Moving from a Product-Based Economy to a Service-Based Economy for a More Sustainable Future

Traditionally, economic growth and prosperity have been linked with the availability, production and distribution of tangible goods as well as the ability of consumers to acquire such goods. Early evidence regarding this connection dates back to Adam Smith's Wealth of Nations (1776), in which any activity not resulting in the production of a tangible good is characterized as unproductive of any value." Since then, this coupling of economic value and material production has been prevalent in both developed and developing economies throughout the world. One unintended consequence of this coupling has been the exponential increase in the amount of solid waste being generated. The reason is that any production and consumption of material goods eventually generates the equivalent amount of (or even more) waste. Exacerbating this problem is the fact that, with today's manufacturing and supply chain management technologies, it has become cheaper to dispose and replace most products rather than to repair and reuse them. This has given rise to what some call a disposable society." To put things in perspective: In 2012 households in the U.K. generated approximately 22 thousand tons of waste, which amounted to 411 kg of waste generated per person (Department for Environment, Food & Rural Affairs, 2015). During the same time period, households in the U.S. generated 251 million tons of waste, which is equivalent to a person generating approximately 2 kg of waste every day (U.S. Environmental Protection Agency, 2012). Out of these 251 million tons of total waste generated, approximately 20% of the discarded items were categorized as durable goods. The disposal of durable goods is particularly worrisome because they are typically produced using material from non- renewable resources such as iron, minerals, and petroleum-based raw materials

It takes two to tango: entrepreneurial interaction and innovation

Innovation management focuses too much on processes and tools, whereas entrepreneurship is pre-occupied with individual personal traits. However, many of the most successful innovations were co-created, by multiple entrepreneurs, and it is this interaction of talent that is at the core of radical innovation, what we call Conjoint Innovation. We examine 15 cases, historical and contemporary, to identify what conjoint innovation is and how it work

Unique Opportunities of Island States to Transition to a Low-Carbon Mobility System

Small islands developing states (SIDS) contribute minuscule proportions to global greenhouse gas (GHG) emissions and energy consumption, but are highly exposed to climate change impacts, in particular to extreme weather events and sea-level rise. However, there is little research on potential decarbonization trajectories unique to SIDS. Here, we argue that insular topology, scale, and economy are distinctive characteristics of SIDS that facilitate overcoming carbon lock-in. We investigate these dimensions for the three islands of Barbados, Fiji, and Mauritius. We find that insular topologies and small scale offer an opportunity for both public transit corridors and rapid electrification of car fleets. The tourism sector enables local decision-makers and investors to experiment with shared mobility and to induce spillover effects by educating tourists about new mobility options. Limited network effects, and the particular economy thus enables to overcome carbon lock-in. We call for targeted investments into SIDS to transition insular mobility systems towards zero carbon in 2040. The decarbonization of SIDS is not only needed as a mitigation effort, but also as a strong signal to the global community underlining that a zero-carbon future is possible.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Alleviating a form of electric vehicle range anxiety through On-Demand vehicle access

On-demand vehicle access is a method that can be used to reduce types of range anxiety problems related to planned travel for electric vehicle owners. Using ideas from elementary queueing theory, basic QoS metrics are defined to dimension a shared fleet to ensure high levels of vehicle access. Using mobility data from Ireland, it is argued that the potential cost of such a system is very low

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars