BayesRec: Personalize search ranking with customer attribute-level willingness-to-pay using heterogeneous booking choice data

2021 ◽  
Vol 94 ◽  
pp. 102885
Author(s):  
P.K.S. Prakash ◽  
Naman Gandhi ◽  
Shubham Jain
Keyword(s):  
Willingness To Pay ◽  
Attribute Level ◽  
Choice Data

scholarly journals Conserving rhinos by legal trade: Insights from a choice experiment on rhino horn consumers

2021 ◽  
Author(s):  
Hoai Nam Dang Vu ◽  
Martin Reinhardt Nielsen ◽  
Jette Bredahl Jacobsen
Keyword(s):  
Willingness To Pay ◽  
Choice Experiment ◽  
Consumer Preferences ◽  
Black Market ◽  
Attribute Level ◽  
Price Difference ◽  
Positive Effect

A legal rhino horn trade is suggested to reduce poaching. To examine this proposition we conducted a choice experiment with 345 rhino horn consumers in Vietnam investigating their preferences for legality, source, price and peer experience of medicinal efficacy as attributes in their decision to purchase rhino horn. We calculated consumers’ willingness to pay for each attribute level. Consumers preferred and were willing to pay more for wild than semi-wild and farmed rhino horn but showed the strongest preference for legal horn although higher-income consumers were less concerned about legality. The number of peers having used rhino horn without positive effect reduced preference for wild-sourced horn and increased preference for legality. Hence, a legal trade in rhino horn would likely not eliminate a parallel black market. Whether poaching would be reduced depends on the price difference in the two markets, campaigns ability to change consumer preferences, and regulation efforts.

Homebuyers’ preferences concerning installed photovoltaic systems

2018 ◽  
Vol 11 (1) ◽  
pp. 102-124 ◽  
Author(s):  
Brano Glumac ◽  
Thomas P. Wissink
Keyword(s):  
Willingness To Pay ◽  
Housing Market ◽  
Choice Model ◽  
Stated Preference ◽  
Photovoltaic System ◽  
Photovoltaic Systems ◽  
Choice Data ◽  
Content Type ◽  
The Impact ◽  
General Preferences

Purpose This paper aims to report on homebuyers’ preferences and willingness to pay for installed home photovoltaic systems. Their influence on the market position of a dwelling is relatively unknown. Considering that expected lifespan of photovoltaic systems is at least 25 years, it is likely that many dwellings with a photovoltaic system will enter the housing market. Design/methodology/approach Few houses with installed photovoltaic systems have been sold in the market to date. Lack of real market data imposes a method based on the stated preference data. Therefore, the general preferences toward photovoltaic systems are determined by a discrete choice model based on responses of 227 homebuyers in the Eindhoven region, The Netherlands. Further, the model estimates were used to assess the indirect willingness to pay for home photovoltaic systems. This initial willingness to pay is further reassessed with the direct willingness to pay collected in an open-ended questionnaire format. Findings Results of the model show that the homebuyers’ preferences for home photovoltaic systems are large and significant. In addition to general preferences, this article reports on the taste heterogeneity carried out by separating observations based on the respondents’ characteristics. For example, photovoltaic systems are more appealing to homebuyers in more urban or central neighbourhoods. Further, the results of the direct survey lead to the conclusion that people are probably willing to pay close to the replacement value of the system and only 22 per cent of all respondents did not want to pay anything for the installed photovoltaic system. Research limitations/implications These findings are exploratory and they raise a number of questions for further investigations, such as those regarding the real estate value of the installed photovoltaic systems. The reported findings must be regarded as local, thus further research is necessary to understand the impact on European housing markets. Practical implications Preferences and willingness to pay for home photovoltaic systems can provide a variety of economic, social and political recommendations to different interested parties such as homeowners, buyers, realtors, retailers, energy companies and governments. For instance, a homeowner would like to know what would be the effect of a photovoltaic system on the housing market. Originality/value As per the knowledge of authors, this is the first paper to estimate the impact of an installed photovoltaic system on housing choice, measured by stated choice data in the local housing market. It expands the existing body of knowledge for increasingly important issues of valuing and measuring preferences for photovoltaic systems installed on dwellings.

