信息不对称条件下竞价排名机制的信息匹配效率研究

本文聚焦消费者依赖搜索引擎平台的关键词检索实施购买商品行为的现象,尝试将消费者购买策略引入搜索平台竞价排名机制,构造内嵌搜索引擎平台、销售商、消费者三方主体的博弈模型,考察在互联网信息不对称条件下,竞价排名机制的信息匹配效率,阐释产品质量信号改善竞价排名机制信息匹配效率的理论机理。研究发现,在信息不对称及无产品质量信号机制的条件下,竞价排名均衡结果完全不能匹配消费者的购买策略,致使消费者福利因销售商逆向选择而遭受双重损失;植入产品质量信号后,搜索引擎平台能够通过识别销售商自带的产品质量信号,提高竞价排名机制的均衡结果与消费者购买策略的匹配度,进而部分地改善竞价排名机制的信息匹配效率。     

The k-means range algorithm for personalized data clustering in e-commerce

This paper describes the k-means range algorithm, a combination of the partitional k-means clustering algorithm with a well known spatial data structure, namely the range tree, which allows fast range searches. It offers a real-time solution for the development of distributed interactive decision aids in e-commerce since it allows the consumer to model his preferences along multiple dimensions, search for product information, and then produce the data clusters of the products retrieved to enhance his purchase decisions. This paper also discusses the implications and advantages of this approach in the development of on-line shopping environments and consumer decision aids in traditional and mobile e-commerce applications.     

Estimating the market shares of stores based on the shopper's search and purchase behavior

Suppose that a consumer has decided to shop around several retail stores in an attempt to find a desired product or service. From his or her past shopping experience, the shopper may know: (1) the assortment size of each store, (2) the search cost per visit, and (3) the price variation among the stores. For such a situation, we first consider the optimal sequence of stores and the optimal search strategy from the shopper's search-theoretic point of view. Based on the assumption that shoppers follow the optimal sequencing and search strategy that maximizes his or her expected net gain, we then estimate the market share of each store in the market area. With a numerical example, we finally analyze the effects of the assortment size, the search cost, and the price variation on the market shares of existing retail stores. Based on the shopper's search and purchase model, we attempt to explain: (1) why shoppers visit bigger stores first, (2) why they visit fewer stores if the search cost is relatively higher than the product price, and (3) why they shop around more stores if the price variation among the stores is large.     

ZIPMAP — A Zero-One Integer Programming Model for Market Segmentation and Product Positioning

An optimization model is proposed to aid marketing managers to search for and develop new product brand ideas. The model, which is founded on individual consumer behaviour constructs, determines a position for a new brand, in the consumers' perceptual space of product attributes, that maximizes company sales. The resulting mathematical model is stated as a large-scale, mixed, zero-one, integer, non-linear mathematical programming problem whose solution is sought through a two-stage optimization approach.     

搜寻成本下可替代产品的定价策略与库存决策

为探寻存在搜寻成本情况下消费者购买可替代产品时的定价与库存问题,从消费者效用出发,对厂商收益构建了基于马尔可夫决策过程的优化模型。在消费者方面,分析了其购买与继续搜寻的条件,并分别在搜寻成本不变和搜寻成本边际递减的情况下研究了消费者保留效用的变化情况以及购买相应产品的概率。此外,与很多相关文献不同的是,由于搜寻成本的存在,该情形下的消费者并不一定会在完成购买之前搜寻完所有的产品。在厂商方面,根据实际情况构建不同搜寻顺序下的收益模型并求解出最优定价策略与库存策略,并将定价模型与库存策略扩展到了动态的环境,为厂商制定价格及库存方案提供相应的决策支持。     

展厅现象下电子零售商与传统零售商的价格竞争

针对双渠道中存在消费者先通过实体店体验产品,而转移电子渠道购买的展厅现象,运用消费者效用理论,建立不同购买方式下电子零售商和传统零售商的定价决策模型,通过对不同情形下最优决策的比较分析,进一步研究展厅现象如何影响电子零售商和传统零售商的定价和利润。研究表明:三种购买方式同时存在时,展厅现象将加剧传统零售商与电子零售商的价格竞争,导致双方利润受损,但当电子渠道接受度较高或是较低且实体店体验对电子渠道接受度的影响较大时,电子零售商可以利用展厅现象提高其销售价格并获利。     

Product variety, pricing and differentiation in a supply chain

Manufacturers typically sell consumer products through retailers and the presence of intermediaries has interesting ramifications for their product variety and pricing decisions. Retailers may want higher variety to help reduce price competition but the costs of variety are borne by the manufacturer. The increased variety may increase demand and profits for the manufacturer too but this depends on market-specific factors as well as costs. We explore these interactions through a model wherein a manufacturer sells multiple product variants at a wholesale price to two retailers who in turn compete for consumers. Consumers choose between the retailers based on the price and variety offered by each retailer and the search or transportation cost incurred by the consumer, equivalent to the level of retailer differentiation in our model. Several insights emerge from the analysis. The manufacturer offers the same variety to both retailers and this variety increases with market size and consumer sensitivity to variety. We find that some retailer differentiation benefits the retailers (not the manufacturer) but too much differentiation hurts both the retailers and the manufacturer. If the market is fully covered, then the channel is coordinated even with a simple wholesale pricing contract. If the retailers incur costs to sell the product, the manufacturer surprisingly loses out more than the retailers and in fact absorbs some or all of the retailer costs. Finally, asymmetry between retailers has some unexpected consequences. For example, variety is not impacted by asymmetry in consumer preferences for a retailer and the manufacturer offers the same variety to both retailers.     

