Group-buying Mechanism Research Articles

Group buying vs individual buying; a competitive approach for two retailers

Development of technology and expansion of social media emerge group-buying mechanism as a popular strategy. In this paper, two competitive retailers are considered that sell the same product to customer in a market, Group buying and individual buying. Three Different competition scenarios are considered, in order to implement the first two strategies, the Stackelberg model is used where the group-buying retailer and the Individual retailer are assumed to be the leader and follower, respectively. For the third strategy, the Nash equilibrium is applied when they decide separately. We analysis the optimal and equilibrium strategy in each scenario. And also determine the conditions for each retailer to be present in the market in each scenarios. Finally, a numerical example is provided, in order to illustrate the effectiveness of the aforementioned three scenarios in models.

Context-Aware Group Buying in Ultra-Dense Small Cell Networks: Unity Is Strength

The ultra-dense small cell networks (SCNs) have been regarded as a promising technology to solve the data traffic explosion in future. However, the complicated relationships among large scale users and cells practically demand a cooperative grouping mechanism to account for the shortage of resources in SCNs. Then, a group buying market mechanism provides a win-win situation and an effective resource allocation in the view of economics. With additional decision information being provided, the context awareness enhances and improves the group buying mechanism. In this article, we propose a Context-Aware Group Buying (CAGB) mechanism to allocate the resources in ultra-dense SCNs. The feasibility, necessity, and effectiveness of CAGB are analyzed first. Then, we introduce the group buying mechanism and some common context awareness. The relationship between context awareness and group buying is also analyzed. Some important technologies in SCNs are discussed in the view of CAGB, such as load balancing, spectrum management, and cooperative caching. Then, the graphical coalition formation games (CFGs) of CAGB are also presented to match the complicated network topologies in SCNs. Two CAGB-based use cases about spectrum market and cooperative caching are presented. Finally, future research issues about context awareness, grouping mechanism, and buying mechanism are discussed.

Consumer Equilibrium, Demand Effects, and Efficiency in Group Buying

Group buying events, in which the unit price for a good or service declines with higher number of customer sign ups, are increasingly becoming popular for retailing goods and services, especially in emerging markets. This paper theoretically and empirically studies consumer equilibrium, pricing, and efficiency of these events. Modeling a continuous time customer arrival and sign-up process, we start by deriving the stochastic dynamic consumer equilibrium. Based on this equilibrium and utilizing sign-up level data from a major Chinese retailer's group buying events, we then structurally estimate consumer arrival rates and utility distributions for 266 events, and empirically verify the fit and predictive power of the model. Utilizing the estimated arrival rates and consumer utility distributions, we then employ a doubly stochastic two-stage Generalized Linear Regression Model to provide empirical evidence for consumer network effects in group buying, and estimate 16.6% increase in consumer demand attributable to the employment of a group buying mechanism. Through counterfactual analysis, we further estimate that employing group buying increased retailer profits by 11.1%, and with better price and discount selections, it can improve profits by more than 30% on average. We further demonstrate that the retailer is better off by setting low deal discounts for very low and very high consumer arrival rates, suggesting that a bell-shaped deal discount pattern as a function of consumer arrival rate is recommendable when employing group buying events.

Allocation and pricing of group-buying based on the fixed bidding

Online group-buying is a popular business mode based on Internet. Group-buying websites can get discount for goods or services through promotion and other means which used to gather enough number of people, and sellers can also sell more quantities of goods. However, the existing group-buying mode is that all buyers unify the fixed pricing, the mechanism cannot distinguish the contribution of different buyers and motivate buyers report truthfully. In this paper, an online group-buying pricing method based on buyer’s fixed bidding is proposed in view of the influence of buyer’s bidding price and demand quantity on the participants’ group in the group-buying mechanism. We introduce the concept of relative importance to the allocation and pricing of mechanisms and propose a new mechanism named Fixed bids Truthful Mechanism for Group Buying (FTM4GB) based on correlation importance. At the end of the paper, we prove the economic attributes of individual rationality, incentive compatibility and budget balance.

