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1

Oh, Min-hwan, and Garud Iyengar. "Multinomial Logit Contextual Bandits: Provable Optimality and Practicality." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (2021): 9205–13. http://dx.doi.org/10.1609/aaai.v35i10.17111.

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We consider a sequential assortment selection problem where the user choice is given by a multinomial logit (MNL) choice model whose parameters are unknown. In each period, the learning agent observes a d-dimensional contextual information about the user and the N available items, and offers an assortment of size K to the user, and observes the bandit feedback of the item chosen from the assortment. We propose upper confidence bound based algorithms for this MNL contextual bandit. The first algorithm is a simple and practical method that achieves an O(d√T) regret over T rounds. Next, we propos
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Gruca, Thomas S., and D. Sudharshan. "Equilibrium Characteristics of Multinomial Logit Market Share Models." Journal of Marketing Research 28, no. 4 (1991): 480–82. http://dx.doi.org/10.1177/002224379102800410.

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Previous research suggests that a multinomial logit model of market share can be used in optimization or equilibrium analyses of marketing decision making. However, there are significant problems with the solutions obtained from such an analysis. The authors show that for any firm with less than a 50% market share, the profit maximizing solution is to increase advertising as much as possible. The same holds true for any other positively signed marketing mix variable. The exponential property of the MNL model precludes reasonable descriptions of firm behavior in this case. Thus, the MNL market
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Inchul, Yang, and Hoon Jeon Woo. "INVESTIGATION AND COMPARISON OF ROUTE CHOICE MODELS." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 4, no. 10 (2017): 50–55. https://doi.org/10.5281/zenodo.1009312.

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In this study, MNL and C-logit are investigated as GEV type model, and MNP as non-GEV type model. Three models are tested in a very simple network to compare their performance and usefulness in practice. The layout of the paper is as follows. Section 2 provides a theoretical aspect of MNL, C-logit and MNP. Section 3 shows implementation of the models in a simple network and comparison of the results. Section 4 provides conclusion.
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Ohdoko, Taro, and Satoru Komatsu. "Integrating a Pareto-Distributed Scale into the Mixed Logit Model: A Mathematical Concept." Mathematics 11, no. 23 (2023): 4727. http://dx.doi.org/10.3390/math11234727.

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A generalized multinomial logit (G-MNL) model is proposed to alleviate the four challenges inherent to the conditional logit model, including (1) simultaneous unidentifiability, (2) the immediacy of decision-making, (3) the homogeneity of preferences in unobservable variables, and (4) the independence of irrelevant alternatives. However, the G-MNL model has some restrictions that are caused by the assumed logit scale of the lognormal distribution used in the G-MNL model. We propose a mixed logit with integrated Pareto-distributed scale (MIXL-iPS) model to address the restriction of the G-MNL m
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Karpov, Nikolai, and Qin Zhang. "Instance-Sensitive Algorithms for Pure Exploration in Multinomial Logit Bandit." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (2022): 7096–103. http://dx.doi.org/10.1609/aaai.v36i7.20669.

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Motivated by real-world applications such as fast fashion retailing and online advertising, the Multinomial Logit Bandit (MNL-bandit) is a popular model in online learning and operations research, and has attracted much attention in the past decade. In this paper, we give efficient algorithms for pure exploration in MNL-bandit. Our algorithms achieve instance-sensitive pull complexities. We also complement the upper bounds by an almost matching lower bound.
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Bunch, David S., and Richard R. Batsell. "A Monté Carlo Comparison of Estimators for the Multinomial Logit Model." Journal of Marketing Research 26, no. 1 (1989): 56–68. http://dx.doi.org/10.1177/002224378902600105.

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Marketing researchers use the multinomial logit (MNL) model to analyze discrete choice, and estimate parameters either by maximum likelihood (ML) or minimum logit chi square (MLCS). Some controversy persists, however, over which is better. Review articles in marketing recommend ML over MLCS, but the statistics literature suggests that MLCS should be preferred. No studies have directly compared the performance of ML and MLCS in a marketing context. The authors assess the relative performance of ML, MLCS, and three other candidate estimators for MNL marketing applications involving repeated-meas
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Li, Xiaowei, Yuting Wang, Yao Wu, Jun Chen, and Jibiao Zhou. "Modeling Intercity Travel Mode Choice with Data Balance Changes: A Comparative Analysis of Bayesian Logit Model and Artificial Neural Networks." Journal of Advanced Transportation 2021 (September 14, 2021): 1–22. http://dx.doi.org/10.1155/2021/9219176.

