Operations Research Perspectives最新文献

英文中文

The impact of information disclosure and smart technology integration on e-retailing performance: A production delivery policy framework

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-02-27 DOI: 10.1016/j.orp.2025.100328

Muhammad Tayyab , Hira Tahir , Muhammad Salman Habib

The electronic retailers face distinct challenges in information sharing compared to their purely offline counterparts, particularly in transparently communicating their environmental practices to increasingly eco-conscious consumers. This complexity increases in e-retailing due to the absence of direct interaction and makes it difficult for consumers to evaluate the sustainability efforts of retailing channel’s stakeholders. In response to it, manufacturers and e-retailers are leveraging social media and blockchain technology for personalized advertising to bridge this information transparency gap. This research presents a sustainable multi-item integrated model for manufacturer–retailer collaboration in e-retailing by incorporating multiple delivery policies and investments in technology aimed at information disclosure and environmental footprint reduction. The manufacturer adopts a smart production system and reuse returned goods in the manufacturing process while investing in Green Emissions Reduction Technology. Meanwhile, the e-retailer enhances product demand through Information Disclosure Technology on social media and blockchain by showcasing their environmental protection efforts. By employing a hybrid analytic-metaheuristic approach, we determine optimal production and delivery policies to improve green consumer service under varying budgetary and spatial constraints. The results demonstrate a 4.39% increase in online consumer demand through information sharing and a 3.86% improvement in profitability of the collaborative retailing system under single-setup multi-delivery policy that confirms robustness of the proposed model. Scenario analysis further provides decision-makers with actionable insights by showcasing 8.44% increment in the system profit by converting traditional production into smart production system. Moreover, the sensitivity of the proposed model to balancing the technology investments among emission control and information disclosure efforts suggests keeping track of the efficiency parameters of these investment options before making technology budget allocations.

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引用次数: 0

An advanced Successive Derivative Shortest Path algorithm for concave cost network flow problems

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-02-19 DOI: 10.1016/j.orp.2025.100331

Lu Yang, Zhouwang Yang

As production scales up, transportation networks increasingly involve nonlinear costs, leading to the concave cost network flow problem (CCNFP), which is notably challenging due to its nonlinearity. Existing nonlinear programming methods addressing the CCNFP often suffer from low efficiency and high computational cost, limiting their practical application. To overcome these limitations, this paper proposes the Successive Derivative Shortest Path (SDSP) algorithm, an efficient approach that combines a sequential linear approximation framework with regional first-order information of the objective function. By integrating regional first-order information and employing an interval reduction mechanism, the SDSP algorithm effectively avoids premature convergence to suboptimal solutions, thereby achieving higher-quality solutions. Numerical experiments, including parameter selection, validation, and comparative analysis, demonstrate that the SDSP algorithm outperforms existing methods in terms of both solution quality and convergence speed. This research offers a robust and efficient solution for the CCNFP, with potential applications in various fields, including logistics and supply chain networks, where concave cost network flow issues are common.

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引用次数: 0

Optimising a closed-loop supply chain inventory system with product, material, and energy recoveries under different coordination structures

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-02-17 DOI: 10.1016/j.orp.2025.100326

Anindya Rachma Dwicahyani , I Nyoman Pujawan , Erwin Widodo

The increasing recognition of environmental concerns and the adoption of Extended Producer Responsibility (EPR) have contributed significantly to the development of sustainable industries. Reverse logistics (RL) and closed-loop supply chain (CLSC) are two concepts that involve effective management of product returns to minimise consumer waste. In this paper, the authors develop a mathematical model for inventory management in CLSC systems with multiple recovery options, including product, material and energy recoveries. The model was developed based on a supply chain structure that includes a supplier, a manufacturer, a retailer, and a material recovery facility (MRF). The proposed model helps to maximise the profit of the supply chain. A hybrid method of analytical and numerical approaches is used to determine the optimal inventory decisions, including order cycle time and number of shipments between parties. Solution procedures are proposed for decentralised (DDMS) and centralised decision-making structures (CDMS). Furthermore, a profit-sharing mechanism is also analysed in the model. A sensitivity analysis is carried out to investigate the model's behaviour concerning variations in crucial parameters, including demand, product returns, recycling cost, post-consumer recycled content, and energy recoverable item rate. The results of this study show that the CDMS, without profit-sharing, generates the highest profits for the system. On the other hand, implementing a profit-sharing mechanism provides a fairer profit enhancement to the parties involved. Applying the energy recovery at the supplier results in financial benefits for the system. Additional discussion is carried out to understand the impact of energy recovery on the model's optimal solution.

