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• A large retrospective survey was designed to assess travel behaviors before / after a workplace relocation. • Transitions in commuter satisfaction was assessed using a multinomial logistic model. • The effect of travel modes attitudes on commuter satisfaction is confirmed, before and after a workplace relocation. • Workplace satisfaction and workplace attachment have significant impact on commuter satisfaction. • The perception of changes in travel time is an important factor in commuting satisfaction changes. • The consideration of 'activity places' proves useful in explaining the commuting satisfaction. While attention has been paid to travel satisfaction studies during the last decade, less research has investigated the relationship between the influence of a sense of place – and more particularly the psycho-environmental concepts of workplace attachment and workplace satisfaction – and commuting satisfaction. Using a retrospective survey, this paper focuses on the relocation of a workplace within the city of Montréal (Canada); the McGill University Healthcare Centre. It examines the motivations and barriers involved in the evolution of commuting characteristics, using the theoretical framework of mobility biographies. The empirical analysis includes a large dataset of independent variables, applying a multinomial logistic model in order to explain the transition of the employees' commuting satisfaction. With regard to the measurement of change in commuting satisfaction, the findings confirm the role of attitudes, while taking into account the contextual differences before and after relocation. The change in travel time is found to be an important factor in the evolution of commuter satisfaction, whereby reduced commuting time improves satisfaction, as expected. In addition, the more an employee is attached to the new workplace, the more the commuting satisfaction will increase. The results provide further evidence that the meaning of the workplace goes beyond a location or a space, and opens up new avenues for research in travel behavior. [ABSTRACT FROM AUTHOR]

COVID-19 measures implied many changes to travel behaviour and transport mode choice during the pandemic. This study seeks to understand what individual characteristics and travel attributes are related to transport mode choice before, during, and after the first lockdown in Italy. Based on an online survey (carried out in May 2020 in Milan), three multinomial regression models are presented. The results show that and in which measure parameters regarding distance and duration of daily travel are markedly related to transport mode before the lockdown. However, these factors are less significantly associated with the transport mode during and after the lockdown. Meanwhile, factors such as Preferences and Worry about using public transport have more significant relationship with the modal choice during the pandemic. Regarding individual characteristics, women are more likely to use active mode during and after the lockdown. Additionally, two personality traits of Agreeableness , and Openness to experiences are related to transport mode during and after the lockdown, respectively. Overall, this study reveals that in addition to socio-demographic factors, other variables such as worry about using public transport, preference, and personality are associated with the choice of transport mode during the lockdown. • Travel well-being is analysed by a survey carried out during Lock-down in March 2020 in Italy. • The survey was made up of three modules on socio-economical and general items, transportation and well-being subjects. • Non-linear regression models are applied to investigate the modal choice behaviour. • Results show that during the pandemic, subjective and objective factors affect differently on the choice of mobility. [ABSTRACT FROM AUTHOR]

Environmental regulation violations (ERVs) result in pollution incidents and environmental degradation. Although different types of ERVs may have specific determinants, few studies have investigated how determinants are associated with different ERV types. This paper investigates region and firm level determinants of three types of violation: unlicensed facility (UF), improper operation (IO) and excessive emission (EE), based on 629 ERV cases reported in Chongqing, China during 2011–2014. At the firm level, a 10% increase in a firm's registered capital is associated with 0.4% less probability of UF and 0.3% less for IO violations, but 0.7% more for EE. Compared with private firms, firms with sole or collective ownership or joint ownership with non-Mainland China capital reduce the probability of UF violations by 15.3% and 14.3%. Joint ownership with non-Mainland China capital increases the probability of IO by 16.1%, while whole ownership of it decreases IO probability by 26.7%. Sole or collective ownership is associated with 27.4% increase of EE violation. At the regional level, a 10% increase in resident population, industry GDP and number of enterprise are significantly associated with higher probability of UF (7.9%, 5.5% and 5.3% respectively). Increased resident population and industry GDP are associated with 7.3% and 4.3% decrease in the probability of EE, while IO violations are not related with any region level factors except number of enterprises (−6.5%). Thus both firm level and region level factors have significant impacts on type-specific violations of environmental regulations, and these results will contribute to effective environmental management practices and cleaner production. [ABSTRACT FROM AUTHOR]

Research in behavioral ecology routinely quantifies individual variation in behavior using transitions between discrete environments, for example prey moving from a no predator to predator treatment. This research often ignores behavioral variation in response to temporal fluctuations in environmental conditions around an unchanging mean environment. In this study we evaluate the effects of temporal fluctuations in predation risk (predator cue concentration of Procambarus spp.), without the confounding effects of a changing mean, on among-individual variation in anti-predator behavior in freshwater snails ( Physa acuta ). We also evaluate how the interaction between environmental and individual variation affects snail survival and reproduction by exposing snails to lethal predators following the behavioral assays. Our analyses revealed a trend towards higher among-individual variation in mean behavior when snails were exposed to intermediate levels of environmental variation compared to highly variable or constant environments. However, because of large uncertainty in estimates of among-individual variation, differences among treatments were indistinguishable from noise for most, but not all behaviors. In the lethal predator trials, snail survival and time to mortality was the lowest in the high variation environment. Also, as environmental variation increased snail egg production decreased and snails laid more of their eggs underneath a provided shelter. [ABSTRACT FROM AUTHOR]