scholarly journals Análisis de la metodología de los puntos de corte para la identificación de las respuestas “inconsistentes” en los modelos de elección discreta

2011 ◽  
Vol 9 (1) ◽  
pp. 3
Author(s):  
Sergio Colombo ◽  
Nick Hanley ◽  
Glenn Bush
Keyword(s):  
Willingness To Pay ◽  
Choice Experiment ◽  
Selection Rule ◽  
Stated Preference ◽  
Rational Selection ◽  
Choice Data ◽  
Selection Rules ◽  
Experiment Method ◽  
Fitting Model

<p>In the choice experiment method respondents are typically assumed to hold a perfectly rational selection rule. However, individuals may use other selection rules when choosing the preferred alternative to simplify the choice. In this paper, we make use of the “cutoffs” model to as a way of handling the non-compensatory nature of choices. Furthermore, we extend it to allow consideration of inconsistencies in choice in stated preference choice data. We find that this allows a better fitting model to be estimated, and that it produces considerable effects on the implied willingness to pay.</p>

Modelling Malaysians willingness-to-pay for electric cars: evidence from discrete choice data

2020 ◽  
Vol 11 (1) ◽  
pp. 33-33
Author(s):  
Meenchee Hong ◽  
Nabsiah Abdul Wahid
Keyword(s):  
Willingness To Pay ◽  
Discrete Choice ◽  
Carbon Emission ◽  
Multinomial Logit Model ◽  
Recent Decade ◽  
Choice Modelling ◽  
Choice Data ◽  
Road Transportation ◽  
Electric Cars ◽  
Electric Car

Road transportation is the major contributing factor of increasing carbon emission to the environment that eventually leads to the severe air pollution. In recent decade, electric vehicles (EVs) have been introduced to replace fossil fuel cars as a way to reduce carbon emission from the road. The study examines Malaysians willingness-to-pay for electric cars by utilising the discrete choice modelling approach. Consumers in Kuala Lumpur and Penang were sampled and given sets of alternatives determined from a systemically review of past studies to make their choices. The choices are made up of three important attributes of EVs: the price, driving range and charging time of the vehicle. This paper also describes the relationship between socio-demographic factors of consumers and their buying decision. Results show that brand, design and safety features of the electric car significantly influence willingness-to-pay for electric cars. This study also reveals that Malaysians have low knowledge and willingness to purchase electric cars. The main reason was the costly battery replacement. Nonetheless, some respondents are willing to pay a higher price for a better performance electric car. The findings may be beneficial to policymakers and car producers in both profit gaining and environment protection. Keywords: Electric cars, willingness-to-pay, multinomial logit model, random utility theory, consumption, carbon emission

scholarly journals Predicting responsiveness to information: consumer acceptance of biotechnology in animal products

2020 ◽  
Vol 47 (5) ◽  
pp. 1644-1667 ◽  
Author(s):  
David L Ortega ◽  
Jayson L Lusk ◽  
Wen Lin ◽  
Vincenzina Caputo
Keyword(s):  
Willingness To Pay ◽  
Mixed Logit ◽  
Consumer Acceptance ◽  
Individual Choice ◽  
Logit Models ◽  
Choice Data ◽  
Animal Products ◽  
Mixed Logit Models ◽  
Preference Uncertainty ◽  
High Level

Abstract We propose a novel framework using individual choice data and Bayesian updating to predict which consumers are most responsive to information—namely those consumers whose pre-information choices reveal a high level of uncertainty surrounding their preferences. We apply our method to the study of consumer acceptance of genetically modified animal products, which prior research has revealed is a particularly polarising subject. Utilising conditional willingness-to-pay estimates from mixed logit models, we find that individuals with higher preference uncertainty prior to receiving information are most responsive. Implications of our results are discussed in the context of recent breakthroughs in biotechnology.

Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink
Keyword(s):  
Willingness To Pay ◽  
Energy Saving ◽  
Subjective Time ◽  
Durable Good ◽  
Discount Function ◽  
Hyperbolic Discount ◽  
The One ◽  
Two Parameter ◽  
Difference Effect ◽  
Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

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