Motivated by real-world applications such as fast fashion retailing and online advertising, the Multinomial Logit Bandit (MNL-bandit) is a popular model in learning operations research, has attracted much attention past decade. In this paper, we give efficient algorithms for pure exploration MNL-bandit. Our achieve instance-sensitive pull complexities. We also complement upper bounds an almost ...

Consider a category of product variants distinguished by some attribute such as color or flavor. A retailer must construct an assortment for the category, i.e., select a subset variants to stock and determine purchase quantities for each offered variant. We analyze this problem using a multinomial logit model to describe the consumer choice process and a newsboy model to represent the retailer’...

This paper presents the process of derivation and development of a spatial multinomial logit model and its application to a housing type choice problem. Over the past few years, a relatively small body of research was developed that tries to capture the spatial and temporal dependencies across decision-makers and alternatives. While temporal dependencies are often considered especially in dynam...

the aim of this study was investigation of the factors affecting the primary choice of consumers in food purchasing in mashhad city by applying cross section data of 201 households in 2012. in this study, 56, 30, and 14% of the consumers chose healthiness of food, price of food, and taste of food, respectively, as the primary preference in food purchase. results of applying multinomial logit mo...

Latent class models offer an alternative perspective to the popular mixed logit form, replacing the continuous distribution with a discrete distribution in which preference heterogeneity is captured by membership of distinct classes of utility description. Within each class, preference homogeneity is usually assumed (i.e., fixed parameters), although interactions with observed contextual effect...

Abstract This study applied a logistic regression model to determine the odds ratio of selecting clean versus unclean energy as main household fuel choice. also undertook establish coefficients factors determining A large microeconomic dataset from KIPPRA’s comprehensive and analysis on use patterns in Kenya (2010) was employed carry out analysis. multinomial logit choices cooking fuels urban K...

Creditworthiness assessment was one of the first areas to apply machine learning techniques in economics. The creditworthiness retrofit protection vital for ESCO determining credit scoring. This study aimed develop a retrofitting model utilize with multinomial logistic (MNL) and life cycle cost analysis (LCCA). aims provide an evaluation models from financing alternative Indonesia's energy effi...

This paper focuses on the relevance of alternate discrete outcome frameworks for modeling driver injury severity. The study empirically compares the ordered response and unordered response models in the context of driver injury severity in traffic crashes. The alternative modeling approaches considered for the comparison exercise include: for the ordered response framework-ordered logit (OL), g...

We compare multinomial logit and mixed logit models for data on California households’ revealed and stated preferences for automobiles. The stated preference data elicited households’ preferences among gas, electric, methanol, and CNG vehicles with various attributes. The mixed logit models provide a much better fit to these data, and forecasting exercises demonstrate substantial differences be...