scholarly journals Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective

2021 ◽  
Vol 13 (6) ◽  
pp. 3035
Author(s):  
Mallikarjun Patil ◽  
Bandhan Bandhu Majumdar ◽  
Prasanta Kumar Sahu ◽  
Long T. Truong
Keyword(s):  
Stated Preference ◽  
Operating Cost ◽  
Random Parameter ◽  
Attractive Alternative ◽  
Indian Context ◽  
Purchase Cost ◽  
Choice Decision ◽  
Random Parameter Logit ◽  
Attribute Levels ◽  
Indian Cities

Electric two-wheelers (E2W) can help de-carbonize transport in Indian cities. To promote E2W as an attractive alternative compared to the conventional two-wheelers, an investigation on prospective users’ choice decisions is necessary. This paper proposed a comprehensive methodology to evaluate the prospective users’ choice decision toward electric two-wheelers and related attributes in the Indian context. In this paper, attributes such as Operating Cost (OC) savings, top speed, range, charging duration, acceleration, and purchase cost were considered to design a Stated Preference (SP) survey to collect data from prospective E2W users in Hyderabad, India. Concurrently, multinomial logit (MNL) and random parameter logit (RPL) models are developed, and the willingness-to-pay (WTP) associated with each of the identified attributes was estimated. Additionally, the effect of socio-economic characteristics on prospective users’ choice decision was also assessed. Subsequently, a sensitivity analysis was carried out to estimate the relative influence of the attributes on an individual’s choice decision in terms of the shift in probability to choose alternatives with better attribute levels than the base alternative. The results revealed that top speed was perceived as the most important attribute influencing an individual’s choice decision, followed by acceleration and charging duration. Age, income, and journey time significantly influenced an individual’s perception toward E2W and related attributes in the Indian context.

scholarly journals User Automotive Powertrain-Type Choice Model and Analysis Using Neural Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 585
Author(s):  
Fabio Luis Marques dos Santos ◽  
Paolo Tecchio ◽  
Fulvio Ardente ◽  
Ferenc Pekár
Keyword(s):  
Internal Combustion Engine ◽  
User Behavior ◽  
Choice Model ◽  
Combustion Engine ◽  
Stated Preference ◽  
Operating Cost ◽  
Internal Combustion ◽  
Ann Model ◽  
Purchase Cost ◽  
Artificial Neural Network Ann

This paper presents an artificial neural network (ANN) model that simulates user’s choice of electric or internal combustion engine automotive vehicles based on basic vehicle attributes (purchase price, range, operating cost, taxes due to emissions, time to refuel/recharge and vehicle price depreciation), with the objective of analyzing user behavior and creating a model that can be used to support policymaking. The ANN was trained using stated preference data from a survey carried out in six European countries, taking into account petrol, diesel and battery electric automotive vehicle attributes. Model results show that the electric vehicle parameters (especially purchase cost, range and recharge times), as well as the purchase cost of internal combustion engine vehicles, have the most influence on consumers’ vehicle choices. A graphical interface was created for the model, to make it easier to understand the interactions between different attributes and their impacts on consumer choices and thus help policy decisions.

Incorporating visitors’ preferences into the policy framework of a Rainforest Discovery Centre

2019 ◽  
Vol 75 (5) ◽  
pp. 779-792
Author(s):  
Fiona Jane Francis ◽  
Azman Hassan ◽  
Syamsul Herman Mohd Afandi ◽  
Alias Radam
Keyword(s):  
Stated Preference ◽  
Random Parameter ◽  
Information Provision ◽  
Policy Framework ◽  
Protection Level ◽  
Content Type ◽  
Sustainable Tourism Development ◽  
Policy Structure ◽  
Random Parameter Logit ◽  
The Individual

Purpose This study aims to incorporate visitors’ preferences for sustainable development into the policy framework of Rainforest Discovery Centre (RDC), Sabah, Malaysia. Design/methodology/approach A stated preference technique known as choice experiment (CE) method is used in this study. Four management attributes, namely, information provision (IP), protection level (PL), guided tour (GT) and entrance fee (FEE), were identified as the most relevant aspects of the RDC in Sabah. Two econometrics models which are conditional logit and random parameter logit were estimated to achieve the purpose of the study. Findings This study finds that visitors support the proposed development of RDC. The alteration of protection level (i.e. improvement of “PL” attribute) is the most concerning matter among visitors. Since the random parameter logit model revealed that PL is specified as random, the individual heterogeneity exists for PL. Practical implications The current issues in ecotourism were studied and integrated into the methodology. A unique and comprehensive policy structure was developed, and enables to respond with any contemporary issues linked to protected areas (PA) without neglecting the natural and cultural endowments. Originality/value This study presents an in-depth understanding of visitors’ preferences in the ecotourism industry and used CE as a mechanism tool to explore visitors’ preferences. This study incorporates the conceptualisation of visitors’ preferences and sustainable tourism development into the PA framework structure.

Analysis of Discrete Choice Data with Repeated Observations: Comparison of Three Techniques in Intercity Travel Case

1997 ◽  
Vol 1607 (1) ◽  
pp. 69-73 ◽  
Author(s):  
Shomik Raj Mehndiratta ◽  
Mark Hansen
Keyword(s):  
Stated Preference ◽  
Random Parameter ◽  
Alternative Methods ◽  
Single Individual ◽  
Logit Models ◽  
Choice Data ◽  
Widespread Application ◽  
Repeated Observations ◽  
Random Parameter Logit ◽  
Repeated Choice

With the acceptance and widespread application of stated preference methods in transportation analysis, there has been a need for the analysis of choice data with repeated observations. Analysis of repeated choice data is complicated by correlation of responses across the choices made by a single individual. In the probit framework, repeated choice can easily be accommodated by way of correlation in the utilities associated with the errors. However, the probit framework has computational limitations; subsequently, researchers have looked to modeling repeated choice by using extensions of the logit model. Random parameter logit models estimated by simulation methods provide a promising modeling framework. The estimation results of some stated preference intercity business travel data are compared by using three alternative estimation techniques to account for correlations across the choices made by a single individual. It is believed that two of the alternative methods, which use random-parameter logit models (developed by researchers for use in an energy application), have not been used before in the transportation context. A comparison of the three techniques provides documentation for researchers and practitioners who plan to analyze such data.

scholarly journals Analyzing Prospective Owners’ Choice Decision towards Plug-in Hybrid Electric Vehicles in Urban India: A Stated Preference Discrete Choice Experiment

2021 ◽  
Vol 13 (14) ◽  
pp. 7725
Author(s):  
Reema Bera ◽  
Bhargab Maitra
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Stated Preference ◽  
Mixed Logit ◽  
Road Transport ◽  
Home Based ◽  
Urban India ◽  
Choice Decision ◽  
The Mean ◽  
Hybrid Electric

Plug-in Hybrid Electric Vehicles (PHEVs) can help decarbonize road transport in urban India. To accelerate the diffusion of PHEVs, investigation of commuter preferences towards the attributes of PHEVs is necessary. Therefore, the present study analyzes prospective owners’ choice decisions towards PHEVs in a typical Indian context. A stated preference survey was designed to collect responses from the current owners of conventional vehicles (CVs) in Delhi, India, and Mixed Logit (ML) models were developed to estimate commuters’ Willingness To Pay (WTP) for a set of key PHEV-specific attributes. The decomposition effect of prospective owners’ sociodemographic characteristics and trip characteristics on the mean estimates of random parameters was investigated by developing ML models with heterogeneity. Subsequently, the influence of improvement of each PHEV-specific attribute on prospective owners’ choice probability was investigated by calculating marginal effects. Among the various PHEV-specific attributes considered in the present study, high WTPs are observed for decrease in battery recharging time, reduction in tailpipe emission and increase in electric range. Therefore, an added emphasis on these attributes by vehicle manufacturers is likely to enhance the attractiveness of PHEVs to Indian commuters. The results also highlight the importance of government subsidy for promoting PHEVs in the Indian market. Prospective owners’ income, availability of home-based parking space, and average daily trip length are found to significantly influence the choice decision of Indian commuters towards PHEVs.

scholarly journals Taste Beats Reputation in New Food Products Choice: The Case of Ready-to-Eat Pomegranate among Young Consumers in Veneto Region (Italy)

Horticulturae ◽  
2021 ◽  
Vol 7 (7) ◽  
pp. 179
Author(s):  
Alice Stiletto ◽  
Erika Rozzanigo ◽  
Elisa Giampietri ◽  
Samuele Trestini
Keyword(s):  
Discrete Choice ◽  
Choice Experiment ◽  
Consumer Preferences ◽  
Random Parameter ◽  
Food Products ◽  
Sensory Features ◽  
Young Consumers ◽  
Random Parameter Logit ◽  
Italian Origin ◽  
Random Parameter Logit Model

This study investigates the preferences for ready-to-eat pomegranate arils in Italy through a discrete choice experiment (DCE) on 264 young consumers in Italy. The aim is to estimate consumers’ willingness to pay (WTP) for the reputational attributes of the product (e.g., the product origin and sales channel) and to discriminate the elicited preferences between tasting and non-tasting situations. To this purpose, a random parameter logit model was employed to assess the heterogeneity in consumer preferences. The results suggest that non-tasters attach a relevant value to the reputational attributes (e.g., +75% WTP for Italian origin). Moreover, considering the sensory features of the products, we found that consumers in this group discriminate against the proposed samples only through their visual characteristics: they prefer the sample with the largest size and red colored arils. In addition, we found that the tasting experience reduced the value attached to the reputational attributes (e.g., −50% WTP for local origin) for consumers, compared to non-tasting situation, thus shifting their preference to the samples that they appreciated the most (high liking). Specifically, we found that consumers in the tasting group preferred the product sample with the highest level of sweetness and the lowest level of sourness and astringency, showing a higher preference for sweetness. The findings contribute to the literature on consumers’ behavior on new food products (NFPs), showing that reputational attributes lose value after the tasting experience. In contrast, the sensory features of the NFPs can help tasters to reduce the information asymmetry, which traditionally represents a hurdle in purchases for new consumers. However, this depends on the individuals’ subjective preferences, as demonstrated by the significant effect of liking levels in discriminating consumers’ choices. To conclude, although these results cannot be extended to the general population, they may give some interesting insights about future trends of NFP demand.

scholarly journals The Effects of Life Course Events on Car Ownership and Sustainable Mobility Tools Adoption Decisions: Results of an Error Component Random Parameter Logit Model

2021 ◽  
Vol 13 (12) ◽  
pp. 6816
Author(s):  
Gaofeng Gu ◽  
Tao Feng ◽  
Chixing Zhong ◽  
Xiaoxi Cai ◽  
Jiang Li
Keyword(s):  
Life Course ◽  
Logit Model ◽  
Random Parameter ◽  
Error Component ◽  
Car Ownership ◽  
Sustainable Mobility ◽  
Car Sharing ◽  
Random Parameter Logit ◽  
Electric Bike ◽  
Random Parameter Logit Model

Life course events can change household travel demand dramatically. Recent studies of car ownership have examined the impacts of life course events on the purchasing, replacing, and disposing of cars. However, with the increasing diversification of mobility tools, changing the fleet size is not the only option to adapt to the change caused by life course events. People have various options with the development of sustainable mobility tools including electric car, electric bike, and car sharing. In order to determine the impacts of life course events on car ownership and the decision of mobility tool type, a stated choice experiment was conducted. The experiment also investigated how the attributes of mobility tools related to the acceptance of them. Based on existing literature, we identified the attributes of mobility tools and several life course events which are considered to be influential in car ownership decision and new types of mobility tools choice. The error component random parameter logit model was estimated. The heterogeneity across people on current car and specific mobility tools are considered. The results indicate people incline not to sell their current car when they choose an electric bike or shared car. Regarding the life course events, baby birth increases the probability to purchase an additional car, while it decreases the probability to purchase an electric bike or joining a car sharing scheme. Moreover, the estimation of error components implies that there is unobserved heterogeneity across respondents on the sustainable mobility tools choice and the decision on household’s current car.

