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Peers and friends are among the most influential social forces affecting adolescent behavior. In this chapter, the authors investigate peer effects on post high school career decisions and on school choice. The authors define peers as students who are in the same classes and social clubs and measure peer effects as spatial dependence among them. Utilizing recent developments in spatial econometrics, the authors formalize a spatial multinomial choice model in which individuals are spatially dependent in their preferences. The authors estimate the model via pseudo maximum likelihood using data from the Texas Higher Education Opportunity Project. The authors do find that individuals are positively correlated in their career and college preferences and examine how such dependencies impact decisions directly and indirectly as peer effects are allowed to reverberate through the social network in which students reside.

This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book in the historical development of the topic area.

Bounded rationality is defined in terms of a strategy to simplify the decision-making process. Based on this definition, different models are reviewed. These models have assumed that individuals simplify the decision-making process by considering a subset of attributes, and/or a subset of choice alternatives and/or by disregarding small differences between attribute differences.

A body of empirical evidence has accumulated showing that under some circumstances the principle of bounded rationality better explains observed choices than the principle of utility maximization. Differences in predictive performance with utility-maximizing models are however small.

The chapter provides a detailed account of the different models, based on the principle of bounded rationality, that have been suggested over the years in travel behaviour analysis. The potential relevance of these models is articulated, model specifications are discussed and a selection of empirical evidence is presented. Aspects of an agenda of future research are identified.

The purpose of this paper is to develop a systemic approach to evaluate physical condition of water pipeline infrastructure with limited condition assessment data that can help asset managers prioritize capital investments in maintenance projects for urban water pipeline systems.

Spatial pattern analyses are conducted in this research to find the spatial pattern of the service life of pipelines. Based on the spatial relationship, the critical areas where groups of pipelines with short service life are likely to be found were located using spatial statistical analyses. A visualized platform was also developed and used to validate the implementation of the proposed approach with the case study of urban water pipeline infrastructure in a city in the Midwest region of the USA.

The results of the spatial pattern analyses reveal that water pipelines are spatially clustered based on their service life. Further, it was found that on average the pipelines in the center of a city have longer service life while the average expected service life of the pipelines in the marginal areas is shorter. The interpolation method produced raster data with continuous information about the service years of pipelines that are useful for asset maintenance planning.

With the limited data, the proposed approach enables identification of the critical area of water pipelines with the likelihood of shorter service life. This result can be used as a priority rule for a rehabilitation plan and contributes to shifting from a responsive to a preventive approach in underground asset management.

This study investigates whether higher catch rates near a marine protected area (MPA), and/or in other fishing areas within a choice set, attract more fishers. A survey conducted in the fishing grounds near an MPA located in south east of Mauritius in the Indian Ocean shows concentration of fishers in regions with lower catch rates. This contrasts with the predictions of the “fishing the line” hypothesis and the ideal free distribution (IFD) that fishers are likely to be attracted near the MPA with higher resource abundance.

Using the random utility model as the framework and the random parameter logit (RPL) model, the study attempts to explain spatial behaviour of fishers. Expected catch and catch variability are modelled using the Just and Pope (JP) production function. The study also estimates effort elasticities with respect to expected catch and catch variability and simulates the relocation of effort from area closure.

The paper concludes that higher catch does attract fishers but is a partial and very restrictive explanation of fishers' behaviour. The “fishing the line” hypothesis does hold to some extent, but it should not be taken for granted that rising catch rates in adjacent waters will increase fishing pressure. The paper concludes that factors such as catch variability, distance from homeport to fishing ground, potential physical risk and attitudes towards risk of fishers affect spatial behaviour of fishers and should be considered for the placement and size of MPAs. The study also finds that the responsiveness of effort to catch rates is lowest in areas which are already heavily fished and easily accessible.

The identification of fishing areas as complements (when fishing in one area increases fishing effort in another) and substitutes is valuable information for determining the placement and size of an MPA. A larger reserve is likely to have more displacement effect in this case than a smaller one. Therefore, a small or a network of a small reserve may be appropriate. The premise to select the site and size of the reserve is to avoid overconcentration of fishers in alternative fishing areas, which can be vulnerable to excessive fishing and unintended effects from fishers.

The paper contributes to an understanding of fishing behaviour and its impact on the configuration of marine reserves. It discusses the importance of effort elasticities to determine the placement and size of an MPA. Studies on this topic are very scanty in the Indian Ocean region. It also shows the application of location choice model, the RPL model and the JP production function in the fisheries sector for a small island.

Purpose – The purpose of this paper is try to answer the following question: to which extent the observed location pattern is driven by network effects or by traditional location factors, like the structure and behaviour of the local labour market, housing market, public goods, and local tax rates? Design/methodology/approach – The paper uses an econometric model derived from random utility maximization. This model is estimated on a panel of Helvetic labor market areas, using a two stages estimation method. The first stage allows the network effect to be estimated. In the second stage, it estimates the impact of standard location factors. Findings – The paper finds evidence of a very strong network effect. This network effect is a very important location factor and implies that a location may attract current immigrants mainly because it attracted previous immigrants, even if the traditional location factors are not a source of attractiveness. Research limitations/implications – The present study corroborates earlier work on the Italian case. There is still some work to be done for taking account of the highly localized nature of network externalities. Originality/value – The impact of network on migrants' behavior is a hotly debated issue. However, there is almost no analysis of this impact on migrants' location. Conversely, if the high level of concentration of immigrants is a well known stylized fact, there is almost no study of the factors explaining this concentration. The research starts filling these two gaps.