Incorporating Customer Preferences and Market Trends in Vehicle Package Design

2007 ◽  
Author(s):  
Deepak Kumar ◽  
Chris Hoyle ◽  
Wei Chen ◽  
Nanxin Wang ◽  
Gianna Gomez-Levi ◽  
...  
Keyword(s):  
Choice Model ◽  
Critical Role ◽  
Choice Modeling ◽  
System Level ◽  
Demand Model ◽  
Package Design ◽  
Customer Preferences ◽  
Demand Models ◽  
Multiple Component ◽  
The Impact

Demand models play a critical role in enterprise-driven design by expressing revenues and costs as functions of product attributes. However, existing demand modeling approaches in the design literature do not sufficiently address the unique issues that arise when complex systems are being considered. Current approaches typically consider customer preferences for only quantitative product characteristics and do not offer a methodology to incorporate customer preference-data from multiple component/subsystem-specific surveys to make product-level design trade-offs. In this paper, we propose a hierarchical choice modeling approach that addresses the special needs of complex engineering systems. The approach incorporates the use of qualitative attributes and provides a framework for pooling data from multiple sources. Heterogeneity in the market and in customer-preferences is explicitly considered in the choice model to accurately reflect choice behavior. Ordered logistic regression is introduced to model survey-ratings and is shown to be free of the deficiencies associated with competing techniques, and a Nested Logit-based approach is proposed to estimate a system-level demand model by pooling data from multiple component/subsystem-specific surveys. The design of the automotive vehicle occupant package is used to demonstrate the proposed approach and the impact of both packaging design decisions and customer demographics upon vehicle choice are investigated. The focus of this paper is on demonstrating the demand (choice) modeling aspects of the approach rather than on the vehicle package design.

Regional Bicycle Network Evaluation and Strategic Planning: A Quantitative Methodological Approach Despite Limited Data Sources for Cycling

2021 ◽  
pp. 036119812110288
Author(s):  
Alex van Dulmen ◽  
Martin Fellendorf
Keyword(s):  
Travel Demand ◽  
Choice Model ◽  
Methodological Approach ◽  
Data Availability ◽  
Data Sources ◽  
Test Case ◽  
Demand Model ◽  
Limited Data ◽  
Demand Models ◽  
Bicycle Infrastructure

In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.

Measuring the impact of crises in the horticultural sector: the case of Spain

2019 ◽  
Vol 121 (5) ◽  
pp. 1050-1063 ◽  
Author(s):  
Juan Carlos Pérez-Mesa ◽  
María del Mar Serrano-Arcos ◽  
Raquel Sánchez-Fernández
Keyword(s):  
Empirical Analysis ◽  
Critical Role ◽  
Point Of View ◽  
Strong Impact ◽  
Short Term ◽  
Content Type ◽  
On Demand ◽  
Demand Models ◽  
The Impact ◽  
Practical Implications

PurposeThe purpose of this paper is to review the literature on image crises in the food industry as well as provide a diachronic analysis to distinguish between the varying types of crises that played a critical role in the horticultural sector in recent decades, focussing on the particular case of Spain as the largest horticultural exporter in Europe. This research also analyses the economic impact of these crises upon demand.Design/methodology/approachAn empirical analysis has been conducted using inverse demand models to determine the prospective impact on demand of the image crises in the main European destination markets.FindingsThe empirical analysis reveals an immediate impact upon demand (imports) in the short term. Sector crises invariably have one or many “explosion” points when they reach the public sphere. These events reduce demand among European consumers, ultimately leading to a decrease in imported goods. The tested models revealed considerably significant losses that subsequently reduce annual exports by more than 3 per cent. The analysis also reveals strong effects of complementarity and substitution among the various products that comprise the horticultural supply.Research limitations/implicationsThis study has not taken into account several movements that have also affected the horticultural sector, such as “anti-consumption” and boycotts. Empirical results reveal a strong impact of image crises on demand (imports) in the short term. Consequently, there is an evident need to undertake actions, managed from the supply origin, that reach the consumer and effectively re-establish the prestige of the Spanish production system.Practical implicationsThis paper highlights the importance of the mass media in consumer attitudes and perceptions, and the need to create channels of direct communication to break the information asymmetry between production and consumption areas.Originality/valueThis paper sheds new light on the literature of image crises. The findings of this research have contributed to greater knowledge of how image crises influence demand. From the point of view of management, these results can have practical implications for the highly competitive sector of horticultural production.

Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?