OPTIMAL IMPLEMENTATION OF LIGHTWEIGHTING AND POWERTRAIN EFFI CIENCY TECHNOLOGY IN PASSENGERS' VEHICLES

Transport ◽  
2012 ◽  
Vol 27 (3) ◽  
pp. 237-249 ◽  
Author(s):  
Erik Wilhelm ◽  
Johannes Hofer ◽  
Warren Schenler ◽  
Lino Guzzella
Keyword(s):  
Technology Implementation ◽  
Energy Use ◽  
Operating Cost ◽  
Cost Curve ◽  
General Strategy ◽  
Efficiency Improvement ◽  
Vehicle Ownership ◽  
Purchase Cost ◽  
Efficiency Measures ◽  
Effi Ciency

Improving powertrain efficiency and reducing vehicle weight are two options for reducing vehicle energy use, emissions, and operating cost that often increase the purchase cost of passenger vehicles. Increasing drivetrain efficiency shrinks the potential for reducing energy use by lightweighting and conversely lighter vehicles benefit less from efficiency improvement. This paper describes a methodology for finding the optimum combination of light-weighting and efficiency measures to achieve minimum lifetime vehicle cost. Using representative technology cost assumptions for a mid-sized passenger car, marginal efficiency improvement in the range of 20 to 30% and lightweighting between 200 and 600 kg are optimal, depending strongly on marginal cost curve characteristics. A reduction in the total cost of vehicle ownership of between 18 and 42% is possible for the representative technology implementation scenarios. In the absence of reliable cost data, a general strategy of designing lightweight vehicles with lower powertrain efficiency or else higher-efficiency powertrains which are integrated in heavier vehicles is recommended.

scholarly journals Fishing location choice and risk preferences among small fishers – Implications for fisheries management policies

2020 ◽  
Vol 15 (2) ◽  
pp. 140-156
Author(s):  
Riad Sultan ◽  
Keyword(s):  
Fisheries Management ◽  
Risk Preferences ◽  
Random Parameter ◽  
Management Policy ◽  
Linear Utility ◽  
South West Coast ◽  
Random Parameter Logit ◽  
Management Policies ◽  
Expected Revenue ◽  
Random Parameter Logit Model

The study provides evidence for how risk preferences determine fishing location choices by artisanal fishers on the south-west coast of the island of Mauritius. Risk preference is modelled using a random linear utility framework defined over mean-standard deviation space. The study estimates expected revenue and revenue risk from the Just and Pope production function and applies the random parameter logit model to account for fisher-specific and location-specific characteristics. The findings are consistent with utility-maximising fishers, whereby the likelihood to choose a fishing location is positively associated with expected revenue and negatively related to revenue risk. Distance from fishing station to fishing grounds affects the choice of fishing location negatively. The estimated model allows heterogeneity in risk preferences and concludes that 51% of fishers can be classified as risk averse, 31% as risk seekers and the remaining as risk neutral. The study also estimates the degree of substitutability and complementarity between fishing locations based on the risk preferences of fishers and discusses the relevance of this for fisheries management policy.

scholarly journals Análisis econométrico de la heterogeneidad de las preferencias de los individuos: Aplicación a la valoración económica de la conservación del paisaje agrícola de montaña

2011 ◽  
Vol 8 (1) ◽  
pp. 103 ◽  
Author(s):  
Sergio Colombo ◽  
Nick Hanley
Keyword(s):  
Latent Class ◽  
Random Parameter ◽  
Choice Models ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Stated Choice ◽  
Empirical Application ◽  
Random Parameter Logit ◽  
Class Models

The need to account for respondents’ preference heterogeneity in stated choice models has motivated researchers to apply random parameter logit and latent class models. In this paper we compare these three alternative ways of incorporating preference heterogeneity in stated choice models and evaluate how the choice of model affects welfare estimates in a given empirical application. Finally, we discuss what criteria to follow to decide which approach is most appropriate.

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