Understanding service failure and recovery: A customer-based phenomenographic approach

To date, researchers have largely considered service failure and recovery as a combination of individual constructs, often in isolation, rather than viewing failure and recovery holistically. Consequently, our understanding is fragmented. Furthermore, while some attempt has been made to gain a better understanding of service failure and recovery from both the customer and the employee’s perspective (cf. Bitner et al.1990; McColl-Kennedy and Sparks 2003), no study has employed an interpretative perspective that potentially offers a rich, in-depth approach to this important area of research. Given this gap, our paper presents the value of taking a customer-based interpretive approach to obtaining a fuller understanding of the way customers view service failure and recovery. In this paper we report the findings of our phenomenography study of twenty in-depth interviews. Not only do we argue the benefits of adopting this fresh approach to studying service failure and recovery, we also present an innovative conceptual framework derived from our phenomenographic research findings, which has significant theoretical and practical implications.

Training Bayesian networks for image segmentation

We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task.

Dynamical local models for segmentation and prediction of financial time series

In the analysis and prediction of many real-world time series, the assumption of stationarity is not valid. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly appropriate for financial markets. We introduce a new model which combines a dynamic switching (controlled by a hidden Markov model) and a non-linear dynamical system. We show how to train this hybrid model in a maximum likelihood approach and evaluate its performance on both synthetic and financial data.

A generative probabilistic oriented wavelet model for texture segmentation

This Letter addresses image segmentation via a generative model approach. A Bayesian network (BNT) in the space of dyadic wavelet transform coefficients is introduced to model texture images. The model is similar to a Hidden Markov model (HMM), but with non-stationary transitive conditional probability distributions. It is composed of discrete hidden variables and observable Gaussian outputs for wavelet coefficients. In particular, the Gabor wavelet transform is considered. The introduced model is compared with the simplest joint Gaussian probabilistic model for Gabor wavelet coefficients for several textures from the Brodatz album [1]. The comparison is based on cross-validation and includes probabilistic model ensembles instead of single models. In addition, the robustness of the models to cope with additive Gaussian noise is investigated. We further study the feasibility of the introduced generative model for image segmentation in the novelty detection framework [2]. Two examples are considered: (i) sea surface pollution detection from intensity images and (ii) image segmentation of the still images with varying illumination across the scene.

The role of oscillatory brain activity in object processing and figure-ground segmentation in human vision

The perception of an object as a single entity within a visual scene requires that its features are bound together and segregated from the background and/or other objects. Here, we used magnetoencephalography (MEG) to assess the hypothesis that coherent percepts may arise from the synchronized high frequency (gamma) activity between neurons that code features of the same object. We also assessed the role of low frequency (alpha, beta) activity in object processing. The target stimulus (i.e. object) was a small patch of a concentric grating of 3c/°, viewed eccentrically. The background stimulus was either a blank field or a concentric grating of 3c/° periodicity, viewed centrally. With patterned backgrounds, the target stimulus emerged--through rotation about its own centre--as a circular subsection of the background. Data were acquired using a 275-channel whole-head MEG system and analyzed using Synthetic Aperture Magnetometry (SAM), which allows one to generate images of task-related cortical oscillatory power changes within specific frequency bands. Significant oscillatory activity across a broad range of frequencies was evident at the V1/V2 border, and subsequent analyses were based on a virtual electrode at this location. When the target was presented in isolation, we observed that: (i) contralateral stimulation yielded a sustained power increase in gamma activity; and (ii) both contra- and ipsilateral stimulation yielded near identical transient power changes in alpha (and beta) activity. When the target was presented against a patterned background, we observed that: (i) contralateral stimulation yielded an increase in high-gamma (>55 Hz) power together with a decrease in low-gamma (40-55 Hz) power; and (ii) both contra- and ipsilateral stimulation yielded a transient decrease in alpha (and beta) activity, though the reduction tended to be greatest for contralateral stimulation. The opposing power changes across different regions of the gamma spectrum with 'figure/ground' stimulation suggest a possible dual role for gamma rhythms in visual object coding, and provide general support of the binding-by-synchronization hypothesis. As the power changes in alpha and beta activity were largely independent of the spatial location of the target, however, we conclude that their role in object processing may relate principally to changes in visual attention.