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引用次数: 0

Physical question, virtual answer: Optimized real-time physical simulations and physics-informed learning approaches for cargo loading stability

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-02-16 DOI: 10.1016/j.orp.2025.100329

Philipp Gabriel Mazur, Johannes Werner Melsbach, Detlef Schoder

Cargo stability is a crucial requirement for safe cargo loading and transport. Current state-of-the-art approaches simplify cargo loading to an idealized static problem and employ geometric- and force-based approaches. In this research, we model cargo loading stability as a dynamic problem and propose two approaches. We use (a) a physical simulation using a real-time physics engine fitted for cargo loading and (b) a physics-informed learning model trained on cargo loading data. Both approaches are capable of handling dynamic physical behavior, either explicitly through simulation, or implicitly through training a recurrent neural network on physically-biased sequential cargo loading data. Given our two objectives of maximal accuracy and minimal runtime, our benchmarking results show that our approaches can outperform current state-of-the-art static stability methods in terms of accuracy depending on the complexity scenario, but consume more runtime.

引用次数: 0

Evolutionary game analysis of stakeholder privacy management in the AIGC model

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-02-13 DOI: 10.1016/j.orp.2025.100327

Yali Lv, Jian Yang, Xiaoning Sun, Huafei Wu

The technological development powered by Artificial Intelligence Generated Content (AIGC) models, exemplified by Generative Pre-trained Transformer 4 (GPT-4) and Bidirectional Encoder Representations from Transformers (BERT), has completely transformed machine language processing and fostered substantial technological advancements. However, their extensive deployment has amplified concerns regarding data privacy risks, which are attributed not only to technological vulnerabilities but also to the intricate conflicts of interest among model providers, application service providers, and privacy regulators. To tackle this challenge, this research develops a tripartite evolutionary game model that examines the strategic interactions and dynamic relationships among large language model providers, application service providers, and privacy regulatory agencies. By employing replicator dynamic equations and Jacobian matrices, the research investigates the stability of strategic equilibria and simulates optimal adjustment paths across diverse policy scenarios. Drawing on the research findings, this paper offers practical recommendations to strengthen data privacy protection in large language models, delivering a solid theoretical foundation for policymakers and industry practitioners.

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引用次数: 0

Pricing strategy of supply chain considering response time of extended warranty service

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-02-12 DOI: 10.1016/j.orp.2025.100330

Xingjian Zhou , Yan Feng , Hongming Chen , Lihua Cai , Vladimir Bashkarev

Extended warranty services (EWS) offers avenues for new profit sources and growth opportunities. In a time-sensitive market, the response time has an important impact on the pricing of EWS and satisfying consumer utility. Applying Stakelberg Game theory, a two-echelon product-service supply chain consisting of a manufacturer and two retailers (Self-owned, Franchised) is construct. Considering the EWS response time and price to characterize the consumer utility function, the EWS pricing strategies in different market stages are studied based on the scenarios of identical response time (IRT) and different response time (DRT). The research shows that: (1) under IRT scenario, the optimal EWS pricing and cost of the self-owned and franchised retailers are negatively related to the response time, therefore, both retailers should consider a trade-off strategy between the EWS price and the response time; (2) under DRT scenario, an EWS response time threshold exists, based on which the self-owned and franchised retailers should develop the optimal EWS pricing strategies; (3) under DRT scenario, the retailers’ optimal EWS prices have a negative relationship with consumers’ price sensitivity coefficient, and a positive relationship with consumers’ time sensitivity coefficient. The manufacturer and the self-owned retailer can significantly reduce EWS response time with a limited increase in the prices. While the franchised retailer need to follow the self-owned retailer in developing its pricing strategy. The study construct a time-sensitive consumer utility function by integrating response time and pricing, more accurately portraying the expected value of EWS. Based on the market characteristics of EWS growth and maturity periods, the EWS pricing strategies are expanded regarding response time differentiation in multiple cycles. It helps companies better understand consumer demand for EWS, and assists them in formulating pricing strategies for different stages of EWS market development,and improving EWS supply chain management.

