Inefficiencies in Digital Advertising Markets

Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research

Market Effects of Sponsored Search Auctions

We investigate the market effects of brand search advertising, within a model where two firms simultaneously choose the price of their (differentiated) product and the bids for the advertising auction which is triggered by own and rival’s brand keywords search; and where there exist sophisticated/attentive consumers (who look for any available in-formation on their screen) and naive/inattentive consumers (who only look at the top link of their screen), both aware of either brand’s characteristics and price. Relative to a benchmark where only organic search exists, in any symmetric equilibrium each firm wins its own brand auction, and advertising has detrimental effects on welfare: (i) the sponsored link crowds out the rival’s organic link, thus reducing competition and choice, and leading to price increases; (ii) the payment of the rival’s bid (may) raise marginal cost, also contributing to raise market prices. Under extreme asymmetry (there is an incumbent and an unknown new entrant), we do find that the market effect of brand bidding might be beneficial, if the search engine does not list the entrant’s link in organic search, and the share of the sophisticated consumers in the economy is large enough for an equilibrium in which the entrant wins the advertising auction on the search for the incumbent’s brand to exist

Towards understanding the process of tournament crowdsourcing:the value co-creation perspective

In the contemporary business environment, firms are increasingly moving from creating business value internally to co-creating business value with external stakeholders. Value cocreation refers to the process where a focal firm involves external stakeholders in its previously in-house performed business processes and interacts intensively with each other to create a stream of value. Tournament crowdsourcing, as an application of crowdsourcing, has become an emerging approach for firms to engage with external crowds in pursuit of business value. In the existing Information Systems literature, scholars’ understanding of valueco-creation and crowdsourcing is still at an explorative stage. The process of value co-creation and crowdsourcing have not been extensively studied. In this research, we adopt an interpretive approach and employ multiple-case designs to investigate the process of tournament crowdsourcing through the lens of value co-creation. The findings of this research contribute to the literature on crowdsourcing by 1) introducing the process framework which examines value-generating phases and value propositions from both the perspective of the focal entity and the crowd, 2) revealing the dynamic involvement of the crowd, the process from value creation to value co-creation, and the dynamic value stream, 3) identifying the combined usage of multiple systems and mechanisms for tournament crowdsourcing by contemporary platforms, and potential conflicts related to the governance of the platform,and 4) identifying phases and associated activities relevant to finding the right crowd members from the perspective of the focal entity during the process of tournament crowdsourcing. The findings of this research also contribute to the literature on value cocreation by 1) introducing a thorough definition of value co-creation, 2) conceptually and empirically enriching the most salient components in value co-creation, and 3) bringing in new insights into the value co-creation phenomenon by examining the context of tournament crowdsourcing. In practical terms, the findings of this research may inspire practitioners of generating better understanding about their roles in facilitating value co-creation, the strategic usage of systems and mechanisms, being aware of potential conflicts and finding the right crowd members when conducting tournament crowdsourcing initiatives

Opening up innovation processes through contests in the food sector

Purpose: The purpose of this paper is to investigate how an adequate mix of technological, organisational and managerial tools might support Open Innovation (OI) processes achieved by contests in the food sector. Design/methodology/approach: The methodology of this paper is exploratory in nature. Data have been gathered about the 140 innovation contests launched by the best global food brands (2013 BusinessWeek/Interbrand Best Global Brands) over the last decade. Findings: The research highlights the main changes that have occurred over the last decade, showing that the choice of platform type for contest launches is often neglected or considered as an ancillary element. Indeed, it is a choice that embeds another set of technological, organisational and managerial tools that strongly influence the collaborative behaviour (and the participation itself) of partners throughout the innovation process. Research limitations/implications: Companies investigated in this paper consist exclusively of top brands in the sector. Future research should strive to obtain larger samples, develop a set of fine-grained hypotheses, and test them by using appropriate statistical techniques. Originality/value: This paper fills an inexplicable gap in academic literature due to the fact that food companies are those that mainly use contests in order to implement OI but they are scarcely researched regarding this issue