Enhancing performance through the introduction of customer orientation into the building components industry

Purpose: This paper aims to describe an investigation into how company performance can be improved by integrating internal and external customers and technology. The approach was developed, implemented and evaluated in the operations of the building components industry. The research was carried out in the precast concrete division of a Singapore company. Design/methodology/ approach: For the purpose of undertaking the investigation an exploratory case study approach was used. This was divided into conceptual and action research stages. The action research was also used to implement the changes in the company. Questionnaire surveys were carried out among company employees and external customers to assess the effect of these changes. Results of the investigation were derived using content and statistical analysis. Triangulation between three sources was used for validating the data. Findings: The exploratory case study strategy resulted in rich research data, which provided evidence of the changes taking place and integration happening, leading to improved performance. The action research approach proved a powerful tool where the uncertainty of outcomes makes it near impossible to make accurate forecasts. Another output of the research was the development of an "integrated customer orientation" (ICO) model. Research limitations/implications: The research in this paper used a single site action research investigation so should be interpreted within the specific company and industry context. There are implications for theory and practice in a number of areas of production and marketing as well as contributions to understanding about productivity improvement and organisational development. The investigation also fulfils the dual objectives of action research by contributing to both knowledge and practice. Originality/value: The paper describes a unique approach towards improving productivity, quality and service through the use of action research to implement changes, as well as providing the research evidence to evaluate both the process of implementation and results achieved. © Emerald Group Publishing Limited.

Testing for market segmentation in the A and B share markets of China

Recent research has suggested that the A and B share markets of China may be informationally segmented. In this paper volatility patterns in the A and B share market are studied to establish whether volatility changes to the A and B share markets are synchronous. A consequence of new information, when investors act upon it is that volatility rises. This means that if the A and B markets are perfectly integrated volatility changes to each market would be expected to occur at the same time. However, if they are segmented there is no reason for volatility changes to occur on the same day. Using the iterative cumulative sum of squares across the different markets. Evidence is found of integration between the two A share markets but not between the A and B markets. © 2005 Taylor & Francis Group Ltd.

Applications of the behavioural homogeneity evaluation framework: the predictive ability of consumer involvement for international food market segmentation

This article proposes a framework of alternative international marketing strategies, based on the evaluation of intra- and inter-cultural behavioural homogeneity for market segmentation. The framework developed in this study provides a generic structure to behavioural homogeneity, proposing consumer involvement as a construct with unique predictive ability for international marketing strategy decisions. A model-based segmentation process, using structural equation models, is implemented to illustrate the application of the framework.

The behavioural homogeneity evaluation framework:Multi-level evaluations of consumer involvement in international segmentation

This paper presents a generic strategic framework of alternative international marketing strategies and market segmentation based on intra- and inter-cultural behavioural homogeneity. Consumer involvement (CI) is proposed as a pivotal construct to capture behavioural homogeneity, for the identification of market segments. Results from a five-country study demonstrate how the strategic framework can be valuable in managerial decision-making. First, there is evidence for the cultural invariance of the measurement of CI, allowing a true comparison of inter- and intra-cultural behavioural homogeneity. Second, CI influences purchase behaviour, and its evaluation provides a rich source of information for responsive market segmentation. Finally, a decomposition of behavioural variance suggests that national-cultural environment and nationally transcendent variables explain differences in behaviour. The Behavioural Homogeneity Evaluation Framework therefore suggests appropriate international marketing strategies, providing practical guidance for implementing involvement-contingent strategies. © 2007 Academy of International Business. All rights reserved.

Innovation in healthcare services: a customer focused approach

Although the various tools and techniques of quality management are routinely deployed in order to improve healthcare quality, an integrated approach is lacking, which combines the customer focus to identify quality issues, analytical techniques for prioritising improvement measures and a project management approach to plan, implement and evaluate the improvement projects. This study develops an innovative framework using Quality Function Deployment (QFD) and a logical framework in order to address this issue, and demonstrates its effectiveness using a case study on the intensive care unit of a hospital.

Optimization of facility location-allocation problem in customer-driven supply chain

This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

Trade-offs in customer-employee focus:Implications on boundary-spanning capabilities

In pursuing their particular strategic goals, organisations place differential emphasis in their activities on employees and customers. Those who focus predominantly on employees see them as key resources contributing to successful achievement of goals, while those who focus on customers believe that customer commitment is the prime source of financial prosperity and competitive advantage. In all firms, there is potential for conflict and subsequent trade-offs in the emphasis placed on employee resources and customers. This paper investigates the implications of these potential trade-offs on firms' boundary-spanning capabilities (those capabilities that enable firms to interact effectively with their customers, their suppliers, their strategic allies and others in their business networks) in European and Australasian markets. The results suggest that those companies which achieve a strong but balanced focus on both employees and customers have heightened boundary-spanning capabilities. The comparison between UK and Australian businesses indicates that the balance is more highly developed in Australasian than European (UK) markets. © 2004 by The Haworth Press, Inc. All rights reserved.