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on Information and Communication Technologies |
By: | Paul Belleflamme (Aix-Marseille Univ., CNRS, EHESS, Centrale Marseille, AMSE; KEDGE Business School; and CESifo); Martin Peitz (Department of Economics and MaCCI, University of Mannheim; CEPR; CESifo; and ZEW) |
Abstract: | The rise and success of digital platforms (such as Airbnb, Amazon, Booking, Expedia, Ebay, and Uber) rely, to a large extent, on their ability to address two major issues. First, to effectively facilitate transactions, platforms need to resolve the problem of trust in the implicit or explicit promises made by the counterparties; they post reviews and ratings to pursue this objective. Second, as platforms operate in marketplaces where information is abundant, they may guide their users towards the transactions that these users may have an interest in; recommender systems are meant to play this role. In this article, we elaborate on review, rating, and recommender systems. In particular, we examine how these systems generate network effects on platforms. |
Keywords: | platforms, network effects, ratings, recommender systems, digital economics |
JEL: | D43 L13 L86 |
Date: | 2018–02 |
URL: | http://d.repec.org/n?u=RePEc:aim:wpaimx:1806&r=ict |
By: | Martínez-Sánchez, Francisco; Romeu, Andrés |
Abstract: | In this paper, the authors analyze the differences in piracy rates from one country to another. Like previous papers on the topic, they find that more developed countries have lower incentives for pirating. Unlike previous papers, they find that the piracy rate is positively correlated with the tax burden rate but negatively correlated with the domestic market size and exports over GDP. The authors also separate the impacts of education and R&D on piracy, and find two effects with opposite signs. Moreover, they find that those countries with smaller, more efficient bureaucracies are likely to protect intellectual property more effectively. Finally, they show that the spread of access to the Internet is negatively correlated with the software piracy rate. |
Keywords: | piracy rate,education,R&D,quality bureaucracies,intellectual property,internet |
JEL: | K42 L86 O3 O57 |
Date: | 2018 |
URL: | http://d.repec.org/n?u=RePEc:zbw:ifwedp:20184&r=ict |
By: | Slivko, Olga |
Abstract: | Economic literature acknowledges the impact of immigration on cross-border patenting and scientific publications. However, the role of immigration ows in the dissemination of knowledge in a broader sense is yet to be assessed. In this paper, I estimate the effect of immigration on the facilitation of online knowledge reagrding destination countries in the native languages of immigrants. To quantify online knowledge, I focus on one of the world's most viewed online knowledge platforms, Wikipedia. I combine data on immigration ows between the pairs of immigrants' origin and destination countries with contributions to Wikipedia describing the countries of immigrants' destinations in the languages spoken in immigrants' origin countries. I specifically focus on knowledge domains describing science and culture. In order to draw a causal inference, I use shocks to immigration due to economic and political crises as exogenous shocks to Wikipedia content and analyze subsequent changes in the contributions to Wikipedia. An increase in immigration yields more knowledge contributed to Wikipedia about science and culture in destination countries in the native languages of the origin countries. Interestingly, the increase in contributions is driven by anonymous contributors. In the Wikipedia community, these are considered occasional contributors who care personally about the topics they contribute to. The increase in content generated anonymously is driven by longer contributions. |
Keywords: | Immigration,Knowledge dissemination,Online knowledge,Wikipedia |
JEL: | L17 O15 O33 H41 L86 |
Date: | 2018 |
URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:18008&r=ict |
By: | Shakeeb Khan (Boston College); Denis Nekipelov (University of Virginia); Justin Rao (Microsoft Research) |
Abstract: | In this paper we aim to conduct inference on the “lift” effect generated by an online advertisement display: specifically we want to analyze if the presence of the brand ad among the advertisements on the page increases the overall number of consumer clicks on that page. A distinctive feature of online advertising is that the ad displays are highly targeted- the advertising platform evaluates the (unconditional) probability of each consumer clicking on a given ad which leads to a higher probability of displaying the ads that have a higher a priori estimated probability of click. As a result, inferring the causal effect of the ad display on the page clicks by a given consumer from typical observational data is difficult. To address this we use the large scale of our dataset and propose a multi-step estimator that focuses on the tails of the consumer distribution to estimate the true causal effect of an ad display. This “identification at infinity” (Chamberlain (1986)) approach alleviates the need for independent experimental randomization but results in nonstandard asymptotics. To validate our estimates, we use a set of large scale randomized controlled experiments that Microsoft has run on its advertising platform. Our dataset has a large number of observations and a large number of variables and we employ LASSO to perform variable selection. Our non-experimental estimates turn out to be quite close to the results of the randomized controlled trials. |
