Experimental Evaluation of Sponsored Search Auction Mechanisms

The theory of sponsored search has been developing rapidly although with disagreement in scientific circles on answers to some basic questions about sponsored search. This study focuses on two of these questions, namely, if a search engine seeks to maximize profits, 1) what should its pricing policy be and 2) what should its ranking policy be. This paper uses experiments with economically motivated human subjects to address these questions. We evaluate six different sponsored search auction formats with two different pricing policies (Pay-per-transaction & Pay-per-click) and three different ranking policies (Rank by relevance, Rank by click-through rate, & Rank by both relevance and click-through rate). Our results suggest that Pay-per-click is superior and the reason behind its superiority is behavioral in nature whereas the ranking policy has significant effect on search engine revenue and advertiser profit

The Citizen Participation Continuum: Where does the US Stand?

Active citizen participation facilitated by information technology can have profound implications for democracy and civic discourse. In this paper we describe a continuum of tools that encourage active participation by citizens. We use a comprehensive review of the web-sites of the 50 States of the U.S. to chart the current position of the country on this continuum. We find that these G2C initiatives provide some tools for passive citizen participation (e.g. on-line feedback) but ignore two important tools for active citizen participation (electronic voting and discussion forums). The lack of discussion forums is especially surprising since they are a low cost scalable tool for fostering deliberation and works equally well under both representational and direct democracy systems. In conclusion, the paper discusses the future implications of the participation continuum

Buyers’ Dynamic Click Behavior on Digital Sales Platforms with Complementarities

With numerous options available on digital platforms, buying products is becoming an increasingly complex decision-making task. Many well-known digital sales platforms like Amazon, Uber, Etsy, or Airbnb try to offer products or services that best match the buyers’ search criteria but Amazon for example often also lists products that can possibly complement the best match (Sloane, 2018). Buyers have access to product and price information, and they have to consider multiple factors in making their decisions on checking available options (Karimi et al., 2015). The buyer needs to know how the platform chooses which products or services to display. The buyers’ decision might also be impacted by the way sellers of products are charged to display their products or services on the platform and by the order in which the products are displayed on the screen. Buyers have to keep track of the prices and deals offered related to the various products they have checked on the platform and also consider their opportunity cost of search. As the complexity and cost of the search process increases, there are searches that often end without success. Understanding better how buyers make click decisions dynamically can help platforms increase the success of product searches, buyer satisfaction and ultimately, profitability. In this study we focus on platforms which offer both primary products (products who best match the buyers’ search criteria) and secondary products (products who complement the primary products) and they rank these products on a buyer’s screen either by relevance or by click-through rate ((Hao et al., 2020). We aim to find answer to the following question: To what extent do product values and product prices determine the order in which the buyer clicks through the primary and secondary products. To answer this question, we create a dynamic model that predicts each step in a buyer’s click strategy. The model incorporates rational decision-making as well as known behavioral biases. Under naturally occurring circumstances information, such as the value of a product to a buyer, is strictly private and unavailable. Therefore, we use lab experiments with human subjects to test our model. The model is able to predict a higher percentage of buyer click behavior than existing static search models. Unlike static search models our model predicts a non-zero percentage of clicks on more than two products and provides some guidance on the factors that can lead buyers to make that decision. This study contributes to the theory of shopping on digital platforms because it is a model of sequential search that incorporates rational decision making as well as known human behavioral biases to explain how buyers shop in sequence given the information they discover. As far as we know this is also the first dynamic model that incorporates product complementarities as part of the decision-making environment

on the efficiency of team-based meritocracies

According to theory a pure meritocracy is efficient because individual members are competitively rewarded according to their individual contributions to society. However, purely individually based meritocracies seldom occur. We introduce a new model of social production called “team-based meritocracy” (TBM) in which individual members are rewarded based on their team membership. We demonstrate that as long as such team membership is both mobile and competitively based on contributions, individuals are able to tacitly coordinate a complex and counterintuitive asymmetric equilibrium that is close to Pareto-optimal, possibly indicating that such a group-based meritocracy could be a social structure to which humans respond with particular ease. Our findings are relevant to many contemporary societies in which rewards are at least in part determined via membership in organizations such as for example firms, and organizational membership is increasingly determined by contribution rather than privilege.social stratification, meritocracies, mechanism design, non-cooperative games, experiment, team production

Experimental Evaluation of Different Pricing Mechanisms for Content Distribution over Peer to Peer Networks

This paper extends previous work by the authors in which they propose a dynamic distribution model based on modified economic growth theory to determine file distribution patterns in peer-to-peer networks. Although the theoretical model provides a good foundation for exploring different pricing mechanisms for peer-to-peer networks, there are several issues that remain unexplored because of computational difficulties. In this paper, we use the methods of experimental economics to create a sequence of experimental designs to explore some of these issues. The designs mimic the structure of the industry, the type of current and future property rights, some technical constraints, and the strategic interactions between the different actors

A Market-Based Approach to Facilitate the Organizational Adoption of Software Component Reuse Strategies

