With the increasing complexity of the distribution environment, customers usually propose higher requirements, such as independent loading of local and foreign cold-chain items in the event of an emergency. Moreover, minimum fuel volume plays an important role in the process of transportation with different speeds and different kinds of vehicles. In this paper, we present a new mathematical model to characterize cold-chain vehicle routing optimization with independent loading of local and foreign items and minimum fuel volume. To address the above mathematical model, an extended particle swarm optimization (PSO) algorithm is proposed by combining original PSO with 2-opt optimization to improve diversity and reduce convergence speed. Six sets of experiments are set to verify the practical performance and stability of the extended PSO algorithm based on three standard datasets of C201, R201, and RC201 from Solomon.

In this work, the coupled nonlinear Schrödinger equation with higher-order effects is studied with the aid of Darboux transformation and an asymptotic analysis. We report mixed localized waves, rogue wave coexisting with breathers in the system. Under certain constraints, the structures and evolutionary processes of solutions have been influenced. For example, The phase, amplitude, and propagating direction of mixed localized waves change when rogue wave collides with breathers. Moreover, the localized waves characteristics together with collision dynamic behaviors of these explicit rogue wave and breathers are exhibited graphically and discussed in detail. These novel results may be meaningful to study integrable systems better.

The application of blockchain technology solves the trust problem between core enterprises (CEs), small and medium-sized enterprises (SMEs), and commercial banks, facilitating CEs and commercial banks to provide guarantee for SMEs and finance them, respectively. This study considers a three-level supply chain composed of a manufacturer, a distributor, and a capital-constrained retailer, and explores the operational strategies of blockchain platform finance (BPF), a supply chain finance mode enabled by blockchain technology. First, optimal decision solutions are obtained through decision and parameter sensitivity analyses. Second, by comparing the BPF and SME independent finance (SIF) modes, we obtain the applicable BPF mode conditions; for instance, when the retailer’s initial capital is low and the production cost is high, BPF is the better option for the manufacturer, distributor, and retailer compared to SIF. Third, we find that risk sharing improves the financing efficiency of the BPF mode. This study provides a theoretical basis for decision makers to implement blockchain supply chain finance at three levels: joint financing and operation decision-making, financing mode selection, and financing efficiency improvement.

Great expectations are placed in carbon capture, utilization, and storage (CCUS) technology to achieve the goal of carbon neutrality. Governments adopt carbon tax policies to discourage manufacturing that is not eco-friendly, and subsidies to encourage low-carbon production methods. This research investigates which carbon reduction incentive policy is more viable for the supply chain under CCUS application. The most significant finding is that carbon tax and low-carbon subsidy policies are applicable to high-pollution and low-pollution supply chains with the goal of maximizing social welfare. Both policies play a significant role in reducing carbon emissions. However, it is very important for the government to set reasonable policy parameters. Specifically, carbon tax and low-carbon subsidy values should be set in the intermediate level rather than being too large or too small to achieve higher social welfare. We also find that the higher the value of carbon dioxide (CO2) in CCUS projects, the higher the economic performance and social welfare, but the lower the environmental efficiency. Governments should properly regulate the value of CO2 after weighing economic performance, environmental efficiency and social welfare. The findings yield useful insights into the industry-wise design of carbon emission reduction policies for CCUS and similar projects.

Online sales and green investment are two important ways to improve the sustainability of the tourism supply chain under the pandemic. This research constructs an omni-channel tourism supply chain consists of two tourism service providers (i.e., TSPs) and one online travel agent (i.e., OTA). Tourism products are sold to consumers through three online sales channels, including two free channels and one bundled channel. The bundled channel is operated by the OTA, and the free channels can be operated by the TSPs or the OTA. Depending on the free channels operators, we depict four online selling models, i.e., the model where two free channels are operated by the two TSPs (TT model), the models where only one free channel is operated by one TSP (TO and OT models), and the model where two free channels are operated by the OTA (i.e., OO model). Through comparing the four models, we find that if the TSPs are responsible for green investment, model TT is the most profitable and greenest model compared to the other three models when the positive externality of greenness is high. Otherwise if the OTA is responsible for green investment, the profit and greening level of the tourism supply chain in model TT become the lowest. This study provides managerial insights for tourism practitioners to rationally operate tourism supply chain from three aspects: joint decisions of operations and greenness, channel structure design, and greening level improvement.

