基于风险厌恶零售商的双渠道闭环供应链运作策略

在对称信息框架下,针对零售商存在风险厌恶特性的双渠道闭环供应链,基于Stackelberg博弈理论探讨了不同的回收再制造模式下(制造商不回收再制造、制造商独立回收再制造、制造商依托零售商回收再制造)供应链各主体的运作决策。研究发现,在不同回收再制造模式下,制造商与风险厌恶的零售商合作能够获得更多收益。市场波动的增大对供应链各主体并非始终是有害的,随着市场波动的增大,带有风险厌恶的零售商收益不断减小,而风险中性的双渠道制造商收益逐步增大,零售商风险厌恶特性为制造商带来了更多的收益。制造商独立回收再制造以及通过零售商进行回收再制造时,双渠道产品定价均低于不进行任何回收再制造模式下的定价,双渠道需求和利润均高于不进行任何回收再制造模式下的渠道需求和利润,即回收再制造模式不仅为下游顾客带来了更多的消费实惠,同时也为供应链各主体带来了更多的收益。     

产需不确定下面向资金约束供应商的供应链融资策略研究

以包含一个供应商和一个分销商的供应链为研究对象,其中分销商面临市场需求不确定性,供应商存在资金约束且面临产出不确定性。 提出期望利率的概念,研究银行贷款期望利率一定的情况下,供应链银行融资最优策略。 构建了供应链预付款融资机制,在此基础上研究预付款模式下供应链的融资与生产订购的最优策略,并讨论了预付款期望利率的可行范围。 研究表明,预付款融资模式下,分销商愿意以低于银行贷款利率的期望利率向供应商提供预付款; 存在预付款期望利率可行区间,实现预付款协调模式下供应链系统的帕累托改进。     

Bayesian Nonparametric Modeling for Multivariate Ordinal Regression

Univariate or multivariate ordinal responses are often assumed to arise from a latent continuous parametric distribution, with covariate effects that enter linearly. We introduce a Bayesian nonparametric modeling approach for univariate and multivariate ordinal regression, which is based on mixture modeling for the joint distribution of latent responses and covariates. The modeling framework enables highly flexible inference for ordinal regression relationships, avoiding assumptions of linearity or additivity in the covariate effects. In standard parametric ordinal regression models, computational challenges arise from identifiability constraints and estimation of parameters requiring nonstandard inferential techniques. A key feature of the nonparametric model is that it achieves inferential flexibility, while avoiding these difficulties. In particular, we establish full support of the nonparametric mixture model under fixed cut-off points that relate through discretization the latent continuous responses with the ordinal responses. The practical utility of the modeling approach is illustrated through application to two datasets from econometrics, an example involving regression relationships for ozone concentration, and a multirater agreement problem. Supplementary materials with technical details on theoretical results and on computation are available online.     

On compact vector formats in the solution of the chemical master equation with backward differentiation

A stochastic chemical system with multiple types of molecules interacting through reaction channels can be modeled as a continuous‐time Markov chain with a countably infinite multidimensional state space. Starting from an initial probability distribution, the time evolution of the probability distribution associated with this continuous‐time Markov chain is described by a system of ordinary differential equations, known as the chemical master equation (CME). This paper shows how one can solve the CME using backward differentiation. In doing this, a novel approach to truncate the state space at each time step using a prediction vector is proposed. The infinitesimal generator matrix associated with the truncated state space is represented compactly, and exactly, using a sum of Kronecker products of matrices associated with molecules. This exact representation is already compact and does not require a low‐rank approximation in the hierarchical Tucker decomposition (HTD) format. During transient analysis, compact solution vectors in HTD format are employed with the exact, compact, and truncated generated matrices in Kronecker form, and the linear systems are solved with the Jacobi method using fixed or adaptive rank control strategies on the compact vectors. Results of simulation on benchmark models are compared with those of the proposed solver and another version, which works with compact vectors and highly accurate low‐rank approximations of the truncated generator matrices in quantized tensor train format and solves the linear systems with the density matrix renormalization group method. Results indicate that there is a reason to solve the CME numerically, and adaptive rank control strategies on compact vectors in HTD format improve time and memory requirements significantly.     

