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Purpose: The objective of this paper is to investigate the impact of the information sharing of the dynamic demand on green technology innovation and profits in supply chain from a long-term perspective. Design/methodology/approach: The authors consider a supply chain consisting of a manufacturer and a retailer. The retailer has access to the information of dynamic demand of the green product, whereas the manufacturer invests in green technology innovation. Differential game theory is adopted to establish three models under three different scenarios, namely (1) decentralized decision without information sharing of dynamic demand (Model N-D), (2) decentralized decision with information sharing of dynamic demand (Model S-D) and (3) centralized decision with information sharing of dynamic demand (Model S-C). Findings: The optimal equilibrium results show that information sharing of dynamic demand can improve the green technology innovation level and increase the green technology stocks only in centralized supply chain. In the long term, the information sharing of dynamic demand can make the retailer more profitable. If the influence of green technology innovation on green technology stocks is great enough or the cost coefficient of green technology innovation is small enough, the manufacturer and decentralized supply chain can benefit from information sharing. In centralized supply chain, the value of demand information sharing is greater than that of decentralized supply chain. Originality/value: The authors used game theory to investigate demand information sharing and the green technology innovation in a supply chain. Specially, the demand information is dynamic, which is a variable that changes over time. Moreover, our research is based on a long-term perspective. Thus, differential game is adopted in this paper. [ABSTRACT FROM AUTHOR]

Although previous research ignores other subsidy groups, we conduct a comprehensive study. In our closed-loop supply chain model, the manufacturer can produce either new products or remanufactured products of end-of-life products recycled by independent recyclers. Our core objective is to explore the production and recycling strategies of the two products under different government subsidy plans and which groups the government subsidy plans should target. Considering the consumers’ discount perception and uncertainty of recycling quantity, we construct four game scenarios: (1) no subsidy (Scenario N); (2) subsidy for the manufacturer (Scenario M); (3) subsidy for the recycler (Scenario R); (4) subsidy for consumers (Scenario C). The results show that the corporate profits and social welfare under scenario Care higher than those under other scenarios. If the government adopts scenario C, enterprise profits and social welfare will always be higher, but the downside is that government expenditure will also be higher. If considering the limited government funds, the government can set a medium subsidy level. Scenario Mwill bring sub-optimal social welfare to the government. For scenario R, government subsidies stimulate the recycling of end-of-life products and help recyclers increase their profits, but from the manufacturer’s perspective, manufacturers may resist this scenario.

Purpose: This paper aims to explore how upstream supply chain companies will control the carbon emissions and price decisions of products when the government implements environmental tax policy on consumers. It provides some suggestions to control carbon emissions for the government and manufacturers. Design/methodology/approach: This study establishes two-echelon Stackelberg game models with and without the implementation of environmental tax policy on consumers in a centralized scenario and a decentralized scenario. Through the comparative analysis of the four models, the optimal emission abatement and pricing strategies are obtained. Findings: This paper concludes that implementing environmental tax policy on consumers within the market's acceptable range is more beneficial to the retailer and the environment, as well as the overall social welfare, except for the manufacturer. Moreover, consumer's low-carbon preference always has a broader impact on carbon abatement and corporate profits than environmental tax coefficient. Finally, the side-payment self-executing contract can effectively ensure that the supply chain members make rational decisions spontaneously while achieving a win-win solution of centralized scenario. Originality/value: This paper first considers how the government's environmental tax policy on consumers will affect the decision-making of supply chain companies, and proposes an improved side-payment self-enforcing contract to maximize environmental and economic benefits of centralized scenario. In addition, it provides a reference for the government to adopt both the carbon cap policy and the environmental tax policy. [ABSTRACT FROM AUTHOR]

We evaluate the respective roles, functions and prospectsof the 15 Chinese ports, intended to be the 'eastern end' of China's Belt and Road Initiative (BRI). To achieve this, and thus contribute to the future development of BRI, we introduce the concept of sustainable development capability. We employ principal component analysis and analytic hierarchy process to build a model which evaluates the (cooperative) sustainability of the ports, based on four dimensions: capacity of port operations; (ambient) economic conditions; environmental factors; and human intellect and technology (HIT). Sensitivity and cluster analysis are used, to classify the ports into four categories (respective roles): international hub ports, regional hub ports, node ports, and regional gate ports. We hope that the port system we present and assess here will provide guidance to ports and countries, especially in Europe, leading to the right 'port alliances', that could turn BRI into an efficient global transportation system.

