scholarly journals A Predictive Fleet Management Strategy for On-Demand Mobility Services: A Case Study in Munich

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1021
Author(s):  
Michael Wittmann ◽  
Lorenz Neuner ◽  
Markus Lienkamp
Keyword(s):  
Service Quality ◽  
Large Scale ◽  
Management Strategies ◽  
Global Market ◽  
Fleet Management ◽  
Bipartite Matching ◽  
Fleet Size ◽  
Original Size ◽  
Real Time Information

The global market for MoD services is in a state of rapid and challenging transformation, with new market entrants in Europe, such as Uber, MOIA, and CleverShuttle, competing with traditional taxi providers. Rapid developments in available algorithms, data sources, and real-time information systems offer new possibilities of maximizing the efficiency of MoD services. In particular, the use of demand predictions is expected to contribute to a reduction in operational costs and an increase in overall service quality. This paper examines the potential of predictive fleet management strategies applied to a large-scale real-world taxi dataset for the city of Munich. A combination of state-of-the art dispatching algorithms and a predictive RHC optimization for idle vehicle rebalancing was developed to determine the scale by which a fleet size can be reduced without affecting service quality. A simulation study was conducted over a one-week period in Munich, which showed that predictive fleet strategies clearly outperform the present strategy in terms of both service quality and costs. Furthermore, the results showed that current taxi fleets could be reduced to 70% of their original size without any decrease in performance. In addition, the results indicated that the reduced fleet size of the predictive strategy was still 20% larger compared to the theoretical optimum resulting from a bipartite matching approach.

scholarly journals The Panglima Laot of Aceh: a case study in large-scale community-based marine management after the 2004 Indian Ocean tsunami

Oryx ◽  
2012 ◽  
Vol 46 (4) ◽  
pp. 495-500 ◽  
Author(s):  
Crispen Wilson ◽  
Matthew Linkie
Keyword(s):  
Indian Ocean ◽  
Local Knowledge ◽  
Large Scale ◽  
Management Strategies ◽  
Indian Ocean Tsunami ◽  
Government Officials ◽  
2004 Indian Ocean Tsunami ◽  
Marine Management ◽  
Data Points

AbstractDespite dating back over 400 years the relevance of traditional fisheries management in Aceh, Indonesia, still remains high. Aceh was, however, greatly affected by the December 2004 Indian Ocean tsunami that claimed an estimated 167,000 lives, including 14,000 fishermen and 59 of the 193 traditional marine leaders (Panglima Laot). This tragic loss of life was accompanied by a substantial loss of local knowledge, such as the locations of hazardous fishing grounds. In this study we describe an innovative project that sought to rebuild a post-tsunami fisheries sector by re-engaging and empowering the Panglima Laot. During April–June 2008 GPS (global positioning system) sounding devices were installed on 53 local fishing boats and hazardous fishing areas mapped based on local knowledge, and shared amongst fishermen. During July–December 2008 nearly five million GPS data points were collected, from which detailed bathymetric maps were produced and shared between fishermen and Aceh government officials. Significant project outputs included a map of fishing areas over 20,000 km2, which included three new seamounts, one of which expanded Aceh's provincial boundary by > 1.3 million ha, and a Panglima Laot decree that reduced fishing in hazardous areas of high coral density by 23.3%. Our findings have wide applicability. Locally, the introduction of GPS technology and sharing of traditional knowledge resulted in fishermen developing and implementing their own management strategies and demonstrating their ability to stay out of restricted areas. Provincially, this project provided a framework through which government agencies and academic institutions could effectively engage with local customary leaders and their fishing communities.

Analyzing Simulation-Based Active Traffic Management Impact on a Large-Scale Regional Network

2019 ◽  
Vol 2673 (8) ◽  
pp. 638-647
Author(s):  
Minha Lee ◽  
Chenfeng Xiong ◽  
Zheng Zhu ◽  
Weiyi Zhou ◽  
Lei Zhang
Keyword(s):  
Traffic Management ◽  
Large Scale ◽  
Dynamic Traffic Assignment ◽  
Management Strategies ◽  
Ramp Metering ◽  
Vast Number ◽  
Traffic Conditions ◽  
Road Systems ◽  
Traffic Impacts

A vast number of real-time corridor management strategies have been introduced because the dynamics of traffic patterns and increased congestion result in challenging problems on road systems. Although these strategies can offer positive impacts on regional traffic, their evaluation tools are often limited to the scope of one specific corridor. To fill this gap, this study integrates a mesoscopic dynamic traffic assignment simulation model with an existing traffic-responsive ramp metering strategy. This integrated model is suitable for network-wide analysis and large-scale simulation of integrated corridor management strategies. The integrated modeling platform is demonstrated as a practice-ready tool. We present a case study that explores the benefits of metering control under various traffic conditions in a real-world network in Maryland. Both local and network-wide impacts are illustrated in the case study. This is one of the first attempts to simultaneously analyze network-wide traffic impacts and capture minute-by-minute demand–supply interactions under managed corridor strategies. The results indicate that ramp metering is beneficial even under non-recurrent traffic conditions at multiple spatial resolutions.

