Article
Management
Caner Canyakmaz, Suleyman Ozekici, Fikri Karaesmen
Summary: This study considers the joint inventory management and pricing problem faced by a retailer selling a product with uncertain selling prices. Unlike previous literature, the study assumes that demand is price-dependent and arrives randomly according to a stochastic arrival process. The objective is to maximize the expected profit by choosing the order quantity and price markup. The study characterizes the optimal inventory and markup levels and demonstrates that more volatile input price processes result in lower expected profits.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Jinzhi Bu, Xiting Gong, Xiuli Chao
Summary: This paper examines periodic review perishable inventory systems with a fixed product lifetime. The objective is to minimize the long-run average holding, penalty, and outdating cost. The paper demonstrates that a simple base-stock policy can be asymptotically optimal under certain conditions.
MANAGEMENT SCIENCE
(2022)
Article
Engineering, Industrial
Chang Xu, Tijun Fan, Qi Zheng, Yang Song
Summary: This study analyzes the markdown-pricing policies of two common cooperation modes between fresh produce suppliers and platforms. The results show that a consignment revenue-sharing contract (CRSC) is beneficial for the supplier but not for the platform, and the platform prefers CRSC due to the high deterioration rate of fresh produce.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Qiang Zhou, Shaochuan Fu, Yefei Yang, Ciwei Dong
Summary: The study investigates the impact of reference price effects on consumers' purchase behavior and retailers' policies. It proposes a solution approach based on proximal policy optimization to address the complexity of continuous domains in the joint pricing and inventory control problem. The results show that the order-up-to level increases with price thresholds, while the sales price decreases and the retailer's profits suffer from the increase in thresholds. The study highlights the effectiveness of black-box deep reinforcement learning algorithms in solving pricing and inventory control problems with psychological and behavioral concerns.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics
Amisha Patel, Isha Talati, Ankit D. Oza, Dumitru Doru Burduhos-Nergis, Diana Petronela Burduhos-Nergis
Summary: This study investigates an inventory model for retailers, focusing on the best pricing and ordering policy. The model's effectiveness is validated through mathematical proofs, numerical examples, and sensitivity analysis, aiming to optimize the retailer's net income.
Article
Business, Finance
Martin B. Tarlie, Georgios Sakoulis, Roy Henriksson
Summary: Using a simple equity valuation model, this study defines stock market bubbles and anti-bubbles as periods of temporarily explosive valuation dynamics. It identifies a mechanism for the creation and destruction of bubbles and anti-bubbles based on the interaction between valuation and expected change in corporate profitability. The study finds that valuation dynamics have been explosive in 2017, suggesting the possible formation of an equity bubble in the US.
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
(2022)
Article
Management
Linwei Xin
Summary: This paper proposes a new family of capped base-stock policies, which combines base-stock and constant-order policies, and proves its theoretical foundation through numerical demonstration. It also shows the superior performance of the capped base-stock policies compared to other well-known heuristics in general scenarios.
OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Valentin Pando, Luis A. San-Jose, Joaquin Sicilia, David Alcaide-Lopez-de-Pablo
Summary: This paper discusses an inventory model in which the demand rate is dependent on the selling price and stock level, with a focus on maximizing the return on inventory management expenses (ROIME). Optimal values for various parameters are proposed, along with sensitivity analysis of the optimal policy. A numerical example is used to compare the solutions for maximum ROIME and maximum profit per unit time.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Economics
Julie Shi, Lirong Liang, Manqi Hou
Summary: English Summary: "The Impact of the Zero-Markup Policy on Hospitalization Expenses and Health Outcomes: Evidence from Beijing" investigates the effect of China's drug price zero-markup policy (ZMP) on inpatients' expenses and health outcomes using administrative data from Beijing. The study finds that the ZMP reduces inpatients' medicine expenses by an average of 20.4%, but does not significantly change total hospitalization expenses. It also finds that the average length of hospital stay increases by 0.588 days. The results suggest that hospitals compensate for the loss in drug revenue through substitution behavior. There is no evidence that the ZMP negatively affects patients' probability of death or readmission.
