Mark P. Walsh

Do social image concerns, such as garnering prestige from others and showing respect to others, affect information-passing about important technologies? In an experiment in rural Pakistan, I measure the effects of social image concerns on information-passing about mobile banking, an important technology in this context, and parse the role of prestige and respect concerns. Villagers (senders) decide whether to pass information designed for high-competence users, a growth-oriented pamphlet, or information designed for low-competence users, a safety-oriented pamphlet, to fellow villagers (receivers). To identify social image concerns, I cross-randomize (i) whether the sender's identity is hidden from the receiver or revealed and (ii) whether the sender's targeting of the receiver is hidden from the receiver (receiver told information passed to "a fellow villager") or revealed (receiver told information passed to "you, specifically"). When senders know their identity and targeting of the receiver will be revealed, they share the growth-oriented pamphlet more and the safety-oriented pamphlet less. These effects are entirely driven by sharing among weak social ties, consistent with signaling concerns being larger among pairs with fewer prior interactions. When only the sender's identity is revealed, effects are smaller and insignificant, suggesting that concerns around showing respect matter more than concerns around garnering prestige in this context. In simulations of a two-topic social learning model using full network data from Indian villages, communication in a network over time generally amplifies the effect of social image concerns on information diffusion, the frequency of conversations about growth relative to safety, and adoption of dangerous technologies, relative to the static effects estimated in the experiment. This amplification is stronger when fewer households are given information initially.

Two-sided or platform markets often face a “chicken & egg" problem where there is little value in adoption for one side unless the other side adopts as well. This coordination problem exacerbates the social learning frictions that stall the diffusion of new technologies, since a potential user must learn about the technology and about the other side’s adoption intentions if they hope to accurately forecast the platform’s value to them. In this paper, we partner with one of the largest mobile banking platforms in Tanzania to run a market-level experiment across 300 markets to test interventions aimed at catalyzing adoption of an important two-sided platform, digital retail payments. The experimental design parses the role of network effects and social learning frictions in stalling adoption, and tests for complementarities between interventions addressing these forces. We will measure the adoption and usage of digital retail payments customers through household surveys and administrative data provided by our partner. Since the Bank of Tanzania is launching an interoperable instant payment system (TIPS) in early 2024, the study also provides an opportunity to offer insights into the amplifying effects of interoperability on digital payments. This study is fully funded, the baseline survey with 1200 merchants and 1800 customers is complete, the intervention is scheduled for February 2024, and the first follow-up survey is scheduled for May 2024.