Centralized vehicle leasing in humanitarian fleet management: the UNHCR case

2015 ◽  
Vol 5 (3) ◽  
pp. 387-404 ◽  
Author(s):  
Nathan Kunz ◽  
Luk N. Van Wassenhove ◽  
Rob McConnell ◽  
Ketil Hov
Keyword(s):  
Poor Performance ◽  
Fleet Management ◽  
Longitudinal Case Study ◽  
Content Type ◽  
Fleet Size ◽  
Humanitarian Organizations ◽  
High Commissioner ◽  
Before And After ◽  
Negative Impacts

Purpose – Fleet management is a key function in humanitarian organizations, but is not always recognized as such. This results in poor performance and negative impacts on the organization. The purpose of this paper is to demonstrates how the UN High Commissioner for Refugees (UNHCR) managed to substantially improve its fleet management through the introduction of an Internal Leasing Program (ILP), in which headquarters procures vehicles and leases them to field offices. Design/methodology/approach – This paper develops a framework for fleet management based on a longitudinal case study with UNHCR. It compares fleet performance indicators before and after implementation of an ILP. Findings – At UNHCR, vehicle procurement was driven by availability of funding. Fleet management was highly decentralized and field offices had limited awareness of its importance. These systems and behaviors led to major challenges for the organization. The introduction of the ILP positively impacted fleet management at UNHCR by reducing fleet size, average age of fleet and procurement costs. Practical implications – This paper provides fleet managers with a tool for analyzing their fleet. The frameworks and actions described in this paper contain practical recommendations for achieving a well-performing fleet. Originality/value – This paper is the first to analyze fleet management before and after introduction of an ILP. It describes the benefits of this model based on empirical data, and develops frameworks to be used by researchers and practitioners.

scholarly journals Environmental Impacts of Reusable Transport Items: A Case Study of Pallet Pooling in a Retailer Supply Chain

2019 ◽  
Vol 11 (11) ◽  
pp. 3147 ◽  
Author(s):  
Riccardo Accorsi ◽  
Giulia Baruffaldi ◽  
Riccardo Manzini ◽  
Chiara Pini
Keyword(s):  
Information System ◽  
Supply Chain ◽  
Geographic Information System ◽  
Environmental Impacts ◽  
Large Scale ◽  
Best Practice ◽  
Management Strategies ◽  
Geographic Information ◽  
Pollutant Emissions

Manufacturing, storage, and transportation processes are typically facilitated by pallets, containers, and other reusable transport items (RTIs) designed to guarantee many cycles along a lifespan of several years. As a consequence, both supply and reverse transportation of RTIs need to be managed to avoid stockout along the supply chain and the unsustainable production of new tools from virgin materials. This paper focuses on the business of pallet management by analyzing the transport operations of a pallet pooling network serving a large-scale nationwide retailer. The pooler is responsible for supplying, collecting, and refurbishing pallets. The combination of the pooler’s management strategies with different retailer network configurations results in different pooling scenarios, which are assessed and compared in this paper through a what-if analysis. The logistical and environmental impacts generated by the pallet distribution activities are quantified per each scenario through a tailored software incorporating Geographic Information System (GIS) and routing functionalities. Findings from this analysis suggest how to reduce vehicle distance traveled (vehicles-km) by 65% and pollutant emissions by 60% by combining network infrastructures and pooling management strategies—identifying an empirical best practice for managers of pallet businesses.

scholarly journals PARADIGM SHIFT: ENGINEERING ARTIFICIAL INTELLIGENCE AND MANAGEMENT STRATEGIES FUSION

2016 ◽  
Vol 4 (2) ◽  
pp. 1-16
Author(s):  
A. H. Harb ◽  
AbdAlhameedAbdAlhameed Alsayyid
Keyword(s):  
Artificial Intelligence ◽  
Strategic Management ◽  
Large Scale ◽  
Qualitative Methodology ◽  
Management Strategies ◽  
Global Market ◽  
Ai Planning ◽  
Time Data ◽  
Test Procedures ◽  
Organizational Goals

The purpose of this paper is to investigate management strategies that use Artificial Intelligence to perceive, capture, and process real-time data to predict and direct the performance of an enterprise.  AI systems can account for errors in human judgment through computational processes that supersede the capabilities of human intelligence alone.  Qualitative methodology was used to assess components such as fuzzy logic that can produce answers determined by multiple factors that can be integrated into a determinant solution. Quantifying the neurocircuitry of strategic management processes in tacticians will serve as the foundation for AI and management strategies engineering fusion.  When AI is programmed to motivate, interact, and make judgements based upon statistical measurements, the fusion of AI and management engineering can increase efficiency and effectiveness in the attainment of organizational goals. Results demonstrated the application of AI planning can range from directing large-scale machinery overhaul procedures, spacecraft mission planning, emergency response, assembling test procedures for rocket launchers, and delivery truck scheduling. A thorough understanding AI for strategic management engineering fusion and its underlying concepts is a prerequisite to competitive advantage in a global market.

