Supply chain pricing and coordination with markdown strategy in the presence of conspicuous consumers

This paper studies the problem of supply chain pricing and coordination with markdown policy in the presence of conspicuous consumption. A two‐period pricing model is proposed to investigate the effect of conspicuous consumption on pricing decisions with markdown pricing policy for a supply chain that consists of a manufacturer and retailer. The optimal pricing strategies for the integrated supply chain and decentralized supply chain are derived respectively. Our results show that an anticipated conspicuous consumption can benefit the supply chain even though the conspicuous consumption aggravates the double marginalization effect. The conspicuous consumption can serve as a level to segment the market and can promote the supply chain revenue. In addition, our results indicate that the supply chain can benefit from rationing. We also introduce a revenue‐sharing contract and prove that it can be applied to coordinate the supply chain with conspicuous consumption. An interval of the revenue‐sharing rate for coordinating with the supply chain can be coordinated without any additional transfer payment being provided.     

Optimal booking limits in the presence of strategic consumer behavior

We consider a two‐period airline yield management problem where customers may act strategically. Specifically, we allow for the possibility that a customer may decide to defer purchase in the hope that a ticket cheaper than those currently on offer will become available. We also allow for the possibility that some customers will buy a more expensive ticket if the cheaper tickets are not available. We show how to find optimal booking limits in the presence of such strategic customer behavior. We also explicitly incorporate the fact that, once a booking limit has been reached, demand distributions are now censored distributions.     

The impact of consumer behavior on preannounced pricing for a dual‐channel supply chain

This study discusses a dual‐channel supply chain in which a manufacturer sells a regular‐priced product through dual channels in the normal sales period and only sells overstocked products through the direct channel in the discounted sales period in the presence of strategic consumers. The manufacturer acts as a Stackelberg leader to adopt a preannounced pricing policy. This study first proposes demand functions for a two‐period dual‐channel model by incorporating consumer utility functions. Based on the demand functions, optimal pricing strategies for both manufacturer and retailer are established. The results show that the manufacturer prefers to raise prices in both periods for consumers with a short delivery lead time. However, counterintuitively, the selling prices set by the manufacturer do not decrease as the degree of consumer patience increases. Finally, there is a Pareto zone under a certain condition where both the manufacturer and the retailer in the two‐period dual‐channel model outperform their counterparts in terms of profit in the single‐period dual‐channel model.     

Understanding the behavior of mobile data services consumers

Due to rapid advances in the Internet and wireless technologies, a ubiquitous computing world is becoming a reality in the form of mobile computing. At the center of this phenomenon is mobile data services which arise from the convergence of advanced mobile communication technologies with data services. Despite the rapid growth in mobile data services, research into consumers’ usage behavior is scarce. This study attempts to identify and empirically assess the factors that drive consumers’ acceptance of mobile data services. A research model based on the decomposed theory of planned behavior and incorporating factors that represent personal needs and motivations in using mobile data services is presented. The model is tested via an online survey of 811 consumers of four categories of mobile data services (i.e., communications, information content, entertainment, and commercial transactions) associated with different usage contexts. We found that attitude, social influence, media influence, perceived mobility, and perceived monetary value influence consumers’ intention to continue usage of mobile data services. In addition, perceived ease of use, perceived usefulness, and perceived enjoyment influence attitude toward continued usage of mobile data services. Finally, separate analysis of the different categories of mobile data services highlights the influence of individual usage context on consumers’ behavior.

考虑绿色网络效应的再制造产品最优生产决策及产品之间的竞争

提出由两个再制造商组成的环保质量和价格竞争的双寡头博弈模型.在一个再制造市场中,同时考虑消费者环保意识以及包括污染税和回收补贴在内的政府财政政策的情况下,探讨绿色网络效应对生产决策的影响,以期使企业的利润最大化.数值实验表明:高质量(低质量)产品的绿色网络效应系数越高(低),可能会反常地减少(增加)两种产品的环保质量和价格,但会促进(削弱)高质量(低质量)产品的销售和利润,而产品产异性不受影响;此外,相比较没有外部网络性的情况,在绿色网络效应的影响下,回收补贴的增加使得高质量(低质量)产品的需求和利润都得到了一定改善(削弱).结果表明,在最优化条件下,监管者总是可以使企业利润和消费者剩余构成的"经济盈余"最大化,并使排放总量最小化.     

