Efficient advert assignment

We develop a framework for the analysis of large-scale ad auctions where adverts are assigned over a continuum of search types. For this pay-per-click market, we provide an efficient mechanism that maximizes social welfare. In particular, we show that the social welfare optimization can be solved in separate optimizations conducted on the time scales relevant to the search platform and advertisers. Here, on each search occurrence, the platform solves an assignment problem and, on a slower time scale, each advertiser submits a bid that matches its demand for click-throughs with supply. Importantly, knowledge of global parameters, such as the distribution of search terms, is not required when separating the problem in this way. Exploiting the information asymmetry between the platform and advertiser, we describe a simple mechanism that incentivizes truthful bidding, has a unique Nash equilibrium that is socially optimal, and thus implements our decomposition. Further, we consider models where advertisers adapt their bids smoothly over time and prove convergence to the solution that maximizes social welfare. Finally, we describe several extensions that illustrate the flexibility and tractability of our framework.The research of Neil Walton was funded by the VENI research programme, which is financed by the Netherlands Organisation for Scientific Research (NWO)

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p

Incentivized optimal advert assignment via utility decomposition

We consider a large-scale Ad-auction where adverts are assigned over a potentially infinite number of searches. We capture the intrinsic asymmetries in information between advertisers, the advert platform and the space of searches: advertisers know and can optimize the average performance of their advertisement campaign; the platform knows and can optimize on each search instance; and, neither party knows the distribution of the infinite number of searches that can occur. We look at maximizing the aggregate utility of the click-through rates of advertisers subject to the matching constraints of online ad allocation. We show that this optimization can be decomposed into subproblems, which occur on timescales relevant to the platform or the advertisers respectively. The interpretation of the subproblems is that advertisers choose prices which are optimal given the average click-through rate they receive, that the platform allocates adverts according to a classical assignment problem per search impression and that prices satisfy a nominal complementary slackness condition. We then place this optimization result in a game-theoretic framework by assuming that advertisers bid strategically to maximize their net benefit. In this setting, we construct a mechanism with a unique Nash equilibrium that achieves the decomposition just described, and thus maximizes aggregate utility. This simple and implementable mechanism is as follows. When a search occurs, the platform allocates advertisement slots in order to maximize the expected bid from a click-throughs - this is a classical assignment problem. If an advert receives a click, the platform then solves the assignment problem a second time with the advertiser's bid replaced by a bid which is uniformly distributed between zero and the original bid. The advertiser is then charged their bid minus a rebate. The rebate is the product of the advertiser's bid and ratio of the advertiser's click-through rate in the second assignment calculation (after a click-through) to the first assignment click-through rate (before the click-through). We demonstrate that, under the assignment and pricing mechanism just described, advertisers bidding strategically will maximize aggregate utility. The novelty of the mechanism just described is that, while maximizing utilitarian objective, it can be implemented by the platform in a strategic environment on the time-scales relevant to the platform (per-impression) and advertiser (on-average) respectively, and neither party requires information on the distribution of searches. We also show that dynamic models, where advertisers adapt their bids smoothly over time, will converge to the solution that maximizes aggregate utility

Towards Consumer 4.0 Insights and Opportunities under the Marketing 4.0 Scenario

This Research Topic is a sequel to our previous Research Topic “From Consumer Experience to Affective Loyalty: Challenges and Prospects in the Psychology of Consumer Behavior 3.0”. This first article collection was devoted to analyze the changes that appeared in different industries and companies, fostered by factors mainly related to the development of technologies. The evolution from consumer 3.0 to consumer 4.0 represents an opportunity to feature the changes that have been occurring lately as well as to gain an insight into the future of consumer behavior. Nowadays, the markets are experiencing several transformations in consumer behavior. These changes have been fueled by several trends: processes of globalization that produced an extraordinary assortment of diverse products and brand alternatives, new business models based on the intensive use of technology advances in communication and mobile technologies that allow customers’ capacity to easily participating in co-creation processes with companies; and big data developments. In this scenario, customers acquired more power than ever before due to their availability of information required to choose among the better priced alternatives product-brand options, as well as the technological means to access to such alternatives. Thus, customers evolved from a position to simply receiving the offer proposed by companies, to a position of power where they had the last word in the decision process, that is, the position of consumer 3.0. These consumers were characterized by their ability to adopt and use new technologies to meet their individual needs. What is more, these types of consumers did not longer easily respond to traditional mass marketing techniques. Instead, this generation of consumers demanded a highly customized approach across all facets of businesses including new product development, communication and customer service, among others. Nevertheless, in the advent of Marketing 4.0, a new type of consumer is observed, namely the customer 4.0. The transition from consumer 3.0 to consumer 4.0 is becoming evident, not only in consumers’ behavior but also in companies’ behavior. Related to the first one, consumers 4.0 are hyper-connected through different technologies, including not only the well-known mobile or digital technologies, but also other type of technologies, such as IoT, nanotech or artificial intelligence. Hence, their behavior is characterized by the demand of technology that have integrated the facets of Marketing 4.0 such as geolocation, marketing virtual and augmented reality facets. Regarding the second one, companies should face a digital transformation affecting not only value areas, but also, the way business interact with the environment. In particular, companies need to incorporate systems and applications that allow them to collect and analyze information, while helping decision making, since in the long run these issues constitute the cornerstone on which to start building a successful marketing strategy 4.0. This Research Topic welcomes scientific papers that covers the following topics (but not limited exclusively): - Consumers’ 4.0. behavior in different countries, industries, products, brands, etc.; - Digital transformations of industries and companies due to new consumption patterns; - New devices launched by companies work to meet the demands of consumer 4.0 (e.g., IoT), as well as the use consumers make of such devices; - The latest technology trends in business areas that make easier the consumer-companies relationships (processing, communication or any other digital technologies)

Sustainable Economic Development

This book is a pivotal publication that addresses the contemporary challenges of globalization and elaborate policy responses to environmental pollution, climate change, economic disruptions, poverty, hunger, and other threats to sustainable economic development. Many parts of the world, territories, and societies are now changing at an unprecedented pace in ways that fundamentally affect the markets, people, the environment, and biodiversity. Such changes are primarily driven by rapid social and economic developments, economic disparities between countries, the internationalization of production and value chains, and industrialization. Increasingly frequently, business interests are interfering with sustainable development goals. The issue is how to converge the economic benefits with the urgent need for establishing resilient production chains, social networks, sustainably-operating markets, and environmental protection. This publication highlights the need for the balanced economic development and comprehensive coverage of many sustainability–business areas. Economic, production, financial, and social factors of sustainability are discussed by over 90 contributors representing 40 universities and research institutions from seven countries. Their findings are translated into workable approaches and policies for the benefit of the global economy, people, and the environment

An aesthetic for sustainable interactions in product-service systems?

Copyright @ 2012 Greenleaf PublishingEco-efficient Product-Service System (PSS) innovations represent a promising approach to sustainability. However the application of this concept is still very limited because its implementation and diffusion is hindered by several barriers (cultural, corporate and regulative ones). The paper investigates the barriers that affect the attractiveness and acceptation of eco-efficient PSS alternatives, and opens the debate on the aesthetic of eco-efficient PSS, and the way in which aesthetic could enhance some specific inner qualities of this kinds of innovations. Integrating insights from semiotics, the paper outlines some first research hypothesis on how the aesthetic elements of an eco-efficient PSS could facilitate user attraction, acceptation and satisfaction

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

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