2019 ◽  
Vol 26 (3) ◽  
pp. 461-474
Author(s):  
Tzu-Ming Liu
Keyword(s):  
Word Of Mouth ◽  
Habit Formation ◽  
Critical Role ◽  
Tourism Demand ◽  
Demand Model ◽  
Dynamic Panel Model ◽  
Empirical Results ◽  
Demand Models ◽  
Lagged Dependent Variable ◽  
Time Lagged

The effects of habit formation/persistence (HFP) and word of mouth (WOM) each play a critical role in influencing tourists’ decisions regarding whether to visit tourism destinations and therefore tourism policies and tourism management resource allocations. Nevertheless, in previous tourism demand studies, the two effects have been represented by the same time-lagged dependent variable, which makes the variable have an ambiguous meaning and biases the empirical results. The purpose of this study is to solve the ambiguity of a lagged dependent variable in tourism demand. We used economic theories regarding internal habits and external habits to clarify the meanings of HFP and WOM and revised the tourism demand model into a spatial dynamic panel model (SDPM). The empirical results suggested that an SDPM is a more accurate model for modeling tourism demand. The effects of variables in an SDPM are more consistent with theoretical expectations.

scholarly journals What Matters Most in Transportation Demand Model Specifications: A Comparison of Outputs in a Mid-size Network

2015 ◽  
Author(s):  
T. Donna Chen ◽  
Kara Kockelman ◽  
Yong Zhao
Keyword(s):  
Travel Demand ◽  
Choice Model ◽  
Mode Choice ◽  
Demographic Data ◽  
Time Of Day ◽  
Demand Model ◽  
Land Use Patterns ◽  
Transportation Demand ◽  
Step Model ◽  
The Impact

This paper examines the impact of travel demand modeling (TDM) disaggregation techniques in the context of medium-sized communities. Specific TDM improvement strategies are evaluated for predictive power and flexibility with case studies based on the Tyler, Texas, network. Results suggest that adding time-of-day disaggregation, particularly in conjunction with multi-class assignment, to a basic TDM framework has the most significant impacts on outputs. Other strategies shown to impact outputs include adding a logit mode choice model and incorporating a congestion feedback loop. For resource-constrained communities, these results show how model output and flexibility vary for different settings and scenarios.BACKGROUND Transportation directly provides for the mobility of people and goods, while influencing land use patterns and economic activity, which in turn affect air quality, social equity, and investment decisions. Driven by the need to forecast future transportation demand and system performance, Manheim (1979) and Florian et al. (1988) introduced a transportation analysis framework for traffic forecasting using aggregated data that provide the basis for what is known as the four-step model: a process involving trip generation, then trip distribution and mode choice, followed by route choice. Aggregating demographic data at the zone level, the four-step model generates trip productions based on socioeconomic data (e.g., household counts by income and size) and trip attractions primarily based on jobs counts. The model then proportionally distributes trips between each origin and destination (OD) zone pair based on competing travel attractions and impedances, under the assumption that OD pairings with higher travel costs draw fewer trips. Trips between each OD pair are split among a variety of transportation modes, allocating trips to private vehicle, transit, or other

System-based probabilistic optimization of fluid viscous dampers equipped in cable-stayed bridges

2018 ◽  
Vol 21 (12) ◽  
pp. 1815-1825 ◽  
Author(s):  
Jian Zhong ◽  
Zhangliang Hu ◽  
Wancheng Yuan ◽  
Liang Chen
Keyword(s):  
Fragility Curves ◽  
System Level ◽  
Viscous Damper ◽  
Optimal Parameters ◽  
Demand Model ◽  
Fluid Viscous Damper ◽  
Fluid Viscous Dampers ◽  
Cable Stayed Bridge ◽  
The Impact ◽  
Cable Stayed Bridges

This study presents a methodology to evaluate the optimal parameters of fluid viscous damper for cable-stayed bridges using the system-level fragility assessment approach. Instead of investigating the impact of different isolation devices on the component’s vulnerability separately, this study focuses on evaluating the optimal parameters of fluid viscous damper to achieve the best overall performance of cable-stayed bridge as a system. Numerical model of a cable-stayed bridge with the most common configuration in China is established using OpenSEES that can account for their nonlinear response and uncertainty treatment. A joint probabilistic seismic demand model and Monte Carlo simulation are employed to obtain the system fragility of cable-stayed bridges by accounting for the contribution of multicomponents to the global damage state. The system-level fragility curves and component fragility curves are compared before and after the application of fluid viscous damper with different parameters. The results indicate that a given parameter of the fluid viscous damper may have a negative impact on some components, yet lead to a better performance of the bridge as a system. Thus, in order to obtain comprehensive knowledge of bridge performance and derive the accurate optimal parameters of fluid viscous damper, it is necessary to consider the fragility based on bridge system.