Keywords: | Endogenous treatment effects, randomized control trials, online advertising, lift effect |
JEL: | C14 C31 C90 M37 |
Date: | 2018–02–01 |
URL: | http://d.repec.org/n?u=RePEc:boc:bocoec:946&r=ict |
By: | Michail Batikas; Jörg Claussen; Christian Peukert |
Abstract: | In this paper, we study the effects of a self-regulatory effort, orchestrated by the European Commission, that aims to reduce advertising revenues for publishers of copyright infringing content. Historical data lets us follow how the third-party advertising and tracking services associated with a large number of piracy websites and a corresponding set of legitimate “placebo” websites change after the agreement to self-regulate went in place. We find that larger EU-based advertisers comply with the initiative and reduce their connections with piracy websites. We do not find reductions for other non-advertising services that track consumers, which has potentially important implications for the efficiency of targeted advertising. |
Keywords: | piracy, copyright enforcement, online advertising, natural experiment |
JEL: | K40 L50 L80 |
Date: | 2018 |
URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_6852&r=ict |
By: | Ginger Zhe Jin |
Abstract: | Thanks to big data, artificial intelligence (AI) has spurred exciting innovations. In the meantime, AI and big data are reshaping the risk in consumer privacy and data security. In this essay, I first define the nature of the problem and then present a few facts about the ongoing risk. The bulk of the essay describes how the U.S. market copes with the risk in current policy environment. It concludes with key challenges facing researchers and policy makers. |
JEL: | D04 D18 D8 L15 L51 |
Date: | 2018–01 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24253&r=ict |
By: | Michael McAleer (Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.); Judit Oláh (Faculty of Economics and Business Institute of Applied Informatics and Logistics University of Debrecen, Hungar.); József Popp (Faculty of Economics and Business Institute of Sectoral Economics and Methodology University of Debrecen, Hungary.) |
Abstract: | The purpose of the paper is to present arguments for and against the use of the Impact Factor (IF) in a rapidly changing digital world. The paper discusses the calculation of IF, as well as the pros and cons of IF. Editorial policies that affect IF are examined, and the merits of open access online publishing are presented. Scientific quality and the IF dilemma are analysed, and alternative measures of impact and quality are evaluated. The San Francisco declaration on research assessment is also discussed. |
Keywords: | Impact Factor, Quality of research, Pros and Cons, Implications, Digital world, Editorial policies, Open access online publishing, SCIE, SSCI. |
JEL: | O34 O31 D02 |
Date: | 2018–01 |
URL: | http://d.repec.org/n?u=RePEc:ucm:doicae:1806&r=ict |
By: | Gaétan de Rassenfosse |
Abstract: | One source of uncertainty in the patent system relates to the difficulty in identifying products that are protected with a patent. This paper studies the adoption by U.S. patentees of “virtual patent marking,” namely the online provision of constructive notice to the public that an article is patented. It proposes a simple model of the decision to adopt patent marking and empirically examines factors that affect adoption. Data suggest that about 12 percent of patent holders overall provide virtual marking information (and perhaps about 25 percent of commercially active assignees). Econometric analysis suggests that the most discriminant factor of the adoption of virtual marking is the size of the patent portfolio. The likelihood of adoption increases with portfolio size, consistent with evidence that firms with a larger patent portfolio are more likely to be infringed. |
JEL: | D23 K29 O34 |
Date: | 2018–02 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24288&r=ict |
By: | Antoci, Angelo (University of Sassari); Bonelli, Laura (Sapienza University of Rome); Paglieri, Fabio (Institute of Cognitive Sciences and Technology); Reggiani, Tommaso G. (Masaryk University); Sabatini, Fabio (Sapienza University of Rome) |
Abstract: | Social media have been credited with the potential of reinvigorating trust by offering new opportunities for social and political participation. This view has been recently challenged by the rising phenomenon of online incivility, which has made the environment of social networking sites hostile to many users. We conduct a novel experiment in a Facebook setting to study how the effect of social media on trust varies depending on the civility or incivility of online interaction. We find that participants exposed to civil Facebook interaction are significantly more trusting. In contrast, when the use of Facebook is accompanied by the experience of online incivility, no significant changes occur in users' behavior. These results are robust to alternative configurations of the treatments. |
