服务供应链视角下SaaS模式免费试用策略分析

针对处于市场推广期的SaaS模式中应用服务需求的不确定性,本文从服务供应链的视角对免费试用策略应对需求不确定性进行建模分析。设计了合作契约保证免费试用策略下服务供应链的协调;将免费试用策略绩效与传统的风险共担策略绩效作比较,得出免费试用策略的适用条件;通过数值分析验证了模型的有效性并得出了其管理学意义。研究表明,与风险共担策略相比,免费试用策略能够激励客户需求和有效规避SaaS模式中服务需求不确定性的风险,并提高服务供应链中各方收益;免费试用策略的适用性和绩效与应用服务提供商(ASP)技术能力水平有关;服务供应链协调可以使免费试用取得更好的效果。     

A portfolio approach to managing procurement risk using multi-stage stochastic programming

Procurement is a critical supply chain management function that is susceptible to risk, due mainly to uncertain customer demand and purchase price volatility. A procurement approach in the form of a portfolio that incorporates the common procurement means is proposed. Such means include long-term contracts, spot procurements and option-based supply contracts. The objective is to explore possible synergies among the various procurement means, and so be able to produce optimal or near optimal results in profit while mitigating risk. The implementation of the portfolio approach is based on a multi-stage stochastic programming model in which replenishment decisions are made at various stages along a time horizon, with replenishment quantities being determined by simultaneously considering the stochastic demand and the price volatility of the spot market. The model attempts to minimise the risk exposure of procurement decisions measured as conditional value-at-risk. Numerical experiments to test the effectiveness of the proposed model are performed using demand data from a large air conditioner manufacturer in China and price volatility data from the Shanghai steel market. The results indicate that the proposed model can fairly reliably outperform other approaches, especially when either the demand and/or prices exhibit significant variability.     

Newsvendor with multiple options of expediting

We consider a manufacturer facing single period inventory planning problem with uncertain demand and multiple options of expediting. The demand comes at a certain time in the future. The manufacturer may order the product in advance with a relatively low cost. She can order additional amount by expediting after the demand is realized. There are a number of expediting options, each of which corresponds to a certain delivery lead time and a unit procurement price. The unit procurement price is decreasing over delivery lead time. The selling price is also decreasing over time. In this paper, we assume that the manufacturer must deliver all products to the customer in a single shipment. The problem can be formulated as a profit maximization problem. We develop structural properties and show how the optimal solution can be identified efficiently. In addition, we compare our model with the classical newsvendor model and obtain a number of managerial insights.     

Risk sharing and information revelation mechanism of a one-manufacturer and one-retailer supply chain facing an integrated competitor

This paper develops an information revelation mechanism model of a one-manufacturer and one-retailer supply chain facing an outside integrated-competitor under demand uncertainty. We investigate how the manufacturer designs a wholesale price-order quantity contract to induce the retailer to report his risk sensitivity information truthfully. We try to explore the effects of the outside competitor and the risk-sharing rule on the optimal price-service level decisions of the retailer and the optimal wholesale prices of the manufacturer. We find that the strategic interaction plays an important role in the effect of risk sensitivity on the order quantity for the retailer. When the fraction of the risk cost shared by the manufacturer is sufficiently large (small), the optimal wholesale price for the high risk-averse retailer is higher (lower) than that for the low risk-averse retailer.     

A comparison of two sourcing tactics for a new component

We compare two sourcing tactics for a manufacturer to purchase a new component to be used in a one-time production run of a new product with uncertain and price-elastic demand. One alternative is to issue a request-for-quote (RFQ), which is where the manufacturer requests a price-quantity schedule from suppliers. The manufacturer uses this information to determine a production quantity and the number of components to purchase from each supplier. The other alternative is to post a bid specifying how the manufacturer’s purchase quantity will depend on the supplier’s component price. The suppliers use this information to compete on quantity.We find that relative to RFQ, which is more challenging for the manufacturer to characterize the supplier response due to the possibility of supplier interaction, the benefit to the manufacturer from posting a bid increases with the number of suppliers due to increased intensity of competition. If the new component is from an emerging industry where there is little mutual awareness among candidate suppliers, then regardless of number of suppliers, expected manufacturer profit is higher under RFQ. Posting a bid is more likely to benefit the manufacturer when the new component is from a more established industry with a high degree of awareness among candidate suppliers.     

Planning performance based contracts considering reliability and uncertain system usage

This paper investigates a novel quantitative approach for planning and contracting performance-based logistics in the presence of uncertain system usage. Our efforts focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose an analytical model to characterize system operational availability by comprehending five performance drivers: inherent failure rate, usage rate, spare parts inventory, repair time, and the fleet size. This analytical insight into the system performance allows the service supplier to minimize the total cost across system design, production, maintenance, and repair. Two contracting schemes are investigated under cost minimization and profit maximization schemes. For the first time in literature, reliability design and service parts logistics are seamlessly integrated into one decision support model for improving operational availability while lowering the lifecycle cost. Numerical examples are provided to demonstrate the applicability and the effectiveness of the proposed decision support tool.     

