Optimal strategy for selling on group-buying website

Purpose: The purpose of this paper is to help business marketers with offline channels to make decisions on whether to sell through Group-buying (GB) websites and how to set online price with the coordination of maximum deal size on GB websites. Design/methodology/approach: Considering the deal structure of GB websites especially for the service fee and minimum deal size limit required by GB websites, advertising effect of selling on GB websites, and interaction between online and offline markets, an analytical model is built to derive optimal online price and maximum deal size for sellers selling through GB website. This paper aims to answer four research questions: (1) How to make a decision on maximum deal size with coordination of the deal price? (2) Will selling on GB websites always be better than staying with offline channel only? (3) What kind of products is more appropriate to sell on GB website? (4)How could GB website operator induce sellers to offer deep discount in GB deals? Findings and Originality/value: This paper obtains optimal strategies for sellers selling on GB website and finds that: Even if a seller has sufficient capacity, he/she may still set a maximum deal size on the GB deal to take advantage of Advertisement with Limited Availability (ALA) effect; Selling through GB website may not bring a higher profit than selling only through offline channel when a GB site only has a small consumer base and/or if there is a big overlap between the online and offline markets; Low margin products are more suitable for being sold online with ALA strategies (LP-ALA or HP-ALA) than high margin ones; A GB site operator could set a small minimum deal size to induce deep discounts from the sellers selling through GB deals. Research limitations/implications: The present study assumed that the demand function is determinate and linear. It will be interesting to study how stochastic demand and a more general demand function affect the optimal strategies. Practical implications: This paper provides a very useful model framework and optimal strategies for sellers’ selling on GB website. It takes advantage of the analytical model to explain much typical practical phenomenon for E-commerce like free sale with limited availability and so forth. It also helps GB website operator to induce deep discount from sellers. Originality/value: This paper is a first attempt to examine the seller's GB sale decision problem regarding to price and bounds on deal sizes. It analyses how the minimum deal size set by the GB website affect the optimal decision of sellers’. Moreover, it also discusses the impact of the interactions between online and offline markets on sellers’ decisionPeer Reviewe

Online Cooperative Promotion and Cost Sharing Policy under Supply Chain Competition

This paper studies online cooperative promotion and cost sharing decisions in competing supply chains. We consider a model of one B2C e-commerce platform and two supply chains each consisting of a supplier and an online retailer. The problem is studied using a multistage game. Firstly, the e-commerce platform carries out the cooperative promotion and sets the magnitude of markdown (the value of e-coupon). Secondly, each retailer and his supplier determine the fraction of promotional cost sharing when they have different bargaining power. Lastly, the retailers decide whether to participate in the cooperative promotion campaign. We show that the retailers are likely to participate in the promotion if consumers become more price-sensitive. However, it does not imply that the retailers can benefit from the price promotion; the promotion decision game resembles the classical prisoner’s dilemma game. The retailers and suppliers can benefit from the cooperative promotion by designing an appropriate cost sharing contract. For a supply chain, the bargaining power between supplier and retailer, consumer price sensitivity, and competition intensity affect the fraction of the promotional cost sharing. We also find that equilibrium value of e-coupon set by the e-commerce platform is not optimal for all the parties

Customer rebates and retailer incentives in the presence of competition and price discrimination

Promotions are important tools for matching supply and demand in many industries. In the United States automotive industry, promotions are frequently offered, which may be given directly to customers (rebates) or given to dealers (incentives) to stimulate demand. We analyze the performance of customer rebate and retailer incentive promotions under competition. We study a setting with two manufacturers making simultaneous pricing and promotion decisions, and with two price-discriminating retailers as Stackelberg followers making simultaneous order quantity decisions. In the benchmark case with no promotions, we characterize the equilibria in closed form. We find that retailer incentives can be used by manufacturers to simultaneously improve each of their profits but can potentially lead to lower retailer profits. When manufacturers use customer rebates, we show that a manufacturer is able to decrease the profit of her competitor while increasing her own profit, although she is also at risk for her competitor to use rebates in a similar fashion. Unlike the monopoly case where the manufacturers are always better off with retailer incentives, customer rebates can be more profitable under some cases in the presence of competition. Using numerical examples we generate insights on the manufacturers' preference of promotions in different market settings.Retailer incentives Customer rebates Competition Automotive industry First-degree price discrimination

