A brand within a brand: an integrated understanding of internal brand management and brand architecture in the public sector

Branding in the public sector is emerging as an interesting area of research, as diverse organisations find themselves using branding principles to promote a consistent, clear brand. However, very little is known how public organisations could, or should, manage their brands. The purpose of this research, therefore, is to explore brand management processes in the public sector, and its implication for brand architecture, from an employee perspective. With a qualitative approach, the study argues that branding is important not only for the organisation, but also for individual departments. Further, unlike branding in the private sector, public organisations may be more concerned with supporting a positive perception and organisational attractiveness rather than a unique and differentiated brand. This may have implications for brand architecture. By allowing individual departments to manage their brand with support from organisational structures that provide alignment and focus, organisations can form a brand architecture that supports a strong organisational brand and employee brand commitment

PREDICTING ADVERTISING EXPENDITURES USING INTENTION SURVEYS

In this article we study the use of intention surveys to predict the effects of a possible entrant. The case under investigation deals with the introduction of private broadcasting in the Netherlands. Several predictions of the advertising expenditures in various media are given which depend on a number of scenarios. These scenarios are used to reduce the discrepancies between behavioural intentions and actual behaviour. The predictions of the most realistic scenario are compared with their realizations, and the differences are analyzed. To this end the prediction error is decomposed into an intention error and a sampling error. This decomposition offers good opportunities to analyze discrepancies between intentions and actual behaviour

Consideration sets, intentions and the inclusion of "don't know" in a two-stage model for voter choice

We present a statistical model for voter choice that incorporates a consideration set stage and final vote intention stage. The first stage involves a multivariate probit (MVP) model to describe the probabilities that a candidate or a party gets considered. The second stage of the model is a multinomial probit (MNP) model for the actual choice. In both stages, we use as explanatory variables data on voter choice at the previous election, as well as sociodemographic respondent characteristics. Importantly, our model explicitly accounts for the three types of "missing data" encountered in polling. First, we include a no-vote option in the final vote intention stage. Second, the "do not know" (DNK) response is assumed to arise from too little difference in the utility between the two most preferred options in the consideration set, or is considered to be a missing observation. Third, the "do not want to say" (DNWTS) response is modeled as a missing observation on the most preferred alternative in the consideration set. Thus. we consider the missing data generating mechanism to be nonignorable and build a model based on utility maximization to describe the vote intentions of these respondents. We illustrate the merits of the model as we have information on a sample of about 5000 individuals from the Netherlands for who we know how they voted last time (if at all), which parties they would consider for the upcoming election, and what their vote intention is. A unique feature of the data set is that information is available on actual individual voting behavior, measured at the day of election. We find that the inclusion of the consideration set stage in the model enables the user to make a more precise inference on the competitive structure in the political domain and to obtain better out-of-sample forecasts. (C) 2004 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved