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The purpose of this paper is to investigate the manufacturer’s production, pricing and green technology investment decision problem when strategic customer behavior and carbon emissions-sensitive random demand is taken into consideration and discuss the impact of carbon emissions-sensitive demand on the manufacturer’s operation strategies, total carbon emissions and maximum expected profit.

The authors formulate a model to introduce carbon emissions-sensitive demand into the newsvendor framework with strategic customer behavior. The authors characterize the rational expectations equilibrium to derive the optimal solutions to the manufacturer. The authors analyze the effects of carbon emissions-sensitive demand on the manufacturer’s optimal strategies, total carbon emissions and maximum expected profit by comparative analysis.

The authors obtain the manufacturer’s optimal production, pricing and green technology investment strategies under rational expectations equilibrium in scenario of price-sensitive demand and that of carbon emissions-sensitive demand, respectively. The authors find that as customer demand changes from price-sensitive demand to carbon emissions-sensitive demand, the manufacturer’s optimal prices are the same but optimal production quantity, optimal unit carbon emissions and maximum expected profit go down. Though the total emissions decrease, the carbon emissions reduction would not increase as the demand is more carbon emissions-sensitive. Whether it increases or decreases depends on the model parameters.

Carbon emissions-sensitive demand and strategic customer behavior are considered simultaneously in an integrated model. The result can guide the manufacturer decision-making. The proposed model are hoped to shed light to the future works in the field of sustainable supply chain management.

This paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.

The methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.

In this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.

The study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

This paper aims to examine the optimal sourcing strategies and pricing decisions of competing toy manufacturers and to discuss how manufacturers’ decisions are impacted by competition.

The authors consider a single-period model to characterise the competition between two competing toy manufacturers. Both of them are free to choose between virgin material and recycled material. The authors consider two types of consumers: sensitive consumers who are concerned about product safety and prefer the toy made of virgin material and insensitive consumers who do not care what material is used in the toy. The competing manufacturers play a Cournot competition.

The results reveal a special case of a win-win situation for both the manufacturer and the consumer. In addition, an increasing number of sensitive consumers does not always raise the price of virgin-material toys.

The authors derive the manufacturer’s equilibrium sourcing strategies, corresponding market-clearing prices and profits obtained.

The paper investigates how toy manufacturers’ optimal sourcing strategies are impacted by competition, considering market segments.

This research work introduces an imperfect production system where the demand is assumed to be stochastic and it is influenced by random selling price. The shift time from an “in-control” state to an “out-of-control” state is exponentially distributed. The accumulated inventory contains both perfect and defective items which are all sold with a free repair warranty (FRW) offer. Complete back ordering of shortages are taken into account. The purpose of this paper is to determine the optimal selling price and hence the optimal production lot size such that the expected profit is maximized.

The general model is discussed separately for both types of uniformly distributed selling price-sensitive demand pattern: additive type and multiplicative type. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the models.

This paper helps the manager to manage future situations and it may be considered as a base work for the researchers to work in this direction.

The main limitation of this model is to consider a single item for a single channel system. There are many correlated issues that need to be further investigated. The future study in this direction may include the consideration of multi-items, diverse demand pattern with different types of price distributions.

In the production inventory literature, plenty of articles are available considering imperfect production but none of them have considered selling price-sensitive stochastic demand where the sales price is random in character under an FRW offer.

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.

The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.

The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.

The vessel carrying capacity is not considered in an explicit way.

This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.

The purpose of this paper is to present a mathematical model that illustrates the trade‐offs between sustainability, demand, costs, and profit in a supply chain with a single supplier and a single manufacturer.

It is assumed that a single product is produced and sold on a market where demand is sensitive to price and quality. Sustainability is treated as a quality attribute and is measured in terms of the levels of scrap and emissions generated in the supply chain. It is assumed that the emissions and scrap can be controlled by varying production rates or by investing in production processes. The impact of cooperative and non‐cooperative behaviour between the supplier and the manufacturer is explored. Numerical studies are used to illustrate the behaviour of the model.

The analysis shows that the supplier and the manufacturer can attract additional customers by controlling scrap and emissions. The behaviour of the supplier and the manufacturer are dictated by the decision criteria, such as changes in the level of sustainability, used by customers to evaluate the product. It is shown that the profit of the system is higher and that the level of quality is lower in the case of cooperation than in the case of non‐cooperation.

Several areas for future work are highlighted. The study of alternative demand functions, linking sustainability to a monetary component, including additional players, and incorporating additional sustainability indicators all offer possibilities for extending the model.

There is an identified need for analytical models that consider sustainability in the supply chain. The results are especially important for companies operating in markets where customers perceive the sustainability of a product as a quality criterion.