The Yang-Mills functional and Laplace's equation on quantum Heisenberg manifolds

In this paper, we discuss the Yang-Mills functional and a certain family of its critical points on quantum Heisenberg manifolds using noncommutative geometrical methods developed by A. Connes and M. Rieffel. In our main result, we construct a certain family of connections on a projective module over a quantum Heisenberg manifold that gives rise to critical points of the Yang-Mills functional. Moreover, we show that there is a relationship between this particular family of critical points of the Yang-Mills functional and Laplace's equation on multiplication-type, skew-symmetric elements of quantum Heisenberg manifolds; recall that Laplacian is the leading term for the coupled set of equations making up the Yang-Mills equation.     

Non-commutative Markov chains and multi-analytic operators

We study a model of repeated interaction between quantum systems which can be thought of as a non-commutative Markov chain. It is shown that there exists an outgoing Cuntz scattering system associated to this model which induces an input-output formalism with a transfer function corresponding to a multi-analytic operator, in the sense of multivariate operator theory. Finally we show that observability for this system is closely related to the scattering theory of non-commutative Markov chains.     

New Route to Polymeric Nanoparticles by Click Chemistry Using Bifunctional Cross-Linkers

A new route to functional polymeric nanoparticles (PNPs) of different chemical nature in the 3 to 20 nm size range is reported by combining both radical addition fragmentation chain transfer (RAFT) polymerization and “click” chemistry (CC) techniques. RAFT polymerization was employed for the synthesis of well-defined statistical copolymers with pending –Cl groups along the macromolecular chain. After transformation of the –Cl groups to –N₃ groups by treatment with sodium azide, an appropriate bifunctional cross-linker is employed to obtain PNPs under CC conditions promoting intramolecular cycloaddition (cross-linking). Following this new route, polystyrene, poly(alkyl (meth)acrylate), polymethacrylic acid, poly(sodium styrenesulfonate) and poly(N-isopropyl) NPs have been synthesized and in-deep characterized.     

Supply chain interactions due to store-brand introductions: The impact of retail competition

Store-brand products are of increasing importance in retailing, often causing channel conflict as they compete with national brands. Focusing on the interactions that arise in single-manufacturer single-retailer settings, previous research suggests that one main driver of store-brand profitability to the retailer is that it leads to a reduction of the national-brand wholesale price. Under retail competition, the Robinson Patman Act then introduces an interesting trade-off: A retailer that introduces a store brand incurs the associated costs and risks, while sharing this benefit with its competition. We show that the resulting interactions can cause retailers to play “chicken”, either of them preferring a store-brand introduction by the competitor. Such interactions do not arise in channels with a single retailer, as has been the object of most previous research, and we show that some of the key insights derived from single-retailer models fail to hold when retailers compete. We conduct a numeric study, and our findings suggest that retailers are more likely to randomize their store-brand introduction strategies when customers have strong store preferences, and when the retailers’ store-brand products are similar to the national-brand product in terms of customer valuations and production cost.     

An optimal production-inventory model for deteriorating items with multiple-market demand

The global markets of today offer more selling opportunities to the deteriorating items’ manufacturers, but also pose new challenges in production and inventory planning. From a production management standpoint, opportunities to exploit the difference in the timing of the selling season between geographically dispersed markets for deteriorating items are important to improving a firm’s profitability. In this paper, we examined the above issue with an insightful production-inventory model of a deteriorating items manufacturer selling goods to multiple-markets with different selling seasons. We also provided a solution procedure to find the optimal replenishment schedule for raw materials and the optimal production plan for finished products. A numerical example was then used to illustrate the model and the solution procedure. Finally, sensitivity analysis of the optimal solution with respect to major parameters was carried out.