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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2024年第2期39卷 1049-1066页

作者： Mutlu, Nazli Gulum Selim, Sibel Altuntas, Serkan Bingol Univ Fac Hlth Sci Occupat Hlth & Safety TR-12000 Bingol Turkiye Manisa Celal Bayar Univ Fac Econ & Adm Sci Dept Econometr TR-45030 Manisa Turkiye Yildiz Tech Univ Fac Mech Engn Dept Ind Engn TR-34349 Istanbul Turkiye

Turkish manufacturing industry is in the top three in terms of occupational accident frequency among sectors. Therefore, there is a need to determine accident cause-effect relationships in order to improve occupational safety and minimize the risks that cause occupational accidents in the manufacturing industry. An integreated data driven approach is proposed to find patterns among occupational accidents in Turkish manufacturing systems. The proposed approach uses multinomial logit model (MLM) and decision tree algorithms, namely C5.0, Classification and Regression Trees (C&RT), The quaternion estimation (QUEST), Chi-square automatic interaction detector (CHAID) ve Random Trees. In this study, 307,590 occupational accidents in the Turkish manufacturing industry between 2013 and 2019 are used. It is found that there is a statistically significant relationship among division, geographical location of the accident, year, deviation, hour day, gender and age for all accidents with injury, death and loss of limb according to the absence of disability. Additionally, division, geographical location of the accident and year are among the top five predictors based on decision tree algorithms.

关键词： Manufacturing industry occupational accidents multinomial logit model decision tree analysis occupational safety and health

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Optimizing extended warranty options with preventive maintenance service under multinomial logit model

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2025年第2期321卷 600-613页

作者： Dai, Anshu Yang, Xi Yang, Duo Li, Ting Wang, Xin He, Shuguang Tianjin Univ Finance & Econ Sch Management Sci & Engn Tianjin 300222 Peoples R China China Automot Informat Technol Tianjin Co Ltd Tianjin 300300 Peoples R China North Univ China Coll Econ & Management Taiyuan 030051 Peoples R China Shanghai Jiao Tong Univ Sino US Global Logist Inst Antai Coll Econ & Management Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Data Driven Management Decis Making Lab Shanghai 200030 Peoples R China Tianjin Univ Coll Management Sci & Econ Tianjin 300072 Peoples R China

Extended warranty (EW) services have become the primary source of profit for manufacturers. How to design the appropriate EW service to balance customer user experience with the manufacturer's profit issues has received great attention. Implementing preventive maintenance (PM) actions can not only reduce the customer's lifecycle cost but also enhance the manufacturer's brand image. Therefore, EW bundled with PM service has emerged in the after-sales market today. To enrich customers' choice, we investigate the design of EW menus bundled with PM service options, and then we jointly determine EW prices and the frequency of PM actions for the provided menus. In the proposed model, we combine the multinomial logit model with prospect theory to characterize customer choice behavior when presented with different EW menu options. Based on that, with the aim of maximizing the manufacturer's profit, we can derive sets of offers, the corresponding EW service prices, and the number of included PM actions. We also introduce two additional models that account for different customer purchase scenarios. Numerical results reveal that when the manufacturer chooses to offer a unified EW menu to all customers, it is consistently more profitable to present the menu at the point of product sales. Another interesting finding is that customized EW menus designed for various customer segments do not always outperform unified ones. Overall, this study will provide a foundation for manufacturers to make informed decisions regarding the selection and design of EW menus in various scenarios.

关键词： multinomial logit model Prospect theory Preventive maintenance Warranty menu Customized extended warranty

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Joint promotional effort and assortment optimization under the multinomial logit model

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NAVAL RESEARCH LOGISTICS 2024年第7期71卷 941-959页

作者： Xiao, Hua Gong, Min Lian, Zhaotong Nip, Kameng City Univ Macau Fac Business Macau Peoples R China Jinan Univ Coll Informat Sci & Technol Guangzhou Peoples R China Univ Macau Fac Business Adm Macau Peoples R China Shenzhen Univ Coll Management Shenzhen Peoples R China

