Economic impact of a supply change in mass transit in urban areas: A Canadian example

This paper aims at estimating the economic impact of a supply change in the bus transit service in a Canadian city of medium size. By using a quasi-experiment approach and a difference-in-differences (DID) estimator, it evaluates the impact of the introduction of a rapid bus transit (RBT) in Quebec City (Canada) through a spatio-temporal analysis of house price variations. The hedonic price model shows that the new service generates an increase in house price ranging from 6.9% to 2.9%, for those properties located close to the service corridor where the population is quite dense and where the service was offered initially. Using sales transaction data and municipal assessment records from 1997, the effect on price is translated into an economic impact for the whole region. The paper shows that the improvement in public transit supply generates, for Quebec City, a significant fiscal impact estimated to $6 M and a plus-value for properties owners close to $35 M over 12 years. Finally, the implications of this kind of analysis for urban planning and development are discussed.     

Correlations between industrial demands (direct and total) for communications and transportation in the U.S. economy 1947–1997

Using input–output (I–O) accounts provided by the U.S. Department of Commerce, this study investigates the aggregate relationships between the transportation and communications inputs demanded (directly and in total) by all industries in the U.S., and compares the results across time. We analyzed five pairs of Spearman correlations of transportation and communications demands (utilities, manufacturing, and overall) using the direct and total coefficient tables from the ten benchmark input–output years spanning 1947 to 1997. To correctly represent the overall economy-wide relationship, each industry (direct table) or commodity (total table) in the correlation was weighted proportionately to the monetary value of its contribution to the U.S. economy. In the analysis using direct I–O coefficients, we found a pattern of predominant complementarity between transportation and communications manufacturing, and substitution between transportation and communications utilities. There are intriguing indications, however, of a shift from substitution to complementarity in the latter case, beginning around 1987. In the analysis using total I–O coefficients, we found a pattern of complementarity for all years between transportation and communications manufacturing, and a pattern changing from substitution to complementarity for the remaining four pairs (transportation manufacturing and communications utilities; transportation utilities and communications manufacturing; the utilities pair; and the overall pair). Thus, from the industrial perspective (which constitutes a sizable proportion of the total demand for communications and transportation), it is not realistic in modern times to expect telecommunications to substitute for travel. Nevertheless, further research is needed into the specific causes of the observed shift from substitution to complementarity, and current trends should continue to be monitored for any changes.

The relationship between the built environment and nonwork travel: A case study of Northern California

Many studies have found that residents living in suburban neighborhoods drive more and walk less than their counterparts in traditional neighborhoods. This evidence supports the advocacy of smart growth strategies to alter individuals’ travel behavior. However, the observed differences in travel behavior may be more of a residential choice than a travel choice. Applying the seemingly unrelated regression approach to a sample from Northern California, we explored the relationship between the residential environment and nonwork travel frequencies by auto, transit, and walk/bicycle modes, controlling for residential self-selection. We found that residential preferences and travel attitudes (self-selection) significantly influenced tripmaking by all three modes, and also that neighborhood characteristics (the built environment and its perception) retained a separate influence on behavior after controlling for self-selection. Both preferences/attitudes and the built environment itself played a more prominent role in explaining the variation in non-motorized travel than for auto and transit travel. Taken together, our results suggest that if cities use land use policies to offer options to drive less and use transit and non-motorized modes more, many residents will tend to do so.     

A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area

This study examined the effects of land use and attitudinal characteristics on travel behavior for five diverse San Francisco Bay Area neighborhoods. First, socio-economic and neighborhood characteristics were regressed against number and proportion of trips by various modes. The best models for each measure of travel behavior confirmed that neighborhood characteristics add significant explanatory power when socio-economic differences are controlled for. Specifically, measures of residential density, public transit accessibility, mixed land use, and the presence of sidewalks are significantly associated with trip generation by mode and modal split. Second, 39 attitude statements relating to urban life were factor analyzed into eight factors: pro-environment, pro-transit, suburbanite, automotive mobility, time pressure, urban villager, TCM, and workaholic. Scores on these factors were introduced into the six best models discussed above. The relative contributions of the socio-economic, neighborhood, and attitudinal blocks of variables were assessed. While each block of variables offers some significant explanatory power to the models, the attitudinal variables explained the highest proportion of the variation in the data. The finding that attitudes are more strongly associated with travel than are land use characteristics suggests that land use policies promoting higher densities and mixtures may not alter travel demand materially unless residents' attitudes are also changed.     

Willingness to pay for improving service quality in a multimodal area

Travellers use the installations at multimodal areas to transfer from one mode of transport to another. In many cases these installations are called interchanges. This article characterises the users of transport interchanges to determine the fundamental attributes which they most value when they pass through the area. A Stated Choice survey is designed and administered and Mixed Logit models are estimated to calculate willingness to pay levels for three main attributes: transfer time, the quality of the available information and the services provided in the area. Travellers place most value on the quality of the information they receive and the available services rather than on transfer time, which contradicts the widely held opinion of experts in the field. This opens up new possibilities in the design of modern interchanges which should concentrate more on being welcoming areas with many information points rather than being based around minimising transfer times.     