Accuracy and Performance of Improved Speed-Flow Curves

1998 ◽  
Vol 1646 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Richard G. Dowling ◽  
Rupinder Singh ◽  
Willis Wei-Kuo Cheng
Keyword(s):  
Travel Demand ◽  
Traffic Assignment ◽  
Demand Model ◽  
Power Functions ◽  
Flow Curves ◽  
Speed Flow ◽  
Demand Models ◽  
Higher Power ◽  
The Impact ◽  
Travel Demand Model

Skabardonis and Dowling recommended updated Bureau of Public Road speed-flow curves for freeways and signalized arterials to improve the accuracy of speed estimates used in transportation demand models. These updated curves generally involved the use of higher power functions that show relatively little sensitivity to volume changes until demand exceeds capacity, when the predicted speed drops abruptly to a very low value. Skabardonis and Dowling demonstrated that the curves provide improved estimates of vehicle speeds under both uncongested and queueing conditions; however, they did not investigate the impact of these curves on the performance of travel demand models. Practitioners have been concerned about the impacts of such abrupt speed-flow curves on the performance of their travel demand models. Spiess has stated that higher power functions are more difficult computationally for computers to evaluate and that more abrupt speed-flow curves adversely affect the rate of convergence to equilibrium solutions in the traffic assignment process. In this paper the impact of the Skabardonis and Dowling updated speed-flow curves on the performance of selected travel demand models is investigated. The updated speed-flow curves were found to significantly increase travel demand model run times. However, it is demonstrated that an alternative speed-flow equation developed by Akçelik has similar or better accuracy and provides much superior convergence properties during the traffic assignment process. The Akçelik curve significantly reduced travel demand model run times.

On the Formation of Travel Demand Models and Economic Evaluation Measures of User Benefit

1977 ◽  
Vol 9 (3) ◽  
pp. 285-344 ◽  
Author(s):  
H C W L Williams
Keyword(s):  
Economic Evaluation ◽  
Travel Demand ◽  
Choice Model ◽  
Demand Model ◽  
Random Utility Theory ◽  
Underlying Assumption ◽  
Evaluation Measures ◽  
Planning Models ◽  
Demand Models ◽  
Special Cases

This paper examines a variety of issues within the context of two main themes: the formation of travel demand models and economic evaluation measures which are mutually consistent within a theory of rational choice; and a consideration of the structure of models which are representations of the trip decision process over several dimensions: location, mode, and route. Random utility theory is invoked to explore both the role and properties of composite costs or index prices in the ‘recursive’ approach to the structuring of travel choice models, and their significance in the economic evaluation problem. It is shown that the specification of these costs must be made very precisely, with respect to the demand model form chosen, in order to retain the underlying assumption that the traveller is an optimal decisionmaker. It is argued that the structure of ‘simultaneous’ models currently in use is inconsistent with the form of utility function assumed to generate those models. Furthermore, it is shown that the ‘simultaneous’ and ‘recursive’ forms are special cases of a more general choice model structure which takes specific account of correlation or ‘commonality’ of trip attributes. A number of applications are discussed in which consistent demand models and perceived user benefit measures are constructed. These include the formation of strategic transport planning models and of models for mixed-mode, multimode, and multiroute systems. The formalism allows definitive answers to be given to a number of problems of current interest in transportation planning, which have been incorrectly or incompletely treated.

Environmental Accounting in Greater Vancouver Transportation System Planning

1997 ◽  
Vol 1601 (1) ◽  
pp. 13-20
Author(s):  
Peter Bein ◽  
Mike Kawczynski
Keyword(s):  
Travel Demand ◽  
Demand Management ◽  
Environmental Accounting ◽  
Environmental Benefits ◽  
System Level ◽  
User Cost ◽  
Demand Model ◽  
Travel Demand Management ◽  
The Impact ◽  
Project Level