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This study conducts a comprehensive comparative analysis of regression-based multinomial models and artificial neural network models in intercity travel mode choices. The four intercity travel modes of airplane, high-speed rail (HSR), train, and express bus were used for analysis. Passengers’ activity data over the process of intercity travel were collected to develop the models. The standard multinomial logit (MNL) regression and Bayesian multinomial logit (BMNL) regression were compared with the radial basis function (RBF) and multilayer perceptron (MLP). The results show that MLP performs b
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Nurlaela, S. "An application of Multinomial Logit Model (MNL) on tourist destination choices." IOP Conference Series: Earth and Environmental Science 202 (November 27, 2018): 012021. http://dx.doi.org/10.1088/1755-1315/202/1/012021.

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Afandizadeh Zargari, Shahriar, and Farshid Safari. "Using Clustering Methods in Multinomial Logit Model for Departure Time Choice." Journal of Advanced Transportation 2020 (January 15, 2020): 1–12. http://dx.doi.org/10.1155/2020/7382569.

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Travellers have to make some decisions for each trip, and one of them is the choice of departure time. Discrete choice models have been employed as an approach to departure time modelling by many researchers. In this method, preparing choice set is a primary challenge which involves the definition of some departure periods to be selected by the traveller. In this research, choice sets were formed by applying the clustering methods on departure times. Afterwards, we developed Multinomial Logit (MNL) models on different choice sets and compared the models. The data used throughout this research
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Swait, Joffre, and Jordan Louviere. "The Role of the Scale Parameter in the Estimation and Comparison of Multinomial Logit Models." Journal of Marketing Research 30, no. 3 (1993): 305–14. http://dx.doi.org/10.1177/002224379303000303.

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Multinomial logit (MNL) models are widely used in marketing research to analyze choice data, but it is not generally recognized that the unit of the utility scale in a MNL model is inversely related to the error variance. This means that, for instance, parameters of two identical utility specifications estimated from different data sources with unequal variances will necessarily differ in magnitude, even if the true model parameters that generated the utilities are identical in both sets. Despite a growing number of papers that compare MNL coefficients, no examples of appropriate tests of the
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Guo, Yanyong, Yao Wu, Jian Lu, and Jibiao Zhou. "Modeling the Unobserved Heterogeneity in E-bike Collision Severity Using Full Bayesian Random Parameters Multinomial Logit Regression." Sustainability 11, no. 7 (2019): 2071. http://dx.doi.org/10.3390/su11072071.

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Understanding the risk factors of e-bike collisions can improve e-bike riders’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates risk factors that significantly contribute to the severity of e-bike collisions. Two months of e-bike collision data were collected in the city of Ningbo, China. A random parameters multinomial logit regression (RP-MNL) is proposed to account for the unobserved heterogeneity across observations. A fixed parameters multinomial logit regression (FP-MNL) is estimated and compared with the RP-MNL under the Bayes
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Boltz, Frederick, and Douglas R. Carter. "Multinomial logit estimation of a matrix growth model for tropical dry forests of eastern Bolivia." Canadian Journal of Forest Research 36, no. 10 (2006): 2623–32. http://dx.doi.org/10.1139/x06-155.

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Multinomial logistic (MNL) regression was employed to estimate the transition probabilities of a matrix growth model for dry forests of the eastern Bolivian lowlands. Probabilities of mortality, stability, and upgrowth of a size and species group were estimated as a function of tree and stand attributes influencing growth and mortality. Data for model estimation were drawn from logged and undisturbed permanent sample plots (PSPs) measured over 6 and 7 years in Chiquitania forests south of Concepción, Santa Cruz, Bolivia. The estimated transition probabilities of the MNL models are not signific
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Yingcui, Du, Liu Benxing, Dong Shulong, Wang Xiaoqing, and Zhao Pengsheng. "Research on Travel Mode Selection Decision Method Based on Discrete Choice Model." Journal of Scientific and Engineering Research 9, no. 8 (2022): 59–67. https://doi.org/10.5281/zenodo.10527716.

