Conceptualising and measuring the equity of online brands

Although brand equity is an important source of competitive advantage online, previous conceptualisations and measures overlook the unique characteristics of the internet that render consumers co-creators of brand value. In view of this, a threephased research programme was undertaken to identify the facets of online retail/service (ORS) brand equity and then develop and validate a scale for its measurement. ORS brand equity was found to be a second order construct with five correlated yet distinct dimensions: emotional connection, online experience, responsive service nature, trust, and fulfilment. A series of tests showed that the ensuing 12-item scale has strong psychometric properties. The implications of this research for marketing researchers and practitioners are discussed.

Taking the brand promise online: challenges and opportunities

Starting from the fact that a 'brand' is a universal concept regardless of environment, but its enactment changes according to environment, this paper provides pointers about brand building on the internet. It presents a three-level model of a brand to help organisations characterise their brands' promises. By expanding this model it then considers how a brand's promise can be enacted on the internet in order to assess the coherence of the brand. Through considering how some organisations have taken advantage of the internet, it highlights three factors critical for success. Ten key action points for marketers are presented.

A tutorial on pseudospectral methods for computational optimal control

[English] This paper is a tutorial introduction to pseudospectral optimal control. With pseudospectral methods, a function is approximated as a linear combination of smooth basis functions, which are often chosen to be Legendre or Chebyshev polynomials. Collocation of the differential-algebraic equations is performed at orthogonal collocation points, which are selected to yield interpolation of high accuracy. Pseudospectral methods directly discretize the original optimal control problem to recast it into a nonlinear programming format. A numerical optimizer is then employed to find approximate local optimal solutions. The paper also briefly describes the functionality and implementation of PSOPT, an open source software package written in C++ that employs pseudospectral discretization methods to solve multi-phase optimal control problems. The software implements the Legendre and Chebyshev pseudospectral methods, and it has useful features such as automatic differentiation, sparsity detection, and automatic scaling. The use of pseudospectral methods is illustrated in two problems taken from the literature on computational optimal control. [Portuguese] Este artigo e um tutorial introdutorio sobre controle otimo pseudo-espectral. Em metodos pseudo-espectrais, uma funcao e aproximada como uma combinacao linear de funcoes de base suaves, tipicamente escolhidas como polinomios de Legendre ou Chebyshev. A colocacao de equacoes algebrico-diferenciais e realizada em pontos de colocacao ortogonal, que sao selecionados de modo a minimizar o erro de interpolacao. Metodos pseudoespectrais discretizam o problema de controle otimo original de modo a converte-lo em um problema de programa cao nao-linear. Um otimizador numerico e entao empregado para obter solucoes localmente otimas. Este artigo tambem descreve sucintamente a funcionalidade e a implementacao de um pacote computacional de codigo aberto escrito em C++ chamado PSOPT. Tal pacote emprega metodos de discretizacao pseudo-spectrais para resolver problemas de controle otimo com multiplas fase. O PSOPT permite a utilizacao de metodos de Legendre ou Chebyshev, e possui caractersticas uteis tais como diferenciacao automatica, deteccao de esparsidade e escalonamento automatico. O uso de metodos pseudo-espectrais e ilustrado em dois problemas retirados da literatura de controle otimo computacional.

Online customer experience in e-retailing: an empirical model of antecedents and outcomes

The theoretical understanding of online shopping behavior has received much attention. Less focus has been given to the formation of the customer experience (CE) that results from online shopper interactions with e-retailers. This study develops and empirically tests a model of the relationship between antecedents and outcomes of online customer experience (OCE) within Internet shopping websites using an international sample. The study identifies and provides operational measures of these variables plus the cognitive and affective components of OCE. The paper makes contributions towards new knowledge and understanding of how e-

Guiding e-learning: introducing online informal learning to a global voluntary organisation

The World Association of Girl Guides and Girl Scouts (WAGGGS) is the umbrella organisation for Member Organisations from 145 countries around the world, with a total membership of ten million. While Member Organisations offer training and development within their own countries, WAGGGS offers international opportunities. This project seeks to explore how technology can be used to offer similar opportunities to those provided by the face-to-face courses to a much wider audience, while retaining the community and interactive learning aspects of the existing programmes.

Online modeling with tunable RBF network

In this paper, we propose a novel online modeling algorithm for nonlinear and nonstationary systems using a radial basis function (RBF) neural network with a fixed number of hidden nodes. Each of the RBF basis functions has a tunable center vector and an adjustable diagonal covariance matrix. A multi-innovation recursive least square (MRLS) algorithm is applied to update the weights of RBF online, while the modeling performance is monitored. When the modeling residual of the RBF network becomes large in spite of the weight adaptation, a node identified as insignificant is replaced with a new node, for which the tunable center vector and diagonal covariance matrix are optimized using the quantum particle swarm optimization (QPSO) algorithm. The major contribution is to combine the MRLS weight adaptation and QPSO node structure optimization in an innovative way so that it can track well the local characteristic in the nonstationary system with a very sparse model. Simulation results show that the proposed algorithm has significantly better performance than existing approaches.