Abstract
Promoting active modes of transport, such as walking and cycling, has a positive impact on environmental sustainability and the health and well-being of citizens. This study explores the elderly population’s perception of comfort, safety and security when using active modes of transport. It begins with a systematic review of the literature considering research works that relate to active travel, the elderly population, and random forest. Then a questionnaire was applied to 653 participants and the results were analyzed. This analysis consisted of using statistics to evaluate the socio-demographic profile, the preferences regarding the use of active modes of this population, and the importance given to each dimension: comfort, safety, distance, and time, comparing these indicators through the Wilcoxon Rank Sum test and the Random Forest algorithm. The results showed that people over 56 years old walk as much as younger people. Furthermore, the importance given by this group of people to indicators referring to active modes is related to safety and security, distance, time, and comfort. The statistical results of the Wilcoxon Rank Sum test indicate the most important indicators: Adequate Travel Distance & Time and Existence of Commercial Areas by age group [0–55], and Absence of Allergenics and Existence of Green Areas by age group [56+]. Finally, the Random Forest algorithm provides the relative importance for both age groups, [0–55] and [56+], where the indicators that stand out in the [56+] age group, which is the focus of our study, are air quality, adequate travel distance & time, adequate crowd density, adequate thermal sensation, absence of allergenic, good street illumination level, adequate traffic volume, and adequate noise level. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
This article presents a framework to assist in the design of technology-based interactive services for active mobility, which allows the data collected from the sensors to be made available to citizens. The proposed framework was developed based on data collected in focus group sessions held with potential stakeholders and on related models and frameworks. It consists of 8 steps, namely: strategy, scope, structure, skeleton, aesthetics and execution. It will enable the presentation of relevant information that will help users of active modes of transport in decision making in choosing a safe and comfortable route, assist professionals involved in the elaboration of interactive projects and promote more collaborative urban planning. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Abstract

Abstract
Problem definition: Online retailers often receive customer orders comprising several products of differing origins. To fulfill these orders, retailers must ship multiple parcels from different locations and-unless they are grouped somewhere along the supply chain-these may reach the customer's doorstep one by one. Academic/practical relevance: We conjecture here that receiving products sequentially instead of all together affects a consumer's reaction to her purchases, possibly influencing-for good or ill-her decision to return products, as well as her overall service satisfaction. We use two-year granular data from an online fashion marketplace to test this hypothesis and characterize consumer behavioral responses to delivery consolidation and examine how it impacts supply chain stakeholders. Methodology: To achieve causal inference, we exploit the fact that the couriers used by the focal marketplace gather together certain parcels for reasons related more to the timing of their arrival than their actual customers, thereby exogenously consolidating the delivery of some orders. We construct a balanced sample of matched twin multiproduct orders that are alike in all respects except their delivery: consolidated (all parcels delivered jointly) versus otherwise (split). Results: We find that delivery consolidation benefits the marketplace and all its suppliers. By eliminating the stress associated with split deliveries, delivery consolidation pleases consumers as it leads to fewer returns and higher overall satisfaction. Managerial implications: Delivering all products in an order together, even if later, reduces the probability of a return, which improves the financial performance of the marketplace and its suppliers and reduces reverse logistics. Our results suggest that in our context, delivery speed matters less than the convenience of receiving all ordered goods in a single delivery, and we provide directions for adapting logistics strategies accordingly. Our empirical findings also imply that the return decisions of multiple products purchased at once should not be considered to be independent. Finding tractable ways of modeling this feature will be necessary in further driving retail practice through theoretical research that accounts for the behavioral implications of delivery consolidation when optimizing fulfillment decisions.

Abstract

Abstract
Interest in integrating lot-sizing and cutting stock problems has been increasing over the years. This integrated problem has been applied in many industries, such as paper, textile and furniture. Yet, there are only a few studies that acknowledge the importance of uncertainty to optimise these integrated decisions. This work aims to address this gap by incorporating demand uncertainty through stochastic programming and robust optimisation approaches. Both robust and stochastic models were specifically conceived to be solved by a column generation method. In addition, both models are embedded in a rolling-horizon procedure in order to incorporate dynamic reaction to demand realisation and adapt the models to a multistage stochastic setting. Computational experiments are proposed to test the efficiency of the column generation method and include a Monte Carlo simulation to assess both stochastic programming and robust optimisation for the integrated problem. Results suggest that acknowledging uncertainty can cut costs by up to 39.7%, while maintaining or reducing variability at the same time.