Group buying (GB) has emerged and evolved into various forms over the past decade. We investigate a distinct form of GB, namely consumer-driven group buying, whereby some consumers form purchase groups to visit stores together and negotiate for discounts. We refer to these consumers as GB consumers that differ from regular consumers who visit stores individually and pay regular prices. Visited by a purchase group, a store has to make an immediate decision to serve their demand in its entirety. Turned down by the first store it visits, the purchase group continues to visit the other store. After accommodating GB demand, the stores use remaining stocks to serve regular consumers. We demonstrate that GB can be a treat to stores that adopt proper policies to utilize it as an instrument to reach consumers. The stores are able to accommodate group demand at a price lower than regular price in most circumstances but still manage to earn stable profits. The presence of regular consumers has a subtle effect on equilibrium formation, by strengthening the stores’ power in negotiating with GB consumers to make group price weakly increase with group size. Moreover, competing stores are able to manipulate the interactions between purchase groups and collectively earn a higher total profit than a monopolist store when GB consumers account for a small fraction of market base and competition is intense.

A novel model for the charging station planning problem of plug-in electric vehicles is proposed in this paper considering the users’ daily travel. With the objective of minimizing the total cost, including the charging stations’ cost (including installing cost and management cost) and the users’ cost (including station access cost and charging cost), the proposed model simultaneously handles the problems where to locate the charging stations and how many chargers to be established in each charging station. Considering that different users may have different perception of station access cost and charging cost, two cases (i.e., homogeneous users and heterogeneous users) are typically investigated. The impacts of different discount rates, operating period of the charging stations, number of electric vehicles and number of charging stations on the location of the charging station are also studied. The simulation results not only show that it is very important to locate the charging stations according to the traveling behavior of users, but also verify the validity of the proposed model.

The development of new technologically advanced products requires the contribution from a range of skills and disciplines, which are often difficult to find within a single company or organization. Requirements establishment practices in Systems Engineering (SE), while ensuring coordination of activities and tasks across the supply network, fall short when it comes to facilitate knowledge sharing and negotiation during early system design. Empirical observations show that when system-level requirements are not available or not mature enough, engineers dealing with the development of long lead-time sub-systems tend to target local optima, rather than opening up the design space. This phenomenon causes design teams to generate solutions that do not embody the best possible configuration for the overall system. The aim of this paper is to show how methodologies for value-driven design may address this issue, facilitating early stage design iterations and the resolution of early stage design trade-offs. The paper describes how such methodologies may help gathering and dispatching relevant knowledge about the ‘design intent’ of a system to the cross-functional engineering teams, so to facilitate a more concurrent process for requirement elicitation in SE. The paper also describes EVOKE (Early Value Oriented design exploration with KnowledgE maturity), a concept selection method that allows benchmarking design options at sub-system level on the base of value-related information communicated by the system integrators. The use of EVOKE is exemplified in an industrial case study related to the design of an aero-engine component. EVOKE’s ability to raise awareness on the value contribution of early stage design concepts in the SE process has been further verified with industrial practitioners in ad-hoc design episodes.

An emerging business model increasingly used by companies in the online software market is to provide both a free basic version and a paid premium version for a service or a product to customers. Such a setting is often called freemium model. The existence of the free version can reduce the customer uncertainty regarding the evaluation of the commercial software and make use of network effect to improve the firm’s profit. However, the freemium model may also have the cannibalization effect which can hurt the profit. Hence, the firm needs to determine the optimal content for the free version and the optimal price for the premium version to maximize its profit. In this paper, first, we obtain the optimal decisions of the freemium model and their properties. Second, we compare the freemium model with the traditional charge-for-everything model that all content of the product need to be charged in terms of the profit, customer welfare, and social welfare. The results show that when customer underestimates the value of the software significantly and the true value of the software is high enough, the freemium model can generate higher profit, higher customer welfare, and higher social welfare. Otherwise, the freemium model may not deliver the desired results.

Numerous empirical studies show that advertising effort can stimulate demand in both current and future periods, and there is an interaction between pricing, advertising and ordering decisions. How do these decisions interact with each other and what is the effect of advertising on pricing and ordering decisions? To understand this interaction, we consider a newsvendor-type firm that sells a perishable product in a stable market and dynamically determines the joint ordering, pricing and advertising strategies. The problem is modeled as an infinite horizon newsvendor problem with an advertising carryover effect and price-sensitive demand. We characterize the optimal pricing, advertising and inventory strategies and their comparative statics, and consider how this policy differs from the traditional approach without the advertising effect. We show that the optimal effective advertising level is monotonically increasing with the effective advertising level in the previous period, and hence the optimal strategies (advertising, pricing, inventory level) globally converge to the steady states in the long run. We numerically show that the optimal policy can reap significant profit, which underscores the importance of the advertising-driven ordering and pricing strategies.