What Influences the Diffusion of Grassroots Innovations for Sustainability? Investigating Community Currency Niches

Community action for sustainability is a promising site of socio-technical innovation. Here we test the applicability of co-evolutionary niche theories of innovation diffusion (Strategic Niche Management, SNM) to the context of ‘grassroots innovations’. We present new empirical findings from an international study of 12 community currency niches (such as LETS, time banks, local currencies). These are parallel systems of exchange, designed to operate alongside mainstream money, meeting additional sustainability needs. Our findings confirm SNM predictions that niche-level activity correlates with diffusion success, but we highlight additional or confounding factors, and how niche theories might be adapted to better fit civil-society innovations. In so doing, we develop a model of grassroots innovation niche diffusion which builds on existing work and tailors it to this specific context. The paper concludes with a series of theoretically-informed recommendations for practitioners and policymakers to support the development and potential of grassroots innovations

ANALYTICS AND DATA SCIENCE APPLIED TO THE TRAJECTORY OUTLIER DETECTION

Nowadays, logistics for transportation and distribution of merchandise are a key element to increase the competitiveness of companies. However, the election of alternative routes outside the panned routes causes the logistic companies to provide a poor-quality service, with units that endanger the appropriate deliver of merchandise and impacting negatively the way in which the supply chain works. This paper aims to develop a module that allows the processing, analysis and deployment of satellite information oriented to the pattern analysis, to find anomalies in the paths of the operators by implementing the algorithm TODS, to be able to help in the decision making. The experimental results show that the algorithm detects optimally the abnormal routes using historical data as a base

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

Exploring Data Driven Models of Transit Travel Time and Delay

Transit travel time and operating speed influence service attractiveness, operating cost, system efficiency and sustainability. The Tri-County Metropolitan Transportation District of Oregon (TriMet) provides public transportation service in the tri-county Portland metropolitan area. TriMet was one of the first transit agencies to implement a Bus Dispatch System (BDS) as a part of its overall service control and management system. TriMet has had the foresight to fully archive the BDS automatic vehicle location and automatic passenger count data for all bus trips at the stop level since 1997. More recently, the BDS system was upgraded to provide stop-level data plus 5-second resolution bus positions between stops. Rather than relying on prediction tools to determine bus trajectories (including stops and delays) between stops, the higher resolution data presents actual bus positions along each trip. Bus travel speeds and intersection signal/queuing delays may be determined using this newer information. This thesis examines the potential applications of higher resolution transit operations data for a bus route in Portland, Oregon, TriMet Route 14. BDS and 5-second resolution data from all trips during the month of October 2014 are used to determine the impacts and evaluate candidate trip time models. Comparisons are drawn between models and some conclusions are drawn regarding the utility of the higher resolution transit data. In previous research inter-stop models were developed based on the use of average or maximum speed between stops. We know that this does not represent realistic conditions of stopping at a signal/crosswalk or traffic congestion along the link. A new inter-stop trip time model is developed using the 5-second resolution data to determine the number of signals encountered by the bus along the route. The variability in inter-stop time is likely due to the effect of the delay superimposed by signals encountered. This newly developed model resulted in statistically significant results. This type of information is important to transit agencies looking to improve bus running times and reliability. These results, the benefits of archiving higher resolution data to understand bus movement between stops, and future research opportunities are also discussed

Factors influencing the choice of shared bicycles and shared electric bikes in Beijing

AbstractChina leads the world in both public bikeshare and private electric bike (e-bike) growth. Current trajectories indicate the viability of deploying large-scale shared e-bike (e-bikeshare) systems in China. We employ a stated preference survey and multinomial logit to model the factors influencing the choice to switch from an existing transportation mode to bikeshare or e-bikeshare in Beijing. Demand is influenced by distinct sets of factors: the bikeshare choice is most sensitive to measures of effort and comfort while the e-bikeshare choice is more sensitive to user heterogeneities. Bikeshare demand is strongly negatively impacted by trip distance, temperature, precipitation, and poor air quality. User demographics however do not factor strongly on the bikeshare choice, indicating the mode will draw users from across the social spectrum. The e-bikeshare choice is much more tolerant of trip distance, high temperatures and poor air quality, though precipitation is also a highly negative factor. User demographics do play a significant role in e-bikeshare demand. Analysis of impact to the existing transportation system finds that both bikeshare and e-bikeshare will tend to draw users away from the “unsheltered modes”, walk, bike, and e-bike. Although it is unclear if shared bikes are an attractive “first-and-last-mile solution”, it is clear that e-bikeshare is attractive as a bus replacement