Strategic vehicle fleet management–a joint solution of make-or-buy, composition and replacement problems

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Adam Redmer
Keyword(s):  
Management Strategy ◽  
Large Scale ◽  
Real Life ◽  
Optimization Methods ◽  
Solution Procedure ◽  
Fleet Management ◽  
Content Type ◽  
Fleet Size ◽  
Real Life Data ◽  
Management Problems

PurposeThe purpose of this paper is to develop an original model and a solution procedure for solving jointly three main strategic fleet management problems (fleet composition, replacement and make-or-buy), taking into account interdependencies between them.Design/methodology/approachThe three main strategic fleet management problems were analyzed in detail to identify interdependencies between them, mathematically modeled in terms of integer nonlinear programing (INLP) and solved using evolutionary based method of a solver compatible with a spreadsheet.FindingsThere are no optimization methods combining the analyzed problems, but it is possible to mathematically model them jointly and solve together using a solver compatible with a spreadsheet obtaining a solution/fleet management strategy answering the questions: Keep currently exploited vehicles in a fleet or remove them? If keep, how often to replace them? If remove then when? How many perspective/new vehicles, of what types, brand new or used ones and when should be put into a fleet? The relatively large scale instance of problem (50 vehicles) was solved based on a real-life data. The obtained results occurred to be better/cheaper by 10% than the two reference solutions – random and do-nothing ones.Originality/valueThe methodology of developing optimal fleet management strategy by solving jointly three main strategic fleet management problems is proposed allowing for the reduction of the fleet exploitation costs by adjusting fleet size, types of exploited vehicles and their exploitation periods.

scholarly journals A Case Study of Factors Affecting the Performance of the Hotel Industry of Chiang Mai in Thailand and the Impact of Covid-19: Taking De Chai Hotel Group as an Example

2020 ◽  
pp. 63-76
Author(s):  
Jui-Lung Chen ◽  
Kusumalee Kitingern
Keyword(s):  
Large Scale ◽  
Management Strategies ◽  
Hotel Industry ◽  
Jel Classification ◽  
Chiang Mai ◽  
Factors Affecting ◽  
Industry Performance ◽  
Group A ◽  
The Impact

Tourism has made a significant contribution to Thailand's economy, bringing considerable tourism revenue to Thailand every year, and driving the sustained growth of related industries. This study focused on the factors that affect the performance of the hotel industry of Chiang Mai in Thailand, taking De Chai Hotel Group, a local large-scale hotel group, as a case study, and discussed the impact of COVID-19 on it and its countermeasures. This study also put forward relevant suggestions as a reference for the hotel industry to formulate management strategies and future development. JEL classification numbers: L25, L83. Keywords: Tourism, Hotel industry, Performance, COVID-19.

The Quality Of Service Delivery In Zimbabwean Urban Councils: A Case Study Of Bindura Municipality 2009 To 2011.

2012 ◽  
Vol 5 ◽  
Author(s):  
Denhere Webster ◽  
Tafirei Felex ◽  
Onias Zivanai ◽  
Muchingami Lovemore
Keyword(s):  
Quality Of Service ◽  
Quality Management ◽  
Service Quality ◽  
Service Delivery ◽  
Survey Design ◽  
Management Strategies ◽  
Total Quality ◽  
Structured Interviews

The study sought to assess the quality of service delivery in Zimbabwean urban councils using Bindura Municipality as a case study. The objectives of the study were to establish the levels of service quality, determine the challenges that hindered quality service delivery, analyse the service quality management strategies and propose suitable strategies Bindura municipality can adopt to enhance service quality delivery.A descriptive survey design was used and questionnaires and structured interviews were used as data collection instruments. A sample of 300 householdswas drawn from the municipality rate payers’ data base. The population was stratified into low, medium and high density residents. Systematic random sampling was used to draw the participants in each stratum. Ten interviews were conducted with senior management using convenience sampling and documentary evidence was generated from menus, minutes and reports. The major findings were that the quality of service delivery was generally poor. This was mainly attributed to inadequate and disintegrated service delivery and management strategies. In addition human resource issues, poor governance structures and political interferences were causes of concern. It was concluded that the quality of service delivery by Bindura Municipality fell far short of residents’ expectations.The study recommended that for effective service delivery the municipality should among other strategies, adopt blue printing and total quality management. 

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