Crowdsourcing and Risk-Management

Content

1. Introduction
1.1. Research Question
1.2. Background
1.3. Early Practice
1.4. Current Use
1.5. Limitations of Crowdsourcing
1.6. Risk Management
1.6.1 Aspects of Risk Management
1.6.2 Stages of Risk Management
1.7. Dissertation Aims & Objectives
1.8. Theoretical & Organizational Context
1.9. Contribution to the Field of Knowledge and Practice
1.10. Dissertation Outline
1.11. Summary and conclusion

2. Literature Review
2.1. Introduction
2.2. Crowdsourcing
2.2.1. Theory of Crowdsourcing
2.2.2. Evolution of Crowdsourcing
2.2.3. Approaches to Crowdsourcing
2.2.3.2. Paid Crowdsourcing
2.2.3.3. Competitive Crowdsourcing
2.2.4. Crowdsourcing Strategies
2.2.4.1. Collective Intelligence
2.2.4.2. Types of collective intelligence
2.2.4.3. Crowdcreation
2.2.4.3. Voting
2.2.4.4. Crowdfunding
2.2.5. Benefits of Crowdsourcing
2.2.5.1. Cost
2.2.5.2. Quality of Output
2.2.5.3. Ease of Use
2.2.6. Obstacles in paid Crowdsourcing
2.2.6.1. Crowd Responsiveness
2.2.6.2. Satisfactory results
2.2.6.3. Security and Privacy
2.2.7. Key Insights
2.3. Innovation
2.3.1. Open innovation
2.3.2. User innovation
2.3.3. Dimensions of innovation
2.3.4. Types of innovation
2.2.3.2. Paid Crowdsourcing
2.2.3.3. Competitive Crowdsourcing
2.2.4. Crowdsourcing Strategies
2.2.4.1. Collective Intelligence
2.2.4.2. Types of collective intelligence
2.2.4.3. Crowdcreation
2.2.4.3. Voting
2.2.4.4. Crowdfunding
2.2.5. Benefits of Crowdsourcing
2.2.5.1. Cost
2.2.5.2. Quality of Output
2.2.5.3. Ease of Use
2.2.6. Obstacles in paid Crowdsourcing
2.2.6.1. Crowd Responsiveness
2.2.6.2. Satisfactory results
2.2.6.3. Security and Privacy
2.2.7. Key Insights
2.3. Innovation
2.3.1. Open innovation
2.3.2. User innovation
2.3.3. Dimensions of innovation
2.3.4. Types of innovation
2.3.5. User innovation vs. Crowdsourcing
2.4. Crowdsourcing as a Business Model of Innovation
2.5. Approaches to Risk Management
2.5.1 Risk Management and Crowdsourcing
2.5.2. Innovation risks
2.5.3. Business risks
2.6. Applications of Crowdsourcing
2.6.1. Crowdsourcing in creative industries
2.6.2. Role of intermediaries in crowdsourcing
2.6.2.1. Research and development platforms
2.6.2.2. Marketing, design and idea platforms
2.6.2.3. Collective intelligence and prediction platforms
2.6.2.4. HR and freelancers' platforms
2.6.2.4. Open innovation software
2.6.2.4.1. Intermediary open innovation software services
2.6.2.5. Creative co-creation
2.6.2.6. Corporate initiatives
2.6.2.7. Peer production and P2P
2.6.2.8. Public Crowdsourcing
2.6.2.8.1. CafePress.com and CrowdSpirit.org
2.6.2.8.2. Funding Circle (Peer Production & P2P)
2.6.3. Management of Risks in Crowdsourcing
2.7. Conceptual Framework

2.8. Summary and Conclusion
3. Research Design and Methodology
3.1. Research Philosophy
3.2. Aim of the Study
3.3. Research Design
3.3.1. Sampling method
3.4. Appropriateness of Design
3.4.1. Consideration of research methods
3.5. Research Questions
3.5.1. Operationalization of survey questions
3.6. Population
3.7. Sampling Frame
3.8. Informed Consent
3.9. Confidentiality
3.10. Data Collection
3.11. Instrumentation
3.12. Validity and Reliability
3.13. Data Analysis
3.13.1 Data Analysis Framework and Process
3.14. Summary and conclusion

4. Analysis of findings
4.1. Introduction
4.2. Demographics
4.2.1. Gender
4.2.2. Age
4.2.3. Crowdsourcing experience
4.3. Analysis of data related to the research aims and objectives
4.3.1. Identify current practice of the commercial use of crowdsourcing
4.3.2. Adaption and relevance of Crowdsourcing to different departments
4.4. Determination of risks involved in the practice in Crowdsourcing
4.4.1. Risk level determination and risk awareness
4.4.2. Opportunistic risk awareness- benefits over risks
4.4.2.1. Growth benefits
4.4.2.2. Cost benefits
4.4.2.3. Scale and diversity benefits
4.4.2.4. Benefit of personal development
4.4.2.5. Application benefits for policy makers
4.4.2.6. Effect on staff performance and work environments
4.4.3. Analysed and allocated risk themes
4.4.4. Quantitative risk level assessment
4.4.4.1. Risk level determination and category analysis
4.4.4.2. Overall risk level assessment
4.5. Risk control and possible strategic solutions scenarios
4.5.1. Quality control
4.5.2. Enhancing motivation
4.5.3. IP protection and confidentiality
4.5.4. Financial risk mitigation
4.5.5. Crowd control
4.6. Conclusion and summary
4.6.1. Adopting basic principles, rules and guidelines
4.6.1.1. Values
4.6.1.2. Diversification of sources
4.6.1.3. Entry evaluation of crowd participants
4.6.1.4. Customer-Focus/ User-Focus

