Information Economics and Policy最新文献

This research empirically analyzes the effect of social media on fragility. It goes beyond political grounds which oppose techno-optimistic to techno-pessimistic perceptions of the impact of social media to analyze its consequences on global, security, economic and social fragilities. The research uses annual data from a panel of 47 African countries for the period 2000–2018. Results reveal that the use of social media by the public to organize offline political actions has no outcome on global fragility. However, its use by elites for the same end accentuates global state fragility. This operates through security and political fragilities. Fragility is negatively associated with higher civil society participation, education and democracy. The use of social media to organize offline political actions either by people or by elites in the context of higher civil society participation reduces fragility, while its use either by people or by elites in the context of higher educational level accentuates state fragility. The use of social media to organize offline political actions by people in the context of democracy boosts fragility but its use by elites in the same framework reduces fragility. There is a need to sensitize people, especially elites in Africa on the threats and opportunities of social media. There is also a necessity to develop a dynamic, well-educated and well-organized civil society and population in order to better valorize the opportunities that social media represents.

We analyse the incentives of a data broker to sell consumer-level data that enable personalised pricing to compete with firms when only a fraction of consumers — centred around one firm that we label “central” — are profiled. The central firm can potentially benefit from the data more than the rival ones (“peripheral”). We show that the data broker may decide not to sell the dataset to the central firm and instead trade with its peripheral competitors. In particular, we identify a strategic reaction of competitors that want to prevent that data increase competition.

Music streaming platforms’ models for sharing revenues with content providers have been the subject of intense debate for nearly a decade. The dominating model involves pooling platform revenues and allocating these funds to songs based on a song's share of the total number of platform streams. Since this model has several controversial consequences, alternative models have been proposed. This paper uses a novel approach to assess the two most discussed models – the “user-centric” and the “artist-centric”. Our approach relies on a unique data set of 154,505 streaming platform users (890 million streams) and simulates how a large-scale implementation of these models may reallocate revenues across different songs and rightsholders. We disentangle the static effects of a transition to a “user-centric” or an “artist-centric” model across each of six different song characteristics. We then compare the results of the two models. We show that contrary to its objective, an artist-centric payment system does not significantly improve remuneration to professional artists while the user-centric payment system would generate more significant changes in revenue reallocation, mainly at the expense of Rap & Hip-hop songs, superstars and new releases. Finally, we analyze the positions of the various stakeholders with regard to each of them.

In this study, we demonstrate that migrant families adopt ICT more than non-migrant households, the diffusion is higher among the recipients of remittances resulting from the long-duration, long-distance international migration than the short-duration, short-distance migration, and that foreign remittance recipients adopt advanced technologies to a greater extent compared to domestic remittance-recipients. We empirically test these hypotheses by using data on 160,624 households from the 2019 to 20 round of the Pakistan Social and Living Standards Measurement Survey and employing an instrumental-variable strategy as well as generalized two-step Heckman and Augmented Inverse Probability Weighting estimators. We come up with evidence of the significant effects of remittances on ICT adoption. Households with at least one domestic or international migrant, on average have 0.27 per capita mobile ownership and 0.12 higher probability of having internet at home compared to non-recipient households. This effect is visible more among international-remittance than domestic-remittance-receiving households. ICT adoption also increases with the amount received. We find that remittances accelerate the adoption of smartphones and social media apps. Besides, while international remittances substantially increase the use of smartphones, internet and social media apps, domestic remittances mainly improve basic phone adoption. Remittances also help reduce the rural-urban and male-female digital divide.

Recent U.S. broadband programs prioritize high-speed infrastructure with download speeds of 100 megabits per second (Mbps) or more. Some internet providers have already built broadband networks capable of gigabit speeds (1000 Mbps) and more of this infrastructure is likely forthcoming due to increased federal support. The availability of this “ultra-fast” internet may have important implications for business creation. Business-level data from Data Axle is combined with the Federal Communication Commission's Form 477 broadband availability data and aggregated to the census block group level to form a six-year panel from 2015 to 2020. We examine the effects of three thresholds of broadband speed availability on business births per 10,000 population in eight U.S. states using an event study design. Results suggest that 100+ Mbps availability increases business births for at least up to five years after being introduced. The impacts are largest in metro block groups and for select industries. Relative to block groups treated at the 100 Mbps level, access to 250 Mbps shows additional benefits for business creation; however, the results for gigabit speed provision are less conclusive. This may change as technology continues to evolve and ultra-fast speed becomes more necessary for business operations.

Agency and wholesale models are widely adopted vertical contractual agreements. This paper compares the private incentives and social welfare of these two business models by highlighting the differences in move order and price structure. With a monopoly platform, the agency model dominates the wholesale model with respect to social welfare and the platform's profit if and only if demand is subconvex. With duopoly platforms, having both platforms adopt the agency model is socially desirable, and it is a dominant-strategy Nash equilibrium if demand is weakly convex. Our findings have novel theoretical contributions and offer insights into some influential antitrust cases.

We consider a duopoly model with history-based price discrimination where firms inherit asymmetric shares of consumers that they might partly recognize according to the degree of information completeness. We analyze the impact of the amount of information on market configuration, profits and welfare. With high degrees of information completeness and sufficiently small asymmetries in the market shares, firms are more likely to use aggressive pricing strategies, both poaching rival's consumers. Otherwise, firms adopt different pricing strategies and price discrimination is enforced only by the smaller firm. Greater information completeness has a non-monotonic effect on profits and a decreasing effect on welfare. Finally, we show that the case with perfect information is a special case whose results do not hold when even a small degree of uncertainty is introduced in the game.

Data on websites that hosted job boards and CV banks in the U.S. from 2000 to 2011 reveal that websites imposed fewer restrictions (in terms of the duration of use) and lower fees for job searchers relative to employers. This asymmetry in the treatment (or the terms of use) changed as the relative scarcity of job searchers and job vacancies in the labor market in which the websites offered their services changed. Compared with job searchers, employers faced less stringent restrictions and lower fees when job searchers were scarce relative to job openings. These adjustments imply that the value of using an employment website changes with the number of potential users and the probability of finding a quality match. We find that these adjustments were most pronounced for websites that relied exclusively on employers and job searchers for their content (job ads and CVs). Whereas existing literature on the role that network size plays in intermediaries’ decision-making has focused on prices, our findings reveal that this focus can overlook other adjustments that affect the terms of use. Given that these adjustments in our context may result in longer periods during which CVs and job ads remain online, our findings suggest that the optimal design of intermediaries must include tools that help users sort through stale information.

This article studies the impact of algorithmic pricing on market competition when firms collect data to charge personalized prices to their past customers. Pricing algorithms offer to each firm a rich set of pricing strategies combining first and third-degree price discrimination: they can choose for each of their past customers whether to charge them personalized or homogeneous prices. The optimal targeting strategy of each firm consists in charging personalized prices to past customers with the highest willingness to pay and a homogeneous price to the remaining consumers, including past customers with a low valuation on whom a firm has information. This targeting strategy maximizes rent extraction while softening competition between firms compared to classical models where firms target all past customers. In turn, price-undercutting and poaching practices are not sustainable with behavior-based algorithmic pricing, resulting in greater industry profits.