Modus Operandi of Crowd Workers : The Invisible Role of Microtask Work Environments

The ubiquity of the Internet and the widespread proliferation of electronic devices has resulted in flourishing microtask crowdsourcing marketplaces, such as Amazon MTurk. An aspect that has remained largely invisible in microtask crowdsourcing is that of work environments; defined as the hardware and software affordances at the disposal of crowd workers which are used to complete microtasks on crowdsourcing platforms. In this paper, we reveal the significant role of work environments in the shaping of crowd work. First, through a pilot study surveying the good and bad experiences workers had with UI elements in crowd work, we revealed the typical issues workers face. Based on these findings, we then deployed over 100 distinct microtasks on CrowdFlower, addressing workers in India and USA in two identical batches. These tasks emulate the good and bad UI element designs that characterize crowdsourcing microtasks. We recorded hardware specifics such as CPU speed and device type, apart from software specifics including the browsers used to complete tasks, operating systems on the device, and other properties that define the work environments of crowd workers. Our findings indicate that crowd workers are embedded in a variety of work environments which influence the quality of work produced. To confirm and validate our data-driven findings we then carried out semi-structured interviews with a sample of Indian and American crowd workers from this platform. Depending on the design of UI elements in microtasks, we found that some work environments are more suitable than others to support crowd workers. Based on our overall findings resulting from all the three studies, we introduce ModOp, a tool that helps to design crowdsourcing microtasks that are suitable for diverse crowd work environments. We empirically show that the use of ModOp results in reducing the cognitive load of workers, thereby improving their user experience without effecting the accuracy or task completion time

Using Amazon Mechanical Turk and Other Compensated Crowd Sourcing Sites

Crowdsourcing is becoming recognized as a powerful tool that organizations can use in order to get work done, this by freelancers and non-employees. We conceptualize crowdsourcing as a subcategory of outsourcing, with compensated crowdsourcing representing situations in which individuals performing the work receive some sort of payment for accomplishing the organization’s tasks. Herein, we discuss how sites that create a crowd, such as Amazon Mechanical Turk, can be powerful tools for business purposes. We highlight the general features of crowdsourcing sites, offering examples drawn from current crowdsourcing sites. We then examine the wide range of tasks that can be accomplished through crowdsourcing sites. Large online worker community websites and forums have been created around such crowdsourcing sites, and we describe the functions they generally play for crowdsourced workers. We also describe how these functions offer opportunities and challenges for organizations. We close by discussing major considerations organizations need to take into account when trying to harness the power of the crowd through compensated crowdsourcing sites

Understanding the Turnover Intention of Crowd Workers of Microtask Crowdsourcing Platform

Microtask crowdsourcing is a relatively new work form enabled by information technologies. For both practitioners and academics, understanding the turnover intention of the users, requesters and crowd workers respectively, of microtask crowdsourcing is very important. However, compared with the relatively large literature on requester, studies focusing on worker crowd workers are limited. Therefore, in this study, we investigate the crowd workers’ intentions to leave the microtask crowdsourcing. The research goal is to analyze the motivations of crowd workers systematically and identify those factors that influenced their turnover intention. Based on perceived value and justice perspectives, a research model is developed. The proposed hypotheses will be tested using data from Amazon Mechanical Turk

Crowd-technology in the selection of personnel

In article is examined the crowdsourcing technology and the technology based on its principles a crowd-recruiting as instruments of staff recruitment in the organization. The presented technologies are new effective tools large-scale by geographical coverage and number of participants of selection of the employees who are really interested in work with this organization. Crowd-technologies, which are based on "the phenomenon of the crowd" can not only greatly speed up the solution of important problems for the company, but also significantly reduce costs. Was designed the methodology of introduction of crowdsourcing technology at staff recruitment in the organization Because of introduction of this methodology is assumed optimization of costs of the personnel, thanks to improvement of staff recruitment by means of crowd-technologies (crowdsourcing, crowd-recruiting, crowd-staffing), namely: increase of qualitative structure of the personnel and reduction of staff turnover thanks to what will be seen labor productivity growth.peer-reviewe

The Duality of Empowerment and Marginalization in Microtask Crowdsourcing: A Replication

This paper describes an exact replication of a study by Deng, Joshi, & Galliers (2016) of crowd worker values on Amazon’s Mechanical Turk (MTurk) crowdsourcing platform. The original study analyzed 210 MTurk crowd workers’ narratives using value sensitive design (VSD). The results uncovered nine shared values: access, autonomy, fairness, transparency, communication, security, accountability, making an impact, and dignity. Further analysis in the original study revealed four crowdsourcing structures: compensation, governance, technology, and microtask, and duality of crowd worker perceptions, empowerment, and marginalization. This replication study also asked Amazon Mechanical Turk crowd workers questions about their work and used the original study’s findings for a priori codes. However, new values and findings emerged in our results, which offers additional implications for further research regarding microtask crowdsourcing

Towards a Taxonomy of Ethical Considerations in Crowdsourcing

Crowdsourcing is a growing industry, where millions of individuals and businesses have begun tapping into the crowd to perform work. Despite this growth, crowd work and labor contains few regulations. Previous researchers have highlighted examples of ethical challenges organizations and individuals face in crowdsourcing. This paper explores these challenges, using Value Sensitive Design and Transparency literature to identify candidate ethical principles in crowdsourcing. Integrating these principles with ethical dilemmas, crowdsourcing models, and affected stakeholders, this research uses a deductive approach to develop a taxonomic framework of ethical considerations in crowdsourcing. The resulting taxonomy provides practical and theoretical contributions. Organizations choosing to use crowdsourcing can refer to the classification to understand ethical implications, as well as accounting for ethical requirements in the design and governance of projects. Researchers can expand the classification to gain understanding of each element and the interrelationships. Finally, we describe specific directions for future research