Abstract
The advent of more proactive consumers, the so-called "prosumers", with production and storage capabilities, is empowering the consumers and bringing new opportunities and challenges to the operation of power systems in a market environment. Recently, a novel proposal for the design and operation of electricity markets has emerged: these so-called peer-to-peer (P2P) electricity markets conceptually allow the prosumers to directly share their electrical energy and investment. Such P2P markets rely on a consumer-centric and bottom-up perspective by giving the opportunity to consumers to freely choose the way they buy their electric energy. A community can also be formed by prosumers who want to collaborate, or in terms of operational energy management. This paper contributes with an overview of these new P2P markets that starts with the motivation, challenges, market designs moving to the potential future developments in this field, providing recommendations while considering a test-case.

Abstract
Today's manufacturing environment is increasingly pressured to higher flexibility induced by uncertain production volumes as well as uncertain product lifetime. A way to improve productivity in a flexible production system is by using a safe and flexible cooperation between robot and operator. Therefore, manufacturing companies are experiencing an increase in human-robot interactions and in the use of collaborative robots (cobots). To make full use of cobots, it is essential to understand the drivers for their adoption as well as how these drivers are aligned with the companies' strategic objectives. By means of in-depth interviews in six companies in Portugal and France, this study provides a comprehensive understanding of the drivers that influence the intent to adopt, or the effective adoption, of cobots and the alignment of these drivers with the strategic objectives of the company. Empirical results reveal "operational efficiency" and "ergonomics and human factors" concerns as important drivers in the adoption intent. In terms of strategic objectives, it was found that drivers are aligned with productivity and flexibility improvement as well as quality improvement strategic objectives. Understanding these drivers can help in motivating manufacturing companies to adopt cobots, in facilitating their adoption, and in reaping the benefits of this technology.

Abstract
Purpose This study aims to demonstrate the values and effects of innovation becomes a challenge when selecting clear and correlating measures. While there is extensive research in the area of innovation measurement, there is a lack of consistent quantifiable measures that organizations can use. The International Association of Innovation Professionals (IAOIP) has partnered with Spigit to crowdsource innovation measures via the Innovation Measurement Standard (IMS) challenge with IAOIP members and the global public to determine the various ways innovation is measured across industries. Design/methodology/approach This study used a mixed-methods approach and a sequential exploratory design to analyze the data collected during the IMS challenge. In the first phase, the qualitative methodology was used to analyze innovation measures submitted during the IMS challenge and participants' interactions and comments. In the second phase, the innovation measures were analyzed quantitatively to identify the most prominent measures. Findings A total of 73 innovation measures were collected during the challenge. In total, 18 top measures were ranked based on the participants' votes, and the top five measures were selected as the winning measures of the challenge. These five measures included intelligent failure rate, financial results of innovation, the results brought to the company, the number of innovative ideas selected for action and innovation portfolio balancing. Originality/value This study is the first to select the innovation metrics while considering their relevance to the community of innovators that included academics, CEOs, consultants, innovation managers, etc. Another original factor of this work is the crowdsourcing approach used to identify innovation measures. This approach allowed us to explore multiple perspectives on the significance of each submitted measure.

Abstract
Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System. In this context, a reliable localization system requires an accurate and redundant information to Global Navigation Satellite System and wheel odometry based system. To pursue this goal and have a reliable localization system in our robotic platform we aim to extract the better performance as possible from a monocular Visual Odometry method. To do so, we present a benchmark of Libviso2 using both perspective and fisheye lens cameras, studying the behavior of the method using both topologies in terms of motion performance in an outdoor environment. Also we analyze the quality of feature extraction of the method using the two camera systems studying the impact of the field of view and omnidirectional image rectification in VO. We propose a general methodology to incorporate a fisheye lens camera system into a VO method. Finally, we briefly describe the robot setup that was used to generate the results that will be presented. © 2019, Springer Nature Switzerland AG.

Abstract
The Transmission Expansion Planning (TEP) problem aims at identifying a list of equipment, among transmission lines, cables and transformers, that will be installed on the grid over a predefined planning horizon. TEP must also identify the respective periods of installations of the selected pieces-of-equipment to expand the grid. TEP is a mixed-integer non-linear and non-convex problem that requires a huge computational effort to be solved and, for this reason, many authors have been proposing relaxed TEP versions to reduce the mentioned computational burden. In this direction, this paper presents a broad comparison between the relaxed static TEP approach and the complete dynamic TEP. Numerical simulations are conducted using the Garver-6-bus and the RTS-24-bus test systems. The problem is handled by a hybrid tool composed by the Evolutionary Particle Swarm Optimization (EPSO) algorithm and a version of Hill-Climbing (HC), besides an AC-optimal power flow model is used to get more realistic operation conditions of the network. Even though dynamic TEP approaches present a higher computational effort, the results show that with this solution approach it is possible to obtain relevant investment savings when compared with the static TEP approach.

Abstract
M-commerce is afast-growing opportunity and is acting as an innovative lever for achieving the purpose of increasing sales while better interacting with the clients. Simultaneously, several emerging technologies have appeared in the market and promise to change the current m-commerce paradigm. Therefore, this chapter plans to explore a set of new trend technologies that can plan to build a more efficient relation between the consumer and the m-commerce platform. This study conducted surveys with several market players like marketers and IT leaders to understand their point of view, perceive the relevance and impact of these emergent technologies in m-commerce, identify resistance and challenge points to the proposed change, and look how to allow cohabitation between this new e-commerce paradigm and the traditional physical trade. The main novelty of this study is the inclusion of multiple points of view on the evolution of m-commerce which will allow companies and citizens to perceive the impact of emerging technologies in the future of m-commerce. © 2020, IGI Global.