Selling Virtual Items in Free-to-Play Games: Transparent Selling vs. Opaque Selling

The market for online games is huge, but research on the economics of online game operations remains nascent. In this paper, we focus on “free-to-play” online games in which a game provider offers players an option to purchase game-specific virtual goods (items) for improving their winning chances before the game begins. Because selling virtual items is the main revenue stream in free-to-play games, it is important for game providers to find ways to entice players to purchase virtual items. We observe that some game providers disclose the opponent’s skill level before the game begins by using a “transparent selling” mechanism to sell virtual items, whereas others conceal this information from the players. This observation motivates us to examine whether and when game providers should adopt transparent selling. By analyzing a game-theoretical model that involves one game provider and two competitive players, we obtain the following results. First, when the price of the virtual goods is endogenously determined by the game provider, we find that transparent selling is not effective: it is optimal for the provider to adopt “opaque selling” by concealing the opponent’s skill level information from players. However, opaque selling hurts the player’s welfare. Second, when the selling price is exogenously given, transparent selling dominates opaque selling when the given price is high. Our results identify the conditions under which transparent selling dominates opaque selling.

Sustainable Supply Chain Decisions under E-Commerce Platform Marketplace with Competition

Motivated by the industrial observation that the e-commerce platform marketplaces (e.g., Amazon) are increasingly launching sustainable strategies, this study aims to build an analytical framework to guide managers on making sustainable decisions. This study builds a stylized game-theoretical model in the sustainable supply chain context, where the competitive traditional product manufacturers sell their products through the platform’s marketplace, while the platform decides whether to introduce the green products and the pricing strategy. We find that, when the evaluation difference for the green product is sufficiently low, the introduction of the green product by the platform benefits the manufacturers (or third-party sellers). Interestingly, a higher platform fee makes a higher likelihood of a win-win situation between the platform and manufacturers. Moreover, when consumers value green products sufficiently higher than traditional products, the traditional products’ manufacturers can also benefit from the green product entry.

Influence network design via multi-level optimization considering boundedly rational user behaviours in social media networks

Social media networks have been playing an increasingly more important role for both socialization and information diffusion. Political campaign can gain more supporters by attracting more mass attention and influencing them directly, while commercial campaigns can increase their companies’ profits by expanding social media connection with new users. To build the optimal network structure to influence the whole, this paper studies mathematical models to simulate the users’ behaviours interacting with others in the information provider’s network. The behaviours of concerns include information re-posting and following/unfollowing other users. Linear threshold propagation model is used to determine the re-posting actions, Boundedly Rational User Equilibrium (BRUE) models are used to determine the following or unfollowing actions. Hence, the topology of the network changes and depends on the information provider’s plan to post various kinds of information. A three-level optimization model is proposed to maximize total number of connections, the goal of the top level. The second level simulates user behaviours under BRUE. The third level maximizes the each user’s utility defined in the second level. This paper solves this problem using exact algorithms for a small-scale synthetic network. For a large-scale problem, this paper uses heuristic algorithms based on large neighbourhood search. This paper also discusses possible reasons why the BRUE model may be a more accurate simulation of users’ actions compared to game theory. Comparisons from the BRUE model to game theoretical model show that the BRUE model performs significantly better than game theoretical model.

Impact of time pressure on software quality: A laboratory experiment on a game-theoretical model

Research suggests the relationship between time pressure and software quality to be more complex than presumed. While software developers can adjust their output to improve observed performance at the expense of software quality, the latter has been found to increase with time pressure in case of work-pace dependent incentives. An untested, but widely disseminated game-theoretical model seeks to resolve this contradiction and hypothesizes that high rates of time pressure avoid so-called ‘shortcuts’, which occur in the form of imperfections induced by developers to meet unrealistically tight deadlines. We conduct two laboratory experiments to empirically test this model for the first time. Our results corroborate the model with regard to its suggestion that shortcuts can be reduced if developers perceive unrealistic deadlines as ever-present. However, we also show that the actual critical probability of unrealistic deadlines–the point at which shortcut taking is drastically reduced–is above the theoretical one. Although final conclusions on the impact of time pressure on software quality remain to be drawn, our results suggest that–considering the contingencies of our study–time pressure helps in striving for quality in software projects.