CHINA ECONOMIC REVIEW
(2023)
Article
Economics
Chun-Da Chen, Riza Demirer
Summary: This paper documents a significant positive premium for oil beta uncertainty in global equity returns. The study shows that oil beta uncertainty carries a significant risk premium, even after controlling for global systematic risk factors. Developed stock markets tend to have low oil beta uncertainty, while emerging stock markets consistently face higher oil beta uncertainty. The research also suggests that oil beta uncertainty captures significant predictive information about future world market excess returns. The findings highlight the importance of oil market uncertainty in driving global stock market returns.
Article
Operations Research & Management Science
Yen-Deng Huang, Gede Agus Widyadana, Hui Ming Wee, Mauricio Fontoura Blos
Summary: Due to the stochastic demand and uncertain environment during the pandemics, the vendor and retailer use revenue sharing and markdown policies to share risks and benefits. Three supply chain coordination policies are developed, and it is found that the revenue sharing contract is more attractive for the retailer while the centralized policy is preferred by the vendor. The sensitivity analysis shows that the number of markdowns is not sensitive to demand variations.
RAIRO-OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
M. Hemmati, S. M. J. Mirzapour Al-e-Hashem, S. M. T. Fatemi Ghomi
Summary: This study focuses on a joint economic lot-sizing model with two complementary products in a supply chain, considering different models that include bundling and separate sales to maximize profit. Results from numerical experiments show that the marginal profit from bundling sales is higher than that of individual products, and supply chain members can benefit from economies of scale in bundling sales.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Management
Mustafa Hekimoglu, Alan Scheller-Wolf
Summary: Companies use different criteria to evaluate suppliers and often use multiple suppliers to reduce stockout risk. However, there may be significant differences in quality levels among suppliers. This study introduces a Dual Sourcing problem with Stock-out dependent substitution (DSWS) that considers quality differences. The optimal policy for DSWS is challenging to determine due to the nonconvexity of the multi-period model.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Zibin Xu, Anthony Dukes
Summary: When consumers' inferences of their reservation values are affected by noise, firms can use customer data aggregation to improve knowledge. This can lead to personalized pricing, but may also cause consumer suspicions of overpaying. To alleviate suspicions, firms can include a list price in their personalization scheme, especially when consumers underestimate their value. Contrary to conventional wisdom, firms cannot abuse their informational advantage to manipulate consumers into overestimation, and price discrimination may actually benefit consumers by preventing overpayment.
MANAGEMENT SCIENCE
(2022)
Article
Business, Finance
Jun Lou, Tat Wing Wong, Ka Wai Terence Fung, Jonas J. Nazimoff Shaende
Summary: The study modifies Bekaert et al.'s model by allowing consumption growth to depend on dividend yield rather than dividend growth. Through the generalized method of moments, the calibrated moments of the model are found to broadly match the first and second moments of stocks, bonds, and other macroeconomic variables in the US. The model's predicted risk aversion is countercyclical and shows significant improvement in predictive power on the price-dividend ratio compared to Campbell and Cochrane's model.
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE
(2021)
Article
Engineering, Manufacturing
He Xu, David D. Yao, Shaohui Zheng
PRODUCTION AND OPERATIONS MANAGEMENT
(2016)
Article
Operations Research & Management Science
Xiuli Chao, Xiting Gong, Shaohui Zheng
ANNALS OF OPERATIONS RESEARCH
(2016)
Article
Engineering, Industrial
Qing Li, He Xu, Shaohui Zheng
Article
Management
Xiuli Chao, Hong Chen, Shaohui Zheng
OPERATIONS RESEARCH
(2009)
Article
Engineering, Manufacturing
Xiting Gong, Xiuli Chao, Shaohui Zheng
PRODUCTION AND OPERATIONS MANAGEMENT
(2014)
Article
Management
Qing Li, Shaohui Zheng
OPERATIONS RESEARCH
(2006)
Article
Engineering, Industrial
SH Zheng
Article
Engineering, Industrial
SH Zheng
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)