5. Discussion and Conclusion
5.1. Introduction
5.2. Crowdsourcing Practices
5.2.1. Open Innovation and User Innovation
5.2.2. Free Crowdsourcing
5.2.3. Paid Crowdsourcing
5.2.4. Competitive crowdsourcing
5.2.5. Civic engagement
5.2.6. Crowd labour
5.2.7. Acceptance of crowdsourcing
5.3. Risks and risk management measures
5.3.1. Turbulence risk
5.3.1.1. Managing turbulence risks
5.3.2. Leakage of sensitive information
5.3.2.1. Managing confidentiality risks
5.3.3. Quality risks
5.3.3.1. Managing quality risks
5.3.4. Financial risks
5.3.4.1. Managing financial risks
5.3.5. Employment law risks
5.3.5.1. Managing employment law risks
5.3.6. Intellectual property ownership risks
5.3.7. Low participation
5.3.7.1. Managing motivation risks
5.4. Conclusion
5.5. Implications and Conclusions
5.5.1. Contribution to research
5.5.2. Contribution to practice
5.6. Limitations of the research
5.6.1. Choice of research instrument
5.6.2. Level of experience

Abstract

The business world has become globally competitive. Innovation is less frequently undertaken in-house, in a closed and integrated way but transformed more into an open call where many actors are involved in the different steps of the innovation process. It is therefore, imperative for organizations to gain competitive advantage by adopting new technologies to apply in company operations. Crowdsourcing Innovation encourages companies in their effort to re-evaluate as well as re-design business processes and diversify a greater task to a heterogeneous group of people for a common goal. The principal objective of this thesis is to identify crowdsourced innovation models and examine the usage in a business context in order to evaluate and establish methods of managing crowdsourcing innovation risks in organizations. The increased potential of crowdsourcing as a tool for business development and innovation has prompted extensive research into this crucial field by academia. This thesis is an added endeavour to crowdsourcing investigative studies and makes a significant contribution to literature as well as commercial practice.

In an effort to outline the research objectives, the research questions seek to provide an understanding of the risks associated with crowdsourcing, the potential of the concept to improve business practices and possible strategies that can be used to manage the identified risks. An initial investigation of the extant literature traced the growth and development of crowdsourcing since its inception and revealed that the concept is marred with criticism and controversy such as economic constraints, social ramifications and ethical implications. An additional objective of the literature review was to critically scrutinise the assessment of crowdsourcing to enrich companies with near infinite problem solving capacities, its ability to pay for solutions, not failures and most importantly, to solve problems possibly faster and with reduced cost of operations. To enable the development of a conceptual risk-framework the thesis gives a detailed analysis of risk management, while defining fundamental aspects of risk regulations.

The study encompassed a qualitative collective survey methodology, which was applied in form of a prepared online questionnaire template to a systematic random sample. A qualitative study with 151 globally sampled industry experts and customers of leading intermediary crowdsourcing platforms has been conducted over an eight-month period. In addition, one-to-one structured formal interviews have been recorded. The selection of participants has been defined by a systematic random sample. The analysis of the aggregated data revealed that the disruptive nature of innovation through crowdsourcing effects every department within an organization. This finding contributes to practice showing that crowdsourcing was particularly not only prevalent within Research and Development and Marketing and Sales, but also involved Human Resources, Logistics and Accounting among others. Even though the overall perception in favour for the opportunities to excel innovation was high, possible risks for adoption were identified. The thesis contributes to academic knowledge and practice by identifying those risks - especially turbulence risk as the most prominent source of risk, followed by organizational, societal risk and financial risk among others. In an attempt to provide a deeper comprehension of the applicability of crowdsourcing the study delivered potential strategic solutions to the risks identified.

The thesis provides a conclusion, which analyses the perceptions held about crowdsourcing by diverse stakeholders such as its immense contribution to sharing of business ideas, collecting business capital and involving customers to drive innovation.

Finally, the dissertation findings form a platform for a proposal of recommendations to identify limitations of crowdsourcing, which include effective risk management through ensuring anonymity of an organisations data, and restriction of access to sensitive materials, among other security measures. This exploratory research seeks to provide a multidisciplinary path for future academic research. From the viewpoint of practical use for managerial decision guidance the study provides new and valuable information on how the crowdsourcing concept advances business practices and how possible risks and restrictions can be managed. These findings are to encourage as a guide in recommending where future researchers could focus or advance the field of study.

R11

Certificate of Research

This is to certify that, except where specific reference is made, the work described in this thesis is the result of the candidate. Neither this thesis, nor any part of it, has been presented, or is currently submitted, in candidature for any degree at any other University.

Signed: …

Candidate

Signed: …

Director of Studies

Date: …

List of Tables

Table 1. Companies, registered workers and gross payments

Table 2. Cases of Crowdsourcing

Table 3. User innovation principles

Table 4. Development of Innovation

Table 5. Characteristics of business models using Crowdsourcing as a key-source

Table 6. Main risk categories associated with Crowdsourcing

Table 7. Research conducted on motives for participation

Table 8. Risk to traditional innovation and innovation through Crowdsourcing

Table 9. Overview of research on integrated and distributed innovation perspectives