Despite the theoretical benefits of software component reuse (and the abundance of component-based software development on the vendor side), the adoption of component reuse strategies at the organizational level (on the client side) remains low in practice. According to research, the main barrier to advancing component-based reuse strategies into a robust industrial process is coordination failures between software producers and their customers, which result in high acquisition costs for customers. We introduce a component reuse licensing model and combine it with a dynamic price discovery mechanism to better coordinate producers’ capabilities and customer needs. Using an economic experiment with 28 IT professionals, we investigate the extent to which organizations may be able to leverage component reuse for performance improvements. Our findings suggest that implementing component reuse can assist organizations in addressing the issue of coordination failure with software producers while also lowering acquisition costs. We argue that similar designs can be deployed in practice and deliver benefits to software development in organizations and the software industry

Strategy Dynamics in Markets of Software Components

In this paper we propose a dynamic model of a software market for component reuse. We investigate the market dynamics using experiments with economically motivated human subjects. Our results suggest that the introduction of the software component market reduces production costs and increases vendor profits. The dynamic interactions in the component market helped vendors coordinate better their production decisions and resulted in production cost savings. The component market can thrive on a balance between competition and cooperation of software vendors. These experimental results could be applied with some modifications to the development of software products in general

Consumer Co-creation of Digital Culture Products: Business Threat or New Opportunity?

New forms of implicit consumer collaborations in online communities and social networks influence demand preferences as consumers themselves increasingly participate in creating cultural products that both complements and competes with firm offerings. Although research findings on these issues vary, strong evidence from both theoretical and empirical work suggests that the increased technology affordance on the consumer side challenges the profitability of conventional producer strategies that are based on pushing product designs that serve large segments of consumers while ignoring the service of more nuanced consumer preferences. In this study, we present a market design in which producers create and sell original digital culture product and, examine the effect of consumer co-creation in the presence of consumer sharing (piracy) on market performance in terms of consumer and producer surplus and consumer choice. Using the methods of experimental economics, we find strong interaction effects between consumer sharing and co-creation, and, more specifically, we find that consumer sharing interacts with consumer-based co-creation and increases product variety and consumer surplus while reducing producer benefits from co-creation

Fire effects in a landscape of fear

Context: A major effect of climatic change is the global increase in forest fires, which potentially creates an increase in food availability for herbivorous species. Also vegetation density and the numbers of tree logs increase in burned sites, and this is thought to influence the perceived risk of herbivore prey species, which affects their anti‐predator behaviour and thereby the patch utilization. This cascading effect of forest fires might have implications on future ecosystem functioning in the burned area, and more knowledge about the effects of landscape features on predator‐prey interactions is needed to adapt conservation and wildlife management policies, to the changing climate. Aim: This study aims to gain insight into how varying food availability, visibility and escape impediments in burned and unburned forest sites, influence patch utilization by two herbivore species, mountain hare (Lepus timidus) and moose (Alces alces). I predicted that i) animals that are under high predation pressure will have a higher utilization of ‘save’ patches in the control sites where perceived risk is lower, and that ii) animals that experience no or low predation pressure will have a higher patch utilization in the burned areas where food availability is high. Methods: I tested these predictions by conducting a correlative cross‐sectional study in three different boreal forests in the north of Sweden, each with a burned site that burned in 2006 and an equal sized unburned control site. The herbivore community there is predominantly comprised of moose and mountain hare. Measurements on species passage rates and the time they spend in front of the camera are derived from footage obtained from remotely triggered cameras with a PIR sensor. Data on food availability, visibility and number of tree logs and other plot characteristics are collected by taking field measurements around each camera trap. I tested the relations between these variables using a multiple regression analysis with zero‐inflated generalized linear models. Results & discussion: In two of the three areas I did not find a difference in patch utilization between the burned and the control site for mountain hare. In one area there even was a significantly higher patch utilization in the burned site instead of the control, and this made sense since mountain hare utilization was positively correlated to the number of tree logs in two of the three areas. The positive correlation of tree logs could be explained by the fact that birds of prey are a dominant predator for mountain hare, in which case tree logs provide cover for the hares instead of increasing their perceived predation risk. For moose there was no significant difference in utilization between the burned and control site per area. However, in the areas with the highest number of moose passages the difference was almost significant. In this area the multiple regression model also showed the predicted positive correlation of patch utilization and food availability. Conclusions: I conclude from the reflections on the results for mountain hare, that depending on the composition of the predator community, the landscape features will have a different effect on the patch utilization of the prey species. In a study area with many different predator types present, it is difficult to find strong correlations between the landscape features and patch utilization, since these features are ambiguous in their effect on perceived predation risk. Therefore, on the basis this study, it remains difficult to draw clear conclusions about the actual effects of forest fires on predator‐prey interactions, since they are very predator specific. For moose it seems plausible that their patch utilization is indeed predicted by food availability, but that this correlation was not found two of the three areas because of the lack of data points there and/or the possible inaccurate proxy for food availability that was used in this study