Scheduling of multistage fast-moving consumer goods plants

Fast-moving consumer goods (FMCG) plants are required to be highly flexible due to their multiproduct nature and frequent portfolio changes with seasons or consumer preferences. The multipurpose nature of equipment units usually results in changeover activities which can increase the production scheduling model’s size significantly. The objective of this paper is to present two approaches to decrease the number of changeover activities. The first approach aims to reduce unit flexibility by reducing the allowable task to unit allocations. The second approach emphasises sequencing operations on units. By limiting the set of possible task sequences in the scheduling problem, the number of allowable activities (especially changeovers) is decreased and the optimisation procedure has a smaller search space. The results of these approaches, tested against realistically sized instances indicate their effectiveness in reducing the model size and the solution time, enabling the solution of industrial examples which previously could not be solved.     

消费需求模型的理论与应用

随着消费需求函数形式的不断丰富和复杂化,形成多种消费需求模型,广泛应用于食品需求结构分析,农产品进出口贸易等研究领域.论文通过对消费需求模型理论研究进行梳理,通过理论假设和理论约束的分析,梳理出应用较广的消费需求模型的主要类型的理论依据和数理分析逻辑,以及模型应用过程中面临的问题和各自的优、缺点.研究结论将有助于加深对消费需求模型理论与实证应用的理解,为有关消费需求的研究提供可选择的研究方法和研究依据.     

消费者公平偏好对制造商开通直销渠道的影响研究

研究了消费者公平偏好对制造商开通直销渠道的影响,并分析消费者公平偏好对制造商和零售商的最优决策、制造商开通直销渠道意愿、零售商利润、以及消费者剩余等的影响。最后通过算例分析消费者公平偏好对制造商开通直销渠道意愿的影响。研究发现:不存在消费者公平偏好时,制造商仅在直销成本较小时开通直销渠道;当直销成本较大时,制造商不应开通直销渠道。然而,消费者公平偏好会降低制造商开通直销渠道的意愿;即使无直销成本,若消费者公平偏好较大,制造商也可能不会开通直销渠道。     

Limit cycles in local preference optimization

We consider the problem of a rational consumer who does nota priori know what his optimal feasible consumption bundle is, but attempts to find it by continuously moving in a direction of increasing preferences, starting with an arbitrary bundle. We show that this process is only then guaranteed to lead to the consumption optimum whena the consumer preferences are transitive; and/orb the consumer follows in each point the exact direction of fastest preference increase (that is in the integrable case: the utility gradient). If this is not the case, there may exist limit cycles to which the consumer may get attracted, thus never reaching his optimum.This note is dedicated to Yves Richelle, the ever-cycling economist.     

Balancing productivity and consumer satisfaction for profitability: Statistical and fuzzy regression analysis

This paper examines the relationships among productivity, consumer satisfaction and profitability using the conventional statistical regression and the new fuzzy regression approaches. For service firms in the context of Hong Kong, we verify the profit hypothesis that individually both productivity and consumer satisfaction are positively linked to profitability as well as the tradeoff hypothesis that aggregately there are negative interactions between productivity and consumer satisfaction for enhancing profitability. Hence service firms should balance their efforts in productivity and consumer satisfaction, possibly by employing appropriate information technologies to improve productivity while without hurting consumer satisfaction, to optimize their profitability. The study takes advantage of the Hong Kong Consumer Satisfaction Index and deliberately focuses on total rather than partial productivity. Several models are first estimated using the ordinary least squares (OLS) method and the results generally support the two hypotheses, but the OLS approach also leaves two puzzles that estimates of the regression coefficients are: (1) not significant before considering the interactions between consumer satisfaction and productivity but significant after introducing the interaction term, and (2) significant although sample data for productivity and the interaction term are highly correlated. These puzzles, together with the observed imprecision in productivity and profitability measurements and especially the subjectivity in measuring consumer satisfaction, lead us to adopt the fuzzy linear regression (FLR) techniques to further examine the two hypotheses. The popular FLR model continues to favor our research hypotheses but fail to offer any additional insights into the examined relationships over the OLS models. We then propose a revised FLR model which, in addition to reconfirming the hypotheses, does help to explain the encountered puzzles and fuzziness, and hence suggests an encouraging methodology for marketing.     

