Crowdsourced delivery represents a rapidly rising segment of global workforce. Crowd-delivery workers enjoy the flexibility to choose when and where to work. This kind of service is the future of work, and the freedom and flexibility that these jobs afford people have attracted more workers to join this industry. It’s where the global workforce is trending. So you want to have a way to optimize or maximize their performance, and the way to do it is through better financial incentives. However, such flexibility brings notorious challenges to online platforms in managing the crowdsourced workforce. Thus, it is inherently important to understand the behavioral and incentive issues of crowd workers.
Earning is a well-known method to motivate workers. In a crowdsourcing platform setting, our joint research project with a leading online platform in China unveils that ratings and penalties play crucial roles in moderating the earning effect. In particular, the positive effect of piece-rate earning decreases when the percentage of five-star ratings increases (negative moderating effect); moreover, this positive effect increases when the monetary penalty increases (positive moderating effect).
Consider two workers: one with 10 five-star ratings, and the other one does not have any. Our research unveils that earnings matter more for the latter one. Because for higher-rated workers, social recognition serves as another positive incentive mechanism to motivate them to work more. Thus, social recognition from positive reviews and higher earnings substitute each other.
On the other hand, our work uncovers that penalty and earnings can actually complement for each other. That is, if a worker receives higher cumulative penalties, he would be more incentivized to work with even a little bit of increase in earnings.