Bicycle transportation is essential in developing a sustainable transportation system. It is important to explore factors that affect bicycle usage levels thus to help with the planning and operation of bicycle transportation systems. This paper explores the influencing factors of bicycle usage levels and their differences at residential and workplace locations, using the dock-based public bicycle sharing system of Xi'an, China. First, six levels of bicycle usage are defined based on cycling frequency, duration, and time of day. Then, five multinomial logistic models are developed to explore the influencing factors of bicycle usage and their differences at residential and workplace locations. Results showed that both the numbers and categories of influencing factors for bicycle usage levels vary with land-use patterns of residential and workplace locations. It is found that perceived cycling-friendly environment contributes a lot to high bicycle usage levels, especially for the group with low education and low monthly income. It is also found that there exists a cooperative relationship between the bicycle system and bus/metro system in some residential areas. The findings of this paper can help planners and decision-makers better understand the key influencing factors in bicycle usage behavior thus to make effective policies in planning and operating bicycle transportation systems. • Bicycle usage levels are developed based on multidimensional behavior indicators. • Perceived cycling-friendly environments are key factors of bicycle usage. • Cooperative relationship between bicycle system and bus/metro system is proved. • Policies should be formulated to ensure the equity of cycling. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we derive locally optimal designs for discrete choice experiments. As in Kanninen (2002) we consider a multinomial logistic model, which contains various qualitative attributes as well as a quantitative one, which may range over a sufficiently large interval. The derived optimal designs improve upon those given in the literature, but have the feature that every choice set contains alternatives, which coincide in all but the quantitative attributes. The multinomial logistic model will then lead to a response behavior, which is apparently unrealistic. [Copyright &y& Elsevier]

Abstract: Kuss and McLerran in a paper in this journal provide SAS code for the estimation of multinomial logistic models for correlated data. Their motivation derived from two papers that recommended to estimate such models using a Poisson likelihood, which is according to Kuss and McLerran “statistically correct but computationally inefficient”. Kuss and McLerran propose several estimating methods. Some of these are based on the fact that the multinomial model is a multivariate binary model. Subsequently a procedure proposed by Wright is exploited to fit the models. In this paper we will show that the new computation methods, based on the approach by Wright, are statistically incorrect because they do not take into account that for multinomial data a multivariate link function is needed. An alternative estimation strategy is proposed using the clustered bootstrap. [Copyright &y& Elsevier]

Abstract: The environmental, cultural and economic consequences of land use change, including abandonment of agricultural use, have been recognized for a long time. It has often been assumed that the transformations of the agricultural systems in developed countries (and particularly in Europe) took place, for the main part, in the immediate years after the Second World War. In this paper we present a review of different statistical and cartographic sources available for a peripheral region in Europe (Galicia, Spain) characterized by small-scale farming and a very fragmented property system, that suggests otherwise: modernization of agriculture apparently took place without major changes in agricultural area until the country gained access to the European Economic Community, and the effect of Common Agricultural Policy reforms during the decade of 1990 is suggested as a major driver for the net decrease of agricultural area in the region between 1956 and 2004. On the other hand, this paper emphasizes the spatial complexity of agricultural abandonment with a case study, showing a large degree of variability at municipal scale and thus the need of future EU-level projects to work at least at municipal (Local Administrative Units 2, LAU 2) level. Finally, a multinomial logistic model for observed changes is included that shows how biophysical limitations were the main drivers behind abandonment of agriculture at parcel scale, while structural qualities related to property structure were strongly associated to the incorporation of former shrublands to agricultural use. Besides, Farm Structure Surveys were revealed as an unreliable source for the assessment of changes in total agricultural area in the studied region. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the bias correction of Akaike’s information criterion (AIC) for selecting variables in multinomial logistic regression models. For simplifying a formula of the bias-corrected AIC, we calculate the bias of the AIC to a risk function through the expectations of partial derivatives of the negative log-likelihood function. As a result, we can express the bias correction term of the bias-corrected AIC with only three matrices consisting of the second, third, and fourth derivatives of the negative log-likelihood function. By conducting numerical studies, we verify that the proposed bias-corrected AIC performs better than the crude AIC. [Copyright &y& Elsevier]

Abstract: We show how multinomial logistic models with correlated responses can be estimated within SAS software. To achieve this, random effects and marginal models are introduced and the respective SAS code is given. An example data set on physicians’ recommendations and preferences in traumatic brain injury rehabilitation is used for illustration. The main motivation for this work are two recent papers that recommend estimating multinomial logistic models with correlated responses by using a Poisson likelihood which is statistically correct but computationally inefficient. [Copyright &y& Elsevier]