1,779 research outputs found

    A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data

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    A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74931/1/j.1540-5915.1993.tb00508.x.pd

    Predicting operator workload during system design

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    A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures

    Measuring Consumer Preferences Using Conjoint Poker

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    We develop and test an incentive-compatible Conjoint Poker (CP) game. The preference data collected in the context of this game are comparable to incentive-compatible choice-based conjoint (CBC) analysis data. We develop a statistical efficiency measure and an algorithm to construct efficient CP designs. We compare incentive-compatible CP to incentive-compatible CBC in a series of three experiments (one online study and two eye-tracking studies). Our results suggest that CP induces respondents to consider more of the profile-related information presented to them compared with CBC

    Human-Machine Interface Development For Modifying Driver Lane Change Behavior In Manual, Automated, And Shared Control Automated Driving

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    Rear-end crashes are common on U.S. roads. Driver assistance and automated driving technologies can reduce rear-end crashes (among other crash types as well). Braking is assumed for forward collision warning (FCW) and automatic emergency braking (AEB) systems. Braking is also used for adaptive cruise control (ACC) and in automated driving systems more generally. However, steering may be advised in an emergency if the adjacent lane is clear and braking is unlikely to avoid a collision. Steering around an obstacle when feasible also eliminates the risk of becoming the new forward collision hazard. Driver assist technology like emergency steer assist (ESA) and Level 2 or Level 3 automated driving systems might facilitate manual emergency lane changes but may require the driver to manually initiate the maneuver, something which drivers are often reluctant to do. An Human-Machine Interface (HMI) might advise the driver of a steerable path when feasible in forward collision hazard situations. Such an HMI might also advise a driver of normal lane change opportunities that can reduce travel time, increase fuel efficiency, or simply enhance the driving experience by promoting `flow.\u27 This dissertation investigated the propensity of drivers to brake only versus steer in both manual and automated driving situations that end in a high-intensity forward collision hazard. A audio-visual Field of Safe Travel (FOST) cluster display and haptic steering wheel HMI were developed to advise drivers in both discretionary and emergency situations of a lane change opportunity. The HMI was tested in a moving base simulator in manual driving, in fully autonomous driving, and in shared-control autonomous driving during a simulated highway commute that ended in an high-intensity forward collision hazard situation. Results indicated that a) driver response was affected by the nature of the automated driving (faster response in hands-on shared control versus hands-off fully autonomous driving); b) exposure to the HMI in normal lane changes both familiarized the driver with the HMI and introduced a mental set that steering was also a possibility rather than braking only; c) but that drivers used their direct vision to determine their response in the emergency event. A methodological issue related to mental set was also uncovered and resolved through screening studies. The final study brought the dissertation full-circle, comparing hands-off fully automated driving to hands-on shared control automated driving in the context of either providing some or no exposure to the developed LCA system concept. Results of the final study indicated that shared control lies somewhere between that of manual driving and hands-off fully automate driving. Benefits were also shown to exist for the LCA system concept irrespective of whether the discrete haptic profiles are included or not. The discrete haptic profiles did not statistically reliably increase response times to the FC hazard event, although they do show a trend toward decreasing response variability. This finding solidified the fact that by implementing a system for benign driving that aids in establishing a mental set to steer around an obstacle may actually be beneficial for rear-end crash scenarios. This dissertation’s contributions include a) audio-visual FOST display concepts; b) discrete haptic steering display concepts; c) a paired-comparisons scaling for urgency for haptic displays applied while driving; d) a new ``mirage scenario\u27\u27 methodology for eliciting subjective assessments in the context of a forward collision hazard, briefly presented then removed, without risk of simulator sickness, and e) a methodological lesson for others who wish to investigate semi-automated and automated driving interventions and must manage driver mental set carefully

    Archives of Data Science, Series A. Vol. 1,1: Special Issue: Selected Papers of the 3rd German-Polish Symposium on Data Analysis and Applications

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    The first volume of Archives of Data Science, Series A is a special issue of a selection of contributions which have been originally presented at the {\em 3rd Bilateral German-Polish Symposium on Data Analysis and Its Applications} (GPSDAA 2013). All selected papers fit into the emerging field of data science consisting of the mathematical sciences (computer science, mathematics, operations research, and statistics) and an application domain (e.g. marketing, biology, economics, engineering)

    The Use of Norms in the Evaluation of the Exchange Process: The Consumer Level.

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    The disciplines of economics and marketing have suggested that consumers derive satisfaction in exchange transactions from both the attributes of the products exchanged and the stores in which exchange takes place. This satisfaction is based on a comparison of the performance of these relatively objective attributes and a standard--the consumer\u27s expectations of these attributes. Recently, the marketing literature has suggested that an additional source of exchange-related satisfaction may arise from the actual process of exchange itself. Before a thorough understanding of this source of satisfaction can occur, we must gain a better knowledge of both the attributes of an exchange process and the standards of comparison used in its evaluation. This dissertation proposes that consumers evaluate exchange processes against a set of norms which serve as standards for the behaviors involved. To explore this proposition, a two stage research plan was developed with the objectives of identifying the operant norms in consumer-retailer exchange processes and assessing their efficacy in satisfaction judgments of the exchange process. The first stage was a qualitative research effort directed towards identifying the behaviors and norms involved in the exchange process. Qualitative analysis indicated that consumers utilize a set of seven exchange related norms in consumer-retailer exchange: appreciative behaviors, product/service knowledge, flexibility, respect for time, role diligence, contra-opportunism, and stand behind good products. Further, the satisfaction derived from the process appeared to be primarily related to the magnitude of the behaviors involved. The second stage involved a quantitative assessment of the existence and impact of these seven norms in exchange related satisfaction judgments, building upon the findings of the qualitative stage. The results provided empirical support for a direct relationship between the magnitudes of behaviors related to a particular norm and the utility or satisfaction derived from those behaviors. Support was also provided for the existence, differences between, and the shape of the return potential curves for each of the seven norm categories proposed in the initial phase of the study. The study identifies several substantive implications for the application and study of exchange-related satisfaction

    Bayesian D-Optimal Choice Designs for Mixtures

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    __Abstract__ \n \nConsumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondents\' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set. \n \nHowever, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating an optimal design for such choice experiments. To this end, we first introduce mixture models in the choice context and next present an algorithm to construct optimal experimental designs, assuming the multinomial logit model is used to analyze the choice data. To overcome the problem that the optimal designs depend on the unknown parameter values, we adopt a Bayesian D-optimal design approach. We also consider locally D-optimal designs and compare the performance of the resulting designs to those produced by a utility-neutral (UN) approach in which designs are based on the assumption that individuals are indifferent between all choice alternatives. We demonstrate that our designs are quite different and in general perform better than the UN designs
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