Promotional effort is a common strategy to induce sales and broaden the market scope by enhancing the products' utility to customers. In this article, we incorporate promotional effort into the customer choice model and study the joint promotional effort and assortment optimization problems, where the customer's choice behavior follows the widely used multinomial-logit (MNL) model. Motivated by various marketing scenarios, we introduce two distinct models that address the allocation of promotional effort: (1) differentiated promotional effort-the retailer can arbitrarily allocate promotional resources to each offered product;(2) uniform promotional effort-the retailer can determine a promotional level, and the promotional effort is equally distributed to each offered product. In the first model, the revenue-ordered assortment strategy is optimal, and we can efficiently determine the optimal promotional effort level. In the second model, the revenue-ordered assortment is no longer optimal. We develop a polynomial time algorithm to solve the joint optimization problem under this model. Using the algorithmic results, we conduct comparative analyses between the assortment optimization problem under the proposed models and the classic MNL model, which does not exert any promotional effort. We show that the assortment size shrinks when the retailer makes the promotional effort in the decision, which indicates that product variety and promotional effort are strategic substitutes. Moreover, the retailer and customers can be better off in the presence of promotional efforts, irrespective of the format. Additionally, we conduct extensive numerical experiments to demonstrate our analytical results and gain more managerial insights.

关键词： assortment optimization multinomial logit model promotional effort revenue management

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Heterogeneity in crash patterns of autonomous vehicles: The latent class analysis coupled with multinomial logit model

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ACCIDENT ANALYSIS AND PREVENTION 2025年 209卷 107827页

作者： Ren, Qiaoqiao Xu, Min Hong Kong Polytech Univ Dept Ind & Syst Engn Hung Hom Hong Kong Peoples R China

Understanding the heterogeneity in autonomous vehicle (AV) crash patterns is crucial for enhancing the safety and public acceptance of autonomous transportation systems. In this paper, 584 AV collision reports from the California Department of Motor Vehicles (CA DMV) were first extracted and augmented by a highly automatic and fast variable extraction framework. Crash damage severities, classified as none, minor, moderate, and major, were set as the dependent variables. Factors including crash, road, temporal, vehicle, and environment characteristics were identified as potential determinants. To account for the heterogeneity inherent in crash data and identify key factors influencing the damage severity in AV crashes, a methodology integrating the latent class analysis and multinomial logit model was employed. Two heterogeneous clusters were determined based on the skewed distributions of vehicle status and driving mode. The model estimation results indicate a positive association between severe crash damage and some risk factors, such as head-on, intersection, multiple vehicles, dark with street lights, dark without street lights, and early morning. This study also reveals significant differences among the variables influencing the damage severity across two distinct subclasses. Moreover, partitioning the AV crash dataset into heterogeneous subsets facilitates the identification of critical factors that remain obscured when the dataset is analyzed as a whole, such as the evening indicator. This paper not only enhances our understanding of AV crash patterns but also paves the way for safer AV technology.

关键词： Autonomous vehicle Damage severity Crash pattern Heterogeneity Latent class analysis multinomial logit model

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Severity Analysis for Occupational Heat-related Injury Using the multinomial logit model

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SAFETY AND HEALTH AT WORK 2024年第2期15卷 200-207页

作者： Lyu, Peiyi Song, Siyuan Univ Alabama Dept Civil Construct & Environm Engn Safety Automat & Visualizat Environm SAVE Lab Tuscaloosa AL 35487 USA

Background: Workers are often exposed to hazardous heat due to their work environment, leading to various injuries. As a result of climate change, heat-related injuries (HRIs) are becoming more problematic. This study aims to identify critical contributing factors to the severity of occupational HRIs. Methods: This study analyzed historical injury reports from the Occupational Safety and Health Administration (OSHA). Contributing factors to the severity of HRIs were identified using text mining and model-free machine learning methods. The multinomial logit model (MNL) was applied to explore the relationship between impact factors and the severity of HRIs. Results: The results indicated a higher risk of fatal HRIs among middle-aged, older, and male workers, particularly in the construction, service, manufacturing, and agriculture industries. In addition, a higher heat index, collapses, heart attacks, and fall accidents increased the severity of HRIs, while symptoms such as dehydration, dizziness, cramps, faintness, and vomiting reduced the likelihood of fatal HRIs. Conclusions: The severity of HRIs was significantly influenced by factors like workers' age, gender, industry type, heat index , symptoms, and secondary injuries. The findings underscore the need for tailored preventive strategies and training across different worker groups to mitigate HRIs risks. (c) 2024 Occupational Safety and Health Research Institute. Published by Elsevier B.V. on behalf of Institute, Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency. This is an open access article under the CC BY-NC-ND license (http://***/ licenses/by-nc-nd/4.0/).

