Managing i-branding to create brand equity

Purpose: Given the emergent nature of i-branding as an academic field of study and a lack of applied research output, the aim of this paper is to explain how businesses manage i-branding to create brand equity.

Design/methodology/approach: Within a case-study approach, seven cases were developed from an initial sample of 20 food businesses. Additionally, utilising secondary data, the analysis of findings introduces relevant case examples from other industrial sectors.

Findings: Specific internet tools and their application are discussed within opportunities to create brand equity for products classified by experience, credence and search characteristics. An understanding of target customers will be critical in underpinning the selection and deployment of relevant i-branding tools. Tools facilitating interactivity – machine and personal – are particularly significant.

Research limitations/implications: Future research positioned within classification of goods constructs could provide further contributions that recognise potential moderating effects of product/service characteristics on the development of brand equity online. Future studies could also employ the i-branding conceptual framework to test its validity and develop it further as a means of explaining how i-branding can be managed to create brand equity.

Originality/value: While previous research has focused on specific aspects of i-branding, this paper utilises a conceptual framework to explain how diverse i-branding tools combine to create brand equity. The literature review integrates fragmented literature around a conceptual framework to produce a more coherent understanding of extant thinking. The location of this study within a classification of goods context proved critical to explaining how i-branding can be managed.

'Ulster's policing goes global': The police reform process in Northern Ireland and the creation of a global brand

This paper engages with contemporary discussions in relation to the commodification of policing and security. It suggests that the existing literature regarding these trends has been geared primarily towards commercial security providers and has failed to address the processes by which public policing models are commodified and marketed both within, and through, the transnational policing community. Drawing upon evidence from the police change process in Northern Ireland, we argue that a Northern Irish Policing Model (NIPM) has emerged in the aftermath of the Independent Commission on Policing (ICP) reforms. This is increasingly branded and promoted on the global stage. Furthermore, we suggest that the NIPM is not monolithic, but segmented, and targeted towards a number of different 'consumers' both domestically and transnationally. Reflecting these diverse markets, the NIPM draws upon two seemingly incongruous constituent elements: the 'best practice' lessons of policing transition, as embodied in the ICP reforms; and, the legacy of counter-terrorism expertise drawn from the preceding decades of conflict. The discussion concludes by querying as to which of these components of the NIPM is in the ascendancy.

International order flows: Explaining equity and exchange rate returns

Macroeconomic models of equity and exchange rate returns perform poorly at high frequencies. The proportion of daily returns that these models explain is essentially zero. Instead of relying on macroeconomic determinants, we model equity price and exchange rate behavior based on a concept from microstructure – order flow. The international order flows are derived from belief changes of different investor groups in a two-country setting. We obtain a structural relationship between equity returns, exchange rate returns and their relationship to home and foreign equity market order flow. To test the model we construct daily aggregate order flow data from 800 million equity trades in the U.S. and France from 1999 to 2003. Almost 60% of the daily returns in the S&P100 index are explained jointly by exchange rate returns and aggregate order flows in both markets. As predicted by the model, daily exchange rate returns and order flow into the French market have significant incremental explanatory power for the daily S&P returns. The model implications are also validated for intraday returns.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.