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.
Table of Contents
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
2.3.5. 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
4.5. 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. Setting Standards and reinforcing them
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
5.6.3. Points of view – relative perspectives
5.7. Recommendations for future research
5.7.1. Focus on a specific category of risks
5.7.2. Focus on a specific industry sectors
5.7.3. Obtain perspective of crowd participants and intermediaries
5.7.4. Crowdsourcing in the public sector
5.7.5. Accountability for the risks of crowdsourcing
5.7.5. Research agenda
Research Objectives and Themes
This thesis identifies crowdsourced innovation models and examines their usage in a business context to evaluate and establish methods for managing innovation risks within organizations. It explores the associated risks, the potential for improving business practices, and strategies to mitigate identified threats, with a particular focus on turbulence, organizational, societal, and financial risks.
- Crowdsourcing innovation models and their business integration.
- Risk management strategies within crowdsourcing processes.
- Categorization and impact of risks (turbulence, organizational, financial, IP).
- Motivation factors and participation in crowdsourced projects.
- Role of intermediaries and crowd control mechanisms.
Excerpt from the Book
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.
Summary of Chapters
1. Introduction: Sets the stage by introducing the research question and context of crowdsourcing as a business tool, identifying the primary research goal and dissertation structure.
2. Literature Review: Evaluates existing academic sources on crowdsourcing concepts, innovation models, and risk management strategies to provide a foundation for the research.
3. Research Design and Methodology: Explains the qualitative research design, detailing the methodology for surveying industry experts and the data analysis processes used.
4. Analysis of Findings: Presents the gathered data on demographic characteristics and practitioners' views, analyzing the identified risks and strategic solutions.
5. Discussion and Conclusion: Synthesizes the research findings, offers recommendations for future study, and concludes with a framework for managing crowdsourcing risks.
Keywords
Crowdsourcing, Risk Management, Innovation Models, Open Innovation, Business Strategy, Turbulence Risk, Intellectual Property, User Innovation, Collective Intelligence, Crowd Participation, Business Processes, Risk Mitigation, Qualitative Research, Survey Methodology, Intermediaries.
Frequently Asked Questions
What is the core focus of this dissertation?
The dissertation focuses on identifying crowdsourced innovation models and examining their application in business to develop methods for managing the risks associated with these innovation practices.
What are the primary thematic fields covered in the work?
The research covers the definition and evolution of crowdsourcing, its relationship with innovation, different types of crowdsourcing models, the associated risks (like IP or turbulence), and risk management strategies.
What is the main research objective or central question?
The central objective is to answer: "How to manage risks of crowdsourcing innovation in companies?" and to identify the specific risks involved when using crowdsourcing in a business context.
Which scientific methods were employed?
The study uses a qualitative collective survey methodology, including online questionnaires and structured one-to-one interviews, to gather data from industry experts and customers of crowdsourcing platforms.
What topics are discussed in the main body of the work?
The main body addresses the current practices of crowdsourcing, the classification of innovation risks, a conceptual framework for risk management, and analysis of survey results regarding performance and risk mitigation.
Which keywords best characterize this work?
The work is characterized by terms such as Crowdsourcing, Risk Management, Open Innovation, Intellectual Property, Turbulence Risk, and Strategic Innovation.
What is the significance of the "Risk Management Avoidance Matrix" created in this study?
The matrix serves as a practical tool for businesses to map identified risks against potential management and mitigation strategies, helping them navigate the challenges of crowdsourcing projects effectively.
Why does the author consider turbulence risk as the most prominent danger?
The research identifies turbulence risk as the most significant because it relates to unpredictable, complex business environments and unforeseen factors that can severely disrupt large-scale corporate operations that are reliant on hierarchical planning.
- Citar trabajo
- Michael Gebert (Autor), 2014, Crowdsourcing and Risk-Management, Múnich, GRIN Verlag, https://www.grin.com/document/294685