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<strong>Abstract</strong> With the development of Sweden&rsquo;s economy, new modes of transportation have gradually developed. In order to understand the acceptance of new modes of transportation by the Swedish people, this paper takes the Swedish people as the research object. The data are obtained by filling out questionnaires on the spot, mailing questionnaires and SP surveys. BIOGEME is used to establish a Multinomial Logit (MNL) model to analyze the travel choice behavior of the Swedish people under various modes of transportation, helping the government to further optimize and improve t
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Wang, Fangru, and Catherine L. Ross. "Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 47 (2018): 35–45. http://dx.doi.org/10.1177/0361198118773556.

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The multinomial logit (MNL) model and its variations have been dominating the travel mode choice modeling field for decades. Advantages of the MNL model include its elegant closed-form mathematical structure and its interpretable model estimation results based on random utility theory, while its main limitation is the strict statistical assumptions. Recent computational advancement has allowed easier application of machine learning models to travel behavior analysis, though research in this field is not thorough or conclusive. In this paper, we explore the application of the extreme gradient b
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Çelik, Ali Kemal, and Betül Tamer. "Household’s Fuel Type Choice for Space Heating in Türkiye: A Comparison of Multinomial Logit and Multinomial Probit Models." International Journal of Energy Economics and Policy 14, no. 6 (2024): 651–64. http://dx.doi.org/10.32479/ijeep.17253.

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Better understanding of households’ fuel type choice behaviour for residential heating, cooking, or lighting purposes would provide valuable information in estimating households’ energy use and in developing efficient fuel switching and energy saving policies; these solutions could include reducing consumption and utilising renewable energy sources. This paper aims to explore potential determinants of household’s fuel choice for residential heating in Türkiye. Using nineteenth wave of Household Budget Survey which was administered to 11,828 households and 40,688 individuals throughout the cou
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Shabbir, Tayyeb. "Multinomial Logit Model of Occupational Choice: A Latent Variable Approach." Pakistan Development Review 32, no. 4II (1993): 687–98. http://dx.doi.org/10.30541/v32i4iipp.687-698.

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Economists and other social scientists have had a long-standing interest in studying the different aspects of an individual's occupational choice. An important issue in this regard is an econometric analysis of the determinants of occupational choice. A rather well-known example of such a work is Schmidt and Strauss (1975) which uses a maximum likelihood procedure to estimate a multinomial logit model (MNL) where occupational choice is determined by an individual's education, experience, race and sex. Regarding the above genre of models (as, in fact, in the parallel and closely related literat
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Lee, Dongwoo, Sybil Derrible, and Francisco Camara Pereira. "Comparison of Four Types of Artificial Neural Network and a Multinomial Logit Model for Travel Mode Choice Modeling." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 49 (2018): 101–12. http://dx.doi.org/10.1177/0361198118796971.

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Discrete choice modeling is a fundamental part of travel demand forecasting. To date, this field has been dominated by parametric approaches (e.g., logit models), but non-parametric approaches such as artificial neural networks (ANNs) possess much potential since choice problems can be assimilated to pattern recognition problems. In particular, ANN models are easily applicable with their higher capability to identify nonlinear relationships between inputs and designated outputs to predict choice behaviors. This article investigates the capability of four types of ANN model and compares their p
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Davis, Peter, and Pasquale Schiraldi. "The flexible coefficient multinomial logit (FC-MNL) model of demand for differentiated products." RAND Journal of Economics 45, no. 1 (2014): 32–63. http://dx.doi.org/10.1111/1756-2171.12041.

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Paetz, Friederike, Maren Hein, Peter Kurz, and Winfried Steiner. "Latent Class Conjoint Choice Models: A Guide for Model Selection, Estimation, Validation, and Interpretation of Results." Marketing ZFP 41, no. 4 (2019): 3–20. http://dx.doi.org/10.15358/0344-1369-2019-4-3.

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The consideration of preference heterogeneity in consumer choice behavior has become state of the art. In addition, the identification of consumer segments remains essential for marketing managers. For disaggregate consumer choice data representing the basis of segmentation, the latent class multinomial logit (MNL) model is currently the most popular approach for estimating segment-specific preferences. After addressing the theoretical background of the latent class MNL model, we use an empirical choice-based conjoint data set to illustrate model estimation and validation, as well as how the e
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Lian, Lian, Shuo Zhang, Zhong Wang, Kai Liu, and Lihuan Cao. "Customers’ Mode Choice Behaviors of Express Service Based on Latent Class Analysis and Logit Model." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/610673.

