scholarly journals Did Attitudes Interpret and Predict “Better” Choice Behaviour towards Innovative and Greener Automotive Technologies? A Hybrid Choice Modelling Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Stefano de Luca ◽  
Roberta Di Pace
Keyword(s):  
Latent Variables ◽  
Psychological Factors ◽  
Choice Model ◽  
Combustion Engine ◽  
Innovative Technology ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Model Framework ◽  
Main Research ◽  
Automotive Technology

It is common opinion that traditional approaches used to interpret and model users’ choice behaviour in innovative contexts may lead to neglecting numerous nonquantitative factors that may affect users’ perceptions and behaviours. Indeed, psychological factors, such as attitudes, concerns, and perceptions may play a significant role which should be explicitly modelled. By contrast, collecting psychological factors could be a time and cost consuming activity, and furthermore, real-world applications must rely on theoretical paradigms which are able to easily predict choice/market fractions. The present paper aims to investigate the above-mentioned issues with respect to an innovative automotive technology based on the after-market hybridization of internal combustion engine vehicles. In particular, three main research questions are addressed: (i) whether and how users’ characteristics and attitudes may affect users’ behaviour with respect to new technological (automotive) scenarios (e.g., after-market hybridization kit); (ii) how to better “grasp” users’ attitudes/concerns/perceptions and, in particular, which is the most effective surveying approach to observe users’ attitudes; (iii) to what extent the probability of choosing a new automotive technology is sensitive to attitudes/concerns changes. The choice to install/not install the innovative technology was modelled through a hybrid choice model with latent variables (HCMs), starting from a stated preferences survey in which attitudes were investigated using different types of questioning approaches: direct questioning, indirect questioning, or both approaches. Finally, a comparison with a traditional binomial logit model and a sensitivity analysis was carried out with respect to the instrumental attributes and the attitudes. Obtained results indicate that attitudes are significant in interpreting and predicting users’ behaviour towards the investigated technology and the HCM makes it possible to easily embed psychological factors into a random utility model/framework. Moreover, the explicit simulation of the attitudes allows for a better prediction of users’ choice with respect to the Logit formulation and points out that users’ behaviour may be significantly affected by acting on users’ attitudes.

scholarly journals Multi-route choice modelling in a metropolitan context: A comparative analysis using Multinomial Logit and Fuzzy Logic based approaches

2020 ◽  
Vol 79 (ET.2020) ◽  
pp. 1-17
Author(s):  
Sowjanya Dhulipala
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Choice Model ◽  
Route Choice ◽  
Fuzzy Rule ◽  
Multinomial Logit ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Linguistic Rules ◽  
Mnl Model

Route choice plays a vital role in the traffic assignment and network building, as it involves decision making on part of riders. The vagueness in travellers’ perceptions of attributes of the available routes between any two locations adds to the complexities in modelling the route choice behaviour. Conventional Logit models fail to address the uncertainty in travellers’ perceptions of route characteristics (especially qualitative attributes, such as environmental effects), which can be better addressed through the theory of fuzzy sets and linguistic variables. This study thus attempts to model travellers’ route choice behaviour, using a fuzzy logic approach that is based on simple and logical ‘if-then’ linguistic rules. This approach takes into consideration the uncertainty in travellers’ perceptions of route characteristics, resembling humans’ decision-making process. Three attributes – travel time, traffic congestion, and road-side environment are adopted as factors driving people’s choice of routes, and three alternative routes between two typical locations in an Indian metropolitan city, Surat, are considered in the study. The approach to deal with multiple routes is shown by analyzing two-wheeler riders’ (e.g. motorcyclists’ and scooter drivers’) route choice behaviour during the peak-traffic time. Further, a Multinomial Logit (MNL) model is estimated, to enable a comparison of the two modelling approaches. The estimated Fuzzy Rule-Based Route Choice Model outperformed the conventional MNL model, accounting for the uncertain behaviour of travellers.

scholarly journals FUZZY LOGIC APPROACH IN MODE CHOICE MODELLING FOR EDUCATION TRIPS: A CASE STUDY OF INDIAN METROPOLITAN CITY

Transport ◽  
2015 ◽  
Vol 30 (3) ◽  
pp. 286-293 ◽  
Author(s):  
Ashu Shivkumar Kedia ◽  
Krishna Bhuneshwar Saw ◽  
Bhimaji Krishnaji Katti
Keyword(s):  
Fuzzy Logic ◽  
Choice Model ◽  
Mode Choice ◽  
Vital Role ◽  
Sustainable Transportation ◽  
Indian Society ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Public Transport System ◽  
Fuzzy Logic Approach

Urban population in India has increased significantly from 62 million in 1951 to 378 million in 2011 in six decades. It is estimated to reach 540 million by the year 2021. This reflects on likely pressure on urban transportation system. The situation necessarily calls plans for balanced personal and public transport system. Mandatory trips bear more importance in this regard owing to their higher share in urban trips. Mode share and their choice behaviour in estimation of such trips play vital role in analysing and boosting sustainable transportation. Logit modelling approach is the conventional method generally adopted for analysing mode choice behaviour, which is based on the principle of random utility maximization derived from econometric theory. However, such models cannot address uncertainity prevailing in the choice decisions. On the contrary, fuzzy logic bypasses the binary crisp derivations of the inputs and accepts multivalued inputs in linguistic expressions, which make possible to resemble the human behaviour closely. Therefore, the attempt here is to develop fuzzy logic based mode choice model for education trips, which constitutes a good share in mandatory trips by covering various income groups of Indian society.

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.

scholarly journals Commuter Train Mode Choice Modelling Using Binary Logit Model

2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ryan Septiady Nugraha
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Mode Choice ◽  
Leisure Activity ◽  
Proper Solution ◽  
Choice Modelling ◽  
School Work ◽  
Trip Purpose ◽  
Public Transport System ◽  
Binary Logit

Car production in Malaysia increasing dramatically. This situation created serious impact such as pollution and congestion. The Malaysian government should find a proper solution to prevent the vehicles growth by controlling them and improve public transportation services. The only way to get people to switch to public transportation is by improving the public transport system becomes more efficient. To find out the solution, an understanding of traveler behavior by applying to mode choice model using binary logit approach is necessary. Stated preferences method was adopted in order to construct hypothetical choice in current and future situations. A total of 250 respondents were selected as the sample based on the research study. This research employed a discrete choice analysis to examine the relationship between the independent variables (travel time, fares, comfort and safety). With variation of trip purpose (school, work, leisure activity, and shopping), model has been developed and tested to check the validity. The result shows that the potential of new train services to compete with the current commuter (KTM) and private car user are quite competitive. This is no doubt due to the characteristics of the respondent to choose a good level of services especially a better comfortability and safety with an affordable price (fares). It can be concluded that scenario 2 has great potential to be implemented since forecasting demand reached above 90%.

scholarly journals The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis

2014 ◽  
Vol 26 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Chuan Ding ◽  
Chao Liu ◽  
Yaoyu Lin ◽  
Yaowu Wang
Keyword(s):  
Co2 Emissions ◽  
Mixed Method ◽  
Latent Variables ◽  
Choice Model ◽  
Mode Choice ◽  
Car Ownership ◽  
Simultaneous Estimation ◽  
Model Parameters ◽  
Employer Attitudes ◽  
The Impact

Reducing car trips and promoting green commuting modes are generally considered important solutions to reduce the increase of energy consumption and transportation CO2 emissions. One potential solution for alleviating transportation CO2 emissions has been to identify a role for the employer through green commuter programs. This paper offers an approach to assess the effects of employer attitudes towards green commuting plans on commuter mode choice and the intermediary role car ownership plays in the mode choice decision process. A mixed method which extends the traditional discrete choice model by incorporating latent variables and mediating variables with a structure equation model was used to better understand the commuter mode choice behaviour. The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process. The results found in this paper provide helpful information for transportation and planning policymakers to test the transportation and planning policies effects and encourage green commuting reducing transportation CO2 emissions.