We employ the joint production decomposition model to conduct a full decomposition of CO2 emission among 36 industrial sectors in China from 1998 to 2011, under the framework of growth accounting. The results show that: (1) the average CO2 emission increases at an annual rate of 3.01%, and production technology progression is the main driving force, while the transformation toward clean production effectively curb the rapid growth of CO2 emissions; (2) the effect of technology changes on CO2 emission is larger during the "10th Five-Year Plan" compared with the "11th Five-Year Plan", which makes the annual growth rate of CO2 emission during the "11th Five-Year Plan" 1% lower than its counterpart; This study has important theoretical and practical significance for understanding the driving factors of CO2 emission and the corresponding emission reduction measures.

Let G be a connected, undirected and simple graph. The distance Laplacian matrix L(G) is defined as L(G)=diag(Tr)−D(G), where D(G) denotes the distance matrix of G and diag(Tr) denotes a diagonal matrix of the vertex transmissions. Denote by ρL(G) the distance Laplacian spectral radius of G. In this paper, we determine a lower bound of the distance Laplacian spectral radius of the n-vertex bipartite graphs with diameter 4. We characterize the extremal graphs attaining this lower bound.

Y An increasing number of manufacturers are introducing voluntary carbon emission reduction (VCER) mechanisms, such as clean development mechanisms (CDMs), to reduce environmental pollution and fulfill their social responsibility goals. In this paper, we build and compare two types of competitive supply chain models, specifically, a model with a monopoly manufacturer and two competing retailers (OT model) and a model with two competing manufacturers and two competing retailers (TT model), and we then explore the impacts of supply chain competition on manufacturers' CDM introduction strategies. The results show that in the OT model, it is optimal for the manufacturer to introduce a CDM. However, in the TT model, the manufacturers' optimal decisions on introducing CDMs are dependent on the trading price of the certified emission reductions (CERs). In particular, manufacturers should introduce CDMs if the CER trading price is low. Otherwise, they should not introduce CDMs. In addition, we study the impacts of the degree of retailer competition on the CDM introduction strategies of manufacturers and the impacts of the CER trading price on all partners' operational decisions, profits, and environmental performance. Finally, we provide managerial insights for manufacturers to reasonably operate CDMs with supply chain competition considerations.

区块链技术正引发供应链金融变革,而信用传递功能在供应链金融中应用最为广泛.考虑由资金充足的生产商、资金约束的分销商和资金约束的零售商共同组成的三级供应链,分销商和零售商的资金困境解决方式包括传统的贸易信用和供应链金融组合融资形式,以及信用传递功能驱动下的区块链供应链金融模式.首先,本文运用Stackelberg博弈方法分别刻画传统供应链金融模式和区块链供应链金融模式;其次,运用逆向归纳法对博弈模型进行优化和求解分析,得到均衡状态下两种融资模式供应链最优批发价、分销价和订货量决策;随后,对零售商初始资金量、企业资金时间价值率等关键参数进行了敏感度分析,对传统供应链金融模式和区块链供应链金融模式进行了比较分析.研究表明:随着零售商初始资金量的降低,生产商期望收益增加,分销商和零售商期望收益下降;相比传统供应链金融模式,区块链供应链金融模式能够为供应链创造价值,且当企业资金时间价值率较高时,区块链供应链金融为供应链创造更大价值,且实现生产商、分销商、零售商三方共赢.本研究论证了区块链技术驱动下的供应链金融模式在运营上的优势,同时为区块链供应链金融的发展提供了决策支持和管理启示.

