Annals of Operations Research最新文献

In simple games, larger coalitions typically wield more power, but do all players align their efforts effectively? Consider a voting scenario where a coalition forms, but needs more voters to pass a bill. The cohesion of the new group of voters hinges on whether all the new members can proficiently collaborate with the existing players to ensure the bill’s passage or if subgroups form that pursue an independent alternative, thus generating antagonism among the new voters. This research introduces two classes of coopetition indices– one relative and one absolute, the latter ranging from −1 to 1, to measure agents’ preferences for cooperation (when positive) or competition (when negative) with the remaining players. These indices, together with a generalized group value, provide a comprehensive picture of the relevance and the cohesion of groups. We discuss the relationship with similar group indices and provide proper coopetition Banzhaf and Shapley-Owen types of indices. By applying our indices to the apex game and symmetric majority games, we observe that cooperation and competition frequently balance each other out, leading to null values for the Shapley-Owen and Banzhaf coopetition indices. An electoral application with real world data is also considered.

Reverse logistics (RL) creates a number of opportunities for electronic equipment manufacturing enterprises and helps to augment the sustainability of a supply chain (SC). In India, outsourcing to Third Party Reverse Logistics Providers (3PRLPs) is a prominent initiative for a successful RL business model. However, small and mid-size enterprises (SMEs) face a number of risks in outsourcing RL activities. In this context, this study fills the literature gap by identifying and analysing the risk factors associated with outsourcing to 3PRLPs by SMEs in electronics sectors in India for a successful and sustainable reverse supply chain (RSC). Initially, 30 risk factors in the context of RL outsourcing are identified and clustered into 6 risk categories, namely “relationship and competence risks”, “economic risks”, “operational risks”, “organizational risks”, “social risks”, and “environmental risks”. Then, a weighted influence non-linear gauge system (WINGS) is used to understand the level of importance of each risk category and, simultaneously, they are also classified in cause and result groups. Similarly, risk factors within each risk category are evaluated. The findings indicate that SMEs in the electronics sector in India encounter several risks in outsourcing RL activities like uncertainty in returns, financial burden, stiff competitions, 3PRLP opportunism, and many more. Hence, an immediate intervention is recommended for SMEs in the electronics sector in India to overcome the risk factors under the “economic” and “relationship and competence” risk categories to implement sustainable and business efficient RL through outsourcing to 3PRLP. The implications drawn from the study will guide the RL team experts of SMEs to deal with risks in the course of outsourcing to 3PRLP.

Driven by the critical global climate, developing green supply chains has become an essential goal for companies. Artificial Intelligence (AI) techniques like ChatGPT have experienced tremendous development in recent years, and the AI content generation techniques have reached a new stage of application. While ChatGPT has made significant contributions to the fields of mass media, computer science, education and others, there is limited research on its application in the supply chain management. Therefore, this research aims to explore the management capabilities of green supply chain by proposing a new application framework for ChatGPT. In this study, empirical data were collected from 215 listed companies in China. By employing ChatGPT to analyse these data and comparing with benchmark statistical analysis methods, this paper reveals the significant potential of ChatGPT in green supply chain management. The empirical analysis results demonstrated that ChatGPT could assist companies in green assessment of internal supply chains and provide management suggestions by exploring green data, and thus assist companies to achieve more efficient green supply chain management. This study provided preliminary application attempts and validated the effectiveness of ChatGPT, which might encourage companies to consider the introduction of ChatGPT-liked large language models in green supply chain management to further promote the construction of green supply chains. Furthermore, this study explored potential research topics of ChatGPT in green supply chain management and seeks to help researchers to develop further research in this topic.

Multicommunication is one of the methods at our disposal to address the significant challenges of reliability and latency in today’s communications. This paper presents a game-theoretical analysis of multicommunication, where we assume that players in a TU-game are restricted in their communication by a multigraph, whose links may or may not have limitations on capacity, frequency, or transmission speed. We generalize the classical position value defined for graph games to assess the importance of different communication providers. Extending to this context the classical properties of component efficiency and balanced link contributions we can characterize the new value. For a wide variety of multicommunications including but not limited to all those where the connections are in series or parallel, the value can be characterized by substituting balanced link contributions for the more restrictive balanced link pack contributions. In the case of limitations in capacity, parallel characterizations are obtained in which component efficiency must be substituted by a certain inefficiency that takes these limitations into account.

