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Volatility transmission is a crucial price phenomenon that influences upstream production and downstream consumption in agricultural commodity markets. However, existing studies offer little evidence on how product perishability is related to price volatility transmission along the agricultural market chain. This study investigates how price volatilities are transmitted across the farm, wholesale, and retail stages using high-frequency data from litchi and apple markets in China. We adopt various MGARCH models and volatility impulse response functions to evaluate the time evolution of price volatility correlation, and the direction and magnitude of price volatility transmission. Empirical results indicate that in the litchi market chain, the wholesale stage plays a dominant role in price volatility transmission, and the wholesale and retail stages have higher volatility spillover effects on the farm stage than vice versa. However, we find little evidence of price volatility transmission along the apple market chain. Our findings suggest that the degree of price volatility transmission is stronger for higher product perishability. [ABSTRACT FROM AUTHOR]

Recently, market globalization and competition have forced companies to find alternative means to boost sales and revenue. The use of the cash flow is increasingly becoming a viable alternative for managers to improve their company's profitability in a supply chain. In today's business transactions, a supplier usually asks a manufacturer to pay via the advance-cash-credit (ACC) payment scheme if the number of goods procured is high. Additionally, product perishability has been considered in an economic production quantity (EPQ) model since it is a real phenomenon. The present work develops an EPQ model for perishable products under the ACC payment scheme. The objective of the proposed model is to determine the optimal selling price and cycle time while maximizing profit under the ACC payment scheme using a discounted cash flow analysis. A nonlinear optimization algorithm is also proposed to solve the problem. In addition, some numerical examples are employed to illustrate the solution approach and show the concavity of the present value of the total annual profit in terms of both selling price and cycle time. The numerical results show that our proposal algorithm could be applied well to solve the problems. In addition, a sensitivity analysis is conducted to obtain some managerial insights. For example, if the impact of advance payment on procurement cost is relatively smaller than that of cash payment, then it is more profitable for the manufacturer to ask for a cash payment than to receive an advance payment and vice versa. [ABSTRACT FROM AUTHOR]

• Presenting a new model for the pharmaceutical supply chain (PCS) in crisis. • Developing a new objective in the PSC to maximize the social satisfaction. • Considering an online phase to update the plans in a case of any disruption. • Considering perishability and substitutability of drugs in the mathematical model. • Validating the mathematical model with a case study in Seattle, USA. Natural disasters refer to a set of harmful incidents, which do not originate in humans and threaten human lives around the world. These incidents are usually unpredictable. While most natural disasters appear to be beyond human control, the damage they cause can be controlled significantly. This is directly related to the human pre-emptive action, in particular designing and managing an efficient and constant scheduling in order to provide the required pharmaceutical materials. This paper addresses crisis management in pharmaceutical supply chains, whose three objective functions are to minimize the network total cost, minimize the unmet demand and maximize the satisfaction of social responsibility. In addition, it considers perishability and substitutability with demand uncertainty. Furthermore, two approaches, i.e. TH and Me, are used to handle the multi-objective model and uncertainty. Finally, a case study is presented to validate the mathematical model. Image, graphical abstract [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive content analysis-based literature review of studies on Inventory Routing Problem incorporating sustainability-related aspects. A total of 40 journal articles are selected from Web of Science and Google Scholar databases, and are reviewed by categorizing them into single-objective and multiple-objective models. The review suggests that studies with single-objective models covered areas including waste management (in reverse logistics models), returnable transport item management (in closed-loop supply chain models), waste prevention and reduction (in models with perishable products), and emission reduction (in models with emission caps and carbon price). Studies on reverse logistics are limited to collecting and storing waste at a collection site, while including waste processing and disposal operations could make them more applicable. Studies on closed-loop supply chains are few with a focus on managing returnable transportation items. Future studies could consider remanufacturing, recycling and disposal of products for efficient waste management. Most of the papers in logistics of perishable products considered waste prevention rather than waste reduction. Previous studies related to emission reduction using carbon policies mainly focused on emissions from transportation. Including emissions from other logistics operations could be useful from a practical perspective. Relatively few studies developed multi-objective models. Environmental objectives in multi-objective models focused on minimizing total emissions. Few studies considered social objectives related to minimizing inventory of hazardous material and infectious medical waste, and improving customer satisfaction. Other social aspects such as those related to traffic congestion and job creation could be considered in future studies. Furthermore, application of efficient models and solution approaches to real case studies could be valuable. [ABSTRACT FROM AUTHOR]

• It takes into account demand uncertainty for the deteriorating products. • It considers managing inventory of deteriorating products at the supplier level. • Two heuristic algorithms based on invasive weed optimization method are developed. • The solution techniques are validated and applied to data from a real-life case. Motivated by a real-life case in the dairy supply chain, we study the management of deteriorating inventories in an existing three-echelon supply chain network with a local retailer with multiple customers. Like many industries, the focal company categorizes the customers into two different clusters in the supply chain downstream with different, uncertain demand functions: (i) many, small, ordinary customers; (ii) few, large, premier customers. The focal company intends to determine the optimal inventory policy while the deterioration rate of the product is time sensitive. The problem is formulated using two concepts: 1) queuing theory and finite-horizon Semi-Markov process to characterize the structure of the optimal inventory policy; 2) integrated inventory system in the supply chain at the network level. We formulate the problem mathematically and show that the model is nonlinear and nonconvex. Therefore, the model cannot be solved by using commercial optimization software products to reach global optimal. Consequently, two solution approaches are designed to solve the problem: (i) a modified version of the Invasive Weed Optimization algorithm, named adaptive Invasive Weed Optimization, which is designed, tuned and validated (using well-known algorithms) to tackle the problem; (ii) an Adaptive Heuristic Method. We show that adaptive Invasive Weed Optimization is superior in the quality of solutions while Adaptive Heuristic Method is faster. Various sensitivity analyses applied to the real data show when facing both perishability and uncertainty, the effect of perishability outweighs the effect of uncertainty. [ABSTRACT FROM AUTHOR]