当商业银行联同核心企业推出供应链金融业务时,部分中小企业在资本市场中仍会选择以贸易信用、互联网金融等其他形式开展融资.对于商业银行而言,合理应对来自资本市场的竞争成为其供应链金融业务发展的关键.本文基于商业银行视角,将供应链金融和其他两种竞争型融资模式进行比较分析,探究资本市场竞争状态下供应链金融模式的适用条件及改进策略.首先,采用Stackelberg博弈模型刻画3种融资方式,运用带约束的双层规划模型进行均衡分析;其次,分析企业针对3种融资模式的选择策略、选择博弈及均衡状态;对供应链金融中的关键参数进行灵敏度分析,获得供应链金融的发展策略.研究表明:在融资成员的选择方面,银行应当优先为初始资金量较低的零售商提供融资;为扩大供应链金融的适用范围,银行应当采用"部分担保"机制,而非"差额担保"机制,即银行应根据零售商初始资金量等参数合理设置核心企业风险分担比例,以激励更多零售商选择采用供应链金融模式.最后,为商业银行高效率开展供应链金融提供了政策建议和管理启示.

当中小企业面临资金约束,越来越多的核心企业承担起投资者角色.考虑生产商向资金约束零售商提供贸易信用、供应链金融等内部融资,零售商也可选择互联网金融等外部融资,且所有融资模式均受投资失败风险影响,本文探究生产商最优投资策略.首先建立优化博弈模型依次分析企业融资运营决策;进而分析投资成功率、风险分担率、零售商初始资金等关键参数影响;最后,分析生产商和零售商最优融资模式选择策略及双方博弈均衡策略,以及生产商冲突应对策略.研究表明:贸易信用融资是生产商最优融资提供策略;不同资金量零售商融资模式选择策略不同;当零售商不选择贸易信用融资时,博弈均衡下融资模式可能对生产商不利;本文提出一类可变参数风险分担机制,以改进传统常数风险分担机制的不足:生产商可根据零售商所持资金合理调整风险担保比例,以改变融资均衡.这有助于同时实现生产商、零售商、商业银行三方共赢.本研究为生产商合理开展中小企业投资运营提供了策略支持.

Many small and medium enterprises (SMEs) with capital constraints often have no access or find it costly to obtain a loan from a bank; the retailer tends to borrow money from other enterprises in the supply chain by trade credit financing. We consider an emission-dependent supply chain with one emission-dependent manufacturer and one capital-constrained retailer in need of financing to explore the optimal operational and environmental strategies of a low-carbon supply chain under trade credit financing. We use a Stackelberg game model to depict the low-carbon supply chain. We analyse the optimal carbon-emission reduction effort, wholesale price, and order quantity in the equilibrium state. The impacts of key parameters, such as the retailer’s internal working capital, the manufacturer’s risk-aversion degree, and the carbon-trading price on the supply chain operation, are analysed. The results show that the retailer’s capital constraint causes the carbon-emission reduction effort, wholesale price, and order quantity to improve synchronously. The supply chain achieves a win-win outcome for both the manufacturer and the retailer when the capital-constrained retailer is funded via trade credit from the manufacturer. The in-depth development of financing is beneficial to the manufacturer but is a disadvantage for the retailer. When the initial carbon-emission quota is low, the manufacturer benefits from a relatively lower carbon-trading price. Otherwise, a higher carbon-trading price is better for the manufacturer. The “carbon-trading price trap” ensures that the retailer’s profit is minimal. We further investigate the scenario in which the manufacturer is risk averse and find that the retailer will purchase fewer products and that the manufacturer will gain less profit to decrease the carbon-emission reduction effort. The manufacturer’s risk aversion is unfavourable to both the economic and environmental outcomes of the whole supply chain. This research provides strategic support for a low-carbon supply chain to carry out operational decisions in the context of enterprise capital constraint. To examine the theoretical results, the data used in the existing literature are further used to simulate the corresponding conclusions. Our research enriches the existing supply chain finance literature and provides decision support for the supply chain core enterprise.

