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We develop a price competition model for a new supply chain that competes in a market comprised of some rival supply chains. The new supply chain has one risk-neutral manufacturer and one risk-averse retailer in which the manufacturer is a leader and retailer is a follower. The manufacturer pays a fraction of the risk cost (caused by demand uncertainty) to the retailer. We apply this competitive model to a real-world case in a supply chain under uncertain environment and obtain the optimal wholesale and retail prices. We show that our obtained prices are better than the existing wholesale and retail prices and admit more profits for both manufacturer and retailer and generally for the entire supply chain. Also, using this case, the effects of risk sensitivity of retailer and fraction of risk cost shared by manufacturer in the total risk cost on the new supply chain’s optimal wholesale and retail prices and profits are illustrated.

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We develop a new coordination contract of manufacturer-retailer in a distribution system. A revenue sharing contract based on retail price is modelled, which is more practical to handle channel conflict. We also integrate two concepts of CSR (Corporate Sociality Responsible) and Semi-TDPD (Semi Third Degree Price Discrimination) into our model. Semi-TDPD strategy makes it possible to exploit the opportunity of customer behavior, by adopting a price discrimination strategy. According to this strategy, some customers who cannot or are not willing to pay the posted price, are allowed to purchase at lower prices through bargaining. To illustrate the proposed approach, we present some numerical examples. Through these examples, we investigate the impact of CSR and Semi-TDPD on decisions and also the good performance of this coordination.

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In this paper, a novel scenario-based two-level inventory control model with a limited budget is formulated. The demand during the selling period is considered to follow a uniform probability distribution. In addition, it is assumed that there will be some customers who are willing to wait for their demands to be satisfied; thus a service level is considered for these customers. The aim is to find the optimal order quantities of the products and the required raw materials such that the relevant expected total profit obtained during the period is maximized. After proving the convexity of the proposed formulation, a penalty function and the Barrier method is proposed to solve the developed nonlinear stochastic programming problem. The problem is solved under different demand scenarios defined in three states of good, fair, and low. Finally, a case study in a dairy manufacturing company is provided to illustrate the application of the proposed methodology in real-world inventory control systems.  

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As one of the main challenges of the 21st century supply chain, complexity has become a crisis, costly, and difficult for many supply chain managers. However, few studies have prioritized this strategy. This study aimed to investigate the effect of supply chain complexity on competitiveness performance in the Iran Khodro Company. To achieve this goal, the relationship between different sources of complexity (upstream complexity, domestic production, and downstream complexity) and competitiveness performance is examined using a conceptual model. The statistical population of this study included all Iran Khodro experts, whose number reached 218 in 2022. Owing to the limitations of the statistical community, all members were selected as a sample. The collection tools for this study included two standard questionnaires: the supply chain and Porter's competitiveness performance. The content validity of the questionnaires was confirmed by experts, its construct validity was confirmed by confirmatory factor analysis, and the reliability of the questionnaires was confirmed using Cronbach's alpha coefficient and the combined reliability index. The collected data were analyzed using the structural equations in the LISREL software. The results of hypothesis testing show that, in general, supply chain complexity has a significant inverse effect on competitiveness performance.
 

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Abstract
Objective: From economic, environmental and social perspectives, the sustainability of the supply chain can give a competitive advantage to organizations. By designing a hybrid discrete event agent-based simulation model based on the simulation-optimization approach and meta-heuristic algorithms, this study has sought to evaluate the sustainability of the supply chain and improve the economic, environmental and social objectives of the supply chain.
Method: First, by identifying supply chain agents, an agent-based simulation model is developed. After designing the hybrid simulation model, the verification and validation phases are performed. By combining the simulation model with meta-heuristic algorithms and using the simulation-optimization approach, the optimal/near-optimal values of the components affecting the sustainability of the supply chain are finally extracted.
Findings: In addition to being able to reflect all the complexities of supply chains, the hybrid simulation optimization approach can also improve the key components affecting the sustainability of the supply chain.
Results: Implementation of sustainable supply chain components without optimizing the key variables of the supply chain can lead to the deterioration of performance and sustainability of the supply chain. The components of the maximum levels of product and inventory maintenance and how to implement environmental and social aspects in all the elements of the supply chain have a direct effect on the chain performance and should have appropriate values in different scenarios.
 

