In this paper, a Kranzberg [32] - Lancaster [34] approach is employed to investigate the microeconomics of mobile payment methods. The adoption of these technical innovations depends, among others, on the acceptance by consumers that can be analyzed with a Lancaster characteristics demand. With a Kranzberg technology matrix, the technical and institutional details of payments can be transformed into salient characteristics of payment instruments that are relevant for Lancaster demand of payment methods. While cash and card-based payments are mostly Kranzberg-complete technologies, novel forms and means of mobile payments lack certain features, i.e., they are Kranzberg-incomplete innovations. Mobile payments are incomplete concerning technical, institutional and regulatory details. As a consequence, this incompleteness may result in a lack of acceptance on the side of consumers since certain salient characteristics of payment methods are not fully developed. In particular, mobile payments are neither widely accepted by merchants, nor are consumers’ data and privacy protected. Kranzberg-completion of novel mobile payments is required to make them universally successful.

The evolution of mobile networks towards the Fifth Generation (5G) introduces many concerns from the technical and economic points of view. Expected new applications exceed mobile networks’ current capabilities, and 4G networks will have to evolve into 5G networks to provide some with a proper service. With regard to the ambitious intended performance of 5G networks, a huge process is required which will need to be faced both technically and economically. The 5G “ready system” standard is scheduled for 2020. However, only a few studies have carried out techno-economic evaluation of 5G. This paper presents a techno-economic analysis to foresee some feasible technical architectures leading to suitable and affordable use cases. The paper presents a new approach based on different evolving technical scenarios, establishing combined 4G/5G technical solutions and a roadmap that could provide useful insights about the most suitable use cases by scenario. Moreover, it analyses these possible use cases to determine their feasibility by optimizing their deployment costs. The study is based on the standardization process, integration of different views of key industrial players and mathematical modelling to address the new applications that 5G will provide. Finally, conclusions are drawn from the analysis and a recommendation score is established, providing useful advice to support the strategic decisions of the different stakeholders, technologists and investors involved in deployment of 5G networks.

To ensure stable operation, Smart Grids rely on ultra-reliable, low latency communications for transmitting critical measurements and control commands. Though modern Information and Communication Technology (ICT) provides adequate means for asserting hard service guarantees, the installation, configuration and operation of corresponding infrastructures is typically very costly, involving significant administration efforts. Therefore, we propose Software-Defined Networking (SDN) to facilitate configuration and administration drastically, thus reducing expenditures. We identify technical advantages of introducing this approach to Smart Grid communication infrastructures and derive economic benefits. Numerical results for a reference power system indicate Operational Expenditures (OPEX)-driven savings that allow SDN solutions to outperform legacy networks within less than four years. Also, SDN-driven network slicing enables sharing infrastructures between critical power systems and end consumer broadband traffic, allowing for further cost reductions, while maintaining hard service guarantees. Under this paradigm, we compare the installation and operation of dedicated infrastructure by the grid operator to arranging service contracts with telecommunication network operators. This is referred to as make or buy decision. It can be deduced that a shared infrastructure, building on network slicing, provides an optimal solution for both parties.

Digitalization is pushing the maritime industry beyond its traditional limits and provides many new opportunities to enhance the productivity, efficiency, and sustainability of logistics. The concept of smart ports, for instance, aims to adopt modern information technologies to enable a better planning and management within and between ports. Strong facilitators of the digitalization are investments into technology and cooperations for promoting information sharing and a better coordination and collaboration, often regarded as a stumbling block in highly competitive environments. Besides many new opportunities, important economic issues and problems arise. We provide an overview of the development and state-of-the-art of digital transformation in modern seaports in order to identify current potentials and barriers. Focusing on the crucial and challenging aspects of coordination and collaboration, we present a conceptual game theoretic framework that allows benefits and cost allocations considering inter-, intra-, and meta-organizational perspectives. We further demonstrate how this framework can be used to develop tools and methods for supporting strategic decision making for driving the digital transformation in seaports and addressing new economic issues and problems.

This paper shows a framework of risk assessment models and analyzes the Mexican context of the supply chain for hazardous materials. A new set of risk assessment models is developed for each main activity of the closed-loop supply chain for hazardous materials. This model can be used to evaluate suppliers, transportation routes, outsourcing options and the material itself. A proportional risk-assessment technique is used to define risk cost calculation for the hazardous materials management using the National Fire Protection Agency classification. Hazardous materials represent a logistics challenge because of the risk involved at their handling. From 2006 to 2009 a total of 1,200 accidents were reported at different points of the supply chain. The investigated models require a previous analysis of the activities in order to calculate factors, such as the accident rate and possible affected population, among others; that could affect the cost in case of an accident. Analyzing the risk, cost values can be used by decision makers to determine which activities should be outsourced in order to avoid the risk itself or to fulfill laws and regulations.

Smart devices such as smartphones and tablets are used extensively in public spaces for the transmission and reception of content in the form of text, photos and streaming videos. Since the bandwidth provided for wireless access is limited in public areas, it becomes an issue for users to gain access to the bandwidth they need at the right times. While an omniscient controller could assign bandwidth to each device on the basis of their needs and overall availability, imperfect information about the instantaneous state of the wifi access patterns and needs of users make for a very inefficient allocation of such bandwidth. This paper provides a solution for bandwidth allocation by creating a market among users of smart devices so that they can bid for extra bandwidth when they need it and sell it when they don't. They do so by using a virtual currency that is conserved so that each device owner maximizes his own utility. This utility function is composed of both the benefit accrued from accessing bandwidth and the loss of the currency incurred in bidding for such bandwidth. Extensive simulations show that this market-based method outperforms an omniscient model when demand is uncertain, while minimizing bandwidth consumption.