scholarly journals The Impact Of Lane Closures On Congestion And Reliability: A Case Study Of Toronto's Gardiner Expressway

2021 ◽  
Author(s):  
Christina Borowiec
Keyword(s):  
Big Data ◽  
Performance Indicators ◽  
System Performance ◽  
Policy Action ◽  
Methods Of Analysis ◽  
Trade Offs ◽  
Regression Framework ◽  
The Impact ◽  
Lane Closures

Usage of big data with before-after methods of analysis makes it possible to evaluate the effect of major transport investments on system performance. In employing before-after methods to investigate the impact of lane closures on congestion and travel reliability, changes and trade-offs in performance indicators are quantified and policy action effectiveness is evaluated. This is illustrated through a case study of two separate lane closure interventions on the Gardiner Expressway in Toronto, Ontario. Models using a regression framework were developed for the pre-, peri-, and post-closure test periods of the first intervention and pre- and peri-closure periods of the second intervention. Results suggest the impacts of policy actions on system performance are strong, and that congestion and travel reliability counterintuitively move in different directions. Reduced demand effects are observed, prompting discussion on how highways and congestion should be managed and whether or not municipalities should add capacity to regional assets.

scholarly journals The Impact Of Lane Closures On Congestion And Reliability: A Case Study Of Toronto's Gardiner Expressway

2021 ◽  
Author(s):  
Christina Borowiec
Keyword(s):  
Big Data ◽  
Performance Indicators ◽  
System Performance ◽  
Policy Action ◽  
Methods Of Analysis ◽  
Trade Offs ◽  
Regression Framework ◽  
The Impact ◽  
Lane Closures

Usage of big data with before-after methods of analysis makes it possible to evaluate the effect of major transport investments on system performance. In employing before-after methods to investigate the impact of lane closures on congestion and travel reliability, changes and trade-offs in performance indicators are quantified and policy action effectiveness is evaluated. This is illustrated through a case study of two separate lane closure interventions on the Gardiner Expressway in Toronto, Ontario. Models using a regression framework were developed for the pre-, peri-, and post-closure test periods of the first intervention and pre- and peri-closure periods of the second intervention. Results suggest the impacts of policy actions on system performance are strong, and that congestion and travel reliability counterintuitively move in different directions. Reduced demand effects are observed, prompting discussion on how highways and congestion should be managed and whether or not municipalities should add capacity to regional assets.

Preliminary Design and Performance of Counter Rotating Turbines for Open Rotors: Part II — 0-D Methodology and Case Study for a 160 PAX Aircraft

2016 ◽  
Author(s):  
Pablo Bellocq ◽  
Inaki Garmendia ◽  
Jordane Legrand ◽  
Vishal Sethi
Keyword(s):  
Design Methodology ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Preliminary Design ◽  
Regulatory Constraints ◽  
Trade Offs ◽  
And Performance ◽  
The Impact

Direct Drive Open Rotors (DDORs) have the potential to significantly reduce fuel consumption and emissions relative to conventional turbofans. However, this engine architecture presents many design and operational challenges both at engine and aircraft level. At preliminary design stages, a broad design space exploration is required to identify potential optimum design regions and to understand the main trade offs of this novel engine architecture. These assessments may also aid the development process when compromises need to be performed as a consequence of design, operational or regulatory constraints. Design space exploration assessments are done with 0-D or 1-D models for computational purposes. These simplified 0-D and 1-D models have to capture the impact of the independent variation of the main design and control variables of the engine. Historically, it appears that for preliminary design studies of DDORs, Counter Rotating Turbines (CRTs) have been modelled as conventional turbines and therefore it was not possible to assess the impact of the variation of the number of stages (Nb) of the CRT and rotational speed of the propellers. Additionally, no preliminary design methodology for CRTs was found in the public domain. Part I of this two-part publication proposes a 1-D preliminary design methodology for DDOR CRTs which allows an independent definition of both parts of the CRT. A method for calculating the off-design performance of a known CRT design is also described. In Part II, a 0-D design point efficiency calculation for CRTs is proposed and verified with the 1-D methods. The 1-D and 0-D CRT models were used in an engine control and design space exploration case study of a DDOR with a 4.26m diameter an 10% clipped propeller for a 160 PAX aircraft. For this application: • the design and performance of a 20 stage CRT rotating at 860 rpm (both drums) obtained with the 1-D methods is presented. • differently from geared open rotors, negligible cruise fuel savings can be achieved by an advanced propeller control. • for rotational speeds between 750 and 880 rpm (relatively low speeds for reduced noise), 22 and 20 stages CRTs are required. • engine weight can be kept constant for different design rotational speeds by using the minimum required Nb. • for any target engine weight, TOC and cruise SFC are reduced by reducing the rotational speeds and increasing Nb (also favourable for reducing CRP noise). However additional CRT stages increase engine drag, mechanical complexity and cost.

