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To provide insight into the role and design of delivery services to address CO₂, NO _x , and PM₁₀ emissions from passenger travel.

A simulated North American data sample is served with three transportation structures: last-mile personal vehicles, local-depot-based truck delivery, and regional-warehouse-based truck delivery. CO₂, NO _x , and PM₁₀ emissions are modeled using values from the US EPA’s MOVES model and are added to an ArcGIS optimization scheme.

Local-depot-based truck delivery requires the lowest amount of vehicle miles traveled (VMT), and last-mile passenger travel generates the lowest levels of CO₂, NO _x , and PM₁₀. While last-mile passenger travel requires the highest amount of VMT, the efficiency gains of the delivery services are not large enough to offset the higher pollution rate of the delivery vehicle as compared to personal vehicles.

This research illustrates the clear role delivery structure and logistics have in impacting the CO₂, NO _x , and PM₁₀ emissions of goods transportation in North America.

This research illustrates tension between goals to reduce congestion (via VMT reduction) and CO₂, NO _x , and PM₁₀ emissions.

This chapter provides additional insight into the role of warehouse location in achieving sustainability targets and provides a novel comparison between delivery and personal travel for criteria pollutants.

There is significant amount of literature tackling different issues related to the port industry. The present chapter focuses on a single business unit of seaports aiming at the documentation of works related to container terminals.

An effort to review, collect and present the majority of the works present in the last 30 years, between 1980 and 2010, has been made in order to picture the problems dealt and methods used by the authors in the specific research field. To facilitate the reader, studies have been grouped under five categories of addressed problems (productivity and competitiveness, yard and equipment utilization, equipment scheduling, berth planning, loading/unloading) and four modelling methodologies (mathematics and operations research, management and economics, simulation, stochastic modelling).

The analysis shows that most works focus on productivity and competitiveness issues followed by yard and equipment utilisation and equipment scheduling. In reference to the methodologies used managerial and economic approaches lead, followed by mathematics and operations research.

In reference to future research, two fields have been identified where there is scope of significant contribution by the academic community: container terminal security and container terminal supply chain integration.

The present chapter provides the framework for researchers in the field of port container terminals to picture the so far works in this research area and enables the identification of gaps at both research question and methodology level for further research.

Purpose – Departure time choice not only depends on the desire to carry out activities at certain times and places; it is a complex decision making process influenced by travel conditions, congestion levels, activity schedules, and external trip factors. To estimate departure time choice models capturing the factors influencing it in appropriate form, a complex data collection procedure allowing to obtain detailed input data from different sources and at different time periods is required.

The main aim of this chapter is to describe and discuss the survey methodology we used in a time-of-day choice project, involving the collection of revealed preference (RP) and stated preference (SP) data to estimate hybrid discrete departure time choice models incorporating latent variables. Preliminary model results are also presented as an example.

Methodology/approach – Data was obtained from 405 workers at different private and public institutions located in the centre of Santiago, Chile. The survey process had three different stages and used various collection methods (e-mail, web-page, and personal interviews at the workplace) in order to satisfy efficiency, reliability and cost criteria.

The RP component survey design was based on the last origin-destination survey implemented in Santiago (i.e. a travel diary filled under an activity recall framework). Relevant level-of-service measures at different time periods were obtained from GPS data measured from instrumented vehicles in the public and private transport networks. A SP-off-RP optimal design considering dependence among attribute levels was also developed. Finally, several 1–7 Likert scale questions were included to incorporate the latent variables.

Findings – The survey methodology described in this chapter represents a successful experience in terms of collecting high quality data, from different sources, with the aim of estimating appropriate time-of-day choice models. The data collection process was carried out in different stages, by means of web pages, email, and personal interviews. The data was further enriched with level-of-service attributes measured at different times of the day with unusual precision. Preliminary results reported in this chapter show that data obtained through this methodology are appropriate to model time-of-day choices.

Originality/value of chapter – The novelty of the survey methodology described in this chapter is the collection of data of a different nature for time-of-day choice modelling through the integration of different collection techniques.

Acquisition of very precise information about preferred departure/arrival times, level of service at different times of the day, detailed information about flexibility in schedules, employment information and attitudes towards departure times, should allow practitioners to estimate hybrid time-of-day choice models incorporating latent variables.

Computer corpus linguistics (CCL) is a scientific innovation that has facilitated the creation and analysis of large corpora in a systematic way by means of computer technology since the 1950s. This article provides an account of the CCL pioneers in general but particularly of those in Germany, the Netherlands, Sweden, and Switzerland. It is found that Germany and Sweden, due to more advantageous financing and weaker communities of generativists, had a faster adoption of CCL than the other two countries. A particular late adopter among the four was Switzerland, which did not take up CCL until foreign professors had been recruited.

The study assesses the significance of environmental uncertainty and its effects on fishing strategies of small-scale fishermen in Ende, Flores, Indonesia. Periodic environmental cycles such as the moon phase can have important effects on fishing strategies by regulating the behavior of stocks and tides. Traditional lunar calendars are used by subsistence fishermen to decide when and where to go fishing. Environmental uncertainty, specifically unprecedented changes in oceanographic and atmospheric conditions, is threatening the predictability of traditional systems of ecological knowledge.

Methods included ethnographic and observational techniques. Interviews (n = 58) and surveys (n = 132) are qualitatively and quantitatively analyzed. A combination of standard statistical tests, multilevel models, and cluster analysis is applied to long-term repeated observations of fishing events (n = 2,633).

Endenese fishermen emphasized the importance of the traditional lunar calendar to allocate their effort in interviews and surveys. This belief does not coincide with observed behavior. Contrary to expectations from the traditional calendar, the lowest probability of fishing happens in the intermediate phases, with fishing also occurring during the full moon. Differences between individuals play an important role in explaining variability in returns. Finally, based on the consideration of variability, three different fishing strategies are identified that suggest an effect of environmental uncertainty in effort regulation.

The paper underlines the importance of studies of variability to identify behavioral flexibility and adaptation. Results emphasize the value of considering individual traits in the analysis of subsistence practices.

Economic globalization is leading large companies to focus on international strategic management. Nowadays, the assets referred to as “corporate intangibles,” such as corporate reputation, are becoming increasingly important because they are considered a key factor for the viability of an organization, and companies therefore need to incorporate them into their scorecards for management. The problem is that their measurement is subjective and latent. These two characteristics impede direct international comparison and require demonstrating the accuracy of comparison via a minimum of two tests – construct equivalence and metric equivalence. As regards corporate reputation, construct equivalence was verified by Naomi Gardberg (2006). However, the subsequent studies did not address metric equivalence. Based on the results of a survey provided by the Reputation Institute (n = 5,950, 50 firms evaluated in 17 countries in the Americas, Europe, Asia and Australia), the degree of RepTrak metric equivalence has been tested, using two different methodologies, multigroup analysis (structural equation model), and a new technique from 2016, the Measurement Invariance of Composite Model procedure from the Partial Least Square Path Modeling family. As one would expect from other cross-cultural studies, reputation metrics do not meet the full metric equivalence, which is why they require standardization processes to ensure international comparability. Both methodologies have identified the same correction parameters, which have allowed validation of the mean and variance of response style by country.