A heuristic for direct consumer participation in primary health care planning

Recent attempts at consumer participation in the health care planning process have proved weak in their ability to responsively account for consumer health welfare. This can be attributed, in large part, to the mechanisms employed for identifying and utilizing the consumer's health care views and preferences. A heuristic planning procedure designed to overcome these problems by directly incorporating consumer preferences is developed. It identifies that (primary) health care delivery system which maximizes total incremental health benefit to a community subject to a prespecified budget constraint. The model assumes a methodology (previously developed by the author) for measuring, in aggregable units, the benefit, B_ip, from some health care facility p as perceived by some consumer i. Application of the procedure and subsequent sensitivity analyses demonstrate its ability to generate valid solutions that are robust to disturbances in the planning system.     

A heuristic method for non-homogeneous redundancy optimization of series-parallel multi-state systems

This paper develops an efficient heuristic to solve the non-homogeneous redundancy allocation problem for multi-state series-parallel systems. Non identical components can be used in parallel to improve the system availability by providing redundancy in subsystems. Multiple component choices are available for each subsystem. The components are binary and chosen from a list of products available on the market, and are characterized in terms of their cost, performance and availability. The objective is to determine the minimal-cost series-parallel system structure subject to a multi-state availability constraint. System availability is represented by a multi-state availability function, which extends the binary-state availability. This function is defined as the ability to satisfy consumer demand that is represented as a piecewise cumulative load curve. A fast procedure is used, based on universal generating function, to evaluate the multi-state system availability. The proposed heuristic approach is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected subspace. The design problem, solved in this study, has been previously analyzed using GA. Numerical results for the test problems from previous research are reported, and larger test problems are randomly generated. These results show that the proposed approach is efficient both in terms of both of solution quality and computational time, as compared to existing approaches.     

物价、利率与收入对居民消费需求影响研究——基于时变参数状态空间模型

运用时变参数状态空间模型对我国改革开放三十年来物价、利率与收入对农村和城镇居民消费需求影响的动态特征进行了研究。发现物价、收入对农村和城镇居民的消费需求弹性不同,农村消费需求受收入影响较大,而城市居民消费需求受物价影响较大;利率对农村和城镇居民消费需求影响不显著,利率机制目前还不是调解中国消费需求的理想工具。在此基础上给出了相应的政策建议。     

Evaluation of the warranty cost of a product with type III stochastic dependence between components

This paper analyses respectively the expected warranty costs from the perspectives of the manufacturer and the consumer. For a two-component series system with stochastic dependence between components, both the non-renewing free replacement policy and the renewing replacement policy are examined. It is assumed that whenever component 1 fails, a random damage to component 2 is occurred while a component 2 failure causes the system failure. Component 2 fails when its total accumulative damage exceeds a pre-determined level L. By considering the consumer’s behavior and the product service time, the warranty costs allocations between the manufacturer and the consumer are presented. Numerical examples are given to demonstrate the applicability of the methodology. It is proved that, independent of the type of the warranty policy, the failure interaction between components impacts the manufacturer profits and the consumer costs. The initial warranty length has also an impact on the product quality preferences to both the consumer and the manufacturer.     

名优产品与劣质产品，孰优孰劣——消费品市场的博弈分析

由于信息不对称,买者通过逆向选择,在消费品市场上形成’伪劣产品”驱逐“名优产品”,类似于货币史上“劣币驱逐良币”,从而伪劣产品泛滥,而在信息畅通的情况下,消费者的选择是购买名优产品,不买劣质产品,厂商的选择是生产名优产品,或者长期生产劣质产品,但产品无人问津.     

Product line selection and pricing analysis: Impact of genetic relaxations

A model for the product line selection and pricing problem (PLSP) is presented andthree solution procedures based on a genetic algorithm are developed to analyze the results based on consumer preference patterns. Since the PLSP model is nonlinear and integer, two of the solution procedures use genetic encoding to “relax” the NP hard model. The relaxations result in linear integer and shortest path models for the fitness evaluation which are solved using branch and bound and labeling algorithms, respectively. Performance of the quality of solutions generated by the procedures is evaluated for various problem sizes and customer preference structures. The results show that the genetic relaxations provide efficient and effective solution methodologies for the problem, when compared to the pure artificial intelligence technique of genetic search. The impact of the preference structure on the product line and the managerial implications of the solution characteristics generated by the genetic relaxations are also discussed. The models can be used to explicitly consider tradeoffs between marketing and operations concerns in designing a product line.     

Consumer heterogeneity and the shape of purchase rate functions

This study suggests that non-monotonic purchase rates, frequently observed in empirical studies of consumer purchase timing, can be an artifact of consumer heterogeneity. We use a theoretical purchase timing model with consumer heterogeneity to develop market scenarios under which non-monotonic rates may obtain. The results suggest that non-monotonic rates are more likely to observe in product markets that are either highly concentrated or where the heavy buyer segment is large. In such markets, therefore, one should not rely on non-monotonic rate curves to predict household purchase incidence. © 1998 John Wiley & Sons, Ltd.