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In this paper the pricing of reverse products in a two-level closed-loop supply chain is considered and a game theory approach is used to solve it. Pricing is a sensitive and vital issue for businesses. In the market of reverse products, this issue will be much more difficult and complex due to difficulties associated with collecting and re-manufacturing processes. On the other hand, the use of the internet and direct channels for collecting products from customers alongside traditional retailers is an important issue that requires management and coordination. The proposed price for buying second-hand and defective products from customers should be high enough to convince them that returning the products has more benefits than discarding or keeping them at home. At the same time, the price should be low enough to make it economically viable for producers to carry out the repair and re-manufacturing operations and resell them in the direct supply chain for the producer. The use of game theory, where the decisions of one player affect the decisions and outcomes of other players as well as their outcomes, is a suitable method for solving the problem of pricing reverse products in a two-level closed-loop supply chain

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In this paper, a closed-loop supply chain (CLSC) is modeled to obtain the best location of retailers and allocate them to other utilities. The structure of CLSC includes production centers, retailers’ centers, probabilistic customers, collection, and disposal centers. In this research, two strategies are considered to find the best location for retailers by focusing on 1) the type of expected movement and 2) expected coverage. To this end, a bi-objective nonlinear programming model is proposed. This model concurrently compares Strategies 1 and 2 to select the best competitor. Based on the chosen strategy, the best allocation is determined by employing two heuristic algorithms, and the locations of the best retailers are determined. As the proposed model is NP-hard, a meta-heuristics (non-dominated sorting genetic) algorithm is employed for the solution process. Afterward, the effectiveness of the proposed model is validated and confirmed, and the obtained results are analyzed. For this purpose, a numerical example is given and solved through the optimization software.
 

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The basic purpose of this study is to investigate and display causal relationships among collaboration components in supply chain 4.0 using a fuzzy framework. The power of collaboration increases with the effect of Industry 4.0 technologies for the improvement of supply chain performance, so supply chain 4.0 is the context of this study. To achieve the research purpose, after reviewing articles and extracting indicators, a collaboration model with trust, initiators, barriers, dimensions, and outcomes was designed. Then using the fuzzy DEMATEL method, the effect of each variable and its position were determined. To collect data targeted sampling and snowball methods were used. 20 questionnaires were distributed to supply chain and digital technologies experts. Findings show that Trust and Information and Communication Technology infrastructure are closely related and are considered the most fundamental factors of the collaboration conceptual model, and can lead to more serious and effective changes in SC 4.0 such as improved Economic and Social performance. SC 4.0 managers can facilitate the development of collaborative trust across the SC By investing in communication and technology infrastructure.
 

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Efficiency plays a pivotal role in impacting costs and optimizing resource utilization for
businesses. This study aims to evaluate the technical and scale efficiency of 15 suppliers within
a production unit over a three-year period (2020-2022) using data envelopment analysis
(DEA). The analysis will involve assessing efficiency under two assumptions - constant returns
to scale and variable returns to scale. Variables were selected based on indicator availability,
representation principles, and expert input, with inputs including investment, nonoperating
expense costs, and operational expenses (comprising raw material costs, wages, and
overheads), while outputs encompass net sales and return on investment. Results from the study
indicated that supplier one, scoring 0.5716 assuming constant returns to scale and 0.6790
under variable returns to scale, emerged as the least efficient supplier. Interestingly, only two
suppliers (8 and 15) demonstrated higher efficiency levels. However, the net technical efficiency
of the supply chain showed an increasing concentration, which indicates the overall reduction
of the gap between suppliers and the improvement of the net technical efficiency in the supply
chain of the production unit. This study provides valuable insights into the differences between
suppliers from a macro perspective and offers guidance for manufacturing units looking to
expand their supply chain.