Context Awareness Group Buying in D2D Networks: A Coalition Formation Game-Theoretic Approach

In this paper, we proposed a context-aware group buying mechanism to reduce users’ data cost based on the content similarity. Each user's cost is formulated as the combination of the content-aware data cost and location-aware sharing cost. Data cost is the payoff of the spectrum owner's channel to download files and sharing cost is the energy and time cost in transmitting files among the coalition. Compared with downloading data alone, users would like to form different groups and download the traffic data first and then share data among the group to achieve a lower cost. The cost reducing problem through group buying mechanism is modeled as a coalition formation game (CFG). Besides the traditional Pareto order, a coalition order maximizing the coalition's benefit and a selfish order maximizing users’ benefit are proposed. The CFGs with the two proposed orders are proved to be potential games, respectively, and the existence of the stable coalition partitions are also guaranteed by Nash equilibria. A cooperative exchange mechanism is designed, where users can make decisions cooperatively to achieve better performance. Simulation results show that the context awareness group buying reduces the cost and improves the benefit significantly compared with the situation without context awareness. The proposed orders both have better performance than the Pareto order.

Efficient three-stage auction schemes for cloudlets deployment in wireless access network

Cloudlet deployment and resource allocation for mobile users (MUs) have been extensively studied in existing works for computation resource scarcity. However, most of them failed to jointly consider the two techniques together, and the selfishness of cloudlet and access point (AP) are ignored. Inspired by the group-buying mechanism, this paper proposes three-stage auction schemes by combining cloudlet placement and resource assignment, to improve the social welfare subject to the economic properties. We first divide all MUs into some small groups according to the associated APs. Then the MUs in same group can trade with cloudlets in a group-buying way through the APs. Finally, the MUs pay for the cloudlets if they are the winners in the auction scheme. We prove that our auction schemes can work in polynomial time. We also provide the proofs for economic properties in theory. For the purpose of performance comparison, we compare the proposed schemes with HAF, which is a centralized cloudlet placement scheme without auction. Numerical results confirm the correctness and efficiency of the proposed schemes.

Group‐buying coupons considering consumers’ perceived ease of use

AbstractThis paper examines the design of the online discount coupon, which is a popular marketing tool that offers consumers group‐buying (GB) discounts when they prepay for participating firms’ goods and services. We develop a two‐stage model for a market in which consumers are heterogeneous in their valuation of a product. In our setup, consumers make purchase decisions at the first stage and update their perceptions of the product. As a result, they adjust their repurchase decisions at the second stage. Through the analysis of price discrimination effect and advertising effect, we demonstrate that consumers make their purchase decisions based on not only the discount rate but also the degree of perceived ease of use of the coupons. We then examine both single‐time and double‐time GB mechanisms, and recommend the optimal design for the firm to increase its profitability. Our model also accommodates uncertainty of the degree of consumers' perceived ease of use and shows that the conditions for the optimal GB mechanism are robust.

Cocoa

Although the Infrastructure-as-a-Service (IaaS) cloud offers diverse instance types to users, a significant portion of cloud users, especially those with small and short demands, cannot find an instance type that exactly fits their needs or fully utilize purchased instance-hours. In the meantime, cloud service providers are also faced with the challenge to consolidate small, short jobs, which exhibit strong dynamics, to effectively improve resource utilization. To handle such inefficiencies and improve cloud resource utilization, we propose Cocoa (COmputing in COntAiners) , a novel group buying mechanism that organizes jobs with complementary resource demands into groups and allocates them to group buying deals predefined by cloud providers. Each group buying deal offers a resource pool for all the jobs in the deal, which can be implemented as either a virtual machine or a physical server. By running each user job on a virtualized container, our mechanism allows flexible resource sharing among different users in the same group buying deal, while improving resource utilization for cloud providers. To organize jobs with varied resource demands and durations into groups, we model the initial static group organization as a variable-sized vector bin packing problem, and the subsequent dynamic group organization problem as an online multidimensional knapsack problem. Through extensive simulations driven by a large amount of real usage traces from a Google cluster, we evaluate the potential cost reduction achieved by Cocoa . We show that through the effective combination and interaction of the proposed static and dynamic group organization strategies, Cocoa greatly outperforms the existing cloud workload consolidation mechanism, substantiating the feasibility of group buying in cloud computing.

A group-buying mechanism for considering strategic consumer behavior

This study investigates a group-buying mechanism that considers strategic consumer behavior. In a market that consists of three types of consumers, the seller offers a product via two channels--spo...