The retail industry is accelerating the transition from multi-channel to omni-channel. A display showroom is a main mode of operation in omni-channel retailing. In this, consumers find products in an online channel, experience products and receive services in offline showrooms, and make a purchase by placing an order online or offline. In practice, the online channel (offline service) can be opened (invested in) by the manufacturer or the retailer. This paper explores the relevant issues by establishing and comparing four kinds of Stackelberg game models: (1) the manufacturer simultaneously opens an online channel and invests in the offline service (MM mode; (2) the manufacturer opens an online channel, but the retailer invests in the offline service (MR mode); (3) the retailer opens an online channel, but the manufacturer invests in the offline service (RM mode); and (4) the retailer simultaneously opens an online channel and invests in the offline service (RR mode). In these models, the online channel and offline channel cooperate through a display showroom. The results show that regardless of the kind of channel structure, a display showroom can generate benefits for the manufacturer, the retailer and the whole omni-channel supply chain. And from the perspectives of the manufacturer and the whole supply chain, if the consumer service perception degree is low, the price competition degree is high (low), and the service cooperation degree are high (low), and the MM (MR) mode is the optimal channel structure. Otherwise, if the consumer service perception degree is high, the RR mode is the most efficient channel structure for the manufacturer and the omni-channel supply chain. For the retailer, the RR mode is always the best channel structure. The improved revenue-sharing contract and two-part tariff contract can achieve full coordination of and improvement in the operational efficiency of the omni-channel supply chain and achieve Pareto improvement for the supply chain members.

ABSTRACT Trade credit finance (TCF), retailer independent finance (RIF), and partial credit guarantee (PCG) finance are all important financing tools for capital‐constrained retailers. Risk aversion has a significant impact on financing, but it is difficult to measure. This research investigates the manufacturer's financing provision strategies considering risk aversion and capital market competition. First, an ordinary least squares method with conditional value at risk criteria is proposed to measure the risk attitude of decision‐makers. Second, the equilibrium mode of financing provision and impacts of risk aversion and the retailer's initial capital are analyzed. Third, a laboratory experiment and numerical analysis are conducted to verify the risk aversion estimation method and other theoretical results. We draw the following conclusions. First, the equilibrium financing provision mode changes with the degree of risk aversion and retailer's initial capital. Although the manufacturer prefers TCF and PCG to RIF, the retailer chooses the RIF mode when its initial capital is low. A variable parameter guarantee mechanism is proposed to encourage more retailers to choose PCG instead of RIF. Second, the risk‐averse financing system realizes super‐centralization (i.e., utility in the decentralized system is larger than that in the centralized system) when the manufacturer is less risk averse than the other participants. A Pareto‐optimality mechanism is designed to realize super‐centralization and coordinate the decentralized financing system. This research provides financing providers with practical guidance on the efficient implementation of supply chain financing.

贸易信用融资被广泛应用于解决中小企业融资困境,而保险正成为解决贸易信用融资风险的重要手段.本文站在核心企业角度,探究贸易信用融资保险的运营策略,运用Stackelberg博弈分析方法分别建立并比较了贸易信用融资、贸易信用融资保险、资金约束无融资、资金充足四类优化模型,探究了博弈均衡下的最优运营决策,并分析了零售商初始资金、生产商风险态度等关键参数的影响.研究表明:融资不仅对供应链有利,还能同时实现生产商及零售商共赢;当生产商风险厌恶程度、保险市场竞争程度较高,零售商初始资金较低时,融资保险能够为生产商及供应链创造价值,否则生产商应当放弃投保.研究结论为工业界合理且高效开展贸易信用融资保险运营提供了策略指导和管理启示.

Let G be a simple and undirected graph. The eigenvalues of the adjacency matrix of G are called the eigenvalues of G. In this paper, we characterize all the n-vertex graphs with some eigenvalue of multiplicity n−2 and n−3, respectively. Moreover, as an application of the main result, we present a family of nonregular graphs with four distinct eigenvalues.