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As the parcel delivery service is booming in China, the competition among express companies intensifies. This paper employed multinomial logit model (MNL) and latent class model (LCM) to investigate customers’ express service choice behavior, using data from a SP survey. The attributes and attribute levels that matter most to express customers are identified. Meanwhile, the customers are divided into two segments (penny pincher segment and high-end segment) characterized by their taste heterogeneity. The results indicate that the LCM performs statistically better than MNL in our sample. Theref
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Adanu, Emmanuel Kofi, and Steven Jones. "Effects of Human-Centered Factors on Crash Injury Severities." Journal of Advanced Transportation 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1208170.

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Factors related to drivers and their driving habits dominate the causation of traffic crashes. An in-depth understanding of the human factors that influence risky driving could be of particular importance to facilitate the application of effective countermeasures. This paper sought to investigate effects of human-centered crash contributing factors on crash outcomes. To select the methodology that best accounts for unobserved heterogeneity between crash outcomes, latent class (LC) logit model and random parameters logit (RPL) model were developed. Model estimation results generally show that s
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Dhulipala, Sowjanya. "Multi-route choice modelling in a metropolitan context: A comparative analysis using Multinomial Logit and Fuzzy Logic based approaches." European Transport/Trasporti Europei 79, ET.2020 (2020): 1–17. http://dx.doi.org/10.48295/et.2020.79.4.

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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 mode
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Xie, Feng, Ming Xie, and Cheng Wang. "Using the MNL Model in a Mobile Device’s Indoor Positioning." Biomimetics 8, no. 2 (2023): 252. http://dx.doi.org/10.3390/biomimetics8020252.

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Indoor Positioning Services (IPS) allow mobile devices or bionic robots to locate themselves quickly and accurately in large commercial complexes, shopping malls, supermarkets, exhibition venues, parking garages, airports, or train hubs, and access surrounding information. Wi-Fi-based indoor positioning technology can use existing WLAN networks, and has promising prospects for broad market applications. This paper presents a method using the Multinomial Logit Model (MNL) to generate Wi-Fi signal fingerprints for positioning in real time. In an experiment, 31 locations were randomly selected an
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Maitra, Bhargab, Santanu Ghosh, Sudhanshu Sekhar Das, and Manfred Boltze. "Effect of model specification on valuation of travel attributes: a case study of rural feeder service to bus stop." Journal of Transport Literature 7, no. 2 (2013): 8–28. http://dx.doi.org/10.1590/s2238-10312013000200002.

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In willingness-to-pay (WTP) studies, stated preference (SP) data are analyzed by developing econometric models. However, the variation of WTP across different model specifications has not been studied adequately. This paper reports a comparison of various econometric models and estimated WTP values with reference to a case study of rural feeder service to bus stop. Econometric models included Multinomial Logit (MNL), Heteroskedastic Extreme Value (HEV), Nested Logit (NL), Covariance Heterogeneity Nested Logit (CHNL), and Random Parameter Logit (RPL). Various econometric models are found to be
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Li, Yang, and Wei (David) Fan. "Pedestrian Injury Severities in Pedestrian-Vehicle Crashes and the Partial Proportional Odds Logit Model: Accounting for Age Difference." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (2019): 731–46. http://dx.doi.org/10.1177/0361198119842828.

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This study investigates factors that significantly contribute to the severity of pedestrian injuries resulting from pedestrian-vehicle crashes. Multinomial logit (MNL) models, mixed logit (ML) models, and ordered logit/probit models have been widely used in modeling crash injury severity, including pedestrian injury severity in pedestrian-vehicle crashes. However, both MNL and ML models treat injury severity levels as non-ordered, ignoring the inherent hierarchical nature of crash injury severities, and the data used in ordered logit models need to be strictly subjected to the proportional odd
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Yan, Yongnan, Xiangdong Xu, and Anthony Chen. "Is it Necessary to Relax the IID Assumptions in the Logsum-Based Accessibility Analysis?" Transportation Research Record: Journal of the Transportation Research Board 2673, no. 4 (2019): 84–96. http://dx.doi.org/10.1177/0361198119839972.

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Accessibility is an important link between transportation and land use. As a typical measure of accessibility, logsum or a utility-based measure has been widely used in project appraisal, urban transit accessibility evaluation, destination choice, and network vulnerability analysis. Since the logsum term is the log of the denominator of the choice probability expression, it inherits the independently and identically distributed (IID) assumptions of the classical multinomial logit (MNL) route choice model. This paper aims to explore whether the IID assumptions have a significant effect on the l
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Ding, Chuan, Binglei Xie, Yaowu Wang, and Yaoyu Lin. "Modeling the Joint Choice Decisions on Urban Shopping Destination and Travel-to-Shop Mode: A Comparative Study of Different Structures." Discrete Dynamics in Nature and Society 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/492307.