关键词： Heat -related injuries Impact factors multinomial logit model Worker safety

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Stochastic approximation for uncapacitated assortment optimization under the multinomial logit model

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NAVAL RESEARCH LOGISTICS 2022年第7期69卷 927-938页

作者： Peeters, Yannik den Boer, Arnoud, V Univ Amsterdam Amsterdam Business Sch Plantage Muidergracht 12 NL-1018 TV Amsterdam Netherlands Univ Amsterdam Korteweg de Vries Inst Math Amsterdam Netherlands

We consider dynamic assortment optimization with incomplete information under the uncapacitated multinomial logit choice model. We propose an anytime stochastic approximation policy and prove that the regret-the cumulative expected revenue loss caused by offering suboptimal assortments-after T$$ T $$ time periods is bounded by T$$ \sqrt{T} $$ times a constant that is independent of the number of products. In addition, we prove a matching lower bound on the regret for any policy that is valid for arbitrary model parameters-slightly generalizing a recent regret lower bound derived for specific revenue parameters. Numerical illustrations suggest that our policy outperforms alternatives by a significant margin when T$$ T $$ and the number of products N$$ N $$ are not too small.

关键词： assortment optimization incomplete information multinomial logit model stochastic approximation

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A high-dimensional multinomial logit model

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JOURNAL OF APPLIED ECONOMETRICS 2024年第3期39卷 481-497页

作者： Nibbering, Didier Monash Univ Dept Econometr & Business Stat Clayton Vic Australia

The number of parameters in a standard multinomial logit model increases linearly with the number of choice alternatives and number of explanatory variables. Because many modern applications involve large choice sets with categorical explanatory variables, which enter the model as large sets of binary dummies, the number of parameters in a multinomial logit model is often large. This paper proposes a new method for data-driven two-way parameter clustering over outcome categories and explanatory dummy categories in a multinomial logit model. A Bayesian Dirichlet process mixture model encourages parameters to cluster over the categories, which reduces the number of unique model parameters and provides interpretable clusters of categories. In an empirical application, we estimate the holiday preferences of 11 household types over 49 holiday destinations and identify a small number of household segments with different preferences across clusters of holiday destinations.

关键词： Dirichlet process prior high-dimensional models large choice sets multinomial logit model

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Technical Note-The multinomial logit model with Sequential Offerings: Algorithmic Frameworks for Product Recommendation Displays

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OPERATIONS RESEARCH 2022年第4期70卷 2162-2184页

作者： Feldman, Jacob Segev, Danny Washington Univ Olin Business Sch St Louis MO 63130 USA Tel Aviv Univ Dept Stat & Operat Res IL-69978 Tel Aviv Israel

In this paper, we consider the assortment problem under the multinomial logit (MNL) model with sequential offerings recently proposed by Liu et al. [INFORMS J. Comput., 2020] to capture a multitude of applications, ranging from appointment scheduling in hospitals, restaurants, and fitness centers to product recommendations in e-commerce settings. In this problem, the purchasing dynamics of customers sequentially unfold over T stages. Within each stage, the retailer selects an assortment of products to make available for purchase with the intent of maximizing expected revenue. However, motivated by practical applications, the caveat is that each product can be offered in at most one stage. Moving from one stage to the next, the customer either purchases one of the currently offered products according to MNL preferences and leaves the system or decides not to make any purchase at that time. In the former scenario, the retailer gains a product-associated revenue;in the latter scenario, the customer progresses to the next stage or eventually leaves the system once all T stages have been traversed. We focus our attention on the most general formulation of this problem, in which purchasing decisions are governed by a stage-dependent MNL choice model, reflecting the notion that customers' preferences may change from stage to stage because of updated perceptions, patience waning over time, etc. Concurrently, we consider a more structured formulation in which purchasing decisions are stage-invariant, utilizing a single MNL model across all stages. Our main contribution comes in the form of a strongly polynomial-time approximation scheme for both formulations of the sequential assortment problem in their utmost generality. We provide evidence for the practical relevance of these theoretical findings through extensive numerical experiments. Finally, we fit our sequential model to historical search data from Expedia's hotel booking platform. We observe substantial gains in fitt