Purpose: This paper aims to analyze the impact of the cost coefficient of product emission reduction, coefficient of low-carbon product advertising effort cost, and sharing ratio of low-carbon product advertising effort cost on the profit of a dual-channel supply chain. After determining the best model and relevant influencing factors, the paper puts forward corresponding management inspirations and suggestions. Design/methodology/approach: The paper opts for an exploratory study using Stackelberg game theory to construct a centralized decision-making (MC mode), a low carbon product advertising effort cost free sharing decentralized decision-making (SD model) and a low carbon product advertising effort cost sharing decentralized decision-making (JD model) game model. Through using optimization methods to get the equilibrium solution, the relevant management suggestions are obtained by comparison analysis. Findings: The paper shows that the JD model is better than the SD model in terms of the profits of the manufacturer, retailer and supply chain, and the improvement of Pareto is realized. The proportion of cost sharing of low carbon product advertising effort is positively related to the wholesale price and direct influence coefficient of low carbon product advertising effort on channel, while negatively related to the retail price and the cross influence coefficient of low carbon product advertising effort on alternative channels. Under the JD model, the manufacturer can reduce advertising costs through improving the efficiency and pertinence of direct channel advertising and urging the retailer to do a better job in sales management to improve gross margin and require the retailer to increase advertising efficiency and pertinence of retail channel to reduce advertising costs of retail channel and other ways to increase their profits. The retailer can make use of its advantages closer with consumers to improve the efficiency and pertinence of advertising in the retail channel to raise the influence coefficient of advertising and reduce the advertising cost in the retail channel. Originality/value: The innovations of this paper are listed as follows: First, it has considered advertising investment from both the manufacturer and the retailer simultaneously. Second, it has considered a low-carbon background to investigate cooperative advertising decision for low-carbon products. Third, it has considered the decision on the level of product emission reduction and the level of low-carbon product advertising effort investment simultaneously. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to develop a bi-objective mixed integer non-linear programing model to optimize the supply chain networks consisting of raw material providers, final product manufacturers and distribution centers. Raw material substitution caused by varying raw material supply amounts, prices and carbon emissions and final product substitution due to different product prices and carbon emissions are considered.Design/methodology/approach The proposed model aims to achieve total profit maximization and total carbon emission minimization. The objective function of carbon emissions is converted into a maximization problem by changing minimum to maximum. The composite objective function is the weighted sum of the bias value of each objective function. The model is then solved using software Lingo12.Findings Numerical analysis results show that an increase in the number of alternate raw materials for original raw material helps improve supply chain network performance, and variation in that number causes detectable but not significant changes in downstream final product substitution results.Originality/value The major differences between this work and existing research are as follows: first, although previous research considered carbon emissions in supply chain network optimization, it has not considered the substitution effects of products or raw materials. This paper considers the substitution of both raw material and productions. Second, the item substitution considered by previous research is derived from inventory shortage or price difference of original items. However, the substitution considered in the present paper is a response to differences in purchase price, production cost and carbon emissions for items. [ABSTRACT FROM AUTHOR]

Abstract:With the development of the Chinese economy, many port cities aim to establish shipping centers. Due to the status of international routes, the scope of the hinterland, the economic development level, the conditions of individual cities, and other factors, different international shipping centers adopt different development strategies. To identify the advantages and disadvantages of individual shipping centers and reasonably determine their relative competitiveness, it is important to establish a competitiveness evaluation index system suitable for evaluating the characteristics of shipping centers. Hierarchical analysis, principal component analysis, and cluster analysis are applied to classify the Chinese shipping centers of main port cities such as Shanghai, Nanjing, Tianjin, Wuhan, Guangzhou, Dalian, Chongqing, and Qingdao. Our method ranks the cities according to both their soft and hard environments to analyze the main influencing factors, as well as establish a corresponding shipping center competitiveness evaluation index system.

Hyperuricemic nephropathy is a highly prevalent kidney disease induced by excessive accumulation and deposition of monosodium urate in kidney, which contributes to the loss of kidney function. The Jiangniaosuan formulation (JNSF) is a Chinese herbal medicine treatment. The aim of this study is to evaluate its efficacy and safety among patients with hyperuricemic nephropathy at chronic kidney disease (CKD) stages 3–4 and with obstruction of phlegm turbidity and blood stasis syndrome.

A transportation network plays a crucial role in delivering emergency goods to people affected by natural and manmade disasters. The purpose of emergency goods transportation is to rapidly provide the appropriate emergency supplies to the disaster-struck areas. This requires a systemic coordination to prioritize the allocation of goods to desired locations. The concept of queuing is well documented in social service literature and transportation engineering literature. However, the queuing concept is limited for analyzing multi-echelon emergency transportation systems which are much more complex than other traffic networks. This paper develops a multi-echelon queuing network model of an emergency goods transportation intended to accelerate goods transportation and to reduce the waste time. The methodology captures differences in humanitarian relief demands, arrival patterns, volumes, and efficiencies of processes in logistics systems of disaster-struck areas. The relief goods stored in multi-echelon locations in a metropolitan area are delivered with an optimization method of the queuing equations by using sojourn time, waiting time, queue length, and overflow probability as quality of service. The multi-echelon queuing model is to minimize both response time in the emergency and transportation time on the road network, and a genetic algorithm is developed to solve the model. Then this method is applied to the comprehensive emergency goods transportation network in the Shanghai metropolitan region. The proposed analysis can be used as tools for improving coordination performance of an emergency goods transportation network.