Table 10. Descriptive statistics on risk levels of Crowdsourcing

Table 11. Motivation for participation in Crowdsourcing

Table 12. Summary of Risks identified

Table 13. Risk management avoidance matrix

Table 14. Implications and conclusions

Table 15. Contribution to research

Table 16. Contribution to practice

List of Figures

Figure 1. Risk impact matrix

Figure 2. Conceptual intersections of crowdsourcing

Figure 3. Approaches to crowdsourcing

Figure 4. Paid Crowdsourcing and work type

Figure 5. Expanded form of collective intelligence

Figure 6. Innovation continuum

Figure 7. Continuum of crowdsourcing practices and cost

Figure 8. Engagement pyramid

Figure 9. Crowdsourcing landscape by examples

Figure 10. Conceptual framework

Figure 11. Data analysis process

Figure 12. Commercial use of crowdsourcing

Figure 13 Personal development as benefit of crowdsourcing

Figure 14 Benefits to policy-makers

Figure 15 Staff performance improvement as crowdsourcing benefit

Figure 16 Company performance improvement as crowdsourcing benefit

LIST OF ABBREVIATIONS

Abbildung in dieser Leseprobe nicht enthalten

1. Introduction

1.1. Research question

In the world of business and technology, the practice of crowdsourcing has become a valuable commercial tool for product development, idea generation and trouble-shooting (Howe 2008; Saxton et al. 2013). This research seeks to validate its use as a tool in a business context, while developing a risk framework addressing all organisational functions. In the United States of America and the European Union, policy makers have taken steps to include crowdsourcing as part of their decision-making processes (Hoover 2009). A recent competition held by software testers used crowdsourcing to successfully identify and isolate 600 flaws in popular search engines, such as Google, Bing, and Yahoo (Flinders 2009). Exploration on Mars has also been facilitated with crowdsourcing. NASA, with the assistance of Microsoft, uses crowdsourcing to help sort through the lengthy data analysis process of counting craters and matching high to low-resolution photos (Viotti et al. 2012). Although crowdsourcing is a relatively new phenomenon, organizations increasingly recognize its capability and potential deployment (Andriole 2010). This is perhaps due to the assertion that crowdsourcing saves both time and money by using the skills of a large, voluntary workforce to solve problems and to expedite research (Flinders 2009; Viotti et al. 2012).

In this thesis, innovations in crowdsourcing will be examined in order to determine its contribution to business settings and to analyse the risks involved. As Nolan observes, “innovation is simply group intelligence having fun” (cited in Libert and Spector 2007: 20). While a playful attitude towards crowdsourcing may be important, it is equally important to assess its use and risks within the business context. Short product life cycles, high product failure rates, and the increasing heterogeneity of consumer needs have recently put considerable pressure on innovative activities (Motzek 2007).

As innovation projects grow and develop over time, the risks of managing the participating crowd have an impact. Goldman and Gabriel (2005: 174) expressed the risks to project managers in crowdsourcing projects, stating: “project leaders and other managers advance by taking responsibility for a tough project and then deliver. But to some this can appear hard to do when control is relinquished to others”.

This dissertation will consider the risks and limitations associated with crowdsourcing, including the issue of trust and reliability. The aim of this research is to illuminate the possibility of mitigating risks associated with crowdsourcing innovation. The objective is to provide an answer to the question ‘How to manage risks of crowdsourcing innovation in companies?’

The research will begin by tracing the development and growth of crowdsourcing practices. It will also provide a context for the use and application of risk management in a business context. Finally, it will consider the link between the two. This analysis will form the basis for the research conducted. Although there is a growing awareness amongst practitioners and academics alike regarding the relationship between these two areas, existing research has not caught up with current practices.

1.2. Background

Crowdsourcing is a relatively new phenomenon. It traces its roots in both technological developments, as well as with the growth of the Internet and the ubiquity of smart mobile devices (Howe 2006b). Howe (2006b:1) first utilised the term in the June 2006 issue of Wired magazine:

“ Technological advances in everything from product design software to digital video cameras are breaking down the cost barriers that once separated amateurs from professionals. Hobbyists, part-timers, and dabblers suddenly have a market for their efforts, as smart companies in industries as disparate as pharmaceuticals and television discover ways to tap the latent talent of the crowd. The labour isn ’ t always free, but it costs a lot less than paying traditional employees. It ’ s not outsourcing; it ’ s crowdsourcing. ”

The above excerpt is an important one as it shows the main differences between “outsourcing” and “crowdsourcing.”

While both, outsourcing and crowdsourcing are products of the current technological phase (Levinson 1998), crowdsourcing, unlike outsourcing, has a much broader application. It is apparent that crowdsourcing would not be possible without the Internet and the rise of mobile computing (Surowiecki 2004). The World Wide Web 2.0 plays a crucial role in supporting this function. Affordable and easy access to the Internet and its attendant technology means that organizations can reach more people than ever before. Just as one can market to millions with a click of a mouse, one can also potentially reach millions of experts, or at least knowledgeable enthusiasts, in precisely the same way. As Howe (2009) points out, crowdsourcing enables businesses to collaborate with countless people in a relatively straightforward and cost-effective way. Oxford University adopted a crowdsourcing approach to its Galaxy Zoo project (Eaton 2009). In this approach, the public was able to provide input for a project to map the galaxy. As a result, the University was able to complete the task in four months, rather than the two years it would have taken, relying on internal staff and resources. Defining crowdsourcing as a new internet-enabled business model to harness the creative power of several individuals, Howe (2006b:5) offers the following definition:

“ Crowdsourcing represents the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in form of an open call. This can take the form of peer-production (when a job is performed collaboratively), but is also often undertaken by sole individuals. The crucial prerequisite is the use of the open call format and the large network of potential labourers. ”

Although Wikipedia (Wikipedia.org, 2012) is not considered a reputable academic reference, it seems particularly appropriate to use it in this instance because Wikipedia is a prime example of crowdsourcing and illustrates both the strengths and weaknesses of this practice. Wikipedia’s entries are crowdsourced, which means they are written and edited by people around the world. As a result, some entries reflect original research and genuine insight while others are blatantly plagiarized from other sources. Many entries provide good overviews of specific subjects; however, others reflect either the ignorance or personal prejudice of an author (Antin and Cheshire 2010). In spite of its many flaws, Wikipedia remains a first stop for many people wishing to learn about a particular subject. While it is generally accepted that information found on Wikipedia is not always accurate, most Web users trust the system of checks and balances to eliminate the worst inaccuracies (Lopes and Carrico 2008). The continued popularity of this website is a testament to both the power and shortcomings of crowdsourcing in a contemporary culture. Wikipedia even tends to be more accurate on dynamic and generally head-to-head with encyclopaedia Britannica (Giles 2005).