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引用次数: 0

Cooperation and competition in an oligopolistic and mature industry: A case study on the cationic reagent industry based on an optimization model

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-01-22 DOI: 10.1016/j.orp.2025.100325

Joohang Kang, Byoungil Choi, Chaehong Lim, Joonyup Eun

A cationic reagent is an essential raw material in printing paper production. The market environment of the cationic reagent industry is influenced by the printing paper industry. Owing to the COVID-19 pandemic, the global expansion of remote work and home education has decreased the demand for printing papers. Consequently, competition among market players (i.e., suppliers and buyers) in the cationic reagent industry is intensifying. This study focuses on cooperation between market players in the cationic reagent industry, representing a typical oligopolistic and mature industry. It proposes a supply chain optimization model that minimizes the costs of the entire supply chain, incorporating buyers’ risk hedge tendency to address market uncertainty. The model is empirically tested using accessible and reliable data to assess its business applicability. Numerical experiments are conducted to explore scenarios that can occur in real market environment, such as levels of risk hedging, trade disputes, decreases in demand, and changes in production capacity. The experimental results provide managerial implications. As buyers maximize the degree to which they diversify their purchase quantities across multiple suppliers to reduce risks, differential costs of the entire supply chain increase by 19%, which are costs that cannot be reduced by suppliers’ capabilities and inevitably arise due to differences between suppliers (e.g., geography, politics, and government policies). However, in unfavorable market conditions, such as trade disputes and decreases in demand, less competitive suppliers can survive. This study shows that when market demand in the cationic reagent industry decreases, two suppliers may potentially experience operational outages. In reality, these two suppliers deteriorated under the challenging market conditions during the COVID-19 pandemic.

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引用次数: 0

Novel shortcut strategies in copositivity detection: Decomposition for quicker positive certificates

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2025-01-02 DOI: 10.1016/j.orp.2024.100324

Johannes Zischg, Immanuel Bomze

Copositivity is a property of symmetric matrices which is NP-hard to check. Nevertheless, it plays a crucial role in tight bounds for conic approaches of several hard optimization problems. In this paper, we present novel promising shortcut strategies to exploit favorable instances in a systematic way, using decomposition strategies based upon the idea to allow for overlapping, smaller blocks, profiting from a beneficial sign structure of the entries of the given matrix. The working hypothesis of this approach is the common empirical observation in the community that for detection of copositivity, a negative certificate is easier to obtain than a positive one. First empirical results on carefully orchestrated randomly generated instances seem to corroborate our approach.

引用次数: 0

Facility location based on Adjusted Present Value

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2024-12-20 DOI: 10.1016/j.orp.2024.100319

Hamidreza Rezaei , Nathalie Bostel , Vincent Hovelaque , Olivier Péton , Jean-Laurent Viviani

Supply chain network design aims to optimize strategic decisions such as facility location decisions.

These decisions have a major impact on the supply chain, but also on the financial value of the company. However, financial considerations are often omitted from facility location mathematical models.

This paper addresses the challenge of identifying a relevant financial indicator that can be practically implemented in facility location models across different industries.

This paper makes several contributions: the Adjusted Present Value (APV) is identified as such a financial indicator; we propose a mathematical formulation that embeds the APV in a facility location model maximizing firm value; computational experiments demonstrate the tractability of the model. Finally, we compare the mathematical model with a sequential approach that first optimizes logistical decisions and then financial decisions. The proposed model improves the sequential approach up to 5.5%, increases the market coverage and anticipates facility location decisions.

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引用次数: 0

Smart allocation of a developer's spending on product quality and non-salary employee benefits in a supply chain of apps

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives

Pub Date : 2024-12-05 DOI: 10.1016/j.orp.2024.100320

Leonard Omer Maly, Tal Avinadav

Qualified and capable employees are crucial for the success of high-tech companies. With an ever-shrinking pool of talent, employers are forced to devise creative recruitment and retention methods, which increasingly take the form of heavy spending on non-salary benefits. The present study contributes to the existing supply-chain literature through examining the role played by such benefits in a two-agent system consisting of a platform and an app developer. In particular, we examine the effect of non-salary benefits on the outgoing quality created by the employees of the app developer. The parties follow a Stackelberg sequential game led by the platform to accurately reflect the interaction in the market, allowing us to reach equilibrium using backward induction. Our results indicate that when app developers are more risk averse or face greater uncertainty, they spend a greater amount on non-salary benefits and comparatively less on app quality. This finding highlights the importance of investing in workers, particularly in uncertain times. We further extend the applicability and robustness of our findings by introducing multiple developers to our two-agent system. The extension proves that the platform charges a universal commission rate, irrespective of the number of developers – a finding that is consistent with current practice. Given the non-linear effect of key model parameters on the profits of the supply-chain members in both the single and the multiple-developer setups, we also utilize numerical analyses and arrive at telling managerial implications for all parties.

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