Essays in Modeling the Consumer Choice Process

In this dissertation, I utilize and develop empirical tools to help academics and practitioners model the consumer\u27s choice process. This collection of three essays strives to answer three main research questions in this theme. In the first paper, I ask: how is the consumer\u27s purchase decision impacted by the search for general product-category information prior to search for their match with a retailer or manufacturer ( sellers )? This paper studies the impact of informational organic keyword search results on the performance of sponsored search advertising. We show that, even though advertisers can target consumers who have specific needs and preferences, for many consumers this is not a sufficient condition for search advertising to work. By allowing consumers to access content that satisfies their information requirements, informational organic results can allow consumers to learn about the product category prior to making their purchase decision. We develop a model characterize the situation in which consumers can search for general information about the product category as well as for information about the individual sellers\u27 offerings. We estimate this model using a unique dataset of search advertising in which commercial websites are restricted in the organic listing, allowing us to identify consumer clicks as informational (from organic links) or purchase oriented (from sponsored links). With the estimation results, we show that consumer welfare is improved by 29%, while advertisers generate 19% more sales, and search engines obtain 18% more paid clicks, as compared to the scenario without informational links. We conduct counterfactuals and find that consumers, advertisers, and the search engine are significantly better off when the search engine provides free general information about the product. When the search engine provides information about the advertisers\u27 specific offerings, however, there are fewer paid clicks and advertisers at high ad positions will obtain lower sales. We further investigate the implications on the equilibrium advertiser bidding strategy. Results show that advertiser bids will remain constant in the former scenario. When the search engine provides advertiser information, advertisers will increase their bids because of the increased conversion rate; however, the search engine still loses revenue due to the decreased paid clicks. The findings shed important managerial insights on how to improve the effectiveness of search advertising. In the second paper, I ask: how is the consumer\u27s search for information, during their choice process and in an advertising context, influenced by the signaling theory of advertising? Using a dataset of travel-related keywords obtained from a search engine, we test to what extent consumers are searching and advertisers are bidding in accordance with the signaling theory of advertising in literature. We find significant evidence that consumers are more likely to click on advertisers at higher positions because they infer that such advertisers are more likely to match with their needs. Further, consumers are more likely to find a match with advertisers who have paid more for higher positions. We also find strong evidence that advertisers increase their bids when there is an improvement in the likelihood that their offerings match with consumers\u27 needs, and the improvement cannot be readily observed by consumers prior to searching advertisers\u27 websites. These results are consistent with the predictions from the signaling theory. We test several alternative explanations and show that they cannot fully explain the results. Furthermore, through an extension we find that advertisers can generate more clicks when competing against advertisers with higher match value. We offer an explanation for this finding based on the signaling theory. In the third paper, I ask: can we model the consumer\u27s choice of brand as a sequential elimination of alternatives based on shared or unique aspects while incorporating continuous variables, such as price? With aggregate scanner data, marketing researchers typically estimate the mixed logit model, which accounts for non-IIA substitution patterns among brands, which arise due to similarity and dominance effects in demand. Using numerical examples and analytical illustrations, this research shows that the mixed logit model, which is widely believed to be a highly flexible characterization of brand switching behavior, is not well designed to handle non-IIA substitution patterns. The probit allows only for pair-wise inter-brand similarities, and ignores third-order or higher dependencies. In the presence of similarity and dominance effects, the mixed logit model and the probit model yield systematically distorted marketing mix elasticities. This limits the usefulness of mixed logit and probit for marketing decision-making. We propose a more flexible demand model that is an extension of the elimination-by-aspects (EBA) model (Tversky 1972a, 1972b) to handle marketing variables. The model vastly expands the domain of applicability of the EBA model to aggregate scanner data. Using an analytical closed-form that nests the traditional logit model as a special case, the EBA demand model is estimated with marketing variables from aggregate scanner data in 9 different product categories. It is compared to the mixed logit and probit models on the same datasets. In terms of multiple fit and predictive metrics (LL, BIC, MSE, MAD), the EBA model outperforms the mixed logit and the probit in a majority of categories in terms of both in-sample fit and holdout predictions. The results show significant differences in the estimated price elasticity matrices between the EBA model and the comparison models. In addition, a simulation shows that the retailer can improve gross profits up to 34.4% from pricing based on the EBA model rather than the mixed logit model. Finally, the results suggest that empirical IO researchers, who routinely use mixed logit models as inputs to oligopolistic pricing models, should consider the EBA demand model as the appropriate model of demand for differentiated products

Co-ordination and Lock-in: Competition with Switching Costs and Network Effects

Switching costs and network effects bind customers to vendors if products are incompatible, locking customers or even markets in to early choices. Lock-in hinders customers from changing suppliers in response to (predictable or unpredictable) changes in effciency, and gives vendors lucrative ex post market power-over the same buyer in the case of switching costs (or brand loyalty), or over others with network effects. Firms compete ex ante for this ex post power, using penetration pricing, introductory offers, and price wars. Such "competition for the market" or "life-cycle competition" can adequately replace ordinary compatible competition, and can even be fiercer than compatible competition by weakening differentiation. More often, however, incompatible competition not only involves direct effciency losses but also softens competition and magnifies incumbency advantages. With network effects, established firms have little incentive to offer better deals when buyers’ and complementors’ expectations hinge on non-effciency factors (especially history such as past market shares), and although competition between incompatible networks is initially unstable and sensitive to competitive offers and random events, it later "tips" to monopoly, after which entry is hard, often even too hard given incompatibility. And while switching costs can encourage small-scale entry, they discourage sellers from raiding one another’s existing customers, and s also discourage more aggressive entry. Because of these competitive effects, even ineffcient incompatible competition is often more profitable than compatible competition, especially for dominant rms with installed-base or expectational advantages. Thus firms probably seek incompatibility too often. We therefore favor thoughtfully pro-compatibility public policy.