Although Howe’s (2006b) definition provides a useful starting point, crowdsourcing may be defined in numerous ways. Aside from this, it must be noted that crowdsourcing is a phenomena arising of the globally interconnecting nature of the Internet, not academia. Therefore, one must consider how the term is used in this context. Wikipedia defines the concept as follows:

Crowdsourcing is a neologism for the act of taking tasks traditionally performed by an employee or contractor and outsourcing them to a group (crowd) of people or community in the form of an open call. For example, the public may be invited to develop a new technology, carry out a design task (also known as community-based design and distributed participatory design), refine or carry out the steps of an algorithm (Human-based computation), or help capture, systematize or analyse large amounts of data.

Although it reflects an important shift in culture, the power of crowdsourcing is also limited by the gap in Internet access, since a significant portion of the world population is still not able to access the Internet (Fox 2005). Of those who do have access, many do not have high- speed connections that will enable them to participate in the same way as those with broadband connections (Fox 2005). Furthermore, providing Web access to the disconnected does not guarantee participation (Winner 2003). Simultaneously, crowdsourcing has come to define our interaction with the world of knowledge. Internet users expect businesses to give them a place to voice their comments and share their views, whether it is an entry in Wiki, a book review on Amazon or a reaction to a new product. The question of whether to regulate crowdsourcing ventures therefore arises (Rossiter 2006).

Several authors trace the roots of crowdsourcing to an open source movement in software (Libert and Spector 2007; Bacon 2009; Howe 2009). Open source is defined as processes involving permission to access the essential elements of a product (such as source code for software) with the aim of encouraging collaboration to improve the product (Perens 2009). It is often linked with software development, though its application need not be limited to this context, but to product development in general. The philosophy behind open source is that providing several individuals access to the design stage and enabling them to develop a product outside of the constraints of traditional intellectual property law, will create an increasingly effective product that is not only developed collaboratively, but also freely available to everyone (Levy 1984; Himanen 2001). Open source grants the rich and the poor alike equal access to information.

In many ways, the open source movement is most effectively defined by its approach, rather than its specific activities (Weber 2005). While corporations such as Microsoft, IBM and Apple are all in the business of producing software; their approach to the process tends to be slightly different than those of the open source movements. Each corporation closely guards its developments and considers details about its applications to be trade secrets. These corporations create software to be sold and marketed as a product (Dalle et al. 2005). In contrast, the open source movement recognizes that software is a product; however, it does not seek to profit from its development. Instead, it suggests that software is a common need and, as such, its development and use should be available to all who need it (Weber 2005). Linux is one of the best-known exemplars of open source software. Over the years, Linux has been developed and refined by a collection of individuals working collectively on a global basis. These individuals come from a wide range of occupations and backgrounds. Generally, there may be those who are enthusiastic to work from home while others may prefer to work in a laboratory or in a professional environment. The systems they have created are widely acknowledged as being highly effective and efficient (Weber 2005). Judging by the number of Personal Computers (PC) in both the home and office, it is clear that Microsoft has won the marketing war. However, few people would argue that Microsoft created a superior product. Windows and its many variants are known for a wide range of glitches and crashes (Krapp 2011). The open source movement succeeded in achieving more than the creation of more effective operating systems. According to Howe (2009: 8), it: “revealed a fundamental truth about humans that had largely gone unnoticed until the connectivity of the Internet brought it into high relief: labour can often be organized more efficiently in the context of community than it can in the context of a corporation.” Crowdsourcing, Howe (2009) argues, could provide varying structures for compensating contributors. Thus it may be seen as a hybrid that combines the transparent and crowd- harnessing elements of open source into a profitable model for doing business, enabled through the Internet. Howe’s observation is an important one for several reasons. Firstly, itchallenges our preconceived notions about work. Many political and social theories have been devoted to the study of work and motivation (Steers et al. 2003). Howe’s (2009) observation challenges the basic assumptions of many of these theories, as well as those of corporate employers. While several theorists would agree that motivation is not solely based on wages or compensation, few would have predicted the willingness of people to work for free in these online projects (Herzberg, Mausner and Bloch-Snyderman 1993; Frey and Jegen 2001; Pinder 2008; Lanfranchi, Narcy and Larguem 2010). It is important, however, to consider the nature of these projects.

Secondly, Howe’s assertion defines the importance of community in this type of work activity. In the open source project, a variety of specialists, albeit with differing levels of education, accomplishments, and experience, were united by a shared goal, namely the creation of the open source software. These individuals shared a fascination with technical matters and were intrinsically motivated. The challenges of creating software appealed to them on an intellectual as well as a practical level. In addition, there was a sense of community that drove this project. The individuals involved share a genuine desire to create the optimum system and they believe that this could best be achieved through the collaborative efforts of all involved (Postigo 2003: 597).

Thirdly, it highlights the importance of the Web to crowdsourcing. The connectivity of the Internet plays a crucial role in the organization and motivation of the collaborative workforce. It would be physically impossible to gather a workforce of this size and scope without the use of the Web. In a crowdsourced project people from around the world are able to communicate quickly and work at any time. New ideas are instantly exchanged, and changes or recommendations could be made in real time.

In many respects, crowdsourcing evidenced in early projects such as the open source movement is anathema to corporate culture. While these movements are largely apolitical, the fundamental principles underpinning open sources of information are in direct opposition to a purely commercial framework (Perens 2009). Businesses seek to sell products at a profit while open source movements focus on research and development as well as production. Furthermore, any profits generated are usually devoted to defraying some of the costs involved. Thus, the non-profit nature of the open source movement appears to inspire many individuals to contribute their time and efforts. In addition, the most successful open source projects have elements of both capitalism and communism (Perens 2009). It is a challenge for businesses to provide a framework for crowdsourcing that can promise the same rewards. Working toward a collective goal has much more appeal than working for the benefit of a multinational corporation. Alternatively, there is also a need to acknowledge that active contributors come from many different walks of life, and their motivations differ widely. Therefore, the overall strength of a crowdsourced project results from the diversity of its users and participants rather than their homogeneity. This diversity of interests leads to the generality of the results, the development of useful pathways that might never have been considered, and the continued support of the project when business falters (Perens 2009). The following subsections describe the development of crowdsourcing by identifying examples of both current and early practices. In a next step, the limitations of crowdsourcing will be considered and some of the drawbacks and existing controversies identified. Finally, the relationship between risk management and crowdsourcing will be outlined to provide a useful context for the discussion and analysis that follow later on in this dissertation.

