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The purpose of this paper is to investigate optimal decision methods under a cooperative situation in two-echelon logistic models.

The authors propose the optimal strategies of exporters in the three types of rival game behaviors: Stackelberg, Collusion, and Cournot, each of which provides the optimal decision for the duopolistic shippers and the oligopolistic forwarders in each scenario.

From the empirical studies the paper finds that among three scenarios, the oligopolistic treatment of forwarders’ actions demonstrates that Stackelberg behavior can carry out the maximum profit, and Collusion game can achieve the maximum profit for the shippers.

Proposed an optimal decision methods in two-echelon logistic models.

The huge demand for fresh goods has stimulated lots of research on the perishable food supply chain. The characteristics of perishable food and the cross-regional transportation have brought many challenges to the operation models of perishable food supply chain. The purpose of this paper is to address these challenges based on the real-time data acquired by the Internet of Things (IoT) devices.

IoT and the modeling of the Supply Hub in Industrial Parks were adopted in the perishable food supply chain.

A conceptual model was established for the IoT-enabled perishable food supply chain with two-echelon supply hubs. The performance of supply chain has improved when implementing the proposed model, as is demonstrated by a case study.

By our model, the supply hubs which act as the dominators of the supply chain can respond to the real-time information captured from the operation processes of an IoT-enabled supply chain, thus to provide public warehousing and logistic services.

This study investigates the pricing and inventory control decisions of a company that owns a coffeehouse chain providing drip coffee and a coffee manufacturing factory producing ready-to-drink (RTD) coffee. To determine a way to maximize profit, optimal pricing and inventory control strategies are studied for both the RTD coffee as well as the coffeehouse chain network.

It is assumed that the company sells only drip coffee through its coffeehouse chain and would like to launch RTD coffee via other channels such as convenience stores, supermarkets and so on to maximize its total profit. A mathematical model–based optimization is adopted to address the decision-making for the given problem situation, where the demand for both drip and RTD coffee are dependent on the values of decision variables. To solve the proposed mathematical model, particle swarm optimization (PSO) is applied due to nonlinearity of the developed model.

It is confirmed that a company can earn more profit by launching RTD coffee, even though the profit from drip coffee would reduce. In addition, the scenario analysis shows that by launching RTD coffee under various conditions, the total profits would also improve.

The value of this study is the proposed basic framework for the industry. In addition to the modeling framework and cost structure, realistic cost figures and technical details can be considered when applying the model to a practical setting.

While in some districts having drinking water is a given reality, there are others where there is a lack of access to this resource. Unfortunately, even today, 10.2% of the world population lives this situation and it could be worse in the coming years, according to UNICEF. Inhabitants in Pamplona Alta at southern Lima, Peru, daily suffer this harsh reality. This social challenge study attempts to define a methodology for an effective logistic planning of water distribution in Torres Minas. Currently, they obtain it from unsanitary and informal vendors. This chapter provides the basis of a new layout of the water distribution network based on clusters to efficiently satisfy water demand. Specifically, we propose the use of orderly delivery points called “bus-stops of water” in a two-echelon distribution system, whose optimization relies on a mixed-integer linear programming (MILP) technique. The objective of these guidelines is minimizing the transactional and transportation cost, while increasing the bargaining power of the community. Results showed a reduction of 52.67% and 26% in transactional and transportation costs, respectively, and a reduction of the associated risks of shortage and contamination of a tight delivery of water. Moreover, we foster the application of this methodology in other similar situations to produce sustainable growth for human settlements; regardless, there is a lack of access to water or a steep geography.

On one side, the purpose of this paper is to numerically analyze the emergency order allocation mechanism and help managers to understand the relationship between the emergency coefficient, uncertainty and emergency cost in two‐echelon logistics service supply chain. On the other side, the purpose of this paper is to help managers understand how to deal with the problem of order allocation in the two‐echelon logistics service supply chain better in the case of emergency.

The paper presents a multi‐objective planning model for emergency order allocation and then uses numerical methods with LINGO 8.0 software to identify the model's properties. The application of the order allocation model is then presented by means of a case study.

With the augment of uncertainty, the general cost of logistics service integrator (LSI) is increasing, while the total satisfaction of all functional logistics service providers (FLSPs) is decreasing, as well as the capacity reliability; at the same time the emergency cost coefficient is closely correlative with the satisfaction and general penalty intensity of FLSPs; finally, the larger the emergency cost coefficient is, the more satisfaction of FLSPs, but the capacity reliability goes up first and down later.

Management should note that it is not better when emergency cost coefficient is bigger. The general satisfaction degree of FLSP increases with the augment of emergency cost coefficient, but there is an upper limit of the value, i.e. it will not increase indefinitely with the augment of emergency cost coefficient. This paper also has some limitations. The optional emergency cost coefficient only adopted a group of data to analyze while the trend of the reliability of logistics capacity needs to be further discussed. In addition, the algorithm of emergency order allocation model in the case of multi‐objective remains to be solved.