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The joint choice of shopping destination and travel-to-shop mode in downtown area is described by making use of the cross-nested logit (CNL) model structure that allows for potential interalternative correlation along the both choice dimensions. Meanwhile, the traditional multinomial logit (MNL) model and nested logit (NL) model are also formulated, respectively. This study uses the data collected in the downtown areas of Maryland-Washington, D.C. region, for shopping trips, considering household, individual, land use, and travel related characteristics. The results of the model reveal the sig
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Koppelman, Frank S., and Chieh-Hua Wen. "Nested Logit Models Which Are You Using?" Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (1998): 1–7. http://dx.doi.org/10.3141/1645-01.

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The adoption of disaggregate analysis in transportation and other fields has led to widespread use of choice models to describe the influence of the characteristics of decision makers and the attributes of alternatives and choices. The multinomial logit model (MNL) is the most used because of its relative simplicity, the potential to add new alternatives, its ease of estimation, and the wide availability of estimation software. However, concerns about the restrictive assumptions of the MNL (independent and identical distribution of error terms) and its properties have led to a search for more
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Jones, Stewart, and David A. Hensher. "Predicting Firm Financial Distress: A Mixed Logit Model." Accounting Review 79, no. 4 (2004): 1011–38. http://dx.doi.org/10.2308/accr.2004.79.4.1011.

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Over the past three decades the literature on financial distress prediction has largely been confined to simple multiple discriminant analysis, binary logistic or probit analysis, or rudimentary multinomial logit models (MNL). There has been a conspicuous absence of modeling innovation in this literature as well as a failure to keep abreast of important methodological developments emerging in other fields of the social sciences. In particular, there has been no recognition of major advances in discrete choice modeling over the last 15 years, which has increasingly relaxed behaviorally question
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Lipovetsky, Stan, and Michael Conklin. "MaxDiff Priority Estimations with and without HB-MNL." Advances in Adaptive Data Analysis 07, no. 01n02 (2015): 1550002. http://dx.doi.org/10.1142/s1793536915500028.

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Maximum difference (MaxDiff) is a discrete choice modeling approach widely used in marketing research for finding utilities and preference probabilities among multiple alternatives. It can be seen as an extension of the paired comparison in Thurstone and Bradley–Terry techniques for the simultaneous presenting of three, four or more items to respondents. A respondent identifies the best and the worst ones, so the remaining are deemed intermediate by preference alternatives. Estimation of individual utilities is usually performed in a hierarchical Bayesian (HB)-multinomial-logit (MNL) modeling.
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Tervonen, Tommi, Francesco Pignatti, and Douwe Postmus. "From Individual to Population Preferences: Comparison of Discrete Choice and Dirichlet Models for Treatment Benefit-Risk Tradeoffs." Medical Decision Making 39, no. 7 (2019): 879–85. http://dx.doi.org/10.1177/0272989x19873630.

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Introduction. The Dirichlet distribution has been proposed for representing preference heterogeneity, but there is limited evidence on its suitability for modeling population preferences on treatment benefits and risks. Methods. We conducted a simulation study to compare how the Dirichlet and standard discrete choice models (multinomial logit [MNL] and mixed logit [MXL]) differ in their convergence to stable estimates of population benefit-risk preferences. The source data consisted of individual-level tradeoffs from an existing 3-attribute patient preference study ( N = 560). The Dirichlet po
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Bastarianto, Faza, Muhammad Irawan, Charisma Choudhury, David Palma, and Imam Muthohar. "A Tour-Based Mode Choice Model for Commuters in Indonesia." Sustainability 11, no. 3 (2019): 788. http://dx.doi.org/10.3390/su11030788.

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With the advent of activity-based modelling, transport planners’ focus has shifted from isolated trips to tours. Tours are series of interconnected trips that start and finish at home. There are different types of tours; we focus on two: hwh (start at home; go to work; and then go back home) and hw+wh (where + represents a non-work activity). Tour types introduce a new dimension to the traditional problem of travel mode choice, as the mode choice might be influenced by the type of tour. This study attempts to measure and compare the relationship between tour type and mode choice using three di
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Clark, WAV, and J. L. Onaka. "An Empirical Test of a Joint Model of Residential Mobility and Housing Choice." Environment and Planning A: Economy and Space 17, no. 7 (1985): 915–30. http://dx.doi.org/10.1068/a170915.