The need for low-carbon development has become a social consensus. Increasing numbers of enterprises implement carbon emission reduction by using carbon cap-and-trade mechanisms to cater to consumers and practice social responsibility. From the manufacturer’s perspective, they can implement carbon emission reduction investment by themselves or outsource it to the retailer or energy service company (referred as ESCO). To explore the best carbon emission reduction mode selection strategy, we built and compared three carbon emission reduction modes—manufacturer emission reduction, retailer emission reduction, and ESCO emission reduction—by using Stackelberg game models. The joint decisions of operation, finance, and environment were obtained by using the backward induction approach. The impacts of key parameters were analyzed, such as the retailer’s initial capital amount and the decision-makers’ risk aversion degree on the low carbon supply chain operation. Our results show that the optimal carbon emission reduction mode for the manufacturer is changed as the retailer’s initial capital amount changes. Carbon emission reduction by the ESCO (retailer) becomes the dominant strategy for both the economy and environment when the cost advantage (cash investment ratio) of the ESCO (retailer) carbon emission reduction mode is sufficiently high (low). Overall, decision-makers’ risk aversion is detrimental to both the economic and environmental developments of the supply chain. We also designed contracts to realize the coordination of risk-neutral, risk-averse, capital-adequate, and capital-constrained low-carbon supply chains. These results give guidance for decision-makers to better manage the low-carbon supply chain in the context of fully considering the influential factors of risk aversion and capital constraint.

With the global consensus on the need for sustainability practices, green governance has attracted increasing attention from international business (IB) scholars and multinational enterprise (MNE) managers. In this study, we propose a more fine-grained framework of the green governance context along two dimensions: foreign direct investment (FDI) policy and environmental regulation. Then, we examine the framework using cluster analysis. On the basis of a multiple-case study comprising 11 Chinese MNEs in pollution-intensive industries operating in four different green governance contexts, we conclude that (1) the green governance context is a significant factor in MNEs' global location choices and is an important driving force behind MNEs' response patterns; (2) environmental capabilities enable MNEs to surmount a host country's environmental entry barrier and facilitate wider global business deployment; (3) technological capabilities increase MNEs' competitive edge and allow them to better harness a host country's growth opportunities; (4) there are four types of green governance response patterns, and the details of the proposed classification structure and its validation are presented; and (5) both strict environmental regulation and friendly FDI policy can positively influence MNEs' adoption of more active response patterns, and greater availability of environmental and technological capabilities does not affect MNEs' environmental commitment. This study contributes to the international strategy-capability-environment alignment of emerging economies' multinational enterprises (EMNEs) in different green governance contexts.

越来越多的核心企业联合金融机构以保兑仓融资形式为其下游分销商提供融资,研究基于运营管理视角深入分析该融资模式运作机理.首先,运用多层规划方法建立Stackelberg博弈模型,通过均衡分析得到博弈均衡策略;其次,对各资金情形进行比较,对分销商初始资金、担保回购价格等关键参数进行敏感度分析;随后,对融资系统的协调开展分析;最后,通过数值仿真对结论进行补充和论证.研究表明:保兑仓融资的实施有助于实现供应链成员共赢,应积极开展;融资开展的越深入,对供应商越有利,供应商应当为资金量更低的分销商提供资金支持;较高的担保回购价格对供应商有利,其应当积极承担回购责任;供应商应关注融资系统协调,改进的融资合同、二部定价合同和收益共享合同均可实现融资系统有效协调、提升系统运作绩效.本研究对于核心企业合理实施保兑仓融资、改善融资效率提供了决策参考.

Considering the large impact of decision-makers' risk attitude on their decision making,this paper studies how each SC partner's risk attitude affects its optimal decisions and profit and the whole SC's profit under DP.The risk attitude is modeled using mean-CVaR criterion.A Stackelberg game model is established to analyze the equilibrium decisions of the manufacturer and the retailer,and the impacts of each firm's risk attitude and the retailer's initial capital are discussed.Two kinds of contracts are designed to coordinate the SC and several numerical studies are performed to demonstrate and supplement the analytical results.The results show that risk averse firms are more conservative in decision making.DP benefits the manufacturer,the retailer and the whole SC.But the retailer should use a reasonable amount of its working capital and not overuse DP,and the manufacturer should seek risk appropriately.The two-part tariff contract and the revenue sharing contract can both achieve SC coordination.