Methodological Approach for Evaluation and Improvement of Quality Transport Service in Public Road Passenger Transport

Achieving the appropriate level of quality transport service is essential in the operations of the carriers in the public road intercity line passenger transport due to an increased competition between road carriers in the market of transport services. Effective assessment of achieved competitiveness is important for the survival and development of public road passenger carriers. The problem of research is reflected in the appropriate organization and giving importance to the criteria of quality of transport service in order to improve the methodology of its evaluation with the aim of optimizing business and competitiveness in public road intercity line passenger traffic. An efficient method for evaluating the quality of transport service would solve the problem of assessing the quality of transport service and assessing the competitiveness of bus carriers. It is proposed to develop a multi-criteria model for evaluating the quality of transport services by the method of measuring passenger satisfaction. The developed VAZP model (Multicriteria Analysis of Passenger Satisfaction) is based on multicriteria analysis AHP (Analytical Hierarchical Process) which is based on the disaggregated approach and linear programming modeling. The results of the research will be described using numerical values and will be graphically presented using descriptive statistical analysis. The ability to qualitatively represent passengerꞌs judgments and preferences makes the model a suitable tool for assessing passenger satisfaction and evaluating quality service in the transportation sector, as well as strategically positioning and gaining a competitive opportunities in the transportation services market. Using the Expert Choice software tool and sensitivity analysis it would establish differences between reached level of the quality of transport service of individual bus carriers and propose possible improvements to the business to gain a competitive advantage in the market of transportation services. Systematic optimization and quality management through continuous assessment of market competitiveness contributes to the development of the business of companies for road passenger transportation

Immunity-based evolutionary algorithm for optimal global container repositioning in liner shipping

Global container repositioning in liner shipping has always been a challenging problem in container transportation as the global market in maritime logistics is complex and competitive. Supply and demand are dynamic under the ever changing trade imbalance. A useful computation optimization tool to assist shipping liners on decision making and planning to reposition large quantities of empty containers from surplus countries to deficit regions in a cost effective manner is crucial. A novel immunity-based evolutionary algorithm known as immunity-based evolutionary algorithm (IMEA) is developed to solve the multi-objective container repositioning problems in this research. The algorithm adopts the clonal selection and immune suppression theories to attain the Pareto optimal front. The proposed algorithm was verified with benchmarking functions and compared with four optimization algorithms to assess its diversity and spread. The developed algorithm provides a useful means to solve the problem and assist shipping liners in the global container transportation operations in an optimized and cost effective manner. © 2010 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

STRATEGI PENINGKATAN PANGSA PASAR ANGKUTAN UMUM DI KOTA SURAKARTA

An important problem in urban areas is traffic congestion that occurs on the road network during the day. One cause of this problem is the high number of private car usage with low occupancy levels while public transport services are under-utilized, although the use of public transport is more efficient than that of private cars. Therefore, efforts to increase public transport use are needed to reduce transportation problems, such as traffic congestion. Mode choice is one important step in transportation modeling because this stage provides information necessary to evaluate the condition of the transportation network, including traffic congestion in the network. This model aims to determine the individual attributes and modes, which influence in selecting a mode among available modes, using the utility function parameters. Sensitivity of mode choice can be seen through the sign and magnitude of the parameters contained in this model. In this study, a simulation was conducted with a purpose to increase the market share of public transport in the City of Surakarta.Keywords: mode choice, utility function, public transpor

A scoping review

The article processing charge was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 491192747 and the Open Access Publication Fund of Humboldt-Universität zu Berlin.Malnutrition continues to be a major problem with negative implications on economic and human development in many parts of the world, including in Sub-Saharan Africa (SSA). Strengthening promising underutilized crops that are nutrient dense, climate resilient, and locally adaptable is an instrumental approach to enhancing dietary diversity. Due to their nutritional and economic benefits, African Indigenous Vegetables (AIVs) have the potential to contribute to livelihoods and address challenges of food and nutrition insecurity. Despite their importance but due to their perishability, AIVs tend to suffer from high post-harvest losses (PHLs). Effective distribution systems along the value chain have the potential to reduce PHLs for AIVs. We therefore conducted a scoping review on transport systems and coordination in AIVs value chains in SSA. The objectives of this review were to summarize and analyze the focus of research in AIVs transport, to analyze the extent to which the literature synthesizes interactions of sub-components of the chains, and to identify knowledge gaps in AIVs transport literature. Based on the research foci, we categorize the reviewed articles into seven themes. Our analyses indicate that distance to agricultural market is a fundamental aspect of AIVs transportation, as it interacts with transport costs, market participation, produce quality, and profit efficiency. Results show that collective action is instrumental in the coordination of AIVs transportation and that it contributes to cost reduction. Following light exploration of determinants of choice of means of transport, we recommend further research in this area for improvement of transportation in AIVs value chains.Peer Reviewe

An integrated fleet assignment and itinerary choice model for a new flexible aircraft

In this paper we present methodologies for improving the demand-responsiveness of air transportation systems. The main ingredients are the flexibility in transportation capacity provided by an innovative aircraft and an integrated model where supply-demand interactions are explicitly formulated. The integrated model benefits from the simultaneous schedule planning and revenue management decisions. The schedule planning consists of schedule design and fleet assignment models. Revenue management decisions are integrated with an itinerary choice model which gives the market shares of the available itineraries in the market according to their price, travel time, number of stops and departure time of the day. The integrated model also includes spill and recapture effects based on the demand model. Furthermore, the demand model is developed for economy and business classes and the seat allocation for these classes is determined by the integrated model. The resulting model is a mixed integer nonlinear problem and we propose a heuristic to tackle with the complexity of the problem