Group-buying and channel coordination under asymmetric information

Social media and improvements in technology allow retailers to offer a group-buying option to consumers in a variety of markets. Extant research shows that when consumers are sufficiently heterogeneous, group-buying helps a retailer practice price discrimination. Our paper examines when a manufacturer may prefer its reseller to employ the group-buying mechanism in conjunction with a traditional posted price. In our model, the retailer is privately informed about market heterogeneity, which is summarized via the relative size and the level of price sensitivity of two consumer segments. We show that any value to the manufacturer, of requiring the retailer to offer group-buying, revolves around how profitability varies with market heterogeneity. Our principal finding is that group-buying benefits the manufacturer more when the retailer is privately informed about market size than about the level of consumer price sensitivity.

Optimal decisions for fixed-price group-buying business originated in China: a game theoretic perspective

In this paper, we study a new group-buying mechanism originated in China where the new mechanism adopts a fixed group price rather than a dynamic pricing mechanism. We employ a sensitive parameter , reflecting the initial customer’s seeking and communication cost and formulate this new group-buying business as a game model. First, we formulate the basic model as a Stackelberg game where the website is the leader and the seller is the follower. Our result shows that the group-buying mechanism is more efficient when the value of is smaller, and there is also an upper bound for to adopt group-buying mechanism. Second, we establish three other group-buying game structures by considering different market power between the website and the seller. By comparing the maximum revenues and optimal decisions obtained under different market structures, some interesting and valuable managerial insights are established such that when to adopt a group-buying mechanism or a non-group-buying mechanism and how to make a decision optimally based on adopted mechanism.

The informational aspect of the group-buying mechanism

This paper studies the group-buying mechanism from a dynamic perspective. We consider a seller that offers a product in the form of group buying (priced low but uncertain) and spot purchasing (priced high but guaranteed). In the case of group buying, the information associated with the number of participating customers is updated in the middle of the sale. Customers are assumed to be strategic with a time-dependent utility. In addition to choosing between spot purchasing and group buying, customers could choose to delay their decisions until the information update. We characterize the customer behavior within a rational expectations framework. We then consider the effect of information and demand dynamics. Our results show that whereas an improvement in information quality has a positive effect on customer surplus and the group-buying success rate, the effect of inter-temporal demand correlation is mixed. We also discuss the seller’s profit maximization problem and derive the condition to be satisfied at the optimal group size.

Re-examining the revival of online group buying mechanisms

In commercial environments consumers with limited order size can aggregate their demand through a group buying mechanism allowing them to enjoy the benefits of a wholesale deal. In electronic commerce, group buying was first introduced in the late 90s. Researchers in various fields conducted studies showing the business viability of the group buying model and it was even regarded as the shopping method for the 21st century. However, web-based group buying did not live up to its initial expectations and experienced an early fall down. In this paper, we provide an evaluation of some of the work carried out on group buying and an analysis of the group buying business model. Moreover, we examine a number of important trends in e-Commerce from a group buying perspective. Based on this analysis, we derive a set of conclusions regarding the re-introduction of the group buying model to the electronic marketplace. Key words: Electronic commerce, group buying, customer coalition formation, group management, demand aggregation mechanisms

An innovative electronic group-buying system for mobile commerce

With the benefits of discount and convenience, the group-buying mechanism has become a popular commerce service. Nevertheless, there exist several drawbacks in current group-buying systems. First, the absence of security consideration may reveal the privacy of involved participants. Moreover, buyers must pay money to the initiator in advance. Without a trusted third party to monitor the purchase, the initiator may vanish after collecting the money. To mitigate the risk of the above weaknesses, we propose a new mechanism introducing a group-buying server to secure and monitor the transaction. Because the server acts as a mediator, it can help the buyer and vender to negotiate with each other through a secure channel. Mutual authentication between the buyer and vender is guaranteed under the BAN logic model. In particular, we employ the Bloom filter and XOR operation to reduce the size of the transaction table and the computational cost. Thus, the new method can be implemented in mobile devices.

Inventory rationing with multiple demand classes: The case of group buying

Web-based group buying is practised in many businesses nowadays. Noting that the group-buying mechanism is often used with traditional selling methods, this paper develops models in which sellers provide customers with a group-buying option and a regular spot-selling option. We prove the optimality of a threshold rationing policy. Our findings help those sellers who offer multiple selling options in designing and implementing an efficient demand and inventory management system.