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A nested multinomial logit (MNL) model is used to estimate the joint choice of moving and housing selection. The coefficients are derived from a sequential application of the standard MNL model using maximum likelihood. The choice of the dwelling type is followed by choice of neighborhood and finally by the choice of moving or staying. The models are estimated for three household categories and nine neighborhoods with data from the Rand Corporation Housing Allowance Supply Experiment. The dwelling-type choice model fits reasonably well and shows the expected significant impact of space on dwel
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Li, Hongmin, Scott Webster, and Gwangjae Yu. "Product Design Under Multinomial Logit Choices: Optimization of Quality and Prices in an Evolving Product Line." Manufacturing & Service Operations Management 22, no. 5 (2020): 1011–25. http://dx.doi.org/10.1287/msom.2019.0788.

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Problem definition: We study a product-line design problem in which customer choice among multiple products is given by a multinomial logit (MNL) model. A firm determines product quality and prices in an evolving product line to maximize profit. In particular, given the prices and quality of products that already exist in a product line, the firm optimizes prices and/or quality of the new products. Academic/practical relevance: We extend the literature on discrete choice models to include the interaction between product quality and product price and consider two variations of the problem, each
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Zhang, Jian, Chun Jing Ma, Xiang Feng Ji, and Gang Zhong. "Modeling and Sensitivity Analysis for Railway Passengers’ Public Transit Mode Choice." Applied Mechanics and Materials 641-642 (September 2014): 678–84. http://dx.doi.org/10.4028/www.scientific.net/amm.641-642.678.

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Comprehensive terminal integrates different modes of transport and sharing rates of different traffic modes influence its planning greatly. To determine the sharing rates, it’s necessary to study mode choice probability of passengers. Based on the theory of disaggregate choice, with the survey of mode choices of passengers arriving by rail in Nanjing south railway station, this paper establishes multinomial logit (MNL) model and nest logit (NL) model, considering three types of modes of transport including the subway, regular bus, and taxi. Models are calibrated with SPSS and validated through
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Wang, Xinyi, and Sung Hoo Kim. "Prediction and Factor Identification for Crash Severity: Comparison of Discrete Choice and Tree-Based Models." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (2019): 640–53. http://dx.doi.org/10.1177/0361198119844456.

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Crash severity is one of the most widely studied topics in traffic safety area. Scholars have studied crash severity through various types of models. Using the publicly available 2017 Maryland crash data from the Department of Maryland State Police, the authors develop a multinomial logit (MNL) model and a random forest (RF) model, which belong to discrete choice and tree-based models, respectively, to (1) identify factors contributing to crash severity and (2) compare prediction performances and interpretation abilities between the two models. Based on the model results, major contributing fa
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Siraj, Md Sifat Bin, Motachim Billah, and Md Ebrahim Shaik. "Exploration of Mode Choice Behavior for Regular and Short Distance Travel in a Developing Country." Journal of Engineering Science 15, no. 1 (2024): 59–73. http://dx.doi.org/10.3329/jes.v15i1.76033.

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The study of mode choice behaviour is receiving a considerable interest in Bangladesh like in other developing countries. Hence, a questionnaire survey of 514 citizens in Chittagong city was conducted to explore mode choice behaviour for short distance and regular travel. Multinomial Logit Model (MNL) was used to assess the factors involved for various mode choices. Gender, age, profession, education, level of income, household type, vehicle ownership, and distance to a stopping spot all seem to be factors that have been found to be important for short-distance and regular travel using the MNL
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Bagozzi, Benjamin E., and Kathleen Marchetti. "Distinguishing Occasional Abstention from Routine Indifference in Models of Vote Choice." Political Science Research and Methods 5, no. 2 (2015): 277–94. http://dx.doi.org/10.1017/psrm.2015.42.

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Researchers commonly employ multinomial logit (MNL) models to explain individual-level vote choice while treating “abstention” as the baseline category. Though many view abstainers as a homogeneous group, we argue that these respondents emerge from two distinct sources. Some nonvoters are likely to be “occasional voters” who abstained from a given election owing to temporary factors, such as a distaste for all candidates running in a particular election, poor weather conditions, or other temporary circumstances. On the other hand, many nonvoters are unlikely to vote regardless of the current p
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Allman, Maxwell, Itai Ashlagi, and Afshin Nikzad. "On rank dominance of tie‐breaking rules." Theoretical Economics 18, no. 2 (2023): 707–48. http://dx.doi.org/10.3982/te4762.

