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on Discrete Choice Models |
| By: | Nguyen, Lien; Jokimäki, Hanna; Linnosmaa, Ismo; Saloniki, Eirini Christina; Batchelder, Laurie; Malley, Juliette; Lu, Hui; Burge, Peter; Trukeschitz, Birgit; Forder, Julien |
| Abstract: | This study developed Finnish preference weights for the seven-attribute Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer) and investigated survey fatigue and learning in best-worst scaling (BWS) experiments. An online survey that included a BWS experiment using the ASCOT-Carer was completed by a sample from the general population in Finland. A block of eight BWS profiles describing different states from the ASCOT-Carer were randomly assigned to each respondent, who consecutively made four choices (best, worst, second best and second worst) per profile. The analysis panel data had 32,160 choices made by 1005 respondents. A scale multinomial logit (S-MNL) model was used to estimate preference weights for 28 ASCOT-Carer attribute levels. Fatigue and learning effects were examined as scale heterogeneity. Several specifications of the generalised MNL model were employed to ensure the stability of the preference estimates. The most and least-valued states were the top and bottom levels of the control over daily life attribute. The preference weights were not on a cardinal scale. We observed the position effect of the attributes on preferences associated with the best or second-best choices. A learning effect was found. The established preference weights can be used in evaluations of the effects of long-term care services and interventions on the quality of life of service users and caregivers. The learning effect implies a need to develop study designs that ensure equal consideration to all profiles (choice tasks) in a sequential choice experiment. |
| Keywords: | adult Social Care Outcomes Toolkit for carers (ASCOT-Carer); best-worst scaling (BWS); evaluation; informal care; learning and fatigue effects; outcome measurement; quality of life; scale multinomial logit |
| JEL: | C35 C90 I18 I31 I39 |
| Date: | 2021–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:111885&r= |
| By: | Elena Georgarakis; Thomas Bauwens; Anne-Marie Pronk; Tarek AlSkaif |
| Abstract: | While the potential for peer-to-peer electricity trading, where households trade surplus electricity with peers in a local energy market, is rapidly growing, the drivers of participation in this trading scheme have been understudied so far. In particular, there is a dearth of research on the role of non-monetary incentives for trading surplus electricity, despite their potentially important role. This paper presents the first discrete choice experiment conducted with prosumers (i.e. proactive households actively managing their electricity production and consumption) in the Netherlands. Electricity trading preferences are analyzed regarding economic, environmental, social and technological parameters, based on survey data (N = 74). The dimensions most valued by prosumers are the environmental and, to a lesser extent, economic dimensions, highlighting the key motivating roles of environmental factors. Furthermore, a majority of prosumers stated they would provide surplus electricity for free or for non-monetary compensations, especially to energy-poor households. These observed trends were more pronounced among members of energy cooperatives. This suggests that peer-to-peer energy trading can advance a socially just energy transition. Regarding policy recommendations, these findings point to the need for communicating environmental and economic benefits when marketing P2P electricity trading platforms and for technical designs enabling effortless and customizable transactions |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.02452&r= |
| By: | David Lowing (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique, GRDF - Gaz Réseau Distribution France); Kevin Techer (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | The search for a compromise between marginalism and egalitarianism has given rise to many discussions. In the context of cooperative games, this compromise can be understood as a trade-off between the Shapley value and the Equal division value. We investigate this compromise in the context of multi-choice games in which players have several activity levels. To do so, we propose new extensions of the Shapley value and of the Weighted Division values to multi-choice games. Contrary to the existing solution concepts for multi-choice games, each one of these values satisfies a core condition introduced by Grabisch and Xie (2007), namely Multi-Efficiency. We compromise between marginalism and egalitarianism by introducing the multi-choice Egalitarian Shapley values, computed as the convex combination of our extensions. To conduct this study, we introduce new axioms for multi-choice games. This allows us to provide an axiomatic foundation for each of these values. |
| Keywords: | Multi-choice games,Multi-choice Shapley value,Multi-choice Equal division value,Multi-choice Egalitarian Shapley values Multi-choice games,Multi-choice Egalitarian Shapley values |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-03334056&r= |
| By: | Subodh Dubey; Ishant Sharma; Sabyasachee Mishra; Oded Cats; Prateek Bansal |
| Abstract: | Due to the unavailability of prototypes, the early adopters of novel products actively seek information from multiple sources (e.g., media and social networks) to minimize the potential risk. The existing behavior models not only fail to capture the information propagation within the individual's social network, but also they do not incorporate the impact of such word-of-mouth (WOM) dissemination on the consumer's risk preferences. Moreover, even cutting-edge forecasting models rely on crude/synthetic consumer behavior models. We propose a general framework to forecast the adoption of novel products by developing a new consumer behavior model and integrating it into a population-level agent-based model. Specifically, we extend the hybrid choice model to estimate consumer behavior, which incorporates social network effects and interplay between WOM and risk aversion. The calibrated consumer behavior model and synthetic population are passed through the agent-based model for forecasting the product market share. We apply the proposed framework to forecast the adoption of autonomous vehicles (AVs) in Nashville, USA. The consumer behavior model is calibrated with a stated preference survey data of 1,495 Nashville residents. The output of the agent-based model provides the effect of the purchase price, post-purchase satisfaction, and safety measures/regulations on the forecasted AV market share. With an annual AV price reduction of 5% at the initial purchase price of $40,000 and 90% of satisfied adopters, AVs are forecasted to attain around 85% market share in thirty years. These findings are crucial for policymakers to develop infrastructure plans and manufacturers to conduct an after-sales cost-benefit analysis. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.06169&r= |