Dynamic pricing and channel efficiency in the presence of the cost learning effect

This paper investigates the impacts of the supply‐side cost learning effect on dynamic pricing strategies and the channel efficiency in a decentralized supply chain consisting of a manufacturer and a retailer. The unit production cost incurred by the manufacturer declines as the cumulative output increases. With the manufacturer being the price leader, the interactions between the two channel members are modeled as a Stackelberg differential game, where the two channel members dynamically set the wholesale and retail prices over time to optimize their respective profits. We find that while the cost learning effect is beneficial to both channel members in terms of long‐term profitability, such an effect is detrimental to the channel inefficiency caused by price double marginalization. In a setting where the manufacturer sells through competing retailers, we show that the channel efficiency can be improved with the emergence of horizontal competition. Our result also indicates that the channel efficiency with a feedback pricing equilibrium is higher than that with an open‐loop equilibrium.     

Assessing the impact of recommender agents on on-line consumer unplanned purchase behavior

Recommendation agents (RAs) have been used by many Internet businesses such as Amazon and Netflix. However, few authors have studied how consumer behavior is affected by those that make suggestions to online consumers based on their recent shopping behavior. Fewer still have examined the role that RAs play in influencing impulse purchasing decisions online. Our study developed a theoretical model to illustrate the impact of RAs on online consumer behavior. The model was tested through an online shopping simulation which used a collaborative filtering based product RA. Particular attention was paid to the effects of an RA on consumer behavior; we found that it increased promotion and product search effectiveness, user satisfaction with the website, and unplanned purchases. Results showed that our model provided insights into the impact of an RA on online consumer behavior and thus provided suggestions for implementing effective systems.     

D-S证据理论在驾驶行为决策中的应用

利用仿生学原理、D-S证据理论、模糊数学知识和产生式规则,研究了一种决策级多传感器信息融合算法。经仿真验证,此算法实时性好,能表示驾驶员的不确定性经验知识,克服其认知局限性,模拟其驾驶行为决策,快速、准确地确定车辆的运行模式,在一个或多个传感器失效的情况下也能保证一定的综合性能,具有良好的容错能力。同时,该研究也为智能车辆自动驾驶系统的仿真及实现提供了基础性理论依据。     

Exploring the Relationship Between Green Consumption Value,Satisfaction, and Loyalty to Hybrid Car in Elderly Consumers

The study aimed to examine the relationship between green consumption value, satisfaction, and loyalty of driving hybrid cars among elderly consumers. Data were collected from a cross‐sectional survey of 314 elderly consumers who purchased hybrid cars in the United States. A partial least squares analysis revealed that elderly consumers’ social, price, and quality values positively influenced the satisfaction of their hybrid car experience, and their satisfaction significantly influenced their loyalty of hybrid car. The relationship between green consumption value, satisfaction, and loyalty toward driving hybrid cars among elderly consumers revealed insight into their value orientations toward the hybrid car. Special efforts are suggested in promoting hybrid car use to elderly consumer groups. Marketers should pay attention to changing beliefs and increasing perceived values of driving a hybrid car for consumers to encourage them to use green products.     

Optimal software pricing in the presence of piracy and word-of-mouth effect

We develop an analytical model that embeds empirical findings on software diffusion to examine optimal pricing strategies for a spreadsheet software product under coalescing effects of piracy and word-of-mouth through its entire life cycle. We find that the demand of the innovators has the most significant impact on the firm's pricing decision. Our research recommends market skimming pricing strategy if innovators' demand is high and the market penetration pricing strategy is preferred otherwise. Surprisingly, the increase of conversion rate of imitators to buyers never significantly alters the pricing strategy pre-determined by the demand of innovators. Most interestingly, the optimal profit from instituting a two prices policy for a software product with five years lifespan outperforms that from a one price policy by no more than 4%, a finding that corroborates the common one price policy observed in reality.     

Reciprocity norms and information-sharing behavior in online consumption communities: An empirical investigation of antecedents and moderators

This study seeks a better understanding of information-sharing behavior in online consumption communities by investigating both the antecedents and moderating mechanisms of such behavior. Using self-reported data collected over two periods, along with objective behavioral data, the authors show that a reciprocity norm functions as a proximal determinant of information-sharing behavior. This norm also channels the effects of social, hedonic, and utilitarian community values on sharing behavior. The results reveal that the conversion of reciprocity norms into information-sharing behavior depends on individual and contextual conditions. These significant insights reflect the integration of consumer resource allocation theory with a reciprocity framework to establish an explanatory platform for members’ information-sharing behavior in online communities. Both theoretical and practical implications are discussed.     

An empirical study of payment technologies,the psychology of consumption,and spending behavior in a retailing context

Our study investigates differences in spending behavior among consumers using three alternative payment technologies: cash, credit cards, and stored value contactless smart cards. We provide a deeper understanding of how different payment mechanisms directly impact consumer spending behavior in a retailing context, their influences on customers’ psychology of consumption, and perceptions of payment technologies. We show that the payment process can do so by significantly affecting the subjective awareness of spending only. In contrast, the source of money can affect perceived payment security only. Both perceived security and convenience have little effect on spending behavior.     