Keywords: | social media, Facebook, online incivility, trust, social networks, cooperation, trust game |
JEL: | C91 D9 D91 Z1 |
Date: | 2018–01 |
URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp11290&r=ict |
By: | Alberto Cavallo; W. Erwin Diewert; Robert C. Feenstra; Robert Inklaar; Marcel P. Timmer |
Abstract: | We show that online prices can be used to construct quarterly purchasing power parities (PPPs) with a closely-matched set of goods and identical methodologies in a variety of developed and developing countries. Our results are close to those reported by the International Comparisons Program (ICP) in 2011 and the OECD in 2014, and can be used to obtain more up-to-date estimates of real consumption across countries without the need for consumer price index extrapolations. We discuss advantages and limitations associated with the use of online prices for PPs, including issues of representativeness and limited coverage of product categories and countries. |
JEL: | E3 E31 F0 F41 O47 |
Date: | 2018–02 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24292&r=ict |
By: | Robert W. Fairlie; Peter Riley Bahr |
Abstract: | This paper provides the first evidence on the earnings, employment and college enrollment effects of computers and acquired skills from a randomized controlled trial providing computers to entering college students. We matched confidential administrative data from California Employment Development Department (EDD)/Unemployment Insurance (UI) system earnings records, the California Community College system, and the National Student Clearinghouse to all study participants for seven years after the random provision of computers. The experiment does not provide evidence that computer skills have short- or medium-run effects on earnings. These null effects are found along both the extensive and intensive margins of earnings (although the estimates are not precise). We also do not find evidence of positive or negative effects on college enrollment. A non-experimental analysis of CPS data reveals large, positive and statistically significant relationships between home computers, and earnings, employment and college enrollment, raising concerns about selection bias in non-experimental studies. |
JEL: | I23 |
Date: | 2018–02 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24276&r=ict |
By: | Carmela Milano; Sandra Rothenberger |
Abstract: | This paper investigates the impact of Facebook on cultural audience, putting the emphasis on the transmission of cultural capital in elitist circles. Our purpose is to provide important evidence concerning the digital opportunities and challenges for the use of social networks in cultural management. Based on an exploratory study, we look closely at the attitudes and reactions of cultural audience to the use of Facebook by theaters. We focus hereby on the democratization (acceptance) or the vulgarization (rejection) effects of the use of Facebook. We conclude that demographics and psychographics such as the generational effect and the personalities of the influence “the acceptance”, while environmental factors such as peer and media influence “the rejection” of the use of Facebook. The present findings help cultural institutions to have a better understanding of the profile of the actual theater audience, their needs, desires and fears. |
Keywords: | social networks and Facebook; arts consumer research; theater management; cultural capital; vulgarization; democratization; structural equation modeling |
JEL: | D23 D83 |
Date: | 2018–02–19 |
URL: | http://d.repec.org/n?u=RePEc:sol:spaper:2013/267649&r=ict |
By: | Matt Taddy |
Abstract: | We have seen in the past decade a sharp increase in the extent that companies use data to optimize their businesses. Variously called the `Big Data' or `Data Science' revolution, this has been characterized by massive amounts of data, including unstructured and nontraditional data like text and images, and the use of fast and flexible Machine Learning (ML) algorithms in analysis. With recent improvements in Deep Neural Networks (DNNs) and related methods, application of high-performance ML algorithms has become more automatic and robust to different data scenarios. That has led to the rapid rise of an Artificial Intelligence (AI) that works by combining many ML algorithms together – each targeting a straightforward prediction task – to solve complex problems. We will define a framework for thinking about the ingredients of this new ML-driven AI. Having an understanding of the pieces that make up these systems and how they fit together is important for those who will be building businesses around this technology. Those studying the economics of AI can use these definitions to remove ambiguity from the conversation on AI's projected productivity impacts and data requirements. Finally, this framework should help clarify the role for AI in the practice of modern business analytics and economic measurement. |
JEL: | C01 C1 O33 |
Date: | 2018–02 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24301&r=ict |