Evaluation Of Lane Use Management Strategies

The limited funding available for roadway capacity expansion and the growing funding gap, in conjunction with the increasing congestion, creates a critical need for innovative lane use management options. Various cost-effective lane use management strategies have been implemented in the United States and worldwide to address these challenges. However, these strategies have their own costs, operational characteristics, and additional requirements for field deployment. Hence, there is a need for systematic methodologies to evaluate lane use management strategies. In this thesis, a systematic simulation-based methodology is proposed to evaluate lane use management strategies. It involves identifying traffic corridors that are suitable for lane use management strategies, and analyzing the strategies in terms of performance and financial feasibility. The state of Indiana is used as a case study for this purpose, and a set of traffic corridors is identified. From among them, a 10-mile stretch of the I-65 corridor south of downtown Indianapolis is selected as the study corridor using traffic analysis. The demand volumes for the study area are determined using subarea analysis. The performance of the traffic corridor is evaluated using a microsimulation-based analysis for alleviating congestion using three strategies: reversible lanes, high occupancy vehicle (HOV) lanes and ramp metering. Furthermore, an economic evaluation of these strategies is performed to determine the financial feasibility of their implementation. Results from the simulation based analysis indicate that the reversible lanes and ramp metering strategies improve traffic conditions on the freeway in the major flow direction. Implementation of the HOV lane strategy results in improved traffic flow conditions on the HOV lanes but aggravated congestion on the general purpose lanes. The HOV lane strategy is found to be economically infeasible due to low HOV volume on these lanes. The reversible lane and ramp metering strategies are found to be economically feasible with positive net present values (NPV), with the NPV for the reversible lane strategy being the highest. While reversible lanes, HOV lanes and ramp metering strategies are effective in mitigating congestion by optimizing lane usage, they do not generate additional revenue required to reduce the funding deficit. Inadequate funds and worsening congestion have prompted federal, state and local planning agencies to explore and implement various congestion pricing strategies. In this context, the high occupancy toll (HOT) lanes strategy is explored here. Equity concerns associated with pricing schemes in transportation systems have garnered increased attention in the recent past. Income inequity potentially exists under the HOT strategy whereby higher-income travelers may reap the benefits of HOT lane facilities. An income-based multi-toll pricing approach is proposed for a single HOT lane facility in a network to simultaneously maximize the toll revenue and address the income equity concern, while ensuring a minimum level-of-service on the HOT lanes and that the toll prices do not exceed thresholds specified by a regulatory entity. The problem is modeled as a bi-level optimization formulation. The upper level model seeks to maximize revenue for the tolling authority subject to pre-specified upper bounds on toll prices. The lower level model solves for the stochastic user equilibrium solution based on commuters\u27 objective of minimizing their generalized travel costs. Due to the computational intractability of the bi-level formulation, an approximate agent-based solution approach is used to determine the toll prices by considering the tolling authority and commuters as agents. Results from numerical experiments indicate that a multi-toll pricing scheme is more equitable and can yield higher revenues compared to a single toll price scheme across all travelers

Understanding econo-political risks: impact of sanctions on an automotive supply chain

Purpose - The purpose of this paper is to introduce econo-political risks (EPRs) to supply chains (SCs). Based on case data from an automotive SC, this research identifies the mechanisms through which a subset of EPRs influences Sc operations and outcomes. Design/methodology/approach - An exploratory case study method is employed for theory development. Interviews with SC professionals of three case companies were the primary data source. Company documents, archival records, and direct observation provided further insights into how EPRs are perceived, how they impact a SC, how SC actors react to them, and what the overall performance results are. Findings - The research identifies EPRs in terms of scope (flow of material, money, and knowledge) and time, and provides concrete examples, along with the channels through which their impact unfolds, and the responses available to SC actors. The authors find secondary impacts of EPRs through economic and regulatory channels to be significant, and bankruptcy, strategic reorientation, and single sourcing are common outcomes. By elaborating on the mechanisms through which sanctions impact upon SCs, and the feasible response trajectories, this research can assist SC actors with more effective management of EPRs. Originality/value - This paper is novel for three reasons: first, it introduces EPRs to research into supply chain risk management (SCRM); second, it addresses SC risks in a developing country, a topic largely missing from the literature; and finally, this research focuses on post-event SC risks, whereas the bulk of SCRM literature focuses on the pre-event phase

e-mission: an open source, extensible platform for human mobility systems

Transportation is the single largest source of carbon emissions in the US. Decarbonizing it is challenging because it depends on individual behaviors, which in turn, depend on local land use planning. The interdisciplinary field of Computational Mobility, focusing on collecting, analysing and influencing human travel behavior, can frame solutions to this challenge.Innovation flows in interdisciplinary fields are bi-directional. The flow to the domain is focused on building a strong foundation for methodological improvements. As the improvements are deployed, they result in use-inspired computational research. This temporal dependency results in our initial focus on the modularity, accuracy and reproducibility of e-mission, an extensible platform for instrumenting human mobility. This open source platform has a modular architecture that supports power efficient duty cycling using virtual sensors, a read-only data model and a pipeline with novel algorithm adaptations for smartphone sensing.We also perform the first empirical evaluations of smartphone-based platforms in this domain. The architectural evaluation is based on three real world deployments: a classic travel diary, a crowdsourcing initiative, and a behavioral study. The accuracy evaluation is based on an novel procedure that uses artificial trips and multiple parallel phones to mitigate concerns over privacy, context sensitive power consumption and inherent sensing error. Data collected from three artifical timelines was used to evaluate the trajectory, segmentation and classification accuracies vs. power for various configurations.On computational side, challenges derived from the deployments can contribute to ongoing CS research in privacy, trustworthiness, incentivization and decision making. On the mobility side, this enables methodological innovations such as Agile Urban Planning for prototyping infrastructure changes