1.3. Early practice

As outlined in the previous section, crowdsourcing can trace its origin back to collaborative efforts such as the development of the Internet as well as the open source movement. The examples given stressed the collaborative nature of crowdsourcing as well as its tendency to promote the public good over profits. It is important to note, however, that crowdsourcing has been used in a number of commercial settings. In this subsection, early examples of crowdsourcing will be discussed. These examples will be drawn from several sources, including knowledge-based projects such as the Galaxy Zoo initiative, and commercial endeavours such as those that took place with apparel companies, like Threadless.

First launched in 2007, Galaxy Zoo had a simple objective. Users were invited to survey and classify data, making simple determinations. The data consisted of approximately one million images taken by a robotic telescope as part of the Sloan Digital Sky Survey (Source: GalaxyZoon.org). Participants would take a small section and review the images. They looked for galaxies in these images and assigned them to one of two categories: elliptical or spiral. While the task itself was not difficult, the sheer volume of data made its completion by ordinary means overwhelming. Response to the project far exceeded the expectations. Initially it was predicted that the project would take three to four years to complete; however, it was finished ahead of schedule and a second phase was recently launched (Charman- Anderson 2009). The high level of respondents has confirmed the accuracy of the data.

While project coordinators initially anticipated a risk for low participation to the extent that each image would receive a maximum of 10 views, or ‘clicks,’ the project generated 10 million views in its first month and overall exceeded expectations. Dr Chris Lintott, a researcher overseeing the project noted: you can have confidence, as we can say, “ 100% of people think that ’ s a spiral galaxy, so it ’ s really, really spirally ” (Charman-Anderson 2009:

2). The response to this project was overwhelming, and enthusiastic volunteers from all over the world were flocking to the site to vet data.

Wikipedia may be controversial however, it is undeniable, that close to five million people use it every month (Libert and Spector 2007). Based on the traditional format of an encyclopaedia, it is a web-based document that is created and maintained by a community of volunteers and readers. While the number of entries continues to grow daily, at present, it is estimated that there are just over three million entries on a wide range of topics, which includes everything from pop culture to history, and theoretical concepts to political discourses. Wikipedia employs only five people; however, its volunteers number in the hundreds of thousands - if not millions - worldwide (Howe 2009). Due to the anonymity of its volunteers and the ability for any visitor to edit most entries, the reliability of Wikipedia has been brought into question. The site, however, has implemented a number of protocols in order to ensure that its entries are accurate and guarded against vandalism. For example, some entries are closed in order to prevent tampering. The entry for a public figure, such as presidents of countries, is semi-protected in order to prevent additions that might be libellous.

Wikipedia´s founder Jimmy Wales is aware of the risks and limitations of the site and states (Denning et.al. 2005:2):

“ Wikipedia contains no formal peer review process for fact-checking, and the editors themselves may not be well-versed in the topics they write about.”

To prevent risk, a background editorial process has been established. However, no one guarantees the accuracy or the authenticity of any information provided in it. To date, there is yet no process for subject-matter experts to review the articles. Although it provides processes for the addition of facts into an article by others, it does not ensure that the full range of human knowledge, past and present, is represented. One of the processes used by the system is that anonymous users cannot make changes to an entry, but well-respected users within the community are allowed to do this. The criteria are as follows: a user must have a confirmed account, as well as record of having made edits previously to Wikipedia. In addition, users are able to make feedback about entries. Wikipedia may flag other entries, which are not protected. These flags will indicate that users have raised some questions about the content of the material. The warning may indicate that the information is either not reliable or may be biased. While the user still needs to use his or her discretion, this method does help guard against potential abuse. Critics often accuse Wikipedia of letting down our culture; however, as Howe and others point out, Wikipedia has succeeded where traditional encyclopaedias have failed. Wikipedia lets users cut out the middleman and access the information they want freely (Howe 2009).

Amazon is acknowledged as one of the pioneers in the field of crowdsourced consumer feedback and recommendation (Libert and Spector 2007). While the company revolutionized the face of retail, both on and offline, it has made an important contribution to the practice of crowdsourcing . Amazon’s online reviews have become a crucial source of information to countless users. Nothing demonstrates a product’s flaws or failings quicker than several poor reviews on Amazon. Accordingly, a cautious consumer who is looking to purchase a new camera may be dissuaded from purchasing a particular brand or model if they see that ten users have reported the item as being defective. The reviewing process also allows the community to share its experiences and insights. This process is one that appeals to an innate part of our humanity. As Godin (2008: 63) points out in his survey of online reviews:

“ I don ’ t know about you, but I want in [...] I want to post my own reviews; I want to join this tribe. If they ask me to pitch in, I will. I ’ m in. Others will scoff and move on, wondering what the obsession is all about. That ’ s what makes it a tribe, of course. There are insiders and outsiders. ”

It is clearly apparent that crowdsourcing appeals to an innate desire to belong and share (Kleemann et al. 2008). In a world that is becomingly increasingly fractured and isolated, it is easy to see the appeal of posting online reviews. The retail clerk may not care what one thinks of the product, but there are others who do. One feels kinship with others who face the same problems. If one’s view is voted as being helpful, there is a feeling of accomplishment or acceptance. While it is possible that this process can be subverted, it is surprising how astute most users and commentators are at identifying bias.

