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Multinomial Logit Model of Pedestrian Crossing Behaviors at Signalized Intersections
Published 2013-01-01“…Moreover, based on the results of SEM, a multinomial logit model with latent variables is developed to describe how the factors influence pedestrians’ behavior. …”
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Multinomial logit regression adoption: Identifying user characteristics of e-wallets in Can Tho City, Vietnam
Published 2024-05-01“…This research adopted Multinomial Logit Regression to investigate factors that influence users’ choice of e-wallets and how these elements affect the probability of current e-wallet usage, suggesting that each service is preferred by different user groups based on demographic and behavioural traits. …”
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A EVALUATION OF CONSUMER’S PREFERENCES IN THE CLUJ-NAPOCA RETAIL MARKET BASED ON A MULTINOMIAL LOGIT MODEL
Published 2009-01-01“…The results obtained in thestudy, through the multinomial logit model, show different aspects of theclient’s behaviour from the Romanian retail market.…”
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The evolving dynamics of airport ground access: A multinomial logit analysis of mode choice at Guwahati Airport, India
Published 2025-06-01“…A total of 700 air passengers were surveyed using a random sampling technique over 15 consecutive days, providing comprehensive data for the analysis. A multinomial logit (MNL) model was employed to examine factors influencing mode choice, considering variables such as age, residential status, group size, car ownership, luggage, safety, and convenience. …”
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Determinants of multiple agricultural technology adoption: evidence from rural Amhara region, Ethiopia
Published 2022-12-01“…The study is based on an Ethiopian socio-economic survey of 2015/16 and a sample of 656 farm households is considered. The paper uses a multinomial logit model to assess the factors affecting the adoption decision of agricultural technology. …”
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A Study on the Dynamic Relationship between Embodied Carbon Productivity and Embodied Value Added in China’s Industrial Sectors: An Empirical Analysis Based on the Decoupling Model...
Published 2024-03-01“…Based on the decoupling theory, this paper analyzes the relationship between the embodied carbon productivity and the embodied value added in China’s industrial sectors, evaluates the development mode of the sectors, and explores a reasonable path to promote the green and low-carbon transformation of the sectors based on the panel multinomial logit model. The empirical conclusions are as follows: (i) Except for the decrease in 2002–2005, the embodied carbon productivity achieved rapid growth in other time periods; during the period of 2002–2020, the embodied value added increased by 339.59 percentage points, with an average annual growth rate of 8.57%, and the embodied carbon productivity increased by 70.59 percentage points, with an average annual growth rate of 3.01%. …”
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Factors influencing land rental market participation: a case study in Northern Ireland
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Assessing the impact of peripheral mega retail centres on traditional urban shopping centres
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Do Payout Policies and Channel Preferences of Banking Industries Shift during the Tranquil Periods? Evidence from Emerging Market
Published 2020-10-01“…Moreover, the results of the multinomial logit model, demonstrate that the payout policy of the commercial banks listed on the PSX, is not influenced by the global financial crisis. …”
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Consumers’ response to genetically modified food: an Italian case study
Published 2024-12-01“…By using a Multinomial Logit Model (MNL), starting from three hypotheses, the study highlights a gap in knowledge transfer and, in general, the communication process. …”
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Elderly travel mode choice in Thailand-evaluating MNL and machine learning models
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Prediksi Dampak Pembangunan Jalan Tol Trans Sumatera Pada Permintaan Perjalanan Udara Antar Provinsi di Pulau Sumatera
Published 2024-10-01“…Keywords: Stated Preference, Multinomial Logit Model, Trans Sumatera Toll Road, Air Demand…”
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Ordered Choice Models: Ordinal Logit and Ordinal Probit
Published 2022-11-01“…If this assumption is not met, the generalized ones of the ordinal logit and ordinal probit models, which are more flexible in terms of assumptions, or the multinomial logit model can be used. …”
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Analysis of selectional preference for grassland ecological compensation methods under the perspective of herders differentiation
Published 2025-05-01“…IntroductionExploring herders’ preferences for grassland ecological compensation methods provides a decision-making basis for strengthening the incentive effects of grassland ecological compensation policies.MethodsThe research utilized survey data of 372 herders from three prefecture-level cities in Inner Mongolia, and comprehensively applied grey relational analysis (GRA) and multinomial logit (MNL) model to empirically analyze herders’ selectional preferences for grassland ecological compensation methods and influencing factors from the perspective of herders differentiation.ResultsThe findings revealed: (1) More than two thirds (69.28%) of the herders preferred simple and convenient “financial compensation” in addition to existing forms of compensation; 10.22%, 10.48%, and 11.02% of the herders preferred in-kind compensation, technological compensation, and policy-based compensation, respectively. (2) Compared with individual and livestock operation characteristics, herders’ differentiated behavioral attitudes and family characteristics were more strongly associated with their preferences for compensation methods. (3) Compared with direct financial compensation, herders’ gender and transport distance to the nearest marketplace significantly influenced the choice of in-kind compensation; herders’ age, livestock numbers, grazing area, and dependence on subsidy and reward policies significantly influenced the choice of technological compensation; herders’ gender, age, number of family laborers, level of part-time income, willingness for professional transformation, and perception of the rationality of compensation types significantly influenced the choice of policy-based compensation.DiscussionTo optimize compensation modes for grassland ecological conservation, a “diversified & differentiated” positive incentive system should be constructed according to herders’ preferences and differentiated characteristics in order to facilitate voluntary livestock reduction, meanwhile a negative incentive should be incorporated to constrain herders’ overgrazing behavior.…”
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Enhancing poverty classification in developing countries through machine learning: a case study of household consumption prediction in Rwanda
Published 2025-12-01“…Among the 12 classifiers evaluated, multiple kernel support vector machines, eXtreme gradient boosting, and multinomial logit demonstrated the highest predictive accuracy, ranging between 86.6% and 88.5%. …”
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COVID-19 Lockdown and Implications for Household Food Security in Zambia: Quality of Diet or Economic Vulnerability?
Published 2025-07-01“…Two complementary food security measures are analysed using multinomial logit regression models: household expenditure share, representing economic vulnerability, and household dietary diversity score (HDDS), representing diet quality. …”
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Factors influencing injury severity in three-wheeled motorized rickshaw and motorcycle collisions
Published 2025-05-01“…The current study aims to fill this gap by investigating the risk factors contributing to injury severity in such crashes, employing a random parameters multinomial logit model with heterogeneity in means and variance. …”
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Assessing heterogeneity in factors influencing three-wheeled motorized rickshaws crash outcomes between weekdays and weekends
Published 2025-04-01“…The current study aims to fill this gap by investigating the risk factors contributing to injury severity in such crashes, employing a random parameters multinomial logit model with heterogeneity in means and variance. …”
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Analysis of school commuting behavior differences based on China family panel studies
Published 2024-03-01“…Utilizing data from the 2020 China family panel studies (CFPS), this study employs a multinomial logit model to comprehensively analyze differences in factors such as individual characteristics, family attributes, school features and geographical characteristics in school travel mode selection. …”
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