Search results for " response latency"

showing 2 items of 2 documents

Design and analysis of discrete choice experiments for models with response time

2013

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaA sector of conjoint analysis (experimental design in marketing research) is made of the so called choice experiments. In choice experiments respondents undergo a questionnaire which is nowadays mostly submitted through the internet. The questionnaire proposes to the respondent a sequence of choice sets each one including two or more profiles being a profile a specific combination of attribute levels. The respondent selects the preferred profile for each choice set. Responses given by a sample of respondents are analysed through suitable methods aimed to eventually find the best combination of attribute levels. One method of analysis adopts the Multinomial Logit (MLN) model. In this article the authors show the results of the MLN analysis compared with another model of analysis which uses an additional response which can be easily recorded by electronically submitted questionnaires. In practice modern survey platforms like “Qualtrics” (the one used for this work) can record the so called “response latency” i.e. the time taken by the respondent to make the choice and select the most preferred profile in the choice set. Thanks to a response latency model further refined in this work it is possible to deduce the relative weight of importance of the profiles for each choice set and respondent. This type of response can be used in place of the dichotomous choice variable in the MLN model. The two models and methods of analysis are deeply compared and it is critically discussed when it is better to use one or the other method. As a result a more reliable estimate of the optimal profile comes up implying lower risks for new investments and marketing decisions.
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A heuristic method for estimating attribute importance by measuring choice time in a ranking task

2012

The evaluation of a product or service in terms of its attributes has been broadly studied in marketing, management and decision sciences. However, methods for finding important attributes have theoretical and practical limitations. The former are related to the selection of the most appropriate model; the latter are due to large number of variables that affect the specific experimental context. This study aims to present a new methodology that captures attribute preferences from a respondent and in particular, by using the choice time in a ranking task, it allows to indirectly obtain the importance weights for several tested attributes through a simple, fast and inexpensive procedure. More…

Statistics and ProbabilityEconomics and EconometricsService (systems architecture)HeuristicComputer scienceSettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaVariable and attributeContext (language use)computer.software_genreTask (project management)RankingRespondentData miningStatistics Probability and UncertaintySettore SECS-S/01 - StatisticacomputerFinanceSelection (genetic algorithm)CHOICE TIME response time response latency attribute rating choice models
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