Amazon’s ‘Mechanical Turk’ is a successful example of the human intelligence test (Ipeirotis, Provost and Wang 2010). With this platform, a certain pay amount is offered to those who successfully complete tasks. Registered users who have logged in can claim tasks and complete jobs (Tapscott and Williams 2006). Casares-Giner et al. (2011) believes that the implementation of web 2.0 technology and the rise of mobile ubiquity through modern smartphones have greatly impacted businesses of today. Previously, top managers, or specific research and development departments, were responsible for generating ideas to initiate progress within the business (Cassiman and Veugelers 2002). This hierarchical approach was challenged with the advent of web 2.0 technologies, namely the introduction of social networking sites (van Zyl 2009). These sites led the way to open innovation, replacing the prior ‘closed process’ approach that had been used in business for a significant duration. This process has changed, giving an up-lift to business practices (Casares-Giner et al. 2011). Kleemann et al. (2008) investigated the phenomena of crowdsourcing and the outsourcing of work to the public over the Internet.

This phenomenon is made possible by technological innovations, but the proof of important change is in the relationships between organizations and their customers. During the initial stages, the customer is the reactive influencing factor. Ultimately, that particular process is under the control of commercial firms. It ends with the negative and positive outcomes of crowdsourcing for the future work of the organization.

In his book-length examination of crowdsourcing, Howe (2009) identifies an early example of the phenomenon in a T-shirt company Threadless (www.threadless.com 2012), which was established by two friends. Their business plan was simple: they liked to wear cool T-shirts, and they knew that there was a market for them. The challenge was to design and promote desirable apparel.

The Internet made this possible. Designers were invited to post their designs on the website, and users were invited to vote on them. The voters were drawn from the community. Designers would enlist their friends and supporters to vote for the products, but the audience continued to grow exponentially as the reputation of the company grew. Consumers liked what they found on the Threadless website and told their friends. People enjoyed the collaborative process. While consumers always had the choice of voting with their wallets, Threadless offered a real opportunity to provide feedback. As Howe (2009: 6) observes, “Threadless really isn ’ t in the T-shirt business, what it sells is community”. Threadless was able to identify its target audience and sell to the audience successfully, using the basic principles of crowdsourcing, while turning a steady profit.

Cambrian House, a Canadian-based company, was established in 2006 as a platform for crowdsourcing. While the business model proved ultimately unsuccessful, the company had 50,000 members at its peak (source: CambrianHouse.com). Cambrian House recognized that there was a gap in the market and sought to address it. Their strategy was to provide a clearinghouse for crowdsourcing. Businesses that were unable to conduct crowdsourcing could hire Cambrian House to do the work for them. The business failed, because Cambrian House was unable to sustain sufficiently high levels of input. Many of the ideas generated were either unworkable or poorly conceived. Ultimately, the business did not manage to build an appropriate community. Howe (2009) acknowledges that this failure is not surprising and places it in the context of the “tech and web” boom of the 1990s, where initiatives launched and failed with great regularity. Hence, when an idea is implemented, there are always two possibilities, success or failure. The element of surprise is inevitable.

1.4. Current use

The examples given in the previous section were selected to illustrate the earliest uses of crowdsourcing. While the phenomenon of crowdsourcing is still a new one, it can already be defined by certain characteristics. The projects initiated by Oxford University reflect the spirit of volunteerism and intellectual curiosity that many crowdsourcing participants possess (Eaton 2009). Threadless and Amazon have set examples and have demonstrated that crowdsourcing can shape and drive commercial ventures. This subsection will focus on the innovative uses of crowdsourcing and how crowdsourcing has shaped the way that individuals approach news and political stories and identify the actual changes that crowdsourcing has made. In addition, new web ventures, including social media, will be examined. Finally, the relationship between Google and crowdsourcing will be considered in order to help to identify emerging trends that are taking place due to crowdsourcing. It will also provide context for the discussion and analysis that follows later in the chapter.

The 2008 US presidential campaign demonstrated not only the power of the Internet, but also the power of crowdsourcing. Voters were able to raise issues and questions through various media platforms, and the immediacy of the web helped to shape issues and politicians’ responses. Obama and his administrative team have become innovators, and have used crowdsourcing and new media during and after their political campaign. One example of this is the website Change.gov (2010), which was established during the transitional period between Obama’s election and inauguration (Howe 2009). The website allowed visitors to submit questions to the new president. Administered in part by the Google Moderator tool, the “Open for Questions” section gave people the opportunity to raise their concerns and to address their most pressing issues (Schonfeld 2009). The feedback received on a wide range of topics, including healthcare and military reform, continues to impact the President’s approach to the issues. In addition developments are currently underway to adopt a crowdsourcing approach to policy making (Hoover 2009). While administrations have

typically sought input from the public through a number of means, technologically-supported crowdsourcing is likely to yield far more meaningful results than traditional methods; i.e. town hall meetings (Herzog 2009). Crowdsourcing has also been adopted as a grassroots democracy movement. For example, in the 2008 election, NPR used Vote Report, which was hosted on Twitter, as a way of reporting on problems around the country. The posts formed an interactive map that identified where there were long lines, broken voting machines, or other problems (Source: www.npr.org/votereport). These reports helped draw attention to problems within the electoral system, which were brought to light during the 2000 election following the “hanging chad” fiasco. It would have been impossible for any news agency, either individually or collectively, to cover every voting station. However, by enlisting reports from users all over the country, it was possible to identify where the problems were. This use of crowdsourcing is invaluable, as it provides transparency in the country’s electoral processes. Similar initiatives to Voter Report are being considered around the world (Hoover 2009; Howe 2009). The impact of crowdsourcing has been felt in news media and reporting - also known as citizen journalism, helping to shape the way events are reported (Howe 2009). For instance, breaking events, such as terrorist attacks or natural disasters, are often communicated by eyewitnesses through a variety of mediums, including telecommunications and the Internet. There is a growing tendency amongst newspapers to give their readers an increased scope to submit articles for publication (Howe 2009). While these items may range from first-person accounts to press releases, the focus on the individual is the important change. While newspapers were once dismissive of such contributions, they now recognize their importance (Howe 2009). As Roberts from Guardian´s crowdsourced news desk describes:

“ We're constantly trying to tweak the different ways we communicate with readers to make these things work and it has to be said the ones that work best are the focused ones ” .