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Lotteries are a common way to resolve ties in assignment mechanisms that ration resources. We consider a model with a continuum of agents and a finite set of resources with heterogeneous qualities, where the agents' preferences are generated from a multinomial‐logit (MNL) model based on the resource qualities. We show that all agents prefer a common lottery to independent lotteries at each resource if every resource is popular, meaning that the mass of agents ranking that resource as their first choice exceeds its capacity. We then prove a stronger result where the assumption that every resour
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Lalisa, Wendimu Biyena. "Perception of effect of climate change and adaptation strategies of beekeepers of Welmera district, Ethiopia." International Journal of Environmental & Agriculture Research 6, no. 9 (2020): 01–09. https://doi.org/10.5281/zenodo.4059140.

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<strong><em>Abstract</em></strong><strong>&mdash;</strong> <em>This study identifies factors affecting smallholder beekeepers&rsquo; decisions to choose strategies to adapt to climate change in Welmera District, Oromia regional state, Ethiopia. Accordingly, quantitative data analysis and a multinomial logit model was used to identify&nbsp; perception of effects of climate change and adaptation strategies, and factors influencing beekeepers&rsquo; choice of adaptation strategies to climate change, respectively. Results signified that skip honey harvesting, additional feeding, bee hive shade and
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Li, Jun, Yulin Huang, and Xinjun Lai. "Modeling Stochastic Route Choice Behaviors with Equivalent Impedance." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/313249.

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A Logit-based route choice model is proposed to address the overlapping and scaling problems in the traditional multinomial Logit model. The nonoverlapping links are defined as a subnetwork, and its equivalent impedance is explicitly calculated in order to simply network analyzing. The overlapping links are repeatedly merged into subnetworks with Logit-based equivalent travel costs. The choice set at each intersection comprises only the virtual equivalent route without overlapping. In order to capture heterogeneity in perception errors of different sizes of networks, different scale parameters
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Saxena, Neeraj, Ruiyang Wang, Vinayak V. Dixit, and S. Travis Waller. "Frequentist and Bayesian Approaches for Understanding Route Choice of Drivers under Stop-and-Go Traffic." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 9 (2020): 371–82. http://dx.doi.org/10.1177/0361198120929332.

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Driving in congested traffic is a nuisance that not only results in longer travel times, but also triggers frustration and impatience among drivers. A few studies have modeled the effects of congested traffic in the resulting route choice behavior of car drivers. The studies used frequentist models such as discrete choice models to analyze large samples. However, these studies did not compare the inferences obtained from the frequentist and Bayesian approaches, particularly for datasets which are not sufficiently large. It has been shown by researchers that Bayesian models perform well, especi
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Shafique, Muhammad Awais, and Eiji Hato. "Incorporating MNL Model into Random Forest for Travel Mode Detection." July 2021 40, no. 3 (2021): 496–501. http://dx.doi.org/10.22581/muet1982.2103.04.

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Mode choice models have been used widely to forecast the relative probabilities of using available travel modes. These depend on mode-related and traveler-related characteristics. On the other hand, smartphones are increasingly being used to collect sensors’ data relating to trips made after selection of a suitable mode. Such sensors’ data may be correlated with decision-making process of travelers regarding travel mode selection. Discrete Choice Modelling is used to simulate this decision-making process by computing utilities of various travel alternatives, and then calculating their respecti
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Etebari, Farhad, Abdolah Aaghaie, and Ammar Jalalimanesh. "Intelligent Decision Support System in the Choice-based Network Revenue Management." Australian Journal of Basic and Applied Sciences 6, no. 9 (2012): 346–52. https://doi.org/10.5281/zenodo.13988435.

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During recent years, independent demand assumption in traditional revenue management models has been faced with serious doubts and has been replaced with choice-based models. More accurate modeling of individual&rsquo;s decisions is a key factor in these models. Although multinomial logit model (MNL) is the most well-known choice model, it has a limitation which causes the ratio of choice probabilities of two distinct alternatives to be independent from the attributes of any other alternatives and is called independence of irrelevant alternative (IIA). Nested logit model can be replaced with M
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Pasha, Md Mosabbir, Mark D. Hickman, and Carlo G. Prato. "Modeling Mode Choice of Air Passengers’ Ground Access to Brisbane Airport." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (2020): 756–67. http://dx.doi.org/10.1177/0361198120949534.