关键词： assortment optimization multinomial logit model appointment scheduling approximation scheme E-commerce

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A multinomial logit model: Safety risk analysis of interchange area based on aggregate driving behavior data

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JOURNAL OF SAFETY RESEARCH 2022年 80卷 27-38页

作者： Zhao, Xiaohua Ding, Yang Yao, Ying Zhang, Yunlong Bi, Chaofan Su, Yuelong Beijing Univ Technol Coll Metropolitan Transportat Beijing Key Lab Traff Engn Beijing 100124 Peoples R China Texas A&M Univ Zachry Dept Civil Engn College Stn TX 77843 USA AutoNavi Software Co Traff Management Solut Div Beijing 100102 Peoples R China

Introduction: Urban expressway interchanges have become accident-prone sites owing to the accelerated increase in motor-vehicle ownership. This study explored the impact of factors, including day of the week, time of day, congestion level, traffic control devices, and road conditions, on road safety risk levels in the interchange area of an urban expressway based on aggregate driving behavior data. Method: A large amount of aggregate driving behavior data were obtained from AutoNavi navigation software. The database was built by matching various types of data and observing their characteristics. Day of the week, time of day, congestion level, road conditions (number of lanes, traffic disturbance, and traffic control devices [the type of advance guide sign system, number of warning signs, and the complexity of the diagrammatic guide sign]) were identified as the explanatory variables. The traffic order index (TOI), based on driving behavior and speed variation, was used to evaluate the road safety risk levels, including risky roads, general roads, and safe roads, which served as the response variables. The multinomial logit model (MNL) was developed to explore the impact of various factors, including traffic control devices and road conditions, on road safety risk levels. Results: The results showed that the factors that significantly influence risky roads include day of the week, number of lanes, congestion level (slow moving), traffic disturbance (with the merge or diverge within 500 m), type of advance guide sign system (three-level advance guide sign system), and complexity of diagrammatic guide signs (low or medium complexity). Practical Applications: This study could offer plausible suggestions for traffic management departments for the rehabilitation of road conditions and traffic control devices in urban expressway interchange areas. (c) 2021 National Safety Council and Elsevier Ltd. All rights reserved.

关键词： Safety risk analysis Urban expressway Interchange Aggregate driving behavior multinomial logit model

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Multiproduct pricing under the multinomial logit model with local network effects

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DECISION SCIENCES 2023年第4期54卷 447-466页

作者： Gopalakrishnan, Mohan Zhang, Heng Zhang, Zhiqi Arizona State Univ WP Carey Sch Business Tempe AZ 85287 USA Washington Univ Olin Business Sch St Louis MO 63110 USA

Motivated by direct interactions with practitioners and real-world data, we study a monopoly firm selling multiple substitute products to customers characterized by their different social network degrees. Under the multinomial logit model framework, we assume that the utility a customer with a larger network degree derives from the seller's products is subject to more impact from her neighbors and describe the customers' choice behavior by a Bayesian Nash game. We show that a unique equilibrium exists as long as these network effects are not too large. Furthermore, we study how the seller should optimally set the prices of the products in this setting. Under the homogeneous product-related parameter assumption, we show that if the seller optimally price-discriminates all customers based on their network degrees, the products' markups are the same for each customer type. Building on this, we characterize the sufficient and necessary condition for the concavity of the pricing problem, and show that when the problem is not concave, we can convert it to a single-dimensional search and solve it efficiently. We provide several further insights about the structure of optimal prices, both theoretically and numerically. Furthermore, we show that we can simultaneously relax the multinomial logit model and homogeneous product-related parameter assumptions and allow customer in- and out-degrees to be arbitrarily distributed while maintaining most of our conclusions robust.

关键词： convex optimization scoial network multinomial logit model multi-product pricing

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