A System Dynamics Approach on Sustainability Assessment of the United States Urban Commuter Transportation

Transportation sector is one of the largest emission sources and is a cause for human health concern due to the high dependency on personal vehicle in the U.S. Transportation mode choice studies are currently limited to micro- and regional-level boundaries, lacking of presenting a complete picture of the issues, and the root causes associated with urban passenger transportation choices in the U.S. Hence, system dynamics modeling approach is utilized to capture complex causal relationships among the critical system parameters affecting alternative transportation mode choices in the U.S. as well as to identify possible policy areas to improve alternative transportation mode choice rates for future years up to 2050. Considering the high degree of uncertainties inherent to the problem, multivariate sensitivity analysis is utilized to explore the effectiveness of existing and possible policy implications in dynamic model in the terms of their potential to increase transit ridership and locating critical parameters that influences the most on mode choice and emission rates. Finally, the dissertation advances the current body of knowledge by integrating discrete event simulation (multinomial fractional split model) and system dynamics for hybrid urban commuter transportation simulation to test new scenarios such as autonomous vehicle (AV) adoption along with traditional policy scenarios such as limiting lane-mile increase on roadways and introducing carbon tax policy on vehicle owners. Overall, the developed simulation models clearly indicate the importance of urban structures to secure the future of alternative transportation modes in the U.S. as the prevailing policy practices fail to change system behavior. Thus, transportation system needs a paradigm shift to radically change current impacts and the market penetration of AVs can be one of the reforms to provoke this transition since it is expected to revolutionize mode choice, emission trends, and the built environment

Market Penetration of New Vehicle Technology: A Generalized Dynamic Approach for Modeling Discrete-Continuous Decisions

Energy consumption and greenhouse gas (GHG) emissions are at their highest levels in history. One of the largest sources of GHG emissions in the United States is from burning fossil fuels for transportation. In developing countries GHG emissions from private vehicles are growing rapidly with their wealth. Government agencies attempt to reduce dependency on fossil fuels by regulating the ownership/usage of private vehicles, promoting vehicles with higher engine efficiency, introducing new fuel types, and defining stricter emission standards. Hybrid and electric vehicles are gaining consumers’ interest and trust, and their sale shares are gradually increasing. Meanwhile, environmental awareness, taxes on conventional gasoline cars, and incentives for cars with new technologies, make small and alternative-fuel vehicles more attractive. The future of personal transportation is uncertain; in particular, car ownership, vehicle type preferences and usage behavior are likely to change in surprising ways. In this context, it is important to assess the influence of the vehicle market evolution on consumer’s vehicle demands and travel behaviors. This dissertation proposes a comprehensive modeling framework that is able to analyze different dimensions of the car purchasing and usage problem. A multi-facet approach is taken for the investigation, and different model types are proposed. The investigation starts with a mixed logit model that accounts for time-series choices, heterogeneity in preferences and correlation across alternatives. This model is estimated on Stated Preference Survey data collected in Maryland and quantifies market elasticities and willingness-to-pays for improving car characteristics. Afterward, a dynamic discrete choice model is developed to predict the diffusion of hybrid and electric cars in Maryland, with consideration of household’s forward-looking behavior and stochasticity in vehicle market evolution. This model focuses on vehicle purchase time and vehicle type choice. To further consider vehicle usage decision, an integrated discrete-continuous choice model is proposed to jointly estimate household’s discrete choices on vehicle type/ownership and continuous choice on vehicle usage. The model is applied to estimate household-level vehicle emissions in Maryland, USA and Beijing, China. The dissertation concludes with a sequential discrete-continuous choice model. The modeling framework is applied to estimate vehicle ownership and usage decisions of forward-looking agents over time in a finite time horizon. In particular, a recursive probit model is formulated to estimate a sequence of vehicle holding decisions, while a regression is used to estimate a sequence of vehicle usage decisions. The proposed model is tested and validated on simulated discrete and continuous choices in a car ownership problem setting. The dissertation contributes to the theory of dynamic models for discrete-continuous decisions. The sequential discrete-continuous choice model is the first to measure the dynamic interdependency between discrete choice and continuous choice over time. The dissertation also contributes to the understanding of critical transportation issues, including market penetration of new vehicle technology, estimation of household-level vehicle emissions, and policy evaluation for promoting green vehicles and reducing dependency on cars and emissions

Air Taxi Skyport Location Problem for Airport Access

Witnessing the rapid progress and accelerated commercialization made in recent years for the introduction of air taxi services in near future across metropolitan cities, our research focuses on one of the most important consideration for such services, i.e., infrastructure planning (also known as skyports). We consider design of skyport locations for air taxis accessing airports, where we present the skyport location problem as a modified single-allocation p-hub median location problem integrating choice-constrained user mode choice behavior into the decision process. Our approach focuses on two alternative objectives i.e., maximizing air taxi ridership and maximizing air taxi revenue. The proposed models in the study incorporate trade-offs between trip length and trip cost based on mode choice behavior of travelers to determine optimal choices of skyports in an urban city. We examine the sensitivity of skyport locations based on two objectives, three air taxi pricing strategies, and varying transfer times at skyports. A case study of New York City is conducted considering a network of 149 taxi zones and 3 airports with over 20 million for-hire-vehicles trip data to the airports to discuss insights around the choice of skyport locations in the city, and demand allocation to different skyports under various parameter settings. Results suggest that a minimum of 9 skyports located between Manhattan, Queens and Brooklyn can adequately accommodate the airport access travel needs and are sufficiently stable against transfer time increases. Findings from this study can help air taxi providers strategize infrastructure design options and investment decisions based on skyport location choices.Comment: 25 page