(McAthy 2012: 2) Crowdsourcing not only provides them with access to breaking news and ensures a higher degree of relevancy for readers, but it also helps to provide a more inclusive and representative view. While traditional media reflect the perspective and concerns of a largely homogenous professional class, crowdsourcing allows for different voices to be heard as Shirky (2008: 65) points out:

“ The mass amateurization of publishing undoes the limitations inherent in having a small number of traditional press outlets ”.

In many respects, social media have evolved alongside crowdsourcing as a means of providing a context and format for the generated content. Tapscott and Williams (2008: 47) observe, the current generation differs significantly from previous generations:

“ This is the collaboration generation for one main reason: Unlike their parents in the United States who watched a tremendous amount of hours of television per week, these youngsters are growing up interacting ” .

Moreover, Tapscott and Williams (2008: 47) argue that this generation has a very different set of expectations:

Rather than being passive recipients of mass consumer culture, the Net-Generation spend time searching, reading, scrutinizing, authenticating, collaborating, and organizing (everything from their MP3 files to protest demonstrations). The Internet makes life an on-going collaboration, and this generation loves it. They typically can ’ t imagine a life where citizens didn ’ t have the tools to constantly think critically, exchange views, challenge, authenticate, verify or debunk. While their parents were passive consumers of media, youth today are active creators of media content and hungry for interaction.

Those among the net-generation have grown up with the expectation that their opinions, views and thoughts will be heard. This is one of the reasons why social media have become so important. Sites such as Twitter (twitter.com 2011) and Facebook (facebook.com 2011) provide users with the opportunity to share their opinions and articulate themselves on the issues that are important to them. Although the extent of such media is broader then ever before, and therefore even more demanding of our analytical attention, radical alternative media express an alternative vision to hegemonic policies, priorities, and perspectives.

As businesses begin to recognize this, companies have developed a presence on social media websites and other networking sites in order to provide consumers a method to demonstrate support and provide valuable feedback (Qualman 2012). In addition, platforms such as blogs provide users with an opportunity to share their views through posts or comments, which are then sourced by businesses via search engines. In many respects, social media has been responsible for refining the process of crowdsourcing. For example, a movie executive need only enter the name of his or her latest film to access the most up-to-date consumer feedback on Twitter or collaborative filter approach on a website like Rotten Tomatoes (Amatriain et al. 2009).

A common example of this is Google (google.com 2011) according to Tapscott & Williams (2008: 41) does Google represent the embodiment of crowdsourcing:

“Google is the runaway leader in search because it harnesses the collective judgments of Web surfers. Its PageRank technology is based on the idea that the best way to find relevant information is to prioritize search results not by the characteristics of the document, but by the number of sites that are linking to it”. Howe (2009: 279) describes it as the “best indicator of the long-term viability of the practice”.

Google and it´s academic pendant Google scholar (scholar.google.com 2011) has a long tradition of crowdsourcing — it not only offers cash rewards for new ideas, but also tests most of its developments, from Gmail to Google Documents, using input from the public. Google has released a new crowdsourcing initiative. It has been determined that the company will make use of public input to develop its map data (McGee 2009). There are several initiatives underway, the first is to invite users to submit data for 3D mapping and the second is to encourage users to identify any elements of the map that require editing. Both of these initiatives will draw on local expertise and interests to ensure the mapping project is completed quickly and efficiently.

1.5. Limitations of crowdsourcing

The use of crowdsourcing is not without criticism and even controversy (Peng 2011). This subsection explores the ethical implications, economic aspects and social ramifications of crowdsourcing. The discussion will be augmented by an analysis, which is presented later in this section.

Crowdsourcing involves a host of ethical concerns, of which some are not generational. The validity and reliability of a document is derived in part from its authorship; therefore, an identifiable author who can verify the authenticity and originality of a specific document provides proof of its reliability. Furthermore, the creation of a document from multiple unaccredited sources is comparable to plagiarism. In fact, some might suggest that crowdsourcing devalues the contribution of the individual and makes it more difficult to support traditional research. Moreover, the cost-effectiveness of crowdsourcing potentially devalues both the work of researchers and other professionals and Intellectual Property (IP), which becomes subject to abuse. Most importantly, crowdsourcing further disenfranchises people on the margins of society (Scholz 2012).

A person’s access to the Internet, computers, and other forms of technology determines the level to which he or she can participate in crowdsourcing. Thus, the economically advantaged often have a disproportionate amount of influence over the process (Stern, Alison and Shaun 2009). Furthermore, the economics of crowdsourcing are not always straightforward. In a project such as Galaxy Zoo, crowdsourcing was a highly successful method of processing the available data in a timely, cost-effective manner. Volunteers enjoyed the prestige of being involved in this project; for many, their contribution was a secondary activity, similar to a hobby (Raddick et al. 2009). The failure of Cambrian House in 2006 shows that the concept of crowdsourcing can be a costly venture. The business was unable to develop a model that generated meaningful results for minimal financial reward. The ideas Cambrian House tapped into were largely worthless; no one could be convinced to provide useful ideas for free. Most importantly, the successful management and integration of data obtained from crowdsourcing

has proved too much of a challenge for many businesses. As the Gartner Research findings (quoted in Libert and Spector 2007: 5-6) indicate:

“Many businesses do not have the time or resources to make good use of crowdsourcing initiatives”.

Finally, the social implications of crowdsourcing are still being assessed (Rushkoff 2005). While crowdsourcing promises greater transparency, it fails to engage with all members of society. Crowdsourcing is chiefly the domain of the privileged and educated classes (Lenhart and Madden 2005; Van Dijk 2006). Moreover, the views represented by this group are not necessarily accurate. If there is overrepresentation of a particular group or point of view, crowdsourcing runs the risk of clouding the issue in many instances. In order to eliminate such risk, specialized intermediary companies such as Crowdflower provide a leveraged representation of crowdworkers.

