Abstract
The phenomenon of missed nursing care is endemic across all sectors. Nurse leaders have drawn attention to the implications of missed care for patient outcomes, with calls to develop clear political, methodological, and theoretical approaches. As part of this call, we describe three structural theories that inform frameworks of missed care: systems theory, economic theory, and neoliberal politics. The final section provides commentary on the strengths and limitations of these three theories, in the light of structuration theory and calls to balance this research agenda by reinstating nurse agency and examining the interactions between nurses as agents and the health systems as structures. The paper argues that a better understanding of variations in structure-agency interaction across the healthcare system might lead to more effective interventions at strategic leverage points.

Abstract
This paper proposes a Local Energy Market using a P2P blockchain-powered marketplace where agents bilaterally trade energy after the consumption and production period, and not before, as usual in electricity market design. The EU and MIBEL regulatory framework for Renewable Energy Communities potentially creates space for such a market, but some improvements in the settlement procedures and agent's participation must be met. © 2020 IEEE.

Abstract
The European Union (EU) has been promoting diverse initiatives towards sustainable development and environment protection. One of these initiatives is the reduction of the greenhouse gas (GHG) emissions in 60% below their 1990 level, by 2050. As the transport sector is responsible for more than 22% of those emissions some strategies need to be taken towards a more sustainable mobility, as the ones proposed in 2011 White Paper on transport. Under this context, this study aims to evaluate the environmental performance of the transport sector in the 28 EU countries towards these goals, from 2015 to 2017. The transport environmental performance is measured through the composite indicator derived from the Benefit of the Doubt (BoD) model. The country transport environmental performance is assessed through the aggregation of multiple sub-indicators using the composite indicator derived from the Data Envelopment Analysis (DEA) model. The results indicate that the EU countries slightly improved their transport environmental performance, on average 2.8%. The areas where the inefficient countries need more improvement were also identified: reducing the GHG emissions from fossil fuels, increasing the share of transport energy from renewable sources and improving the public transport share of the total passenger transport.

Abstract
The potential of the Internet of Things (IoT) and other technologies in the realm of Industry 4.0 to generate valuable data for monitoring the performance of the production processes and the whole supply chain is well established. However, these large volumes of data can be used within planning and control systems (PCSs) to enhance real-time planning and decision-making. This paper conducts a literature review to envisage an overall system architecture that combines IoT and PCS for planning, monitoring and control of operations at the level of an industrial production process or at the level of its supply chain. Despite the extensive literature on IoT implementations, few studies explain the interactions between IoT and the components of PCS. It is expected that, with the increasing digitization of business processes, approaches with PCS and IoT become ubiquitous in the near future. © 2020, Springer Nature Switzerland AG.

Abstract
Purpose Dyadic interactions between customers and service providers rarely occur in isolation. Still, there is a lack of systematic knowledge about the roles that different types of nontechnological third parties - that is, other customers, pets, other employees and other firms - can adopt in relation to customers and service providers during encounters. The present study aims to unravel these roles and highlight their implications for customers, service providers and/or third parties. Design/methodology/approach This research relies on a systematic review of literature in the Web of Science using a search string pertaining to the research study's objectives. In total, 2,726 articles were screened by title and abstract using clear inclusion and exclusion criteria, thereby extracting 189 articles for full-text eligibility. The final sample consisted of 139 articles for coding and analysis. Findings The analyses reveal that other customers, pets, other employees and other firms can adopt five roles: bystander, connector, endorser, balancer and partner. Each role has different implications for customers, service providers and/or third parties. Additionally, the five roles are associated with distinct constellations of the customer, the service provider and the third party. These roles and constellations are dynamic and not mutually exclusive. Originality/value This research contributes to the service encounter literature by providing a thorough understanding of the various third-party roles and their implications for customers, service providers and/or third parties during encounters. As such, this research sheds light on the conditions under which third parties become "significant others" in service encounters and identifies avenues for future research.

Abstract
When planning a selling season, a car rental company must decide on the number and type of vehicles in the fleet to meet demand. The demand for the rental products is uncertain and highly price-sensitive, and thus capacity and pricing decisions are interconnected. Moreover, since the products are rentals, capacity "returns". This creates a link between capacity with fleet deployment and other tools that allow the company to meet demand, such as upgrades, transferring vehicles between locations or temporarily leasing additional vehicles. We propose a methodology that aims to support decision-makers with different risk profiles plan a season, providing good solutions and outlining their ability to deal with uncertainty when little information about it is available. This matheuristic is based on a co-evolutionary genetic algorithm, where parallel populations of solutions and scenarios co-evolve. The fitness of a solution depends on the risk profile of the decision-maker and its performance against the scenarios, which is obtained by solving a mathematical programming model. The fitness of a scenario is based on its contribution in making the scenario population representative and diverse. This is measured by the impact the scenarios have on the solutions. Computational experiments show the potential of this methodology regarding the quality of the solutions obtained and the diversity and representativeness of the set of scenarios generated. Its main advantages are that no information regarding probability distributions is required, it supports different decision-making risk profiles, and it provides a set of good solutions for an innovative complex application.