After a long day you are called in by your boss to meet her at her office. You are exhausted, because you have been working hard lately for a high status company. Your boss compliments you and is impressed with your work. At the end of that day, you leave the office with extra motivation to keep putting in the effort. This anecdote serves as an illustration of how traditional companies can motivate their employees to keep them happy and productive. Recently, the advancements in technology have made it possible for traditional firms to organize their work over the internet and source particular tasks to an online crowd of independent contractors referred to as crowdsourcing (Afuah and Tucci, 2012). Workers on so-called crowdsourcing platforms, like Amazon Mechanical Turk and Deliveroo, work on a voluntary basis as they are not formal employees of the company. Therefore, it is interesting to look at what drives this new generation of crowd workers in contrast to traditional employees to actively participate on these platforms as this is currently not well understood.

Nowadays, organizations use crowdsourcing for different purposes such as problem solving, idea generation, information pooling, or outsourcing tasks (Tsekouras, 2019). Companies use the crowd as they might be able to solve certain problems faster and cheaper than in house employees (Blohm et al, 2018). Hence, from a firms’ perspective it becomes evident to use the crowd as it allows for lower transaction costs, repetitive tasks that require human intelligence and keeping control over sensitive data by splitting up the tasks (Tsekouras, 2019). Although you might think you have never participated in a crowdsourcing task, most of you have even unintentionally. To illustrate, Google uses your search history to look for interesting keywords for ads (Kitter et al., 2008). 

From a crowd workers’ perspective, it is harder to trace the drivers. Why would you participate on a crowdsourcing platform? There are of course factors such as under- and unemployment which may drive people towards crowdsourcing platforms for obvious reasons such as money (Burtch et al, 2018). Nonetheless, there are also less straightforward motives such as glory, love, or a product reward as drivers for contribution (Tsekouras, 2019). To frame it from a customer-centric perspective, customers get the opportunity to speak their minds about product solutions and in that way reduce the costs of firms to obtain detailed consumer information (Tsekouras, 2019). In other words, you might benefit from the information pooling of companies. You might have an interesting feature for Apple that you want them to introduce in their new Iphone.

For the survival of a platform it is important to drive members for continuous cooperative behavior, referring back to the earlier mentioned voluntary nature. In a way, members of crowdsourcing platforms can be seen as a community in which attachment is crucial for success (Ren et al., 2012; Boons et al., 2015). Consequently, a study by Boons et al. (2015) was conducted to look into feelings of pride and respect as drivers of ongoing member activity on crowdsourcing platforms. The non-traditional work setting of crowd workers asks for a research method which is able to explain member activity on a voluntary basis. Therefore, the engagement model was used as it is capable of measuring cooperative behaviors in groups in a voluntary setting (Boons et al. 2015). The engagement model measures identification with the firm to increase activity as a result from perceived feelings of pride and respect. 

Think of the anecdote in the introduction, the compliment you got from your boss. You were positively evaluated by someone which made you feel respected (Boons et al., 2015). Furthermore, the organization is one with high regard which gives you a feeling of pride. Due to these two factors you are more likely to identify with your group of colleagues and the company. This identification gave you the extra motivation to keep putting in the effort.  However, according to Boons et al. (2015) it may be difficult to compare a crowdsourcing platform to a traditional firm as they are virtual organizations lacking the physical proximity and interaction. In contrast, they argue that it is still possible to use the engagement model as members are able to develop a sense of pride and respect based on an autonomous evaluation against personally held norms and standards (Boons et al., 2015). This is in harmony with initial thoughts of Ren et al. (2012) as they do not expect the identification process to be dependent on bonding with other members. Therefore, the engagement model is expected to fit the needs of this research.  

The authors collected data from a platform that matches organizations, that seek for idea generation, to its community of solvers. A survey was conducted amongst its members (n=153) who had participated on tasks and received feedback. The survey looked into the three earlier discussed items pride, perceived respect and organizational identification (Boons et al., 2015). These items suggest a positive cue which in turn could lead to active participation. The authors found that only pride was an important predictor of member participation (figure 1). However, the authors did not find support for perceived respect and organizational identification as predictors of ongoing member activity. Although, perceived respect and pride both were positively related to organizational identification (Figure 2). These findings implicate that the authors were able to use the engagement model in a non-traditional setting to find drivers on crowdsourcing platforms (Boons et al., 2015). Furthermore, they contribute to literature by suggesting that in a crowdsourcing setting the perceived organizational identification is inferior to pride for member activity. 

So, how can you increase pride to enhance members’ performance? As a platform leader you can benefit from this research by increasing members’ pride by communicating positive media attention about your platform. Your community will associate positive news items with the status of the organization as a whole thereby increasing members pride and activity. 

To conclude, crowdsourcing platforms differ a lot from traditional organizations in terms of interaction with workers. Therefore, finding out what drives them is important and was not well understood. However, Boons et al. (2015) build on the engagement model to find out what drives members’ activity influenced by feelings of pride and respect. They contribute to existing literature by successfully using the engagement model in another setting than traditional companies. Furthermore, they found support for pride as a driver for ongoing member activity.

Bibliography:

Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review, 37(3), 355-375.

Boons, M., Stam, D., & Barkema, H. G. (2015). Feelings of pride and respect as drivers of ongoing member activity on crowdsourcing platforms. Journal of Management studies, 52(6), 717-741.

Burtch, G., Ghose, A., & Wattal, S. (2013). An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets. Information Systems Research, 24(3), 499-519.

Kittur, A., Chi, E. H., & Suh, B. (2008, April). Crowdsourcing user studies with Mechanical Turk. In Proceedings of the SIGCHI conference on human factors in computing systems(pp. 453-456). ACM.

Ren, Y., Harper, F. M., Drenner, S., Terveen, L., Kiesler, S., Riedl, J., & Kraut, R. E. (2012). Building member attachment in online communities: Applying theories of group identity and interpersonal bonds. Mis Quarterly, 841-864.

Tsekouras, D.K. 2019. Lecture 3: Crowdsourcing