Knowledge that Transforms

Token incentives are the lifeblood of blockchain ventures, motivating diverse contributors to participate, maintain, and expand shared blockchain infrastructure; however, their reliability in markets teeming with speculative activity is not guaranteed. This study examines whether token incentives effectively motivate developer contribution—the core engine of blockchain development—when opportunistic events such as pump-and-dump (P&D) exploit and distort token value. We find that token-based incentives alone cannot sustain ongoing development contributions in either quantity or originality. The damage is more severe in projects with more concentrated token ownership and weaker decentralization, where developers have less influence and face higher risks of self-interested governance. We offer actionable implications for multiple stakeholders. For project leaders and token designers, the message is straightforward: Token rewards should be paired with safeguards that protect incentive value and contributor confidence, alongside governance designs that grant developers credible voice and decision rights. For policymakers and regulators, we outline recommendations to mitigate distorted incentives, reduce token concentration, and promote long-term market stability.

Online professional networks (OPNs) are an increasingly common tool used by recruiters to find and vet qualified job candidates for open positions. These sites allow users to publish recommendations given by other users to supplement their profile information and add credibility to the information provided. OPN recommendations offer a rich source of information to recruiters. Unlike recommendations shared in other ways (non-OPN recommendations), OPN recommendations are publicly accessible, and candidates have complete control over which recommendations they show to others. In this study, we investigate how recommendations may have a different effect when presented as an OPN recommendation versus a non-OPN recommendation. Furthermore, we explore how to improve the effectiveness of recommendations. We conducted a field study where we leveraged the candidate tracking system of a large recruitment firm to measure the varying impact recommendations have on recruiters’ decisions. Our findings show that OPN and non-OPN recommendations that discuss an expected weakness positively affect a candidate’s likelihood of being interviewed. In contrast, recommendations that discuss an unexpected weakness have a negative effect. Furthermore, we find that non-OPN recommendations with no discussion of weakness are significantly more effective than OPN recommendations with no discussion of weakness. We then show that the potential benefits of discussing an expected weakness are more pronounced for OPN recommendations, whereas the potential harm of discussing an unexpected weakness is more severe for non-OPN recommendations.