Transportation facility and system options for the greater Vancouver region are evaluated using the provincial guidelines for full-cost accounting. The impact of the monetized environmental accounts on the overall evaluation is presented, using facility, system option, and pricing examples from the regional plan. Within project options that are homogeneous with respect to travel demand management or modal split, environmental account values do not differ much, just as in the user cost accounts. Monetized environmental account values are two to three times smaller than the user cost in project-level cases. At the system level, in which travel demand management and modal choice are among the principal objectives, environmental benefits are decisive, whereas user benefits may be inconclusive. The estimated monetized subsidy to full costs of the automobile underpricing of personal transport has increased from 20 percent to more than 50 percent with analytical advances since 1993. Serious intangible externalities remain unmonetized, but should nevertheless be considered. Limitations of transportation demand model and data (peak spreading, 24-hr operation, and determination of vehicle speeds) require remediation for accurate environmental accounting. Fuel consumption and vehicle operating costs at low levels of service, and impacts of travel demand management on travel behavior, are decisive for system appraisals. At the project level, queueing data, level of service, and capacity must be available. Speed-and vehicle-specific emission rates are also necessary for accurate accounting at the project and system levels.

scholarly journals A methodological review of demand analysis: An example of health care services

2012 ◽  
pp. 119-130 ◽  
Author(s):  
Shiva Raj Adhikari
Keyword(s):  
Health Care ◽  
Health Services ◽  
Discrete Choice ◽  
Choice Model ◽  
Health Sector ◽  
Choice Behaviour ◽  
Time Duration ◽  
Continuous Choice ◽  
Demand Models ◽  
The Impact

Demand describes the quantity of goods or services per unit of time that an individual purchases and consumes given the set of the prices and income of the consumer. The demand models based on continuous choice or discrete choice are popular in the economic literatures. Discrete choice depicts where and what kinds of health services to consume while the continuous choice portrays how much of health services to consume. Specification of the behavioural model and estimation of the parameters of the model that are interrelated tasks in discrete choice model are challenging for the researchers. Health sector data have special features like discrete nature of the data, problems of censoring, integer counts or time duration and several factors complicate attempts to obtain unbiased estimates of the impact of variables that influence demand for health care. The health care data provide wider applications of econometrics models. These models have some advantages in presenting and analyzing the choice behaviour; however, they have some limitations as well. Subsequently, the researchers are continuously interested to find and to apply appropriate models to describe the choice behaviour of the decision makers.DOI: http://dx.doi.org/10.3126/ejdi.v13i0.7215 Economic Journal of Development Issues Vol.13 & 14 2011, pp.119-130

scholarly journals Evaluating the Flexibility Benefits of Smart Grid Innovations in Transmission Networks

2021 ◽  
Vol 11 (22) ◽  
pp. 10692
Author(s):  
Vasiliki Vita ◽  
Christos Christodoulou ◽  
Ilias Zafeiropoulos ◽  
Ioannis Gonos ◽  
Markos Asprou ◽  
...  
Keyword(s):  
Smart Grid ◽  
Power System ◽  
Performance Indicators ◽  
Renewable Energy Sources ◽  
Critical Role ◽  
Clean Energy ◽  
Electricity Sector ◽  
System Level ◽  
Use Case ◽  
The Impact

The decision-making process during system planning of power systems is something that requires integrated tools that evaluate technical parameters, environmental impact, and overall costs and benefits with various performance indicators (i.e., key performance indicators KPIs). Several cost–benefit analysis approaches have been presented worldwide, providing analytic procedures to quantify the impact and practical effects of specific electricity projects. The implementation of innovation technology into the electricity networks play a critical role to optimizing overall costs. The targets set by the Clean Energy Package have been the main driver for the disruption occurring in the electricity sector, setting electrification of sectors and digitalization as additional emerging challenges. In the present paper, an evaluation approach for the flexibility benefits of smart grid innovations will be presented, as it has been developed and implemented in the context of the Horizon 2020 Research and Innovation project FLEXITRANSTORE. Flexibility is a prerequisite in an effort to achieve an electrical system of low CO2 emissions. Moreover, flexibility contributes to the increase of renewable energy sources penetration, to the network investments deferral and to the enhancement of the efficiency of the system operation, avoiding generation capacity oversizing. Thus, flexibility has been the scope of many projects lately. FLEXITRANSTORE pilot projects are implemented in various sites across Europe and are briefly presented and the respective technologies are propagated on system level approach, evaluating the respective benefits on a specific use case for the power system of Cyprus, where the one of the pilots is located. The paper tries to show the big picture of the project and presents system study use case to highlight the system impacts of the technologies. To this direction, the installation of a BESS to the Cypriot power system is studied, in an effort to examine its impact to the enhancement of the system’s flexibility, considering IRRE as an indicator.

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