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Like other developed countries, Australia is experiencing considerable growth in air travel demand. This growth is putting tremendous pressure on airports to improve the capacity and level of service of access and egress modes. The main goal of this study was to develop a robust mode choice model for passengers’ access to airports, in the context of Brisbane, Australia. The novelty of this study includes (1) the use of recent techniques to combine passengers’ revealed and stated preferences for mode of access to airports and (2) the development of both traditional multinomial logit (MNL) as we
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Han, Haidi, and Shanxia Sun. "Identifying Heterogeneous Willingness to Pay for New Energy Vehicles Attributes: A Discrete Choice Experiment in China." Sustainability 16, no. 7 (2024): 2949. http://dx.doi.org/10.3390/su16072949.

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New energy vehicles (NEVs) have emerged as a promising solution to reduce carbon emissions and address environmental concerns in the transportation sector. In order to effectively accelerate market acceptance, it is crucial to prioritize the heterogeneity of consumer preferences for NEV attributes. This study employs the multinomial logit model (MNL) and latent class model (LCM) to investigate both observed and unobserved preference heterogeneity based on stated preferences obtained from a discrete choice experiment conducted across seven cities in China. Results from the MNL model indicate th
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Wang, Xiong-zhi, and Wenliang Zhou. "Integrating Dynamic Pricing and Inventory Control for Fresh Agriproduct under Multinomial Logit Choice." Mathematical Problems in Engineering 2018 (December 25, 2018): 1–12. http://dx.doi.org/10.1155/2018/5936971.

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In this article, we investigate a joint pricing and inventory problem for a retailer selling fresh agriproducts (FAPs) with two-period shelf lifetime in a dynamic stochastic setting, where new and old FAPs are on sale simultaneously. At the beginning of each period the retailer makes ordering decision for new FAP and sets regular and discount price for new and old inventories, respectively. After demand realization, the expired leftover is disposed and unexpired inventory is carried to the next period, continuing selling. Unmet demand of all FAPs is backordered. The objective is to maximize th
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Deng, Yajuan, Meiye Li, Qing Tang, Renjie He, and Xianbiao Hu. "Heterogenous Trip Distance-Based Route Choice Behavior Analysis Using Real-World Large-Scale Taxi Trajectory Data." Journal of Advanced Transportation 2020 (September 9, 2020): 1–16. http://dx.doi.org/10.1155/2020/8836511.

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Most early research on route choice behavior analysis relied on the data collected from the stated preference survey or through small-scale experiments. This manuscript focused on the understanding of commuters’ route choice behavior based on the massive amount of trajectory data collected from occupied taxicabs. The underlying assumption was that travel behavior of occupied taxi drivers can be considered as no different than the well-experienced commuters. To this end, the DBSCAN algorithm and Akaike information criterion (AIC) were first used to classify trips into different categories based
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A.T.D., M.Sc.(Eng)., Dr Masrono Yugihartiman,, and Firga Ariani. "Mengukur Efek Marjinal dan Elastisitas Permintaan Transjakarta dan Jaklingko dengan Multinomial Logit Model." Jurnal Transportasi Multimoda 22, no. 1 (2024): 16–29. https://doi.org/10.25104/mtm.v22i1.2360.

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Wacana kenaikan tarif BRT Transjakarta yang ditetapkan sejak tahun 2005 sering muncul di media masa. Untuk memberikan evidence response penumpang terhadap tarif tersebut, penelitian ini dilakukan. Adapun tujuan penelitian ini adalah untuk mengestimasi efek marjinal dan elastisitas permintaan dua jenis pelayanan, yaitu BRT Transjakarta dan Jaklingko. Metode penghitungan efek marjinal dan elastisitas menggunaknan multinomial logit model (MNL) dan conditional logit model (CLM). Pengumpulan data dilakukan dengan menggunakan stated preference survey terhadap 1.202 responden, yang terdiri dari 621 r
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Kim, GwanSeon, Mehdi Nemati, Steven Buck, Nicholas Pates, and Tyler Mark. "Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture." Sustainability 12, no. 7 (2020): 2917. http://dx.doi.org/10.3390/su12072917.

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This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as we
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