Abstract
Discrete choice models can forecast market shares and individual choice probabilities with different price and alternative set scenarios. This work introduces a method to personalize choice models involving causal variables, such as price, using rich observational data. The model provides interpretable customer- and context-specific preferences, and price sensitivity, with an estimation procedure that uses orthogonalization. We caution against the nalive use of regularization to deal with the high-dimensional observational data challenge. We experiment with the attended home delivery (AHD) slot choice problem using data from a European online retailer. Our results indicate that while the popular non-personalized multinomial logit (MNL) model does very well at the aggregate (day-slot) level, personalization provides significantly and substantially more accurate predictions at the individual-context level. But the nalive personalization approach using regularization without orthogonalization wrongly predicts that the choice probability will increase if the slot price increases, rendering it unfit for forecasting demand with pricing scenarios. The proposed method avoids this problem. Further, we introduce features based on potential consideration sets in the AHD slot choice context that increase accuracy and allow for more realistic substitution patterns than the proportional substitution implied by MNL.

Abstract
PurposeDisruptions are appearing more frequently and having an ever greater impact on supply chains (SC), affecting the vulnerability and sustainability of organisations. Our study proposes an innovative approach to address contemporary challenges by introducing coopetition as a strategic capability. The aim of this study is to enable companies to adapt and thrive by applying a tool that measures and monitors different logistical scenarios to improve performance and antifragility.Design/methodology/approachWith the aim of jointly planning transport activities of two competing companies, we present a linear programming model that promotes synergies which enhance resource utilisation. To demonstrate the validity of the model, a case study is conducted to measure, monitor and evaluate the results obtained after collaborating on SC activities.FindingsCurrent tools to support logistics planning are not effective because they hamper information exchange, cost allocation and performance measurements. Our innovative model optimises collaborative networks (CNs) and monitors economic, environmental and social improvements. The case study shows the reduction of logistics costs (13%), carbon footprint (37%) and the improvement of social antifragility when agility and flexibility emerge.Originality/valueCNs have become an effective means of enhancing resilience, but there are no empirical contributions to demonstrate how to achieve this. We provide a real case with computational experiments that provide empirical evidence of the effectiveness of the model, which measures, optimises and evaluates SC performance in coopetitive environments. This approach is a guide to researchers and practitioners when creating simulations to reduce risks and facilitate decision-making.

Abstract
Background: The coffee industry is one of the most important world supply chains, with an estimated consumption of two billion cups daily, making it the most consumed beverage worldwide. Coffee beans are primarily grown in tropical countries, with Brazil accounting for almost 50% of the production. The objective of this study is to examine the Brazilian trade between 2018 and 2022, focusing on state producers, logistical corridors, and importer countries. Methods: The methodology approach revolves around a quantitative method using Social Network Analysis measures. Results: The results reveal a massive concentration in local production (99.5%-Minas Gerais), port movements (99.9%-Santos, Itaguai, and Rio de Janeiro), and country buyers (80.9%-the United States, United Kingdon, and Japan). Conclusions: The study concludes that the Brazilian green coffee supply chain relies on a fragile and overloaded logistical network. Due to that, this study indicates that the stakeholders and decision-makers involved must consider this high concentration of production in some areas and companies. They must also address the bottlenecks in logistical corridors and the fierce competition involved in acquiring and processing Brazilian coffee production because these factors can drastically affect the revenue of the companies operating in this sector.

Abstract
Hydropower currently generates more than all other renewable energies combined. Considering the challenges of climate change and the transition to green energy, it is expected to remain the world's largest source of renewable electricity generation. This paper proposes a tool for performance evaluation and benchmarking of hydropower generation to inform dispatching. Through them, strengths and weaknesses of asset operations can be set, identifying areas with the best performance, gathering insights from their strategies and best practices, and comprehending factors that lead to variations in performance levels. The results allow for optimising energy resource use by indicating the dispatching rules with maximum power production and minimum wearand-tear impact. This framework allows the formulation of practical guidelines for dispatching policies. The proposed methodology is applied to analyse two real-world case studies: the Vogelgr & uuml;n run of river hydropower plant (France) and the Frades 2 pump-storage powerplant (Portugal).

Abstract
This review is an analysis of the literature on public transport and mobile ticketing systems and their gamification. The review is divided into three main topics: (i) Behavioral Change in relation to Public Transport, (ii) Gamification, and (iii) Gamification in Public Transport and Mobile Ticketing. This study shows the diversity of the theme of gamification applied to the transport sector and demonstrates its potential to attract and retain more customers for more sustainable means of transport.

Abstract
The aim of this work is to determine, based on a market research, the level of passenger satisfaction with public transport services, in order to support better marketing decisions. This survey involves dimensions such as the level of satisfaction with timetables and frequency, vehicle conditions, driver attitudes and behavior, fares and information made available to passengers. The study was applied to the case of public transport in the Porto Metropolitan Area, Portugal, and aims to help define recommendations to improve the quality of service and define more effective marketing strategies.