This study develops a comprehensive policy-making model to diffuse sustainable supply chain management (SSCM) across pharmaceutical supply chains (PSCs), addressing triple bottom line (TBL) concerns—people, planet, and profit—while considering stakeholder dynamics interactions and unexpected events like global pandemics. Initially, the pharma industry's most essential TBL criteria are extracted by systematically reviewing the extant literature. Next, two different types of evolutionary game theory (EGT) (i.e., pairwise contest game (PCG) and tripartite evolutionary game (TEG)) are innovatively integrated to describe the stakeholders' interactions, providing a theoretical basis for assessing strategy stability and sustainable practice diffusion across multi-tiered and multi-echelon PSCs under regulators' interventions. Then, a system dynamics (SD) model is developed based on the EGT models to simulate the targeted policy-making system based on Iran's PSC as a case study. Key findings reveal that COVID-19 health protocols and lockdowns increased work avoidance among Regulatory Enterprises (REs), but long-term adherence to sustainable policies by distributors (Ds) and retailers (Rs) is projected by 2228. Five policies—imposing fines, segregation and public disclosure, increased punishments and incentives, rewards for sustainable practices, and subsidies for sustainable purchases—are recommended to accelerate sustainable adoption by 2056, eliminate RE work avoidance, and achieve significant outcomes: a monthly reduction of over 2,000 expired products, a decrease of around 1,000 TCO2e (Tons of Carbon Dioxide Equivalent) in upstream CO₂ emissions, an increase of over 600 TCO2e in CO₂ neutralisation, and over 100 new monthly job vacancies. This highlights the model's potential to diffuse economic, environmental, and social sustainability in PSCs post-COVID-19 under regulations.

Systems commonly experience competing risks of internal degradation and random shocks. Random shocks may cause damage to the system, and the degrees of the damage affect system degradation differently. In this paper, we consider a system, namely, a damage-resistant system, designed to withstand shocks up to a specified threshold. To consider the system damage resistance, we first propose a new shock classification based on the shock magnitude and define the damage resistance level of the system accordingly. Furthermore, because the system will be more vulnerable to shocks over time, we divide the system degradation process into two stages and propose nonlinear Wiener process degradation models with two stages by incorporating the system damage resilience level with the new shock classification. The closed-form system reliability functions for these two stages are further derived. Lastly, we conduct numerical examples with real-world data to demonstrate the practical application of our proposed model.

In this paper we examine the relation between the “bad outputs as inputs” with other approaches of modeling undesirable outputs in non-parametric production analysis and we end up with six equivalencies among them. Based on these, we argue that the “bad outputs as inputs” is a valid modeling option as long as the assumption of extended strong disposability and thus of reverse outputs is reasonable in a particular setting. In this case, the “bad outputs as inputs” approach can easily be implemented by means of a conventional input-oriented DEA model with variable returns to scale where the translated additive inverse transformation is applied to undesirable output quantities.

We study a loss-averse (LA) retailer with a quantity-oriented reference point (RP) in a piecewise form in a random market. The proposed RP is characterized by a two-fold convex combination of three elements (profits in three environments) at low reference levels, and a standard convex combination of two elements (profits in two environments) at high reference levels. We aim to use prospect theory with the above piecewise-formed RP to characterize the LA retailer’s optimal procurement strategy in maximizing her expected profit, and describe the effect on the procurement strategy from some parameters. We prove that there exists a procurement strategy inducing the LA retailer to make her optimal ordering decision given a random market with a general distribution. We analyze the respective effect of LA degree and reference level on retailer’s optimal procurement strategy, and obtain some intuitive insights, such as, a LA retailer always orders less than a loss-neutral one; increasing LA degree leads to more cautious ordering behavior; a lower RP level leads retailer to over-order, and a higher RP leads to under-order. Moreover, we find that the joint effect from LA degree and RP level on the optimal order quantity is mutually reinforcing. This joint effect also presents results consistent with people’s cognition, that is, the optimal order quantity of a LA retailer with RP is more likely to be lower than a classical retailer, compared to a risk-neutral retailer with RP. We finally provide the sensitivity analysis of parameters on the optimal order strategy.

Circular supply chain management is expected to shift the steel sector from a conventional economic paradigm to a more fruitful circular economy. Furthermore, tracing reusable and recyclable metals across the steel industry’s supply chain necessitates multi-stakeholders’ involvement. Radio frequency identification (RFID) may assist in the governance of the complexity of circular steel supply chain management (CSSCM), strengthening the steel industry’s transparency as well as efficiency. The following research develops a decentralized and service-oriented RFID-enabled blockchain-integrated conceptual framework that incorporates a circular steel supply chain strategy for the B2B steel sector to achieve this goal. Industrial methods, inventory management, and resource utilization are examined in this study. The findings show that RFID-enabled blockchain technology enhanced firm’s capacity to share real-time knowledge with CSSCM stake-holders and aid organizations in the B2B steel sector in understanding the aspects that influence the steel sector’s overall performance. Management must need to understand the value of associated technologies to deliver CSSCM and make choices faster. The implications of adopting RFID-enabled blockchain technology to serve the circular economy are discussed from theoretical, practical, and social perspectives.