Under emergency conditions, LSIs can adopt this kind of model to manage their FLSPs to obtain the higher logistics performance. But LSIs should be careful selecting emergency cost coefficient. In accordance with different degrees of emergency logistics demand, LSIs can determine reasonable emergency cost coefficient, but not the bigger, the better, on the premise that LSIs acquire maximum capacity guarantee degree and overall satisfaction degree of FLSPs. FLSPs can make contract bargaining of reasonable emergency coefficient with LSIs to make both sides get the best returns and realize the benefit balance.

Many studies have emphasized the capacity allocation of manufactures, order allocation of manufacturing supply chain and scheduling model of emergency resources without monographic study of supply chain order allocation of logistics service. Because the satisfaction degree of FLSPs the cost of integrators needs to be considered in the process of order allocation, and the inventory cost of capacity does not exist, it is different from the issue of capacity allocation planning of manufacture supply chain. Meanwhile, the match of different kinds of logistics service capacity must be considered for the reason of the integrated feature of logistics service. Additionally, cost is not the most important decision objective because of the characteristics of demand uncertainty and weak economy. Accordingly, this paper considers these issues.

The purpose of this paper is to determine the effects of corporate social responsibility (CSR) on financial performance in firms in the Korean manufacturing industry. In addition, the authors examine the moderating role of differentiation and outside investment in the same relationship.

The mixed methods are used in this study. The authors first take an analytical modeling approach, in which the authors assume that CSR has a positive effect on consumer perceptions, which in turn can improve firm performance. Subsequently, the authors verify the propositions with data from the Korean manufacturing industry. Additionally, the authors explore the moderating roles of various factors in the CSR-financial performance relationship.

The results of the analysis demonstrate that the positive relationship between CSR and financial performance depends on the levels of product differentiation and outside investment. Specifically, these contingent variables magnify the effects of CSR on financial performance.

This study is particularly useful to supply chain managers. According to the results, CSR may provide benefits for both manufacturers and retailers. As brand reputations can be source for competitive advantage, the analytical model suggests that products made by socially responsible firms are attractive to consumers.

To the authors’ knowledge, there are few studies that examine the multiple moderating effects of differentiation and outside investment on the relationship between CSR and financial performance (return on assets). The authors thus provide a clearer understanding of the effects of CSR activity on firm profitability using these business strategies.

This study focuses on a specific method of meat production that involves carcass purchase and meat production by packing facilities with a novel two-stage model that simultaneously considers location-routing and inventory-production operating decisions. The considered problem aims to reduce variable and fixed transportation and production costs, inventory holding cost and the cost of opening cold storage facilities.

The proposed model encompasses a two-stage model consisting of a single-echelon and a three-echelon many-to-many network with deterministic demand. The proposed model is a mixed-integer linear programming (MILP) model which was tested with the general algebraic modelling system (GAMS) software for a real-world case study in Iran. A sensitivity analysis was performed to examine the effect of retailers' holding capacity and supply capacity at carcass suppliers.

In this research, the number of products transferred at each level, the number of products held, the quantity of red meat produced, the required cold storage facilities and the required vehicles were optimally specified. The outcomes indicated a two percent (2%) decrease in cost per kg of red meat. Eventually, the outcomes of the first and second sensitivity analysis indicated that reduced retailers' holding capacity and supply capacity at carcass suppliers leads to higher total costs.

This research proposes a novel multi-period location-inventory-routing problem for the red meat supply chain in an emerging economy with a heterogeneous vehicle fleet and logistics decisions. The proposed model is presented in two stages and four-echelon including carcass suppliers, packing facilities, cold storage facilities and retailers.

Blockchain-driven supply chain finance (BCT-SCF) has recently been receiving increased global attention. A number of business programmes have been carried out using this approach, but existing research has rarely focussed on this novel SCF model. This paper aims to fill this gap by proposing a mathematical model to analyse the value of BCT-SCF.

First, this paper considers a multi-period two-echelon supply chain consisting of a capital-constrained supplier and a newsvendor-like retailer. Then, two financing channels are proposed. The supply chain actors can either factor accounts receivable (AR) from a bank or obtain financing through a BCT-SCF platform by which AR can be converted into a bill receivable and used to make payment. Further, to investigate the preferences of all actors between the two financing channels, this paper compares the two channels and examines how the degree of financial constraints and the cost of implementing the BCT-SCF model impact the financing preferences of all actors.

BCT-SCF model can help a supply chain realise its optimisation both in production and financing efficiency, the preference for the BCT-SCF model increases as the initial capital of supplier and the BCT-SCF platform usage fee rate decrease.

This research bridges the gap between theoretical analysis of BCT-SCF and its realistic application. The results demonstrate that with the BCT-SCF model, a win-win situation among supply chain actors is possible, which is helpful for the supply chain to choose a more efficient financing channel.

This research introduces a mathematical model based on the “receivable chain” of CZBank and the model is set in a multi-period supply chain, which is the first time BCT-SCF has been considered as part of a more complex but realistic background setting.