Manufacturing Management and Decision Support using Simulation-based Multi-Objective Optimisation

A majority of the established automotive manufacturers are under severe competitive pressure and their long term economic sustainability is threatened. In particular the transformation towards more CO2-efficient energy sources is a huge financial burden for an already investment capital intensive industry. In addition existing operations urgently need rapid improvement and even more critical is the development of highly productive, efficient and sustainable manufacturing solutions for new and updated products. Simultaneously, a number of severe drawbacks with current improvement methods for industrial production systems have been identified. In summary, variation is not considered sufficient with current analysis methods, tools used are insufficient for revealing enough knowledge to support decisions, procedures for finding optimal solutions are not considered, and information about bottlenecks is often required, but no accurate methods for the identification of bottlenecks are used in practice, because they do not normally generate any improvement actions. Current methods follow a trial-and-error pattern instead of a proactive approach. Decisions are often made directly on the basis of raw static historical data without an awareness of optimal alternatives and their effects. These issues could most likely lead to inadequate production solutions, low effectiveness, and high costs, resulting in poor competitiveness. In order to address the shortcomings of existing methods, a methodology and framework for manufacturing management decision support using simulation-based multi-objective optimisation is proposed. The framework incorporates modelling and the optimisation of production systems, costs, and sustainability. Decision support is created through the extraction of knowledge from optimised data. A novel method and algorithm for the detection of constraints and bottlenecks is proposed as part of the framework. This enables optimal improvement activities with ranking in order of importance can be sought. The new method can achieve a higher improvement rate, when applied to industrial improvement situations, compared to the well-established shifting bottleneck technique. A number of “laboratory” experiments and real-world industrial applications have been conducted in order to explore, develop, and verify the proposed framework. The identified gaps can be addressed with the proposed methodology. By using simulation-based methods, stochastic behaviour and variability is taken into account and knowledge for the creation of decision support is gathered through post-optimality analysis. Several conflicting objectives can be considered simultaneously through the application of multi-objective optimisation, while objectives related to running cost, investments and other sustainability parameters can be included through the use of the new cost and sustainability models introduced. Experiments and tests have been undertaken and have shown that the proposed framework can assist the creation of manufacturing management decision support and that such a methodology can contribute significantly to regaining profitability when applied within the automotive industry. It can be concluded that a proof-of-concept has been rigorously established for the application of the proposed framework on real-world industrial decision-making, in a manufacturing management context.Volvo Car Corporation, Sweden University of Skövde, Swede

Luxury retail brands and their consumers in emerging markets: developing mobile marketing and sustaining the brand value

Understanding an individual’s self-interests remains a challenging task for consumer marketing because brands have no direct access to individual’s inner mind in order to satisfy his or her consumption-related wants, needs and expectations. In the case of luxury brands, customer service experts only seek to maintain close relationships with wealthy and elite customers, and they cannot extend the same individualized services to mass-market consumers. Among the new middle classes in emerging markets, consumers do not have strong brand attachments, but they do have high purchasing power with regard to luxuries. To bridge this gap, mobile technology could be an ideal interface through which luxury brands could enhance interactive communication and engagement with consumers. Nevertheless, research findings have revealed major discrepancies in the adoption of technology. While luxury brands have been ‘slow’ in their adoption of such technologies, consumers have adopted mobile devices as extensions of themselves in the digital world, which greatly enrich their lifestyles. Therefore, a medium should be developed to bridge this gap. The Gearbox of Exchange is proposed to help integrate the consumer’s self-interests with those of luxury brands. Through conditional access with a mutually agreed-upon exchange value to balance privacy concerns and financial risks, the consumer might be willing to share customized information with the brands with which they trust to engage. The luxury brands will benefit from the sharing of this customized information, as they can better predict an individual’s preferences and choices. This virtual engagement will revitalize customization to activate personalized services for every individual. These mutually agreed-upon interactions will develop into a mutual interdependence, a B2B2C relationship. This bond will protect brands from severe competition. More importantly, their knowledge of customized information, which is provided through their direct access to consumers’ self-interests, will fill the black box of radical behaviourism and enhance these brands’ abilities to predict individual choices. Therefore, the knowledge generated from the Gearbox of Exchange will not be meaningless to transform consumer analysis into micro marketing