Analyzing Intercity Modal Choice and Competition Between High Speed Rail (HSR) and Other Transport Modes in Indian Context

2016 ◽  
pp. 146-160
Author(s):  
Ashish Verma ◽  
Varun Raturi
Keyword(s):  
High Speed ◽  
Mode Choice ◽  
Transport Infrastructure ◽  
Infrastructure Investment ◽  
Theoretic Approach ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
High Speed Rail ◽  
Game Theoretic ◽  
Game Theoretic Approach

In this study, a theoretical framework is developed in order to assess the viability of transport infrastructure investment in the form of High Speed Rail (HSR) by assessing, the mode choice behaviour of the passengers and the strategies of the operators, in the hypothetical scenario. Discrete choice modelling (DCM) integrated with a game theoretic approach is used to model this dynamic market scenario. DCM is incorporated to predict the mode choice behaviour of the passengers in the new scenario and the change in the existing market equilibrium and strategies of the operators due to the entry of the new mode is analysed using the game theoretic approach. The outcome of this market game will describe the strategies for operators corresponding to Nash equilibrium. In conclusion, the impact of introduction of HSR is assessed in terms of social welfare by analysing the mode choice behaviour and strategic decision making of the operators, thus reflecting on the economic viability of the transport infrastructure investment.

scholarly journals Turning the Tap or Buying the Bottle? Consumers’ Personality, Understanding of Risk, Trust and Conspicuous Consumption of Drinking Water in Norway

2020 ◽  
Vol 12 (18) ◽  
pp. 7560
Author(s):  
Geir Wæhler Gustavsen ◽  
Atle Wehn Hegnes
Keyword(s):  
Water Consumption ◽  
Latent Variables ◽  
Statistical Tests ◽  
Research Question ◽  
Conspicuous Consumption ◽  
Expected Frequency ◽  
Main Research ◽  
Social Distinction ◽  
Water Drinking ◽  
Theoretical Approaches

This paper contributes to the debate on sustainable water consumption by exploring the relation between consumers’ personality, understanding of risk/trust and social distinction in water drinking practices in Norway. Our main research question, how can we understand preferences for water consumption?, is approached by answering a set of hypotheses inspired by a combination of three theoretical approaches. Latent variables measuring personality and conspicuous attitudes are included in frequency models based on the statistical beta distribution together with other predictors. Statistical tests were performed to find the connection between expected frequency of water consumption, personality, risk/trust and conspicuous attitudes. The conclusion is that the consequence of the connections between consumers’ personality, understanding of risk and conspicuous consumption of water should be considered by Norwegian stakeholders when planning future strategies and methods for more sustainable water consumption.

scholarly journals Impact of Perceived Uncertainty on Public Acceptability of Congestion Charging: An Empirical Study in China

2018 ◽  
Vol 11 (1) ◽  
pp. 129 ◽  
Author(s):  
Yacan Wang ◽  
Yu Wang ◽  
Luyao Xie ◽  
Huiyu Zhou
Keyword(s):  
Traffic Congestion ◽  
Latent Variables ◽  
Choice Model ◽  
Stated Preference ◽  
The Public ◽  
Public Acceptability ◽  
Revenue Allocation ◽  
Negative Effect ◽  
The Government ◽  
Congestion Charging

Severe traffic congestion is now a common problem in major cities worldwide, causing huge economic, environmental, and social losses to overall welfare. Governments are now considering congestion charging as an effective way to manage congestion. However, since congestion charging has not yet been implemented widely, the public remains uncertain about it. Few scholars have explored public uncertainty about congestion charging. This paper examined how the public perceived uncertainty toward fairness and efficiency affects willingness to accept congestion charging. Through an experimental study of stated preference, this paper analyzes the influence of observable variables and unobserved latent variables on public acceptability and compares the results with a traditional discrete choice model. The results indicated that the public’s perceived uncertainty about congestion charging will have significant negative effect on acceptability and that the perception of fairness has an even larger effect. As for uncertainty about the effectiveness of congestion charging on alleviating congestion, the implementation efficiency of the government is the most significant. For uncertainty about fairness, whether charge collection and revenue allocation are reasonable is the most significant. These findings provide an empirical basis for reducing public uncertainty and increasing public acceptance of congestion charging.

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