The purpose of this study is to investigate the impact of greening and promotional effort dependent stochastic market demand on the remanufacturer's and the collector's profits when the quality of used products for remanufacturing is uncertain in a reverse supply chain.

The proposed model is developed to obtain optimal profits for the remanufacturer, the collector and the whole supply chain. Both the centralized and decentralized scenarios are considered. To motivate the collector through profit enhancement, the remanufacturer designs a cost-sharing contract. Through numerical examples and sensitivity analysis, the consequences of greenness and promotional effort on optimal profits are investigated.

The results show that the remanufacturer gets benefited from greening and promotional effort enhancement. However, a higher value of minimum acceptable quality level decreases the profits of the manufacturer and the collector. A cost-sharing contract coordinates the supply chain and improves the remanufacturer's and the collector's profits. Besides green innovation, remanufacturing mitigates the harmful effects of waste in the environment.

Two different viewpoints of remanufacturing are considered here – environmental sustainability and economic sustainability. This paper considers a reverse supply chain with a remanufacturer who remanufactures the used products collected by the collector. The quality of used products is uncertain, and customer demand is stochastic, green and promotional effort sensitive. These two types of uncertainty with green and promotional effort sensitive customer demand differs the current paper from the existing literature.

The purpose of this paper is to focus on determining the optimal sales price for non-instantaneous deterioration items according to consideration of freshness and demand.

In this model, the authors have described the demand function which is dependent on price as well time. The products that the deterioration is considered as non-instantaneous have a determinate shelf life, and their demand rate will decrease over time after the beginning of the selling period. This paper depicts that the total profit of non-instantaneous deterioration items using the dynamic pricing strategy is higher than that using fixed pricing strategy.

Finally, to illustrate and validate the model, the authors have used some numerical examples. A new freshness function and the model to study pricing policy are developed as well applied to solve managerial decision problems.

This paper complements the lack of the existing theoretical research of pricing for non-instantaneous deterioration items under an e-commerce environment. A new freshness function and the model to study pricing policy are developed as well applied to solve managerial decision problems.

To study these issues, the authors chose a GFSC with one producer and one material supplier as research object, the supplier will offer green material to the producer and the producer will make green food using green production technology. Then, the authors proposed that consumers' perceived value was determined by the trustworthiness levels of the related green and quality-safety information provided by the supplier and the producer. Then, considering the trustworthiness levels of the green and quality information provided by the supplier and the producer, the authors improved the demand function. Afterwards, we constructed four investment models and their income models are built and then a cost-sharing and revenue-sharing contract (hereafter, CSRS) was adopted to coordinate the GFSC.

With the growth of consumers environmental awareness and life level, consumers' requirements for green and high quality food are growing. In recently years, to increase consumers' perceived trustworthiness on the product greenness and quality levels, stakeholders in green food supply chain (hereafter, GFSC) start to adopt the blockchain-based traceability system (hereafter, BLTS). For investors, they need to know the investment conditions and how to coordinate the GFSC.

(1) When the revenue-sharing coefficient is less than three-fourths and higher then a certain vaule, the cost-sharing and revenue-sharing contract can make the GFSC coordinate. (2) The investment cost threshold of the BLTS has a positive relationship with the trustworthiness improvement levels of the green and quality information, the green degree of food products and the quality of food products. (3) In the proposed four investment situations, as the growth of consumers perceived credibility coefficient about the greenness information and the quality information, chain members' revenues will increase. In addition, comparing with co-investing the BLTS, benefits of chain members are lower than them in the sole investment model.

(1) The demand function we proposed can help chain members forecast market demand to support production or ordering decisions. (2) The investment decision policies can offer a theoretical reference for chain members to use the BLTS. (3) The CSRS will offer the theoretical reference for coordinating the supply chain after using the BLTS. Furthermore, our study method can be referenced by other scholars. (4) The study method can offer a method reference for researchers who do a similar discussion in a manufacturing supply chain. Although, our research cannot guide the industrial practices, it can serve as a reference of the similar research in industry.

This study examines the potential of contracts as one of the supply chain coordination mechanisms under competitive conditions. It also investigates a two-echelon supply chain model with two manufacturers and two retailers to develop a competitive structure in grey stochastic demand.

Supply chain demand is considered as a stochastic phenomenon depending on the selling price of the product. Also, products can be replaced by market manufacturers. Each retailer faces the pricing of products from two manufacturers, leading to competition between downstream retailers. In the present study, the duopoly supply chain model was presented based on the wholesale price contract, revenue-sharing contract and quantity discount contract separately.

Grey optimization and analysis of their coordination were presented. The results showed the high performance of revenue-sharing contracts in the supply chain. Thus, manufacturers will give the next priority to quantity discount contracts.

Ordering is the main factor contributing to competitive decision-making. Meanwhile, decision-making along with ordering and pricing will be required due to the nature of the demand.