Vertical pricing competition in supply chains: the effect of production experience and coordination

We consider a two‐echelon supply chain consisting of a single supplier (producer) and a retailer. The supplier determines the wholesale price with a production cost decreasing with experience. The retailer orders products from the supplier to meet demands. Negative effects of a vertical competition in static supply chain models are typically attributed to a double marginalization. Using an intertemporal supply chain problem, defined by a differential game, we show that in addition to the “cost” of double marginalization, the margin gained from reducing production costs affects the supply chain performance as well. In our analysis, performance is shown to deteriorate even more than the deterioration observed in static problems with no learning (experience). To improve the performance, we provide a time‐variant version to the well‐known, pure, two‐part tariff strategy, which in its dynamic framework may coordinate the supply chain only partially. Efficient coordination in a supply chain is shown to be possible if a mixed two‐part tariff strategy is employed, however.     

The role of atmospheric cues in online impulse-buying behavior

This study extends a stimulus–organism–response (S–O–R) model to include impulse-buying behavior, which plays a vital role in electronic shopping but has not gained much attention in e-commerce research. Grounding our research in environmental psychology, we test the effects of virtual atmospheric cues on online impulse-buying behavior and spending, via a consumer survey. The study applies elaborated mediating variables (shopping enjoyment and impulsiveness) to develop a structural model linking three categories of atmospheric cues of an electronic store (content, design, and navigation) to approach behavior variables (impulse-buying behavior and expenditure). The results support the validity of the S–O–R model in the context of online impulse-buying behavior and show a significant positive effect of two dimensions of virtual atmospheric cues (design and navigation).     

区块链环境下电商消费者网络多子群混合增长模型构建及特性研究

为探究区块链环境下电商消费者行为的复杂网络特性,在对传统局域网络与BBV增长网络研究的基础上,针对区块链环境下电子商务消费者行为的特性,提出2个方面的创新优化： （1）建立基于声誉的有限信任共识机制; （2）构建基于去中心化特性的消费者社团交互选择的智能合约。将共识机制与智能合约融入多子群混合增长模型中,研究在特定参数下,区块链电商消费者网络在复杂网络结构方面的特性。实证研究表明：即使是在具有去中心化、去信任的区块链电子商务环境下,消费者网络依旧会呈现出节点幂律分布的特点和小世界特性。在多子群混合增长模型中,消费者社团划分明显,消费者之间会出现“富者愈富”的马太效应,但是与传统网络电子商务消费者网络相比,其社团结构则更为松散,具有反垄断的特性。实验表明,在该环境下消费者的消费行为更加自由与透明。     

Modeling default behavior in the presence of information and its application to the route choice problem

A new approach for modeling default behavior is presented and applied to route choice behavior in the presence of information. It is based on the assumption that drivers follow their usual behavior pattern and modify it only if the information received differs substantially from their existing perceptions and knowledge. Default behavior is linked to the interactions between existing knowledge and new information. These interactions are modeled through measures of compatibility, and several measures are suggested and analyzed. The approximate-reasoning model, which was earlier suggested for modeling discrete choices made in the presence of information, is adapted to handle default behavior. The model is briefly presented and its implementation and calibration are discussed. Default behavior is implemented by discounting existing knowledge when it does not agree with the new information, and by discounting the new information when it does not significantly differ from existing knowledge. A small case study is conducted using a driver simulator to collect data from two types of drivers: familiar and unfamiliar. The results obtained provide interesting insights on the choice behavior of the sample population, and support a default type of behavior among the familiar drivers. ©1999 John Wiley & Sons, Inc.     

基于逐渐覆盖的自提点选址模型与算法研究

实践表明自提点类型和自提点覆盖距离影响消费者自提服务的满意度。为解决消费者满意度选址问题,基于逐渐覆盖理论,用凹凸函数刻画消费者的满意度,构建了基于逐渐覆盖的自提点选址模型。根据模型的特点,设计了相应的拉格朗日松弛算法。最后,运用大量的随机算例进行计算,并与传统覆盖模型的选址结果进行了比较。算例分析结果揭示了所构建的模型和算法在自提点选址决策中的有效性。     

A Dominance-based Rough Set Approach to customer behavior in the airline market

Market segmentation is a crucial activity in the present business environment. Data mining is a useful tool for identifying customer behavior patterns in large amounts of data. This information can then be used to help with decision-making in areas such as the airline market. In this study, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining customer attitudes and loyalties, which can help managers develop strategies to acquire new customers and retain highly valued ones. A set of rules is derived from a large sample of international airline customers, and its predictive ability is evaluated. The results, as compared with those of multiple discriminate analyses, are very encouraging. They prove the usefulness of the proposed method in predicting the behavior of airline customers. This study demonstrates that the DRSA model helps to identify customers, determine their characteristics, and facilitate the development of a marketing strategy.