Abstract
One of the main decisions that a car rental company has to make regards the definition of the fleet size and mix, i.e., the capacity to meet demand. This demand is highly unpredictable and price-sensitive; thus, the definition of the prices charged influences capacity decisions. Moreover, capacity decisions are also linked to other company strategies to meet demand, such as offering upgrades or transferring empty cars between stations. Typically, these problems are tackled focusing on the maximization of profits, disregarding the environmental impacts associated with these decisions. There is a growing need for models and analytical tools that can support decisions considering the trade-off between profit and environmental impact in mobility. Therefore, this work incorporates environmental concerns into the capacity-pricing problem for car rental, proposing a bi-objective model to tackle the trade-off between profit and environmental impact. The Life Cycle Assessment method is applied not only to vehicles but also to fuel to define environmental parameters accurately. Four types of vehicles are considered: internal combustion engine vehicles, hybrids, hybrids plug-in, and electric vehicles. Solving multi-objective models is a computationally challenging problem, which requires efficient and applicable methods. These methods can support policy and business decisions in a real-world context, running different scenarios and evaluating solutions under varying conditions. Due to its efficiency in solving bi-objective models, an Epsilon-constraint method is developed and applied in diverse situations to retrieve managerial insights. The results obtained enable quantifying the feasible trade-offs, overall showing that, on average, with a decrease of 14.44% in financial results, it is possible to obtain a decrease of 63.41% in environmental impact. Additional insights are also retrieved related to the fleet, fuel, prices and demand.

Abstract

Abstract
We present heuristics for two related two-dimensional non-guillotine packing problems. The first problem aims to pack a set of items into the minimum number of larger identical bins, while the second aims to pack the items that generates most value into one bin. Our approach successively creates sequences of items that defines a packing order considering knowledge obtained from sequences previously generated. Computational experiments demonstrated that the proposed heuristics are very effective in terms of solution quality with small computing times. © 2021, Springer Nature Switzerland AG.

Abstract
The production and supply chain management of biofuels from organic waste as raw material has been identified as a promising strategy in the field of renewable energies and circular economy initiatives. This industry involves complex tasks such as strategic land use, feedstock purchasing, production plant location, production capacity strategy, and material flows, which can be solved by mathematical modeling. The study proposed a multi-objective mixed-integer linear programming model to design a sustainable supply chain of biofuels with forest residues from its triple function: economic, environmental, and social. The trade-offs between the proposed objectives were determined with computational results. The proposed objectives were profit maximization, CO2 minimization, and employment generation maximization. Thus, the proposed model serves as a tool for decision-making, allowing the projection of a long-term structure of the biofuel supply chains and contribute to the United Nations Sustainable Development Goals.

Abstract
Engagement plays a key role for most organizations. Establishing close relationships with consumers and other stakeholders - thus promoting their loyalty and participation in the value creation process - has become an element of competitive advantage. Extant literature has focused consumer-brands relationships in commercial contexts; yet, when it comes to non-commercial or non-profit contexts - where communities of decidedly engaged individuals voluntarily invest their time and energy to a cause - research is still in its infancy. This study sets out to understand how non-profit organizations (NPO) can generate a sense of engagement among volunteers and which volunteers' behaviours - associated with that psychological state - entice value co-creation with NPO. Group interviews were carried out with volunteers to gain insights on drivers and outcomes of Volunteer Engagement (VE). Value congruence between volunteers and NPO, a sense of community, as well as perceptions of competence and autonomy, were identified as drivers of VE. The study further validated the impact of VE not only on somewhat predictable outcomes, such as NPO loyalty and advocacy, but also on the co-creation of value with NPO through the recruitment of new volunteers and the development of new ideas for service innovation.

Abstract
The beginning of the 21st century brought a new Industrial Revolution - the 4th Industrial Revolution which assumes that each physical object is equipped with an integrated technology that allows its connection with other objects. Therefore, Cyber-Physical Systems (CPSs) are becoming essential elements to be implemented in the companies' workspace in order to improve their production efficiency and flexibility by bringing digitalisation to the production processes. The implementation of these CPSs creates several changes for companies' operations that are expected to have a deep impact in human workers. A lack of studies on the social impact of the use of CPSs has been identified and, through a comprehensive literature review, this work aims at contributing for this discussion by defining a questionnaire about the topic. In the future, this questionnaire is intended to be sent to companies to collect data from their C-level managers about the use of CPSs applied to manufacturing.