考虑合同保质期的快速失效药品的二级供应链库存策略研究

医院药品对保质期和服务水平有非常高的要求,同时,药品的库存空间在医药库存中也有重要影响。首先针对快速失效的医药药品考虑了医药库存的合同保质期以及库存空间约束,同时考虑医院库存以及制造商库存,基于经济订货批量模型和经济生产批量模型建立了二级供应链的医药库存模型,然后用MATLAB软件求解了模型最优解,并对一些重要参数进行了敏感性分析。研究发现,合同保质期对医院订购批量、制造商生产批量和总库存成本有一定的影响,其中对于制造商的生产批量以及医院的库存成本影响较大。如果不考虑合同保质期的约束,将会对总库存成本带来更大损失。     

Joint modeling of longitudinal proportional measurements and survival time with a cure fraction

In cancer clinical trials and other medical studies, both longitudinal measurements and data on a time to an event (survival time) are often collected from the same patients. Joint analyses of these data would improve the efficiency of the statistical inferences. We propose a new joint model for the longitudinal proportional measurements which are restricted in a finite interval and survival times with a potential cure fraction. A penalized joint likelihood is derived based on the Laplace approximation and a semiparametric procedure based on this likelihood is developed to estimate the parameters in the joint model. A simulation study is performed to evaluate the statistical properties of the proposed procedures. The proposed model is applied to data from a clinical trial on early breast cancer.     

Proportion-based robust optimization and team orienteering problem with interval data

In this paper, a proportion-based robust optimization approach is developed to deal with uncertain combinatorial optimization problems. This approach assumes that a certain proportion of uncertain coefficients in each solution are allowed to change and optimizes a deterministic model so as to achieve a trade-off between optimality and feasibility when the coefficients change. We apply this approach on team orienteering problem with interval data (TOPID), a variant of vehicle routing problem, which has not yet been studied before. A branch and price algorithm is proposed to solve the robust counterpart by using two novel dominance relations. Finally, numerical study is performed. The results show the usefulness of the proposed robust optimization approach and the effectiveness of our algorithm.     

Price discount based on early order commitment in a single manufacturer–multiple retailer supply chain

Early order commitment (EOC) is a strategy for supply chain coordination, wherein the retailer commits to purchasing from a manufacturer a fixed order quantity a few periods in advance of the regular delivery lead time. In this paper, we formulate and analyze the EOC strategy for a decentralized, two-level supply chain consisting of a single manufacturer and multiple retailers, who face external demands that follow an autocorrelated AR(1) process over time. We characterize the special structure of the optimal solutions for the retailers’ EOC periods to minimize the total supply chain cost and discuss the impact of demand parameters and cost parameters. We then develop and compare three solution approaches to solving the optimal solution. Using this optimal cost as the benchmark, we investigate the effectiveness of using the wholesale price-discount scheme for the manufacturer to coordinate this decentralized system. We give numerical examples to show the benefits of EOC to the whole supply chain, examine the efficiency of the discount scheme in general situation, and provide the special conditions when the full coordination is achieved.     

市场需求不确定结构模型研究

在一个由原始设备制造商、合同制造商和原材料供应商组成的三级链中,简述了在市场需求不确定情况下存在成本信息不对称的整合外包模型,并对这个模型进行了分析.最后,运用MATLAB进行了实例分析,说明了市场需求不确定对模型的影响.     

Models and estimation methods for clinical HIV-1 data

Clinical HIV-1 data include many individual factors, such as compliance to treatment, pharmacokinetics, variability in respect to viral dynamics, race, sex, income, etc., which might directly influence or be associated with clinical outcome. These factors need to be taken into account to achieve a better understanding of clinical outcome and mathematical models can provide a unifying framework to do so. The first objective of this paper is to demonstrate the development of comprehensive HIV-1 dynamics models that describe viral dynamics and also incorporate different factors influencing such dynamics. The second objective of this paper is to describe alternative estimation methods that can be applied to the analysis of data with such models. In particular, we consider: (i) simple but effective two-stage estimation methods, in which data from each patient are analyzed separately and summary statistics derived from the results, (ii) more complex nonlinear mixed effect models, used to pool all the patient data in a single analysis. Bayesian estimation methods are also considered, in particular: (iii) maximum posterior approximations, MAP, and (iv) Markov chain Monte Carlo, MCMC. Bayesian methods incorporate prior knowledge into the models, thus avoiding some of the model simplifications introduced when the data are analyzed using two-stage methods, or a nonlinear mixed effect framework. We demonstrate the development of the models and the different estimation methods using real AIDS clinical trial data involving patients receiving multiple drugs regimens.     