Enabling integrated business planning through big data analytics: a case study on sales and operations planning

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alexander Schlegel ◽  
Hendrik Sebastian Birkel ◽  
Evi Hartmann
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Data Analytics ◽  
Single Case ◽  
Big Data Analytics ◽  
Business Planning ◽  
Operations Planning ◽  
Content Type ◽  
The Impact

PurposeThe purpose of this study is to investigate how big data analytics capabilities (BDAC) enable the implementation of integrated business planning (IBP) – the advanced form of sales and operations planning (S&OP) – by counteracting the increasing information processing requirements.Design/methodology/approachThe research model is grounded in the organizational information processing theory (OIPT). An embedded single case study on a multinational agrochemical company with multiple geographically distinguished sub-units of analysis was conducted. Data were collected in workshops, semistructured interviews as well as direct observations and enriched by secondary data from internal company sources as well as publicly available sources.FindingsThe results show the relevancy of establishing BDAC within an organization to apply IBP by providing empirical evidence of BDA solutions in S&OP. The study highlights how BDAC increase an organization's information processing capacity and consequently enable efficient and effective S&OP. Practical guidance toward the development of tangible, human and intangible BDAC in a particular sequence is given.Originality/valueThis study is the first theoretically grounded, empirical investigation of S&OP implementation journeys under consideration of the impact of BDAC.

scholarly journals Temporal changes in greenspace in a highly urbanized region

2011 ◽  
Vol 7 (5) ◽  
pp. 763-766 ◽  
Author(s):  
Martin Dallimer ◽  
Zhiyao Tang ◽  
Peter R. Bibby ◽  
Paul Brindley ◽  
Kevin J. Gaston ◽  
...  
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
National Level ◽  
Urban Land Use ◽  
Policy Reforms ◽  
Trade Offs ◽  
Dramatic Shift ◽  
Urbanized Region ◽  
The Impact

The majority of the world's population now lives in towns and cities, and urban areas are expanding faster than any other land-use type. In response to this phenomenon, two opposing arguments have emerged: whether cities should ‘sprawl’ into the wider countryside, or ‘densify’ through the development of existing urban greenspace. However, these greenspaces are increasingly recognized as being central to the amelioration of urban living conditions, supporting biodiversity conservation and ecosystem service provision. Taking the highly urbanized region of England as a case study, we use data from a variety of sources to investigate the impact of national-level planning policy on temporal patterns in the extent of greenspace in cities. Between 1991 and 2006, greenspace showed a net increase in all but one of 13 cities. However, the majority of this gain occurred prior to 2001, and greenspace has subsequently declined in nine cities. Such a dramatic shift in land use coincides with policy reforms in 2000, which favoured densification. Here, we illustrate the dynamic and policy-responsive nature of urban land use, thereby highlighting the need for a detailed investigation of the trade-offs associated with different mechanisms of urban densification to optimize and secure the diverse benefits associated with greenspaces.

scholarly journals Study on the Impact of the COVID-19 Pandemic on the Spatial Behavior of Urban Tourists Based on Commentary Big Data: A Case Study of Nanjing, China

2021 ◽  
Vol 10 (10) ◽  
pp. 678
Author(s):  
Yu Gao ◽  
Dongqi Sun ◽  
Jingxiang Zhang
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Central City ◽  
Spatial Behavior ◽  
Natural Landscape ◽  
Considerable Impact ◽  
Study Methodology ◽  
Spatial Trajectory ◽  
The Impact

The global outbreak of the COVID-19 epidemic has caused a considerable impact on humans, which expresses the urgency and importance of studying its impacts. Previous studies either frequently use aggregated research methods of statistic data or stay during COVID-19. The afterward impacts of COVID-19 on human behaviors need to be explored further. This article carries out a non-aggregated study methodology in human geography based on big data from social media comments and takes Nanjing, China, as the research case to explore the afterward impact of the COVID-19 epidemic on the spatial behavior of urban tourists. Precisely, we propose the methodology covers two main aspects regarding travel contact trajectory and spatial trajectory. In contact trajectory, we explore three indicators—Connection Strength, Degree Centrality, and Betweenness Centrality—of the collected attractions. Then, in spatial trajectory, we input the results from contact trajectory into ArcGIS by using the Orientation–Destination Model and Standard Deviation Ellipse to explore the influences on the spatial pattern. By setting up comparative groups for the three periods of before, during, and after the COVID-19 in Nanjing, this study found that, in the post-epidemic era, (1) the spatial behavior of urban tourists showed a state of overall contraction; (2) the objects of contraction changed from urban architectural attractions to urban natural attractions; (3) the form of contraction presents concentric circles with the central city (Old City of Nanjing) as the core; (4) the direction of contraction heads to the large-scale natural landscape in the central city, which highlights the importance of green open spaces in the post-epidemic era.

