Article
Economics
Matthias Ulrich, Hermann Jahnke, Roland Langrock, Robert Pesch, Robin Senge
Summary: This study introduces an automated model selection framework for retail demand forecasting, aiming to improve forecasting accuracy and reduce costs by considering the diversity of demand patterns. Promising results were found in comparison to established benchmarks, highlighting the need for case-specific solutions.
INTERNATIONAL JOURNAL OF FORECASTING
(2022)
Article
Business
Xin Tian, Haoqing Wang, E. Erjiang
Summary: The study proposes a Markov-combined method (MCM) for forecasting intermittent demand, which divides the prediction process into two stages and shows more accurate results than traditional forecasting methods.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2021)
Article
Engineering, Industrial
Haytham Omar, Walid Klibi, M. Zied Babai, Yves Ducq
Summary: Omnichannel retailing has increased the complexity of supply chain demand forecasting, as customers now purchase diverse products through various channels. This study proposes a new approach using customer shopping basket data to forecast demand and improve accuracy and stock control in omnichannel retailing. By utilizing network graph theory and marketing literature, four attributes are identified to promote connectivity between products in shopping baskets. Empirical analysis conducted on a major cosmetics retailer in France demonstrates the effectiveness of the proposed forecasting methods, showcasing the benefits of joint forecasting and shared inventory between online and store channels in reducing shortages.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Management
Will Ma
Summary: This study focuses on the dynamic fulfillment problem in e-commerce and proposes two improved schemes. These schemes aim to minimize the allocation of items to multiple fulfillment centers while satisfying frequency constraints, with results close to optimal. Numerical tests show that these schemes improve runtime, reduce code complexity, and significantly enhance performance in practical applications.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2023)
Article
Agricultural Economics & Policy
Svetlana Fedoseeva, Ellen Van Droogenbroeck
Summary: The sudden demand spike for online grocery purchases during the Covid-19 pandemic and supply bottlenecks caused by disrupted global value chains put immense pressure on prices. We analyze the prices of the largest German online grocers to test how these challenges affected prices during the first wave of the pandemic. Using a large dataset of online price quotes, we shed light on the magnitude of price changes across retailer types, product categories, and stages of the pandemic. We show that online prices went up as the intensity of Covid-19 containment measures increased. The magnitude of price increases was heterogeneous across retailers and product categories: pure online retailers showed a lower price response compared to hybrid stores, while the prices of essential food items such as baby foods and pantry products increased more than those of other product categories or beverages.
Article
Chemistry, Multidisciplinary
Yuk Ming Tang, Ka Yin Chau, Yui-yip Lau, Zehang Zheng
Summary: Building an adaptive, flexible, resilient, and reliable inventory management system is crucial for cross-border e-commerce, as it ensures a steady supply of products, meets changing customer demands, and enables automation of e-commerce services. This study conducts intensive data collection and establishes an AI-based forecasting framework to optimize inventory management. The XGBoost method shows the best performance in accuracy and computation time. The research findings have practical implications for implementing algorithms in other e-commerce enterprises and highlight the current trend of logistics 4.0 solutions.
APPLIED SCIENCES-BASEL
(2023)
Article
Business
Anett Erdmann, Jose M. Ponzoa
Summary: This research examines the cost-result relationship of Inbound Marketing actions used by grocery ecommerce, analyzing the mix of SEO and SEM techniques among 29 leading companies over a six-year period. The results suggest that ecommerce is optimizing Digital Inbound Marketing in accordance with an established model, although differences were identified based on format type (pure player versus brick and mortar) and country level (UK and USA versus others).
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Computer Science, Artificial Intelligence
Luiz Augusto C. G. Andrade, Claudio B. Cunha
Summary: This study proposes a more effective approach to forecast inventory for retailers at store level, using XGBoost as the learning algorithm and a structural change correction method. The results show that this approach outperforms the widely used benchmark model in terms of accuracy and inventory management.
APPLIED SOFT COMPUTING
(2023)
Article
Business
Erik Ernesto Vazquez
Summary: The growth of e-retail has expanded to a wide range of product categories, with e-retailers competing in a multichannel environment using various social media platforms. This study proposes a theoretical framework to assess the effect of different SMPs on consumers' perception of product quality, which was partially validated through empirical data. The research findings offer insights for practitioners to organize e-retail product displays across diverse SMPs and for scholars studying e-retailing and digital media.
ELECTRONIC MARKETS
(2021)
Article
Management
Ju Myung Song, Yao Zhao
Summary: This study examines the coordination of an E-commerce supply chain between online sellers and third party shippers, focusing on the impact of shipping contracts and supply chain coordination. The results show that under information symmetry, the flat rate contract is as good as the risk penalty contract for the shipper, but under information asymmetry, the risk penalty can benefit the shipper more.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Review
Green & Sustainable Science & Technology
Yi Yang, Komal Habib, Michael O. Wood
Summary: The growth of online retail has led to an increase in packaging waste. Current research focuses on packaging design and material choices, but guidelines, policies, strategies, and practices for e-commerce packaging waste management need to be determined.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Business
Jing Yu, Jingjing Zhao, Chi Zhou, Yufei Ren
Summary: E-commerce platform plays a crucial role in the online retailing market, and the selling decisions between the platform and brand manufacturers significantly impact profitability. Being a reseller on the e-commerce platform is always more profitable for brand manufacturers, regardless of the business mode. Additionally, new brand manufacturers benefit more when consumers are less accepting of their products. Moreover, competition among brand manufacturers is beneficial to the e-commerce platform.
JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH
(2022)
Article
Engineering, Chemical
I-Fei Chen, Chi-Jie Lu
Summary: This study integrated clustering analysis, extreme learning machines, and support vector regression to construct models for demand forecasting in the fashion industry, with results showing improved prediction accuracy and the KM-ELM model being particularly suitable for retailers with and without physical stores.
Article
Engineering, Manufacturing
Jia Guo, Burcu B. Keskin
Summary: This paper studies the optimal supply chain design for a dual-channel retailer, focusing on integrating the supply chain operations of physical and web-based stores. The researchers formulate the problem as a two-stage stochastic programming model and explore four supply chain design options based on different omni-channel strategy decisions. The study shows that omni-channel strategies may not always be profitable under all market conditions, but they can be beneficial when the company can allocate its inventory perfectly and serve web-based customers and in-store customers effectively.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Business
Fengying Hu, Zhenglong Zhou
Summary: The integration of offline and online channels is crucial for the transformation and development of e-commerce platforms. This study examines the optimal information service and omnichannel strategy choice for a platform and two suppliers under different agreements. The findings suggest that the platform can increase offline information service and profits through an omnichannel strategy under a reselling agreement when product competition intensity is low. However, under high product competition intensity, the optimal choice is an omnichannel strategy under a hybrid retailing agreement, where the platform transfers profit to suppliers through a smaller referral fee.
ELECTRONIC COMMERCE RESEARCH
(2023)
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)