Identifying potential cycling market segments in Dar-es-Salaam, Tanzania

Most travel behaviour studies that seek to promote cycling define market segments based on socio-demographics, travel mode use or attitudes. They do not address the stages of change process in travel behaviour, whereas this information can be instrumental in influencing travel behaviour change. This paper adopts the stages of change model to identify potential cycling market segments and to analyse and profile each of the market segments based on socio-economic factors, current travel behaviour, attitudes, perceptions and motivations. A survey was conducted among 620 individual regular commuters in the city of Dar-es-Salaam. On the basis of cycling behaviour attitudinal-variable statements, as developed from the stages of change model, the survey data were classified in six different segments: pre-contemplation, contemplation, prepared for action, action, maintenance and relapse. The study revealed that the different segments have different needs and are motivated by different factors suggesting that they need to be treated in different ways. These market segments can have important implications for designing cycling policies and promotional strategies that best serve the needs of each segment. The results indicate that urban policies and marketing strategies which aim to promote bicycle use may first target the contemplation, prepared for action and action segments that are most motivated to change and willing to cycle.     

When Precaution Creates Misunderstandings: The Unintended Effects of Precautionary Information on Perceived Risks,the EMF Case

In the past decade, growing public concern about novel technologies with uncertain potential long‐term impacts on the environment and human health has moved risk policies toward a more precautionary approach. Focusing on mobile telephony, the effects of precautionary information on risk perception were analyzed. A pooled multinational experimental study based on a 5 × 2 × 2 factorial design was conducted in nine countries. The first factor refers to whether or not information on different types of precautionary measures was present, the second factor to the framing of the precautionary information, and the third factor to the order in which cell phones and base stations were rated by the study participants. The data analysis on the country level indicates different effects. The main hypothesis that informing about precautionary measures results in increased risk perceptions found only partial support in the data. The effects are weaker, both in terms of the effect size and the frequency of significant effects, across the various precautionary information formats used in the experiment. Nevertheless, our findings do not support the assumption that informing people about implemented precautionary measures will decrease public concerns.     

Simplified Estimating Functions for Diffusion Models with a High-dimensional Parameter

We consider estimating functions for discretely observed diffusion processes of the following type: for one part of the parameter of interest we propose to use a simple and explicit estimating function of the type studied by Kessler (2000); for the remaining part of the parameter we use a martingale estimating function. Such an approach is particularly useful in practical applications when the parameter is high-dimensional. It is also often necessary to supplement a simple estimating function by another type of estimating function because only the part of the parameter on which the invariant measure depends can be estimated by a simple estimating function. Under regularity conditions the resulting estimators are consistent and asymptotically normal. Several examples are considered in order to demonstrate the idea of the estimating procedure. The method is applied to two data sets comprising wind velocities and stock prices. In one example we also propose a general method for constructing diffusion models with a prescribed marginal distribution which have a flexible dependence structure.     

The impact of attitude strength on customer-oriented priority setting by decision-makers: An empirical investigation

A key question in marketing decision-making pertains to what makes decision-makers focus on various types of information in different ways. Particularly in relation to a key marketing and management variable such as customer satisfaction this is an important issue. Costly derived customer satisfaction measures need to provide customer-oriented guidance regarding where to prioritise. Traditional research on intelligence use has mainly focused on objective research attributes, such as research quality. In this article, however, we will adopt the idea that decision-makers weigh information differently based on their perception of its relevance. With respect to crucial customer satisfaction information this represents an exciting, but nevertheless unexplored field of research. The results of latent variable modelling show that the strength of decision-makers’ attitudes toward customer satisfaction leads to a differentiated usage of satisfaction intelligence. By taking this into consideration, management and intelligence providers will be able to more effectively disseminate customer satisfaction information and facilitate a more customer-oriented perspective within firms.     

A Hausman test for Brownian motion

New tests are proposed for the specification of the intraday price process of a risky asset, based on open, high, low, and close prices. Under the null of a Brownian process we derive two stochastically independent, unbiased volatility estimators. For a Hausman specification test we prove its equivalence with an F-test, consider its robustness against variation in drift and volatility, and analyze the power against an Ornstein–Uhlenbeck process, as well as a random walk with alternative distributions.     

Growth Fetish

Clive Hamilton, Pluto Press, London, 262 pp., ISBN 0 7453 22514 (hb), 0 7543 2250 6 (pb) Hamilton has an ambitious agenda: not simply a critique of theenvironmental and other dangers that come with the myopic pursuitof growth above all else but a new agenda to mobilize what hesees as a politically moribund left. Hamilton takes effectiveaim at the vacuities of the Third Way and     

Environmental assessment in forestry: the initial experience

This study analyses the effectiveness of the European Community's Environmental Assessment Directive of 1985 in its application in the U.K. forestry sector. It assesses the applicability of the regulations in the provision of the public and private outputs of forestry. The environmental assessment regulation may contribute to the provision of the optimal amount of these public and private goods in theory, but it is concluded that, in common with initial results of the environmental assessment process in other sectors, the regulations do not make this contribution in practice in the forestry sector. The main deficiencies of the environmental statements examined were the failure to identify the significant potential impacts; to present alternative project sites and design features; and the erroneous measure of particular externalities. The environmental assessment process was also found to be unsatisfactory in the lack of public accessibility and consultation. The need for revision of the process in the forestry sector is highlighted.     

Morbidity measures in the presence of recurrent composite endpoints

The analysis of recurrent event data in clinical trials presents a number of difficulties. The statistician is faced with issues of event dependency, composite endpoints, unbalanced follow‐up times and informative dropout. It is not unusual, therefore, for statisticians charged with responsibility for providing reliable and valid analyses to need to derive new methods specific to the clinical indication under investigation. One method is proposed that appears to have possible advantages over those that are often used in the analysis of recurrent event data in clinical trials. Based on an approach that counts periods of time with events instead of single event counts, the proposed method makes an adjustment for patient time on study and incorporates heterogeneity by estimating an individual per‐patient risk of experiencing a morbid event. Monte Carlo simulations demonstrate that, with use of a real clinical study data, the proposed method consistently outperforms other measures of morbidity. Copyright © 2003 John Wiley & Sons, Ltd.