Coastal Livelihood Diversification as a Pathway Out of Poverty and Vulnerability: Experiences from Tanzania

Livelihood diversification can increase the number of activities generating income and is often adopted as a means to reduce vulnerability to risk and provide a pathway out of poverty. Previous empirical studies, however, have found that this diversification carries no guarantee of success. This study examines the impacts of investments in conservation-based enterprises and micro-credit interventions implemented in coastal Tanzania. Project beneficiaries (n = 178) and non-beneficiaries (n = 117) from seventeen communities surrounding Saadani National Park and the Menai Bay Conservation area were surveyed in 2013, to gather quantitative and qualitative data on a suite of parameters including the number of livelihood activities, total annual income, and engagement in extractive activities. We found that the beneficiaries reported an average of 2.15 livelihoods, which was significantly higher than the 1.44 average reported by the non-beneficiaries. The beneficiaries also had significantly higher mean annual incomes than the non-beneficiaries as the former reported an annual mean income of US $2,076 while the latter reported US $646. The research found a complex relationship between occupational diversity and people's interactions with the environment and it is clear that livelihood diversification is not a blanket solution to reducing pressure on coastal resources. Another important finding from the research is that there are distinct differences between types of livelihood interventions and it is crucial to be clear about the goal of a livelihoods intervention. If the goal is diversifying livelihoods and strengthening resilience, then livelihoods that provide a small and steady income for many entrepreneurs may be enough. However, if the goal is to bring people out of a poverty trap, then it makes more sense to invest in livelihoods that bring in a higher income, even if that means reaching fewer beneficiaries.     

On the role of bridges as anchor points in route choice modeling

This work builds upon the thought that individuals allocate higher levels of importance to some particular features of the route, so called anchor points. Previous route choice models have either ignored the effects of anchor points (route-based models), or have given an exclusive attention to their effects and ignored the behavioral accuracy and practicality of these models (anchor-based models). In this work we argue that the consideration of both route-level attributes and anchor points would enhance the behavioral aspect of route choice models as well as their estimation and prediction abilities. Global Positioning System traces have been used to investigate the effect of bridges as anchor points for trips between Montreal and its Northern suburb, Laval. A classic Nested Logit and a nested Logit Kernel model have been estimated, in which interdependencies among routes crossing the same bridge are captured through the nested structure and the adopted factor analytic approach, respectively. A Metropolis–Hastings path-sampling algorithm is applied, for the first time, on a large road network with more than 40,000 nodes and 19,000 links to provide the consideration choice set. Estimates are then compared to three alternate models, representing route-based and anchor-based formulations; namely Path-Size Logit, Extended Path-Size Logit, and Independent Availability Logit models. Empirical results showed that the proposed nested structures with MH sampling provide better estimates and also perform better in the validation step with respect to comparative models. Findings underscore the importance of considering anchor points in conjunction with route level attributes in route choice decisions.     

Integrating parking behaviour in activity-based travel demand modelling: Investigation of the relationship between parking type choice and activity scheduling process

Traditionally, the parking choice/option is considered to be an important factor in only in the mode choice component of a four-stage travel demand modelling system. However, travel demand modelling has been undergoing a paradigm shift from the traditional trip-based approach to an activity-based approach. The activity-based approach is intended to capture the influences of different policy variables at various stages of activity-travel decision making processes. Parking is a key policy variable that captures land use and transportation interactions in urban areas. It is important that the influences of parking choice on activity scheduling behaviour be identified fully. This paper investigates this issue using a sample data set collected in Montreal, Canada. Parking type choice and activity scheduling decision (start time choice) are modelled jointly in order to identify the effects of parking type choice on activity scheduling behaviour. Empirical investigation gives strong evidence that parking type choice influences activity scheduling process. The empirical findings of this investigation challenge the validity of the traditional conception which considers parking choice as exogenous variable only in the mode choice component of travel demand models.     

Using structural equations modeling to unravel the influence of land use patterns on travel behavior of workers in Montreal

This paper addresses the relations between travel behavior and land use patterns using a Structural Equations Modeling (SEM) framework. The proposed model structure draws on two earlier models developed for Lisbon and Seattle which show significant effects of land use patterns on travel behavior. The travel behavior variables included here are multifaceted including commuting distance, car ownership, the amount of mobility by mode (car, transit and non-motorized modes), both in terms of total kilometers travelled and number of trips. The model also includes a travel scheduling variable, which is the total time spent between the first and last trips to reflect daily constraints in time allocation and travel.The modeled land use variables measure the levels of urban concentration and density, diversity, both in terms of types of uses and the mix between jobs and inhabitants/residents, the transport supply levels, transit and road infrastructure, and accessibility indicators. The land use patterns are described both at the residence and employment zones of each individual included in the model by using a factor analysis technique as a data reduction and multicollinearity elimination technique. In order to explicitly account for self selection bias the land use variables are explicitly modeled as functions of socioeconomic attributes of individuals and their households.The results obtained show that people with different socioeconomic characteristics tend to work and live in places of substantially different urban environments. But besides these socioeconomic self-selection effects, land use variables significantly affect travel behavior. More precisely the effects of land use are in great part passed thru variables describing long term decisions like commuting distance, and car ownership. These results point to similar conclusions from the models developed for Lisbon and Seattle and thus give weight to the use of land use policies as tools for changing travel behavior.     

Integrated Coastal Management in the Philippines: Testing New Paradigms

With fisheries declining, coral reefs battered, mangrove forests under threat, pollution levels rising, and coastal communities experiencing increased poverty, the Philippines faces severe challenges in managing its coastal resources. Coastal management efforts began in the Philippines more than 20 years ago through various community-based projects. Now, integrated coastal management is expanding in the country and holds the potential to reverse the trends. This article analyzes the situation in relation to new approaches for coastal management being undertaken through the Coastal Resource Management Project supported by the United States Agency for International Development implemented by the Department of Environment and Natural Resources. This project, drawing on the lessons generated by past and ongoing coastal management initiatives, is emphasizing integrated approaches to management over narrowly focused fisheries management and habitat protection efforts. It highlights the increasingly important role of local governments and the changing roles of national government to effectively support integrated coastal management. Multisectoral collaboration is explained as standard procedure to achieve outcomes that are broad based and sustainable. Local and national level activities are contrasted and shown as essential complements in building institutionalization of resources management within all levels of government. A practical result framework is explained for measuring relative success at the local government level of implementing best practices for coastal management. Finally, lessons being learned related to collaboration, level of focus, education, and communication; who is responsible; and expansion of the project are highlighted.     

A time-use investigation of shopping participation in three Canadian cities: is there evidence of social exclusion?

Increasing awareness and concern about the status of mobility-disadvantaged groups in society has given rise to a wide body of research that focuses on the social exclusion dimension of transportation. To date, much of the empirical work on this topic is mainly spatial in nature despite recent developments that call for the inclusion of time use analyses in social exclusion research. In this paper we attempt to fill this gap by estimating activity and trip durations to determine whether poverty, old age, or being a single parent results in time use patterns indicative of exclusion. Given the importance of shopping and using services for social inclusion objectives, these activities are the focus of this investigation. In terms of methods, use of a multiple equation approach allows for the estimation of the daily duration of shopping activities and trips while simultaneously controlling for daily durations of four broad categories of activities as well as their associated travel times. The results indicate: that being a senior citizen increases travel durations while decreasing shopping activity durations; that coming from a low income household decreases shopping activity durations; and single-parent status does not impact shopping activity durations when holding income and other activity durations constant. These results highlight the feasibility and challenges of time-use and activity analysis in social exclusion research.