Understanding and Designing for Cultural Differences on Crowdsourcing Marketplaces
Crowdsourcing marketplaces, such as Mechanical Turk, enable tasks to be distributed to workers from all over the world for completion. While this global quality of crowdsourcing provides numerous benefits to requesters of work (e.g., more diverse labor force that is available at all hours of the day), it could, however, pose challenges in terms of labor management. Much prior work has demonstrated the effects of cultural backgrounds on individual’s thoughts, value, and even behavior. Therefore, the diverse cultural backgrounds on crowdsourcing marketplaces may interact with incentive types, amounts, and task types to impact workers’ task performance, engagement, and selection. My research program explores the effects of cultural differences on these online marketplaces in order to build more efficient global crowdsourcing marketplaces.
In the overall ownership cost of enterprise system, the maintenance cost consists of a major percentage. During the lifetime of an enterprise system, process customization is the most frequent maintenance efforts. However, current processing method has limited scalability and efficiency. In this case study, we explained how a scalable and efficient customization processing method was implemented. This method used the carbon emission trading mechanism to facilitate the cost benefit analysis of customization request. It also used distributed processing principle to improve the overall processing efficiency. Feedback from a pilot implementation in a large manufacturer included.