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.

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.

Abstract

Abstract
Demand for leisure activities has increased due to some reasons such as increasing wealth, ageing populations and changing lifestyles, however, the efficiency of public transport system relies on solid demand levels and well-established mobility patterns and, so, providing quality public transportation is extremely expensive in low, variable and unpredictable demand scenarios, as it is the case of non-routine trips. Better prediction estimations about the trip purpose helps to anticipate the transport demand and consequently improve its planning. This paper addresses the contribution in comparing the traditional approach of considering municipality division to study such trips against a proposed approach based on clustering of dense concentration of services in the urban space. In our case, POIs (Points of Interest) collected from social networks (e.g. Foursquare) represent these services. These trips were associated with the territory using two different approaches: 'municipalities' and 'clusters' and then related with the likelihood of choosing a POI category (Points-of-Interest). The results obtained for both geographical approaches are then compared considering a multinomial model to check for differences in destination choice. The variables of distance travelled, travel time and whether the trip was made on a weekday or a weekend had a significant contribution in the choice of destination using municipalities approach. Using clusters approach, the results are similar but the accuracy is improved and due to more significant results to more categories of destinations, more conclusions can be drawn. These results lead us to believe that a cluster-based analysis using georeferenced data from social media can contribute significantly better than a territorial-based analysis to the study of non-routine mobility. We also contribute to the knowledge of patterns of this type of travel, a type of trips that is still poorly valued and difficult to study. Nevertheless, it would be worth a more extensive analysis, such as analysing more variables or even during a larger period.