考虑多提前期的厨房电器供应链网络库存系统鲁棒控制研究

在厨房电器供应链的管理实践中,市场、技术、客户需求等具有不确定,牛鞭效应也会影响供应链系统的稳定性,造成系统性的损失。为了提高厨房电器供应链的鲁棒性能,本文首先基于Takagi-Sugeno模糊控制系统,考虑采购、生产、销售等多种提前期以及客户需求的不确定性,构建一类厨房电器供应链网络动态模型;其次,根据不同周期下厨房电器供应链制造商的库存状况,对制造商的生产策略进行了设计;随后,提出了基于模糊鲁棒控制策略对多提前期、多种不确定因素对厨房电器供应链的影响;最后,基于厨房电器供应链的实际数据进行了仿真,结果显示本文提出的厨房电器供应链鲁棒策略是可行和有效的。     

Capacity reservation contracts for high-tech industry

Capacity reservation provides a risk-sharing mechanism that encourages a manufacturer to expand its capacity more. We propose a deductible reservation (DR) contract where customers reserve future capacity with a fee that is deductible from the purchasing price. The manufacturer’s ex ante announcement of the “excess” capacity that she will have in addition to the reservation amount is a unique feature of the DR contract. An individually rational DR contract that provides channel coordination always exists. Since there is a unique Nash equilibrium for the reservation game among multiple customers, the main results of the one-customer case can be extended to the n-customer case. The DR contract is compared with another capacity reservation contract called take-or-pay. While the manufacturer may gain more profit under a take-or-pay contract, there may not be a channel-coordinated contract that is also individually rational for the customer. Finally, the similarities and differences between the capacity reservation contracts and other well-known supply contracts are discussed.     

A Markov decision process model for equitable distribution of supplies under uncertainty

Many individuals suffering from food insecurity obtain assistance from governmental programs and nonprofit agencies such as food banks. Much of the food distributed by food banks come from donations which are received from various sources in uncertain quantities at random points in time. This paper presents a model that can assist food banks in distributing these uncertain supplies equitably and measure the performance of their distribution efforts. We formulate this decision problem as a discrete-time, discrete state Markov decision process that considers stochastic supply, deterministic demand and an equity-based objective. We investigate three different allocation rules and describe the optimal policy as a function of available inventory. We also provide county level estimates of unmet need and determine the probability distribution associated with the number of underserved counties. A numerical study is performed to show how the allocation policy and unmet need are impacted by uncertain supply and deterministic, time-varying demand. We also compare different allocation rules in terms of equity and effectiveness.     

Forecasting portfolio returns using weighted fuzzy time series methods

We propose using weighted fuzzy time series (FTS) methods to forecast the future performance of returns on portfolios. We model the uncertain parameters of the fuzzy portfolio selection models using a possibilistic interval-valued mean approach, and approximate the uncertain future return on a given portfolio by means of a trapezoidal fuzzy number. Introducing some modifications into the classical models of fuzzy time series, based on weighted operators, enables us to generate trapezoidal numbers as forecasts of the future performance of the portfolio returns. This fuzzy forecast makes it possible to approximate both the expected return and the risk of the investment through the value and ambiguity of a fuzzy number.We incorporate our proposals into classical fuzzy time series methods and analyze their effectiveness compared with classical weighted fuzzy time series models, using historical returns on assets from the Spanish stock market. When our weighted FTS proposals are used to point-wise forecast portfolio returns the one-step ahead accuracy is improved, also with respect to non-fuzzy forecasting methods.     

Accounting for Time Series Errors in Partially Linear Model With Single- or Multiple-Runs

This article concerns statistical estimation of the partially linear model (PLM) for time course measurements, which are temporally correlated and allow multiple-runs for repeated measurements to enhance experimental accuracy without extending the number of time points within each trial. Such features arise naturally from biomedical data, for example, in brain fMRI, and call for special treatment beyond classical methods in either a purely nonparametric regression model or a PLM with independent errors. We develop a stepwise procedure for estimating the parametric and nonparametric components of the multiple-run PLM and making inference for parameters of interest, adaptive to either single- or multiple-run, in the presence of error temporal dependence. Simulation study and real fMRI data applications illustrate the computational simplicity and effectiveness of the proposed methods. Supplementary material for this article is available online.     

Coordinating a decentralized supply chain with customer returns and price-dependent stochastic demand using a buyback policy

We investigate a decentralized supply chain that consists of a manufacturer and a retailer where the retailer simultaneously determines the retail price and order quantity while experiencing customer returns and price dependent stochastic demand. We propose an agreement between the manufacturer and the retailer that includes two buyback prices, one for unsold inventory and a second for customer returns, and show that this type of easy-to-implement agreement can achieve perfect supply chain coordination and be a win-win for both manufacturer and retailer when a complementary profit-sharing agreement is included.     

Warranty cost analysis: Increasing warranty repair times

In this study, we model the warranty servicing costs under nonrenewing and renewing free repair warranties. We assume nonzero increasing repair times with the warranty cost depending on the length of the repair time. An increasing geometric process is used to model the consecutive repair times. We introduce the generalised alternating renewal process, which is an alternating process with cycles consisting of an item's operational time followed by the corresponding repair time. We derive analytical results for a generalised alternating renewal process with a finite time horizon and use them to evaluate the warranty costs over the warranty period and over the life cycle of the product under the nonrenewing free repair warranty and renewing free repair warranty. Properties of the model are demonstrated through a simulation study and through the application to warranty claims data from an automotive manufacturer.