Multiperiod supply chain network dynamics under investment in sustainability, externality cost, and consumers’ willingness to pay
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Externality
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Supply chain network
Investment Decisions
Assessment of the Disparity between Willingness to Accept(WTA) and Willingness to Pay (WTP) by Value
This paper offers systematical reviews of the 30 years' studies on the disparity between willingness to pay (WTP) and willingness to accept (WTA). The paper presents a new explanation of the disparity between willingness to pay (WTP) and willingness to accept (WTA), based on previous research, especially on the experiments on the gap of WTP and WTA and through the analysis of value and existence value. The explanation means that willingness to accept (WTA) subtract willingness to pay (WTP) equals existence value that cannot be transacted, or larger. The paper highlights a better solution to the disparity between willingness to pay (WTP) and willingness to accept (WTA), features the equation of calculating the existence value of every unit article, and introduces the use of this equation to explain the generation, change and disappearance of the existence value.
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The aerospace supply chain network has evolved and become more complex over the years. New methods are needed to design and analyze the system, and to establish the interactions between aircraft (product) design and supply chain (process) design. This paper aims to introduce a strategic multi-product, multi-period design model for the manufacturing of an aircraft wing-box with a planning horizon of the full program duration. The supply chain systems consist of a number of external suppliers, candidate manufacturing sites, and a number of customers at fixed locations. The design model is a mixed-integer linear programming optimization routine that minimizes the total time-discounted network cost. The model generates a system configuration that specifies the location and capacity of the manufacturing sites, the material flow, and the transportation routes within the network. The model is implemented using open-source tools, and has a comprehensive and flexible data structure to support the decision-making process during the early aircraft design stages.
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this study aims to measure the willingness to pay of the visitors for any objects in the tourism place in Tirtamaya Beach and to perceive factors which affect the willingness to pay. This study uses primary data with number of respondents 270 as random sampling. Willingness to Pay can be estimated by using the Contingent Valuation Method (CVM) approach. Based on the analysis, the average value of willingness to pay per person is IDR 10,000 which is obtained by dichotomous choice. Factors that significantly influence the amount of Willingness to Pay for responses of the visitor are income and recreation budget that have a positive and significantly influence. Age and distance, has negative and significantly influence. While the level of education, visitor satisfaction and visiting hours insignificantly have no significant influence on Willingness to Pay.
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We propose a mixed integer nonlinear programming model for the design of a one‐period planning horizon supply chain with integrated and flexible decisions on location of plants and of warehouses, on levels of production and of inventory, and on transportation models, considering stochastic demand and the ABC classification for finished goods, which is an NP‐hard industrial engineering optimization problem. Furthermore, computational implementation of the proposed model is presented through the direct application of the outer approximation algorithm on some randomly generated supply chain data.
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This paper extends a traditional supply chain network design problem through two perspectives, i.e., the multiperiod decision environment and the environmental concerns. A planning horizon contains multiple periods. Different periods have different demands of products and hence should have different supply chain decisions, which mainly include facilities' locations, the environment protection level in facilities, as well as the transportation flows of products in the supply chain. For each facility in two consecutive periods, the changes of the location and environment protection level related decisions may incur adjustment cost. A bi-objective mixed-integer programming model is proposed to minimize both the total cost and the CO2 emissions of the supply chain during the planning horizon with multiple periods. A solution approach is proposed to solve the model. Numerical experiments are conducted to validate the effectiveness of the proposed model and algorithm.
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The resilient supply chain considers many capabilities for companies to overcome financial crises and to supply and distribute products. In this study, we address the allocation of inventory distribution for a distribution network, including a factory, a number of potential locations for distribution centers and a number of retailers. Customers demand is assumed to be certain and deterministic for all periods but time varying in the limited planning horizon. The proposed model in this research is a linear complex integer programming model with two-objective functions. The first objective function minimizes the total costs of the entire distribution system in the planning horizon, and the second objective function seeks to minimize the difference between the maximum and minimum distances traveled by vehicles over the planning horizon. Therefore, the model tries to satisfy the demand and at the same time reduce costs using the best route transportation option configuration and transportation option. The routing problem is developed, and as the problem is a NP-hard problem, a meta-heuristic method is used to solve it. In this model, the demand volume for each customer in a period of the network, vehicle capacity, factory capacity, constant transportation cost, variable transportation cost, etc., are considered as factors affecting the model. The results show that the model proposed in the network can be used as a lever to improve the performance of the financial economic supply network through saving in routes.
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This study aims to determine the tariff of Jakarta LRT based on the analysis of ability to pay and willingness to pay for taxi users. The ability to pay value analysis approach uses travel cost method and determination of willingness to pay value using discrete choice analysis. From the analysis results can be seen that the value of the ability to pay is Rp. 63.316 and the willingness to pay value is Rp. 11.500. This indicates that the willingness to pay taxi users is less than the ability to pay.
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A strategic model for exact supply chain network design and its application to a global manufacturer
This paper presents a comprehensive model that captures significant strategic decisions involved in designing or redesigning high-performance supply chains from the perspective of the manufacturer. The problem considers deterministic demand by multiple clients, for multiple products, over the periods of a long-term horizon. The design decisions involve selection of suppliers, establishment or resizing of production facilities and distribution centres, possible subcontracting of related activities, and selection of transportation modes and routes. The problem is formulated by a Mixed Integer Linear Programming model. Its objective is to minimise the overall costs associated with procurement, production, inventory, warehousing, and transportation over the design horizon. Appropriate constraints model the complex relationships among the links of the supply chain. The proposed model has been applied to a large case study of a global manufacturing firm, providing valuable insights into the transformation of the firm's current supply chain network, as well as into the potential of the proposed approach.
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