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From Crowdsourcing to Crowdservicing

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Illustration: from the article Incentives and Rewarding in Social Computing

Unfortunately, there are virtually no serious research papers on crowdsourcing in Russian, as well as on the related areas such as social computing, innovation management, social platforms, etc.  Internet search for 2013 Russian scientific publications with the word “crowdsourcing” produces a rather long list of results the first of which says, ‘Crowdsourcing came to Russia in 2011…  There are not many companies offering crowdsourcing services.  One of the most successful is Witology whose clients are Sberbank, Rosatom, Renaissance Insurance Agency, the Agency for Strategic Initiatives and some other.’
With all due respect to the authors who think high of Witology, I have to state the following.  The above mentioned inquiry reveals no material I could consider as a serious research study on crowdsourcing.  All works are written by students, journalists and various specialists from sociologists and marketers to psychologists and public administration officers who are not engaged in crowdsourcing in a professional way.

Meanwhile, dozens of research papers on crowdsourcing, social computing, innovation management, social platforms, etc. are published in English every month.  But not many Russians read those works.  As a result, there is an increasingly large gap between what the current state of the technologies, as well as their potential and ways to implement them, really is and what Russians understand by all these things. So, to somehow improve the situation I have decided to publish my reviews of the most important and interesting foreign research publications on our blog.

Let me start with Ognjen Scekic, Hong-Linh Truong, and Schahram Dustdar’s article Incentives and Rewarding in Social Computing published in the Communications of the ACM, Vol. 56 No. 6, June 2013.
The authors work at the Technical University of Vienna’s Distributed Systems Group (DSG) headed by Professor Schahram Dustdar.

The DSG has developed the model Interaction Modeling in Crowd Computing Environments that underlies the concept of Socially Enhanced Services Computing and the notion of Crowdservicing.

The article reviews methods of motivating participation in social computing which, as shown in the article, comprises two classes of related technologies.  First, there are micro-task platforms. Second, there are technologies to run creativity contests.

Traditionally, the first class is unpretentiously called crowdsourcing.  The second one, besides Creativity Contests, is called Cocreation, Ideation, Idea Management, Open Innovation, etc.

In addition to the methods of motivating participation, the article discusses the structure of agents and collaboration models.  All technologies and methods are analyzed on the basis of a survey of 1,600 companies positioning themselves as specializing in Social Computing and Crowdsourcing.  The authors’ most important conclusions are as follows.

1. Social computing is developing in two ways:
а. crowdsourcing technologies underlying social computing are becoming more and more sophisticated and efficient,
б. business processes are increasingly being socialized – they are purposefully changed through the integration of elements of social computing.

2. Both the ways pursue three goals:
а. solve more intricate tasks,
б. improve the efficiency of the organizational and management structure of problem solving processes,
с. increase the significance of “virtual career.”

3. The first goal (solve more intricate tasks) is achieved, first of all, by means of:
а. the decomposition of tasks into subtasks (structuring),
б. the accurate and subtle detection of the key problems of tasks (task problematization).

4. The second goal (improve the efficiency of the organizational and management structure of problem solving processes) is mostly achieved through:
а. better management of problem solving processes,
б. the advanced evaluation of the performance of participants and more sophisticated incentive schemes to motivate participation,
с. the formation of virtual teams, whose performance is taken into account to adjust the incentive schemes,

5. The third goal (give “career in the cloud” a higher profile) is mainly achieved through the use of “cloud ratings” (meta ratings) which:
а. evaluate a person’s contributions to crowdsourcing and/or open innovations campaigns,
б. are taken into account when assessing the “class” of every participant at the beginning of every new crowdsourcing and/or open innovation campaign/project.

Achieving the above three goals requires new social computing technologies.

Existing technologies of crowdsourcing and idea management do not yet allow all three goals together to be achieved.

This is the authors’ conclusion based on analysis of 1,600 existing systems (social applications, platforms, solutions) that deal in Social Computing and Crowdsourcing.

Among other things, the analysis shows the following.

- Most systems (83%) have only one mechanism for measuring the performance of individuals.  Only three companies employ more than three evaluation mechanisms. Note: Witology uses 14 mechanisms.
- Only 2% of companies can measure not only the performance of individual agents, but also that of virtual teams. Note: Witology can do this.
- None of the 1,600 systems surveyed boasts the possibility of building “virtual career” based on meta-ratings (“The idea of building a “career in the cloud” is a distant dream”).Note: Witology has such a possibility.
- Only one of the companies surveyed positions its technology as an effective crowd management tool i.e. a means of collective problem solving process management (“ScalableWorkforce.com is the only company we studied that advertises the importance of crowd (work-force) management”). Note: Witology’s sintellectual crowdsourcing technology is oriented toward crowd management.
- Only three of the systems discussed in the article are capable of forming virtual teams and taking into account the results of their work in incentive schemes (“Team-based compensation was used by only three companies we surveyed”). Note: Witology has such possibilities.

The analysis of the technological limitations of existing crowdsourcing and ideas management systems makes it possible for us to understand what directions of the development of these technologies are the most promising ones.

It may be particularly interesting for Russian readers that the Russian platform Witology already has many elements of the next-generation social computing technologies, which are missing so far in more than one and a half thousand systems surveyed by the authors of the article.

In other words, Witology’s sintellectual crowdsourcing is not so much crowdsourcing as crowdservicing.

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Sergey Karelov

Соучредитель и CTO Witology