从4Ps到3Rs+4Ps──对经典营销理论的再思考

随着社会环境与市场环境的剧变,专家断言：世界经济开始进入了“服务经济时代”,而服务营销理念的提出,还需要在营销理论的深度上获得支撑．本文因此而尝试对经典营销理论进行审视和思考：从４Ｐｓ到３Ｒｓ＋４Ｐｓ。     

家具销售中预测模型的研究

用灰色非线性建模理论，建立了家具销售方面的两个预测模型，为家具企业的生产、销售，提供了一个科学而又容易操作的决策方法。     

金融POS机在公用分组交换网上的应用

金融ＰＯＳ机在公用分组交换网上的应用,对使用信用卡的客户购物更方便。工程中对传统电话网组网方式和公用分组交换网方式进行了分析比较,结果采用了后者来实现对信息的处理,从而提高了金融机构信用卡的服务质量,这将对金卡工程起到积极的促进作用。     

Fuzzy linear regression and its applications to forecasting in uncertain environment

Linear regression has been used for many years in developing mathematical models for application in marketing, management, and sales forecasting. In this paper, two different sales forecasting techniques are discussed. The first technique involves non-fuzzy abstract methods of linear regression and econometrics. A study of the international market sales of cameras, done in 1968 by John Scott Armstrong, utilized these non-fuzzy forecasting techniques. The second sales forecasting technique uses fuzzy linear regression introduced by H. Tanaka, S. Uejima, and K. Asai, in 1980. In this paper, a study of the computer and peripheral equipment sales in the United States is discussed using fuzzy linear regression. Moreover, fuzzy linear regression is applied to forecasting in an uncertain environment. Finally, some possible improvements and suggestions for further study are mentioned.     

Coordinating a supply chain with effort and price dependent stochastic demand

This paper investigates the issue of channel coordination for a supply chain facing stochastic demand that is sensitive to both sales effort and retail price. In the standard newsvendor setting, the returns policy and the revenue sharing contract have been shown to be able to align incentives of the supply chain’s members so that the decentralized supply chain behaves as well as the integrated one. When the demand is influenced by both retail price and retailer sales effort, none of the above traditional contracts can coordinate the supply chain. To resolve this issue, we explore a variety of other contract types including joint return policy with revenue sharing contract, return policy with sales rebate and penalty (SRP) contract, and revenue sharing contract with SRP. We find that only the properly designed returns policy with SRP contract is able to achieve channel coordination and lead to a Pareto improving win–win situation for supply chain members. We then provide analytical method to determine the contract parameters and finally we use a numerical example to illustrate the findings and gain more insights.     

零售商双渠道供应链的定价与协调机制研究

主要研究了一个建立线上线下双渠道的零售商,如何进行定价协调零售商线上线下的水平冲突,并最终到达零售商整体的利润的优化.根据实际情况引入了销售努力补偿的协调机制,并通过算例分析发现当零售商对其网络渠道提供合适的销售努力程度时,零售商的利润可以得到优化.并在双渠道的零售商实现水平协调的基础上,考虑供应链垂直方向上因零售商和制造商双方博弈下带来了双重边际效应,进一步设计了收入共享契约,研究表明当零售商提供合适的收入分配比时,可以实现制造商和零售商利润的优化,实现了供应链成员Pareto改进,这样零售商双渠道就实现了水平和垂直方向的全协调,供应链成员的利润得到了优化.     

Sales effort free riding and coordination with price match and channel rebate

This paper studies sales effort coordination for a supply chain with one manufacturer and two retail channels, where an online retailer offers a lower price and free-rides a brick-and-mortar retailer’s sales effort. The free riding effect reduces brick-and-mortar retailer’s desired effort level, and thus hurts the manufacturer’s profit and the overall supply chain performance. To achieve sales effort coordination, we designed a contract with price match and selective compensation rebate. We also examined other contracts, including the target rebate contract and the wholesale price discount contract, both with price match. The numerical analysis shows that the selective rebate outperforms other contracts in coordinating the brick-and-mortar retailer’s sales effort and improving supply chain efficiency.     

Inventory and sales effort management under unobservable lost sales

A retailer needs to make decisions regarding how much to order and how much sales effort to exert in an environment with uncertain demand. One intrinsic complexity in a typical retail environment is caused by the fact that the retailer can obtain information about demand only based on sales, as demand itself is unobservable. Taking a Bayesian approach, Lariviere and Porteus (1999) show that in such a setting a retailer should stock more to increase the probability of an exact demand observation. In this article, we extend their work by allowing the retailer to control both the stocking quantity and sales effort, which can be used to affect demand. We show that their insights with respect to information stalking carry over to this setting. In addition, our model allows gaining a better understanding of optimal sales effort strategies. We find that demand management has a dual role in supporting information gathering: while at the beginning of a product life cycle it is optimal to support learning effects by sharply reducing sales effort, at later stages of the product life cycle an aggressive strategy of increased promotional activities can be used to harvest the information gathered in earlier periods.     

All-pay auctions with pre- and post-bidding options

Motivated by the emergence of online penny or pay-to-bid auctions, in this study, we analyze the operational consequences of all-pay auctions competing with fixed list price stores. In all-pay auctions, bidders place bids, and highest bidder wins. Depending on the auction format, the winner pays either the amount of their bid or that of the second-highest bid. All losing bidders forfeit their bids, regardless of the auction format. Bidders may visit the store, both before and after bidding, and buy the item at the fixed list price. In a modified version, we consider a setting where bidders can use their sunk bid as a credit towards buying the item from the auctioneer at a fixed price (different from the list price). We characterize a symmetric equilibrium in the bidding/buying strategy and derive optimal list prices for both the seller and auctioneer to maximize expected revenue. We consider two situations: (1) one firm operating both channels (i.e. fixed list price store and all-pay auction), and (2) two competing firms, each operating one of the two channels.     

Forecasting using belief functions: An application to marketing econometrics

A method is proposed to quantify uncertainty on statistical forecasts using the formalism of belief functions. The approach is based on two steps. In the estimation step, a belief function on the parameter space is constructed from the normalized likelihood given the observed data. In the prediction step, the variable Y to be forecasted is written as a function of the parameter θ and an auxiliary random variable Z with known distribution not depending on the parameter, a model initially proposed by Dempster for statistical inference. Propagating beliefs about θ and Z through this model yields a predictive belief function on Y. The method is demonstrated on the problem of forecasting innovation diffusion using the Bass model, yielding a belief function on the number of adopters of an innovation in some future time period, based on past adoption data.