Hydrographic structure and zooplankton abundance and diversity off Paita, northern Peru (1994 to 2004) — ENSO effects, trends and changes

The objective of the present study was to verify possible spatial, seasonal, and inter-annual changes in the zooplankton off Paita (northern Peru), an upwelling area located closely to the limits of cold Humboldt Current and warm Equatorial Surface Waters. Zooplankton was sampled at subsurface on 53 occasions from August 1994 to December 2004 at four stations located 2 to 30 km offshore with a WP-2 net (300 µm). Extremely high surface water temperatures combined with low salinities were observed during the 1997/98 El Niño up to 29.0 °C) and in April 2002 (up to 25.0 °C). Temperatures more than 2 °C above monthly average were also observed in October 1994, in April 2000, and in November 2004. Significant trends were observed for oxygen concentration (increase) and several horizontal and vertical gradients. Among the copepods (72% of all individuals), the most abundant species were Paracalanus parvus (28%), Acartia tonsa (26%), and Calanus sp. (10%). The strong 1997–98 El Niño (EN) event led to drastic changes in species composition that were reversed during the 1998–99 La Niña (LN) event. Community parameters such as total abundance, diversity, equitability and species richness displayed marked variations associated with the 1997–98 EN and long-term trends. Long-term trends were significant for several vertical and horizontal temperature and oxygen gradients, indicating an increase in upwelling intensity at the shelf during the study period. 10-year-trends were also significant for total zooplankton abundance (increase) and community evenness (J, decline). Our data confirmed the importance of the weak EN in 2002/03 for the study region. Within the trend of increasing zooplankton abundance, a sharp step or shift was observed from 1999 to 2000. When using sequential t-tests to detect shifts in (x + 1) transformed abundance data, a significant rupture was found between the last sampling in 1999 and the first sampling in 2000. Also, a substantial decrease in diel variability occurred after 1999, probably due to changes in vertical migration patterns. The considerable increase in zooplankton abundance over the study period, the ENSO effect, and the 1999–2000 transition are discussed with regard to synchronicity with other zooplankton time series. The present study contributes with the first evidence from an important area located in the Humboldt Current for synchronous trends and changes that were previously observed elsewhere in the Pacific. Our results demonstrated the importance of long-term zooplankton monitoring studies in upwelling areas, and confirms the idea of dramatic changes in pelagic ecosystem structure occurring in the East Pacific.     

Fuzzy logic based decision making system for collision avoidance of ocean navigation under critical collision conditions

This paper focuses on a fuzzy logic based intelligent decision making system that aims to improve the safety of marine vessels by avoiding collision situations. It can be implemented in a decision support system of an oceangoing vessel or included in the process of autonomous ocean navigation. Although Autonomous Guidance and Navigation (AGN) is meant to be an important part of future ocean navigation due to the associated cost reduction and improved maritime safety, intelligent decision making capabilities should be an integrated part of the future AGN system in order to improve autonomous ocean navigational facilities. In this study, the collision avoidance of the Target vessel with respect to the vessel domain of the Own vessel has been analyzed and input, and output fuzzy membership functions have been derived. The if–then rule based decision making process and the integrated novel fuzzy inference system are formulated and implemented on the MATLAB software platform. Simulation results are presented regarding several critical collision conditions where the Target vessel fails to take appropriate actions, as the “Give way” vessel to avoid collision situations. In these situations, the Own vessel is able to take critical actions to avoid collisions, even when being the “Stand on” vessel. Furthermore, all decision rules are formulated in accordance with the International Maritime Organization Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), 1972, to avoid conflicts that might occur during ocean navigation.     

Epilogue: the new frontiers of behavioral research on the interrelationships between ICT,activities, time use and mobility

This special issue is a product of the international symposium on “ICT, Activities, Time Use and Travel” that was hosted by Nanjing University from 16 to 18 July 2016. The symposium brought together leading scholars from all over the world to congregate with Chinese scholars and students and to share and discuss the research frontiers at this nexus. It was motivated by a recognition of the changing goals and scope of Information and Communications Technology (ICT) research in conjunction with the development of new ICTs and the emergence of new ICT-enabled behaviors. Consequently, the symposium and later this special issue have drawn together significant scholarly contributions that provide new behavioral insights as well as new theoretical and methodological advances. The symposium culminated in three roundtable panel discussions addressing the following cross-cutting themes: (1) time use while travelling (led by Glenn Lyons); (2) ICT and travel behavior (led by Pat Mokhtarian); and (3) Big Data, activities and urban space (led by Eran Ben-Elia). In this epilogue to the special issue we offer a distillation of these discussions.     

Grouping travelers on the basis of their different car and transit levels of use

Market segmentation studies in travel behavior research are ordinarily based on socioeconomic characteristics and personality traits. This study explores the usefulness of a different approach, where the actual overall mobility levels across different ground transportation modes, along with desired changes in the use of cars and transit, are used as clustering variables. Using a given mode can in fact influence the personal representation of that mode, which in turn has been proven to be a key element in transport behaviours. We form such multimodality-based clusters from two field studies, one involving employees of the French transportation research institute INRETS and the other a representative sample of residents of the US San Francisco Bay Area. We find that strong users of a given mode would like to bring more balance to their “modal consumptions” by decreasing the use of this mode more than the average, and increasing the use of the alternative mode. However, concerning ground transport travel budgets, the desire to travel more (or less) overall seems less strongly related to the composition of the modal balance. The US dataset shows also a greater latent demand for travel than the French one. Socioeconomic characteristics of the clusters could not explain the patterns that were found, confirming the importance of taking into account multimodality issues in travel behavior research. Some policy implications from these findings are finally reported.