scholarly journals An Assessment of Impact of Leadership Training on Health System Performance in Selected Counties in Kenya

2021 ◽  
Vol 8 ◽  
Author(s):  
Tecla Chelagat ◽  
James Rice ◽  
Joseph Onyango ◽  
Gilbert Kokwaro
Keyword(s):  
Health Care ◽  
Health System ◽  
Leadership Training ◽  
Performance Indicators ◽  
System Performance ◽  
Individual Development ◽  
Control Group ◽  
Health System Performance ◽  
For Profit ◽  
The Impact

Introduction: The provision of health care services in Kenya was devolved from the national government to the counties in 2013. Evidence suggests that health system performance in Kenya remains poor. The main issue is poor leadership resulting in poor health system performance. However, most training in Kenya focuses on “leaders” (individual) development as opposed to “leadership” training (development of groups from an organization). The purpose of that study was to explore the impact of leadership training on health system performance in selected counties in Kenya.Methods: A quasi-experimental time-series design was employed. Pretest, posttest control-group design was utilized to find out whether the leadership development program positively contributed to the improvement of health system performance indicators compared with the non-trained managers. Questionnaires were administered to 31 trained health managers from the public, private for-profit, and private not-for-profit health institutions within the same counties.Results: The pretest and posttest means for all the six health system (HS) pillar indicators of the treatment group were higher than those of the control group. The regression method to estimate the DID structural model used to calculate the “fact” and “counterfactual” revealed that training had a positive impact on the intended outcome on the service delivery, information, leadership and governance, human resources, finance, and medical products with impact value ≥1 (57.2).Conclusion: The study findings support both hypotheses that trained health care management teams had a significant difference in the implementation status of priority projects and, hence, had a significant impact on health system performance indicators compared with non-trained managers.

scholarly journals Improving the Measurement of Health System Performance across the Rural-Urban Continuum

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Naushaba Degani ◽  
Sharon Gushue ◽  
Alex Yurkiewich ◽  
Emmalin Buajitti ◽  
Matthew Kumar ◽  
...  
Keyword(s):  
Health Care ◽  
Health Outcomes ◽  
Health System ◽  
Performance Indicators ◽  
System Performance ◽  
Working Group ◽  
Geographic Location ◽  
Key Performance Indicators ◽  
Health System Performance ◽  
The Impact

IntroductionWe report on key performance indicators to highlight quality and variation in health care. Given Ontario’s diverse geography, we have prioritized improving measurement across the rural-urban continuum. This will improve our ability to discern the impact of geography on health care and health status to inform planning and decision making. Objectives and ApproachBuilding on previous work to advance measurement of equity in health care, we struck a technical working group of experts to review methods for stratifying health system performance data by geographic location in the Ontario context. These methods were applied to a set of key performance indicators. The working group’s review of the results of this analysis will lead to recommendations for the best method to refine and standardize how geographic location is measured and stratified. This will improve our ability to discern the impact of geography on health system performance and health status for our suite of public-reporting products. ResultsThe technical working group identified three methodologies for consideration that used linked postal code data: Population Centre (POPCTR), Statistical Area Classification (SAC) and a hybrid POPCTR/SAC methodology. These methods were tested against a set of key performance indicators across dimensions of quality including timeliness, effectiveness, population health and health outcomes. The results show that, in the health system performance dimensions of effectiveness and timeliness, as well as for a subset of health outcomes, there is variation in performance across the urban-rural continuum, though not always in a linear way. This may reflect differences in health care access, health risk factors, sociodemographic or socioeconomic characteristics across the urban-rural continuum. More definitive conclusions and recommendations will be available when the working group meets to review the results. Conclusion/ImplicationsIdentifying a robust methodology for measuring performance across geographic locations will improve our ability to discern the impact of geography on health care including where geography may impact access and effectiveness of services as well as health outcomes. This information will enable better health system planning and decision-making.

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