1.6. Risk management

Risk management may be defined as an organized process that identifies, analyses, and responds to risk (Crockford 1986). It does so by applying risk-management principles and strategies to a specific process or project. In this context, the process or project may refer to either an on-going or specific instance of crowdsourcing. According to the classification provided by Krantz (quoted in Tusler 1996: 1),

“Risk is characterized by a combination of constraint and uncertainty. These usually manifest as limitations and are faced by most businesses and corporations during the development of new projects or implementation of current ones. Limitations can be created by social, environmental, technical, and logistical factors.”

Because limits exist in every context, organizations need to find ways to limit the consequences of these constraints and develop strategies in order to reduce uncertainty. Risk management is a multifaceted process (Crockford 1986). The first step is to measure or assess the risk factors. The second step is to develop a strategy to manage or control the risks identified. Once the risks have been assessed, it is necessary to develop a prioritization process to determine what risks carry the greatest loss, and which risks have the greatest probability of occurring or recurring. Risks with a high probability of occurring are a top priority and are dealt with first, while risks with a lower probability of occurring and fewer possible losses are secondary. The level of a risk is determined by the law of large numbers. This principle simply states that a situation outcome becomes more predictable as the number of instances increase. Implementing this system of prioritization may be a difficult course of action. It can be complicated to choose between risks with a high probability of occurring and lower loss, and risks with a high potential loss, but a low probability of occurring.

1.6.1 Aspects of risk management

Alexander and Sheedy (2005) define four aspects of risk management as follows:

Avoidance: The avoidance technique consists of refraining from potentially dangerous activities. With this approach, any activity that carries a risk of injury or loss would be avoided. For example, a school or community may choose to adopt the avoidance approach when developing a playground. Certain pieces of equipment, such as slides, may be prohibited since their use carries a high probability of injury. Users may fall off the sides, slip on the ladder, or hurt themselves when they land at the bottom. Considering these risk factors, it may seem sensible to prohibit slides in favour of safer equipment. Avoidance may appear to be a fail-safe approach to eluding risk; however, excessive avoidance sometimes results in missing potential gains. Returning to the example of the slide on the playground, this equipment might help children develop their sense of balance and build strength. Some might argue that exposure to moderate levels of risk would ultimately benefit the children by allowing them to learn from the situation. Therefore, it is important to carefully weigh the advantages and disadvantages before adopting the avoidance approach.

Reduction: This approach relies on finding methods to reduce the risks or the severity of any potential loss. Since almost every situation carries a certain amount of risk, this technique allows people to minimize the consequences while still pursuing a wide range of activities. For example, any motorist risks injury or even death every time he or she gets behind the wheel. It is not feasible, however, for most of us to stop driving, as many of us depend on our vehicles for both our personal and professional activities. Therefore, we take certain measures and precautions in order to ensure our safety. For example, we can reduce the potential hazard to our health and well-being by avoiding unsafe activities, such as consuming alcohol or speeding. While we cannot control what other drivers do, it is possible to develop our own skills and learn to drive defensively. This approach depends on developing a full understanding of the existing risks and a carefully thought-out plan to minimize them.

Prevention: As with the above-described approach, the prevention technique seeks to minimize risks through careful planning. This method identifies measures that will prevent loss or risk. Returning to the example of the playground slide, this technique would consider the inherent risks and develop a method of addressing them. For instance, there is a possibility that a child might jump or fall from the top of a slide. One way to prevent this from occurring would be to install a cover at the top of the slide. This would control the environment and prevent users from being injured in a fall. Although children would no longer be able to stand at the top of the slide, the cover would not interfere with their ability to use the slide. It is important that preventative measures do not interfere with the activity itself; otherwise, the positive effect would be mitigated.

Separation: The separation technique identifies risk and seeks to minimize hazards by separating them. For example, divided motorways reduce the risk of head-on collisions. This solution exemplifies the nature of the separation technique. It recognizes that motorists driving at high speeds may misjudge the distance and time needed to safely overtake another vehicle. Creating divided roads diminishes the potential for risk. The two directions of traffic are divided, which greatly reduces the possibility of a head-on collision.

1.6.2 Stages of risk management

This section will identify and discuss the four stages involved in preparing for effective risk management (Alexander and Sheedy 2005). These include risk identification, risk quantification, risk response, and risk monitoring and control. As indicated previously, risk management has changed significantly since its emergence in the 1970s when the primary focus was the conservation of resources (Tye 1980). The impetus behind risk management has shifted to the development of an effective strategy that allows organizations to not only protect themselves from loss, but also to grow and adapt to a changing marketplace (Egbuji

1999). Risk management is not only the responsibility of specialists and consultants. Managers at every level within an organization need to develop effective strategies in order to identify and mitigate the effects of risk on operational activities (Robinson and Robertson 1987). In this post 9/11 era, our understanding of risk management has expanded far beyond the fiscal security of board members, executives, and investors (Mundy 2004).

Risk Identification: In the risk identification stage, as its name implies, people involved identify and name the risks. Risk identification is a basic step in the risk management process, but it plays an essential role in effectiveness of any management approach (Tchankova 2002). A workshop approach can, as one choice of strategy, involve and engage different levels of management. This approach would allow for an open discussion and has the potential to either identify or avoid potential biases. Ideally, the views and experience of the group would be diverse enough to ensure that a balanced outcome is achieved. Brainstorming or listing risks are two strategies often used. It should be noted, however, that some research suggests that risk identification needs to evolve beyond the production of lists (Hillson 2003). The risks identified can often seem overwhelming. Hillson recommends using a risk breakdown structure (RBS). RBS is hierarchical and allows an organization to identify common themes and the distribution of risk (Hillson 2003). Different types of risks are usually involved in the businesses. As Turbit (2005) points out, generic risks exist in all types of projects, as they are inevitable to every company. Early risk identification, in conjunction with a comprehensive mapping of risk factors, enables an organization to overcome biases and to identify the appropriate measures to take in order to avoid or minimize the consequences of risk.

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