumers in an Australian state capital city. The questionnaire used to collect data included an experimental design such that two categories of retailers were included in the study: department stores and specialty stores, with three retailers representing each category. The relationship between consumer-based retailer equity and customer satisfaction was examined using multivariate analysis of variance. Findings – Results indicate that retail brand equity varies with customer satisfaction. For department stores, each consumer-based retailer equity dimension varied according to customer satisfaction with the retailer. However, for specialty stores, only three of the consumer-based retailer equity dimensions, namely retailer awareness, retailer associations and retailer perceived quality, varied according to customer satisfaction level with the retailer. Originality/value – The principal contribution of the present research is that it demonstrates empirically a positive relationship between customer satisfaction and an intangible asset such as retailer equity.

Introducing employee social identification to customer satisfaction research: a hotel industry study

The purpose of this paper is to address the concept of linkage research and propose the addition of social identity theory as an important consideration in managing employee-customer interactions and customer satisfaction.

A fuzzy approach to texture segmentation

The texture segmentation techniques are diversified by the existence of several approaches. In this paper, we propose fuzzy features for the segmentation of texture image. For this purpose, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors such as maximum, entropy, and energy for each window. To segment the texture image, the modified mountain clustering that is unsupervised and fuzzy c-means clustering have been used. The performance of the proposed features is compared with that of fractal features.

Automatic texture segmentation for texture-based image retrieval

Texture-segmentation is the crucial initial step for texture-based image retrieval. Texture is the main difficulty faced to a segmentation method. Many image segmentation algorithms either can’t handle texture properly or can’t obtain texture features directly during segmentation which can be used for retrieval purpose. This paper describes an automatic texture segmentation algorithm based on a set of features derived from wavelet domain, which are effective in texture description for retrieval purpose. Simulation results show that the proposed algorithm can efficiently capture the textured regions in arbitrary images, with the features of each region extracted as well. The features of each textured region can be directly used to index image database with applications as texture-based image retrieval.